HAL : hal-00264207, version 1

DOI : 10.1111/j.1461-0248.2007.01142.x

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Ecology Letters 11, 3 (2008) 235-244

Prediction uncertainty of environmental change effects on temperate European biodiversity.

Carsten F. Dormann (  Auteur correspondant ) 1, Oliver Schweiger 1, Paul Arens 2, Isabel Augenstein 1, Stéphanie Aviron 3, 4, Debra Bailey 3, Jacques Baudry 5, 6, Regula Billeter 7, Rob Bugter 8, Roman Bukacek 9, Francoise Burel 4, Martin Cerny 10, Rafael De Cock 11, Gert De Blust 12, Riccardo Defilippi 3, Tim Diekotter 7, Jolanda Dirksen 8, Walter Durka 1, Peter J. Edwards 13, Mark Frenzel 1, Roman Hamersky 9, Frédéric Hendrickx 14, 15, Felix Herzog 3, Stefan Klotz 1, 16, 17, 18, 19, Beno Koolstra 8, Angela Lausch 1, Didier Le Coeur 20, Jan Liira 21, Jean-Pierre Maelfait 14, 22, Paul Opdam 8, Martina Roubalova 10, Agnès Schermann-Legionnet 4, Nicolas Schermann 5, Torsten Schmidt 1, Marinus J.M. Smulders 1, Marjan Speelmans 14, P. Simova 9, Jana Verboom 8, Walter Van Wingerden 8, Marlin Zobel 21

GREENVEINS (projet europeen) Collaboration(s)

(2008)

Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections.

1 :	UFZ Centre for Environmental Research Leipzig-Halle (UFZ)
	UFZ
2 :	Plant Research International
	wageningen University
3 :	Agroscope FAL Reckenholz (AGROSCOPE)
	ETH
4 :	Ecosystèmes, biodiversité, évolution (ECOBIO)
	CNRS : UMR6553 – Université de Rennes 1 – INEE – Observatoire des Sciences de l'Univers de Rennes
5 :	INRA SAD Armorique
	Institut national de la recherche agronomique (INRA)
6 :	Centre Armoricain de Recherche en Environnement (CARE)
	CNRS : FR2116 – Institut national de la recherche agronomique (INRA) – Université de Rennes 1 – Université de Rennes II - Haute Bretagne – Ecole Nationale Supérieure Agronomique de Rennes
7 :	Swiss Federal Institute of Technology (ETH)
	Swiss Federal Institute of Technology
8 :	Alterra Green World Research (AGWR)
	wageningen University
9 :	Nature Conservation Authority (NCA)
	Nature Conservation Authority
10 :	Institute of Forest Ecosystem Research (IFER)
	Institute of Foret Ecosystem Research
11 :	INBO - Research Institute for Nature and Forest
	Research Institute for Nature and Forest
12 :	INBO
	Research Institute for Nature and Forest
13 :	Institute of Integrative Biology (ETH)
	ETH Zurich
14 :	Terrestrial Ecology Unit (TEREC) (TEREC)
	State University of Ghent
15 :	INBO - Research Institute for Nature and Forest
	State University of Ghent
16 :	Institut de minéralogie et de physique des milieux condensés (IMPMC)
	CNRS : UMR7590 – IPG PARIS – Université Pierre et Marie Curie [UPMC] - Paris VI – Université Paris VII - Paris Diderot
17 :	Paléoenvironnement et paléobiosphère (PP)
	CNRS : UMR5125 – INSU – Université Claude Bernard - Lyon I
18 :	Institut für Geowissenschaften,
	Universität Tübingen
19 :	Institute of Geosciences, University of Tübingen
	University of Tübingen
20 :	INRA-SAD Armorique
	Institut national de la recherche agronomique (INRA)
21 :	Institute of Botany and Ecology
	University of Tartu
22 :	Research Institute for Nature and Forest (INBO)
	State University of Ghent

Domaine

:

Planète et Univers/Interfaces continentales, environnement Sciences de l'environnement/Milieux et Changements globaux Sciences de l'environnement/Biodiversité et Ecologie

Mots Clés : Biodiversity – climate change – environmental change – multimodel inference – projection – species richness – uncertainty analysis.

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Contributeur : Valerie Briand <>

Soumis le : Vendredi 14 Mars 2008, 15:10:00

Dernière modification le : Vendredi 14 Mars 2008, 15:10:00