Quantifying trait selection driving community assembly: a test in herbaceous plant communities under contrasted land use regimes

Plant traits are particularly important in determining plant community structure. However, how can one identify which traits are the most important in driving community assembly? Here we propose a method 1) to quantify the direction and strength of trait selection during community assembly and 2) to obtain parsimonious lists of traits that can predict species relative abundances in plant communities. We tested our method using floristic data from 32 plots experiencing different treatments (fertilisation and grazing) in southern France. Twelve functional traits were measured on 68 species. We determined the direction and strength of selection on these 12 traits using a metric derived from a maximum entropy model (i.e. lambda). We then determined our parsimonious list of traits using a backward selection of traits based on these lambda values (for all treatments and in each treatment separately). We finally compared our method to two other methods: one based on iterative RLQ and the other based on an entropy‐based forward selection of traits. We found major differences in the direction and strength of selection across the 12 traits and treatments. From the 12 traits, plant vegetative and reproductive heights, leaf dry matter content leaf nitrogen content, specific leaf area, and leaf phosphorus content were particularly important for predicting species relative abundances when considering all treatments together. Our method yielded results similar to those produced by the entropy‐based approach but differed from those produced by the iterative RLQ, whose selected traits could not significantly predict species relative abundances. Together these results suggest that the assembly of these communities is primarily driven by a small number of key functional traits. We argue that our method provides an objective way of determining a parsimonious list of traits that together accurately predict community structure and which, despite its complementarities with entropy‐based method, offers significant advantages.     

Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests

Patterns of phylogenetic relatedness within communities have been widely used to infer the importance of different ecological and evolutionary processes during community assembly, but little is known about the relative ability of community phylogenetics methods and null models to detect the signature of processes such as dispersal, competition and filtering under different models of trait evolution. Using a metacommunity simulation incorporating quantitative models of trait evolution and community assembly, I assessed the performance of different tests that have been used to measure community phylogenetic structure. All tests were sensitive to the relative phylogenetic signal in species metacommunity abundances and traits; methods that were most sensitive to the effects of niche-based processes on community structure were also more likely to find non-random patterns of community phylogenetic structure under dispersal assembly. When used with a null model that maintained species occurrence frequency in random communities, several metrics could detect niche-based assembly when there was strong phylogenetic signal in species traits, when multiple traits were involved in community assembly, and in the presence of environmental heterogeneity. Interpretations of the causes of community phylogenetic structure should be modified to account for the influence of dispersal.     

Constraints on trait combinations explain climatic drivers of biodiversity: the importance of trait covariance in community assembly

Trade‐offs maintain diversity and structure communities along environmental gradients. Theory indicates that if covariance among functional traits sets a limit on the number of viable trait combinations in a given environment, then communities with strong multidimensional trait constraints should exhibit low species diversity. We tested this prediction in winter annual plant assemblages along an aridity gradient using multilevel structural equation modelling. Univariate and multivariate functional diversity measures were poorly explained by aridity, and were surprisingly poor predictors of community richness. By contrast, the covariance between maximum height and seed mass strengthened along the aridity gradient, and was strongly associated with richness declines. Community richness had a positive effect on local neighbourhood richness, indicating that climate effects on trait covariance indirectly influence diversity at local scales. We present clear empirical evidence that declines in species richness along gradients of environmental stress can be due to increasing constraints on multidimensional phenotypes.     

Species traits for future biomonitoring across ecoregions: patterns along a human-impacted river

