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Summary: Through enviromics, precision breeding leverages innovative geotechnologies to customize crop varieties to specific environments, potentially improving both crop yield and genetic selection gains.In Brazil's four southernmost states, data from 183 distinct geographic field trials (also accounting for 2017–2021) covered information on 164 genotypes: 79 phenotyped maize hybrid genotypes for grain yield and their 85 nonphenotyped parents. Additionally, 1342 envirotypic covariates from weather, soil, sensor‐based, and satellite sources were collected to engineer 10 K synthetic enviromic markers via machine learning.Soil, radiation light, and surface temperature variations remarkably affect differential genotype yield, hinting at ecophysiological adjustments including evapotranspiration and photosynthesis. The enviromic ensemble‐based random regression model showcases superior predictive performance and efficiency compared to the baseline and kernel models, matching the best genotypes to specific geographic coordinates. Clustering analysis has identified regions that minimize genotype‐environment (G × E) interactions. These findings underscore the potential of enviromics in crafting specific parental combinations to breed new, higher‐yielding hybrid crops.The adequate use of envirotypic information can enhance the precision and efficiency of maize breeding by providing important inputs about the environmental factors that affect the average crop performance. Generating enviromic markers associated with grain yield can enable a better selection of hybrids for specific environments. See also the Commentary on this article by Bowerman, 245: 9–10. [ABSTRACT FROM AUTHOR]

Some insect species have been proposed as a sustainable alternative to traditional animal‐based food and feed sources. Optimisation of insect production can generally be achieved using two main approaches: optimising environmental conditions and improving traits of interest through selective breeding. These avenues are not inseparable as performance of a genotype might differ between environments due to phenotypic plasticity and because genotypes can respond differently to environmental changes, that is genotype‐by‐environment interactions (G × E). In insect production, diets can be of variable quality and consist of waste‐ and by‐products of low nutritional value, which might result in decreased performance and/or increased trait variability within a population. Therefore, it is of interest to investigate how genotypes perform across various diets. Here, we investigated plasticity and G × E for mean performance and trait variation, which we define as the ability of a genotype to produce consistent phenotypes within and across environments. We did this by rearing 190 full‐sib families of house fly larvae, Musca domestica L. (Diptera: Muscidae), on two diets based on either alfalfa, Medicago sativa L. (Fabales: Fabaceae), or deproteinated grass. Four larval traits were assessed: egg‐to‐larva viability, surface area, dry weight and relative lipid content. Reaction norms were used to investigate the effects of diet on full‐sib family mean and trait variation within and across environments. We found that families reared on the grass‐based diet had higher performance across all investigated traits than families reared on the alfalfa‐based diet. For both mean performance and trait variation, we found G × E for all investigated traits. These findings suggest that there is genetic variation for plasticity (slope of reaction norms) for both trait mean and trait variation, and thus that there is a potential to breed for genotypes with high performance as well as for genotypes with low trait variation within and across diets. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the impact of genotype-environment interaction (GEI) on the manifestation of traits such as age at first calving (AFC), age at first service (AFS), and calving interval (CI) through the application of the reaction norm model in Holstein cattle raised in Paraná state, Brazil. Utilizing data from the milk testing service of the Paraná Association of Holstein Cattle Breeders (APCBRH), this study analyzed records from 179,492 animals undergoing their first, second, and third lactations from the years 2012 to 2022. These animals were part of 513 herds spread across 72 municipalities in Paraná. The environmental gradient was established by normalizing contemporary group solutions, derived from the animal model, with the 305-day-corrected milk yield serving as the dependent variable. Subsequently, reaction norms were determined utilizing a Random Regression Model. Spearman’s correlation was then applied to compare the estimates of breeding values across different environmental gradients for the studied traits. The highest EG (+ 4) indicates the least challenging environments, where animals experience better environmental conditions. Conversely, lower EG (-4) values represent the most challenging environments, where animals endure worse conditions. The only trait that exhibited a moderate heritability magnitude was AFC (0.23) in the least challenging environmental condition. The other traits were classified as having low heritability magnitudes regardless of the evaluated environmental gradient. While minimal evidence was found for the influence of GEI on CI, a clear GEI effect was observed for AFC and AFS across all environmental gradients examined. A reversal in genotype ranking occurred under extreme environmental conditions. The findings suggest that the best-performing genotype under one environmental gradient may not necessarily excel under another. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Rate‐temperature scaling relationships have fascinated biologists for nearly two centuries and are increasingly important in our era of global climate change. These relationships are hypothesized to originate from the temperature‐dependent kinetics of rate‐limiting biochemical reactions of metabolism. Several prominent theories have formalized this hypothesis using the Arrhenius model, which characterizes a monotonic temperature dependence using an activation energy E. However, the ubiquitous unimodal nature of biological temperature responses presents important theoretical, methodological, and conceptual challenges that restrict the promise for insight, prediction, and progress. Here we review the development of key hypotheses and methods for the temperature‐scaling of biological rates. Using simulations, we examine the constraints of monotonic models, illustrating their sensitivity to data nuances such as temperature range and noise, and their tendency to yield variable and underestimated E, with critical consequences for climate change predictions. We also evaluate the behaviour of two prominent unimodal models when applied to incomplete and noisy datasets. We conclude with recommendations for resolving these challenges in future research, and advocate for a shift to unimodal models that better characterize the full range of biological temperature responses. [ABSTRACT FROM AUTHOR]

