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Abstract Phenotypic plasticity, the ability of a single genotype to produce different phenotypes under different environmental conditions, plays a profound role in several areas of evolutionary biology. One important role is as an adaptation to a variable environment. While plasticity is extremely well documented in response to many environmental factors, there is controversy over how much of that plasticity is adaptive. Evidence is also mixed over how often conspecific populations display qualitative differences in the nature of plasticity. We present data on the reaction norms of growth and maturation to variation in temperature and salinity in male and female sailfin mollies (Poecilia latipinna) from three locally adjacent populations from South Carolina (SC). We compare these reaction norms to those previously reported in locally adjacent populations from north Florida (NF). In general, patterns of plasticity in fish from SC were similar to those in fish from NF. The magnitude of plasticity differed; fish from SC displayed less plasticity than fish from NF. This was because SC fish grew faster and matured earlier at the lower temperatures and salinities compared to NF fish. This is a countergradient pattern of variation, in which SC fish grew faster and matured earlier in conditions that would otherwise slow growth and delay maturity. Among fish from both regions, males were much less plastic than females, especially for length at maturity. While there was no detectable heterogeneity among populations from NF, males from one of the SC populations, which is furthest from the other two, displayed a qualitatively different response in age at maturity to temperature variation than did males from the other two SC populations. The pattern of population variation in plasticity within and among regions suggests that gene flow, which diminishes with distance in sailfin mollies, plays a critical role in constraining divergence in norms of reaction.

Climate change-induced rise in global temperatures has intensified heat stress on dairy cattle and is contributing to the generally observed low milk productivity. Selective breeding aimed at enhancing animals’ ability to withstand rising temperatures while maintaining optimal performance is crucial for ensuring future access to dairy products. However, phenotypic indicators of heat tolerance are yet to be effectively factored into the objectives of most selective breeding programs. This study investigated the response of milk production to changing heat load as an indication of heat tolerance and the influence of calving season on this response in multibreed dairy cattle performing in three agroecological zones Kenya. First-parity 7-day average milk yield (65 261 milk records) of 1 739 cows were analyzed. Based on routinely recorded weather data that were accessible online, the Temperature-Humidity Index (THI) was calculated and used as a measure of heat load. THI measurements used represented averages of the same 7-day periods corresponding to each 7-day average milk record. Random regression models, including reaction norm functions, were fitted to derive two resilience indicators: slope of the reaction norm (Slope) and its absolute value (Absolute), reflecting changes in milk yield in response to the varying heat loads (THI 50 and THI 80). The genetic parameters of these indicators were estimated, and their associations with average test-day milk yield were examined. There were no substantial differences in the pattern of milk yield response to heat load between cows calving in dry and wet seasons. Animals with ≤50% Bos taurus genes were the most thermotolerant at extremely high heat load levels. Animals performing in semi-arid environments exhibited the highest heat tolerance capacity. Heritability estimates for these indicators ranged from 0.06 to 0.33 and were mostly significantly different from zero (P

Each individual is equipped with a distinct genetic disposition and ontogenetic history and experiences environmental conditions in a unique way. As a result, individuals vary in terms of phenotypic differences regarding their responses to internal and external conditions. By modulating hormone secretion, an individual can react to changing conditions, thus maintaining homeostasis. Cortisol and triiodothyronine (T3) are involved in mediating energy homeostasis. The secretion of metabolic hormones enables individuals to respond flexibly to internal and external conditions. However, this flexibility may be constrained by tradeoffs between average hormone levels and the degree of hormonal plasticity and the impact of the HPA axis on T3 secretion and effects. Like many other species, bonobos (Pan paniscus) are confronted with rapid ecological and climatic perturbations, resulting in challenges to energetic homeostasis. Due to their limited genetic diversity, K-strategist and stenoecious species characteristics, they are predicted to have only limited potential for adaptation. Therefore, it is important to quantify individual cortisol and T3 reaction norms and examine their relationship with each other to understand the level of flexibility of metabolic hormone phenotypes. Using a multivariate random slope model, we found that diurnal urinary excretion patterns of cortisol and T3 in wild female bonobos have (i) no relationship between average phenotype and plasticity within the reaction norms of both hormones. (ii) We also found a negative correlation between the intercepts of the two metabolic hormones, but (iii) no relationship between their slopes. (iv) Standard deviations of cortisol and T3 intercepts and slopes between females indicate little variation among females. Our data show that plasticity within and between the two metabolic hormones is not related to overall low or high hormone levels, but there is a linear negative relationship between cortisol and T3 average phenotypes. Thus, individuals with high average cortisol levels, investing in restoring energy depots, have low average T3 levels, reducing energy expenditure, and vice versa. From this we conclude that the plasticity of diurnal hormone excretion is not affected by average metabolic hormone phenotypes. Evaluations of cortisol and T3 plasticity along ecological gradients can enhance our understanding of the adaptive potential of a given species to environmental changes.

