Geology topics

Emily D. Thorne

Publications and source records attributed to Emily D. Thorne.

13 recordsLinked to original sources

USGS2024

Second guessing the maximum likelihood estimator values for bat surveys

T The U.S. Fish and Wildlife Service allows acoustical surveys and automated identification software to determine the presence of the endangered northern long-eared bat ( Myotis septentrionalis ) and Indiana bat ( Myotis sodalis ). Analytical software is required to assess presence probability on a site-night basis using a maximum likelihood estimator (MLE) that accounts for interspecific bat misclassification rates. The current standard for occupancy is a returned MLE P-value < 0.05 at the nightly level irrespective of the number of files identified as either northern long-eared bats or Indiana bats. These MLE P-values can vary based on presence of other bat species with similar calls and the relative proportions of all species recorded. Accordingly, there is concern that with few nightly northern long-eared bat or Indiana bat recordings or the presence of large numbers of high-frequency bats, false-negative findings from a swamping effect could result. Using data collected in 2020–2021 by the U.S. Fish and Wildlife Service to set nationwide acoustic monitoring guidelines, we examined the relationship of returned software MLE P-values from 4873 site-nights of acoustic detector data relative to nightly counts of northern long-eared bats and Indiana bats, overall counts of other high-frequency bats, and habitat cover type. For both northern long-eared bats and Indiana bats, nights with one or more echolocation pass files identified as either species but above the MLE P-value threshold largely occurred where nightly counts of the target species was <15 and their proportion to the count of high-frequency bat species was low. We followed this analysis with a simulation using a known call library and observed similar patterns. Accordingly, with few nightly cholocation passes, post-hoc visual assessment following automated software identification easily could be undertaken. Evidence of swamping by other high-frequency species causing positive file identification creating false-negative or false-positives of northern long-eared bats and Indiana bats was not apparent at nightly counts of either species > 10.

Alabama, Arkansas, Illinoise, Indiana, Kentucky, M↗

USGS2024

Home range size and resource use by eastern spotted skunks in Virginia

Throughout much of the eastern U.S., many forested ecosystems have lost large amounts of core forest areas due to land-use change, isolating wildlife in forest fragments. The eastern spotted skunk ( Spilogale putorius ) is considered a species of conservation concern in Virginia, where populations are restricted to spatially disjunct forest patches in the central Appalachian Mountains. We caught and radio-tagged eastern spotted skunks in the Appalachian Mountains of Virginia to assess whether current habitat fragmentation restricts skunk movements and hence distribution, potentially leading to isolation among habitat patches. Denning home range size (approximately 3.7 km 2 ) in our study was smaller than those in other studies of eastern spotted skunks and excursive movements were primarily limited to core forested areas (>2 km 2 ). Core forested areas were used more than non-forested and forest-edge areas. We conclude core forest area fragmentation limits eastern spotted skunk movement between mountain ridges. Increased forest patch connectivity may help prevent genetic and demographic isolation, reduce the likelihood of local extinctions, and facilitate colonization of suitable unoccupied areas.

Virginia↗

USGS2024

Seasonal activity patterns of northern long-eared bats on the coastal Mid-Atlantic

Conservation of bats declining from white-nose syndrome (WNS) impacts requires an understanding of both temporal and landscape-level habitat relationships. Traditionally, much of the research on bat ecology has focused on behavior of summer maternity colonies within species’ distribution cores, including that of the endangered northern long-eared bat ( Myotis septentrionalis ). To further our knowledge of this species, we evaluated multi-season activity patterns in eastern North Carolina and Virginia, including areas where populations were recently discovered. We used passive acoustic monitoring to assess relative and probable activity of northern long-eared bats from October 2016 to August 2021. Northern long-eared bat relative activity was greatest in areas containing greater proportions of woody wetlands and upland pine-dominated evergreen forests. However, the likelihood of recording northern long-eared bats was associated with smaller proportions of woody wetlands and open water resources. Furthermore, we observed a higher probability of recording northern long-eared bats during non-winter seasons. Probable activity was greatest at temperatures between 10 and 25 C, potentially highlighting an optimal thermoneutral zone for the species regionally. Relative activity of northern long-eared bats on the Coastal Plain of Virginia and North Carolina was primarily driven by cover features, whereas probable activity was driven by a combination of cover features, seasonality, and temperature. Therefore, acoustical surveys for this species may be most effective when targeting woody wetlands adjacent to upland forests, particularly upland pine-dominated evergreen stands, during moderate temperatures of non-winter seasons (1 April–15 November). Moreover, conservation of a diverse mosaic of woody wetlands juxtaposed by upland forests may promote both roosting and overwintering habitat, thereby enhancing overwintering survival, maternity colony establishment, and ultimately, successful reproduction of northern long-eared bats.

