Putting the genes into community genetics

As part of the long‐term fusion of evolutionary biology and ecology (Ford, 1964), the field of community genetics has made tremendous progress in describing the impacts of plant genetic variation on community and ecosystem processes. In the “genes‐to‐ecosystems” framework (Whitham et al., 2003), genetically based traits of plant species have ecological consequences, but previous studies have not identified specific plant genes responsible for community phenotypes. The study by Barker et al. (2019) in this issue of Molecular Ecology uses an impressive common garden experiment of trembling aspen (Figure 1) to test for the genetic basis of tree traits that shape the insect community composition. Using a Genome‐Wide Association Study (GWAS), they found that genomic regions associated with phytochemical traits best explain variation in herbivore community composition, and identified specific genes associated with different types of leaf‐modifying herbivores and ants. This is one of the first studies to identify candidate genes underlying the heritable plant traits that explain patterns of insect biodiversity.     

Importance of species interactions to community heritability: a genetic basis to trophic-level interactions

Recent community genetics studies have shown that specific genotypes of a host plant support distinct arthropod communities. Building upon these findings, we examined the hypothesis that a trophic community consisting of cottonwood trees, a galling herbivore and avian predators could also be related to the genetics of the host tree. We found genetic correlations among phytochemistry of individual tree genotypes, the density of a galling herbivore, and the intensity of avian predation on these herbivores. We detected significant broad-sense heritability of these interactions that range from H      = 0.70 to 0.83. The genetic basis of these interactions tended to increase across trophic levels suggesting that small genetic changes in the cottonwood phenotype could have major consequences at higher trophic levels affecting species interactions and energy flow. These findings show a heritable basis to trophic-level interactions indicating that there is a significant genetic basis to community composition and energy flow that is predictable by plant genotype. Our data clearly link plant genetics to patterns of avian foraging and show that species interactions are important components of community heritability and ecosystem processes. Overall, these data support the hypothesis that evolution of plant traits can alter trophic-level interactions and community composition.     

Plant genetics shapes inquiline community structure across spatial scales

Recent research in community genetics has examined the effects of intraspecific genetic variation on species diversity in local communities. However, communities can be structured by a combination of both local and regional processes and to date, few community genetics studies have examined whether the effects of instraspecific genetic variation are consistent across levels of diversity. In this study, we ask whether host-plant genetic variation structures communities of arthropod inquilines within distinct habitat patches – rosette leaf galls on tall goldenrod ( Solidago altissima ). We found that genetic variation determined inquiline diversity at both local and regional spatial scales, but that trophic-level responses varied independently of one another. This result suggests that herbivores and predators likely respond to heritable plant traits at different spatial scales. Together, our results show that incorporating spatial scale is essential for predicting the effects of genetically variable traits on different trophic levels and levels of diversity within the communities that depend on host plants.     

Systems biology strategy to study lipotoxicity and the metabolic syndrome

Systems biology views and studies the biological systems in the context of complex interactions between their building blocks and processes. Given its multi-level complexity, metabolic syndrome (MetS) makes a strong case for adopting the systems biology approach. Despite many MetS traits being highly heritable, it is becoming evident that the genetic contribution to these traits is mediated via gene–gene and gene–environment interactions across several spatial and temporal scales, and that some of these traits such as lipotoxicity may even be a product of long-term dynamic changes of the underlying genetic and molecular networks. This presents several conceptual as well as methodological challenges and may demand a paradigm shift in how we study the undeniably strong genetic component of complex diseases such as MetS. The argument is made here that for adopting systems biology approaches to MetS an integrative framework is needed which glues the biological processes of MetS with specific physiological mechanisms and principles and that lipotoxicity is one such framework. The metabolic phenotypes, molecular and genetic networks can be modeled within the context of such integrative framework and the underlying physiology.     

