This paper examines the frequencies of mammal roadkill in two adjacent biogeographic ecoregions (Atlantic Forest and Cerrado) of Brazil. Mammals were recorded during a seven-year period and over 3,900 km of roads, in order to obtain data for frequencies of species in habitats (sites) and frequencies of species killed by cars on roads. Sites (n = 80) within ecoregions (Cerrado, n = 57; Atlantic Forest, n = 23) were searched for records of mammals. Species surveyed in the entire region totaled 33, belonging to nine orders and 16 families. In the Cerrado, 31 species were recorded in habitats; of these, 25 were found dead on roads. In the Atlantic Forest ecoregions, however, we found 21 species in habitats, 16 of which were also found dead on roads. There was no overall significant difference between ecoregions for frequencies of occurrence in habitats or for roadkills, but there were differences between individual species. Hence, anteaters were mostly recorded in the Cerrado ecoregion, whereas caviomorph rodents tended to be more frequent in the Atlantic Forest ecoregion (seen mainly by roadkills). The greater number of species (overall and threatened) and the greater abundance of species records in the Cerrado suggest that this ecoregion has a greater biodiversity and is better conserved than the Atlantic Forest ecoregion, in the state of Mato Grosso do Sul, south-western Brazil

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Mortality from collision with vehicles is the most visible impact of road traffic on wildlife. Mortality due to roads (hereafter road-kill) can affect the dynamic of populations of many species and can, therefore, increase the risk of local decline or extinction. This is especially true in Brazil, where plans for road network upgrading and expansion overlaps biodiversity hotspot areas, which are of high importance for global conservation. Researchers, conservationists and road planners face the challenge to define a national strategy for road mitigation and wildlife conservation. The main goal of this dataset is a compilation of geo-referenced road-kill data from published and unpublished road surveys. This is the first Data Paper in the BRAZIL series (see ATLANTIC, NEOTROPICAL, and BRAZIL collections of Data Papers published in Ecology), which aims make public road-kill data for species in the Brazilian Regions. The dataset encompasses road-kill records from 45 personal communications and 26 studies published in peer-reviewed journals, theses and reports. The road-kill dataset comprises 21,512 records, 83% of which are identified to the species level (n = 450 species). The dataset includes records of 31 amphibian species, 90 reptile species, 229 bird species, and 99 mammal species. One species is classified as Endangered, eight as Vulnerable and twelve as Near Threatened. The species with the highest number of records are: Didelphis albiventris (n = 1,549), Volatinia jacarina (n = 1,238), Cerdocyon thous (n = 1,135), Helicops infrataeniatus (n = 802), and Rhinella icterica (n = 692). Most of the records came from southern Brazil. However, observations of the road-kill incidence for non-Least Concern species are more spread across the country. This dataset can be used to identify which taxa seems to be vulnerable to traffic, analyze temporal and spatial patterns of road-kill at local, regional and national scales and also used to understand the effects of road-kill on population persistence. It may also contribute to studies that aims to understand the influence of landscape and environmental influences on road-kills, improve our knowledge on road-related strategies on biodiversity conservation and be used as complementary information on large-scale and macroecological studies. No copyright or proprietary restrictions are associated with the use of this data set other than citation of this Data Paper.

Abstract. The data set represents the first attempt at a large-scale inventory of non-volant mammals, with potential applications to performing macroecological studies, developing conservation strategies, and undertaking population and community ecology research, but also to evaluate the ecological consequences of fragmentation and defaunation. Our objectives for compiling these data were to summarize information about inventories of non-volant mammals in the critically important area of the Upper Parana River Basin by focusing on species richness and index of frequency of occurrence and to identify gaps in knowledge regarding non-volant mammal communities in order to guide future sampling efforts. The data set comprises studies on communities of non-volant mammals from 52 locations covering more than 1,000 km 2 and comprises portion of four Brazilian states in the Upper Parana River Basin. We listed 81 species of non-volant mammals distributed among 58 genera, 22 families, and 9 orders. Rodentia (28 species) was the richest order, followed by Carnivora (17 spp.) and Didelphimorphia (15 spp.). The richest family was Cricetidae (20 spp.), followed by Didelphidae (15 spp.), and Dasypodidae and Felidae (six spp.). Considering national conservation status, one species are considered endangered and 16 vulnerable. Considering global conservation status, 7 species are considered vulnerable, 10 are considered near threatened, and 6 are data deficient. According to the index of frequency of occurrence, Myrmecophaga tridactyla was the most frequent species, occurring at 88.64% of all sites, while 25 species were considered very restricted, occurring in just 2.56% of all sites. In general, the non-volant mammal fauna was composed of mainly very restricted (VR, 25 species) and localized species (L, 25 species), which account for 61.7% of the known species, while 38.3% are restricted (R, 8 species), common (C, 16 species), and widespread (W, 7 species). Seven marsupials and five small rodents had their distributions extended in the central-south of Brazil. All of these species are considered data deficient or threatened, which highlights the importance of these records. No copyright restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications. We also request that researchers and teachers inform us of how they are using the data.