Do well-connected landscapes promote road-related mortality?

Roadkill mortality decreases after road inauguration

The main factors affecting specific road casualty rates are related to life-history traits, road features, and landscape variables. After road inauguration, roadkill rate and spatial and temporal patterns can change substantially due to changes in traffic intensity, avoidance behaviour or local population decline. Despite the Canary Islands constituting a biodiversity hotspot, Canarian ecosystems are highly threatened because of the high human density, and studies on anthropogenic sources of mortality of wildlife are scarce. Here, we counted roadkills during two annual cycles after the inauguration of an 8.8-km-road section on Tenerife, the largest and most densely populated island of the Canaries. We counted 694 roadkills belonging to a minimum of 19 species of birds and six species of introduced mammals. Seasonal variation was apparent during both annual cycles, particularly for birds, being the majority of victims concentrated in May and June. Although traffic intensity increased since road inauguration, the number of roadkills decreased significantly in the second annual cycle. The reduction in road mortality in the second cycle could be related to some non-mutually exclusive factors such as population decline, road avoidance, or weather conditions. As road networks of the Canary Islands are still increasing, further studies quantifying road mortality impacts on Canarian ecosystems and threatened species are urgently needed to guarantee the management and conservation of its fragile wildlife.

Quantifying Landscape Degradation Following Construction of a Highway Using Landscape Metrics in Southern Iran

Rapid expansion of roads is among the strongest drivers of the loss and degradation of natural habitats. The goal of the present study is to quantify landscape fragmentation and degradation before and after the construction of the Isfahan-Shiraz highway in southern Iran. To this end, the ecological impacts of the highway on forests, rangelands, and protected areas were evaluated. Impacts of the construction of the highway were studied within a 1,000-m buffer around the road, which was then overlaid on maps of forests, rangelands, and protected areas. Class area, number of patches, largest patch index, edge density, landscape shape index, mean patch size, and patch cohesion index were used to gauge changes in the spatial configuration of the landscape; the ecological impacts of the highway were quantified using effective mesh size (MESH), division index, and splitting index. The results indicated that after the construction of the highway, 6,406.9 ha of forest habitat, 16,647.1 ha of rangeland habitat, and 912 of the Tang-e Bostanak Protected Area will be lost. The effective MESH metric showed that after the construction of the highway, the area of forest, rangeland habitats and protected area will decrease by 20,537, 49,149, and 71,822 ha, respectively. Our findings revealed drastic habitat loss and landscape fragmentation associated with construction of the highway, serving as references for conservation planning and development.

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.

How far from the road should land cover be assessed? A case study on mesopredator mortality on roads

The methods used to assess the significance of land cover in the vicinity of a road for the mortality of mesopredators are diverse. In assessing the effect of land cover along the road on road causalities, scientists use various buffer sizes, or even no buffer along the road. The aim of this study was to verify how results of land cover effects on the mortality of mesopredators on roads may differ when analyzing various buffer sizes from the road. We assessed road causalities in the Warmian-Masurian voivodeship (Poland) from 3 consecutive years: 2015, 2016, and 2017. The roads were divided into equal sections of 2000 m each with buffer size of radius: 10, 250, 500, and 1000 m. We analyzed the number of road kills of red fox and European badger separately in a generalized linear model, whereas explanatory variables we used land cover types (based on the Corine Land Cover inventory) and traffic volume. Mean annual mortality from road collisions amounts to 2.36% of the red fox population and 3.82% of the European badger population. We found that the buffer size determines the results of the impact of land cover on mesocarnivore mortality on roads. The red fox differed from the European badger in response to land cover depending on the buffer size. The differences we have shown relate in particular to built-up areas. Our results indicate a 500-m buffer as best reflecting the land cover effects in road kills of both species. This was confirmed by model evaluation and a tendency to use or avoid the vicinity of human settlements of the analyzed species. We concluded that buffer size will probably affect mostly the significance of cover types that are spatially correlated with roads, positively or negatively. We suggest that the home range size of given species in local conditions should be assessed before determining the size of the buffer for analysis.

