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Brain development and the nature versus nurture debate

Affiliation.

1 Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA. [email protected]
PMID: 21489380
DOI: 10.1016/B978-0-444-53884-0.00015-4

Over the past three decades, developmental neurobiologists have made tremendous progress in defining basic principles of brain development. This work has changed the way we think about how brains develop. Thirty years ago, the dominant model was strongly deterministic. The relationship between brain and behavioral development was viewed as unidirectional; that is, brain maturation enables behavioral development. The advent of modern neurobiological methods has provided overwhelming evidence that it is the interaction of genetic factors and the experience of the individual that guides and supports brain development. Brains do not develop normally in the absence of critical genetic signaling, and they do not develop normally in the absence of essential environmental input. The fundamental facts about brain development should be of critical importance to neuropsychologists trying to understand the relationship between brain and behavioral development. However, the underlying assumptions of most contemporary psychological models reflect largely outdated ideas about how the biological system develops and what it means for something to be innate. Thus, contemporary models of brain development challenge the foundational constructs of the nature versus nurture formulation in psychology. The key to understanding the origins and emergence of both the brain and behavior lies in understanding how inherited and environmental factors are engaged in the dynamic and interactive processes that define and guide development of the neurobehavioral system.

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Article contents

Nature and nurture as an enduring tension in the history of psychology.

Hunter Honeycutt Hunter Honeycutt Bridgewater College, Department of Psychology
https://doi.org/10.1093/acrefore/9780190236557.013.518
Published online: 30 September 2019

Nature–nurture is a dichotomous way of thinking about the origins of human (and animal) behavior and development, where “nature” refers to native, inborn, causal factors that function independently of, or prior to, the experiences (“nurture”) of the organism. In psychology during the 19th century, nature-nurture debates were voiced in the language of instinct versus learning. In the first decades of the 20th century, it was widely assumed that that humans and animals entered the world with a fixed set of inborn instincts. But in the 1920s and again in the 1950s, the validity of instinct as a scientific construct was challenged on conceptual and empirical grounds. As a result, most psychologists abandoned using the term instinct but they did not abandon the validity of distinguishing between nature versus nurture. In place of instinct, many psychologists made a semantic shift to using terms like innate knowledge, biological maturation, and/or hereditary/genetic effects on development, all of which extend well into the 21st century. Still, for some psychologists, the earlier critiques of the instinct concept remain just as relevant to these more modern usages.

The tension in nature-nurture debates is commonly eased by claiming that explanations of behavior must involve reference to both nature-based and nurture-based causes. However, for some psychologists there is a growing pressure to see the nature–nurture dichotomy as oversimplifying the development of behavior patterns. The division is seen as both arbitrary and counterproductive. Rather than treat nature and nurture as separable causal factors operating on development, they treat nature-nurture as a distinction between product (nature) versus process (nurture). Thus there has been a longstanding tension about how to define, separate, and balance the effects of nature and nurture.

nature–nurture
development
nativism–empiricism
innate–learned
behavioral genetics
epigenetics

Nature and Nurture in Development

The oldest and most persistent ways to frame explanations about the behavioral and mental development of individuals is to distinguish between two separate sources of developmental causation: (a) intrinsic, preformed, or predetermined causes (“nature”) versus (b) extrinsic, experiential, or environmental causes (“nurture”). Inputs from these two sources are thought to add their own contribution to development (see Figure 1 ).

Figure 1. The traditional view of nature and nurture as separate causes of development. In the traditional view, nature and nurture are treated as independent causal influences that combine during development to generate outcomes. Note that, during development, the effects of nature and nurture (shown in horizontal crossing lines) remain independent so that their effects on outcomes are theoretically separable.

Because some traits seem to derive more from one source than the other, much of the tension associated with the nature–nurture division deals with disagreements about how to balance the roles of nature and nurture in the development of a trait.

Evidence of Nature in Development

Evidence to support the nature–nurture division usually derives from patterns of behavior that suggest a limited role of environmental causation, thus implying some effect of nature by default. Table 1 depicts some common descriptors and conditions used to infer that some preference, knowledge, or skill is nature based.

Table 1. Common Descriptors and Associated Conditions for Inferring the Effects of Nature on Development

Descriptors	Associated Conditions
Innate or unlearned	Displayed in the absence of relevant experience
Preparedness for learning	Rapidly or easily learned
Constraints on learning	Difficult or impossible to learn
Universal	Found in all like members of a species
Imperviousness	Difficult to modify following its appearance
Maturational	Emerges in an orderly sequence or at a specific time
Hereditary	Runs in families or with degrees of kinship

It is important to reiterate that nature-based causation (e.g., genetic determination) is inferred from these observations. Such inferences can generate tension because each of the observations listed here can be explained by nurture-based (environmental) factors. Confusion can also arise when evidence of one descriptor (e.g., being hereditary) is erroneously used to justify a different usage (e.g., that the trait is unlearned).

The Origins of Nature Versus Nurture

For much of recorded history, the distinction between nature and nurture was a temporal divide between what a person is innately endowed with at birth, prior to experience (nature), and what happens thereafter (nurture). It was not until the 19th century that the temporal division was transformed into a material division of causal influences (Keller, 2010 ). New views about heredity and Darwinian evolution justified distinguishing between native traits and genetic causes from acquired traits and environmental causes. More so than before, the terms nature and nurture were often juxtaposed in an opposition famously described by Sir Francis Galton ( 1869 ) as that between “nature versus nurture.”

Galton began writing about heredity in the mid-1860s. He believed we would discover laws governing the transmission of mental as well as physical qualities. Galton’s take on mental heredity, however, was forged by his desire to improve the human race in a science he would later call “eugenics.” In the mid- 19th century , British liberals assumed humans were equivalent at birth. Their social reform efforts were geared to enhancing educational opportunities and improving living conditions. Galton, a political conservative, opposed the notion of natural equality, arguing instead that people were inherently different at birth (Cowan, 2016 ), and that these inherited mental and behavioral inequalities were transmitted through lineages like physical qualities. Because Galton opposed the widely held Lamarckian idea that the qualities acquired in one’s lifetime could modify the inherited potential of subsequent generations, he believed long-lasting improvement of the human stock would only come by controlling breeding practices.

To explain the biological mechanisms of inheritance, Galton joined a growing trend in the 1870s to understand inheritance as involving the transmission of (hypothetical) determinative, germinal substances across generations. Foreshadowing a view that would later become scientific orthodoxy, Galton believed these germinal substances to be uninfluenced by the experiences of the organism. His theory of inheritance, however, was speculative. Realizing he was not equipped to fully explicate his theory of biological inheritance, Galton abandoned this line of inquiry by the end of that decade and refocused his efforts on identifying statistical laws of heredity of individual differences (Renwick, 2011 ).

Historians generally agree that Galton was the first to treat nature (as heredity) and nurture (everything else) as separate causal forces (Keller, 2010 ), but the schism gained biological legitimacy through the work of the German cytologist Auguste Weismann in the 1880s. Whereas Galton’s theory was motivated by his political agenda, Weismann was motivated by a scientific, theoretical agenda. Namely, Weismann opposed Lamarckian inheritance and promoted a view of evolution driven almost entirely by natural selection.

Drawing upon contemporary cytological and embryological research, Weismann made the case that the determinative substances found in the germ cells of plants and animals (called the “germ-plasm”) that are transmitted across generations were physically sequestered very early in embryogenesis and remained buffered from the other cells of the body (“somato-plasm”). This so-called, Weismann’s barrier meant that alterations in the soma that develop in the lifetime of the organism through the use or disuse of body parts would not affect the germinal substances transmitted during reproduction (see Winther, 2001 , for review). On this view, Lamarckian-style inheritance of acquired characteristics was not biologically possible.

Galton and Weismann’s influence on the life sciences cannot be overstated. Their work convinced many to draw unusually sharp distinctions between the inherited (nature) and the acquired (nurture). Although their theories were met with much resistance and generated significant tension in the life sciences from cytology to psychology, their efforts helped stage a new epistemic space through which to appreciate Mendel’s soon to be rediscovered breeding studies and usher in genetics (Muller-Wille & Rheinberger, 2012 ).

Ever since, psychology has teetered between nature-biased and nurture-biased positions. With the rise of genetics, the wedge between nature–nurture was deepened in the early to mid- 20th century , creating fields of study that focused exclusively on the effects of either nature or nurture.

The “Middle Ground” Perspective on Nature–Nurture

Twenty-first-century psychology textbooks often state that the nature–nurture debates have been resolved, and the tension relaxed, because we have moved on from emphasizing nature or nurture to appreciating that development necessarily involves both nature and nurture. In this middle-ground position, one asks how nature and nurture interact. For example, how do biological (or genetic) predispositions for behaviors or innate knowledge bias early learning experiences? Or how might environmental factors influence the biologically determined (maturational) unfolding of bodily form and behaviors?

Rejection of the Nature–Nurture Divide

For some, the “middle-ground” resolution is as problematic as “either/or” views and does not resolve a deeper source of tension inherent in the dichotomy. On this view, the nature–nurture divide is neither a legitimate nor a constructive way of thinking about development. Instead, developmental analysis reveals that the terms commonly associated with nature (e.g., innate, genetic, hereditary, or instinctual) and nurture (environmental or learned) are so entwined and confounded (and often arbitrary) that their independent effects cannot be meaningfully discussed. The nature–nurture division oversimplifies developmental processes, takes too much for granted, and ultimately hinders scientific progress. Thus not only is there a lingering tension about how to balance the effects of nature and nurture in the middle-ground view, but there is also a growing tension to move beyond the dichotomous nature–nurture framework.

Nativism in Behavior: Instincts

Definitions of instinct can vary tremendously, but many contrast (a) instinct with reason (or intellect, thought, will), which is related to but separable from contrasting (b) instinct with learning (or experience or habit).

Instinct in the Age of Enlightenment

Early usages of the instinct concept, following Aristotle, treated instinct as a mental, estimative faculty ( vis aestimativa or aestimativa naturalis ) in humans and animals that allowed for the judgments of objects in the world (e.g., seeing a predator) to be deemed beneficial or harmful in a way that transcends immediate sensory experience but does not involve the use of reason (Diamond, 1971 ). In many of the early usages, the “natural instinct” of animals even included subrational forms of learning.

The modern usage of instincts as unlearned behaviors took shape in the 17th century . By that point it was widely believed that nature or God had implanted in animals and humans innate behaviors and predispositions (“instincts”) to promote the survival of the individual and the propagation of the species. Disagreements arose as to whether instincts derived from innate mental images or were mindlessly and mechanically (physiologically) generated from innately specified bodily organization (Richards, 1987 ).

Anti-Instinct Movement in the Age of Enlightenment

Challenges to the instinct concept can be found in the 16th century (see Diamond, 1971 ), but they were most fully developed by empiricist philosophers of the French Sensationalist tradition in the 18th century (Richards, 1987 ). Sensationalists asserted that animals behaved rationally and all of the so-called instincts displayed by animals could be seen as intelligently acquired habits.

For Sensationalists, instincts, as traditionally understood, did not exist. Species-specificity in behavior patterns could be explained by commonalities in physiological organization, needs, and environmental conditions. Even those instinctual behaviors seen at birth (e.g., that newly hatched chicks peck and eat grain) might eventually be explained by the animal’s prenatal experiences. Erasmus Darwin ( 1731–1802 ), for example, speculated that the movements and swallowing experiences in ovo could account for the pecking and eating of grain by young chicks. The anti-instinct sentiment was clearly expressed by the Sensationalist Jean Antoine Guer ( 1713–1764 ), who warned that instinct was an “infantile idea” that could only be held by those who are ignorant of philosophy, that traditional appeals to instincts in animals not only explained nothing but served to hinder scientific explanations, and that nothing could be more superficial than to explain behavior than appealing to so-called instincts (Richards, 1987 ).

The traditional instinct concept survived. For most people, the complex, adaptive, species-specific behaviors displayed by naïve animals (e.g., caterpillars building cocoons; infant suckling behaviors) appeared to be predetermined and unlearned. Arguably as important, however, was the resistance to the theological implications of Sensationalist philosophy.

One of the strongest reactions to Sensationalism was put forward in Germany by Herman Samuel Reimarus ( 1694–1768 ). As a natural theologian, Reimarus, sought evidence of a God in the natural world, and the species-specific, complex, and adaptive instincts of animals seemed to stand as the best evidence of God’s work. More so than any other, Reimarus extensively catalogued instincts in humans and animals. Rather than treat instincts as behaviors, he defined instincts as natural impulses (inner drives) to act that were expressed perfectly, without reflection or practice, and served adaptive goals (Richards, 1987 ). He even proposed instincts for learning, a proposal that would resurface in the mid- 20th century , as would his drive theory of instinct (Jaynes & Woodward, 1974 ).

Partly as a result of Reimarus’ efforts, the instinct concept survived going into the 19th century . But many issues surrounding the instinct concept were left unsettled. How do instincts differ from reflexive behaviors? What role does learning play in the expression of instincts, if any? Do humans have more or fewer instincts than animals? These questions would persist well into the first decades of the 20th century and ultimately fuel another anti-instinct movement.

Instinct in the 19th Century

In the 19th century , the tension about the nature and nurture of instincts in the lifetime of animals led to debates about the nature and nurture of instincts across generations . These debates dealt with whether instincts should be viewed as “inherited habits” from previous generations or whether they result from the natural selection. Debating the relative roles of neo-Lamarckian use-inheritance versus neo-Darwinian natural selection in the transmutation of species became a significant source of tension in the latter half of the 19th century . Although the neo-Lamarckian notion of instincts as being inherited habits was rejected in the 20th century , it has resurged in recent years (e.g., see Robinson & Barron, 2017 ).

Darwinian evolutionary theory required drawing distinctions between native and acquired behaviors, and, perhaps more so than before, behaviors were categorized along a continuum from the purely instinctive (unlearned), to the partially instinctive (requiring some learning), to the purely learned. Still, it was widely assumed that a purely instinctive response would be modified by experience after its first occurrence. As a result, instinct and habit were very much entangled in the lifetime of the organism. The notion of instincts as fixed and unmodifiable would not be widely advanced until after the rise of Weismann’s germ-plasm theory in the late 19thcentury .

Given their importance in evolutionary theory, there was greater interest in more objectively identifying pure instincts beyond anecdotal reports. Some of the most compelling evidence was reported by Douglas Spalding ( 1844–1877 ) in the early 1870s (see Gray, 1967 ). Spalding documented numerous instances of how naïve animals showed coordinated, seemingly adaptive responses (e.g., hiding) to objects (e.g., sight of predators) upon their first encounter, and he helped pioneer the use of the deprivation experiment to identify instinctive behaviors. This technique involved selectively depriving young animals of seemingly critical learning experiences or sensory stimulation. Should animals display some species-typical action following deprivation, then, presumably, the behavior could be labeled as unlearned or innate. In all, these studies seemed to show that animals displayed numerous adaptive responses at the very start, prior to any relevant experience. In a variety of ways, Spalding’s work anticipated 20th-century studies of innate behavior. Not only would the deprivation experiment be used as the primary means of detecting native tendencies by European zoologists and ethologists, but Spalding also showed evidence of what would later be called imprinting, critical period effects and evidence of behavioral maturation.

Reports of pure instinct did not go unchallenged. Lloyd Morgan ( 1896 ) questioned the accuracy of these reports in his own experimental work with young animals. In some cases, he failed to replicate the results and in other cases he found that instinctive behaviors were not as finely tuned to objects in the environment as had been claimed. Morgan’s research pointed to taking greater precision in identifying learned and instinctive components of behavior, but, like most at the turn of the 20th century , he did not question that animal behavior involved both learned and instinctive elements.

A focus on instinctive behaviors intensified in the 1890s as Weismann’s germ-plasm theory grew in popularity. More so than before, a sharp distinction was drawn between native and acquired characteristics, including behavior (Johnston, 1995 ). Although some psychologists continued to maintain neo-Lamarckian notions, most German (Burnham, 1972 ) and American (Cravens & Burnham, 1971 ) psychologists were quick to adopt Weismann’s theory. They envisioned a new natural science of psychology that would experimentally identify the germinally determined, invariable set of native psychological traits in species and their underlying physiological (neural) basis. However, whereas English-speaking psychologists tended to focus on how this view impacted our understanding of social institutions and its social implications, German psychologists were more interested in the longstanding philosophical implications of Weismann’s doctrine as it related to the differences (if any) between man and beast (Burnham, 1972 ).

Some anthropologists and sociologists, however, interpreted Weismann’s theory quite differently and used it elevate sociology as its own scientific discipline. In the 1890s, the French sociologist Emil Durkheim, for example, interpreted Weismann’s germinal determinants as a generic force on human behavior that influenced the development of general predispositions that are molded by the circumstances of life (Meloni, 2016 ). American anthropologists reached similar conclusions in the early 20th century (Cravens & Burnham, 1971 ). Because Weismann’s theory divorced biological inheritance from social inheritance, and because heredity was treated as a generic force, sociologists felt free to study social (eventually, “cultural”) phenomena without reference to biological or psychological concerns.

Anti-Instinct Movement in the 1920s

Despite their differences, in the first two decades of the 20th century both psychologists and sociologists generally assumed that humans and animals had some native tendencies or instincts. Concerns were even voiced that instinct had not received enough attention in psychology. Disagreements about instincts continued to focus on (the now centuries old debates of) how to conceptualize them. Were they complex reflexes, impulses, or motives to act, or should instinct be a mental faculty (like intuition), separate from reasoning and reflex (Herrnstein, 1972 )?

In America, the instinct concept came under fire following a brief paper in 1919 by Knight Dunlap titled “Are There Any Instincts?” His primary concern dealt with teleological definitions of instincts in which an instinct referred to all the activities involved in obtaining some end-state (e.g., instincts of crying, playing, feeding, reproduction, war, curiosity, or pugnacity). Defined in this way, human instincts were simply labels for human activities, but how these activities were defined was arbitrarily imposed by the researchers. Is feeding, for instance, an instinct, or is it composed of more basic instincts (like chewing and swallowing)? The arbitrariness of classifying human behavior had led to tremendous inconsistencies and confusion among psychologists.

Not all of the challenges to instinct dealt with its teleological usage. Some of the strongest criticisms were voiced by Zing-Yang Kuo throughout the 1920s. Kuo was a Chinese animal psychologist who studied under Charles Tolman at the University of California, Berkeley. Although Kuo’s attacks on instinct changed throughout the 1920s (see Honeycutt, 2011 ), he ultimately argued that all behaviors develop in experience-dependent ways and that appeals to instinct were statements of ignorance about how behaviors develop. Like Dunlap, he warned that instincts were labels with no explanatory value. To illustrate, after returning to China, he showed how the so-called rodent-killing instinct in cats often cited by instinct theorists is not found in kittens that are reared with rodents (Kuo, 1930 ). These kittens, instead, became attached to the rodents, and they resisted attempts to train rodent-killing. Echoing the point made by Guer, Kuo claimed that appeals to instinct served to stunt scientific inquiry into the developmental origins of behavior.

But Kuo did not just challenge the instinct concept. He also argued against labeling behaviors as “learned.” After all, whether an animal “learns” depends on the surrounding environmental conditions, the physiological and developmental status of the animal, and, especially, the developmental (or experiential) history of that animal. Understanding learning also required developmental analysis. Thus Kuo targeted the basic distinction between nature and nurture, and he was not alone in doing so (e.g., see Carmichael, 1925 ), but his call to reject it did not spread to mainstream American psychologists.

By the 1930s, the term instinct had fallen into disrepute in psychology, but experimental psychologists (including behaviorists) remained committed to a separation of native from acquired traits. If anything, the dividing line between native and acquired behaviors became more sharply drawn than before (Logan & Johnston, 2007 ). For some psychologists, instinct was simply rebranded in the less contentious (but still problematic) language of biological drives or motives (Herrnstein, 1972 ). Many other psychologists simply turned to describing native traits as due to “maturation” and/or “heredity” rather than “instinct.”

Fixed Action Patterns

The hereditarian instinct concept received a reboot in Europe in the 1930s with the rise of ethology led by Konrad Lorenz, Niko Tinbergen, and others. Just as animals inherit organs that perform specific functions, ethologists believed animals inherit behaviors that evolved to serve adaptive functions as well. Instincts were described as unlearned (inherited), blind, stereotyped, adaptive, fixed action patterns, impervious to change that are initiated (released) by specific stimuli in the environment.

Ethologists in 1930s and 1940s were united under the banner of innateness. They were increasingly critical of the trend by American psychologists (i.e., behaviorists) to focus on studying on how a limited number of domesticated species (e.g., white rat) responded to training in artificial settings (Burkhardt, 2005 ). Ethologists instead began with rich descriptions of animal behavior in more natural environments along with detailed analyses of the stimulus conditions that released the fixed action patterns. To test whether behavioral components were innate, ethologists relied primarily on the deprivation experiment popularized by Spalding in the 19th century . Using these methods (and others), ethologists identified numerous fascinating examples of instinctive behaviors, which captured mainstream attention.

In the early 1950s, shortly after ethology had gained professional status (Burkhardt, 2005 ), a series of challenges regarding instinct and innateness were put forth by a small cadre of North American behavioral scientists (e.g., T. C. Schneirla, Donald Hebb, Frank Beach). Arguably the most influential critique was voiced by comparative psychologist Daniel Lehrman ( 1953 ), who presented a detailed and damning critique of deprivation experiments on empirical and logical grounds. Lehrman explained that deprivation experiments isolate the animal from some but not all experiences. Thus deprivation experiments simply change what an animal experiences rather than eliminating experience altogether, and so they cannot possibly determine whether a behavior is innate (independent of experience). Instead, these experiments show what environmental conditions do not matter in the development of a behavior but do not speak to what conditions do matter .

Lehrman went on to argue that the whole endeavor to identify instinctive or innate behavior was misguided from the start. All behavior, according to Lehrman, develops from a history of interactions between an organism and its environment. If a behavior is found to develop in the absence of certain experiences, the researcher should not stop and label it as innate. Rather, research should continue to identify the conditions under which the behavior comes about. In line with Kuo, Lehrman repeated the warning that to label something as instinctive (or inherited or maturational) is a statement of ignorance about how that behavior develops and does more to stunt than promote research.

Lehrman’s critique created significant turmoil among ethologists. As a result, ethologists took greater care in using the term innate , and it led to new attempts to synthesize or re-envision learning and instinct .

Some of these attempts focused on an increased role for learning and experience in the ontogeny of species-typical behaviors. These efforts spawned significant cross-talk between ethologists and comparative psychologists to more thoroughly investigate behavioral development under natural conditions. Traditional appeals to instinct and learning (as classical and operant conditioning) were both found to be inadequate for explaining animal behavior. In their stead, these researchers focused more closely on how anatomical, physiological, experiential, and environmental conditions influenced the development of species-typical behaviors.

Tinbergen ( 1963 ) was among those ethologists who urged for greater developmental analysis of species-typical behaviors, and he included it as one of his four problems in the biological study of organisms, along with causation (mechanism), survival value (function), and evolution. Of these four problems, Tinbergen believed ethologists were especially well suited to study survival value, which he felt had been seriously neglected (Burkhardt, 2005 ).

The questions of survival value coupled with models of population genetics would gain significant momentum in the 1960s and 1970s in England and the United States with the rise of behavioral ecology and sociobiology (Griffiths, 2008 ). But because these new fields seemed to promote some kind of genetic determinism in behavioral development, they were met with much resistance and reignited a new round of nature–nurture debates in the 1970s (see Segerstrale, 2000 ).

However, not all ethologists abandoned the instinct concept. Lorenz, in particular, continued to defend the division between nature and nurture. Rather than speaking of native and acquired behaviors, Lorenz later spoke of two different sources of information for behavior (innate/genetic vs. acquired/environmental), which was more a subtle shift in language than it was an actual change in theory, as Lehrman later pointed out.

Some ethologists followed Lorenz’s lead and continued to maintain more of a traditional delineation between instinct and learning. Their alternative synthesis viewed learning as instinctive (Gould & Marler, 1987 ). They proposed that animals have evolved domain-specific “instincts to learn” that result from the its genetic predispositions and innate knowledge. To support the idea of instincts for learning, ethologists pointed to traditional ethological findings (on imprinting and birdsong learning), but they also drew from the growing body of work in experimental psychology that seemed to indicate certain types of biological effects on learning.

Biological Constraints and Preparedness

While ethology was spreading in Europe in the 1930s–1950s, behaviorism reigned in the United States. Just as ethologists were confronted with including a greater role of nurture in their studies, behaviorists were challenged to consider a greater role of nature.

Behaviorists assumed there to be some behavioral innateness (e.g., fixed action patterns, unconditioned reflexes, primary reinforcers and drives). But because behaviorists focused on learning, they tended to study animals in laboratory settings using biologically (or ecologically) irrelevant stimuli and responses to minimize any role of instinct (Johnston, 1981 ). It was widely assumed that these studies would identify general laws of learning that applied to all species regardless of the specific cues, reinforcers, and responses involved.

Challenges to the generality assumption began to accumulate in the 1960s. Some studies pointed to failures that occurred during conditioning procedures. Breland and Breland ( 1961 ), for example, reported that some complex behaviors formed through operant conditioning would eventually become “displaced” by conditioned fixed action patterns in a phenomenon they called “instinctive drift.” Studies of taste-aversion learning (e.g., Garcia & Koelling, 1966 ) also reported the failure of rats to associate certain events (e.g., flavors with shock or audiovisual stimuli with toxicosis).

Other studies were pointing to enhanced learning. In particular, it was found that rats could form strong conditioned taste aversions after only a single pairing between a novel flavor and illness. (This rapid “one trial learning” was a major focus in the research from Niko Tinbergen’s ethological laboratory.) Animals, it seemed, had evolved innate predispositions to form (or not form) certain associations.

In humans, studies of biological constraints on learning were mostly limited to fear conditioning. Evidence indicated that humans conditioned differently to (biologically or evolutionarily) fear-relevant stimuli like pictures of spiders or snakes than to fear-irrelevant stimuli like pictures of mushrooms or flowers (Ohman, Fredrikson, Hugdahl, & Rimmö, 1976 ).

These findings and others were treated as a major problem in learning theory and led to calls for a new framework to study learning from a more biologically oriented perspective that integrated the evolutionary history and innate predispositions of the species. These predispositions were described as biological “constraints” on, “preparedness,” or “adaptive specializations” for learning, all of which were consistent with the “instincts to learn” framework proposed by ethologists.

By the 1980s it was becoming clear that the biological preparedness/constraint view of learning suffered some limitations. For example, what constraints count as “biological” was questioned. It was well established that there were general constraints on learning associated with the intensity, novelty, and timing of stimuli. But, arbitrarily it seemed, these constraints were not classified as “biological” (Domjan & Galef, 1983 ). Other studies of “biological constraints” found that 5- and 10-day old rats readily learned to associated a flavor with shock (unlike in adults), but (like in adults) such conditioning was not found in 15-day-old rats (Hoffman & Spear, 1988 ). In other words, the constraint on learning was not present in young rats but developed later in life, suggesting a possible role of experience in bringing about the adult-like pattern.

Attempts to synthesize these alternatives led to numerous calls for more ecologically oriented approaches to learning not unlike the synthesis between ethology and comparative psychology in the 1960s. All ecological approaches to learning proposed that learning should be studied in the context of “natural” (recurrent and species-typical) problems that animals encounter (and have evolved to encounter) using ecologically meaningful stimuli and responses. Some argued (e.g., Johnston, 1981 ) that studies of learning should take place within the larger context of studying how animals develop and adapt to their surround. Others (Domjan & Galef, 1983 ) pointed to more of a comparative approach in studying animal learning in line with behavioral ecology that takes into account how learning can be influenced by the possible selective pressures faced by each species. Still, how to synthesize biological constraints (and evolutionary explanations) on learning with a general process approach remains a source of tension in experimental psychology.

Nativism in Mind: Innate Ideas

Nativism and empiricism in philosophy.

In the philosophy of mind, nature–nurture debates are voiced as debates between nativists and empiricists. Nativism is a philosophical position that holds that our minds have some innate (a priori to experience) knowledge, concepts, or structure at the very start of life. Empiricism, in contrast, holds that all knowledge derives from our experiences in the world.

However, rarely (if ever) were there pure nativist or empiricist positions, but the positions bespeak a persistent tension. Empiricists tended to eschew innateness and promote a view of the mental content that is built by general mechanisms (e.g., association) operating on sensory experiences, whereas nativists tend to promote a view of mind that contains domain-specific, innate processes and/or content (Simpson, Carruthers, Laurence, & Stich, 2005 ). Although the tension about mental innateness would loosen as empiricism gained prominence in philosophy and science, the strain never went away and would intensify again in the 20th century .

Nativism in 20th Century Psychology: The Case of Language Development

In the first half of the 20th century , psychologists generally assumed that knowledge was gained or constructed through experience with the world. This is not to say that psychologists did not assume some innate knowledge. The Swiss psychologist Jean Piaget, for example, believed infants enter the world with some innate knowledge structures, particularly as they relate to early sensory and motor functioning (see Piaget, 1971 ). But the bulk of his work dealt with the construction of conceptual knowledge as children adapt to their worlds. By and large, there were no research programs in psychology that sought to identify innate factors in human knowledge and cognition until the 1950s (Samet & Zaitchick, 2017 )

An interest in psychological nativism was instigated in large part by Noam Chomsky’s ( 1959 ) critique of B. F. Skinner’s book on language. To explain the complexity of language, he argued, we must view language as the knowledge and application of grammatical rules. He went on to claim that the acquisition of these rules could not be attributed to any general-purpose, learning process (e.g., reinforcement). Indeed, language acquisition occurs despite very little explicit instruction. Moreover, language is special in terms of its complexity, ease, and speed of acquisition by children and in its uniqueness to humans. Instead, he claimed that our minds innately contain some language-specific knowledge that kick-starts and promotes language acquisition. He later claimed this knowledge can be considered some sort of specialized mental faculty or module he called the “language acquisition device” (Chomsky, 1965 ) or what Pinker ( 1995 ) later called the “language instinct.”

