Reaction Norms Research Articles

Re-Equilibrating Sex Ratios: Adjustment of Reaction Norms in Species With Temperature-Dependent Sex Determination.

Fisher's general principle for sex allocation holds that population sex ratios are typically balanced because parents producing the rare sex are benefited and the rare sex alternates over time. In species that have temperature-dependent sex determination (TSD), thermal reaction norms need to be adjusted at the population level to avoid extremely biased sex ratios and extinction. Extant species with TSD experienced drastic climatic changes in the geological past and must necessarily have mechanisms of adaptation. I propose here a conceptual framework to explain how TSD curves could be adjusted by means of natural selection, based on Fisher's equilibrium sex-ratio principle. Through a process that alternatively favors mothers that tend to produce the rare sex under new temperatures, sex ratios eventually return toward a theoretical equilibrium. Prerequisites for this model are variability among mothers in the tendency to produce a particular sex at a given temperature (i.e., variability in the thermal reaction norm), inheritance of this trend, and higher fitness of the rare sex. This straightforward mechanism could facilitate thermal adaptation in species with TSD over multiple generations.

Developmental reaction norms vary among families of lizards in response to multivariate nest environments

Developmental plasticity is the capacity of a single genotype to express multiple phenotypes in response to different early‐life environments. Such responses are defined by reaction norms, which may vary among individuals or populations. Variation in developmental reaction norms allows natural selection to operate on plasticity and is rarely examined in vertebrates. We quantified variation in embryonic developmental plasticity within and between populations using the brown anole lizard. We captured lizards from two islands in the Matanzas River (Florida, USA) and incubated their eggs under one of two multivariate treatments that mimicked the temperature, moisture and substrates of nest sites in either a shaded or open habitat. We measured hatchling morphology, performance, and physiology to quantify variation in family‐level reaction norms. We observed evidence of family‐level variation in reaction norms for morphology but not for performance or physiology, indicating an opportunity for natural selection to shape plasticity in hatchling body size. Overall, the results indicate that multiple abiotic conditions in natural nests combine to increase or reduce phenotypic variation, and that family‐level variation in reaction norms provides a potential for natural selection to shape plasticity.

Redefining the accumulated temperature index for accurate prediction of rice flowering time in diverse environments.

Accurate prediction of flowering time across diverse environments is crucial for effective crop management and breeding. While the accumulated temperature index (ATI) is widely used as an indicator for estimating flowering time, its traditional definition lacks systematic evaluation and genetic basis understanding. Here, using data from 422 rice hybrids across 47 locations, we identified the optimal ATI calculation window as 1 day after sowing to 26 days before flowering. Based on this redefined ATI, we developed a single-parameter model that outperforms the state-of-the-art reaction norm index model in both accuracy and stability, especially with limited training data. We identified 10 loci significantly associated with ATI variation, including two near known flowering time genes and four linked to ecotype differentiation. To enhance practical utility, we developed an efficient flowering time prediction kit using 28 functionally relevant markers, complemented by a user-friendly online tool (http://xielab.hzau.edu.cn/ATI). Our approach can be easily applied to other crops, as ATI is commonly used across various agricultural systems.

Genetic determinism of sensitivity to environmental challenges using daily feed intake records in three lines of pigs.