North Carolina, Virginia↗

USGS2024

Second guessing the maximum likelihood estimator values for bat surveys.

The U.S. Fish and Wildlife Service allows acoustical surveys and automated identification software to determine the presence of the endangered northern long-eared bat ( Myotis septentrionalis ) and Indiana bat ( Myotis sodalis ). Analytical software is required to assess presence probability on a site-night basis using a maximum likelihood estimator (MLE) that accounts for interspecific bat misclassification rates. The current standard for occupancy is a returned MLE P-value < 0.05 at the nightly level irrespective of the number of files identified as either northern long-eared bats or Indiana bats. These MLE P-values can vary based on presence of other bat species with similar calls and the relative proportions of all species recorded. Accordingly, there is concern that with few nightly northern long-eared bat or Indiana bat recordings or the presence of large numbers of high-frequency bats, false-negative findings from a swamping effect could result. Using data collected in 2020–2021 by the U.S. Fish and Wildlife Service to set nationwide acoustic monitoring guidelines, we examined the relationship of returned software MLE P-values from 4873 site-nights of acoustic detector data relative to nightly counts of northern long-eared bats and Indiana bats, overall counts of other high-frequency bats, and habitat cover type. For both northern long-eared bats and Indiana bats, nights with one or more echolocation pass files identified as either species but above the MLE P-value threshold largely occurred where nightly counts of the target species was <15 and their proportion to the count of high-frequency bat species was low. We followed this analysis with a simulation using a known call library and observed similar patterns. Accordingly, with few nightly cholocation passes, post-hoc visual assessment following automated software identification easily could be undertaken. Evidence of swamping by other high-frequency species causing positive file identification creating false-negative or false-positives of northern long-eared bats and Indiana bats was not apparent at nightly counts of either species > 10.

Alabama, Arkansas, Illinois, Indiana, Kentucky, Mi↗

USGS2023

Activity patterns of Allegheny Woodrats (Neotoma magister) and two potential competitors in Virginia

Neotoma magister (Allegheny Woodrat) is a nocturnal, emergent rock-habitat specialist (i.e., inhabits rocky outcrops, boulderfields, and caves). Woodrat populations have declined range-wide due to habitat fragmentation, endoparasites, and interspecific competition. We estimated the diel activity curves of Allegheny Woodrats and assessed the effects of habitat type (exposed rock habitat/cave-exterior vs. cave-interior) and season (spring, summer, and fall) on curve shape. We also investigated the effect of 2 granivorous competitors' presence and activity curves ( Peromyscus spp. and Tamias striatus [Eastern Chipmunk]) on woodrat activity. Additionally, we investigated whether the presence or absence of Procyon lotor (Raccoon), a primary carrier of Baylisascaris procyonis (Raccoon Roundworm), significantly affects the presence or absence of Allegheny Woodrats. We used remote-detecting cameras to document the diel cycles of Allegheny Woodrats and 2 competitors across 83 sites in western Virginia and 2 sites in West Virginia from 2017 to 2022. For 13,002 recorded events, we detected woodrats at 36 of 85 sites (3778 camera events). We observed a higher proportion of daytime activity by woodrats within cave interiors than cave exteriors. Allegheny Woodrat activity curves differed among seasons, with the greatest differences observed between summer and fall and with ∼80% activity overlap. These activity curves differed significantly when co-occurring with versus not co-occurring with a competitor. Additionally, Allegheny Woodrats showed an inverse activity rate with Peromyscus spp. Thus, our results suggest that competition avoidance via temporal partitioning occurs between these species. Allegheny Woodrats and Raccoons occurred together more often than expected suggesting the presence of woodrats is currently not reduced by the presence of Raccoons. Our remote-detecting camera data help elucidate relationships of Allegheny Woodrats with presumptive competitors, and open avenues for further investigation in Virginia.

