Ethan P White

University of North Carolina at Chapel Hill, Chapel Hill, NC, United States

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Publications (39)315.18 Total impact

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    Xiao Xiao, Daniel J. McGlinn, Ethan P. White
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    ABSTRACT: The Maximum Entropy Theory of Ecology (METE) is a unified theory of biodiversity that predicts a large number of macroecological patterns using only information on the species richness, total abundance, and total metabolic rate of the community. We conducted a strong test of METE, where four of its major predictions were evaluated simultaneously using data from 60 globally distributed communities including over 300,000 individuals and nearly 2000 species. While METE successfully captured 96% and 93% of the variation in the species abundance distribution and the individual size distribution, it performed poorly when characterizing the size-density relationship and the intraspecific distribution of individual body size. Specifically, METE predicts a negative correlation between individual energy use and species abundance, which is weak in natural communities. By evaluating multiple predictions with large quantities of data, our study not only identifies a mismatch between abundance and body size in METE, but also serves as a general example on the importance of conducting strong tests of ecological theories.
    08/2013;
  • Kenneth J Locey, Ethan P White
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    ABSTRACT: The species abundance distribution (SAD) is one of the most intensively studied distributions in ecology and its hollow-curve shape is one of ecology's most general patterns. We examine the SAD in the context of all possible forms having the same richness (S) and total abundance (N), i.e. the feasible set. We find that feasible sets are dominated by similarly shaped hollow curves, most of which are highly correlated with empirical SADs (most R(2) values > 75%), revealing a strong influence of N and S on the form of the SAD and an a priori explanation for the ubiquitous hollow curve. Empirical SADs are often more hollow and less variable than the majority of the feasible set, revealing exceptional unevenness and relatively low natural variability among ecological communities. We discuss the importance of the feasible set in understanding how general constraints determine observable variation and influence the forms of predicted and empirical patterns.
    Ecology Letters 07/2013; · 17.95 Impact Factor
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    ABSTRACT: Abstract Studies of biodiversity typically assume that all species are equivalent. However, some species in a community maintain viable populations in the study area, while others occur only occasionally as transient individuals. Here we show that North American bird communities can reliably be divided into core and transient species groups and that the richness of each group is driven by different processes. The richness of core species is influenced primarily by local environmental conditions, while the richness of transient species is influenced primarily by the heterogeneity of the surrounding landscape. This demonstrates that the well-known effects of the local environment and landscape heterogeneity on overall species richness are the result of two sets of processes operating differentially on core and transient species. Models of species richness should focus on explaining two distinct patterns, those of core and transient species, rather than a single pattern for the community as a whole.
    The American Naturalist 04/2013; 181(4):E83-E90. · 4.55 Impact Factor
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    Benjamin D Morris, Ethan P White
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    ABSTRACT: Ecological research relies increasingly on the use of previously collected data. Use of existing datasets allows questions to be addressed more quickly, more generally, and at larger scales than would otherwise be possible. As a result of large-scale data collection efforts, and an increasing emphasis on data publication by journals and funding agencies, a large and ever-increasing amount of ecological data is now publicly available via the internet. Most ecological datasets do not adhere to any agreed-upon standards in format, data structure or method of access. Some may be broken up across multiple files, stored in compressed archives, and violate basic principles of data structure. As a result acquiring and utilizing available datasets can be a time consuming and error prone process. The EcoData Retriever is an extensible software framework which automates the tasks of discovering, downloading, and reformatting ecological data files for storage in a local data file or relational database. The automation of these tasks saves significant time for researchers and substantially reduces the likelihood of errors resulting from manual data manipulation and unfamiliarity with the complexities of individual datasets.
