Limitations of trait‐based approaches for stressor assessment: The case of freshwater invertebrates and climate drivers

The appeal of trait‐based approaches for assessing environmental vulnerabilities arises from the potential insight they provide into the mechanisms underlying the changes in populations and community structure. Traits can provide ecologically based explanations for observed responses to environmental changes, along with predictive power gained by developing relationships between traits and environmental variables. Despite these potential benefits, questions remain regarding the utility and limitations of these approaches, which we explore focusing on the following questions: (a) How reliable are predictions of biotic responses to changing conditions based on single trait–environment relationships? (b) What factors constrain detection of single trait–environment relationships, and how can they be addressed? (c) Can we use information on meta‐community processes to reveal conditions when assumptions underlying trait‐based studies are not met? We address these questions by reviewing published literature on aquatic invertebrate communities from stream ecosystems. Our findings help to define factors that influence the successful application of trait‐based approaches in addressing the complex, multifaceted effects of changing climate conditions on hydrologic and thermal regimes in stream ecosystems. Key conclusions are that observed relationships between traits and environmental stressors are often inconsistent with predefined hypotheses derived from current trait‐based thinking, particularly related to single trait–environment relationships. Factors that can influence findings of trait‐based assessments include intercorrelations of among traits and among environmental variables, spatial scale, strength of biotic interactions, intensity of habitat disturbance, degree of abiotic stress, and methods of trait characterization. Several recommendations are made for practice and further study to address these concerns, including using phylogenetic relatedness to address intercorrelation. With proper consideration of these issues, trait‐based assessment of organismal vulnerability to environmental changes can become a useful tool to conserve threatened populations into the future.     

Fish assemblage convergence along stream environmental gradients: an intercontinental analysis

Species that pass through similar environmental filters, regardless of geographic proximity or evolutionary history, are expected to share many traits, resulting in similar assemblage trait distributions. Convergence of assemblage trait distributions among different biotic regions would indicate that consistent ecological processes produce repeated patterns of adaptive evolution. This study analyzes trait–environment relationships across multiple stream fish assemblages representing evolutionarily divergent faunas. We hypothesized that trait–environment patterns converge across regional faunas in response to a common set of environmental filters acting on functional traits. One hundred and ninety‐seven species and forty streams were sampled from five regions: Belize, Benin, Brazil, Cambodia and USA. By examining trait–environment plots, multiple congruent trait–environment patterns were found across all regions, indicative of a consistent set of environmental filters acting on local community assembly. The consistency of these patterns strongly suggests that water velocity and habitat structural complexity function as universal environmental filters, producing similar assemblage trait distributions in streams across all regions. Bivariate relationships were not universal, and only one of the associations between a single functional trait and single environmental variable was statistically significant across all five regions. Strong phylogenetic signal was found in traits and habitat use, which implies that niche conservatism also influenced assemblage trait distributions. Overall, results support the idea that habitat templates structure trait distributions of stream fish assemblages and do so in a consistent manner.     

On the importance of trait interrelationships for understanding environmental responses of stream macroinvertebrates

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Common ancestry or environmental trait filters: cross‐continental comparisons of trait–habitat relationships in tropical anuran amphibian assemblages

Aim To investigate whether trait–habitat relations in biological communities converge across three global regions. The goal is to assess the role of habitat templets in shaping trait assemblages when different assembly mechanisms are operating and to test whether trait–habitat relations reflect a common evolutionary history or environmental trait filters. Location Guiana Shield, South America; Upper Guinea Forest Block, West Africa; Borneo rain forests, Southeast Asia. Methods We compared large anuran amphibian data sets at both the regional and cross‐continental scale. We applied a combination of three‐table ordinations (RLQ) and permutation model‐based multivariate fourth‐corner statistics to test for trait–habitat relationships at both scales and used phylogenetic comparative methods to quantify phylogenetic signal in traits that enter these analyses. Results Despite the existence of significant trait–habitat links and congruent trait patterns, we did not find evidence for the existence of a universal trait–habitat relationship at the assemblage level and no clear sign for cross‐continental convergence of trait–habitat relations. Patterns rather varied between continents. Despite the fact that a number of traits were conserved across phylogenies, the phylogenetic signal varied between regions. Trait–habitat relations therefore not only reflect a common evolutionary history, but also more recently operating environmental trait filters that ultimately determine the trait composition in regional assemblages. Main conclusions Integrating trait–habitat links into analyses of biological assemblages can enhance the predictive power and general application of species assembly rules in community and macroecology, particularly when phylogenetic comparative methods are simultaneously applied. However, in order to predict trait composition based on habitat templets, trait–habitat links cannot be assumed to be universal but rather have to be individually established in different regions prior to model building. Only then can direct trait‐based approaches be useful tools for predicting fundamental community patterns.     

