Ungulate use of non-wildlife underpasses.

Wildlife crossing structures can provide safe passage for wildlife across transportation corridors, and can help mitigate the effects of highways and exclusion fencing on wildlife. Due to their costs, wildlife crossing structures are usually installed sparsely and at strategic locations along transportation networks. Alternatively, non-wildlife underpasses (i.e. conventional underpasses for human and domestic animal use) are usually abundant along major infrastructure corridors and could potentially provide safe crossing opportunities for wildlife. To investigate this, we monitored the use of 40 non-wildlife underpasses by roe deer (Capreolus capreolus), and moose (Alces alces) in south-central Sweden. We found that roe deer and moose use non-wildlife underpasses, and prefer underpasses that are at least 11.5 m wide and 5 m tall. Furthermore, roe deer used structures that had little human co-use and were in locations where the forest cover differed on both sides of the highway. In most cases, roe deer and moose were detected within 50 m of the underpass more than they were detected crossing under them. This suggests that animals often approach underpasses without crossing under them, however modifications to underpass design may improve non-wildlife underpass use. We recommend non-wildlife underpasses at gravel and minor roads, particularly those with little human co-use and with variable forest cover on both sides of the highway, be built wider than 11.5 m and taller than 5 m.

Mortandad de vertebrados por atropellos en carreteras en Tambogrande, Piura, Perú / Vertebrates road-killed in Tambogrande, Piura, Peru

Resumen Entre los impactos negativos sobre la biodiversidad que causan las obras viales, como las carreteras, se tiene la mortandad de fauna por atropello. En el presente estudio se determina la mortandad de anfibios, reptiles, aves y mamíferos por atropello, en tres carreteras que confluyen en el distrito de Tambogrande (Piura en el norte de Perú) y establecer los sitios de mayor incidencia. Los datos se colectaron entre enero y junio de 2018 en 24 recorridos una vez por semana entre las 7:00 y 14:00 horas. Los recorridos se realizaron sobre una moto lineal a 25 km/h, los datos registrados fueron coordenadas geográficas del punto de atropello principalmente. La mortandad de vertebrados en los transectos se analizó usando el Índice Kilométrico de Abundancia. Los sitios de alta incidencia de atropellos se determinaron con un análisis de densidad de Kernel. Se hallaron 437 animales atropellados pertenecientes a 29 especies. Los animales atropellados más abundantes fueron los mamíferos seguidos de aves, reptiles y anfibios. El IKA promedio fue de 0.2 (IC 95% 0.1 - 0.3) N° de atropellos/Km. Se presentaron 24 puntos de alta incidencia en el área de estudio cercanos entre sí. Utilizando la información de este trabajo se sugiere construir ocho pasos de fauna para vertebrados según estándares internacionales y complementados con señalética adecuada.

Abstract Among the negative impacts on biodiversity caused by road works, such as road and highways, are the killed caused by collisions with vehicles. In this study, the mortality of amphibians, reptiles, birds and mammals by collision with vehicles is determined, on three roads that converge in the Tambogrande district (Piura in northern Peru), and the places with the highest incidence are established. Observations were between January and June of 2018 with a frequency of 24 trips once a week between the hours of 7.00 and 14.00. The trips were taken on a motorcycle at 25 km/h. Geographical coordinates of the point of collisions were recorded. The vertebrates mortality in transects lines was analyzed using the Kilometric Abundance Index (KAI). High incidence places were determined with a Kernel Density Analysis. 437 animals were found dead corresponding to 29 species. The animal group most affected was mammals followed by birds, reptiles and amphibians in that order. The mean KAI was 0.2 (95% CI 0.1 - 0.3) N° of incidences/km. We determinate 24 points of high incidence, they were close to each other. Based in our results, we propose to build eight animal crossing structures for vertebrates complemented with appropriate transit signals.

Demographic connectivity for ursid populations at wildlife crossing structures in Banff National Park.

Wildlife crossing structures are one solution to mitigating the fragmentation of wildlife populations caused by roads, but their effectiveness in providing connectivity has only been superficially evaluated. Hundreds of grizzly (Ursus arctos) and black bear (Ursus americanus) passages through under and overpasses have been recorded in Banff National Park, Alberta, Canada. However, the ability of crossing structures to allow individual and population-level movements across road networks remains unknown. In April 2006, we initiated a 3-year investigation into whether crossing structures provide demographic connectivity for grizzly and black bears in Banff National Park. We collected hair with multiple noninvasive methods to obtain genetic samples from grizzly and black bears around the Bow Valley. Our objectives were to determine the number of male and female grizzly and black bears that use crossing structures; examine spatial and temporal patterns of crossings; and estimate the proportions of grizzly and black bear populations in the Bow Valley that use crossing structures. Fifteen grizzly (7 female, 8 male) and 17 black bears (8 female, 9 male) used wildlife crossing structures. The number of individuals detected at wildlife crossing structures was highly correlated with the number of passages in space and time. Grizzly bears used open crossing structures (e.g., overpasses) more often than constricted crossings (e.g., culverts). Peak use of crossing structures for both bear species occurred in July, when high rates of foraging activity coincide with mating season. We compared the number of bears that used crossings with estimates of population abundance from a related study and determined that substantial percentages of grizzly (15.0% in 2006, 19.8% in 2008) and black bear (17.6% in 2006, 11.0% in 2008) populations used crossing structures. On the basis of our results, we concluded wildlife crossing structures provide demographic connectivity for bear populations in Banff National Park.

Evaluating the intersection of a regional wildlife connectivity network with highways.

BACKGROUND: Reliable predictions of regional-scale population connectivity are needed to prioritize conservation actions. However, there have been few examples of regional connectivity models that are empirically derived and validated. The central goals of this paper were to (1) evaluate the effectiveness of factorial least cost path corridor mapping on an empirical resistance surface in reflecting the frequency of highway crossings by American black bear, (2) predict the location and predicted intensity of use of movement corridors for American black bear, and (3) identify where these corridors cross major highways and rank the intensity of these crossings. RESULTS: We used factorial least cost path modeling coupled with resistant kernel analysis to predict a network of movement corridors across a 30.2 million hectare analysis area in Montana and Idaho, USA. Factorial least cost path corridor mapping was associated with the locations of actual bear highway crossings. We identified corridor-highway intersections and ranked these based on corridor strength. We found that a major wildlife crossing overpass structure was located close to one of the most intense predicted corridors, and that the vast majority of the predicted corridor network was "protected" under federal management. However, narrow, linear corridors connecting the Greater Yellowstone Ecosystem to the rest of the analysis area had limited protection by federal ownership, making these additionally vulnerable to habitat loss and fragmentation. CONCLUSIONS: Factorial least cost path modeling coupled with resistant kernel analysis provides detailed, synoptic information about connectivity across populations that vary in distribution and density in complex landscapes. Specifically, our results could be used to quantify the structure of the connectivity network, identify critical linkage nodes and core areas, map potential barriers and fracture zones, and prioritize locations for mitigation, restoration and conservation actions.