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Effect of diet on the structure of animal personality
Frontiers in Zoology volume 12, Article number: S5 (2015)
There is increasing interest in the proximate factors that underpin individual variation in suites of correlated behaviours. In this paper, we propose that dietary macronutrient composition, an underexplored environmental factor, might play a key role. Variation in macronutrient composition can lead to among-individual differentiation in single behaviours (‘personality’ ) as well as among-individual covariation between behaviours (‘behavioural syndromes’ ). Here, we argue that the nutritional balance during any life stage might affect the development of syndrome structure and the expression of genes with pleiotropic effects that influence development of multiple behaviours, hence genetic syndrome structure. We further suggest that males and females should typically differ in diet-dependent genetic syndrome structure despite a shared genetic basis. We detail how such diet-dependent multivariate gene-environment interactions can have major repercussions for the evolution of behavioural syndromes.
Animals require multiple nutrients for the process of somatic maintenance, growth, development and reproduction [1, 2]. Typically, individuals do not aim to consume all foods maximally. Instead, they usually balance the intake of key nutrients. Animals have multiple behavioural and physiological regulatory mechanisms to absorb the optimal mixture of nutrients to meet energetic and structural needs, which is referred to as their intake target[3, 4] (Figure 1a). An optimal mix of nutrients has been hypothesised to facilitate optimal growth (cf. fitness) .
When it is inevitable to consume nutritionally imbalanced diets, animals can solve the problem by selectively consuming multiple types of foods (i.e. nutritionally complementary foods; [5, 6]). However, when faced with a single nutritionally imbalanced diet, animals might not reach their intake target (Figure 1b). Under such conditions, animals typically consume as much as needed to acquire sufficient amounts of the most important nutrient (i.e., in terms of fitness returns), and thus under- or over-consume certain nutrients (Figure 1b, ). Although excess nutrients can be utilised and selectively excreted, individuals may not be able to void the excesses if the degree of imbalance exceeds the capacity to excrete them. For example, when consuming carbohydrate-biased food, animals ingest surpluses of carbohydrates to acquire adequate amounts of protein. Surplus amounts of carbohydrates are, in turn, typically converted to lipids and stored in the body . Both deficits and surpluses of nutrients can strongly influence behaviour, physiology, reproductive output, growth, or survival [9–17].
In ecology and evolution, there has been considerable interest in the effect of nutritional condition on life-history traits, morphology and longevity [11, 13, 17–21]. Nutrition can also be regarded as a major component of behavioural development since it represents a key environmental factor (see ). Nutritional conditions early in an individual's life can provide reliable cues on the optimal level of various behaviours expressed later in life [11, 23–27]. Individuals reared on diets of high quality are, for example, generally more active than individuals feeding on a low-quality diet . Malnutrition can also affect the level of boldness and aggression .
Despite the well-known existence of nutritional effects on behavioural development, only a few studies have used experiments to investigate effects of macronutrient composition (and their balance) on behaviour and its development (i.e., by controlling the amount of certain nutrients or the ratio of them), with most research to date focusing on invertebrates (insects and spiders: Table 1, [9–11, 13, 14, 16, 29]). The expression of reproductive behaviour (i.e., calling effort) of male crickets (Teleogryllus commodus) is, for example, increased by a low-protein high-carbohydrate diet  because carbohydrates represent the main energy source for metabolic processes, allowing muscle and tissue to exert high metabolic activity. Drosophila males, furthermore, increase their mating frequency and courtship when fed on a protein-high diet [9, 10]. The incidence of cannibalism in Mormon crickets (Anabrus simplex) decreases when individuals can access high-protein food sources . Given the diversity of nutritional requirements that different kinds of animal species (i.e., herbivores, carnivores and omnivores) face, intake targets, and their effects on behavioural phenotypes, can vary greatly across species.
Nutritional balance can also affect the extent of individual differentiation in behaviour (i.e., among-individual variance), for example, because diet can induce long-term effects in morphology or physiology, hence behaviour. For example, deficiencies or excesses of certain nutrients might facilitate or attenuate the expression of behaviour of most individuals, thereby increasing or decreasing the among-individual variance in behaviour. Although one study showed that the extent of among-individual differentiation in behaviours was not a function of nutritional environment , the relationship between diet and among-individual variation in behaviour remains largely unexplored.
Nutritional balance can also affect the amount of among-individual covariance between functionally distinct behaviours. Behavioural correlations exist not just due to pleiotropic effect of genes (or linkage disequilibrium) but also due to pleiotropic environmental effects (such as macronutrient composition) . The covariance between behaviours is thus shaped by the combined effects of environmental and genetic correlations (see below). Interestingly, environmental conditions can also affect the expression of gene pleiotropy, and thereby the strength of genetic correlations between behaviours (e.g. ). In certain nutritional environments, there might thus be more or less genetic variation expressed, leading to environment-specific heritability (cf. G×E) .
Furthermore, because of their shared genetic basis, males and females within a species are typically not thought to differ in the expression of genetic (co)variation in behaviours. However, given sexual differences in the optimal diet for fitness maximisation , we expect diet-dependent among-individual variation and covariation in behaviour to be sex-specific. We discuss how such sex-specificity should arise in our general discussion.