Survival rates indicate that correlations between community‐weighted mean traits and environments can be unreliable estimates of the adaptive value of traits

Correlations between community‐weighted mean (CWM) traits and environmental gradients are often assumed to quantify the adaptive value of traits. We tested this assumption by comparing these correlations with models of survival probability using 46 perennial species from long‐term permanent plots in pine forests of Arizona. Survival was modelled as a function of trait × environment interactions, plant size, climatic variation and neighbourhood competition. The effect of traits on survival depended on the environmental conditions, but the two statistical approaches were inconsistent. For example, CWM‐specific leaf area (SLA) and soil fertility were uncorrelated. However, survival was highest for species with low SLA in infertile soil, a result which agreed with expectations derived from the physiological trade‐off underpinning leaf economic theory. CWM trait–environment relationships were unreliable estimates of how traits affected survival, and should only be used in predictive models when there is empirical support for an evolutionary trade‐off that affects vital rates.     

Towards a functional basis for predicting vegetation patterns; incorporating plant traits in habitat distribution models

Reliably predicting vegetation distribution requires habitat distribution models (HDMs) that are ecologically sound. Current correlative HDMs are increasingly criticized because they lack sufficient functional basis. To include functional information into these models, we integrated two concepts from community ecology into a new type of HDM. We incorporated: 1) species selection by their traits in which only those species that pass the environmental filter can be part of the community (assembly theory); 2) that the occurrence probability of a community is determined by the extent to which the community mean traits fit the required traits as set by the environment. In this paper, our trait‐based HDM is presented and its predictive capacity explored. Our approach consists of two steps. In step 1, four plant traits (stem‐specific density and indicator values for nutrients, moisture and acidity) are predicted from four dominant environmental drivers (disturbance, nutrient supply, moisture supply and acidity) using regression. In step 2, these traits are used to predict the occurrence probability of 13 vegetation types, covering the majority of vegetation types across the Netherlands. The model was validated by comparison to the observed vegetation type for 263 plots in the Netherlands. Model performance was within the range of conventional HDMs and decreased with increasing uncertainty in the environment‐trait relationships and with an increasing number of vegetation types. This study shows that including functionality into HDMs is not necessarily at the cost of model performance, while it has several conceptual advantages among including an increased insight in the functional characteristics of the vegetation and sources of unpredictability in community assembly. As such it is a promising first step towards more functional HDMs. Further development of a trait‐based HDM hinges on replacing indicator values by truly functional traits and the translation of these relationships into mechanistic relationships.     

Linking trait variation to the environment: critical issues with community‐weighted mean correlation resolved by the fourth‐corner approach

Establishing trait–environment relationships has become routine in community ecology. Here, we demonstrate that the community weighted means correlation (CWM) and its parallel approach in linking trait variation to the environment, the species niche centroid correlation (SNC), have important shortcomings, arguing against their continuing application. Using mathematical derivations and simulations, we show that the two major issues are inconsistent parameter estimation and unacceptable significance rates when only the environment or only traits are structuring species distributions, but they themselves are not linked. We show how both CWM and SNC are related to the fourth‐corner correlation and propose to replace all by the Chessel fourth‐corner correlation, which is the fourth‐corner correlation divided by its maximum attainable value. We propose an appropriate hypothesis testing procedure that is not only unbiased but also has much greater statistical power in detecting trait–environmental relationships. We derive an additive framework in which trait variation is partitioned among and within communities, which can be then modeled against the environment. We finish by presenting a contrast between methods and an application of our proposed framework across 85 lake‐fish metacommunities.     

