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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]

Abstract.-Taxonomic categories should be representative of natural groupings based on a shared lineage. Approaches to implementing this tenet are numerous and diverse with molecular methods such as gene sequencing being [...]

Knowledge regarding the locations of populations of endangered species is a critical part of recovery and facilitates land use planning that avoids unnecessary impacts. Regulatory agencies often support the development of survey guidelines designed to standardize the methods and maximize the probability of detection, thereby avoiding incorrectly concluding a species is absent from a site. Here, using simulations with data collected using automated recording devices (ARDs) we evaluated the efficacy of the existing U.S. Fish and Wildlife Service’s survey requirements for the endangered Houston Toad (Anaxyrus houstonensis). We explored the effect of (1) increasing survey duration, (2) increasing the number of surveys, and (3) combinations of environmental conditions (e.g., temperature, humidity, rainfall) on the detection probability and the number of surveys needed to be 95% confident of absence. We found that increases in both the duration of the survey and the number of surveys conducted decreased the likelihood of incorrectly concluding the species was absent from the site, and that the number of surveys required to be 95% confident greatly exceeded the existing survey requirements. Targeting specific environmental conditions was also an effective way to decrease the number of surveys required but the infrequency in which these conditions occurred might make application difficult in some years. Overall, we suggest that the survey effort necessary to achieve confidence in the absence of Houston Toads at a site is more practically achievable with the use of ARDs, but this may not be suitable in all monitoring scenarios. [ABSTRACT FROM AUTHOR]

The spread of invasive species is considered a major threat to biodiversity, second only to habitat loss. Red Imported Fire Ants (Solenopsis invicta) are a globally invasive species with negative impacts reported on native invertebrate and vertebrate species. Federally endangered Houston Toads (Bufo [=Anaxyrus] houstonensis), endemic to Texas, are among the vertebrates reportedly negatively impacted by Red Imported Fire Ants (RIFA). Threats posed by RIFA to Houston Toads needed to be explicitly characterized. Large-scale chemical treatments to suppress RIFA and facilitate brood survival in Attwater's prairie-chickens (Tympanuchus cupido attwateri) at the Attwater Prairie Chicken National Wildlife Refuge (APCNWR) afforded us an opportunity to experimentally examine the influence of RIFA abundance on juvenile Houston Toad growth and survival. We also sought to examine whether juvenile Houston Toads could grow and survive in a vegetation type similar to a historic species locality. We conducted a terrestrial mesocosm experiment to test whether the application of baitdriven suppressant decreased counts of RIFA relative to untreated sites. We examined whether counts of native ant and non-ant native invertebrates were higher in response to potential decreases in RIFA. We compared growth and survival rates in juvenile Houston Toads among treated and untreated sites, expecting juvenile growth and survival to be higher in response to potentially decreased RIFA counts and increased native invertebrate counts. We saw lower counts of RIFA in treated prairies, but we also observed a decrease in native ant counts possibly due to chemical treatment. Therefore, the application of bait-driven suppressant may not affect RIFA alone. We saw no difference in counts of non-ant invertebrates among treated and untreated sites. Juvenile Houston Toads did not differ in growth and survival among treated and untreated sites. We recognize that the lack of a relationship between juvenile growth and survival with a treatment effect, and therefore RIFA abundance, may be limited to APCNWR. We encourage additional experimental studies to elucidate RIFA impacts at other sites. We extrapolated apparent survival estimates from our study to one year. These appear comparable to juvenile survivorship required in simulations for Houston Toad population persistence and on this basis, we recommend that APCNWR be reevaluated as a reintroduction site for Houston Toads. We also recommend further studies to potentially broaden the regulatory definition of Houston Toad habitat beyond the current restrictive view of canopied forest alone. Such studies would need to examine the utility of native grasslands as dispersal corridors/upland habitat for juvenile Houston Toads. Our findings emphasize the utility of experimental studies in directly examining the influence of perceived threats to imperiled species and the role of such clarifications in adapting recovery efforts. [ABSTRACT FROM AUTHOR]

Research has been conducted on painted turtle Chrysemys picta, a continentally distributed polytypic species. The authors report the study of variation in rapidly evolving mitochondrial control region in turtles from different localities carried out in testing the hypothesis that the painted turtle is a continentally distributed species based on molecular analysis.

