Roadkill Hotspots Research Articles

Testing the Value of Citizen Science for Roadkill Studies: A Case Study from South Africa

Roads impact wildlife through a range of mechanisms from habitat loss and decreased landscape connectivity to direct mortality through wildlife-vehicle collisions (roadkill). These collisions have been rated amongst the highest modern risks to wildlife. With the development of ‘citizen science’ projects, in which members of the public participate in data collection, it is now possible to monitor the impacts of roads over scales far beyond the limit of traditional studies. However, the reliability of data provided by citizen scientists for roadkill studies remains largely untested. This study used a dataset of 2 666 roadkill reports on national and regional roads in South Africa (total length ~170 000 km) over three years. We first compared roadkill data collected from trained road patrols operating on a major highway with data submitted by citizen scientists on the same road section (431 km). We found that despite minor differences, the broad spatial and taxonomic patterns were similar between trained reporters and untrained citizen scientists. We then compared data provided by two groups of citizen scientists across South Africa: 1) those working in the zoology/conservation sector (that we have termed ‘regular observers’, whose reports were considered to be more accurate due to their knowledge and experience), and 2) occasional observers, whose reports required verification by an expert. Again, there were few differences between the type of roadkill report provided by regular and occasional reporters; both types identified the same area (or cluster) where roadkill was reported most frequently. However, occasional observers tended to report charismatic and easily identifiable species more often than road patrols or regular observers. We conclude that citizen scientists can provide reliable data for roadkill studies when it comes to identifying general patterns and high-risk areas. Thus, citizen science has the potential to be a valuable tool for identifying potential roadkill hotspots and at-risk species across large spatial and temporal scales that are otherwise impractical and expensive when using standard data collection methodologies. This tool allows researchers to extract data and focus their efforts on potential areas and species of concern, with the ultimate goal of implementing effective roadkill-reduction measures.

ROAD AND LANDSCAPE FEATURES THAT AFFECT BAT ROADKILLS IN SOUTHEASTERN BRAZIL

The most studied impact on road ecology is roadkill, however, there is little information about the relations between highways and specific groups like bats. This study intended to identify the species of bats roadkilled and to evaluate the existence of temporal fluctuation between the roadkill rates, specific stretches of the road with higher rates, and characteristics of the road/landscape that may influence those rates. We encountered at least nine bat species among 65 roadkills (most Phyllostomidae), which comprise a subgroup of the local fauna that presents ecologic features that make them susceptible to being hit, especially Artibeus lituratus. The medium roadkill rate was of 0.01 individuals/km/day of monitoring, and there was no significant temporal variation. We identified five hotspots through special 2D HotSpot Identification Analysis. The selection of theoretical models through Generalized Linear Models showed that roadkill occurrence has a positive relation with vehicular traffic and negative relation with presence of marginal pasture and forests. As the major part of records was of species that are tolerant to human-disturbances, the increase in traffic consequently affected a higher number of bats capable to explore the area occupied by the road. The presence of native forest close to the road can lead to a decrease of animals hit by vehicles, once it offers more resources and favorable habitats, which reduces the need for bats to cross the roads for foraging. On the other hand, many species that necessarily depend on areas sheltered by trees for shelter, and do not possess the ability to fly long distances do not occur in open areas such as pastures. In this context, we suggest that the main measure of mitigation regard bat species would be the traffic control through speed limit, especially on the roadkill hotspots areas.

