6 research outputs found

    ATLANTIC ‐ PRIMATES : a dataset of communities and occurrences of primates in the Atlantic Forests of South America

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    Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co‐occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. 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.Fil: Culot, Laurence. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Pereira, Lucas Augusto. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Agostini, Ilaria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Universidad Nacional de Misiones. Instituto de Biología Subtropical; Argentina. Centro de Investigaciones del Bosque Atlántico; ArgentinaFil: de Almeida, Marco Antônio Barreto. Pontificia Universidade Católica do Rio Grande do Sul; BrasilFil: Alves, Rafael Souza Cruz. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Baldovino, María Celia. Centro de Investigaciones del Bosque Atlántico; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo. Instituto Miguel Lillo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Di Bitetti, Mario Santiago. Centro de Investigaciones del Bosque Atlántico; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Oklander, Luciana Inés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; ArgentinaFil: Holzmann, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta. Instituto de Bio y Geociencias del NOA. Universidad Nacional de Salta. Facultad de Ciencias Naturales. Museo de Ciencias Naturales. Instituto de Bio y Geociencias del NOA; ArgentinaFil: Dums, Marcos. RUMO S.A. Licenciamento Ambiental; BrasilFil: Lombardi, Pryscilla Moura. RUMO S.A. Licenciamento Ambiental; BrasilFil: Bonikowski, Renata Twardowsky Ramalho. RUMO S.A. Licenciamento Ambiental; BrasilFil: Age, Stéfani Gabrieli. RUMO S.A. Licenciamento Ambiental; BrasilFil: Souza Alves, João Pedro. Universidade Federal de Pernambuco; BrasilFil: Chagas, Renata. Universidade Federal da Paraíba; BrasilFil: da Cunha, Rogério Grassetto Teixeira. Universidade Federal de Alfenas; BrasilFil: Valença Montenegro, Monica Mafra. Centro Nacional de Pesquisa e Conservaçao de Primates Brasileiros; BrasilFil: Ludwig, Gabriela. Centro Nacional de Pesquisa e Conservaçao de Primates Brasileiros; BrasilFil: Jerusalinsky, Leandro. Centro Nacional de Pesquisa e Conservaçao de Primates Brasileiros; BrasilFil: Buss, Gerson. Centro Nacional de Pesquisa e Conservaçao de Primates Brasileiros; BrasilFil: de Azevedo, Renata Bocorny. Centro Nacional de Pesquisa e Conservaçao de Primates Brasileiros; BrasilFil: Filho, Roberio Freire. Universidade Federal de Pernambuco; BrasilFil: Bufalo, Felipe. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Milhe, Louis. Université D'Avignon et des Pays du Vaucluse; FranciaFil: Santos, Mayara Mulato dos. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Sepulvida, Raíssa. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Ferraz, Daniel da Silva. Universidade do Estado de Minas Gerais; BrasilFil: Faria, Michel Barros. Universidade do Estado de Minas Gerais; BrasilFil: Ribeiro, Milton Cezar. Universidade Estadual Paulista Julio de Mesquita Filho; BrasilFil: Galetti, Mauro. Universidade Estadual Paulista Julio de Mesquita Filho; Brasi

    ATLANTIC-PRIMATES: a dataset of communities and occurrences of primates in the Atlantic Forests of South America

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    Primates play an important role in ecosystem functioning and offer critical insights into human evolution, biology, behavior, and emerging infectious diseases. There are 26 primate species in the Atlantic Forests of South America, 19 of them endemic. We compiled a dataset of 5,472 georeferenced locations of 26 native and 1 introduced primate species, as hybrids in the genera Callithrix and Alouatta. The dataset includes 700 primate communities, 8,121 single species occurrences and 714 estimates of primate population sizes, covering most natural forest types of the tropical and subtropical Atlantic Forest of Brazil, Paraguay and Argentina and some other biomes. On average, primate communities of the Atlantic Forest harbor 2 ± 1 species (range = 1–6). However, about 40% of primate communities contain only one species. Alouatta guariba (N = 2,188 records) and Sapajus nigritus (N = 1,127) were the species with the most records. Callicebus barbarabrownae (N = 35), Leontopithecus caissara (N = 38), and Sapajus libidinosus (N = 41) were the species with the least records. Recorded primate densities varied from 0.004 individuals/km 2 (Alouatta guariba at Fragmento do Bugre, Paraná, Brazil) to 400 individuals/km 2 (Alouatta caraya in Santiago, Rio Grande do Sul, Brazil). Our dataset reflects disparity between the numerous primate census conducted in the Atlantic Forest, in contrast to the scarcity of estimates of population sizes and densities. With these data, researchers can develop different macroecological and regional level studies, focusing on communities, populations, species co-occurrence and distribution patterns. Moreover, the data can also be used to assess the consequences of fragmentation, defaunation, and disease outbreaks on different ecological processes, such as trophic cascades, species invasion or extinction, and community dynamics. There are no copyright restrictions. 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. © 2018 by the The Authors. Ecology © 2018 The Ecological Society of Americ

    Surface Urban Heat Islands along a climatic gradient in the state of São Paulo

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    O impacto das ilhas de calor urbanas tornou-se mais significativo diante do atual contexto de mudanças climáticas. Compreender os padrões e os mecanismos que controlam esse fenômeno é crucial para desenvolver planos eficazes de adaptação climática nas cidades. Este estudo examinou 52 áreas urbanizadas e seus arredores não urbanizados no estado de São Paulo, desde pequenas cidades até a vasta região metropolitana de São Paulo, com mais de 20 milhões de habitantes. Utilizando dados do satélite Landsat 8 entre 2013 e 2023, obtidos pela plataforma Google Earth Engine, foram investigados os padrões de temperatura de superfície e das ilhas de calor urbanas de superfície (ICUS), bem como os impactos do uso e cobertura da terra na temperatura superficial. Os resultados destacam uma influência clara do ambiente urbano nas temperaturas superficiais, com uma diferença média de 5°C entre a temperatura de superfície urbanizada (TsU) e a temperatura de superfície não urbanizada (TsNU) durante a estação úmida, estação que expressou consistentemente um aquecimento mais pronunciado. Não foram encontradas diferenças significativas na Ts média considerando a população das cidades, revelando, na verdade um controle da continentalidade através da formação de um gradiente climático de Ts em escala regional ao longo do estado, tanto em áreas urbanizadas quanto não urbanizadas, em todas as formas de uso e cobertura da terra. Um limiar de NDVI entre 0,2 e 0,4 para áreas urbanizadas e entre 0,3 e 0,8 para áreas não urbanizadas foi identificado, com variações sazonais na distribuição, com valores mais elevados durante a estação úmida. O estreitamento do intervalo de valores de NDVI nas áreas U sugere uma redução da biomassa vegetal e menor diversidade de usos do solo. A relação entre a Ts diurna e o NDVI indicou uma dependência nas áreas não urbanizadas, sugerindo um resfriamento da temperatura com o aumento da biomassa verde. As ICUS apresentaram uma média de 5 °C na estação úmida e 2 °C na estação seca, destacando-se a Região Metropolitana de São Paulo como a de maior ICUS, atingindo em torno de 10 °C na estação úmida. Foi constatada uma relação não linear negativa entre o NDVI de áreas urbanizadas e a ICUS, indicando que a biomassa verde nas áreas urbanizadas contribui para a redução da ICUS. A relação de dependência não linear da ICUS com o gradiente espacial NDVI sugere uma funcionalidade da ICUS dependente da variação da cobertura de superfície em escala mesorregional. O uso do solo demonstrou ser um fator relevante no aquecimento da superfície. Áreas urbanizadas apresentaram uma diferença de até 10oC na mediana em comparação com áreas florestais, sendo 2oC mais quentes que áreas de soja e cana-de-açúcar, 3oC mais aquecidas que pastagens e 5oC mais quentes que áreas com mosaico de usos, durante a estação úmida. Em conclusão, este estudo fornece achados importantes sobre os padrões de ICUS em diferentes cidades do estado de São Paulo, sobre a presença de um gradiente climático de temperatura de superfície e destaca a relevância do uso e cobertura da terra no arrefecimento do calor. A compreensão desses padrões sazonais e fatores de influência é essencial para o planejamento urbano e políticas de adaptação climática.The impact of surface urban heat islands has become more significant in the current context of climate change. Understanding the patterns and mechanisms that control this phenomenon is crucial for developing effective climate adaptation plans in cities. This study examined 52 urbanized areas and their surrounding non-urbanized regions in the state of São Paulo, ranging from small towns to the vast São Paulo metropolitan region, with over 20 million inhabitants. Using data from the Landsat 8 satellite between 2013 and 2023, obtained via the Google Earth Engine platform, the patterns of surface temperature and surface urban heat islands (SUHI), as well as the impacts of land use and land cover on surface temperature, were investigated. The results highlight a clear influence of the urban environment on surface temperatures, with an average difference of 5°C between the urbanized surface temperature (TsU) and the non-urbanized surface temperature (TsNU) during the wet season, which consistently exhibited more pronounced warming. No significant differences were found in the average Ts when considering city populations, instead revealing a control by continentality through the formation of a regional-scale Ts climatic gradient across the state, in both urbanized and non-urbanized areas, across all forms of land use and land cover. An NDVI range between 0.2 and 0.4 for urbanized areas and between 0.3 and 0.8 for non-urbanized areas was identified, with seasonal variations in distribution, showing higher values during the wet season. The narrowing of the NDVI range in urban areas suggests a reduction in vegetation biomass and lower land use diversity. The relationship between daytime Ts and NDVI indicated a dependency in non-urbanized areas, suggesting a cooling of temperatures with increased green biomass. SUHIs averaged 5°C in the wet season and 2°C in the dry season, with the São Paulo Metropolitan Region standing out as the area with the highest SUHI, reaching around 10°C in the wet season. A negative nonlinear relationship was found between the NDVI of urbanized areas and the SUHI, indicating that green biomass in urbanized areas contributes to reducing the SUHI. The nonlinear dependency of the SUHI on the spatial NDVI gradient suggests a UHI functionality dependent on surface cover variation on a mesoregional scale. Land use was shown to be a relevant factor in surface warming. Urbanized areas exhibited a difference of up to 10°C in the median compared to forest areas, being 2°C warmer than soybean and sugarcane areas, 3°C warmer than pastures, and 5°C warmer than areas with a mosaic of uses, during the wet season. In conclusion, this study provides important findings on SUHI patterns in different cities in the state of São Paulo, the presence of a surface temperature climatic gradient, and highlights the relevance of land use and land cover in cooling heat. Understanding these seasonal patterns and influencing factors is essential for urban planning and climate adaptation policies

    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 CARNIVORES: a data set on carnivore distribution in the Neotropics

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    Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data
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