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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #345318
Title: A conceptual model of agroecosystem function as a basis for synthesis

Author
item Bestelmeyer, Brandon
item Spiegal, Sheri
item Strickland, Timothy
item SWAIN, HILARY - Archbold Biological Station
item BOUGHTON, RAOUL - University Of Florida
item BOUGHTON, ELIZABETH - Macarthur Agro-Ecology Research Center

Submitted to: Agronomy Society of America, Crop Science Society of America, Soil Science Society of America Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 6/1/2017
Publication Date: 10/22/2017
Citation: Bestelmeyer, B.T., Spiegal, S.A., Strickland, T.C., Swain, H., Boughton, R., Boughton, E. 2017. A conceptual model of agroecosystem function as a basis for synthesis [abstract]. Agronomy Society of America, Crop Science Society of America, Soil Science Society of America Meeting. October 22-25, 2017, Tampa, Florida, pg. 258-3.

Interpretive Summary:

Technical Abstract: A primary challenge for LTAR is to organize information about sustainable agricultural intensification such that it can be synthesized across multiple research programs addressing disparate problems. Such synthesis facilitates not only regional to national-scale generalizations to inform the public and policy, but also provides a platform for agricultural researchers to collaborate, learn from one another’s research traditions and tools, and identify previously unrecognized research needs. In this talk, we describe a conceptual model of agroecosystem function that identifies fundamental interactions between agriculture, environment, and society. The model focuses on agricultural producers and their decisions in selecting a production system. Feedback loops mediated by environmental effects, economics, societal factors, and policies can reinforce the status quo or prompt producers to adopt an alternative production system. External shocks (drivers and perturbations that are unaffected by feedbacks) can also tip the system into alternative production states. The model was used effectively as a basis for organizing interactions within production systems into questions and predictions. These questions served as the basis for an LTAR-wide survey and synthesis described in a companion talk.