Integrating life history traits into predictive phylogeography

Predictive phylogeography seeks to aggregate genetic, environmental and taxonomic data from multiple species in order to make predictions about unsampled taxa using machine‐learning techniques such as Random Forests. To date, organismal trait data have infrequently been incorporated into predictive frameworks due to difficulties inherent to the scoring of trait data across a taxonomically broad set of taxa. We refine predictive frameworks from two North American systems, the inland temperate rainforests of the Pacific Northwest and the Southwestern Arid Lands (SWAL), by incorporating a number of organismal trait variables. Our results indicate that incorporating life history traits as predictor variables improves the performance of the supervised machine‐learning approach to predictive phylogeography, especially for the SWAL system, in which predictions made from only taxonomic and climate variables meets only moderate success. In particular, traits related to reproduction (e.g., reproductive mode; clutch size) and trophic level appear to be particularly informative to the predictive framework. Predictive frameworks offer an important mechanism for integration of organismal trait, environmental data, and genetic data in phylogeographic studies.     

Strong patterns of intraspecific variation and local adaptation in Great Basin plants revealed through a review of 75 years of experiments

Variation in natural selection across heterogeneous landscapes often produces (a) among‐population differences in phenotypic traits, (b) trait‐by‐environment associations, and (c) higher fitness of local populations. Using a broad literature review of common garden studies published between 1941 and 2017, we documented the commonness of these three signatures in plants native to North America's Great Basin, an area of extensive restoration and revegetation efforts, and asked which traits and environmental variables were involved. We also asked, independent of geographic distance, whether populations from more similar environments had more similar traits. From 327 experiments testing 121 taxa in 170 studies, we found 95.1% of 305 experiments reported among‐population differences, and 81.4% of 161 experiments reported trait‐by‐environment associations. Locals showed greater survival in 67% of 24 reciprocal experiments that reported survival, and higher fitness in 90% of 10 reciprocal experiments that reported reproductive output. A meta‐analysis on a subset of studies found that variation in eight commonly measured traits was associated with mean annual precipitation and mean annual temperature at the source location, with notably strong relationships for flowering phenology, leaf size, and survival, among others. Although the Great Basin is sometimes perceived as a region of homogeneous ecosystems, our results demonstrate widespread habitat‐related population differentiation and local adaptation. Locally sourced plants likely harbor adaptations at rates and magnitudes that are immediately relevant to restoration success, and our results suggest that certain key traits and environmental variables should be prioritized in future assessments of plants in this region.     

Taxonomic and biological trait differences of stream macroinvertebrate communities between mediterranean and temperate regions: implications for future climatic scenarios

Streams in mediterranean regions have highly seasonal discharge patterns, with predictable torrential floods and severe droughts. In contrast, discharge is less variable in temperate regions and intermittent flow conditions are uncommon. Hydroclimatic models predict that climate change would increase frequency and severity of floods and droughts across Europe, thus increasing the proportion of streams with mediterranean characteristics in actually temperate areas. Correspondingly, understanding actual ecological differences between mediterranean and temperate streams may help to anticipate large‐scale ecological impacts of climate change. Given that large‐scale factors determine local community composition, we hypothesized that climatic differences between mediterranean and temperate regions should affect the taxonomic and biological trait composition in streams. We assembled the abundance of stream macroinvertebrate genera of 265 sites each from the Mediterranean Basin and from temperate Europe and linked these abundances to published information on 61 categories of 11 biological traits reflecting the potential of resilience from and resistance to disturbances. Although regional taxonomic richness was higher in the mediterranean than in the temperate region, local taxonomic richness and diversity did not significantly differ between regions. Local trait richness and diversity were significantly higher in the mediterranean region. Both local taxonomic and trait‐community composition differed between regions, but the former varied much more than the latter, highlighting that climate change could produce large changes in the taxonomic but rather weak changes in the trait composition. The mediterranean region was characterized by macroinvertebrates with higher dispersion and colonization capabilities, suggesting that species loss in the temperate region, by extinction or northward emigration of taxa, would be compensated for by immigration of southern mediterranean taxa. Thus, climate change would likely have stronger implications for the local conservation of taxa than for the trait composition of stream macroinvertebrate communities.     