IntroductionPhenotypic plasticity (PP) could be an important short-term mechanism to modify physiological and morphological traits in response to climate change and global warming, particularly for high-mountain tree species. The objective was to evaluate PP response of growth ring traits to temperature and precipitation in Pinus hartwegii Lindl. populations located at the ends of its elevational gradient on two volcanic mountains in central Mexico (La Malinche and Nevado de Toluca).MethodsIncrement cores collected from 274 P. hartwegii trees were used to estimate their PP through reaction norms (RN), which relate the ring width and density traits with climate variables (temperature and precipitation). We estimated the trees’ sensitivity (significant RN) to climatic variables, as well as the relative proportion of RN with positive and negative slope. We also estimated the relationship between the PP of ring width and density traits using correlation and Principal Component (PC) analyses.ResultsOver 70% of all trees showed significant RN to growing season and winter temperatures for at least one growth ring trait, with a similar proportion of significant RN at both ends of the gradient on both mountains. Ring width traits had mostly negative RN, while ring density traits tended to have positive RN. Frequency of negative RN decreased from lower to higher elevation for most traits. Average PP was higher at the lower end of the gradient, especially on LM, both for ring width and ring density traits, although high intrapopulation variation in PP was found on both mountains.DiscussionResults indicate that P. hartwegii presents spatially differentiated plastic responses in width and density components of radial growth. PP was particularly strong at the lower elevation, which has higher temperature and water stress conditions, putting these populations at risk from the continuing global warming driven by climate change.

The Sixth Assessment of the Intergovernmental Panel on Climate Change describes negative effects of climate change on animals occurring on a larger scale than previously appreciated. Animal species are increasingly experiencing more frequent and extreme weather in comparison with conditions in which the species evolved. Individual variation in behavioural and physiological responses of animals to stimuli from the environment is ubiquitous across all species. Populations with relatively high levels of individual variation are more likely to be able to survive in a range of environmental conditions and cope with climate change than populations with low levels of variation. Behavioural and physiological responses are linked in animals, and personality can be defined as consistent individual behavioural and physiological responses of animals to changes in their immediate environment. Glucocorticoids (cortisol and corticosterone) are hormones that, in addition to metabolic roles, are released when the neuroendocrine stress system is activated in response to stimuli from the environment perceived to be threatening. The size of a glucocorticoid response of an animal is an indication of the animal’s personality. Animals with reactive personalities have relatively high glucocorticoid responses, are relatively slow and thorough to explore new situations, and are more flexible and able to cope with changing or unpredictable conditions than animals with proactive personalities. Animals with reactive personalities are likely to be better able to cope with environmental changes due to climate change than animals with proactive personalities. A reaction norm shows the relationship between phenotype and environmental conditions, with the slope of a reaction norm for an individual animal a measure of phenotypic plasticity. If reaction norm slopes are not parallel, there is individual variation in plasticity. Populations with relatively high individual variation in plasticity of reaction norms will have more animals that can adjust to a new situation than populations with little variation in plasticity, so are more likely to persist as environments change due to climate change. Future studies of individual variation in plasticity of responses to changing environments will help understanding of how populations of animals may be able to cope with climate change.

