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.
%0 Journal Article
%1 paschalis2020rainfallmanipulation
%A Paschalis, Athanasios
%A Fatichi, Simone
%A Zscheischler, Jakob
%A Ciais, Philippe
%A Bahn, Michael
%A Boysen, Lena
%A Chang, Jinfeng
%A Kauwe, Martin De
%A Estiarte, Marc
%A Goll, Daniel
%A Hanson, Paul J.
%A Harper, Anna B.
%A Hou, Enqing
%A Kigel, Jaime
%A Knapp, Alan K.
%A Larsen, Klaus Steenberg
%A Li, Wei
%A Lienert, Sebastian
%A Luo, Yiqi
%A Meir, Patrick
%A Nabel, Julia E.M.S.
%A Ogaya, Romà
%A Parolari, Anthony J
%A Peng, Changhui
%A Peñuelas, Josep
%A Pongratz, Julia
%A Rambal, Serge
%A Schmidt, Inger Kappel
%A Shi, Hao
%A Sternberg, Marcelo
%A Tian, Hanqin
%A Tschumi, Elisabeth
%A Ukkola, Anna
%A Vicca, Sara
%A Viovy, Nicolas
%A Wang, Ying-Ping
%A Wang, Zhuonan
%A Williams, Karina
%A Wu, Donghai
%A Zhu, Qiuan
%D 2020
%I Wiley
%J Global Change Biology
%K KW landsurface model precip vegetation
%R 10.1111/gcb.15024
%T Rainfall-manipulation experiments as simulated by terrestrial biosphere models: where do we stand?
%U https://doi.org/10.1111/gcb.15024
%X 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.
@article{paschalis2020rainfallmanipulation,
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.},
added-at = {2020-04-02T18:38:28.000+0200},
author = {Paschalis, Athanasios and Fatichi, Simone and Zscheischler, Jakob and Ciais, Philippe and Bahn, Michael and Boysen, Lena and Chang, Jinfeng and Kauwe, Martin De and Estiarte, Marc and Goll, Daniel and Hanson, Paul J. and Harper, Anna B. and Hou, Enqing and Kigel, Jaime and Knapp, Alan K. and Larsen, Klaus Steenberg and Li, Wei and Lienert, Sebastian and Luo, Yiqi and Meir, Patrick and Nabel, Julia E.M.S. and Ogaya, Rom{\`{a}} and Parolari, Anthony J and Peng, Changhui and Pe{\~{n}}uelas, Josep and Pongratz, Julia and Rambal, Serge and Schmidt, Inger Kappel and Shi, Hao and Sternberg, Marcelo and Tian, Hanqin and Tschumi, Elisabeth and Ukkola, Anna and Vicca, Sara and Viovy, Nicolas and Wang, Ying-Ping and Wang, Zhuonan and Williams, Karina and Wu, Donghai and Zhu, Qiuan},
biburl = {https://www.bibsonomy.org/bibtex/26d510dedf6100b52248cb458991f5a6e/pbett},
doi = {10.1111/gcb.15024},
interhash = {a1120245bbbb237fb1dcf596ba3b393b},
intrahash = {6d510dedf6100b52248cb458991f5a6e},
journal = {Global Change Biology},
keywords = {KW landsurface model precip vegetation},
month = feb,
publisher = {Wiley},
timestamp = {2020-04-15T09:28:56.000+0200},
title = {Rainfall-manipulation experiments as simulated by terrestrial biosphere models: where do we stand?},
url = {https://doi.org/10.1111/gcb.15024},
year = 2020
}