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Carbon exchange responses of a mesic grassland to an extreme gradient of precipitation

Author:
Felton, Andrew J., Knapp, Alan K., Smith, Melinda D.
Source:
Oecologia 2019 v.189 no.3 pp. 565-576
ISSN:
0029-8549
Subject:
atmospheric precipitation, carbon, ecosystems, grasslands, growing season, meteorological data, models, net primary productivity, soil respiration, soil water, uncertainty
Abstract:
Growing evidence indicates that ecosystem processes may be differentially sensitive to dry versus wet years, and that current understanding of how precipitation affects ecosystem processes may not be predictive of responses to extremes. In an experiment within a mesic grassland, we addressed this uncertainty by assessing responses of two key carbon exchange processes—aboveground net primary production (ANPP) and soil respiration (Rₛ)—to an extensive gradient of growing season precipitation. This gradient comprised 11 levels that specifically included extreme values in precipitation; defined as the 1st, 5th, 95th, and 99th percentiles of the 112-year climate record. Across treatments, our experimental precipitation gradient linearly increased soil moisture availability in the rooting zone (upper 20 cm). Relative to ANPP under nominal precipitation amounts (defined as between the 15th and 85th percentiles), the magnitude of ANPP responses were greatest to extreme increases in precipitation, with an underlying linear response to both precipitation and soil moisture gradients. By contrast, Rₛ exhibited marginally greater responses to dry versus wet extremes, with a saturating relationship best explaining responses of Rₛ to both precipitation and soil moisture. Our findings indicate a linear relationship between ANPP and precipitation after incorporating responses to precipitation extremes in the ANPP–precipitation relationship, yet in contrast saturating responses of Rₛ. As a result, current linear ANPP–precipitation relationships (up to ~ 1000 mm) within mesic grasslands appear to hold as appropriate benchmarks for ecosystems models, yet such models should incorporate nonlinearities in responses of Rₛ amid increased frequencies and magnitudes of precipitation extremes.
Agid:
6326325