Taxon sampling, correlated evolution, and independent contrasts

Independent contrasts are widely used to incorporate phylogenetic information into studies of continuous traits, particularly analyses of evolutionary trait correlations, but the effects of taxon sampling on these analyses have received little attention. In this paper, simulations were used to investigate the effects of taxon sampling patterns and alternative branch length assignments on the statistical performance of correlation coefficients and sign tests; "full-tree" analyses based on contrasts at all nodes and "paired-comparisons" based only on contrasts of terminal taxon pairs were also compared. The simulations showed that random samples, with respect to the traits under consideration, provide statistically robust estimates of trait correlations. However, exact significance tests are highly dependent on appropriate branch length information; equal branch lengths maintain lower Type I error than alternative topological approaches, and adjusted critical values of the independent contrast correlation coefficient are provided for use with equal branch lengths. Nonrandom samples, with respect to univariate or bivariate trait distributions, introduce discrepancies between interspecific and phylogenetically structured analyses and bias estimates of underlying evolutionary correlations. Examples of nonrandom sampling processes may include community assembly processes, convergent evolution under local adaptive pressures, selection of a nonrandom sample of species from a habitat or life-history group, or investigator bias. Correlation analyses based on species pairs comparisons, while ignoring deeper relationships, entail significant loss of statistical power and as a result provide a conservative test of trait associations. Paired comparisons in which species differ by a large amount in one trait, a method introduced in comparative plant ecology, have appropriate Type I error rates and high statistical power, but do not correctly estimate the magnitude of trait correlations. Sign tests, based on full-tree or paired-comparison approaches, are highly reliable across a wide range of sampling scenarios, in terms of Type I error rates, but have very low power. These results provide guidance for selecting species and applying comparative methods to optimize the performance of statistical tests of trait associations.     

An index for measuring functional extension and evenness in trait space

Most existing functional diversity indices focus on a single facet of functional diversity. Although these indices are useful for quantifying specific aspects of functional diversity, they often present some conceptual or practical limitations in estimating functional diversity. Here, we present a new functional extension and evenness (FEE) index that encompasses two important aspects of functional diversity. This new index is based on the straightforward notion that a community has high diversity when its species are distant from each other in trait space. The index quantifies functional diversity by evaluating the overall extension of species traits and the interspecific differences of a species assemblage in trait space. The concept of minimum spanning tree (MST) of points was adopted to obtain the essential distribution properties for a species assembly in trait space. We combined the total length of MST branches (extension) and the variation of branch lengths (evenness) into a raw FEE₀ metric and then translated FEE₀ to a species richness‐independent FEE index using a null model approach. We assessed the properties of FEE and used multiple approaches to evaluate its performance. The results show that the FEE index performs well in quantifying functional diversity and presents the following desired properties: (a) It allows a fair comparison of functional diversity across different species richness levels; (b) it preserves the essence of single‐facet indices while overcoming some of their limitations; (c) it standardizes comparisons among communities by taking into consideration the trait space of the shared species pool; and (d) it has the potential to distinguish among different community assembly processes. With these attributes, we suggest that the FEE index is a promising metric to inform biodiversity conservation policy and management, especially in applications at large spatial and/or temporal scales.     

Evolutionary Diversification of Continuous Traits: Phylogenetic Tests and Application to Seed Size in the California Flora

Evolutionary diversification of a phenotypic trait reflects the tempo and mode of trait evolution, as well as the phylogenetic topology and branch lengths. Comparisons of trait variance between sister groups provide a powerful approach to test for differences in rates of diversification, controlling for differences in clade age. We used simulation analyses under constant rate Brownian motion to develop phylogenetically based F-tests of the ratio of trait variances between sister groups. Random phylogenies were used for a generalized evolutionary null model, so that detailed internal phylogenies are not required, and both gradual and speciational models of evolution were considered. In general, phylogenetically structured tests were more conservative than corresponding parametric statistics (i.e., larger variance ratios are required to achieve significance). The only exception was for comparisons under a speciational evolutionary model when the group with higher variance has very low sample size (number of species). The methods were applied to a large data set on seed size for 1976 species of California flowering plants. Seven of 37 sister-group comparisons were significant for the phylogenetically structured tests (compared to 12 of 37 for the parametric F-test). Groups with higher diversification of seed size generally had a greater diversity of fruit types, life form, or life history as well. The F-test for trait variances provides a simple, phylogenetically structured approach to test for differences in rates of phenotypic diversification and could also provide a valuable tool in the study of adaptive radiations.     