In pig breeding, environmental challenges can affect the welfare and productivity of animals. Resilient animals have the capacity to be minimally affected by these environmental challenges. Understanding the genetic basis of sensitivity to these environmental challenges is crucial for selecting more resilient animals, thereby enhancing welfare and productivity. The aims of this study were to: (1) estimate the probability of the occurrence of an unrecorded environmental challenge at a given day using daily feed intake (DFI) data, and (2) evaluate the genetic determinism of environmental sensitivity in three pig lines bred in real selection conditions. Data comprised of 100,799, 186,247, and 304,826 DFI records from 1,618, 2,517, and 3,788 Landrace (LA), Large White (LW) and Piétrain (PI) male pigs, respectively. The pedigree included 3,730, 5,649, and 9,293 animals for LA, LW, and PI, respectively. The probabilities of the occurrence of an unrecorded environmental challenge at a given day were estimated via a mixture model. The probabilities (p) of being "high CV days" were then taken as reference and used in genetic analysis as an environmental descriptor to describe the environment. DFI records were analysed using two linear models: a linear reaction norm animal model (RNAM) and the animal model. (Co)variance components were estimated using average-information restricted maximum likelihood (AI-REML). The means of the probabilities of the occurrence of an environmental challenge for LA, LW, and PI were 0.24, 0.10, and 0.22, respectively, indicating that the probability of an environmental challenge was low for most of the days. The genetic correlations between the intercept and the slope obtained from the RNAM for LA, LW, PI were -0.52, 0.06, and -0.36, respectively. These findings suggest that selecting hypothetically for decreased DFI in non-stressful conditions would result in pigs with increased DFI in stressful conditions in the LA and PI lines, whereas it would have a minor impact on the environmental sensitivity of LW. The proportion of resilient animals for LA, LW, and PI was 75.0, 74.2, and 72.2%, respectively, implying that most of the animals were resilient. The study demonstrated that the slope of DFI is heritable and can effectively be used as an indicator of sensitivity to environmental challenges. These results are valuable in improving the resilience of livestock species to environmental challenges through genetic selection.

Developmental Thermal Reaction Norms of Leatherback Marine Turtles at Nesting Beaches.

Accurate scientific information is critical for undertaking appropriate conservation and management practices for imperiled species. One source of concern is that research findings might vary for non-biological reasons, including experimental design and analytical methods. To illustrate, we provide detailed modern analysis of reproductive data for leatherback turtles (Dermochelys coriacea). This species exhibits significant fluctuations in nesting densities across different regions, possibly driven by local rather than global factors. Key factors influencing these changes include hatching success and sex determination, both sensitive to incubation temperatures (e.g., lower temperatures yield more males, higher temperatures yield females). This study updates the understanding of temperature-dependent sex determination (TSD) in this species using Bayesian statistics. Growth rate data from the West Pacific and Northwest Atlantic populations show a similar, monotone increase with temperature, affirming the reliability of the models used. The analysis of TSD patterns indicates that observed differences are more likely due to study methodologies and clutch-specific factors rather than regional differences. These findings challenge previous assumptions, showing that leatherback TSD does not conform to a simple on/off pattern but is influenced by multiple, interacting environmental factors. Population dynamics models must account for these complexities, recognizing that both sex ratios and hatching success are critical to understand the rapid changes observed in some leatherback populations.

Genetic and Environmental Patterns Underlying Phenotypic Plasticity in Flowering Time and Plant Height in Sorghum.

Phenotypic plasticity is the property of a genotype to produce different phenotypes under different environmental conditions. Understanding genetic and environmental factors behind phenotypic plasticity helps answer some longstanding biology questions and improve phenotype prediction. In this study, we investigated the phenotypic plasticity of flowering time and plant height with a set of diverse sorghum lines evaluated across 14 natural field environments. An environmental index was identified to quantitatively connect the environments. Reaction norms were then obtained with the identified indices for genetic dissection of phenotypic plasticity and performance prediction. Genome-wide association studies (GWAS) detected different sets of loci for reaction-norm parameters (intercept and slope), including 10 new genomic regions in addition to known maturity (Ma1) and dwarfing genes (Dw1, Dw2, Dw3, Dw4 and qHT7.1). Cross-validations under multiple scenarios showed promising results in predicting diverse germplasm in dynamic environments. Additional experiments conducted at four new environments, including one from a site outside of the geographical region of the initial environments, further validated the predictions. Our findings indicate that identifying the environmental index enriches our understanding of gene-environmental interplay underlying phenotypic plasticity, and that genomic prediction with the environmental dimension facilitates prediction-guided breeding for future environments.

Larval growth rate is not a major determinant of adult wing shape and eyespot size in the seasonally polyphenic butterfly Melanitis leda.

