Carbon exchange in an Amazon forest: From hours to years

Hayek, MN; Longo, M; Wu, J; Smith, MN; Restrepo-Coupe, N; Tapajós, R; Da Silva, R; Fitzjarrald, DR; Camargo, PB; Hutyra, LR; Alves, LF; Daube, B; William Munger, J; Wiedemann, KT; Saleska, SR; Wofsy, SC

Carbon exchange in an Amazon forest: From hours to years

Hayek, MN Longo, M Wu, J Smith, MN Restrepo-Coupe, N

Tapajós, R Da Silva, R Fitzjarrald, DR Camargo, PB Hutyra, LR Alves, LF Daube, B William Munger, J Wiedemann, KT Saleska, SR Wofsy, SC

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Publication Type:: Journal Article
Citation:: Biogeosciences, 2018, 15 (15), pp. 4833 - 4848
Issue Date:: 2018-08-15

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Field	Value	Language
dc.contributor.author	Hayek, MN	en_US
dc.contributor.author	Longo, M	en_US
dc.contributor.author	Wu, J	en_US
dc.contributor.author	Smith, MN	en_US
dc.contributor.author	Restrepo-Coupe, N https://orcid.org/0000-0003-3921-1772	en_US
dc.contributor.author	Tapajós, R	en_US
dc.contributor.author	Da Silva, R	en_US
dc.contributor.author	Fitzjarrald, DR	en_US
dc.contributor.author	Camargo, PB	en_US
dc.contributor.author	Hutyra, LR	en_US
dc.contributor.author	Alves, LF	en_US
dc.contributor.author	Daube, B	en_US
dc.contributor.author	William Munger, J	en_US
dc.contributor.author	Wiedemann, KT	en_US
dc.contributor.author	Saleska, SR	en_US
dc.contributor.author	Wofsy, SC	en_US
dc.date.issued	2018-08-15	en_US
dc.identifier.citation	Biogeosciences, 2018, 15 (15), pp. 4833 - 4848	en_US
dc.identifier.issn	1726-4170	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127495
dc.description.abstract	© Author(s) 2018. In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well (R 2 Combining double low line 0.81 and 0.59, respectively). Modeled phenology explained 1 % of hourly and 26 % of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light- or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgC ha'1 of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.	en_US
dc.relation.ispartof	Biogeosciences	en_US
dc.relation.isbasedon	10.5194/bg-15-4833-2018	en_US
dc.subject.classification	Meteorology & Atmospheric Sciences	en_US
dc.title	Carbon exchange in an Amazon forest: From hours to years	en_US
dc.type	Journal Article
utslib.citation.volume	15	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
utslib.for	0502 Environmental Science and Management	en_US
utslib.for	060799 Plant Biology not elsewhere classified	en_US
utslib.for	0607 Plant Biology	en_US
utslib.for	04 Earth Sciences	en_US
utslib.for	05 Environmental Sciences	en_US
utslib.for	06 Biological Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
utslib.copyright.status	open_access
pubs.issue	15	en_US
pubs.publication-status	Published	en_US
pubs.volume	15	en_US

Abstract:

© Author(s) 2018. In Amazon forests, the relative contributions of climate, phenology, and disturbance to net ecosystem exchange of carbon (NEE) are not well understood. To partition influences across various timescales, we use a statistical model to represent eddy-covariance-derived NEE in an evergreen eastern Amazon forest as a constant response to changing meteorology and phenology throughout a decade. Our best fit model represented hourly NEE variations as changes due to sunlight, while seasonal variations arose from phenology influencing photosynthesis and from rainfall influencing ecosystem respiration, where phenology was asynchronous with dry-season onset. We compared annual model residuals with biometric forest surveys to estimate impacts of drought disturbance. We found that our simple model represented hourly and monthly variations in NEE well (R 2 Combining double low line 0.81 and 0.59, respectively). Modeled phenology explained 1 % of hourly and 26 % of monthly variations in observed NEE, whereas the remaining modeled variability was due to changes in meteorology. We did not find evidence to support the common assumption that the forest phenology was seasonally light- or water-triggered. Our model simulated annual NEE well, with the exception of 2002, the first year of our data record, which contained 1.2 MgC ha'1 of residual net emissions, because photosynthesis was anomalously low. Because a severe drought occurred in 1998, we hypothesized that this drought caused a persistent, multi-year depression of photosynthesis. Our results suggest drought can have lasting impacts on photosynthesis, possibly via partial damage to still-living trees.

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http://hdl.handle.net/10453/127495