Northeastern Naturalist↗

USGS2023

Maximum likelihood estimator and nightly acoustic count values as weight of evidence of bat maternity activity

Since the spread of white-nose syndrome in North America, several bat species have shown precipitous declines in abundance and distribution. With lower netting detection probabilities for the currently threatened but proposed endangered northern long-eared bat ( Myotis septentrionalis ) and endangered Indiana bats ( Myotis sodalis ), determination of presence or absence for regulatory clearance often has shifted to the use of acoustic sur- veys. However, acoustic surveys are unable to differentiate between non-reproductive individuals versus a maternity colony. We used recorded nightly echolocation pass counts of bat species-specific probabilities with maximum likelihood estimator (MLE) scores to determine thresholds by cover type and reproductive period whereby the potential for northern long-eared bat or Indiana bat maternity colonies occurs. Where nightly MLE P- values were <0.05, mean predicted nightly pass counts were significantly higher in areas of known northern long-eared bat and Indiana bat maternity colonies versus sites that were in either species’ distribution but with no maternity activity known. Nightly pass counts (MLE P < 0.05) were higher for sites with observed maternity activity for both bat species across forest, forest-field edge, and riparian areas versus sites where no maternity activity was known. For northern long-eared bats, nightly pass counts were highest in the juvenile volancy period (after 15 July) whereas, for Indiana bats, nightly pass counts were highest in the lactation period (16 June to 15 July). Except for edge conditions for northern long-eared bats, a MLE P < 0.05 combined with nightly pass counts above thresholds developed from surveys at known maternity colony sites for both species may indicate potential presence of a maternity colony locally and provide a tool to more efficiently use targeted mist-netting for further determination.

eastern United States↗

USGS2023

Estimating elk abundance using the Lincoln-Petersen method

Achieving a target population size is often the first goal of species restorations. From 2012 to 2014, the Virginia Department of Wildlife Resources released 75 elk ( Cervus canadensis ) originating from Kentucky into Buchanan County in southwestern Virginia. These individuals were ear tagged with unique numbers upon release with an additional 33 elk tagged within the Virginia Elk Management Zone (VEMZ) from 2019 through early 2022. To assess post-release population size, we conducted visual driving surveys throughout Buchanan County from January through mid-April, 2021 and January through March, 2022, counting elk and noting sex, age class, and tagged individuals when observed. We conducted four surveys annually, each consisting of pooled elk counts from eight driving routes, and calculated a Lincoln-Petersen population estimate with Chapman’s bias correction for each survey, then averaged estimates for each year. The population estimate in Buchanan County was 250 (95% CI: 100–400) elk in 2021 and 303 (155–452) in 2022. Our elk population estimates indicate Virginia is on the trajectory of meeting the first goal in their 2019–2028 elk management plan of achieving a viable elk population.

Virginia↗

USGS2022

Drivers of habitat quality for a reintroduced elk herd

Understanding spatiotemporal variation in habitat quality is essential for guiding wildlife reintroduction and restoration programs. The habitat productivity hypothesis posits that home range size is inversely related to habitat quality. Thus, home range size may be used as a proxy for habitat quality and can identify important land cover features for a recovering species. We sought to quantify variation in home range size across the biological cycle (seasons) for a reintroduced elk ( Cervus canadensis ) population in southwestern Virginia, USA and quantify habitat quality by linking home range sizes to the land cover types they contain using linear mixed-effects models. We found mean home range size was largest during late gestation for female elk. Additionally, throughout the year, smaller home ranges were associated with larger proportions of non-forested habitats whereas forested habitats were generally the opposite. However, both presumed poor- and high-quality habitats influenced female elk space use. Our approach revealed spatial variation in habitat quality for a recovering elk herd, demonstrated the importance of non-forested habitats to elk, can guide decisions regarding the location of future elk reintroduction programs, and serve as a model for evaluating habitat quality associated with wildlife reintroductions.

