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2,581 results for “amphibians”
FIGURE 9. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 9. A, Syntype of Crotalus jimenezii (HE 356); B, Syntype of Crotalus jimenezii, skull, ventral view (HE 1141); C, Syntype of Crotalus jimenezii, skull, dorsal view (HE 1142). D, Specimen erroneously catalogued as Bathysiredon dumerilii queretarensis (HE 1184). Neither specimen coincides with Maldonado-Koerdell's description (1948b).
FIGURE 10. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 10. A, Specimen erroneously catalogued as Bathysiredon dumerilii queretarensis (HE 1185, see comment on Figure 9D); B, C, Specimens of Sceloporus intermedius (HE 369, 370); D, Specimen of Adelophis copei (HE 963).
FIGURE 5. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 5. A, Jar containing three syntypes of Hemitriton asper (HE 1219–1221); B, Holotype of Hemichirotes tridactylus (HE 127); C, Syntype of Hemidactylus navarri, adult (HE 647); D, Syntype of Hemidactylus navarri, juvenile (HE 1222).
FIGURE 1. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 1. A, Hylodes augusti (HE 324) neotype designated by Smith & Necker (1943), and as precious assets by CDBPUG (2009); B, C, Skeletons of Hylodes augusti (HE 999, 1000, Holotype); D, Syntype of Ambystoma altamirani (HE 314).
FIGURE 8. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 8. A, Holotype of Oreophis boulengeri (HE 103); B, Holotype of Rhinocheilus antonii (HE 1223); C, Neotype of Elaps diastema michoacanensis (HE 1); D, Syntype of Crotalus jimenezii (HE 55).
FIGURE 4. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 4. A, Syntype of Amblystoma velasci, adult (HE 580); B, Syntype of Amblystoma velasci, larvae (HE 581); C, Syntype of Siredon dumerilii (HE 315); D, Specimen of Siredon dumerilii (HE 546) incorrectly labeled as Colima, Mexico. It has no type status.
FIGURE 7. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 7. A, Mandible of the holotype Erythrolamprus grammophrys (HE 1094); B, Parts of the skeleton of the type specimen of Geophis tecpanecus (HE 1139).C, Type specimen of Liophis janii (HE 102); D, Lectotype of Morenoa orizabensis (HE 126).
FIGURE 3. A, B in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 3. A, B, Skeletons of Ambystoma altamirani (HE 964, 965); C, Syntype of Ambystoma altamirani (HE 322); D, Syntype of Amblystoma velasci, adult (HE 579).
FIGURE 6. A in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 6. A, Holotype of Tapaya orbicularis longicaudatus (HE 422); B, Holotype of Eumeces altamirani (HE 397); C, Holotype of Eumeces rovirosae (HE 189); D, Holotype of Erythrolamprus grammophrys (HE 112).
FIGURE 11. A, B in Alfredo Dugès' type specimens of amphibians and reptiles revisited
FIGURE 11. A, B, Specimens erroneously designated types of Hylodes alfredi (HE 1038, 1039), see text; C, Specimen of Phrynosoma taurus (HE 446).
Data for: Epidemiological landscape of Batrachochytrium dendrobatidis and its impact on amphibian diversity at global scale
<p>Chytridiomycosis, caused by the fungal pathogen <em>Batrachochytrium dendrobatidis </em>(<em>Bd</em>), is a major driver of amphibian decline worldwide. The global presence of <em>Bd </em>is driven by a synergy of factors, such as climate, species life history, and amphibian host susceptibility. Here, using a Bayesian data-mining approach, we modeled the epidemiological landscape of <em>Bd </em>to evaluate how infection varies across several spatial, ecological, and phylogenetic scales. We compiled global information on <em>Bd </em>occurrence, climate, species ranges, and phylogenetic diversity to infer the potential distribution and prevalence of <em>Bd</em>. By calculating the degree of co-distribution between <em>Bd </em>and our set of environmental and biological variables (e.g. climate and species), we identified the factors that could potentially be related to <em>Bd </em>presence and prevalence using a geographic correlation metric, epsilon (ε). We fitted five ecological models based on 1) amphibian species identity, 2) phylogenetic species variability values for a given species assemblage, 3) temperature, 4) precipitation and 5) all variables together. Our results extend the findings of previous studies by identifying the epidemiological landscape features of <em>Bd</em>. This ecological modeling framework allowed us to generate explicit spatial predictions for <em>Bd </em>prevalence at the global scale and a ranked list of species with high/low probability of <em>Bd </em>presence. Our geographic model identified areas with high potential for <em>Bd </em>prevalence (potential <em>Bd</em>-risk areas) and areas with low potential <em>Bd </em>prevalence as potential refuges (free <em>Bd</em>). At the amphibian assemblage level, we found a non-relationship with amphibian phylogenetic signals, but a significantly negative correlation between observed species richness and <em>Bd </em>prevalence indicated a potential dilution effect at the landscape scale. Our model may identify species and areas potentially susceptible and at risk for <em>Bd </em>presence, which could be used to prioritize regions for amphibian conservation efforts and to assess species and assemblage at risk.</p>
Figure 1 in Exploring the phylogenetic landscape: unravelling the relationships and biogeography of the Cosmocerca genus in amphibians
Figure 1. Phylogenetic tree created using the maximum likelihood method based on the molecular marker COI gene of 11 species of cosmocercid nematodes.