In this opinion paper, we discuss the effects of extreme biological scenarios where the composition of macronutrients in the nutritional environment is so biased that individuals are unable to consume the optimal amount of nutrients for the intake target (e.g. a protein-deficient environment). In the natural environment, this situation may occur when animals consistently stay within one habitat, which might occur when animals face restrictions in dispersion [22, 34, 35]. In such situations, individuals may be unable to avoid fitness costs associated with nutrient deficiencies or consumption of excesses of biased nutrients [1, 36]. Our aim is thus to explore how the level of nutritional imbalance might influence the genetic and environmental underpinning of suites of correlated behaviours. We propose that the composition of diet with respect to macronutrients can have major pleiotropic effects on suites of behaviours, thereby explaining why they might covary. We further introduce a quantitative genetics approach to empirically test how nutritional composition might affect (the interacting effects of) developmental and genetic factors underpinning behavioural syndromes.
The structure of behavioural syndromes and environmental effects
Over the last decade, a large number of behavioural studies have shown that individuals of the same population differ consistently in their behaviour . Individual differences in behaviour that are repeatable over time and across different contexts or situations are commonly referred to as ‘animal personality’ in the behavioural ecology literature . The repeatable components of animal behaviour are often also correlated with each other across traits (meta-analysis: ), and such among-individual correlations are called ‘behavioural syndromes’ [40–44]. The most widely-documented example is the aggressiveness-boldness syndrome: individuals that are on average relatively aggressive towards conspecifics are also relatively active and bold towards predators, compared to less aggressive individuals. Behavioural syndromes may also include other functionally distinct behaviours, such as dispersal tendency, exploration, docility, cooperation, sociability, and mating strategy [45, 46].
Behavioural correlations are the product of the joint influences of ‘among-individual’ and ‘within-individual’ correlations ([40, 44, 47], Figure 2). The among-individual correlation is the correlation between each individual's average phenotype across multiple behaviours, i.e. the correlation between the repeatable parts of behavioural traits. Within-individual correlations, in contrast, exist when within-individual plasticity is correlated across traits due to ‘integration of plasticity’ unless caused by correlated measurement errors. Behavioural syndromes refer to among-individual correlations rather than simple un-partitioned phenotypic correlations, and are estimated with considerable bias if within-individual correlations are not accounted for .
Among-individual correlations are themselves shaped by two main contributors: genetic (G) and environmental effects (E)  (Figure 2). First, genetic correlations between behavioural traits result in among-individual correlations because of gene pleiotropy (i.e., a single gene governs the expression of multiple behavioural traits) or linkage disequilibrium (i.e., genes affecting one behaviour are correlated with genes affecting another) . Second, non-genetic (i.e., environmental) factors can also cause among-individual correlations, either when environmental factors have long-term effects on the development of multiple behavioural traits (e.g. due to environmental factors with pleiotropic effects) [49–53] or when environmental factors with short-term effects are themselves repeatable across individuals (also called ‘permanent’ environmental effects). The known occurrence of such environmental effects in natural populations [44, 54–56] implies that environmental conditions (such as feeding conditions in early life) can profoundly influence behavioural syndrome structure.
There is already considerable evidence for a major role of genetic correlations in shaping behavioural syndromes [41, 57, 58]. The contribution of permanent environmental correlations has, in contrast, largely been ignored (e.g. ). Permanent environment correlations may shape among-individual correlations independently from genetic correlations (leading to additive effects: G+E). Among-individual correlations can, by contrast, also result from interactions between genetic and long-lasting environmental effects (i.e. G×E). For example, environmental conditions can alter the expression level of a gene involved in a signalling pathway connected to a behaviour [59, 60], and affect the expression, hence heritability, of genetic variation in behaviour . The strength of genetic correlations between behaviours can also depend on the environment when environmental conditions affect the gene expression related to the breakdown of a neurotransmitter, such as histamine, connected to multiple behaviours (e.g. aggression, exploration and boldness) [60, 61]. That is, if genes with pleiotropic effects are disproportionally more expressed in specific environments, genetic correlations become a function of the environment. Environmental factors, such as nutritional balance, might thus greatly affect the expression of genetic correlations that underpin behavioural syndromes .
Multivariate effects of nutritional condition on behavioural phenotypes
Given that nutrition is known to affect behaviour and its development [9–11, 13–16], we predict that the composition of macronutrients might similarly represent an important environmental effect causing correlations between suites of behaviours (i.e., behavioural syndrome structure, Figure 2). Behavioural effects of excesses (or deficits) in consumption of single nutrients (relative to intake target, Figure 1b) likely depends on the functional context in which behaviour is expressed. For example, activity, exploration, dispersal and parental care are predicted to be sensitive to excesses and deficits of carbohydrate in the diet. This is because carbohydrates act as a main energy source used to ‘fuel’ the expression of such energetically demanding behaviours; high carbohydrate intake might also increase metabolic rate, thereby again facilitating the expression of energetically demanding behaviours . Males exposed to high-carbohydrate diets might therefore be more active and explorative, and more willing to engage in active mate choice and courtship compared to individuals on low-carbohydrate diets. In addition, since sexual behaviours such as courtship or female resistance generally show condition dependence [63–66], such expression might also depend on nutrition. Similarly, sociality or cooperative behaviour is also predicted to be sensitive to the amount of carbohydrate or protein in the diet. Since cooperative/social behaviours are regulated by neuroendocrine mechanisms , the known adverse effect of poor nutrition on neuromuscular development [68–72] could influence the expression of cooperative/social behaviours. Aggressive behaviour is particularly predicted to vary with level of protein intake . Protein-deprived individuals are expected to be bolder and more aggressive than those under balanced diets because they have less to lose in terms of future fitness expectations (following ref. ). In cannibalistic species such as Mormon crickets, protein deficiency is also likely to increase the expression of aggressive behaviour because the deficit of proteins leads to increased frequency of cannibalism .
