We examined the evolution of four public wildlife management issues using theories from collective action, social networks, and social constructionism to understand key roles and perspectives among stakeholders engaged in collective actions related to wildlife management policies. We conducted semi-structured telephone interviews with 50 key stakeholders in four communities in New York State that experienced collective stakeholder interactions in the contexts of waterfowl hunting or wildlife trapping.

This article describes the use of a Bayesian network (BN) for the classification of land cover from satellite imagery in northern Swaziland. The main objective of this work was to apply and evaluate the efficacy of a BN for land-cover classification using gap-filled and terrain-corrected Landsat 7 Enhanced Thematic Mapper Plus (ETM+) imagery acquired on 15 May 2007. The posterior probabilities (parameters) were estimated using the expectation-maximization (EM) and conjugate gradient descent (CGD) algorithms.

We assessed past and present vegetation patterns in relation to land use on a municipal commonage in South Africa. We asked specifically whether the reassignment of the commonage for the use of historically disadvantaged town residents after 1994 has impacted negatively on the vegetation of the commonage. Analysis of land cover change using aerial photography time series revealed that the most significant human impacts on the Bathurst commonage occurred prior to 1942 due to heavy and uncontrolled communal land use.