Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes

Zhang, Y; Susan Moran, M; Nearing, MA; Ponce Campos, GE; Huete, AR; Buda, AR; Bosch, DD; Gunter, SA; Kitchen, SG; Henry McNab, W; Morgan, JA; McClaran, MP; Montoya, DS; Peters, DPC; Starks, PJ

Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes

Zhang, Y Susan Moran, M Nearing, MA Ponce Campos, GE Huete, AR

Buda, AR Bosch, DD Gunter, SA Kitchen, SG Henry McNab, W Morgan, JA McClaran, MP Montoya, DS Peters, DPC Starks, PJ

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Publication Type:: Journal Article
Citation:: Journal of Geophysical Research: Biogeosciences, 2013, 118 (1), pp. 148 - 157
Issue Date:: 2013-03-01

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Field	Value	Language
dc.contributor.author	Zhang, Y	en_US
dc.contributor.author	Susan Moran, M	en_US
dc.contributor.author	Nearing, MA	en_US
dc.contributor.author	Ponce Campos, GE	en_US
dc.contributor.author	Huete, AR https://orcid.org/0000-0003-2809-2376	en_US
dc.contributor.author	Buda, AR	en_US
dc.contributor.author	Bosch, DD	en_US
dc.contributor.author	Gunter, SA	en_US
dc.contributor.author	Kitchen, SG	en_US
dc.contributor.author	Henry McNab, W	en_US
dc.contributor.author	Morgan, JA	en_US
dc.contributor.author	McClaran, MP	en_US
dc.contributor.author	Montoya, DS	en_US
dc.contributor.author	Peters, DPC	en_US
dc.contributor.author	Starks, PJ	en_US
dc.date.issued	2013-03-01	en_US
dc.identifier.citation	Journal of Geophysical Research: Biogeosciences, 2013, 118 (1), pp. 148 - 157	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26284
dc.description.abstract	Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000-2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (P<inf>T</inf>) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both P<inf>T</inf> and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as P <inf>T</inf>. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change. Key Points Extreme rainfall events reduced the sensitivity of ANPP to total annual rainfallCo-occurrence of intense rainfall and longer dry interval reduced greater ANPPA new model improved predictions of ANPP by accounting for extreme patterns ©2012. American Geophysical Union. All Rights Reserved.	en_US
dc.relation.ispartof	Journal of Geophysical Research: Biogeosciences	en_US
dc.relation.isbasedon	10.1029/2012JG002136	en_US
dc.title	Extreme precipitation patterns and reductions of terrestrial ecosystem production across biomes	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	118	en_US
utslib.for	0404 Geophysics	en_US
utslib.for	0602 Ecology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	118	en_US

Abstract:

Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000-2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as P T. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change. Key Points Extreme rainfall events reduced the sensitivity of ANPP to total annual rainfallCo-occurrence of intense rainfall and longer dry interval reduced greater ANPPA new model improved predictions of ANPP by accounting for extreme patterns ©2012. American Geophysical Union. All Rights Reserved.

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http://hdl.handle.net/10453/26284