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Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

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posted on 2025-07-31, 22:37 authored by D Wu, P Ciais, N Viovy, AK Knapp, K Wilcox, M Bahn, MD Smith, S Vicca, S Fatichi, J Zscheischler, Y He, X Li, A Ito, A Arneth, A Harper, A Ukkola, A Paschalis, B Poulter, C Peng, D Ricciuto, D Reinthaler, G Chen, H Tian, H Genet, J Mao, J Ingrisch, JESM Nabel, J Pongratz, LR Boysen, M Kautz, M Schmitt, P Meir, Q Zhu, R Hasibeder, S Sippel, SRS Dangal, S Sitch, X Shi, Y Wang, Y Luo, Y Liu, S Piao
Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon-water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

Funding

This study was supported by National Natural Science Foundation of China (41530528). PC was supported by the European Research Council Synergy project SyG-2013-610028 IMBALANCE-P. The field work at Stubai was funded by the EU FP7 project Carbo-Extreme and the Austrian Science Fund (FWF); the synthesis and contribution to the manuscript was supported by the Austrian Academy of Sciences (ClimLUC). We also acknowledge support from the ClimMani COST action (ES1308). Sara Vicca is a postdoctoral fellow of the Fund for Scientific Research – Flanders. Markus Kautz acknowledges support from the EU FP7 project LUC4C, grant 603542. We thank Jeffrey S. Dukes, Shiqiang Wan and the organizers of the conference for the model– experiment interaction study in Beijing. We thank Sibyll Schaphoff, Werner von Bloh, Susanne Rolinski and Kirsten Thonicke from PIK as well as Matthias Forkel from TU Vienna for their support of the LPJmL code. Jiafu Mao, Daniel Ricciuto and Xiaoying Shi were supported by the Terrestrial Ecosystem Science Scientific Focus Area (TES SFA) project funded through the Terrestrial Ecosystem Science Program in the Climate and Environmental Sciences Division (CESD) of the Biological and Environmental Research (BER) Program in the US Department of Energy Office of Science. The simulations of CLM4.5 used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the US Department of Energy under contract no. DE-AC05-00OR22725.

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© Author(s) 2018. Open access. This work is distributed under the Creative Commons Attribution 4.0 License: https://creativecommons.org/licenses/by/4.0/

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This is the final version. Available on open access from EGU via the DOI in this record

Journal

Biogeosciences

Publisher

European Geosciences Union (EGU) / Copernicus Publications

Language

en

Citation

Vol. 15, pp. 3421 - 3437

Department

  • Mathematics and Statistics
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