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We used species distribution modeling to investigate the potential effects of climate change on 24 species of Neotropical anurans of the genus Melanophryniscus. These toads are small, have limited mobility, and a high percentage are endangered or present restricted geographical distributions. We looked at the changes in the size of suitable climatic regions and in the numbers of known occurrence sites within the distribution limits of all species. We used the MaxEnt algorithm to project current and future suitable climatic areas (a consensus of IPCC scenarios A2a and B2a for 2020 and 2080) for each species. 40% of the species may lose over 50% of their potential distribution area by 2080, whereas 28% of species may lose less than 10%. Four species had over 40% of the currently known occurrence sites outside the predicted 2080 areas. The effect of climate change (decrease in climatic suitable areas) did not differ according to the present distribution area, major habitat type or phylogenetic group of the studied species. We used the estimated decrease in specific suitable climatic range to set a conservation priority rank for Melanophryniscus species. Four species were set to high conservation priority: M. montevidensis, (100% of its original suitable range and all known occurrence points potentially lost by 2080), M. sp.2, M. cambaraensis, and M. tumifrons. Three species (M. spectabilis, M. stelzneri, and M. sp.3) were set between high to intermediate priority (more than 60% decrease in area predicted by 2080); nine species were ranked as intermediate priority, while eight species were ranked as low conservation priority. We suggest that monitoring and conservation actions should be focused primarily on those species and populations that are likely to lose the largest area of suitable climate and the largest number of known populations in the short-term.

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

No abstract