Resilience of Amazon forests emerges from plant trait diversity
Application of a terrestrial biogeochemical model that simulates diverse forest communities suggests that plant trait diversity may enable the Amazon rainforest to adjust to new climate conditions via a process of ecological sorting. Climate change threatens ecosystems worldwide, yet their potential...
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Published in | Nature climate change Vol. 6; no. 11; pp. 1032 - 1036 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Nature Publishing Group UK
01.11.2016
Nature Publishing Group |
Subjects | |
Online Access | Get full text |
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Summary: | Application of a terrestrial biogeochemical model that simulates diverse forest communities suggests that plant trait diversity may enable the Amazon rainforest to adjust to new climate conditions via a process of ecological sorting.
Climate change threatens ecosystems worldwide, yet their potential future resilience remains largely unquantified
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. In recent years many studies have shown that biodiversity, and in particular functional diversity, can enhance ecosystem resilience by providing a higher response diversity
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,
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. So far these insights have been mostly neglected in large-scale projections of ecosystem responses to climate change
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. Here we show that plant trait diversity, as a key component of functional diversity, can have a strikingly positive effect on the Amazon forests’ biomass under future climate change. Using a terrestrial biogeochemical model that simulates diverse forest communities on the basis of individual tree growth
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, we show that plant trait diversity may enable the Amazon forests to adjust to new climate conditions via a process of ecological sorting, protecting the Amazon’s carbon sink function. Therefore, plant trait diversity, and biodiversity in general, should be considered in large-scale ecosystem projections and be included as an integral part of climate change research and policy. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1758-678X 1758-6798 |
DOI: | 10.1038/nclimate3109 |