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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #367437
Research Project: Science and Technologies for the Sustainable Management of Western Rangeland Systems

Location: Range Management Research

Title: State-and-transition modelling

Author
item Bestelmeyer, Brandon
item FERNANDEZ GIMENEZ, MARIA - Colorado State University
item DENSAMBUU, BULGAMAA - Ministry Of Agriculture - Mongolia
item BRUEGGER, RETTA - Colorado State University

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 12/20/2020
Publication Date: 7/20/2021
Citation: Bestelmeyer, B.T., Fernández-Giménez, M., Densambuu, B., Bruegger, R. 2021. The Routledge Handbook of Research Methods for Social-Ecological Systems. Chpt 27. State and transition models. London:Routledge p.371-382.

Interpretive Summary: State-and-transition model development is described, including the use of literature review, participatory data collection, and interviews to develop models. Local knowledge is also critical to describing the causes of transitions among states. Historical ecological states and processes that may be considered as references for ecological assessment are discovered via historical profiling/assessment techniques. The characteristics of extant ecological states are identified through ecological field data collection on vegetation, soils, and sometimes animal communities. Statistical analysis, including multivariate and machine learning techniques, are used to develop and validate concepts for ecological states. Management experiments are used to test the processes involved in transitions. Spatial mapping, via automated image classification or manual polygon delineations using remotely sensed imagery, is used to map ecological states for use in management.

Technical Abstract: State-and-transition model development, as described in this chapter, relies on a suite of other methods to develop models. Science and local knowledge is synthesized and initial models developed via literature review, participatory data collection, and interviews. Local knowledge is also critical to describing the causes of transitions among states. Historical ecological states and processes that may be considered as references for ecological assessment are discovered via historical profiling/assessment techniques. The characteristics of extant ecological states are identified through ecological field data collection on vegetation, soils, and sometimes animal communities. Statistical analysis, including multivariate and machine learning techniques, are used to develop and validate concepts for ecological states. Management experiments are used to test the processes involved in transitions and for structural or functional thresholds (sensu Lopez et al. 2011, Sasaki et al. 2018). Spatial mapping, via automated image classification or manual polygon delineations using remotely sensed imagery, is used to map ecological states for use in management.