1. Current budgets for environmental management are high, tend to increase, and are used to support policy and legislation which is standardized for large geographic units. Therefore, the search for tools to monitor the effects of this investment is a major issue in applied ecology. Ideally, such a biomonitoring tool should: (1) be as general as possible with respect to its geographic application; (2) be as specific as possible by separating different types of human impact on a given ecosystem; (3) reliably indicate changes in human impact of a particular type; and (4) be derived from a sound theoretical concept in ecology. 2. We developed an approach to biomonitoring which matches these ‘ideal’ characteristics by focusing on numerous, general biological species traits (e.g. size, number of descendants per reproductive cycle, parental care, mobility) and on the habitat templet concept, which relates trends in these general species traits to disturbance patterns. Using the French Rhône River and benthic macroinvertebrates as an example, we have used the data to demonstrate a general framework and the potential of our approach rather than to produce a ready-made tool. Our data covered a large river and its major tributaries, which has a catchment that crosses ecoregions, and known gradients and discontinuities in human impact. 3. We applied multivariate analyses to evaluate how the distribution of species traits in invertebrate communities could discriminate environmental differences along the Rhône in comparison to traditionally used approaches (e.g. community structure, based on species abundances, or ecological species traits, such as velocity preferences and pollution tolerance). Invertebrate community structure expressed in terms either of the abundance or the traits of species reliably indicated differences in overall human impact. The community structure based on biological traits was less confounded by natural spatial gradients and reliably indicated human impact, while community structure based on ecological traits was the most confounded by natural spatial gradients and was the poorest indicator of human impact. Community structure based on species abundances was an intermediate indicator of human impact. 4. These results indicate that a revision of biomonitoring approaches which have been based on a single aspect of the biological responses may be warranted. The biological traits of species could separate the different types of human impact. Therefore, the use of these traits in biomonitoring could improve existing multi-metric approaches. Future research has to show if the general applicability of species traits allows the development of a unique biomonitoring tool for running waters of the European Union, for running waters in temperate climates on several continents, for freshwater, marine and terrestrial systems, and/or for global biodiversity assessment.     

Discriminating trait‐convergence and trait‐divergence assembly patterns in ecological community gradients

Question: Whereas similar ecological requirements lead to trait‐convergence assembly patterns (TCAP) of species in communities, the interactions controlling how species associate produce trait‐divergence assembly patterns (TDAP). Yet, the linking of the latter to community processes has so far only been suggested. We offer a method to elucidate TCAP and TDAP in ecological community gradients that will help fill this gap. Method: We evaluated the correlation between trait‐based described communities and ecological gradients, and using partial correlation, we separated the fractions reflecting TCAP and TDAP. The required input data matrices describe operational taxonomic units (OTUs) by traits, communities by the quantities or presence‐absence of these OTUs, and community sites by ecological variables. We defined plant functional types (PFTs) or species as community components after fuzzy weighting by the traits. The measured correlations for TCAP and TDAP were tested by permutation. The null model for TDAP preserves the trait convergence, the structure intrinsic in the fuzzy types, and community total abundances and autocorrelation. Results: We applied the method to trait‐based data from plant communities in south Brazil, one set in natural grassland experimental plots under different nitrogen and grazing levels, and another in sapling communities colonizing Araucaria forest patches of increasing size in a forest‐grassland mosaic. In these cases, depending on the traits considered, we found strong evidence of either TCAP or TDAP, or both, that was related to the environmental gradients. Conclusions: The method developed is able to reveal TCAP and TDAP that are more likely to be functional for specified ecological gradients, allowing establishment of objective hypotheses on their links to community processes.     

Hierarchical effects of environmental filters on the functional structure of plant communities: a case study in the French Alps

Understanding the influence of the environment on the functional structure of ecological communities is essential to predict the response of biodiversity to global change drivers. Ecological theory suggests that multiple environmental factors shape local species assemblages by progressively filtering species from the regional species pool to local communities. These successive filters should influence the various components of community functional structure in different ways. In this paper, we tested the relative influence of multiple environmental filters on various metrics of plant functional trait structure (i.e. ‘community weighted mean trait’ and components of functional trait diversity, i.e. functional richness, evenness and divergence) in 82 vegetation plots in the Guisane Valley, French Alps. For the 211 sampled species we measured traits known to capture key aspects of ecological strategies amongst vascular plant species, i.e. leaf traits, plant height and seed mass (LHS). A comprehensive information theory framework, together with null model based resampling techniques, was used to test the various environmental effects. Particular community components of functional structure responded differently to various environmental gradients, especially concerning the spatial scale at which the environmental factors seem to operate. Environmental factors acting at a large spatial scale (e.g. temperature) were found to predominantly shape community weighted mean trait values, while fine‐scale factors (topography and soil characteristics) mostly influenced functional diversity and the distribution of trait values among the dominant species. Our results emphasize the hierarchical nature of ecological forces shaping local species assemblage: large‐scale environmental filters having a primary effect, i.e. selecting the pool of species adapted to a site, and then filters at finer scales determining species abundances and local species coexistence. This suggests that different components of functional community structure will respond differently to environmental change, so that predicting plant community responses will require a hierarchical multi‐facet approach.     

