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iForest - Biogeosciences and Forestry

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Landscape genetics of fragmented forests: anticipating climate change by facilitating migration

MJM Smulders (1)   , MMP Cobben (1), P Arens (1), J Verboom (2)

iForest - Biogeosciences and Forestry, Volume 2, Issue 4, Pages 128-132 (2009)
doi: https://doi.org/10.3832/ifor0505-002
Published: Jul 30, 2009 - Copyright © 2009 SISEF

Review Papers

Collection/Special Issue: EFI 2008 Annual Conference Week - Orvieto (Italy)
Adaptation of Forest Landscape to Environmental Changes
Guest Editors: Giuseppe Scarascia Mugnozza (CRA - Rome, Italy)


Habitat fragmentation is a threat to the survival of species and causes population decline, as isolated populations are more susceptible to demographic and genetic stochasticity. This can be compensated for by sufficient spatial connectivity between habitat patches to allow dispersal of individuals among populations. In that case such a network of populations may effectively form a metapopulation. In this paper we discuss some aspects of metapopulation theory, notably with respect to maintaining genetic diversity in fragmented forest patches. In addition we will discuss recent studies that explore ways for forest management to anticipate and mitigate the expected climate change, in relation to range shifts and colonisation opportunities.

  Keywords


Genetic diversity, Management, Connectivity, Habitat fragmentation

Authors’ address

(1)
MJM Smulders
MMP Cobben
P Arens
Plant Research International, Wageningen UR, Wageningen (The Netherlands)
(2)
J Verboom
Alterra, Wageningen UR, Wageningen (The Netherlands)

Corresponding author

 
MJM Smulders
rene.smulders@wur.nl

Citation

Smulders MJM, Cobben MMP, Arens P, Verboom J (2009). Landscape genetics of fragmented forests: anticipating climate change by facilitating migration. iForest 2: 128-132. - doi: 10.3832/ifor0505-002

Academic Editor

Marco Borghetti

Paper history

Received: Apr 08, 2009
Accepted: Apr 09, 2009

First online: Jul 30, 2009
Publication Date: Jul 30, 2009
Publication Time: 3.73 months

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