The functional trait space of tree species is influenced by the species richness of the canopy and the type of forest

Analysing how species modify their trait expression along a diversity gradient brings insight about the role that intraspecific variability plays over species interactions, e.g. competition versus complementarity. Here, we evaluated the functional trait space of nine tree species dominant in three types of European forests (a continental‐Mediterranean, a mountainous mixed temperate and a boreal) growing in communities with different species richness in the canopy, including pure stands. We compiled whole‐plant and leaf traits in 1719 individuals, and used them to quantify species trait hypervolumes in communities with different tree species richness. We investigated changes along the species richness gradient to disentangle species responses to the neighbouring environment, in terms of hypervolume size (trait variance), shape (trait relative importance) and centroid translation (shifts of mean trait values) using null models. Our main results showed differences in trait variance and shifts of mean values along the tree diversity gradient, with shorter trees but with larger crowns in mixed stands. We found constrained functional spaces (trait convergence) in pure stands, suggesting an important intraspecific competition, and expanded functional spaces (trait divergence) in two‐species admixtures, suggesting competition release due to interspecific complementarity. Nevertheless, further responses to increasing species richness were different for each forest type, waning species complementarity in sites with limiting conditions for growth. Our results demonstrate that tree species phenotypes respond to the species richness in the canopy in European forests, boosting species complementarity at low level of canopy diversity and with a site‐specific pattern at greater level of species richness. These outcomes evidence the limitation of functional diversity measures based only on traits from pure stands or general trait database values.     

Assessing the Importance of Intraspecific Variability in Dung Beetle Functional Traits

Functional diversity indices are used to facilitate a mechanistic understanding of many theoretical and applied questions in current ecological research. The use of mean trait values in functional indices assumes that traits are robust, in that greater variability exists between than within species. While the assertion of robust traits has been explored in plants, there exists little information on the source and extent of variability in the functional traits of higher trophic level organisms. Here we investigated variability in two functionally relevant dung beetle traits, measured from individuals collected from three primary forest sites containing distinct beetle communities: body mass and back leg length. In doing so we too addressed the following questions: (i) what is the contribution of intra vs. interspecific differences in trait values; (ii) what sample size is needed to provide representative species mean trait values; and (iii) what impact does omission of intraspecific trait information have on the calculation of functional diversity (FD) indices from naturally assembled communities? At the population level, interspecific differences explained the majority of variability in measured traits (between 94% and 96%). In accordance with this, the error associated with calculating FD without inclusion of intraspecific variability was low, less than 20% in all cases. This suggests that complete sampling to capture intraspecific variance in traits is not necessary even when investigating the FD of small and/or naturally formed communities. To gain an accurate estimation of species mean trait values we encourage the measurement of 30–60 individuals and, where possible, these should be taken from specimens collected from the site of study.     

Contrasting Diversity Values: Statistical Inferences Based on Overlapping Confidence Intervals

Ecologists often contrast diversity (species richness and abundances) using tests for comparing means or indices. However, many popular software applications do not support performing standard inferential statistics for estimates of species richness and/or density. In this study we simulated the behavior of asymmetric log-normal confidence intervals and determined an interval level that mimics statistical tests with P(α) = 0.05 when confidence intervals from two distributions do not overlap. Our results show that 84% confidence intervals robustly mimic 0.05 statistical tests for asymmetric confidence intervals, as has been demonstrated for symmetric ones in the past. Finally, we provide detailed user-guides for calculating 84% confidence intervals in two of the most robust and highly-used freeware related to diversity measurements for wildlife (i.e., EstimateS, Distance).     

