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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.

Plant biomass or productivity and the species richness of birds are associated across a range of spatial scales. Species-energy theory is generally assumed to explain these correlations. If true, bird richness should also track productivity temporally, and there should be spatial and temporal relationships between productivity and both bird abundance and bird richness. Using the summer normalized difference vegetation index (NDVI) for 1982-2006 and the North American Breeding Bird Survey, we evaluated the response of avian richness and abundance to interannual changes in plant biomass or productivity. We found positive spatial relationships between richness and NDVI for all 25 years. Temporally, however, richness and NDVI were positively associated at 1579 survey sites and negatively associated at 1627 sites (mean r2 = 0.09). Further, total abundance and NDVI were unrelated spatially (r2 values spanning < 0.01 and 0.03) and weakly related temporally (mean r2 = 0.10). We found no evidence that productivity drives bird richness beyond the spatial correlations, and neither prediction arising from species-energy theory was confirmed. Spatial relationships between productivity and bird richness may thus be largely spurious, arising via covariance between plant biomass or productivity and vegetation structural complexity, and the latter may be driving bird communities. This is consistent with the MacArthurs' classic hypothesis that the vertical profile of foliage drives bird species diversity.

Although fungal communities are known to vary along latitudinal gradients, mechanisms underlying this pattern are not well-understood. We used high-throughput sequencing to examine the large-scale distributions of soil fungi and their relation to evolutionary history. We tested the Tropical Conservatism Hypothesis, which predicts that ancestral fungal groups should be more restricted to tropical latitudes and conditions than would more recently derived groups. We found support for this hypothesis in that older phyla preferred significantly lower latitudes and warmer, wetter conditions than did younger phyla. Moreover, preferences for higher latitudes and lower precipitation levels were significantly phylogenetically conserved among the six younger phyla, possibly because the older phyla possess a zoospore stage that is vulnerable to drought, whereas the younger phyla retain protective cell walls throughout their life cycle. Our study provides novel evidence that the Tropical Conservatism Hypothesis applies to microbes as well as plants and animals.

AimThe fossil record has led to a historical explanation for forest diversity gradients within the cool parts of the Northern Hemisphere, founded on a limited ability of woody angiosperm clades to adapt to mid-Tertiary cooling. We tested four predictions of how this should be manifested in the phylogenetic structure of 91,340 communities: (1) forests to the north should comprise species from younger clades (families) than forests to the south; (2) average cold tolerance at a local site should be associated with the mean family age (MFA) of species; (3) minimum temperature should account for MFA better than alternative environmental variables; and (4) traits associated with survival in cold climates should evolve under a niche conservatism constraint. LocationThe contiguous United States. MethodsWe extracted angiosperms from the US Forest Service's Forest Inventory and Analysis database. MFA was calculated by assigning age of the family to which each species belongs and averaging across the species in each community. We developed a phylogeny to identify phylogenetic signal in five traits: realized cold tolerance, seed size, seed dispersal mode, leaf phenology and height. Phylogenetic signal representation curves and phylogenetic generalized least squares were used to compare patterns of trait evolution against Brownian motion. Eleven predictors structured at broad or local scales were generated to explore relationships between environment and MFA using random forest and general linear models. ResultsConsistent with predictions, (1) southern communities comprise angiosperm species from older families than northern communities, (2) cold tolerance is the trait most strongly associated with local MFA, (3) minimum temperature in the coldest month is the environmental variable that best describes MFA, broad-scale variables being much stronger correlates than local-scale variables, and (4) the phylogenetic structures of cold tolerance and at least one other trait associated with survivorship in cold climates indicate niche conservatism. Main conclusionsTropical niche conservatism in the face of long-term climate change, probably initiated in the Late Cretaceous associated with the rise of the Rocky Mountains, is a strong driver of the phylogenetic structure of the angiosperm component of forest communities across the USA. However, local deterministic and/or stochastic processes account for perhaps a quarter of the variation in the MFA of local communities.