Reptile road-kills in Southern Brazil: Composition, hot moments and hotspots

Understanding road-kill patterns is the first step to assess the potential effects of road mortality on wildlife populations, as well as to define the need for mitigation and support its planning. Reptiles are one of the vertebrate groups most affected by roads through vehicle collisions, both because they are intentionally killed by drivers, and due to their biological needs, such as thermoregulation, which make them more prone to collisions. We conducted monthly road surveys (33months), searching for carcasses of freshwater turtles, lizards, and snakes on a 277-km stretch of BR-101 road in Southernmost Brazil to estimate road-kill composition and magnitude and to describe the main periods and locations of road-kills. We modeled the distribution of road-kills in space according to land cover classes and local traffic volume. Considering the detection capacity of our method and carcass persistence probability, we estimated that 15,377 reptiles are road-killed per year (55reptiles/km/year). Road-kills, especially lizards and snakes, were concentrated during summer, probably due to their higher activity in this period. Road-kill hotspots were coincident among freshwater turtles, lizards, and snakes. Road-kill distribution was negatively related to pine plantations, and positively related to rice plantations and traffic volume. A cost-benefit analysis highlighted that if mitigation measures were installed at road-kill hotspots, which correspond to 21% of the road, they could have avoided up to 45% of recorded reptile fatalities, assuming a 100% mitigation effectiveness. Given the congruent patterns found for all three taxa, the same mitigation measures could be used to minimize the impacts of collision on local herpetofauna.

Compassionate approaches for the conservation and protection of fire salamanders

The Near Eastern fire salamander, Salamandra infraimmaculata, is considered an endangered species in Israel and is near-threatened regionally. For 25 years, our laboratory has sought ethical sampling methods to protect individuals and populations of Salamandra. To “mark” individuals for estimating dispersal and population size, we use non-invasive individual-specific markings from photographs of larvae and adults. We demonstrated through mesocosm experiments (which are less mortality-driven than in nature) that exotic Gambusia affinis have extreme negative mortality effects on Salamandra larvae. From a compassionate conservation aspect, G. affinis should not be killed and placed in habitats where amphibians are not in danger and mosquitoes can be controlled. We identified breeding-site characteristics demonstrating that permanent breeding sites support larger adult populations than temporary breeding sites. For population genetics studies, we take minimal sized tail tips from adults (which have no adverse effects) for microsatellite data. For gene expression studies, rather than sacrifice entire bodies, we demonstrated that by taking only small larval tail tips, we could follow gene expression. We additionally demonstrated that tail tip removal does not affect survival, time to or size at metamorphosis. We documented high road kill rates at a specific breeding site. To prevent potential disease spread, we sterilize boots and sampling gear. We use results for implementing or recommending conservation of individuals and populations – e.g., identifying: movement corridors for breeding site dispersal; roadkill hotspots for under-road tunnels; suitable habitat for pool construction for more effective conservation; utilizing population genetics for recommending management units; information on demography and genetic diversity to identify hotspots for conservation; removal of Gambusia for amphibian protection.

Amphibian and reptile road-kills on tertiary roads in relation to landscape structure: using a citizen science approach with open-access land cover data

BackgroundAmphibians and reptiles are among the most endangered vertebrate species worldwide. However, little is known how they are affected by road-kills on tertiary roads and whether the surrounding landscape structure can explain road-kill patterns. The aim of our study was to examine the applicability of open-access remote sensing data for a large-scale citizen science approach to describe spatial patterns of road-killed amphibians and reptiles on tertiary roads. Using a citizen science app we monitored road-kills of amphibians and reptiles along 97.5 km of tertiary roads covering agricultural, municipal and interurban roads as well as cycling paths in eastern Austria over two seasons. Surrounding landscape was assessed using open access land cover classes for the region (Coordination of Information on the Environment, CORINE). Hotspot analysis was performed using kernel density estimation (KDE+). Relations between land cover classes and amphibian and reptile road-kills were analysed with conditional probabilities and general linear models (GLM). We also estimated the potential cost-efficiency of a large scale citizen science monitoring project.ResultsWe recorded 180 amphibian and 72 reptile road-kills comprising eight species mainly occurring on agricultural roads. KDE+ analyses revealed a significant clustering of road-killed amphibians and reptiles, which is an important information for authorities aiming to mitigate road-kills. Overall, hotspots of amphibian and reptile road-kills were next to the land cover classes arable land, suburban areas and vineyards. Conditional probabilities and GLMs identified road-kills especially next to preferred habitats of green toad, common toad and grass snake, the most often found road-killed species. A citizen science approach appeared to be more cost-efficient than monitoring by professional researchers only when more than 400 km of road are monitored.ConclusionsOur findings showed that freely available remote sensing data in combination with a citizen science approach would be a cost-efficient method aiming to identify and monitor road-kill hotspots of amphibians and reptiles on a larger scale.