A comparison between two GAM models in quantifying relationships of environmental variables with fish richness and diversity indices

Various regression methods can be used to quantify the relationships between fish populations and their environment. Strong correlations often existing between environmental variables, however, can cause multicollinearity, resulting in overfitting in modeling. This study compares the performance of a regular generalized additive model (GAM) with raw environmental variables as explanatory variables (regular GAM) and a GAM based on principal component analysis (PCA-based GAM) in modeling the relationship between fish richness and diversity indices and environmental variables. The PCA-based GAM tended to perform better than the regular GAM in cross-validation tests, showing a higher prediction precision. The variables identified being significant in modeling differed between the two models, and differences between the two models were also found in the scope and range of predicted richness and diversity indices for demersal fish community. This implies that choices between these two statistical modeling approaches can lead to different ecological interpretations of the relationships between fish communities and their habitats. This study suggests that the PCA-based GAM is a better approach than the original GAM in quantifying the relationship between fish richness and diversity indices and environmental variables if the environmental variables are highly correlated.     

Functional diversity changes during tropical forest succession

Functional diversity (FD) ‘those components of biodiversity that influence how an ecosystem operates or functions’ is a promising tool to assess the effect of biodiversity loss on ecosystem functioning. FD has received ample theoretical attention, but empirical studies are limited. We evaluate changes in species richness and FD during tropical secondary forest succession after shifting cultivation in Mexico. We also test whether species richness is a good predictor of FD. FD was calculated based on a combination of nine functional traits, and based on two individual traits important for primary production (specific leaf area) and carbon sequestration (wood density). Stand basal area was a good predictor of successional changes in diversity and FD, in contrast to fallow age. Incidence-based FD indices increased logarithmically with stand basal area, but FD weighted by species’ importance values lacked pattern with succession. Species richness and diversity are strong predictors of FD when all traits were considered; linear relationships indicate that all species are equally functionally complementary, suggesting there is little functional redundancy. In contrast, when FD was calculated for individual traits and weighted for abundances, species richness may underestimate FD.Selection of functional trait(s) critically determines FD, with large consequences for studies relating biodiversity to ecosystem functioning. Careful consideration of the traits required to capture the ecosystem process of interest is thus essential.     

Human land use promotes the abundance and diversity of exotic species on Caribbean islands

Human land use causes major changes in species abundance and composition, yet native and exotic species can exhibit different responses to land use change. Native populations generally decline in human‐impacted habitats while exotic species often benefit. In this study, we assessed the effects of human land use on exotic and native reptile diversity, including functional diversity, which relates to the range of habitat use strategies in biotic communities. We surveyed 114 reptile communities from localities that varied in habitat structure and human impact level on two Caribbean islands, and calculated species richness, overall abundance, and evenness for every plot. Functional diversity indices were calculated using published trait data, which enabled us to detect signs of trait filtering associated with impacted habitats. Our results show that environmental variation among sampling plots was explained by two Principal Component Analysis (PCA) ordination axes related to habitat structure (i.e., forest or nonforest) and human impact level (i.e., addition of man‐made constructions such as roads and buildings). Several diversity indices were significantly correlated with the two PCA axes, but exotic and native species showed opposing responses. Native species reached the highest abundance in forests, while exotic species were absent in this habitat. Human impact was associated with an increase in exotic abundance and species richness, while native species showed no significant associations. Functional diversity was highest in nonforested environments on both islands, and further increased on St. Martin with the establishment of functionally unique exotic species in nonforested habitat. Habitat structure, rather than human impact, proved to be an important agent for environmental filtering of traits, causing divergent functional trait values across forested and nonforested environments. Our results illustrate the importance of considering various elements of land use when studying its impact on species diversity and the establishment and spread of exotic species.     

The ancestral distance test: what relatedness can reveal about correlated evolution in large lineages with missing character data and incomplete phylogenies

The ancestral distance test is introduced to detect correlated evolution between two binary traits in large phylogenies that may lack resolved subclades, branch lengths, and/or comparative data. We define the ancestral distance as the time separating a randomly sampled taxon from its most recent ancestor (MRA) with extant descendants that have an independent trait. The sampled taxon either has (target sample) or lacks (nontarget sample) a dependent trait. Modeled as a Markov process, we show that the distribution of ancestral distances for the target sample is identical to that of the nontarget sample when characters are uncorrelated, whereas ancestral distances are smaller on average for the target sample when characters are correlated. Simulations suggest that the ancestral distance can be estimated using the time, total branch length, taxonomic rank, or number of speciation events between a sampled taxon and the MRA. These results are shown to be robust to deviations from Markov assumptions. A Monte Carlo technique estimates P-values when fully resolved phylogenies with branch lengths are available, and we evaluate the Monte Carlo approach using a data set with known correlation. Measures of relatedness were found to provide a robust means to test hypotheses of correlated character evolution.     