Community heritability measures the evolutionary consequences of indirect genetic effects on community structure

The evolutionary analysis of community organization is considered a major frontier in biology. Nevertheless, current explanations for community structure exclude the effects of genes and selection at levels above the individual. Here, we demonstrate a genetic basis for community structure, arising from the fitness consequences of genetic interactions among species (i.e., interspecific indirect genetic effects or IIGEs). Using simulated and natural communities of arthropods inhabiting North American cottonwoods (Populus), we show that when species comprising ecological communities are summarized using a multivariate statistical method, nonmetric multidimensional scaling (NMDS), the resulting univariate scores can be analyzed using standard techniques for estimating the heritability of quantitative traits. Our estimates of the broad-sense heritability of arthropod communities on known genotypes of cottonwood trees in common gardens explained 56-63% of the total variation in community phenotype. To justify and help interpret our empirical approach, we modeled synthetic communities in which the number, intensity, and fitness consequences of the genetic interactions among species comprising the community were explicitly known. Results from the model suggest that our empirical estimates of broad-sense community heritability arise from heritable variation in a host tree trait and the fitness consequences of IGEs that extend from tree trait to arthropods. When arthropod traits are heritable, interspecific IGEs cause species interactions to change, and community evolution occurs. Our results have implications for establishing the genetic foundations of communities and ecosystems.     

Testing a ‘genes‐to‐ecosystems’ approach to understanding aquatic–terrestrial linkages

A ‘genes‐to‐ecosystems’ approach has been proposed as a novel avenue for integrating the consequences of intraspecific genetic variation with the underlying genetic architecture of a species to shed light on the relationships among hierarchies of ecological organization (genes → individuals → communities → ecosystems). However, attempts to identify genes with major effect on the structure of communities and/or ecosystem processes have been limited and a comprehensive test of this approach has yet to emerge. Here, we present an interdisciplinary field study that integrated a common garden containing different genotypes of a dominant, riparian tree, Populus trichocarpa, and aquatic mesocosms to determine how intraspecific variation in leaf litter alters both terrestrial and aquatic communities and ecosystem functioning. Moreover, we incorporate data from extensive trait screening and genome‐wide association studies estimating the heritability and genes associated with litter characteristics. We found that tree genotypes varied considerably in the quality and production of leaf litter, which contributed to variation in phytoplankton abundances, as well as nutrient dynamics and light availability in aquatic mesocosms. These ‘after‐life’ effects of litter from different genotypes were comparable to the responses of terrestrial communities associated with the living foliage. We found that multiple litter traits corresponding with aquatic community and ecosystem responses differed in their heritability. Moreover, the underlying genetic architecture of these traits was complex, and many genes contributed only a small proportion to phenotypic variation. Our results provide further evidence that genetic variation is a key component of aquatic–terrestrial linkages, but challenge the ability to predict community or ecosystem responses based on the actions of one or a few genes.     

An Effective Method to Identify Heritable Components from Multivariate Phenotypes

Multivariate phenotypes may be characterized collectively by a variety of low level traits, such as in the diagnosis of a disease that relies on multiple disease indicators. Such multivariate phenotypes are often used in genetic association studies. If highly heritable components of a multivariate phenotype can be identified, it can maximize the likelihood of finding genetic associations. Existing methods for phenotype refinement perform unsupervised cluster analysis on low-level traits and hence do not assess heritability. Existing heritable component analytics either cannot utilize general pedigrees or have to estimate the entire covariance matrix of low-level traits from limited samples, which leads to inaccurate estimates and is often computationally prohibitive. It is also difficult for these methods to exclude fixed effects from other covariates such as age, sex and race, in order to identify truly heritable components. We propose to search for a combination of low-level traits and directly maximize the heritability of this combined trait. A quadratic optimization problem is thus derived where the objective function is formulated by decomposing the traditional maximum likelihood method for estimating the heritability of a quantitative trait. The proposed approach can generate linearly-combined traits of high heritability that has been corrected for the fixed effects of covariates. The effectiveness of the proposed approach is demonstrated in simulations and by a case study of cocaine dependence. Our approach was computationally efficient and derived traits of higher heritability than those by other methods. Additional association analysis with the derived cocaine-use trait identified genetic markers that were replicated in an independent sample, further confirming the utility and advantage of the proposed approach.     

Functional diversity: a tool for answering challenging ecological questions

Functional trait diversity provides a powerful means of addressing ecology's persistent questions, through its dual role as an indicator of mechanisms driving differences in species composition between communities and as a predictor of ecosystem‐level processes. Functional traits provide a means of testing mechanisms behind species turnover between communities because environmental heterogeneity, competition and disturbance influence species fitness via their traits. Functional traits also provide a link between species and multiple ecosystem‐level processes, such as primary productivity, nutrient fluxes and resilience, since species influence these processes via their traits. This special issue demonstrates that functional diversity offers a practical means of investigating ecology's persistent questions.     

