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ARS Home » Northeast Area » University Park, Pennsylvania » Pasture Systems & Watershed Management Research » Research » Publications at this Location » Publication #314069

Research Project: Multifunctional Farms and Landscapes to Enhance Ecosystem Services

Location: Pasture Systems & Watershed Management Research

Title: Making landscape classification relevant for agriculture

item Goslee, Sarah

Submitted to: US-International Association for Landscape Ecology
Publication Type: Abstract Only
Publication Acceptance Date: 3/3/2015
Publication Date: 7/6/2015
Citation: Goslee, S.C. 2015. Making landscape classification relevant for agriculture. US-International Association for Landscape Ecology World Congress, July 5-10, 2015, Portland, Oregon. p. 1.

Interpretive Summary:

Technical Abstract: Most regional and larger landscape classifications have focused on natural vegetation types, but these broad classifications have potential uses in agriculture as well. Defining a site type in terms of the vegetation it can support, whether natural or managed, can provide an extremely flexible framework to serve as the basis for management. A hierarchical fuzzy classification methodology based on topographic, edaphic, and climatic variables important to the ecological processes delimiting species distributions can define the potential vegetation at a site. State and transition models based on expert knowledge and simulation modeling formalize the relationships between these potential uses and management options. A team of USDA ARS and NRCS scientists and practitioners have been collaborating to identify the necessary components of an agriculturally-relevant landscape classification system. We have completed the first phase of classification for the continental United States, and have compared this classification to existing divisions such as the NRCS's Major Land Resource Area. Site type delineation within this larger continental classification is ongoing, beginning with the northeastern US and expanding westward. The combination of multivariate analysis to simplify complex quantitative data and expert knowledge to facilitate interpretation is a powerful approach to understanding agricultural landscapes and will serve as the basis for national modeling and monitoring.