English

Abstract

The evaluation of road-kill spatial patterns is an important tool to identify priority locations for mitigation measures aiming to reduce wildlife mortality on roads. Single target or multi-species approaches are usually adopted to implement such measures, although their success must be evaluated. We aim to test if road-kill hotspots are coincident among different vertebrate groups. If this is true, data on accidents from one group could be used to plan measures applicable to other groups. We identified hotspots using five different grouping criteria: vertebrate classes (reptiles, mammals or birds), body size (large or small), species commonness (common or rare), type of locomotion (flying or non-flying), and time of activity (preferably nocturnal/crepuscular or diurnal). We analyzed data from road-kill surveys on four roads in southern Brazil, each one with at least one year of monitoring. Using SIRIEMA software, we performed a modified Ripley's K statistic to recognize scales of road-kill aggregation and we carried out Hotspot analyses to identify the location of road-kill aggregations for each group described above in each road. To test for similarity in hotspot location among different groups we performed an association test using correlation as resemblance measure. Hotspot analyses and association tests were done using different scales to evaluate scale effect on similarities. Correlation results between groups presented low values in small scales although had a tendency to increase with increasing scales. Our results show that road-kill hotspots are different among groups, especially when analyzed in small scales. We suggest that, for a successful biodiversity approach in mitigation, one should first select general hotspots in large scales and then identify specific hotspots in small scales to implement specific measures. These findings are relevant in a context of road networks already implemented, where mitigation measures are being planned to reduce their impact on wildlife.