Trait Covariation Research Articles

Environmental variation drives the decoupling of leaf and root traits within species along an elevation gradient.

Plant performance is enhanced by balancing above- and below-ground resource uptake through the intraspecific adjustment of leaf and root traits. It is assumed that these organ adjustments are at least partly coordinated, so that analogous leaf and root traits broadly covary. Understanding the extent of such intraspecific leaf-root trait covariation would strongly contribute to our understanding of how plants match above- and below-ground resource use strategies as their environment changes, but comprehensive studies are lacking. We measured analogous leaf and root traits from 11 species, as well as climate, soil and vegetation properties along a 1000-m elevation gradient in the French Alps. We determined how traits varied along the gradient, to what extent this variation was determined by the way different traits respond to environmental cues acting at different spatial scales (i.e. within and between elevations), and whether trait pairs covaried within species. Leaf and root trait patterns strongly diverged: across the 11 species along the gradient, intraspecific leaf trait patterns were largely consistent, whereas root trait patterns were highly idiosyncratic. We also observed that, when compared with leaves, intraspecific variation was greater in root traits, due to the strong effects of the local environment (i.e. at the same elevation), while landscape-level effects (i.e. at different elevations) were minor. Overall, intraspecific trait correlations between analogous leaf and root traits were nearly absent. Our study suggests that environmental gradients at the landscape level, as well as local heterogeneity in soil properties, are the drivers of a strong decoupling between analogous leaf and root traits within species. This decoupling of plant resource acquisition strategies highlights how plants can exhibit diverse whole-plant acclimation strategies to modify above- and below-ground resource uptake, improving their resilience to environmental change.

Leaf morphological traits as adaptations to multiple climate gradients.

Leaf morphological traits vary systematically along climatic gradients. However, recent studies in plant functional ecology have mainly analysed quantitative traits, while numerical models of species distributions and vegetation function have focused on traits associated with resource acquisition; both ignore the wider functional significance of leaf morphology.A dataset comprising 22 leaf morphological traits for 662 woody species from 92 sites, representing all biomes present in China, was subjected to multivariate analysis in order to identify leading dimensions of trait covariation (correspondence analysis), quantify climatic and phylogenetic contributions (canonical correspondence analysis with variation partitioning) and characterise co‐occurring trait syndromes (k‐means clustering) and their climatic preferences.Three axes accounted for >20% of trait variation in both evergreen and deciduous species. Moisture index, precipitation seasonality and growing‐season temperature explained 8%–10% of trait variation; family 15%–32%. Microphyll or larger, mid‐ to dark green leaves with drip tips in wetter climates contrasted with nanophyll or smaller glaucous leaves without drip tips in drier climates. Thick, entire leaves in less seasonal climates contrasted with thin, marginal dissected, aromatic and involute/revolute leaves in more seasonal climates. Thick, involute, hairy leaves in colder climates contrasted with thin leaves with marked surface structures (surface patterning) in warmer climates. Distinctive trait clusters were linked to the driest and most seasonal climates, for example the clustering of picophyll, fleshy and succulent leaves in the driest climates and leptophyll, linear, dissected, revolute or involute and aromatic leaves in regions with highly seasonal rainfall. Several trait clusters co‐occurred in wetter climates, including clusters characterised by microphyll, moderately thick, patent and entire leaves or notophyll, waxy, dark green leaves. Synthesis. The plastic response of size, shape, colour and other leaf morphological traits to climate is muted, thus their apparent shift along climate gradients reflects plant adaptations to environment at a community level as determined by species replacement. Information on leaf morphological traits, widely available in floras, could be used to strengthen predictive models of species distribution and vegetation function.