Abstract Diurnal fluctuations in temperature are ubiquitous in terrestrial environments, and insects and other ectotherms have evolved to tolerate or acclimate to such fluctuations. Few studies have examined whether ectotherms acclimate to diurnal temperature fluctuations, or how natural and domesticated populations differ in their responses to diurnal fluctuations. We examine how diurnally fluctuating temperatures during development affect growth, acclimation, and stress responses for two populations of Manduca sexta: a field population that typically experiences wide variation in mean and fluctuations in temperature, and a laboratory population that has been domesticated in nearly constant temperatures for more than 300 generations. Laboratory experiments showed that diurnal fluctuations throughout larval development reduced pupal mass for the laboratory but not the field population. The differing effects of diurnal fluctuations were greatest at higher mean temperature (30°C): Here diurnal fluctuations reduced pupal mass and increased pupal development time for the laboratory population, but had little effect for the field population. We also evaluated how mean and fluctuations in temperature during early larval development affected growth rate during the final larval instar as a function of test temperature. At an intermediate (25°C) mean temperature, both the laboratory and field population showed a positive acclimation response to diurnal fluctuations, in which subsequent growth rate was significantly higher at most test temperatures. In contrast at higher mean temperature (30°C), diurnal fluctuations significantly reduced subsequent growth rate at most test temperatures for the laboratory population, but not for the field population. These results suggest that during domestication in constant temperatures, the laboratory population has lost the capacity to tolerate or acclimate to high and fluctuating temperatures. Population differences in acclimation capacity in response to temperature fluctuations have not been previously demonstrated, but they may be important for understanding the evolution of reaction norms and performance curves.

The architecture is based on a dialectical search for new ways of matter representation. We deal with the form of contemporary architecture under two approaches: expression and content. The article examines how mathematical principles based on natural growth can be applied in architectural design to create a dynamic, not static, structure. The dynamic process of the cell and its growth provides the basic structure. The continuity of the domain is exemplified by the impact of the new forms on the society that has already begun to emerge from the obscurity. The paper argues that without a deeper and more receptive connection between geometry and performance from a bio-morphogenetic perspective of complex systems. The experimental design methods are applied both to generate and to evaluate an architecture of the futuristic lines. These methodological frameworks focus on cyclically restated themes in the field of parametrises, which are identified as endemic to architecture: the realization of buildings, of multifunctional volumes and customized per se through a gradual approach of the architectural properties and the exploitation of a "concept construction" integrated as a process, obtained through innovative modelling environments. And so, and the reconstruction of architecture as an organ of nature is demonstrated. The new vanguard of proto architecture describes difficulties and inconsistencies in the relationship between theories and structures, difficulties arising from the very idea of "virtually" itself. It becomes difficult to say that a drawing in cyberspace is an architectural form or just a graph of architectural theory; in the virtual space, there is no difference between the particular structure and the general principle. Therefore, the form is first designed, only after to be constructed. Naturally, it is impossible (theoretically or technically) for design and construction processes to take place simultaneously. Predictably, bio-morphosis leads to multiple forms of expression, defined and transmitted in geometric terms. Doi: 10.28991/esj-2020-01248 Full Text: PDF

Abstract The neurotransmitter dopamine has been shown to play an important role in modulating behavioral, morphological, and life history responses to food abundance. However, costs of expressing high dopamine levels remain poorly studied and are essential for understanding the evolution of the dopamine system. Negative maternal effects on offspring size from enhanced maternal dopamine levels have previously been documented in Daphnia. Here, we tested whether this translates into fitness costs in terms of lower starvation resistance in offspring. We exposed Daphnia magna mothers to aqueous dopamine (2.3 or 0 mg/L for the control) at two food levels (ad libitum vs. 30% ad libitum) and recorded a range of maternal life history traits. The longevity of their offspring was then quantified in the absence of food. In both control and dopamine treatments, mothers that experienced restricted food ration had lower somatic growth rates and higher age at maturation. Maternal food restriction also resulted in production of larger offspring that had a superior starvation resistance compared to ad libitum groups. However, although dopamine exposed mothers produced smaller offspring than controls at restricted food ration, these smaller offspring survived longer under starvation. Hence, maternal dopamine exposure provided an improved offspring starvation resistance. We discuss the relative importance of proximate and ultimate causes for why D. magna may not evolve toward higher endogenous dopamine levels despite the fitness benefits this appears to have.