Insects often show adaptive phenotypic plasticity where environmental cues during early stages are used to produce a phenotype that matches the environment experienced by adults. Many tropical satyrine butterflies (Nymphalidae: Satyrinae) are seasonally polyphenic and produce distinct wet- and dry-season form adults, providing tight environment-phenotype matching in seasonal environments. In studied Mycalesina butterflies, dry-season forms can be induced in the laboratory by growing larvae at low temperatures or on poor food quality. Since both these factors also tend to reduce larval growth rate, larval growth rate may be an internal cue that translates the environmental cues into the expression of phenotypes. If this is the case, we predict that slower-growing larvae would be more likely to develop a dry-season phenotype. We performed the first experimental study on seasonal polyphenism of a butterfly in the tribe Melanitini. We measured both larval growth rate and adult phenotype (eyespot size and wing shape) of common evening brown butterflies (Melanitis leda), reared at various temperatures and on various host-plant species. We constructed provisional reaction norms, and tested the hypothesis that growth rate mediates between external cues and adult phenotype. Reaction norms were similar to those found in Mycalesina butterflies. We found that both among and within treatments, larvae with lower growth rates (low temperature, particular host plants) were more likely to develop dry-season phenotypes (small eyespots, falcate wing tips). However, among temperature treatments, similar growth rates could lead to very different wing phenotypes, and within treatments the relationships were weak. Moreover, males and females responded differently, and eyespot size and wing shape were not strongly correlated with each other. Overall, larval growth rate seems to be weakly related to eyespot size and wing shape, indicating that seasonal plasticity in M. leda is primarily mediated by other mechanisms.

Selection for heat tolerance in Atlantic salmon (Salmo salar) using reaction norms

Selection for heat tolerance is a key strategy for aquaculture to cope with the effects of climate change. Different alternatives exist to select aquatic species for heat tolerance. Here, we investigated the feasibility of applying reaction norms in summer growth of Atlantic salmon (Salmo salar) naturally exposed to diverse heat loads as a strategy to genetically improve heat tolerance. For this, summer growth of 40,044 fish from 2685 families and 21 cohorts, distributed across 14 years and 2 sites in Tasmania, was analysed under different reaction norm models (RNM), using a function of the average daily seawater temperature during the summer period (ranging from 12.8 to 19.7 °C) as the environment descriptor (heat load). RNM results unravelled substantial genotype by environment interaction for summer growth, specially between intermediate and high heat loads. Quadratic and spline linear-linear RNM outperformed linear RNM, showing a non-linear behaviour of the additive genetic effect on summer growth across different heat load gradients. The predictive ability of breeding values from RNM revealed opportunities to select for heat tolerance either for the highest heat load or for sensitivity to thermal variation (slope of RNM). Genomic-based breeding values presented better statistical properties than pedigree-based breeding values, highlighting the importance of using genomic information for a better predictive ability of heat tolerance. Genome-wide association analysis reinforced the polygenic nature of heat tolerance, indicating genomic selection as a more effective strategy to improve heat tolerance in Atlantic salmon, compared to strategies targeting specific genomic regions/genes.

Analysis of resting status reveals distinct elevational variation in metabolisms of lizards.

Animals spend a considerable proportion of their life span at rest. However, resting status has often been overlooked when investigating how species respond to environmental conditions. This may induce a large bias in understanding the local adaptation of species across environmental gradients and their vulnerability to potential environmental change. Here, we conducted an empirical study on montane agamid lizards, combined with mechanistic modeling, to compare elevational variations in body temperature and metabolisms (cumulative digestion and maintenance cost) between resting and active status. Our study on three populations of an agamid lizard along an elevational gradient revealed a trend of decreasing body temperature toward higher elevations, the main contributor of which was resting status of the lizards. Using population-specific reaction norms, we predicted greater elevational variation in hourly and cumulative digestion for resting lizards than for active lizards. Climate-change impacts, estimated as the change in cumulative digestion, also show greater elevational variation when resting status is factored into the analysis. Further, our global analysis of 98 agamid species revealed that in about half of their combined distributional range, the contribution of resting status in determining the elevational variation in cumulative digestion and maintenance cost of lizards was greater than the contribution made by a lizard's active status. Our study highlights the importance of considering resting status when investigating how species respond to environmental conditions, especially for those distributed over tropical and subtropical mountain areas.

Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions

Accurate genomic predictions of breeding values for traits included in the selection indexes are paramount for optimizing genetic progress in populations under selection. The size of the reference populations is a major factor influencing the accuracy of genomic predictions, which is even more important for lowly-heritable traits such as fertility and reproduction indicators. Combining data from different geographical regions or countries can be beneficial for genomic prediction of these lowly heritable traits. Therefore, the objectives of this study were to: 1) evaluate the benefits of performing across-regional genomic evaluations for reproduction traits in Chinese Holstein cattle; and, 2) assess the feasibility of validating genomic predictions across environments based on reaction norm models (RNM) and the Linear Regression (LR) method after accounting for genotype-by-environment interactions. Phenotypic records from 194,574 cows collected across 47 farms located in 2 regions of China were used for this study. The reference and validation populations were defined based on birth year for applying the LR validation method. The traits evaluated included: interval from first to last insemination (IFL), conception rate at the first insemination (CR_f), and number of inseminations (NS) recorded in heifers and first-parity cows. The results indicated that combining data from different regions resulted in greater genomic prediction accuracies compared with using data from single regions, with increases ranging from 2.74% to 93.81%. This improvement was particularly notable for the region with the least amount of available data, where the increases ranged from 26.49% to 93.81%. Furthermore, the predictive abilities could be validated for all studied traits based on the LR method across different environments when fitting RNM. The prediction accuracies and bias of genomic breeding values based on RNM were better than regular single-trait animal models in extreme climatic conditions for IFL and NS, whereas limited increases in predictive abilities were observed for CR_f. Across-regional genomic prediction by RNM can account for genotype-by-environment interactions, potentially increase the accuracy of genomic prediction, and predict the performances of individuals in the environments with limited phenotypic data available.

Influence of different environmental challenges on the expression of reproductive traits in Holstein cattle in Southern Brazil.

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.

Functional Activity of the Antioxidant System of Artemisia Genus Plants in the Republic of Buryatia (Russia) and Its Significance in Plant Adaptation.

Plants are sessile organisms and any changes in environmental factors activate various responses and defense mechanisms. Artemisia plants widely inhabit harsh conditions of arid and semiarid ecosystems. Using two species-a subshrub, Artemisia frigida, and an annual-biennial herb, Artemisia scoparia-the functioning of the antioxidant system of plants in semiarid territories have been examined. The activity of enzymatic antioxidants and the content of non-enzymatic antioxidants in both species as well as the antiradical activity of their extracts have been shown. Although the plants were collected in areas differing in moisture supply, the activity of enzymatic antioxidants and the content of non-enzymatic antioxidants corresponds to their physiological level, within the range of the norm of reaction, in wormwood. Consequently, conditions of differing moisture deficiency do not cause a specific biochemical response at the level of the antioxidant system in the studied species, which confirms their adaptability to these conditions. Meanwhile, A. frigida plants show greater morphological and biochemical plasticity than A. scoparia under changing growth conditions. Both species contain tissue monoterpenoids and sesquiterpenoids, the emission of which provides additional protection against high temperatures and drought. Their composition and contents of phenolic components illustrates the differences in adaptation between perennial and annual plants.

Phenotypic plasticity of water-related traits reveals boundaries to the adaptive capacity of a dominant European grass species under increased drought

The intensification of droughts due to climate change is a global concern, and many plant species face increasing water deficits. Understanding the role of phenotypic plasticity in plant adaptation to these changing conditions is crucial. This research focuses on Bromopsis erecta, a dominant perennial grass in European and Mediterranean grasslands, to predict its potential adaptation to climate change. We assessed plants from shallow and deep soils (i.e., with contrasting water reserves) of a Mediterranean rangeland in southern France, and tested the effect of six years of experimentally increased summer drought compared to the ambient conditions on plant traits, survival and abundance. In both field and common garden experiments, we measured water-related traits, including static traits under non-limiting water conditions, and dynamic traits, such as rates of trait variation during drought. Trait plasticity was determined as a reaction norm to increasing soil water stress and was tested against changes in B. erecta abundance over the past decade, including the study period. Trait plasticity was detected only for leaf dry matter content (LDMC), revealing that the resource strategy of B. erecta became more conservative over less than a decade with higher LDMC and leaf thickness according to the plant economic spectrum. No plasticity was found for osmotic potential or specific leaf area. The variability of other traits was ascribed to the possible lagging effect of previous water stress and was associated more with soil depth than with previous summer drought intensity. The abundance decline of B. erecta, which dropped from 20 % to around 5 % in shallow soils, was not associated with the plasticity of LDMC but was positively correlated with variations in leaf base membrane damage, meaning unexpectedly, that plants exposed to the most severe summer drought also had the most sensitive leaf base membranes, a possible sign of maladaptive trait plasticity in the population. This key trait response reveals boundaries to the adaptive capacity of this perennial grass to survive pluri-annual drought.