Using DNA barcode to relate landscape attributes to small vertebrate roadkill

Large vertebrates are the main focus of roadkill studies because their greater size facilitates taxonomic identification and the collection of statistical data. However, these studies fail to effectively include and identify small vertebrates and correlate roadkill events with the surrounding landscape. Here we showed the effectiveness of molecular data to identify small vertebrate roadkill, and we correlated landscape structure attributes with the location of roadkill for functional groups of varying mobility. The extraction of DNA from roadkilled individuals was followed by the amplification of two mitochondrial genes. We compared each DNA sequence to a database and used the highest similarity values for species identification. The species were classified according to their taxa and degree of mobility: birds, reptilia and amphibia with low and intermediate movement capability. After calculating the landscape attributes for each roadkill point, we used a competing model approach based on Akaike Information Criteria to determine which landscape variable best explained the occurrence of roadkills. Combining molecular and morphological characteristics, we identified 82.93% of the roadkilled animals. DNA barcoding allowed the identification of 310% more specimens than by morphological characteristics alone. Roadkilled birds with intermediate movement capability were strongly influenced by dominated areas by agriculture and sugar cane monocultures. Roadkilled reptiles with low movement capability were positively correlated with the presence of forest remnants, while those with intermediate movement capability seemed to be more frequent in heavily anthropized landscapes. We showed that molecular data is a powerful tool for precisely identifying small-sized roadkilled animals. Our results also highlight that different landscape structure attributes enable the prediction of roadkill occurrence along roads, which in turn allows us to identify roadkill hotspots and plan appropriate mitigation actions.

Roadkill hotspots in a protected area of Cerrado in Brazil: planning actions to conservation

Objective. Here we aimed to identify the main points of animal death by roadkill in the view of helping mitigation plans and reducing the impact over the local fauna of a protected area. Materials and methods. We surveyed the roads around a protected area of Cerrado (São Paulo, Brazil) from May 2012 to August 2013. We recorded the local of roadkills, biometric and morphologic data of the animals, and collected samples of tissue for molecular species confirmation. Results. Thirty-one roadkilled animals were registered, including threatened species: Leopardus pardalis; Cuniculus paca and Chrysocyon brachyurus. Most roadkills were represented by mammals (54.8%) and reptiles (38.7%), and the mortality rate was 1.46 animals/km/year. Three roadkill hotspots were detected, suggesting that they were important points of animal crossing, probably because of the existence of natural remnant vegetation and intersection of roads by riparian vegetation. Conclusions. This work provided strong evidence of the most critical points where mitigation strategies should be immediately implemented and highlighted the importance of detecting roadkill hotspots and the species or taxonomic groups more affected, helping to elaborate effective actions that can improve fauna conservation.

ANALYZE THE IMPACT OF HABITAT PATCHES ON WILDLIFE ROAD-KILL

Abstract. The ecosystem fragmentation due to transportation infrastructure causes a road-kill phenomenon. When making policies for mitigating road-kill it is important to select target-species in order to enhance its efficiency. However, many wildlife crossing structures have been questioned regarding their effectiveness due to lack of considerations such as target-species selection, site selection, management, etc. The purpose of this study is to analyse the impact of habitat patches on wildlife road-kill and to suggest that spatial location of habitat patches should be considered as one of the important factors when making policies for mitigating road-kill. Habitat patches were presumed from habitat variables and a suitability index on target-species that was chosen by literature review. The road-kill hotspot was calculated using Getis-Ord Gi*. After that, we performed a correlation analysis between Gi Z-score and the distance from habitat patches to the roads. As a result, there is a low negative correlation between two variables and it increases the Gi Z-score if the habitat patches and the roads become closer.