The vulnerability of fish populations to climate change is driven primarily by impacts on their most vulnerable life stages. The earliest life stages may, in many cases, be more thermally sensitive than juvenile and adult fish, as developing embryos cannot behaviourally thermoregulate. We quantified the survivorship of brook trout (Salvelinus fontinalis) embryos under a range of winter thermal regimes. In the laboratory, embryos from four populations with varying amounts of native or hatchery-introgressed ancestry were reared under four simulated winter thermal regimes relevant to the central portion of the species' range: ambient stream temperatures, ambient + 2 °C, ambient with a simulated winter snowmelt event, and ambient followed by an early rise to spring temperatures. Embryo survival (hatching success) differed significantly among populations across all thermal regimes, with the pure native population having the lowest survival. No consistent differences in survivorship across thermal regimes were detected, although native populations exhibited more among-family variability in response to thermal stress. Our study does not align closely with others that found reduced embryo survival under thermal stress, but concurs with observations of substantial intraspecific variation in thermal performance in coldwater fishes. Our results suggest that brook trout embryos may be somewhat resilient in the face of warmer and more variable incubation conditions, but it is likely that their resiliency varies among populations. Future experiments that include more extreme and variable conditions to clarify environmental limits of early life stages of brook trout would be useful for conservation planning. [ABSTRACT FROM AUTHOR]

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

The selection of better-evaluated genotypes for a target region depends on the characterization of the climate conditions of the environment. With the advancement of computer technology and daily available information about the weather, integrating such information in selection and interaction genotype × environment studies has become a challenge. This article presents the use of the technique of artificial neural networks associated with reaction norms for the processing of climate and georeferenced data for the study of genetic behaviors and the genotype × environment interaction of soybean genotypes. The technique of self-organizing maps (SOM) consists of competitive learning between two layers of neurons; one is the input, which transfers the data to the map, and the other is the output, where the topological structure formed by the competition generates weights, which represent the dissimilarity between the neural units. The methodologies used to classify these neurons and form the target populations of environments (TPE) were the discriminant analysis (DA) and the principal component analysis (PCA). To study soybean genetic behavior within these TPE, the random regression model was adopted to estimate the components of variance, and the reaction norms were adjusted through the Legendre polynomials. The SOM methodology allowed for an explanation of 99% of the variance of the climate data and the formation of well-structured TPE, with the membership probability of the regions within the TPE above 80%. The formation of these TPE allowed us to identify and quantify the response of the genotypes to sensitive changes in the environment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Introduction: Phenotypic 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). Methods: Increment 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. Results: Over 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. Discussion: Results 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. [ABSTRACT FROM AUTHOR]

In seasonal environments, a high responsiveness of development to increasing temperatures in spring can infer benefits in terms of a longer growing season, but also costs in terms of an increased risk of facing unfavourable weather conditions. Still, we know little about how climatic conditions influence the optimal plastic response. Using 22 years of field observations for the perennial forest herb Lathyrus vernus, we assessed phenotypic selection on among-individual variation in reaction norms of flowering time to spring temperature, and examined if among-year variation in selection on plasticity was associated with spring temperature conditions. We found significant among-individual variation in mean flowering time and flowering time plasticity, and that plants that flowered earlier also had a more plastic flowering time. Selection favoured individuals with an earlier mean flowering time and a lower thermal plasticity of flowering time. Less plastic individuals were more strongly favoured in colder springs, indicating that spring temperature influenced optimal flowering time plasticity. Our results show how selection on plasticity can be linked to climatic conditions, and illustrate how we can understand and predict evolutionary responses of organisms to changing environmental conditions. [ABSTRACT FROM AUTHOR]

