Roadkill Hotspots Research Articles

Combining roadkill hotspots and landscape features to guide mitigation measures on highways

Identifying highway sections with high vertebrate roadkill and associated landscape features is crucial for proposing mitigation measures to reduce the negative impacts of wildlife-vehicle collisions on biodiversity, human safety, and the economy. Focusing on highways in the State of Mato Grosso do Sul, Brazil, this study proposes a prioritization of road segments for implementing mitigation measures based on landscape characteristics and roadkill hotspots recorded between 2016 and 2018. Roadkills distribution was assessed using Hotspot Identification, detecting sections with the highest collision intensity. The effect of landscape variables, such as the area and distance of natural vegetation and anthropic land use within 1 km of the highways, on roadkill was modelled using General Linear Mixed Models, which were evaluated based on two response variables: (1) roadkill presence/absence and (2) roadkill abundance, with model selection by the Akaike information criterion. Based on roadkill hotspot identification analysis and predictive models of the influence of landscape elements on roadkill occurrence and abundance, an evaluation criterion was proposed to determine the priority sites for installing wildlife crossings, speed bumps, and signposts. Wildlife-vehicle collisions were positively associated with riparian vegetation areas and urban areas, while negatively associated with silviculture and distance to “cerradão” (forest Cerrado) patches. Eleven road sections were identified as top priority, two as high priority and 78 as medium priority for the installation of mitigation measures with varying cost-benefit ratios. Our results can potentially guide decision-making at broader scales and provide mitigating alternatives applicable to dry ecosystems such as the Cerrado (Brazilian Savanna).

Impact of BR-282 highway on the mortality of wild felids in the extreme west of Santa Catarina, Brazil: threat to conservation

Among human impacts, road kills are an important source of mortality for wild animals, as highways and roads result in the fragmentation of natural habitats. Felids are strongly negatively impacted and, although roads are mentioned as potential threats, few studies address how felids interact with these environments. We aimed to describe the richness and composition of wild felids, analyze the spatial and temporal effect, and identify road-kill hotspots of these species on a stretch of the BR-282 highway between the cities of São Miguel do Oeste and Paraíso, in the extreme west of the State of Santa Catarina, southern Brazil. From December 2021 to November 2022, we traveled a 28-km stretch weekly to collect data on road-killed wild felids, and at each carcass sighted, the vehicle was parked to collect information, photographs, and geographical coordinates. During this period, 26 specimens of three different species were found, viz. Leopardus guttulus (southern tiger cat), Leopardus wiedii (margay), and Herpailurus yagouaroundi (jaguarundi). In addition to the significant number of wild felids found, a hotspot for road kills of these species was identified.

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

Abstract The determination of suitable habitats and roadkill hotspots allows for the prioritization of areas of conservation and the identification of road sections that require appropriate planning and development. Understanding the factors that influence the species’ presence and those contributing to its road-related fatalities is crucial. This study demonstrates the use of MaxEnt modeling to map the potential distribution of the striped hyaena (Hyaena hyaena) in Batna province (East Algeria) using occurrence records and a set of environmental variables. The results indicated that the two primary environmental variables that influence the distribution of the species are the shrubland, and the slope with a contribution of 37.5 and 30.2 %, respectively, followed by built-up areas (12 %) and distance to roads (7.2 %). The species may occupy steep terrain with shrubland near anthropized areas. Road collisions represent a threat to the species, with 28 documented casualties from 2010 to 2020 in Batna. The kernel density estimation revealed an important roadkill hotspot along the national roads 3 and 28. This study represents a preliminary step for the use of wildlife ecological niche modeling and road management in Algeria.