Sampling effects on the identification of roadkill hotspots: Implications for survey design

Although locating wildlife roadkill hotspots is essential to mitigate road impacts, the influence of study design on hotspot identification remains uncertain. We evaluated how sampling frequency affects the accuracy of hotspot identification, using a dataset of vertebrate roadkills (n = 4427) recorded over a year of daily surveys along 37 km of roads. “True” hotspots were identified using this baseline dataset, as the 500-m segments where the number of road-killed vertebrates exceeded the upper 95% confidence limit of the mean, assuming a Poisson distribution of road-kills per segment. “Estimated” hotspots were identified likewise, using datasets representing progressively lower sampling frequencies, which were produced by extracting data from the baseline dataset at appropriate time intervals (1–30 days). Overall, 24.3% of segments were “true” hotspots, concentrating 40.4% of roadkills. For different groups, “true” hotspots accounted from 6.8% (bats) to 29.7% (small birds) of road segments, concentrating from <40% (frogs and toads, snakes) to >60% (lizards, lagomorphs, carnivores) of roadkills. Spatial congruence between “true” and “estimated” hotspots declined rapidly with increasing time interval between surveys, due primarily to increasing false negatives (i.e., missing “true” hotspots). There were also false positives (i.e., wrong “estimated” hotspots), particularly at low sampling frequencies. Spatial accuracy decay with increasing time interval between surveys was higher for smaller-bodied (amphibians, reptiles, small birds, small mammals) than for larger-bodied species (birds of prey, hedgehogs, lagomorphs, carnivores). Results suggest that widely used surveys at weekly or longer intervals may produce poor estimates of roadkill hotspots, particularly for small-bodied species. Surveying daily or at two-day intervals may be required to achieve high accuracy in hotspot identification for multiple species.

Citizen science and smartphones take roadkill monitoring to the next level

Road networks, even in industrialized countries, become denser year after year and traffic volumes continue to increase at a steady pace. It is imperative that we monitor the impact of this trend on wildlife, but monitoring roads for flattened fauna is a time consuming effort and roadkill monitoring projects conducted up till now have been relatively small scale both in terms of time and space. This hampers the progress of road ecology analyses at the population level and at larger landscape extents. We demonstrate that citizen science projects in combination with smartphones and other new technologies allow analysis at this level and extent, and simultaneously offer more complete data for safer transportation and mitigation of roadkill hotspots. Monitoring roadkill with citizen scientists poses certain challenges regarding data quality and people management, but we show that these challenges can be addressed, which allows researchers to benefit from the many other advantages and possible applications of monitoring roadkill with citizen scientists, including raising public awareness on the matter.

Does regional landscape connectivity influence the location of roe deer roadkill hotspots?

Linear infrastructures have both direct and indirect effects on ecosystems. Wildlife-vehicle collisions are the most visible direct effect and can result in severe human injuries. In Europe, the roe deer population is growing and roe deer roadkills are becoming more common. Roe deer movements depend on landscape features and regional-scale connectivity. Here, we investigate the influence of the landscape network on the location of roe deer roadkill hotspots. In order to localize new potential hotspots along the national roads of Franche-Comte (Eastern France), we first show that roe deer roadkills are not distributed randomly and we identify hotspots. Then, we explain roe deer hotspot locations using a predictive model by combining landscape composition variables, road-related properties, and graph-based connectivity metrics. We test three centrality metrics at three dispersal distances and we assess the relative contribution of the connectivity metrics to the best model. Finally, in order to define high-risk sections, we find the probability that reduces the costs of misclassification that the model produces. We validate the model with a new set of roe deer roadkills.