Differential effects of functional traits on aboveground biomass in semi-natural grasslands

Despite increasing evidence on the importance of species functional characteristics for ecosystem processes, two major hypotheses suggest different mechanisms: the ‘mass ratio hypothesis’ assumes that functional traits of the dominant species determine ecosystem processes, while the ‘complementarity hypothesis’ predicts that resource niches may be used more completely when a community is functionally more diverse. Here, we present a method which uses two different groups of biotic predictor variables being (1) abundance‐weighted mean (=aggregated) trait values and (2) functional trait diversity based on Rao's quadratic diversity (FD_Q) to test the competing hypotheses on biodiversity–ecosystem functioning relationships after accounting for co‐varying abiotic factors. We applied this method to data recorded on biodiversity–biomass relationships and environmental variables in 35 semi‐natural temperate grasslands and used a literature‐based matrix of fourteen plant functional traits to assess the explanatory power of models including different sets of predictor variables. Aboveground community biomass did not correlate with species richness. Abiotic factors, in particular soil nitrogen concentration, explained about 50% of variability in aboveground biomass. The best model incorporating functional trait diversity explained only about 30%, while the best model based on aggregated trait values explained about 54% of variability in aboveground biomass. The inclusion of all predictor variable groups in a combined model increased the predictive power to about 75%. This model comprised soil nitrogen concentration as abiotic factor, aggregated traits being indicative for species competitive dominance (rooting depth, leaf distribution, specific leaf area, perennial life cycle) and functional trait diversity in vegetative plant height, leaf area and life cycle. Our study strongly suggests that abiotic factors, trait values of the dominant species and functional trait diversity in combination may best explain differences in aboveground community biomass in natural ecosystems and that their isolated consideration may be misleading.     

Stress from cold and drought as drivers of functional trait spectra in North American angiosperm tree assemblages

Understanding how environmental change alters the composition of plant assemblages, and how this in turn affects ecosystem functioning is a major challenge in the face of global climate change. Assuming that values of plant traits express species adaptations to the environment, the trait‐based approach is a promising way to achieve this goal. Nevertheless, how functional traits are related to species’ environmental tolerances and how trait spectra respond to broad‐scale environmental gradients remains largely unexplored. Here, we identify the main trait spectra for US angiosperm trees by testing hypotheses for the relationships between functional traits and species’ environmental tolerances to environmental stresses, as well as quantifying the environmental drivers of assemblage means and variances of these traits. We analyzed >74,000 community assemblages from the US Forest Inventory and Analysis using 12 functional traits, five traits expressing species’ environmental tolerances and 10 environmental variables. Results indicated that leaf traits, dispersal traits, and traits related to stem hydraulics were related to cold or drought tolerance, and their assemblage means were best explained by minimum temperatures. Assemblage means of traits related to shade tolerance (tree growth rate, leaf phosphorus content, and bark thickness) were best explained by aridity index. Surprisingly, aridity index, rather than minimum temperature, was the best predictors of assemblage variances of most traits, although these relationships were variable and weak overall. We conclude that temperature is likely to be the most important driver of functional community structure of North American angiosperm trees by selecting for optimum strategies along the cold and drought stress trade‐off. In turn, water availability primarily affects traits related to shade tolerance through its effect on forest canopy structure and vegetation openness.     

