Species distribution models (SDMs) are widely used in ecology. In theory, SDMs capture (at
least part of) species' ecological niches and can be used to make inferences about the …

Much biodiversity data is collected worldwide, but it remains challenging to assemble the
scattered knowledge for assessing biodiversity status and trends. The concept of E ssential …

Checking that models adequately represent data is an essential component of applied
statistical inference. Ecologists increasingly use hierarchical Bayesian statistical models in …

The contributions of species to ecosystem functions or services depend not only on their
presence but also on their local abundance. Progress in predictive spatial modelling has …

Quasi‐Poisson and negative binomial regression models have equal numbers of
parameters, and either could be used for overdispersed count data. While they often give …

It is thought that species abundance is correlated with environmental suitability and that
environmental variables, scale, and type of model fitting can confound this relationship. We …

Habitat loss and degradation, driven largely by agricultural expansion and intensification,
present the greatest immediate threat to biodiversity. Tropical forests harbour among the …

Microbiome research and microbiome data analysis are one of the fast-growing areas in
biomedical and public health research. It is evidenced and catalyzed by publications in …

This document is an introduction to species distribution modeling with R. Species
distribution modeling (SDM) is also known under other names including envelope-modeling …

Owing to the huge number of species observations that can be collected by non-
professional scientists,“citizen science” has great potential to contribute to scientific …