Vertebrate road-kill patterns in Mediterranean habitats: Who, when and where

Road-kill is the most recognized impact of traffic and an important threat for biodiversity. Nevertheless, most research on this topic deals with particular species or with road features, describing proximate correlates and rarely making inference on the mechanisms. Here we provide a more general approximation by describing life-history, temporal and spatial factors affecting vertebrate road-kills in Mediterranean landscapes, which are a biodiversity hotspot with little studied road impacts. During one year we recorded the casualties found on paved roads within Doñana Natural Park. We found 2368 road-kills belonging to 66 species (32% of the study area checklist), with abundant ectotherm species more likely to be road-killed. We also investigated the temporal and spatial factors affecting the road-kill patterns of different taxonomic and functional groups. The phenology of the species was the main factor affecting road-kill temporal patterns for lizards, all birds and small mammals. Additionally, rainfall events were associated with the road-kill peaks of wintering birds, whereas high temperatures were related to the increase of road-killed snakes and the decrease of road-killed amphibians. Amphibians, snakes, lizards and small passerines were mainly road-killed according with their spatial abundance. Mitigation measures such as wildlife road-crossing structures showed contradictory effectiveness for small vertebrates due to the lack of adequate drift fences. We suggest prioritizing the mitigation measures which can permanently decrease the risk of been road-killed for ectotherm species, such as specific road-crossing structures with effective drift fences on road-kill hotspots. Concurrently, group-specific temporal mitigation measures should be applied during the road-kill seasonal peaks. The present work provides recommendations to decrease road-kill impacts in Mediterranean environments, but simultaneously tries to contribute to a more general development of road ecology research, suggesting several useful guidelines to perform road-kill studies.

야생동물 서식지 패치와 로드킬 핫스팟의 상관관계 연구

The ecosystem fragmentation due to transportation infrastructure causes road-kill phenomenon. When making policy for reducing road-kill it is important to select target-species in order to enhance its efficiency. However, many corridors installed in Korea have been raised issues about their effectiveness due to lack of considerations such as target-species selection, site selection, and management, etc. In this study, we are to grasp relationship between road-kill area and habitat patches and suggest that spatial location of habitat patches should be considered as one of the important factors when making policy for reducing road-kill. Habitat patches were presumed from overlying suitability index that chosen by literature review and road-kill hotspot was determined by Getis-Ord analysis. Afterwards, we performed a correlation analysis between Z-score and the distance from habitat patches to the roads. As a result, there is a negative correlation between two variables, It affects the Z-score going up if the habitat patches and the roads become closer.

A Study on Building Methodology for Identifying Road-kill Hot-spots on Highways and Its Empirical Application

Road-kill accidents on highways cause considerable social and economic costs. Therefore, it is critical to minimize the frequency of occurrence through taking appropriate actions such as accident prevention and reduction programs/tools including eco-corridor construction and fence installation. Due to the constraints in allocating available public resource, it may help decision-makers to determine where to put priorities when taking actions The objective of this study is to construct a spatial statistical methodology for pinpointing spatial clusters of road-kill accidents The model is defined based on the assumption that road-kill accident follows Poisson spatial process over geographic space, whereby expected frequency of accident is estimated and then the difference from the actual frequency is calculated. The higher the difference is the higher the degree of spatial clustering is. Interpretively, spatial clustering may be possible outcomes due partly to some environmental factors. This interpretation, which is not readily induced solely form pin-mapping of raw data, makes it possible to identify regions (road-segments) showing higher spatial clustering tendency of road-kill accidents. Analysis results lead to the brief discussions on where to put priorities when taking relevant actions.

Moonlight-related mortality: lunar conditions and roadkill occurrence in the Amami WoodcockScolopax mira

Roadkill is one of the most striking ecological problems related to roads and traffic. The Amami Woodcock, Scolopax mira, an endemic and endangered species on the islands of southwestern Japan, ventures out on roads at night, making it susceptible to becoming roadkill. In the present study, I investigated woodcock behavior on roads at night, trends in nighttime traffic at roadkill hotspots, and dates when roadkill occurred in the past on Amami-Oshima Island in southwestern Japan, to develop mitigation measures to prevent roadkill in this species. Woodcocks were abundant on roads when the moon was waxing; ∼90% of nighttime traffic was recorded between dusk and midnight. These findings were consistent with the occurrence pattern of roadkill in the past, that is, roadkills occurred frequently during the first half of the synodic month when the waxing moon crosses the meridian from dusk until midnight. This pattern was obvious particularly in the breeding season (Feb–May). As a mitigation measure, drivers should be asked to reduce their vehicle speed on moonlit nights, particularly several days before the full moon in March, because this is the most vulnerable period for the Amami Woodcock. The present study revealed that the interplay of three factors (woodcock behavior, trends in nighttime driving, and lunar conditions) accounts for the seasonal, periodic, and temporal patterns of roadkill specific to this species. Because night activities of various animals are affected by phases of the moon, lunar conditions may have stronger effects on roadkill in a wider variety of animals than has been previously recognized. Taking lunar conditions into consideration would be important for better understanding of roadkill patterns in a wide variety of animals using roads at night.