    PLoS ONE 01/2013; 8(6):e65848. · 3.53 Impact Factor
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    Daniel J McGlinn, Xiao Xiao, Ethan P White
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    ABSTRACT: The Maximum Entropy Theory of Ecology (METE) predicts a universal species-area relationship (SAR) that can be fully characterized using only the total abundance (N) and species richness (S) at a single spatial scale. This theory has shown promise for characterizing scale dependence in the SAR. However, there are currently four different approaches to applying METE to predict the SAR and it is unclear which approach should be used due to a lack of empirical comparison. Specifically, METE can be applied recursively or non-recursively and can use either a theoretical or observed species-abundance distribution (SAD). We compared the four different combinations of approaches using empirical data from 16 datasets containing over 1000 species and 300,000 individual trees and herbs. In general, METE accurately downscaled the SAR (R (2) > 0.94), but the recursive approach consistently under-predicted richness. METE's accuracy did not depend strongly on using the observed or predicted SAD. This suggests that the best approach to scaling diversity using METE is to use a combination of non-recursive scaling and the theoretical abundance distribution, which allows predictions to be made across a broad range of spatial scales with only knowledge of the species richness and total abundance at a single scale.
    PeerJ. 01/2013; 1:e212.
  • Ecology 12/2012; 93(2505):2505-2511. · 5.18 Impact Factor
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    ABSTRACT: Macroecological patterns such as the species-area relationship (SAR), the species-abundance distribution (SAD), and the species-time relationship (STR) exhibit regular behavior across ecosystems and taxa. However, determinants of these patterns remain poorly understood. Emerging theoretical frameworks for macroecology attempt to understand this regularity by ignoring detailed ecological interactions and focusing on the influence of a small number of community-level state variables, such as species richness and total abundance, on these patterns. We present results from a 15-year rodent removal experiment evaluating the response of three different macroecological patterns in two distinct annual plant communities (summer and winter) to two levels of manipulated seed predation. Seed predator manipulations significantly impacted species composition on all treatments in both communities, but did not significantly impact richness, community abundance, or macroecological patterns in most cases. How'ever, winter community abundance and richness responded significantly to the removal of all rodents. Changes in richness and abundance were coupled with significant shifts in macroecological patterns (SADs, SARs, and STRs). Because altering species interactions only impacted macroecological patterns when the state variables of abundance and richness also changed, we suggest that, in this system, local-scale processes primarily act indirectly through these properties to determine macroecological patterns.
    Ecology 12/2012; 93(12):2505-11. · 5.18 Impact Factor
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    ABSTRACT: The species abundance distribution (SAD) is one of themost studied patterns in ecology due to its potential insights into commonness and rarity, community assembly, and patterns of biodiversity. It is well established that communities are composed of a few common and many rare species, and numerous theoretical models have been proposed to explain this pattern. However, no attempt has been made to determine how well these theoretical characterizations capture observed taxonomic and global-scale spatial variation in the general form of the distribution. Here, using data of a scope unprecedented in community ecology, we show that a simple maximum entropy model produces a truncated log-series distribution that can predict between 83% and 93% of the observed variation in the rank abundance of species across 15 848 globally distributed communities including birds, mammals, plants, and butterflies. This model requires knowledge of only the species richness and total abundance of the community to predict the full abundance distribution, which suggests that these factors are sufficient to understand the distribution for most purposes. Since geographic patterns in richness and abundance can often be successfully modeled, this approach should allow the distribution of commonness and rarity to be characterized, even in locations where empirical data are unavailable.
    Ecology 08/2012; 93(8):1772-8. · 5.18 Impact Factor
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    ABSTRACT: Power-law relationships are among the most well-studied functional relationships in biology. Recently the common practice of fitting power laws using linear regression (LR) on log-transformed data has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations, we demonstrate that the error distribution determines which method performs better, with NLR better characterizing data with additive, homoscedastic, normal error and LR better characterizing data with multiplicative, heteroscedastic, lognormal error. Analysis of 471 biological power laws shows that both forms of error occur in nature. While previous analyses based on log-transformation appear to be generally valid, future analyses should choose methods based on a combination of biological plausibility and analysis of the error distribution. We provide detailed guidelines and associated computer code for doing so, including a model averaging approach for cases where the error structure is uncertain.
