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

Abstract

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.

Influence of climate variables on roadkill rates of wild vertebrates in the cerrado biome, Brazil

“…In Europe, USA and Canada some studies tried to understand this (CLEVENGER et al, 2003;GRILO et al, 2009;GRILO et al, 2012;D'AMICO et al, 2015;GARRIGA et al, 2017) and concluded that temperature influences roadkill (D'AMICO et al, 2015;GARRIGA et al, 2017). In Brazil, we have just started, our researches investigate if there are more roadkill in the rainy or dry season (BUENO; ALMEIDA, 2010;RAMOS et al, 2011;BRAZ;FRANÇA, 2016) or the stretches of the highway with higher roadkill rates (CÁCERES et al, 2012;BUENO et al, 2012;SANTANA, 2012;FERREIRA et al, 2014;CARVALHO et al, 2015;ASCENSÃO et al, 2017;SANTOS et al, 2017). We still need to understand better the influence of climate variables on roadkill in tropical countries, such as Brazil.…”

Spatio-Temporal Patterns of Mammal Road Mortality in Middle Magdalena Valley, Colombia

“…For example, the generalist behaviour of D. marsupialis and P. cancrivorus, the freeze antipredator response of C. thous, and the clumsy and slow terrestrial locomotion of T. mexicana have been invoked to explain the high road mortality rates of these species (Artavia et al 2015). Likewise, many species do not show car avoidance behaviour, increasing their roadkill probability, especially when population's densities are high (Jaeger et al 2005, Ascensão et al 2017. Moreover, wildlife communities with high species richness will be more susceptible to road mortality effects because a higher number of species are prone to be roadkilled (Ascensão et al 2017).…”

“…Likewise, many species do not show car avoidance behaviour, increasing their roadkill probability, especially when population's densities are high (Jaeger et al 2005, Ascensão et al 2017. Moreover, wildlife communities with high species richness will be more susceptible to road mortality effects because a higher number of species are prone to be roadkilled (Ascensão et al 2017). Road size, road quality, and vehicular speed represent additional factors that could influence the number of local wildlife roadkills and deserve further investigation.…”

“…Wildlife roadkills are assumed to be spatially and temporally aggregated in function of species' traits, road attributes, landscape features, and climate (Jaeger et al 2005, Gunson et al 2011, Marsh & Jaeger 2015. Road segments with significant roadkill aggregations (hotspots) are frequently used as priority locations for mitigation measures (Coelho et al 2008, van der Grift et al 2013, Ascensão et al 2017. However, the identification of hotspots location is insufficient to understand how different species occupy and move through the landscape surrounding road networks , Beckmann et al 2010.…”

“…Thus, the challenge is to identify wildlife crossing locations capable of improving multispecies connectivity at regional scales over the long term (Mimet et al 2016). In this sense, roadkill research should integrate connectivity analyses with hotspot identification as criteria for ranking where to install mitigation measures (see Ascensão et al 2017).…”