Search

The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state.

Multiple scale-dependent ecological processes infl uence species distributions. Uncovering these drivers of dynamic range boundaries can provide fundamental ecological insights and vital knowledge for species management. We develop a transferable methodology that uses widely available data and tools to determine critical scales in range expansion and to infer dominating scale-dependent forces that infl uence spread. We divide a focal geographic region into diff erent sized square cells, representing diff erent spatial scales. We then used herbarium records to determine the species ’ occupancy of cells at each spatial scale. We calculated the growth in cell occupancy across scales to infer the scale dependent expansion rate. Th is is the fi rst time such a ‘ box-counting ’ method is used to study range expansion. We coupled this multi-scale analysis with species distribution models to determine the range and spatial scales where suitable climate allows the species to spread, and where other factors may be infl uencing the expansion. We demonstrate our methodology by assessing the spread of invasive Sahara mustard in North America. We detect critical scales where its spread is limited (100 – 500 km) or unconstrained (5 – 50 km) by climatic variables. Using climate-based models to assess the similarity of climate envelopes in its native and invaded range, we fi nd that the climate in the invaded range generally predicts the native distribution, suggesting that either there has been little local adaptation to climate occurring since introduction or the biological interaction experienced in the invaded range has not driven the species to occupy climatic conditions much diff erent from its native range. Our novel method can be broadly utilized in other studies to generate critical insights into the scale dependency of diff erent ecological drivers that infl uence the spread and distribution limits, as well as to help parameterizing predictions of future spread, and thus inform management decisions.

We argue for expanding the role of theory in ecology to accelerate scientific progress, enhance the ability to address environmental challenges, foster the development of synthesis and unification, and improve the design of experiments and large-scale environmental-monitoring programs. To achieve these goals, it is essential to foster the development of what we call efficient theories, which have several key attributes. Efficient theories are grounded in first principles, are usually expressed in the language of mathematics, make few assumptions and generate a large number of predictions per free parameter, are approximate, and entail predictions that provide well-understood standards for comparison with empirical data. We contend that the development and successive refinement of efficient theories provide a solid foundation for advancing environmental science in the era of big data.

Not too fast, not too slow, somewhere in between In early depictions, dinosaurs lumbered slowly, dragging their tails. More recently, we have imagined them lifting their tails and running. The question boils down to whether dinosaurs had energetic systems closer to those of rapidly metabolizing mammals and birds, or to those of slower reptiles that do not internally regulate their body temperature. However, determining the metabolic rate of extinct organisms is no easy task. Grady et al. analyzed a huge data set on growth rate in both extinct and living species, using a method that considers body temperature and body size. Dinosaur metabolism seems to have been neither fast nor slow, but somewhere in the middle—so, dinosaurs did not fully regulate their internal temperature but they were also not entirely at the whim of the environment; neither slow goliaths nor supercharged reptiles. Science , this issue p. 1268

Leaf venation networks provide an integrative linkage between plant form, function and climate niche, because leaf water transport underlies variation in plant performance. Here, we develop theory based on leaf physiology that uses community-mean vein density to predict growing season temperature and atmospheric CO2 concentration. The key assumption is that leaf water supply is matched to water demand in the local environment. We test model predictions using leaves from 17 temperate and tropical sites that span broad climatic gradients. We find quantitative agreement between predicted and observed climate values. We also highlight additional leaf traits that may improve predictions. Our study provides a novel approach for understanding the functional linkages between functional traits and climate that may improve the reconstruction of paleoclimate from fossil assemblages.

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.

The extent to which species' ecological and phylogenetic relatedness shape their co-occurrence patterns at large spatial scales remains poorly understood. By quantifying phylogenetic assemblage structure within geographic ranges of >8000 bird species, we show that global co-occurrence patterns are linked - after accounting for regional effects - to key ecological traits reflecting diet, mobility, body size and climatic preference. We found that co-occurrences of carnivorous, migratory and cold-climate species are phylogenetically clustered, whereas nectarivores, herbivores, frugivores and invertebrate eaters tend to be more phylogenetically overdispersed. Preference for open or forested habitats appeared to be independent from the level of phylogenetic clustering. Our results advocate for an extension of the tropical niche conservatism hypothesis to incorporate ecological and life-history traits beyond the climatic niche. They further offer a novel species-oriented perspective on how biogeographic and evolutionary legacies interact with ecological traits to shape global patterns of species coexistence in birds.

To answer many of the major questions in comparative botany, ecology, and global change biology it is necessary to extrapolate across enormous geographic, temporal and taxonomic scales. Yet much ecological knowledge is still based on observations conducted within a local area or even a few hundred square meters. Understanding ecological patterns and how plants respond to global warming and human alteration of landscapes and ecosystems necessitates a holistic approach. Such an approach must be conducted at a scale that is commensurate with the breadth of the questions being asked. Further, it requires identification, retrieval, and integration of diverse data from a global confederation of collaborating scientists across a broad range of disciplines. We propose to network core databases and data networks to create a novel resource for quantitative plant biodiversity science. The grand challenge is to assemble and share the world’s rapidly accumulating botanical information from plots and collections to create a distributed, web-accessible, readily analyzable data resource. With such a resource, we will answer major questions of direct relevance to plant ecology, plant evolution, plant geography, conservation, global change biology, and protection of biodiversity and ecosystem services. In particular, how does climate influence the distribution and abundance of plant species, how does the phylogenetic diversity of plants vary across broad environmental and climatic gradients, and how are plants assembled into ecological communities? While these and associated questions are at the core of many research endeavors in comparative botany and ecology, our past collective inability to integrate data on a large scale has significantly limited our ability to address these questions head on. This proposed Grand Challenge team will create a data resource of unprecedented size and scope together with the tools for its use, thereby empowering botanists and the general public to better address fundamental issues in plant ecology and global change biology. Although we will focus on plants of the New World, the infrastructure and protocols developed will be scalable to all geographic regions and all types of organisms. Future steps will enable cross-cutting linkages to emerging networks on plant genomics, physiology, and phylogeny, allowing us to address fundamental genetic and evolutionary questions at unprecedented spatial and temporal scales.