An Analysis of the Effectiveness of Mitigation Measures at Roadkill Hotspots in South Korea

Collisions between wildlife and vehicles or roadkill remain a persistent issue. This poses a significant threat to the safety of both wildlife and drivers. The lack of systematically managed roadkill records poses challenges for nationwide research and comprehensive assessment in South Korea. Since 2018, the Ministry of Environment (MOE), Ministry of Land, Infrastructure and Transport (MOLIT), and National Institute of Ecology (NIE) in South Korea have been implementing roadkill investigations and management. The areas selected for roadkill mitigation measures were determined through hotspot analysis based on nationwide roadkill data collected using the Korean Roadkill Observation System (KROS), an integrated online platform. In this study, the top 50 roadkill hotspots were selected, and appropriate mitigation measures, including wildlife fences, warning signs, and speed enforcement cameras, were implemented. A total of 190.6 km of wildlife fences, 75 warning signs, and 27 speed enforcement cameras were installed. The results of these implementations revealed an average reduction in roadkill incidents of 80.2%. Subsequently, we compared and analyzed roadkill incidents before and after these mitigation measures were implemented. The comparative analysis based on hotspot grades showed that areas with lower grades had relatively lower reductions in roadkill incidents. Moreover, the study showed that the presence of multiple mitigation measures in a single area did not significantly differ from the effects of a single mitigation measure. This research will contribute to an enhanced understanding of roadkill mitigation measures and aid in preventing wildlife accidents on the road.

Hotspots and Factors Influencing Vertebrate Roadkill on the Ring Changbai Mountain Scenic Road, China

The spatial aggregation patterns of wildlife-vehicle collisions are used to inform where mitigation measures are most needed. Based on 10 years of observations of vertebrate roadkill on the Ring Changbai Mountain Scenic Road, the spatial distribution characteristics of roadkill incidence were analyzed in this study. Using the field survey method to investigate roadkill incidents and their influencing factors, we applied generalized linear mixed modeling (GLMM) for model selection and constructed roadkill models for different taxa groups. The spatial distribution patterns of roadkill hotspots vary among different taxa and exhibit a unimodal or multimodal distribution. The road section along a river and with a minimal distance between the road and the water has a high incidence of roadkill. The density of roadkill for various taxa decreases as the distances from rivers, bridges, and ponds increases. However, there appears to be no correlation between the density of bird roadkill and any factors. Finally, wildlife crossing facilities and guidance measures aimed at reducing the incidence of roadkill and enhancing the selection of routes and wildlife crossing structures in the area are formulated.

Landscape and road features linked to wildlife mortality in the Amazon

Roads impact wildlife around the world; however, dedicated studies are lacking in many biodiverse areas such as the Amazon. Identifying which species are more often hit by vehicles and which landscape and road-related features promote roadkill is essential to guide future development and ensure adequate mitigation actions. For six months, we monitored 240 km of roads in the Ecuadorian Amazon and recorded 1125 dead vertebrates (149 species). Reptiles were the most observed Class with 380 individuals (56 species), followed by amphibians with 278 individuals (11 species), birds with 259 individuals (62 species), and mammals with 208 individuals (20 species). We used Random Forest models to explore the role of various land cover types and road sinuosity on the observed mortality. Additionally, we created heatmaps to visualize the road segments where roadkills were more frequent. For all vertebrates, mortality was more likely in straight road sections near rivers. The effects of other variables were taxa-specific. Amphibian mortality was more likely near bare soil or forest, birds and mammals died more often near herbaceous-shrubby vegetation, and reptile mortality occurred more often in areas with high cover of agriculture. Road segments with high mortality (i.e., roadkill hotspots) varied across taxa. These hotspots identify areas where further research into mitigation is needed to assess road impacts and prevent collisions. Among records, we found rare and threatened species, for which road mortality could be a significant threat. Roadkill surveys not only aid in quantifying threats and informing future planning but can also provide insight into local biodiversity.

Mammalian Roadkill in a Semi-Arid Region of Brazil: Species, Landscape Patterns, Seasonality, and Hotspots

