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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #319263
Title: Forecasting regional grassland and shrubland responses to directional changes in climate using multi-year dry or wet periods

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: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/13/2015
Publication Date: 8/30/2015
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. Forecasting regional grassland and shrubland responses to directional changes in climate using multi-year dry or wet periods [abstract]. LTER 2015 All Scientists meeting, August 30 - September 2, 2015, Estes Park, CO.

Interpretive Summary:

Technical Abstract: Ecologists are being challenged to predict ecosystem responses under changing climatic conditions. Although air temperatures are increasing, the magnitude and direction of change in precipitation (increase or decrease) are uncertain for many sites. Given that water availability is the primary driver of ecosystem processes in temperate grasslands and shrublands, these uncertainties in precipitation mean that ecologists must account for both possibilities. Long-term research sites (LTER, LTAR) provide natural experiments for ecological responses that occurred historically during multi-year drought or wet periods 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 seven sites in North America where precipitation showed sequences (> 3 years) 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 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 or the equation using individual dry years. 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 rainfall 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 drought or number of wet years can be used to explain historic patterns, such as the 1930s drought or unusual grass recovery patterns, as well as improve future predictions under directional climate change.