Author(s): Buzzard, Vanessa; Michaletz, Sean T; Deng, Ye; He, Zhili; Ning, Daliang; Shen, Lina; Tu, Qichao; Van Nostrand, Joy D; Voordeckers, James W; Wang, Jianjun; Weiser, Michael D; Kaspari, Michael; Waide, Robert B; Zhou, Jizhong; Enquist, Brian J | Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Much ecological research aims to explain how climate impacts biodiversity and ecosystem-level processes through functional traits that link environment with individual performance. However, the specific climatic drivers of functional diversity across space and time remain unclear due largely to limitations in the availability of paired trait and climate data. We compile and analyze a global forest dataset using a method based on abundance-weighted trait moments to assess how climate influences the shapes of whole-community trait distributions. Our approach combines abundance-weighted metrics with diverse climate factors to produce a comprehensive catalog of trait-climate relationships that differ dramatically-27% of significant results change in sign and 71% disagree on sign, significance, or both-from traditional species-weighted methods. We find that (

Author(s): Weiser, MD; Ning, D; Buzzard, V; Michaletz, ST; He, Z; Enquist, BJ; Waide, RB; Zhou, J; Kaspari, M | Abstract: The metabolic theory of ecology assumes that rates of selection and adaptation for organisms are functions of temperature. Niche theory predicts that strong selection pressure should simplify assemblages as species are extirpated and taxa pre-adapted for the new environment thrive. Here, we use closed mesocosms to test the prediction that higher temperatures decrease species richness and increase assemblage similarity more and faster than lower temperatures. We incubated two temperate forest soil types at constant temperatures from 10° to 35°, destructively sampling mesocosms at 30, 180, and 440nd. We quantified taxonomic richness and assemblage similarity of soil bacteria using 16S rRNA gene amplicons. As predicted, mesocosms at higher temperatures lost more taxa than those at lower temperature. Contrary to predictions, the simplified assemblages at higher temperatures became less similar to each other over time. After 440nd of incubation, the number of taxa lost was a linear function of the difference between treatment temperature and site mean annual temperature, while assemblage similarity decreased as an accelerating function of this temperature difference.

 Premise of the study: Darwin fi rst proposed that species with larger ecological breadth have greater phenotypic variation. We tested this hypothesis by comparing intraspecifi c variation in specifi c leaf area (SLA) to species’ local elevational range and by assessing how external (abiotic) fi lters may infl uence observed differences in ecological breadth among species. Understanding the patterns of individual variation within and between populations will help evaluate differing hypotheses for structuring of communities and distribution of species.  Methods: We selected 21 species with varying elevational ranges and compared the coeffi cient of variation of SLA for each species against its local elevational range. We examined the infl uence of external fi lters on local trait composition by determining if intraspecifi c changes in SLA with elevation have the same direction and similar rates of change as the change in community mean SLA value.  Key results: In support of Darwin’s hypothesis, we found a positive relationship between species’ coeffi cient of variation for SLA with species’ local elevational range. Intraspecifi c changes in SLA had the same sign, but generally lower magnitude than the community mean SLA.  Conclusions: The results indicate that wide-ranging species are indeed characterized by greater intraspecifi c variation and that species’ phenotypes shift along environmental gradients in the same direction as the community phenotypes. However, across species, the rate of intraspecifi c trait change, refl ecting plastic and/or adaptive changes across populations, is limited and prevents species from adjusting to environmental gradients as quickly as interspecifi c changes resulting from community assembly.

Several theories predict whole-tree function on the basis of allometric scaling relationships assumed to emerge from traits of branching networks. To test this key assumption, and more generally, to explore patterns of external architecture within and across trees, we measure branch traits (radii/lengths) and calculate scaling exponents from five functionally divergent species. Consistent with leading theories, including metabolic scaling theory, branching is area preserving and statistically self-similar within trees. However, differences among scaling exponents calculated at node- and whole-tree levels challenge the assumption of an optimised, symmetrically branching tree. Furthermore, scaling exponents estimated for branch length change across branching orders, and exponents for scaling metabolic rate with plant size (or number of terminal tips) significantly differ from theoretical predictions. These findings, along with variability in the scaling of branch radii being less than for branch lengths, suggest extending current scaling theories to include asymmetrical branching and differential selective pressures in plant architectures.

Summary 1. The leaf economics spectrum (LES) describes global interspecific correlations between leaf traits. Despite recent theoretical advances, the biological scale at which LES correlations emerge and the physiological and climatic causes of these correlations remains partially unknown. 2. Here, we test an extant theory based on universal trade-offs in leaf venation networks that predicts that (i) the LES primarily originates within individuals; (ii) minor vein density drives LES trait correlations; and (iii) between individuals, LES correlations reflects variation in minor vein density driven by water availability. To test these predictions, we sample leaves within and between clones of Populus tremuloides across a wide climate gradient. 3. We show that predictions i) and iii) are supported but ii) is only partially supported. To account for this discrepancy, we develop a more general venation theory. This theory describes linkages between vein density, leaf area and leaf thickness that can modulate LES correlations across scales. This theory helps to identify multiple selective pressures that can drive trait covariation underlying the LES. 4. Synthesis. Our results broaden the range of biological scales at which the leaf economics spectrum (LES) is found and highlight the complex causal roles of venation networks in LES correlations. This study points to the need to better understand the coupling between venation networks, leaf size and climate to fully understand the LES.

