Organizing principles for vegetation dynamics.
Journal
Nature plants
ISSN: 2055-0278
Titre abrégé: Nat Plants
Pays: England
ID NLM: 101651677
Informations de publication
Date de publication:
05 2020
05 2020
Historique:
received:
31
07
2019
accepted:
02
04
2020
pubmed:
13
5
2020
medline:
10
2
2021
entrez:
13
5
2020
Statut:
ppublish
Résumé
Plants and vegetation play a critical-but largely unpredictable-role in global environmental changes due to the multitude of contributing processes at widely different spatial and temporal scales. In this Perspective, we explore approaches to master this complexity and improve our ability to predict vegetation dynamics by explicitly taking account of principles that constrain plant and ecosystem behaviour: natural selection, self-organization and entropy maximization. These ideas are increasingly being used in vegetation models, but we argue that their full potential has yet to be realized. We demonstrate the power of natural selection-based optimality principles to predict photosynthetic and carbon allocation responses to multiple environmental drivers, as well as how individual plasticity leads to the predictable self-organization of forest canopies. We show how models of natural selection acting on a few key traits can generate realistic plant communities and how entropy maximization can identify the most probable outcomes of community dynamics in space- and time-varying environments. Finally, we present a roadmap indicating how these principles could be combined in a new generation of models with stronger theoretical foundations and an improved capacity to predict complex vegetation responses to environmental change.
Identifiants
pubmed: 32393882
doi: 10.1038/s41477-020-0655-x
pii: 10.1038/s41477-020-0655-x
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
444-453Références
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