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

Spatiotemporal Patterns of Reptile and Amphibian Road Fatalities in a Natura 2000 Area: A 12-Year Monitoring of the Lake Karla Mediterranean Wetland

The pervasive expansion of human-engineered infrastructure, particularly roads, has fundamentally reshaped landscapes, profoundly affecting wildlife interactions. Wildlife-vehicle collisions, a common consequence of this intricate interplay, frequently result in fatalities, extending their detrimental impact within Protected Areas (PAs). Among the faunal groups most susceptible to road mortality, reptiles and amphibians stand at the forefront, highlighting the urgent need for global comprehensive mitigation strategies. In Greece, where road infrastructure expansion has encroached upon a significant portion of the nation's PAs, the plight of these road-vulnerable species demands immediate attention. To address this critical issue, we present a multifaceted and holistic approach to investigating and assessing the complex phenomenon of herpetofauna road mortality within the unique ecological context of the Lake Karla plain, a rehabilitated wetland complex within a PA. To unravel the intricacies of herpetofauna road mortality in the Lake Karla plain, we conducted a comprehensive 12-year investigation from 2008 to 2019. Employing a combination of statistical modeling and spatial analysis techniques, we aimed to identify the species most susceptible to these encounters, their temporal and seasonal variations, and the ecological determinants of their roadkill patterns. We documented a total of 340 roadkill incidents involving 14 herpetofauna species in the Lake Karla's plain, with reptiles, particularly snakes, being more susceptible, accounting for over 60% of roadkill occurrences. Moreover, we found that environmental and road-related factors play a crucial role in influencing roadkill incidents, while spatial analysis techniques, including Kernel Density Estimation, the Getis-Ord Gi*, and the Kernel Density Estimation plus methods revealed critical areas, particularly in the south-eastern region of Lake Karla's plain, offering guidance for targeted interventions to address both individual and collective risks associated with roadkill incidents.

Temporal and spatial patterns of small vertebrate roadkill in a supercity of eastern China

An assessment of animal roadkill can help develop road mitigation measures. This article is the first to report data on animal-vehicle collisions (AVCs) in Nanjing, a supercity in eastern China. The research was conducted on a 224.27 km stretch of nine roads in Nanjing. In the period, between November 2020 and October 2021, 26 fortnightly monitoring missions were conducted to gather roadkill carcasses so that we could analyze their temporal and spatial distribution patterns. A total of 259 carcasses were collected, comprising 22 different species, of which 46.42% were mammals and 48.81% were birds. Cats and dogs are the most roadkill mammals, and blackbirds and sparrows are the most roadkill birds. The temporal analysis demonstrated that the peak of vertebrate roadkill occurred from May to July. Spatial analysis showed that the distribution patterns of vertebrate roadkill on different roads varied with a generally non-random distribution and aggregation. By mapping accidents using kernel density analysis, we were able to pinpoint locations that were at high risk for roadkill. Due to the fortnightly survey, our results would underestimate the casualties, even if, our study suggests that the problem of car accidents due to animals should be a cause for concern, and the results of the analysis of temporal and spatial patterns contribute to the establishment of mitigation measures.

Identifying connectivity for two sympatric carnivores in human-dominated landscapes in central Iran

Central Iran supports a diversity of carnivores, most of which are threatened by habitat loss and fragmentation. Carnivore conservation requires the identification and preservation of core habitats and ensuring connectivity between them. In the present study, we used species distribution modeling to predict habitat suitability and connectivity modeling to predict linkage (resistant kernel and factorial least-cost path analyses) for grey wolf and golden jackal in central Iran. For grey wolf, elevation, topographic ruggedness, and distance to Conservation Areas (CAs) were the strongest predictors; for golden jackal, distance to human settlements, dump sites and topographic ruggedness were the most influential variables in predicting the occurrence of this species. Our results also indicated a high potential for large parts of the landscape to support the occurrence of these two canid species. The largest and the most crucial core habitats and corridor paths for the conservation of both species are located in the southern part of the study landscape. We found a small overlap between golden jackal corridor paths and core habitats with CAs, which has important implications for conservation and future viability of the golden jackal populations. Some sections of core areas are bisected by roads, where most vehicle collisions with grey wolf and golden jackal occurred. To minimize mortality risk, we propose that successful conservation of both species will necessitate integrated landscape-level management, as well as conservation of core areas and corridors and development of mitigation strategies to reduce vehicle collisions.