Questions Are patterns of intra- and inter-specific functional trait variation consistent with greater abiotic filtering on community assembly at high latitudes and elevations, and greater biotic filtering at low latitudes and elevations? Locations Area de Conservacion Guanacaste, Costa Rica; Santa Catalina Mountains, Arizona; Siskiyou Mountains, Oregon. Methods We measured woody plant species abundance and a key functional trait associated with competition for resources and environmental tolerance (specific leaf area, SLA) along elevational gradients in low-latitude tropical (Costa Rica), mid-latitude desert (Arizona) and high latitude mediterranean (southern Oregon) biomes. We explored patterns of abiotic and biotic filtering by comparing observed patterns of community-weighted means and variances along elevational and latitudinal gradients to those expected under random assembly. In addition, we related trait variability to niches and explored how total trait space and breadth vary across broad spatial gradients by quantifying the ratio of intra- to inter-specific variation. Results Both the community-wide mean and variance of SLA decreased with increasing latitude, consistent with greater abiotic filtering at higher latitudes. Further, low-elevation communities had higher trait variation than expected by chance, consistent with greater biotic filtering at low elevations. Finally, in the tropics and across latitude the ratio of intra- to inter-specific variation was negatively correlated to species richness, which further suggests that biotic interactions influence plant assembly at low latitudes. Conclusions Intra- and inter-specific patterns of SLA variation appeared broadly consistent with the idea that the relative strength of biotic and abiotic drivers on community assembly changes along elevational and latitudinal gradients; evidence for biotic drivers appeared more prominent at low latitudes and elevations and evidence for abiotic drivers appeared more prominent at high latitudes and elevations.

This dataset provides growth form classifications for 67,413 vascular plant species from North, Central, and South America. The data used to determine growth form were compiled from five major integrated sources and two original publications: the Botanical Information and Ecology Network (BIEN), the Plant Trait Database (TRY), the SALVIAS database, the USDA PLANTS database, Missouri Botanical Garden's Tropicos database, Wright (2010), and Boyle (1996). We defined nine plant growth forms based on woodiness (woody or non-woody), shoot structure (self-supporting or not self-supporting), and root traits (rooted in soil, not rooted in soil, parasitic or aquatic): Epiphyte, Liana, Vine, Herb, Shrub, Tree, Parasite, or Aquatic. Species with multiple growth form classifications were assigned the growth form classification agreed upon by the majority (> 2/3) of sources. Species with ambiguous or otherwise not interpretable growth form assignments were excluded from the final dataset but are made available with the original data. Comparisons with independent estimates of species richness for the Western hemisphere suggest that our final dataset includes the majority of New World vascular plant species. Coverage is likely more complete for temperate than for tropical species. In addition, aquatic species are likely under-represented. Nonetheless, this dataset represents the largest compilation of plant growth forms published to date, and should contribute to new insights across a broad range of research in systematics, ecology, biogeography, conservation, and global change science.

One of the major challenges in ecology is to understand how ecosystems respond to changes inenvironmental conditions, and how taxonomic and functional diversity mediate these changes. Inthis study, we use a trait-spectra and individual-based model, to analyse variation in forest primaryproductivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accuratelypredicted the magnitude and trends in forest productivity with elevation, with solar radiation andplant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, andwood density) collectively accounting for productivity variation. Remarkably, explicit representationof temperature variation with elevation was not required to achieve accurate predictions offorest productivity, as trait variation driven by species turnover appears to capture the effect oftemperature. Our semi-mechanistic model suggests that spatial variation in traits can potentiallybe used to estimate spatial variation in productivity at the landscape scale. Fil: Fyllas, Nikolaos M.. University of Oxford; Reino Unido Fil: Patrick Bentley, Lisa. University of Oxford; Reino Unido Fil: Shenkin, Alexander. University of Oxford; Reino Unido Fil: Asner, Gregory P.. Carnegie Institution for Science. Department of Global Ecology; Reino Unido Fil: Atkin, Owen K.. The Australian National University. ARC Centre of Excellence in Plant Energy Biology. Research School of Biology; Australia Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; Argentina Fil: Enquist, Brian J.. Arizona State University; Estados Unidos Fil: Farfan Rios, William. University Wake Forest; Estados Unidos Fil: Gloor, Emanuel. University of Leeds; Reino Unido Fil: Guerrieri, Rossella. Universitat Autònoma de Barcelona; España. University of Edinburgh; Reino Unido Fil: Huaraca Huasco, Walter. Universidad Nacional de San Antonio Abad del Cusco; Perú Fil: Ishida, Yoko. James Cook University; Australia Fil: Martin, Roberta E.. Carnegie Institution for Science. Department of Global Ecology; Estados Unidos Fil: Meir, Patrick. University of Edinburgh; Reino Unido. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Phillips, Oliver. University of Leeds; Reino Unido Fil: Salinas, Norma. University of Oxford; Reino Unido. Pontificia Universidad Católica de Perú; Perú Fil: Silman, Miles. University Wake Forest; Estados Unidos Fil: Weerasinghe, Lasantha K.. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia Fil: Zaragoza Castells, Joana. The Australian National University. Research School of Biology. Division of Plant Sciences; Australia. University of Exeter; Reino Unido Fil: Malhi, Yadvinder. University of Oxford; Reino Unido

Leaf thermoregulation has been documented in a handful of studies, but the generality and origins of this pattern are unclear. We suggest that leaf thermoregulation is widespread in both space and time, and originates from the optimization of leaf traits to maximize leaf carbon gain across and within variable environments. Here we use global data for leaf temperatures, traits and photosynthesis to evaluate predictions from a novel theory of thermoregulation that synthesizes energy budget and carbon economics theories. Our results reveal that variation in leaf temperatures and physiological performance are tightly linked to leaf traits and carbon economics. The theory, parameterized with global averaged leaf traits and microclimate, predicts a moderate level of leaf thermoregulation across a broad air temperature gradient. These predictions are supported by independent data for diverse taxa spanning a global air temperature range of ∼60 °C. Moreover, our theory predicts that net carbon assimilation can be maximized by means of a trade-off between leaf thermal stability and photosynthetic stability. This prediction is supported by globally distributed data for leaf thermal and photosynthetic traits. Our results demonstrate that the temperatures of plant tissues, and not just air, are vital to developing more accurate Earth system models.