Covariance structure in the skull of Catarrhini: a case of pattern stasis and magnitude evolution

The study of the genetic variance/covariance matrix (G-matrix) is a recent and fruitful approach in evolutionary biology, providing a window of investigating for the evolution of complex characters. Although G-matrix studies were originally conducted for microevolutionary timescales, they could be extrapolated to macroevolution as long as the G-matrix remains relatively constant, or proportional, along the period of interest. A promising approach to investigating the constancy of G-matrices is to compare their phenotypic counterparts (P-matrices) in a large group of related species; if significant similarity is found among several taxa, it is very likely that the underlying G-matrices are also equivalent. Here we study the similarity of covariance and correlation structure in a broad sample of Old World monkeys and apes (Catarrhini). We made phylogenetically structured comparisons of correlation and covariance matrices derived from 39 skull traits, ranging from between species to the superfamily level. We also compared the overall magnitude of integration between skull traits (r²) for all Catarrhini genera. Our results show that P-matrices were not strictly constant among catarrhines, but the amount of divergence observed among taxa was generally low. There was significant and positive correlation between the amount of divergence in correlation and covariance patterns among the 30 genera and their phylogenetic distances derived from a recently proposed phylogenetic hypothesis. Our data demonstrate that the P-matrices remained relatively similar along the evolutionary history of catarrhines, and comparisons with the G-matrix available for a New World monkey genus (Saguinus) suggests that the same holds for all anthropoids. The magnitude of integration, in contrast, varied considerably among genera, indicating that evolution of the magnitude, rather than the pattern of inter-trait correlations, might have played an important role in the diversification of the catarrhine skull.     

Evolution and stability of the G-matrix on a landscape with a moving optimum

In quantitative genetics, the genetic architecture of traits, described in terms of variances and covariances, plays a major role in determining the trajectory of evolutionary change. Hence, the genetic variance-covariance matrix (G-matrix) is a critical component of modern quantitative genetics theory. Considerable debate has surrounded the issue of G-matrix constancy because unstable G-matrices provide major difficulties for evolutionary inference. Empirical studies and analytical theory have not resolved the debate. Here we present the results of stochastic models of G-matrix evolution in a population responding to an adaptive landscape with an optimum that moves at a constant rate. This study builds on the previous results of stochastic simulations of G-matrix stability under stabilizing selection arising from a stationary optimum. The addition of a moving optimum leads to several important new insights. First, evolution along genetic lines of least resistance increases stability of the orientation of the G-matrix relative to stabilizing selection alone. Evolution across genetic lines of least resistance decreases G-matrix stability. Second, evolution in response to a continuously changing optimum can produce persistent maladaptation for a correlated trait, even if its optimum does not change. Third, the retrospective analysis of selection performs very well when the mean G-matrix (G) is known with certainty, indicating that covariance between G and the directional selection gradient beta is usually small enough in magnitude that it introduces only a small bias in estimates of the net selection gradient. Our results also show, however, that the contemporary G-matrix only serves as a rough guide to G. The most promising approach for the estimation of G is probably through comparative phylogenetic analysis. Overall, our results show that directional selection actually can increase stability of the G-matrix and that retrospective analysis of selection is inherently feasible. One major remaining challenge is to gain a sufficient understanding of the G-matrix to allow the confident estimation of G.     

