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Title: Can we use the past as a lens to the future? Using historic events to predict regional grassland and shrubland responses to multi-year drought or wet periods under climate change

Author
item Peters, Debra
item YAO, JIN - New Mexico State University
item BURRUSS, N. DYLAN - New Mexico State University
item Havstad, Kris
item SALA, OSVALDO - Arizona State University
item Derner, Justin
item Hendrickson, John
item Sanderson, Matt
item BLAIR, JOHN - Kansas State University
item COLLINS, SCOTT - University Of New Mexico

Submitted to: Ecological Society of America Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 4/20/2015
Publication Date: 8/9/2015
Citation: Peters, D.C., Yao, J., Burruss, N., Havstad, K.M., Sala, O., Derner, J.D., Hendrickson, J.R., Sanderson, M.A., Blair, J.M., Collins, S.L. 2015. Can we use the past as a lens to the future? Using historic events to predict regional grassland and shrubland responses to multi-year drought or wet periods under climate change [abstract}. 100th Annual Meeting of the Ecological Society of America (ESA). August 9-14, 2015. Baltimore, MD. COS 5-5.

Interpretive Summary:

Technical Abstract: Background/Question/Methods Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, but uncertainty in the magnitude and direction of change in precipitation (increase or decrease) at site to regional scales reduces the predictive capacity to determine future trends with robust levels of acceptable risk for land managers. Long-term research networks of sites (LTER, LTAR) provide natural experiments for system responses that occurred historically during multi-year drought or wet periods (>=4 y) that can be used to make predictions under future climate scenarios. We tested three alternative hypotheses using long-term data (12 to > 50y) of aboveground net primary production (ANPP) from eight sites in North America where precipitation showed sequences of wet periods, multi-year drought, and no trend years. 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. We compared regression slopes and r2 values among equations at each site to determine the relationship with the best fit. For most sites across the region, the equation developed using ANPP and precipitation during drought periods was a better predictor of ANPP during drought compared with the long-term equation. In addition, the drought period equation had a steeper slope than the long-term equation. Thus, approaches that use long-term ANPP-precipitation relationships to predict ANPP during multi-year drought will result in over-estimates of ANPP. In contrast, in wet periods at some 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 relating ANPP to precipitation during multi-year drought or number of wet years can be used to explain historic patterns, such as the during the 1930s drought or unusual grass recovery patterns, as well as to improve future predictions under directional climate change.