Potential Movement Corridors and High Road-Kill Likelihood do not Spatially Coincide for Felids in Brazil: Implications for Road Mitigation

The negative effects of roads on wildlife populations are a growing concern. Movement corridors and road-kill data are typically used to prioritize road segments for mitigation measures. Some research suggests that locations where animals move across roads following corridors coincide with locations where they are often killed by vehicles. Other research indicates that corridors and road-kill rarely occur in the same locations. We compared movement corridor and road mortality models as means of prioritizing road segments for mitigation for five species of felids in Brazil: tiger cats (Leopardus tigrinus and Leopardus guttulus were analyzed together), ocelot (Leopardus pardalis), jaguarundi (Herpailurus yagouaroundi), and puma (Puma concolor). We used occurrence data for each species and applied circuit theory to identify potential movement corridors crossed by roads. We used road-kill records for each species and applied maximum entropy to determine where mortality was most likely to occur on roads. Our findings suggest that movement corridors and high road mortality are not spatially associated. We suggest that differences in the behavioral state of the individuals in the species occurrence and road-kill data may explain these results. We recommend that the road segments for which the results from the two methods agree (~5300 km for all studied species combined at 95th percentile) should be high-priority candidates for mitigation together with road segments identified by at least one method in areas where felids occur in low population densities or are threatened by isolation effects.

Simulating the Consequences of Roads for Wildlife Population Dynamics

Rapidly expanding road networks have been a key driver of the fragmentation and isolation of many wildlife species, and are a source of significant mortality due to collisions with vehicles. But not all animals are affected equally by transportation infrastructure, and in most cases little is known about the population-scale consequences of roads for wildlife. Even less information is available to characterize species' behavioral responses to roads. Although research shows that maned wolves (Chrysocyon brachyurus) in Brazil are experiencing considerable fragmentation and road mortality, the degree to which these disturbances are impacting the species' viability is unknown. The goal of this study was to analyze the potential effects of roads on maned wolf population size and structure. We used a simulation model to evaluate the population-scale consequences of individual maned wolf interactions with roads, which can result in road crossing, avoidance, or mortality due to a collision with a vehicle. We also forecasted where in Brazil these impacts might be most significant. Our model incorporated species demographic and movement parameters, plus habitat quality and a map of the road network. We found that even moderate rates of road mortality led to severe declines in population size, and that four specific locations accounted for a disproportionate fraction of roadkill events. Our approach will be generally useful for evaluating the relative importance of road effects on species conservation in many ecological systems, for prioritizing data collection efforts, and for informing conservation policies and mitigation strategies.

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.

Individuals matter: predicting koala road crossing behaviour in south-east Queensland

The ability to predict the frequency with which koalas (Phascolarctos cinereus) cross roads is an important step in developing mitigation strategies aimed at maintaining metapopulation viability for this species. In south-east Queensland, Australia, rapid urban development, including fragmentation and vehicle-related mortality, has contributed to a dramatic decline in local koala populations. Assessment of wildlife crossing structures that mitigates the impact of roads demonstrates these to be beneficial for many species. However, building enough structures to enable animals to move freely across impacted landscapes may be prohibitive in complex urban landscapes. The focus for this study was to consider the role of differing characteristics for species at risk. We examined the frequency of road crossings by individual koalas among six subpopulations in south-east Queensland. We explored the influence of potential predictor variables including: age, sex, and distance from roads. We established that road crossings were limited to a subset of individuals, with only 18 of 51 (~35%) koalas studied ever crossing a road. We found that koalas were disproportionately more likely to cross a road if they had initially been found within a distance of 100 m of that road. Males were more likely to cross roads than females, as were koalas aged less than five years. We suggest that successful wildlife road mitigation can be improved by better understanding the road-crossing behaviour of species such as the koala.

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.

Using complementary remote detection methods for retrofitted eco-passages: a case study for monitoring individual koalas in south-east Queensland

Context Vehicle-strike has been identified as a key threatening process for koala (Phascolarctos cinereus) survival and persistence in Australia. Roads and traffic act as barriers to koala movement and can impact dispersal and metapopulation dynamics. Given the high cost of wildlife mitigation structures such as purpose-built fauna-specific underpasses or overpasses (eco-passages), road construction and management agencies are constantly seeking cost-effective strategies that facilitate safe passage for fauna across roads. Here we report on an array of detection methods trialled to verify use of retrofitted road infrastructure (existing water culverts or bridge underpasses) by individual koalas in fragmented urban landscapes in south-east Queensland. Aims The study examined whether the retrofitting of existing road structures at six sites facilitated safe passage for koalas across roads. Our primary objective was to record utilisation of retrofitted infrastructure at the level of the individual. Methods We used a combination of existing monitoring methods such as GPS/VHF collars, camera traps, sand plots, and RFID tags, along with a newly developed animal-borne wireless identification (WID) tag and datalogging system, specifically designed for this project, to realise the study aims. Key results We were able to verify 130 crossings by koalas involving a retrofitted structure or a road surface over a 30-month period by using correlated data from complementary methods. We noted that crossings were generally uncommon and mostly undertaken by only a subset of our tagged individuals at each site (21% overall). Conclusions An important element of this study was that crossing events could be accurately determined at the level of the individual. This allowed for detailed assessment of eco-passage usage, rather than the more usual approach of simply recording species’ presence. Implications This study underscores the value of identifying the constraints of each individual monitoring method in relation to site conditions. It also highlights the benefits of contingency planning to limit data loss (i.e. using more than one method to collect data). We suggest an approach that uses complementary monitoring methods has significant advantages for researchers, particularly with reference to improving understanding of whether eco-passages are meeting their prescribed conservation goals.

