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International audience; Understanding road-kill patterns is the first step to assess the potential effects of road mortality on wildlife populations, as well as to define the need for mitigation and support its planning. Reptiles are one of the vertebrate groups most affected by roads through vehicle collisions, both because they are intentionally killed by drivers, and due to their biological needs, such as thermoregulation, which make them more prone to collisions. We conducted monthly road surveys (33 months), searching for carcasses of freshwater turtles, lizards, and snakes on a 277-km stretch of BR-101 road in Southernmost Brazil to estimate road-kill composition and magnitude and to describe the main periods and locations of road-kills. We modeled the distribution of road-kills in space according to land cover classes and local traffic volume. Considering the detection capacity of our method and carcass persistence probability, we estimated that 15,377 reptiles are road-killed per year (55 reptiles/km/year). Road-kills, especially lizards and snakes, were concentrated during summer, probably due to their higher activity in this period. Road-kill hotspots were coincident among freshwater turtles, lizards, and snakes. Road-kill distribution was negatively related to pine plantations, and positively related to rice plantations and traffic volume. A cost-benefit analysis highlighted that if mitigation measures were installed at road-kill hotspots, which correspond to 21% of the road, they could have avoided up to 45% of recorded reptile fatalities, assuming a 100% mitigation effectiveness. Given the congruent patterns found for all three taxa, the same mitigation measures could be used to minimize the impacts of collision on local herpetofauna.

Made available in DSpace on 2018-12-11T17:22:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-01-01 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. Setor de Ecologia Aplicada Universidade Federal de Lavras PPG Análise e Modelagem de Sistemas Ambientais Departamento de Cartografia Instituto de Geociências Universidade Federal de Minas Gerais NERF-UFRGS Núcleo de Ecologia de Rodovias e Ferrovias Departamento de Biologia Universidade Federal do Rio Grande do Sul Programa de Pós Graduação em Ecologia Instituto de Biociências Universidade Federal do Rio Grande do Sul Centro Brasileiro de Estudos em Ecologia de Estradas (CBEE) Universidade Federal de Lavras Núcleo em Ecologia e Desenvolvimento Sócio-Ambiental de Macaé Universidade Federal do Rio de Janeiro (UFRJ) Autopista Fluminense S. A., Av. São Gonçalo, 100, Unidade 101, Bairro Boa Vista Universidade Federal de Uberlandia (UFU) Programa de Pós Graduação em Políticas Públicas Núcleo de Ciências Ambientais Universidade de Mogi das Cruzes Spatial Ecology and Conservation Lab (LEEC) Departamento de Ecologia Universidade Estadual Paulista - UNESP Programa de Pós-graduação em Ecologia e Biodiversidade Instituto de Biociências Universidade Estadual Paulista - UNESP Ciências Biológicas Núcleo de Ciências Ambientais Universidade de Mogi das Cruzes Caipora Cooperativa, Rua Desembargador Vitor Lima, 260/908 Setor de Mastozoologia Museu de Ciências Naturais Fundação Zoobotânica do Rio Grande do Sul Programa de Pós Graduação em Ecologia Animal Universidade Federal do Rio Grande do Sul Departamento de Zoologia Instituto de Biociências Universidade Federal do Rio Grande do Sul UFRGS Universidade Federal de São Carlos Pós Graduação em Conservação em Fauna Universidade Federal de São Carlos Programa de Pós Graduação em Genética Biodiversidade e Conservação Universidade Estadual do Sudoeste da Bahia Jequié Departamento de Biologia Universidade Federal Rural de Pernambuco Universidade Federal de Mato Grosso do Sul, Pioneiros Departamento de Biologia Centro de Ciências Exatas Naturais e da Saúde Universidade Federal do Espírito Santo Departamento de Ciências Biológicas Universidade Estadual do Sudoeste da Bahia Laboratório de Ecologia e Conservação Universidade Federal da Fronteira Sul, Campus Erechim Universidade Federal do Rio Grande do Sul CETESB - Companhia Ambiental do Estado de São Paulo Universidade Federal do Pampa Universidade Veiga de Almeida Instituto Tecnológico de Transportes e Infraestrutura Universidade Federal do Paraná Laboratório de Ecologia de Manguezal Instituto de Estudos Costeiros Universidade Federal do Pará Programa de Pós-Graduação em Biologia Universidade do Vale do Rio dos Sinos Arcadis Laboratório de Ecologia e Biogeografia de Mamíferos Universidade Estadual de Goiás Laboratório de Zoologia Universidade Federal do Amazonas, Coroado I IPÊ Pantanal, Rua Licuala, 622, Damha 1 Departamento de Patologia Veterinária Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista Faculdade de Biociências Pontifícia Universidade Católica do Rio Grande do Sul Instituto Chico Mendes de Conservação da Biodiversidade – ICMBio Ministério do Meio Ambiente Centro Universitario de Rivera Universidad de la República, Ituzaingó 667 Departamento de Genética e Evolução Universidade Federal de São Carlos Laboratório de Biodiversidade Molecular e Conservação Departamento de Genética e Evolução Universidade Federal de São Carlos Centro Universitário de Anápolis Universidade Federal da Paraíba Departamento de Engenharia e Meio Ambiente Rua Botuverá, 257 Dom Joaquim Departamento de Ecologia -Universidade Federal do Rio Grande do Norte Instituto Conservação Brazil (ICB), Rua dos Angicos, 185, Recanto dos Angicos R Embrapa Pantanal, Rua 21 de Setembro, n 1.880, Bairro Nossa Senhora de Fátima, Caixa Postal: 109 Departamento de Biologia Geral Agrárias e Humanas Instituto de Ciências da Saúde Centro Universitário do Planalto de Araxá UNIARAXÁ Hori Consultoria Ambiental, Rua Paulo Gorski, 2058, Mussunguê Centro Brasileiro para Conservação dos Felinos Neotropicais, Av. Emílio Antonon, 1000 – Chácara Aeroporto Programa de Pós-Graduação em Ecologia e Recursos Naturais Universidade Federal de São Carlos Programa de Pós Graduação em Ecologia Instituto de Ciências Biológicas Universidade de Brasília, Campus Darcy Ribeiro Centro de Ciências Biologicas e de Saude Universidade Federal de São Carlos Instituto de Ciências Biologicas Universidade de Brasília Núcleo de Licenciamento Ambiental, Superintendência do Ibama em São Paulo/SP, Alameda Tietê, 637, 10° andar Curso de Medicina Veterinária Centro Universitário de Lavras (Unilavras) Departamento de Engenharia Florestal Universidade de Brasília Pontifícia Universidade Católica do Paraná Universidade Estadual de Goiás Complexo Cultural e Científico de Peirópolis Departamento de Biologia Universidade Federal de Lavras Spatial Ecology and Conservation Lab (LEEC) Departamento de Ecologia Universidade Estadual Paulista - UNESP Programa de Pós-graduação em Ecologia e Biodiversidade Instituto de Biociências Universidade Estadual Paulista - UNESP Departamento de Patologia Veterinária Faculdade de Ciências Agrárias e Veterinárias Universidade Estadual Paulista