High intraspecific trait variation results in a resource allocation spectrum of a subtropical pine across an elevational gradient

AbstractAimPlant functional traits are broadly used to quantify and predict impacts of climate change on vegetation. However, high intraspecific trait variation can bias mean values when few measurements are available. Here, we determine the extent of individual leaf trait variation and covariation across a highly heterogeneous environmental gradient for a widely distributed subtropical pine. We demonstrate the implications of trait variation for characterising species by assessing data availability and variability across the Pinus genus.LocationCentral Mountain Range, Taiwan.TaxonPinus taiwanensis Hayata (Pinaceae).MethodsWe measured eight functional traits suggested to reflect plant strategies: needle length, area, thickness, dry and fresh mass, stomatal row density (SD), leaf dry matter content (LDMC) and specific leaf area (SLA). We examined trait variation in response to climatic and physiographic factors across an elevational gradient of 495–3106 m a.s.l. using linear mixed effects models (LMMs). Intraspecific trait covariation was explored using principal component analyses (PCAs) and LMMs. Descriptive statistics were calculated for Pinus records in the global TRY plant trait database.ResultsIntraspecific variability among traits was high (CV 20%–44%) and predictable with elevation (generally p < 0.05, with declining needle size and LDMC with elevation and increasing SD). However, 41%–92% of variance was un‐explained by topography. Sixty‐five percent of variation was explained by two trait covariation axes, with predictable changes with elevation (p < 0.001). Pinus data availability in TRY was low. Across traits, only 12.5%–53% of species had sufficient sample sizes for intraspecific analyses.Main conclusionsWe show substantial trait variation for a single species, here likely driven by temperature differences and additional biotic and abiotic drivers across the elevational range. Improved understanding of the extent and implications of intraspecific variability is necessary for reliable quantifications and predictions of the impacts of environmental change, especially in understudied, hyper‐diverse ecosystems such as tropical forests.

Modeling the Process of Speciation Using a Multiscale Framework Including A Posteriori Error Estimates

This paper concerns the modeling and numerical simulation of the process of speciation. In particular, given conditions for which one or more speciation events within an ecosystem occur, our aim is to develop the necessary modeling and simulation tools. Care is also taken to establish a solid mathematical foundation on which our modeling framework is built. This is the subject of the first half of the paper. The second half is devoted to developing a multiscale framework for eco-evolutionary modeling, where the relevant scales are that of species and individual/population, respectively. The species level model we employ can be considered as an extension of the classical Lotka--Volterra model, where in addition to the species abundance, the model also governs the evolution of the species mean traits and species trait covariances and in this sense generalizes the purely ecological Lotka--Volterra model to an eco-evolutionary model. Although the model thus allows for evolving species, it does not (by construction) allow for the branching of species, i.e., speciation events. The reason for this is related to that of separate scales; the unit of species is too coarse to capture the fine-scale dynamics of a speciation event. Instead, the branching species should be regarded as a population of individuals moving along a selection of trait axes (i.e., trait-space). For this, we employ a trait-specific population density model governing the dynamics of the population density as a function of evolutionary traits. At this scale there is no a priori definition of species, but both species and speciation may be defined a posteriori as, e.g., local maxima and saddle points of the population density, respectively. Hence, a system of interacting species can be described at the species level, while for branching species a population level description is necessary. Our multiscale framework thus consists of coupling the species and population level models where speciation events are detected in advance and then resolved at the population scale until the branching is complete. Moreover, since the population level model is formulated as a PDE, we first establish the well-posedness in the time-discrete setting and then derive the a posteriori error estimates, which provides a fully computable upper bound on an energy-type error, including also for the case of general smooth distributions (which will be useful for the detection of speciation events). Several numerical tests validate our framework in practice.