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.     

Stability of the G-matrix in a population experiencing pleiotropic mutation, stabilizing selection, and genetic drift

Abstract. Quantitative genetics theory provides a framework that predicts the effects of selection on a phenotype consisting of a suite of complex traits. However, the ability of existing theory to reconstruct the history of selection or to predict the future trajectory of evolution depends upon the evolutionary dynamics of the genetic variance-covariance matrix (G-matrix). Thus, the central focus of the emerging field of comparative quantitative genetics is the evolution of the G-matrix. Existing analytical theory reveals little about the dynamics of G, because the problem is too complex to be mathematically tractable. As a first step toward a predictive theory of G-matrix evolution, our goal was to use stochastic computer models to investigate factors that might contribute to the stability of G over evolutionary time. We were concerned with the relatively simple case of two quantitative traits in a population experiencing stabilizing selection, pleiotropic mutation, and random genetic drift. Our results show that G-matrix stability is enhanced by strong correlational selection and large effective population size. In addition, the nature of mutations at pleiotropic loci can dramatically influence stability of G. In particular, when a mutation at a single locus simultaneously changes the value of the two traits (due to pleiotropy) and these effects are correlated, mutation can generate extreme stability of G. Thus, the central message of our study is that the empirical question regarding G-matrix stability is not necessarily a general question of whether G is stable across various taxonomic levels. Rather, we should expect the G-matrix to be extremely stable for some suites of characters and unstable for others over similar spans of evolutionary time.     

Disentangling the relative importance of species occurrence,abundance and intraspecific variability in community assembly: a trait‐based approach at the whole‐plant level in Mediterranean forests

Understanding which factors and rules govern the process of assembly in communities constitutes one of the main challenges of plant community ecology. The presence of certain functional strategies along broad environmental gradients can help to understand the patterns observed in community assembly and the filtering mechanisms that take place. We used a trait‐based approach, quantifying variations in aboveground (leaf and stem) and belowground (root) functional traits along environmental gradients in Mediterranean forest communities (south Spain). We proposed a new practical method to quantify the relative importance of species turnover (distinguishing between species occurrence and abundance) versus intraspecific variation, which allowed us to better understand the assemblage rules of these plant communities along environmental gradients. Our results showed that the functional structure of the studied plant communities was highly determined by soil environment. Results from our modelling approach based on maximum likelihood estimators showed a predominant influence of soil water storage on most of the community functional traits. We found that changes in community functional structure along environmental gradients were mainly promoted by species turnover rather than by intraspecific variability. Specifically, our new method of variance decomposition demonstrated that between‐site trait variation was the result of changes in species occurrence rather than in the abundance of certain dominant species. In conclusion, this study showed that water availability promoted the predominance of specific trait values (both in above and belowground fractions) associated to a resource acquisition or conservation strategy. In addition, we provided evidence that changes on community functional structure along the environmental gradient were mainly promoted by a process of species replacement, which represent a crucial step towards a more general understanding of the relative importance of intraspecific versus interspecific trait variation in these woody Mediterranean communities.     

Effects of exotic annual grass litter and local environmental gradients on annual plant community structure

Exotic annual grasses have been introduced into many semi-arid ecosystems worldwide, often to the detriment of native plant communities. The accumulation of litter from these grasses (i.e. residual dry biomass) has been demonstrated to negatively impact native plant communities and promote positive feedbacks to exotic grass persistence. More targeted experiments are needed, however, to determine the relative impact of exotic grass litter on plant community structure across local environmental gradients. We experimentally added exotic grass litter to annual forb-dominated open woodland communities positioned along natural canopy cover gradients in southwest Western Australia. These communities are an important component of this region’s plant biodiversity hotspot and are documented to be under threat from exotic annual grasses. After a one-year treatment period, we measured the effects of exotic grass litter, soil properties, and canopy cover on native and exotic species richness and abundance, as well as common species’ biomass and abundances. Plant community structure was more strongly influenced by soil properties and canopy cover than by grass litter. Total plant abundances per plot, however, were significantly lower in litter addition plots than control plots, a trend driven by native species. Exotic grass litter was also associated with lower abundances of one very common native species: Waitzia acuminata. Our results suggest that exotic grass litter limits the establishment of some native species in this system. Over multiple years, these subtle impacts may contribute substantially to the successful advancement of exotic species into this system, particularly in certain microenvironments.     