When solving numerically the stiff second order ODE system obtained after semidiscretizing the wave-type partial differential equation (PDE) with the finite element method (FEM), and similarly to the HHT-α method, which allows the numerical damping of the undesirable high frequency modes associated to FEM semidiscretization, we have constructed a modification of the 2-order BDF method (the BDF2 method), which we have called BDF-α. This new method is second-order accurate and with a smaller local truncation error than the BDF2, it is unconditionally stable for some values of α and it permits a parametric control of numerical dissipation.

In this paper we modify the MEBDF method using the NDFs as predictors instead of the BDFs. We have done it in three different ways: changing both predictors of the MEBDF, changing only the first predictor and changing only the second one. We have called the new methods MENDF, MENBDF and MEBNDF respectively. The new methods are A-stable up to order 4 and the stability properties of the new methods are better than the MEBDF method.

In this paper we modify the EBDF method using the NDFs as predictors instead of BDFs. This modification, that we call ENDF, implies the local truncation error being smaller than in the EBDF method without losing too much stability. We will also introduce two more changes, called ENBDF and EBNDF methods. In the first one, the NDF method is used as the first predictor and the BDF as the second predictor. In the EBNDF, the BDF is the first predictor and the NDF is the second one. In both modifications the local truncation error is smaller than in the EBDF. Moreover, the EBNDF method has a larger stability region than the EBDF.

After the extensive research on the capabilities of the Boundary Integral Equation Method produced during the past years the versatility of its applications has been well founded. Maybe the years to come will see the in-depth analysis of several conflictive points, for example, adaptive integration, solution of the system of equations, etc. This line is clear in academic research. In this paper we comment on the incidence of the manner of imposing the boundary conditions in 3-D coupled problems. Here the effects are particularly magnified: in the first place by the simple model used (constant elements) and secondly by the process of solution, i.e. first a potential problem is solved and then the results are used as data for an elasticity problem. The errors add to both processes and small disturbances, unimportant in separated problems, can produce serious errors in the final results. The specific problem we have chosen is especially interesting. Although more general cases (i.e. transient)can be treated, here the domain integrals can be converted into boundary ones and the influence of the manner in which boundary conditions are applied will reflect the whole importance of the problem.