Plant species’ coexistence relationships may shift according to life history traits and seasons

Although several studies have demonstrated that disturbance contributes to species’ diversity, little emphasis has been placed on the identification of species’ coexistence mechanisms related to life history traits. In this study, we compared species’ richness and components of plant communities around river confluences to explore how disturbance promotes the coexistence of species with different life history traits. Sites upstream and downstream of confluences are ideal for such comparisons because they draw on the same species’ pools and have similar ambient conditions, but differ markedly in the extents of flooding disturbance. We compared sites upstream and downstream of confluences by calculating species’ richness and community similarity indices for several life history traits in both summer and spring. In summer, the combined richness of all the species, of annual- and summer-flowering species, was higher downstream from confluences than upstream, but this was not the case for perennials. Similarity analyses suggested that plant communities are constructed according to a neutral process, whereby interactions between the coexisting species are neutral. However, in spring, species’ richness was similar upstream and downstream of confluences for all life history traits. Similarity analyses suggested that under these circumstances, the communities were constructed through a species-sorting process; i.e., each life history trait had a distinct habitat preference. Thus, the relative strengths of different community assembly processes may change seasonally. We concluded that species groups differing in their responses to disturbance may coexist in a single community. Thus, community structuring following disturbance may involve two processes: a neutral and a species-sorting process. The relative importance of each may vary between species’ life history traits and between seasons, and the interaction may account for current community structures.     

Functional flower traits and their diversity drive pollinator visitation

Recent studies have shown that the diversity of flowering plants can enhance pollinator richness and visitation frequency and thereby increase the resilience of pollination. It is assumed that flower traits explain these effects, but it is still unclear which flower traits are responsible, and knowing that, if pollinator richness and visitation frequency are more driven by mass‐ratio effects (mean trait values) or by trait diversity. Here, we analyse a three‐year data set of pollinator observations collected in a European grassland plant diversity experiment (The Jena experiment). The data entail comprehensive flower trait measurements, including reward traits (nectar and pollen amount), morphological traits (height, symmetry, area, colour spectra) and chemical traits (nectar‐amino acid and nectar‐sugar concentration). We test if pollinator species richness and visitation frequency of flower communities depend on overall functional diversity combining all flower traits within a community, single trait diversities (within trait variation) and community‐weighted means of the single traits, using Bayesian inference. Overall functional diversity did not affect pollinator species richness, but reduced visitation frequency. When looking at individual flower traits separately, we found that single trait diversity of flower reflectance and flower morphology were important predictors of pollinator visitation frequency. Moreover, independent of total flower abundance, community‐weighted means of flower height, area, reflectance, nectar‐sugar concentration and nectar‐amino acid concentration strongly affected both pollinator species richness and visitation frequency. Our results, challenge the idea that functional diversity always positively affects ecosystem functions. Nonetheless, we demonstrate that both single trait diversity and mass‐ratio effects of flower traits play an important role for diverse and frequent flower visits, which underlines the functionality of flower traits for pollination services.     

Correlated evolution in fig pollination

This is the first comparative study of correlated evolution between figs (Ficus species, Moraceae) and their pollinators (Hymenoptera: Agaoninae) based on molecular phylogenies of both lineages. Fig relationships based on the internal transcribed spacer region (ITS) of nuclear ribosomal DNA and pollinator relationships inferred from mitochondrial cytochrome oxidase I (COI) sequences enabled the study of correlated evolution based on molecular phylogenies for the largest set of interacting species ever compared. Comparative methods have been applied to tests of adaptation, but the application of these methods in tests of coadaptation, defined as reciprocal evolutionary change in interacting lineages, has received less attention. I have extended tests of correlated evolution between two traits along a phylogeny to the case of interacting lineages, where two traits may or may not share a common phylogenetic history. Independent contrasts and phylogenetic autocorrelation rejected the null hypothesis that trait correlations within lineages are stronger than trait correlations between interacting lineages. Fig style lengths and pollinator ovipositor lengths, for example, were more highly correlated than were pollinator body size and ovipositor length. Mutualistic interactions between figs and their pollinators illustrate the novel ways in which phylogenies and comparative methods can detect patterns of correlated evolution. The most outstanding evidence of correlated evolution between these obligate mutualists is that interacting trait correlations are stronger than within-lineage allometric relationships.     

