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Simple Summary: Chagas disease is endemic to the state of Texas in the United States but does not have consistent surveillance or reporting. We utilized multiple sampling sites and different species of triatomine to gain data on the blood meal sources found by DNA testing for the host and vector species identities. From domestic, peridomestic, and rural sites, we found a breadth of blood meal origins including mammals, chickens, and reptiles. Unique non-native taxa utilized for blood meals enabled us to also report on extensive foraging distances for the vectors. Understanding the diversity of blood meal sources and the distances the vectors travel between meals and daytime refuges are both important aspects for understanding the spread of this disease. The prevalence of Trypanosoma cruzi was assessed in 117 triatomine insects from central Texas. The qPCR-based results revealed T. cruzi in 59% of the insects (62 adults and eight nymphs), with overall prevalences of T. cruzi of 0% (0/9), 64% (11/17), 58% (10/17), 73% (30/41), and 57% (19/33) for the Bastrop, Caldwell, Gonzales, Guadalupe, and Hays counties, respectively. Analyses of 18S rRNA fragments confirmed T. cuzi in 81% of these samples. Vectors were identified as Triatoma gerstaeckeri (35% of which 65% were positive for T. cruzi), T. sanguisuga (21%, 43% positive), and Paratriatoma leticularia (0.3%, 100% positive). Food sources were recovered from 29% of the insects. Raccoons were 53% of the blood meals (83% positive for T. cruzi), while the remainder came from a variety of sources, including humans (33% positive), house geckos, Eastern woodrats, plain-bellied water snakes (50% positive), hispid cotton rats (0% positive), chickens (100% positive); Asian forest turtles, bison, and pigs (0% positive). The serendipitous detection of blood meal sources at known minimum distances from the collection of the vector insect enabled us to provide several instances where the insect foraging distance was greater than 400 m. These vector foraging distances are novel information that can assist in our understanding of the landscape dynamics for the spread of the pathogen. [ABSTRACT FROM AUTHOR]

The molecular detection of DNA fragments that are shed into the environment (eDNA) has become an increasingly applied tool used to inventory biological communities and to perform targeted species surveys. This method is particularly useful in habitats where it is difficult or not practical to visually detect or trap the target organisms. Central Texas Eurycea salamanders inhabit both surface and subterranean aquatic environments. Subterranean surveys are challenging or infeasible, and the detection of salamander eDNA in water samples is an appealing survey technique for these situations. Here, we develop and validate an eDNA assay using quantitative PCR for E. chisholmensis, E. naufragia, and E. tonkawae. These three species are federally threatened and constitute the Septentriomolge clade that occurs in the northern segment of the Edwards Aquifer. First, we validated the specificity of the assay in silico and with DNA extracted from tissue samples of both target Septentriomolge and non-target amphibians that overlap in distribution. Then, we evaluated the sensitivity of the assay in two controls, one with salamander-positive water and one at field sites known to be occupied by Septentriomolge. For the salamander-positive control, the estimated probability of eDNA occurrence (ψ) was 0.981 (SE = 0.019), and the estimated probability of detecting eDNA in a qPCR replicate (p) was 0.981 (SE = 0.011). For the field control, the estimated probability of eDNA occurring at a site (ψ) was 0.938 (95% CRI: 0.714–0.998). The estimated probability of collecting eDNA in a water sample (θ) was positively correlated with salamander relative density and ranged from 0.371 (95% CRI: 0.201–0.561) to 0.999 (95% CRI: 0.850– > 0.999) among sampled sites. Therefore, sites with low salamander density require more water samples for eDNA evaluation, and we determined that our site with the lowest estimated θ would require seven water samples for the cumulative collection probability to exceed 0.95. The estimated probability of detecting eDNA in a qPCR replicate (p) was 0.882 (95% CRI: 0.807–0.936), and our assay required two qPCR replicates for the cumulative detection probability to exceed 0.95. In complementary visual encounter surveys, the estimated probability of salamanders occurring at a known-occupied site was 0.905 (SE = 0.096), and the estimated probability of detecting salamanders in a visual encounter survey was 0.925 (SE = 0.052). We additionally discuss future research needed to refine this method and understand its limitations before practical application and incorporation into formal survey protocols for these taxa. [ABSTRACT FROM AUTHOR]

