Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

ABSTRACT:

Aim

Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods.

Location

Eastern North America (as an example).

Methods

Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulat

SUBMITTER: Talluto MV 

PROVIDER: S-EPMC4975518 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature