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14 - The impact of climate change on the origin and future of East African rainforest trees

from Section 3 - Biogeography, migration and ecological niche modelling

Published online by Cambridge University Press:  16 May 2011

L. W. Chatrou
Affiliation:
Wageningen University, Netherlands
J. J. Wieringa
Affiliation:
Wageningen University, Netherlands
T. L. P. Couvreur
Affiliation:
Institut de Recherche pour le Développement, Montpellier, France
Trevor R. Hodkinson
Affiliation:
Trinity College, Dublin
Michael B. Jones
Affiliation:
Trinity College, Dublin
Stephen Waldren
Affiliation:
Trinity College, Dublin
John A. N. Parnell
Affiliation:
Trinity College, Dublin
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Summary

Abstract

East African rainforests are characterised by a high percentage of endemic species. The occurrence of Annonaceae in the area conforms to this pattern. We review the historical biogeography of species of this family endemic to East Africa, in the light of episodes of climate change during the Tertiary. Based on herbarium specimen data, and using a phyloclimatic modelling approach, we identify the environmental variables that are associated with the origin of East African endemics of the genus Monodora. We discuss the possible responses of Monodora to future trends, based on inferences from past evolutionary changes linked to climatic transitions.

Introduction

Ecological changes due to the process of global warming and climate change are increasingly documented (Hannah et al., 2005; Lovett et al., 2005a; Lewis, 2006). Species distributions have shifted, and changes in ethology and phenology have caused the disruption of synchrony in plant–insect and predator–prey interactions (Parmesan, 2006). One of the tools applied to study the effect of climate change on organisms is species distribution modelling (Heikkinen et al., 2006; Beaumont et al., 2007). These models, also named bioclimatic envelopes or bioclimatic niches (see Kearney, 2006, for a discussion of species distribution modelling and terms involved), reflect the potential distribution of a species that is predicted on the basis of the relationships between species absence/presence, or presence-only, data, and environmental parameters of areas in which these species occur.

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Publisher: Cambridge University Press
Print publication year: 2011

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