The extent to which intake of macronutrients is balanced is also expected to affect the expressed amount of among-individual variance in behaviour (Figure 2, 3). That is, in one diet treatment the repeatability might be higher or lower compared to another. For example, in rich environmental conditions with ad libitum balanced food intake, among-individual variation in behavioural traits might be much higher than in a nutritionally impoverished environment (c.f. with imbalanced food availability) because the expression of genetic variation is typically increased under favourable conditions ([74, 75], but see ). This is because under nutritionally imbalanced conditions, most individuals fail to get enough resources (e.g. carbohydrate or protein) to express costly behaviours, resulting in decreased individuality in behaviour. Otherwise, the imbalanced composition of macronutrients could also make all individuals increase the expression of types of behaviour that enable them to escape nutritional deficiency (e.g. foraging behaviour), which would result in increased among-individual variance in behaviour. Therefore, given the effect of the composition of macronutrients on the expression of among-individual variation in behaviour, we expect that the dietary balance plays a key role in shaping among-individual correlations between behaviours (i.e. environment-specific behavioural syndromes).
Diet-dependent genetic correlations underlying behavioural syndromes
Quantitative genetic analyses can be utilized to simultaneously quantify the relative importance of environmental effects (e.g. due to diet) versus diet-specific genetic correlations underlying among-individual behavioural correlations. Quantitative genetic analyses and animal models enable estimation of the G-matrix (a tabulation of additive genetic variances and additive genetic covariances) which has an important role in constraining evolution of phenotypes in response to selection or genetic drift . Despite its central role, the stability of the G-matrix remains incompletely understood [78–82]. Although G-matrices are highly conserved among populations of certain species , empirical studies conducted in natural and laboratory populations show that G can change [83–89]. It is also largely unknown whether G-matrices for behavioural traits vary across environments. Given that behavioural traits are likely to be subject to permanent environmental effects, we predict that G-matrices for behavioural traits can change across different environments such as those differing in availability of different types of nutrients (i.e., G×E).
G-matrices measured for different macronutrient composition environments can be used to study cross-environment (dietary balances) genetic correlations as well as diet-specific genetic correlations, and reveal the genetic architecture and stability of the G-matrix; this is a powerful approach that has rarely been applied in the context of behaviour (but see ). The genetic correlation between morphological or life history traits (e.g. development time, body size, weight, longevity, fecundity etc.), for instance, can differ considerably between nutritional environments (e.g. calories) (see reviews, [90, 91]). Likewise, as the amount of among-individual variance in behaviour is expected to vary between environments, the amount of genetic variance within a given behaviour and covariance between behaviours (i.e. genes with pleiotropic effects), are also expected to depend on the environment [30, 92] (Figure 3). For example, as the phenotypic and genotypic variance in traits increase under favourable conditions , nutritional imbalance can decrease the amount of genetic variation in behavioural expression. On the other hand, the amount of genetic variation in behaviour expressed in nutritionally imbalanced environments could far exceed that expressed in nutritionally balanced environments when imbalanced nutritional compositions increase the expression of behaviour (e.g. increased foraging to escape nutritional deficiency or increased cannibalism). Furthermore, nutritional imbalance can similarly assert a direct influence on the covariation between behaviours [91, 93]. This implies that the expression of genes with pleiotropic effects can differ in direction between nutritionally imbalanced and balanced environments.
Imagine, for example, an insect species where protein-deficient diet increases aggression towards conspecifics but decreases reproductive behaviours ([9, 10, 14, 29], Table 1). In such a species, protein intake can affect the expression of genetic variation in behaviour and genetic correlations among behaviours. Proteins are a source of nitrogen for growth and maintenance of tissues, production of enzymes or spermatophores, as well as a source of metabolic energy via gluconeogenesis. Thus individuals faced with protein-deficient diet could express a high incidence of cannibalism  and fail to produce gametes of high quality [17, 94, 95], which could also induce less active reproductive behaviours (e.g. less courting) [9, 10]. As a result, if fed protein-deficit diets, males are likely to differ in their strategy to express aggressive behaviours using limited proteins, thereby leading to more genetic variance in aggressive behaviours. In contrast, genetic variation in reproductive behaviours might decrease because the limitation of overall protein availability in the food decreases reproductive activity. In addition to its effect on the expression of genetic variation, the level of protein intake can also directly influence level of genetic covariation among behaviours. This would occur if diet affects particular genes with pleiotropic effects on the expressions of multiple behaviours only. Therefore genetic variation in behaviours sensitive to protein intake (e.g. courtship behaviour, aggression) is likely to vary as a function of the amount of protein in the diet. The composition of diets with respect to macronutrients could also affect the direction of genetic correlations among behaviours via pleiotropic gene actions. Hence, genetic correlations between types of behaviours are predicted to be diet-specific.
