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An article on preprints in biology. It was developed on github (https://github.com/PhDP/article_preprint) and appeared in PLOS Biology (http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001563): Desjardins-Proulx P, White EP, Adamson JJ, Ram K, Poisot T, et al. (2013) The Case for Open Preprints in Biology. PLoS Biol 11(5): e1001563. doi:10.1371/journal.pbio.1001563

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.

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.

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.

Background 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. Methodology/Principal Findings 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. Conclusions/Significance 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.

Metrics of journal quality (e.g., impact factors) are often used to make important judgements 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 more 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.

Major shifts in many ecosystem-level properties of tropical forests have been observed, but the processes driving these changes are poorly understood. Over the past two decades, the forest on Barro Colorado Island, Panama (BCI) exhibited a 20% decrease in the number of trees and a 10% increase in average tree diameter. Here we show that these changes are consistent with a zero-sum constraint operating in this forest. Zero-sum constraints result when the total resource use of an ecosystem is limited by available resources. This causes increases in resource use by some groups of organisms to be compensated for by decreases in other groups. 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 by an individual resulted in no net change in the rate resources are fluxed by the forest. The observed changes in the forest are not consistent with other hypotheses, such as changes in overall resource availability or existing self-thinning models. The framework successfully predicts interrelated changes in size, abundance, and temperature, indicating the utility of metabolic zero-sum dynamics for understanding changes in the structure and dynamics of ecosystems.

Recent models of community assembly, structure, and dynamics have incorporated, to varying degrees, three mechanistic processes: resource limitation and interspecific competition, niche requirements of species, and exchanges between a local community and a regional species pool. Synthesizing 30 years of data from an intensively studied desert rodent community, we show that all of these processes, separately and in combination, have influenced the structural organization of this community and affected its dynamical response to both natural environmental changes and experimental perturbations. In addition, our analyses suggest that zero-sum constraints, niche differences, and metacommunity processes are inextricably linked in the ways that they affect the structure and dynamics of this system. Explicit consideration of the interaction of these processes should yield a deeper understanding of the assembly and dynamics of other ecological communities. This synthesis highlights the role that long-term data, especially when coupled with experimental manipulations, can play in assessing the fundamental processes that govern the structure and function of ecological communities.

The resemblance between time and space, in its simplest form, may be seen by driving a stake into the open water of a lake and then taking a transect toward the shore. We pass first through planktonic vegetation, then perhaps water lilies, then marsh, then grassland, then a succession of forest stages to climax forest. But we can pass through the same succession in the same order without moving at all. We may just sit by the stake for a few years or centuries and the seral stages will come to us one after the other as the lake fills in or drains. Frank W. Preston (1960) Introduction Understanding observed patterns of species diversity is a major focus of ecological research (e.g. Hutchinson, 1959; Brown, 1981; Gaston, 2000). However, it is increasingly well established that observed patterns and correlates of species richness are strongly dependent on the spatial scale of analysis (e.g. Levin, 1992; Wright, Currie & Maurer, 1993; Mittelbach et al ., 2001; Rahbek & Graves, 2001). This dependence results from differences in how species richness changes with the area sampled (Scheiner et al ., 2000; Chase & Leibold, 2002; Lyons & Willig, 2002). There are literally hundreds of studies on the effects of spatial scale on species richness (the species–area relationship), and numerous additional studies on spatial species turnover (e.g. Connor & McCoy, 1979; Rosenzweig, 1995; Koleff, Gaston & Lennon, 2003).

Resource limitation represents an important constraint on ecological communities, which restricts the total abundance, biomass, and community energy flux a given community can support. However, the exact relationship among these three measures of biological activity remains unclear. Here we use a simple framework that links abundance and biomass with an energetic constraint. Under constant energetic availability, it is expected that changes in abundance and biomass can result from shifts in the distribution of individual masses. We test these predictions using long-term data from a desert rodent community. Total energy use for the community has not changed directionally for 25 years, but species composition has. As a result, the average body size has decreased by almost 50%, and average abundance has doubled. These results lend support to the idea of resource limitation on desert rodent communities and demonstrate that systems are able to maintain community energy flux in the face of environmental change, through changes in composition and structure.

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. The complete data sets corresponding to abstracts published in the Data Papers section of the journal are published electronically in Ecological Archives at 〈http://esapubs.org/archive〉. (The accession number for each Data Paper is given directly beneath the title.)

Nee et al . (Reports, 19 August 2005, p. 1236) used a null model to argue that life history invariants are illusions. We show that their results are largely inconsequential for life history theory because the authors confound two definitions of invariance, and rigorous analysis of their null model demonstrates that it does not match observed data.