Fluctuations in Density-Dependent Selection Drive the Evolution of a Pace-of-Life Syndrome Within and Between Populations

AbstractThe pace-of-life syndrome (POLS) hypothesis posits that suites of traits are correlated along a slow-fast continuum owing to life history trade-offs. Despite widespread adoption, environmental conditions driving the emergence of POLS remain unclear. A recently proposed conceptual framework of POLS suggests that a slow-fast continuum should align to fluctuations in density-dependent selection. We tested three key predictions made by this framework with an eco-evolutionary agent-based population model. Selection acted on responsiveness (behavioral trait) to interpatch resource differences and the reproductive investment threshold (life history trait). Across environments with density fluctuations of different magnitudes, we observed the emergence of a common axis of trait covariation between and within populations (i.e., the evolution of a POLS). Slow-type (fast-type) populations with high (low) responsiveness and low (high) reproductive investment threshold were selected at high (low) population densities and less (more) intense and frequent density fluctuations. In support of the predictions, fast-type populations contained a higher degree of variation in traits and were associated with higher intrinsic reproductive rate (r0) and higher sensitivity to intraspecific competition (γ), pointing to a universal trade-off. While our findings support that POLS aligns with density-dependent selection, we discuss possible mechanisms that may lead to alternative evolutionary pathways.

Evidence of Differences in Covariation Among Root Traits Across Plant Growth Forms, Mycorrhizal Types, and Biomes.

Fine roots play an important role in plant ecological strategies, adaptation to environmental constraints, and ecosystem functions. Covariation among root traits influence the physiological and ecological processes of plants and ecosystems. Root trait covariation in multiple dimensions at the global scale has been broadly discussed. How fine-root traits covary at the regional scale and whether the covariation is generalizable across plant growth forms, mycorrhizal types, and biomes are largely unknown. Here, we collected six key traits – namely root diameter (RD), specific root length (SRL), root tissue density (RTD), root C content (RCC), root N content (RNC), and root C:N ratio (RCN) – of first- and second-order roots of 306 species from 94 sampling sites across China. We examined the covariation in root traits among different plant growth forms, mycorrhizal types, and biomes using the phylogenetic principal component analysis (pPCA). Three independent dimensions of the covariation in root traits were identified, accounting for 39.0, 26.1, and 20.2% of the total variation, respectively. The first dimension was represented by SRL, RNC, RTD, and RCN, which was in line with the root economics spectrum (RES). The second dimension described a negative relationship between RD and SRL, and the third dimension was represented by RCC. These three main principal components were mainly influenced by biome and mycorrhizal type. Herbaceous and ectomycorrhizal species showed a more consistent pattern with the RES, in which RD, RTD, and RCN were negatively correlated with SRL and RNC within the first axis compared with woody and arbuscular mycorrhizal species, respectively. Our results highlight the roles of plant growth form, mycorrhizal type, and biome in shaping root trait covariation, suggesting that root trait relationships in specific regions may not be generalized from global-scale analyses.

Montane Temperate-Boreal Forests Retain the Leaf Economic Spectrum Despite Intraspecific Variability

Trait-based analyses provide powerful tools for developing a generalizable, physiologically grounded understanding of how forest communities are responding to ongoing environmental changes. Key challenges lie in (1) selecting traits that best characterize the ecological performance of species in the community and (2) determining the degree and importance of intraspecific variability in those traits. Recent studies suggest that globally evident trait correlations (trait dimensions), such as the leaf economic spectrum, may be weak or absent at local scales. Moreover, trait-based analyses that utilize a mean value to represent a species may be misleading. Mean trait values are particularly problematic if species trait value rankings change along environmental gradients, resulting in species trait crossover. To assess how plant traits (1) covary at local spatial scales, (2) vary across the dominant environmental gradients, and (3) can be partitioned within and across taxa, we collected data on 9 traits for 13 tree species spanning the montane temperate—boreal forest ecotones of New York and northern New England. The primary dimension of the trait ordination was the leaf economic spectrum, with trait variability among species largely driven by differences between deciduous angiosperms and evergreen gymnosperms. A second dimension was related to variability in nitrogen to phosphorous levels and stem specific density. Levels of intraspecific trait variability differed considerably among traits, and was related to variation in light, climate, and tree developmental stage. However, trait rankings across species were generally conserved across these gradients and there was little evidence of species crossover. The persistence of the leaf economics spectrum in both temperate and high-elevation conifer forests suggests that ecological strategies of tree species are associated with trade-offs between resource acquisition and tolerance, and may be quantified with relatively few traits. Furthermore, the assumption that species may be represented with a single trait value may be warranted for some trait-based analyses provided traits were measured under similar light levels and climate conditions.

