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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
20/02/2017 |
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Data da última atualização: |
20/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
WU, J.; GUAN, K.; HAYEK, M.; RESTREPO-COUPE, N.; WIEDEMANN, K. T.; XU, X.; WEHR, R.; CHRISTOFFERSEN, B. O.; MIAO, G.; SILVA, R. da; ARAUJO, A. C. de; OLIVEIRA JUNIOR, R. C. de; CAMARGO, P. B.; MONSON, R. K.; HUETE, A. R.; SALESKA, S. R. |
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Afiliação: |
JIN WU, University of Arizona; KAIYU GUAN, University of Illinois at Urbana Champaign; MATTHEW HAYEK, Harvard University; NATALIA RESTREPO-COUPE, University of Arizona / University of Technology Sydney; KENIA T. WIEDEMANN, University of Arizona / Harvard University; XIANGTAO XU, Princeton University; RICHARD WEHR, University of Arizona; BRADLEY O. CHRISTOFFERSEN, University of Arizona / Los Alamos National Laboratory; GUOFANG MIAO, University of Illinois at Urbana Champaign / North Carolina State University at Raleigh; RODRIGO DA SILVA, UFOPA; ALESSANDRO CARIOCA DE ARAUJO, CPATU; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; PLINIO B. CAMARGO, CENA/USP; RUSSELL K. MONSON, University of Arizona; ALFREDO R. HUETE, University of Technology Sydney; SCOTT R. SALESKA, University of Arizona. |
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Título: |
Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Global Change Biology, v. 23, n. 3, p. 1240-1257, Mar. 2017. |
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DOI: |
10.1111/gcb.13509 |
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Idioma: |
Inglês |
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Conteúdo: |
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2 = 0.77) to interannual (R2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms. MenosGross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2 = 0.77) to interannual (R2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental ... Mostrar Tudo |
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Thesagro: |
Fenologia; Fisiologia; Floresta Tropical; Fotossíntese. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
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001 2064783
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024 7 $a10.1111/gcb.13509$2DOI
100 1 $aWU, J.
245 $aPartitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales.$h[electronic resource]
260 $c2017
520 $aGross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R2 = 0.77) to interannual (R2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.
650 $aFenologia
650 $aFisiologia
650 $aFloresta Tropical
650 $aFotossíntese
700 1 $aGUAN, K.
700 1 $aHAYEK, M.
700 1 $aRESTREPO-COUPE, N.
700 1 $aWIEDEMANN, K. T.
700 1 $aXU, X.
700 1 $aWEHR, R.
700 1 $aCHRISTOFFERSEN, B. O.
700 1 $aMIAO, G.
700 1 $aSILVA, R. da
700 1 $aARAUJO, A. C. de
700 1 $aOLIVEIRA JUNIOR, R. C. de
700 1 $aCAMARGO, P. B.
700 1 $aMONSON, R. K.
700 1 $aHUETE, A. R.
700 1 $aSALESKA, S. R.
773 $tGlobal Change Biology$gv. 23, n. 3, p. 1240-1257, Mar. 2017.
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