    Ecology 10/2011; 92(10):1887-94. · 5.18 Impact Factor
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    Kenneth J Locey, Ethan P White
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    ABSTRACT: The study of large-scale genome structure has revealed patterns suggesting the influence of evolutionary constraints on genome evolution. However, the results of these studies can be difficult to interpret due to the conceptual complexity of the analyses. This makes it difficult to understand how observed statistical patterns relate to the physical distribution of genomic elements. We use a simpler and more intuitive approach to evaluate patterns of genome structure. We used randomization tests based on Morisita's Index of aggregation to examine average differences in the distribution of purines and pyrimidines among coding and noncoding regions of 261 chromosomes from 223 microbial genomes representing 21 phylum level groups. Purines and pyrimidines were aggregated in the noncoding DNA of 86% of genomes, but were only aggregated in the coding regions of 52% of genomes. Coding and noncoding DNA differed in aggregation in 94% of genomes. Noncoding regions were more aggregated than coding regions in 91% of these genomes. Genome length appears to limit aggregation, but chromosome length does not. Chromosomes from the same species are similarly aggregated despite substantial differences in length. Aggregation differed among taxonomic groups, revealing support for a previously reported pattern relating genome structure to environmental conditions. Our approach revealed several patterns of genome structure among different types of DNA, different chromosomes of the same genome, and among different taxonomic groups. Similarity in aggregation among chromosomes of varying length from the same genome suggests that individual chromosome structure has not evolved independently of the general constraints on genome structure as a whole. These patterns were detected using simple and readily interpretable methods commonly used in other areas of biology.
    PLoS ONE 01/2011; 6(2):e14651. · 3.53 Impact Factor
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    ABSTRACT: Aim An understanding of the relationship between forest biomass and climate is needed to predict the impacts of climate change on carbon stores. Biomass patterns have been characterized at geographically or climatically restricted scales, making it unclear if biomass is limited by climate in any general way at continental to global scales. Using a dataset spanning multiple climatic regions we evaluate the generality of published biomass–climate correlations. We also combine metabolic theory and hydraulic limits to plant growth to first derive and then test predictions for how forest biomass should vary with maximum individual tree biomass and the ecosystem water deficit.Location Temperate forests and dry, moist and wet tropical forests across North, Central and South America.Methods A forest biomass model was derived from allometric functions and power‐law size distributions. Biomass and climate were correlated using extensive forest plot (276 0.1‐ha plots), wood density and climate datasets. Climate variables included mean annual temperature, annual precipitation, their ratio, precipitation of the driest quarter, potential and actual evapotranspiration, and the ecosystem water deficit. The water deficit uniquely summarizes water balance by integrating water inputs from precipitation with water losses due to solar energy.Results Climate generally explained little variation in forest biomass, and mixed support was found for published biomass–climate relationships. Our theory indicated that maximum individual biomass governs forest biomass and is constrained by water deficit. Indeed, forest biomass was tightly coupled to maximum individual biomass and the upper bound of maximum individual biomass declined steeply with water deficit. Water deficit similarly constrained the upper bound of forest biomass, with most forests below the constraint.Main conclusions The results suggest that: (1) biomass–climate models developed at restricted geographic/climatic scales may not hold at broader scales; (2) maximum individual biomass is strongly related to forest biomass, suggesting that process‐based models should focus on maximum individual biomass; (3) the ecosystem water deficit constrains biomass, but realized biomass often falls below the constraint; such that (4) biomass is not strongly limited by climate in most forests so that forest biomass may not predictably respond to changes in mean climate.
    Global Ecology and Biogeography 01/2011; 20(5). · 7.22 Impact Factor
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    ABSTRACT: Ecologists have long sought to understand the mechanisms underlying the assembly and structure of communities. Such understanding is relevant to both basic science and conservation-related issues. The macroecological approach to this problem involves asking scientific questions using a large number of communities in order to elucidate generalities in pattern and process. Such analyses are typically conducted using a substantial amount of data from a particular taxonomic group across a diversity of systems. Large community databases are available for a number of taxa, but no publicly available database exists for mammals. Given the logistical challenges of collecting such data de novo, compiling existing information from the literature provides the best avenue for acquiring the necessary data. Here, we provide a data set that includes species lists for 1000 mammal communities, excluding bats, with species-level abundances available for 940 of these communities. All communities found in the literature that included complete, site-specific sampling data, composed of species lists with or without associated abundances, were included in the data set. Most, but not all, sites are limited to species groups that are sampled using a single technique (e.g., small mammals sampled with Sherman traps). The data set consists of 7977 records from 1000 georeferenced sites encompassing a variety of habitats throughout the world, and it includes data on 660 mammal species with sizes ranging from 2 g to >500 kg.