To support the idea of linguistic nativism, Chomsky and others appealed to the poverty of the stimulus argument. In short, this argument holds that our experiences in life are insufficient to explain our knowledge and abilities. When applied to language acquisition, this argument holds children’s knowledge of language (grammar) goes far beyond the limited, and sometimes broken, linguistic events that children directly encounter. Additional evidence for nativism drew upon the apparent maturational quality of language development. Despite wide variations in languages and child-rearing practices across the world, the major milestones in language development appear to unfold in children in a universal sequence and timeline, and some evidence suggested a critical period for language acquisition.

Nativist claims about language sparked intense rebuttals by empiricist-minded psychologists and philosophers. Some of these retorts tackled the logical limitations of the poverty of stimulus argument. Others pointed to the importance of learning and social interaction in driving language development, and still others showed that language (grammatical knowledge) may not be uniquely human (see Tomasello, 1995 , for review). Nativists, in due course, provided their own rebuttals to these challenges, creating a persistent tension in psychology.

Extending Nativism Beyond Language Development

In the decades that followed, nativist arguments expanded beyond language to include cognitive domains that dealt with understanding the physical, psychological, and social worlds. Developmental psychologists were finding that infants appeared to be much more knowledgeable in cognitive tasks (e.g., on understanding object permanence) and skillful (e.g., in imitating others) than had previously been thought, and at much younger ages. Infants also showed a variety of perceptual biases (e.g., preference for face-like stimuli over equally complex non-face-like stimuli) from very early on. Following the standard poverty of the stimulus argument, these findings were taken as evidence that infants enter the world with some sort of primitive, innate, representational knowledge (or domain-specific neural mechanisms) that constrains and promotes subsequent cognitive development. The nature of this knowledge (e.g., as theories or as core knowledge), however, continues to be debated (Spelke & Kinzler, 2007 ).

Empiricist-minded developmental psychologists responded by demonstrating shortcomings in the research used to support nativist claims. For example, in studies of infants’ object knowledge, the behavior of infants (looking time) in nativist studies could be attributed to relatively simple perceptual processes rather than to the infants’ conceptual knowledge (Heyes, 2014 ). Likewise, reports of human neonatal imitation not only suffered from failures to replicate but could be explained by simpler mechanisms (e.g., arousal) than true imitation (Jones, 2017 ). Finally, studies of perceptual preferences found in young infants, like newborn preferences for face-like stimuli, may not be specific preferences for faces per se but instead may reflect simpler, nonspecific perceptual biases (e.g., preferences for top-heavy visual configurations and congruency; Simion & Di Giorgio, 2015 ).

Other arguments from empiricist-minded developmental psychologists focused on the larger rationale for inferring innateness. Even if it is conceded that young infants, like two-month-olds, or even two-day-olds, display signs of conceptual knowledge, there is no good evidence to presume the knowledge is innate. Their knowledgeable behaviors could still be seen as resulting from their experiences (many of which may be nonobvious to researchers) leading up to the age of testing (Spencer et al., 2009 ).

In the 21st century , there is still no consensus about the reality, extensiveness, or quality of mental innateness. If there is innate knowledge, can experience add new knowledge or only expand the initial knowledge? Can the doctrine of innate knowledge be falsified? There are no agreed-upon answers to these questions. The recurring arguments for and against mental nativism continue to confound developmental psychologists.

Maturation Theory

The emergence of bodily changes and basic behavioral skills sometimes occurs in an invariant, predictable, and orderly sequence in a species despite wide variations in rearing conditions. These observations are often attributed to the operation of an inferred, internally driven, maturational process. Indeed, 21st-century textbooks in psychology commonly associate “nature” with “maturation,” where maturation is defined as the predetermined unfolding of the individual from a biological or genetic blueprint. Environmental factors play a necessary, but fundamentally supportive, role in the unfolding of form.

Preformationism Versus Epigenesis in the Generation of Form

The embryological generation of bodily form was debated in antiquity but received renewed interest in the 17th century . Following Aristotle, some claimed that embryological development involved “epigenesis,” defined as the successive emergence of form from a formless state. Epigenesists, however, struggled to explain what orchestrated development without appealing to Aristotelean souls. Attempts were made to invoke to natural causes like physical and chemical forces, but, despite their best efforts, the epigenesists were forced to appeal to the power of presumed, quasi-mystical, vitalistic forces (entelechies) that directed development.

The primary alternative to epigenesis was “preformationism,” which held that development involved the growth of pre-existing form from a tiny miniature (homunculus) that formed immediately after conception or was preformed in the egg or sperm. Although it seems reasonable to guess that the invention and widespread use of the microscope would immediately lay to rest any claim of homuncular preformationism, this was not the case. To the contrary, some early microscopists claimed to see signs of miniature organisms in sperm or eggs, and failures to find these miniatures were explained away (e.g., the homunculus was transparent or deflated to the point of being unrecognizable). But as microscopes improved and more detailed observations of embryological development were reported in the late 18th and 19th centuries , homuncular preformationism was finally refuted.

From Preformationism to Predeterminism

Despite the rejection of homuncular preformationism, preformationist appeals can be found throughout the 19th century . One of the most popular preformationist theories of embryological development was put forth by Ernst Haeckel in the 1860s (Gottlieb, 1992 ). He promoted a recapitulation theory (not original to Haeckel) that maintained that the development of the individual embryo passes through all the ancestral forms of its species. Ontogeny was thought to be a rapid, condensed replay of phylogeny. Indeed, for Haeckel, phylogenesis was the mechanical cause of ontogenesis. The phylogenetic evolution of the species created the maturational unfolding of embryonic form. Exactly how this unfolding takes place was less important than its phylogenetic basis.

Most embryologists were not impressed with recapitulation theory. After all, the great embryologist Karl Ernst von Baer ( 1792–1876 ) had refuted strict recapitulation decades earlier. Instead, there was greater interest in how best to explain the mechanical causes of development ushering in a new “experimental embryology.” Many experimental embryologists followed the earlier epigenesists by discussing vitalistic forces operating on the unorganized zygote. But it soon became clear that the zygote was structured, and many people believed the zygote contained special (unknown) substances that specified development. Epigenesis-minded experimental embryologists soon warned that the old homuncular preformationism was being transformed into a new predetermined preformationism.

As a result, the debates between preformationism and epigenesis were reignited in experimental embryology, but the focus of these debates shifted to the various roles of nature and nurture during development. More specifically, research focused on the extent to which early cellular differentiation was predetermined by factors internal to cells like chromosomes or cytoplasm (preformationism, nature) or involved factors (e.g., location) outside of the cell (epigenesis, nurture). The former emphasized reductionism and developmental programming, whereas the latter emphasized some sort of holistic, regulatory system responsive to internal and external conditions. The tension between viewing development as predetermined or “epigenetic” persists into the 21st century .

Preformationism gained momentum in the 20th century following the rediscovery of Mendel’s studies of heredity and the rapid rise of genetics, but not because of embryological research on the causes of early differentiation. Instead, preformationism prevailed because it seemed embryological research on the mechanisms of development could be ignored in studies of hereditary patterns.

The initial split between heredity and development can be found in Galton’s speculations but is usually attributed to Weismann’s germ-plasm theory. Weismann’s barrier seemed to posit that the germinal determinants present at conception would be the same, unaltered determinants transmitted during reproduction. This position, later dubbed as “Weismannism,” was ironically not one promoted by Weismann. Like nearly all theorists in the 19th century , he viewed the origins of variation and heredity as developmental phenomena (Amundson, 2005 ), and he claimed that the germ-plasm could be directly modified in the lifetime of the organism by environmental (e.g., climactic and dietary) conditions (Winther, 2001 ). Still, Weismann’s theory treated development as a largely predetermined affair driven by inherited, germinal determinants buffered from most developmental events. As such, it helped set the stage for a more formal divorce between heredity and development with the rise of Mendelism in the early 20th century .

Mendel’s theory of heredity was exceptional in how it split development from heredity (Amundson, 2005 ). More so than in Weismann’s theory, Mendel’s theory assumed that the internal factors that determine form and are transmitted across generations remain unaltered in the lifetime of the organism. To predict offspring outcomes, one need only know the combination of internal factors present at conception and their dominance relations. Exactly how these internal factors determined form could be disregarded. The laws of hereditary transmission of the internal factors (e.g., segregation) did not depend on the development or experiences of the organism or the experiences the organism’s ancestors. Thus the experimental study of heredity (i.e., breeding) could proceed without reference to ancestral records or embryological concerns (Amundson, 2000 ). By the mid-1920s, the Mendelian factors (now commonly called “genes”) were found to be structurally arranged on chromosomes, and the empirical study of heredity (transmission genetics) was officially divorced from studies of development.

The splitting of heredity and development found in Mendel’s and Weismann’s work met with much resistance. Neo-Lamarckian scientists, especially in the United States (Cook, 1999 ) and France (Loison, 2011 ), sought unsuccessfully to experimentally demonstrate the inheritance of acquired characteristics into the 1930s.

In Germany during the 1920s and 1930s, resistance to Mendelism dealt with the chromosomal view of Mendelian heredity championed by American geneticists who were narrowly focused on studying transmission genetics at the expense of developmental genetics. German biologists, in contrast, were much more interested in the broader roles of genes in development (and evolution). In trying to understand how genes influence development, particularly of traits of interest to embryologists, they found the Mendelian theory to be lacking. In the decades between the world wars, German biologists proposed various expanded views of heredity that included some form of cytoplasmic inheritance (Harwood, 1985 ).

Embryologists resisted the preformationist view of development throughout the early to mid- 20th century , often maintaining no divide between heredity and development, but their objections were overshadowed by genetics and its eventual synthesis with evolutionary theory. Consequently, embryological development was treated by geneticists and evolutionary biologists as a predetermined, maturational process driven by internal, “genetic” factors buffered from environmental influence.

Maturation Theory in Psychology

Maturation theory was applied to behavioral development in the 19th century in the application of Haeckel’s recapitulation theory. Some psychologists believed that the mental growth of children recapitulated the history of the human race (from savage brute to civilized human). With this in mind, many people began to more carefully document child development. Recapitulationist notions were found in the ideas of many notable psychologists in the 19th and early 20th centuries (e.g., G. S. Hall), and, as such, the concept played an important role in the origins of developmental psychology (Koops, 2015 ). But for present purposes what is most important is that children’s mental and behavioral development was thought to unfold via a predetermined, maturational process.

With the growth of genetics, maturational explanations were increasingly invoked to explain nearly all native and hereditary traits. As the instinct concept lost value in the 1920s, maturation theory gained currency, although the shift was largely a matter of semantics. For many psychologists, the language simply shifted from “instinct versus learning” to “maturation versus practice/experience” (Witty & Lehman, 1933 ).

Initial lines of evidence for maturational explanations of behavior were often the same as those that justified instinct and native traits, but new embryological research presented in the mid-1920s converged to show support for strict maturational explanations of behavioral development. In these experiments (see Wyman, 2005 , for review), spanning multiple laboratories, amphibians (salamanders and frogs) were exposed to drugs that acted as anesthetics and/or paralytics throughout the early stages of development, thus reducing sensory experience and/or motor practice. Despite the reduced sensory experiences and being unable to move, these animals showed no delays in the onset of motor development once the drugs wore off.

This maturational account of motor development in amphibians fit well with contemporaneous studies of motor development in humans. The orderly, invariant, and predictable (age-related) sequential appearance of motor skills documented in infants reared under different circumstances (in different countries and across different decades) was seen as strong evidence for a maturational account. Additional evidence was reported by Arnold Gessell and Myrtle McGraw, who independently presented evidence in the 1920s to show that the pace and sequence of motor development in infancy were not altered by special training experiences. Although the theories of these maturation theorists were more sophisticated when applied to cognitive development, their work promoted a view in which development was primarily driven by neural maturation rather than experience (Thelen, 2000 ).

Critical and Sensitive Periods

As the maturation account of behavioral development gained ground, it became clear that environmental input played a more informative role than had previously been thought. Environmental factors were found to either disrupt or induce maturational changes at specific times during development. Embryological research suggested that there were well-delineated time periods of heightened sensitivity in which specific experimental manipulations (e.g., tissue transplantations) could induce irreversible developmental changes, but the same manipulation would have no effect outside of that critical period.

In the 1950s–1960s a flurry of critical period effects were reported in birds and mammals across a range of behaviors including imprinting, attachment, socialization, sensory development, bird song learning, and language development (Michel & Tyler, 2005 ). Even though these findings highlighted an important role of experience in behavioral development, evidence of critical periods was usually taken to imply some rigid form of biological determinism (Oyama, 1979 ).

As additional studies were conducted on critical period effects, it became clear that many of the reported effects were more gradual, variable, experience-dependent, and not necessarily as reversible as was previously assumed. In light of these reports, there was a push in the 1970s (e.g., Connolly, 1972 ) to substitute “sensitive period” for “critical period” to avoid the predeterminist connotations associated with the latter and to better appreciate that these periods simply describe (not explain) certain temporal aspects of behavioral development. As a result, a consensus emerged that behaviors should not be attributed to “time” or “age” but to the developmental history and status of the animal under investigation (Michel & Tyler, 2005 ).

Heredity and Genetics

In the decades leading up to and following the start of the 20th century , it was widely assumed that many psychological traits (not just instincts) were inherited or “due to heredity,” although the underlying mechanisms were unknown. Differences in intelligence, personality, and criminality within and between races and sexes were largely assumed to be hereditary and unalterable by environmental intervention (Gould, 1996 ). The evidence to support these views in humans was often derived from statistical analyses of how various traits tended to run in families. But all too frequently, explanations of data were clouded by pre-existing, hereditarian assumptions.

Human Behavioral Genetics

The statistical study of inherited human (physical, mental, and behavioral) differences was pioneered by Galton ( 1869 ). Although at times Galton wrote that nature and nurture were so intertwined as to be inseparable, he nevertheless devised statistical methods to separate their effects. In the 1860s and 1870s, Galton published reports purporting to show how similarities in intellect (genius, talent, character, and eminence) in European lineages appeared to be a function of degree of relatedness. Galton considered, but dismissed, environmental explanations of his data, leading him to confirm his belief that nature was stronger than nurture.

Galton also introduced the use of twin studies to tease apart the relative impact of nature versus nurture, but the twin method he used was markedly different from later twin studies used by behavioral geneticists. Galton tracked the life history of twins who were judged to be very similar or very dissimilar near birth (i.e., by nature) to test the power of various postnatal environments (nurture) that might make them more or less similar over time. Here again, Galton concluded that nature overpowers nurture.

Similar pedigree (e.g., the Kallikak study; see Zenderland, 2001 ) and twin studies appeared in the early 1900s, but the first adoption study and the modern twin method (which compares monozygotic to dizygotic twin pairs) did not appear until the 1920s (Rende, Plomin, & Vandenberg, 1990 ). These reports led to a flurry of additional work on the inheritance of mental and behavioral traits over the next decade.

Behavioral genetic research peaked in the 1930s but rapidly lost prominence due in large part to its association with the eugenics movement (spearheaded by Galton) but also because of the rise and eventual hegemony of behaviorism and the social sciences in the United States. Behavioral genetics resurged in the 1960s with the rising tide of nativism in psychology, and returned to its 1930s-level prominence in the 1970s (McGue & Gottesman, 2015 ).

The resurgence brought with a new statistical tool: the heritability statistic. The origins of heritability trace back to early attempts to synthesize Mendelian genetics with biometrics by Ronald Fisher and others. This synthesis ushered in a new field of quantitative genetics and it marked a new way of thinking about nature and nurture. The shift was to no longer think about nature and nurture as causes of traits in individuals but as causes of variation in traits between populations of individuals. Eventually, heritability came to refer to the amount of variance in a population sample that could be statistically attributed to genetic variation in that sample. Kinship (especially twin) studies provided seemingly straightforward ways of partitioning variation in population trait attributes into genetic versus environmental sources.

Into the early 21st century , hundreds of behavioral genetic studies of personality, intelligence, and psychopathology were reported. With rare exceptions, these studies converge to argue for a pervasive influence of genetics on human psychological variation.

These studies have also fueled much controversy. Citing in part behavioral genetic research, the educational psychologist Arthur Jensen ( 1969 ) claimed that the differences in intelligence and educational achievement in the United States between black and white students appeared to have a strong genetic basis. He went on to assume that because these racial differences appeared hereditary, they were likely impervious to environmental (educational) intervention. His article fanned the embers of past eugenics practices and ignited fiery responses (e.g., Hirsch, 1975 ). The ensuing debates not only spawned a rethinking of intelligence and how to measure it, but they ushered in a more critical look at the methods and assumptions of behavioral genetics.

Challenges to Behavioral Genetics

Many of the early critiques of behavioral genetics centered on interpreting the heritability statistic commonly calculated in kinship (family, twin, and adoption) studies. Perhaps more so than any other statistic, heritability has been persistently misinterpreted by academics and laypersons alike (Lerner, 2002 ). Contrary to popular belief, heritability tells us nothing about the relative impact of genetic and environmental factors on the development of traits in individuals. It deals with accounting for trait variation between people, not the causes of traits within people. As a result, a high heritability does not indicate anything about the fixity of traits or their imperviousness to environmental influence (contra Jensen), and a low heritability does not indicate an absence of genetic influence on trait development. Worse still, heritability does not even indicate anything about the role of genetics in generating the differences between people.

Other challenges to heritability focused not on its interpretation but on its underlying computational assumptions. Most notably, heritability analyses assume that genetic and environmental contributions to trait differences are independent and additive. The interaction between genetic and environmental factors were dismissed a priori in these analyses. Studies of development, however, show that no factor (genes, hormones, parenting, schooling) operates independently, making it impossible to quantify how much of a given trait in a person is due to any causal factor. Thus heritability analyses are bound to be misleading because they are based on biologically implausible and logically indefensible assumptions about development (Gottlieb, 2003 ).

Aside from heritability, kinship studies have been criticized for not being able to disentangle genetic and environmental effects on variation. It had long been known that that in family (pedigree) studies, environmental and genetic factors are confounded. Twin and adoption studies seemed to provide unique opportunities to statistically disentangle these effects, but these studies are also deeply problematic in assumptions and methodology. There are numerous plausible environmental reasons for why monozygotic twin pairs could resemble each other more than dizygotic twin pairs or why adoptive children might more closely resemble their biological than their adoptive parents (Joseph & Ratner, 2013 ).

A more recent challenge to behavioral genetics came from an unlikely source. Advances in genomic scanning in the 21st century made it possible in a single study to correlate thousands of genetic polymorphisms with variation in the psychological profiles (e.g., intelligence, memory, temperament, psychopathology) of thousands of people. These “genome-wide association” studies seemed to have the power and precision to finally identify genetic contributions to heritability at the level of single nucleotides. Yet, these studies consistently found only very small effects.

The failure to find large effects came to be known as the “missing heritability” problem (Maher, 2008 ). To account for the missing heritability, some behavioral geneticists and molecular biologists asserted that important genetic polymorphisms remain unknown, they may be too rare to detect, and/or that current studies are just not well equipped to handle gene–gene interactions. These studies were also insensitive to epigenetic profiles (see the section on Behavioral Epigenetics), which deal with differences in gene expression. Even when people share genes, they may differ in whether those genes get expressed in their lifetimes.

But genome-wide association studies faced an even more problematic issue: Many of these studies failed to replicate (Lickliter & Honeycutt, 2015 ). For those who viewed heritability analyses as biologically implausible, the small effect sizes and failures to replicate in genome-wide association studies were not that surprising. The search for independent genetic effects was bound to fail, because genes simply do not operate independently during development.

Behavioral Epigenetics

Epigenetics was a term coined in the 1940s by the developmental biologist Conrad Waddington to refer to a new field of study that would examine how genetic factors interact with local environmental conditions to bring about the embryological development of traits. By the end of the 20th century , epigenetics came to refer to the study of how nongenetic, molecular mechanisms physically regulate gene expression patterns in cells and across cell lineages. The most-studied mechanisms involve organic compounds (e.g., methyl-groups) that physically bind to DNA or the surrounding proteins that package DNA. The addition or removal of these compounds can activate or silence gene transcription. Different cell types have different, stable epigenetic markings, and these markings are recreated during cell division so that cells so marked give rise to similar types of cells. Epigenetic changes were known to occur during developmental periods of cellular differentiation (e.g., during embryogenesis), but not until 2004 was it discovered that these changes can occur at other periods in the life, including after birth (Roth, 2013 )

Of interest to psychologists were reports that different behavioral and physiological profiles (e.g., stress reactivity) of animals were associated with different epigenetic patterns in the nervous system (Moore, 2015 ). Furthermore, these different epigenetic patterns could be established or modified by environmental factors (e.g., caregiving practices, training regimes, or environmental enrichment), and, under certain conditions, they remain stable over long periods of time (from infancy to adulthood).

Because epigenetic research investigates the physical interface between genes and environment, it represents an exciting advance in understanding the interaction of nature and nurture. Despite some warnings that the excitement over behavioral epigenetic research may be premature (e.g., Miller, 2010 ), for many psychologists, epigenetics underscores how development involves both nature and nurture.

For others, what is equally exciting is the additional evidence epigenetics provides to show that the genome is an interactive and regulated system. Once viewed as the static director of development buffered from environment influence, the genome is better described as a developing resource of the cell (Moore, 2015 ). More broadly, epigenetics also points to how development is not a genetically (or biologically) predetermined affair. Instead, epigenetics provides additional evidence that development is a probabilistic process, contingent upon factors internal and external to the organism. In this sense, epigenetics is well positioned to help dissolve the nature–nurture dichotomy.

Beyond Nature–Nurture

In the final decades of the 20th century , a position was articulated to move beyond the dichotomous nature–nurture framework. The middle-ground position on nature–nurture did not seem up to the task of explaining the origins of form, and it brought about more confusion than clarity. The back-and-forth (or balanced) pendulum between nature- and nurture-based positions throughout history had only gone in circles. Moving forward would require moving beyond such dichotomous thinking (Johnston, 1987 ).

The anti-dichotomy position, referred to as the Developmentalist tradition, was expressed in a variety of systems-based, metatheoretical approaches to studying development, all of which extended the arguments against nature–nurture expressed earlier by Kuo and Lehrman. The central problem with all nativist claims according to Developmentalists is a reliance on preformationism (or predeterminism).

The problem with preformationism, they argue, besides issues of evidence, is that it is an anti-developmental mindset. It presumes the existence of the very thing(s) one wishes to explain and, consequently, discourages developmental analyses. To claim that some knowledge is innate effectively shuts down research on the developmental origins of that knowledge. After all, why look for the origins of conceptual knowledge if that knowledge is there all along? Or why search for any experiential contributions to innate behaviors if those behaviors by definition develop independently of experience? In the words of Developmentalists Thelen and Adolph ( 1992 ), nativism “leads to a static science, with no principles for understanding change or for confronting the ultimate challenge of development, the source of new forms in structure and function” (p. 378).

A commitment to maturational theory is likely one of the reasons why studies of motor development remained relatively dormant for decades following its heyday in the 1930–1940s (Thelen, 2000 ). Likewise, a commitment to maturational theory also helps explain the delay in neuroscience to examine how the brain physically changes in response to environmental conditions, a line of inquiry that only began in the 1960s.

In addition to the theoretical pitfalls of nativism, Developmentalists point to numerous studies that show how some seemingly native behaviors and innate constraints on learning are driven by the experiences of animals. For example, the comparative psychologist Gilbert Gottlieb ( 1971 ) showed that newly hatched ducklings display a naïve preference for a duck maternal call over a (similarly novel) chicken maternal call (Gottlieb, 1971 ), even when duck embryos were repeatedly exposed to the chicken call prior to hatching (Gottlieb, 1991 ). It would be easy to conclude that ducklings have an innate preference to approach their own species call and that they are biologically constrained (contraprepared) in learning a chicken call. However, Gottlieb found that the naïve preference for the duck call stemmed from exposure to the duck embryos’ own (or other) vocalizations in the days before hatching (Gottlieb, 1971 ). Exposure to these vocalizations not only made duck maternal calls more attractive, but it hindered the establishment of a preference for heterospecific calls. When duck embryos were reared in the absence of the embryonic vocalizations (by devocalizing embryos in ovo ) and exposed instead to chicken maternal calls, the newly hatched ducklings preferred chicken over duck calls (Gottlieb, 1991 ). These studies clearly showed how seemingly innate, biologically based preferences and constraints on learning derived from prenatal sensory experiences.

For Developmentalists, findings like these suggest that nativist explanations of any given behavior are statements of ignorance about how that behavior actually develops. As Kuo and Lehrman made clear, nativist terms are labels, not explanations. Although such appeals are couched in respectable, scientific language (e.g., “X is due to maturation, genes, or heredity”), they argue it would be more accurate simply to say that “We don’t know what causes X” or that “X is not due to A, B, or C.” Indeed, for Developmentalists, the more we unpack the complex dynamics about how traits develop, the less likely we are to use labels like nature or nurture (Blumberg, 2005 ).

On the other hand, Developmentalists recognize that labeling a behavior as “learned” also falls short as an explanatory construct. The empiricist position that knowledge or behavior is learned does not adequately take into account that what is learned and how easily something is learned depends on (a) the physiological and developmental status of the person, (b) the nature of the surrounding physical and social context in which learning takes place, and the (c) experiential history of the person. The empiricist tendency to say “X is learned or acquired through experience” can also short-circuit developmental analyses in the same way as nativist claims.

Still, Developmentalists appreciate that classifying behaviors can be useful. For example, the development of some behaviors may be more robust, reliably emerging across a range of environments and/or remaining relatively resistant to change, whereas others are more context-specific and malleable. Some preferences for stimuli require direct experience with those stimuli. Other preferences require less obvious (indirect) types of experiences. Likewise, it can still be useful to describe some behaviors in the ways shown in Table 1 . Developmentalists simply urge psychologists to resist the temptation to treat these behavioral classifications as implying different kinds of explanations (Johnston, 1987 ).

Rather than treat nature and nurture as separate developmental sources of causation (see Figure 1 ), Developmentalists argue that a more productive way of thinking about nature–nurture is to reframe the division as that between product and process (Lickliter & Honeycutt, 2015 ). The phenotype or structure (one’s genetic, epigenetic, anatomical, physiological, behavioral, and mental profile) of an individual at any given time can be considered one’s “nature.” “Nurture” then refers to the set of processes that generate, maintain, and transform one’s nature (Figure 2 ). These processes involve the dynamic interplay between phenotypes and environments.

Figure 2. The developmentalist alternative view of nature–nurture as product–process. Developmentalists view nature and nurture not as separate sources of causation in development (see Figure 1 ) but as a distinction between process (nurture) and product (nature).

It is hard to imagine any set of findings that will end debates about the roles of nature and nurture in human development. Why? First, more so than other assumptions about human development, the nature–nurture dichotomy is deeply entrenched in popular culture and the life sciences. Second, throughout history, the differing positions on nature and nurture were often driven by other ideological, philosophical, and sociopolitical commitments. Thus the essential source of tension in debates about nature–nurture is not as much about research agendas or evidence as about basic differences in metatheoretical positions (epistemological and ontological assumptions) about human behavior and development (Overton, 2006 ).

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Published: 08 January 2021

Nurture might be nature: cautionary tales and proposed solutions

Sara A. Hart ORCID: orcid.org/0000-0001-9793-0420 1 , 2 ,
Callie Little 2 , 3 &
Elsje van Bergen ORCID: orcid.org/0000-0002-5860-5745 4

npj Science of Learning volume 6 , Article number: 2 ( 2021 ) Cite this article

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Human behaviour

Across a wide range of studies, researchers often conclude that the home environment and children’s outcomes are causally linked. In contrast, behavioral genetic studies show that parents influence their children by providing them with both environment and genes, meaning the environment that parents provide should not be considered in the absence of genetic influences, because that can lead to erroneous conclusions on causation. This article seeks to provide behavioral scientists with a synopsis of numerous methods to estimate the direct effect of the environment, controlling for the potential of genetic confounding. Ideally, using genetically sensitive designs can fully disentangle this genetic confound, but these require specialized samples. In the near future, researchers will likely have access to measured DNA variants (summarized in a polygenic scores), which could serve as a partial genetic control, but that is currently not an option that is ideal or widely available. We also propose a work around for when genetically sensitive data are not readily available: the Familial Control Method. In this method, one measures the same trait in the parents as the child, and the parents’ trait is then used as a covariate (e.g., a genetic proxy). When these options are all not possible, we plead with our colleagues to clearly mention genetic confound as a limitation, and to be cautious with any environmental causal statements which could lead to unnecessary parent blaming.