Estimating Road Mortality Hotspots While Accounting for Imperfect Detection: A Case Study with Amphibians and Reptiles

Wildlife road mortality tends to aggregate spatially at locations commonly referred to as road mortality hotspots. Predictive models can be used to identify locations appropriate for mitigation measures that reduce road mortality. However, the influence of imperfect detection (e.g., false absences) during road mortality surveys can lead to inaccurate or imprecise spatial patterns of road mortality hotspots and suboptimal implementation of mitigation measures. In this research, we used amphibians and reptiles as a case study to address imperfect detection issues when estimating the probability of road mortality hotspots using occupancy detection modeling. In addition, we determined the survey effort needed to achieve a high probability of detecting large roadkill events. We also assessed whether vehicle travel reductions associated with the COVID-19 pandemic travel restrictions led to reductions in road mortality. We conducted surveys at 48 sites throughout Rhode Island, USA, from 2019–2021. In total, we observed 657 carcasses representing 19 of Rhode Island’s 37 native species. Of the 19 native species, eight species of frogs, four species of salamanders, four species of snakes, and three species of turtles were observed. We documented a reduction in roadkill density and the proportion of dead versus live amphibians and reptiles in pandemic years (2020 and 2021), but we were unable to link reductions in roadkill density to reductions in traffic volume. Our model results indicated that large roadkill events were more likely to occur on roads near wetlands and with low traffic volume and were more likely to be detected as daily precipitation increased. We determined that there was a low probability of detecting large roadkill events, suggesting that imperfect detection influences detection of large roadkill events, and many were likely missed during our surveys. Therefore, we recommend using occupancy modeling to account for the influence of imperfect detection when estimating road mortality hotspots. This approach will more effectively guide the implementation of mitigation measures.

Implications for conservation and game management of the roadkill levels of the endemic Iberian hare (Lepus granatensis)

The Iberian hare (Lepus granatensis) is an important small game species endemic to the Iberian Peninsula for which the incidence of roadkill is unknown. We surveyed Iberian hare-vehicle accidents on road networks in southern Spain, focusing on roads that mainly run through favorable habitats for this species: Mediterranean landscapes with plots of arable crops, olive groves, and vineyards. We recorded roadkills over a 5-month period, estimated hare accident densities on roads, and compared these numbers to hare hunting yields in adjoining hunting estates. We also analyzed the spatial patterns of and potential factors influencing hare roadkills. We detected the existence of black spots for hare roadkills in areas with high landscape heterogeneity that also included embankments and nearby crossroads and had high traffic intensity. Hare roadkill levels ranged from 5 to 25% of the annual harvest of hares killed on neighboring hunting estates. We suggest that road collisions should be considered in Iberian hare conservation in addition to hunting, since they may represent an additive source of mortality. Game managers should address the issue of hare roadkill in harvest planning to compensate for hare accidents, adjusting hunting quotas to account for this unnatural source of mortality. Our results suggest future directions for applied research in road ecology, including further work on demographic compensation and roadkill mitigation.

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.

Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns

The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.

Spatiotemporal persistence of bat roadkill hotspots in response to dynamics of habitat suitability and activity patterns

Wildlife roadkill hotspots are frequently used to identify priority locations for implementing mitigation measures. However, understanding the landscape-context and the spatial and temporal dynamics of these hotspots is challenging. Here, we investigate the factors that drive the spatiotemporal variation of bat mortality hotspots on roads along three years. We hypothesize that hotspot locations occur where bat activity is higher and that this activity is related to vegetation density and productivity, probably because this is associated with food availability. Statistically significant clusters of bat-vehicle collisions for each year were identified using the Kernel Density Estimation (KDE) approach. Additionally, we used a spatiotemporal analysis and generalized linear mixed models to evaluate the effect of local spatiotemporal variation of environmental indices and bat activity to predict the variation on roadkill hotspot locations and to asses hotspot strength over time. Between 2009 and 2011 we conducted daily surveys of bat casualties along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 509 casualties and we identified 86 statistically significant roadkill hotspots, which comprised 12% of the road network length and contained 61% of the casualties. Hotspots tended to be located in areas with higher accumulation of vegetation productivity along the three-year period, high bat activity and low temperature. Furthermore, we found that only 17% of the road network length was consistently classified as hotspots across all years; while 43% of hotspots vanished in consecutive years and 40% of new road segments were classified as hotspots. Thus, non-persistent hotspots were the most frequent category. Spatiotemporal changes in hotspot location are associated with decreasing vegetation production and increasing water stress on road surroundings. This supports our hypothesis that a decline on overall vegetation productivity and increase of roadside water deficit, and the presumed lower abundance of prey, have a significant effect on the decrease of bat roadkills. To our knowledge, this is the first study demonstrating that freely available remote sensing data can be a powerful tool to quantify bat roadkill risk and assess its spatiotemporal dynamics.

