Geology topics

Robert Charles Lonsinger

Publications and source records attributed to Robert Charles Lonsinger.

33 records · Page 2Linked to original sources

USGS2024

Abundance estimates of Gunnison’s prairie dogs compared to the number of active burrows

Reliable estimates of prairie dog ( Cynomys spp.) population size and distribution are critical for assessing the status of prairie dogs and for selecting sites to reintroduce black-footed ferrets ( Mustela nigripes ). The density of active prairie dog burrows has commonly been used as an index of prairie dog abundance. Indices derived from active burrow counts were developed for black-tailed ( C. ludovicianus ) and white-tailed ( C. leucurus ) prairie dogs, but their efficacy has not been evaluated for all prairie dog species and studies affirming their validity with robust abundance estimators are few. We indexed or estimated the abundance of Gunnison's prairie dogs ( C. gunnisoni ) in the Aubrey Valley, Arizona, USA, in 2006 at 2 different time periods using 4 different methods—maximum above ground counts (MAGC), minimum number known alive (MNKA), capture-mark-recapture (CMR), and mark-resight—and compared these estimates to active burrow counts in 2005 and 2006. We found no positive relationship between active burrow counts and any abundance estimators. Mark-resight estimates of abundance were greater than the MNKA and were positively correlated with both the MNKA ( r 2 = 0.30) and CMR estimates ( r 2 = 0.49). Both CMR estimates and MAGC were typically below the MNKA and therefore biased low. Our results indicated that more rigorous estimation methods may be necessary to accurately estimate prairie dog abundance and assess habitat quality for ferret conservation.

Arizona↗

USGS2024

Sources of bias in applying close-kin mark–recapture to terrestrial game species with different life histories

Close-kin mark–recapture (CKMR) is a method analogous to traditional mark–recapture but without requiring recapture of individuals. Instead, multilocus genotypes (genetic marks) are used to identify related individuals in one or more sampling occasions, which enables the opportunistic use of samples from harvested wildlife. To apply the method accurately, it is important to build appropriate CKMR models that do not violate assumptions linked to the species’ and population's biology and sampling methods. In this study, we evaluated the implications of fitting overly simplistic CKMR models to populations with complex reproductive success dynamics or selective sampling. We used forward-in-time, individual-based simulations to evaluate the accuracy and precision of CKMR abundance and survival estimates in species with different longevities, mating systems, and sampling strategies. Simulated populations approximated a range of life histories among game species of North America with lethal sampling to evaluate the potential of using harvested samples to estimate population size. Our simulations show that CKMR can yield nontrivial biases in both survival and abundance estimates, unless influential life history traits and selective sampling are explicitly accounted for in the modeling framework. The number of kin pairs observed in the sample, in combination with the type of kinship used in the model (parent–offspring pairs and/or half-sibling pairs), can affect the precision and/or accuracy of the estimates. CKMR is a promising method that will likely see an increasing number of applications in the field as costs of genetic analysis continue to decline. Our work highlights the importance of applying population-specific CKMR models that consider relevant demographic parameters, individual covariates, and the protocol through which individuals were sampled.

Ecology↗

USGS2024

Using down-scan capabilities from recreational-grade side-scan sonar systems to sample paddlefish and evaluate depth use in a reservoir

Recreational-grade side-scan sonar (SSS) has only recently been applied to estimate abundance of Paddlefish Polyodon spathula , a large pelagic planktivore, in reservoirs. Current recreational-grade SSS units also have a dedicated down-scan channel, which may be useful for detecting Paddlefish in reservoirs because the range of depths they inhabit. We investigated the utility of down-scan images using SSS data from a previously published study of Paddlefish in Keystone Lake, Oklahoma. Two readers counted Paddlefish and estimated the depth of each fish and the water column. We used proximity functions in a geographic information system to find individual Paddlefish that were common between the readers. We further used proximity functions to identify common fish observed from the SSS survey conducted previously as an aid to compare and refine down-scan estimates. Depth of Paddlefish averaged approximately 7 m, but fish were deeper when water was deeper. Density estimates from down-scan were comparable to side-scan, but only after utilizing the side-scan data to adjust for detection-by-distance in a dual-gear approach. Down-scan data thus appear to be useful for not only estimating density of Paddlefish, but also for incorporating depth use, creating a three-dimensional database of locations that can inform managers of optimal depths for sampling gear (e.g., gill nets), improve monitoring efficiency, and facilitate better management of reservoir populations.