Dissecting polygenic signals from genome-wide association studies on human behaviour

Genetic architecture of Environmental Sensitivity reflects multiple heritable components: a twin study with adolescents

Behavioural genetics methods

Most parents spend hours fretting over decisions about the environment they provide to their children. The scientific literature mirrors this idea. Across a wide range of studies from many psychological domains, researchers often conclude that the environment parents provide and children’s outcomes are causally linked, through environmental transmission (see Box 1 ). For example, a study examining the association of having a home library as an adolescent and later adult literacy, numeracy and technology skills drew our attention because of in-depth coverage in the Guardian ( https://www.theguardian.com/books/2018/oct/10/growing-up-in-a-house-full-of-books-is-major-boost-to-literacy-and-numeracy-study-finds ). This study used a very rich and well-powered dataset, and found a correlation between the number of books in adolescents’ homes and literacy performance in adulthood. They conclude that “growing up with home libraries boosts adult skills”, inferring a causal connection 1 . This is depicted in Fig. 1 . Here we discuss how the correlation between the environments parents provide, the “rearing environment”, and their children’s outcomes can indeed be fully due to a causal association, or importantly, can also be partly or fully due to a genetic confounding, illustrated in Fig. 2 (see Footnote 1 in the Supplementary Notes ). After highlighting the problem, we suggest ways that psychological scientists can examine research questions related to the rearing environment and children’s outcomes in ways that account for, or at least acknowledge, genetic confounding.

Number of books in the home is thought to be an environmental causal effect on children’s reading ability. Figure by ref. 66 available at https://bit.ly/3gl8MVk under a CC BY 4.0 license.

Parents share genes related to reading ability with their children, and also control the number of books in their home. This creates gene–environment interplay. It is important to note that the environmental effect may still have a causal role, even with gene–environment interplay. If genes play a role but are not modeled (as in Fig. 1 ), the correlation between the environmental measure and the child’s trait is genetically confounded. Here, the role of genes is modeled, allowing for an estimation of the genetic effect and the environmental effect. Figure by ref. 66 available at https://bit.ly/31c52z9 under a CC BY 4.0 license.

Genetic control of exposure to the environment

Decades of work from behavioral genetics show that children’s traits are influenced by both genetic and environmental effects 2 , 3 . Likely more surprising to hear for most is that genetic influences are often seen on measures of the “environment”, suggesting that the contexts surrounding children are partly under genetic control 4 . For example, a meta-analysis found cumulative support for genetic influences on the parenting children received 5 . This idea, that there is genetic influence on exposure to environments, is called a gene–environment correlation. A gene–environment correlation describes the process by which a person’s genotype influences their exposure to the environment 6 . It is certainly not the case that genes are doing this directly, but instead genotypes matter for aspects of our personality, behaviors and cognitions, which then influence how we interact with our environment and how others interact with us 7 . This concept of an individual purposely and dynamically interacting with their surrounding environment is not limited to behavioral genetics; similar processes have been described in other literatures, for example person-centered interactions 8 and the Selective Optimization with Compensation 9 .

Specifically, there are three types of gene–environment correlations that can result in genetic confounds 6 . First, a “passive gene–environment correlation” describes the association between the genotype a child inherits from their parents and the environment the child is raised in. Another way to think of it is that genes are a third variable which influence both the rearing environment a child receives as well as the child’s own traits, via genetic transmission from parents to child. This means it is not possible to draw causal conclusions between the rearing environment and children’s traits. For example, home environments have been found to be less chaotic for children with high effortful control, with results indicating that the same genes in parents which contribute to the levels of structure in their home (i.e., factors such as absence of noise and crowding, as well as presence of structure and routine) are also transmitted to their children and contribute to effortful control 10 . Second, an “evocative gene–environment correlation” is when a person’s genetically influenced trait elicits, or evokes, a specific response from others in the environment. For example, it has been found that a person’s genes are associated with being rated as “more likeable” by others, meaning how others perceive you as a social partner, and then likely interact with you, is influenced by your genes 11 . Third, an “active gene–environment correlation” describes the association of a person’s genetically influenced traits and the environments they select. For example, the genetically influenced personality trait of socialization, measured in childhood, was associated with exposure to risky environments related to substance abuse in adolescence, in that children with low socialization were exposed to more risky environments 12 . All three have the potential to cloud the true combination of genetic and environmental influences transmitted between parents and children (i.e., genetic confounding), but it is theorized that passive gene–environment correlations have a greater effect in childhood 13 , and as such passive gene–environment correlations are the focus of our review.

To give an example of how (passive) gene–environment correlations can result in genetic confounding in studies focused on the rearing environment, a high impact finding reported that parents with higher math anxiety have children with higher math anxiety, solely due to the home environment 14 . The authors attribute helping with math homework as the causal environmental factor, concluding that parents with high math anxiety should not help with their children’s math homework. This causal connection could exist, but equally parents with math anxiety also pass on genetic (and environmental) risks related to both lower math cognition and higher math anxiety 15 . Because this genetic transmission was not controlled for, causal claims and associated parenting advice are not justified.

Another example, this time from the medical literature, examined the intergenerational transmission of smoking behavior from parents to adolescents, concluding that “the attitudes, beliefs, and behaviors toward [adolescent] cigarette use are learned through [parent] modeling” 16 . Again, this study focused on the environmental transmission from parents to offspring without accounting for the transmission of genes related to smoking behaviors and risk-taking behaviors 17 . Furthermore, the authors conclude that smoking cessation interventions in adults can reduce smoking in subsequent generations. Parent-centered interventions might help to reduce adolescent smoking, but what is overlooked is that children carry their own genetic risks for smoking, and direct intervention with the adolescents 18 could more strongly influence their smoking behaviors.

We are certainly not the first to point out this familial transmission confound within the ecological literature. Indeed, nearly 40 years ago, Scarr and McCartney proposed that “the human experience and its effects on development depend primarily on the evolved nature of the human genome” 13 , and nearly 30 years ago Plomin and Bergeman 19 addressed the prevalence of genetic confounding by illustrating that genetic influences are found on most if not all environmental measures. Since then, several reviews have pointed to multiple examples from parental warmth to alcohol use to depression where causal pathways from parent behavior to child outcomes are reported, without accounting for genetic confounding 20 , 21 , 22 . These reviews have called for researchers to use caution with causal statements, and to address genetic confounding in their limitations. Further, they have asked for journal editors and reviewers to be better watch-dogs in this endeavor; to insist that manuscripts adhere to these standards. However, based on our experience listening to conference presentations and reading press releases and newspaper articles, we believe these guidelines are not yet being met.

We believe a reason why these previous reviews have not successfully changed minds and methods is because they have not given actionable correlational design solutions to researchers outside of behavior genetics. Therefore, when faced with not doing the work or publishing work with only a potential genetic confound, researchers have chosen the latter. Therefore, in the following section we will give many possible solutions, from genetically sensitive designs to design solutions that work in lieu of genetically sensitive data, and finally, a renewed call for changes in reporting standards.

Box 1 A glossary of some key terms

Environmental transmission (also called: cultural or phenotypic transmission):	Transmission of traits from parents to their children by non-genetic means. It is used to describe when parents’ traits impact their child’s traits through the environment they create.
Familial Control Method:	Using a measure of the same trait in the parent as the child as a covariate in models estimating the effect of the rearing environment. That covariate then serves as a proxy control for the genetic transmission effect.
Familial transmission:	Transmission of traits from parents to their children, both by genetic and non-genetic means. Familial transmission gives rise to parent–child resemblance.
Gene–environment correlation:	Genetic influence on the exposure to the environment. There are three types: passive, evocative, and active (see text).
Genetic confounding:	Confounding due to gene–environment correlation. Here we focus on confounding due to a gene–environmental correlation, describing a situation where the influence of parental traits on children’s traits is not (solely) due to environmental transmission.
Genetic transmission:	Transmission of traits from parents to their children by genetic means (i.e., children inherit genes from their parents for a given trait).
Genotype:	An individual’s complete heritable information. A combination of alleles for a specific gene or across the whole genome.
GWAS:	Genome-wide association study. Identifies genetic variants (i.e., SNPs) across the genome that are linked to a trait.
Phenotype:	An individual’s observable traits, like eye color, reading ability, or parenting style.
SNP (pronounced “snip”):	Single nucleotide polymorphisms (SNPs). A single position in a DNA sequence that varies among individuals. For example, if a particular SNP can be nucleotide G or nucleotide C, then individuals can have GG, GC, or CC (one nucleotide from each parent). SNPs are the basis for genome-wide association studies.

What researchers can do

The designs that we discuss below present a not all-encompassing but global overview of genetically sensitive designs and polygenic-scores (PGS) designs, and include a genetic-proxy control design (the “Familial Control Method”), which we recommend when genetically sensitive data are not available, as well as several other proxy control designs. These designs vary in how well they disentangle the genetic confound and in how challenging they are in terms of obtaining and analyzing the data.

Genetically sensitive designs

Genetically sensitive designs are ideal for studying genetic and environmental influences and their interplay. These designs take advantage of samples of related individuals that differ in genetic relatedness (e.g., monozygotic and dizygotic twins; Fig. 3 ) or differ in environmental exposure (e.g., monozygotic twins reared apart). By far the most commonly used genetically sensitive design is the classical twin design. This design works because twins share either all (identical or monozygotic twins) or half (non-identical or dizygotic twins) of their genes 23 . Both types of twins share some parts of their environment such as their home, school, and neighborhood (referred to as common or shared environmental influences), and experience some aspects of their environments separately from each other such as peer groups, hobbies, or illness (referred to as unique or non-shared environmental influences). By comparing the average correlation between the two twins in a twin pair on a trait for monozygotic versus dizygotic twins, variance can be partitioned into additive genetic influences or heritability, shared environmental influences, and non-shared environmental influences (see Footnote 2 in the Supplementary Notes ) (Fig. 4 ). Heritability of a trait is indicated if the correlation between monozygotic twins is higher than that of dizygotic twins. Shared environmental influences are estimated by subtracting the heritability estimate from the monozygotic twin correlation, and the estimated shared environmental influences is larger when the correlation coefficient between monozygotic versus dizygotic twins are close in magnitude. Finally, non-shared environmental influences are estimated by subtracting the monozygotic twin correlation from one.

The scatter plots depict how much the two types of (reared-together) twins resemble their co-twin on reading ability. Each dot represents the reading scores of both children within a pair. It can be seen that monozygotic twins are much more alike. From this, it can be concluded that differences between children are largely due to genetic differences. The data come from van Bergen et al. 34 and represent word-reading fluency test scores in Grade 2 of twin pairs with complete data. The score is the number of words read correctly within 1 min. In this sample, the monozygotic and dizygotic twin correlations were 0.84 and 0.46, respectively, which yield estimates using the Falconer formulas 67 of A = 0.76, C = 0.08, and E = 0.16 (see Fig. 4 ). Figure by ref. 66 available at https://bit.ly/3k4w2Ji under a CC BY 4.0 license.

In behavioral-genetic models, the three sources of influences on individual differences are commonly labeled by the letters A, C, and E, respectively, stemming from A dditive genetic influences (also known as heritability, and sometimes represented by an h 2 instead on an A), C ommon environmental influences (also known as shared environmental influences), and non-shared E nvironmental influences (and measurement E rror). Note that the latter are by definition uncorrelated between twins. See for a detailed representation of the classical twin model, for example, Figure A.9 in ref. 23 ; r MZ = monozygotic twin correlation; r DZ = dizygotic twin correlation. Figure by ref. 66 available at https://bit.ly/2Xkr29P under a CC BY 4.0 license.

With regard to disentangling possible genetic confounds and instead studying the direct effect of specific aspects of the rearing environment, classical twin studies are limited because both type of twins commonly share their rearing environments. For example, twin children growing up together are exposed to the same home library or household income, so monozygotic and dizygotic twin resemblance cannot be compared for these types of environmental measures. However, a classical twin study can begin to separate the direct effect of the home environment in two cases. First, child twins can be asked to individually rate their own rearing environment (Fig. 4 ). Since individual experiences are correlated with genetic predisposition, monozygotic twins often rate their experiences of the home environment more similarly with each other than dizygotic twins do. Therefore, when child twins can report their own ratings of their rearing environment, these estimates can serve to differentiate monozygotic and dizygotic twins. Twins who are children might not differ in how many books they have in the home, but they will likely differ in how much their parents read to them, or how much their parents monitor their reading. In these cases, the extent to which aspects of children’s rating of their rearing environment do not show entirely environmental influences, in other words, some heritability is measured on the “rearing environment”, this infers that there is a genetic confound, via a passive gene–environment correlation 4 , 19 . Using child twin ratings of their rearing environment, Hanscombe et al. 24 found that 22% of the variance of chaos in the home was attributable to genetic factors, and moreover, 37% of association between chaos in the home and school achievement was due to shared genes. This suggests that this “environmental” variable of chaos in the home, measuring noise and lack of structure in the home, is partially genetically confounded. This means that chaos in the home does not have a completely direct, or causal role, on children’s school achievement.

The second way that the classical twin model can be used to identify the direct effect of the home environment, free of genetic confounding, is by focusing on the environment that adult twins create (see Fig. 4 , but replace “reading ability” with “books in their home” or the like). When twins are adults they can differ in how many books they own and the income of their household, so genetic and environmental influences on their home environments can be studied. These studies quantify genetic and environmental influences on the home environment that twins create 4 , but they do not quantify the influence of these home characteristics on outcomes in their offspring.

Other genetically sensitive designs that can address the direct effect of the rearing environment, after accounting for genetic confounding, are adoption studies, within-family sibling studies, and twin-family studies 25 . In an adoption design, resemblance between adopted children and their biological parents is due to heritability (plus the prenatal environment). In contrast, resemblance between adopted children and their adoptive parents is fully due to the environment that the parents have provided. Another way to examine the rearing environment while partially controlling for genetic confounding is to use non-twin biological siblings within a family 26 , 27 . Because biological siblings, like dizygotic twins, share half of their genes, sibling resemblance on a trait suggests the influence of genetic factors along with some shared environmental influences. However, non-twin siblings can differ on several aspects of the rearing environment such as family size or parental health and age at birth, therefore, any dissimilarity between siblings can help to determine the influences of these non-shared aspects of the rearing environments on a given trait. Sibling designs have also recently incorporated the use of genome-wide PGS which strengthen their ability to control for confounding by disentangling direct genetic influences from gene–environment correlations 28 , 29 . PGS designs are discussed in more detail, below.

Twin-family studies include twins and their family members, like young twins and their parents, or adult twins and their children. The latter, referred to as children-of-twins design (Fig. 5 ), is particularly suitable to study the effect of children’s rearing environment, free of genetic confounding 21 . Put simply, consider a mother who has an identical twin sister. The mother’s son shares half of his genetic variants with his mother, but also with his aunt. If for a given trait he resembles his mother as much as his aunt, this suggests that the resemblance is fully due to shared genes. Conversely, if he is more like his mother than aunt, this demonstrates that the resemblance between mother and son is at least partially due to the environment provided by his mother (see Footnote 3 in the Supplementary Notes ). There are even more complex extended twin family designs, described well in Keller et al. 30 and McAdams et al. 31 .

In the given example, the (adult) twins are sisters. The genetic transmission (left hand side) is fixed at 0.50 because parents and children share 50% of their genome. The other set of genes that influence the child trait (bottom left) are genetic influences that explain variance in the child trait but not the parent trait. The crucial test for presence of environmental transmission is whether the p-path is significant. Note that ‘child’ can refer to child or adult offspring. See, for the full and detailed model, ref. 31 . Figure by ref. 66 available at https://bit.ly/2D0aNYJ under a CC BY 4.0 license.

In sum, genetically sensitive designs can assess whether the rearing environment is influencing children’s outcomes, outside of genetic confounds. Although they are observational and hence cannot establish causality, or the absence thereof, they can strongly infer causality above and beyond the majority of typical observational studies. An important point to make is if a genetically sensitive study suggests no direct causality of the rearing environment on children’s outcomes, it does not imply that intervening is pointless. Successful parenting interventions are able to experimentally induce changes in parents’ skills or behaviors, which then causally improve child outcomes. Thus, observational studies, such as all the genetically sensitive designs described here, and experimental studies (preferably randomized controlled trials 32 ) answer related but different questions: the first on “what is”, so causality in the natural situation, and the second on “what could be”, so causality due to intervening 33 , 34 .

Returning to genetically sensitive designs, the disadvantage is that they require access to such data, which are challenging to collect and analyze. We note for a reader interested in using twin data to better answer their questions about the direct role of the rearing environment, twin datasets are increasingly becoming publically available. For example, TwinLife ( https://www.twin-life.de/en ), TEDS ( http://www.teds.ac.uk/researchers ), NLSY kinship links ( http://nlsy-links.github.io/NlsyLinks/ ), Netherlands Twin Register ( http://tweelingenregister.vu.nl/research ), and others are available online or via application. In addition, there is a data sharing culture in the behavioral genetics community, and most will likely share when asked. We suggest that researchers consider using these resources to better test their research questions.

PGS designs

A new avenue to study intertwined genetic and environmental effects employs genome-wide PGS. This method relies on genome-wide association studies (GWASs) which pinpoint genetic variants (i.e., single nucleotide polymorphisms (SNPs)) that are linked to a trait (Fig. 6 ). The most powerful GWAS to date ( N > 1 million) has identified 1271 genetic variants associated with educational attainment 35 . Each of them has a tiny effect, but these tiny effects can be summed in a PGS. The PGS, calculated for all (unrelated) individuals in an independent sample, explains 12% of the variance in educational attainment. Note that twin studies estimate the heritability of educational attainment at 40% 36 , so the PGS currently captures less than one-third of this; the remainder is the “missing heritability” 37 .

Left panel: A published genome-wide association study (GWAS) serves as an external database. In an extremely large sample, a GWAS estimates tiny associations ( \({\hat{\mathrm b}}\) ) between the trait of interest and millions of genetic variants. Specifically, the genetic variants studied are single-nucleotide polymorphisms (SNPs), located across the genome. Middle panel: Polygenic scoring can be done in a sample that was not part of the GWAS. For each individual in this sample, the SNP effects ( \({\hat{\mathrm b}}\) ) are multiplied by the number of trait-associated alleles (0, 1, or 2) the person carries. These values are summed across all SNPs to arrive at the individual’s PGS. Right panel: The resulting PGSs across individuals in that sample are normally distributed. If the trait of interest is a disorder, like ADHD, the individuals in the right tail have the highest genetic risk for developing ADHD. PGSs are not yet strong enough for predictions at the individual level, but see the main text for examples of how PGSs advance science at the group level. Figure adapted from ref. 69 . Figure by ref. 66 available at https://bit.ly/2BPcCXP under a CC BY 4.0 license.

As we speak, novel methods are being designed to disentangle nature and nurture that draw on PGS. Below, we list some examples of recent developments. First, Dolan et al. 38 bring PGS into the classical twin design. By doing so, one can estimate the gene–environment correlation, rather than assume it is absent. Second, Lee et al. 35 and Selzam et al. 29 found that for cognitive traits, the predictive power of a PGS within a family was about 50% lower than across unrelated individuals. The attenuation of the PGS’ predictive power within families suggests that passive gene–environment correlations (as captured by the PGS) contribute to children’s cognitive development. As a third example, both Kong et al. 39 and Bates et al. 40 separately proposed the same design incorporating parental and offspring PGS to disentangle environmental transmission from genetic transmission (i.e., account for the genetic confound between the home environment and child outcomes). In both cases, the researchers split the genetic variants of the parents in half—those that the parent had and had not transmitted to the offspring—and calculated for each half the PGS for educational attainment (Fig. 7 ). The researchers do this because of the biological fact that a parent only transmits a random half of their genes to their child. And for this design to work, both parents and their child must be included (but see ref. 41 for a work around). Amazingly, what the researchers found was both sets of parent PGS predicted adult offspring’s educational attainment. The predictive value of the transmitted PGS was unsurprising, as this captures directly transmitted genetic effects. But the predictive value of the non-transmitted PGS was not certain. If non-transmitted PGS influence children’s traits, this effect must be environmental, likely acting through rearing behaviors that affect the child’s development. Kong et al. 39 aptly coined this genetic effect through the rearing environment “genetic nurturing”. Belsky et al. 42 did a similar analysis but with an updated PGS score. Interestingly, when this design is expanded to include grandparents, there is little evidence for genetic nurturing from the grandparent generation 43 . Fourth, Wertz et al. 44 incorporated both PGS of mothers and children, as well as direct measures of parenting. They showed that mothers’ cognitive stimulation explained the relation of the maternal non-transmitted PGS to child educational attainment. This indicated that there is a direct environmental transmission of parenting on children’s outcomes, unconfounded by correlated genetic transmission. Finally, de Zeeuw et al. 45 and Willoughby et al. 46 both used the full genetic-nurturing design (employing DNA of children and both parents) and found (thereby replicated) genetic-nurturing effects on adults’ educational attainment. Crucially, for outcomes in childhood, academic achievement and ADHD-symptoms, Zeeuw et al. 45 only found direct genetic effects; no genetic nurturing. They concluded that a large contributor to why the rearing environment predicts child outcomes may well be intergenerational transmission of genetic effects.

In this design, one needs genotypes of parents and offspring, and a measured trait in the offspring generation only. The trait in the parents, for example educational attainment, is unobserved and indexed by a polygenic score of, in this example, educational attainment. The child receives half of the genotypes of father (top left) and mother (top right) and these transmitted alleles influence the child trait directly. The parental alleles that the child does not receive can still influence the child trait indirectly, via genetically influenced behaviors in the parents (denoted by the dotted genetic-nurturing paths). Genetic nurturing is present if the polygenic score of the untransmitted alleles explains a significant proportion of the variance in the child trait. The proportion of variance explained by the polygenic score of the transmitted alleles include both genetic nurturing and direct effects. Note that ‘child’ can refer to child or adult offspring. T = transmitted, NT = non-transmitted. Figure adapted from ref. 39 . Figure by ref. 66 available at https://bit.ly/2PjpkRu under a CC BY 4.0 license.

At the moment, measured genetic variants only explain small proportions of variance and the papers mentioned above may be seen by behavioral researchers as only a proof-of-principle. Nevertheless, these exciting developments will gain in strength when increasingly larger GWASs of all sorts of traits yield more refined PGS. By this we mean that PGSs will begin to explain more and more portions of the variance in outcomes we are interested in, with the hope that eventually they will reach the theoretical upper limit of SNP heritability. Even then, using them as a genetic control (i.e., as a covariate) will continue to underestimate the total genetic effects we are looking to control. PGSs account for only one type of genetic effect, namely common variants. There is increasing evidence that traits such as educational attainment are influenced by not only common variants, but also rare variants 47 , 48 . Another concern is that new work is indicting that a PGS is not a measure of only genetic variance. Instead, it likely represents not only causal genetic effects, but genetic ancestry, assortative mating, gene x environment interactions, direct environmental influences (i.e., genetic nurture), and environmental confounds from, for example, SES 49 , 50 . Therefore, a measure of genes (i.e., a PGS) can predict trait variance via environmental routes. This parallels our earlier notion that a measure of the environment can predict trait variance via genetic routes.

In summary, at the moment the PGS is not a perfect “genetic control”, as it does not account for all of the genetic effects and also accounts for other effects, including the very environment we are interested in. But, we believe that next to no control, using a PGS as a statistical control is still better. Costs of genotyping are falling and the number of cohorts with genotype data is growing 51 . We predict that in the not-so-far future, using simply and cheaply collected genotypic information will become a regular part of the behavioral researchers’ data collection protocol, especially as the predictive validity of the PGSs increases. This means that PGSs will allow researchers to partly control for genetic confounds in their models. We foresee that it will be easier to use PGSs than rely on genetically sensitive designs.

Genetic-proxy control designs: the Familial Control Method

The designs discussed above are the current gold-standards. However, as these types of samples discussed above are not currently easy to collect and analyze, we propose here a useful work around 52 , 53 . Our colleagues can measure the same trait in both the parents as the child, and use the paternal and maternal traits as covariates. We advise to assess the traits in both parents (but acknowledge the challenge that brings), because the child shares only 50% of their genes with one parent, but all of their genes with both parents. Hence, both parents are needed to best tag the child’s genetic liability. The parental traits, included as two covariates, then serve as a proxy for the familial transmission, including genetic transmission. In doing so, you have a proxy control for the familial effect. Hence, we term this method the Familial Control Method.

The Familial Control Method is designed for traits that are mostly transmitted from parent to child through genes rather than the environment, like reading ability 54 , 55 (see Footnote 4 in the Supplementary Notes ). Van Bergen et al. 53 capitalized on this in studying whether children’s reading ability is influenced by the home literacy environment, like reading habits of the parents and the number of books in the home. Analyses consisted of straight-forward step-wise regression analyses, illustrated in Fig. 8 . The home literacy environment correlated with children’s reading ability, but for most home-literacy indicators the effect was no longer significant after accounting for the reading ability of the parents. This suggests genetic confound rather than a genuine environmental effect. The one exception was the number of books children grow up with, which did explain variance over and beyond parents’ reading skills (Fig. 8 ). This suggests a genuine environmental effect on children’s reading by the number of books itself, or something related, like the value that the family places on reading 45 .

The findings that are depicted here come from van Bergen et al. 53 . The key question is whether the environmental measure explains variance beyond the familial effect, as this indicates a genuine environmental effect. In the example given, this was 5% and significant. This was negligible and non-significant for the other environmental measures reported in ref. 53 . Figure by ref. 66 available at https://bit.ly/2Pfjelh under a CC BY 4.0 license.

A similar approach was taken by Hart et al. 52 in studying the effect of the home numeracy environment on children’s math ability. When a parent’s math ability was included in the model, some effects of aspects of the home numeracy environment on children’s math ability were attenuated, but most held up. A note of caution is that the skills of only one parent could be obtained and controlled for, so the study lacked a proxy for the genetic liability passed on by the other parent. The authors concluded that doing more math-related activities with your children does seem to directly boost their math.

We advise researchers who are interested in applying the Familial Control Method to search first in the literature for adoption and twin-family studies. Such studies with the outcome trait of interest (e.g., reading ability) assessed in both the parent and the offspring generation, test whether parent to offspring transmission is mainly genetic or environmental in nature 54 , 55 . However, such studies are scarce. If such studies for the trait of interest do not exist, a good starting point are classical twin studies. Traits with no or a small influence of the shared environment (referred to as C), like neurological traits, are more likely to be transmitted just genetically compared to traits with large shared-environment influences, like social values. Results of meta-analyses of twin studies on a very large number of traits can be found in Polderman et al. 2 and the accompanying webtool ( http://match.ctglab.nl/ ).

The Familial Control Method, using a parental trait as genetic proxy, is not watertight, and certain assumptions must be made for it to be effective for your research question (see Footnote 5 in the Supplementary Notes ). First, if, for a certain trait, parent–child resemblance is not only due to genetic transmission but also environmental transmission, the Familial Control Method can be too conservative, as it also takes away some of the variance due to true environmental effects. However, one could argue that for many situations, being slightly too cautious in causal claims about environmental influences is less harmful than being too lax. However, this might not be the case for all researchers, and we encourage behavioral researchers to consider if being too conservative is actual harmful (e.g., for the effect of an unsafe home environment on child psychopathology) Second, as mentioned earlier, the trait measured in the parents should be the same or highly similar as the trait measured in the child. This means that traits which are not at least reasonably the same in childhood as adulthood (i.e., across birth cohorts and across the lifespan) would not work in this design. So the trait should be at least reasonably measurement invariant and relatedly, show reasonable genetic stability. Fortunately, for many phenotypes, children’s phenotypes are simply developmental precursors to the adult phenotypes (e.g., for reading ability 56 , and for ADHD 57 ). A researcher must decide if the mentioned assumptions are appropriate for their trait of interest, but fortunately we do believe that these assumptions are reasonable for most to make. Third, correlations among the parent and child trait and the environmental measure of interest will be attenuated by measurement error. To reduce measurement error, one can do regressions according to the Familial Control Method in a structural equation modeling framework, with multiple indicators per construct. One can fit a model with as the outcome the latent child trait of interest, and as (correlated) predictors, the latent traits of both parents and the environmental measure of interest. If dropping the regression path ‘environmental measure → child outcome’ leads to a significantly worse model fit, this implies that the environmental measure is associated with the outcome above and beyond the familial effect. If the trait of interest is genetically transmitted, this equates to above and beyond genetic confounding, so suggests a direct environmental influence. The effect size here is given by the difference in explained variance in the child outcome of the models with and without the ‘environmental measure → child outcome’ path. Adopting a structural equation modeling framework with latent variables is especially advisable for constructs that are notoriously hard to measure reliably. Another advantage of this framework, compared to stepwise regressions, is that families with missing data can be retained.

It is likely the case that for most behavioral researchers interested in the direct role of the rearing environment, the Familial Control Method is currently the most feasible proxy genetic control. It does not require data of twin or adoption families, nor collecting DNA samples. In terms of prediction, parental traits capture more of the variance in children’s outcome than polygenic scores, so likely also capture more of the genetic confound. For the example of reading ability, it has been found that the abilities of both of the parents explain 21% of the ability of children 58 . In comparison, polygenic scores (based on the educational-attainment GWAS) have been found to explain only 2–5% of reading ability in children 59 , and more recently 5–14% of “educational achievement” (including reading, writing, speaking, listening, and mathematics) in ages 7 to 16 years 60 . Certainly this proportion of variance explained from simple polygenic scores is not trivial, and the predictive ability of polygenic scores is anticipated to increase in the coming years. However, for most behavioral scientists the trait in the parents is not only easier to measure, but currently also a better predictor. On a related note, the value of parental traits as predictors of child outcomes has been used for decades in studying precursors of developmental disorders. In such family-risk studies, children with a family history of say dyslexia, attention-deficit/hyperactivity disorder or autism are followed from an early age, before the disorder manifests itself. These children have an increased risk to develop the disorder 61 , 62 .