The Genetic Architecture of Arabidopsis thaliana in Response to Native Non-Pathogenic Bacterial Species Revealed by Genome-Wide Association Mapping in Field Conditions

Non-pathogenic bacteria can substantially contribute to plant health by mobilizing and supplying nutrients, providing protection against pathogens, and alleviating abiotic stresses. However, the number of genome-wide association studies reporting the genetic architecture of the response to individual members of the beneficial microbiota remains limited. In this study, we established a genome-wide association study under field conditions to estimate the level of genetic variation and the underlying genetic architecture among 162 accessions of Arabidopsis thaliana originating from 54 natural populations in the southwest of France in response to 13 strains of seven of the most abundant and prevalent non-pathogenic bacterial species isolated from the leaf compartment of A. thaliana in the same geographical region. Using a high-throughput phenotyping methodology to score vegetative growth-related traits, extensive genetic variation was detected among A. thaliana accessions in response to these leaf bacteria, at both the species and strain levels. The presence of crossing reaction norms between each strain and the mock treatment indicates that declaring a strain as a plant growth-promoting bacterium is highly dependent on the host genotype tested. In line with the strong genotype-by-genotype interactions, we detected a complex and highly flexible genetic architecture between the 13 strains. Finally, the candidate genes underlying the quantitative trait loci revealed significant enrichment in several biological pathways, including cell, secondary metabolism, signaling, and transport. Altogether, plant innate immunity appears as a significant source of natural genetic variation in plant–microbiota interactions and opens new avenues for better understanding the ecologically relevant molecular dialog during plant–microbiota interactions. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Detecting context dependence in the expression of life history trade-offs.

Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general.

A quantitative model of temperature-dependent diapause progression

Winter diapause in insects is commonly terminated through cold exposure, which, like vernalization in plants, prevents development before spring arrives. Currently, quantitative understanding of the temperature dependence of diapause termination is limited, likely because diapause phenotypes are generally cryptic to human eyes. We introduce a methodology to tackle this challenge. By consecutively moving butterfly pupae of the species Pieris napi from several different cold conditions to 20 °C, we show that diapause termination proceeds as a temperature-dependent rate process, with maximal rates at relatively cold temperatures and low rates at warm and extremely cold temperatures. Further, we show that the resulting thermal reaction norm can predict P. napi diapause termination timing under variable temperatures. Last, we show that once diapause is terminated in P. napi, subsequent development follows a typical thermal performance curve, with a maximal development rate at around 31 °C and a minimum at around 2 °C. The sequence of these thermally distinct processes (diapause termination and postdiapause development) facilitates synchronous spring eclosion in nature; cold microclimates where diapause progresses quickly do not promote fast postdiapause development, allowing individuals in warmer winter microclimates to catch up, and vice versa. The unveiling of diapause termination as one temperature-dependent rate process among others promotes a parsimonious, quantitative, and predictive model, wherein winter diapause functions both as an adaptation against premature development during fall and winter and for synchrony in spring.

Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates.

Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well-studied major crops. Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre- and postanthesis maximum temperature, mid-season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well-studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

The genetics of phenotypic plasticity. XVIII. Developmental limits restrict adaptive plasticity.

