Wednesday, August 6, 2008

PS 50-157: Social-biophysical feedbacks and land change in an arid rangeland region

Brandon T. Bestelmeyer, USDA-ARS Jornada Experimental Range and Rhonda K. Skaggs, New Mexico State University.

Background/Question/Methods

Studies of human-dominated ecosystems have traditionally externalized human agents and their behavior. Rangelands of the southwestern U.S. are no exception: in spite of century-long studies of vegetation change, the specific role of human decisions and their feedbacks with land condition are unknown. It is likely that prevention of future land degradation as well as opportunities for restoration will depend largely on our ability to manipulate these feedbacks. To support this perspective, we undertook a region-scale study of the relationships between the geophysical setting, land condition, and the history and current attributes of Bureau of Land Management (BLM) grazing allotments in south-central New Mexico. National Cooperative Soil Survey soil maps coupled to Ecological Site Descriptions were used to characterize the geophysical setting and inherent resilience, expert-supported, remote-sensed maps of vegetation states were used to characterize land condition, and BLM allotment records were used to characterize human dimensions variables including frequency of allotment turnover, the sense of impermanence, agency conflict, ranch type (trophy or dependent family) and management type (cautious vs. incautious). BLM allotment polygons were then attributed with human dimensions and geophysical/land condition data for analysis.

Results/Conclusions

We found evidence for spatial autocorrelation in turnover frequency and impermanence and a positive association between turnover and impermanence. Turnover was associated with non-resilient soil types. Allotments characterized by high turnover and impermanence had higher percentage composition of degraded states than others, and this relationship was contingent on soil type. The results suggest that there may be systematic relationships between the biophysical and human social characteristics of landscapes, and that quantification of these relationships may facilitate a predictive understanding of social-ecological dynamics.