Other proxy control designs

Other proxy controls such as sociodemographic factors (e.g., SES) have been used ubiquitously, but these statistical adjustments are not capable of accounting for genetic confounding as adequately as the Familial Control Method, for several reasons. First, although sociodemographic factors such as educational attainment have been significantly associated with genetic factors through twin studies (40% 36 ) and GWAS (~14% 35 ), the estimates are less than unity which indicates that genetic influences are not entirely responsible for individual differences in SES. Indeed, work examining the intergenerational transmission of SES has suggested that both genetic and environmental transmission occurs 63 . In this scenario where SES is transmitted through genetic and environmental pathways, when controlling for SES in data analyses, a proportion of variance attributable to other background or environmental factors is also being controlled for in the model, unintentionally leading to reduced associations between potentially important family-level predictors and child outcomes. In other words, you’d be throwing the baby out with the bathwater.

On the other hand, controlling for SES does not actually control for all of the genetic confounding. Say a researcher is interested in controlling for genetic confounding when examining the direct influence of books in the home on children’s reading. Parental SES is a proxy for parental reading skill, but not a perfect correlate (average correlation is 0.26 64 ). Controlling for parental SES would not control for all of the potential genetic confounds on the association between books in the home and children’s reading ability. In conclusion, when controlling for SES, other potential sources of environmental variance are also being removed from the prospective models, and at the same time would not capture the extent of genetic confounding. We believe this would happen with other proxy control measures as well, outside of the Familial Control Method described above.

Here we have laid out numerous ways that genetic confounding can be controlled for when examining the rearing environment, summarized in a decision flowchart (Fig. 9 ). We can certainly foresee times that none of these options are possible. Therefore, we conclude that in those instances, our colleagues need to clearly mention the possible genetic confounding as a limitation, and to be cautious with any environmental causal statements which could lead to unnecessary parent blaming or to interventions that are a waste of time and resources. To return to our first example, expecting all homes to have plenty of books is an idealistic goal, as it would surround all children with the opportunity to read if they wished. But unfortunately, having the opportunity to read as one wishes does not unlock the code of reading for all children. Reading is a skill that requires direct instruction and practice, and children with a family history of dyslexia themselves have a 45% chance of dyslexia despite adequate instruction and practice 61 . Simply having books around the home is not enough 65 , yet the message that parents are getting is that it is. The take home messages from that are that either parents who do not have the resources for a home library are hurting their children, or parents with children struggling to read are at blame because they did not have quite enough books in the home. This is unfair and inaccurate. In the end, we believe that it is important to discover true environmental effects as well as how genes and environments interplay, especially when malleable, because then we can focus as a field on creating and testing interventions that have a greater chance of directly improving children’s outcomes.

DK = don’t know. Figure by ref. 66 available at https://bit.ly/3gkM6Et under a CC BY 4.0 license.

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Acknowledgements

S.A.H. is supported by Eunice Kennedy Shriver National Institute of Child Health & Human Development Grants HD052120 and HD095193. Views expressed herein are those of the authors and have neither been reviewed nor approved by the granting agencies. E.vB. is supported by NWO VENI fellowship 451-15-017 (“Decoding the gene-environment interplay of reading ability”) and ZonMw grant 531003014 (“Genetics as a research tool: A natural experiment to elucidate the causal effects of social mobility on health”). She is a member of the Consortium on Individual Development (CID; NWO Gravitation grant 024.001.003) and of Research Institute LEARN!.

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Hart, S.A., Little, C. & van Bergen, E. Nurture might be nature: cautionary tales and proposed solutions. npj Sci. Learn. 6 , 2 (2021). https://doi.org/10.1038/s41539-020-00079-z

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ORIGINAL RESEARCH article

Nature vs. nurture: disentangling the influence of inheritance, incubation temperature, and post-natal care on offspring heart rate and metabolism in zebra finches.

Centre d’Etudes Biologiques de Chizé, CNRS—La Rochelle Université, Villiers en Bois, France

A historic debate in biology is the question of nature vs. nurture. Although it is now known that most traits are a product of both heredity (“nature”) and the environment (“nurture”), these two driving forces of trait development are rarely examined together. In birds, one important aspect of the early developmental environment is egg incubation temperature. Small changes (<1°C) in incubation temperature can have large effects on a wide-array of offspring traits. One important trait is metabolism, because it is related to life-history traits and strategies, organismal performance, and energetic and behavioral strategies. Although it has been shown that embryonic and post-hatch metabolism are related to egg incubation temperature, little is known about how this may vary as a function of genetic differences or post-hatching environmental conditions. Here, we investigated this question in zebra finches ( Taeniopygia guttata ). We experimentally incubated eggs at two different temperatures: 37.5°C (control), which is optimal for this species and 36.3°C (low), which is suboptimal. We first measured embryonic heart rate as a proxy of embryonic metabolic rate. Then, at hatch, we cross-fostered nestlings to differentiate genetic and pre-hatching factors from post-hatching environmental conditions. When offspring were 30 days-old, we measured their resting metabolic rate (RMR; within the thermoneutral zone) and thermoregulatory metabolic rate (TMR; 12°C; birds must actively thermoregulate). We also measured RMR and TMR of all genetic and foster parents. We found that embryonic heart rate was greater in eggs incubated at the control temperature than those at the low temperature. Further, embryonic heart rate was positively related to genetic father RMR, suggesting that it is both heritable and affected by the pre-natal environment. In addition, we found that post-hatch metabolic rates were positively related to genetic parent metabolic rate, and interactively related to incubation temperature and foster mother metabolic rate. Altogether, this suggests that metabolism and the energetic cost of thermoregulation can be influenced by genetics, the pre-natal environment, and the post-natal environment. Our study sheds light on how environmental changes and parental care may affect avian physiology, as well as which traits may be susceptible to natural selection.

1 Introduction

Whole-organism metabolism is a fundamental aspect animal physiology, and thus understanding the drivers of individual variation in metabolism is crucial ( Burton et al., 2011 ; White and Kearney, 2013 ; Pettersen et al., 2018 ). Resting metabolic rate (RMR) represents an individual’s minimum energy requirements for self-maintenance ( Daan et al., 1990 ; Bryant, 1997 ), excluding physiological processes such as thermoregulation, digestion, and activity ( McNab, 1997 ). RMR is important for understanding basal metabolic rate, and is also related to individual life history traits and strategies, performance, energetic strategies, behavior, reproductive success, and survival ( Careau et al., 2008 ; Biro and Stamps, 2010 ; Williams et al., 2010 ; Careau and Garland, 2012 ; Rønning et al., 2016 ; Auer et al., 2018 ; Pettersen et al., 2018 ). While metabolic rate varies depending on current environmental conditions ( Broggi et al., 2004 ; Norin and Metcalfe, 2019 ), there is evidence that, across taxa, individual differences in metabolic rate are repeatable ( Nespolo and Franco, 2007 ; Careau et al., 2008 ; Broggi et al., 2009 ; Réveillon et al., 2019 ; Baškiera and Gvoždík, 2021 ; Dezetter et al., 2021 ) and heritable (reviewed in Pettersen et al., 2018 ). Further, conditions during early development and parental effects can also have lasting effects on individual metabolism ( Burton et al., 2011 ). For example, in oviparous species, maternal hormone deposition to eggs can affect offspring post-hatch metabolic rate ( Groothuis et al., 2005 ; Tobler et al., 2007 ; Nilsson et al., 2011 ). However, little is known about how different drivers (e.g., heritability and parental effects) may interact to influence metabolism ( Burton et al., 2011 ; White and Kearney, 2013 ; Pettersen et al., 2018 ; McFarlane et al., 2021 ). Understanding the sources of inter-individual variation in metabolism will shed light on how environmental changes, parental care decisions, and natural selection can shape this important aspect of physiology.

In birds, some of the most important sources of variation in offspring physiology arise from parental care decisions. Aside from important maternal effects during egg-laying (e.g., nutrient/hormone transfer to eggs; ( Groothuis et al., 2005 ; Tobler et al., 2007 ; Nilsson et al., 2011 ), two essential ways in which parents must ensure proper offspring development are through egg incubation and post-hatch nestling care. Incubation is necessary for eggs to hatch ( Deeming and Ferguson, 1991 ), but energetically costly and time consuming for parents ( Tinbergen and Williams, 2002 ; Nord and Williams, 2015 ). In turn, incubation investment varies among parents, due to factors such as ambient temperature, clutch size, parental experience, and individual quality ( Aldrich and Raveling, 1983 ; Haftorn and Reinertsen, 1985 ; Conway and Martin, 2000 ; Ardia and Clotfelter, 2007 ; Coe et al., 2015 ; Amininasab et al., 2016 ; Hope et al., 2020 ; Williams et al., 2021 ). This causes incubation temperatures to vary both among and within nests ( Boulton and Cassey, 2012 ; Coe et al., 2015 ; Hope et al., 2021 ). Importantly, small differences in temperature can have large effects on offspring physiology, such as metabolic rate, thermoregulation, glucocorticoid hormone levels, immune function, and telomere length ( Nord and Nilsson, 2011 ; DuRant et al., 2013 ; Hepp et al., 2015 ; Wada et al., 2015 ; Stier et al., 2020 ; Hope et al., 2021 ). Similarly, in altricial species, parental food provisioning is essential for the proper growth and development of offspring. However, parents vary in their nestling provisioning rates due to factors such as food availability, the sex of the parent, parental experience, ambient temperature, brood size, and predation risk ( Wright et al., 1998 ; Wiebe and Neufeld, 2003 ; Barba et al., 2009 ; Low et al., 2012 ; Ghalambor et al., 2013 ), with some evidence that provisioning behavior is repeatable and that some individuals are consistently “good” parents ( Schwagmeyer and Mock, 2003 ). As with incubation temperature, differences in provisioning can affect offspring morphology and physiology. For example, food limitation during nestling development is related to low body masses, slow growth rates, altered glucocorticoid hormone levels, higher metabolic rates, and lower survival ( Lepczyk and Karasov, 2000 ; Killpack and Karasov, 2012 ; Schmidt et al., 2012 ).

There is evidence that genetics, incubation temperature, and post-hatch parental care can influence both juvenile and adult avian metabolic rate. For example, avian RMR has been shown to be repeatable within individuals and heritable through adulthood ( Bech et al., 1999 ; Rønning et al., 2005 , 2007 ; Broggi et al., 2009 ; Nilsson et al., 2009 ). Further, studies have found that eggs incubated at lower temperatures have slower embryonic development and lower embryonic metabolic rates ( DuRant et al., 2011 ; Stier et al., 2020 ) but, after hatching, produce offspring that have higher RMR early in life compared to those incubated at a warmer temperature ( Nord and Nilsson, 2011 ; Wada et al., 2015 ). Moreover, environmental stressors during the post-hatch development, such as glucocorticoid exposure ( Spencer and Verhulst, 2008 ; Dupont et al., 2019 ), food restriction ( Moe et al., 2005 ; Criscuolo et al., 2008 ; Rønning et al., 2009 ; Careau et al., 2014 ), and sibling competition ( Burness et al., 2000 ; Verhulst et al., 2006 ), can have long-lasting effects on offspring RMR. Additionally, another important aspect of metabolism is thermoregulatory metabolic rate (TMR), which is the metabolic rate organisms express under challenging thermal conditions, and represents the metabolic cost associated with thermoregulation ( Broggi et al., 2004 ; Carleton and Rio, 2005 ; Nzama et al., 2010 ; DuRant et al., 2012 ; Dupont et al., 2019 ). Although less-often studied compared to RMR, there is also some evidence that avian TMR can be affected by incubation temperature and the post-hatch environment. For example, one study found that wood ducks ( Aix sponsa ) incubated at a lower temperature had higher TMR than those incubated at a warmer temperature ( DuRant et al., 2012 ). Further, one study found that house sparrows ( Passer domesticus ) with increased glucocorticoid exposure during post-hatch development had lower TMR than control nestlings ( Dupont et al., 2019 ). However, despite the evidence for the influence of genetics and pre- and post-hatch parental effects on both avian RMR and TMR, no study to date has investigated whether these different drivers may interact to affect metabolism.

In this study, we investigated whether genetics, incubation temperature, and/or post-hatch parental care interact to explain individual variation in avian RMR or TMR. To do this, we incubated zebra finch ( T. guttata ) eggs at two different temperatures: 37.5°C (control), which is optimal for this species and 36.3°C (low), which is suboptimal in this species, as shown in other studies ( Wada et al., 2015 ; Berntsen and Bech, 2016 ). During incubation, as a proxy of embryonic metabolic rate, we measured embryonic heart rate ( Sheldon et al., 2018 ). Then, at hatch, we cross-fostered nestlings to decouple genetic and pre-hatching factors from post-hatching environmental conditions. Lastly, we measured the RMR and TMR of all offspring at Day 30 (i.e., nutritional independence), and of all parents after reproduction had ended. Our main hypothesis was that offspring metabolism is shaped through a combination of inheritance, incubation conditions, and post-natal care. We tested the following predictions:

1) Embryonic heart rate and offspring metabolic rate on Day 30 are positively related to the metabolic rate of genetic parents (i.e., metabolic rate is heritable; Rønning et al., 2007 ; Nilsson et al., 2009 ).

2) Lower incubation temperatures lead to slower embryonic heart rates ( Rubin, 2019 ; Stier et al., 2020 ), but higher RMR ( Nord and Nilsson, 2011 ; Wada et al., 2015 ) and TMR ( DuRant et al., 2012 ) at Day 30.

3) We considered the relationship between foster parent and offspring metabolic rate to be representative of the overall influence of the post-hatch environment and predicted that offspring metabolic rate would also be related to the metabolic rate of foster parents.

Along with these predictions, we also tested for interactive effects among our incubation temperature treatment and parental metabolism, with the expectation that offspring metabolic rate and embryonic heart rate may have different relationships with parental metabolic rate, depending on the incubation temperature treatment.

2 Materials and Methods

2.1 general husbandry and breeding.

We used a breeding colony of zebra finches ( T. guttata ; N = 20 pairs; “parents”) housed at the CEBC (CNRS) for this study. We first housed the 40 birds together in an indoor aviary for 10 days and we formed pairs based on mating behaviors that we observed (e.g., singing, proximity, etc.). We then housed pairs in cages (47.5 × 38 × 51 cm) with external nest boxes (12 × 13 × 16 cm). Ambient temperature was kept at a constant 22°C and the photoperiod was set to a 14:10 day:night cycle, for all aspects of the study, including pair formation, reproduction, and nestling rearing. We provided birds with ∼10 g of alfalfa hay every day, and then ∼1 g of coconut fiber once the hay completely covered the bottom of the nest box. We misted pairs with water once per day until their first egg was laid, to stimulate reproduction. We provided birds with ad libitum food (Versele-Laga Prestige Tropical Finches seed mix), water supplemented with vitamins, cuttlefish bone, and grit. We also gave birds ∼2 g of chopped hard-boiled eggs (including the shells) every day from pair formation until nestling Day 30, along with endives and millet sprays once per week ( Olson et al., 2014 ). All procedures in this study were approved by the national ethics committee for animal experimentation under file number APAFIS#23727-2020011311559318.

2.2 Egg Incubation

We checked nest boxes daily at 10:00. Once an egg was found, we marked it with a unique ID using a small marker, weighed it, and placed it in an incubator (Brinsea © Ovation 28 Advance digital egg incubator) at one of two temperatures. We followed an incubation protocol similar to Wada et al. (2015) . The “control” incubator was set at a constant 37.5°C (± 0.1 [SD]), which is likely optimal for zebra finches. The “low” incubator was set at a constant 36.3°C (± 0.1 [SD]), which is within the natural range of zebra finch incubation temperatures, but there is evidence that it produces suboptimal offspring phenotypes in this species ( Wada et al., 2015 ). Both incubators were set at a humidity of 55%. We verified the temperature and humidity by placing iButton © (Hygrochron DS 1923, Maxim Integrated ™ ) temperature loggers inside of each incubator. We randomly assigned the incubation treatment to the first laid egg of each breeding pair, and then systematically alternated among temperature treatments for each subsequent egg for the entire length experiment. Multiple clutches from each breeding pair were used in this study, to attain a sufficient sample size. During artificial incubation, we gave parents fake clay eggs to incubate so that they stayed in the breeding phase. One day before the predicted hatching date (day 13 for “control” eggs and day 14 for “low” eggs), we transferred eggs to a hatcher that was set at a temperature of 37.5°C and 67% humidity.

2.3 Embryonic Heart Rate

Embryonic heart rate is correlated with embryonic oxygen consumption ( Du et al., 2010 ), and thus can be used as a proxy for energy expenditure during embryonic development. We measured embryonic heart rate by placing eggs in the Buddy digital egg monitor (Vetronic Services, Abbotskerswell, Devon, United Kingdom). We considered that a reading was reliable when the curve and heart rate outputs were relatively consistent for ∼10 s ( Sheldon et al., 2018 ). At each timepoint (see below), we took three repeated heart rate measures within 3 min of taking each egg (individually) out of the incubator and noted the time (seconds) that it took to take each measure. If any/all of the readings were unreliable (e.g., due to embryo movement; Sheldon et al., 2018 ), they were excluded from the analyses. All readings were taken in a room at a constant temperature of 22°C. If there was a consistent heart rate reading of “0”, we candled eggs and determined if they were infertile or had died during development.

We measured heart rates of embryos after 11, 12 and 13 days for incubation for “control” eggs and after 12, 13 and 14 days of incubation for “low” eggs. These three measures are hereafter referred to as “readings 1, 2 and 3”. We chose these days because the incubation period of “control” eggs is about 1 day shorter than that of and “low” eggs ( Table 1 ) and, thus, we chose to investigate differences in heart rate among embryos at the same stage of development (i.e., “developmental age”), instead of after the same number of days (i.e., “calendar age”). We validated that our embryonic heart rate results were not driven by differences in eggshell temperature, and that they were not affected by our choice of using “developmental age” instead of “calendar age” (see Supplementary Appendix S1 ). We placed eggs in the hatcher after the final heart rate readings.

TABLE 1 . Summary statistics of hatch success, incubation period, body mass, and metabolic rate.

2.4 Nestling Monitoring

We checked the hatcher for hatching multiple times each day and, at a minimum, once at 9:00 and once at 17:00. Once hatched, we weighed and marked nestlings by removing distinct patches of down feathers ( Adam et al., 2014 ). Then, we cross-fostered nestlings. We gave parents up to two nestlings, which were never from the same incubation treatment, and nestlings were never more than 1 day apart in age. We housed nestlings with their foster parents until independence (i.e., Day 30), and then we conducted the metabolism measurements. Afterward, we housed independent offspring in sex-specific communal cages for use in future studies. We banded nestlings on Day 10 and determined their sex using plumage characteristics on Day 30.

2.5 Metabolism

We quantified energy metabolism in both parents and offspring by measuring oxygen consumption rates using multichannel open-circuit respirometry (Sable Systems Int., Las Vegas, NV, United States; Brischoux et al., 2017 ). We measured offspring when they were 32 ± 2.9 (range: 28–39) days-old, and we measured parents after they had finished reproduction [75 ± 26 days after their last foster nestling reached Day 30 (for those that successfully raised at least one nestling); 102 ± 20 days since their last laid egg (all birds)]. We measured metabolism of each bird twice: once at 32°C (RMR; within the thermoneutral zone; Calder, 1964 ) and once at 12°C (TMR; when birds must actively thermoregulate; Dupont et al., 2019 ), to determine whether incubation temperature might affect energy expenditure during a thermal challenge. Measurements at different temperatures were conducted on consecutive days and the order was randomized among incubation temperature treatments. We weighed birds at ∼20:15 and began respirometry at ∼20:30. Up to 7 birds were measured each night, and the system measured oxygen consumption of each bird for 10 min and systematically alternated among chambers, with 15 min of baseline reading (empty chamber) each time a full cycle was completed. Birds were removed and weighed again at ∼8:30 the next morning. We did not analyze the first 3 h of data because this was the time when birds fasted ( Wada et al., 2015 ). Oxygen flow was set at ∼350 ml/min, and O 2 at 20.95%, which was recalibrated each night.

To calculate metabolic rate, we first chose the value of oxygen consumption for each 10 min run of each individual that was the lowest and most consistent, using the computer software ExpeData (Sable Systems). Then, we calculated metabolic rate using the Hoffman Equation for VO 2 (ml/h), and then corrected for body mass (ml/h/g). Lastly, we calculated the mean VO 2 of all runs of each individual to obtain the final VO 2 value (ml/h/g) for each individual.

2.6 Statistical Analyses

We conducted all statistical analyses using R v 3.5.1 ( R Core Team, 2018 ). We reduced models using stepwise backwards elimination of non-significant terms ( p > 0.10), starting with non-significant interactions. After eliminating the term with the highest p -value, we reran the model and continued this process until only significant ( p < 0.05) or marginally significant (0.05 < p < 0.10) terms remained in the model. Incubation temperature was always treated as a categorical variable. We ensured that all models met the assumptions of normal and homoscedastic residuals by investigating histograms of residuals, normal quantile plots, and fitted vs. residuals plots. We verified that models met the assumption of non-multicollinearity by investigating the variance inflation factors ( vif ). Further, all continuous independent variables that were used in interactions were scaled and centered to reduce multicollinearity. We used the package lme4 ( Bates et al., 2015 ) for mixed effects models and emmeans ( Lenth, 2018 ) for post-hoc tests, including slope comparisons for interactions. p -values were calculated using the Anova function using the car ( Fox and Weisberg, 2011 ) package. R 2 values for mixed effects models were calculated using the MuMln package ( Bartoń, 2018 ). Figures were created using the plyr ( Wickham, 2011 ) and ggplot2 ( Wickham, 2016 ) packages. Two male parents died for reasons unrelated to the experiment before parental metabolic rates were measured, and thus their RMR, TMR, and ΔMR were not able to be included in the analyses. Neither of these males was a genetic father to any offspring that lived until Day 30 in this study, and only one of these males was a foster father to a single individual that lived until Day 30.

First, to determine whether embryonic heart rate was related to incubation temperature and/or parent metabolism, we built one linear mixed effect model with heart rate as the dependent variable. The independent variables were incubation temperature, reading (1, 2 or 3), the time it took to take the measurement (seconds), the RMR of both the genetic mother and father, along with all two-way interactions with incubation temperature. Parent TMR was not included in this model because 1) we predicted only that parental RMR would be related with embryonic metabolism, measured when embryos were at warm temperatures (i.e., incubation) and 2) parent TMR and RMR were correlated ( r = 0.42; p < 0.01), and thus including them both in the model would increase multicollinearity. We also included whether the egg hatched or not as an independent variable, and egg mass as a covariate. Egg ID was included as a random effect to control for repeated measures.

Second, to determine whether offspring metabolism was related to incubation temperature and the temperature at which the measurement was taken, we built one linear mixed effects model. Offspring metabolism (VO 2, ml/h/g) was the dependent variable, and it was log-transformed to meet model assumptions. The independent variables were incubation temperature, the temperature of the measurement (12°C or 32°C), and their interaction. Sex and age were also included as covariates, as well as the interaction between incubation temperature and sex. Individual ID, genetic parent ID, and foster parent ID were included as random effects to account for repeated measures within individuals and among siblings.

Next, we determined whether offspring metabolism was related to parental metabolism. First, we calculated heritability ( h 2 ) as the slope of the regression between the mean value of genetic parent metabolism (either RMR or TMR) and offspring metabolism ( Åkesson et al., 2008 ; Wray and Visscher, 2008 ). Then, to examine relationships among all parents (genetic and foster; separated by sex), and to test whether there was an interactive effect of incubation temperature and parental metabolism, we built three linear models. For all models, the dependent variable was offspring metabolism (VO 2, ml/h/g) and the independent variables were incubation temperature, the metabolism of the genetic mother, genetic father, foster mother, and foster father, along with all two-way interactions with incubation temperature. The difference among the three models was that the first included only RMR data (both parents and offspring), the second included only TMR data, and the third used the difference between TMR and RMR (i.e., additional amount of energy expended during thermoregulation; hereafter ΔMR) for all individuals.

Lastly, to determine whether embryonic heart rate and offspring metabolism (at Day 30) were correlated within individuals, we built one linear mixed effect model. The dependent variable was embryonic heart rate, and only individuals that lived until the metabolic measurement (∼Day 30) were included in the model. The independent variables were incubation temperature, reading (1, 2 or 3), offspring RMR, and all two-way interactions with incubation temperature. Offspring TMR was not included in this model because 1) we predicted only that offspring RMR would be related with embryonic metabolism, measured when embryos were at warm temperatures (i.e., incubation) and 2) offspring TMR and RMR were correlated ( r = 0.73; p < 0.001), and thus including them both in the model would increase multicollinearity. We also included sex and its interaction with incubation temperature in this analysis because, contrary to the first analysis, we had data on the sex of all individuals (i.e., only individuals that lived until Day 30 were included). The time it took to take the measurement (seconds) and egg mass were also included as covariates. Egg ID, genetic parent ID, and foster parent ID were included as random effects to control for repeated measures among siblings.

3.1 Hatching Success, Incubation Period, and Body Mass

Summary statistics for hatching success, incubation period, and nestling body mass (Days 0 and 30) are reported in Table 1 . There were no differences in hatching success, body mass at Day 0, or body mass at Day 30 between incubation temperature treatment groups (all p > 0.25; simple linear models). However, eggs incubated at the lower temperature had a longer incubation period than those incubated at the control temperature ( p < 0.001).

3.2 Embryonic Heart Rate: Relationship With Incubation Temperature and Parental Metabolism

Embryonic heart rate was related to both incubation temperature and parent metabolic rate. We found that heart rate was greater in embryos from the control treatment compared to the low treatment ( p < 0.001; Table 2 ; Figure 1 ), and that heart rate increased throughout the course of incubation (reading: p < 0.001; Table 2 ). There was an interactive effect of incubation temperature and reading on heart rate ( p < 0.001; Table 2 ), and post-hoc tests revealed significant differences for all pairwise comparisons (all p < 0.001), except between the heart rate of control embryos on days 11 and 12 ( p > 0.99; Figure 1 ). Although embryonic heart rate was significantly related to mother RMR in the full model, it was not retained in the final model ( Table 2 ; Figure 2A ). However, embryonic heart rate was positively correlated with father RMR ( p = 0.0003; Table 2 ; Figure 2B ). There was also a relationship between whether or not the egg hatched and its heart rate ( p = 0.049; Table 2 ), where embryos with greater heart rates were more likely to hatch. Further, heart rate increased as egg mass increased ( p < 0.001; Table 2 ), and heart rate decreased with the time that it took to take the measurement ( p < 0.001; Table 2 ).

TABLE 2 . Full and reduced models investigating the relationship of embryonic heart rate with incubation temperature and parental metabolism.

FIGURE 1 . Zebra finch embryonic heart rate (beats per minute; bpm) at three different time points during development and incubated at two different temperatures (black = control; gray = low). To correct for different developmental rates, readings were taken on control eggs after (1) 11, (2) 12, and (3) 13 days of incubation, while readings were taken on low eggs after (1) 12, (2) 13, and (3) 14 days. Mean ± SE are shown.

FIGURE 2 . The relationships between egg heart rate (bpm) and (A) genetic mother RMR and (B) genetic father RMR. Eggs were incubated at two different temperatures (black = control; gray = low). All egg heart rate measurements are shown. Regression lines are included only for significant relationships.

3.3 Offspring Metabolic Rate: Relationship With Incubation Temperature and Parental Metabolism

Although we found no differences in metabolic rate among offspring incubated at different temperatures or between sexes ( Table 3 ), we found that offspring metabolism was related to the temperature at which the measurement was taken. As expected, metabolism was greater when the measurement was taken at 12°C (TMR) than at 32°C (RMR) ( p < 0.0001; Table 3 ; Figure 3 ).

TABLE 3 . Full and reduced models investigating the effects of incubation temperature and temperature of measurement on offspring metabolism at Day 30.

FIGURE 3 . Zebra finch metabolic rate (VO 2 ; ml/h/g) measured at two different temperatures (black = TMR: 12°C; gray = RMR: 32°C). Individuals were measured at Day 30 and had hatched from eggs incubated at two different temperatures (i.e., control or low).

The regression of mean genetic parent RMR with offspring RMR revealed that RMR was significantly heritable [ h 2 = 0.53 ± 0.22 (SE), p = 0.02]. When we examined the relationships of all parents (genetic and foster) as individual factors, we found that genetic mother RMR was positively related to offspring RMR ( p = 0.014; Table 4 ; Figure 4A ). However, offspring RMR was not related to any other parental RMR, and there were no interactive relationships with incubation temperature ( Table 4 ; Figure 4B–D ).

TABLE 4 . Full and reduced models investigating the relationship of offspring metabolism at Day 30 with interactions between incubation temperature and parental metabolism.

FIGURE 4 . Relationship between offspring RMR on Day 30 and the RMR of the (A) genetic mother, (B) genetic father, (C) foster mother, and (D) foster father. Offspring had been incubated at two different temperatures as eggs (black = control; gray = low). Regression lines are included only for significant relationships.

The regression of mean genetic parent TMR with offspring TMR revealed that the heritability of TMR was not statistically significant [ h 2 = 0.38 ± 0.28 (SE), p = 0.19]. However, when examining parents separately (i.e., all genetic and foster parents as separate independent variables), we found a trend that genetic father TMR was positively related to offspring TMR ( p = 0.093; Table 4 ). Further, there was an interactive effect of incubation temperature and foster mother TMR on offspring TMR ( p = 0.033; Table 4 ), where the TMR of offspring from the control group was not related to foster mother TMR (slope estimate: 0.022; confidence interval: −0.32 to 0.37) while the TMR of offspring from the low group was negatively related to the TMR of their foster mother (slope estimate: −0.56; confidence interval: −0.95 to −0.16). There were no relationships between offspring TMR and their genetic mother or foster father ( Table 4 ).

