Skip to main content
ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #171301

Title: APPLICATIONS OF MULTI- AND CROSS-SCALE ANALYSES TO MANAGEMENT OF DYNAMIC SYSTEMS

Author
item Bestelmeyer, Brandon
item Herrick, Jeffrey - Jeff
item Havstad, Kris
item Frederickson, Eddie
item BROWN, JOEL - USDA-NRCS

Submitted to: Chihuahuan Desert Symposium
Publication Type: Abstract Only
Publication Acceptance Date: 10/1/2004
Publication Date: 10/15/2004
Citation: Bestelmeyer, B.T., Herrick, J.E., Havstad, K.M., Fredrickson, E.L., Brown, J.R. 2004. Applications of multi- and cross-scale analyses to management of dynamic systems [abstract]. Sixth Symposium on the Natural Resources of the Chihuahuan Desert Region, October 14-17, 2004, Alpine, Texas. p. 19.

Interpretive Summary:

Technical Abstract: Decades of research on the management and monitoring of Chihuahuan Desert grasslands have emphasized (1) fine-scale patterns, (2) uniformity of dominant processes, and thus (3) standard, vegetation-based protocols for directing and measuring change. Although this was a necessary step, alone it is an insufficient approach to detecting and responding to degradation. We describe recent conceptual and empirical approaches to measuring the variety of pattern and process in vegetation transition based on soil-geomorphic-climate relationships, multiple scales of vegetation/soil pattern, and cross-scale interactions among grass loss in patches, patch connectivity and flux regulation, and climate-forcing functions. These approaches are being used to develop and refine tools that classify different pathways of vegetation response (state-and-transition models) according to soil and climate variables (ecological site descriptions). Pathways featuring cross-scale interactions can explain irreversible and nonlinear rates of change in time and space. These interactions indicate that different processes drive change at particular times and spatial locations, even within same vegetation type. Identification of the dominant processes governing vegetation change indicates the spatial pattern of change. In turn, this pattern indicates the appropriate scale and strategy for monitoring and designing and implementing management responses.