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AIM: The Hutchinsonian hypervolume is the conceptual foundation for many lines of ecological and evolutionary inquiry, including functional morphology, comparative biology, community ecology and niche theory. However, extant methods to sample from hypervolumes or measure their geometry perform poorly on high‐dimensional or holey datasets. INNOVATION: We first highlight the conceptual and computational issues that have prevented a more direct approach to measuring hypervolumes. Next, we present a new multivariate kernel density estimation method that resolves many of these problems in an arbitrary number of dimensions. MAIN CONCLUSIONS: We show that our method (implemented as the ‘hypervolume’ R package) can match several extant methods for hypervolume geometry and species distribution modelling. Tools to quantify high‐dimensional ecological hypervolumes will enable a wide range of fundamental descriptive, inferential and comparative questions to be addressed.

1. Plant phenotypic diversity is shaped by the interplay of trade-offs and constraints in evolution. Closely integrated groups of traits (i.e. trait dimensions) are used to classify plant phenotypic diversity into plant strategies, but we do not know the degree of interdependence among trait dimensions. To assess how selection has shaped the phenotypic space, we examine whether trait dimensions are independent. 2. We gathered data on saplings of 24 locally coexisting tree species in a temperate forest, and examined the correlation structure of 20 leaf, branch, stem and root traits. These traits fall into three well-established trait dimensions (the leaf economic spectrum, the wood spectrum and Corner's Rules) that characterize vital plant functions: resource acquisition, sap transport, mechanical support and canopy architecture. Using ordinations, network analyses and Mantel tests, we tested whether the sapling phenotype of these tree species is organized along independent trait dimensions. 3. Across species, the sapling phenotype is not structured into clear trait dimensions. The trait relationships defining trait dimensions are either weak or absent and do not dominate the correlation structure of the sapling phenotype as a whole. Instead traits from the three commonly recognized trait dimensions are organized into an integrated trait network. The effect of phylogeny on trait correlations is minimal. 4. Our results indicate that trait dimensions apparent in broad-based interspecific surveys do not hold up among locally coexisting species. Furthermore, architectural traits appear central to the phenotypic network, suggesting a pivotal role for branching architecture in linking resource acquisition, mechanical support and hydraulic functions. 5. Synthesis. Our study indicates that local and global patterns of phenotypic integration differ and calls into question the use of trait dimensions at local scales. We propose that a network approach to assessing plant function more effectively reflects the multiple trade-offs and constraints shaping the phenotype in locally co-occurring species.

Understanding, modeling, and predicting the impact of global change on ecosystem functioning across biogeographical gradients can benefit from enhanced capacity to represent biota as a continuous distribution of traits. However, this is a challenge for the field of biogeography historically grounded on the species concept. Here we focus on the newly emergent field of functional biogeography: the study of the geographic distribution of trait diversity across organizational levels. We show how functional biogeography bridges species-based biogeography and earth science to provide ideas and tools to help explain gradients in multifaceted diversity (including species, functional, and phylogenetic diversities), predict ecosystem functioning and services worldwide, and infuse regional and global conservation programs with a functional basis. Although much recent progress has been made possible because of the rising of multiple data streams, new developments in ecoinformatics, and new methodological advances, future directions should provide a theoretical and comprehensive framework for the scaling of biotic interactions across trophic levels and its ecological implications.

Trait-based approaches have taken an increasingly dominant role in community ecology. Although trait-based strategy dimensions such as the leaf economic spectrum (LES) have been identified primarily at global-scales, trait variation at the community scale is often interpreted in this context. Here we argue from several lines of evidence that a research priority should be to determine whether global-scale trait relationships hold at more local scales. We review recent literature assessing trait variation at smaller scales, and then present a case study exploring the relationship between the correlation strength of leaf traits and their similarity in variation structure across ecological scales. We find that the correlation strength between pairs of leaf traits does not predict whether the traits respond similarly to different drivers of variation. Instead, correlation strength only sets an upper bound to the dissimilarity in trait variation structure. With moderate correlation strengths, LES traits largely retain the ability to respond independently to different drivers of phenotypic variation at different scales. Recent literature and our results suggest that LES relationships may not hold at local scales. Clarifying under what conditions and at which scales the LES is consistently expressed is necessary for us to make the most of the emerging trait toolbox.

A prominent signal of the Anthropocene is the extinction and population reduction of the megabiota—the largest animals and plants on the planet. However, we lack a predictive framework for the sensitivity of megabiota during times of rapid global change and how they impact the functioning of ecosystems and the biosphere. Here, we extend metabolic scaling theory and use global simulation models to demonstrate that (i) megabiota are more prone to extinction due to human land use, hunting, and climate change; (ii) loss of megabiota has a negative impact on ecosystem metabolism and functioning; and (iii) their reduction has and will continue to significantly decrease biosphere functioning. Global simulations show that continued loss of large animals alone could lead to a 44%, 18% and 92% reduction in terrestrial heterotrophic biomass, metabolism, and fertility respectively. Our findings suggest that policies that emphasize the promotion of large trees and animals will have disproportionate impact on biodiversity, ecosystem processes, and climate mitigation. Human-driven losses of megafauna and megaflora may have disproportionate ecological consequences. Here, the authors combine metabolic scaling theory and global simulation models to show that past and continued reduction of megabiota have and will continue to decrease ecosystem and biosphere functioning.