In summary, genetic correlations can thus differ between balanced-nutrient and imbalanced-nutrient conditions because of gene-environment interactions acting on behavioural correlations. This implies that the genetic correlation should be diet-specific, which has consequences for the evolutionary potential of behavioural traits . Such environment-specific genetic correlations would contribute to the (in)stability of behavioural G-matrices across dietary balances and also drive within-species polymorphism in behaviours when populations are faced with a diversity of nutritional habitats.
Sex differences in diet-dependent genetic correlations
Since males and females share a common genetic basis, sex differences in environment-dependent genetic correlations might generally be rare. However, sex-specific alleles and genetic variance in traits can occur when strong selection on shared traits in one sex displaces the other sex from its phenotypic optimum in spite of genetic constraints . In turn, such sex-specificity in expression contributes to the evolution of sexual dimorphism [97–99]. In the same way, sex-specific environment-dependent genetic correlations can also arise as a form of sexual dimorphism [89, 99–103].
Males and females differ in their optimal diet because the balance of nutrients for the optimal performance and fitness maximisation is normally sex-specific . In crickets, for example, females prefer protein-rich diets for egg production, whereas males prefer carbohydrate-rich diet for energetically demanding courtship behaviour. Thus male crickets raised on carbohydrate-biased diet accumulate body lipid more readily than females . Another example comes from caterpillars, where males prefer diets with a balanced protein/carbohydrate ratio while female caterpillars prefer a more protein-biased diet [104, 105]. In addition, female caterpillars utilise the excess of proteins more efficiently than males . This indicates that intake targets and physiological systems that animals use to deal with the nutritional imbalance might typically differ between sexes.
Given a striking sex difference in responses to environmental stress from nutritional imbalance, we might expect relatively weak cross-sex genetic correlations between behaviours. In a protein-deficient environment, females are unable to produce many eggs and suffer fitness costs . In contrast, since small amounts of protein suffice males to produce sperm, males do not suffer equally from protein-deficiency. Thus, based on the fact that protein is an important resource for females to produce eggs, protein-deficient environments will be more stressful for females. Thus cross-diet environment genetic correlations of females may be ephemeral because the correlation would easily break down under a protein-deficient environment. Cross-diet environment genetic correlations of males, however, may instead be fixed.
Therefore, behaviours involved in reproduction are likely to show sex differences in diet-dependent genetic correlations. In particular, dietary effects on sex-specific variation in one behavioural trait can result in correlated effects on sex-specific covariation between behavioural traits via pleiotropy. Because of sex-specific pleiotropy, we thus expect that males and females differ in diet-dependent among-individual variation in behaviours and covariation among them. Furthermore, given that the effects of diet may strongly depend on the specific life-history trajectories (or strategies) of each species, the magnitude of sex differences in diet-dependent genetic correlations should be species-specific.
Animals need multiple nutrients to maximize their fitness. A variety of nutrients must be ingested in an optimal blend required for best performance. If the animal fails to attain the optimal balance of nutrients, nutritional imbalance will likely exert an effect on the expression of behavioural correlations, morphology (e.g. body composition), and physiology at the among-individual level. Though behavioural traits are heritable [106–108], there is a basic lack of understanding of how environmental effects interact with genetic variation to influence the development of behaviour . Our conceptual framework addressing effects of dietary composition with respect to macro nutrients on the development of behavioural syndromes highlights how the expression of behavioural phenotypes can be altered by environmental stimuli, and reveals the role of nutritional balance on the plastic expression of behavioural genetic correlations. Research on nutrition and behavioural syndromes will thus spur a new wave of research beyond simply documenting behavioural correlations and testing the mechanisms that shape variation in behavioural syndromes and its underlying genetics. Studies on sex-specific genetic covariance, finally, represent an important step toward understanding intra-locus sexual conflict as well as the evolutionary basis of individual differences in behaviour.
Publication costs for this article were funded by the German Research Foundation (FOR 1232) and the Open Access Publication Fund of Bielefeld University and Muenster University.
Raubenheimer D, Simpson SJ: Integrative models of nutrient balancing: application to insects and vertebrates. Nutrition Research Reviews. 1997, 10 (1): 151-179.
Simpson SJ, Sibly RM, Lee KP, Behmer ST, Raubenheimer D: Optimal foraging when regulating intake of multiple nutrients. Animal Behaviour. 2004, 68 (6): 1299-1311.
Chambers PG, Simpson SJ, Raubenheimer D: Behavioural mechanisms of nutrient balancing in Locusta migratoria nymphs. Animal Behaviour. 1995, 50 (6): 1513-1523.
Trumper S, Simpson SJ: Regulation of salt intake by nymphs of Locusta migratoria. Journal of Insect Physiology. 1993, 39 (10): 857-864.
Behmer ST, Cox E, Raubenheimer D, Simpson SJ: Food distance and its effect on nutrient balancing in a mobile insect herbivore. Animal Behaviour. 2003, 66 (4): 665-675.
