AuthorHayek, Matthew N.
Smith, Marielle N.
da Silva, Rodrigo
Fitzjarrald, David R.
Camargo, Plinio B.
Hutyra, Lucy R.
Alves, Luciana F.
Munger, J. William
Wiedemann, Kenia T.
Saleska, Scott R.
Wofsy, Steven C.
AffiliationUniv Arizona, Dept Ecol & Evolutionary Biol
MetadataShow full item record
PublisherCOPERNICUS GESELLSCHAFT MBH
CitationHayek, M. N., Longo, M., Wu, J., Smith, M. N., Restrepo-Coupe, N., Tapajós, R., da Silva, R., Fitzjarrald, D. R., Camargo, P. B., Hutyra, L. R., Alves, L. F., Daube, B., Munger, J. W., Wiedemann, K. T., Saleska, S. R., and Wofsy, S. C.: Carbon exchange in an Amazon forest: from hours to years, Biogeosciences, 15, 4833-4848, https://doi.org/10.5194/bg-15-4833-2018, 2018.
Rights© Author(s) 2018. This work is distributed under the Creative Commons Attribution 4.0 License.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractIn 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 = 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 MgCha(-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.
NoteOpen access journal
VersionFinal published version
SponsorsNational Science Foundation PIRE fellowship [OISE 0730305]; US Department of Energy grant [DE-SC0008311]