Advertisement and release calls of Rhinella scitula (Caramaschi and Niemeyer, 2003) (Anura: Bufonidae)

The anuran calls descriptions have given important taxonomic information in studies within problematic species group. Herein, we describe the advertisement and release calls of R. scitula. We analyzed calls recorded in three localities in Mato Grosso do Sul state, Brazil, including the type locality. Males were calling at the margins of permanent streams in forest fragments ca. 21:00 h. The advertisement call of R. scitula is multi-pulsed with interior amplitude modulation, resulting in pulse groups. Males emitted non-regular call series with duration of 0.27s ± 0.03 (0.23–0.36), note duration of 0.015s ± 0.004 (0.007–0.040), pulse duration of 0.008s ± 0.001 (0.005–0.015, n=180), pulse group per call of 6.6 ± 0.92 (5–8) and dominant frequency of 1439.7 Hz ± 46.1 (1378.1–1550.4). The release calls were characterized by a dominant frequency of 1115.8Hz ± 102.2 (947.5–1550.4), a frequency bandwidth of 2001.6Hz ± 527.4 (861.3–3876). They are formed by pulsed and/or pulsatile notes spaced by non-regular intervals or series of 2–19 calls. From all R. margaritifera species group with described advertisement calls, the most different to R. scitula and other species in the group was R. magnussoni, which has a structurally distinct call. The release calls in R. granulosa species group and R. scitula has the same pattern of pulsed and/or non-pulsed notes.Asociación Herpetológica Argentin

Distribution pattern of anurans from three mountain complexes in southeastern Brazil and their conservation implications

Biogeographic tools support spatial distribution pattern hypotheses and help to determine priority areas for conservation. Our aim was to verify biogeographic patterns for anurans in three mountain complexes in southeastern Brazil, as well as to discuss the status of species conservation recorded and the biogeographical units evaluated. We selected 16 areas distributed in the Serra da Mantiqueira complex, south of Serra do Espinhaço and Serra da Canastra. We used the occurrence (geographic coordinates) of each species in the localities to determine areas of endemism applying the Endemicity Analysis method. We also tested whether similarity between areas was explained by geographic distance (Multiple Regression on distance Matrices-MRM). The Serra do Itatiaia, Serra da Canastra, Plateau of Poços de Caldas and Serra do Cipó were the areas that presented the highest number of species restricted to them. Through the Endemicity Analysis, we identified four areas of endemism with higher scores. The MRM revealed that the geographic distance explained 41% of species dissimilarity between areas. Most of the endemic species from these areas have inaccurate conservation statuses (data deficient or unevaluated). These results highlight the need for greater research efforts towards understanding species restricted by distribution, as well as the priority in conserving these endemic areas

A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring

Global change is predicted to induce shifts in anuran acoustic behavior, which can be studied through passive acoustic monitoring (PAM). Understanding changes in calling behavior requires automatic identification of anuran species, which is challenging due to the particular characteristics of neotropical soundscapes. In this paper, we introduce a large-scale multi-species dataset of anuran amphibians calls recorded by PAM, that comprises 27 hours of expert annotations for 42 different species from two Brazilian biomes. We provide open access to the dataset, including the raw recordings, experimental setup code, and a benchmark with a baseline model of the fine-grained categorization problem. Additionally, we highlight the challenges of the dataset to encourage machine learning researchers to solve the problem of anuran call identification towards conservation policy. All our experiments and resources have been made available at https://soundclim.github.io/anuraweb/The authors acknowledge financial support from the intergovernmental Group on Earth Observations (GEO) and Microsoft, under the GEO-Microsoft Planetary Computer Programme (October 2021); São Paulo Research Foundation (FAPESP #2016/25358–3; #2019/18335–5); the National Council for Scientific and Technological Development (CNPq #302834/2020–6; #312338/2021–0, #307599/2021–3); National Institutes for Science and Technology (INCT) in Ecology, Evolution, and Biodiversity Conservation, supported by MCTIC/CNpq (proc. 465610/2014–5), FAPEG (proc. 201810267000023); CNPQ/MCTI/CONFAP-FAPS/PELD No 21/2020 (FAPESC 2021TR386); Comunidad de Madrid (2020-T1/AMB-20636, Atracción de Talento Investigador, Spain) and research projects funded by the European Commission (EAVESTROP–661408, Global Marie S. Curie fellowship, program H2020, EU); and the Ministerio de Economía, Industria y Competitividad (CGL2017–88764-R, MINECO/AEI/FEDER, Spain). We also thank Tom Denton for machine learning evaluation suggestions, dataset revision, and comments on the manuscrip