The Modern Synthesis has received criticism for its purported gene-centrism. That criticism relies on a concept of the gene as a unit of instructional information. In this paper I discuss information concepts and endorse one, developed from Floridi, that sees information as a functional relationship between data and context. I use this concept to inspect developmental criticisms of the Modern Synthesis and argue that the instructional gene arose as an idealization practice when evolutionary biologists made comment on development. However, a closer inspection of key claims shows that at least some associated with the Modern Synthesis were in fact adopting the data led definition I favour and made clear arguments for the role of developmental processes beyond genetic input. There was no instructional gene. [ABSTRACT FROM AUTHOR]

Simple Summary: The prenatal environment can influence the postnatal performance of cattle. Especially in tropical regions, pregnant beef cows may experience nutritional restriction during gestation, which coincides with the season of poor quality and quantity of feed. Thus, it was verified that the offspring of cows subjected to a better gestation environment exhibited better productive and reproductive performances throughout their lives. In terms of genetic merit, it was found that the best animals in a restricted gestational environment are not necessarily the same in a favorable gestational environment. In other words, for each condition of the gestational environment, there are animals specifically suited to perform better. In addition, regions in the genome of these animals responsible for several traits of economic importance in cattle were identified. Thus, for a more efficient selection process, breeders must consider the effect of genotype by prenatal environment interaction and provide adequate management and nutrition care for pregnant cows. The prenatal environment is recognized as crucial for the postnatal performance in cattle. In tropical regions, pregnant beef cows commonly experience nutritional restriction during the second half of the gestation period. Thus, the present study was designed to analyze the genotype by prenatal environment interaction (G × Epn) and to identify genomic regions associated with the level and response in growth and reproduction-related traits of beef cattle to changes in the prenatal environment. A reaction norm model was applied to data from two Nelore herds using the solutions of contemporary groups for birth weight as a descriptor variable of the gestational environment quality. A better gestational environment favored weights until weaning, scrotal circumference at yearling, and days to first calving of the offspring. The G × Epn was strong enough to result in heterogeneity of variance components and genetic parameters in addition to reranking of estimated breeding values and SNPs effects. Several genomic regions associated with the level of performance and specific responses of the animals to variations in the gestational environment were revealed, which harbor QTLs and can be exploited for selection purposes. Therefore, genetic evaluation models considering G × Epn and special management and nutrition care for pregnant cows are recommended. [ABSTRACT FROM AUTHOR]

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 physiological performance of organisms depends on their environmental context, resulting in performance–response curves along environmental gradients. Parasite performance–response curves are generally expected to be broader than those of their hosts due to shorter generation times and hence faster adaptation. However, certain environmental conditions may limit parasite performance more than that of the host, thereby providing an environmental refuge from disease. Thermal disease refuges have been extensively studied in response to climate warming, but other environmental factors may also provide environmental disease refuges which, in turn, respond to global change. Here, we (1) showcase laboratory and natural examples of refuges from parasites along various environmental gradients, and (2) provide hypotheses on how global environmental change may affect these refuges. We strive to synthesize knowledge on potential environmental disease refuges along different environmental gradients including salinity and nutrients, in both natural and food‐production systems. Although scaling up from single host–parasite relationships along one environmental gradient to their interaction outcome in the full complexity of natural environments remains difficult, integrating host and parasite performance–response can serve to formulate testable hypotheses about the variability in parasitism outcomes and the occurrence of environmental disease refuges under current and future environmental conditions. [ABSTRACT FROM AUTHOR]

Global change encompasses many co‐occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction‐norm perspective can improve our ability to make predictions of interactions at higher levels of organization—that is, community and food web. Building on the framework of consumer–resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof‐of‐concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today. [ABSTRACT FROM AUTHOR]

