Preprints
Filtering by Subject: Multivariate Analysis
Aligning evidence and action: The Research-to-Decision (RED) Framework to address modern environmental and ecological challenges
Published: 2026-09-28
Subjects: Applied Statistics, Artificial Intelligence and Robotics, Biodiversity, Databases and Information Systems, Ecology and Evolutionary Biology, Environmental Health and Protection, Environmental Indicators and Impact Assessment, Environmental Monitoring, Longitudinal Data Analysis and Time Series, Models and Methods, Multivariate Analysis, Natural Resources and Conservation, Natural Resources Management and Policy, Statistical Methodology, Statistical Models
Ecological and biodiversity crises are intensifying amid rapid advances in sensing, computation, and artificial intelligence (AI). AI offers unprecedented capabilities to understand complex ecological systems, provided outputs are interpretable, applied responsibly, and evaluated by domain experts. When addressing key challenges, science-policy frictions arise through different requirements [...]
One Toolbox, Many Tools: A Practitioner’s Guide to Model-based Ordination for Community Ecology
Published: 2026-02-05
Subjects: Ecology and Evolutionary Biology, Multivariate Analysis, Research Methods in Life Sciences, Statistical Methodology, Statistical Models
This article presents the case for model-based ordination by way of Generalized Linear Latent Variable Models (GLLVMs) as a go-to choice of statistical method for any community ecologist wanting to tackle a range of present-day ecological research questions. Model-based ordination brings tools and capabilities from classic (mixed-effects) regression models to multivariate community analysis, [...]
Generalized graphical mixed models connect ecological theory with widely used statistical models
Published: 2025-06-06
Subjects: Applied Statistics, Aquaculture and Fisheries Life Sciences, Biodiversity, Environmental Sciences, Multivariate Analysis
Ecological dynamics are analyzed across multiple sites, times, and variables. Here, we introduce the family of generalized graphical mixed models (GGMMs) and show that it extends structural equation, generalized additive, and generalized linear mixed models. GGMMs represent ecological systems using a mathematical graph, where each analytic unit (node for each site-time-variable) has a direct [...]
Model-based ordination for phenological studies: from controlling sampling bias to inferring temporal associations
Published: 2025-03-17
Subjects: Biostatistics, Ecology and Evolutionary Biology, Integrative Biology, Longitudinal Data Analysis and Time Series, Multivariate Analysis, Statistical Methodology
Willig et al. (Methods in Ecology and Evolution, 15, 868--885, 2024) cautioned that unequal sampling effort and pseudoreplication can bias the characterisation of species phenology using circular statistics. Borrowing concepts from rarefaction, they proposed bootstrapping to control for time-varying marginal totals that arise from unequal sampling effort over time. This study extends their [...]
Beyond single-species models: leveraging multispecies forecasts to navigate the dynamics of ecological predictability
Published: 2023-03-13
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 [...]
Estimating complex ecological variables at high resolution in heterogeneous terrain using multivariate matching algorithms
Published: 2021-04-16
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 [...]