Bounding species distribution models
Author(s) -
Thomas J. Stohlgren,
Catherine S. Jarnevich,
Wayne E. Esaias,
Jeffrey T. Morisette
Publication year - 2011
Publication title -
current zoology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.971
H-Index - 38
eISSN - 2058-5888
pISSN - 1674-5507
DOI - 10.1093/czoolo/57.5.642
Subject(s) - bounding overwatch , principle of maximum entropy , species distribution , computer science , bounded function , habitat , environmental niche modelling , ecology , mathematics , artificial intelligence , biology , ecological niche , mathematical analysis
Species distribution models are increasing in popularity for mapping suitable habitat for species of management con- cern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for "clamping" model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding ex- trapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suit- able habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used (Current Zoology 57 (5): 642-647, 2011).
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom