Automatic variable selection in ecological niche modeling: A case study using Cassin's Sparrow (Peucaea cassinii).

ABSTRACT: MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max's Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a

SUBMITTER: Schnase JL 

PROVIDER: S-EPMC8782318 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature