H51Q-04
Forecasting Regional Agroecosystems Responses to Drought and Wet Periods using Long Term Data from LTAR and LTER sites
Friday, 18 December 2015: 08:45
3011 (Moscone West)
Debra P C Peters1,2, Jin Yao3, Nathan D. Burruss3, Kris Havstad2, Osvaldo E Sala4, Justin D Derner5, John Hendrickson6, Matt Sanderson6, John Blair7, Scott L Collins8, Laureano Gherardi4, Patrick j Starks9 and Jean L. Steiner9, (1)USDA Washington DC, Washington, DC, United States, (2)USDA ARS, Las Cruces, NM, United States, (3)New Mexico State University Main Campus, Las Cruces, NM, United States, (4)Arizona State University, School of Life Sciences, Tempe, AZ, United States, (5)USDA ARS, Northern Plains Regional Climate Hub, Cheyenne, WY, United States, (6)USDA ARS, Northern Great Plains Research Lab, Mandan, ND, United States, (7)Kansas State University, Manhattan, KS, United States, (8)University of New Mexico Main Campus, Albuquerque, NM, United States, (9)USDA-ARS, El Reno, OK, United States
Abstract:
Long-term research networks of sites (LTAR, LTER) provide natural experiments for agroecosystem responses that occurred historically during multi-year drought or wet periods (>=4 y) that can be used to make predictions about dynamics under future climate scenarios. We used long-term data (12 to > 50y) of aboveground net primary production (ANPP) and rainfall from eight sites in the central grasslands region of the U.S. to test three alternative hypotheses. We hypothesized that ANPP in wet (or drought) periods can be best explained by: (1) long-term relationships between ANPP and precipitation, (2) relationships between ANPP and precipitation in individual wet or dry years, or (3) relationships between ANPP and precipitation in wet or dry periods of years. We compared regression slopes and r2 values among equations at each site to determine the relationship with the best fit. For most sites, the equation developed using ANPP and precipitation during drought periods was a better predictor of ANPP during drought compared with the long-term equation, and the drought period equation had a steeper slope than the long-term equation. In wet periods at the southern sites, the number of wet years in a row was a better predictor of ANPP than the amount of precipitation during the wet period. Cumulative processes, including plant-soil water feedbacks, sequential plant population processes, and plant or soil legacies may be operating to influence these temporal dynamics. These equations based on long-term data relating ANPP to precipitation during multi-year drought or number of wet years can be used to improve future predictions of agroecosystem dynamics under directional changes in climate. Synthesizing similar data from multiple sites and networks (LTAR, LTER) was necessary to capture the temporal variability and spatial heterogeneity across this large region.