Roadkill is one of the principal causes of the loss of biodiversity around the world. The effects of roads on mammals are still poorly understood in regions with a semi-arid climate, where many knowledge gaps persist. The present study provides an inventory of the mammalian species affected on highways in northeastern Brazil, as well as identifying roadkill hotspots and contributing to the understanding of how seasonality and the landscape may influence the roadkill patterns of wild mammals. A total of 6192.52 km of road were sampled in 53 field surveys conducted between 2013 and 2017. Landsat 8 satellite images and data from the MapBiomas platform were used to classify land use and cover for analysis. Buffers of 1 km, 5 km, and 10 km were created around the study roads to identify the landscape variables associated with roadkill events. Ripley’s 2D K-Statistics and the 2D HotSpot test were used to identify roadkill aggregations and hotspots; GLMMs were generated for the landscape variables and evaluated using the Akaike Information Criterion. The Kruskal–Wallis test was applied to investigate the potential effects of seasonality. A total of 527 wild animal carcasses were recorded as a result of vehicular collision. The species with the highest roadkill records were Cerdocyon thous, Euphractus sexcinctus, and Procyon cancrivorus, while two species—Leopardus emiliae and Herpailurus yagouaroundi—are considered to be under threat of extinction. For mammals in general, the best GLMM indicated an increase in roadkills with increasing density of local vegetation areas, and a decrease as urban areas increased. The model also found that the mammals were less impacted in the vicinity of a protected area. In the specific case of C. thous, the roadkill rate was lower when urban infrastructure was more common than dense vegetation; the rate increased as areas of dense vegetation increased. In the case of P. cancrivorus and E. sexcinctus, the best models of roadkill patterns included an area of exposed soil and sparse vegetation, respectively. Roadkill rates were higher in the rainy season for all the mammals, with the exception of C. thous. These results reflect the ecological characteristics of the species with the highest roadkill rates. The findings of the present study raise concerns with regard to the impact of highways on the populations of C. thous, as well as the region’s most threatened species. They also indicate the potential functionality of the local protected area, as well as identifying roadkill hotspots, which will support the development of effective mitigation measures.

Identifying Roadkill Hotspots for Mammals in the Brazilian Atlantic Forest using a Functional Group Approach.

A critical step to design wildlife mitigating measures is the identification of roadkill hotspots. However, the effectiveness of mitigations based on roadkill hotspots depends on whether spatial aggregations are recurrent over time, spatially restricted, and most importantly, shared by species with diverse ecological and functional characteristics. We used a functional group approach to map roadkill hotspots for mammalian species along the BR-101/North RJ, a major road crossing important remnants of the Brazilian Atlantic Forest. We tested if functional groups present distinct hotspot patterns, and if they converge into the same road sectors, in that case, favoring optimal mitigating actions. Roadkill rates were monitored and recorded between October/2014 and September/2018 and species were classified into six functional groups based on their home range, body size, locomotion mode, diet, and forest-dependency. Hotspots along the roads were mapped for comparison of spatial patterns between functional groups. Results demonstrated that the roadkill index varied idiosyncratically for each functional group throughout the months and that no group presented seasonality. Seven hotspots were shared by two or more functional groups, highlighting the importance of these road stretches to regional mammal fauna. Two of the stretches are associated with aquatic areas extending from one side of the road to the other, and the remaining are connected to patches of native vegetation on both sides. This work brings a promising approach, yet hardly used in ecological studies on roads to analyze roadkill dynamics, assigning more importance to ecological instead of taxonomical characteristics, normally used to identify spatiotemporal patterns.

Identification of Emerging Roadkill Hotspots on Korean Expressways Using Space-Time Cubes.

Collisions with wild animals on high-speed expressways not only lead to roadkill but can also cause accidents that incur considerable human and economic costs. Based on roadkill data from 2004-2019 for four common wildlife species involved in collisions with vehicles on expressways in Korea (water deer, common raccoon dog, Korean hare, and wild boar), the present study conducted optimized hotspot analysis and identified spatiotemporal patterns using a space-time cube (STC) approach. Temporal and spatial differences in the roadkill data were observed between species. Water deer were the most common roadkill species of the four studied, with hotspots in the southern region of the capital area, in the Chungnam region, and in the western Chungbuk and Gangwon-do regions. However, the instances of water deer roadkill over time differed between each region. In addition, it was found that the number of cases of wild boar roadkill has increased recently. In particular, a number of new hotspot areas were observed centered on the metropolitan area Gyeonggi-do, which contains a high population and significant infrastructure. Overall, the emerging hotspot analysis based on STCs was able to determine cold spot and hotspot trends over time, allowing for a more intuitive understanding of spatiotemporal clustering patterns and associated changes than cumulative density-oriented hotspot analysis. As a result, it becomes easier to analyze the causes of roadkill and to establish reduction measures according to priority.