Simple Summary: The disappearance of many reptiles and amphibian species is directly and indirectly connected with habitat modification, introducing invasive species, disease, pollution, and climate change. Monitoring endangered species is essential for conservation action to mitigate the predominant threats to endangered species. According to wildlife researchers, visual information provides definitive evidence of an animal's distribution patterns and activity within an environmental context. At the Department of Biology and The Ingram School of Engineering at Texas State University and Texas A&M University, we collaborated on a camera trap project to monitor species from images in Texas, USA. We developed a framework to analyze the acquired images using artificial intelligence-driven technology and computer vision methods. The project aims to classify three broad groups of herpetofaunal species (i.e., toads/frogs, lizards, and snakes) from camera trap images with deep learning architectures. The experiment includes balancing the imbalanced dataset, investigating several image preprocessing techniques, and augmentation procedures. The classification results present tremendous prospects for automated species identification from challenging biological image data. The research outcome is essential to the academic community and wildlife researchers for conservation and monitoring purpose. Accurate identification of animal species is necessary to understand biodiversity richness, monitor endangered species, and study the impact of climate change on species distribution within a specific region. Camera traps represent a passive monitoring technique that generates millions of ecological images. The vast numbers of images drive automated ecological analysis as essential, given that manual assessment of large datasets is laborious, time-consuming, and expensive. Deep learning networks have been advanced in the last few years to solve object and species identification tasks in the computer vision domain, providing state-of-the-art results. In our work, we trained and tested machine learning models to classify three animal groups (snakes, lizards, and toads) from camera trap images. We experimented with two pretrained models, VGG16 and ResNet50, and a self-trained convolutional neural network (CNN-1) with varying CNN layers and augmentation parameters. For multiclassification, CNN-1 achieved 72% accuracy, whereas VGG16 reached 87%, and ResNet50 attained 86% accuracy. These results demonstrate that the transfer learning approach outperforms the self-trained model performance. The models showed promising results in identifying species, especially those with challenging body sizes and vegetation. [ABSTRACT FROM AUTHOR]

The article focuses on observing climbing behavior in the federally endangered Bufo [Anaxyrus] houstonensis, highlighting a notable instance of arboreal activity in a subadult individual observed atop a dead tree in Bastrop County, Texas, USA.

The article focuses on the discovery of frugivory (fruit consumption) in Xantusia vigilis (Desert Night Lizard), a species previously believed to be primarily insectivorous, and highlights the need for further research into the dietary habits of these small lizards in the wild.

The article informs about the county record of the presence of a Hemidactylus Turnicus or Mediterraniean Gecko that was observed in Coryell County, Texas on January 30, 2021.

The article discusses research on the specie, "Hyla Squirella (Squirrel Treefrog)" and explores about its geographical distribution and collection of specimen.

The article informs about the county record of the presence of a Thamnophis Proximus or Western Ribbonsnake that was found along the intersection of County Road with Ranch to Market Road in Sutton County, Texas on August18, 2021.

The article informs about the county record of the presence of a population of Siren Intermedia or Lesser Siren that was discovered during excavation on the Old Pin Oak Road in the town of Paige in Bastrop County, Texas on Ocober 12, 2021.

The article informs about the county record of the presence of eight Eleutherodactylus Cystignathoides or Rio Grande Chirping Frog that were heard calling from a forested site on private lands in Rockwall County, Texas on July 31, 2020.

The prevalence of leech attachment on anuran taxa is largely uncharacterized. When parasitic, such relationships may regulate amphibian populations and function as an obstacle to the recovery of imperiled species. We evaluated the prevalence of leech attachment in a population of endangered Bufo (= Anaxyrus) houstonensis (Houston Toad) in Bastrop County, TX, during the spring of 2021. Of 191 toads examined, 2 (1%) were each infested with a single leech. Molecular analysis of the cytochrome c oxidase subunit I gene identified 1 of those leeches as Helobdella austinensis. This constitutes the first reported association of H. austinensis with a vertebrate host and extends the known range of H. austinensis ~50 km eastward. Leech attachment in this Houston Toad population is rare and the nature of the association remains unclear. [ABSTRACT FROM AUTHOR]

