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United States Department of Agriculture

Agricultural Research Service

Research Project: MANAGEMENT TECHNOLOGIES FOR ARID RANGELANDS

Location: Range Management Research

Title: State-and-transition models for heterogeneous landscapes: A strategy for development and application

Authors
item Bestelmeyer, Brandon
item Tugel, Arlene - NRCS, JORNADA
item Peacock, George - NRCS
item Robinett, Daniel - ROBINETT RANGELAND RES
item Shaver, Patrick - NRCS, OREGON
item Brown, Joel - NRCS, JORNADA
item Herrick, Jeffrey
item Sanchez, Homer - NRCS, TEXAS
item Havstad, Kris

Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: October 8, 2008
Publication Date: January 15, 2009
Repository URL: http://hdl.handle.net/10113/30040
Citation: Bestelmeyer, B.T., Tugel, A., Peacock, G.L., Robinett, D., Shaver, P.L., Brown, J., Herrick, J.E., Sanchez, H., Havstad, K.M. 2009. State-and-transition models for heterogeneous landscapes: A strategy for development and application. Rangeland Ecology and Management. 62:1-15.

Interpretive Summary: In this paper, we outline concepts and a practical approach to potential-based land classification (specifically ecological sites) and state-and-transition model (STM) development that emphasizes inventory-based data collection. The paper describes 8 sequential steps for this process. We then provide an example of how inventory data and synthesis of informal observations and the literature can be used to evalaute ecological site classes and provide support to statements in an STM.

Technical Abstract: Interpretation of assessment and monitoring data requires information about reference conditions and ecological resilience. Reference conditions used as benchmarks can be specified via potential-based land classifications (e.g., ecological sites) that describe the plant communities potentially observed in an area based on soil and climate. State-and-transition models (STMs) coupled to ecological sites can specify indicators of ecological resilience and thresholds. Although general concepts surrounding STMs and ecological sites have received increasing attention, strategies for their data-driven development have not. In this paper, we outline concepts and a practical approach to potential-based land classification and STM development. Quantification emphasizes inventory techniques readily available to natural resource professionals and that can reveal processes interacting across spatial scales. We recommend a sequence of 8 steps for the co-development of land classes and STMs including 1) creation of initial ecological site concepts and STMs based on literature and workshops; 2) extensive, low-intensity traverses to assist in generating initial concepts and to plan inventory; 3) development of a spatial hierarchy for sampling based on climate, geomorphology, and soils; 4) stratified medium-intensity inventory of plant communities and soils across a broad extent and with large sample sizes; 5) storage of plant and soil data in a database; 6) model-building and analysis of inventory data to test initial concepts; 7) support and/or refinement of concepts; and 8) high-intensity characterization and monitoring of states. Second, we offer a simple example of how data assembled via our sequence can be used to refine ecological site classes and STMs. The linkage of inventory to expert knowledge and site-based mechanistic experiments and monitoring provides a powerful means for specifying management hypotheses and, ultimately, promoting resilience in grassland, shrubland, savanna and forest ecosystems.

Last Modified: 9/10/2014
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