Predictive models are central to many scientific disciplines and vital for informing
management in a rapidly changing world. However, limited understanding of the accuracy …

Ecological data often show temporal, spatial, hierarchical (random effects), or phylogenetic
structure. Modern statistical approaches are increasingly accounting for such dependencies …

Species distribution models (SDMs) constitute the most common class of models across
ecology, evolution and conservation. The advent of ready‐to‐use software packages and …

Abstract Machine learning algorithms have become very popular for spatial mapping of the
environment due to their ability to fit nonlinear and complex relationships. However, this …

Reporting specific modelling methods and metadata is essential to the reproducibility of
ecological studies, yet guidelines rarely exist regarding what information should be noted …

Species distribution models (SDMs) are widely used to explain and predict species ranges
and environmental niches. They are most commonly constructed by inferring species' …

Background Changes in Earth's climate over time can be measured in many ways. The
different metrics available represent alternative dimensions of climate change, each with …

Correlational models of species' ecological niches are commonly used to transfer model
rules onto other sets of conditions to evaluate species' distributional potential. As with any …

Understanding and predicting the ecological consequences of different management
alternatives is becoming increasingly important to support environmental management …

Modeling the distributions of species, especially of invasive species in non‐native ranges,
involves multiple challenges. Here, we developed some novel approaches to species …