Microhabitat selection of the poorly known lizard Tropidurus lagunablanca (Squamata: Tropiduridae) in the Pantanal, Brazil

Understanding how different environmental factors influence species occurrence is a key issue to address the study of natural populations. However, there is a lack of knowledge on how local traits influence the microhabitat use of tropical arboreal lizards. Here, we investigated the microhabitat selection of the poorly known lizard Tropidurus lagunablanca (Squamata: Tropiduridae) and evaluated how environmental microhabitat features influence animal’s presence. We used a Resource Selection Function approach, in a case/control design where we analyzed the effect of substrate temperature and tree’s diameter at breast height (DBH) in the probability of presence of lizards using mixed Conditional Logistic Regression. We found that T. lagunablanca uses trees with DBH from 0.40 m to 4 m and substrate temperatures ranging from 25.9℃ to 42℃. Moreover, we showed that thickness of the trees and substrate temperatures significantly increased the probability of presence of T. lagunablanca individuals, being the probability of presence higher than 50% for trees up to 1.5 m DBH and temperature of substrate up to 37.5℃. Our study probed that T. lagunablanca individuals choose trees non-randomly, selecting thicker and warmer tree trunks. This information advances the knowledge of the spatial ecology of Neotropical arboreal lizards and is relevant for conservation, putting an emphasis on preserving native vegetation in the Pantanal

Efficiency of photo identification of inguinal color patterns of Pithecopus gonzagai (Anura: Phyllomedusidae) from northeastern Brazil

Animal monitoring research involving mark-recapture techniques increasingly requires non-invasive methods of individual identification. The photographic identification method (PIM) is an excellent tool for this purpose and has been applied successfully to many taxa. However, the utility of PIM is a function of species-specific features that are judged suitable for a given target-species. Herein, the suitability of inguinal color patterns for photo identification of individuals of Pithecopus gonzagai are evaluated by comparing two widely used computer-assisted photographic matching programs (I³S and Wild.ID). Both programs accurately identified more than 70% of individuals in the top 20 potential matching photographs. Wild.ID was slightly better than I³S in matching efficiency and has a faster processing time. Thus, PIM is useful to identify individual P. gonzagai; however, before implementing the technique in animal-monitoring studies of other taxa, one must evaluate the suitability PIM for the target species and calibrate the relative efficiency of the software programs in identifying individuals

Distribution extension of Amphisbaena lumbricalis Vanzolini, 1996 with its first predation record by snake Erythrolamprus viridis (Günther, 1862)

We expand the geographical distribution of Amphisbaena lumbricalis throughout the first record for a semiarid Caatinga area in the Paraíba state, northeastern Brazil. Furthermore, we report the first predation report of A. lumbricalis by the snake Erythrolamprus viridis. Our findings contribute with information about the habitats occupied by a hitherto considered “Data Deficient” species, beyond to reveal the potential of E. viridis to prey upon reptiles.Asociación Herpetológica Argentin

HELMINTOFAUNA DE DOS LAGARTOS GECONÍDEOS, HEMIDACTYLUS AGRIUS Y LYGODACTYLUS KLUGEI (GEKKONIDADE), EN EL BIOMA CAATINGA, NORESTE DEL BRASIL

This study presented data on helminth fauna of two gecko lizards, Hemidactylus agrius and Lygodactylus klugei, from Caatinga biome in northeastern Brazil. It was found four helminth species parasitizing H. agrius, cistacanth of Centrorhynchidae (Acanthocephala) and the nematodes Physalopteridae (larvae), Parapharyngodon alvarengai (Pharyngodonidae) and Skrjabinelazia sp. (Seuratidade). The host Lygodactylus klugei presented two helminth species, one individual of Mesocoelium monas (Trematoda: Mesocoeliidae) in the small intestine and one encysted larvae of Physalopteridae (Nematoda: Physalopteridae) attached at stomach wall. The lizard species showed a low prevalence and low richness of helminths. Moreover, H. agrius presented a low intensity of infection. The foraging mode, arboreal habit and a restricted composition of diet could favoring the low prevalence, low infection rates and low richness of helminths found in these geckonid host species.Este estudio presenta datos sobre la fauna de helmintos de dos lagartos geconídeos, Hemidactylus agrius y Lygodactylus klugei, en el bioma caatinga en el noreste del Brasil. Hay cuatro especies de helmintos parásitos de H. agrius, cistacanto de Centrorhynchidae (Acanthocephala) y nematodos Physalopteridae (estadios larvarios), Parapharyngodon alvarengai (Pharyngodonidae) y Skrjabinelazia sp. (Seuratidade). El hospedador Lygodactylus klugei presentó dos especies de helmintos, un individuo de Mesocoelium monas (Trematoda: Mesocoeliidae) en el intestino delgado y una larva enquistada de Physalopteridae (Nematoda: Physalopteridae) adjunta a la pared del estómago. Las especies de lagarto mostraron una baja prevalencia y baja riqueza de helmintos. Además, H. agrius mostró una baja intensidad de infección. El modo de búsqueda de alimento, el hábito arbóreo y la composición de una dieta restringida pudieran haber favorecido la baja prevalencia, las bajas tasas de infección y riqueza baja de helmintos que se encontraron en las especies hospedadoras

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