Perigo sob rodas: atropelamentos de mamíferos na ameaçada Mata Atlântica de baixada no sudeste do Brasil

ABSTRACT Understanding the ecological impacts of roads on mammals requires periodic monitoring of roads, and identification of both temporal and spatial distribution of roadkills (i.e., roadkill hotspots). The main aim of the study was to identify the most roadkilled mammals and evaluate the temporal and spatial distribution of roadkills in the RJ-122, a highway that crosses the threaten lowland Atlantic Forest in the state of Rio de Janeiro, southeast Brazil. Between October 2017 and January 2020, an intense monitoring study was conducted, with the carcasses of the roadkilled mammals being collected three times a week. Overall, we recorded 295 roadkilled mammals belonging to 22 species, resulting in 11 roadkills per month for the RJ-122 highway. The black-eared opossum, Didelphis aurita (N=149, 51%) stood out as the most roadkilled mammal, followed by porcupine, Coendou spinosus (N= 24, 8%), crab-eating fox, Cerdocyon thous (N= 23, 8), nine-banded armadillo, Dasypus novemcinctus (N= 23, 8%), and white-tufted marmoset, Callithrix jacchus (N= 20, 7%). Roadkills on the RJ-122 varied throughout the year, being more frequent in the rainy season (N=180) than in the dry season (N=115), and were concentrated in two hotspots, indicating some critical points with high roadkill frequency. Hotspots were associated with areas with dense natural vegetation, which can function as forest corridors in this fragmented landscape. Based on our results, several mitigation measures are recommended for the RJ-122 highway.

Vertebrates’ roadkill in the southern region of the Atlantic Forest, Paraná coast – Brazil

Being a significant global biodiversity hotspot, the Atlantic Forest has been drastically reduced by human activities. Among the anthropic activities that most affect the biodiversity of this biome is the construction and operation of roads and highways. Between harmful effects of these infrastructures, wildlife roadkill is currently considered one of the biggest causes of mortality of wild vertebrates. This study evaluated patterns of vertebrates' roadkill on two roads in the coastal region of the largest continuous remnant of the Brazilian Atlantic Forest. For twelve months, we carry out weekly samples with a motor vehicle at a constant speed of 40 km/h to search for carcasses along the roads. All carcasses found were georeferenced and identified to the lowest possible taxonomic level. Then, using Siriema v.2.0 software, we analyzed roadkill aggregation and the spatial distribution of hotspots of wildlife roadkill. In 43 sampling days, 209 road-killed animals were registered (average roadkill rate of 0.105 and 0.111 animals/kilometer/day for PR-407 e PR-508, respectively). Extrapolating the rates found, we estimate that about 1,773 animals can be roadkill every year on these roads. The most affected groups were birds (33.01%) and amphibians (30.62%), followed by reptiles (19.13%) and mammals (17.33%). Warmer months had the highest roadkill rates. We found two critical roadkill hotspots for the PR-407 (kilometer 11.7 to 12.5 and kilometer 14.7 to 16.7). For the PR-508, we found a critical point of 5.2 km (kilometer 5 to 10.2). As a short-term measure, we recommend installing speed reducers in the identified stretches and implementing environmental education campaigns with residents and tourists, especially during the summer months, aiming to mitigate the roadkill on both roads. However, due to the importance and environmental fragility of the area, we emphasize the need for running periodic road ecology and local wildlife population viability studies in the medium and long term.

