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Title: Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

Journal Article · · Journal of Geophysical Research. Biogeosciences
DOI:https://doi.org/10.1002/2016JG003503· OSTI ID:1379577
 [1];  [1];  [1];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [1]
  1. ETH Zurich, Zurich (Switzerland)
  2. Univ. of Colorado, Boulder, CO (United States)
  3. The Ohio State Univ., Columbus, OH (United States)
  4. USDA Forest Service, New Lisbon, NJ (United States)
  5. Univ. of Wisconsin, Madison, WI (United States)
  6. USDA Forest Service, Durham, NH (United States)
  7. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  8. Indiana Univ., Bloomington, IN (United States)

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence of favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the “most active hours/days” (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1379577
Journal Information:
Journal of Geophysical Research. Biogeosciences, Vol. 121, Issue 8; ISSN 2169-8953
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 55 works
Citation information provided by
Web of Science

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Cited By (5)

Forests dominate the interannual variability of the North American carbon sink journal August 2018
Plant species richness and functional groups have different effects on soil water content in a decade‐long grassland experiment journal August 2018
Maximum carbon uptake rate dominates the interannual variability of global net ecosystem exchange journal July 2019
Eddy Covariance vs. Biometric Based Estimates of Net Primary Productivity of Pedunculate Oak (Quercus robur L.) Forest in Croatia during Ten Years journal December 2018
A Brief Review of Random Forests for Water Scientists and Practitioners and Their Recent History in Water Resources journal April 2019