Divergent biogeography of native and introduced soil macroinvertebrates in North America north of Mexico

To improve understanding of the biogeographical consequences of species introduction, we examined whether introduced soil macroinvertebrates differ from natives in the relationship between species richness and key environmental predictors, and whether such differences affect the relationship between native and introduced species richness. For North America north of Mexico, we summarized jurisdiction occurrence data for seven macroinvertebrate taxa with strong influences on soil biodiversity or processes. We analysed the relationships of native and introduced species richness to each other using linear regression; to latitude using Gaussian regressions; and, using the residuals of the richness–latitude regressions, to distance from coasts, human population density, and human population size using regression and correlation. We found weak to strong positive relationships between native and introduced species richness. This variation was related to divergent relationships of native and introduced species with latitude, human population density, and distance from coasts. Native species richness declined with increasing latitude for all taxa, as did introduced species richness for taxa with predominantly lower‐latitude origins (ants, termites, non‐lumbricid earthworms). In contrast, introduced species richness peaked at higher latitudes for four taxa of predominantly Palearctic origins (weevils, ground beetles, lumbricid earthworms, isopods). Partitioning introduced taxa within these groups based on region of origin, we found that Palearctic taxa were distributed at higher latitudes than non‐Palearctic taxa. Thus source region appears to strongly influence introduced species richness–latitude relationships. Compared to natives, introduced species exhibited more positive relationships with human population density and negative relationships with distance from coasts, but did not differ in relationships with human population size. Thus coastal, densely populated regions are likely to have a higher proportion of introduced soil macroinvertebrate species. These differences between distribution of native and introduced species tend to weaken positive correlations between native and introduced species richness, especially for taxa dominated by Palearctic introductions.     

A 7000‐year history of changing plant trait composition in an Amazonian landscape; the role of humans and climate

Tropical forests are shifting in species and trait composition, but the main underlying causes remain unclear because of the short temporal scales of most studies. Here, we develop a novel approach by linking functional trait data with 7000 years of forest dynamics from a fossil pollen record of Lake Sauce in the Peruvian Amazon. We evaluate how climate and human disturbances affect community trait composition. We found weak relationships between environmental conditions and traits at the taxon level, but strong effects for community‐mean traits. Overall, community‐mean traits were more responsive to human disturbances than to climate change; human‐induced erosion increased the dominance of dense‐wooded, non‐zoochorous species with compound leaves, and human‐induced fire increased the dominance of tall, zoochorous taxa with large seeds and simple leaves. This information can help to enhance our understanding of forest responses to past environmental changes, and improve predictions of future changes in tropical forest composition.     

Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping

Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time‐consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation–environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation–environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation–environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well‐structured vegetation–environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation–environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.     

The interplay among intraspecific leaf trait variation,niche breadth and species abundance along light and soil nutrient gradients

It is assumed that widespread, generalist species have high phenotypic variation, but we know little about how intraspecific trait variation (ITV) relates to species abundance and niche breadth. In the temperate rainforest of southern Chile, we hypothesized that species with wide niche breadth would exhibit 1) high among‐plot ITV, 2) a strong relationship between trait values and the environment, and 3) a close fit between traits and local environment trait optima. We measured leaf functional traits (leaf area, LMA, leaf N and P concentrations) of saplings in woody species, and compared the relative abundance of each species with its niche breadth, measured as the range of light, soil N and P availability. We used the slope of the linear regression of species’ trait–environment relationships to assess the strength and direction of these relationships, and measured the degree to which species’ trait values track the environmental optimum across plots. In some cases, species having wide niche breadth had high ITV in leaf N and also matched traits (LMA and leaf P) to local optima along the light gradient; they also had high ITV in general and matched leaf P to local optima along the soil P gradient. The relationship between species with wide niche breadth and the strength of intraspecific trait–environment relationships was generally weak and varied depending on the niche dimension and trait in question. Species varied considerably in the strength of trait–environment relationships and total magnitude of ITV, and this variation was not generally strongly related to species abundances or niche breadth patterns. In conclusion, trait variation at the community level is not driven by a few abundant, widely distributed species, but depends on the aggregate trait responses of both abundant and rare species. This makes it difficult to scale individual species trait responses up to the community level.     