Waxy compounds form the boundary layer of the living leaf and contribute biomarkers to soils, and lake and marine sediments. Cataloging the variation in leaf wax traits between species and across environmental gradients may contribute to the understanding of plant functional processes in modern ecosystems, as well as to calibration efforts supporting reconstruction of past ecosystems and environments from the sedimentary archives of leaf wax biomarkers. Towards these goals, we have surveyed the distributions of leaf wax n-alkanes in trees from the lowland tropical rainforest (TR) and montane cloud forest (TMCF) of Peru. Molecular abundances were quantified via gas chromatography flame ionization detection (GC-FID) for 632 individuals, 152 species, 99 genera and 51 families across 9 forest plots spanning 0.2–3.6 km elevation. We found the expected abundance distributions; for example, they were dominated by long chain, odd numbered n-alkanes, especially C29 and C31. New observations included a tendency to increasing total alkane concentration at higher elevation. We propose that the well known leaf economic strategy to increase leaf mass per unit area with elevation, provides a theoretical basis for understanding the increase in leaf wax n-alkane abundance with elevation: we infer an increased investment in foliar defense associated with increased leaf lifespan and in response to environmental pressures including cloud immersion and declining temperature. Furthermore, we combined measurements of n-alkane concentration with estimates of forest productivity to provide new ways to quantify ecosystem-scale forest alkane productivity. We introduce a new concept of n-alkane net primary productivity (NPPalk; the product of alkane concentration and leaf NPP) and find that alkane productivity estimates range from 300 to 5000 g C/ha/yr, associated with ecological and environmental changes across the elevation profile.

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.

Understanding and forecasting species' geographic distributions in the face of global change is a central priority in biodiversity science. The existing view is that one must choose between correlative models for many species versus process-based models for few species. We suggest that opportunities exist to produce process-based range models for many species, by using hierarchical and inverse modeling to borrow strength across species, fill data gaps, fuse diverse data sets, and model across biological and spatial scales. We review the statistical ecology and population and range modeling literature, illustrating these modeling strategies in action. A variety of large, coordinated ecological datasets that can feed into these modeling solutions already exist, and we highlight organisms that seem ripe for the challenge.

© 2016, National Academy of Sciences. All rights reserved. The respiratory release of carbon dioxide (CO2) from soil is a major yet poorly understood flux in the global carbon cycle. Climatic warming is hypothesized to increase rates of soil respiration, potentially fueling further increases in global temperatures. However, despite considerable scientific attention in recent decades, the overall response of soil respiration to anticipated climatic warming remains unclear. We synthesize the largest global dataset to date of soil respiration, moisture, and temperature measurements, totaling >3,800 observations representing 27 temperature manipulation studies, spanning nine biomes and over 2 decades of warming. Our analysis reveals no significant differences in the temperature sensitivity of soil respiration between control and warmed plots in all biomes, with the exception of deserts and boreal forests. Thus, our data provide limited evidence of acclimation of soil respiration to experimental warming in several major biome types, contrary to the results from multiple single-site studies. Moreover, across all nondesert biomes, respiration rates with and without experimental warming follow a Gaussian response, increasing with soil temperature up to a threshold of ∼25 °C, above which respiration rates decrease with further increases in temperature. This consistent decrease in temperature sensitivity at higher temperatures demonstrates that rising global temperatures may result in regionally variable responses in soil respiration, with colder climates being considerably more responsive to increased ambient temperatures compared with warmer regions. Our analysis adds a unique cross-biome perspective on the temperature response of soil respiration, information critical to improving our mechanistic understanding of how soil carbon dynamics change with climatic warming.

During the Late Pleistocene and early Holocene 59 species of South American megafauna went extinct. Their extinction potentially triggered population declines of large-seeded tree species dispersed by the large-bodied frugivores with which they co-evolved, a theory first proposed by Janzen and Martin (1982). We tested this hypothesis using species range maps for 257 South American tree species, comparing 63 species thought to be primarily distributed by megafauna with 194 distributed by other animals. We found a highly significant (p 95% following disperser extinction. A numerical gap dynamic simulations suggests that over a 10 000 yr period following the disperser extinctions, the average convex hull range size of large-seeded tree species decreased by ∼ 31%, while the estimated decrease in population size was ∼ 54%, indicating a likely greater decrease in species population size than indicated by the empirical range patterns. Finally, we found a positive correlation between seed size and wood density of animal-dispersed tree species implying that the Late Pleistocene and early Holocene megafaunal extinctions reduced carbon content in the Amazon by ∼ 1.5 ± 0.7%. In conclusion, we 1) provide some empirical evidence that megafauna distributed fruit species have a smaller mean range size than wind, water or other animal-dispersed species, 2) demonstrate mathematically that such range reductions are expected from megafauna extinctions ca 12 000 yr ago, and 3) illustrate that these extinctions may have reduced the Amazon's carbon storage capacity.