History and Future Challenges of Roadkill Research in South Korea

Roadkill has been one of the most problematic issues with wildlife under urbanization. South Korea, one of the fastest industrializing countries in the world, has been affected by the same roadkill issues and has researched how to mitigate wildlife–vehicle collisions (WVCs). In the present study, we aimed to (i) review scientific studies concerning roadkill conducted in South Korea (51 domestic, 15 international papers, 19 reports, and 1 thesis), (ii) compare bibliographic networks between international and South Korean roadkill studies, and (iii) discuss future challenges. From a search in the core collection of Web of Science peer-reviewed papers published from 1992 to 2022, keywords were extracted to create a bibliometric visualization map, using VOSviewer. Among the 85 articles related to WVCs, those about eco-corridors have steadily increased since 1998, while mitigation system and roadkill articles have been published since the mid-2000s. With increased awareness, more systems have been established, and research related to WVCs has been increasingly established. Currently, there are two systematic roadkill monitoring systems in South Korea, and an increasing number of modeling studies have suggested where roadkill hotspots are located. How to mitigate roadkill incidents has also been explored. A comparison of associations between international and Korean research shows that the network structures of Korean society were more disconnected and less dispersed. In addition, the keywords were narrower than those used in studies from the international community. Although studies on landscape connectivity and road ecology are few, their number and scope in South Korea have increased and broadened. These studies could be more rapidly developed in the future as some systems are equipped.

Hotspots and Season Related to Wildlife Roadkill in the Amazonia–Cerrado Transition

The construction of new roads opens access to native environments, resulting in changes to the landscape. These roads cause the death of native wildlife due to collisions with vehicles, which is the main cause of human-induced vertebrate death. This work aimed to investigate the spatial distribution of roadkills on the BR-163 highway, Mato Grosso, Brazil, an Amazonia–Cerrado transition zone, to identify roadkill hotspots. The study area consisted of 244 km of road. Twenty-five trips were made totaling 6100 km of surveyed roadway between 2008 and 2011. A total of 1005 individuals from 65 species was recorded in this study. Mammals were the most affected, both in number of individuals and species, followed by birds, reptiles, and amphibians. The species with the highest roadkill rates were Cerdocyon thous and Tyto furcata. Identified endangered mammals included Myrmecophaga tridactyla, Chrysocyon brachyurus, Priodontes maximus, Speothos venaticus, Tapirus terrestris, Pteronura brasiliensis, and Ateles marginatus. The highest rates of roadkill were recorded during the wet season. The location and number of hotspots varied among classes and were related to different environmental variables such as waterbodies, forest fragments, and agricultural areas. Roadkills may be a major threat for vulnerable species and should therefore be studied to define conservation plans for local species and road traffic.

Identification of roadkill hotspots and the factors affecting wombat vehicle collisions using the citizen science tool, WomSAT

Roads directly impact wildlife through vehicle collisions. In Australia only a few studies have examined the impact of environmental characteristics on wombat roadkill. We analysed wombat roadkills reported into WomSAT, a website and application where citizen scientists can upload sightings of wombats, to map wombat roadkill across their distribution. We used Maxent software to identify the main factors influencing wombat roadkill hotspots. A total of 2391 wombat deaths on roads were reported by 567 citizen scientists from 2015 to 2019. More wombat roadkill deaths occurred in winter, with most unaffected by sarcoptic mange. The average daily solar exposure, distance to populated areas, precipitation of warmest quarter (bio 18), temperature seasonality (bio 4), and precipitation seasonality (bio 15) were identified as the main factors influencing wombat roadkill. The most roadkills reported per kilometre (3.7/km) occurred on Old Bega Road and Steeple Flat Road, in the New South Wales southern tablelands. Reduced reporting corresponded with a reduced number of citizen scientists continuing to report sightings over time, reflecting the limitations of the data collected by citizen scientists. However, data should continue to be collected by citizen scientists as it is an easy and low-cost method of collecting data over large areas, and can provide information to managers to support conservation efforts directed at reducing roadkill. Our study emphasises the need to continue to engage and reward citizen scientists for their efforts.

Modelling of road-kill hotspots in steppe landscape in Turkey

Modelling of road-kill hotspots in steppe landscape in Turkey

Monitoring the use of a canopy bridge and underpasses by arboreal mammals on a Brazilian coastal road