We compiled 46 broadscale data sets of species richness for a wide range of terrestrial plant, invertebrate, and ectothermic vertebrate groups in all parts of the world to test the ability of metabolic theory to account for observed diversity gradients. The theory makes two related predictions: (1) In-transformed richness is linearly associated with a linear, inverse transformation of annual temperature, and (2) the slope of the relationship is near -0.65. Of the 46 data sets, 14 had no significant relationship; of the remaining 32, nine were linear, meeting prediction 1. Model I (ordinary least squares, OLS) and model II (reduced major axis, RMA) regressions then tested the linear slopes against prediction 2. In the 23 data sets having nonlinear relationships between richness and temperature, split-line regression divided the data into linear components, and regressions were done on each component to test prediction 2 for subsets of the data. Of the 46 data sets analyzed in their entirety using OLS regression one was consistent with metabolic theory (meeting both predictions), and one was possibly consistent. Using RMA regression, no data sets were consistent. Of 67 analyses of prediction 2 using OLS regression on all linear data sets and subsets, two were consistent with the prediction, and four were possibly consistent. Using RMA regression, one was consistent (albeit weakly), and four were possibly consistent. We also found that the relationship between richness and temperature is both taxonomically and geographically conditional, and there is no evidence for a universal response of diversity to temperature. Meta-analyses confirmed significant heterogeneity in slopes among data sets, and the combined slopes across studies were significantly lower than the range of slopes predicted by metabolic theory based on both OLS and RMA regressions. We conclude that metabolic theory, as currently formulated, is a poor predictor of observed diversity gradients in most terrestrial systems.

There have been numerous claims in the ecological literature that spatial autocorrelation in the residuals of ordinary least squares (OLS) regression models results in shifts in the partial coefficients, which bias the interpretation of factors influencing geographical patterns. We evaluate the validity of these claims using gridded species richness data for the birds of North America, South America, Europe, Africa, the ex-USSR, and Australia. We used richness in 110x110 km cells and environmental predictor variables to generate OLS and simultaneous autoregressive (SAR) multiple regression models for each region. Spatial correlograms of the residuals from each OLS model were then used to identify the minimum distance between cells necessary to avoid short-distance residual spatial autocorrelation in each data set. This distance was used to subsample cells to generate spatially independent data. The partial OLS coefficients estimated with the full dataset were then compared to the distributions of coefficients created with the subsamples. We found that OLS coefficients generated from data containing residual spatial autocorrelation were statistically indistinguishable from coefficients generated from the same data sets in which short-distance spatial autocorrelation was not present in all 22 coefficients tested. Consistent with the statistical literature on this subject, we conclude that coefficients estimated from OLS regression are not seriously affected by the presence of spatial autocorrelation in gridded geographical data. Further, shifts in coefficients that occurred when using SAR tended to be correlated with levels of uncertainty in the OLS coefficients. Thus, shifts in the relative importance of the predictors between OLS and SAR models are expected when small-scale patterns for these predictors create weaker and more unstable broad-scale coefficients. Our results indicate both that OLS regression is unbiased and that differences between spatial and nonspatial regression models should be interpreted with an explicit awareness of spatial scale.

Aim The aim of this study was to test a variant of the evolutionary time hypothesis for the bird latitudinal diversity gradient derived from the effects of niche conservatism in the face of global climate change over evolutionary time. Location The Western Hemisphere. Methods We used digitized range maps of breeding birds to estimate the species richness at two grain sizes, 756 and 12,100 km(2). We then used molecular phylogenies resolved to family to quantify the root distance (RD) of each species as a measure of its level of evolutionary development. Birds were classified as 'basal' or 'derived' based on the RD of their family, and richness patterns were contrasted for the most basal and most derived 30% of species. We also generated temperature estimates for the Palaeogene across the Western Hemisphere to examine how spatial covariation between past and present climates might make it difficult to distinguish between ecological and evolutionary hypotheses for the current richness gradient. Results The warm, wet tropics support many species from basal bird clades, whereas the northern temperate zone and cool or dry tropics are dominated by species from more recent, evolutionarily derived clades. Furthermore, crucial to evaluating how niche conservatism among birds may drive the hemispherical richness gradient, the spatial structure of the richness gradient for basal groups is statistically indistinguishable from the overall gradient, whereas the richness gradient for derived groups is much shallower than the overall gradient. Finally, modern temperatures and the pattern of climate cooling since the Eocene are indistinguishable as predictors of bird species richness. Main conclusions Differences in the richness gradients of basal vs. derived clades suggest that the hemispherical gradient has been strongly influenced by the differential extirpation of species in older, warm-adapted clades from parts of the world that have become cooler in the present. We propose that niche conservatism and global-scale climate change over evolutionary time provide a parsimonious explanation for the contemporary bird latitudinal diversity gradient in the New World, although dispersal limitation of some highly derived clades probably plays a secondary role.

