Table 1.

Nine categories of methods defined in this review that were used to build species distribution models

Modeling method	Definition (example)
CTA	Classification tree analysis methods, including classification and regression trees, boosted regression trees, and random forest
Ensemble	A weighted or unweighted average, or combination, of models built with different methods
Envelope	Models that identify the boundaries of species’ ecological tolerance directly from data, without the use of machine learning (e.g., BIOCLIM, CLIMEX, CliMond, DOMAIN)
GARP	Genetic algorithm for rule-set production, generates mathematical rules for estimating species presence
MaxEnt	Maximum entropy, for expressing probability distributions
Mechanistic	Process-based models, often using parameters of physiological limits to estimate distributions (e.g., species thermal limits)
Mixed	Uses two or more methods to estimate species distributions, but does not average or combine output into a model ensemble
Regression	Non-machine learning regression models (e.g., logistic regression, generalized linear models, generalized additive models, etc.)
Other	Less commonly used methods that did not fit into another category (e.g., ecological niche factor analysis, environmental suitability thresholds, logic thresholds)