Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling

Haynes, Katherine D.; Baker, Ian T.; Denning, A. Scott; Wolf, Sebastian; Wohlfahrt, Georg; Kiely, Gerard; Minaya, Renee C.; Haynes, John M.

doi:10.1029/2018ms001541

Title: Representing Grasslands Using Dynamic Prognostic Phenology Based on Biological Growth Stages: Part 2. Carbon Cycling

Journal Article · Sun Dec 01 00:00:00 EST 2019 · Journal of Advances in Modeling Earth Systems

DOI:https://doi.org/10.1029/2018ms001541· OSTI ID:1800139

Haynes, Katherine D. ^[1]; Baker, Ian T. ^[1]; Denning, A. Scott ^[1]; Wolf, Sebastian ^[2]; Wohlfahrt, Georg ^[3]; Kiely, Gerard ^[4]; Minaya, Renee C. ^[5]; Haynes, John M. ^[1]

Colorado State Univ., Fort Collins, CO (United States)
Eidgenoessische Technische Hochschule (ETH), Zurich (Switzerland)
Univ. Innsbruck (Austria)
University College Cork (Ireland)
University Corporation for Atmospheric Research Boulder, CO (United States)

Grasslands are one of the most widely distributed and abundant vegetation types globally, and land surface models struggle to accurately simulate grassland carbon dioxide, energy, and water fluxes. Here we hypothesize that this is due to land surface models having difficulties in reproducing grassland phenology, in particular in response to the seasonal and interannual variability of precipitation. Using leaf area index (LAI), net primary productivity, and flux data at 55 sites spanning climate zones, the aim of this study is to evaluate a novel prognostic phenology model (Simple Biosphere Model, SiB4) while simultaneously illustrating grassland relationships across precipitation gradients. Evaluating from 2000 to 2014, SiB4 predicts daily LAI, carbon, and energy fluxes with root-mean-square errors < 15% and individual biases <10%; however, not including management likely reduces its performance. Grassland mean annual LAI increases linearly with mean annual precipitation, with both SiB4 and the Moderate Resolution Imaging Spectroradiometer (MODIS) showing a 0.13 increase in LAI per 100-mm increase in precipitation. Both gross primary production and ecosystem respiration increase with growing season length by ~8.5 g C m^-2 per day, with SiB4 and Fluxnet estimates within 18%. Despite differences in mean annual precipitation and growing season length, all grassland sites shift to seasonal carbon sinks one month prior to peak uptake. During a U.S. drought, MODIS and SiB4 had nearly identical LAI responses, and the LAI change due to drought was less than the LAI change across the precipitation gradient, indicating that grassland drought response is not as strong as the overlying climate response.

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Research Organization:: Univ. of California, San Diego, CA (United States); Univ. of California, Oakland, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: FG02-03ER63638; AC02-05CH11231

OSTI ID:: 1800139

Journal Information:: Journal of Advances in Modeling Earth Systems, Vol. 11, Issue 12; ISSN 1942-2466

Publisher:: American Geophysical Union (AGU)Copyright Statement

Country of Publication:: United States

Language:: English

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