Documenting changes in the distribution and abundance of a given taxon requires historical data. In the absence of long-term monitoring data collected throughout the range of a taxon, conservation biologists often rely on preserved museum specimens to determine the past or present, putative geographic distribution. Distributional data for the Houston Toad ( Anaxyrus houstonensis ) has consistently been confounded by similarities with a sympatric congener, the Dwarf American Toad ( A. americanus charlesmithi ), both in monitoring data derived from chorusing surveys, and in historical data via museum specimens. In this case, misidentification can have unintended impacts on conservation efforts, where the Houston Toad is federally endangered, and the Dwarf American Toad is of least concern. Previously published reports have compared these two taxon on the basis of their male advertisement call and morphological appearance, often with the goal of using these characters to substantiate their taxonomic status prior to the advent of DNA sequencing technology. However, numerous studies report findings that contradict one another, and no consensus on the true differences or similarities can be drawn. Here, we use contemporary recordings of wild populations of each taxon to test for quantifiable differences in male advertisement call. Additionally, we quantitatively examine a subset of vouchered museum specimens representing each taxon to test previously reported differentiating morphometric characters used to distinguish among other Bufonids of East-Central Texas, USA. Finally, we assemble and qualitatively evaluate a database of photographs representing catalogued museum vouchers for each taxon to determine if their previously documented historic ranges may be larger than are currently accepted. Our findings reveal quantifiable differences between two allopatric congeners with respect to their male advertisement call, whereas we found similarities among their detailed morphology. Additionally, we report on the existence of additional, historically overlooked, museum records for the Houston Toad in the context of its putative historic range, and discuss errors associated with the curation of these specimens whose identity and nomenclature have not been consistent through time. These results bookend decades of disagreement regarding the morphology, voice, and historic distribution of these taxa, and alert practitioners of conservation efforts for the Houston Toad to previously unreported locations of occurrence., Competing Interests: Andrew R. MacLaren is employed by Cambrian Environmental., (©2024 MacLaren et al.)

Accurate identification of animal species is necessary to understand biodiversity richness, monitor endangered species, and study the impact of climate change on species distribution within a specific region. Camera traps represent a passive monitoring technique that generates millions of ecological images. The vast numbers of images drive automated ecological analysis as essential, given that manual assessment of large datasets is laborious, time-consuming, and expensive. Deep learning networks have been advanced in the last few years to solve object and species identification tasks in the computer vision domain, providing state-of-the-art results. In our work, we trained and tested machine learning models to classify three animal groups (snakes, lizards, and toads) from camera trap images. We experimented with two pretrained models, VGG16 and ResNet50, and a self-trained convolutional neural network (CNN-1) with varying CNN layers and augmentation parameters. For multiclassification, CNN-1 achieved 72% accuracy, whereas VGG16 reached 87%, and ResNet50 attained 86% accuracy. These results demonstrate that the transfer learning approach outperforms the self-trained model performance. The models showed promising results in identifying species, especially those with challenging body sizes and vegetation., Competing Interests: The authors declare no conflict of interest.

Illumina-based 16S rRNA V3 amplicon sequencing of total DNA obtained from soft tissue lesions (joint granulomas) of the endangered Houston toad (Anaxyrus houstonensis) demonstrated that many reads represented members of the actinobacterial Mycobacterium chelonae-abscessus complex. In order to quantify members of this complex in those lesions, we designed three complex-specific primer set/probe combinations (sets I, II and III) targeting variable regions on the 23S rRNA gene for SybrGreen- and Taqman-based quantitative polymerase chain reaction (qPCR). Both SybrGreen- and Taqman-based analyses specifically detected members of the M. chelonae-abscessus complex in lesion samples, with numbers between 10 4 and 10 7 cells per 100-mg sample. Values within individual samples were generally comparable between SybrGreen- and Taqman-based detection methods and between all primer set/probe combinations, except for SybrGreen-based analyses of a few samples analyzed with primer set I that used a less specific forward primer. The development of highly specific detection and quantification methods for members of the M. chelonae-abscessus complex in lesion samples can enable group specific tracking of these organisms, particularly in captive or stewardship settings where source and transmission monitoring are valuable tools to husbandry and species conservation., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a "Green List of Species" (now the IUCN Green Status of Species). A draft Green Status framework for assessing species' progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species' viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics (conservation legacy, conservation dependence, conservation gain, and recovery potential). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species' recovery scores, we propose the following species recovery categories: fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty-nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics, indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard., (© 2021 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology.)