Behmer ST, Raubenheimer D, Simpson SJ: Frequency-dependent food selection in locusts: a geometric analysis of the role of nutrient balancing. Animal Behaviour. 2001, 61 (5): 995-1005.
Simpson SJ, Raubenheimer D: The nature of nutrition: a unifying framework from animal adaptation to human obesity. 2012, Princeton University Press
Warbrick-Smith J, Behmer ST, Lee KP, Raubenheimer D, Simpson SJ: Evolving resistance to obesity in an insect. Proc Natl Acad Sci U S A. 2006, 103 (38): 14045-14049.
Blay S, Yuval B: Nutritional correlates of reproductive success of male Mediterranean fruit flies (Diptera: Tephritidae). Animal Behaviour. 1997, 54 (1): 59-66.
Droney DC: Environmental influences on male courtship and implications for female choice in a lekking HawaiianDrosophila. Animal Behaviour. 1996, 51 (4): 821-830.
Hunt J, Brooks R, Jennions MD, Smith MJ, Bentsen CL, Bussiere LF: High-quality male field crickets invest heavily in sexual display but die young. Nature. 2004, 432 (7020): 1024-1027.
Kasumovic MM, Hall MD, Brooks RC: The juvenile social environment introduces variation in the choice and expression of sexually selected traits. Ecology and Evolution. 2012, 2 (5): 1036-1047.
Maklakov AA, Simpson SJ, Zajitschek F, Hall MD, Dessmann J, Clissold F, et al: Sex-specific fitness effects of nutrient intake on reproduction and lifespan. Curr Biol. 2008, 18 (14): 1062-1066.
Wilder SM, Rypstra AL: Diet quality affects mating behaviour and egg production in a wolf spider. Animal Behaviour. 2008, 76 (2): 439-445.
Zajitschek F, Hunt J, Jennions MD, Hall MD, Brooks RC: Effects of juvenile and adult diet on ageing and reproductive effort of male and female black field crickets Teleogryllus commodus. Functional Ecology. 2009, 23 (3): 602-611.
Zajitschek F, Lailvaux SP, Dessmann J, Brooks R: Diet, sex, and death in field crickets. Ecology and Evolution. 2012, 2 (7): 1627-1636.
Lee KP, Simpson SJ, Clissold FJ, Brooks R, Ballard JW, Taylor PW, et al: Lifespan and reproduction in Drosophila: new insights from nutritional geometry. Proc Natl Acad Sci U S A. 2008, 105 (7): 2498-2503.
Partridge L, Brand MD: Special issue on dietary restriction: dietary restriction, longevity and ageing—the current state of our knowledge and ignorance. Mech Ageing Dev. 2005, 126 (9): 911-912.
Maklakov AA, Hall MD, Simpson SJ, Dessmann J, Clissold FJ, Zajitschek F, et al: Sex differences in nutrient-dependent reproductive ageing. Aging Cell. 2009, 8 (3): 324-330.
Sentinella AT, Crean AJ, Bonduriansky R: Dietary protein mediates a trade – off between larval survival and the development of male secondary sexual traits. Functional Ecology. 2013, 27 (5): 1134-1144.
Adler MI, Cassidy EJ, Fricke C, Bonduriansky R: The lifespan-reproduction trade-off under dietary restriction is sex-specific and context-dependent. Experimental Gerontology. 2013, 48 (6): 539-548.
Tremmel M, Müller C: Insect personality depends on environmental conditions. Behavioral Ecology. 2013, 24 (2): 386-392.
Chapman T, Partridge L: Female fitness in Drosophila melanogaster: an interaction between the effect of nutrition and of encounter rate with males. Proc Biol Sci. 1996, 263 (1371): 755-759.
Hunt J, Jennions MD, Spyrou N, Brooks R: Artificial selection on male longevity influences age-dependent reproductive effort in the black field cricket Teleogryllus commodus. Am Nat. 2006, 168 (3): E72-E86.
Johnston SL, Grune T, Bell L, Murray S, Souter DM, Erwin SS, et al: Having it all: historical energy intakes do not generate the anticipated trade-offs in fecundity. Proc Biol Sci. 2006, 273 (1592): 1369-1374.
Romanyukha AA, Carey JR, Karkach AS, Yashin AI: The impact of diet switching on resource allocation to reproduction and longevity in Mediterranean fruitflies. Proc Biol Sci. 2004, 271 (1545): 1319-1324.
Tatar M, Carey JR: Nutrition mediates reproductive trade-offs with age-specific mortality in the beetle Callosobruchus maculatus. Ecology. 1995, 76 (7): 2066-2073.
Lima SL, Dill LM: Behavioral decisions made under the risk of predation: a review and prospectus. Canadian Journal of Zoology. 1990, 68 (4): 619-640.
Simpson SJ, Sword GA, Lorch PD, Couzin ID: Cannibal crickets on a forced march for protein and salt. Proc Natl Acad Sci U S A. 2006, 103 (11): 4152-4156.
van Oers K, de Jong G, van Noordwijk AJ, Kempenaers B, Drent PJ: Contribution of genetics to the study of animal personalities: a review of case studies. Behaviour. 2005, 142 (9-10): 1191-1212.