Similar to TMR, the heritability of ΔMR (i.e., TMR−RMR) was not statistically significant [ h 2 = 0.18 ± 0.27 (SE), p = 0.51]. However, when examining parents separately, although there was no relationship between genetic mother ΔMR and offspring ΔMR ( Table 4 ; Figure 5A ), we found that there was a significant positive relationship between genetic father ΔMR and offspring ΔMR ( p = 0.049; Table 4 ; Figure 5B ). There was also an interactive effect of incubation temperature and foster mother ΔMR on offspring ΔMR ( p = 0.025; Table 4 ; Figure 5C ). This relationship mimicked that of TMR: the ΔMR of offspring from the control group was not related to foster mother ΔMR (slope estimate: −0.12; confidence interval: −0.34 to 0.11; Figure 5C ) while the ΔMR of offspring from the low group was negatively related to the ΔMR of their foster mother (slope estimate: −0.55; confidence interval: −0.85 to −0.25; Figure 5C ). There was no relationship between offspring ΔMR and that of their foster father ( Table 4 ; Figure 5D ).

FIGURE 5 . Relationship between the difference in offspring TMR and RMR (ΔMR) on Day 30 and the ΔMR of the (A) genetic mother, (B) genetic father, (C) foster mother, and (D) foster father. Offspring had been incubated at two different temperatures as eggs (black = control; gray = low). Regression lines are included only for significant relationships.

3.4 Embryonic Heart Rate and Metabolic Rate: Relationship Within Individuals

Embryonic heart rate and offspring RMR were not correlated within individuals ( Table 5 ). Further, there were no significant interactive effects of incubation temperature and RMR. The only terms that remained in the model ( Table 5 ) were incubation temperature ( p < 0.001), reading ( p < 0.001), time to take the measurement ( p < 0.001), and incubation temperature x reading ( p < 0.001), as already found previously in Section 3.2.

TABLE 5 . Full and reduced models investigating the relationship between embryonic heart rate and Day 30 metabolism.

4 Discussion

Here, we manipulated the developmental environment of zebra finches to disentangle the impact of inheritance, incubation temperature, and post-hatch rearing conditions (i.e., cross-fostering) on the energy metabolism of embryos and offspring at nutritional independence (i.e., Day 30). We found that embryonic heart rate, a proxy of embryonic metabolism, was positively related to genetic father RMR and that embryos incubated at the higher incubation temperature had faster heart rates than those incubated at the lower temperature. Further, we found evidence that post-hatch offspring RMR is heritable and has a positive correlation with genetic mother RMR, although we found no relationship between offspring RMR and either foster parent RMR or incubation temperature. Lastly, we found that the metabolic cost of thermoregulation (i.e., TMR and ΔMR) had a lower heritability than RMR, but was positively related to genetic father TMR and ΔMR. Interestingly, foster mother TMR and ΔMR were negatively correlated with offspring TMR and ΔMR, respectively, but this relationship was only apparent when offspring were incubated at the lower temperature. This suggests that there are combined effects of the pre-natal environment and post-natal parental care on the metabolic cost of thermoregulation.

4.1 Effects of Incubation Temperature

As predicted, eggs that were incubated at the lower temperature had slower embryonic heart rates than those incubated at the higher temperature. Because embryonic heart rate should be an indicator of embryonic metabolism ( Du et al., 2010 ; Sheldon et al., 2018 ), this suggests that low incubation temperatures lead to a lower embryonic metabolic rate. Our results agree with two other studies that have investigated the relationship between incubation temperature and embryonic heart rate ( Rubin, 2019 ; Stier et al., 2020 ), and with one study that found that wood duck ( Aix sponsa ) eggs incubated at lower temperatures had lower daily embryonic oxygen consumption compared to those incubation at higher temperatures ( DuRant et al., 2011 ). This lower energy expenditure during embryonic development should be related to slower developmental rates ( Vedder et al., 2017 ; Sheldon and Griffith, 2018 ). Indeed, we found that eggs incubated at the lower temperature had a longer developmental duration (i.e., incubation period) than those incubated at the higher temperature ( Table 1 ). Importantly, we still found a difference in embryonic heart rate between incubation temperatures when we corrected for differences in eggshell temperature and differences in developmental rate (i.e., developmental age vs. calendar age; see Supplementary Material ). This suggests that incubation temperature alters physiology during development, more so than just a linear relationship with current temperature or developmental rate.

We predicted that offspring incubated at the low temperature would have greater post-hatch metabolic rates than those incubated at the control temperature because previous studies have found this effect of incubation temperature on both RMR ( Nord and Nilsson, 2011 ; Wada et al., 2015 ) and TMR ( DuRant et al., 2012 ) in birds. However, contrary to our predictions, offspring metabolic rate (RMR and TMR) was not affected by our incubation temperature treatments (control: 37.5°C; low: 36.3°C). This disagrees with some other avian studies. For example, Nord and Nilsson (2011) found that 14-day-old blue tits ( Cyanistes caeruleus ) incubated at a low temperature had higher RMR than those incubated at a warmer temperature and DuRant et al. (2012) found that 1-day-old wood ducks ( Aix sponsa ) incubated at a lower temperature had higher TMR than those incubated at a warmer temperature. To date, no study has investigated the effect of incubation temperature on zebra finch TMR, and two studies have examined the effects of incubation temperature on zebra finch RMR, with conflicting results. Supporting our findings, Berntsen and Bech (2021) found no difference in RMR among zebra finches that were incubated at 35.9°C and 37.9°C, measured at 15 and 45 days-old. In contrast, Wada et al. (2015) found that 25-day-old zebra finches incubated at 36.2°C had a higher RMR than those incubated at 37.4°C, although this effect was only found in females. In our study, we did not find an effect of sex on metabolic rate. In light of these conflicting results among species, it is possible that the effect of incubation temperature on metabolic rate is species-specific. For example, zebra finches may be a species that is more resistant to small changes in the embryonic thermal environment, and offspring develop similar physiological traits regardless of their developmental conditions. It is also possible that metabolic rate is more influenced by inheritance than by either the early developmental environment or sex, which could explain differences among zebra finch studies. Indeed, we found evidence that both RMR and TMR are heritable (see below). If our breeding parents displayed more genetic variation than those in the study of Wada et al. (2015) , this could have masked any effects of incubation temperature and could explain the difference in results of our two studies. It should also be noted that there was relatively low hatching success in our study, although it was within the range of hatching success found in other captive zebra finch studies (e.g., von Engelhardt et al., 2004 ; Von Engelhardt et al., 2006 ; Criscuolo et al., 2011 ; Winter et al., 2013 ). Nevertheless, we cannot exclude the possibility that there was a selective process during hatching, and that all offspring that succeeded to hatch had similar metabolic rates, regardless of incubation temperature.

4.2 Relationship With Genetic Parents

Embryonic heart rate was positively related to genetic father RMR, suggesting that there could be a genetic component to embryonic metabolism. Although there is evidence that embryonic heart rate and metabolism vary among different genetic lines in poultry ( Druyan, 2010 ), and that there are significant among-clutch differences in embryonic heart rate in wild zebra finches ( Sheldon et al., 2018 ), this is the first study to our knowledge that has explicitly investigated the relationship between parental and embryonic metabolism in birds. Although the correlation between genetic parent metabolism and embryonic heart rate could also be due to maternal effects during egg formation, such as egg yolk composition ( Ho et al., 2011 ), the relationship between embryonic heart rate and genetic mother RMR was not significant. In contrast, because the relationship with genetic father RMR was statistically significant, this suggests that maternal effects may not be as important as genetics for determining embryonic metabolism in zebra finches.

As predicted, we found evidence that offspring RMR was highly heritable ( h 2 = 0.53). This agrees with other studies that show that RMR is a heritable trait. For example, both Rønning et al. (2007) and Nilsson et al. (2009) measured RMR heritability by using restricted maximum likelihood to compare RMR among siblings and found evidence that RMR was heritable in zebra finches ( h 2 = 0.25) and blue tits ( h 2 = 0.59), respectively. Further, using methods similar to that of our study (i.e., parent-offspring regression), Bushuev et al. (2011) found evidence for heritability of RMR ( h 2 = 0.43) in pied flycatchers ( Ficedula hypoleuca ). Further in line with our results, Bushuev et al. (2011) found that offspring RMR was correlated with genetic parent RMR, but not foster parent RMR. The relationship between genetic parent and offspring RMR that we found in this study could also be due to non-genetic maternal effects, such as hormone deposition to the egg. Indeed, in contrast to what we found for embryonic heart rate, when we examined the RMR of the genetic mother and genetic father as separate factors, we only found a relationship between offspring RMR and genetic mother RMR, and not genetic father RMR. This suggests that pre-incubation maternal effects may play a large role in determining post-hatch offspring RMR. For example, zebra finch eggs with higher testosterone concentrations produce nestlings and adults with higher RMR ( Tobler et al., 2007 ; Nilsson et al., 2011 ). If the mothers with higher RMR in our study also deposited more testosterone into their eggs, this could partly explain the relationship that we found between parent and offspring RMR.

In comparison to RMR, the metabolic cost of thermoregulation (i.e., TMR and ΔMR) was less heritable. It may be expected that TMR would have a lower heritability than RMR because it may be more variable due to its dependence on the insulation capacity of plumage. For example, the body feathers of juvenile birds have different structural properties than those of adult birds ( Butler et al., 2008 ), which could mask relationships between the TMR of parents and young offspring. However, although the h 2 of TMR ( h 2 = 0.38) and ΔMR ( h 2 = 0.18) were not statistically significant, the h 2 of TMR was still within the range of those found for RMR (see above). Further, offspring TMR tended to be positively related to genetic father TMR, and offspring ΔMR was positively related to genetic father ΔMR. This is the first evidence that we are aware of for the heritability of TMR or ΔMR, and suggests that the metabolic expenditure associated with thermoregulation could be shaped by natural selection. However, in contrast to RMR, we found little evidence for non-genetic maternal effects because, when genetic mother and genetic father were tested as separate factors, genetic mother TMR and ΔMR were not related to that of their offspring. Thus, any non-genetic maternal effect that may have influenced RMR either did not translate into differences in thermoregulatory capacity, or was masked by other driving factors (e.g., post-hatch environment; see below).

4.3 Relationship With Foster Parents

Although there were no relationships between foster parent and offspring RMR, we found that foster mother TMR and ΔMR were negatively related to that of their foster offspring, but only for offspring in the low treatment. This suggests that the impact of foster mother metabolism, and thus post-hatch parental care, is not on RMR, but rather on the ability of offspring to increase their metabolic rate when faced with a thermal energetic challenge. Thus, the ability of parents to increase their metabolic rate in response to an energetic challenge may be important for effective post-hatch parental care. Because most studies focus on RMR, our results call for future studies to focus more on TMR.

Specifically, we found that the more energy that foster mothers expended on thermoregulation, the less energy that their foster offspring expended on thermoregulation. It is possible that this relationship can be explained by differences in nestling provisioning. For example, foster mothers with a high metabolic rate should also have a high investment in parental care ( Daan et al., 1990 ; Koteja, 2004 ; Sadowska et al., 2013 ), and provide a better developmental environment for their offspring (e.g., more food provisioning; Nilsson, 2002 ). In zebra finches, a greater food supply during nestling development, as opposed to food restriction, is related to lower offspring metabolic rate later in life ( Criscuolo et al., 2008 ; Careau et al., 2014 ). Thus, this could explain the negative relationship that we found between foster mother and offspring TMR and ΔMR. In our study, offspring growth rate between Day 0 and Day 30 was not correlated with foster mother TMR ( p = 0.9), and thus we did not find evidence to support the hypothesis that foster mother TMR is positively related to food provisioning and/or better parental care. However, we did not measure parental care behavior (i.e., provisioning rates) in this study, and thus future studies are needed to determine whether there is a relationship between parental TMR and nestling provisioning rates, along with offspring growth rates and metabolism.

It is important to note that the relationships between foster mother and offspring TMR and ΔMR were only present in offspring incubated at the low temperature, and not the control temperature. This suggests that the impact of post-hatch care (e.g., nestling provisioning) is dependent on the quality of pre-natal care (i.e., incubation temperature). It is possible that offspring incubated at the control temperature are more resistant to differences in their post-hatch environment than those incubated at the low temperature, although little is known about how incubation temperature may influence trait plasticity or canalization. Future research is needed to investigate how different thermal environments shape avian thermoregulatory ability across generations, especially in the context of acclimation and adaptation in response to climate change ( Nord and Giroud, 2020 ).

4.4 Relationship Between Heart Rate, Hatch Success, and Metabolic Rate Within Individuals

Embryonic heart rate is important because it can be used as a proxy for embryonic metabolic rate ( Du et al., 2010 ), and can also provide insights into developmental rate, hatchling phenotype, and the effects of environmental stressors (reviewed in Sheldon et al., 2018 ) . Contrary to what we expected, we did not find that embryonic heart rate was related to offspring RMR at Day 30. However, to our knowledge, this is the first study that has investigated whether there is a relationship between embryonic heart rate and offspring metabolism later in life. Our results suggest that individual metabolic rate can change throughout different stages of development, and that embryonic heart rate cannot be used to predict later-life metabolic rate in zebra finches. Indeed, studies that have found a positive relationship between heart rate and metabolic rate measured these two traits at the same developmental stage (i.e., embryonic; Du et al., 2010 ; Ide et al., 2017 ; Goodchild et al., 2020 ), and one study did not find a relationship between heart rate and metabolism even when measured at the same developmental stage (i.e., embryonic and hatching; Sartori et al., 2017 ). Similarly, one study on zebra finches found no relationship between embryonic heart rate and post-hatch growth rate or activity levels ( Sheldon and Griffith, 2018 ). Thus, it appears that embryonic heart rate may not be able to be extrapolated to phenotypic differences later in life.

However, when we investigated an endpoint closer to embryonic development—hatch success—we did find a relationship with embryonic heart rate. Eggs that hatched had greater embryonic heart rates than those that did not hatch, suggesting that heart rate may be an indicator of embryo quality or hatching probability. Although heart rate has been used in other studies to predict hatching date or to confirm embryonic mortality (reviewed in Sheldon et al., 2018 ), this is the first study to our knowledge that has explicitly linked the magnitude of embryonic heart rate to hatching probability. Because all individuals that hatch also have high heart rates as embryos, this could create a selective process for a particular metabolic functioning. It is possible that this could mask potential effects of the incubation treatment or parental care on offspring metabolic rate, and could also explain why we did not find some of the relationships that we had predicted (e.g., effect of incubation temperature on RMR, relationship with foster parent RMR).

5 Conclusion

In this study, we show that avian metabolic rate throughout development, from the embryo to nutritional independence, is related to parental inheritance, the pre-hatch environment (i.e., incubation temperature), and post-hatch conditions (i.e., foster parent). Revealing how these different factors are related to RMR and TMR sheds light on how metabolism and the energetic cost of thermoregulation can be shaped by environmental changes, parental care decisions, and natural selection. Although most studies to date focus on RMR, our study reveals important relationships with TMR, which could be particularly important in the context of climate change for understanding how the early thermal environment and parental care affect thermoregulatory ability, and the possibility that thermoregulatory ability can be shaped by natural selection. More work is needed to determine if the differences in RMR and TMR that we found in this study have effects on short- or long-term offspring fitness.

Data Availability Statement

The raw data supporting the conclusion of this article will be made available by the authors, without undue reservation.

Ethics Statement

The animal study was reviewed and approved by the Autorisation de Projet Utilisant des Animaux à des Fins Scientifiques under file number APAFIS#23727-2020011311559318.

Author Contributions

SH and FA contributed to the conception of the study. SH, OL and FA designed the study methods. SH and LS collected the data. SH performed the analyses and wrote the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

This study is based on work funded by a Fyssen Foundation Post-doctoral Study Grant (to SH), the CPER ECONAT, the CNRS, and the Agence Nationale de la Recherche (ANR project URBASTRESS, ANR-16-CE02-0004-01, and ANR project VITIBIRD) (to FA).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

We thank Lucie Michel, Clémence Furic, and Elsa Daniaud for help with animal husbandry and experimental procedures and Sophie Dupont for help with respirometry. We also thank Stephen Ferguson and Ila Mishra for reviewing the manuscript and for their helpful comments.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fphys.2022.892154/full#supplementary-material

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Keywords: incubation temperature, heritability, metabolic rate, thermoregulation, embryonic heart rate, cost of thermoregulation

Citation: Hope SF, Schmitt L, Lourdais O and Angelier F (2022) Nature vs. Nurture: Disentangling the Influence of Inheritance, Incubation Temperature, and Post-Natal Care on Offspring Heart Rate and Metabolism in Zebra Finches. Front. Physiol. 13:892154. doi: 10.3389/fphys.2022.892154

Received: 08 March 2022; Accepted: 19 April 2022; Published: 10 May 2022.

Reviewed by:

Copyright © 2022 Hope, Schmitt, Lourdais and Angelier. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Sydney F. Hope, [email protected]

† ORCID ID: Sydney F. Hope, orcid.org/0000-0002-3711-8593 Frédéric Angelier, orcid.org/0000-0003-2619-167X

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

DOI: 10.1016/S0262-4079(18)30710-3
Corpus ID: 46957112

Nature Versus Nurture

A. Ananthaswamy , Kate Douglas
Published 21 April 2018
Psychology, Philosophy
New Scientist

63 References

Beyond versus: the struggle to understand the interaction of nature and nurture, nature, nurture, and individual change, nature and nurture in early child development, understanding autism., the nature (and nurture) of personality disorders., social learning and imitation, problems of nosology and psychodynamics of early infantile autism., ‘why are we an ignored group’ mainstream educational experiences and current life satisfaction of adults on the autism spectrum from an online survey, the controversy that will not go away: vaccines and autism, infantile autism, related papers.

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Nature vs. Nurture Debate In Psychology

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

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The nature vs. nurture debate in psychology concerns the relative importance of an individual’s innate qualities (nature) versus personal experiences (nurture) in determining or causing individual differences in physical and behavioral traits. While early theories favored one factor over the other, contemporary views recognize a complex interplay between genes and environment in shaping behavior and development.

Key Takeaways

Nature is what we think of as pre-wiring and is influenced by genetic inheritance and other biological factors.
Nurture is generally taken as the influence of external factors after conception, e.g., the product of exposure, life experiences, and learning on an individual.
Behavioral genetics has enabled psychology to quantify the relative contribution of nature and nurture concerning specific psychological traits.
Instead of defending extreme nativist or nurturist views, most psychological researchers are now interested in investigating how nature and nurture interact in a host of qualitatively different ways.
For example, epigenetics is an emerging area of research that shows how environmental influences affect the expression of genes.

The nature-nurture debate is concerned with the relative contribution that both influences make to human behavior, such as personality, cognitive traits, temperament and psychopathology.

Examples of Nature vs. Nurture

Nature vs. nurture in child development.

In child development, the nature vs. nurture debate is evident in the study of language acquisition . Researchers like Chomsky (1957) argue that humans are born with an innate capacity for language (nature), known as universal grammar, suggesting that genetics play a significant role in language development.

Conversely, the behaviorist perspective, exemplified by Skinner (1957), emphasizes the role of environmental reinforcement and learning (nurture) in language acquisition.

Twin studies have provided valuable insights into this debate, demonstrating that identical twins raised apart may share linguistic similarities despite different environments, suggesting a strong genetic influence (Bouchard, 1979)

However, environmental factors, such as exposure to language-rich environments, also play a crucial role in language development, highlighting the intricate interplay between nature and nurture in child development.

Nature vs. Nurture in Personality Development

The nature vs. nurture debate in personality psychology centers on the origins of personality traits. Twin studies have shown that identical twins reared apart tend to have more similar personalities than fraternal twins, indicating a genetic component to personality (Bouchard, 1994).

However, environmental factors, such as parenting styles, cultural influences, and life experiences, also shape personality.

For example, research by Caspi et al. (2003) demonstrated that a particular gene (MAOA) can interact with childhood maltreatment to increase the risk of aggressive behavior in adulthood.

This highlights that genetic predispositions and environmental factors contribute to personality development, and their interaction is complex and multifaceted.

Nature vs. Nurture in Mental Illness Development

The nature vs. nurture debate in mental health explores the etiology of depression. Genetic studies have identified specific genes associated with an increased vulnerability to depression, indicating a genetic component (Sullivan et al., 2000).

However, environmental factors, such as adverse life events and chronic stress during childhood, also play a significant role in the development of depressive disorders (Dube et al.., 2002; Keller et al., 2007)

The diathesis-stress model posits that individuals inherit a genetic predisposition (diathesis) to a disorder, which is then activated or exacerbated by environmental stressors (Monroe & Simons, 1991).

This model illustrates how nature and nurture interact to influence mental health outcomes.

Nature vs. Nurture of Intelligence

The nature vs. nurture debate in intelligence examines the relative contributions of genetic and environmental factors to cognitive abilities.

Intelligence is highly heritable, with about 50% of variance in IQ attributed to genetic factors, based on studies of twins, adoptees, and families (Plomin & Spinath, 2004).

Heritability of intelligence increases with age, from about 20% in infancy to as high as 80% in adulthood, suggesting amplifying effects of genes over time.

However, environmental influences, such as access to quality education and stimulating environments, also significantly impact intelligence.

Shared environmental influences like family background are more influential in childhood, whereas non-shared experiences are more important later in life.

Research by Flynn (1987) showed that average IQ scores have increased over generations, suggesting that environmental improvements, known as the Flynn effect , can lead to substantial gains in cognitive abilities.

Molecular genetics provides tools to identify specific genes and understand their pathways and interactions. However, progress has been slow for complex traits like intelligence. Identified genes have small effect sizes (Plomin & Spinath, 2004).

Overall, intelligence results from complex interplay between genes and environment over development. Molecular genetics offers promise to clarify these mechanisms. The nature vs nurture debate is outdated – both play key roles.

Nativism (Extreme Nature Position)

It has long been known that certain physical characteristics are biologically determined by genetic inheritance.

Color of eyes, straight or curly hair, pigmentation of the skin, and certain diseases (such as Huntingdon’s chorea) are all a function of the genes we inherit.

These facts have led many to speculate as to whether psychological characteristics such as behavioral tendencies, personality attributes, and mental abilities are also “wired in” before we are even born.

Those who adopt an extreme hereditary position are known as nativists. Their basic assumption is that the characteristics of the human species as a whole are a product of evolution and that individual differences are due to each person’s unique genetic code.

In general, the earlier a particular ability appears, the more likely it is to be under the influence of genetic factors. Estimates of genetic influence are called heritability.

Examples of extreme nature positions in psychology include Chomsky (1965), who proposed language is gained through the use of an innate language acquisition device. Another example of nature is Freud’s theory of aggression as being an innate drive (called Thanatos).

Characteristics and differences that are not observable at birth, but which emerge later in life, are regarded as the product of maturation. That is to say, we all have an inner “biological clock” which switches on (or off) types of behavior in a pre-programmed way.

The classic example of the way this affects our physical development are the bodily changes that occur in early adolescence at puberty.

However, nativists also argue that maturation governs the emergence of attachment in infancy , language acquisition , and even cognitive development .

Empiricism (Extreme Nurture Position)

At the other end of the spectrum are the environmentalists – also known as empiricists (not to be confused with the other empirical/scientific approach ).

Their basic assumption is that at birth, the human mind is a tabula rasa (a blank slate) and that this is gradually “filled” as a result of experience (e.g., behaviorism ).

From this point of view, psychological characteristics and behavioral differences that emerge through infancy and childhood are the results of learning. It is how you are brought up (nurture) that governs the psychologically significant aspects of child development and the concept of maturation applies only to the biological.

For example, Bandura’s (1977) social learning theory states that aggression is learned from the environment through observation and imitation. This is seen in his famous bobo doll experiment (Bandura, 1961).

Also, Skinner (1957) believed that language is learned from other people via behavior-shaping techniques.

Evidence for Nature

Biological Approach
Biology of Gender
Medical Model

Freud (1905) stated that events in our childhood have a great influence on our adult lives, shaping our personality.

He thought that parenting is of primary importance to a child’s development , and the family as the most important feature of nurture was a common theme throughout twentieth-century psychology (which was dominated by environmentalists’ theories).

Behavioral Genetics

Researchers in the field of behavioral genetics study variation in behavior as it is affected by genes, which are the units of heredity passed down from parents to offspring.

“We now know that DNA differences are the major systematic source of psychological differences between us. Environmental effects are important but what we have learned in recent years is that they are mostly random – unsystematic and unstable – which means that we cannot do much about them.” Plomin (2018, xii)

Behavioral genetics has enabled psychology to quantify the relative contribution of nature and nurture with regard to specific psychological traits. One way to do this is to study relatives who share the same genes (nature) but a different environment (nurture). Adoption acts as a natural experiment which allows researchers to do this.

Empirical studies have consistently shown that adoptive children show greater resemblance to their biological parents, rather than their adoptive, or environmental parents (Plomin & DeFries, 1983; 1985).

Another way of studying heredity is by comparing the behavior of twins, who can either be identical (sharing the same genes) or non-identical (sharing 50% of genes). Like adoption studies, twin studies support the first rule of behavior genetics; that psychological traits are extremely heritable, about 50% on average.

The Twins in Early Development Study (TEDS) revealed correlations between twins on a range of behavioral traits, such as personality (empathy and hyperactivity) and components of reading such as phonetics (Haworth, Davis, Plomin, 2013; Oliver & Plomin, 2007; Trouton, Spinath, & Plomin, 2002).

Implications

Jenson (1969) found that the average I.Q. scores of black Americans were significantly lower than whites he went on to argue that genetic factors were mainly responsible – even going so far as to suggest that intelligence is 80% inherited.

The storm of controversy that developed around Jenson’s claims was not mainly due to logical and empirical weaknesses in his argument. It was more to do with the social and political implications that are often drawn from research that claims to demonstrate natural inequalities between social groups.

For many environmentalists, there is a barely disguised right-wing agenda behind the work of the behavioral geneticists. In their view, part of the difference in the I.Q. scores of different ethnic groups are due to inbuilt biases in the methods of testing.

More fundamentally, they believe that differences in intellectual ability are a product of social inequalities in access to material resources and opportunities. To put it simply children brought up in the ghetto tend to score lower on tests because they are denied the same life chances as more privileged members of society.

Now we can see why the nature-nurture debate has become such a hotly contested issue. What begins as an attempt to understand the causes of behavioral differences often develops into a politically motivated dispute about distributive justice and power in society.

What’s more, this doesn’t only apply to the debate over I.Q. It is equally relevant to the psychology of sex and gender , where the question of how much of the (alleged) differences in male and female behavior is due to biology and how much to culture is just as controversial.

Polygenic Inheritance

Rather than the presence or absence of single genes being the determining factor that accounts for psychological traits, behavioral genetics has demonstrated that multiple genes – often thousands, collectively contribute to specific behaviors.

Thus, psychological traits follow a polygenic mode of inheritance (as opposed to being determined by a single gene). Depression is a good example of a polygenic trait, which is thought to be influenced by around 1000 genes (Plomin, 2018).

This means a person with a lower number of these genes (under 500) would have a lower risk of experiencing depression than someone with a higher number.

While still limited in predictive power, polygenic risk scores provide a way to quantify innate genetic risk, allowing researchers to study how this interacts with environmental factors to influence outcomes.

The high polygenicity of psychiatric disorders (many genes each contributing small effects) revealed by genetic architecture studies shows that there isn’t a simple genetic determinism for most psychiatric conditions.

This complexity is further increased when you consider how these genes might interact with each other (epistasis) and with environmental factors. The same genetic profile might lead to different outcomes in different environments.

The Nature of Nurture

Nurture assumes that correlations between environmental factors and psychological outcomes are caused environmentally. For example, how much parents read with their children and how well children learn to read appear to be related. Other examples include environmental stress and its effect on depression.

However, behavioral genetics argues that what look like environmental effects are to a large extent really a reflection of genetic differences (Plomin & Bergeman, 1991).

People select, modify and create environments correlated with their genetic disposition. This means that what sometimes appears to be an environmental influence (nurture) is a genetic influence (nature).

So, children that are genetically predisposed to be competent readers, will be happy to listen to their parents read them stories, and be more likely to encourage this interaction.

Interaction Effects

However, in recent years there has been a growing realization that the question of “how much” behavior is due to heredity and “how much” to the environment may itself be the wrong question.

Take intelligence as an example. Like almost all types of human behavior, it is a complex, many-sided phenomenon which reveals itself (or not!) in a great variety of ways.

The “how much” question assumes that psychological traits can all be expressed numerically and that the issue can be resolved in a quantitative manner.

Heritability statistics revealed by behavioral genetic studies have been criticized as meaningless, mainly because biologists have established that genes cannot influence development independently of environmental factors; genetic and nongenetic factors always cooperate to build traits. The reality is that nature and culture interact in a host of qualitatively different ways (Gottlieb, 2007; Johnston & Edwards, 2002).

Instead of defending extreme nativist or nurturist views, most psychological researchers are now interested in investigating how nature and nurture interact.

For example, in psychopathology , this means that both a genetic predisposition and an appropriate environmental trigger are required for a mental disorder to develop. For example, epigenetics state that environmental influences affect the expression of genes.

What is Epigenetics?

Epigenetics is the term used to describe inheritance by mechanisms other than through the DNA sequence of genes. For example, features of a person’s physical and social environment can effect which genes are switched-on, or “expressed”, rather than the DNA sequence of the genes themselves.

Epigenetics refers to changes in gene expression that don’t involve alterations to the DNA sequence itself. Instead, these changes affect how genes are read and translated into proteins.

