ARS | Publication request: REGION-WIDE EMPIRICAL TESTING OF STATE-AND-TRANSITION MODELS

Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: December 20, 2003
Publication Date: January 25, 2004
Citation: BESTELMEYER, B.T., BROWN, J.R., HAVSTAD, K.M., TRUJILLO, D.A. REGION-WIDE EMPIRICAL TESTING OF STATE-AND-TRANSITION MODELS. 57TH ANNUAL MEETING, SOCIETY FOR RANGE MANAGEMENT. 2004. ABSTRACT NO. 31.

Technical Abstract: Conceptual state-and-transition models for southern New Mexico were developed from literature reviews and expert opinion. These models describe patterns and causes of succession and persistent transitions in vegetation for particular ecological sites (groups of soil types), as well as indicators of the mechanisms underlying those dynamics. Propositions in state-and-transition models are difficult to test because vegetation transitions and patterns of resilience are expressed over decades in semiarid environments and because valid tests must be conducted at regional scales. We are using long-term (up to 35 yr) trend-plot photographic records and other sources of repeat photography from throughout southern New Mexico, coupled with detailed soil and landscape characterization to evaluate several predictions arising from state-and-transition models. We report evidence that (1) vegetation on fine-textured and shallow, skeletal soils is comparatively resistant and resilient, while that on fine to coarse loamy soils continues to undergo transitions, (2) transitions may be caused by contagious processes, such as sand deposition from adjacent sites, that depend on landscape context rather than local management, (3) encroaching shrub species that are featured in current state-and-transition models may not be the shrub species that will cause future transitions, and (4) subtle variations in regional climate and soil properties may have a greater impact on the probability of transition than was previously recognized. We discuss the general problem of using localized historical studies to generate region-scale forecasts in rangelands.