When comparing somatic growth thermal performance curves (TPCs), higher somatic growth across experimental temperatures is often observed for populations originating from colder environments. Such countergradient variation has been suggested to represent adaptation to seasonality, or shorter favourable seasons in colder climates. Alternatively, populations from cold climates may outgrow those from warmer climates at low temperature, and vice versa at high temperature, representing adaptation to temperature. Using modelling, we show that distinguishing between these two types of adaptation based on TPCs requires knowledge about (i) the relationship between somatic growth rate and population growth rate, which in turn depends on the scale of somatic growth (absolute or proportional), and (ii) the relationship between somatic growth rate and mortality rate in the wild. We illustrate this by quantifying somatic growth rate TPCs for three populations of Daphnia magna where population growth scales linearly with proportional somatic growth. For absolute somatic growth, the northern population outperformed the two more southern populations across temperatures, and more so at higher temperatures, consistent with adaptation to seasonality. In contrast, for the proportional somatic growth TPCs, and hence population growth rate, TPCs tended to converge towards the highest temperatures. Thus, if the northern population pays an ecological mortality cost of rapid growth in the wild, this may create crossing population growth TPCs consistent with adaptation to temperature. Future studies within this field should be more explicit in how they extrapolate from somatic growth in the lab to fitness in the wild. [ABSTRACT FROM AUTHOR]

Ecological modeling refers to the construction and analysis of mathematical models aimed at understanding the complexity of ecological processes and at predicting how real ecosystems might evolve. It is a quickly expanding approach boosted by impressive accelerations in the availability of computational resources and environmental databases. In the light of foreseeing the effect of climate change on forest ecosystems, the branch of ecological modeling focusing on species distribution models (SDMs) has become widely used to estimate indices of habitat suitability and to forecast future tree distributions. However, SDMs are usually informed based solely on environmental data without any reference to the genetic makeup underlying responses to the environment, the possibility of exchanging variants helping to persist in situ, or the capacity to chase suitable conditions elsewhere. Among the main evolutionary processes that may complement forecasts of range shifts are local adaptation and gene flow, i.e., the occurrence of genetic variants conferring a population the optimal fitness in its own habitat and the exchange of adaptive alleles between populations. Local adaptation and gene flow could be described by indices of genetic diversity and structure, genetic load, genomic offset, and an admixture of genetic lineages. Here, we advocate for the development of a new analytical approach integrating environmental and genomic information when projecting tree distributions across space and time. To this aim, we first provide a literature review on the use of genetics when modeling intraspecific responses to the environment, and we then discuss the potential improvements and drawbacks deriving from the inclusion of genomic data into the current SDM framework. Finally, we speculate about the potential impacts of genomic-informed predictions in the context of forest conservation and provide a synthetic framework for developing future forest management strategies. [ABSTRACT FROM AUTHOR]

Phenotypic variations between populations often correlate with climatic variables. Determining the presence of phenotypic plasticity and local adaptation of a species to different environments over a large spatial scale can provide insight on the persistence of a species across its range. Amphibians, and in particular their larvae, are good models for studies of phenotypic variation as they are especially sensitive to their immediate environment. Few studies have attempted to determine the mechanisms that drive phenotypic variation between populations of a single amphibian species over a large spatial scale especially across contrasting climatic regimes. The African clawed frog, Xenopus laevis, occurs in two regions with contrasting rainfall regimes in southern Africa. We hypothesised that the phenotypic variation of life-history traits of X. laevis tadpoles emerges from a combination of plastic and genetic responses. We predicted that plasticity would allow the development of tadpoles from both regions in each environment. We also predicted that local adaptation of larval traits would drive the differentiation of reaction norms between populations and lower survival in tadpoles reared away from their home environment. We measured growth, time to metamorphosis, and survival in a reciprocal transplant experiment using outdoor mesocosms. Supporting our prediction, we found that the measured variation of all traits was explained by both adaptation and plasticity. However, the reaction norms differed between populations suggesting adaptive and asymmetric plasticity. All tadpoles experienced lower survival when translocated, but only translocated tadpoles from the winter rainfall region matched survival of local tadpoles. This has implications for the dynamics of translocated X. laevis into novel environments, especially from the winter rainfall region. Our discovery of their asymmetric capacity to overcome novel environmental conditions by phenotypic plasticity alone provides insight into their invasion success. [ABSTRACT FROM AUTHOR]

To overcome the multiple challenges currently faced by agriculture, such as climate change and soil deterioration, more efficient plant breeding strategies are required. Genomic selection (GS) is crucial for the genetic improvement of quantitative traits, as it can increase selection intensity, shorten the generation interval, and improve selection accuracy for traits that are difficult to phenotype. Tropical perennial crops and plantation trees are of major economic importance and have consequently been the subject of many GS articles. In this review, we discuss the factors that affect GS accuracy (statistical models, linkage disequilibrium, information concerning markers, relatedness between training and target populations, the size of the training population, and trait heritability) and the genetic gain expected in these species. The impact of GS will be particularly strong in tropical perennial crops and plantation trees as they have long breeding cycles and constrained selection intensity. Future GS prospects are also discussed. High-throughput phenotyping will allow constructing of large training populations and implementing of phenomic selection. Optimized modeling is needed for longitudinal traits and multi-environment trials. The use of multi-omics, haploblocks, and structural variants will enable going beyond single-locus genotype data. Innovative statistical approaches, like artificial neural networks, are expected to efficiently handle the increasing amounts of heterogeneous multi-scale data. Targeted recombinations on sites identified from profiles of marker effects have the potential to further increase genetic gain. GS can also aid re-domestication and introgression breeding. Finally, GS consortia will play an important role in making the best of these opportunities. [ABSTRACT FROM AUTHOR]

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.

