Multiscale consensus habitat modeling for landscape level conservation prioritization.

Globally, wide-ranging carnivore populations are imperiled due to human-caused habitat fragmentation. Where populations are fragmented, habitat quantification is often the first step in conservation. Presence-only species distribution models can provide robust results when proper scales and data are considered. We aimed to identify habitat for a fragmented carnivore population at two scales and aid conservation prioritization by identifying potential future habitat fragmentation. We used location data and environmental variables to develop a consensus model using Maxent and Mahalanobis distance to identify black bear (Ursus americanus floridanus) habitat across Florida, USA. We compared areas of habitat to areas of predicted sea level rise, development, and protected areas. Local-scale models performed better than state-scale models. We identified 23,798 km2 of habitat at the local-scale and 45,703 km2 at the state-scale. Approximately 10% of state- and 14% of local-scale habitat may be inundated by 2100, 16% of state- and 7% of local-scale habitat may be developed, and 54% of state- and 15% of local-scale habitat is unprotected. Results suggest habitat is at risk of fragmentation. Lack of focused conservation and connectivity among bear subpopulations could further fragmentation, and ultimately threaten population stability as seen in other fragmented carnivore populations globally.

The road to deforestation: Edge effects in an endemic ecosystem in Sumatra, Indonesia.

Worldwide, roads are a main driver of deforestation and degradation as they increase forest access along the forest edge. In many tropical areas, unofficial roads go unreported and unrecorded, resulting in inaccurate estimates of intact forested areas. This is the case in central Sumatra, which boasts populations of critically endangered Sumatran elephants (Elephas maximus sumatrensis), tigers (Panthera tigris sumatrae) and other endemic flora and fauna that make the area globally unique. However, maps do not reflect the reality of forest loss in the area. Here we present new maps from 2002 and 2016 of digitized and ground-truthed roads in one of Sumatra's unique lowland tropical protected areas, Tesso Nilo National Park. Using our newly created roads dataset, we examine the distribution of forest with respect to distance to roads. Our data show >2,400 km of roads within the national park in 2016 -nearly a 10-fold increase from roads known in 2002. Most forest (82-99%) within Tesso Nilo falls within 100 m, 500 m, and 1000 m of road edges. Length of road increased 157% and road density increased from 1.06 km/km2 to 2.63 km/km2 from 2002-2016. Our results suggest that this endemic ecosystem is facing substantial threat from roads and their associated impacts. Without swift management action, such as road closures and increased enforcements by park management, this ecosystem, and its endemic wildlife, could be lost. It is imperative that protected areas worldwide more rigorously consider roads and road effects on ecosystem fragmentation in their conservation plans.

Mapping and predicting forest loss in a Sumatran tiger landscape from 2002 to 2050.

Riau Province in central Sumatra, with its peatland, lowland, and montane forest habitats, was once a stronghold for Sumatran tiger (Panthera tigris sumatrae) populations. Today, Riau may have one of the highest deforestation rates in the world and wildlife populations are dwindling, with natural forest now comprising approximately only 18% of the province, mostly contained within protected areas. Agriculture (acacia, rubber, and oil palm) makes up the majority of Riau's land cover and deforestation for the creation of new plantations is rampant. Natural forest and tigers still remain in Bukit Tigapuluh National Park and Rimbang Baling Wildlife Reserve, which remain connected to tiger populations in montane forest on the western edge of Sumatra. In this study, using freely available Landsat imagery and a maximum likelihood classification algorithm, we create land cover maps for central Sumatra from 2002 to 2016. We then use current land cover, elevation, and slope variables to predict changes from forest to plantation from 2016 to 2050 at five year intervals using a multilayer perceptron neural network. Finally, we compare connectivity based on a 100 km distance threshold (based on potential tiger dispersal) across the landscape and across years. Land cover maps had 80-90% accuracy, and we predict forest in Tesso Nilo and the western edge of the study area to be lost by 2050 given current rates of deforestation. Our connectivity analysis shows that Tesso Nilo and the area between Rimbang Baling and Bukit Tigapuluh are important components for maintaining connectivity throughout the study area. Focusing conservation and rehabilitation efforts on forests close to plantations in flat areas, including Tesso Nilo, is necessary to maintain forests and increase connectivity in Riau to ensure future habitat connectivity for survival of tigers and Sumatra's other diverse endemic species.

Three Portraits, 2 Artists, and 1 Harvard Department of Anaesthesia: the Brigham Chairs and the Artists Who Rendered Them.

BACKGROUND: Many forms of art accurately depict physical attributes of their subjects. But how precisely do portraits capture personal, emotional, and behavioral aspects of individuals holding leadership positions in academic departments of anesthesiology? METHODS: We examined formal portraits of the first three academic chairmen of anesthesiology in our department - Leroy D. Vandam, Benjamin G. Covino, and Simon Gelman and obtained information about the artists (George Augusta and Marc Klionsky) regarding how they conducted research on their subjects, and the methods they used to depict significant character traits into their art. We then correlated the artistic depiction with known biographical and behavioral qualities of these leaders. RESULTS: We found that the artists were remarkably astute in their observations and that they successfully captured both physical and emotional aspects of these chairmen in their portraits. Moreover, in one instance, significant early life experiences were added to the composition with subtlety. Individuals familiar with these chairmen and aware of their management style can easily appreciate the techniques employed by the artists. SUMMARY: We conclude that art successfully depicted personal and executive attributes of these three academic anesthesia chairmen.

Modeling fence location and density at a regional scale for use in wildlife management.

Barbed and woven wire fences, common structures across western North America, act as impediments to wildlife movements. In particular, fencing influences pronghorn (Antilocapra americana) daily and seasonal movements, as well as modifying habitat selection. Because of fencing's impacts to pronghorn and other wildlife, it is a potentially important factor in both wildlife movement and habitat selection models. At this time, no geospatial fencing data is available at regional scales. Consequently, we constructed a regional fence model using a series of land tenure assumptions for the Hi-Line region of northern Montana--an area consisting of 13 counties over 103,400 km(2). Randomized 3.2 km long transects (n = 738) on both paved and unpaved roads were driven to collect information on habitat, fence densities and fence type. Using GIS, we constructed a fence location and a density model incorporating ownership, size, neighboring parcels, township boundaries and roads. Local knowledge of land ownership and land use assisted in improving the final models. We predict there is greater than 263,300 km of fencing in the Hi-Line region, with a maximum density of 6.8 km of fencing per km(2) and mean density of 2.4 km of fencing per km(2). Using field data to assess model accuracy, Cohen's Kappa was measured at 0.40. On-the-ground fence modification or removal could be prioritized by identifying high fence densities in critical wildlife areas such as pronghorn migratory pathways or sage grouse lekking habitat. Such novel fence data can assist wildlife and land managers to assess effects of anthropogenic features to wildlife at various scales; which in turn may help conserve declining grassland species and overall ecological functionality.

Comparing habitat suitability and connectivity modeling methods for conserving pronghorn migrations.

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.