Both environmental and biotic factors regulate tropical forest photosynthesis, with environment explaining short-term (hourly), but not longer-timescale (monthly and yearly) dynamics.
Tropical forest photosynthesis varies 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 photosynthesis in a central Amazon evergreen forest into two main causes (i.e. environmental vs. biological), and identified the differential regulation of tropical forest photosynthesis at different timescales.
This study has three important implications for the broader ecology, evolutionary biology, plant physiology, and modeling communities: (1) our work challenges modeling approaches that assume tropical forest photosynthesis is primarily controlled by the environment at both short and long timescales; (2) advances ecophysiological understanding of resource limitation (i.e. light vs. water) and the temperature sensitivity of tropical evergreen forest; and (3) highlights the importance of accounting for differential regulation of tropical forest photosynthesis at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.
Canopy-scale photosynthesis (Gross Ecosystem Productivity, GEP) of a central Amazonian evergreen forest in Brazil was derived from the k67 eddy covariance tower (2002-2005 and 2009-2011) using the standard approach to partition ecosystem respiration from eddy covariance measurements of net ecosystem exchange. We used statistical models to partition the variability of seven-year eddy covariance derived GEP into two causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) and biotic variation in canopy photosynthetic light-use-efficiency. The ‘full' model was driven by both environmental and biotic factors and the ‘Env' model was driven by environmental factors only. The models were trained by using the hourly data of years 2003, 2005, 2009, and 2011, and validated by the independent data of years 2002, 2004, and 2010, including the aggregation to different timescales (i.e. daily and monthly). Our results showed that both models (‘full' vs. ‘Env') simulated photosynthetic dynamics well at hourly timescales; however, when aggregating the model results into other timescales (i.e. daily, monthly, and yearly), the ‘Env' model showed continuous decline in the model performance. By contrast, the ‘full' model consistently simulated the photosynthetic dynamics across all timescales. Our results thus suggest that environmental variables dominate photosynthetic dynamics at shorter-timescales (i.e. hourly to daily) but not at longer-timescale (i.e. monthly and yearly), and highlight the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.
Contacts (BER PM)
Lead author contact information
Brookhaven National Laboratory
Brookhaven National Laboratory
J. Wu and B. Christoffersen were supported in part by the Next-Generation Ecosystem Experiment (NGEE-Tropics) project. The NGEE-Tropics project is supported by the Office of Biological and Environmental Research in the Department of Energy, Office of Science.
Wu J, Guan K, Hayek M, Restrepo-Coupe N, Wiedemann KT, Xu X, Wehr R, Christoffersen BO, Miao G, Silva R, Araujo AC, Oliviera RC, Camargo PB, Monson RK, Huete, AR, Saleska SR. Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales. Global Change Biology 23:1240-57 (2017). DOI:10.1111/gcb.13509. (Reference link)
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