Nussey DH, Wilson AJ, Brommer JE: The evolutionary ecology of individual phenotypic plasticity in wild populations. J Evol Biol. 2007, 20 (3): 831-844.
Dingemanse NJ, Van der Plas F, Wright J, Réale D, Schrama M, Roff DA, et al: Individual experience and evolutionary history of predation affect expression of heritable variation in fish personality and morphology. Proc Biol Sci. 2009, 276 (1660): 1285-1293.
Reddiex AJ, Gosden TP, Bonduriansky R, Chenoweth SF: Sex-specific fitness consequences of nutrient intake and the evolvability of diet preferences. Am Nat. 2013, 182 (1): 91-102.
Edgecomb RS, Harth CE, Schneiderman AM: Regulation of feeding behavior in adult Drosophila melanogaster varies with feeding regime and nutritional state. J Exp Biol. 1994, 197: 215-235.
Raubenheimer D, Jones SA: Nutritional imbalance in an extreme generalist omnivore: tolerance and recovery through complementary food selection. Animal Behaviour. 2006, 71 (6): 1253-1262.
Raubenheimer D: Tannic acid, protein, and digestible carbohydrate: dietary imbalance and nutritional compensation in locusts. Ecology. 1992, 73 (3): 1012-1027.
Bell AM, Hankison SJ, Laskowski KL: The repeatability of behaviour: a meta-analysis. Animal Behaviour. 2009, 77 (4): 771-783.
Réale D, Garant D, Humphries MM, Bergeron P, Careau V, Montiglio P-O: Personality and the emergence of the pace-of-life syndrome concept at the population level. Proc Biol Sci. 2010, 365 (1560): 4051-4063.
Garamszegi LZ, Markó G, Herczeg G: A meta-analysis of correlated behaviours with implications for behavioural syndromes: mean effect size, publication bias, phylogenetic effects and the role of mediator variables. Evol Ecol. 2012, 26 (5): 1213-1235.
Dingemanse NJ, Dochtermann NA: Quantifying individual variation in behaviour: mixed-effect modelling approaches. Journal of Animal Ecology. 2013, 82 (1): 39-54.
Dochtermann NA, Dingemanse NJ: Behavioral syndromes as evolutionary constraints. Behavioral Ecology. 2013, 24 (4): 806-811.
Sih A, Bell A, Johnson JC: Behavioral syndromes: an ecological and evolutionary overview. Trends Ecol Evol. 2004, 19 (7): 372-378.
Sih A, Bell AM, Johnson JC, Ziemba RE: Behavioral syndromes: an integrative overview. Q Rev Biol. 2004, 79 (3): 241-277.
Dingemanse NJ, Dochtermann NA, Nakagawa S: Defining behavioural syndromes and the role of ‘syndrome deviation’ in understanding their evolution. Behavioral Ecology and Sociobiology. 2012, 66 (11): 1543-1548.
Réale D, Reader SM, Sol D, McDougall PT, Dingemanse NJ: Integrating animal temperament within ecology and evolution. Biol Rev Camb Philos Soc. 2007, 82 (2): 291-318.
Garamszegi LZ, Markó G, Herczeg G: A meta-analysis of correlated behaviors with implications for behavioral syndromes: relationships between particular behavioral traits. Behavioral Ecology. 2013, 24 (5): 1068-
Brommer JE: On between-individual and residual (co) variances in the study of animal personality: are you willing to take the “individual gambit”?. Behav Ecol Sociobiol. 2013, 67 (6): 1027-1032.
Falconer DS, Mackay TFC: Introduction to Quantitative Genetics. 1996, London: Prentice Hall, 4 edn.
Del Giudice M: Plasticity as a Developing Trait: Exploring the Implications. Frontiers in Zoology. 2015, 12 (Suppl 1): S4-
Hennessy MB, Kaiser S, Tiedtke T, Sachser N: Stability and change: Stress responses and the shaping of behavioral phenotypes over the life span. Frontiers in Zoology. 2015, 12 (Suppl 1): S18-
Hudson R, Rangassamy M, Saldaña A, Bánszegi O, Rödel HG: Stable individual differences in separation calls during early development in cats and mice. Frontiers in Zoology. 2015, 12 (Suppl 1): S12-
Kaiser S, Hennessy MB, Sachser N: Domestication affects the structure, development and stability of biobehavioural profiles. Frontiers in Zoology. 2015, 12 (Suppl 1): S19-
Müller T, Müller C: Behavioural phenotypes over the lifetime of a holometabolous insect. Frontiers in Zoology. 2015, 12 (Suppl 1): S8-
Nicolaus M, Tinbergen JM, Bouwman KM, Michler SP, Ubels R, Both C, et al: Experimental evidence for adaptive personalities in a wild passerine bird. Proc Biol Sci. 2012, 279 (1749): 4885-4892.
Quinn JL, Patrick SC, Bouwhuis S, Wilkin TA, Sheldon BC: Heterogeneous selection on a heritable temperament trait in a variable environment. J Anim Ecol. 2009, 78 (6): 1203-1215.