The incidence and causality of inverse size‐dependent phenology was investigated for spruce budworm, Choristoneura fumiferana (Clemens) (Lepidoptera: Tortricidae), in part due to large sample size [>22000 feral females with known body size (wing area) and timing of emergence/occurrence]. Data collected in three Canadian provinces (New Brunswick, Nova Scotia, Quebec) between 1976 and 2019 included a wide array of sampling procedures grouped along gradients of reproductive classes. (1) For resident females of local origin (collected as pupae and allowed to emerge in the laboratory), body size declined over time at seven of seven sites, indicative of inverse size‐dependent timing of emergence. (2) Females foraging on trees (collected by fogging host trees or with sweep nets) exhibited declines in body size over time at five of five sites. (3) For behaviorally active females collected at traps (malaise, light, and canopy traps), inverse size‐dependent phenology of flight was observed at 20 of 23 combination of trap types/sites; partition of variance indicated limited variation in body size as a function of trap type, thus all inflight females were pooled in subsequent analyses. (4) In contrast to other sampling procedures, dead females collected on drop trays exhibited size‐dependent timing of mortality at only one of five sites. The article includes first body size measurements of migrant females captured in the troposphere with a kite balloon; as with other sampling procedures, body size decreased during the interval of sampling. Ongoing studies combining measurements of body size and dry weight of females (wing load) aim at inferring consequences of inverse size‐dependent phenology on reproduction and migration of budworms, including linkages with population dynamics. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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.

Predicting complex species‐environment interactions is crucial for guiding conservation and mitigation strategies in a dynamically changing world. Phenotypic plasticity is a mechanism of trait variation that determines how individuals and populations adapt to changing and novel environments. For individuals, the effects of phenotypic plasticity can be quantified by measuring environment–trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations. The assumption that environment–trait relationships validated for individuals indicate how populations respond to environmental change is commonly made without sufficient justification. Here we derive a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics. Applying the framework to the classical example of Nicholson's blowflies, we show how seemingly sensible predictions made from environment–trait relationships do not generalise to population responses. As a consequence, trait‐based analyses that do not incorporate population feedbacks risk mischaracterising the effect of environmental change on populations. [ABSTRACT FROM AUTHOR]

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.

Dispersal is a central determinant of spatial dynamics in communities and ecosystems, and various ecological factors can shape the evolution of constitutive and plastic dispersal behaviours. One important driver of dispersal plasticity is the biotic environment. Parasites, for example, influence the internal condition of infected hosts and define external patch quality. Thus, state‐dependent dispersal may be determined by infection status and context‐dependent dispersal by the abundance of infected hosts in the population. A prerequisite for such dispersal plasticity to evolve is a genetic basis on which natural selection can act. Using interconnected microcosms, we investigated dispersal in experimental populations of the freshwater protist Paramecium caudatum in response to the bacterial parasite Holospora undulata. For a collection of 20 natural host strains, we found substantial variation in constitutive dispersal and to a lesser degree in dispersal plasticity. First, infection tended to increase or decrease dispersal relative to uninfected controls, depending on strain identity, indicative of state‐dependent dispersal plasticity. Infection additionally decreased host swimming speed compared to the uninfected counterparts. Second, for certain strains, there was a weak negative association between dispersal and infection prevalence, such that uninfected hosts dispersed less when infection was more frequent in the population, indicating context‐dependent dispersal plasticity. Future experiments may test whether the observed differences in dispersal plasticity are sufficiently strong to be picked up by natural selection. The evolution of dispersal plasticity as a strategy to mitigate parasite effects spatially may have important implications for epidemiological dynamics. [ABSTRACT FROM AUTHOR]

