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Title: Mean annual precipitation predicts primary production resistance and resilience to extreme drought

Abstract

Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystemsmore » are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.« less

Authors:
ORCiD logo; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Univ. of Tennessee, Knoxville, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23). Climate and Environmental Sciences Division; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1435432
Alternate Identifier(s):
OSTI ID: 1435422
Grant/Contract Number:  
SC0010562
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Science of the Total Environment
Additional Journal Information:
Journal Volume: 636; Journal Issue: C; Related Information: Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2018.04.290.; Journal ID: ISSN 0048-9697
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
Forest; Grassland; Extreme drought; Primary productivity; Resistance; Resilience; 54 ENVIRONMENTAL SCIENCES

Citation Formats

Stuart-Haëntjens, Ellen, De Boeck, Hans J., Lemoine, Nathan P., Mänd, Pille, Kröel-Dulay, György, Schmidt, Inger K., Jentsch, Anke, Stampfli, Andreas, Anderegg, William R. L., Bahn, Michael, Kreyling, Juergen, Wohlgemuth, Thomas, Lloret, Francisco, Classen, Aimée T., Gough, Christopher M., and Smith, Melinda D.. Mean annual precipitation predicts primary production resistance and resilience to extreme drought. United States: N. p., 2018. Web. doi:10.1016/j.scitotenv.2018.04.290.
Stuart-Haëntjens, Ellen, De Boeck, Hans J., Lemoine, Nathan P., Mänd, Pille, Kröel-Dulay, György, Schmidt, Inger K., Jentsch, Anke, Stampfli, Andreas, Anderegg, William R. L., Bahn, Michael, Kreyling, Juergen, Wohlgemuth, Thomas, Lloret, Francisco, Classen, Aimée T., Gough, Christopher M., & Smith, Melinda D.. Mean annual precipitation predicts primary production resistance and resilience to extreme drought. United States. doi:10.1016/j.scitotenv.2018.04.290.
Stuart-Haëntjens, Ellen, De Boeck, Hans J., Lemoine, Nathan P., Mänd, Pille, Kröel-Dulay, György, Schmidt, Inger K., Jentsch, Anke, Stampfli, Andreas, Anderegg, William R. L., Bahn, Michael, Kreyling, Juergen, Wohlgemuth, Thomas, Lloret, Francisco, Classen, Aimée T., Gough, Christopher M., and Smith, Melinda D.. Sat . "Mean annual precipitation predicts primary production resistance and resilience to extreme drought". United States. doi:10.1016/j.scitotenv.2018.04.290.
@article{osti_1435432,
title = {Mean annual precipitation predicts primary production resistance and resilience to extreme drought},
author = {Stuart-Haëntjens, Ellen and De Boeck, Hans J. and Lemoine, Nathan P. and Mänd, Pille and Kröel-Dulay, György and Schmidt, Inger K. and Jentsch, Anke and Stampfli, Andreas and Anderegg, William R. L. and Bahn, Michael and Kreyling, Juergen and Wohlgemuth, Thomas and Lloret, Francisco and Classen, Aimée T. and Gough, Christopher M. and Smith, Melinda D.},
abstractNote = {Extreme drought is increasing in frequency and intensity in many regions globally, with uncertain consequences for the resistance and resilience of ecosystem functions, including primary production. Primary production resistance, the capacity to withstand change during extreme drought, and resilience, the degree to which production recovers, vary among and within ecosystem types, obscuring generalized patterns of ecological stability. Theory and many observations suggest forest production is more resistant but less resilient than grassland production to extreme drought; however, studies of production sensitivity to precipitation variability indicate that the processes controlling resistance and resilience may be influenced more by mean annual precipitation (MAP) than ecosystem type. Here, we conducted a global meta-analysis to investigate primary production resistance and resilience to extreme drought in 64 forests and grasslands across a broad MAP gradient. We found resistance to extreme drought was predicted by MAP; however, grasslands (positive) and forests (negative) exhibited opposing resilience relationships with MAP. Our findings indicate that common plant physiological mechanisms may determine grassland and forest resistance to extreme drought, whereas differences among plant residents in turnover time, plant architecture, and drought adaptive strategies likely underlie divergent resilience patterns. The low resistance and resilience of dry grasslands suggests that these ecosystems are the most vulnerable to extreme drought – a vulnerability that is expected to compound as extreme drought frequency increases in the future.},
doi = {10.1016/j.scitotenv.2018.04.290},
journal = {Science of the Total Environment},
number = C,
volume = 636,
place = {United States},
year = {Sat Sep 01 00:00:00 EDT 2018},
month = {Sat Sep 01 00:00:00 EDT 2018}
}

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