Brommer JE, Class B: The importance of genotype-by-age interactions for the development of repeatable behavior and correlated behaviors over lifetime. Frontiers in Zoology. 2015, 12 (Suppl 1): S2-
Dochtermann NA: Testing Cheverud's conjecture for behavioral correlations and behavioral syndromes. Evolution. 2011, 65 (6): 1814-1820.
van Oers K, Drent PJ, De Goede P, Van Noordwijk AJ: Realized heritability and repeatability of risk-taking behaviour in relation to avian personalities. Proc Biol Sci. 2004, 271 (1534): 65-73.
Filby AL, Paull GC, Searle F, Ortiz-Zarragoitia M, Tyler CR: Environmental estrogen-induced alterations of male aggression and dominance hierarchies in fish: a mechanistic analysis. Environ Sci Technol. 2012, 46 (6): 3472-3479.
Norton WH, Stumpenhorst K, Faus-Kessler T, Folchert A, Rohner N, Harris MP, et al: Modulation of Fgfr1a signaling in zebrafish reveals a genetic basis for the aggression–boldness syndrome. J Neurosci. 2011, 31 (9): 13796-13807.
Norton W, Bally-Cuif L: Unravelling the proximate causes of the aggression-boldness behavioural syndrome in zebrafish. Behaviour. 2012, 149 (10-12): 1063-1079.
Mathot KJ, Dingemanse NJ: Energetics and behavior: unrequited needs and new directions. Trends Ecol Evol. 2015, 30 (4): 199-206.
Bonduriansky R: The Evolution of condition-dependent sexual dimorphism. Am Nat. 2007, 169 (1): 9-19.
Cotton S, Fowler K, Pomiankowski A: Do sexual ornaments demonstrate heightened condition-dependent expression as predicted by the handicap hypothesis?. Proc Biol Sci. 2004, 271 (1541): 771-783.
Hunt J, Brooks R, Jennions MD: Female mate choice as a condition – dependent life – history trait. Am Nat. 2005, 166 (1): 79-92.
Tomkins JL, Radwan J, Kotiaho JS, Tregenza T: Genic capture and resolving the lek paradox. Trends Ecol Evol. 2004, 19 (6): 323-328.
Soares MC, Bshary R, Fusani L, Goymann W, Hau M, Hirschenhauser K, Oliveira RF: Hormonal mechanisms of cooperative behaviour. Proc Biol Sci. 2010, 365 (1553): 2737-2750.
Akman C, Zhao Q, Liu X, Holmes GL: Effect of food deprivation during early development on cognition and neurogenesis in the rat. Epilepsy Behav. 2004, 5 (4): 446-454.
Buchanan KL, Leitner S, Spencer KA, Goldsmith AR, Catchpole CK: Developmental stress selectively affects the song control nucleus HVC in the zebra finch. Proc Biol Sci. 2004, 271 (1555): 2381-2386.
Fernstrom JD: Can nutrient supplements modify brain function?. Am J Clin Nutr. 2000, 71 (6 Suppl): 1669S-1673S.
Nowicki S, Peters S, Podos J: Song learning, early nutrition and sexual selection in songbirds. Amer Zool. 1998, 38 (1): 179-190.
Wainwright PE: Dietary essential fatty acids and brain function: a developmental perspective on mechanisms. Proc Nutr Soc. 2002, 61 (1): 61-69.
Dingemanse NJ, Wolf M: Recent models for adaptive personality differences: a review. Proc Biol Sci. 2010, 365 (1560): 3947-3958.
Charmantier A, Garant D: Environmental quality and evolutionary potential: lessons from wild populations. Proc Biol Sci. 2005, 272 (1571): 1415-1425.
Hoffmann AA, Merilä J: Heritable variation and evolution under favourable and unfavourable conditions. Trends Ecol Evol. 1999, 14 (3): 96-101.
Husby A, Visser ME, Kruuk LE: Speeding up microevolution: the effects of increasing temperature on selection and genetic variance in a wild bird population. PLoS Biol. 2011, 9 (2): e1000585-
Lande R: Quantitative genetic analysis of multivariate evolution, applied to brain: body size allometry. Evolution. 1979, 33 (1): 402-416.
Arnold SJ, Bürger R, Hohenlohe PA, Ajie BC, Jones AG: Understanding the evolution and stability of the G-matrix. Evolution. 2008, 62 (10): 2451-2461.
Jones AG, Arnold SJ, Bürger R: Stability of the G – matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift. Evolution. 2003, 57 (8): 1747-1760.
Jones AG, Bürger R, Arnold SJ, Hohenlohe PA, Uyeda JC: The effects of stochastic and episodic movement of the optimum on the evolution of the G – matrix and the response of the trait mean to selection. J Evol Biol. 2012, 25 (11): 2210-2231.
Steppan SJ, Phillips PC, Houle D: Comparative quantitative genetics: evolution of the G matrix. Trends Ecol Evol. 2002, 17 (7): 320-327.
Turelli M: Phenotypic evolution, constant covariances, and the maintenance of additive variance. Evolution. 1988, 42 (6): 1342-1347.
Cano JM, Laurila A, Palo J, Merilä J: Population differentiation in G matrix structure due to natural selection in Rana temporaria. Evolution. 2004, 58 (9): 2013-2020.
Doroszuk A, Wojewodzic MW, Gort G, Kammenga JE: Rapid divergence of genetic variance – covariance matrix within a natural population. Am Nat. 2008, 171 (3): 291-304.
