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Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest
The relative contribution of gross primary production and ecosystem respiration to seasonal changes in the net carbon flux of tropical forests remains poorly quantified by both modelling and field studies. We use data assimilation to combine nine ecological time series from an eastern Amazonian fore...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BlackWell Publishing Ltd
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298765/ https://www.ncbi.nlm.nih.gov/pubmed/23996917 http://dx.doi.org/10.1111/gcb.12375 |
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author | Rowland, Lucy Hill, Timothy Charles Stahl, Clement Siebicke, Lukas Burban, Benoit Zaragoza-Castells, Joana Ponton, Stephane Bonal, Damien Meir, Patrick Williams, Mathew |
author_facet | Rowland, Lucy Hill, Timothy Charles Stahl, Clement Siebicke, Lukas Burban, Benoit Zaragoza-Castells, Joana Ponton, Stephane Bonal, Damien Meir, Patrick Williams, Mathew |
author_sort | Rowland, Lucy |
collection | PubMed |
description | The relative contribution of gross primary production and ecosystem respiration to seasonal changes in the net carbon flux of tropical forests remains poorly quantified by both modelling and field studies. We use data assimilation to combine nine ecological time series from an eastern Amazonian forest, with mass balance constraints from an ecosystem carbon cycle model. The resulting analysis quantifies, with uncertainty estimates, the seasonal changes in the net carbon flux of a tropical rainforest which experiences a pronounced dry season. We show that the carbon accumulation in this forest was four times greater in the dry season than in the wet season and that this was accompanied by a 5% increase in the carbon use efficiency. This seasonal response was caused by a dry season increase in gross primary productivity, in response to radiation and a similar magnitude decrease in heterotrophic respiration, in response to drying soils. The analysis also predicts increased carbon allocation to leaves and wood in the wet season, and greater allocation to fine roots in the dry season. This study demonstrates implementation of seasonal variations in parameters better enables models to simulate observed patterns in data. In particular, we highlight the necessity to simulate the seasonal patterns of heterotrophic respiration to accurately simulate the net carbon flux seasonal tropical forest. |
format | Online Article Text |
id | pubmed-4298765 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BlackWell Publishing Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-42987652015-01-27 Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest Rowland, Lucy Hill, Timothy Charles Stahl, Clement Siebicke, Lukas Burban, Benoit Zaragoza-Castells, Joana Ponton, Stephane Bonal, Damien Meir, Patrick Williams, Mathew Glob Chang Biol Primary Research Articles The relative contribution of gross primary production and ecosystem respiration to seasonal changes in the net carbon flux of tropical forests remains poorly quantified by both modelling and field studies. We use data assimilation to combine nine ecological time series from an eastern Amazonian forest, with mass balance constraints from an ecosystem carbon cycle model. The resulting analysis quantifies, with uncertainty estimates, the seasonal changes in the net carbon flux of a tropical rainforest which experiences a pronounced dry season. We show that the carbon accumulation in this forest was four times greater in the dry season than in the wet season and that this was accompanied by a 5% increase in the carbon use efficiency. This seasonal response was caused by a dry season increase in gross primary productivity, in response to radiation and a similar magnitude decrease in heterotrophic respiration, in response to drying soils. The analysis also predicts increased carbon allocation to leaves and wood in the wet season, and greater allocation to fine roots in the dry season. This study demonstrates implementation of seasonal variations in parameters better enables models to simulate observed patterns in data. In particular, we highlight the necessity to simulate the seasonal patterns of heterotrophic respiration to accurately simulate the net carbon flux seasonal tropical forest. BlackWell Publishing Ltd 2014-03 2014-01-20 /pmc/articles/PMC4298765/ /pubmed/23996917 http://dx.doi.org/10.1111/gcb.12375 Text en © 2013 The Authors Global Change Biology Published by John Wiley & Sons Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Primary Research Articles Rowland, Lucy Hill, Timothy Charles Stahl, Clement Siebicke, Lukas Burban, Benoit Zaragoza-Castells, Joana Ponton, Stephane Bonal, Damien Meir, Patrick Williams, Mathew Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title | Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title_full | Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title_fullStr | Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title_full_unstemmed | Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title_short | Evidence for strong seasonality in the carbon storage and carbon use efficiency of an Amazonian forest |
title_sort | evidence for strong seasonality in the carbon storage and carbon use efficiency of an amazonian forest |
topic | Primary Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298765/ https://www.ncbi.nlm.nih.gov/pubmed/23996917 http://dx.doi.org/10.1111/gcb.12375 |
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