    Ecology 01/2011; 92:2316. · 5.18 Impact Factor
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    ABSTRACT: Aim  Body size often plays a significant role in community assembly through its impacts on the life history and ecological attributes of species. Insight into the importance of size in structuring communities can be gained by examining the distribution of sizes of individuals [i.e. the individual size distribution (ISD) or size spectrum] in a community. ISDs have been studied extensively in aquatic and tree communities, but have received little attention in terrestrial animal communities. Here, we conduct the first macroecological analysis of ISDs in terrestrial animal communities to determine whether they show broad-scale consistency in shape.Location  North America, north of Mexico.Methods  Using likelihood-based methods and Gaussian mixture modelling, coupled with data from the Breeding Bird Survey and Christmas Bird Count, we determine whether the ISDs for thousands of breeding and wintering North American bird communities are: (1) monotonically decreasing, (2) unimodal or (3) multimodal.Results  We find that avian ISDs are consistently multimodal, with most characterized by more than five modes in both breeding and wintering communities from local to continental scales. In addition, the positions of these modes along the size axis are remarkably consistent.Main conclusions  The striking consistency in the ISD within bird communities, as with tree and aquatic communities, indicates that the ISD is an important and informative characterization of resource utilization within an ecological assemblage. The differences in shape of the ISD among these groups also suggest that differences in body size-related constraints affect interactions within a group and with the environment. Our results confirm that avian assemblages do exhibit structure along the body size axis, and therefore it will be fruitful to explore this pattern in greater detail.
    Global Ecology and Biogeography. 12/2010; 20(1):145 - 153.
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    ABSTRACT: Understanding species richness patterns represents one of the most fundamental problems in ecology. Most research in this area has focused on spatial gradients of species richness, with a smaller area of emphasis dedicated to understanding the temporal dynamics of richness. However, few attempts have been made to understand the linkages between the spatial and temporal patterns related to richness. Here, we argue that spatial and temporal richness patterns and the processes that drive them are inherently linked, and that our understanding of richness will be substantially improved by considering them simultaneously. The species-time-area relationship provides a case in point: successful description of the empirical spatio-temporal pattern led to a rapid development and testing of new theories. Other areas of research on species richness could also benefit from an explicitly spatio-temporal approach, and we suggest future directions for understanding the processes common to these two traditionally isolated fields of research.
    Philosophical Transactions of The Royal Society B Biological Sciences 11/2010; 365(1558):3633-43. · 6.23 Impact Factor
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    ABSTRACT: Arid systems are characterized by spatiotemporal variability in resources and, as such, make ideal systems for examining the role of resource limitation in the long-term dynamics of populations. Using 28 years of data, we examine the long-term relationships of 3 guilds of desert rodent consumers with precipitation and primary productivity in a changing environment. Lags in rodent response to precipitation increased with increasing trophic level over the entire time series, consistent with resource limitation. However, we found that consumer– resource dynamics are complex and variable through time. Precipitation exhibited increasing influence on both primary producers and consumers in this system over time. Experimental evidence suggests that reorganization of community composition, coincident with environmental change, likely explains some of the increasing influence of precipitation. Additional, indirect evidence suggests some role for increasing shrub density and changing precipitation regimes. Results from our long-term study demonstrate that the global phenomena of changing precipitation regimes, increasing frequency of extreme climatic events, and shrub encroachment are likely to have strong, interactive impacts in reorganizing ecological communities, with significant consequences for ecosystem dynamics.