Abstract Roads disrupt the canopy and can affect arboreal animals in different ways, such as reducing canopy connectivity, generating habitat loss and degradation, and increasing direct mortality. Since arboreal animals mainly use the canopy for movement, mitigation measures for these species usually focus on maintaining or restoring canopy connectivity to guarantee safe crossings. Here we present a case study of a Brazilian coastal road (ES-060) for which we described the use of a canopy bridge and multiple underpasses by three arboreal mammal species and compared these data with roadkill records of the same species in the vicinity of the crossing structures. Our study includes a 75 m long steel cable canopy bridge, monitored for 3 years, and clusters of different types of underpasses, monitored for 16 years. The use of the crossing structures was monitored with sand track beds installed at entrances on both sides, and roadkill surveys were conducted daily for 16 years. We considered a crossing to be successful if tracks of the same species were recorded on either side of a structure and showed opposite movement trajectories. The canopy bridge survey resulted in an observed rate of 0.16 crossings/month for Callithrix geoffroyi, 7.79 for Coendou insidiosus, and 0.46 for Didelphis aurita, and all types of underpasses combined demonstrated a rate of 0.33, 1.94, and 8.43 crossings/month for each species, respectively. The roadkill surveys resulted in an observed rate of 1.41, 0.78, 2.94 roadkills/month for Callithrix geoffroyi, Coendou insidiosus, and Didelphis aurita, respectively. Even with mitigation structures confirmed to be used by these three species, roadkill hotspots occurred in the road sections with the crossing structures. Our study demonstrated the use of a canopy bridge and different types of underpasses by arboreal mammal species. The canopy bridge was mostly used by Coendou insidiosus, while the underpasses were mainly used by Didelphis aurita. As roadkill hotspots occurred red in the same segments where mitigation crossing structures were installed, our results indicate that some important improvements are needed to mitigate roadkills of arboreal mammals in this area, mainly preventing that these species access the road. We present recommendations for a research agenda to support mitigation planning for arboreal mammals, namely: (1) testing the efficiency of different canopy bridge designs for multispecies mitigation, (2) testing the use of connecting structures, such as ropes that connect to the surrounding forest, to encourage underpass use by arboreal species, and (3) testing fence adaptations to block the access of arboreal mammals to roads.

Roadkill risk for capybaras in an urban environment

Wildlife vehicle-collision is one of the most visible negative effects that roads exerts on animals and has increased dramatically across the world. Despite its conspicuousness, studies about roadkills in cities have been neglected lacking in road ecology. We developed new approach for estimating capybara roadkill hotspots in Campo Grande, a big city in Brazil. We also investigated potential driving factors correlated with roadkill occurrence, to build a predictive roadkill map for the entire city and propose mitigation measures. We monitored capybara roadkills for thirteen years and found hotspots using a graph-based kernel density estimation. We tested four predictors to identify which characteristics influence roadkill occurrence: distance from water bodies, distance from parks, vegetation cover, and traffic flow. We used a generalized linear mixed model to test for significant effects and to predict roadkill occurrences. Hotspots analysis showed four hotspots surrounding large green areas and water bodies, probably due to capybara habitat and physiological requirements. The predictive map shows latent hotspots, locations that have the characteristics necessary for a capybara to live but where we do not have observed deaths. To mitigate risk, we recommend using speed reduction tools around parks. A decrease in capybaras roadkills could positively impact human population welfare and material damage caused by these collisions.

Predicting spatial and seasonal patterns of wildlife–vehicle collisions in high-risk areas

Context Vehicle collisions with wildlife can injure or kill animals, threaten human safety, and threaten the viability of rare species. This has led to a focus in road-ecology research on identifying the key predictors of ‘road-kill’ risk, with the goal of guiding management to mitigate its impact. However, because of the complex and context-dependent nature of the causes of risk exposure, modelling road-kill data in ways that yield consistent recommendations has proven challenging. Aim Here we used a multi-model machine-learning approach to identify the spatio-temporal predictors, such as traffic volume, road shape, surrounding vegetation and distance to human settlements, associated with road-kill risk. Methods We collected data on the location, identity and wildlife body size of each road mortality across four seasons along eight roads in southern Tasmania, a ‘road-kill hotspot’ of management concern. We focused on three large-bodied and frequently affected crepuscular Australian marsupial herbivore species, the rufous-bellied pademelon (Thylogale billardierii), Bennett’s wallaby (Macropus rufogriseus) and the bare-nosed wombat (Vombatus ursinus). We fit the point-location data using ‘lasso-regularisation’ of a logistic generalised linear model (LL-GLM) and out-of-bag optimisation of a decision-tree-based ‘random forests’ (RF) algorithm for optimised predictions. Results The RF model, with high-level feature interactions, yielded superior out-of-sample prediction results to the linear additive model, with a RF classification accuracy of 84.8% for the 871 road-kill observations and a true skill statistic of 0.708, compared with 61.2% and 0.205 for the LL-GLM. The lasso rejected road visibility and human density, ranking roadside vegetation type and presence of barrier fencing as the most influential predictors of road-kill locality. Conclusions Forested areas with no roadside barrier fence along curved sections of road posed the highest risk to animals. Seasonally, the frequency of wildlife–vehicle collisions increased notably for females during oestrus, when they were more dispersive and so had a higher encounter rate with roads. Implications These findings illustrate the value of using a combination of attributive and predictive modelling using machine learning to rank and interpret a complexity of possible predictors of road-kill risk, as well as offering a guide to practical management interventions that can mitigate road-related hazards.