An adaptive plan for prioritizing road sections for fencing to reduce animal mortality

Mortality of animals on roads is a critical threat to many wildlife populations and is poised to increase strongly because of ongoing and planned road construction. If these new roads cannot be avoided, effective mitigation measures will be necessary to stop biodiversity decline. Fencing along roads effectively reduces roadkill and is often used in combination with wildlife passages. Because fencing the entire road is not always possible due to financial constraints, high-frequency roadkill areas are often identified to inform the placement of fencing. We devised an adaptive fence-implementation plan to prioritize road sections for fencing. In this framework, areas along roads of high, moderate, and low levels of animal mortality (respectively, roadkill hotspots, warmspots, and coldspots) are identified at multiple scales (i.e., in circles of different diameters [200-2000 m] in which mortality frequency is measured). Fence deployment is based on the relationship between the amount of fencing being added to the road, starting with the strongest roadkill hotspots, and potential reduction in road mortality (displayed in mortality-reduction graphs). We applied our approach to empirical and simulated spatial patterns of wildlife-vehicle collisions. The scale used for analysis affected the number and spatial extent of roadkill hot-, warm-, and coldspots. At fine scales (e.g., 200 m), more hotspots were identified than at coarse scales (e.g., 2000 m), but combined the fine-scale hotspots covered less road and less fencing was needed to reduce road mortality. However, many short fences may be less effective in practice due to a fence-end effect (i.e., animals moving around the fence more easily), resulting in a trade-off between few long and many short fences, which we call the FLOMS (few-long-or-many-short) fences trade-off. Thresholds in the mortality-reduction graphs occurred for some roadkill patterns, but not for others. Thresholds may be useful to consider when determining road-mitigation targets. The existence of thresholds at multiple scales and the FLOMS trade-off have important implications for biodiversity conservation.

Wildlife roadkill patterns in a fragmented landscape of the Western Amazon

One of the most evident and direct effects of roads on wildlife is the death of animals by vehicle collision. Understanding the spatial patterns behind roadkill helps to plan mitigation measures to reduce the impacts of roads on animal populations. However, although roadkill patterns have been extensively studied in temperate zones, the potential impacts of roads on wildlife in the Neotropics have received less attention and are particularly poorly understood in the Western Amazon. Here, we present the results of a study on roadkill in the Amazon region of Ecuador; a region that is affected by a rapidly increasing development of road infrastructure. Over the course of 50 days, in the wet season between September and November 2017, we searched for road-killed vertebrates on 15.9 km of roads near the city of Tena, Napo province, for a total of 1,590 surveyed kilometers. We recorded 593 dead specimens, predominantly reptiles (237 specimens, 40%) and amphibians (190, 32%), with birds (102, 17%) and mammals (64, 11%) being less common. Recorded species were assigned to three functional groups, based on their movement behavior and habitat use ("slow," "intermediate," and "fast"). Using Ripley's K statistical analyses and 2D HotSpot Identification Analysis, we found multiple distinct spatial clusters or hotspots, where roadkill was particularly frequent. Factors that potentially determined these clusters, and the prevalence of roadkill along road segments in general, differed between functional groups, but often included land cover variables such as native forest and waterbodies, and road characteristics such as speed limit (i.e., positive effect on roadkill frequency). Our study, which provides a first summary of species that are commonly found as roadkill in this part of the Amazon region, contributes to a better understanding of the negative impacts of roads on wildlife and is an important first step toward conservation efforts to mitigate these impacts.