Oklahoma↗

USGS2024

Pasture and diurnal temperature are key predictors of regional Plains Spotted Skunk (Spilogale interrupta) distribution

The Plains Spotted Skunk ( Spilogale interrupta ) is a small carnivore native to central North America that has experienced significant population reductions, and there is a lack of information about the species that could inform conservation. Our study aimed to address knowledge gaps about the distribution and habitat associations of the species in South Dakota using species distribution modeling. We used species location data collected from state natural resource managers, trappers, and members of online social media groups dedicated to hunting and wildlife conservation; environmental predictors; and 6 predictive modeling algorithms (i.e., artificial neural networks, artificial classification tree analysis, generalized boosting models, maximum entropy, multivariate adaptive regression splines, and random forests) to develop climate and landcover ensemble distribution models. The most important climate and landcover predictors were mean temperature diurnal range (i.e., average monthly differences between daily high and low temperatures) and proportion of area classified as pasture. Ensemble model concordance identified approximately 31,300 km 2 of potential Plains Spotted Skunk habitat primarily in eastern South Dakota and between the watersheds of the Missouri and James rivers. Our results offer insights that can guide conservation and inform effective management strategies for conserving Plains Spotted Skunk populations in the northern Great Plains. The promotion of low-intensity agricultural practices such as maintaining pastures, farm buildings, fences rows, and the management of woodland encroachment may improve habitat suitability and facilitate the recovery of plains spotted skunks in the region.

South Dakota↗

USGS2024

Updated distribution for two freshwater mussel species of conservation concern in Oklahoma

Qualitative and quantitative sampling efforts in the Verdigris River, OK (upstream of Lake Oologah), yielded new distributional records of 2 freshwater mussel species of conservation need: Cyprogenia aberti (Western Fanshell) and Ptychobranchus occidentalis (Ouachita Kidneyshell). The Ouachita Kidneyshell has not been documented alive during a scientific survey in the Oklahoma portion of the Verdigris River in nearly 100 years. Our observations extend the known distribution for the Western Fanshell further downstream into Oklahoma by ∼36 river km. These findings indicate an expansion in the known range and potential improvement in the populations of 2 imperiled mussel species, contrary to the prevailing global trend of mussel population decline.

Oklahoma↗

USGS2024

White-backed hog-nosed skunk (Conepatus Leuconotus) occurrence in the Oklahoma panhandle

The white-backed hog-nosed skunk ( Conepatus leuconotus ) is an understudied mesocarnivore thought to be declining throughout its range in the southwestern United States. With the exception of a single skull of unknown age, hog-nosed skunks have not been documented in Oklahoma since 1930. We conducted a camera trapping survey in Cimarron County, Oklahoma during summer 2022 and confirmed the presence of a hog-nosed skunk in Oklahoma. This finding provides the first evidence of a hog-nosed skunk in Oklahoma in over 90 years and is within the range of a poorly documented subspecies ( C. l. figginsi ) believed to be in decline.

Oklahoma↗

USGS2024

Survey and monitoring methods for furbearers

There is a continuing need to assess the state (distribution and abundance) of furbearer populations throughout North America for state and provincial agencies to properly manage furbearers. With an expanding human population and continued changes in land-use practices, habitat loss and fragmentation, declines in natural prey, increases in disease transmission from domestic species, and increased competition with other species, many wildlife agencies have placed the management and conservation of some furbearer species as a top priority. Paramount to making informed decisions regarding management of furbearer populations is accurate information on their current distribution and population status.

Book chapter↗

USGS2023

Efficacy of machine learning image classification for automated occupancy-based monitoring

