Skip to main content
ARS Home » Pacific West Area » Tucson, Arizona » SWRC » Research » Publications at this Location » Publication #382524

Research Project: Understanding Water-Driven Ecohydrologic and Erosion Processes in the Semiarid Southwest to Improve Watershed Management

Location: Southwest Watershed Research Center

Title: Dynamic global vegetation models underestimate net CO2 flux mean and inter-annual variability in dryland ecosystems

Author
item MACBEAN, N. - University Of Indiana
item Scott, Russell - Russ
item Biederman, Joel
item PEYLIN, P. - Université Paris-Saclay
item KOLB, T. - Northern Arizona University
item LITVAK, M. - University Of New Mexico
item KRISHNAN, P. - National Oceanic & Atmospheric Administration (NOAA)
item MEYERS, T. - National Oceanic & Atmospheric Administration (NOAA)
item ARORA, V. - Environment And Climate Change Canada
item BASTRIKOV, V. - Université Paris-Saclay
item GOLL, D. - Université Paris-Saclay
item LOMBARDOZZI, D.L,. - National Center For Atmospheric Research (NCAR)
item NABEL, J. - Max-Planck-institut Für Meteorologie
item PONGRATZ, J. - Max-Planck-institut Für Meteorologie
item SITCH, S. - University Of Exeter
item WALKER, A.P. - Oak Ridge National Laboratory
item ZAEHLE, S. - Max-Planck-institut Für Meteorologie
item MOORE, D.J. - University Of Arizona

Submitted to: Environmental Research Letters
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/3/2021
Publication Date: 8/24/2021
Citation: Macbean, N., Scott, R.L., Biederman, J.A., Peylin, P., Kolb, T., Litvak, M., Krishnan, P., Meyers, T., Arora, V., Bastrikov, V., Goll, D., Lombardozzi, D., Nabel, J., Pongratz, J., Sitch, S., Walker, A., Zaehle, S., Moore, D. 2021. Dynamic global vegetation models underestimate net CO2 flux mean and inter-annual variability in dryland ecosystems. Environmental Research Letters. 16, Article 094023. https://doi.org/10.1088/1748-9326/ac1a38.
DOI: https://doi.org/10.1088/1748-9326/ac1a38

Interpretive Summary: Recent studies have shown that arid regions are an important component of the global carbon cycle. However, unlike wetter regions, the state-of-the-art land surface models used in these studies have not yet been extensively evaluated for arid regions. Here, we address this gap by comparing 14 models against data from 12 arid monitoring sites in the southwestern US encompassing a range of climate and vegetation (forest, shrub- and grassland). We find the models underestimate both the average carbon uptake and release as well as the annual change in these quantities, suggesting that these regions may play an even more important role in the global carbon cycle than previously thought. We found these discrepancies are explained by the models’ muted response of photosynthesis to soil moisture - particularly in the spring for high elevation forested sites, and during the monsoon for low elevation desert shrub and grass sites. We propose a range of hypotheses related to plant physiology and phenology for why model photosynthesis does not respond sufficiently to soil moisture that can serve as a guide for future model developments.

Technical Abstract: Recent studies have shown that semi-arid regions dominate inter-annual variability (IAV) in the global carbon (C) cycle (Poulter et al., 2014; Ahlstrom et al., 2015). However, unlike more mesic ecosystems, the dynamic global vegetation models (DGVMs) used in these studies have not yet been extensively evaluated for semi-arid regions. Here, we address this gap by comparing an ensemble of 14 DGVMs (TRENDY v7) against net ecosystem exchange (NEE) data from 12 semi-arid flux sites in the southwestern US encompassing a range of climate and vegetation (forest, shrub- and grassland). We find the models underestimate both mean annual C uptake/release as well as the magnitude of NEE interannual variability (IAV), suggesting that semi-arid regions may have an even more important role to play in global C cycle variability than previously thought. We analyzed which season, and which gross CO2 flux, may be causing model-data discrepancies in mean annual NEE and IAV. Spring biases in modeled GPP dominate the underestimate of mean annual NEE, whereas both spring and summer monsoon GPP is responsible for inability to capture NEE IAV. We found these discrepancies are explained by the models’ lack of GPP response to plant available moisture - particularly in the spring for high elevation forested sites, and during the monsoon for low elevation shrub and grass sites. We propose a range of hypotheses related to plant physiology and phenology for why model GPP does not respond sufficiently to changing water availability that can serve as a guide for future semi-arid DGVM developments.