• Heat tolerance is not factored into the objectives of most dairy breeding programs. • Reaction norm functions offer an option to quantify and breed for heat tolerance. • Slope of the reaction norm can be used as a measure of heat tolerance. • Heat tolerance capacity is negatively correlated to milk production potential. • Simultaneous breeding for heat tolerance and milk production improves productivity. 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 < 0.05). Slope at THI 80 had high (0.64–0.71) negative correlations with average daily milk yield, revealing that high-producing cows are more vulnerable to heat stress and vice versa. A high (0.63–0.74) positive correlation was observed between Absolute and average milk yield at THI 80. This implied that low milk-producing cows have a more stable milk production under heat-stress conditions and vice versa. The study demonstrated that the slope of the reaction norms and its absolute value can effectively measure the resilience of crossbred dairy cattle to varying heat load conditions. The implications of these findings are valuable in improving the heat tolerance of livestock species through genetic selection. [ABSTRACT FROM AUTHOR]

Populations adapt to novel environmental conditions by genetic changes or phenotypic plasticity. Plastic responses are generally faster and can buffer fitness losses under variable conditions. Plasticity is typically modeled as random noise and linear reaction norms that assume simple one‐to‐one genotype–phenotype maps and no limits to the phenotypic response. Most studies on plasticity have focused on its effect on population viability. However, it is not clear, whether the advantage of plasticity depends solely on environmental fluctuations or also on the genetic and demographic properties (life histories) of populations. Here we present an individual‐based model and study the relative importance of adaptive and nonadaptive plasticity for populations of sexual species with different life histories experiencing directional stochastic climate change. Environmental fluctuations were simulated using differentially autocorrelated climatic stochasticity or noise color, and scenarios of directional climate change. Nonadaptive plasticity was simulated as a random environmental effect on trait development, while adaptive plasticity as a linear, saturating, or sinusoidal reaction norm. The last two imposed limits to the plastic response and emphasized flexible interactions of the genotype with the environment. Interestingly, this assumption led to (a) smaller phenotypic than genotypic variance in the population (many‐to‐one genotype–phenotype map) and the coexistence of polymorphisms, and (b) the maintenance of higher genetic variation—compared to linear reaction norms and genetic determinism—even when the population was exposed to a constant environment for several generations. Limits to plasticity led to genetic accommodation, when costs were negligible, and to the appearance of cryptic variation when limits were exceeded. We found that adaptive plasticity promoted population persistence under red environmental noise and was particularly important for life histories with low fecundity. Populations producing more offspring could cope with environmental fluctuations solely by genetic changes or random plasticity, unless environmental change was too fast. [ABSTRACT FROM AUTHOR]

Aim: The few fish species able to reproduce across wide osmotic ranges either plastically acclimate sperm performance to, or are locally adapted to, different salinities. The invasive round goby (Neogobius melanostomus) is spreading in Eurasia and the Americas, into both fresh and brackish water. We aim to understand if reproduction in different salinities is affected by an ability to acclimate. Location: Brackish and freshwater systems of northern Europe and the Baltic Sea. Methods: We cross‐exposed round gobies of freshwater and brackish origin to 0 and 16 practical salinity units (PSU), and the fish were given nest boxes in which to spawn. After 4 weeks, we measured their sperm performance in both 0 and 16 PSU; fertilization success of each egg clutch was measured through visual analysis of eggs. Clutches were split and allowed to develop in both 0 and 16 PSU salinity, and reproductive success (zygote development) was measured 20 ± 1 days later. Responses were analysed using generalized mixed models. Results: After a month, the fish showed no plasticity in sperm performance to their acclimation salinity, regardless of their origin. Sperm velocity was highest in the salinity similar to the males' origin. Significantly lower fertilization success was measured for individuals that reproduced outside their salinity of origin despite recurring spawning events in all treatment groups. Among fertilized eggs, zygote development was similar regardless of salinity treatment of either eggs or parents. Main Conclusions: Short‐term acclimation to new salinities does not affect sperm performance in the round goby. Alternative hypotheses such as local adaption should be further investigated. Limits to the species' reproductive success, and therefore invasion processes, are likely dependent on environment‐phenotype matches. Fish of brackish origin spawned successfully in freshwater, pointing to an increased risk of introducing populations of brackish origin into freshwater. [ABSTRACT FROM AUTHOR]

