Comparative gastrointestinal organ lengths among Amazonian primates (Primates: Platyrrhini)

ObjectivesThe morphological features of the gastrointestinal tract (GIT) in mammals reflect a species' food niche breadth and dietary adaptations. For many wild mammals, the relationship between the structure of the GIT and diet is still poorly understood, for example, the GIT for frugivorous primates is usually classified as unspecialized and homogeneous. Here, we compare the GIT structure of 13 primate species from the three families of extant platyrrhines (Atelidae, Pitheciidae, and Cebidae) in Amazonia, and discuss possible evolutionary adaptations to different diets and trophic niches.MethodsWe measured the length of the esophagus, stomach, small intestine, large intestine, cecum, colon, and rectum of the digestive tracts of 289 primate specimens. We determined the allometric relationships of the different tubular organs with the total length of the GIT as a proxy of specimen body size. Allometric parameters were used to establish the quotients of differentiation of every organ for each primate specimen.ResultsThere was a high differentiation in structure of the digestive organs among genera. Alouatta specimens clearly separated from the other genera based on dissimilarities in gastric, colonic, and rectal quotients, likely linked to the fermentation of plant contents. In contrast, all cebines (Sapajus, Cebus, and Saimiri) and Cacajao species had similar small intestine quotients, which is expected due to their high rates of animal matter consumed.ConclusionsWe show that diverse adaptations in digestive structure exist among frugivorous primates, which in turn reflect different dietary patterns within this group that may enable the geographic coexistence of different primate species

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

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

Ilhas fluviais são ilhas "verdadeiras" para os mamíferos? Respostas das espécies às mudanças na estrutura espacial da paisagem

After the publication of the theory of island biogeography, the idea that habitat patches are comparable to oceanic islands have popularized in ecology, and later in conservation biology. The discipline of landscape ecology came afterward, studying the relationship between spatial patterns of landscape structure and ecological processes. One such pattern is the species-area relationship (SAR), which predicts that larger areas will contain more species. However, the patch size effects may be biased if the number of species in a given island or fragment increase only due the increment of the sampled area, instead of a patch size effect per se. Recently, it has been proposed that the amount of habitat in the local landscape simplifies both patch size and isolation effects and, consequently, it should be the main driver of species distribution in patchy systems. This study aimed to: (i) test if SAR from mammals inhabiting fluvial islands in the middle-Solimões River region, in Central Amazon, occurs due to an island effect or to a sample area effect; (ii) evaluate the independent effects of habitat amount in landscape and island size on species richness estimated by a standardized sampling effort; and (iii) analyze how habitat amount in landscape and matrix resistance are related to species composition. For this, the occurrence of mammals in fluvial islands was registered on 15 islands, and the landscapes surrounding the islands were characterized based on satellite images. The sample area effect alone explained the SAR found in the islands, and the relationship did not remain after species richness being accessed by standardized sampling effort. Habitat amount in the local landscape was able to predict the species richness estimated by standardized sample effort, and was also related to the species composition pattern. On the other hand, matrix resistance was not correlated with species composition. Even if islands are considered literally as true islands, i.e. portions of land surrounded by water, these findings suggest that these islands may not be considered as "real" islands under the equilibrium perspective of MacArthur-Wilson model. These findings support the hypothesis that habitat amount in landscape explains the distribution of mammal species in the fluvial islands of middle-Solimões region.Desde a publicação da teoria da biogeografia de ilhas, a ideia de que manchas de habitat são comparáveis a ilhas oceânicas popularizou-se na ecologia e, mais tarde, na biologia da conservação. Mais recentemente, surge a ecologia da paisagem, a qual busca explicar a relação entre os padrões espaciais de estrutura da paisagem e os processos ecológicos. Um dos padrões espaciais mais estudados é a relação espécie-área (REA), a qual prevê que áreas maiores devem conter maior riqueza de espécies. Porém, a constatação desses efeitos pode estar enviesada se o número de espécies em uma ilha ou parcela (fragmento) de habitat aumentar somente em decorrência do incremento da área amostrada ao invés de ser influenciado pelo tamanho da mancha per se. Em decorrência desse debate, recentemente foi proposto que a quantidade de habitat na paisagem local do entorno das manchas simplifica os efeitos do seu tamanho e isolamento e, por isso, deve ser o principal fator determinante da distribuição de espécies em sistemas de manchas. Os objetivos desse trabalho foram: (i) testar se a REA de mamíferos habitando ilhas fluviais na região do médio-Solimões, Amazônia Central, ocorre devido a um efeito de ilha ou a um artefato amostral; (ii) avaliar os efeitos independentes da quantidade de habitat na paisagem e do tamanho da ilha na riqueza de espécies estimada por um esforço amostral padronizado; e (iii) analisar como a quantidade de habitat e a resistência da matriz ao fluxo biológico na paisagem estão relacionados com a composição de espécies das ilhas. Para isso, registrou-se a ocorrência de mamíferos em 15 ilhas fluviais, cujas paisagens foram caracterizadas espacialmente a partir de imagens de satélite. A REA de mamíferos nas ilhas foi explicada somente pelo efeito da área amostral e o seu padrão não se manteve quando a riqueza de espécies foi estimada em amostras de tamanho padronizado, independente do tamanho da ilha. A quantidade de habitat na paisagem local foi capaz de prever a riqueza de espécies estimada por um esforço amostral padronizado, bem como o padrão de estrutura da assembleia de mamíferos nas ilhas. Por outro lado, a resistência da matriz não apresentou relação com a composição de espécies de mamíferos nas ilhas. Embora as ilhas fluviais estudadas representem áreas de terra isoladas por uma matriz de água, elas não podem ser consideradas ilhas "verdadeiras" sob a perspectiva de equilíbrio do modelo de MacArthur-Wilson. Em suma, esse estudo suporta a hipótese de que a quantidade de habitat explica a distribuição de mamíferos nas ilhas fluviais do médio-Solimões

AMAZONIA CAMTRAP: A data set of mammal, bird, and reptile species recorded with camera traps in the Amazon forest

The Amazon forest has the highest biodiversity on Earth. However, information on Amazonian vertebrate diversity is still deficient and scattered across the published, peer-reviewed, and gray literature and in unpublished raw data. Camera traps are an effective non-invasive method of surveying vertebrates, applicable to different scales of time and space. In this study, we organized and standardized camera trap records from different Amazon regions to compile the most extensive data set of inventories of mammal, bird, and reptile species ever assembled for the area. The complete data set comprises 154,123 records of 317 species (185 birds, 119 mammals, and 13 reptiles) gathered from surveys from the Amazonian portion of eight countries (Brazil, Bolivia, Colombia, Ecuador, French Guiana, Peru, Suriname, and Venezuela). The most frequently recorded species per taxa were: mammals: Cuniculus paca (11,907 records); birds: Pauxi tuberosa (3713 records); and reptiles: Tupinambis teguixin (716 records). The information detailed in this data paper opens up opportunities for new ecological studies at different spatial and temporal scales, allowing for a more accurate evaluation of the effects of habitat loss, fragmentation, climate change, and other human-mediated defaunation processes in one of the most important and threatened tropical environments in the world. The data set is not copyright restricted; please cite this data paper when using its data in publications and we also request that researchers and educators inform us of how they are using these 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