Remote cameras have become a widespread data-collection tool for terrestrial mammals, but classifying images can be labor intensive and limit the usefulness of cameras for broad-scale population monitoring. Machine learning algorithms for automated image classification can expedite data processing, but image misclassifications may influence inferences. Here, we used camera data for three sympatric species with disparate body sizes and life histories – black-tailed jackrabbits ( Lepus californicus ), kit foxes ( Vulpes macrotis ), and pronghorns ( Antilocapra americana ) – as a model system to evaluate the influence of competing image classification approaches on estimates of occupancy and inferences about space use. We classified images with: (i) single review (manual), (ii) double review (manual by two observers), (iii) an automated-manual review (machine learning to cull empty images and single review of remaining images), (iv) a pretrained machine-learning algorithm that classifies images to species (base model), (v) the base model accepting only classifications with ≥95% confidence, (vi) the base model trained with regional images (trained model), and (vii) the trained model accepting only classifications with ≥95% confidence. We compared species-specific results from alternative approaches to results from double review, which reduces the potential for misclassifications and was assumed to be the best approximation of truth. Despite high classification success, species-level misclassification rates for the base and trained models were sufficiently high to produce erroneous occupancy estimates and inferences related to space use across species. Increasing the confidence thresholds for image classification to 95% did not consistently improve performance. Classifying images as empty (or not) offered a reasonable approach to reduce effort (by 97.7%) and facilitated a semi-automated workflow that produced reliable estimates and inferences. Thus, camera-based monitoring combined with machine learning algorithms for image classification could facilitate monitoring with limited manual image classification.

Utah↗

USGS2023

The first documented interaction between a long-tailed weasel (Mustela frenata) and a plains spotted skunk (Spilogale interrupta) carcass

A novel interaction between a long-tailed weasel ( Mustela frenata ) and a plains spotted skunk ( Spilogale interrupta ) carcass is detailed. In November 2020, a farmer in Edmunds County in north-central South Dakota sent in a video recording of a long-tailed weasel with a spotted skunk carcass. Location of the event, carcass condition, and recorded behavior of the long-tailed weasel offer probable, but unconfirmed, evidence that the spotted skunk was killed by the long-tailed weasel.

South Dakota↗

USGS2023

Viability of side-scan sonar to enumerate Paddlefish, a large pelagic freshwater fish, in rivers and reservoirs

Recreational-grade side-scan sonar (SSS) has become an invaluable tool for inland fisheries, particularly when characterizing underwater habitat, but it is being increasingly used for enumerating large-bodied (> 1 m total length [TL]) aquatic fauna. We used SSS in river and reservoir environments to evaluate methods for identifying and counting Paddlefish Polyodon spathula , a large pelagic planktivore of recreational and economic importance that can exceed 2 m in length and weigh over 70 kg. We assessed accuracy and precision among readers to identify Paddlefish by assigning confidence scores (1–3; with 3 being more confident) to sonar images of a ballistics-gel filled fiberglass replica Paddlefish. Readers varied in their confidence scores for the replica Paddlefish and no reader could identify the target beyond 25 m from the transducer. Afterwards, we used SSS to survey several kilometers of a reservoir during summer residency and a large river during springtime spawning migrations. Two readers counted Paddlefish images in the SSS recordings and we estimated population size in the surveyed area with distance sampling. In the reservoir, the number of Paddlefish counted ranged from 172 to 184. In the river, the number of Paddlefish counted ranged from 165 to 617. The exponential model of distance was most-supported for detection in both environments, except there was support for a half-norm distribution for one reader in the river. In the reservoir, abundance estimates were statistically similar between readers at approximately 1500 (7/ha) in the total scanned area. In the river, similar abundance estimates were obtained with the half-norm model from one reader compared to the exponential model of the other reader, resulting in approximately 1500 individuals (30/ha) in the surveyed area. The application of SSS to count Paddlefish has some clear advantages to traditional methods, such as gill netting, and can be done at multiple times of the year. Distance sampling methods compensated for differences in counts among readers, indicating distance sampling can produce similar abundance estimates even when variation in counts exists among readers.

