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.
•Sampling frequency strongly affects roadkill hotspot identification.•Hotspot spatial accuracy declines rapidly with increasing interval between surveys.•Missing true hotspots is the main source of error.•Hotspot accuracy is lower for small-bodied species.•Widely used study designs may provide inaccurate hotspots.
Recent studies suggest that roads can significantly impact bat populations. Though bats are one of the most threatened groups of European vertebrates, studies aiming to quantify bat mortality and ...determine the main factors driving it remain scarce. Between March 16 and October 31 of 2009, we surveyed road-killed bats daily along a 51-km-long transect that incorporates different types of roads in southern Portugal. We found 154 road-killed bats of 11 species. The two most common species in the study area,
Pipistrellus kuhlii
and
P. pygmaeus
, were also the most commonly identified road-kill, representing 72 % of the total specimens collected. About two-thirds of the total mortality occurred between mid July and late September, peaking in the second half of August. We also recorded casualties of threatened and rare species, including
Miniopterus schreibersii
,
Rhinolophus ferrumequinum
,
R. hipposideros
,
Barbastella barbastellus
, and
Nyctalus leisleri
. These species were found mostly in early autumn, corresponding to the mating and swarming periods. Landscape features were the most important variable subset for explaining bat casualties. Road stretches crossing or in the vicinity of high-quality habitats for bats—including dense Mediterranean woodland (“montado”) areas, water courses with riparian gallery, and water reservoirs—yielded a significantly higher number of casualties. Additionally, more road-killed bats were recorded on high-traffic road stretches with viaducts, in areas of higher bat activity and near known roosts.
Collision with vehicles is an important source of bird mortality, but it is uncertain why some species are killed more often than others. Focusing on passerines, we tested whether mortality is ...associated with bird abundances, and with traits reflecting flight manoeuvrability, habitat, diet, and foraging and social behaviours. We also tested whether the species most vulnerable to road-killing were scarcer near (<500m) or far (>500–5000m) from roads. During the breeding seasons of 2009–2011, we surveyed roadkills daily along 50km of roads, and estimated bird abundances from 74 point counts. After correcting for phylogenetic relatedness, there was strong correlation between roadkill numbers and the abundances of 28 species counted near roads. However, selectivity indices indicated that Blue tit (Parus caeruleus), Blackcap (Sylvia atricapilla) and European goldfinch (Carduelis carduelis) were significantly more road-killed than expected from their abundances, while the inverse was found for seven species. Using phylogenetic generalised estimating equations, we found that selectivity indexes were strongly related to foraging behaviour and habitat type, and weakly so to body size, wing load, diet and social behaviour. The most vulnerable passerines were foliage/bark and swoop foragers, inhabiting woodlands, with small body size and low wing load. The species most vulnerable to road collisions were not scarcer close to roads. Overall, our study suggests that traits provide a basis to identify the passerine species most vulnerable to road collisions, which may be priority targets for future research on the population-level effects of roadkills.
•Roadkill numbers and bird abundances near roads were strongly correlated.•Some species (36%) were more (or less) killed than expected from their abundances.•Selective mortality was strongly related to foraging behaviour and habitat associations.•Small woodland passerines that often forage in shrubs and small trees were most vulnerable.•Bird communities near roads were not depleted in species most vulnerable to road killing.
The effects of roads on bats are still a poorly documented issue. Most of the available research focuses on large and high-traffic highways, while low-medium-traffic roads are often assumed to have ...negligible impacts. However, small roads are ubiquitous in landscapes around the world. We examined the effects of these roads, as well as habitat types, on the activity of three bat guilds (short-, mid- and long-range echolocators) and the most common bat species Pipistrellus kuhlii. We performed three bat acoustic surveys between May and October 2015, with these surveys being performed along twenty transects that were each 1000 m long and perpendicular to three roads with different traffic volumes. The surveys were performed in dense Mediterranean woodland (“montado”) and open agricultural field habitats, which were the two dominant land uses. At each transect, bat activity was simultaneously registered at 0, 50, 100, 200, 500 and 1000 m from the road with the use of an ultrasound recorder. According to the generalized linear mixed effects models, the overall activity of bats and of the short- and mid-range echolocators increased with increased distance from the roads and was dependent on the surrounding habitats. In contrast, the long-range echolocators and P. kuhlii were more tolerant to road. Our results also show that the activity was higher in woodland areas, however road verges seem to be a significant habitat in an open agricultural landscape. The major negative effects extended to approximately 300 m from the roads in woodlands and penetrate further into the open field (>500 m). The management of roadside vegetation, combined with the bat habitat improvement in areas that are further from the roads, may mitigate the negative effects. To make road-dominated landscapes safer for bats, the transport agencies need to balance the trade-offs between habitat management and road kill risk.
