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Fig. 3 in Road Mortality Of Carnivores (Mammalia, Carnivora) In Belarus

Fig. 3. Seasonal dynamics of mortality rates of carnivorous mammals on national highways in Belarus, 2007– 2018.

Fig. 6. Amphibian fences with bucket-traps along T1425 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 6. Amphibian fences with bucket-traps along T1425 road section in Roztochia Nature Reserve (April, 2018).

Fig. 4 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 4. The example of degradation of amphibian breeding pond (Strilkovychi village; 49.497690 23.141543).

Fig. 3 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 3. The distribution of amphibian mortality (%) based on the distance between their breeding habitat and the nearest road section.

Fig. 5 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 5. The distribution of investigated sites under the traffic influence on amphibians on the surveyed roads of Lviv Region (green circle — low level impact, yellow — middle, red — high, white — no amphibian mortality).

Figure 1 in Can wildlife mortality on a local road tell something general? An answer from a protected area in south-western Romania

Figure 1. Study area (blue line–rivers, black line–roads, discontinuous line–Iron Gates Natural Park limits, black dots–localities, red dots–the six studied sectors on the road to Bigăr).

Figure 2 in Can wildlife mortality on a local road tell something general? An answer from a protected area in south-western Romania

Figure 2. The studied road in Sector 2 (up left) and Sector 3 (up right), and two road–killed vertebrates identified on the road: Salamandra salamandra (down left) and Talpa sp. (down right).

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Fig. 2 in Road Mortality Of Carnivores (Mammalia, Carnivora) In Belarus

Fig. 2. The species composition of carnivorous mammals died on roads in Belarus, 2007–2018.

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Fig. 1 in Road Mortality Of Carnivores (Mammalia, Carnivora) In Belarus

Fig. 1. The study area of 100×100 km in Central Western Belarus.

Fig. 2 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 2. Surveyed road sections of Lviv Region (open circles indicate sections with

Fig. 1 in Mortality Of Amphibians On The Roads Of Lviv Region (Ukraine): Trend For The Last Decade

Fig. 1. Investigated roads of Lviv Region.

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dryad36/100

Assessing changes in clusters of wildlife road mortalities after the construction wildlife mitigation structures

<p>Collisions with vehicles can be a major threat to wildlife populations, so wildlife mitigation structures, including exclusionary fencing and wildlife crossings, are often constructed. To assess mitigation structure effectiveness, it is useful to compare wildlife road mortalities (WRMs) before, during, and after mitigation structure construction; however, differences in survey methodologies may make comparisons of counts impractical. Location-based cluster analyses provide a means to assess how WRM spatial patterns have changed over time. We collected WRM data between 2015 and 2019 on State Highway 100 in Texas, USA. Five wildlife crossings and exclusionary fencing, were installed in this area between Sep 2016 and May 2018 for the endangered ocelot (Leopardus pardalis) and other similarly sized mammals. Roads intersecting State Highway 100 were mitigated by gates, wildlife guards, and wing walls. However, these structures may have provided wildlife access to the highway. We combined local hot spot analysis and time series analysis to assess how WRM cluster intensity changed after mitigation structure construction at fine spatial and temporal scales and generalized linear regression to assess how gaps in fencing and landcover were related to WRM cluster intensity in the before, during, and after construction periods. Overall, WRMs/survey day decreased after mitigation structure construction and most hot spots occurred where there were more fence gaps, and, while cluster intensity increased in a few locations, these were not at fence gaps. Cluster intensity of WRMs increased when nearer to fence gaps in naturally vegetated areas, especially forested areas, and decreased nearer to fence gaps in areas with less natural vegetation. We recommend that if fence gaps are necessary in forested areas, less permeable mitigation structures, such as gates should be used. Local hot spot analysis, coupled with time series and regression techniques, can effectively assess how WRM clustering changes over time.</p>

Figure 3 in Can wildlife mortality on a local road tell something general? An answer from a protected area in south-western Romania

Figure 3. Similarity between sectors (S1–S6–studied sectors).

Figure 4 in Can wildlife mortality on a local road tell something general? An answer from a protected area in south-western Romania

Figure 4. Similarity between periods (I–XII–studied months).

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Assessing changes in clusters of wildlife road mortalities after the construction wildlife mitigation structures

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Data from: Highway widening and underpass effects on vertebrate road mortality

Road widening (a.k.a. road dualling) and the presence of mitigation structures may have opposing effects on the number of animal-vehicle collisions. Their influence in tropical areas is poorly quantified, and we know little about how modifications of road structure affect fauna roadkill and mitigation. We evaluated how road widening and proximity to a wildlife underpass affect roadkill of medium and large mammals, using roadkill records from before and after the widening of 150 km of road with new and old wildlife underpasses. Roadkilled species were divided into three groups based on mobility and sensitivity to human disturbance. Four out of 16 species exhibited significantly higher roadkill after widening. Roadkill near underpasses was generally higher than by chance, despite our expectation of reduction of roadkills. This result indicates that we must adopt more effective mitigation measures, such as appropriate fencing combined with underpasses.

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Figure 7 in Understanding habitat suitability and road mortality for the conservation of the striped hyaena (Hyaena hyaena) in Batna (East Algeria)

Figure 7: Adult roadkilled hyaenas in Batna (Algeria) during the study period on the national road 3: (A) January, (B) December 2018, (C) October 2020, (D) December 2020 (FCB reports).

Figure 6 in Understanding habitat suitability and road mortality for the conservation of the striped hyaena (Hyaena hyaena) in Batna (East Algeria)

Figure 6: Response curves plot generated by MaxEnt that show how each environmental variable affects the MaxEnt prediction: (A) shrubland, (B) slope, (C) built-up areas, (D) distance to roads.

Figure 5 in Understanding habitat suitability and road mortality for the conservation of the striped hyaena (Hyaena hyaena) in Batna (East Algeria)

Figure 5: Jacknife test for the relative importance of environmental variables in the development of the MaxEnt model for the hyaena.

Figure 4 in Understanding habitat suitability and road mortality for the conservation of the striped hyaena (Hyaena hyaena) in Batna (East Algeria)

Figure 4: Habitat suitability for hyaena in Batna, Algeria. The model is based on occurrence records and seven environmental variables. Warmer colours represent the most suitable habitats. The probability of species occurrence ranges from 0 (unsuitable) to 1 (most suitable).