Figure 2 in Exploring the phylogenetic landscape: unravelling the relationships and biogeography of the Cosmocerca genus in amphibians
Figure 2. Phylogenetic tree created using the maximum likelihood method based on the internal transcribed spacer (ITS) gene molecular marker of 11 species of cosmocercid nematodes.
Dataset and statistical analysis related to "Amphibian studies to investigate the endocrine disrupting properties of chemicals through the Thyroid modality: a comparison of their statistical power"
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Supplementary material 2 from: Armijos-Ojeda D, Székely D, Székely P, Cogălniceanu D, Cisneros-Heredia DF, Ordóñez-Delgado L, Escudero A, Espinosa CI (2021) Amphibians of the equatorial seasonally dry forests of Ecuador and Peru. ZooKeys 1063: 23-48. https://doi.org/10.3897/zookeys.1063.69580
Appendix 1. Reference list for life-history characteristics of amphibians of the Equatorial Seasonally Dry Forest (Table 1)
Local and landscape characteristics shape amphibian communities across production landscapes in the Western Ghats
<ol> <li>Global tropical forests have been modified and fragmented by commodity agroforests, leading to significant alterations in ecological communities. Nevertheless, these production landscapes offer secondary habitats that support and sustain local biodiversity. In this study, we assess community level and species-specific responses of amphibians to land management in areca, coffee and rubber, three of the largest commodity agroforests in the Western Ghats.</li> <li>A total of 106 agroforests across a 30,000 km<sup>2</sup> landscape were surveyed for amphibians using a combination of visual and auditory encounter surveys. We used a Bayesian multi-species occupancy modeling framework to examine patterns of species richness, beta diversity, dominance structure and individual species occupancies. The influence of biogeographic variables such as elevation and latitude as well as microhabitat availability of streams, ponds and unpaved plantation roads were tested on amphibian species occupancy. </li> <li>Coffee agroforests had the highest species richness and lowest dominance when compared to areca and rubber. Beta diversity was highest in areca for within agroforest measures. Compared across agroforests, coffee had highest beta diversity with areca and rubber. Both elevation and latitude showed an overall positive association with amphibian occupancy although species-specific responses varied considerably. </li> <li>Microhabitat availability was one of the strongest predictors of amphibian occupancy, with mean community response being positive with presence of water bodies and roads. Pond presence increased species richness per site by 37% (species-specific responses in occupancy ranged from -2.7% to 327%). Stream presence alone did not change species richness but species-specific response ranged from -59% to 273%). Presence of plantation roads also increased species richness by 21.5% (species-specific response range -82% to 656%). Being unpaved with little vehicular traffic, plantation roads seem to provide additional habitats for amphibians. Presence of all three microhabitats at a site increased species richness by 75%.</li> <li>Our study highlights the importance of land management strategies that maintain diverse native canopy and freshwater bodies and other microhabitats in sustaining amphibian fauna. Market driven land-use change from coffee to other agroforest types will have detrimental effects on amphibian communities and their long-term sustainability in the Western Ghats.</li> </ol>
Physiology and acclimation potential are tuned with phenology in larvae of a prolonged breeder amphibian
Due to the speed of climate changes, rapid buffering mechanisms such as phenotypic plasticity – which may depend on breeding phenology – could be key to avoid extinction. The links between phenology and plasticity, however, remain understudied. Here we explored the matching between phenology and the thermal sensitivity of standard (SMR) and routine metabolic rates (RMR), metabolic scope (i.e. the difference between RMR and SMR), survival and growth-development trajectories in larvae of a prolonged breeder amphibian (Alytes almogavarii) acclimated to 10 and 20ºC, belonging to three cohorts: autumn pre-overwintering, autumn overwintering and spring tadpoles. At 20ºC, survival of autumn pre-overwintering larvae was lower than for the rest. Although all cohorts showed acclimation potential, patterns for SMR and RMR differed, leading to differences in metabolic scope. Regardless of temperature, overwintering tadpoles arrested growth and development, while pre-overwintering and spring tadpoles showed higher growth and development at 20ºC. At 10ºC pre-overwintering tadpoles allocated more energy to development compared to spring tadpoles to advance development before winter. Overall, we demonstrate that the effects of temperature depend on phenology, consistent with future, expected thermal regimes. This suggests that extreme events can yield different vulnerability to climate change within populations (e.g., associated to discrete within-year cohorts), and not only between species or populations.