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•Low-medium traffic roads have a major negative impact on bat activity.•Road-effect zone is guild-specific and depends on the surrounding habitat.•Negative effects extend to about 300 m from the roads in woodland and >500 m in open field habitat.•High-suitable habitats buffer the negative effects of roads.•Road verges may provide resources for bats in lower-suitable habitat.
The effective management of species with small and fragmented populations requires an in-depth understanding of how the effects of human-induced habitat disturbance shape the structure and gene flow ...at fine spatial scales. Identification of putative environmental barriers that affect individual exchange among subpopulations is imperative to prevent extinction risks. Here, we investigated how landscape affects the gene flow and relatedness structure of a population of the endangered lesser horseshoe bat (Rhinolophus hipposideros). We also assessed the effects of sexbiased dispersal on genetic relatedness. We genotyped 287 bat samples collected across southern Portugal and developed resistance surfaces for landscape variables hypothesized to affect gene flow. Then, we used spatially explicit models to fit relatedness distance through the resistance surfaces. We found genetic evidence of sex-biased dispersal and identified a significant fine scale structuring in the relatedness regarding females, the philopatric sex. Males displayed uniform levels of relatedness throughout the landscape. The results indicated less relatedness between the female´ from roosts located on proximity of roads than in roosts away from roads. Also, when analysing the sexes together the relatedness on roosts separated by highway were subtly less related in comparison to those occurring on the same side. Roads seem to be major shapers of the contemporary population structure of females, regardless of being relatively recent structures in the landscape. Furthermore, the relatedness patterns detected suggested that high tree density among roosts and continuity of forest patches in broader surrounding areas, promotes the relatedness among individuals. Landscape heterogeneity among roosts slightly decreases genetic relatedness. Nevertheless, those relationships are still weak, suggesting that population structuring driven by those factors is slowly ongoing. Thus, effective management measures should focus on issues for promoting safe road passages and suitable habitat corridors, allowing for the exchange of individuals and gene flow among lesser horseshoe bat roosts.
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•Landscape resistance is the major driver of gene flow for lesser horseshoe bats.•Effect of landscape features on gene flow is sex-specific, more noticed in females.•Roads may be acting as semi-permeable filters, slightly reducing gene flow.•Tree cover and landscape homogeneity promote genetic relatedness.•No current clear genetic differentiation, but long-term structuring may be ongoing.
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.
•Bat roadkill hotspot locations may shift along time.•Stable hotspots accounted only for 3% of road length, but for 27% of roadkilled bats.•Spatiotemporal congruence of hotspots declined with decreasing vegetation productivity.•Water stress on roadsides decrease the persistence of bat roadkill hotspots.•Remote sensing information may be a tool for planners to minimize the impact of roads.
Context
Road impacts on biodiversity are increasing worldwide. Few attempts have been made to integrate multiple taxonomic groups into roadkill mitigation plans, while using remotely sensed habitat ...suitability and functional connectivity.
Objectives
We pinpoint high-risk road locations (road planning units) for 19 woodland species from different taxonomic groups (non-flying mammals, birds, and bats) to enhance prioritisation and versatility of roadkill mitigation plans.
Methods
In Southern Portugal, we collected species occurrence data, roadkill, and high-resolution satellite imageries, along 15 years. We identified remotely sensed habitat metrics, in turn weighted together with functional connectivity models and road metrics to estimate roadkill vulnerability, using random forests. The roadkill cumulative risk across species is then estimated, as well the likelihood variation within and between taxonomic groups to verify prediction consistency.
Results
Remote sensing information thoroughly explained habitat suitability, identifying similar metrics within each group, and non-uniform environmental tolerance across species. Functional connectivity and habitat suitability significantly explained mortality, highlighting connected woodlands and neighbouring matrices. The roadkill cumulative risk endorses a conspicuous prioritisation of road planning units for implementing mitigation structures useful for multiple species, with high precision and low probability variation within each group. Some discrepancies in prediction consistency still emerge after group comparisons regarding bats.