AnuraSet: A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring

Global change is predicted to induce shifts in anuran acoustic behavior, which can be studied through passive acoustic monitoring (PAM). Understanding changes in calling behavior requires the identification of anuran species, which is challenging due to the particular characteristics of neotropical soundscapes. In this paper, we introduce a large-scale multi-species dataset of anuran amphibians calls recorded by PAM, that comprises 27 hours of expert annotations for 42 different species from two Brazilian biomes. We provide open access to the dataset, including the raw recordings, experimental setup code, and a benchmark with a baseline model of the fine-grained categorization problem. Additionally, we highlight the challenges of the dataset to encourage machine learning researchers to solve the problem of anuran call identification towards conservation policy. All our experiments and resources can be found on our GitHub repository https://github.com/soundclim/anuraset

Database

Dataset used in the manuscrip

Rhinella scitula (Caramaschi & Niemeyer, 2003) (Amphibia: Anura: Bufonidae): New distribution records

Rhinella scitula is a small frog belonging to the R. margaritifera group that is found in southwestern and central Mato Grosso do Sul, Brazil, and in the provinces of Amambay and Concepcion in Paraguay. We extend the distribution of the species across the north and the southeast prior distribution limit, and provide an updated map. The distribution of R. scitula encompasses mainly areas with seasonal forests and mountainous landscape in central-western Brazil and northeastern Paraguay

Data from: Satellite image texture for the assessment of tropical anuran communities

The relationship between environmental heterogeneity and biodiversity represents a cornerstone of ecological research. While environmental descriptors over large extents usually have medium to low spatial resolution, in-situ measures provide accurate information for limited areas, and a gap remains in providing remote descriptors that represent local environmental structure. Texture from satellite images can represent fine-scale heterogeneity over wide spatial coverage, but to date, it has mostly been used to predict general aspects of species diversity, such as richness. Here, we assess the utility of image textures from high resolution satellite images (RapidEye 3A) and in-situ variables to predict differences in the composition of anuran communities in a tropical savanna (Cerrado) of Brazil. While in-situ measures accounted for compositional differences of the whole community, two measures of image textures were associated only with the variation of species within the Hylidae family (adj. R² = 0.16 and 0.14). Comparatively, image textures predicted ~2/3 of the variation explained by in-situ­ measures (adj. R² = 0.23). When both approaches were combined, a greater compositional variation was achieved (adj. R² = 0.28), with 1/5 of it shared by both in-situ and textures, and 1/5 attributed solely to texture. Our findings suggest that image texture can complement the assessment of environmental heterogeneity acting on the assembly of local anuran communities. This approach can be valuable for explicitly including spatial heterogeneity in biological assessments over broad spatial extents, especially for biological groups strongly filtered by environmental conditions

Lepidobatrachus asper Budgett,1899 (Amphibia: Anura: Ceratophryidae): new country record, distribution map and natural history notes

Lepidobatrachus asper is a large to medium frog known from the Chaco lowlands of Paraguay and Argentina. We provide the first species record for the Brazilian Chaco, which extends the species geographical distribution ca. 73 km northeast from Puerto Casado, Alto Paraguay Departament, Paraguay. We also provide a distribution map and information about the species habitat conditions and diet. The Brazilian Chaco is still poorly surveyed, and the rapid environmental degradation can lead to local extinctions of certain species

Distribution pattern of anurans from three mountain complexes in southeastern Brazil and their conservation implications

ABSTRACT Biogeographic tools support spatial distribution pattern hypotheses and help to determine priority areas for conservation. Our aim was to verify biogeographic patterns for anurans in three mountain complexes in southeastern Brazil, as well as to discuss the status of species conservation recorded and the biogeographical units evaluated. We selected 16 areas distributed in the Serra da Mantiqueira complex, south of Serra do Espinhaço and Serra da Canastra. We used the occurrence (geographic coordinates) of each species in the localities to determine areas of endemism applying the Endemicity Analysis method. We also tested whether similarity between areas was explained by geographic distance (Multiple Regression on distance Matrices-MRM). The Serra do Itatiaia, Serra da Canastra, Plateau of Poços de Caldas and Serra do Cipó were the areas that presented the highest number of species restricted to them. Through the Endemicity Analysis, we identified four areas of endemism with higher scores. The MRM revealed that the geographic distance explained 41% of species dissimilarity between areas. Most of the endemic species from these areas have inaccurate conservation statuses (data deficient or unevaluated). These results highlight the need for greater research efforts towards understanding species restricted by distribution, as well as the priority in conserving these endemic areas