Synergistic epistasis enhances the co-operativity of mutualistic interspecies interactions

Early evolution of mutualism is characterized by big and predictable adaptive changes, including the specialization of interacting partners, such as through deleterious mutations in genes not required for metabolic cross-feeding. We sought to investigate whether these early mutations improve cooperativity by manifesting in synergistic epistasis between genomes of the mutually interacting species. Specifically, we have characterized evolutionary trajectories of syntrophic interactions of Desulfovibrio vulgaris (Dv) with Methanococcus maripaludis (Mm) by longitudinally monitoring mutations accumulated over 1000 generations of nine independently evolved communities with analysis of the genotypic structure of one community down to the single-cell level. We discovered extensive parallelism across communities despite considerable variance in their evolutionary trajectories and the perseverance within many evolution lines of a rare lineage of Dv that retained sulfate-respiration (SR+) capability, which is not required for metabolic cross-feeding. An in-depth investigation revealed that synergistic epistasis across pairings of Dv and Mm genotypes had enhanced cooperativity within SR− and SR+ assemblages, enabling their coexistence within the same community. Thus, our findings demonstrate that cooperativity of a mutualism can improve through synergistic epistasis between genomes of the interacting species, enabling the coexistence of mutualistic assemblages of generalists and their specialized variants.Subject terms: Microbial ecology, Population genetics, Symbiosis, Population dynamics, Molecular evolution     

Linking plant genes to insect communities: Identifying the genetic bases of plant traits and community composition

Community genetics aims to understand the effects of intraspecific genetic variation on community composition and diversity, thereby connecting community ecology with evolutionary biology. Thus far, research has shown that plant genetics can underlie variation in the composition of associated communities (e.g., insects, lichen and endophytes), and those communities can therefore be considered as extended phenotypes. This work, however, has been conducted primarily at the plant genotype level and has not identified the key underlying genes. To address this gap, we used genome‐wide association mapping with a population of 445 aspen (Populus tremuloides) genets to identify the genes governing variation in plant traits (defence chemistry, bud phenology, leaf morphology, growth) and insect community composition. We found 49 significant SNP associations in 13 Populus genes that are correlated with chemical defence compounds and insect community traits. Most notably, we identified an early nodulin‐like protein that was associated with insect community diversity and the abundance of interacting foundation species (ants and aphids). These findings support the concept that particular plant traits are the mechanistic link between plant genes and the composition of associated insect communities. In putting the “genes” into “genes to ecosystems ecology”, this work enhances understanding of the molecular genetic mechanisms that underlie plant–insect associations and the consequences thereof for the structure of ecological communities.     

Phylogenetic diversity and the functioning of ecosystems

Phylogenetic diversity (PD) describes the total amount of phylogenetic distance among species in a community. Although there has been substantial research on the factors that determine community PD, exploration of the consequences of PD for ecosystem functioning is just beginning. We argue that PD may be useful in predicting ecosystem functions in a range of communities, from single-trophic to complex networks. Many traits show a phylogenetic signal, suggesting that PD can estimate the functional trait space of a community, and thus ecosystem functioning. Phylogeny also determines interactions among species, and so could help predict how extinctions cascade through ecological networks and thus impact ecosystem functions. Although the initial evidence available suggests patterns consistent with these predictions, we caution that the utility of PD depends critically on the strength of phylogenetic signals to both traits and interactions. We advocate for a synthetic approach that incorporates a deeper understanding of how traits and interactions are shaped by evolution, and outline key areas for future research. If these complexities can be incorporated into future studies, relationships between PD and ecosystem function bear promise in conceptually unifying evolutionary biology with ecosystem ecology.     

