Ecography · 2016 · 1.3K citations · 117 references
Life SciencesEcologyBiogeographyCommunity EcologySpatial EcologyBiodiversityNiche PartitioningSpecies DiversityData ExplorationData ExtrapolationEcological Niche AssessmentEcological Niche DynamicsModelingNiche ModelingPermutation TestsPhylogenetic Diversity Metrics
The ecospat package aims to provide novel tools and methods for coherent spatial analyses and modeling of species niches and distributions, encouraging comprehensive approaches to species and community distribution modeling. Implemented in R, ecospat offers pre‑modeling tools for niche quantification, phylogenetic diversity, and extrapolation detection; core modeling via ensemble of small models and the SESAM framework; and post‑modeling evaluation using Boyce index, community predictions, and cross‑validation, while also providing functions to complement biomod2.
The aim of the ecospat package is to make available novel tools and methods to support spatial analyses and modeling of species niches and distributions in a coherent workflow. The package is written in the R language (R Development Core Team) and contains several features, unique in their implementation, that are complementary to other existing R packages. Pre‐modeling analyses include species niche quantifications and comparisons between distinct ranges or time periods, measures of phylogenetic diversity, and other data exploration functionalities (e.g. extrapolation detection, ExDet). Core modeling brings together the new approach of ensemble of small models (ESM) and various implementations of the spatially‐explicit modeling of species assemblages (SESAM) framework. Post‐modeling analyses include evaluation of species predictions based on presence‐only data (Boyce index) and of community predictions, phylogenetic diversity and environmentally‐constrained species co‐occurrences analyses. The ecospat package also provides some functions to supplement the ‘biomod2’ package (e.g. data preparation, permutation tests and cross‐validation of model predictive power). With this novel package, we intend to stimulate the use of comprehensive approaches in spatial modelling of species and community distributions.
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