Background: Natural selection optimizes phenotypic plasticity in plants found in environmentally variable habitats. However, it is unclear how artificial selection has affected the phenotypic plasticity of crops. Reduced plasticity in crop yield is often considered a desirable feature in cultivated plants; however, limited phenotypic plasticity in this and other traits may also affect the ability of crops to cope with environmental variation. Study species: Wild and domesticated chaya (Cnidoscolus aconitifolius (Mill.) I.M. Johnst). Question: How domestication has affected the phenotypic plasticity of vegetative traits in response to the light environment? Methods: Leaf area, leaf perimeter, leaf specific area, leaf production, trichome density, stem elongation, growth in stem diameter and slenderness were measured in clones of wild and domesticated plants. These clones were allocated to two contrasting light treatments: fully exposed to sun vs. placement beneath a shade cloth. The phenotypic traits and reaction norms were compared between the genotypes of wild and domesticated plants. Results: Lower plasticity in leaf production and slenderness was observed in the domesticated compared to the wild plants. Leaf production and slenderness are associated with the shade avoidance syndrome, which was evident in wild plants but not manifested in domesticated plants. Reduced plasticity in leaf production also suggests yield stability. Conclusion: Artificial selection reduces phenotypic plasticity in the yield of chaya and in its response to variation in light availability.

The deep ocean ecosystem hosts high biodiversity and plays a critical role for humans through the ecosystem services it provides, such as fisheries and climate regulation. However, high longevity, late reproduction, and low fecundity of many organisms living in the deep ocean make them particularly vulnerable to fishing and climate change. A better understanding of how exploitation and changing environmental conditions affect life-history parameters (e.g., growth) of commercially important fish species is crucial for their long-term sustainable management. To this end, we used otolith increment widths and a mixed-effects modeling approach to develop a 42-year growth chronology (1975–2016) of the commercially important deep-sea fish species blackspot seabream (Pagellus bogaraveo) among the three island groups of the Azores archipelago (Northeast Atlantic). Growth was related to intrinsic (age and age-at-capture) and extrinsic factors (capture location, temperature-at-depth, North Atlantic Oscillation (NAO), Eastern Atlantic Pattern (EAP), and proxy for exploitation (landings)). Over the four decades analyzed, annual growth patterns varied among the three island groups. Overall, temperature-at-depth was the best predictor of growth, with warmer water associated with slower growth, likely reflecting physiological conditions and food availability. Average population growth response to temperature was separated into among-individual variation and within-individual variation. The significant among-individual growth response to temperature was likely related to different individual-specific past experiences. Our results suggested that rising ocean temperature may have important repercussions on growth, and consequently on blackspot seabream fishery production. Identifying drivers of blackspot seabream growth variation can improve our understanding of past and present condition of the populations toward the sustainable management of the fishery.

Seasonal polyphenisms are cases in which individuals representing generations occurring in different times of the year systematically differ in their morphological, physiological, and/or behavioral traits. Such differences are often assumed to constitute adaptive responses to seasonally varying environments, but the evidence for this is still scarce. The adaptive character of the response would be corroborated by the pattern in which the decision about choosing a particular seasonal phenotype is made before the onset of respective environmental conditions (anticipatory plasticity). Alternatively, the between-generation differences can be caused by immediate effects of seasonally varying environments (responsive plasticity). Here we reared the larvae of the seasonally polymorphic map butterfly Araschnia levana under two different photoperiodic regimes, which provided different seasonal cues. These two treatments induced direct development and diapause pathways, respectively. Replicating the experiment at different temperatures and levels of host plant quality allowed us to evaluate both the anticipatory and the responsive components of the associated plastic changes in life-history traits. Larvae representing the direct development pathway invariably had higher growth rates and shorter development periods, although the difference between the developmental pathways was smaller at inferior host quality. Body size differences between the developmental pathways turned out to be less consistent, as the natural pattern of higher pupal mass of the directly developing individuals could only be reproduced at lower rearing temperature. Though being considerably modified by immediate environmental effects, the between-generation differences in size, growth rates, and larval are largely based on anticipatory plasticity (= responses to photoperiodic cues) and should be treated as seasonal adaptations in A. levana. In a more general context, we show how investigating the proximate basis of size differences can serve the purpose of identifying the limits of phenotypic plasticity in juvenile growth schedules.

Dairy cattle production is distributed throughout the Brazilian regions. However, Brazilian producing regions are different in air temperature and humidity, diet, birth season, and other factors that may alter the reproductive performances of cows. The age of the cow at first calving (AFC) is a good indicator of sexual precocity since it shows the beginning of the female reproductive life and has a great influence on cow replacement costs. Researches on genotype-environment interaction (GEI) show the importance of using specific bulls for the different production systems in Brazil since most semen used in the country is imported. The objective of this work was to evaluate GEI for AFC in Holstein cows in Brazil, using reaction norms. The statistical models used were the standard animal model, which disregards the GEI, and hierarchical reaction norm models with homoscedastic (HRNMHO) and heteroscedastic (HRNMHE) residual variance, and one (HRNMHO1S and HRNMHE1S) and two (HRNMHO2S and HRNMHE2S) steps. HRNMHO1S presented better fit to the data, with lower heritability for environments with lower AFC, and higher heritability for environments with higher AFC. The GEI found was complex, with a reclassification of bulls, denoting the importance of considering GEI for evaluation and selection of bulls for different production levels. The reduction of AFC is possible when using breeding bulls adapted to the tropical and subtropical conditions of Brazil.

Living organisms adapt to changes in environment by phenotypic plasticity and evolution by natural selection (or they migrate). At detailed genetic levels these phenomena are complicated, and quantitative genetics attempts to capture essential processes at a higher abstraction level. Phenotypic plasticity is then commonly modeled by reaction norms, which describe how individual traits in a population are expressed in response to changes in environmental variables. The mean reaction norms are evolvable, and here I present a general quantitative genetics state-space model for evolutionary reaction norm dynamics. Reaction norms make use of a reference environment, which is traditionally set to zero. This is problematic when the reference environment is the environment a population is adapted to, for the reason that this environment is a population property, which in itself may be evolvable. With reference to Ergon (2018), I describe models that take such evolvability into account. The resulting models are fundamentally different from most engineering system models, where given reference values are constant, and therefore without consequences can be set to zero. For simplicity I assume only temporal variations in environment, although there obviously are a lot of spatial variations in nature, and I assume that no mutations are involved. Fundamentals from quantitative evolutionary theory are given in appendices.

The real world is highly variable and unpredictable, and so fine-tuned robot controllers that successfully result in group-level “emergence” of swarm capabilities indoors may quickly become inadequate outside. One response to unpredictability could be greater robot complexity and cost, but this seems counter to the “swarm philosophy” of deploying (very) large numbers of simple agents. Instead, here I argue that bioinspiration in swarm robotics has considerable untapped potential in relation to the phenomenon of phenotypic plasticity: when a genotype can produce a range of distinctive changes in organismal behavior, physiology and morphology in response to different environments. This commonly arises following a natural history of variable conditions; implying the need for more diverse and hazardous simulated environments in offline, pre-deployment optimization of swarms. This will generate—indicate the need for—plasticity. Biological plasticity is sometimes irreversible; yet this characteristic remains relevant in the context of minimal swarms, where robots may become mass-producible. Plasticity can be introduced through the greater use of adaptive threshold-based behaviors; more fundamentally, it can link to emerging technologies such as smart materials, which can adapt form and function to environmental conditions. Moreover, in social animals, individual heterogeneity is increasingly recognized as functional for the group. Phenotypic plasticity can provide meaningful diversity “for free” based on early, local sensory experience, contributing toward better collective decision-making and resistance against adversarial agents, for example. Nature has already solved the challenge of resilient self-organisation in the physical realm through phenotypic plasticity: swarm engineers can follow this lead.

