The R language provides most applications (packages) currently available for ecological
niche modelling. In the last few years, these packages have increased substantially. There …

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 …

Ecological niche models are widely used in ecology and biogeography. Maxent is one of the
most frequently used niche modeling tools, and many studies have aimed to optimize its …

Species distribution modeling (SDM) is a booming area of research that has had an
exponential increase in use and development in recent years. We performed a search of …

Aim Forecasting changes in species distribution under future scenarios is one of the most
prolific areas of application for species distribution models (SDMs). However, no consensus …

The random forest (RF) algorithm is an ensemble of classification or regression trees and is
widely used, including for species distribution modelling (SDM). Many researchers use …

Balancing model complexity is a key challenge of modern computational ecology,
particularly so since the spread of machine learning algorithms. Species distribution models …

Species distribution models are used to study biogeographic patterns and guide decision‐
making. The variable quality of these models makes it critical to assess whether a model's …

The discriminating capacity (ie ability to correctly classify presences and absences) of
species distribution models (SDM s) is commonly evaluated with metrics such as the area …

Aim Accounting for sampling bias is the greatest challenge facing presence‐only and
presence‐background species distribution models; no matter what type of model is chosen …