Abundance estimates play an important part in the regulatory and conservation decision-making process. It is important to correct monitoring data for imperfect detection when using these data to track spatial and temporal variation in abundance, especially in the case of rare and elusive species. This paper presents the first attempt to estimate abundance of the Rio Grande cooter (Pseudemys gorzugi) while explicitly considering the detection process. Specifically, in 2016 we monitored this rare species at two sites along the Black River, New Mexico via traditional baited hoop-net traps and less invasive visual surveys to evaluate the efficacy of these two sampling designs. We fitted the Huggins closed-capture estimator to estimate capture probabilities using the trap data and distance sampling models to estimate detection probabilities using the visual survey data. We found that only the visual survey with the highest number of observed turtles resulted in similar abundance estimates to those estimated using the trap data. However, the estimates of abundance from the remaining visual survey data were highly variable and often underestimated abundance relative to the estimates from the trap data. We suspect this pattern is related to changes in the basking behavior of the species and, thus, the availability of turtles to be detected even though all visual surveys were conducted when environmental conditions were similar. Regardless, we found that riverine habitat conditions limited our ability to properly conduct visual surveys at one site. Collectively, this suggests visual surveys may not be an effective sample design for this species in this river system. When analyzing the trap data, we found capture probabilities to be highly variable across sites and between age classes and that recapture probabilities were much lower than initial capture probabilities, highlighting the importance of accounting for detectability when monitoring this species. Although baited hoop-net traps seem to be an effective sampling design, it is important to note that this method required a relatively high trap effort to reliably estimate abundance. This information will be useful when developing a larger-scale, long-term monitoring program for this species of concern. [ABSTRACT FROM AUTHOR]

The article focuses on the use of automated recording devices (ARDs) to monitor the chorusing behavior of the endangered Houston Toad, providing more precise and detailed data compared to traditional manual call surveys. It discusses how ARDs help in identifying the environmental variables, such as temperature and barometric pressure, that influence the toads' vocalization patterns.

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.

For many rare or endangered anurans, monitoring is achieved via auditory cues alone. Human-performed audio surveys are inherently biased, and may fail to detect animals when they are present. Automated audio recognition tools offer an alternative mode of observer-free monitoring. Few commercially available platforms for developing these tools exist, and little research has investigated whether these tools are effective at detecting rare vocalization events. We generated a recognizer for detecting the vocalization of the endangered Houston toad Anaxyrus houstonensis using SongScope& bioacoustics software. We developed our recognizer using a large sample of training data that included only the highest quality of recorded audio (i.e., low noise, no interfering vocalizations) divided into small, manageable batches. To track recognizer performance, we generated an independent set of test data through randomly sampling a large population of audio known to possess Houston toad vocalizations. We analyzed training data and test data recursively, using a criterion of zero tolerance for false-negative detections. For each step, we incorporated a new batch of training data into the recognizer. Once we included all training data, we manually verified recognizer performance against one full month (March 2014) of audio taken from a known breeding locality. The recognizer successfully identified 100% of all training data and 97.2% of all test data. However, there is a trade-off between reducing false-negative and increasing false-positive detections, which limited the usefulness of some features of SongScope. Methods of automated detection represent a means by which we may test the efficacy of the manual monitoring techniques currently in use. The ability to search any collection of audio recordings for Houston toad vocalizations has the potential to challenge the paradigms presently placed on monitoring for this species of conservation concern. [ABSTRACT FROM AUTHOR]

Abundance estimates play an important part in the regulatory and conservation decision-making process. It is important to correct monitoring data for imperfect detection when using these data to track spatial and temporal variation in abundance, especially in the case of rare and elusive species. This paper presents the first attempt to estimate abundance of the Rio Grande cooter (Pseudemys gorzugi) while explicitly considering the detection process. Specifically, in 2016 we monitored this rare species at two sites along the Black River, New Mexico via traditional baited hoop-net traps and less invasive visual surveys to evaluate the efficacy of these two sampling designs. We fitted the Huggins closed-capture estimator to estimate capture probabilities using the trap data and distance sampling models to estimate detection probabilities using the visual survey data. We found that only the visual survey with the highest number of observed turtles resulted in similar abundance estimates to those estimated using the trap data. However, the estimates of abundance from the remaining visual survey data were highly variable and often underestimated abundance relative to the estimates from the trap data. We suspect this pattern is related to changes in the basking behavior of the species and, thus, the availability of turtles to be detected even though all visual surveys were conducted when environmental conditions were similar. Regardless, we found that riverine habitat conditions limited our ability to properly conduct visual surveys at one site. Collectively, this suggests visual surveys may not be an effective sample design for this species in this river system. When analyzing the trap data, we found capture probabilities to be highly variable across sites and between age classes and that recapture probabilities were much lower than initial capture probabilities, highlighting the importance of accounting for detectability when monitoring this species. Although baited hoop-net traps seem to be an effective sampling design, it is important to note that this method required a relatively high trap effort to reliably estimate abundance. This information will be useful when developing a larger-scale, long-term monitoring program for this species of concern. [ABSTRACT FROM AUTHOR]