Where will it cross next? Optimal management of road collision risk for otters in Italy

Collisions with vehicles represent the main conflict between infrastructures and wildlife, causing damages to both humans and animals. As to the latter, road mortality is a growing phenomenon and the largest single cause of death for many vertebrates. When focusing on endangered species, the Eurasian otter (Lutra lutra) is among the most vulnerable to road-kills, which represent the predominant cause of deaths recorded in Europe. We propose a large scale spatially-explicit assessment of road-kill risk for the Eurasian otter in Italy as a tool to identify road stretches at high collision risk, thus optimizing the location of mitigation measures. The modelling approach was produced for South Central Italy, hosting the only remnant viable population of otters in Italy. We used a maximum entropy approach including 56 road collision events recorded between 2004 and 2016 through a citizen science initiative, along with seven environmental predictors measured on 1 km grid cells. Four predictors were selected to describe roads characteristics, i.e. density of highways, and of state, regional and local roads. The remaining three variables referred to the quality of otter habitat in the surrounding of the collision sites, i.e. elevation, density of freshwater bodies, and a measure of landscape heterogeneity calculated on land-cover categories. The model achieved a good predictive accuracy (AUC > 0.8; Boyce index > 0.8). The collision probability was mostly affected by elevation, density of state roads, and density of freshwater bodies. Specifically, collision risk was higher in areas at low elevation and medium density of state roads located near rivers and wetlands. In addition, model predictions evidenced that implementing mitigation measures along 10% of road network in the study area could have potentially hampered ca. 50% of otter casualties recorded during the study period.

Accounting for Connectivity Uncertainties in Predicting Roadkills: a Comparative Approach between Path Selection Functions and Habitat Suitability Models

Functional connectivity modeling is increasingly used to predict the best spatial location for over- or underpasses, to mitigate road barrier effects and wildlife roadkills. This tool requires estimation of resistance surfaces, ideally modeled with movement data, which are costly to obtain. An alternative is to use occurrence data within species distribution models to infer movement resistance, although this remains a controversial issue. This study aimed both to compare the performance of resistance surfaces derived from path versus occurrence data in identifying road-crossing locations of a forest carnivore and assess the influence of movement type (daily vs. dispersal) on this performance. Resistance surfaces were built for genet (Genetta genetta) in southern Portugal using path selection functions with telemetry data, and species distribution models with occurrence data. An independent roadkill dataset was used to evaluate the performance of each connectivity model in predicting roadkill locations. The results show that resistance surfaces derived from occurrence data are as suitable in predicting roadkills as path data for daily movements. When dispersal was simulated, the performance of both resistance surfaces was equally good at predicting roadkills. Moreover, contrary to our expectations, we found no significant differences in locations of roadkill predictions between models based on daily movements and models based on dispersal. Our results suggest that species distribution models are a cost-effective tool to build functional connectivity models for road mitigation plans when movement data are not available.

On reliable identification of factors influencing wildlife-vehicle collisions along roads

Wildlife-vehicle collisions (WVCs) pose a serious global issue. Factors influencing the occurrence of WVC along roads can be divided in general into two groups: spatially random and non-random. The latter group consists of local factors which act at specific places, whereas the former group consists of globally acting factors. We analyzed 27,142 WVC records (roe deer and wild boar), which took place between 2012 and 2016 on Czech roads. Statistically significant clusters of WVCs occurrence were identified using the clustering (KDE+) approach. Local factors were consequently measured for the 75 most important clusters as cases and the same number of single WVCs outside clusters as controls, and identified by the use of odds ratio, Bayesian inference and logistic regression. Subsequently, a simulation study randomly distributing WVC in clusters into case and control groups was performed to highlight the importance of the clustering approach. All statistically significant clusters with roe deer (wild boar) contained 34% (27%) of all records related to this species. The overall length of the respective clusters covered 0.982% (0.177%) of the analyzed road network. The results suggest that the most pronounced signal identifying the statistically significant local factors is achieved when WVCs were divided according to their occurrence in clusters and outside clusters. We conclude that application of a clustering approach should precede regression modeling in order to reliably identify the local factors influencing spatially non-random occurrence of WVCs along the transportation infrastructure.

