Forest Management Assessment Using LASSO and the Critical List of Variables for Sustaining the Commons: Four Cases in the Monarch Reserve

Abstract

In the Monarch Reserve, four cases were selected for exploratory analysis using the critical list of variables for sustaining the commons and LASSO regression to determine which of these are most influential in the successful maintenance of forest cover over a decade. Forest recovery from degraded to dense forest is found to be inversely related to resource size, consistent with theory. However, in four other categories of forest change, the size of the resource is less influential, though it is still a significant, variable with a positive relationship to forest cover change which is inconsistent with theory. The analysis also showed that less overlap, greater poverty and lower dependence on the resource are associated both with forest gain and with mitigation of forest loss, which is contrary to theory and most research. Also associated with poverty in the LASSO regression are homogeneity of identity and ease of enforcement of rules. These show a negative relation to transitions from non-forest to dense forest, with low coefficients. This is inconsistent with theory. Possible reasons for the divergence from theory are discussed in detail, as is the utility of this approach for assessment and monitoring.