Assessing the consistency of hotspot and hot-moment patterns of wildlife road mortality over time

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

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

Spatially prioritizing mitigation for amphibian roadkills based on fatality estimation and landscape conversion

Roads cause biodiversity loss and the effects of wildlife-vehicle collisions may ripple from individuals and populations to ecosystem functioning. Amphibians are threatened worldwide and, despite being particularly prone to roadkill impacts, they are often neglected in assessments. Here, we develop a sampling and analytical framework for spatially prioritizing mitigation actions for anuran amphibian roadkills based on fatality estimation and landscape conversion. The framework is composed of the six following steps: (1) pre-selection of segments to survey using the wetland coverage in the surroundings and the presence of roadkills of aquatic reptiles as a proxy for wet areas; (2) spatiotemporally replicated counts with a dependent double-observer protocol, that is, each segment is sampled multiple times by two pairs of people on foot; (3) extraction of covariates hypothesized to affect spatial and temporal variation in roadkill rates and persistence; (4) hierarchical open-population N-mixture modelling to estimate population dynamics parameters, which accounts for imperfect detection and spatiotemporal heterogeneity in removal, detection, and roadkill rates, and explicitly estimates carcass entries per time interval. (5) Assessment of land cover transition to infer landscape stability; and (6) prioritization of segments based on higher fatality rates and lower landscape conversion rates. We estimated a mean of 136 (95%CrI = 130–142) anurans roadkill per km per day in the 50 sample sites selected. The initial number of carcasses had a positive relationship with the percentage occupied by wetlands and a negative association with the percentage occupied by urban areas. The number of entrant carcass per interval was higher in the presence of rainfall and had a positive association with the wetlands cover. Carcass persistence probability was higher at night and lower in sites with high traffic volume. Ten segments (~1% of road extension) were prioritized using the median as threshold for fatality estimates and landscape conversion. It is urgent to appropriately evaluate the number of amphibians roadkilled aiming to plan and implement mitigation measures specifically designed for these small animals. Our approach accounts for feasibility (focused on sites with greater relevance), robustness (considering imperfect detection), and steadiness (less prone to loss of effectiveness due to landscape dynamics).

Forecasting seasonal peaks in roadkill patterns for improving road management

For several species, roadkill is not spatially aggregated on hotspots, having instead a more diffuse pattern along the roads. For such species, management measures such as road passages may be insufficient for effective mitigation, since a large part of the road crossings is likely to occur outside the influence of those structures. One complementary approach could be to implement temporary mitigation actions, such as traffic calming. This requires understanding when roadkill peaks may occur. We tested the feasibility of predicting seasonal peaks of roadkill using data from a 3-year systematic monitoring (78 surveys over ca. 960 km of roads) from eight non-flying vertebrate species from Mato Grosso do Sul, Brazil, with different body size and life history traits (ca. 6400 records from focal species). We modelled the time-series of the roadkill of these species at large scale (state level) using generalized additive mixed models (GAMMs). We used the data of the first 2 years as training datasets, and the information from the third year of surveys as testing datasets to evaluate the prediction performance of models. Overall, the models of species feed with a higher number of records were able to follow reasonably well the variations of roadkill over time, although they were not able to correctly predict the number of collisions. For species with fewer observations, the models presented a poorer goodness-of-fit and prediction ability. Our results suggest that, at least for those species with higher roadkill rates, it can be possible to forecast periods of higher probability of occurring hot-moments of mortality. Such models can provide valuable information to implement seasonal management actions.

Do the roadkills of different mammal species respond the same way to habitat and matrix?