Turning the threat into a solution: using roadways to survey cryptic species and to identify locations for conservation

Freshwater turtles are one of the most imperilled groups of vertebrates globally, and roads have been associated with their decline. Although roads are typically viewed as an imminent threat to population persistence, because of direct mortality and increased landscape fragmentation, we argue that they are an important sampling tool for collecting a wide variety of data that can inform conservation efforts. Road surveys can yield important presence data when conducting species inventories, particularly for cryptic species, and can also indicate where to implement road mitigation measures. Our research examined three road survey methods from two previous studies (walking versus bicycling and walking versus driving) to test their relative effectiveness at locating turtles. We found that walking surveys yielded the highest number of turtles per kilometre; however, bicycling and driving surveys also presented advantages (specifically, the ability to survey longer lengths of road more quickly). We recommend using walking surveys in areas of specific interest (e.g. to investigate suitable habitat for imperilled species or to investigate the presence of cryptic species), and bicycling or driving surveys between sections of specific interest. Road survey methods could be used in addition to more traditional sampling approaches (e.g. trapping and visual surveys), and do not need to be restricted to areas where roadwork projects are in progress or being planned. Road surveys could also be used during general environmental assessments and ecological research, to effectively incorporate turtle presence data into conservation efforts.

Spatial patterns of road mortality of medium–large mammals in Mato Grosso do Sul, Brazil

Context Brazil has one of the richest biodiversity and one of the most extensive road networks in the world. Several negative impacts emerge from this interaction, including wildlife–vehicle collisions (WVC), which may represent a significant source of non-natural mortality in several species. The understanding of the main drivers of WVC is, therefore, crucial to improve the safe coexistence between human needs (transportation of goods and people) and animal populations. Aims We aimed to (1) evaluate the relative influence of land-cover patterns on the distribution of WVC, (2) assess whether WVCs are clustered forming hotspots of mortality, and, if so, (3) evaluate the benefits of mitigating only hotspot sections. Methods We collected WVC data involving medium–large mammals (4–260kg) along three road transects (920km), fortnightly over 1 year (n=1006 records). We used boosted regression trees to relate the WVC locations with a set of environmental variables including a roadkill index, reflecting overall habitat suitability and landscape connectivity, while accounting for spatial autocorrelation effects. We identified hotspots of mortality using Ripley’s K statistic and testing whether data follow a random Poisson distribution correcting for Type I error. Key results We found a strong association between WVC probability and roadkill index for all focal species. Distance to riparian areas, tree cover, terrain ruggedness and distance to urban areas were also important predictors, although to a lesser extent. We detected 21 hotspots of mortality, yet with little spatial overlapping as only four road sections (2%) were classified as hotspot for more than one species. Conclusions Our results supported that WVC mainly occur in road sections traversing areas with more abundant and diverse mammal communities. Hotspots of mortality may provide important information to prioritise road sections for mitigation, but this should be used in complement with roadkill indexes accounting for overall mortality. Implications The results support focusing on hotspots and habitat quality and landscape connectivity for a better assessment of road mortality. At the local scale, a larger number and improved road passages with exclusionary fencing of appropriate mesh size in riparian areas may provide safe crossings for many species and constitute a promising mitigation measure.

Phalangeal bone anomalies in the European common toad Bufo bufo from polluted environments

Every spring, many of amphibians are killed by motor vehicles on roads. These road-killed animals can be used as valuable material for non-invasive studies showing the effect of environmental pollution on amphibian populations. The aims of our research were to check whether the phalanges of road-killed toads may be useful as material for histological analysis, and whether various degrees of human impact influence the level in bone abnormalities in the common toad. We also examined whether the sex and age structure of toads can differ significantly depending in the different sites. We chose three toad breeding sites where road-killed individuals had been observed: near the centre of a city, the outskirts of a city, and a rural site. We collected dead individuals during spring migration in 2013. The sex of each individual was determined and the toes were used to determine age using the skeletochronology method. While performing age estimates, we looked for abnormalities in relation to normal bone tissue structure. In urban site, females dominate males (sex ratio 2.6:1), but in populations from rural and semi-urban sites, sex ratio was reverse (1:2.2 and 1:1.4, respectively). However, we did not find any significant differences between age structure of all populations (average age of each population: approximately 4 years). We observed abnormalities in more than 80 % of all toads from the city, compared to approximately 20 % from the rural and semi-urban sites. In particular, we found hypertrophic bone cells, misaligned intercellular substance, and irregular outer edges of bones. We suggest that these malformations are caused by different pollution, e.g. with heavy metals.