There is a paradigm shift from the traditional focus on the “average” individual towards the definition and analysis of trait variation within individual life-history and among individuals in populations. This is a result of increasing availability of individual phenotypic data. The shift allows the use of genetic and environment-driven variations to assess robustness to challenge, gain greater understanding of organismal biological processes, or deliver individual-targeted treatments or genetic selection. These consequences apply, in particular, to variation in ontogenetic growth. We propose an approach to parameterise mathematical models of individual traits (e.g., reaction norms, growth curves) that address two challenges: 1) Estimation of individual traits while making minimal assumptions about data distribution and correlation, addressed via Approximate Bayesian Computation (a form of nonparametric inference). We are motivated by the fact that available information on distribution of biological data is often less precise than assumed by conventional likelihood functions. 2) Scaling-up to population phenotype distributions while facilitating unbiased use of individual data; this is addressed via a probabilistic framework where population distributions build on separately-inferred individual distributions and individual-trait interpretability is preserved. The approach is tested against Bayesian likelihood-based inference, by fitting weight and energy intake growth models to animal data and normal- and skewed-distributed simulated data. i) Individual inferences were accurate and robust to changes in data distribution and sample size; in particular, median-based predictions were more robust than maximum- likelihood-based curves. These results suggest that the approach gives reliable inferences using few observations and monitoring resources. ii) At the population level, each individual contributed via a specific data distribution, and population phenotype estimates were not disproportionally influenced by outlier individuals. Indices measuring population phenotype variation can be derived for study comparisons. The approach offers an alternative for estimating trait variability in biological systems that may be reliable for various applications, for example, in genetics, health, and individualised nutrition, while using fewer assumptions and fewer empirical observations. In livestock breeding, the potentially greater accuracy of trait estimation (without specification of multitrait variance-covariance parameters) could lead to improved selection and to more decisive estimates of trait heritability.

Developmental plasticity refers to the property by which the same genotype produces distinct phenotypes depending on the environmental conditions under which development takes place. By allowing organisms to produce phenotypes adjusted to the conditions that adults will experience, developmental plasticity can provide the means to cope with environmental heterogeneity. Developmental plasticity can be adaptive and its evolution can be shaped by natural selection. It has also been suggested that developmental plasticity can facilitate adaptation and promote diversification. Here, we summarize current knowledge on the evolution of plasticity and on the impact of plasticity on adaptive evolution, and we identify recent advances and important open questions about the genomics of developmental plasticity in animals. We give special attention to studies using transcriptomics to identify genes whose expression changes across developmental environments and studies using genetic mapping to identify loci that contribute to variation in plasticity and can fuel its evolution.

In order to assess the extent of genotype by environment interactions (G×E) and environmental sensitivity in sheep farm systems, environmental factors must be identified and quantified, after which the relationship with the traits(s) of interest can be investigated. The objectives of this study were to develop a farm environment (FE) scale, using a canonical correlation analysis, which could then be used in linear reaction norm models. Fine-scale farm survey data, collected from a sample of 39 Texel flocks across the United Kingdom, was combined with information available at the national level. The farm survey data included information on flock size and concentrate feed use. National data included flock performance averages for 21-week-old weight (21WT), ultrasound back-fat (UFD) and muscle (UMD) depths, as well as regional climatic data. The FE scale developed was then combined with 181 555 (21WT), 175 399 (UMD) and 175 279 (UFD) records from lambs born between 1990 and 2011, on 494 different Texel flocks, to predict reaction norms for sires used within the population. A range of sire sensitivities estimated across the FE scale confirmed the presence of genetic variability as both ‘plastic’ and ‘robust’ genotypes were observed. Variations in heritability estimates were also observed indicating that the rate genetic progress was dependent on the environment. Overall, the techniques and approaches used in this study have proven to be useful in defining sheep FEs. The results observed for 21WT, UMD and UFD, using the reaction norm models, indicate that in order to improve genetic gain and flock efficiency, future genetic evaluations would benefit by accounting for the G×E observed.