After environmental change, the trait evolution needed to rescue a population depends on the functional form of the plastic change (reaction norm) of that trait. Nearly all previous models of plasticity evolution for continuous traits have assumed that the functional form is linear, i.e., no limits on the range of plasticity. This paper examines the effect of developmental limits, modeled as a sigmoidal reaction norm, on evolutionary rescue after an abrupt environmental change and the subsequent evolution of plasticity, including genetic assimilation. We examined four different scenarios: (1) developmental limits only, (2) developmental limits plus a cost of plasticity, (3) developmental limits with developmental noise, and (4) developmental limits plus environmental variation. The probability of evolutionary rescue increased with an increase in phenotypic variation allowed by plastic development. With a smaller limit to the range of the plastic phenotype, the evolution of adaptive plasticity was limited, meaning the evolution of non-plastic genes was necessary. The addition of developmental constraints to the model did not speed up genetic assimilation, suggesting new theory is needed to understand empirical observations. The modeling framework presented here could be extended to different ecological and evolutionary conditions, alternative reaction norm shapes, the evolution of additional reaction norm parameters such as the range or the location of the inflection point on the environmental axis, or other function-valued traits.

Thermal plasticity in protective wing pigmentation is modulated by genotype and food availability in an insect model of seasonal polyphenism

Abstract Phenotypic variation in natural populations results from complex interactions between organisms and their changing environments. The environment shapes both phenotypic frequencies (during adaptation) and organismal phenotypes (through phenotypic plasticity). Developmental plasticity, in particular, refers to the phenomenon whereby an organism's phenotype depends on the environmental conditions during development. It can match phenotype to ecological conditions and help organisms to cope with environmental heterogeneity, including differences between alternating seasons. Experimental studies of developmental plasticity often focus on the impact of individual environmental cues and do not take explicit account of genetic variation. In contrast, natural environments are complex, comprising multiple variables with combined effects that are poorly understood and may vary among genotypes. We investigated the effects of multifactorial environments on the development of the seasonally plastic eyespots of Bicyclus anynana butterflies. Eyespot size depends on developmental temperature and is involved in alternative seasonal strategies for predator avoidance. In nature, both temperature and food availability undergo seasonal fluctuations. However, our understanding of how thermal plasticity in eyespot size varies in response to food availability and across genotypes remains limited. To address this, we investigated the combined effects of temperature (T; two levels: 20°C and 27°C) and food availability (N; two levels: control and limited) during development. We examined their impact on wing and eyespot size in adult males and females from multiple genotypes (G; 28 families). We found evidence of thermal and nutritional plasticity and temperature‐by‐nutrition interactions (significant T × N) on the size of eyespots in both sexes. Food limitation resulted in relatively smaller eyespots and tempered the effects of temperature. Additionally, we found differences among families for thermal plasticity (significant G × T effects), but not for nutritional plasticity (non‐significant G × N effects) nor for the combined effects of temperature and food limitation (non‐significant G × T × N effects). Our results reveal the context dependence of thermal plasticity, with the slope of thermal reaction norms varying across genotypes and across nutritional environments. We discuss these results in the light of the ecological significance of pigmentation and the value of considering thermal plasticity in studies of the biological impact of climate change. Read the free Plain Language Summary for this article on the Journal blog.

Strawberry phenotypic plasticity in flowering time is driven by the interaction between genetic loci and temperature.

Flowering time (FT), which determines when fruits or seeds can be harvested, is subject to phenotypic plasticity, that is, the ability of a genotype to display different phenotypes in response to environmental variation. Here, we investigated how the environment affects the genetic architecture of FT in cultivated strawberry (Fragaria × ananassa) and modifies its quantitative trait locus (QTL) effects. To this end, we used a bi-parental segregating population grown for 2 years at widely divergent latitudes (five European countries) and combined climatic variables with genomic data (Affymetrix SNP array). Examination, using different phenological models, of the response of FT to photoperiod, temperature, and global radiation indicated that temperature is the main driver of FT in strawberry. We next characterized in the segregating population the phenotypic plasticity of FT by using three statistical approaches that generated plasticity parameters including reaction norm parameters. We detected 25 FT QTLs summarized as 10 unique QTLs. Mean values and plasticity parameter QTLs were co-localized in three of them, including the major 6D_M QTL whose effect is strongly modulated by temperature. The design and validation of a genetic marker for the 6D_M QTL offers great potential for breeding programs, for example selecting early-flowering strawberry varieties well adapted to different environmental conditions.