Premium
DOES THE SELF‐SIMILAR SPECIES DISTRIBUTION MODEL LEAD TO UNREALISTIC PREDICTIONS
Author(s) -
Hui Cang,
McGeoch Melodie A.
Publication year - 2008
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/07-1451.1
Subject(s) - occupancy , similarity (geometry) , ecology , scale (ratio) , probability distribution , self similarity , mathematics , computer science , statistics , geography , biology , artificial intelligence , cartography , geometry , image (mathematics)
J. Harte et al. demonstrated that the power law form of the species–area relationship may be derived from a bisected, self‐similar landscape and a community‐level probability rule. Harte's self‐similarity model has been widely applied in modeling species distributions. However, R. D. Maddux showed that this self‐similarity model generates biologically unrealistic predictions. We resolve the Harte–Maddux debate by demonstrating that the problems identified by Maddux result from an assumption that the probability of occurrence of a species at one scale is independent of its probability of occurrence at the next. We refer to this as a “non‐heritage assumption.” By altering this assumption to one in which each species in the community has an occupancy status that is partially inherited across scales (a scale‐heritage assumption), the predictions of the self‐similarity model are neither mathematically inconsistent nor biologically unrealistic. Harte's self‐similarity model remains an important framework for modeling species distributions. Our results illustrate the importance of considering patterns of species co‐occurrence, and the way in which species occupancy patterns change with scale, when modeling species distributions.