Preprints
Filtering by Subject: Statistics and Probability
A pluralistic framework for measuring and stratifying heterogeneity in meta-analyses
Published: 2023-11-24
Subjects: Ecology and Evolutionary Biology, Statistics and Probability
1. Measuring heterogeneity, or inconsistency, among effect sizes is a crucial step for interpreting the meta-analytic evidence across diverse taxonomic groups and spatiotemporal contexts. However, ecologists and evolutionary biologists often interpret mean population effects (i.e., meta-analytic mean effect size) as consistent, either explicitly or implicitly, without proper [...]
Robust point and variance estimation for ecological and evolutionary meta-analyses with selective reporting and dependent effect sizes
Published: 2023-10-04
Subjects: Life Sciences, Medicine and Health Sciences, Statistics and Probability
Meta-analysis produces a quantitative synthesis of evidence-based knowledge, shaping not only research trends but also policy and practices in ecology and evolution. However, two statistical issues, selective reporting and statistical dependence, can severally distort meta-analytic evidence. Here, we propose a two-step procedure to tackle these challenges concurrently and re-analyse 448 [...]
Beyond single-species models: leveraging multispecies forecasts to navigate the dynamics of ecological predictability
Published: 2023-03-14
Subjects: Desert Ecology, Ecology and Evolutionary Biology, Life Sciences, Multivariate Analysis, Population Biology, Statistical Methodology, Statistical Models, Statistics and Probability
Forecasting the responses of natural populations to environmental change is a key priority in the management of ecological systems. This is challenging because the dynamics of multispecies ecological communities are influenced by many factors. Populations can exhibit complex, nonlinear responses to environmental change, often over multiple temporal lags. In addition, biotic interactions, and [...]
Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology
Published: 2022-09-12
Subjects: Biology, Ecology and Evolutionary Biology, Environmental Sciences, Life Sciences, Physical Sciences and Mathematics, Statistics and Probability
Collaborative assessments of direct replicability of empirical studies in the medical and social sciences have exposed alarmingly low rates of replicability, a phenomenon dubbed the ‘replication crisis’. Poor replicability has spurred cultural changes targeted at improving reliability in these disciplines. Given the absence of equivalent replication projects in ecology and evolutionary biology, [...]
Decline effects are rare in ecology: Comment
Published: 2022-06-06
Subjects: Ecology and Evolutionary Biology, Life Sciences, Physical Sciences and Mathematics, Statistical Methodology, Statistical Models, Statistics and Probability
Recently, Costello and Fox (2022) tested, with a large dataset, the hypothesis of whether there is a widespread decline effect in the discipline of ecology. In other words, the magnitude of the reported ecological effect sizes declines over time (Leimu and Koricheva 2004). Contrary to early results from much smaller datasets (Jennions and Møller 2002, Barto and Rillig 2012), Costello and Fox [...]
Multi-population analysis reveals spatial consistency in drivers of population dynamics of a declining migratory bird
Published: 2022-04-22
Subjects: Biodiversity, Biology, Biostatistics, Ecology and Evolutionary Biology, Life Sciences, Longitudinal Data Analysis and Time Series, Physical Sciences and Mathematics, Population Biology, Research Methods in Life Sciences, Statistical Methodology, Statistical Models, Statistics and Probability, Survival Analysis, Terrestrial and Aquatic Ecology
Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets. We capitalized [...]
Interpolation of temporal biodiversity change, loss, and gain across scales: a machine learning approach
Published: 2022-03-16
Subjects: Applied Statistics, Biodiversity, Ecology and Evolutionary Biology, Life Sciences, Physical Sciences and Mathematics, Statistics and Probability
1. Estimates of temporal change of biodiversity, and its components loss and gain, are needed at local and geographical scales. However, we lack them because of data in-completeness, heterogeneity, and lack of temporal replication. Hence, we need a tool to integrate heterogeneous data and to account for their incompleteness. 2. We introduce spatiotemporal machine learning interpolation that can [...]
Estimating complex ecological variables at high resolution in heterogeneous terrain using multivariate matching algorithms
Published: 2021-04-17
Subjects: Ecology and Evolutionary Biology, Life Sciences, Multivariate Analysis, Physical Sciences and Mathematics, Research Methods in Life Sciences, Statistics and Probability
1. Simulation models are valuable tools for estimating ecosystem structure and function under various climatic and environmental conditions and disturbance regimes, and are particularly relevant for investigating the potential impacts of climate change on ecosystems. However, because computational requirements can restrict the number of feasible simulations, they are often run at coarse scales or [...]
BetaBayes - A Bayesian approach for comparing ecological communities
Published: 2021-04-09
Subjects: Biodiversity, Biology, Ecology and Evolutionary Biology, Life Sciences, Physical Sciences and Mathematics, Statistics and Probability
Ecological communities change due to both natural and human factors. Distinguishing between the two is critical to ecology and conservation science. One of the most common approaches for modelling species composition changes is calculating Beta diversity indices and then relating index changes to covariates changes. The main difficulty with these analyses is that Beta diversity indices are paired [...]
ausplotsR: An R package for rapid extraction and analysis of vegetation and soil data collected by Australia’s Terrestrial Ecosystem Research Network
Published: 2020-12-15
Subjects: Biostatistics, Botany, Life Sciences, Other Plant Sciences, Physical Sciences and Mathematics, Plant Biology, Plant Sciences, Statistics and Probability
The Terrestrial Ecosystem Research Network (TERN), Australia’s national land ecosystem monitoring program, measures critical environmental attributes from local to continental scale and generates quality data for research and land management. Since 2011, TERN has performed standardised field surveys and sampling across a national plot network. At each plot, TERN records vegetation structure, [...]
Phylogenetic multilevel meta-analysis: A simulation study on the importance of modeling the phylogeny
Published: 2020-11-23
Subjects: Ecology and Evolutionary Biology, Life Sciences, Physical Sciences and Mathematics, Statistical Models, Statistics and Probability
1. Meta-analyses in ecology and evolution require special attention due to certain study characteristics in these fields. First, the primary articles in these fields usually report results that are observed from studies conducted with different species, and the phylogeny among the species violates the independence assumption. Second, articles frequently allow the computation of multiple effect [...]
Motif: an open-source R tool for pattern-based spatial analysis
Published: 2020-10-18
Subjects: Categorical Data Analysis, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Life Sciences, Physical Sciences and Mathematics, Statistics and Probability, Terrestrial and Aquatic Ecology
*Context* Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns. *Objectives* We developed an R package **motif** as a set of open-source tools for pattern-based spatial analysis. *Methods* This package provides [...]