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  Using dynamic vegetation models to simulate plant range shifts

Snell, R. S., Huth, A., Nabel, J. E. M. S., Bocedi, G., Travis, J. M. J., Gravel, D., et al. (2014). Using dynamic vegetation models to simulate plant range shifts. Ecography, 37, 1184-1197. doi:10.1111/ecog.00580.

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 Creators:
Snell, R. S.1, Author
Huth, A.1, Author
Nabel, Julia E. M. S.1, Author           
Bocedi, G.1, Author
Travis, J. M. J.1, Author
Gravel, D.1, Author
Bugmann, H.1, Author
Gutierrez, A. G.1, Author
Hickler, T.1, Author
Higgins, S. I.1, Author
Reineking, B.1, Author
Scherstjanoi, M.1, Author
Zurbriggen, N.1, Author
Lischke, H.1, Author
Affiliations:
1external, ou_persistent22              

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Free keywords: DISTANCE SEED DISPERSAL; TREE SPECIES MIGRATION; CLIMATE-CHANGE; TEMPERATURE-DEPENDENCE; COMMUNITY COMPOSITION; MECHANISTIC MODELS; FUTURE CHALLENGES; FOREST SUCCESSION; MOUNTAIN PLANTS; RAIN-FOREST
 Abstract: Dynamic vegetation models (DVMs) follow a process-based approach to simulate plant population demography, and have been used to address questions about disturbances, plant succession, community composition, and provisioning of ecosystem services under climate change scenarios. Despite their potential, they have seldom been used for studying species range dynamics explicitly. In this perspective paper, we make the case that DVMs should be used to this end and can improve our understanding of the factors that influence species range expansions and contractions. We review the benefits of using process-based, dynamic models, emphasizing how DVMs can be applied specifically to questions about species range dynamics. Subsequently, we provide a critical evaluation of some of the limitations and trade-offs associated with DVMs, and we use those to guide our discussions about future model development. This includes a discussion on which processes are lacking, specifically a mechanistic representation of dispersal, inclusion of the seedling stage, trait variability, and a dynamic representation of reproduction. We also discuss upscaling techniques that offer promising solutions for being able to run these models efficiently over large spatial extents. Our aim is to provide directions for future research efforts and to illustrate the value of the DVM approach.

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Language(s): eng - English
 Dates: 2014
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000345849400004
DOI: 10.1111/ecog.00580
 Degree: -

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Title: Ecography
Source Genre: Journal
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Pages: - Volume / Issue: 37 Sequence Number: - Start / End Page: 1184 - 1197 Identifier: ISSN: 0906-7590