Oklahoma↗

USGS2023

The Factors Affecting Female Black Bear Harvest Rates in Pennsylvania

Pennsylvania’s black bear ( Ursus americanus ) population increased in abundance and distribution during the latter third of the 20th century, leading to an increase in human-bear conflicts. Increases in harvest opportunities from 2002–2018 aimed to stabilize black bear population growth but did not substantially increase harvest, and annual harvest was often below the desired goal of 20% removal. Consequently, additional changes to Pennsylvania’s black bear hunting seasons occurred from 2019–2021, including starting harvest earlier, expanding the length of seasons, and adding additional seasons (i.e., a muzzleloader and special rifle season). Understanding how earlier harvest seasons and new methods of take (i.e., muzzleloader) influence female black bear harvest vulnerability is important to informing harvest management. We trapped and GPS-collared adult female bears in the Sproul State Forest in northcentral Pennsylvania from 2019–2021 to determine home range sizes, patterns of resource selection, and sources of mortality during fall harvest seasons. We assessed annual variability in relative abundance of fall hard mast. We evaluated temporal and spatial variation in hunter activity with road-side surveys and remote camera traps, respectively. We estimated fall and weekly home range size with utilization distributions through an autocorrelated kernel density estimation and evaluated the influence of predictors hypothesized to influence third-order resource selection using generalized linear mixed models. We investigated factors hypothesized to influence female black bear survival during hunting seasons with known-fate models. Mean fall home range size was 248.7 km 2 (range = 6.1–2636.1 km 2 ). Home range sizes varied by year and were generally smaller during archery harvest season than other periods. Patterns of weekly resource selection indicated bears selected steeper slopes and higher elevations outside of harvest seasons but shifted to less-steep areas in the week before harvest and the first week of harvest, and to lower elevations during harvest. Bears selected for areas containing oak ( Quercus spp.) trees throughout the fall. Survival was lower in older age bears, greater relative mast abundance conditions, steeper slopes, and areas of greater hunter space use during the general firearms season. Survival was higher in areas of greater hunter space use during archery season. Harvest rate of adult female bears was 0.345 in 2019, 0.321 in 2020, and 0.150 in 2021, and averaged 0.272 across all three years. The probability of an adult female black bear surviving all harvest seasons each year was 0.611 (SE = 0.086, 95% CI = 0.436, 0.761). The high harvest rate and low predicted survival may lead to population reduction.

Pennsylvania↗

USGS2022

The effect of scent lures on detection is not equitable among sympatric species

Context: Camera trapping is an effective tool for cost-efficient monitoring of species over large temporal and spatial scales and it is becoming an increasingly popular method for investigating wildlife communities and trophic interactions. However, camera trapping targeting rare and elusive species can be hampered by low detection rates, which can decrease the accuracy and precision of results from common analytical approaches (e.g., occupancy modeling, capture-recapture). Consequently, researchers often employ attractants to increase detection without accounting for how attractants influence detection of species among trophic levels. Aims: We aimed to evaluate the influences of a commonly used non-species-specific olfactory lure (i.e. sardines) and sampling design on detection of four species (i.e. bobcat [ Lynx rufus ], coyote [ Canis latrans ], raccoon [ Procyon lotor ], and eastern cottontail [ Sylvilagus floridanus ]) that represented a range of foraging guilds in an agricultural landscape. Methods: We set 180 camera stations, each for ∼28 days, during the summer of 2019. We set cameras with one of three lure treatments: (1) olfactory lure, (2) no olfactory lure, or (3) olfactory lure only during the latter half of the survey. We evaluated the influence of the lure at three temporal scales of detection (i.e. daily probability of detection, independent sequences per daily detection, and triggers per independent sequence). Key results: The lure tended to positively influence detection of coyotes and raccoons but negatively influenced detection of bobcats and eastern cottontails. The influence of the lure varied among temporal scales of detection. Conclusions: Scent lures can differentially influence detection of species within or among tropic levels, and the influence of a scent lure may vary among temporal scales. Implications: Our results demonstrate the importance of evaluating the influence of an attractant for each focal species when using camera data to conduct multi-species or community analyses, accounting for variation in sampling strategies across cameras, and identifying the appropriate species-specific temporal resolution for assessing variation in detection data. Furthermore, we highlight that care should be taken when using camera data as an index of relative abundance (e.g. as is commonly done with prey species) when there is variation in the use of lures across cameras.

Wildlife Research↗

USGS2022

Co-occurrence models fail to infer underlying patterns of avoidance and aggregation when closure is violated