Leaf aging is a fundamental driver of changes in leaf traits, thereby regulating ecosystem processes and remotely sensed canopy dynamics. We explore leaf reflectance as a tool to monitor leaf age and develop a spectra-based partial least squares regression (PLSR) model to predict age using data from a phenological study of 1099 leaves from 12 lowland Amazonian canopy trees in southern Peru. Results demonstrated monotonic decreases in leaf water (LWC) and phosphorus (Pmass ) contents and an increase in leaf mass per unit area (LMA) with age across trees; leaf nitrogen (Nmass ) and carbon (Cmass ) contents showed monotonic but tree-specific age responses. We observed large age-related variation in leaf spectra across trees. A spectra-based model was more accurate in predicting leaf age (R2 =0.86; percent root mean square error (%RMSE)=33) compared with trait-based models using single (R2 =0.07-0.73; %RMSE=7-38) and multiple (R2 =0.76; %RMSE=28) predictors. Spectra- and trait-based models established a physiochemical basis for the spectral age model. Vegetation indices (VIs) including the normalized difference vegetation index (NDVI), enhanced vegetation index 2 (EVI2), normalized difference water index (NDWI) and photosynthetic reflectance index (PRI) were all age-dependent. This study highlights the importance of leaf age as a mediator of leaf traits, provides evidence of age-related leaf reflectance changes that have important impacts on VIs used to monitor canopy dynamics and productivity and proposes a new approach to predicting and monitoring leaf age with important implications for remote sensing.

Summary Advances in both informatics and mobile technology are providing exciting new opportunities for generating, disseminating, and engaging with information in the biological sciences at unprecedented spatial scales, particularly in disentangling information on the distributions and natural history of hyperdiverse groups of organisms. We describe an application serving as a mobile catalog of all of the plants of the Americas developed using species distribution models estimated from field observations of plant occurrences. The underlying data comprise over 3·5 million standardized observations of over 88 000 plant species. Plant-O-Matic, a free iOS application, combines the species distribution models with the location services built into a mobile device to provide users with a list of all plant species expected to occur in the 100 × 100 km geographic grid cell corresponding to the user's location. The application also provides ancillary information on species’ attributes (when available) including growth form, reproductive mode, flower color, and common name. Results can be searched and conditionally filtered based on these attributes. Links to externally sourced specimen images further aid in identification of species by the user. The application's ability to assemble locally relevant lists of plant species and their attributes on demand for anywhere in the Americas provides a powerful new tool for identifying, exploring, and understanding plant diversity. Mobile applications such as Plant-O-Matic can facilitate dynamic new approaches to science, conservation, and science education.

 Premise of the Study: Leaf area is a key trait that links plant form, function, and environment. Measures of leaf area can be biased because leaf area is often estimated from dried or fossilized specimens that have shrunk by an unknown amount. We tested the common assumption that this shrinkage is negligible.  Methods: We measured shrinkage by comparing dry and fresh leaf area in 3401 leaves of 380 temperate and tropical species and used phylogenetic and trait-based approaches to determine predictors of this shrinkage. We also tested the effects of rehydration and simulated fossilization on shrinkage in four species.  Key Results: We found that dried leaves shrink in area by an average of 22% and a maximum of 82%. Shrinkage in dried leaves can be predicted by multiple morphological traits with a standard deviation of 7.8%. We also found that mud burial, a proxy for compression fossilization, caused negligible shrinkage, and that rehydration, a potential treatment of dried herbarium specimens, eliminated shrinkage.  Conclusions: Our fi ndings indicate that the amount of shrinkage is driven by variation in leaf area, leaf thickness, evergreenness, and woodiness and can be reversed by rehydration. The amount of shrinkage may also be a useful trait related to ecologically and physiological differences in drought tolerance and plant life history.

Summary Leaf venation networks mediate many plant resource fluxes and are therefore of broad interest to research questions in plant physiology, systematics, paleoecology, and physics. However, the study of these networks is limited by slow and destructive imaging methods. X-ray imaging of leaf veins is potentially rapid, of high resolution, and nondestructive. Here, we have developed theory for absorption- and phase-contrast X-ray imaging. We then experimentally test these approaches using a synchrotron light source and two commercially available X-ray instruments. Using synchrotron light, we found that major veins could be consistently visualized using absorption-contrast imaging with X-ray energies

Summary 1. Metabolic scaling theory predicts how tree water flow rate (Q) scales with tree mass (M) and assumes identical scaling for biomass growth rate (G )w ithM. Analytic models have derived general scaling expectations from proposed optima in the rate of axial xylem conduit taper (taper function) and the allocation of wood space to water conduction (packing function). Recent predictions suggest G andQ scale with M to the � 0·7 power with 0·75 as an upper bound. 2. We complement this a priori optimization approach with a numerical model that incorporates species-specific taper and packing functions, plus additional empirical inputs essential for predicting Q (effects of gravity, tree size, heartwood, bark, and hydraulic resistance of leaf, root and interconduit pits). Traits are analysed individually, and in ensemble across tree types, to define a 2D ‘scaling space’ of absolute Q vs. its scaling exponent with tree size. 3. All traits influenced Q and many affected its scaling with M. Constraints driving the optimization of taper or packing functions, or any other trait, can be relaxed via compensatory changes in other traits. 4. The scaling space of temperate trees overlapped despite diverse anatomy and winter-adaptive strategies. More conducting space in conifer wood compensated for narrow tracheids; extensive sapwood in diffuse-porous trees compensated for narrow vessels; and limited sapwood in ring-porous trees negated the effect of large vessels. Tropical trees, however, achieved the greatest Q and steepest size-scaling by pairing large vessels with extensive sapwood, a combination compatible with minimal water stress and no freezing-stress. 5. Intraspecific scaling across all types averaged Q / M 0·63 (maximum = Q / M 0·71 ) for size-invariant root–shoot ratio. Scaling reached Q / M 0·75 only if conductance increased faster in roots than in shoots with size. Interspecific scaling could reach Q / M 0·75 , but this may require the evolution of size-biased allometries rather than arising directly from biophysical constraints. 6. Our species-level model is more realistic than its analytical predecessors and provides a tool for interpreting the adaptive significance of functional trait diversification in relation to wholetree water use and consequent metabolic scaling.