1. Using two sources of data to estimate butterfly species richness, the potential influences of 11 environmental variables on the richness gradient of butterflies in western/central Europe and northern Africa were examined with multiple regression and spatial autocorrelation analysis. A measure of water-energy balance, actual evapotranspiration, explained 79% of the variance in butterfly species richness using data derived from range maps, and 72% of the variance using data derived from grid-based distribution maps. All other variables explained less than 4% of the variance in the regression models and differed depending on the data source. 2. The spatial analysis indicated that actual evapotranspiration successfully removed most of the spatial autocorrelation in both richness data sets at all spatial scales, confirming the ability of the model to account for the spatial pattern in butterfly richness. 3. Plant species richness, a rarely tested variable hypothesised to be an important determinant of herbivore diversity, was weakly associated with butterfly richness, suggesting that it has little or no direct influence on butterfly richness. 4. A historical variable, the length of time that areas have been exposed for recolonisation after the retreat of the ice sheet following the last ice age, was also not associated with richness patterns, indicating that butterfly richness is in equilibrium with contemporary climate. 5. It was not possible to confirm a result reported for Canadian butterflies that land cover diversity is a strong predictor of butterfly richness, possibly because of methodological differences in the studies, differences in the range of climates found in Canada and the western Palearctic, or because of the highly modified landscape characteristic of Europe. 6. Water-energy balance offers a parsimonious explanation for the butterfly richness gradient in this region, operating partially indirectly via effects on plant productivity and partially directly via physiological effects on butterflies, and this conclusion is robust to differences in the types of distribution maps used to estimate richness patterns.

Studies mostly focused on communities of primary producers have shown that species richness provides and promotes fundamental ecosystem services. However, we know very little about the factors influencing ecosystem services provided by higher trophic levels in natural food webs. Here we present evidence that differences in food web structure and the richness of herbivores in 19 plant-herbivore-parasitoid food webs influence the service supplied by natural enemies, namely, the parasitism rates on hosts. Specifically, we find that parasitoids function better in simple food webs than in complex ones, a result relevant to biological control practice. More generally, we show that species richness per se only contributes partially to the understanding of higher-level ecosystem services in multitrophic communities, and that changes in food web complexity should also be taken into account when predicting the effects of human-driven disturbances in natural communities.

Aim Spatial autocorrelation in ecological data can inflate Type I errors in statistical analyses. There has also been a recent claim that spatial autocorrelation generates 'red herrings', such that virtually all past analyses are flawed. We consider the origins of this phenomenon, the implications of spatial autocorrelation for macro-scale patterns of species diversity and set out a clarification of the statistical problems generated by its presence. Location To illustrate the issues involved, we analyse the species richness of the birds of western/central Europe, north Africa and the Middle East. Methods Spatial correlograms for richness and five environmental variables were generated using Moran's I coefficients. Multiple regression, using both ordinary least-squares (OLS) and generalized least squares (GLS) assuming a spatial structure in the residuals, were used to identify the strongest predictors of richness. Autocorrelation analyses of the residuals obtained after stepwise OLS regression were undertaken, and the ranks of variables in the full OLS and GLS models were compared. Results Bird richness is characterized by a quadratic north-south gradient. Spatial correlograms usually had positive autocorrelation up to c. 1600 km. Including the environmental variables successively in the OLS model reduced spatial autocorrelation in the residuals to non-detectable levels, indicating that the variables explained all spatial structure in the data. In principle, if residuals are not autocorrelated then OLS is a special case of GLS. However, our comparison between OLS and GLS models including all environmental variables revealed that GLS de-emphasized predictors with strong autocorrelation and long-distance clinal structures, giving more importance to variables acting at smaller geographical scales. Conclusion Although spatial autocorrelation should always be investigated, it does not necessarily generate bias. Rather, it can be a useful tool to investigate mechanisms operating on richness at different spatial scales. Claims that analyses that do not take into account spatial autocorrelation are flawed are without foundation.