Scaling environmental change through the community-level: a trait-based response-and-effect framework for plants

Predicting ecosystem responses to global change is a major challenge in ecology. A critical step in that challenge is to understand how changing environmental conditions influence processes across levels of ecological organization. While direct scaling from individual to ecosystem dynamics can lead to robust and mechanistic predictions, new approaches are needed to appropriately translate questions through the community level. Species invasion, loss, and turnover all necessitate this scaling through community processes, but predicting how such changes may influence ecosystem function is notoriously difficult. We suggest that community‐level dynamics can be incorporated into scaling predictions using a trait‐based response–effect framework that differentiates the community response to environmental change (predicted by response traits) and the effect of that change on ecosystem processes (predicted by effect traits). We develop a response‐and‐effect functional framework, concentrating on how the relationships among species' response, effect, and abundance can lead to general predictions concerning the magnitude and direction of the influence of environmental change on function. We then detail several key research directions needed to better scale the effects of environmental change through the community level. These include (1) effect and response trait characterization, (2) linkages between response‐and‐effect traits, (3) the importance of species interactions on trait expression, and (4) incorporation of feedbacks across multiple temporal scales. Increasing rates of extinction and invasion that are modifying communities worldwide make such a research agenda imperative.     

A trait-based experimental approach to understand the mechanisms underlying biodiversity–ecosystem functioning relationships

Plant functional characteristics may drive plant species richness effects on ecosystem processes. Consequently, the focus of biodiversity–ecosystem functioning (BEF) experiments has expanded from the manipulation of plant species richness to manipulating functional trait composition. Involving ecophysiological plant traits in the experimental design might allow for a better understanding of how species loss alters ecosystem processes. Here we provide the theoretical background, design and first results of the ‘Trait-Based Biodiversity Experiment’ (TBE), established in 2010 that directly manipulates the trait composition of experimental plant communities.Analysis of six plant traits related to resource acquisition and use were analyzed using principal component analysis of 60 grassland species. The resulting two main axes describe gradients in functional similarity, and were used as the basis for designing plant communities with different functional and species diversity levels. Using such an approach allowed us to manipulate different levels of complementarity in spatial and temporal plant resource acquisition. In contrast to previous biodiversity experiments, the TBE is designed according to more realistic scenarios of non-random species loss along orthogonal axes of species trait dissimilarities. This allows us to tease apart the relative importance of selection and complementarity effects on multiple ecosystem processes, and to mechanistically study the consequences of plant community simplification.     

Towards an assessment of multiple ecosystem processes and services via functional traits

Managing ecosystems to ensure the provision of multiple ecosystem services is a key challenge for applied ecology. Functional traits are receiving increasing attention as the main ecological attributes by which different organisms and biological communities influence ecosystem services through their effects on underlying ecosystem processes. Here we synthesize concepts and empirical evidence on linkages between functional traits and ecosystem services across different trophic levels. Most of the 247 studies reviewed considered plants and soil invertebrates, but quantitative trait–service associations have been documented for a range of organisms and ecosystems, illustrating the wide applicability of the trait approach. Within each trophic level, specific processes are affected by a combination of traits while particular key traits are simultaneously involved in the control of multiple processes. These multiple associations between traits and ecosystem processes can help to identify predictable trait–service clusters that depend on several trophic levels, such as clusters of traits of plants and soil organisms that underlie nutrient cycling, herbivory, and fodder and fibre production. We propose that the assessment of trait–service clusters will represent a crucial step in ecosystem service monitoring and in balancing the delivery of multiple, and sometimes conflicting, services in ecosystem management.     

Ecosystem allometry: the scaling of nutrient stocks and primary productivity across plant communities

A principal challenge in ecology is to integrate physiological function (e.g. photosynthesis) across a collection of individuals (e.g. plants of different species) to understand the functioning of the entire ensemble (e.g. primary productivity). The control that organism size exerts over physiological and ecological function suggests that allometry could be a powerful tool for scaling ecological processes across levels of organization. Here we use individual plant allometries to predict how nutrient content and productivity scale with total plant biomass (phytomass) in whole plant communities. As predicted by our model, net primary productivity as well as whole community nitrogen and phosphorus content all scale allometrically with phytomass across diverse plant communities, from tropical forest to arctic tundra. Importantly, productivity data deviate quantitatively from the theoretically derived prediction, and nutrient productivity (production per unit nutrient) of terrestrial plant communities decreases systematically with increasing total phytomass. These results are consistent with the existence of pronounced competitive size hierarchies. The previously undocumented generality of these 'ecosystem allometries' and their basis in the structure and function of individual plants will likely provide a useful quantitative framework for research linking plant traits to ecosystem processes.     