Disentangling roadkill: the influence of landscape and season on cumulative vertebrate mortality in South Korea

This study recorded and analyzed cumulative vertebrate roadkill data on 107 km of roads in rural South Korea and reports the first intensive roadkill study results from Asia. Over 30 months, roadkill strikes and adjacent landscape factors were recorded daily or every other day on three types of roads: highway, local, and riverside. For analysis, roads were segmented into 250-m units, and roadkill hotspot segments were calculated with the Getis–Ord Gi* statistic. Eighteen road characteristics and landscape factors were correlated to roadkill hotspots using multiple logistic regression analysis. Mammal mortality increased from spring to fall, whereas bird mortality peaked in summer. Reptile and amphibian mortality peaked during fall. Seasonal focal species’ mortality tracked the taxonomic groups they represent, except oriental scops owl (Otus scops), for which yearly mortality peaked 2 months earlier than for most birds. Mammal and bird roadkill hotspots were concentrated on the highway, which passes across mountains, whereas amphibian and reptile hotspots were on the riverside road because of movements related to breeding, juvenile dispersal, and hibernation. However, many species used the spatially complex agricultural fields along the local road, especially during harvest season. The significant site and landscape factors that influenced overall roadkill hotspots were a high landscape percentage of water and rice paddies, low traffic volumes, high percentage of natural vegetation, an absence of road banking, high roadside grass presence, and an absence of drainage. South Korea has an active wildlife-crossing management program, and these findings can inform avoidance, minimization, and mitigation strategies and practices.

Relative Effects of Road Risk, Habitat Suitability, and Connectivity on Wildlife Roadkills: The Case of Tawny Owls (Strix aluco)

BackgroundDespite its importance for reducing wildlife-vehicle collisions, there is still incomplete understanding of factors responsible for high road mortality. In particular, few empirical studies examined the idea that spatial variation in roadkills is influenced by a complex interplay between road-related factors, and species-specific habitat quality and landscape connectivity.Methodology/Principal FindingsIn this study we addressed this issue, using a 7-year dataset of tawny owl (Strix aluco) roadkills recorded along 37 km of road in southern Portugal. We used a multi-species roadkill index as a surrogate of intrinsic road risk, and we used a Maxent distribution model to estimate habitat suitability. Landscape connectivity was estimated from least-cost paths between tawny owl territories, using habitat suitability as a resistance surface. We defined 10 alternative scenarios to compute connectivity, based on variation in potential movement patterns according to territory quality and dispersal distance thresholds. Hierarchical partitioning of a regression model indicated that independent variation in tawny owl roadkills was explained primarily by the roadkill index (70.5%) and, to a much lesser extent, by landscape connectivity (26.2%), while habitat suitability had minor effects (3.3%). Analysis of connectivity scenarios suggested that owl roadkills were primarily related to short range movements (<5 km) between high quality territories. Tawny owl roadkills were spatially autocorrelated, but the introduction of spatial filters in the regression model did not change the type and relative contribution of environmental variables.ConclusionsOverall, results suggest that road-related factors may have a dominant influence on roadkill patterns, particularly in areas like ours where habitat quality and landscape connectivity are globally high for the study species. Nevertheless, the study supported the view that functional connectivity should be incorporated whenever possible in roadkill models, as it may greatly increase their power to predict the location of roadkill hotspots.