Larval Density, Sex, and Allocation Hierarchy Affect Life History Trait Covariances in a Bean Beetle

AbstractLife history theory aims to understand how different environments result in differential investment in fitness-related traits. While trade-offs between traits are expected, many studies show positive or no correlation between pairs of costly traits. One hypothesis that may explain the inconsistency of trade-offs in the literature is that trait investment may occur in a dichotomous hierarchy (the tree model), which allows for differential trait investment weighted by the traits' respective positions within the hierarchy. Previous mathematical models predict different covariances between traits depending on their position on the allocation tree. While hierarchical differential investment is often used to discuss findings in life history theory, the role of an allocation hierarchy in trait covariances has not been directly tested. In turn, this study aims to identify trait covariances between behavioral and morphological phenotypes on different branches of an allocation tree for the bean beetle, Callosobruchus maculatus. While trade-offs between copulatory behaviors and morphology were found for both males and females, only traits at the base and far from each other in the hierarchy negatively covaried. This study empirically shows that trade-offs may be the result of hierarchical investment.

Estimation of co-variance components and genetic parameters of fertility and production traits in crossbred cattle of Kerala

Estimation of co-variance components and genetic parameters of fertility and production traits will help to find out the relative importance of genetic and environmental components of each trait and to develop a genetic evaluation system for overall improvement in performances of crossbred cattle of Kerala. In the present study, major fertility trait considered was daughters pregnancy rate (DPR), measures the percentage of non-pregnant animals that become pregnant during each oestrous cycle. Data pertaining to 1180 crossbred cattle sired by 208 Frieswal bulls, spread over a period of 16 years from 2003 to 2019, maintained at different farms of Kerala Veterinary and Animal Sciences University and field centres of ICAR- Filed Progeny Testing Scheme were analysed in the study. Estimates of covariance components and genetic parameters were obtained using restricted maximum likelihood (REML) approach using average information (AI) algorithm. It was observed that DPR had low heritability (0.092 ± 0.03), compared to 305 days milk yield (MY) (0.170 ± 0.094) and fat percent (FP) (0.173 ± 0.072). Phenotypic (rp), genetic (rg) and residual (re) correlation indicated unfavourable association of fertility with production traits. The estimates of variance and (co)variance components were computed by multivariate animal model. The results indicated that DPR was having lower direct additive (σ2a) 0.046 and environmental variance (σ2c) 0.063 compared to other traits. Highest additive genetic variance (σ2a) 27035.8 was obtained for MY. The study estimates the magnitude of correlations and covariances of fertility and production traits. Since DPR had lower additive genetic variance and negative association with milk production traits in cattle, it would be included as an indirect measure in the evaluation and breeding programs of crossbred cattle of Kerala.

Sex-specific covariance between metabolic rate, behaviour and morphology in the ground beetle Carabus hortensis.

BackgroundIndividuals within the same species often differ in their metabolic rates, which may covary with behavioural traits (such as exploration), that are consistent across time and/or contexts, and morphological traits. Yet, despite the frequent occurrence of sexual dimorphisms in morphology and behaviour, few studies have assessed whether and how sexes differ in metabolic trait covariances.MethodsWe investigated sex-specific relationships among resting or active metabolic rate (RMR and AMR, respectively) with exploratory behaviour, measured independently of metabolic rate in a novel environment, body size and body mass, in Carabus hortensis ground beetles.ResultsRMR, AMR and exploratory behaviour were repeatable among individuals across time, except for male RMR which was unrepeatable. Female RMR neither correlated with exploratory behaviour nor body size/body mass. In contrast, AMR was correlated with both body size and exploratory behaviour. Males with larger body sizes had higher AMR, whereas females with larger body sizes had lower AMR. Both male and female AMR were significantly related to exploratory behaviour, though the relationships between AMR and exploration were body mass-dependent in males and temperature-dependent in females.DiscussionDifferences between sexes exist in the covariances between metabolic rate, body size and exploratory behaviour. This suggests that selection acts differently on males and females to produce these trait covariances with potentially important consequences for individual fitness.