Summary 1. A 17-parameter ‘species model’ that predicts metabolic scaling from vascular architecture was tested in a diffuse-porous maple (Acer grandidentatum) and a ring-porous oak (Quercus gambelii). Predictions of midday water transport (Q) and its scaling with above-ground mass (M) were compared with empirical measurements. We also tested the assumption that Q was proportional to the biomass growth rate of the shoot (G). 2. Water transport and biomass growth rate were measured on 18 trees per species that spanned a broad range in trunk diameter (4–26 cm). Where possible, the same trees were used for obtaining the 17 model parameters that concern external branching, internal xylem conduit anatomy, and soil-to-canopy sap pressure drop. 3. The model succeeded in predicting the Q by M b scaling exponent, b, being within 8% (maple) and 6% (oak) of measured exponents from sap flow data. In terms of absolute Q, the model was better in maple (16% Q overestimate) than oak (128% overestimate). The overestimation of Q was consistent with the model not accounting for cavitation, which is reportedly more prevalent in oak than in maple at the study site. 4. The modelled and measured Q by M b exponents averaged within 3·6% of the measured G by M b exponents, supporting the assumption that G / Q 1 . The average b exponent was 0·62 ± 0·016 (mean ± SE) across species, rejecting b =0 ·75 for intraspecific scaling. 5. The performance of this species model, both for scaling purposes as well as for predicting rates of water consumption within and between species, argues for its further refinement and wider application in ecology and ecosystem biology.

Plants are expected to differentially allocate resources to reproduction, growth, and survival in order to maximize overall fitness. Life history theory predicts that the allocation of resources to reproduction should occur at the expense of vegetative growth. Although it is known that both organism size and resource availability can influence life history traits, few studies have addressed how size dependencies of growth and reproduction and variation in resource supply jointly affect the coupling between growth and reproduction. In order to understand the relationship between growth and reproduction in the context of resource variability, we utilize a long-term observational data set consisting of 670 individual trees over a 10-year period within a local population of Bursera simaruba (L.) Sarg. We (1) quantify the functional form and variability in the growth-reproduction relationship at the population and individual-tree level and (2) develop a theoretical framework to understand the allometric dependence of growth and reproduction. Our findings suggest that the differential responses of allometric growth and reproduction to resource availability, both between years and between microsites, underlie the apparent relationship between growth and reproduction. Finally, we offer an alternative approach for quantifying the relationship between growth and reproduction that accounts for variation in allometries.

A commonly used null model for species association among forest trees is a well-mixed community (WMC). A WMC represents a non-spatial, or spatially implicit, model, in which species form nearest-neighbor pairs at a rate equal to the product of their community proportions. WMC models assume that the outcome of random dispersal and demographic processes is complete spatial randomness (CSR) in the species ’ spatial distributions. Yet, stochastic dispersal processes often lead to spatial autocorrelation (SAC) in tree species densities, giving rise to clustering, segregation, and other nonrandom patterns. Although methods exist to account for SAC in spatially-explicit models, its impact on non-spatial models often remains unaccounted for. To investigate the potential for SAC to bias tests based upon non-spatial models, we developed a spatially-heterogeneous (SH) modelling approach that incorporates measured levels of SAC. Using the mapped locations of individuals in a tropical tree community, we tested the hypothesis that the identity of nearest-neighbors represents a random draw from neighborhood species pools. Correlograms of Moran ’ s I confi rmed that, for 50 of 51 dominant species, stem density was signifi cantly autocorrelated over distances ranging from 50 to 200 m. Th e observed patterns of SAC were consistent with dispersal limitation, with most species occurring in distinct patches. For nearly all of the 106 species in the community, the frequency of pairwise association was statistically indistinguishable from that projected by the null models. However, model comparisons revealed that non-spatial models more strongly underestimated observed species-pair frequencies, particularly for conspecifi c pairs. Overall, the CSR models projected more signifi cant facilitative interactions than did SH models, yielding a more liberal test of niche diff erences. Our results underscore the importance of accounting for stochastic spatial processes in tests of association, regardless of whether spatial or non-spatial models are employed.

Aim In recent years evidence has accumulated that plant species are differentially sorted from regional assemblages into local assemblages along local-scale environmental gradients on the basis of their function and abiotic filtering. The favourability hypothesis in biogeography proposes that in climatically difficult regions abiotic filtering should produce a regional assemblage that is less functionally diverse than that expected given the species richness and the global pool of traits. Thus it seems likely that differential filtering of plant traits along local-scale gradients may scale up to explain the distribution, diversity and filtering of plant traits in regional-scale assemblages across continents. The present work aims to address this prediction.

Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.

The functional association between body size and metabolic rate (BS-MR) is one of the most intriguing issues in ecological physiology. An average scaling exponent of 3/4 is broadly observed across animal and plant taxa. The numerical value of 3/4 is theoretically predicted under the optimized version of West, Brown, and Enquist's vascular resource supply network model. Insects, however, have recently been proposed to express a numerically different scaling exponent and thus application of the WBE network model to insects has been rejected. Here, we re-analyze whether such variation is indeed supported by a global deviation across all insect taxa at the order and family levels to assess if specific taxa influence insect metabolic scaling. We show that a previous reported deviation is largely due to the effect of a single insect family (Termitidae). We conclude that the BS-MR relationship in insects broadly supports the core predictions of the WBE model. We suggest that the deviation observed within the termites warrants further investigation and may be due to either difficulty in accurately measuring termite metabolism and/or particularities of their life history. Future work on allometric scaling should assess the nature of variation around the central tendencies in scaling exponents in order to test if this variation is consistent with core assumptions and predictions of the WBE model that stem by relaxing its secondary optimizing assumptions that lead to the 3/4 exponent.

