8 research outputs found

    Review of the underpass alocation on the highway SP-225, Brotas-SP, Brazil, and the relationship with wild animals roadkills and landscape structure

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    The Road Ecology theme is new in Brazil and in Latin America in \ud general. Few studies and scientific publications were made in this area \ud with specific and replicable methodology. Underpasses were allocated on \ud the highway SP- 225, in the year of 2008, according to previous studies of \ud hotspots of roadkills made by IBAMA (Environmental Brazilian Institute), \ud but none of them considered the influence of the landscape structure on \ud the surrounding habitat. So, we aimed to analyze and understand which \ud component of the landscape structure can influence the roadkills in a \ud Brazilian highway and analyze if these underpasses was located in areas \ud of hotspots roadkills. Medium and large mammals carcasses were \ud collected by Centrovias (a private enterprise that managed the road) from \ud May 2005 to June 2006 in 56 km stretch on the highway SP- 225 in the \ud 110 \ud city of Brotas, São Paulo, Brazil. Were created occurrences reports for \ud each roadkilled animal containing: date, time, local on the highway (km + \ud m), geographic coordinate and the specie affected. Forest-patch metrics \ud (number of fragments, proportion of forest and size of the largest pacth) \ud were extracted from a 2008 CBERS 2B-CCD image using Fragstats \ud (version 3.3) to examine the best predictor to medium and large \ud mammals roadkills. Following a visual classification three land cover \ud classes were mapped (forest, non-forest and water) and 13 buffers zones \ud with 5 km were selected around the highway SP-225. An exploratory data \ud analysis was conducted through the Pearson‟s correlation and 6 models (1 \ud null model) were built to conduct a model selection procedure based on \ud the AICc value. There were 48 medium and large mammals roadkills on \ud the 56 stretch sampled between May 2005 and June 2006. The best model \ud selected to predict medium and large mammals roadkills on the SP- 225, \ud was the proportion of forest (wAICc = 0.97) on the 5 km surrounding \ud habitat. From 13 buffer zones analyzed, 4 presented the highest number \ud of roadkills (mean = 21.75, sd = 2.21) and the highest proportion of \ud forest (mean = 24.17, sd = 2.34), so the higher the proportion of forest, \ud higher will be the number of roadkills. In two of these buffer zones were \ud allocated an appropriate number of underpasses. In all the buffer zones \ud we had roadkills occurrence, but in three of them none underpass was \ud allocated. Despite the fact that there is a low number of roadkills in these \ud buffers (range: 2-4) the presence of at least one underpass will be \ud necessary to avoid these roadkills. The others buffers also had a low \ud number of roadkills (range: 4-6) but there are almost the same number of \ud underpasses allocated in the buffers zones with the higher number of \ud roadkills. The number of roadkills is strictly related to the proportion of \ud forest in the surrounding habitat, so we highlight the importance of the \ud landscape structure to predict the occurrence of medium size and large \ud bodied mammals roadkills and the use of this tool to allocate underpasses \ud in future road ecology studies

    NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

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    Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

    NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

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    Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data

    NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

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    Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data
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