Variation in terrestrial net primary production (NPP) with climate is thought to originate from a direct influence of temperature and precipitation on plant metabolism. However, variation in NPP may also result from an indirect influence of climate by means of plant age, stand biomass, growing season length and local adaptation. To identify the relative importance of direct and indirect climate effects, we extend metabolic scaling theory to link hypothesized climate influences with NPP, and assess hypothesized relationships using a global compilation of ecosystem woody plant biomass and production data. Notably, age and biomass explained most of the variation in production whereas temperature and precipitation explained almost none, suggesting that climate indirectly (not directly) influences production. Furthermore, our theory shows that variation in NPP is characterized by a common scaling relationship, suggesting that global change models can incorporate the mechanisms governing this relationship to improve predictions of future ecosystem function. Net primary production is affected by temperature and precipitation, but whether this is a direct kinetic effect on plant metabolism or an indirect ecological effect mediated by changes in plant age, plant biomass or growing season length is unclear — this study develops metabolic scaling theory to be able to answer this question and applies it to a global data set of plant productivity, concluding that it is indirect effects that explain the influence of climate on productivity, which is characterized by a common scaling relationship across climate gradients. Plant productivity response to climate Net primary production is affected by temperature and precipitation, but is this a direct effect on plant metabolism or an indirect ecological effect mediated by changes in growing season length and plant biomass? Here, Sean Michaletz et al . develop metabolic scaling theory to test the relative importance of direct and indirect climate effects. Applying their model to a global data set of plant productivity, the authors conclude that it is indirect effects that explain the influence of climate on productivity. Temperature and water availability are fundamental drivers of plant physiology and ecosystem metabolism at local scales, but at global scales climate influences net primary production indirectly via plant age and stand biomass, which is largely driven by maximum plant size.

While community-weighted means of plant traits have been linked to mean environmental conditions at large scales, the drivers of trait variation within communities are not well understood. Local environmental heterogeneity (such as microclimate variability), in addition to mean environmental conditions, may decrease the strength of environmental filtering and explain why communities support different amounts of trait variation. Here, we assess two hypotheses: first, that more heterogeneous local environments and second, that less extreme environments, should support a broader range of plant strategies and thus higher trait variation. We quantified drivers of trait variation across a range of environmental conditions and spatial scales ranging from sub-meter to tens of kilometers in montane and alpine plant communities. We found that, within communities, both environmental heterogeneity and environmental means are drivers of trait variation. However, the importance of each environmental factor varied depending on the trait. Our results indicate that larger-scale trait–climate linkages that hold across communities also apply at small spatial scales, suggesting that microclimate variation within communities is a key driver of community functional diversity. Microclimatic variation provides a potential mechanism for helping to maintain diversity in local communities and also suggests that small-scale environmental heterogeneity should be measured as a better predictor of functional diversity.

Trees are pivotal to global biodiversity and nature’s contributions to people, yet accelerating global changes threaten global tree diversity, making accurate species extinction risk assessments necessary. To identify species that require expert-based re-evaluation, we assess exposure to change in six anthropogenic threats over the last two decades for 32,090 tree species. We estimated that over half (54.2%) of the assessed species have been exposed to increasing threats. Only 8.7% of these species are considered threatened by the IUCN Red List, whereas they include more than half of the Data Deficient species (57.8%). These findings suggest a substantial underestimation of threats and associated extinction risk for tree species in current assessments. We also map hotspots of tree species exposed to rapidly changing threats around the world. Our data-driven approach can strengthen the efforts going into expert-based IUCN Red List assessments by facilitating prioritization among species for re-evaluation, allowing for more efficient conservation efforts. Tree species may be vulnerable to multiple global change factors. Here, the authors find that more than 17 thousand tree species are exposed to increasing anthropogenic threats, including many species classified as data-deficient in the IUCN Red List.

Climate warming is increasingly leading to marked changes in plant and animal biodiversity, but it remains unclear how temperatures affect microbial biodiversity, particularly in terrestrial soils. Here we show that, in accordance with metabolic theory of ecology, taxonomic and phylogenetic diversity of soil bacteria, fungi and nitrogen fixers are all better predicted by variation in environmental temperature than pH. However, the rates of diversity turnover across the global temperature gradients are substantially lower than those recorded for trees and animals, suggesting that the diversity of plant, animal and soil microbial communities show differential responses to climate change. To the best of our knowledge, this is the first study demonstrating that the diversity of different microbial groups has significantly lower rates of turnover across temperature gradients than other major taxa, which has important implications for assessing the effects of human-caused changes in climate, land use and other factors. Climate warming has a wide range of effects on biodiversity. Here, Zhou et al . show that although variation in environmental temperature is a primary driver of soil microbial biodiversity, microbes show much lower rates of turnover across temperature gradients than other major taxa.

Species diversity is promoted and maintained by ecological and evolutionary processes operating on species attributes through space and time. The degree to which variability in species function regulates distribution and promotes coexistence of species has been debated. Previous work has attempted to quantify the relative importance of species function by using phylogenetic relatedness as a proxy for functional similarity. The key assumption of this approach is that function is phylogenetically conserved. If this assumption is supported, then the phylogenetic dispersion in a community should mirror the functional dispersion. Here we quantify functional trait dispersion along several key axes of tree life-history variation and on multiple spatial scales in a Neotropical dry-forest community. We next compare these results to previously reported patterns of phylogenetic dispersion in this same forest. We find that, at small spatial scales, coexisting species are typically more functionally clustered than expected, but traits related to adult and regeneration niches are overdispersed. This outcome was repeated when the analyses were stratified by size class. Some of the trait dispersion results stand in contrast to the previously reported phylogenetic dispersion results. In order to address this inconsistency we examined the strength of phylogenetic signal in traits at different depths in the phylogeny. We argue that: (1) while phylogenetic relatedness may be a good general multivariate proxy for ecological similarity, it may have a reduced capacity to depict the functional mechanisms behind species coexistence when coexisting species simultaneously converge and diverge in function; and (2) the previously used metric of phylogenetic signal provided erroneous inferences about trait dispersion when married with patterns of phylogenetic dispersion.