The genetics of human personality

Personality traits are the relatively enduring patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances. Twin and family studies have showed that personality traits are moderately heritable, and can predict various lifetime outcomes, including psychopathology. The Research Domain Criteria characterizes psychiatric diseases as extremes of normal tendencies, including specific personality traits. This implies that heritable variation in personality traits, such as neuroticism, would share a common genetic basis with psychiatric diseases, such as major depressive disorder. Despite considerable efforts over the past several decades, the genetic variants that influence personality are only beginning to be identified. We review these recent and increasingly rapid developments, which focus on the assessment of personality via several commonly used personality questionnaires in healthy human subjects. Study designs covered include twin, linkage, candidate gene association studies, genome‐wide association studies and polygenic analyses. Findings from genetic studies of personality have furthered our understanding about the genetic etiology of personality, which, like neuropsychiatric diseases themselves, is highly polygenic. Polygenic analyses have showed genetic correlations between personality and psychopathology, confirming that genetic studies of personality can help to elucidate the etiology of several neuropsychiatric diseases.     

Human‐aided admixture may fuel ecosystem transformation during biological invasions: theoretical and experimental evidence

Biological invasions can transform our understanding of how the interplay of historical isolation and contemporary (human‐aided) dispersal affects the structure of intraspecific diversity in functional traits, and in turn, how changes in functional traits affect other scales of biological organization such as communities and ecosystems. Because biological invasions frequently involve the admixture of previously isolated lineages as a result of human‐aided dispersal, studies of invasive populations can reveal how admixture results in novel genotypes and shifts in functional trait variation within populations. Further, because invasive species can be ecosystem engineers within invaded ecosystems, admixture‐induced shifts in the functional traits of invaders can affect the composition of native biodiversity and alter the flow of resources through the system. Thus, invasions represent promising yet under‐investigated examples of how the effects of short‐term evolutionary changes can cascade across biological scales of diversity. Here, we propose a conceptual framework that admixture between divergent source populations during biological invasions can reorganize the genetic variation underlying key functional traits, leading to shifts in the mean and variance of functional traits within invasive populations. Changes in the mean or variance of key traits can initiate new ecological feedback mechanisms that result in a critical transition from a native ecosystem to a novel invasive ecosystem. We illustrate the application of this framework with reference to a well‐studied plant model system in invasion biology and show how a combination of quantitative genetic experiments, functional trait studies, whole ecosystem field studies and modeling can be used to explore the dynamics predicted to trigger these critical transitions.     

The capture of heritable variation for genetic quality through social competition

In theory, females of many species choose mates based on traits that are indicators of male genetic quality. A fundamental question in evolutionary biology is why genetic variation for such indicator traits persists despite strong persistent selection imposed by female preference, which is known as the lek paradox. One potential solution to the lek paradox suggests that the traits that are targets of mate choice should evolve condition-dependent expression and that condition should have a large genetic variance. Condition is expected to exhibit high genetic variance because it is affected by a large number of physiological processes and hence, condition-dependent traits should 'capture' variation contributed by a large number of loci. We suggest that a potentially important cause of variation in condition is competition for limited resources. Here, we discuss a pair of models to analyze the evolutionary genetics of traits affected by success in social competition for resources. We show that competition can contribute to genetic variation of 'competition-dependent' traits that have fundamentally different evolutionary properties than other sources of variation. Competition dependence can make traits honest indicators of genetic quality by revealing the relative competitive ability of males, can provide a component of heritable variation that does not contribute to trait evolution, and can help maintain heritable variation under directional selection. Here we provide a general introduction to the concept of competition dependence and briefly introduce two models to demonstrate the potential evolutionary consequences of competition-dependent trait expression.     

Functional structure of biological communities predicts ecosystem multifunctionality

The accelerating rate of change in biodiversity patterns, mediated by ever increasing human pressures and global warming, demands a better understanding of the relationship between the structure of biological communities and ecosystem functioning (BEF). Recent investigations suggest that the functional structure of communities, i.e. the composition and diversity of functional traits, is the main driver of ecological processes. However, the predictive power of BEF research is still low, the integration of all components of functional community structure as predictors is still lacking, and the multifunctionality of ecosystems (i.e. rates of multiple processes) must be considered. Here, using a multiple-processes framework from grassland biodiversity experiments, we show that functional identity of species and functional divergence among species, rather than species diversity per se, together promote the level of ecosystem multifunctionality with a predictive power of 80%. Our results suggest that primary productivity and decomposition rates, two key ecosystem processes upon which the global carbon cycle depends, are primarily sustained by specialist species, i.e. those that hold specialized combinations of traits and perform particular functions. Contrary to studies focusing on single ecosystem functions and considering species richness as the sole measure of biodiversity, we found a linear and non-saturating effect of the functional structure of communities on ecosystem multifunctionality. Thus, sustaining multiple ecological processes would require focusing on trait dominance and on the degree of community specialization, even in species-rich assemblages.     

