Decomposition of the maximum entropy niche function – A step beyond modelling species distribution. (October 2015)

• Record Type: Journal Article
• Authors: Cunze, Sarah; Tackenberg, Oliver
• Is Part Of: Environmental modelling & software. Volume 72(2015:Oct.)
• Page Start: 250
• Page End: 260
• Publication Date: 2015-10
• Subjects: Ecological niche modelling -- Eigenvalue decomposition -- Niche function -- Niche visualization -- Specialisation -- Species distribution modelling; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.05.004
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Some algorithms used to model species' distributions are often only considered as black boxes; coefficients of the underlying niche functions are often not interpreted ecologically. Here, we focus on the maximum entropy approach that is commonly and successfully applied in order to model species' distribution. By means of an eigenanalysis, we decompose the niche function into independent factors that can be interpreted separately. In addition, we derive parameters that can be used to characterize the species' niche, especially considering the steepness of the modelled niche function and the sensitivity of the considered species against changes in certain environmental conditions. On the example of three well-studied Taiga forest tree species we illustrate the capability and scope of our approach. Given the easy availability of environmental data and species occurrences, the presented approach seems to be a feasible way to gain deeper insights into the factors that are related to species' distributions. Highlights: We decompose a special Maxent niche model into independent (multiplicative) factors. These factors allow interpretation, dimension reduction, and visualization. The same model suits estimation of the ecological niche and of species distribution.