The study of elevational diversity gradients dates back to the foundation of biogeography. Although elevational patterns of plant and animal diversity have been studied for centuries, such patterns have not been reported for microorganisms and remain poorly understood. Here, in an effort to assess the generality of elevational diversity patterns, we examined soil bacterial and plant diversity along an elevation gradient. To gain insight into the forces that structure these patterns, we adopted a multifaceted approach to incorporate information about the structure, diversity, and spatial turnover of montane communities in a phylogenetic context. We found that observed patterns of plant and bacterial diversity were fundamentally different. While bacterial taxon richness and phylogenetic diversity decreased monotonically from the lowest to highest elevations, plants followed a unimodal pattern, with a peak in richness and phylogenetic diversity at mid-elevations. At all elevations bacterial communities had a tendency to be phylogenetically clustered, containing closely related taxa. In contrast, plant communities did not exhibit a uniform phylogenetic structure across the gradient: they became more overdispersed with increasing elevation, containing distantly related taxa. Finally, a metric of phylogenetic beta-diversity showed that bacterial lineages were not randomly distributed, but rather exhibited significant spatial structure across the gradient, whereas plant lineages did not exhibit a significant phylogenetic signal. Quantifying the influence of sample scale in intertaxonomic comparisons remains a challenge. Nevertheless, our findings suggest that the forces structuring microorganism and macroorganism communities along elevational gradients differ.elevation gradient ͉ microbial ecology ͉ phylogenetic diversity ͉ macroecology ͉ biogeography R oughly 250 years ago, Carolus Linnaeus (1) documented how distinct plant and animal communities characterized the succession of climatic zones along the slopes of mountains. Such elevational gradients are characterized by dramatic changes in climate and biotic turnover over short geographic distances. The patterns observed by Linnaeus and his contemporaries played a foundational role in the development of ecology and biogeography (2

AimThe 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 highdimensional 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 conclusionsWe 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.

The processes causing the latitudinal gradient in species richness remain elusive. Ecological theories for the origin of biodiversity gradients, such as competitive exclusion, neutral dynamics, and environmental filtering, make predictions for how functional diversity should vary at the alpha (within local assemblages), beta (among assemblages), and gamma (regional pool) scales. We test these predictions by quantifying hypervolumes constructed from functional traits representing major axes of plant strategy variation (specific leaf area, plant height, and seed mass) in tree assemblages spanning the temperate and tropical New World. Alpha-scale trait volume decreases with absolute latitude and is often lower than sampling expectation, consistent with environmental filtering theory. Beta-scale overlap decays with geographic distance fastest in the temperate zone, again consistent with environmental filtering theory. In contrast, gamma-scale trait space shows a hump-shaped relationship with absolute latitude, consistent with no theory. Furthermore, the overall temperate trait hypervolume was larger than the overall tropical hypervolume, indicating that the temperate zone permits a wider range of trait combinations or that niche packing is stronger in the tropical zone. Although there are limitations in the data, our analyses suggest that multiple processes have shaped trait diversity in trees, reflecting no consistent support for any one theory. S pecies richness increases toward the equator (1, 2) in major clades of both extant and extinct species of plants and animals (3, 4). The generality of the pattern hints at a correspondingly general explanation, yet the latitudinal gradient in species richness remains one of ecology's greatest unsolved puzzles. Long-running debates over the causes of the latitudinal gradient of species richness have focused on ecological, evolutionary, and geographic explanations (5-10). Although there has been some progress (11), it is also increasingly clear that there are numerous obstacles to understanding the primary drivers of the latitudinal gradient, including an ever-increasing number of hypotheses (12, 13), challenges in clearly separating their interdependencies (14, 15), and difficulties in rigorously falsifying their assumptions and predictions (16).More powerful tests of biodiversity theories need to move beyond species richness and instead explicitly focus on the mechanisms generating the gradient, by recasting the theories in terms of other measures of diversity, such as functional diversity (17-19). For example, explanations that assume species richness is limited by resource availability have often focused on the strength of species interactions, life history differences, and environmental constraints on how species pack into niche space (20). Evolutionary hypotheses have focused on differences in diversification rates, as well as the influence of species interactions on diversification rates (9). These interaction-based explanations implicitly refer to the degree of ecol...

Hutchinson's n‐dimensional hypervolume concept underlies many applications in contemporary ecology and evolutionary biology. Estimating hypervolumes from sampled data has been an ongoing challenge due to conceptual and computational issues. We present new algorithms for delineating the boundaries and probability density within n‐dimensional hypervolumes. The methods produce smooth boundaries that can fit data either more loosely (Gaussian kernel density estimation) or more tightly (one‐classification via support vector machine). Further, the algorithms can accept abundance‐weighted data, and the resulting hypervolumes can be given a probabilistic interpretation and projected into geographic space. We demonstrate the properties of these methods on a large dataset that characterises the functional traits and geographic distribution of thousands of plants. The methods are available in version ≥2.0.7 of the hypervolume r package. These new algorithms provide: (i) a more robust approach for delineating the shape and density of n‐dimensional hypervolumes; (ii) more efficient performance on large and high‐dimensional datasets; and (iii) improved measures of functional diversity and environmental niche breadth.