Statistics of eigenvalue dispersion indices: Quantifying the magnitude of phenotypic integration.

Analysis of trait covariation plays a pivotal role in the study of phenotypic evolution. The magnitude of covariation is often quantified with statistics based on dispersion of eigenvalues of a covariance or correlation matrix-eigenvalue dispersion indices. This study clarifies the statistical justifications of these statistics and elaborates on their sampling properties. The relative eigenvalue variance of a covariance matrix is known in the statistical literature a test statistic for sphericity, and thus is an appropriate measure of eccentricity of variation. The same of a correlation matrix is equal to the average squared correlation, which has a straightforward interpretation as a measure of integration. Here, expressions for the mean and variance of these statistics are analytically derived under multivariate normality, clarifying the effects of sample size N, number of variables p, and parameters on sampling bias and error. Simulations confirm that approximations involved are reasonably accurate with a moderate sample size (N ≥ 16-64). Importantly, sampling properties of these indices are not adversely affected by a high p:N ratio, promising their utility in high-dimensional phenotypic analyses. They can furthermore be applied to shape variables and phylogenetically structured data with appropriate modifications.

Scaling-up trait covariation: Coordination and trade-offs within and among plant species in alpine meadow communities

<p indent="0mm">Functional traits and their covariation could reflect specific ecological strategies of organisms in response and adaptation to changing environment as the basis of understanding organism-environment relations at the individual, population, and community levels. Many studies report trait coordination and trade-offs among species over broad scales, especially for the leaf economic spectrum at regional and global scales. An increasing number of studies have attempted to explain and predict the functional (trait) structure of populations, communities, and vegetation in response to environmental change, but the mechanisms underpinning trait coordination and trade-offs may differ across ecological levels. We know little about this trait coordination and trade-offs within and among species in local communities, lacking not only relevant theoretical frameworks but also experimental evidence. Merging trait covariation into theory for community assembly, we predict: (1) Significant trait coordination or trade-offs among coexisting species occur when coexisting species occupy distinct ecological niches, similar to the pattern induced by specialization of species niches on a broad scale and (2) if trait covariations are induced by functional balance and/or structural optima, then consistent trait coordination and trade-offs within and among species will occur and scale up to the community and ecosystem levels. In this study, we experimentally test these predictions in local communities and discuss the potential mechanisms underpinning trait coordination and trade-offs from the scale of individual plants to vegetation. In Tibetan alpine meadows with high plant species richness but low environmental heterogeneity, we sampled two leaf stoichiometric traits (leaf nitrogen and phosphorus content), two leaf morphological traits (specific leaf area and leaf dry matter content) and mature plant height for three to five individuals for all coexisting species within each of 36 plant communities (plots) distributed along a gradient of environmental harshness. In each plot, we averaged trait values of individual samples of each species at the population-level, and used the mean of all populations of each species to indicate the species-level traits. We assessed pairwise trait correlation within and among 29 frequent species by standardized major axis regression and trait coordination and trade-offs among multiple traits by principal component analysis. Similar to the broad-scale pattern, we found that leaf nitrogen and phosphorus contents were significantly positively correlated with specific leaf area (negatively correlated with leaf dry matter content) among 29 coexisting species, but these trade-offs were significant at a population level in only a few species. Both among species and within most species, (1) leaf nitrogen content was significantly positively correlated with phosphorus content, likely induced by functional balance, (2) specific leaf area was negatively correlated with leaf dry matter content, indicating a structural optimum, (3) neither leaf stoichiometric nor morphological traits significantly correlated with plant height. Trait coordination and trade-offs were stronger for multiple trait relationships than for bivariate correlations. These results support our predictions and provide a basis and experimental evidence for scaling up trait covariations from individuals to communities.

