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Persistent Identifier
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perma:LIST.C7K8L4 |
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Publication Date
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2025-12-09 |
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Title
| Organizing principles for vegetation dynamics [* Cross-Reference *] |
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Other Identifier
| https://doi.org/10.1038/s41477-020-0655-x |
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Author
| Franklin, Oskar (International Institute for Applied Systems Analysis, Laxenburg, Sveriges lantbruksuniversitet) - ORCID: 0000-0002-0376-4140
Harrison, Sandy P. (University of Reading) - ORCID: 0000-0001-5687-1903
Dewar, Roderick (ANU Research School of Biology, Helsingin Yliopisto)
Farrior, Caroline E. (The University of Texas at Austin)
Brännström, Åke (International Institute for Applied Systems Analysis, Laxenburg, Umeå Universitet)
Dieckmann, Ulf (International Institute for Applied Systems Analysis, Laxenburg, The Graduate University for Advanced Studies)
Pietsch, Stephan (International Institute for Applied Systems Analysis, Laxenburg)
Falster, Daniel (UNSW Sydney) - ORCID: 0000-0002-9814-092X
Cramer, Wolfgang (Aix Marseille Université) - ORCID: 0000-0002-9205-5812
Loreau, Michel (CNRS Centre National de la Recherche Scientifique)
Wang, Han (Tsinghua University) - ORCID: 0000-0003-2482-1818
Mäkelä, Annikki (Helsingin Yliopisto)
Rebel, Karin T. (Copernicus Institute of Sustainable Development)
Meron, Ehud (Ben-Gurion University of the Negev, Ben-Gurion University of the Negev)
Schymanski, Stanislaus J. (Luxembourg Institute of Science and Technology) - ORCID: 0000-0002-0950-2942
Rovenskaya, Elena (International Institute for Applied Systems Analysis, Laxenburg)
Stocker, Benjamin D. (ETH Zürich, Centre de Recerca Ecològica i Aplicacions Forestals (CREAF-CERCA)) - ORCID: 0000-0003-2697-9096
Zaehle, Sönke (Max Planck Institute for Biogeochemistry) - ORCID: 0000-0001-5602-7956
Manzoni, Stefano (Stockholms universitet, Bolin Centre for Climate Research) - ORCID: 0000-0002-5960-5712
van Oijen, Marcel (UK Centre for Ecology & Hydrology) - ORCID: 0000-0003-4028-3626
Wright, Ian J. (Macquarie University) - ORCID: 0000-0001-8338-9143
Ciais, Philippe (Université de Versailles Saint-Quentin-en-Yvelines) - ORCID: 0000-0001-8560-4943
van Bodegom, Peter M. (Universiteit Leiden) - ORCID: 0000-0003-0771-4500
Peñuelas, Josep (Centre de Recerca Ecològica i Aplicacions Forestals (CREAF-CERCA), Consejo Superior de Investigaciones Científicas) - ORCID: 0000-0002-7215-0150
Hofhansl, Florian (International Institute for Applied Systems Analysis, Laxenburg) - ORCID: 0000-0003-0073-0946
Terrer, Cesar (Lawrence Livermore National Laboratory) - ORCID: 0000-0002-5479-3486
Soudzilovskaia, Nadejda A. (Universiteit Leiden) - ORCID: 0000-0003-4659-2585
Midgley, Guy (Stellenbosch University) - ORCID: 0000-0001-8264-0869
Prentice, I. Colin (Tsinghua University, Macquarie University, Imperial College London) |
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Point of Contact
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Use email button above to contact.
LIST RDS (LIST) |
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Description
| 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. (2020-01-01)
***This entry has been automatically imported via Infodoc(ASO) CSV by LIST harvest scripts. Please refer to https://doi.org/10.1038/s41477-020-0655-x for the original and latest version of the dataset and data downloads*** (2025-12-05) |
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Subject
| Other |
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Keyword
| play a critical
largely unpredictable
role in global
temporal scales
multitude of contributing |
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Deposit Date
| 2020-01-01 |
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Data Type
| Review |