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Title: Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales

Journal Article · · Global Change Biology
DOI:https://doi.org/10.1111/gcb.13509· OSTI ID:1351750
 [1];  [2];  [3]; ORCiD logo [4];  [5];  [6];  [7];  [8];  [9];  [10];  [11];  [12];  [13];  [7];  [14];  [7]
  1. Univ. of Arizona, Tucson, AZ (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
  2. Univ. of Illinois at Urbana Champaign, Urbana, IL (United States)
  3. Harvard Univ., Cambridge, MA (United States)
  4. Univ. of Arizona, Tucson, AZ (United States); Univ. of Technology Sydney, Sydney, NSW (Australia)
  5. Univ. of Arizona, Tucson, AZ (United States); Harvard Univ., Cambridge, MA (United States)
  6. Princeton Univ., Princeton, NJ (United States)
  7. Univ. of Arizona, Tucson, AZ (United States)
  8. Univ. of Arizona, Tucson, AZ (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  9. Univ. of Illinois at Urbana Champaign, Urbana, IL (United States); North Carolina State Univ., Raleigh, NC (United States)
  10. Univ. of Western Para-UFOPA, Para (Brazil)
  11. Embrapa Amazonia Oriental, Belem (Brasil)
  12. Embrapa Amazonia Oriental, Santarem (Brasil)
  13. Univ. de Sao Paulo, Piracicaba (Brasil)
  14. Univ. of Technology Sydney, Sydney, NSW (Australia)

Abstract 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 ( R = 0.77) to interannual ( R = 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.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
SC00112704; DE‐SC0008383
OSTI ID:
1351750
Alternate ID(s):
OSTI ID: 1401016
Report Number(s):
BNL-113771-2017-JA; R&D Project: 21087; YN0100000
Journal Information:
Global Change Biology, Vol. 23, Issue 3; ISSN 1354-1013
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 86 works
Citation information provided by
Web of Science

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