The objective of the present study was to determine the presence of genotype by environment interaction (G × E) and to characterize the phenotypic plasticity of birth weight (BW), weaning weight (WW), postweaning weight gain (PWG) and yearling scrotal circumference (SC) in composite beef cattle using the reaction norms model with unknown covariate. The animals were born between 1995 and 2008 on 33 farms located throughout all Brazilian biomes between latitude −7° and −31°, longitude −40° and −63°. The contemporary group was chosen as the environmental descriptor, that is, the environmental covariate of the reaction norms. In general, higher estimates of direct heritability were observed in extreme favorable environments. The mean of direct heritability across the environmental gradient ranged from 0.05 to 0.51, 0.09 to 0.43, 0.01 to 0.43 and from 0.12 to 0.26 for BW, WW, PWG and SC, respectively. The variation in direct heritability observed indicates a different response to selection according to the environment in which the animals of the population are evaluated. The correlation between the level and slope of the reaction norm for BW and PWG was high, indicating that animals with higher average breeding values responded better to improvement in environmental conditions, a fact characterizing a scale of G × E. Low correlation between the intercept and slope was obtained for WW and SC, implying re-ranking of animals in different environments. Genetic variation exists in the sensitivity of animals to the environment, a fact that permits the selection of more plastic or robust genotypes in the population studied. Thus, the G × E is an important factor that should be considered in the genetic evaluation of the present population of composite beef cattle.

The rates at which birds use energy may have profound effects on fitness, thereby influencing physiology, behavior, ecology and evolution. Comparisons of standardized metabolic rates (e.g., lower and upper limits of metabolic power output) present a method for elucidating the effects of ecological and evolutionary factors on the interface between physiology and life history in birds. In this paper we review variation in avian metabolic rates [basal metabolic rate (BMR; minimum normothermic metabolic rate), summit metabolic rate (Msum; maximal thermoregulatory metabolic rate), and maximal metabolic rate (MMR; maximal exercise metabolic rate)], the factors associated with this variation, the evidence for functional links between these metabolic traits, and the ecological and evolutionary significance of avian metabolic diversity. Both lower and upper limits to metabolic power production are phenotypically flexible traits, and vary in association with numerous ecological and evolutionary factors. For both inter- and intraspecific comparisons, lower and upper limits to metabolic power production are generally upregulated in response to energetically demanding conditions and downregulated when energetic demands are relaxed, or under conditions of energetic scarcity. Positive correlations have been documented between BMR, Msum and MMR in some, but not all studies on birds, providing partial support for the idea of a functional link between lower and upper limits to metabolic power production, but more intraspecific studies are needed to determine the robustness of this conclusion. Correlations between BMR and field metabolic rate (or daily energy expenditure), in birds are variable, suggesting that the linkage between these traits is subject to behavioral adjustment, and studies of the relationship between field and maximal metabolic rates are lacking. Our understanding of avian metabolic diversity would benefit from future studies of: (1) the functional and mechanistic links between lower and upper limits of metabolic power output; (2) the environmental and ecological cues driving phenotypically flexible metabolic responses, and how responses to such cues might impact population responses to climate change; (3) the shapes of metabolic reaction norms and their association with environmental variability; and (4) the relationship of metabolic variation to fitness, including studies of repeatability and heritability of minimum and maximum metabolic power output [Current Zoology 56 (6): 741–758, 2010].

Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

The increasing size of the human population is projected to result in an increase in meat consumption. However, at the same time, the dominant position of meat as the centre of meals is on the decline. Modern objections to the consumption of meat include public concerns with animal welfare in livestock production systems. Animal breeding practices have become part of the debate since it became recognized that animals in a population that have been selected for high production efficiency are more at risk for behavioural, physiological and immunological problems. As a solution, animal breeding practices need to include selection for robustness traits, which can be implemented through the use of reaction norms analysis, or though the direct inclusion of robustness traits in the breeding objective and in the selection index. This review gives a historic overview of genotype  environment interactions (the influence of the environment, reaction norms, canalization, genetic homeostasis, and phenotypic plasticity), reaction norms analysis in livestock production, options for selection for increased levels of production and against environmental sensitivity, and the direct inclusion of robustness traits in the selection index. Ethical considerations of breeding for improved animal welfare are discussed. The discussion on animal breeding practices has been initiated and is very alive today. This positive trend is part of the sustainable food production movement that aims at feeding 9.15 billion people not just in the near future but also beyond.