A maximum entropy approach to species distribution modeling

Abstract

We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, specifically, sequential-update algorithms that can handle a very large number of features. We describe experiments comparing maxent with a standard distribution-modeling tool, called GARP, on a dataset containing observation data for North American breeding birds. We also study how well maxent performs as a function of the number of training examples and training time, analyze the use of regularization to avoid overfitting when the number of examples is small, and explore the interpretability of models constructed using maxent.

DOI: 10.1145/1015330.1015412

Extracted Key Phrases

8 Figures and Tables

Showing 1-4 of 4 references

Quantitative methods for modeling species habitat: Comparative performance and an application to Australian plants Quantitative methods for conservation biology

  • J Elith
  • 2002
Highly Influential
3 Excerpts

Predicting species' geographic distributions based on ecological niche modeling. The Condor

  • A T Peterson
  • 2001
Highly Influential
3 Excerpts
Showing 1-10 of 248 extracted citations
0204060'04'05'06'07'08'09'10'11'12'13'14'15'16'17
Citations per Year

398 Citations

Semantic Scholar estimates that this publication has received between 325 and 491 citations based on the available data.

See our FAQ for additional information.