Unexpected patterns of sensitivity to drought in three semi-arid grasslands

Unexpected patterns of sensitivity to drought in three semi-arid grasslands Global climate models forecast an increase in the frequency and intensity of extreme weather events, including severe droughts. Based on multi-year relationships between precipitation amount and aboveground annual net primary production (ANPP), semi-arid grasslands are projected to be among the most sensitive ecosystems to changes in precipitation. To assess sensitivity to drought, as well as variability within the shortgrass steppe biome, we imposed moderate and severe rainfall reductions for two growing seasons in three undisturbed grasslands that varied in soil type and climate. We predicted strong drought-induced reductions in ANPP at all sites and greater sensitivity to drought in sites with lower average precipitation, consistent with continental-scale patterns. Identical experimental infrastructure at each site reduced growing season rainfall events by 50 or 80%, and significantly reduced average soil moisture in both years (by 21 and 46% of control levels, respectively). Despite reductions in soil moisture, ANPP responses varied unexpectedly—from no reduction in ANPP to a 51% decrease. Although sensitivity to drought was highest in the semi-arid grassland with lowest mean annual precipitation, patterns in responses to drought across these grasslands were also strongly related to rainfall event size. When growing season rainfall patterns were dominated by many smaller events, ANPP was significantly reduced by drought but not when rainfall patterns were characterized by large rain events. This interaction between drought sensitivity and rainfall event size suggests that ANPP responses to future droughts may be reduced if growing season rainfall regimes also become more extreme. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Oecologia Springer Journals

Unexpected patterns of sensitivity to drought in three semi-arid grasslands

Oecologia, Volume 169 (3) – Jan 6, 2012

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Publisher
Springer Journals
Copyright
Copyright © 2012 by Springer-Verlag
Subject
Life Sciences; Plant Sciences; Ecology
ISSN
0029-8549
eISSN
1432-1939
D.O.I.
10.1007/s00442-011-2235-2
Publisher site
See Article on Publisher Site

Abstract

Global climate models forecast an increase in the frequency and intensity of extreme weather events, including severe droughts. Based on multi-year relationships between precipitation amount and aboveground annual net primary production (ANPP), semi-arid grasslands are projected to be among the most sensitive ecosystems to changes in precipitation. To assess sensitivity to drought, as well as variability within the shortgrass steppe biome, we imposed moderate and severe rainfall reductions for two growing seasons in three undisturbed grasslands that varied in soil type and climate. We predicted strong drought-induced reductions in ANPP at all sites and greater sensitivity to drought in sites with lower average precipitation, consistent with continental-scale patterns. Identical experimental infrastructure at each site reduced growing season rainfall events by 50 or 80%, and significantly reduced average soil moisture in both years (by 21 and 46% of control levels, respectively). Despite reductions in soil moisture, ANPP responses varied unexpectedly—from no reduction in ANPP to a 51% decrease. Although sensitivity to drought was highest in the semi-arid grassland with lowest mean annual precipitation, patterns in responses to drought across these grasslands were also strongly related to rainfall event size. When growing season rainfall patterns were dominated by many smaller events, ANPP was significantly reduced by drought but not when rainfall patterns were characterized by large rain events. This interaction between drought sensitivity and rainfall event size suggests that ANPP responses to future droughts may be reduced if growing season rainfall regimes also become more extreme.

Journal

OecologiaSpringer Journals

Published: Jan 6, 2012

References

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