TY - JOUR
T1 - Land carbon models underestimate the severity and duration of drought’s impact on plant productivity
AU - Kolus, Hannah R.
AU - Huntzinger, Deborah N.
AU - Schwalm, Christopher R.
AU - Fisher, Joshua B.
AU - McKay, Nicholas
AU - Fang, Yuanyuan
AU - Michalak, Anna M.
AU - Schaefer, Kevin
AU - Wei, Yaxing
AU - Poulter, Benjamin
AU - Mao, Jiafu
AU - Parazoo, Nicholas C.
AU - Shi, Xiaoying
N1 - Funding Information:
Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; http://nacp.ornl. gov/MsTMIP.shtml) activity was provided through NASA ROSES Grants #NNX10AG01A and NNX14A154G. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (ORNL; http://nacp.ornl.gov), with funding through NASA ROSES Grant #NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC (http://daac.ornl.gov). We also want to acknowledge the modeling groups that provided results to MsTMIP. JBF contributed to this paper from the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the NASA. Government sponsorship acknowledged. JBF was supported by NASA programs: CARBON, IDS, INCA, SUSMAP, and TE/ABoVE. We thank Victor O. Leshyk (Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ) for providing the illustration in Figure 1. Copyright 2018. All rights reserved.
Publisher Copyright:
© 2019, The Author(s).
PY - 2019/12/1
Y1 - 2019/12/1
N2 - The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0–6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO 2 .
AB - The ability to accurately predict ecosystem drought response and recovery is necessary to produce reliable forecasts of land carbon uptake and future climate. Using a suite of models from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we assessed modeled net primary productivity (NPP) response to, and recovery from, drought events against a benchmark derived from tree ring observations between 1948 and 2008 across forested regions of the US and Europe. We find short lag times (0–6 months) between climate anomalies and modeled NPP response. Although models accurately simulate the direction of drought legacy effects (i.e. NPP decreases), projected effects are approximately four times shorter and four times weaker than observations suggest. This discrepancy between observed and simulated vegetation recovery from drought reveals a potential critical model deficiency. Since productivity is a crucial component of the land carbon balance, models that underestimate drought recovery time could overestimate predictions of future land carbon sink strength and, consequently, underestimate forecasts of atmospheric CO 2 .
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U2 - 10.1038/s41598-019-39373-1
DO - 10.1038/s41598-019-39373-1
M3 - Article
C2 - 30808971
AN - SCOPUS:85062148954
SN - 2045-2322
VL - 9
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 2758
ER -