PLANT RESPONSES TO CLIMATE IN THE CAPE FLORISTIC REGION OF SOUTH AFRICA: EVIDENCE FOR ADAPTIVE DIFFERENTIATION IN THE PROTEACEAE

Local adaptation along environmental gradients may drive plant species radiation within the Cape Floristic Region (CFR), yet few studies examine the role of ecologically based divergent selection within CFR clades. In this study, we ask whether populations within the monophyletic white protea clade (Protea section Exsertae, Proteaceae) differ in key functional traits along environmental gradients and whether differences are consistent with local adaptation. Using seven taxa, we measured trait–environment associations and selection gradients across 35 populations of wild adults and their offspring grown in two common gardens. Focal traits were leaf size and shape, specific leaf area (SLA), stomatal density, growth, and photosynthetic rate. Analyses on wild and common garden plants revealed heritable trait differences that were associated with gradients in rainfall seasonality, drought stress, cold stress, and less frequently, soil fertility. Divergent selection between gardens generally matched trait–environment correlations and literature‐based predictions, yet variation in selection regimes among wild populations generally did not. Thus, selection via seedling survival may promote gradient‐wide differences in SLA and leaf area more than does selection via adult fecundity. By focusing on the traits, life stages, and environmental clines that drive divergent selection, our study uniquely demonstrates adaptive differentiation among plant populations in the CFR.     

Intraspecific variation in epiphyte functional traits reveals limited effects of microclimate on community assembly in temperate deciduous oak canopies

Forest canopies are heterogeneous environments where changes in microclimate over short distances create an opportunity for niche‐based filtering of canopy‐dwelling species assemblages. This environmental filtering may not occur if species' physiological capacities are flexible or if rapid dispersal alleviates compositional differences. I assess the role of humidity, light and temperature gradients in structuring epiphyte communities in temperate deciduous oak (Quercus) canopies and determine whether gradients filter species with fixed traits or whether environmental constraints act primarily to alter individual phenotypes. I measured environmental conditions and seven functional traits related to water and light acquisition on individual macrolichens at 60 sample locations in northern red oaks Quercus rubra in two Piedmont forests in North Carolina, USA. The effects of environmental variables on individual‐level traits and community composition were evaluated using linear mixed models and constrained ordination (RDA). In general, traits and community composition responded weakly to environmental variables and trait variation within taxa was high. Cortex thickness exhibited the strongest response, such that individuals with thicker cortices were found in samples experiencing lower humidity and higher light levels. Overall, gradients of humidity, light and temperature were not strong environmental filters that caused large changes in community composition. This was probably due to phenotypic variability within taxa that enabled species to persist across the full range of environmental conditions measured. Thus, humidity affected the phenotype of individuals, but did not limit species distributions or alter community composition at the scale of branches within trees. Community and trait responses were primarily associated with site‐level differences in humidity, suggesting that in these forests landscape‐scale climatic gradients may be stronger drivers of epiphyte community assembly than intra‐canopy environmental gradients.     

Leaf trait-environment relationships in a subtropical broadleaved forest in South-East China

Although trait analyses have become more important in community ecology, trait-environment correlations have rarely been studied along successional gradients. We asked which environmental variables had the strongest impact on intraspecific and interspecific trait variation in the community and which traits were most responsive to the environment. We established a series of plots in a secondary forest in the Chinese subtropics, stratified by successional stages that were defined by the time elapsed since the last logging activities. On a total of 27 plots all woody plants were recorded and a set of individuals of every species was analysed for leaf traits, resulting in a trait matrix of 26 leaf traits for 122 species. A Fourth Corner Analysis revealed that the mean values of many leaf traits were tightly related to the successional gradient. Most shifts in traits followed the leaf economics spectrum with decreasing specific leaf area and leaf nutrient contents with successional time. Beside succession, few additional environmental variables resulted in significant trait relationships, such as soil moisture and soil C and N content as well as topographical variables. Not all traits were related to the leaf economics spectrum, and thus, to the successional gradient, such as stomata size and density. By comparing different permutation models in the Fourth Corner Analysis, we found that the trait-environment link was based more on the association of species with the environment than of the communities with species traits. The strong species-environment association was brought about by a clear gradient in species composition along the succession series, while communities were not well differentiated in mean trait composition. In contrast, intraspecific trait variation did not show close environmental relationships. The study confirmed the role of environmental trait filtering in subtropical forests, with traits associated with the leaf economics spectrum being the most responsive ones.     

Environmental,spatial and phylogenetic determinants of fish life‐history traits and functional composition of Australian rivers

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