De'ath, Glenn (2002) Multivariate regression trees: a new technique for modeling species-environment relationships. Ecology, 83 (4). pp. 1105-1117.

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Abstract

Multivariate regression trees (MRT) are a new statistical technique that can be used to explore, describe, and predict relationships between multispecies data and environmental characteristics. MRT forms clusters of sites by repeated splitting of the data, with each split defined by a simple rule based on environmental values. The splits are chosen to minimize the dissimilarity of sites within clusters. The measure of species dissimilarity can be selected by the user, and hence MRT can be used to relate any aspect of species composition to environmental data. The clusters and their dependence on the environmental data are represented graphically by a tree. Each cluster also represents a species assemblage, and its environmental values define its associated habitat. MRT can be used to analyze complex ecological data that may include imbalance, missing values, nonlinear relationships between variables, and high-order interactions. They can also predict species composition at sites for which only environmental data are available. MRT is compared with redundancy analysis and canonical correspondence analysis using simulated data and a field data set.

Item ID:	27267
Item Type:	Article (Research - C1)
ISSN:	1939-9170
Date Deposited:	29 May 2013 05:17
FoR Codes:	07 AGRICULTURAL AND VETERINARY SCIENCES > 0799 Other Agricultural and Veterinary Sciences > 079999 Agricultural and Veterinary Sciences not elsewhere classified @ 34% 07 AGRICULTURAL AND VETERINARY SCIENCES > 0705 Forestry Sciences > 070504 Forestry Management and Environment @ 33% 07 AGRICULTURAL AND VETERINARY SCIENCES > 0705 Forestry Sciences > 070501 Agroforestry @ 33%
SEO Codes:	96 ENVIRONMENT > 9608 Flora, Fauna and Biodiversity > 960806 Forest and Woodlands Flora, Fauna and Biodiversity @ 50% 96 ENVIRONMENT > 9613 Remnant Vegetation and Protected Conservation Areas > 961306 Remnant Vegetation and Protected Conservation Areas in Forest and Woodlands Environments @ 50%
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