Regeneration niche differentiates functional strategies of desert woody plant species

Plant communities vary dramatically in the number and relative abundance of species that exhibit facilitative interactions, which contributes substantially to variation in community structure and dynamics. Predicting species’ responses to neighbors based on readily measurable functional traits would provide important insight into the factors that structure plant communities. We measured a suite of functional traits on seedlings of 20 species and mature plants of 54 species of shrubs from three arid biogeographic regions. We hypothesized that species with different regeneration niches—those that require nurse plants for establishment (beneficiaries) versus those that do not (colonizers)—are functionally different. Indeed, seedlings of beneficiary species had lower relative growth rates, larger seeds and final biomass, allocated biomass toward roots and height at a cost to leaf mass fraction, and constructed costly, dense leaf and root tissues relative to colonizers. Likewise at maturity, beneficiaries had larger overall size and denser leaves coupled with greater water use efficiency than colonizers. In contrast to current hypotheses that suggest beneficiaries are less “stress-tolerant” than colonizers, beneficiaries exhibited conservative functional strategies suited to persistently dry, low light conditions beneath canopies, whereas colonizers exhibited opportunistic strategies that may be advantageous in fluctuating, open microenvironments. In addition, the signature of the regeneration niche at maturity indicates that facilitation expands the range of functional diversity within plant communities at all ontogenetic stages. This study demonstrates the utility of specific functional traits for predicting species’ regeneration niches in hot deserts, and provides a framework for studying facilitation in other severe environments.     

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.     

Integrating correlation between traits improves spatial predictions of plant functional composition

Functional trait composition is increasingly recognized as key to better understand and predict community responses to environmental gradients. Predictive approaches traditionally model the weighted mean trait values of communities (CWMs) as a function of environmental gradients. However, most approaches treat traits as independent regardless of known tradeoffs between them, which could lead to spurious predictions. To address this issue, we suggest jointly modeling a suit of functional traits along environmental gradients while accounting for relationships between traits. We use generalized additive mixed effect models to predict the functional composition of alpine grasslands in the Guisane Valley (France). We demonstrate that, compared to traditional approaches, joint trait models explain considerable amounts of variation in CWMs, yield less uncertainty in trait CWM predictions and provide more realistic spatial projections when extrapolating to novel environmental conditions. Modeling traits and their co‐variation jointly is an alternative and superior approach to predicting traits independently. Additionally, compared to a ‘predict first, assemble later’ approach that estimates trait CWMs post hoc based on stacked species distribution models, our ‘assemble first, predict later’ approach directly models trait‐responses along environmental gradients, and does not require data and models on species’ distributions, but only mean functional trait values per community plot. This highlights the great potential of joint trait modeling approaches in large‐scale mapping applications, such as spatial projections of the functional composition of vegetation and associated ecosystem services as a response to contemporary global change.     

Community traits affect plant–plant interactions across climatic gradients

Plant abundances and demography often vary along gradients of environmental stress, and neighboring plants can amplify or diminish such variation. We asked to what degree the effects of neighboring plants on a focal species can be explained by the traits and abundances of species in the surrounding community. We studied a common understory herb, Trientalis latifolia, across climatic gradients created by topography in the Siskiyou Mountains, southwestern Oregon. We compared Trientalis fitness along these gradients with and without neighbor removal, and asked whether the effects of neighboring plants could be predicted by their community‐weighted trait values and abundances. Environmental conditions alone did not explain whether neighbors had competitive or facilitative effects on Trientalis. However, the environment interacted with neighbor traits and biomass to influence neighbor effects: at cool, higher elevations, high neighbor biomass was associated with stronger facilitative effects, while at warm, lower elevations, high neighbor dissimilarity from Trientalis was associated with stronger competitive effects. We suggest that covariation and interactions among environmental and community characteristics are key to understanding species performance along climatic gradients.