Rainfall manipulation experiments as simulated by terrestrial biosphere models: Where do we stand?

Athanasios Paschalis, Simone Fatichi, Jakob Zscheischler, Philippe Ciais, Michael Bahn, Lena Boysen, Jinfeng Chang, Martin De Kauwe, Marc Estiarte, Daniel Goll, Paul J. Hanson, Anna B. Harper, Enqing Hou, Jaime Kigel, Alan K. Knapp, Klaus S. Larsen, Wei Li, Sebastian Lienert, Yiqi Luo, Patrick MeirJulia E.M.S. Nabel, Romà Ogaya, Anthony J. Parolari, Changhui Peng, Josep Peñuelas, Julia Pongratz, Serge Rambal, Inger K. Schmidt, Hao Shi, Marcelo Sternberg, Hanqin Tian, Elisabeth Tschumi, Anna Ukkola, Sara Vicca, Nicolas Viovy, Ying Ping Wang, Zhuonan Wang, Karina Williams, Donghai Wu, Qiuan Zhu

Research output: Contribution to journalArticlepeer-review

Abstract

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily–monthly) timescales and reduces on longer (seasonal–annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models.

Original languageEnglish
Pages (from-to)3336-3355
Number of pages20
JournalGlobal Change Biology
Volume26
Issue number6
DOIs
StatePublished - 1 Jun 2020

Keywords

  • drought
  • irrigation
  • rainfall manipulation experiment
  • terrestrial biosphere models

All Science Journal Classification (ASJC) codes

  • General Environmental Science
  • Global and Planetary Change
  • Ecology
  • Environmental Chemistry

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