Variation in fine root traits with thinning intensity in a Chinese fir plantation insights from branching order and functional groups

Thinning is a widely used practice in forest management, but the acclimation mechanisms of fine roots to forest thinning are still unclear. We examined the variations in fine root traits of different branching orders and functional groups along a thinning intensity gradient in a 26-year-old Chinese fir (Cunninghamia lanceolata) plantation. With increasing thinning intensity, the root C concentration (RCC), root N concentration (RNC), specific root area (SRA), and specific root length (SRL) of the absorptive roots (the first two orders) significantly decreased, while root abundance (root biomass and root length density) and root tissue density (RTD) significantly increased. Fifty-four percent of the variation in the absorptive root traits could be explained by the soil N concentration and the biomass and diversity of the understorey vegetation. Conversely, transport root (third- and higher-order) traits did not vary significantly among different thinning intensities. The covariation of absorptive root traits across thinning intensities regarding two dimensions was as follows: the first dimension (46% of the total variation) represented changes in root abundance and chemical traits (related to RCC, RNC), belonging to an extensive foraging strategy; the second dimension (41% of the total variation) represented variations in root morphological traits (related to RTD, SRL and SRA), which is an intensive foraging strategy (i.e., root economic spectrum). These results suggested that the absorptive roots of Chinese fir adopt two-dimensional strategies to acclimate to the altered surroundings after thinning.

A Bivariate Mapping Model Identifies Major Covariation QTLs for Biomass Allocation Between Leaf and Stem Growth of Catalpa bungei.

Biomass allocation plays a critical role in plant morphological formation and phenotypic plasticity, which greatly impact plant adaptability and competitiveness. While empirical studies on plant biomass allocation have focused on molecular biology and ecology approaches, detailed insight into the genetic basis of biomass allocation between leaf and stem growth is still lacking. Herein, we constructed a bivariate mapping model to identify covariation QTLs governing carbon (C) allocation between the leaves and stem as well as the covariation of traits within and between organs in a full-sib mapping population of C. bungei. A total of 123 covQTLs were detected for 23 trait pairs, including six leaf traits (leaf length, width, area, perimeter, length/width ratio and petiole length) and five stem traits (height, diameter at breast height, wood density, stemwood volume and stemwood biomass). The candidate genes were further identified in tissue-specific gene expression data, which provided insights into the genetic architecture underlying C allocation for traits or organs. The key QTLs related to growth and biomass allocation, which included UVH1, CLPT2, GAD/SPL, COG1 and MTERF4, were characterised and verified via gene function annotation and expression profiling. The integration of a bivariate Quantitative trait locus mapping model and gene expression profiling will enable the elucidation of genetic architecture underlying biomass allocation and covariation growth, in turn providing a theoretical basis for forest molecular marker-assisted breeding with specific C allocation strategies for adaptation to heterogeneous environments.

Differences in germination response to temperature, salinity, and water potential among Prosopis laevigata populations are guided by the tolerance-exploitation trade-off.

Exploring the mechanisms that promote population divergence represents a central point in evolutionary ecology. Along their distribution, species commonly experience contrasting environmental conditions, which impose local selection pressures to which populations tend to adapt resulting, for example, in ways to deal with resource shortage or abundance. In this study, we explored if germination performance varies under different levels of temperature, water potential and salinity among populations of Prosopis laevigata, a widespread mesquite species from the arid and semi-arid zones of Mexico. Given the wide distribution of P. laevigata and the sensitivity of the germination phase to environmental conditions, we hypothesized the existence of differential responses during this crucial stage of plant development. Thus, we expected germination in populations of P. laevigata from more arid zones to be less sensitive to high temperatures, salinity, and water deficit. Also, we explored if the exploitation–tolerance trade-off guides the differentiation of P. laevigata populations in germination performance under varying conditions. Germination of all populations was very sensitive to water scarcity but not to variation in temperature or salinity. We identified two major axes of trait covariation in germination physiology: one defined by tolerance of germination to water and saline stress versus germination velocity, and the other defined by the tolerance to extreme temperatures. We found evidence that variation in tolerance among the populations was related with their distribution along environmental gradients. Overall, populations with a higher capacity to germinate under water deficit stress, salinity, and extreme temperatures inhabit warmer and more saline areas. Our study provides strong evidence of existing local adaptations during germination of P. laevigata from across its distribution in the arid lands of Mexico.