Aim To evaluate the strength of evidence for hypotheses explaining the relationship between climate and species richness in forest plots. We focused on the effect of energy availability which has been hypothesized to influence species richness: (1) via the effect of productivity on the total number of individuals (the more individuals hypothesis, MIH); (2) through the effect of temperature on metabolic rate (metabolic theory of biodiversity, MTB); or (3) by imposing climatic limits on species distributions. Location Global. Methods We utilized a unique ‘Gentry-style’ 370 forest plots data set comprising tree counts and individual stem measurements, covering tropical and temperate forests across all six forested continents. We analysed variation in plot species richness and species richness controlled for the number of individuals by using rarefaction. Ordinary least squares (OLS) regression and spatial regressions were used to explore the relative performance of different sets of environmental variables. Results Species richness patterns do not differ whether we use raw number of species or number of species controlled for number of individuals, indicating that number of individuals is not the proximate driver of species richness. Productivityrelated variables (actual evapotranspiration, net primary productivity, normalized difference vegetation index) perform relatively poorly as correlates of tree species richness. The best predictors of species richness consistently include the minimum temperature and precipitation values together with the annual means of these variables. Main conclusion Across the world’s forests there is no evidence to support the MIH, and a very limited evidence for a prominent role of productivity as a driver of species richness patterns. The role of temperature is much more important, although this effect is more complex than originally assumed by the MTB. Variation in forest plot diversity appears to be mostly affected by variation in the minimum climatic values. This is consistent with the ‘climatic tolerance hypothesis’ that climatic extremes have acted as a strong constraint on species distribution and diversity.

The leaf economics spectrum describes biome-invariant scaling functions for leaf functional traits that relate to global primary productivity and nutrient cycling. Here, we develop a comprehensive framework for the origin of this leaf economics spectrum based on venation-mediated economic strategies. We define a standardized set of traits - density, distance and loopiness - that provides a common language for the study of venation. We develop a novel quantitative model that uses these venation traits to model leaf-level physiology, and show that selection to optimize the venation network predicts the mean global trait-trait scaling relationships across 2548 species. Furthermore, using empirical venation data for 25 plant species, we test our model by predicting four key leaf functional traits related to leaf economics: net carbon assimilation rate, life span, leaf mass per area ratio and nitrogen content. Together, these results indicate that selection on venation geometry is a fundamental basis for understanding the diversity of leaf form and function, and the carbon balance of leaves. The model and associated predictions have broad implications for integrating venation network geometry with pattern and process in ecophysiology, ecology and palaeobotany.

Disentangling the relative roles of biotic and abiotic forces influencing forest structure, function, and local community composition continues to be an important goal in ecology. Here, utilizing two forest surveys 20-year apart from a Central American dry tropical forest, we assess the relative role of past disturbance and local climatic change in the form of increased drought in driving forest dynamics. We observe: (i) a net decrease in the number of trees; (ii) a decrease in total forest biomass by 7.7 Mg ha � 1 but when calculated on subquadrat basis the biomass per unit area did not change indicating scale sensitivity of forest biomass measures; (iii) that the decrease in the number of stems occurred mainly in the smallest sizes, and in more moist and evergreen habitats; (iv) that there has been an increase in the proportion of trees that are deciduous, compound leaved and are canopy species, and a concomitant reduction in trees that are evergreen, simple-leaved, and understory species. These changes are opposite to predictions based on recovery from disturbance, and have resulted in (v) a uniform multivariate shift from a more mesic to a more xeric forest. Together, our results show that over relatively short time scales, community composition and the functional dominance may be more responsive to climate change than recovery to past disturbances. Our findings point to the importance of assessing proportional changes in forest composition and not just changes in absolute numbers. Our findings are also consistent with the hypothesis that tropical tree species exhibit differential sensitivity to changes in precipitation. Predicted future decreases in rainfall may result in quick differential shifts in forest function, physiognomy, and species composition. Quantifying proportional functional composition offers a basis for a predictive framework for how the structure, and diversity of tropical forests will respond to global change.

Summary 1. Coomes & Allen (2009) propose a new statistical method to test the Metabolic Scaling Theory prediction for tree growth rate size scaling (scaling constant α = 1/3) presented in Enquist et al. (1999). This method finds values of the scaling constant that yield standardized major axis (SMA) slopes of one in a comparison of allometrically transformed diameter census data. This SMA ‘slope-of-one’ method produces results that contrast with those generated by maximum-likelihood estimation (MLE; Russo, Wiser & Coomes 2007; Coomes & Allen 2009). 2. We hypothesize that the SMA slope-of-one method is inappropriate for this application because it assumes, unrealistically, that there is no biological or error variance in tree growth size scaling. To test our hypothesis, we simulate ‘allometric’ tree growth with biological and error variance in parameters and measurements. We find that the SMA slope-of-one method is sensitive to the amount of biological and error variance and consistently returns biassed parameter estimates, while the MLE method displays relatively little bias, particularly at larger sample sizes. 3. Synthesis. The conclusions of Coomes & Allen (2009) should be reconsidered in the light of our findings. Investigations of tree growth rate size scaling must consider the influence of biological and error variance in model-fitting procedures to ultimately unravel the effects of tree architecture and ecological factors on patterns of size-dependent growth.