The spatial distribution of Mustelidae in France

We estimated the spatial distribution of 6 Mustelidae species in France using the data collected by the French national hunting and wildlife agency under the “small carnivorous species logbooks” program. The 1500 national wildlife protection officers working for this agency spend 80% of their working time traveling in the spatial area in which they have authority. During their travels, they occasionally detect dead or living small and medium size carnivorous animals. Between 2002 and 2005, each car operated by this agency was equipped with a logbook in which officers recorded information about the detected animals (species, location, dead or alive, date). Thus, more than 30000 dead or living animals were detected during the study period. Because a large number of detected animals in a region could have been the result of a high sampling pressure there, we modeled the number of detected animals as a function of the sampling effort to allow for unbiased estimation of the species density. For dead animals -- mostly roadkill -- we supposed that the effort in a given region was proportional to the distance traveled by the officers. For living animals, we had no way to measure the sampling effort. We demonstrated that it was possible to use the whole dataset (dead and living animals) to estimate the following: (i) the relative density -- i.e., the density multiplied by an unknown constant -- of each species of interest across the different French agricultural regions, (ii) the sampling effort for living animals for each region, and (iii) the relative detection probability for various species of interest.

Inter-individual variability of stone marten behavioral responses to a highway

Efforts to reduce the negative impacts of roads on wildlife may be hindered if individuals within the population vary widely in their responses to roads and mitigation strategies ignore this variability. This knowledge is particularly important for medium-sized carnivores as they are vulnerable to road mortality, while also known to use available road passages (e.g., drainage culverts) for safely crossing highways. Our goal in this study was to assess whether this apparently contradictory pattern of high road-kill numbers associated with a regular use of road passages is attributable to the variation in behavioral responses toward the highway between individuals. We investigated the responses of seven radio-tracked stone martens (Martes foina) to a highway by measuring their utilization distribution, response turning angles and highway crossing patterns. We compared the observed responses to simulated movement parameterized by the observed space use and movement characteristics of each individual, but naïve to the presence of the highway. Our results suggested that martens demonstrate a diversity of responses to the highway, including attraction, indifference, or avoidance. Martens also varied in their highway crossing patterns, with some crossing repeatedly at the same location (often coincident with highway passages). We suspect that the response variability derives from the individual's familiarity of the landscape, including their awareness of highway passage locations. Because of these variable yet potentially attributable responses, we support the use of exclusionary fencing to guide transient (e.g., dispersers) individuals to existing passages to reduce the road-kill risk.

Relative effects of road risk, habitat suitability, and connectivity on wildlife roadkills: the case of tawny owls (Strix aluco)

Background

Despite 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 Findings

In 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.

Conclusions

Overall, 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.

Spatial analysis of amphibian road mortality levels in northern Portugal country roads

Animal mortality caused by vehicle collisions is one of the main ecological impacts of roads. Amphibians are the most affected group and road fatalities have a significant impact on population dynamics and viability. Several studies on Iberian amphibians have shown the importance of country roads on amphibian road mortality, but still, little is known about the situation in northern Portugal. By being more permeable to amphibian passage, country roads represent a greater source of mortality than highways, which act as barriers. Thus, mitigation measures should be applied, but due to the extensive road network, the identification of precise locations (hotspots) and variables related to animal-vehicle collision is needed to plan these measures successfully. The aim of the study was to analyse the spatial occurrence and related factors linked to amphibian mortality on a number of country roads in northern Portugal, using spatial statistics implemented in GIS and applying a binary logistical regression. We surveyed 631 km of road corresponding to seven transects, and observed 404 individual amphibians: 74 (18.3%) alive and 330 (81.7%) road-killed. Bufo bufo represented 80% of the mortality records. Three transects showed clustered distribution of road-kills, and broadleaved forests and road ditches were the most important factors associated with hotspots of road-kill. Logistic regression models showed that habitat quality, Bufo bufo’s habitat preferences, and road ditches are positively associated with amphibians’ road mortality in northern Portugal, whereas average altitude and length of walls were negatively associated. This study is a useful tool to understand spatial occurrence of amphibian road-kills in the face of applying mitigation measures on country roads from northern Portugal. This study also considers the necessity of assessing the condition of amphibian local populations to understand their road-kills spatial patterns and the urgency to apply mitigation measures on country roads.