4.8 Article

Effect of precipitation variability on net primary production and soil respiration in a Chihuahuan Desert grassland

Journal

GLOBAL CHANGE BIOLOGY
Volume 17, Issue 4, Pages 1505-1515

Publisher

WILEY
DOI: 10.1111/j.1365-2486.2010.02363.x

Keywords

carbon cycle; desert grasslands; leaf gas exchange; precipitation variability; primary production; soil respiration

Funding

  1. University of New Mexico
  2. NSF [DEB-0620482]
  3. DoE NICCR
  4. Div Of Biological Infrastructure
  5. Direct For Biological Sciences [0934263] Funding Source: National Science Foundation

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Precipitation regimes are predicted to become more variable with more extreme rainfall events punctuated by longer intervening dry periods. Water-limited ecosystems are likely to be highly responsive to altered precipitation regimes. The bucket model predicts that increased precipitation variability will reduce soil moisture stress and increase primary productivity and soil respiration in aridland ecosystems. To test this hypothesis, we experimentally altered the size and frequency of precipitation events during the summer monsoon (July through September) in 2007 and 2008 in a northern Chihuahuan Desert grassland in central New Mexico, USA. Treatments included (1) ambient rain, (2) ambient rain plus one 20 mm rain event each month, and (3) ambient rain plus four 5 mm rain events each month. Throughout two monsoon seasons, we measured soil temperature, soil moisture content (theta), soil respiration (R-s), along with leaf-level photosynthesis (A(net)), predawn leaf water potential (Psi(pd)), and seasonal aboveground net primary productivity (ANPP) of the dominant C-4 grass, Bouteloua eriopoda. Treatment plots receiving a single large rainfall event each month maintained significantly higher seasonal soil theta which corresponded with a significant increase in R-s and ANPP of B. eriopoda when compared with plots receiving multiple small events. Because the strength of these patterns differed between years, we propose a modification of the bucket model in which both the mean and variance of soil water change as a consequence of interannual variability from 1 year to the next. Our results demonstrate that aridland ecosystems are highly sensitive to increased precipitation variability, and that more extreme precipitation events will likely have a positive impact on some aridland ecosystem processes important for the carbon cycle.

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