English

The evaluation of road-kill spatial patterns is an important tool to identify priority locations for mitigation measures aiming to reduce wildlife mortality on roads. Single target or multi-species approaches are usually adopted to implement such measures, although their success must be evaluated. We aim to test if road-kill hotspots are coincident among different vertebrate groups. If this is true, data on accidents from one group could be used to plan measures applicable to other groups. We identified hotspots using five different grouping criteria: vertebrate classes (reptiles, mammals or birds), body size (large or small), species commonness (common or rare), type of locomotion (flying or non-flying), and time of activity (preferably nocturnal/crepuscular or diurnal). We analyzed data from road-kill surveys on four roads in southern Brazil, each one with at least one year of monitoring. Using SIRIEMA software, we performed a modified Ripley's K statistic to recognize scales of road-kill aggregation and we carried out Hotspot analyses to identify the location of road-kill aggregations for each group described above in each road. To test for similarity in hotspot location among different groups we performed an association test using correlation as resemblance measure. Hotspot analyses and association tests were done using different scales to evaluate scale effect on similarities. Correlation results between groups presented low values in small scales although had a tendency to increase with increasing scales. Our results show that road-kill hotspots are different among groups, especially when analyzed in small scales. We suggest that, for a successful biodiversity approach in mitigation, one should first select general hotspots in large scales and then identify specific hotspots in small scales to implement specific measures. These findings are relevant in a context of road networks already implemented, where mitigation measures are being planned to reduce their impact on wildlife.

Anuran road-kills neighboring a peri-urban reserve in the Atlantic Forest, Brazil

Mortality from road-kills may figure among the important causes of decline in amphibian populations and species extinctions worldwide. Evaluation of the magnitude, composition, and temporal and spatial distributions of amphibian road-kills is a key step for mitigation planning, especially in peri-urban reserves. Once a month for 16 months, we surveyed, on foot, a 4.4 km section of state road ERS-389 bordering the Itapeva reserve in the southern Atlantic Forest. We recorded 1433 anuran road-kills and estimated a mortality rate of 9002 road-kills/km/year. The species most often recorded were the largest ones: Leptodactylus latrans, Rhinella icterica, Leptodactylus gracilis and Hypsiboas faber; 54.5% of the carcasses could not be identified. Anuran mortality was concentrated in summer, and was associated with temperature, rainfall and photoperiod. Leptodactylus road-kills were strongly influenced by vehicle traffic, probably because of its high abundance during the entire study period. Road-kill hotspots differed for anurans as a group and for single species, and we found an association among spatial patterns of mortality and types of land cover, distance from the nearest waterbody, roadside ditches, and artificial light. Traffic should be banned temporarily during periods of high mortality, which can be forecasted based on meteorological data. A comprehensive mitigation approach should take into account hotspots of all anuran records, and also of target species for selecting locations for amphibian passages and fencing. Roadside ditches, artificial waterbodies, and conventional street lights should be reduced as much as possible, since they may represent ecological traps for anuran populations.

Identification methods and deterministic factors of owl roadkill hotspot locations in Mediterranean landscapes

AbstractRoad fatalities are among the major causes of mortality for Strigiformes species and may affect the population's survival. The use of mitigation strategies must be considered to overcome this problem. However, because mitigation along the total length of all roads is not financially feasible, the locations where Strigiformes roadkills are more frequent (i.e., road fatality hotspots) must be identified. In addition to hotspot identification, factors that influence the occurrence of such fatalities should be recognized to allow mitigation measures to be delineated. We used road fatality data collected from 311 km of southern Portugal roads over a 2‐year period to compare the performance of five hotspot identification methods: binary logistic regression (BLR), ecological niche factor analysis (ENFA), Kernel density estimation, nearest neighbor hierarchical clustering (NNHC), and Malo's method. BLR and ENFA modelling were also used for recognizing roadkill deterministic factors. Our results suggest that Malo's method should be preferred for hotspot identification. The main factors driving owl roadkillings are those associated with good habitat conditions for species occurrence and specific conditions that promote hunting behavior near roads. Based on these factors, several mitigation measures are recommended.