Mountain big sagebrush (Artemisia tridentata Nutt. ssp. vaseyana) covers large areas in arid regions of western North America. Climate-change models predict a decrease in the range of sagebrush, but few studies have examined details of predicted changes on sagebrush growth and the potential impacts of these changes on the commu- nity. We analyzed effects of temperature, precipitation, and snow depth on sagebrush annual ring width for 1969 to 2007 in the Gunnison Basin of Colorado. Temperature at all times of year except winter had negative correlations with ring widths; summer temperature had the strongest negative relationship. Ring widths correlated positively with precipita- tion in various seasons except summer; winter precipitation had the strongest relationship with growth. Maximum snow depth also correlated positively and strongly with ring width. Multiple regressions showed that summer temperature and either winter precipitation or maximum snow depth, which recharges deeper soil horizons, are both important in controlling growth. Overall, water stress and perhaps especially maximum snow depth appear to limit growth of this species. With predicted increases in temperature and probable reduced snow depth, sagebrush growth rates are likely to decrease. If so, sagebrush populations and cover may decline, which may have substantial effects on community com- position and carbon balance.

Aim It is increasingly accepted that the mean wood density of trees within a forest is tightly coupled to above-ground forest biomass. It is unknown, however, if a positive relationship between forest biomass and mean community wood density is a general phenomenon across forests. Understanding spatial variation in biomass as a function of wood density both within and among forests is important for predicting changes in stored carbon in response to global change, and here we evaluated the generality of a positive biomass‐wood density relationship within and among six tropical forests. Location Costa Rica, Panama, Puerto Rico and Ecuador.

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.

The species abundance distribution (SAD) is one of the few universal patterns in ecology. Research on this fundamental distribution has primarily focused on the study of numerical counts, irrespective of the traits of individuals. Here we show that considering a set of Generalized Species Abundance Distributions (GSADs) encompassing several abundance measures, such as numerical abundance, biomass and resource use, can provide novel insights into the structure of ecological communities and the forces that organize them. We use a taxonomically diverse combination of macroecological data sets to investigate the similarities and differences between GSADs. We then use probability theory to explore, under parsimonious assumptions, theoretical linkages among them. Our study suggests that examining different GSADs simultaneously in natural systems may help with assessing determinants of community structure. Broadening SADs to encompass multiple abundance measures opens novel perspectives in biodiversity research and warrants future empirical and theoretical developments.

Here, we present the second part of a quantitative theory for the structure and dynamics of forests under demographic and resource steady state. The theory is based on individual-level allometric scaling relations for how trees use resources, fill space, and grow. These scale up to determine emergent properties of diverse forests, including size–frequency distributions, spacing relations, canopy configurations, mortality rates, population dynamics, successional dynamics, and resource flux rates. The theory uniquely makes quantitative predictions for both stand-level scaling exponents and normalizations. We evaluate these predictions by compiling and analyzing macroecological datasets from several tropical forests. The close match between theoretical predictions and data suggests that forests are organized by a set of very general scaling rules. Our mechanistic theory is based on allometric scaling relations, is complementary to “demographic theory,” but is fundamentally different in approach. It provides a quantitative baseline for understanding deviations from predictions due to other factors, including disturbance, variation in branching architecture, asymmetric competition, resource limitation, and other sources of mortality, which are not included in the deliberately simplified theory. The theory should apply to a wide range of forests despite large differences in abiotic environment, species diversity, and taxonomic and functional composition.

Aim Many ecological surveys record only the presence or absence of species in the cells of a rectangular grid. Ecologists have investigated methods for using these data to predict the total abundance of a species from the number of grid cells in which the species is present. Our aim is to improve such predictions by taking account of the spatial pattern of occupied cells, in addition to the number of occupied cells. Innovation We extend existing prediction models to include a spatial clustering variable. The extended models can be viewed as combining two macroecological regularities, the abundance‐occupancy regularity and a spatial clustering regularity. The models are estimated using data from five tropical forest censuses, including three Panamanian censuses (4, 6 and 50 ha), one Costa Rican census (16 ha) and one Puerto Rican census (16 ha). A serpentine grassland census (8 × 8 m) from northern California is also studied. Main conclusions Taking account of the spatial clustering of occupied cells improves abundance prediction from presence‐absence data, reducing the mean square error of log-predictions by roughly 54% relative to a benchmark Poisson predictor and by roughly 34% relative to current prediction methods. The results have high statistical significance.

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.

Local population abundance often declines with increasing distance from the center of the species' geographic range. This pattern has been hypothesized to parallel the decline in the probability of encountering favorable niche requirements, implying that local abundance is primarily a reflection of local environmental conditions. In this study we evaluate a potential corollary of this hypothesis. We postulate that local conditions that depress abundance are also likely to perturb development. Accordingly, we predicted that spatial patterns in abundance should be mirrored by spatial patterns of developmental instability. To test this prediction we compared 38 contemporary and Pleistocene populations, belonging to 30 mollusc species. Samples were collected at a single site along the Gulf of California, differentially located in relation to the center of each species' geographic range. We identified, as boundaries to triangular bivariate distributions, a negative relationship between developmental instability and relative abundance, and a positive relationship between instability and relative distance from the center of the range. Overall, however, the observed pattern deviated from the expected in that the majority of low-abundance peripheral populations exhibit relatively low levels of developmental instability.

Power-law frequency distributions characterize a wide array of natural phenomena. In ecology, biology, and many physical and social sciences, the exponents of these power laws are estimated to draw inference about the processes underlying the phenomenon, to test theoretical models, and to scale up from local observations to global patterns. Therefore, it is essential that these exponents be estimated accurately. Unfortunately, the binning-based methods traditionally used in ecology and other disciplines perform quite poorly. Here we discuss more sophisticated methods for fitting these exponents based on cumulative distribution functions and maximum likelihood estimation. We illustrate their superior performance at estimating known exponents and provide details on how and when ecologists should use them. Our results confirm that maximum likelihood estimation outperforms other methods in both accuracy and precision. Because of the use of biased statistical methods for estimating the exponent, the conclusions of several recently published papers should be revisited.