WILDLIFE ROADKILL IN THE SURROUNDINGS OF EMAS NATIONAL PARK, CERRADO BIOME, BRAZIL

Roadkill is a serious threat to biodiversity conservation especially when roads are near natural habitats of wildlife, such as the Emas National Park (ENP), a Protected Area in Mid-west Brazil in the Cerrado Biome. We aimed to identify the species killed on a stretch of the GO-341 highway that is tangent to the ENP. We investigated if roadkills were influenced by seasonality, sugar cane harvest and by the activity pattern of the animals (diurnal/nocturnal). We also analyzed if roadkills were aggregated in space, where the roadkill hotspots were located, if they were influenced by seasonality, and if they were different for the most abundant species. The highway was monitored with a vehicle, in the morning, at a speed of 40 to 60 km/hour, daily, with two observers. We covered a total of 4,230 km during the 90-day monitoring period, which included dry and rainy seasons. We recorded 132 wild animals’ roadkills: 67 birds (51 %), 60 mammals (45 %) and 5 reptiles (4 %). We identified 22 vertebrate species, including 13 birds, six mammals and three reptiles. The roadkill rate was 0.03 animals/km/day. During the dry season, the blue-and-yellow macaw (Ara ararauna) had higher roadkill rates. The crab-eating fox (Cerdocyon thous) was the only species with higher roadkill rates during the sugarcane harvest. Most birds killed had diurnal habits, for mammals, no difference was observed concerning the activity pattern. Bird roadkills were aggregated considering the entire data set, as well as for the dry and rainy seasons separately. Mammal roadkills were aggregated only when considering the entire data set. The location of bird roadkill hotspots differed between seasons. The roadkill hotspot location of birds and mammals highly overlapped those observed for the two most abundant species of these taxa, respectively, Ara ararauna and Euphractus sexcinctus.

Roadkill-Data-Based Identification and Ranking of Mammal Habitats

Wildlife–vehicle collisions, as well as environmental factors that affect collisions and mitigation measures, are usually modelled and analysed in the vicinity of or within roads, while habitat attractiveness to wildlife along with risk to drivers remain mostly underestimated. The main goal of this study was the identification, characterisation, and ranking of mammalian habitats in Lithuania in relation to 2002–2017 roadkill data. We identified habitat patches as areas (varying from 1 to 1488 square kilometres) isolated by neighbouring roads characterised by at least one wildlife–vehicle collision hotspot. We ranked all identified habitats on the basis of land cover, the presence of an ecological corridor, a mammalian pathway, and roadkill hotspot data. A ranking scenario describing both habitat attractiveness to wildlife and the risk to drivers was defined and applied. Ranks for each habitat were calculated using multiple criteria spatial decision support techniques. Multiple regression analyses were used to identify the relationship between habitat ranks, species richness, and land cover classes. Strong relationships were identified and are discussed between the habitat patch ranks in five (out of 28) land cover classes and in eight (out of 28) species (97% of all mammal road kills). We conclude that, along with conventional roadkill hotspot identification, roadkill-based habitat identification and characterisation as well as species richness analysis should be used in road safety infrastructure planning.