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete‐case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete‐case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.     

Founding events in species invasions: genetic variation, adaptive evolution, and the role of multiple introductions

Invasive species are predicted to suffer from reductions in genetic diversity during founding events, reducing adaptive potential. Integrating evidence from two literature reviews and two case studies, we address the following questions: How much genetic diversity is lost in invasions? Do multiple introductions ameliorate this loss? Is there evidence for loss of diversity in quantitative traits? Do invaders that have experienced strong bottlenecks show adaptive evolution? How do multiple introductions influence adaptation on a landscape scale? We reviewed studies of 80 species of animals, plants, and fungi that quantified nuclear molecular diversity within introduced and source populations. Overall, there were significant losses of both allelic richness and heterozygosity in introduced populations, and large gains in diversity were rare. Evidence for multiple introductions was associated with increased diversity, and allelic variation appeared to increase over long timescales (~100 years), suggesting a role for gene flow in augmenting diversity over the long‐term. We then reviewed the literature on quantitative trait diversity and found that broad‐sense variation rarely declines in introductions, but direct comparisons of additive variance were lacking. Our studies of Hypericum canariense invasions illustrate how populations with diminished diversity may still evolve rapidly. Given the prevalence of genetic bottlenecks in successful invading populations and the potential for adaptive evolution in quantitative traits, we suggest that the disadvantages associated with founding events may have been overstated. However, our work on the successful invader Verbascum thapsus illustrates how multiple introductions may take time to commingle, instead persisting as a ‘mosaic of maladaptation’ where traits are not distributed in a pattern consistent with adaptation. We conclude that management limiting gene flow among introduced populations may reduce adaptive potential but is unlikely to prevent expansion or the evolution of novel invasive behaviour.     

TESTING FOR PHYLOGENETIC SIGNAL IN BIOLOGICAL TRAITS: THE UBIQUITY OF CROSS‐PRODUCT STATISTICS

To evaluate rates of evolution, to establish tests of correlation between two traits, or to investigate to what degree the phylogeny of a species assemblage is predictive of a trait value so‐called tests for phylogenetic signal are used. Being based on different approaches, these tests are generally thought to possess quite different statistical performances. In this article, we show that the Blomberg et al. K and K*, the Abouheif index, the Moran's I, and the Mantel correlation are all based on a cross‐product statistic, and are thus all related to each other when they are associated to a permutation test of phylogenetic signal. What changes is only the way phylogenetic and trait similarities (or dissimilarities) among the tips of a phylogeny are computed. The definitions of the phylogenetic and trait‐based (dis)similarities among tips thus determines the performance of the tests. We shortly discuss the biological and statistical consequences (in terms of power and type I error of the tests) of the observed relatedness among the statistics that allow tests for phylogenetic signal. Blomberg et al. K* statistic appears as one on the most efficient approaches to test for phylogenetic signal. When branch lengths are not available or not accurate, Abouheif's C_mean statistic is a powerful alternative to K*.     

Using Phylogenetic,Functional and Trait Diversity to Understand Patterns of Plant Community Productivity

Background

Two decades of research showing that increasing plant diversity results in greater community productivity has been predicated on greater functional diversity allowing access to more of the total available resources. Thus, understanding phenotypic attributes that allow species to partition resources is fundamentally important to explaining diversity-productivity relationships.

Methodology/Principal Findings

Here we use data from a long-term experiment (Cedar Creek, MN) and compare the extent to which productivity is explained by seven types of community metrics of functional variation: 1) species richness, 2) variation in 10 individual traits, 3) functional group richness, 4) a distance-based measure of functional diversity, 5) a hierarchical multivariate clustering method, 6) a nonmetric multidimensional scaling approach, and 7) a phylogenetic diversity measure, summing phylogenetic branch lengths connecting community members together and may be a surrogate for ecological differences. Although most of these diversity measures provided significant explanations of variation in productivity, the presence of a nitrogen fixer and phylogenetic diversity were the two best explanatory variables. Further, a statistical model that included the presence of a nitrogen fixer, seed weight and phylogenetic diversity was a better explanation of community productivity than other models.