Conclusions
We provide novel insights for multitaxa ecological responses and roadkill evaluations, demonstrating a possible spatial prioritisation in mortality patterns from species with different traits. The identified road units support resilience and multifunctionality over long-term, enabling to assist cost-effective mitigation plans. Findings ultimately offer versatility during the mitigation planning phase throughout the identification of road sub-optimal units, and opportunity costs given their potential for different taxa.
The European rabbit Oryctolagus cuniculus, a keystone species of Mediterranean ecosystems, is the target of several recovery and management plans throughout the Iberian Peninsula. The majority of ...these plans are limited in time by budget constraints and lack postintervention monitoring of population trends. This study was conducted in south‐west Portugal and aimed to understand the effect of habitat management and its early cessation on rabbit populations. We assessed rabbit presence and relative abundance before management (2007), during the implementation of measures (2008), immediately after (2009) and 3 years after measures ended (2012). We applied a model selection approach, using generalized linear models to determine the relative importance of MANAGED and UNMANAGED habitat features on rabbit presence in each year. We used spatial eigenvector mapping to describe the spatial autocorrelation in rabbit presence and a variation partitioning approach to quantify the relative effects of management‐related variables, unmanaged environmental descriptors and spatial characteristics on rabbit presence. Rabbit presence and abundance increased shortly after the management intervention but decreased 3 years after. Rabbit presence was positively related to the proximity of installed crops and the existence of favorable soils for digging. Habitat management‐related variables explained most of the variation in all models. Habitat improvement actions, particularly the sowing of pastures, contributed to increased rabbit presence. We propose a continued long‐term intervention and the cultivation of crops with auto‐regeneration properties (e.g., subterranean clover—Trifolium subterraneum) with the aim of continuing to increase rabbit presence and abundance in areas where rabbit populations are scarce.
This study, conducted in south‐west Portugal, aimed to understand the effect of habitat management and its early cessation on European rabbit populations. Rabbit presence and abundance increased shortly after the management intervention (2008 and 2009) but decreased, to pre‐management levels, three years after (2012). Habitat improvement actions, particularly the sowing of pastures, contributed to increased rabbit presence and habitat management‐related variables explained most of the variation in all models, although their influence decreased in 2012.
•Efficient species detection over large scales is key to infer distribution changes.•We compare method-specific occupancy detection of Cabrera voles in large grid cells.•Sign surveys provided higher ...detectability at lower cost than owl pellet analysis.•Large scale monitoring of certain small mammals may rely on sign survey methods.
Monitoring the status and trends of wildlife is key to understand how species respond to natural and human-derived threats, and to evaluate and improve conservation planning and management. Large-scale, grid-based assessment of species distribution, abundance, and population trends over time is an important component of biodiversity monitoring. However, such assessments still present important challenges related, for instance, to how the choice of the sampling method may affect species detectability and thus, overall data accuracy. Here, we address this issue, focusing on the Cabrera vole (Microtus cabrerae), a threatened small mammal, listed in the Habitats Directive (Annexes II and IV), hence requiring regular evaluation of its population status and trends. We used occupancy modelling to estimate method-specific detection probability of the species over large-scale, grid-based (10 × 10 km2) surveys relying on two non-invasive sampling techniques: sign surveys and owl pellet analysis. Results provided evidence for a greater cost-effectiveness of sign surveys compared to owl pellet analysis for detecting the species in occupancy surveys, suggesting that large-scale population monitoring of Cabrera voles (or other species also producing easily identifiable signs of their presence) may fairly rely on sign-surveys. Overall, our study supported the view that while owl pellet analysis provides a valuable option when the aim is to assess small mammal assemblages (i.e. multiple species) in a region, other complementary methods may be required to increase the detection probability of certain species that because of their secretive behaviour or rarity remain less predated by owls. We thus argue that the choice of the sampling method should be context-dependent and evaluated based on the study aims, the surveyed area (i.e. local factors), the target species (i.e. life history traits) and the available resources. Based on our results we recommend that researchers and managers explore survey-design trade-offs to ensure the proposed designs have sufficient power to detect real population trends.
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