Quantifying thermal performance curves (TPCs) for biological rates has many applications to important problems such as predicting responses of biological systems—from individuals to communities—to directional climate change or climatic fluctuations.Current software tools for fitting TPC models to data are not adequate for dealing with the immense size of new datasets that are increasingly becoming available. We require tools capable of tackling this issue in a simple, reproducible and accessible way.We present a new, reproducible pipeline in r that allows for relatively simple fitting of 24 different TPC models using nonlinear least squares (NLLS) regression. The pipeline consists of two packages—rTPC and nls.multstart—that provide functions which conveniently address common problems with NLLS fitting such as the NLLS parameter starting values problem. rTPC also includes functions to set starting values, estimate key TPC parameters and calculate uncertainty around parameter estimates as well as the fitted model as a whole.We demonstrate how this pipeline can be combined with other packages in r to robustly and reproducibly fit multiple mathematical models to multiple TPC datasets at once. In addition, we show how model selection or averaging, weighted model fitting and bootstrapping can be easily implemented within the pipeline.This new pipeline provides a flexible and reproducible approach that makes the challenging task of fitting multiple TPC models to data accessible to a wide range of users across ecology and evolution. [ABSTRACT FROM AUTHOR]

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.

Many species cope with heterogeneous environments through adaptive phenotypic plasticity, and plasticity of body colour is a widely used means of minimizing predation risk. Pupal colour in many butterflies is a plastic trait sensitive to pupation substrate, with green and brown pupae primarily formed on leaf and off-leaf substrates respectively. This is thought to be an example of adaptive phenotypic plasticity because the green and brown pupae are better camouflaged against their respective backgrounds. We tested whether pupal 'spots'—paired circular markings on the anterior abdominal pupal segments of many butterflies—are also phenotypically plastic. Using experiments on the tropical satyrine butterfly Mycalesis mineus, we confirm that pupal spot size is plastic. Because it is known that pupation substrate influences pupal colour in this species, we tested whether substrate also influences pupal spot size. Further, we explored whether there was a correlation between pupal colour and spot size. We tested the effects of pupation substrate and pupal colour on both absolute spot size and spot size relative to body size. Pupal spot size (absolute and relative) was correlated with both pupal colour and pupation substrate. Brown pupae had larger spots, and green pupae formed off-leaf had intermediate sized spots compared to green pupae formed on leaves and brown pupae, the latter of which always formed off-leaf. Thus, the reaction norm of pupal spot size is partially coupled with both pupal colour and pupation substrate in this species. Since pupation substrate in turn influences pupal colour, the correlated traits of pupal colour and pupal spot could comprise a single functional suite, suggesting a developmental link. We speculate that pupal spots may function against predation, but further studies are needed to understand their possible adaptive significance. [ABSTRACT FROM AUTHOR]

Developing organisms typically mature earlier and at larger sizes in favorable growth conditions, while in rarer cases, maturity is delayed. The rarer reaction norm is easily accommodated by general life history models, whereas the common pattern is not. Theory suggests that a solution to this paradox lies in the existence of critical size thresholds at which maturation or metamorphosis can commence, and in the evolution of these threshold sizes in response to environmental variation. For example, ephemeral environments might favor the evolution of smaller thresholds, enabling earlier maturation. The threshold model makes two unique and untested predictions. First, reaction norms for age and size should steepen, and even change sign, with decreases in threshold size; second, food reductions at sizes below the threshold should delay maturation, while those occurring after the threshold should accelerate maturation. We test these predictions through food manipulations in five damselfly species that theory suggests should differ in threshold size. The results provide strong support for the threshold model's predictions. In all species, early food reductions delayed maturation, while late reductions accelerated maturation. Reaction norms were steeper, and the effect of food reductions changed from decelerating to accelerating at a much smaller size in species from ephemeral habitats. These results support the view that developmental thresholds can account for the widespread observation of negative correlations between age and size at maturity. Moreover, evolution of the threshold appears to be both predictable and central to the observed diversity of reaction norms for age and size at maturity. [ABSTRACT FROM AUTHOR]

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.

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. [ABSTRACT FROM AUTHOR]

Expression of adaptive reaction norms of life-history traits to spatio-temporal variation in food availability is crucial for individual fitness. Yet little is known about the neural signalling mechanisms underlying these reaction norms. Previous studies suggest a role for the dopamine system in regulating behavioural and morphological responses to food across a wide range of taxa. We tested whether this neural signalling system also regulates life-history reaction norms by exposing the zooplankton Daphnia magna to both dopamine and the dopamine reuptake inhibitor bupropion, an antidepressant that enters aquatic environments via various pathways. We recorded a range of life-history traits across two food levels. Both treatments induced changes to the life-history reaction norm slopes. These were due to the effects of the treatments being more pronounced at restricted food ration, where controls had lower somatic growth rates, higher age and larger size at maturation. This translated into a higher population growth rate (r) of dopamine and bupropion treatments when food was restricted. Our findings show that the dopamine system is an important regulatory mechanism underlying life-history trait responses to food abundance and that bupropion can strongly influence the life history of aquatic species such as D. magna. We discuss why D. magna do not evolve towards higher endogenous dopamine levels despite the apparent fitness benefits. [ABSTRACT FROM AUTHOR]