Mechanisms of Epigenetic Modification

Epigenetic modifications provide a direct biological mechanism by which environmental experiences (nurture) can alter how our genes (nature) function. This challenges the idea of genes as a fixed, unchangeable blueprint.

Epigenetic changes can occur throughout life, but certain periods (like early development or adolescence) may be particularly sensitive to these modifications.

There are several ways epigenetic changes can occur:

DNA methylation : Adding methyl groups to DNA, typically suppressing gene expression.
Histone modification : Changes to the proteins that DNA wraps around, affecting how tightly or loosely genes are packaged.
Non-coding RNA : RNA molecules that can regulate gene expression.

Environmental Stressors

Environmental stressors have been shown to induce epigenetic changes, with substantial evidence from both animal and human studies (Klengel et al., 2016).

These stressors can include malnutrition, exposure to toxins, extreme stress, or trauma, leading to alterations in DNA methylation patterns, histone modifications, and changes in non-coding RNA expression (Bale, 2015).

Transgenerational Epigenetic Inheritance

Some epigenetic modifications may be passed down to future generations, suggesting that environmental influences on one generation could affect the genetic expression of subsequent generations.

One such example is what is known as the Dutch Hunger Winter, during last year of the Second World War. What they found was that children who were in the womb during the famine experienced a life-long increase in their chances of developing various health problems compared to children conceived after the famine.

Epigenetic effects can sometimes be passed from one generation to the next, although the effects only seem to last for a few generations. There is some evidence that the effects of the Dutch Hunger Winter affected grandchildren of women who were pregnant during the famine.

Therefore, it makes more sense to say that the difference between two people’s behavior is mostly due to hereditary factors or mostly due to environmental factors.

This realization is especially important given the recent advances in genetics, such as polygenic testing. The Human Genome Project, for example, has stimulated enormous interest in tracing types of behavior to particular strands of DNA located on specific chromosomes.

If these advances are not to be abused, then there will need to be a more general understanding of the fact that biology interacts with both the cultural context and the personal choices that people make about how they want to live their lives.

There is no neat and simple way of unraveling these qualitatively different and reciprocal influences on human behavior.

The Concept of “Memories” Being Passed Down

While there’s evidence that environmental stressors can induce epigenetic changes that might affect future generations, the concept of specific “memories” being passed down is not supported by current scientific evidence.

This concept often stems from misinterpretation of studies showing behavioral or physiological changes in offspring related to parental experiences.

Some animal studies have demonstrated that offspring of stressed parents exhibit altered stress responses or behavioral changes.

For example, Dias and Ressler (2014) showed in mice that fear responses to specific odors can be passed down to subsequent generations. However, these are not “memories” in the conventional sense, but rather alterations in stress response systems or sensory sensitivities.

Human studies in this area are much more complex and limited. Research has examined children of trauma survivors (e.g., Holocaust survivors, 9/11 survivors) and found differences in stress hormone levels or risk for PTSD (Yehuda et al., 2016).

However, these studies face significant challenges in separating genetic, epigenetic, and social/cultural factors.

The challenges in interpreting human studies are substantial. Humans have complex social structures and cultural transmission of information, making it often impossible to separate the effects of biological inheritance from social learning and shared environments (Heard & Martienssen, 2014).

The longer lifespan and generation time in humans also make it challenging to study transgenerational effects. What’s often observed is not the transmission of specific memories, but rather altered predispositions or sensitivities.

For example, children of trauma survivors might have an altered stress response system, making them more sensitive to stress, but they don’t inherit specific memories of the trauma (Bowers & Yehuda, 2016).

While specific memories aren’t passed down, changes in gene expression related to stress response systems could potentially be inherited. These could affect how future generations respond to stress or process sensory information (Zannas et al., 2015).

Epigenetics: Licking Rat Pups

Michael Meaney and his colleagues at McGill University in Montreal, Canada conducted the landmark epigenetic study on mother rats licking and grooming their pups.

This research found that the amount of licking and grooming received by rat pups during their early life could alter their epigenetic marks and influence their stress responses in adulthood.

Pups that received high levels of maternal care (i.e., more licking and grooming) had a reduced stress response compared to those that received low levels of maternal care.

Meaney’s work with rat maternal behavior and its epigenetic effects has provided significant insights into the understanding of early-life experiences, gene expression, and adult behavior.

It underscores the importance of the early-life environment and its long-term impacts on an individual’s mental health and stress resilience.

Epigenetics: The Agouti Mouse Study

Waterland and Jirtle’s 2003 study on the Agouti mouse is another foundational work in the field of epigenetics that demonstrated how nutritional factors during early development can result in epigenetic changes that have long-lasting effects on phenotype.

In this study, they focused on a specific gene in mice called the Agouti viable yellow (A^vy) gene. Mice with this gene can express a range of coat colors, from yellow to mottled to brown.

This variation in coat color is related to the methylation status of the A^vy gene: higher methylation is associated with the brown coat, and lower methylation with the yellow coat.

Importantly, the coat color is also associated with health outcomes, with yellow mice being more prone to obesity, diabetes, and tumorigenesis compared to brown mice.

Waterland and Jirtle set out to investigate whether maternal diet, specifically supplementation with methyl donors like folic acid, choline, betaine, and vitamin B12, during pregnancy could influence the methylation status of the A^vy gene in offspring.

Key findings from the study include:

Dietary Influence : When pregnant mice were fed a diet supplemented with methyl donors, their offspring had an increased likelihood of having the brown coat color. This indicated that the supplemented diet led to an increased methylation of the A^vy gene.

Health Outcomes : Along with the coat color change, these mice also had reduced risks of obesity and other health issues associated with the yellow phenotype.

Transgenerational Effects : The study showed that nutritional interventions could have effects that extend beyond the individual, affecting the phenotype of the offspring.

The implications of this research are profound. It highlights how maternal nutrition during critical developmental periods can have lasting effects on offspring through epigenetic modifications, potentially affecting health outcomes much later in life.

The study also offers insights into how dietary and environmental factors might contribute to disease susceptibility in humans.

Challenges in Epigenetic Research:

Epigenetic changes can be tissue-specific, making it challenging to study in the living human brain
The causal direction (whether epigenetic changes cause disorders or result from them) is often unclear
The complexity of interactions between multiple epigenetic mechanisms and genetic variants

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Further Information

Genetic & Environmental Influences on Human Psychological Differences

Evidence for Nurture

Classical Conditioning
Little Albert Experiment
Operant Conditioning
Behaviorism
Social Learning Theory
Bronfenbrenner’s Ecological Systems Theory
Social Roles
Attachment Styles
The Hidden Links Between Mental Disorders
Visual Cliff Experiment
Behavioral Genetics, Genetics, and Epigenetics
Epigenetics
Is Epigenetics Inherited?
Physiological Psychology
Bowlby’s Maternal Deprivation Hypothesis
So is it nature not nurture after all?

Evidence for an Interaction

Genes, Interactions, and the Development of Behavior
Agouti Mouse Study
Biological Psychology

What does nature refer to in the nature vs. nurture debate?

In the nature vs. nurture debate, “nature” refers to the influence of genetics, innate qualities, and biological factors on human development, behavior, and traits. It emphasizes the role of hereditary factors in shaping who we are.

What does nurture refer to in the nature vs. nurture debate?

In the nature vs. nurture debate, “nurture” refers to the influence of the environment, upbringing, experiences, and social factors on human development, behavior, and traits. It emphasizes the role of external factors in shaping who we are.

Why is it important to determine the contribution of heredity (nature) and environment (nurture) in human development?

Determining the contribution of heredity and environment in human development is crucial for understanding the complex interplay between genetic factors and environmental influences. It helps identify the relative significance of each factor, informing interventions, policies, and strategies to optimize human potential and address developmental challenges.

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The Nature vs. Nurture Debate

Genetic and Environmental Influences and How They Interact

Verywell / Joshua Seong

Definitions
Interaction
Contemporary Views

Nature refers to how genetics influence an individual's personality, whereas nurture refers to how their environment (including relationships and experiences) impacts their development. Whether nature or nurture plays a bigger role in personality and development is one of the oldest philosophical debates within the field of psychology .

Learn how each is defined, along with why the issue of nature vs. nurture continues to arise. We also share a few examples of when arguments on this topic typically occur, how the two factors interact with each other, and contemporary views that exist in the debate of nature vs. nurture as it stands today.

Nature and Nurture Defined

To better understand the nature vs. nurture argument, it helps to know what each of these terms means.

Nature refers largely to our genetics . It includes the genes we are born with and other hereditary factors that can impact how our personality is formed and influence the way that we develop from childhood through adulthood.
Nurture encompasses the environmental factors that impact who we are. This includes our early childhood experiences, the way we were raised , our social relationships, and the surrounding culture.

A few biologically determined characteristics include genetic diseases, eye color, hair color, and skin color. Other characteristics are tied to environmental influences, such as how a person behaves, which can be influenced by parenting styles and learned experiences.

For example, one child might learn through observation and reinforcement to say please and thank you. Another child might learn to behave aggressively by observing older children engage in violent behavior on the playground.

The Debate of Nature vs. Nurture

The nature vs. nurture debate centers on the contributions of genetics and environmental factors to human development. Some philosophers, such as Plato and Descartes, suggested that certain factors are inborn or occur naturally regardless of environmental influences.

Advocates of this point of view believe that all of our characteristics and behaviors are the result of evolution. They contend that genetic traits are handed down from parents to their children and influence the individual differences that make each person unique.

Other well-known thinkers, such as John Locke, believed in what is known as tabula rasa which suggests that the mind begins as a blank slate . According to this notion, everything that we are is determined by our experiences.

Behaviorism is a good example of a theory rooted in this belief as behaviorists feel that all actions and behaviors are the results of conditioning. Theorists such as John B. Watson believed that people could be trained to do and become anything, regardless of their genetic background.

People with extreme views are called nativists and empiricists. Nativists take the position that all or most behaviors and characteristics are the result of inheritance. Empiricists take the position that all or most behaviors and characteristics result from learning.

Examples of Nature vs. Nurture

One example of when the argument of nature vs. nurture arises is when a person achieves a high level of academic success . Did they do so because they are genetically predisposed to elevated levels of intelligence, or is their success a result of an enriched environment?

The argument of nature vs. nurture can also be made when it comes to why a person behaves in a certain way. If a man abuses his wife and kids, for instance, is it because he was born with violent tendencies, or is violence something he learned by observing others in his life when growing up?

Nature vs. Nurture in Psychology

Throughout the history of psychology , the debate of nature vs. nurture has continued to stir up controversy. Eugenics, for example, was a movement heavily influenced by the nativist approach.

Psychologist Francis Galton coined the terms 'nature versus nurture' and 'eugenics' and believed that intelligence resulted from genetics. Galton also felt that intelligent individuals should be encouraged to marry and have many children, while less intelligent individuals should be discouraged from reproducing.

The value placed on nature vs. nurture can even vary between the different branches of psychology , with some branches taking a more one-sided approach. In biopsychology , for example, researchers conduct studies exploring how neurotransmitters influence behavior, emphasizing the role of nature.

In social psychology , on the other hand, researchers might conduct studies looking at how external factors such as peer pressure and social media influence behaviors, stressing the importance of nurture. Behaviorism is another branch that focuses on the impact of the environment on behavior.

Nature vs. Nurture in Child Development

Some psychological theories of child development place more emphasis on nature and others focus more on nurture. An example of a nativist theory involving child development is Chomsky's concept of a language acquisition device (LAD). According to this theory, all children are born with an instinctive mental capacity that allows them to both learn and produce language.

An example of an empiricist child development theory is Albert Bandura's social learning theory . This theory says that people learn by observing the behavior of others. In his famous Bobo doll experiment , Bandura demonstrated that children could learn aggressive behaviors simply by observing another person acting aggressively.

Nature vs. Nurture in Personality Development

There is also some argument as to whether nature or nurture plays a bigger role in the development of one's personality. The answer to this question varies depending on which personality development theory you use.

According to behavioral theories, our personality is a result of the interactions we have with our environment, while biological theories suggest that personality is largely inherited. Then there are psychodynamic theories of personality that emphasize the impact of both.

Nature vs. Nurture in Mental Illness Development

One could argue that either nature or nurture contributes to mental health development. Some causes of mental illness fall on the nature side of the debate, including changes to or imbalances with chemicals in the brain. Genetics can also contribute to mental illness development, increasing one's risk of a certain disorder or disease.

Mental disorders with some type of genetic component include autism , attention-deficit hyperactivity disorder (ADHD), bipolar disorder , major depression , and schizophrenia .

Other explanations for mental illness are environmental. This includes being exposed to environmental toxins, such as drugs or alcohol, while still in utero. Certain life experiences can also influence mental illness development, such as witnessing a traumatic event, leading to the development of post-traumatic stress disorder (PTSD).

Nature vs. Nurture in Mental Health Therapy

Different types of mental health treatment can also rely more heavily on either nature or nurture in their treatment approach. One of the goals of many types of therapy is to uncover any life experiences that may have contributed to mental illness development (nurture).

However, genetics (nature) can play a role in treatment as well. For instance, research indicates that a person's genetic makeup can impact how their body responds to antidepressants. Taking this into consideration is important for getting that person the help they need.

Interaction Between Nature and Nurture

Which is stronger: nature or nurture? Many researchers consider the interaction between heredity and environment—nature with nurture as opposed to nature versus nurture—to be the most important influencing factor of all.

For example, perfect pitch is the ability to detect the pitch of a musical tone without any reference. Researchers have found that this ability tends to run in families and might be tied to a single gene. However, they've also discovered that possessing the gene is not enough as musical training during early childhood is needed for this inherited ability to manifest itself.

Height is another example of a trait influenced by an interaction between nature and nurture. A child might inherit the genes for height. However, if they grow up in a deprived environment where proper nourishment isn't received, they might never attain the height they could have had if they'd grown up in a healthier environment.

A newer field of study that aims to learn more about the interaction between genes and environment is epigenetics . Epigenetics seeks to explain how environment can impact the way in which genes are expressed.

Some characteristics are biologically determined, such as eye color, hair color, and skin color. Other things, like life expectancy and height, have a strong biological component but are also influenced by environmental factors and lifestyle.

Contemporary Views of Nature vs. Nurture

Most experts recognize that neither nature nor nurture is stronger than the other. Instead, both factors play a critical role in who we are and who we become. Not only that but nature and nurture interact with each other in important ways all throughout our lifespan.

As a result, many in this field are interested in seeing how genes modulate environmental influences and vice versa. At the same time, this debate of nature vs. nurture still rages on in some areas, such as in the origins of homosexuality and influences on intelligence .

While a few people take the extreme nativist or radical empiricist approach, the reality is that there is not a simple way to disentangle the multitude of forces that exist in personality and human development. Instead, these influences include genetic factors, environmental factors, and how each intermingles with the other.

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By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Nature vs. Nurture in Science: The Effect of Researchers Segregation on Papers’ Citation Histories

Conference paper
First Online: 30 March 2023
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Ana Maria Jaramillo ORCID: orcid.org/0000-0003-2409-3064 6 ,
Felipe Montes ORCID: orcid.org/0000-0002-9923-4004 7 &
Ronaldo Menezes ORCID: orcid.org/0000-0002-6479-6429 6 , 8

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

Included in the following conference series:

International Workshop on Complex Networks

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Academia is a competitive world where researchers are judged by their productivity, and their strategies to get visibility and success (i.e., number of citations) vary. In addition to conducting rigorous research, there are social strategies that influence authors’ and their papers’ level of citations. The author’s position in the co-authorship network affects the success of their papers. Hence, we want to understand if the authors’ segregation in the co-authorship network relates to citations gained by a paper over time. We address this question by examining the patterns in Computer Science from 1975 to 2015 (and citations until 2020) from the Semantic Scholar Open Research Corpus. Specifically, we identify communities in the co-authorship network and classify them into segregation categories and core positions. Then, we compare the citation histories of papers written in those communities. We examine papers written solely by members of the same community (internal) and different communities (external), resulting in the following five categories: internal highly-segregated, internal non-segregated, external highly-segregated, external non-segregated, and external mixed. Our results show that from 1998 to 2010, internal highly-segregated papers gained fewer citations than internal non-segregated and external mixed papers. Also, from 2010 to 2015, external mixed papers gained more citations than internal non-segregated papers and even more citations than internal highly-segregated papers. We also found that in the network nucleus (from core decomposition), there is little difference in the citations of internal non- and highly-segregated papers. In contrast, in the network’s periphery, internal non-segregated papers tend to gain more citations than internal highly-segregated papers since 2005. From this work, we conclude that papers written by a more diverse set of authors (measured by their network connectivity) receive more citations over time and that to compensate for the lack of diversity, their authors should be in central positions of the co-authorship network. Hence, this work could incentivise diverse co-authorships and strengthen researchers’ cohesion to increase their papers’ success.

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The structure of segregation in co-authorship networks and its impact on scientific production

The emergence of the higher education research field (1976–2018): preferential attachment, smallworldness and fragmentation in its collaboration networks

A network-driven study of hyperprolific authors in computer science

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Jaramillo, A.M., Montes, F., Menezes, R. (2023). Nature vs. Nurture in Science: The Effect of Researchers Segregation on Papers’ Citation Histories. In: Teixeira, A.S., Botta, F., Mendes, J.F., Menezes, R., Mangioni, G. (eds) Complex Networks XIV. CompleNet 2023. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-28276-8_13

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Published: 12 December 2013

Perceptions of nature, nurture and behaviour

Mairi Levitt 1

Life Sciences, Society and Policy volume 9 , Article number: 13 ( 2013 ) Cite this article

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Trying to separate out nature and nurture as explanations for behaviour, as in classic genetic studies of twins and families, is now said to be both impossible and unproductive. In practice the nature-nurture model persists as a way of framing discussion on the causes of behaviour in genetic research papers, as well as in the media and lay debate. Social and environmental theories of crime have been dominant in criminology and in public policy while biological theories have been seen as outdated and discredited. Recently, research into genetic variations associated with aggressive and antisocial behaviour has received more attention in the media. This paper explores ideas on the role of nature and nurture in violent and antisocial behaviour through interviews and open-ended questionnaires among lay publics. There was general agreement that everybody’s behaviour is influenced to varying degrees by both genetic and environmental factors but deterministic accounts of causation, except in exceptional circumstances, were rejected. Only an emphasis on nature was seen as dangerous in its consequences, for society and for individuals themselves. Whereas academic researchers approach the debate from their disciplinary perspectives which may or may not engage with practical and policy issues, the key issue for the public was what sort of explanations of behaviour will lead to the best outcomes for all concerned.

Trying to separate out nature and nurture as explanations for behaviour, as in classic genetic studies of twins and families, is now said to be both impossible and unproductive. The nature-nurture debate is declared to be officially redundant by social scientists and scientists, ‘outdated, naive and unhelpful’ (Craddock, 2011 , p.637), ‘a false dichotomy’ (Traynor 2010 , p.196). Geneticists argue that nature and nurture interact to affect behaviour through complex and not yet fully understood ways, but, in practice, the debate continues 1 . Research papers by psychologists and geneticists still use the terms nature and nurture, or genes and environment, to consider their relative influences on, for example, temperament and personality, childhood obesity and toddler sleep patterns (McCrae et al., 2000 ; Anderson et al., 2007 ; Brescianini, 2011 ). These papers separate out and quantify the relative influences of nature/genes and nurture/environment. These papers might be taken to indicate how individuals acquire their personality traits or toddlers acquire their sleep patterns; part is innate or there at birth and part is acquired after birth due to environmental influences. The findings actually refer to technical heritability which is, ‘the proportion of phenotypic variation attributable to genetic differences between individuals’ (Keller, 2010 , p.57). In practice, as Keller illustrates, there is ‘slippage’ between heritability, meaning a trait being biologically transmissible, and technical heritability. This is not simply a mistake made by the media or ‘media hype’ but is, she argues, ‘almost impossible to avoid’ (ibid, p.71).

While researchers are aware of the complexity of gene-environment interaction, the ‘nature and nurture’ model persists as a simple way of framing discussion on the causes of behaviours. It is also a site of struggle between (and within) academic disciplines and, through influence on policy, has consequences for those whose behaviours are investigated. There is general agreement between social scientists and geneticists about the past abuses of genetics but disagreement over whether it will be possible for the new behavioural genetics to avoid discrimination and eugenic practices, and about the likely benefits that society will gain from this research (Parens et al. 2006 , xxi). In a special issue of the American Journal of Sociology ‘Exploring genetics and social structure’, Bearman considers the reasons why sociologists are concerned about genetic effects on behaviour; first they see it as legitimating existing societal arrangements, which assumes that ‘genetic’ is unchangeable. Second, if sociologists draw on genetic research it contaminates the sociological enterprise and, third, whatever claims are made to the contrary, it is a eugenicist project (Bearman, 2008 , vi). As we will see all these concerns were expressed by the publics in this study. Policy makers and publics are interested in explaining problem behaviour in order to change/control it, not in respecting disciplinary boundaries, and will expect the role of genetics to be considered alongside social factors. 2

Social and environmental theories of criminal behaviour have been dominant in criminology, and in public policy (Walsh, 2009 , p.7). Genetic disorders and mental illness have provided explanations for a small minority of offenders with specific conditions. A 2007 survey of American criminologists found that ‘criminologists of all ideological persuasions view alleged biosocial causes of crime (hormonal, genetic, and evolutionary factors and possibly low intelligence) as relatively unimportant’ compared with environmental causes (Cooper et al., 2010 ). Sociology textbooks have typically discussed biological theories of criminality only as discredited (Haralambos and Holborn, 2004 , Giddens, 2009 ). Biosocial theories are seen as attractive to ‘agents of social control’ and to be more likely to lead to abusive treatment of offenders. However, with increasing research and public interest in genetics more attention has been paid to biological aspects of crime and to genetic variations within the normal range. Research has focussed on violent and antisocial behaviours which are criminal or may be seen as a precursor to criminal behaviour, for example, antisocial behaviour in young people. Media reports have headlined ‘warrior genes’, ‘the aggressive gene’ and the ‘get out of jail free gene’, all referring to levels of monoamine oxidase A (MAOA) (Lea and Chambers, 2007 ; Levitt and Pieri, 2009 ) 3 . Think tanks and ethics groups have considered the ethics and practicalities of genetic testing for behavioural traits (Campbell and Ross, 2004 ; Dixon, 2005 Nuffield Council on Bioethics, 2002 ).

An attraction of research into genes and behaviour is the hope that identifying a genetic factor that is correlated with an increased incidence of, say, violent and antisocial behaviour, will point to a way of reducing such behaviour. Fotaki discusses the attraction of biological explanations of inequalities in health based on the assumption that genetic interventions ‘would succeed in addressing the causes of ill health that public health policies cannot.’ (Fotaki, 2011 , p.641). The danger is that biological explanations ‘are once more employed for political purposes to explain away the social roots of health inequalities.’ (ibid). Social scientists, and criminologists, have presented biological/genetic explanations of behaviour as dangerous in terms of their potential effect on the individuals or groups identified as genetically at risk. There are obvious dangers of discrimination against, and the stigmatisation of, already vulnerable groups who would be the first to be tested i.e. ‘problem’ families or minority ethnic groups. Discrimination could affect education, employment and family life. The effect of an individual being told s/he has a risk based on a genetic test has been much discussed in relation to health risks (Claassen et al., 2010 . While such information could be motivating, because it is personalised, it can also induce a fatalistic attitude that discourages the person from taking preventative measures. Claasen et al. conclude that it is important to identify those vulnerable to the fatalistic impact and to tailor health risk information (ibid p.194). Identifying risk for behaviour, rather than for disease, is likely to be more problematic because of the difficulty of finding preventative measures that are within the individuals’ own control.

..using DNA to assess risk, make a diagnosis or tailor treatments, may weaken beliefs in the efficacy of preventive behaviour and reinforce biological ways of reducing risk, resulting in a preference for medication as opposed to behavioural means to control or reduce risk (ibid, xiv).

Claasen et al.’s comment on genetic tests for health conditions could apply equally to parents given a behavioural risk for their young child from a genetic test, perhaps before any problem behaviour was evident. The test result could weaken parents’ belief that they could take action to prevent/reduce the risk of the behaviour developing in their child and pharmaceutical solutions, as posited by Caspi et al. might not be available (Caspi et al., 2002 , xvii). However, it is not necessarily the case that evidence of genetic or biological influence on behaviour leads to more punitive treatment. DeLisi et al. give the example of the use of findings from adolescent brain science in the case of Roper v. Simmons in the US which abolished the death penalty for adolescents. On the basis of the research it was stated that young people under the age of 18 ‘are more vulnerable or susceptible to negative influences and outside pressures including peer pressure’ (DeLisa et al., 2010 , p.25) When evidence on genetic traits associated with criminal behaviour has been allowed by courts, mainly in the US, it has so far more often been accepted as a mitigating rather than an aggravating factor in the offenders’ behaviour (Denno, 2009 , Farahany and Coleman, 2006 ).

Environmental explanations of behaviour can, of course, also be presented as deterministic, claiming a closed future for those experiencing poverty and disadvantage. However, it is biological explanations that have caused more concern not only because of the history of eugenics but also because they may be seen as more fundamental, being there from birth, and as harder to change. The public in surveys are reported to see the greatest role for genetic factors in physical features, a lesser role in health conditions and a smaller role still in human behaviour (Condit, 2010 , p.619).

Public perceptions

The model of nature/genes and nurture/environment is still used in behavioural genetics, as well as in popular culture, and has implications for public policy, including the treatment of offenders who claim that a genetic trait has influenced their criminal behaviour. The aim of this research was to explore ideas on the causes of behaviour, particularly violent and antisocial behaviour and examine how respondents use the nature/nurture model. This qualitative research looks at the ways in which lay publics in different age groups conceptualise the factors and influences that made them who they are and their explanations for the behaviour of other people; especially violent behaviour. It was hypothesised that the increased research and media emphasis on the role of genetic factors in health and behaviour might result in an increasing interest in ‘nature’, biology and genes as explanations for behaviour particularly among the young, but, when explaining their own behaviour people might prefer to see themselves as agents with control over their lives. By exploring explanations of behaviour with respondents from different generations, age differences should be apparent.

The views of 78 respondents from 3 generations were gathered by individual interview and questionnaires, using the same open ended questions and responses to two real-life criminal court case studies where environmental or genetic factors had been used by the defence team. Respondents were drawn from a group of retired people participating in an informal ‘senior learners’ programme at Lancaster University, a group of their mainly younger relatives and, in order to recruit more third generation respondents, a group of first year students taking a criminology module. The senior learners group had a programme of talks and discussions and could attend undergraduate lectures. They had, by definition, shown an interest in current issues in a range of fields. There were no educational or age requirements for the group but all the volunteers were retired from paid work and were aged from around 65 years to over 80 years.. They had had similar careers to those popular with social science students; social work, probation, teaching and administrative positions. The senior learners were asked to pass on questionnaires to younger relatives to investigate age differences in attitudes. The first 13 senior learners who responded were interviewed but as only 15 questionnaires were received from their relatives ethical approval was obtained to distribute the same questionnaire to Lancaster University students taking the criminology first year module. Most students were enrolled on social science degrees, including psychology and sociology, and age 18 or 19. While the sample of senior learners and relatives had only a few more women than men, 78 per cent of the students were female reflecting the gender balance on the module as a whole. This makes it difficult to comment on any gender differences in responses. No claims to generalisability are made for this exploratory study. Responses were coded and entered on SPSS and also analysed thematically using Atlas-ti.

The introduction to the interviews and questionnaire was ‘I am interested in your views and ideas on what makes us the people we are; what makes people behave the way they do? What is the influence of nature and nurture?’ The terms, nature and nurture were not used again until the final question. Although the terms were not defined all respondents readily used them with consistent meanings. They identified ‘nature’ with biology, ‘what you are born with’ and genes or DNA and nurture with all aspects of the environment including parenting, socio-economic conditions, the food you eat, culture and other people. Their understanding of environment was therefore similar to that used by genetic researchers; environment as everything that is external to the individual, although they tended to refer more to the social than the biological environment.

A general warm-up question asked whether, in their own family, there was anything they thought of as a ‘family trait’. Then respondents were asked; ‘Imagine a baby swapped at birth and brought up in a completely different family– which influences do you think would be most important – the influence of the birth parents or the influences of the new family- and why?’ 4 The rest of the interview schedule, and the subsequent questionnaire, consisted of open-ended questions.

Respondents were asked how they would explain different kinds of behaviour if they came across a child who is kind and considerate; a young person who displays antisocial and aggressive behaviour adult and an adult with criminal convictions for violence. This was to tap into any differences in general explanations of good and bad behaviour in young people and adults. A quotation about the child killers in the Bulger case being ‘unreformable’ was used to ascertain whether they saw some types of violent behavior, and the actors concerned, as immutable. In order to see how respondents conceptualized the influences of nature/biology/genes and environment/people/experiences in their own lives, respondents were asked to write down ‘what or who made you what you are today’ and any explanation of their responses. Comments were gathered on the introduction of an environmental factor (childhood neglect) by the defence in a violent attack by two young boys in England, and on a genetic factor (MAOA levels) introduced by the defence in an criminal court in Italy. Respondents were asked how they thought such evidence should be dealt with; whether it should affect the degree of blame and whether it should affect criminal responsibility. The final question asked if it mattered ‘for individuals or society’ whether nature or nurture was seen as most important in explaining problem behaviour. Those interviewed were asked if they had any further comments and there was a space for any additional comments on the questionnaire.

This paper focuses on the ways in which respondents employed nature/genes and nurture/environment in their responses as a whole and what other concepts they drew on when explaining behaviour.

