Modern disturbances to a long-lasting community-based resource management system: The Taos Valley acequias

Long-lasting community-based resource management systems have offered scholars important lessons in the study of human-environment relations. The examination of such systems has suffered from a sampling bias, however, in that it has focused disproportionately on successful systems. There are fewer studies that have explored the deterioration of such systems, particularly with an interdisciplinary approach. This shortfall is problematic given the increasing social and biophysical disturbances that communities are facing as they become more integrated into, and affected by, larger-scale processes.This study addresses this gap by analyzing the modern condition of a long-lasting community-based irrigation system known as the acequias in northern New Mexico. Using a mix of interview, survey, remote sensing, and census data, I examine the extent to which important indicators for the acequias have shifted in the last several decades and explore reasons for these changes. A mix of statistical and qualitative comparative techniques is used to conduct the analysis.By examining longitudinal data we find that the acequias are producing less than they have in the past and have mostly lost their common-property-based livestock pasturing system. While some of these changes can be attributed to similar declines in water availability, much of the change results from social drivers including demographic changes, regional-to-global market forces, and public policies. Overall the shift of the acequias to their current state is a result of their integration into a much larger-scale set of social and economic forces than they have experienced in the past. This shift will be very difficult to reverse, meaning the acequia farmers must adapt to the current condition. It is likely that these themes are common across many community-based resource management systems in many locations. In the future, further progress should be made in synthetically comparing such cases in ways that have already been done for long-lasting successful systems.