While road network expansion connects human settlements between themselves, it also leads to deforestation and land use changes, reducing the connectivity between natural habitat patches, and increasing roadkill risk. More than 30% of registered mammal roadkills in Brazil are concentrated in four species: Cerdocyon thous (crab-eating fox); Euphractus sexcinctus (six-banded armadillo); Tamandua tetradactyla (collared anteater) and Myrmecophaga tridactyla (giant anteater), the latter being categorized as vulnerable by IUCN redlist. Our aim was to understand how these animals’ roadkills could be related to the land use proportions on landscapes all over the Brazilian territory, and investigate if the roadkill patterns differ among species. We collected secondary data on mammal roadkills (N = 2698) from several studies in different regions of Brazil. Using MapBiomas’ data on land use and land cover, we extracted landscape composition around each roadkill sample. Through the proportion of land use and land cover in the area of influence where the roadkill occurred, we built binomial GLM models and selected the best ones by Akaike Information Criteria. For crab-eating fox and the six-banded armadillo, the best models include matrix coverage resulting in increased roadkill risk, while both anteaters’ species have a habitat and a matrix component in their best models, with an interaction between the variables. These four species seem to be roadkilled in different landscape arrangements, but in all scenarios, anthropic areas had an important influence over the models. For habitat-dependent and more sensible species, such as Tamandua tetradactyla and Myrmecophaga tridactyla, the amount of matrix influencing the roadkill risk depends on habitat availability in the landscape. It changes the strength and direction of the effect according to the proportion of natural areas in the region, while with generalist species such as Cerdocyon thous and Euphractus sexcinctus, the quantity of human-modified coverage increases the risk.

Hit the road bat! High bat activity on the road verges in Brazilian savanna

Roads have direct and indirect impacts on animals present in the surrounding habitats. Bats have extensive foraging ranges which may include roads, and are therefore particularly affected by them. This study aimed to analyze the effects of roads on bat activity and diversity in the Brazilian savanna. Nine transects were established in protected areas in central Brazil with sampling points at 0, 500, 1,000, and 1,500 m away from roads. At each point, we recorded bat echolocation for 12 h and evaluated the influence of road type and distance from the road on bat activity, diversity, and foraging effort. Season, normalized difference vegetation index (NDVI), and distance to water also were included in the models. We found that species richness in the dry season and activity of open space insectivores were significantly higher on road verges than on areas farther from roads, while foraging effort and activity of edge space insectivores were only influenced by season. The activity of edge space insectivores also increased significantly with increasing distance to water during the rainy season. We suggest that bat individuals do not forage near roads, but rather use them as flyways or cross them to forage in sites outside the protected areas, which can increase the risk of collision with vehicles.

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.

Spatio-Temporal Patterns and Consequences of Road Kills: A Review

Simple Summary

Road kill continues to be a challenge in the 21st century. Numerous studies have sought to explain the causes and risks of animal-vehicle collisions that result in road kills, and how best to mitigate these events. This review evaluates the relevant literature on road kills, in order to determine how to effectively address them. Identifying methodologies and sources used in previous studies, how mortalities are normally recorded and reported was determined. Previous literature has suggested that spatial proximity, road infrastructure, traffic volume and velocity, driver awareness, landscape, climate and weather conditions, and animal behavior are the primary factors contributing to the spatio-temporal patterns of road kills. Important socioeconomic and environmental impacts of animal-vehicle collisions that result in road kills were also identified. Current mitigation measures for addressing road kills were examined from previous studies; including road management and wildlife crossing structures. Shortcomings to strategies and methodologies for addressing animal-vehicle collisions were subsequently assessed. Thereafter, the paper analysed geospatial technologies that have been utilised inroad kill studies. This review recommends focusing an all road kills in an area, using larger study locations, taking timelier observations, the increased use of citizen science, more research on nighttime driving speeds, and popularising effective road kill apps.

Abstract

The development and expansion of road networks have profoundly impacted the natural landscape and various life forms. Animals are affected by these roads in a myriad of ways, none as devastating as road mortalities. This article reviews the literature on the magnitude, spatiotemporal patterns, factors, and consequences of Animal-Vehicle Collisions (AVCs) and the subsequent road kills. Furthermore, the review paper briefly outlines the relationship between roads and animals in the surrounding landscape and later examines the nature and impacts of AVCs. This article evaluates the statistics on the number of road kills and a critical analysis of the spatiotemporal patterns of these mortalities is also evaluated. Subsequently, the review paper examines current mitigation measures and the challenges impeding their success. The paper then concludes with an evaluation of geospatial tools (GIS) and other technologies used in road kill studies. The relevant findings of this paper are that, (1) factors influencing road kill patterns interact with one another; (2) AVCs have serious environmental, economic and social consequences; (3) road kill mitigation strategies suffer several challenges hindering their success; and (4) specific geospatial tools and other technologies have been utilised in assessing AVC road kill patterns. The review, therefore, recommends including overall road kill clusters of all animals in mortality surveys, increasing the spatial coverage of road kill observations, consistent surveying, sufficient research on nighttime driving distances and speed, utilising citizen science in all road mortality studies and incorporating GIS into all apps used for recording road kills. An increased sufficiency in road kill data coupled with improved technologies can enable more effective mitigation strategies to prevent AVCs.