Habitat Selection by a Threatened Desert Amphibian
<p><strong><em>Aim. </em></strong>Habitat degradation and fragmentation are major drivers of amphibian declines. The loss of environmental features that allow for movement between water sources may be particularly detrimental for amphibians in arid environments. Climate changes will increase the importance of microhabitats to amphibians. Enhancing areas to facilitate movement may be a necessary conservation strategy for many animal species that depend on wetlands, including federally-threatened Chiricahua leopard frogs (Lithobates chiricahuensis). Habitat preferences of this frog species are not well understood. We sought to better understand fine-scale habitat selection, to inform conservation of Chiricahua leopard frogs.</p> <p><em><strong>Location. </strong></em>We conducted our study on the Ladder Ranch, a privately-owned working bison ranch in New Mexico, USA that supports a large proportion of the remaining Chiricahua leopard frogs in the state.</p> <p><em><strong>Methods.</strong></em> We attached radio transmitters to 44 frogs during summer 2014. We located each frog daily for up to 8 weeks (median = 30 days). We assessed fine-scale habitat selection by comparing characteristics at each frog location and a random location 5 meters away using conditional logistic regression. </p> <p><em><strong>Results.</strong></em> Frogs preferred features that likely reduce desiccation, even after accounting for the presence of water. Frogs selected areas with more low-lying cover, especially aquatic vegetation and woody debris, a tree overstory, and a mud substrate. </p> <p><em><strong>Main Conclusions. </strong></em>We recommend managing potential movement corridors for Chiricahua leopard frogs by ensuring the presence of muddy creek bottoms, woody debris, riparian overstory, low-lying ground cover, and pools. Microclimates created by these features seem especially valuable given warming temperatures and modified precipitation regimes, resulting in decreased surface water, soil moisture, and vegetation cover. Retaining or creating preferred habitat features and microclimates in areas between water sources may increase connectivity among isolated populations of Chiricahua leopard frogs and could improve persistence and recovery of other water-obligate species in arid landscapes.</p>
Supplementary material 1 from: Duran M (2021) An annotated checklist of the amphibians and reptiles of North Padre Island, Texas, USA, with comparisons to adjacent barrier island and mainland herpetofauna. ZooKeys 1073: 119-175. https://doi.org/10.3897/zookeys.1073.57241
Museum and iNaturalist records for Aransas, Cameron, Kenedy, Kleberg, Nueces, San Patricio, and Willacy counties, Texas, and iNaturalist records for North and South Padre and Mustang islands, Texas
Data from: Asynchrony, density dependence, and persistence in an amphibian
<p>The wood frog (<em>Rana sylvatica</em> = <em>Lithobates sylvaticus</em>) is a common, early-spring breeding anuran species in the United States and Canada. Females typically lay their egg masses in concentrated areas of a few meters over several days. Most female wood frogs mature after two years. Each female lays one egg mass in a given year, and most show high (~100%) site fidelity after first breeding, although a small portion of juveniles disperse up to 2000 m away from their natal site before their first breeding season. The lifespan of wood frogs depends on latitude, but they rarely live longer than five years. From 2000 to 2020 we conducted wood frog egg mass counts in 64 freshwater nonpermanent wetlands in the 3212 hectare Yale-Myers Forest in northeastern Connecticut, USA. The wetlands varied in surface area (average = 2642 m<sup>2</sup>, range = 24–41361 m<sup>2</sup>, CV = 252), canopy closure (i.e., global site factor; average = 52%, range = 0–98%, CV = 68), depth (average = 52 cm, range = 22–118, CV = 46), and egg mass counts (average = 71, range = 0–1113, CV = 130). As each female only lays one egg mass per year (i.e., only produces one clutch) and site fidelity is high, egg mass counts offer an accurate proxy for the number of breeding females within a pond in a given year. Previous work indicates egg mass counts are an accurate and precise technique for monitoring wood frog populations.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.