Open AccessUsing generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment
Author(s) -
Ferrier Simon,
Manion Glenn,
Elith Jane,
Richardson Karen
Publication year - 2007
Publication title -
diversity and distributions
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.918
H-Index - 118
eISSN - 1472-4642
pISSN - 1366-9516
DOI - 10.1111/j.1472-4642.2007.00341.x
Subject(s) - beta diversity , biological dispersal , biodiversity , ecology , range (aeronautics) , spatial ecology , geography , spatial analysis , environmental resource management , environmental science , biology , population , sociology , materials science , demography , remote sensing , composite material
Generalized dissimilarity modelling (GDM) is a statistical technique for analysing and predicting spatial patterns of turnover in community composition (beta diversity) across large regions. The approach is an extension of matrix regression, designed specifically to accommodate two types of nonlinearity commonly encountered in large‐scaled ecological data sets: (1) the curvilinear relationship between increasing ecological distance, and observed compositional dissimilarity, between sites; and (2) the variation in the rate of compositional turnover at different positions along environmental gradients. GDM can be further adapted to accommodate special types of biological and environmental data including, for example, information on phylogenetic relationships between species and information on barriers to dispersal between geographical locations. The approach can be applied to a wide range of assessment activities including visualization of spatial patterns in community composition, constrained environmental classification, distributional modelling of species or community types, survey gap analysis, conservation assessment, and climate‐change impact assessment.