基于功能性状的生态系统服务研究框架

功能性状通过影响生态系统的属性和过程及其维持来影响生态系统服务。功能多样性-生态系统功能关系的研究有助于深入探讨生态系统服务形成机制, 也为生态系统服务研究提供了一个切入点。该文对目前的功能性状和生态系统服务研究框架进行了介绍, 回顾了功能多样性-生态系统功能关系的研究现状, 总结了目前功能性状在生态系统服务研究中的应用, 提出了基于功能性状的生态系统服务研究框架。在这个研究框架中, 首先选取对生态系统功能影响显著的非生物因子和功能多样性指数, 然后量化非生物因子和功能多样性与生态系统功能, 以及生态系统功能-生态系统服务之间的关系, 进而构建功能多样性与生态系统服务的数量关系。与此同时, 利用群落构建理论和物种共存机制分析功能多样性-生态系统功能变化的机制联系, 以研究生态系统服务形成和变化机制, 为生态系统服务管理决策提供科学依据。     

Plant diversity and root traits benefit physical properties key to soil function in grasslands

Plant diversity loss impairs ecosystem functioning, including important effects on soil. Most studies that have explored plant diversity effects belowground, however, have largely focused on biological processes. As such, our understanding of how plant diversity impacts the soil physical environment remains limited, despite the fundamental role soil physical structure plays in ensuring soil function and ecosystem service provision. Here, in both a glasshouse and a long‐term field study, we show that high plant diversity in grassland systems increases soil aggregate stability, a vital structural property of soil, and that root traits play a major role in determining diversity effects. We also reveal that the presence of particular plant species within mixed communities affects an even wider range of soil physical processes, including hydrology and soil strength regimes. Our results indicate that alongside well‐documented effects on ecosystem functioning, plant diversity and root traits also benefit essential soil physical properties.     

Functional traits explain phytoplankton community structure and seasonal dynamics in a marine ecosystem

A fundamental yet elusive goal of ecology is to predict the structure of communities from the environmental conditions they experience. Trait‐based approaches to terrestrial plant communities have shown that functional traits can help reveal the mechanisms underlying community assembly, but such approaches have not been tested on the microbes that dominate ecosystem processes in the ocean. Here, we test whether functional traits can explain community responses to seasonal environmental fluctuation, using a time series of the phytoplankton of the English Channel. We show that interspecific variation in response to major limiting resources, light and nitrate, can be well‐predicted by lab‐measured traits characterising light utilisation, nitrate utilisation and maximum growth rate. As these relationships were predicted a priori, using independently measured traits, our results show that functional traits provide a strong mechanistic foundation for understanding the structure and dynamics of ecological communities.     

A test for the genetic basis of natural selection: an individual-based longitudinal study in a stream-dwelling fish

In addition to the well-studied evolutionary parameters of (1) phenotype-fitness covariance and (2) the genetic basis of phenotypic variation, adaptive evolution by natural selection requires that (3) fitness variation is effected by heritable genetic differences among individuals and (4) phenotype-fitness covariances must be, at least in part, underlain by genetic covariances. These latter two requirements for adaptive evolutionary change are relatively unstudied in natural populations. Absence of the latter requirements could explain stasis of apparently directionally selected heritable traits. We provide complementary analyses of selection and variation at phenotypic and genetic levels for juvenile growth rate in brook charr Salvelinus fontinalis in Freshwater River, Newfoundland, Canada. Contrary to the vast majority of reports in fish, we found very little viability selection of juvenile body size. Large body size appears nonetheless to be selectively advantageous via a relationship with early maturity. Genetic patterns in evolutionary parameters largely reflected phenotypic patterns. We have provided inference of selection based on longitudinal data, which are uncommon in high fecundity organisms. Furthermore we have provided a practicable framework for further studies of the genetic basis of natural selection.