Quantifying population-level conservation impacts for a perpetual conservation program on private land.

Area-based targets, such as percentages of regions protected, are popular metrics of success in the protection of nature. While easily quantified, these targets can be uninformative about the effectiveness of conservation interventions and should be complemented by program impact evaluations. However, most impact evaluations have examined the effect of protected areas on deforestation. Studies that have extended these evaluations to more dynamic systems or different outcomes are less common, largely due to data availability. In these cases, simulations might prove to be a valuable tool for gaining an understanding of the potential range of program effect sizes. Here, we employ simulations of wetland drainage to estimate the impact of the United States Fish and Wildlife Service Small Wetlands Acquisition Program (SWAP) across a ten-year period in terms of wetland area, and breeding waterfowl and brood abundance in the Prairie Pothole Region of North Dakota, South Dakota, and Montana. Using our simulation results, we estimate a plausible range of program impact for the SWAP as an avoided loss of between 0.00% and 0.02% of the carrying capacity for broods and breeding waterfowl from 2008-2017. Despite the low programmatic impact that these results suggest, the perpetual nature of SWAP governance provides promising potential for a higher cumulative conservation impact in the long term if future wetland drainage occurs.

Geographical analysis of the distribution of certified genetic counselors in the United States.

The number of certified genetic counselors (CGCs) in the genetic counseling workforce has increased over the past few decades as the number of training programs increases and CGCs expand into new patient-facing and non-patient-facing roles. Few studies have explored the distribution of CGCs across the United States. We sought to identify the U.S. geographical regions with the highest number of CGCs and those regions where the physical presence of CGCs is sparser. Deidentified city, state, and ZIP code information for each CGC in the United States were obtained from the American Board of Genetic Counseling (ABGC) database. A countrywide analysis of the distribution of CGCs was completed using geographic information system (GIS) mapping software. The data were organized into U.S. metropolitan or micropolitan statistical areas, if applicable, and analyzed by CGC per capita. We included a total of 4,554 data points (92.2%) in the analysis. Results showed there is one CGC for every 71,842 people nationwide. Of 3,141 total counties (or county equivalents) in the United States, 535 counties had at least one CGC (17.0%). The majority (98.7%) of CGCs live or work within metropolitan statistical areas (MSAs), which are defined by this study as geographical areas with greater than 50,000 people. Of the MSAs with a CGC, approximately half have more than one CGC per 100,000 people. These results are consistent with the overall distribution of the U.S. population. We believe that the MSAs with the most CGCs per capita are due to associations with specific institutions, that is, genetic counseling training programs, health system headquarters, or genetic laboratories. Although the present study cannot draw definite conclusions regarding direct patient care services provided by CGCs, it does provide a snapshot of current CGC distribution within the country. Knowing the distribution of CGCs provides a tool to conduct further workforce analyses to determine the number of CGCs needed to serve the U.S. population.

Multi-scale habitat assessment of pronghorn migration routes.

We studied the habitat selection of pronghorn (Antilocapra americana) during seasonal migration; an important period in an animal's annual cycle associated with broad-scale movements. We further decompose our understanding of migration habitat itself as the product of both broad- and fine-scale behavioral decisions and take a multi-scale approach to assess pronghorn spring and fall migration across the transboundary Northern Sagebrush Steppe region. We used a hierarchical habitat selection framework to assess a suite of natural and anthropogenic features that have been shown to influence selection patterns of pronghorn at both broad (migratory neighborhood) and fine (migratory pathway) scales. We then combined single-scale predictions into a scale-integrated step selection function (ISSF) map to assess its effectiveness in predicting migration route habitat. During spring, pronghorn selected for native grasslands, areas of high forage productivity (NDVI), and avoided human activity (i.e., roads and oil and natural gas wells). During fall, pronghorn selected for native grasslands, larger streams and rivers, and avoided roads. We detected avoidance of paved roads, unpaved roads, and wells at broad spatial scales, but no response to these features at fine scales. In other words, migratory pronghorn responded more strongly to anthropogenic features when selecting a broad neighborhood through which to migrate than when selecting individual steps along their migratory pathway. Our results demonstrate that scales of migratory route selection are hierarchically nested within each other from broader (second-order) to finer scales (third-order). In addition, we found other variables during particular migratory periods (i.e., native grasslands in spring) were selected for across scales indicating their importance for pronghorn. The mapping of ungulate migration habitat is a topic of high conservation relevance. In some applications, corridors are mapped according to telemetry location data from a sample of animals, with the assumption that the sample adequately represents habitat for the entire population. Our use of multi-scale modelling to predict resource selection during migration shows promise and may offer another relevant alternative for use in future conservation planning and land management decisions where telemetry-based sampling is unavailable or incomplete.

Rural Health Networks and Care Coordination: Health Care Innovation in Frontier Communities to Improve Patient Outcomes and Reduce Health Care Costs.

Rural residents' health is challenged by high health care costs, chronic diseases, and policy decisions affecting rural health care. This single-case, embedded design study, guided by community-based participatory research principles and using mixed methods, describes outcomes of implementation of a community care team (CCT) and care coordination to improve outcomes of patients living in a frontier community. Seventeen organizations and 165 adults identified as potential care coordination candidates constituted the target populations. Following CCT development, collaboration and cohesion increased among organizations. Patients who participated in care coordination reported similar physical and lower emotional health quality of life than national counterparts; emergency department use decreased following care coordination. Key components identified as successful in urban settings seem applicable in rural settings, with emphasis on the key role of team facilitators; need for intense care coordination for people with complex health needs, especially behavioral health needs; and access to specialty care through technology.

Wind and wildlife in the Northern Great Plains: identifying low-impact areas for wind development.

Wind energy offers the potential to reduce carbon emissions while increasing energy independence and bolstering economic development. However, wind energy has a larger land footprint per Gigawatt (GW) than most other forms of energy production and has known and predicted adverse effects on wildlife. The Northern Great Plains (NGP) is home both to some of the world's best wind resources and to remaining temperate grasslands, the most converted and least protected ecological system on the planet. Thus, appropriate siting and mitigation of wind development is particularly important in this region. Steering energy development to disturbed lands with low wildlife value rather than placing new developments within large and intact habitats would reduce impacts to wildlife. Goals for wind energy development in the NGP are roughly 30 GW of nameplate capacity by 2030. Our analyses demonstrate that there are large areas where wind development would likely have few additional impacts on wildlife. We estimate there are ∼1,056 GW of potential wind energy available across the NGP on areas likely to have low-impact for biodiversity, over 35 times development goals. New policies and approaches will be required to guide wind energy development to low-impact areas.