A test of the fast–slow plant economy hypothesis in a subtropical rain forest

ABSTRACT Background The fast–slow plant economy hypothesis predicts strong co-variation in key resource-use traits due to the trade-off between growth and survival of species. Accordingly, it is expected that trait variation may be reduced to a single dimension along a growth-survival gradient. However, some studies warn against such reductionism and promote investigating how a multi-dimensional trait space can be interpreted in a growth-survival trade-off context. Aim To quantify the dimensionality of the trait variation of trees and tree-like species to test the fast–slow plant economy hypothesis in a subtropical rain forest. Methods We conducted phylogenetic Principal Components Analyses and correlation test on traits describing carbon and water economy in the leaves, stem, and seeds to evaluate the dimensionality of trait space and covariation among traits. Results We found five axes explaining 71% of trait variation. The first and second axes described carbon capture and allocation. Water use economy was related to carbon capture and was also represented on the third axis. Stomata traits were related to the fourth axis and plant potential height to the fourth and fifth axes. Conclusion The high dimensionality we found suggests that ecological strategies to water and carbon use are diverse in (sub)tropical montane forest species. Therefore, contrary to the expectation, these plants could use different ecological strategies to achieve a similar fitness in the growth–survival gradient.

Early-life patterns of growth are linked to levels of phenotypic trait covariance and postfledging mortality across avian species.

Life history studies have established that trade‐offs between growth and survival are common both within and among species. Identifying the factor(s) that mediate this trade‐off has proven difficult, however, especially at the among‐species level. In this study, we examined a series of potentially interrelated traits in a community of temperate‐zone passerine birds to help understand the putative causes and consequences of variation in early‐life growth among species. First, we examined whether nest predation risk (a proven driver of interspecific variation in growth and development rates) was correlated with species‐level patterns of incubation duration and nestling period length. We then assessed whether proxies for growth rate covaried with mean trait covariance strength (i.e., phenotypic correlations ( rp), which can be a marker of early‐life stress) among body mass, tarsus length, and wing length at fledging. Finally, we examined whether trait covariance strength at fledging was related to postfledging survival. We found that higher nest predation risk was correlated with faster skeletal growth and that our proxies for growth corresponded with increased trait covariance strength ( rp), which subsequently, correlated with higher mortality in the next life stage (postfledging period). These results provide an indication that extrinsic pressures (nest predation) impact rates of growth, and that there are costs of rapid growth across species, expressed as higher mean rp and elevated postfledging mortality. The link between higher levels of trait covariance at fledging and increased mortality is unclear, but increased trait covariance strength may reflect reduced phenotypic flexibility (i.e., phenotypic canalization), which may limit an organism's capacity for coping with environmental or ecological variability.

Environmental effects on the genetic architecture of fitness components in a simultaneous hermaphrodite.

Understanding how environmental change affects genetic variances and covariances of reproductive traits is key to formulate firm predictions on evolutionary responses. This is particularly true for sex-specific variance in reproductive success, which has been argued to affect how populations can adapt to environmental change. Our current knowledge on the impact of environmental stress on sex-specific genetic architecture of fitness components is still limited and restricted to separate-sexed organisms. However, hermaphroditism is widespread across animals and may entail interesting peculiarities with respect to genetic constraints imposed on the evolution of male and female reproduction. We explored how food restriction affects the genetic variance-covariance (G) matrix of body size and reproductive success of the simultaneously hermaphroditic freshwater snail Physa acuta. Our results provide strong evidence that the imposed environmental stress elevated the opportunity for selection in both sex functions. However, the G-matrix remained largely stable across the tested food treatments. Importantly, our results provide no support for cross-sex genetic correlations suggesting no strong evolutionary coupling of male and female reproductive traits. We discuss potential implications for the adaptation to changing environments and highlight the need for more quantitative genetic studies on male and female fitness components in simultaneous hermaphrodites.

