Modeling cocaine traffickers and counterdrug interdiction forces as a complex adaptive system.

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.

Targeted reforestation could reverse declines in connectivity for understory birds in a tropical habitat corridor.

Re-establishing connectivity between protected areas isolated by habitat clearing is a key conservation goal in the humid tropics. In northeastern Costa Rica, payments for environmental services (PES) and a government ban on deforestation have subsidized forest protection and reforestation in the San Juan-La Selva Biological Corridor (SJLSBC), resulting in a decline in mature forest loss and the expansion of tree plantations. We use field studies and graph models to assess how conservation efforts have altered functional connectivity over the last 25 years for four species of insectivorous understory birds. Field playback studies assessed how reforestation habitat quality affected the willingness of Myrmeciza exsul, Henicorhina leucosticta, Thamnophilus atrinucha, and Glyphorynchus spirurus to travel outside forest habitat for territorial defense. Observed travel distances were greatest in nonnative and native tree plantations with high understory stem density, regardless of overstory composition. In contrast, tree plantations with low stem density had travel responses comparable to open pasture for three of the four bird species. We modeled landscape connectivity for each species using graph models based on varying possible travel distances in tree plantations, gallery forests, and pastures. From 1986 to 2011, connectivity for all species declined in the SJLSBC landscape (5825 km2 ) by 14% to 21% despite only a 4.9% net loss in forest area and the rapid expansion of tree plantations over 2% of the landscape. Plantation placement in the landscape limited their potential facilitation of connectivity because they were located either far from forest cover or within already contiguous forest areas. We mapped current connectivity bottlenecks and identified priority areas for future reforestation. We estimate that reforestation of priority areas could improve connectivity by 2% with only a 1% gain in forest cover, an impressive gain given the small area reforested. Results indicate key locations where spatial targeting of PES within the SJLSBC study region would protect existing forest connectivity and enhance the connectivity benefits of reforestation.

Climate change and ecosystem shifts in the southwestern United States.

Climate change shifts ecosystems, altering their compositions and instigating transitions, making climate change the predominant driver of ecosystem instability. Land management agencies experience these climatic effects on ecosystems they administer yet lack applied information to inform mitigation. We address this gap, explaining ecosystem shifts by building relationships between the historical locations of 22 ecosystems (c. 2000) and abiotic data (1970-2000; bioclimate, terrain) within the southwestern United States using 'ensemble' machine learning models. These relationships identify the conditions required for establishing and maintaining southwestern ecosystems (i.e., ecosystem suitability). We projected these historical relationships to mid (2041-2060) and end-of-century (2081-2100) periods using CMIP6 generation BCC-CSM2-MR and GFDL-ESM4 climate models with SSP3-7.0 and SSP5-8.5 emission scenarios. This procedure reveals how ecosystems shift, as suitability typically increases in area (~ 50% (~ 40% SD)), elevation (12-15%) and northing (4-6%) by mid-century. We illustrate where and when ecosystems shift, by mapping suitability predictions temporally and within 52,565 properties (e.g., Federal, State, Tribal). All properties had ≥ 50% changes in suitability for ≥ 1 ecosystem within them, irrespective of size (≥ 16.7 km2). We integrated 9 climate models to quantify predictive uncertainty and exemplify its relevance. Agencies must manage ecosystem shifts transcending jurisdictions. Effective mitigation requires collective action heretofore rarely instituted. Our procedure supplies the climatic context to inform their decisions.

An iterative and targeted sampling design informed by habitat suitability models for detecting focal plant species over extensive areas.

Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives.