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

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

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

ATLANTIC-CAMTRAPS: a dataset of medium and large terrestrial mammal communities in the Atlantic Forest of South America

Our understanding of mammal ecology has always been hindered by the difficulties of observing species in closed tropical forests. Camera trapping has become a major advance for monitoring terrestrial mammals in biodiversity rich ecosystems. Here we compiled one of the largest datasets of inventories of terrestrial mammal communities for the Neotropical region based on camera trapping studies. The dataset comprises 170 surveys of medium to large terrestrial mammals using camera traps conducted in 144 areas by 74 studies, covering six vegetation types of tropical and subtropical Atlantic Forest of South America (Brazil and Argentina), and present data on species composition and richness. The complete dataset comprises 53,438 independent records of 83 species of mammals, includes 10 species of marsupials, 15 rodents, 20 carnivores, eight ungulates and six armadillos. Species richness averaged 13 species (±6.07 SD) per site. Only six species occurred in more than 50% of the sites: the domestic dog Canis familiaris, crab-eating fox Cerdocyon thous, tayra Eira barbara, south American coati Nasua nasua, crab-eating raccoon Procyon cancrivorus and the nine-banded armadillo Dasypus novemcinctus. The information contained in this dataset can be used to understand macroecological patterns of biodiversity, community, and population structure, but also to evaluate the ecological consequences of fragmentation, defaunation, and trophic interactions. © 2017 by the Ecological Society of Americ

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

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

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Forest fragmentation and selective logging affect the seed survival and recruitment of a relictual conifer

•We surveyed seed removal and recruitment of Araucaria angustifolia in several sites.•Diverse animal species maintain interaction with A. angustifolia seeds.•Araucaria angustifolia dominance is important to seed survival and recruitment.•Forest fragmentation and selective logging may affect A. angustifolia recruitment.•Conservation measures are required to increase A. angustifolia recruitment. Defaunation, invasive species and forest fragmentation are considered to be the major drivers for the disruption of key ecological processes, particularly those related to plant animal-interactions such as seed dispersal and predation. The disruption of critical phases in the plant life cycle may ultimately have negative impacts on plant recruitment and the survival of plant populations. Here, for the first time we compared the seed removal and recruitment of Araucaria angustifolia, a critically endangered and relictual gymnosperm species, in multiple sites, including continuous and fragmented forest areas in the Brazilian Atlantic subtropical forest. Our sampling included seed removal experiment monitored by camera traps and surveys of A. angustifolia recruitment. We found that seed survival and recruitment were related to the density of adult A. angustifolia. Therefore the formation of large and dense groves, which is a characteristic of pristine Araucaria moist forests endangered by forest fragmentation and selective logging, may be an attempt to satiate seed predator communities. Additionally, forest fragmentation and the introduction of wild boar decreased seed survival to very low, and forest fragmentation decreased recruitment by fourfold on average. Increase protection and recuperation of Araucaria moist forests and the eradication of the invasive wild boar where possible are necessary measures for increasing seed survival rates and the recruitment of this relictual conifer

White-lipped peccaries are recorded at Iguaçu National Park after 20 years

The white-lipped peccary (WLP) is the most endangered ungulate in the Neotropics. In the recent years, this species has undergone a large reduction in range size and experienced the loss of several populations. An emblematic case was the local extinction of this species from the Iguaçu National Park (INP) in the mid-1990s. After the report of this particular WLP disappearance, surveys conducted along the 2000s confirmed its absence in the park. However, in 2016, after 20 years of previous reports, we obtained five records of WLP herds, indicating a possible population recovery probably resulting from emigration. To effectively re-establish white-lipped peccary population and, consequently, restore its ecological role, urgent practical conservation measures are necessary