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.

Are Roadkill Hotspots in the Cerrado Equal Among Groups of Vertebrates?

Understand the spatial distribution of wildlife roadkill is necessary to design mitigation measures minimizing damage to the fauna and the human population. Thus, we aimed to analyze the spatial distribution of wildlife roadkill in the Brazilian savanna ("Cerrado") to test whether roadkill hotspots match between the studied animal groups. We collected data of wildlife roadkill over a year in the southwest region of the state of Goiás, Brazil. To understand the distribution of roadkill on highways and to identify the aggregation hotspots, we used the modified two-dimensional Ripley K test and the two-dimensional hotspot identification analysis. We detected that birds and mammals have different aggregation points. These points may vary when the two groups are analyzed together or when species with greater abundance are removed from the analyses. Hence, we concluded that using generalist approaches including several species, are not enough, and can lead to erroneous conclusions. Therefore, it is necessary that the analyses be done in groups.

Scale, rank and model selection in evaluations of land cover influence on wildlife–vehicle collisions

Abstract ContextExamining land cover’s influences on roadkills at single predetermined scales is more common than evaluating multiple scales, but examining land cover at the appropriate scale may be necessary for efficient design of mitigation measures, and that appropriate scale may be difficult to discern a priori. In addition, the taxonomic rank at which data is analysed may influence results and subsequent conclusions concerning mitigation. AimsThe objective of the present study was to assess the influence of variation in spatial scales of land cover explanatory variables and taxonomic rank of response variables in models of wildlife–vehicle collisions (WVCs). Research questions include: (1) do the scales of land cover measurement that produce the highest quality models differ among species; (2) do the factors that influence roadkill events differ within species at different scales of measurement and among species overall; and (3) does the taxonomic rank at which data is analysed influence the selection of explanatory variables? MethodsFour frequent WVC species representing diverse taxonomic classes, i.e. two mammals (Cerdocyon thous and Hydrochaeris hydrochaeris), one reptile (Caiman yacare) and one bird (Caracara plancus), were examined. WVCs were buffered, land cover classes from classified satellite imagery at three buffer radii were extracted, and logistic regression model selection was used. Key resultsThe scale of land cover variables selected for the highest quality models (and the selected variables themselves) may vary among wild fauna. The same explanatory variables and formulae are not always included in the candidate models in all compared scales for a given species. Explanatory variables may differ among taxonomically similar species, e.g. mammals, and pooling species at higher taxonomic ranks can result in models that do not correspond with species-level models of all pooled species. ConclusionsThe most accurate analyses of WVCs will likely be found when species are analysed individually and multiple scales of predictor variable collection are evaluated. ImplicationsMitigating the effects of roadways on wildlife population declines for both common and rare species is resource intensive. Resources spent optimising models for spatially targeting management actions may reduce the amount of resources used and increase the effectiveness of these actions.

Patterns and composition of medium and large vertebrate roadkill, based on six annual surveys along two adjoining highways in south-eastern Queensland, Australia

Six annual single-pass roadkill surveys along two adjoining rural Queensland highways near Carnarvon Gorge National Park revealed 612 medium-size to large vertebrates, representing more than 18 taxa. Most were mammals (92%), particularly macropods. Losses averaged 0.26 animals km–1 year–1 (range = 0.17–0.33), with variation possibly reflecting road repair/reconstruction and record seasonal rainfalls. Annual roadkill totals for the 390-km highway were projected to be over 5000 vertebrates, with more than half being large macropods. A consistent hotspot or ecological trap was noted along a 17-km high-traffic-volume stretch north of Roma. Because the sparsely populated outback is habitat for much Australian wildlife, multiyear baseline data are vital to identify the magnitude of the problem and inform future research.