The influence of divergent reproductive strategies in shaping modularity and morphological evolution in mammalian jaws.

Marsupial neonates are born at an earlier developmental stage than placental mammals, but the rapid development of their forelimbs and cranial skeleton allows them to climb to the pouch, begin suckling and complete their development ex utero. The mechanical environment in which marsupial neonates develop is vastly different from that of placental neonates, which exhibit a more protracted development of oral muscles and bones. This difference in reproductive strategy has been theorized to constrain morphological evolution in the oral region of marsupials. Here, we use 3D morphometrics to characterize one of these oral bones, the lower jaw (dentary), and assess modularity (pattern of covariation among traits), morphological disparity and rates of morphological evolution in two clades of carnivorous mammals: the marsupial Dasyuromorphia and placental fissiped Carnivora. We find that dasyuromorph dentaries have fewer modules than carnivorans and exhibit tight covariation between the angular and coronoid processes, the primary attachment sites for jaw-closing muscles. This pattern of modularity may result from the uniform action of muscles on the developing mandible during suckling. Carnivorans are free from this constraint and exhibit a pattern of modularity that more strongly reflects genetic and developmental signals of trait covariation. Alongside differences in modularity, carnivorans exhibit greater disparity and faster rates of morphological evolution compared with dasyuromorphs. Taken together, this suggests dasyuromorphs have retained a signal of trait covariation that reflects the outsized influence of muscular force during early development, a feature that may have impacted the ability of marsupial carnivores to explore specialized regions of morphospace.

Quantifying Leaf Trait Covariations and Their Relationships with Plant Adaptation Strategies along an Aridity Gradient.

Simple SummaryPlants usually adopt different strategies to adapt to their surrounding environments. Accurately quantifying plant strategies is of great interest in trait-based ecology, in particular to understand the responses of ecological structures and processes. In the last two decades, these strategies have been described qualitatively; however, the use of quantitative methods is still lacking. In this study, we used a plant functional trait approach to discuss plant strategies along an aridity gradient. We found that eight functional traits divided into four dimensions represent four adaptation strategies: energy balance, resource acquisition, resource investment and water use efficiency. We also concluded that climate and soil together with family (vegetation succession) were the main driving forces of trait covariations. Our study provided a new perspective to understand plant functional responses to aridity gradients, which is helpful for ecological management and vegetation restoration programs in arid regions.A trait-based approach is an effective way to quantify plant adaptation strategies in response to changing environments. Single trait variations have been well depicted before; however, multi-trait covariations and their roles in shaping plant adaptation strategies along aridity gradients remain unclear. The purpose of this study was to reveal multi-trait covariation characteristics, their controls and their relevance to plant adaptation strategies. Using eight relevant plant functional traits and multivariate statistical approaches, we found the following: (1) the eight studied traits show evident covariation characteristics and could be grouped into four functional dimensions linked to plant strategies, namely energy balance, resource acquisition, resource investment and water use efficiency; (2) leaf area (LA) together with traits related to the leaf economic spectrum, including leaf nitrogen content per area (Narea), leaf nitrogen per mass (Nmass) and leaf dry mass per area (LMA), covaried along the aridity gradient (represented by the moisture index, MI) and dominated the trait–environmental change axis; (3) together, climate, soil and family can explain 50.4% of trait covariations; thus, vegetation succession along the aridity gradient cannot be neglected in trait covariations. Our findings provide novel perspectives toward a better understanding of plant adaptations to arid conditions and serve as a reference for vegetation restoration and management programs in arid regions.