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-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

Space use by the brown brocket deer (Mazama gouazoubira; Fisher, 1814): a comparison between GPS collars and fecal DNA

Informações sobre o uso do espaço são importantes para o entendimento de processos ecológicos que envolvem uma espécie e a determinação de seu estado de conservação. Tais informações são escassas para o gênero Mazama, o mais diverso entre os cervídeos neotropicais, sendo que desenvolver metodologias para obtenção de dados ecológicos do gênero torna-se fundamental para qualquer ação de manejo envolvendo o grupo. O estudo do DNA fecal surge como uma ferramenta importante para viabilizar a coleta sistemática de informações sobre o gênero. Assim, o presente trabalho visou a estimar a área de vida e a seleção de hábitat do veado-catingueiro, comparando duas metodologias, com intuito de avaliar a aplicação do DNA fecal como alternativa para se estudar a espécie. O trabalho contou com 6 animais que tiveram suas localizações obtidas a cada 13 horas por colares GPS, no período de um ano. Nesse mesmo período e na mesma área, foram coletadas mensalmente amostras fecais, gerando um total de 830 amostras, cujo DNA foi extraído para identificação genética. A espécie das amostras foi determinada com o uso de um marcador mitocondrial (cit-b), e a identificação individual, com um painel de 11 microssatélites. Os valores de área de vida pelo método do MPC 95% variaram de 33 ha a 97 ha, e pelo método Kernel com 95% das localizações, variaram de 17 ha a 77 ha. Observou-se que as áreas de vida são alocadas nos diferentes habitats da região conforme o disponível (p = 0,072), porém são utilizadas internamente de forma selecionada (p=0,001). Neste nível, a espécie apresentou preferência pelos hábitats de cerrado e campo cerrado e evitou o campo (p < 0,005). Foram identificadas 670 amostras de veado-catingueiro e 15 genótipos únicos. A análise espacial das fezes também sugeriu uso desproporcional dos hábitats em relação à sua disponibilidade, sendo que a comparação direta entre os dois métodos revelou iguais distribuições no nível de espécie (p=0,178). As amostras individualizadas sugeriram um padrão de alta sobreposição de área de uso por diferentes indivíduos, mas avanços são necessários para melhor elucidar a questão. Perante os resultados observados, entende-se que há muito em se avançar na análise molecular das fezes que, realizada em larga escala, pode fornecer respostas importantes anteriormente inviáveis para espécies florestais.Space use information is a key element to understand the ecological processes regarding a species and its conservation status. Such information is scarce for the genus Mazama, the most diverse group among Neotropical deer. The development of methods to obtain ecological data is fundamental to management actions concerning the group. The study of fecal DNA emerges as an important tool to enable systematic information collection about Mazama genus. Therefore, the present study aimed to estimate the home range and habitat selection of brown brocket deer comparing two methodologies in order to assess the application of fecal DNA as an alternative to study this species. Six animals were monitored with GPS collars and their location data was collected every 13 hours within one year time. Fecal samples were collected monthly in the same period and in the same area, generating a total of 830 samples whose DNA was extracted for genetic identification. The species identification was determined by a mitochondrial marker (cit-b) and individuals were identified applying a panel of 11 microsatellites. Home range was 33-97 h by MPC 95% and 17-77 h by Kernel 95%. Home rages are allocated in different habitats as available in the region (p = 0.072), but its use is internally selected (p = 0.001). At this level, the species showed preference for \"cerrado\" and \"campo cerrado\" habitats and avoidance to open field areas (p < 0.005). Genetics analysis identified 670 brown brocket deer samples and 15 unique genotypes. Feces spatial analysis suggested disproportionate use of habitats in relation to their availability in the field and the direct comparison between the two methods revealed equal distributions at the species level (p = 0.178). The genotyped samples suggested an overlapping home range pattern for different individuals, but advances are needed to further elucidate the issue. There is need for improvements in feces molecular analysis and, if held on large scale, it can provide important and previously unviable answers for forest species

Revalidation of Passalites Gloger, 1841 for the Amazon brown brocket deer P. nemorivagus (Cuvier, 1817) (Mammalia, Artiodactyla, Cervidae)

Mazama nemorivaga (Cuvier, 1817) is a gray brocket deer that inhabits the Amazon region. An assessment of previous studies revealed inconsistencies in its current taxonomic classification, suggesting the need for an update in its genus classification. A taxonomic repositioning of this species is proposed through the collection of a specimen from its type locality (French Guiana) with subsequent morphological (coloring pattern, body measurements, and craniometry), cytogenetics (G Band, C Band, conventional Giemsa, Ag-NOR staining, and BAC probe mapping), and molecular phylogenetic analysis (mitochondrial genes Cyt B of 920 bp, COI I of 658 bp, D-loop 610 bp), and comparisons with other specimens of the same taxon, as well as other Neotropical deer species. The morphological and cytogenetic differences between this and other Neotropical Cervidae confirm the taxon as a unique and valid species. The phylogenetic analysis evidenced the basal position of the M. nemorivaga specimens within the Blastocerina clade. This shows early diversification and wide divergence from the other species, suggesting that the taxon should be transferred to a different genus. A taxonomic update of the genus name is proposed through the validation of Passalites Gloger, 1841, with Passalites nemorivagus (Cuvier, 1817) as the type species. Future research should focus on evaluating the potential existence of other species within the genus Passalites, as suggested in the literature

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

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

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

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

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

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