All known vertebrate clones have originated from hybridization events and some have produced distinct evolutionary lineages via hybrid speciation. Amazon mollies (Poecilia formosa) present an excellent study system to investigate how clonal species have adapted to heterogeneous environments because they are the product of a single hybridization event between male sailfin mollies (Poecilia latipinna) and female Atlantic mollies (Poecilia mexicana). Here, we ask whether the hybrid species differs from the combination of its parental species' genes in its plastic response to different environments. Using a three‐way factorial design, we exposed neonates produced by Amazon mollies and reciprocal F1 hybrid crosses to different thermal (24°C and 29°C) and salinity (0/2, 12, and 20 ppt) regimes. We measured various ontogenetic and life history characteristics across the life span of females. Our major results were as follows: (1) Reaction norms of growth and maturation to temperature and salinity are quite similar between the two hybrid crosses; (2) Amazon molly reaction norms were qualitatively different than the P. latipinna male and P. mexicana female (L×M) hybrids for the ontogenetic variables; (3) Amazon molly reaction norms in reproductive traits were also quite different from L×M hybrids; and (4) The reaction norms of net fertility were very different between Amazon mollies and L×M hybrids. We conclude that best locale for Amazon mollies is not the best locale for hybrids, which suggests that Amazon mollies are not just an unmodified mix of parental genes but instead have adapted to the variable environments in which they are found. Hybridization resulting in asexuality may represent an underappreciated mechanism of speciation because the unlikely events required to produce such hybrids rarely occur and is dependent upon the genetic distance between parental species. [ABSTRACT FROM AUTHOR]

Alexandrium catenella , the main species associated with harmful algal blooms, has progressively increased its distribution through one of the most extensive and highly variable fjord systems in the world. In order to understand this successful expansion, we evaluated the effects of different salinities, light intensity, temperatures, nitrogen (N) forms and nitrogen/phosphate (N:P) ratio levels on the growth performance, using clones isolated from different locations across its wide geographic distribution. Results showed that the growth responses were plastic and, in some cases, different reaction norms among clones were observed. Despite plasticity, the optimal growth of A. catenella (i.e. highest growth rate and highest maximal cells density) was reached within a narrow thermal range (12–15°C), while salinity (20–30 PSU) and light intensity (20–120 μmol m−2 s−1) ranges were wider. These results are partially consistent with the highest cell densities recorded in the field. Furthermore, optimal growth was reached using reduced forms of nitrogen (i.e. urea and NH4+) and in unbalanced N:P ratios (18:1 and 30:1). These characteristics likely allow A. catenella to grow in highly variable environmental conditions and might partly explain the recent expansion of this species. [ABSTRACT FROM AUTHOR]

Adaptive integration of life history and behaviour is expected to result in variation in the pace‐of‐life. Previous work focused on whether 'risky' phenotypes live fast but die young, but reported conflicting support. We posit that individuals exhibiting risky phenotypes may alternatively invest heavily in early‐life reproduction but consequently suffer greater reproductive senescence.We used a 7‐year longitudinal dataset with >1,200 breeding records of >800 female great tits assayed annually for exploratory behaviour to test whether within‐individual age dependency of reproduction varied with exploratory behaviour. We controlled for biasing effects of selective (dis)appearance and within‐individual behavioural plasticity.Slower and faster explorers produced moderate‐sized clutches when young; faster explorers subsequently showed an increase in clutch size that diminished with age (with moderate support for declines when old), whereas slower explorers produced moderate‐sized clutches throughout their lives. There was some evidence that the same pattern characterized annual fledgling success, if so, unpredictable environmental effects diluted personality‐related differences in this downstream reproductive trait.Support for age‐related selective appearance was apparent, but only when failing to appreciate within‐individual plasticity in reproduction and behaviour.Our study identifies within‐individual age‐dependent reproduction, and reproductive senescence, as key components of life‐history strategies that vary between individuals differing in risky behaviour. Future research should thus incorporate age‐dependent reproduction in pace‐of‐life studies. [ABSTRACT FROM AUTHOR]

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.