Respondents’ explanations of what makes people behave the way they do are discussed through three themes.

Nurture is more influential than nature

Nature and nurture interact

Emphasising nature (but never nurture) can be dangerous

Theme 1: Nurture is more influential than nature

Whether asked about influences on a baby adopted at birth, on their own lives, on an aggressive child or a violent young person, almost all respondents emphasised nurture. Parents and family were seen as the most important influences for babies and young children, moving to peer group and other relationships and experiences for a young person. The explanation for the violent behaviour of an adult had more to do with the individual and the importance of nurture/environment in explaining behaviour weakened. The quotations below explaining behaviour in a child adopted at birth, a young person and an adult illustrate the widening of influences from infancy through childhood and the onus on adults to take responsibility for themselves.

[a child] The environment in which a child grows up in, particularly the influence and role of the parents shapes how a child will grow up and what sort of adult they will be (77 Student).

[a young person] I believe that upbringing shapes a person’s personality. Provisions of education, lifestyle opportunities and friendship groups all determine ….outlook. You can see evidence in young people at the school I teach at (20 Relative).

Once adult they have to take responsibility for themselves and address whatever has been in their background. An adult can’t turn round and say it’s not my fault (5 Senior Learner).

Participants also saw themselves as shaped by the people surrounding them, starting with their parents, or those who brought them up. Several mentioned the illness and/or death of a parent during their childhood and older respondents talked about separation due to the second world war. Students were especially likely to mention the influence of morals instilled in them by their parents, the core values and discipline that they were taught at home. Educational experiences were important to all. For the senior learners the school leaving age had been age 15, so whether or not they stayed on at school and took public examinations was crucial for their future, and, this decision depended largely on their parents and environment. For the student respondents who had come to university from school, life so far has been ‘kind of set-out’ (41 Student), in the sense that they had progressed through the education system to gain qualifications for university. For their peer group it was normal still to be in education or training at the age of 18.

The lasting effects of early influences were particularly striking among the senior learners, because they were much further removed in years from their childhood. Many related stories about parental influence and also about teachers who taught them at least 50 years ago and had affected them for better or worse. For example a senior learner recalled one of her teachers;

I hated primary school – the teacher in 3rd or 4th year juniors [for ages 9–11] I hated her she was not a nice woman….. I passed to go to the grammar school and it shocked her. She made a derogatory comment – may not have been directed at me but felt it was- about some who should have passed and didn’t and some passing who should not have done…… I always vowed I would never be like that when I was teaching….(11 Senior Learner).

Those who related negative influences presented themselves as active in response, not necessarily at the time but later in their lives. For example a student whose mother had died wrote that ‘it made me more independent’ and another student who was bullied at school wrote that ‘it made me stronger’. The adult had to deal with all the influences (negative or positive) and take control.

Theme 2: Nature and nurture interact

While respondents’ view of themselves and of a child adopted at birth assigned greater influence to environment this did not mean that they held a simplistic model of, for example 60:40 nurture to nature. In this one question when they were asked to choose one or other as the major influence, almost all chose nurture, as many social scientists might do. However, in open questions and comments more complex interactive models were expressed. Environment/nurture can affect genes/nature and vice versa. No one used the term epigenetics but responses referred to the possibility of environmental influences affecting gene expression, for example;

People with certain predispositions (e.g. to violence) are affected by society, and society affects how their genes are expressed (40 Student).

An older respondent reflects on personal experience of child rearing and asks whether nurture is influenced by nature;

I think the nature nurture debate is very interesting. In my family I can see where my children have their own natures that have developed despite being brought up in the same family with the same boundaries etc. However, as a parent did I alter how I nurture them to take into account their nature? (14 Senior Learner).

This quotation illustrates the inseparability of nature and nurture. The child is developing within the family and the parent is developing parenting strategies informed by previous experiences and by other influences including the reactions of the children.

It was obvious to respondents that both genetic and environmental factors impact on everyone (although the role of genes is not yet understood) and it will be harder for some than for others to behave well because of their genes and environment. These people may need different treatment or extra help if they have committed violent and aggressive crimes but that does not excuse their behaviour. Only in exceptional cases, like insanity, can a young person or adult be said to have no choice but to act in a particular way. It is important that people are seen as responsible while also giving them the help they need. In these two comments the treatment for environmental problems and ‘biology’ are similar; the individual can be helped to modify his/her behaviour.

No, [nature and nurture] both play a part, but they can’t be the explanation for everything. Some people grow up in broken homes and get treated appallingly- yet they seem to understand right + wrong and accept responsibility for their actions. There are too many excuses and we never solve any problems, just make them harder to resolve.......I think if you are sane and you know right from wrong you need to suffer the consequences if you’ve committed a crime, but I do appreciate you may need help psychologically if you have anger issues, for example. If we constantly find reasons to diminish blame from people who have committed heinous acts of crime more people will think they can get away with it and it will cause more harm than good (78 Student).

Some say you can’t fight your biology, but there are social factors that can stop bad behaviour like learned restraint (72 Student).

The desire to leave a space for individual agency may be linked to the finding that emphasising nature, but never nurture, could be dangerous. It is clear that as children grow up they can exercise more control over their environment, although some have more control and choices than others. On the other hand, whatever the individual is born with (genes and nature) is, or seems to be, less malleable which could lead to different criminal justice policies and different social perceptions of the criminal.

Theme 3: Emphasising nature (but never nurture) can be dangerous for society as a whole as well as for the criminal and victims

The question asked was whether it mattered ‘for individuals or society’ if either nature or nurture was seen as most important in explaining problem behavior. The two most popular answers were that both nature and nurture were needed to explain behaviour, or, that nurture was more important and that there were dangers in emphasising nature. No one in the sample regarded an emphasis on nurture as dangerous or detrimental to the individual or society. On the contrary, emphasising nurture was thought more likely to lead to non-punitive treatment of offenders. There would be attempts to alter future behaviour through improved education and parenting and spreading of knowledge in society about the impact nurture has on young people. Society as a whole would share the blame rather than the individual. As a student put it; ‘society as a whole [would be] open for criticism’ (55 S). An emphasis on nurture was therefore seen as more likely to lead to understanding of problem behaviours and effective treatment, however, the individuals were still to be held responsible for their behaviour.

In contrast there was a mistrust of nature/genetic explanations that again centred on the practical consequences for individuals. It would affect the way criminals were treated by others but could also change their view of themselves. Behaviour would be seen as unchangeable, out of the control of the individual or social action. As a consequence, individual accountability might be removed. The idea that individuals must normally be held responsible for their actions was constantly emphasised (Levitt, 2013 ).

It does [matter] because [if nurture is emphasised] people will care, parent and look after and raise people with more care. However if it’s proven it is nature, then people may lose the will to live (60 Student).

Several SLs referred to the examination at the end of primary education (the ‘eleven plus’) when explaining why they emphasised environment/nurture rather than nature, or, in this case, innate intelligence. The ‘eleven plus’ examination was used to decide which children would be offered a place at an academically selective grammar school and was based on the idea that intelligence, and future academic achievement, could be accurately measured and predicted at the age of 10 or 11.

‘The 11+ was a nature thing. I did the 11+ − it had an effect. Saying children not going to improve or change. Very embedded in the whole idea of nature – it can’t really be true’ (8 Senior Learner).

An emphasis on nature has practical detrimental consequences for individuals. Their status is fixed, for example as ‘not academic’ or ‘born evil’ and suggests, to them and to others, that their ‘nature’ is unchangeable or very difficult to change by individual or social action.

Yes, [it matters] hugely as position of blame is dependent on whether a person chose to do what they did .....nature suggests no control (35 Student).

Those who thought an emphasis on nature meant people were irredeemable either gave that as a reason not to emphasise nature or to suggest that in fact ‘defects’ of nature could be overcome, as in this comment by a student emphasising the power of education;

Yes it is very important because it helps to understand if people are reformable (nurture) or irredeemable (nature). I believe we are determined by our education and thus with the proper help we can change. In the case of people with major biological defects, education is still a way to get over these obstacles and society should be ready to help these people (38 Student).

It might be thought that offenders themselves would embrace a genetic explanation of their behaviour if this was interpreted, as the respondents feared, as meaning they were not responsible for their crimes. However, a small study of juvenile offenders in the Netherlands found that they gave social explanations of their crimes and most rejected the idea that biology might be a factor. They committed a crime for a specific purpose like to get money or to impress others or they gave environmental reasons such as a deprived background or peer pressure or explained their offences were due to psychological conditions brought on by the use of alcohol and soft drugs (Horstkötter et al., 2012 , p.291). Whether they gave goal directed or environmental reasons ‘most of them also state that they had a choice and that it was their choice to commit the crime’ (ibid p.292). As one young offender said in interview;

In the end the person makes the choice himself… The choices I have made also had a share in my past. But in the end I am the one who has made these choices (ibid).

Genes and environment

Respondents were at ease with the language of nature and nurture which was only used in the introduction to the questionnaire or interview. They readily equated genes with nature and nurture with all sorts of environmental influences. There was an acknowledgement that our understanding of environmental factors is greater than our understanding of genetics but that that would change. Older respondents were more likely to be concerned about such a change.

They're going to be doing a lot more with genetics. Influences policy profoundly and people have to be very careful. It worries me that seen to be [more determining]. The complexities don’t get looked at. If you emphasise environment it is safer from a policy point of view because given that most people don’t know what they are talking about it is safer to see the person as redeemable than to come down on the side of genetics and write people off (3 Senior Learner).

This quotation is typical in its view that nature/genes are seen as determining even though the influences on behaviour are, in reality, complex. Like the studies quoted at the beginning of the article respondents often acknowledged the complexities as nature and nurture interact but separated them when explaining the causes of specific behaviours. Students were less likely to be fearful of genetic explanations of behaviour despite their academic interest in social science. However, the hypothesis that young people might be more likely to be interested in genetic explanations for behaviour was not shown in this small study. The senior learners were more likely to refer to reading on genes and display knowledge of genetics. Older respondents and their relatives more often echoed the sociologists’ concerns about behavioural genetics discussed by Bearman earlier (Bearman, 2008 ). For those who feared the practical consequences of genetic explanations, like the respondent quoted above, ‘it is safer’ to keep away from them.

Some respondents in all age groups were prepared for advances in genetics to change their understanding of behaviour and prepared for current views of genes/nature as more basic, fixed and unchanging to change too. One of the youngest relatives, in her 20s, emphasised our incomplete knowledge of genetic influences on behaviour as a reason for focussing on nurture ‘at present’;

It is very tricky as we cannot see genes and I am not sure that I totally trust the idea of blaming genes for violent behaviour- maybe the person has a gene for passive behaviour as well. …….In any case we can change nurture but at present we cannot change nature so let’s do one thing at a time (20 Relative).

As respondents in this small study grappled with explanations for their own and others’ behaviour they focussed on the practical consequences leading to a greater concern over explanations based on nature than the more familiar ones based on a complex web of environmental factors. Whereas academic researchers approach the debate from their disciplinary perspectives which may or may not engage with practical and policy issues, the key issue for the public was what sort of explanations of behaviour will lead to the best outcomes for all concerned.

1 Behavioural epigenetic research has indicated that life experiences can affect gene expression. While controversial the research suggests the possibility of further complications for the nature-nurture relationship as nurture may be said to shape nature (Buchen, 2010 Powledge, 2011 ). 2 Bearman op cit iv. The ESRC Cambridge Network Social Contexts of Pathways into Crime (SCoPiC) promoted multidisciplinary research into the causes of crime and included the E risk longitudinal twin study led by Terri Moffitt which investigated how genetic and environmental factors shape children's disruptive behaviour http://www.scopic.ac.uk Accessed 3 Sep 2013. 3 Violent and antisocial behaviour in this longitudinal study was correlated with a common genetic trait (low expression of MAOA) only where the person was severely maltreated in childhood. Behaviour was measured on 4 outcomes; diagnoses of conduct disorder, psychological tests of aggression and anti-social personality disorder and convictions for violent crime. Caspi et al. 2002 (supplementary material). 4 This initial warm-up question implied that the influences of nature and nurture could be separated and quantified as in common usage both in academic and popular discourses. As discussed respondents were able to express their views more fully (and with more complexity) in the subsequent open questions.

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The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. This work was part of the Research Programme of the ESRC Genomics Network at Cesagen (ESRC Centre for Economic and Social Aspects of Genomics).

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Levitt, M. Perceptions of nature, nurture and behaviour. Life Sci Soc Policy 9 , 13 (2013). https://doi.org/10.1186/2195-7819-9-13

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Nature vs. Nurture Debate: What Really Matters in Psychology

Is your life and personality shaped by your genes or environment? This is the big question of the nature vs. nurture debate, science has the answer.

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Are you simply a product of your environment, or do your genes have the final say? This is the ultimate question of the nature vs. nurture debate. Take a deep dive into the origins of the debate, and learn how epigenetics has upended the argument once and for all.

What is Nature vs. Nurture?

Nature vs. nurture can be defined as the difference between the genetics that people inherit (nature) vs. the environmental influences that accumulate over a lifetime (nurture). For years, many people have believed that nature rules supreme and reject the idea that environment or parenting has a large role in shaping people.

The big question in the debate is this––how much of a person’s personality is a result of genes, and how much is related to environment and experiences? People have been arguing about this for years for political, personal, and social reasons.

So, what’s the answer…are we shaped by nature or nurture? The answer is both, and it depends on which traits. Read on for the science of nature or nurture below.

Examples of Nature vs. Nurture

Let’s look at some examples to see how nature and nurture impact a person’s development.

Examples of Nature Impacting Human Development:

Genetically predisposed to be tall.
Inherited red hair and blue eyes from the maternal side of the family.
ADHD, when it appears together with conduct disorder, is attributed to genes 1 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303131/ .
Genes contribute to genetic disorders such as Edwards syndrome, Patau syndrome, and Warkany syndrome.
Anxiety and depression occurring together 1 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303131/ are considered to be connected to a genetic predisposition.

Examples of Nurture Impacting Human Development:

The mother experienced high amounts of prenatal stress 2 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676865/#:~:text=Overall%2C%20maternal%20anxiety%20and%20depression,2017%3B%20Takegata%20et%20al.%2C , contributing to a fearful personality in the child, who is likely to express positive emotions.
Lack of healthy attachment to the caregiver impacts relationships with others throughout life.
Growing up malnourished 3 https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01886/full can stunt height and contribute to obesity.
A supportive community environment 4 https://digitalscholarship.unlv.edu/cgi/viewcontent.cgi?article=1583&context=jhdrp contributed to feelings of confidence and the ability to succeed.
Growing up during political instability causes heightened aggression and revenge-seeking 5 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3712526/#:~:text=There%20is%20now%20convincing%20documentation,disorders%2C%20fear%20and%20panic%2C%20poor later in life.

How Has Nature vs. Nurture Changed Over Time?

Nature vs. nurture has changed in many ways, perhaps the most significant change being the understanding of nurture. Early developmentalists saw nurture as the care given to the child by their parents (usually with an emphasis on the mother). Today scientists continue to discover that nurture includes many environmental influences––from prenatal to end-of-life.

While the nature vs. nurture debate was once hotly disputed, most human developmentalists agree that both nature and nurture have a hand in shaping individuals.

What you should know: The study of epigenetics 6 https://developingchild.harvard.edu/resources/what-is-epigenetics-and-how-does-it-relate-to-child-development/ has changed the nature vs. nurture debate landscape. Genes are not static but are impacted by nurture (environment), making it possible to change and override gene expression.

We’ll get to even more examples below, but let’s look at a couple of scenarios of how nurture can impact genes.

Scenario 1: You are genetically predisposed to obesity, but your mom had excellent dietary health during pregnancy; this impacts your epigenome 7 https://ehp.niehs.nih.gov/doi/10.1289/ehp.8700?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed , reducing the risk for obesity and increasing your lifespan.

Scenario 2: In early childhood, you have several negative experiences that deeply impact you. These experiences have the ability to override your natural gene expression 8 https://www.sciencedirect.com/science/article/abs/pii/S0306452212003028?via%3Dihub and “increase the risk not only for poor physical and mental health outcomes but also for impairments in future learning capacity and behavior.”

Everything from social interactions to diet to air quality can impact how genes interact and are expressed.

“Contrary to popular belief, the genes inherited from one’s parents do not set a child’s future development in stone.” — Harvard Center on the Developing Child

The question, as we’ll see, isn’t nature or nurture, but rather nature and nurture.

What Does Nature vs. Nurture Have to Do With Psychology, Sociology, and Genetics?

The nature vs. nurture debate has both been influenced by and has influenced psychology, sociology, and genetics.

Psychology is largely concerned with the mind and behavior of the individual.
Sociology is concerned with the collective experiences and behavior of society.
Genetics studies how genes and traits are passed down through families.

Ultimately, all three are concerned with studying how and why people behave the way they do. But this isn’t just about behavior; nature vs. nurture has been extensively studied in relation to the body. Scientists want to know how genes and the environment impact everything from low back pain 9 https://pubmed.ncbi.nlm.nih.gov/23335362/ to obesity 10 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3224976/ .

Let’s dive deeper so you can decide for yourself how much nature or nurture may have had a hand in shaping your own personality.

How To Set Better Goals Using Science

Do you set the same goals over and over again? If you’re not achieving your goals – it’s not your fault! Let me show you the science-based goal-setting framework to help you achieve your biggest goals.

Who Came Up With Nature vs. Nurture?

Sir Francis Galton is credited with first coining the nature vs. nurture phrase. To better understand the beginning of the nature vs. nurture debate, we have to go back to the 1800s to look at why Galton came up with “nature vs. nurture” in the first place. Hold on because it’s not pretty.

Galton was a particularly unlikable anthropologist who gave us fingerprinting (great!) and invented eugenics (why was he knighted?).

He sought to defend his beliefs with science and set out to prove that nature, not nurture, determined the intelligence and “excellence” of a person 11 https://galton.org/books/hereditary-genius/ . His cousin, Darwin, gave his stamp of approval on the “capital account” 12 https://galton.org/letters/darwin/correspondence.htm given by Galton in his book, Hereditary Genius 13 https://galton.org/books/hereditary-genius/text/v5/galton-1869-hereditary-genius-v5.htm#_Toc68688332 .

In the book, Galton used the nature over nurture argument to propose and legitimize the ultimate elimination of criminals, “worthless” individuals, and “inferior” races (including Africans, Australians, Jews, working-class women in London, etc.) by controlling who could procreate and who couldn’t.

While it’s unfortunate Galton had such a negative impact on science, it provides important context. Understanding where the debate originated helps us understand the ethical implications of how an unbalanced view of nature has been used to justify ongoing injustice both in policymaking and the treatment of individuals.

Even though the argument for nature had a sordid start, let’s not throw it out completely! There is a lot we can learn about ourselves, as both nature and nurture have a hand in shaping who we are.

How Nature and Nurture Impact Human Development & Personality

Most developmentalists believe each person is unique and responds to a situation or experience based on many factors. As you try to understand the impact of nature and nurture on yourself or others, please remember while human development is a refined science, people are not computers. People can, and often do, defy the expectations of science, either becoming more or less resilient in the face of challenges.

How Nature Impacts Personality

Now remember, nature involves the genetics that impact a person’s development and personality. Studies have found a person’s genes impact 30-60% of personality 14 https://www.nature.com/articles/s41380-018-0263-6 . If this sounds like a broad range, it is! But, we must consider all the variables that interact with a person’s genes.

A number of studies 15 https://journals.sagepub.com/doi/10.1111/j.0963-7214.2004.00295.x have found a connection between genetics and emotional well-being.
While personality seems to be heritable, to some extent, researchers are still trying to understand the actual “genetic basis of personality 16 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012279/ .”

What this really means: Researchers would like to attribute personality traits like neuroticism or extroversion to a specific gene in your body, but, at the end of the day, they can’t. Studies have linked genetics with certain behavior and traits, but studies are often difficult to replicate 16 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012279/ and may have gaps in the research. Nature clearly impacts a person, but science isn’t as hard and fast as some might think.

Watch our video below to learn what type of personality you have:

How Nurture Impacts Personality

Remember the variables we mentioned that impact nature? Those variables are largely introduced by nurture. Here are some examples of how nurture can impact personality.

Maternal stress during pregnancy 17 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5052760/ has been found to increase the child’s stress. This, in turn, impacts the temperament of the child 18 https://srcd.onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-8624.1995.tb00851.x .
A study in Germany 19 https://pubmed.ncbi.nlm.nih.gov/22275337/ found that military training decreased agreeableness in personalities, and this change persisted even after a person left the military and re-entered the workforce.
Social expectations create the most profound personality changes 20 https://pubmed.ncbi.nlm.nih.gov/21859226/ in the young and the elderly.
Food insecurity harmfully impacts mental health 21 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7282962/ , causing everything from anxiety to maternal depression. Interestingly, food insecurity also increases the risk of obesity 3 https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01886/full .

As you can see, nurture isn’t just how much a mother holds and comforts her baby! This is a limited view of nurture when in reality, there are so many external factors involved. The psychologist Urie Bronfenbrenner identified six key ecological systems that profoundly impact a person. All of these systems are an element of nurture.

Microsystem: Immediate social relationships, including family and peers.
Exosystem: Local institutions such as school, churches, temples, mosques, etc.
Macrosystem: The larger setting that a person inhabits, such as culture, economics, and politics, creates a sense of shared beliefs and expectations of behavior.
Mesosystem: How other systems are interconnected.
Chronosystem: The historical context that a person lives in, including values, events, technologies, and birth cohort (e.g., Boomer, Gen X, Millennial, Gen Z).
Bioecological: The internal biology of a person.

The ecological systems don’t just impact a person during childhood development. Psychology recognizes that people change through all phases of life! Personality is not set in stone 22 https://pubmed.ncbi.nlm.nih.gov/12757147/ . As a person ages and lives in various environments, this impacts how the person experiences the world around them.

“In the real world, there is no nature vs. nurture argument, only an infinitely complex and moment-by-moment interaction between genetic and environmental effects” — Gabor Maté, Physician and Author

Can You Change Your Genes?

At the end of the day, your genes (nature) are directly impacted by your environment (nurture). This means you have the power to change your genes!

If that doesn’t make sense and you’re still wondering which is more important––nature or nurture, the delightful world of epigenetics has the answers. Let’s start with this beautifully explained infographic from Harvard 6 https://developingchild.harvard.edu/resources/what-is-epigenetics-and-how-does-it-relate-to-child-development/ .

An infographic from Harvard University talking about Epigenetics which relates back to the nature vs. nurture topic.

Image: Harvard Center on the Developing Child

Essentially, epigenetics put to rest the old question of whether nature or nurture is more important in shaping identity and personality. Because of how epigenetics work in your body, nature, and nurture have a symbiotic relationship––one impacting the other and creating an ebb and flow in personality.

You can change your genes by changing your behavior and your environment.

Pro Tip: Studies have found you can begin to modify your epigenetic patterns 23 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3752894/ when you…

Adjust your diet
Add in physical exercise
Reduce alcohol consumption
Remove tobacco
Limit exposure to environmental pollutants
Learn to manage stress
Avoid working night shifts
Have supportive, safe relationships

How Nature and Nurture Impacted Your Own Development

As you think about how nature and nurture have impacted you, we encourage you to reflect on your experiences both in the past and the present. Think about the experiences of your parents. What was it like for your mom when she was pregnant with you, the environment you grew up in, and where you find yourself today?

Your life is an intricate story woven with tiny threads of your experiences, the experiences of your environment and community, and the experiences of your ancestors. The past had a hand in shaping the person you are today, but you have the amazing ability to change the direction of who you will become.

The Highlights:

Inherited genes may impact things like height, personality, and health.
Experiences and environment impact how genes are activated and released. This is epigenetics and impacts everything from what triggers you to how you respond in social situations.
Safe relationships and supportive environments can positively impact the epigenome.
As much as possible, choose to be in positive environments. Surrounding yourself with beauty, clean air, nature, and healthy relationships builds your capacity for change.

As you identify the areas of your life that you’d like to improve or change, emotional intelligence is an excellent place to start. This is a skill that will help you connect with yourself and others. Check out our article on 10 Emotional Intelligence Traits to Master for Self-Growth .

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Nature vs. nurture: Depression amplified in difficult environments for youth with a larger left hippocampus, study finds

by Shanice Harris, Northwestern University

While the mental health crisis has touched the lives of young people across a broad age spectrum, new Northwestern University research has found that the presence of difficult social environments and the absence of positive social environments predicted greater increases in depressive symptoms in youth, aged 9–11, over a two-year period.

In addition to environment, left hippocampal volume amplified the social context effects, suggesting that youth with a larger left hippocampus experience greater increases in major depressive disorder symptoms in challenging social spaces.

"Our research has implications not only for future research, but we also hope it increases awareness among parents, educators, mental health professionals and policy makers," said co-lead author Claudia Haase, associate professor of human development and social policy at Northwestern's School of Education and Social Policy (SESP).

"Over the years, the pendulum has swung back and forth between some researchers and practitioners emphasizing the role of nature and others emphasizing the role of nurture. And we have come to really appreciate that we need to look at both and their interplay together."

The study , in Proceedings of the National Academy of Sciences , underscores the importance of families, peers and schools in the development of depression during adolescence, and how variation in neural structure can amplify or diminish sensitivity to their environment.

The study was first authored by Matías Martínez, doctoral student at SESP, with senior co-authors Haase and Yang Qu, associate professor of human development and social policy at SESP. Titled "Depressive symptoms during the transition to adolescence: Left hippocampal volume as a marker of social context sensitivity," additional authors include Tianying Cai; Beiming Yang; Zexi Zhou; Stewart Shankman; and Vijay A. Mittal.

"Our study emphasizes the importance of paying attention to individual differences and how some people are more sensitive to social environments than others," Qu said. "We should never assume that the same environment will have the same impact for everyone. There is no one size fits all."

The findings

Since neuroscience has seen major developments over the past few years, the researchers focused on brain-based sensitivity in the development of depressive symptoms .

"Previous studies have focused on physiological processes or genetic variants, but with the development of neuroscience, now we can look at how the brain can play a role in the sensitivity to environments," Martinez said.

"There's a longstanding debate on whether some individuals are more or less sensitive to environments and in this study, we focused on sensitivity to social experiences, both negative and positive."

The results concluded that the left hippocampus—a region of the brain that is primarily associated with memory, learning and how humans experience the world around them—plays an important role in whether a person becomes depressed if they find themselves in a challenging social space. A larger hippocampus would result in an individual being better able to remember an experience or recall a memory.

"It is one of the most plastic regions of the brain," Martinez said. "It's very responsive to the environment, especially in a person's early years. Our findings show that this brain region is playing a role in making youth more sensitive to difficult environments and to the absence of positivity in their life experiences—leading to depression symptoms."

That area of the brain being larger in a child could result in that child having more sensitivity to social experiences—family conflicts, primary caregiver's depressive symptoms, peer victimization, parental warmth and prosocial school environment—into adolescence.

"Some people tend to assume that we are 'born this way' when it comes to the human brain. But the more we learn about the brain, the more scientists have come to understand how open and malleable our brains are, not just in infancy but across the life span," Haase said.

"Our brains can change in response to the environments we find ourselves in—and studies show that this is certainly the case for the hippocampus as a brain region."

The researchers examined two-year longitudinal data from the Adolescent Brain Cognitive Development study. The study—one of the largest studies in the U.S. conducted by 21 research sites across the country—aims to follow a diverse sample of 11,800 kids aged 9–11 over a 10-year period to observe their cognitive, brain, social and emotional development over time.

"The ABCD study is phenomenal, and we are deeply indebted to the National Institutes of Health and all the researchers involved for making this possible, and, of course, to all the youth and their families who are participating," Qu said. "It's the largest long-term study of brain development and child health in the United States."

The data revealed a stronger association between socio-experiential environments and MDD symptoms for youth with a larger left hippocampal volume and no differences in MDD symptoms between individuals with different sizes of left hippocampus at low levels of negative and high levels of positive context exposure.

What's next

The researchers are hoping the study helps parents, teachers and policymakers better understand and support youth's mental health during adolescence. Martinez is hoping their expanded research can better explain how children in difficult social environments adapt to their surroundings in the long term.

"The ABCD study is such a comprehensive project that will continue to follow youth development for many more years," Martinez said. "It will be exciting to examine what the interplay between exposure to different environments, hippocampal volume and depressive symptoms looks like as our youth navigate their teenage years."

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The nature and nurture of high IQ: An extended sensitive period for intellectual development

Angela m brant.

1 Department of Psychology, The Pennsylvania State University, University Park, PA 16802-3106

2 Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder CO, USA, 80309

Yuko Munakata

Dorret i boomsma.

3 Department of Biological Psychology, VU University, Van der Boechorststraat 1, 1081 BT Amsterdam, The Netherlands

John C DeFries

4 Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder CO, USA, 80309

Claire MA Haworth

5 Social, Genetic and Developmental Psychiatry Centre (MRC), Institute of Psychiatry - PO80, DeCrespigny Park, Denmark Hill, London, United Kingdom, SE5 8AF

Matthew C Keller

Nicholas g martin.

6 Queensland Institute of Medical Research, Locked Bag 2000, Royal Brisbane Hospital, Herston, Qld 4029, Australia

Matthew McGue

7 University of Minnesota, Psychology Department, N218 Elliott Hall, 75 East River Road, Minneapolis, MN, 55455-0344

Stephen A Petrill

8 Ohio State University, The Department of Human Development and Family Science, 135 Campbell Hall, 1787 Neil Avenue, Columbus, OH, 43210

Robert Plomin

Sally j wadsworth, margaret j wright, john k hewitt, associated data.

