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Making better biogeographical predictions of species’ distributions
Author(s) -
GUISAN ANTOINE,
LEHMANN ANTHONY,
FERRIER SIMON,
AUSTIN MIKE,
OVERTON JACOB MC. C.,
ASPINALL RICHARD,
HASTIE TREVOR
Publication year - 2006
Publication title -
journal of applied ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.503
H-Index - 181
eISSN - 1365-2664
pISSN - 0021-8901
DOI - 10.1111/j.1365-2664.2006.01164.x
Subject(s) - context (archaeology) , biological dispersal , ecology , biodiversity , range (aeronautics) , ecosystem , environmental resource management , species distribution , ecological network , documentation , computer science , geography , environmental science , habitat , biology , population , materials science , demography , archaeology , sociology , composite material , programming language
Summary1 Biogeographical models of species’ distributions are essential tools for assessing impacts of changing environmental conditions on natural communities and ecosystems. Practitioners need more reliable predictions to integrate into conservation planning (e.g. reserve design and management). 2 Most models still largely ignore or inappropriately take into account important features of species’ distributions, such as spatial autocorrelation, dispersal and migration, biotic and environmental interactions. Whether distributions of natural communities or ecosystems are better modelled by assembling individual species’ predictions in a bottom‐up approach or modelled as collective entities is another important issue. An international workshop was organized to address these issues. 3 We discuss more specifically six issues in a methodological framework for generalized regression: (i) links with ecological theory; (ii) optimal use of existing data and artificially generated data; (iii) incorporating spatial context; (iv) integrating ecological and environmental interactions; (v) assessing prediction errors and uncertainties; and (vi) predicting distributions of communities or collective properties of biodiversity. 4 Synthesis and applications . Better predictions of the effects of impacts on biological communities and ecosystems can emerge only from more robust species’ distribution models and better documentation of the uncertainty associated with these models. An improved understanding of causes of species’ distributions, especially at their range limits, as well as of ecological assembly rules and ecosystem functioning, is necessary if further progress is to be made. A better collaborative effort between theoretical and functional ecologists, ecological modellers and statisticians is required to reach these goals.