Conclusions

Evolutionary relationships among species appear to explain patterns of grassland productivity. Further, these results reveal that functional differences among species involve a complex suite of traits and that perhaps phylogenetic relationships provide a better measure of the diversity among species that contributes to productivity than individual or small groups of traits.     

Independent evolution of leaf and root traits within and among temperate grassland plant communities

In this study, we used data from temperate grassland plant communities in Alberta, Canada to test two longstanding hypotheses in ecology: 1) that there has been correlated evolution of the leaves and roots of plants due to selection for an integrated whole-plant resource uptake strategy, and 2) that trait diversity in ecological communities is generated by adaptations to the conditions in different habitats. We tested the first hypothesis using phylogenetic comparative methods to test for evidence of correlated evolution of suites of leaf and root functional traits in these grasslands. There were consistent evolutionary correlations among traits related to plant resource uptake strategies within leaf tissues, and within root tissues. In contrast, there were inconsistent correlations between the traits of leaves and the traits of roots, suggesting different evolutionary pressures on the above and belowground components of plant morphology. To test the second hypothesis, we evaluated the relative importance of two components of trait diversity: within-community variation (species trait values relative to co-occurring species; α traits) and among-community variation (the average trait value in communities where species occur; β traits). Trait diversity was mostly explained by variation among co-occurring species, not among-communities. Additionally, there was a phylogenetic signal in the within-community trait values of species relative to co-occurring taxa, but not in their habitat associations or among-community trait variation. These results suggest that sorting of pre-existing trait variation into local communities can explain the leaf and root trait diversity in these grasslands.     

Trait variation and functional diversity maintenance of understory herbaceous species coexisting along an elevational gradient in Yulong Mountain,Southwest China

Characterizing trait variation across different ecological scales in plant communities has been viewed as a way to gain insights into the mechanisms driving species coexistence. However, little is known about how changes in intraspecific and interspecific traits across sites influence species richness and community assembly, especially in understory herbaceous communities. Here we partitioned the variance of four functional traits (maximum height, leaf thickness, leaf area and specific leaf area) across four nested biological scales: individual, species, plot, and elevation to quantify the scale-dependent distributions of understory herbaceous trait variance. We also integrated the comparison of the trait variance ratios to null models to investigate the effects of different ecological processes on community assembly and functional diversity along a 1200-m elevational gradient in Yulong Mountain. We found interspecific trait variation was the main trait variation component for leaf traits, although intraspecific trait variation ranged from 10% to 28% of total variation. In particular, maximum height exhibited high plasticity, and intraspecific variation accounted for 44% of the total variation. Despite the fact that species composition varied across elevation and species richness decreased dramatically along the elevational gradient, there was little variance at our largest (elevation) scale in leaf traits and functional diversity remained constant along the elevational gradient, indicating that traits responded to smaller scale influences. External filtering was only observed at high elevations. However, strong internal filtering was detected along the entire elevational gradient in understory herbaceous communities, possibly due to competition. Our results provide evidence that species coexistence in understory herbaceous communities might be structured by differential niche-assembled processes. This approach--integrating different biological scales of trait variation--may provide a better understanding of the mechanisms involved in the structure of communities.     

Patterns of climber distribution in the temperate forests of the Americas

Aims and Methods We propose a standard protocol at the landscape to continental scale for examining to what extent the range of ecological conditions found in temperate latitudes explains the variations in climber species richness and traits. The protocol was tested in forests of the two Americas. The data set included 151 climber species. We selected four categorical traits and grouped these species into six clusters with regard to these traits. Floristic records of American forests were first gathered into alliances, second combined with bioclimatic indices (rainfall, temperature, continentality). We obtained a total of 59 vegetational units in which we calculated values of climber species richness and proportion of clusters. Vegetational units were ultimately gathered into five forest formations (characterized by leaf longevity). Wetlands and uplands were considered separately.Important findings Our results emphasize clear trends in large-scale patterns of climber distribution, independently of taxonomy. Climber species richness (in particular woody climbers) peaks in moist and warm upland forests with oceanic climates, and where conifers are rare. In flooded areas, climber richness is also very high and peaks in seasonally flooded large floodplains. In ecological conditions of frost, dryness or lack of nutrients, climber species richness, abundance and trait diversity decline, resulting in the dominance of small, twining and deciduous life traits.