Co-management agreements among indigenous people, state agencies, and other stakeholders offer substantial promise as a way of dealing with natural resource conflicts in a participatory and equitable manner. However, experience shows that co-management regimes can set into motion new conflicts or cause old ones to escalate. In practice the result may not be power sharing but rather a strengthening of the state's control over resource policy, management, and allocation. Instead of contributing to local empowerment, such arrangements may further marginalize communities and resource users. We use case material, primarily from northern Canada and South Asia, to explore the pervasive role of conflict in generating, shaping, and influencing the performance of co-management regimes. The paper analyzes the divergent interests and motives of state agencies in planning and implementing co-management arrangements. It highlights the cultural, political, and legal obstacles encountered by indigenous people and other rural communities in trying to negotiate co-management arrangements. We also explore the conflicts that can arise in co-management regimes where local participation in decision making is very limited. General lessons and recommendations are drawn from our analysis.

Drug trafficking is taking a toll on Central America's biodiverse forests.

No abstract

Counterdrug interdiction efforts designed to seize or disrupt cocaine shipments between South American source zones and US markets remain a core US “supply side” drug policy and national security strategy. However, despite a long history of US-led interdiction efforts in the Western Hemisphere, cocaine movements to the United States through Central America, or “narco-trafficking,” continue to rise. Here, we developed a spatially explicit agent-based model (ABM), called “NarcoLogic,” of narco-trafficker operational decision making in response to interdiction forces to investigate the root causes of interdiction ineffectiveness across space and time. The central premise tested was that spatial proliferation and resiliency of narco-trafficking are not a consequence of ineffective interdiction, but rather part and natural consequence of interdiction itself. Model development relied on multiple theoretical perspectives, empirical studies, media reports, and the authors’ own years of field research in the region. Parameterization and validation used the best available, authoritative data source for illicit cocaine flows. Despite inherently biased, unreliable, and/or incomplete data of a clandestine phenomenon, the model compellingly reproduced the “cat-and-mouse” dynamic between narco-traffickers and interdiction forces others have qualitatively described. The model produced qualitatively accurate and quantitatively realistic spatial and temporal patterns of cocaine trafficking in response to interdiction events. The NarcoLogic model offers a much-needed, evidence-based tool for the robust assessment of different drug policy scenarios, and their likely impact on trafficker behavior and the many collateral damages associated with the militarized war on drugs.

A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential 'narco-capitalized' signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country-and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F ¼ 9.90, p ¼ 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio ¼ 2.98, p ¼ 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.