Eroukhmanoff F, Svensson E: Evolution and stability of the G – matrix during the colonization of a novel environment. J Evol Biol. 2011, 24 (6): 1363-1373.
Sgrò CM, Blows MW: The genetic covariance among clinal environments after adaptation to an environmental gradient in Drosophila serrata. Genetics. 2004, 167 (3): 1281-1291.
Barker BS, Phillips PC, Arnold SJ: A test of the conjecture that G – matrices are more stable than B-matrices. Evolution. 2010, 64 (9): 2601-2613.
Shaw FH, Shaw RG, Wilkinson GS, Turelli M: Changes in genetic variances and covariances: G whiz!. Evolution. 1995, 49 (6): 1260-1267.
Gosden TP, Chenoweth SF: The evolutionary stability of cross-sex, cross-trait genetic covariances. Evolution. 2014, 68 (6): 1687-1697.
Reznick D, Nunney L, Tessier A: Big houses, big cars, superfleas and the costs of reproduction. Trends Ecol Evol. 2000, 15 (10): 421-425.
Sgro CM, Hoffmann AA: Genetic correlations, tradeoffs and environmental variation. Heredity (Edinb). 2004, 93 (3): 241-248.
Han CS, Brooks RC: The interaction between genotype and juvenile and adult density environment in shaping multidimensional reaction norms of behaviour. Functional Ecology. 2015, 29 (1): 78-87.
Hoffmann AA, Parsons PA: Evolutionary genetics and environmental stress. 1991, New York: Oxford University Press
Wheeler D: The role of nourishment in oogenesis. Annu Rev Entomol. 1996, 41: 407-431.
Wheeler DE, Buck NA: A role for storage proteins in autogenous reproduction in Aedes atropalpus. J Insect Physiol. 1996, 42 (10): 961-966.
Lande R: Sexual dimorphism, sexual selection, and adaptation in polygenic characters. Evolution. 1980, 34 (2): 292-305.
Arnqvist G, Rowe L: Sexual Conflict. 2005, Princeton: Princeton University Press
Bonduriansky R, Chenoweth SF: Intralocus sexual conflict. Trends Ecol Evol. 2009, 24 (5): 280-288.
Poissant J, Wilson AJ, Coltman DW: Sex–specific genetic variance and the evolution of sexual dimorphism: a systematic review of cross–sex genetic correlations. Evolution. 2010, 64 (1): 97-107.
Ingleby FC, Innocenti P, Rundle HD, Morrow EH: Between–sex genetic covariance constrains the evolution of sexual dimorphism in Drosophila melanogaster. J Evol Biol. 2014, 27 (8): 1721-1732.
Lewis Z, Wedell N, Hunt J: Evidence for strong intralocus sexual conflict in the Indian meal moth, Plodia interpunctella. Evolution. 2011, 65 (7): 2085-2097.
Gosden TP, Shastri KL, Innocenti P, Chenoweth SF: The B-matrix harbors significant and sex-specific constraints on the evolution of multicharacter sexual dimorphism. Evolution. 2012, 66 (7): 2106-2116.
Wyman MJ, Stinchcombe JR, Rowe L: A multivariate view of the evolution of sexual dimorphism. J Evol Biol. 2013, 26 (10): 2070-2080.
Lee KP: Sex-specific differences in nutrient regulation in a capital breeding caterpillar Spodoptera litura (Fabricius). J Insect Physiol. 2010, 56 (11): 1685-1695.
Telang A, Booton V, Chapman RF, Wheeler DE: How female caterpillars accumulate their nutrient reserves. J Insect Physiol. 2001, 47 (9): 1055-1064.
Dingemanse NJ, Dochtermann NA: Individual behaviour: behavioural ecology meets quantitative genetics. Wild Quantitative Genetics. Edited by: Edited by Charmantier A, Garant D, Kruuk LEB. 2014, Oxford: Oxford University Press
Stirling DG, Réale D, Roff DA: Selection, structure and the heritability of behaviour. J Evol Biol. 2002, 15 (2): 277-289.
Van Oers K, Sinn DL: Quantitative and molecular genetics of animal personality. Animal Personalities: Behavior, Physiology, and Evolution. Edited by: Edited by Carere C, Maestripieri D. 2014, University of Chicago Press
This research was supported by a Marie Curie International Incoming Fellowship from the 7th EC Framework Programme of the European Union to CH. NJD was supported by the Max Planck Society (MPG). We thank the organisers and participants of the workshop “New perspectives in behavioural development: adaptive shaping of behaviour over a lifetime” financed by the Center for Interdisciplinary Research (ZiF) and the DFG (FOR1232) for stimulating feedback. We further thank Petri Niemelä, Francesca Santostefano, Philipp Sprau, Cristina Tuni, Fritz Trillmich and two anonymous reviewers for comments on previous versions of the manuscript.
The authors declare that they have no competing interests
CSH and NJD conceived and wrote the manuscript. All authors read and approved the final manuscript.
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Han, C.S., Dingemanse, N.J. Effect of diet on the structure of animal personality. Front Zool 12, S5 (2015) doi:10.1186/1742-9994-12-S1-S5
- behavioural syndrome
- gene-environment interaction
- genetic correlation
- intake target
- quantitative genetics