Advances in multi-species monitoring have prompted an increase in the use of multi-species occupancy analyses to assess patterns of co-occurrence among species, even when data were collected at scales likely violating the assumption that sites were closed to changes in the occupancy state for the target species. Violating the closure assumption may lead to erroneous conclusions related to patterns of co-occurrence among species. Occurrence for two hypothetical species was simulated under patterns of avoidance, aggregation, or independence, when the closure assumption was either met or not. Simulated populations were sampled at two levels ( N = 250 or 100 sites) and two scales of temporal resolution for surveys. Sample data were analyzed with conditional two-species occupancy models, and performance was assessed based on the proportion of simulations recovering the true pattern of co-occurrence. Estimates of occupancy were unbiased when closure was met, but biased when closure violations occurred; bias increased when sample size was small and encounter histories were collapsed to a large-scale temporal resolution. When closure was met and patterns of avoidance and aggregation were simulated, conditional two-species models tended to correctly find support for non-independence, and estimated species interaction factors (SIF) aligned with predicted values. By contrast, when closure was violated, models tended to incorrectly infer a pattern of independence and power to detect simulated patterns of avoidance or aggregation that decreased with smaller sample size. Results suggest that when the closure assumption is violated, co-occurrence models often fail to detect underlying patterns of avoidance or aggregation, and incorrectly identify a pattern of independence among species, which could have negative consequences for our understanding of species interactions and conservation efforts. Thus, when closure is violated, inferred patterns of independence from multi-species occupancy should be interpreted cautiously, and evidence of avoidance or aggregation is likely a conservative estimate of true pattern or interaction.

Ecology and Evolution↗

USGS2022

Using noninvasive genetics for estimating density and assessing diet of urban and rural coyotes in Florida, USA

Coyotes ( Canis latrans ) are expanding their range and due to conflicts with the public and concerns of Coyotes affecting natural resources such as game or sensitive species, there is interest and often a demand to monitor Coyote populations. A challenge to monitoring is that traditional invasive methods involving live-capture of individual animals are costly and can be controversial. Natural resource management agencies can benefit from contemporary noninvasive genetic sampling approaches aimed at determining key aspects of Coyote ecology (e.g., population density and food habits). However, the efficacy of such approaches under different environmental conditions is poorly understood. Our objectives were to 1) examine accumulation and nuclear DNA degradation rates of Coyote scats in metropolitan and rural sites in Florida to help optimize methods to estimate population density; and 2) explore new genetic methods for determining diet of Coyotes based on vertebrate, plant, and invertebrate species DNA identified in scat. Recently developed DNA metabarcoding approaches make it possible to simultaneously identify DNA from multiple prey species in predator scat samples, but an exploration of this tool for assessing Coyote diet has not been pursued. We observed that scat accumulation rates (0.02 scats/km/day) did not vary between sites and fecal DNA amplification success decreased and genotyping errors increased over time with exposure to sun and precipitation. DNA sampling allowed us to generate a Coyote density estimate for the urban environment of eight Coyotes per 100 km2, but lack of recaptures in the rural area precluded density estimation. DNA metabarcoding showed promise for assessing diet contributions of vertebrate species to Coyote diet. Feral Swine (Sus scrofa) were detected as prey at higher frequencies than previously reported. We identify several considerations that can be used to optimize future noninvasive sampling efforts for Coyotes in the southeastern United States. We also discuss strengths and drawbacks of utilizing DNA metabarcoding for assessing diet of generalist carnivores such as Coyotes.

Florida↗

USGS2021

Seasonal variation in resource selection by subadult golden eagles in the Great Basin Desert

Golden eagles Aquila chrysaetos are a long-lived and wide-ranging species believed to be stable or in slight decline across North America. Golden eagles have an extended subadult stage (4–5 years) that is critical to maintaining recruitment into the breeding population and population viability. Compared to adult golden eagles, the ecology of subadult golden eagles (hereafter, subadults) has received little attention. We investigated patterns of resource selection for subadults in the Great Basin Desert of the western United States during summer and winter, 2013–2019. We monitored 46 subadults with GPS transmitters and related locations (n = 99 037) with predictors hypothesized to influence seasonal patterns of space use with mixed-effects logistic regression. Subadults selected for ridges and upper slopes in summer and winter, but higher elevations in summer. Subadults showed weak selection for lower ridge density in summer, which was likely facilitated by selection for areas with greater thermal wind current potential. In contrast, subadults showed strong selection for higher ridge density in winter. Subadults selected areas further from roads in summer and closer to roads and electrical transmission lines in winter, which may be related to winter scavenging of road-killed ungulates. Resource selection functions suggested subadults selected for shrublands and woodlands in both seasons, but odds ratios revealed that during winter subadults avoided shrublands and increased selection of woodlands relative to summer. Subadults selected for areas with infrequent fires in both seasons; areas with frequent fires were avoided in summer but selected for in winter. Seasonal changes in resource selection suggested that subadults used woodlands more than expected, potentially reflecting spatial partitioning by subadults to lower-quality habitats to minimize competition with breeding adults during winter when energetic demands for thermoregulation were presumably higher and prey more limited.

Utah↗