摘要
Understanding the complex dynamics of social-ecological systems (SES) is difficult because rigorous methodologies and methods for this purpose are lacking. Multi-scale (temporal and geographical) linkages and pathways can mask feedbacks. Thus, understanding SES requires multi-dimensional analyses. This study presents a potential methodology and method for multi-dimensional analyses of a SES in the Upper Rio Grande-San Luis Valley (URG-SLV), Colorado. A driver identification process identified 5 major drivers in the URG-SLV, including stream flow, climate, agriculture, and endogenous and exogenous policy. Several of these drivers possessed more than one longitude. Data for these drivers begins as early as 1852 and extends to 2007. Changes in driver longitudes (long-term datasets within a single driver; maximum, minimum and mean annual temperature comprise climate longitudes) were detected via change point analysis, occurring at several transitional points. Linkages were defined using known relationships between drivers (e.g., stream flow and water rights). Cross-scale relationships between the URG-SLV and downstream users through policy changes and climate also presented a temporal cross-scale linkage. Using the relationships and cross-scale linkages, a historical evolution of the system was constructed throughout the 150-plus years of record to illustrate the effects of changes in drivers and cross-scale linkages in the system.