    Journal of Mammalogy 03/2010; 91:787-797. · 2.31 Impact Factor
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    Sarah R Supp, Ethan P White
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    ABSTRACT: Metrics of journal quality (e.g., impact factors) are often used to make important judgments regarding journal quality and importance. It is well known that reviews are more highly cited than original research articles. Therefore, it is not surprising that review journals within a field tend to have the highest scores on measures of journal impact/quality. However, many journals publish both reviews and original research, which may lead to a misleading ranking system because published metrics are a mixture of two potentially independent measures with different means. In addition, journals under pressure to increase their impact factors have suggested that changing publication practices to include more reviews is a legitimate manipulation. However, the proportion of reviews published is not directly related to journal quality. Using 20 top ecology journals, we measure the influence of reviews on impact factor and clearly show that the proportion of reviews published by a journal can explain greater than 75% of the observed variability in measures of journal quality. We suggest that these measures will be more useful if they are reported separately for articles and reviews. In contrast to other articles published on the problems with impact factors, we suggest a clear, simple solution that could be readily instituted with little change to the existing system.
    iee. 01/2010; 3.
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    Ethan P White, Allen H Hurlbert
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    ABSTRACT: It is generally accepted that local species richness at a site reflects the combined influence of local and regional processes. However, most empirical studies evaluate the influence of either local environmental variables or regional enrichment but not both simultaneously. Here we demonstrate the importance of combining these processes to understand continental-scale richness patterns in breeding birds. We show that neither regional enrichment nor the local environment in isolation is sufficient to characterize observed patterns of species richness. Combining both sets of variables into a single model results in improved model fit and the removal of residual spatial autocorrelation. At short timescales, local processes are most important for determining local richness, but as the timescale of analysis increases, regional enrichment becomes increasingly important. These results emphasize the need for increased integration of multiple scales of processes into models of species richness.
    The American Naturalist 12/2009; 175(2):E35-43. · 4.55 Impact Factor
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    ABSTRACT: 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.
    Ecology Letters 07/2009; 12(6):488-501. · 17.95 Impact Factor
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    ABSTRACT: Major shifts in many ecosystem-level properties of tropical forests have been observed, but the processes driving these changes are poorly understood. The forest on Barro Colorado Island (BCI) exhibited a 20% decrease in the number of trees and a 10% increase in average diameter. Using a metabolism-based zero-sum framework, we show that increases in per capita resource use at BCI, caused by increased tree size and increased temperature, compensated for the observed declines in abundance. This trade-off between abundance and average resource use resulted in no net change in the rate resources are fluxed by the forest. Observed changes in the forest are not consistent with other hypotheses, including changes in overall resource availability and existing self-thinning models. The framework successfully predicts interrelated changes in size, abundance and temperature, indicating its utility for understanding changes in the structure and dynamics of ecosystems.
    Ecology Letters 05/2009; 12(6):507-15. · 17.95 Impact Factor
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    ABSTRACT: Theoretical models for allometric relationships between organismal form and function are typically tested by comparing a single predicted relationship with empirical data. Several prominent models, however, predict more than one allometric relationship, and comparisons among alternative models have not taken this into account. Here we evaluate several different scaling models of plant morphology within a hierarchical Bayesian framework that simultaneously fits multiple scaling relationships to three large allometric datasets. The scaling models include: inflexible universal models derived from biophysical assumptions (e.g. elastic similarity or fractal networks), a flexible variation of a fractal network model, and a highly flexible model constrained only by basic algebraic relationships. We demonstrate that variation in intraspecific allometric scaling exponents is inconsistent with the universal models, and that more flexible approaches that allow for biological variability at the species level outperform universal models, even when accounting for relative increases in model complexity.
    Ecology Letters 05/2009; 12(7):641-51. · 17.95 Impact Factor

Publication Stats

967 Citations
315.18 Total Impact Points

Top Journals

Institutions

  • 2013
    • University of North Carolina at Chapel Hill
      • Department of Biology
      Chapel Hill, NC, United States
  • 2006–2013
    • Utah State University
      • Department of Biology
      Logan, Ohio, United States
  • 2007–2011
    • The University of Arizona
      • Department of Ecology and Evolutionary Biology
      Tucson, Arizona, United States
    • McGill University
      • Department of Biology
      Montréal, Quebec, Canada
  • 2003–2005
    • University of New Mexico
      • Department of Biology
      Albuquerque, NM, United States