Summary1. Spatial variation in filters imposed by the abiotic environment causes variation in functional traits within and among plant species. This is abundantly clear for plant species along elevational gradients, where parallel abiotic selection pressures give rise to predictable variation in leaf phenotypes among ecosystems. Understanding the factors responsible for such patterns may provide insight into the current and future drivers of biodiversity, local community structure and ecosystem function. 2. In order to explore patterns in trait variation along elevational gradients, we conducted a meta-analysis of published observational studies that measured three key leaf functional traits that are associated with axes of variation in both resource competition and stress tolerance: leaf mass:area ratio (LMA), leaf nitrogen content per unit mass (N mass ) and N content per unit area (N area ). To examine whether there may be evidence for a genetic basis underlying the trait variation, we conducted a review of published results from common garden experiments that measured the same leaf traits. 3. Within studies, LMA and N area tended to decrease with mean annual temperature (MAT) along elevational gradients, while N mass did not vary systematically with MAT. Correlations among pairs of traits varied significantly with MAT: LMA was most strongly correlated with N mass and N area at high-elevation sites with relatively lower MAT. The strengths of the relationships were equal or greater within species relative to the relationships among species, suggesting parallel evolutionary dynamics along elevational gradients among disparate biomes. Evidence from common garden studies further suggests that there is an underlying genetic basis to the functional trait variation that we documented along elevational gradients. 4. Taken together, these results indicate that environmental filtering both selects locally adapted genotypes within plant species and constrains species to elevational ranges based on their ranges of potential leaf trait values. If individual phenotypes are filtered from populations in the same way that species are filtered from regional species pools, changing climate may affect both the species and functional trait composition of plant communities.

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (Nm) and phosphorus (Pm), we characterize how traits vary within and among over 50,000 ∼50 × 50-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.odeling global climate and the carbon cycle with Earth system models (ESMs) requires maps of plant traits that play key roles in leaf-and ecosystem-level metabolic processes (1-4). Multiple traits are critical to both photosynthesis and respiration, foremost leaf nitrogen concentration (Nm ) and specific leaf area (SLA) (5-7). More recently, variation in leaf phosphorus concentration (Pm ) has also been linked to variation in photosynthesis and foliar respiration (7-12). Estimating detailed global geographic patterns of these traits and corresponding trait-environment relationships has been hampered by limited measurements (13), but recent improvements in data coverage (14) allow for greater detail in spatial estimates of these key traits.Previous work has extrapolated trait measurements across continental or larger regions through three methodologies: (i) grouping measurements of individuals into larger categories that share a set of properties [a working definition of plant functional types (PFTs)] (4, 15), (ii) exploiting trait-environment relationships (e.g., leaf Nm and mean annual temperature) (1,(16)(17)(18)(19)(20), or (iii) restricting the analysis to species whose presence has been widely estimated on the ground (21-24). Each of these methods has limitations-for example, trait-environment relationships do not well explain observed trait spatial patterns (1, 25), while species-based approaches limit the scope of extrapolation to only areas with well-measured species abundance. More critically, the first two global methodologies emp...

Faculty and staff were surveyed to assess the professional development (PD) for teaching provided to biology graduate students at academic institutions. Although more than 90% of institutions provided PD, it was most often presemester and less than 10 h. Respondents most satisfied with their PD had programs with greater breadth and institutional support.

Issue Geodiversity (i.e., the variation in Earth's abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA's Shuttle Radar Topography Mission (SRTM) and c . 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature.

Abstract. Macroecology seeks to understand broad-scale patterns in the diversity and abundance of organisms, but macroecologists typically study aboveground macroorganisms. Belowground organisms regulate numerous ecosystem functions, yet we lack understanding of what drives their diversity. Here, we examine the controls on belowground diversity along latitudinal and elevational gradients. We performed a global meta-analysis of 325 soil communities across 20 studies conducted along temperature and soil pH gradients. Belowground taxa, whether bacterial or fungal, observed along a given gradient of temperature or soil pH were equally likely to show a linear increase, linear decrease, humped pattern, trough-shaped pattern, or no pattern in diversity along the gradient. Land-use intensity weakly affected the diversity-temperature relationship, but no other factor did so. Our study highlights disparities among diversity patterns of soil microbial communities. Belowground diversity may be controlled by the associated climatic and historical contexts of particular gradients, by factors not typically measured in community-level studies, or by processes operating at scales that do not match the temporal and spatial scales under study. Because these organisms are responsible for a suite of key processes, understanding the drivers of their distribution and diversity is fundamental to understanding the functioning of ecosystems.

Summary 1.While an appreciation of plant-soil feedbacks (PSF) continues to expand for community and ecosystem ecology, the eco-evolutionary mechanisms and consequences of such feedbacks remain largely unknown or untested. 2. Determining the cause and effect of plant phenotypes is central for understanding these ecoevolutionary dynamics since phenotypes respond to soil selective gradients that are, in turn, modified by plant traits. Genetic variation in plant phenotypes can change soil processes and biotic communities; oppositely, soil gradients and microbial communities can influence the expression and evolution of plant phenotypes. 3. Although these processes represent the two halves of genetic based PSF, research in these areas has developed independently from one another. Greater connectivity between research on ecosystem consequences of plant genetic variation and soil selective gradients that drive plant phenotypic evolution will create novel and important opportunities to link ecology and evolution in natural systems. 4. Papers in this special feature build on the inherent ecological and evolutionary processes involved in PSF, outlining many ways to identify and test mechanisms that connect ecosystem ecology and evolution.

The productivity of ecosystems and their capacity to support life depends on access to reactive nitrogen (N). Over the past century, humans have more than doubled the global supply of reactive N through industrial and agricultural activities. However, long-term records demonstrate that N availability is declining in many regions of the world. Reactive N inputs are not evenly distributed, and global changes—including elevated atmospheric carbon dioxide (CO 2 ) levels and rising temperatures—are affecting ecosystem N supply relative to demand. Declining N availability is constraining primary productivity, contributing to lower leaf N concentrations, and reducing the quality of herbivore diets in many ecosystems. We outline the current state of knowledge about declining N availability and propose actions aimed at characterizing and responding to this emerging challenge.

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