US-IALE 2018

AUTHORS: David Huggins*, USDA-ARS; Harsimran Kaur, Washington State University

ABSTRACT: Land use is a dynamic, emergent property of multiple socio-economic and bio-physical determinants and highly relevant to complex issues such as land change science, climate change and agricultural sustainability. Agro-ecological classification has primarily relied on methods that integrate multiple geo-spatial layers of relatively stable bio-physical drivers such as climate, physiography, geology, soil and native vegetation to create unique zones with specific ranges of land use constraints and potentials. We use a contrasting approach to define dynamic agro-ecological classes (AECs) based on actual land uses that have emerged as consequences of bio-physical and socio-economic drivers. Here, USDA NASS cropland datalayers (2007-2016) were employed to derive dynamic cropping system AECs of the inland Pacific Northwest and to further define the agro-ecoregion of the R.J. Cook Agronomy Farm, USDA Long Term Agro-ecosystem Research (LTAR) site. Resultant AECs are subject to annual changes as various bio-physical and socio-economic perturbations impact cropping systems. Using dynamic AECs we: (1) enable the capacity to evaluate shifts in AECs over time; (2) assess the bio-physical (e.g. climate, soils, terrain) and socio-economic factors (e.g. commodity prices) that are impacting current AECs or potential future shifts; and (3) develop AEC-relevant sustainable land use research and practices. Following development of dynamic AECs, we applied the concept to quantify empirical relationships between bio-climatic variables and the current geo-spatial distribution of six cropping system AECs. We then applied bio-climatic projections from downscaled climate models to assess geo-spatial shifts of AECs that could result from climate change. Here, projected climate change would potentially shift AECs from stable to more dynamic, resulting in more annual fallow, greater hazards for soil erosion, greater cropping system uncertainty, and less cropping system flexibility. These adverse projections are being incorporated into current research to develop climate change adaptation strategies and more sustainable agricultural systems.