IQ predicts many measures of life success, as well as trajectories of brain development. Prolonged cortical thickening observed in individuals with higher IQ might reflect an extended period of synaptogenesis and high environmental sensitivity or plasticity. We tested this hypothesis by examining the timing of changes in the magnitude of genetic and environmental influences on IQ as a function of IQ score. We find that individuals with higher IQ show high environmental influence on IQ into adolescence (resembling younger children), whereas individuals with lower IQ show high heritability of IQ in adolescence (resembling adults), consistent with an extended sensitive period for intellectual development in more intelligent individuals. These patterns hold across a cross-sectional sample of almost 11,000 twin pairs, and a longitudinal sample of twins, biological siblings, and adoptive siblings.

Introduction

Adult IQ is a measure of cognitive ability that is predictive of social and occupational status, educational and job performance, adult health and longevity ( Gottfredson, 1997 ; Neisser et al , 1996 ; Whalley & Deary, 2001 ). Individuals with IQ scores at the high end of the distribution show distinct timing of postnatal structural changes in cortical regions known to support intelligence, which has been posited to reflect an extended “sensitive period” ( Shaw et al , 2006 ). Specifically, change in cortical thickness in frontal and temporal regions is cubic during development, with initial thickening in childhood, followed by thinning in late childhood/adolescence that levels out in young adulthood (see also Shaw et al , 2008 ), matching the patterns of synaptogenesis and pruning observed in postmortem prefrontal tissue ( Petanjek et al , 2011 ). Individuals of superior IQ (compared to average and high) show more intense and prolonged cortical thickening, followed by more rapid thinning. This distinct trajectory may reflect prolonged synaptogenesis and an extended sensitive period, during which the brain is particularly responsive to environmental input ( Shaw et al , 2006 ).

Further evidence for a link between cortical thickness and IQ comes from the finding that common genes influence change in cortical thickness and IQ in adulthood ( Brans et al., 2010 ). In addition, IQ and cortical thickness show similar patterns of change across development in the magnitude of genetic and environmental influences. Specifically, the heritability (magnitude of genetic influence) of IQ and the heritability of cortical thickness in brain regions associated with IQ both increase during childhood and adolescence, while environmental influences decrease in importance ( Haworth et al., 2010 ; Bartels, Rietveld, Van Baal & Boomsma, 2002 ; Brant, Haberstick, Corley, Wadsworth, DeFries & Hewitt,, 2009 ; Lenroot et al , 2009 ).

These results are suggestive of an extended sensitive period for IQ development: cortical thickening, which is associated with IQ, occurs over an extended period for individuals with higher IQ, corresponding to prolonged sensitivity to the environment. These results are only suggestive, however, because developmental changes do not necessarily correspond to changes in sensitivity to the environment. There is no direct evidence for individual differences in the length of a sensitive period for IQ.

We provide an empirical test of the extended sensitive-period hypothesis of high IQ, by examining changes in the magnitude of genetic and environmental influence on individual differences in IQ scores throughout development. As noted above, the magnitude of environmental influences on IQ decreases across development. We test whether these decreases in environmental influence occur later in development for individuals with higher IQ, consistent with a prolonged sensitivity to the environment. We focus on influences of the shared family environment rather than individual-specific environment, because the developmental change in environmental influence on intelligence is mainly driven by a reduction in influence of the shared family environment. Additionally, the shared family environment should arguably be the driving force behind experiential influence on IQ, because shared family environmental influences are highly correlated across different ages such that their effects can accumulate across development, while individual-specific environmental factors tend to be more age-specific and include measurement error ( Brant et al , 2009 ).

We use a cross-sectional sample of 11,000 twin pairs aged from 4 –71 years, and a smaller longitudinal replication sample of twins, biological siblings and adoptive siblings tested from ages 1 to 16. Previously published investigations using the datasets examined here have tested for differences between high IQ and IQ in the normal range. Although no difference was reported in the etiology of individual differences ( Haworth et al , 2009 ; cross-sectional GHCA sample) nor in their trajectories of developmental change ( Brant et al , 2009 ; Longitudinal Twin Sample), these investigations discretized IQ rather than examining continuous trends, and did not test whether the relationship between IQ score and heritiability/environmentality was specific to adolescence. Here we test this hypothesis explicitly. We predict that environmental influences should remain high for longer in higher IQ individuals, and that genetic influences conversely should remain lower for longer. IQ score should therefore be associated with magnitude of genetic and environmental influence in adolescence (but not in childhood or adulthood, where regardless of IQ, environmental influences should be high or genetic influences should be high, respectively).

Participants and Measures

Participants for the initial cross-sectional analysis were 10,897 monozygotic (MZ; identical) and dizygotic (DZ; fraternal) twin pairs amalgamated from the 6 institutions in four different countries (USA, UK, The Netherlands and Australia) that constitute the Genetics of High Cognitive Ability Consortium (GHCA). Zygosity was determined in almost all cases by analysis of DNA microsatellites, blood group polymorphisms or other genetic variants (for sample-specific detail see supplementary materials ). The sample is described in detail elsewhere ( Haworth et al , 2010 ) and is summarized in Table 1 .

Genetics of High Cognitive Ability Consortium Sample Characteristics

Sample	Number of pairs	Mean Age (Range)	IQ measure
Ohio, USA: The Western Reserve Reading Project	292 (121MZ, 171DZ)	6.07 (4.33–7.92) 100% child	Stanford Binet Intelligence Scale (short form). Summed and standardized for age and sex.
United Kingdom: Twins Early Development Study (TEDS)	4061 (1529MZ, 2532DZ)	11.57 (10.08–12.84) 100% child	Two WISC-III verbal subtests (information and vocabulary), WISC-III picture completion, Ravens Standard and Advanced Progressive Matrices. Standarized and summed.
Minnesota, USA: The Minnesota Center for Twin and Family Research (MCTFR)	1870 (1187MZ, 683DZ)	13 (11–17) 51% child 49% adolescent	Abbreviated WISC-R or WAIS-R as age-appropriate.
Colorado, USA: Longitudinal Twin Study (LTS), Colorado Twin Study (CTS), Colorado Learning Disabilities Research Center (CLDRC)	2863 (LTS=390, CTS=696, CLDRC=1777; 1299MZ, 1564DZ).	13.12 (6–25) 47% child 45% aolescent 8% adult	WISC-R, WISC-III, WAIS-III or WAIS-R (block design & vocab. only in CTS).
Australia: The Twin Cognition Study	853 (338MZ, 515DZ)	16.00 (15–22) ~100% adolescent <1% adult	3 verbal and 2 performance subtests from the Multidimensional Aptitude Battery.
Netherlands: The Netherlands Twin Register	958 (437MZ, 521DZ)	17.99 (5.67–71.03) 54% child 19% adolescent 27% adult	Standard age-appropriate IQ tests (see Boomsma , 2008 for further details)
Total Sample	10897 (4911MZ, 5986DZ)	13.06 (4.33–71.03) 55.5% child 39.5% adolescent 5% adulthood	scores standarized within each study after residualization for age and sex

note: WISC-III = Wechsler Intellegence Scales for children -Third Edition; WISC-R = Wechsler Intellegence Scales for children - Revised; WAIS-R = Wechsler Adult Intelligence Scale - Revised; WAIS-III = Wechsler Adult Intelligence Scale - Third Edition.

The longitudinal sample included MZ and DZ twins from the Colorado Logitudinal Twin Study (LTS) and adoptive and biological sibling pairs from the Colorado Adoption Project (CAP), two prospective community studies of behavioral development at the Institute for Behavioral Genetics (IBG; University of Colorado at Boulder). A total of 483 same-sex twin pairs have participated in the LTS study, ascertained from local birth records (264 MZ and 219 DZ) * . Twin zygosity status was determined using 12 molecular genetic markers as described elsewhere ( Haberstick and Smolen, 2004 ). In the CAP, families with an adoptive child and matched community families were ascertained in infancy. If siblings were born or adopted into the families they were included in the study. For many families, more than one sibling pair per family was available. The current analysis used the sib pair with complete IQ data at the most ages. The final sample consisted of 185 biological sibling pairs and 184 adoptive sibling pairs. Of these, 64 biological pairs were available only at age 16 and the same was true for 75 adoptive pairs. For more details on the samples see Rhea, Gross, Haberstick and Corley, 2006 (LTS) and DeFries, Plomin and Fulker, 1994 (CAP). The IQ tests administered at each of the seven measured ages are outlined in Table 2 . The scores were standardized within age and across samples to maintain the slightly higher mean scores in the CAP.

Demographic and descriptive information for the LTS/CAP samples

Age	n pairs LTS	n pairs CAP	mean age (sd)	Test administered	mean score (sd)
1 yr	342 (245MZ,197DZ)	291 (150Bio., 141Ad.)	1.12 (.09)	BSMD	106.86 (13.83)
2 yrs	398 (215MZ, 183DZ)	270 (139Bio., 131Ad.)	2.03 (.05)	BSMD	108.00 (17.86)
3 yrs	381 (204MZ, 177DZ)	254 (130Bio. 124Ad.)	3.03 (.06)	S. Binet Intell. Scale	104.61 (16.93)
4 yrs	378 (203MZ, 175DZ)	260 (134Bio., 126Ad.)	4.01 (.03)	S. Binet Intell. Scale	105.73 (13.94)
7 yrs	410 (222MZ, 188DZ)	262 (134Bio., 128Ad.)	7.41 (.37)	WISC-III; WISC-R	108.66 (13.43)
12 yrs	377 (195MZ, 182DZ)	267 (137Bio., 130Ad.)	12.45 (.38)	WISC-III; WISC-R	106.02 (12.95)
16 yrs	399 (213MZ, 186DZ)	352 (178Bio., 174Ad.)	16.6 (1.02)	WAIS-III; WAIS-R	103.92 (11.60)

Full	483 (264MZ, 219DZ)	384 (193Bio., 191Ad.)

note: MZ = monozygotic twin pairs; DZ = dizygotic twin pairs, Bio. = Biological sibships, Ad. = adoptive sibships (no genetic relationship); BSMD = Bayley Scales of Mental Development, S. Binet = Stanford Binet Intelligence Scale, WISC-III = Wechsler Inelligence Scale for Children - Third Edition; WISC-R = Wechsler Intelligence Scale for Children - Revised; WAIS-III = Wechsler Adult Intelligence Scale - Third Edition; WAIS-R = Wechsler Adult Intelligence Scale - Revised

Twin Methodology

Extensions of DeFries-Fulker regression, a special case of linear regression for deriving genetic and environmental components of variance in pairs of related individuals, were employed. DeFries-Fulker regression (for details see Cherny, Cardon, Fulker & DeFries, 1992 ) predicts the score of one member of a sibling pair from the score of the other, the coefficient of relationship - which takes a value of 1.0 for MZ twins (100% genetic sharing), 0.5 for DZ twins and biological siblings (50% genetically related on average) and 0.0 for adoptive siblings (who are not genetically related) - and the interaction between these two variables. When the data is standardized, as it is here, this regression yields direct estimates of the heritability (h 2 ) of the measured trait and proportional influence of the family-wide environment (c 2 ) on differences between individuals in the sampled population. The influence of individual-specific environments (e 2 ) can be derived by subtraction.

The addition of other variables into the regression equation, which are allowed to interact with the existing predictors, tests whether the magnitude of either h 2 or c 2 is changeable in the population according to the variables of interest. In the current study, we were interested in whether the magnitude of h 2 or c 2 for IQ is moderated by IQ score itself, so we added a quadratic ability term (the predicting siblings’ scores squared) and quadratic term × coefficient of relationahip interaction ( Cherny et al , 1992 ). The significance of these interaction terms assesses whether there is a linear, contnuous relationship between IQ score and c 2 or h 2 respectively.

To directly test the extended-sensitive period hypothesis of high IQ, we were additionally interested in whether any effect of score on h 2 or c 2 was restricted to a certain age range. This was examined by estimating the coefficients for the quadratic score term separately at each measured age. In the cross-sectional GHCA sample, we were able to additionally test for signiificant differences between the magnitude of the ability-dependent terms at each age by adding an age covariate into the regression equation. The sensitive period hypothesis predicts that there is only a relationship between IQ score in adolescence (i.e. the coefficient for the age term should be zero at all other times. For this reason continuous modeling of the effect of age was not possible and it was therefore decided to use discrete age categories. We split the sample into three age groups: childhood (4yrs to 12yrs; n pairs = 6044), adolescence (13–18yr; n pairs = 4304) and adulthood (18yrs +; n pairs = 549) and constructed orthogonal contrast codes based on these criteria: A linear code comparing the childhood and adulthood groups and a quadratic code that compared these groups collectively to the adolescent group. Since our hypothesis predicts the values of h 2 and c 2 to be dependent on IQ score only in adolescence (where higher scoring participants will have a child-like etiology and lower scorers will resemble adults), we expected that the three-way interactions between the quadratic age contrast code, ability and the h 2 and c 2 terms would be significant, while the equivalent terms for the linear age code would not be (as no interactions with ability are expected in either childhood or adulthood). Although the appropriate bounderies between the age categories were somewhat ambiguous, the broad expected pattern was clear, so we chose childhood, adolescent and adulthood age boundries as typically defined.

In the longitudinal sample, we added an extra covariate, age gap in days between the siblings in each pair, into the regression (0 for all twin pairs), and all results reported from this sample are from analyses including this as an interacting variable with the c 2 and h 2 terms and the ability-dependent terms. Since maximum sharing of the family environment occurs when siblings are the same age, and the groups in our sample differ systematically not only by genetic relatedness but also by average age gap (adoptive siblings being more disparate than biological siblings and biological siblings more than twins), it is prudent to account for this confounding variable in the analysis, so as not to overestimate the magnitude of the heritability estimates.

For every analysis described, each pair appears twice in the data set, with the score of each member of a pair appearing once as a predictor and once as a dependent variable. This is routine in DeFries-Fulker regression using unselected samples because there is no a priori reason to favor a particular twin assignment. This procedure does, however, artificially narrow the standard errors derived from regression analysis (which assumes independence). We addressed this by bootstrapping the regression estimates in the GHCA sample by resampling first at the family level and then at the twin assignment level, and by following the robust standard error correction outlined by Kohler and Rodgers (2001) in the longitudinal follow-up, which accounts for the fact that observations are only independent at the level of the twin pair and not the individual observations. Further explanation and details of all analyses including the regression equations can be found in the supplementary materials .

Cross-sectional analysis of the GHCA sample

Sample characteristics and sample-wide analysis.

Table 1 outlines the size and mean age of the 6 subsamples, along with the different tests used to measure IQ. The mean age of the sample is 13.06 years (range :4.33 and 70.03 years). Mean age differs considerably between the subsamples, from 6 in the Western Reserve sample to almost 18 in the Netherlands twin register. There is also a considerable difference in the range between the samples, meaning that some age groups are primarily made up of particular samples. The proportion of pairs for each sub-sample and the total sample falling into each of the three age groups is outlined in Table 1 . The IQ tests used differ between samples, reflecting age- appropriate, widely-used and validated tests. For the analyses shown here, after residualization for age and sex, the IQ scores were standardized within each study to maintain the subsample structure.

For the sample as a whole, the proportional heritability (h 2 ) was .55 (95% CI .49–.61), influence of the family environment (c 2 ) .22 (95% CI .18–.26) and of the individual-specific environment (e 2 ) .23 (95% CI.16–.39). This finding closely matches the results found in the same sample using different methodology (structural equation modeling; Haworth et al , 2010 ). Examining the influence of IQ score on these parameters, there was a significant effect on c 2 (β = .036, p = .026), such that the influence of c 2 increased as IQ score increased. There was a slight trend for a decrease in h 2 as IQ score increased (β = −,027, bootstrapped p= .187). “Etiology” in the following section collectively refers to the estimates for c 2 and h 2 . As anticipated (for reasons outlined in the introduction), there were no detectable influences of IQ score on the magnitude of e 2 . For this reason we do not report results for this predictor beyond the sample-wide value.

Age as a moderating variable

Separate analysis of the subsamples indicated variability in the strength of the relationship between IQ score and the causal influences on IQ, suggesting a moderation of this relationship by age. We therefore performed the regression analysis with age as an interacting variable, as described in the methods to test the age-dependence of the interaction between score and both heritability and family environmental effects described above. r. As expected there was no moderation by the linear age contrast on the score-etiology relationship (on separate analysis of the age groups, the score-etiology relationship in both childhood (ages 4–12) and adulthood (age 18+) was not significantly different from zero). However, the quadratic contrast code, comparing the adolescent (age 12–18) group to the childhood and adulthood groups collectively, showed that the adolescent group had a larger association between IQ and both higher environmental influence and lower genetic influence, consistent with the extended sensitive period hypothesis. Specifically, both the increase in c 2 and the decrease in h 2 as IQ score increased were significantly greater in adolescence (β = ,05, p=.04 and β = −.06, p = .04, respectively). In adolescence, IQ score predicts the pattern of genetic influence (β = −.14, p < .001) and environmental influence (β = .12, p < .001), in a manner consistent with lower IQ individuals transitioning earlier to an adult-like pattern of these influences * .

Analyses removing scores below the 5 th and above the 95 th percentile ruled out undue influence of extreme scores on the results. We also assessed whether any of these results differed according to the sex by repeating the analysis with non sex-residualized data and adding sex as an interacting variable. Males have a slightly higher mean IQ in this sample (β sex = .061, p < .001) as would be predicted given the age range of our sample ( Lynn & Kanazawa, 2011 ). However, no significant interactions by sex were found.

Transitions in causal influences

Figure 1 displays estimates for heritability and the influence of the shared family environment in the 4–12, 12–18 and 18+ year old participants separately estimated for the top and bottom half of the ability distribution (median split) at each age, to visualizing the relationship between age, IQ score and the etiological influences on IQ † . It can be seen that the estimates of both c 2 and h 2 change with age, with the magnitude of shared environmental influence decreasing and genetic influence increasing between childhood and adulthood, consistent with previous results in this sample and others (see e.g. Haworth et al , 2010 ). The magnitude of these effects is largely equal across ability for the two groups, representing a consistent beginning and end point in developmental change irrespective of ability level. However, the timing of this transition is different for the two ability groups. For the lower ability group the period of maximum change occurs between childhood and adolescence, indexed by the steeper slope of the hashed lines between these two time points. There is largely no change between adolescence and adulthood, as reflected by the relatively flat hashed lines between these points. For the higher ability group, however, a reciprical relationship exists. In this group there is largely no change between childhood and adolescence (the solid lines between these points are again nearly flat), with the change in causal influence occurring between adolescence and adulthood.

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Ability-related differences in the magnitude of genetic and environmental influence were observed specifically during adolescence. Notably, the lower-ability subjects underwent more age-related change before this point, as indicated by the sloped dotted lines (left side). In contrast, the higher-ability subjects underwent more age-related change after this point, as indicated by the sloped solid lines (right side). c_squ = proportion of variance accounted for by the family-wide environment, h_squ = proportion of variance accounted for by genetic influences. Note: High/Low IQ refers to subjects scoring above/below the median score at each age. Estimates at each age do not sum to 1 as e 2 is not plotted .

Longitudinal sample

Table 2 presents descriptive statistics for the longitudinal sample. The estimates of h 2 and c 2 for each of the seven testing ages (with age gap modeled) are presented in Table 3 . The pattern of increasing genetic influence and decreasing influence of the shared environment corroborates that seen previously, rising from .42 at age one to .85 at age 16. The influence of the shared environment shows the opposite effect, reducing in importance from a high of .39 to a low of .01. Additionally, we confirmed the influence of IQ score on the estimates of these parameters in adolescence in the same direction as in the cross-sectional analysis (last two columns of Table 3 ). At age 16, the estimate of c 2 increased as ability increased and h 2 decreased in importance, with no significant influence of ability at the earlier ages. We were, however, unable to test the sample in adulthood to confirm the transience of this effect.

Heritability and shared environmental effects in the LTS/CAP combined sample when age gap between sibling pairs is modeled as an interacting variable, with 95% confidence intervals. Rightmost two columns report the moderating effect of ability score on these estimates.

Age group	h (95% c.i.s)	c (95% c.i.s)	ability*h (95% c.i.s)	ability*c (95% c.i.s)
1 (n = 635 pairs)	0.42 (.12,.72)	0.17 (−.07,.41)	−0.03 (−.13,.08)	0.00 (−.07,.06)
2 (n = 583 pairs)	0.42 (.23,.62)	0.39 (.21,.57)	−0.01 (−.12,.09)	−0.03 (−.12, .07)
3 (n = 556 pairs)	0.33 (−.02,.67)	0.35 (.08,.62)	−0.14 (−.36,.08)	0.05 (−.08, .18)
4 (n = 561 pairs)	0.55 (.30,.79)	0.21 (0.00,.43)	−0.07 (−.17,.03)	0.01 (−.06,.08)
7 (n = 601 pairs)	0.54 (.33,.75)	0.28 (.09,.47)	−0.03 (−.10,.44)	−0.01 (−.07,.04)
12 (n = 571 pairs)	0.63 (.43,.82)	0.20 (.02,.38)	−0.01 (−.29,.21)	0.04 (−.15,.23)
16 (n =730 pairs)	0.85 (.67,1.03)	0.01 (−.16,.19)	−0.08 (−.16, −.001)	0.07 (.003, .14)

We have presented evidence from two separate sets of data that supports the existence of a sensitive period in IQ development that is extended in individuals of higher IQ. Using a large-cross-sectional dataset of twins, we found a shift in causal influences on IQ between childhood and adulthood, away from environmental and towards genetic influences. Moreover, we found that the period of child-like levels of environmental influence was prolonged in higher IQ individuals, while lower IQ individuals shifted earlier to an adult-like pattern, demonstrating that higher IQ is associated with a prolonged sensitive period. This result was replicated in a longitudinal sample of twin, biological and adoptive siblings. These results were found for the influence of the family-wide environment and not the individual specific environment (including measurement error), consistent with predictions from prior longitudinal behavior genetic research showing age related changes in the relative magnitude of the former but not the latter component of variance.

Alternative explanations of these results can be ruled out (see supplementary materials for details of supporting analyses). First, assortative mating (the tendency for parents to resemble each other in cognitive ability) could artifactually increase the influence of the family-wide environment, and so could contribute to our results if assortative mating were higher in the parents of higher IQ individuals. However, we find that higher IQ parents actually show less assortative mating; the difference between parental IQ scores is positively correlated with mean parental IQ score. Thus, assortative mating could only contribute to an underestimation of the strength of the results reported here. Second, if different traits were being measured at different IQ levels, and these traits differed in their extent of genetic and environmental influences, this could give a false impression of a single trait that varied by IQ in the extent of genetic and environmental influences. However, principal component analyses showed that the same trait was measured across IQ levels. Finally, genotype-environment interactions could contribute to our results, if the environmental variables were correlated with IQ, and estimates of environmental influence were greater for higher levels of the environmental variable. We tested for gene-environment interactions with parental education and parental IQ in the LTS twins‘ age 16 scores. However, no interaction was present for parental education, and heritability of IQ was higher at higher levels of parental IQ, which would cause underestimation of the interaction between the individual’s own score and their environmental sensitivity. Moreover, all of these alternative explanations would face an additional challenge in explaining why the link between IQ and genetic and environmental influence changes across development.

Our findings raise the question of why a prolonged sensitive period in IQ development might be associated with higher IQ. One possibility is that protracted development is beneficial for development of higher and uniquely human cognitive functions, such as those measured by IQ tests ( Rougier et al., 2005 ). This pattern may be supported via genetic polymorphisms in higher IQ individuals which limit the rate of developmental cellular changes. Similar arguments have been made for prolonged immaturity being beneficial for other aspects of cognitive development ( Bjorkland, 1997 ; Newport, 1990 ; Thompson-Schill, 2009 ). However , individuals with an eventual high IQ show this tendency from early in development ( Deary, Whalley, Lemmon, Crawford & Starr, 2000 ), challenging the idea that prolonged immaturity alone leads to higher IQ. An alternative possibility is that having a higher IQ prolongs sensitivity to the environment. For example, heightened levels of attention and arousal, as one may find in individuals of higher IQ, may allow plasticity to occur later into development ( Knudsen, 2004 ). Relatedly, individuals of higher IQ may be more open to experience, more likely to try things and change in response to experience, whereas lower IQ individuals are less motivated as they do not get as much positive feedback from learning experiences. However, this explanation is not without its own issues. The increase in genetic influence over development comes from both an increase in importance of existing genetic influences and addition of new genetic influences ( Brant et al , 2009 ). If the extension of the sensitive period is a feedback process from increased cognitive ability, it is unclear how this feedback process would lead to a delay in the introduction of new genetic influences.

The most prominent theory of developmental increases in heritability of IQ posits that individuals gain more scope throughout development to shape their own environments, based on their genetic propensities (active gene-environment correlation), which causes an increase in genetic influence over time ( Plomin, DeFries & Loehlin, 1977 ; Haworth et al , 2010 ). Our results challenge this explanation as they show a later increase in heritability for individuals of higher IQ. To explain these results in the context of active gene-environment correlations, one would need to posit, counter-intuitively, that higher IQ individuals seek out environments concordant with their genetic propensities later in development than lower IQ individuals.

The reason for developmental increases in heritability of IQ thus remains unclear - other possibilities include amplification of existing genetic influence by increasing population variance in cognitive ability and the simultaneous limiting of environmental influences/introduction of new genetic influences by synaptic pruning processes and myelination at the end of the sensitive period ( Plomin, 1986 ; Plomin, DeFries & Loehlin, 1977 ; Tau & Peterson, 2010 ). While resolving that debate is beyond the scope of the current work, our key contribution is in showing for the first time that the timing of the decline in the magnitude of environmental influence depends upon IQ, consistent with the extended sensitive period hypothesis. Further research investigating the developmental influence of specific genes and environments and aided by a better molecular-level understanding of the mechanisms underlying typical brain development will help resolve this question.

Our results suggest that, like cortical thickness, other brain-related measures (such as functional connectivity, synaptic density, and characteristics of neurotransmitter systems) will show differing relationships to IQ across development, and that the timing of this change will be dependent on IQ score. This indicates an important new direction in the search for biological and cognitive markers of IQ, and in the study of the genetic variation and developmental processes underlying individual differences in cognitive ability.

Supplementary Material

Acknowledgements.

This work was supported by the John Templeton Foundation through the Genetics of High Cognitive Ability Consortium (grant number 13575). The opinions expressed in this report are those of the authors and do not necessarily reflect the views of the John Templeton Foundation. Recruitment and data collection for the Longitudinal Twin Sample and the Colorado Adoption Project was funded by NIH grant HD010333. Support obtained for the GHCA consortium members’ twin studies are outlined in Haworth Iet al I(2010) . JKH and YM were also supported by MH079485.

* This total exceeds that reported in cross-sectional sample, which included only twins that had an IQ score measured at age 7 or above.

† For these analyses, a sibling pair was only double entered if both siblings met the score criteria.

A.M.B. developed the study concept, performed analyses and wrote the manuscript under the supervision of J.K.H. Y.M. provided theoretical input to inform interpretation and critical revisions. Testing and longitudinal data collection was directed by D.B., J.C.D., J.K.H., M.M., N.G.M., S.A.P., R.P., S.J.W. & M.J.W. M.C.K. and C.M.A.H. aided in data analysis. All authors provided feedback on the manuscript.

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Individuals of superior IQ (compared to average and high) show more intense and prolonged cortical thickening, followed by more rapid thinning. This distinct trajectory may reflect prolonged synaptogenesis and an extended sensitive period, during which the brain is particularly responsive to environmental input (Shaw et al, 2006).

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Nature and Nurture in Development

Evidence of Nature in Development

Table 1. Common Descriptors and Associated Conditions for Inferring the Effects of Nature on Development

The Origins of Nature Versus Nurture

The “Middle Ground” Perspective on Nature–Nurture

Rejection of the Nature–Nurture Divide

Nativism in Behavior: Instincts

Instinct in the Age of Enlightenment

Anti-Instinct Movement in the Age of Enlightenment

Instinct in the 19th Century

Anti-Instinct Movement in the 1920s

Fixed Action Patterns

Biological Constraints and Preparedness

Nativism in Mind: Innate Ideas

Nativism in 20th Century Psychology: The Case of Language Development

Extending Nativism Beyond Language Development

Maturation Theory

Preformationism Versus Epigenesis in the Generation of Form

From Preformationism to Predeterminism

Maturation Theory in Psychology

Critical and Sensitive Periods

Heredity and Genetics

Human Behavioral Genetics

Challenges to Behavioral Genetics

Behavioral Epigenetics

Beyond Nature–Nurture

Nurture might be nature: cautionary tales and proposed solutions

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Behavioural genetics methods

Genetic control of exposure to the environment

Box 1 A glossary of some key terms

What researchers can do

Genetically sensitive designs

PGS designs

Genetic-proxy control designs: the Familial Control Method

Other proxy control designs

Reporting summary

Data availability

Code availability

Acknowledgements

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Supplementary information

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ORIGINAL RESEARCH article

1 Introduction

2 Materials and Methods

2.2 Egg Incubation

2.3 Embryonic Heart Rate

2.4 Nestling Monitoring

2.5 Metabolism

2.6 Statistical Analyses

3.1 Hatching Success, Incubation Period, and Body Mass

3.2 Embryonic Heart Rate: Relationship With Incubation Temperature and Parental Metabolism

3.3 Offspring Metabolic Rate: Relationship With Incubation Temperature and Parental Metabolism

3.4 Embryonic Heart Rate and Metabolic Rate: Relationship Within Individuals

4 Discussion

4.1 Effects of Incubation Temperature