Virginia↗

USGS2022

Comparison of two detection methods of a declining rodent, the Allegheny woodrat, in Virginia

Allegheny woodrats Neotoma magister are an imperiled small mammal species most associated with emergent rock habitats in the central Appalachian Mountains and the Ohio River Valley. The monitoring of populations and their spatiotemporal distributions typically has relied on labor-intensive livetrapping. The use of remote-detecting cameras holds promise for being an equally or more effective method to determine species presence, although trap-based captures permit the estimation of other parameters (e.g., survival, population size, site fidelity). In 2017, 2018, and 2020 we compared standard livetrapping with paired cameras for determining site occupancy of Allegheny woodrats in the central Appalachian Mountains of western Virginia. We further examined the influence of baited vs. unbaited cameras at several sites of confirmed occupancy in 2019. We observed that the detection probability using cameras was approximately 1.7 times that of live traps. Also, detection probability at baited camera traps was 1.3–2.0 times that of unbaited camera traps. Estimates of occupancy ranged from 0.44 to 0.49. Our findings suggest that the use of baited remote-detecting cameras provides a more effective method than livetrapping for detecting Allegheny woodrats. Our study provides a framework for the development of a large-scale, long-term monitoring protocol of Allegheny woodrats with the goals of identifying changes in the distribution of the species and quantifying local extinction and colonization rates at emergent rock outcrops and caves throughout the species' known distribution.

Virginia↗

USGS2022

Redundancy analysis reveals complex den use patterns by eastern spotted skunks, a conditional specialist

Wildlife managers tasked with understanding habitat and resource selection at the population level attempt to characterize patterns in nature that aid and inform conservation. Resource selection functions (RSFs), such as discrete choice analyses, are the standard convention to characterize the effects of habitat attributes on resource selection patterns. These tools are invaluable for wildlife management and conservation and have proven successful in numerous studies. However, the analysis of small datasets using RSF becomes problematic when attempting to account for complex sources of variation, and the inclusion of factors such as weather or intrinsic variation on target species' response may produce models with poor predictive ability. We compared the application of generalized linear mixed-effects modeling (GLMM) and redundancy analysis (RDA) on Appalachian spotted skunk ( Spilogale putorius putorius ) den selection data at four study sites within the George Washington, Jefferson, and Monongahela National Forests, and surrounding private lands in the Appalachian Mountains of western Virginia and northeastern West Virginia. We assessed the need for the inclusion of alternative sources of variation (i.e., weather conditions and individual intrinsic variation) in addition to standard habitat attributes to better identify sources of variation in den selection. The RDA elucidated complex and opposing relationships, whereby den type use was based on reproductive status or weather condition, which were not evident in the GLMM model that relied solely on habitat measures. Our results demonstrated the importance of examining resource selection data using multivariate techniques in addition to conventional discrete choice analyses to better understand intricate habitat–species relationships, especially for small datasets. Furthermore, from our analyses, we proposed that spotted skunks are neither a true generalist nor specialist species. We introduced and define the term “conditional specialist” to represent a species that is conditionally selective of a given resource in response to one or more current environmental or intrinsic conditions.

Viginia, West Virginia↗

USGS2021

Predicted spatial distribution of the Eastern Spotted Skunk (Spilogale putorius) in Virginia using detection and non-detection records

The geographic distribution of a species is a fundamental component in understanding its ecology and is necessary for forming effective conservation plans. For rare and elusive species of conservation concern, accurate maps of predicted occurrence are particularly problematic and often highly subjective. Spilogale putorius (Eastern Spotted Skunk) populations have experienced large declines since the 1940s. Their elusive behavior and perceived rarity result in low detection probability when using conventional methods for sampling small mammals. Low detection probability often causes uncertainty as to where Eastern Spotted Skunks could be a management concern. We modeled the distribution of predicted occurrence of Eastern Spotted Skunks using verifiable occurrence and non-detection records obtained throughout Virginia from 2010 to 2020. Occurrence data consisted of trapping records reported to the Virginia Department of Wildlife Resources, incidental photo-verified reports of sightings and road-killed animals, and remote-camera detections. Non-detections were presumed at baited remote-camera locations following intense survey efforts. We fit predicted occurrence models using generalized linear modeling in an information-theoretic framework using the package ‘stats’ in Program R. Our results incidated a greater probability of presence from the Blue Ridge westward, increasing with slope steepness along northeastern- to southeastern-facing slopes and decreasing with slope steepness along southeastern- to southwestern-facing slopes. Emergent rock outcrops prominent along northeastern slopes offer ample protective rocky cover, whereas mixed Quercus spp. (oak), Kalmia latifolia (Mountain Laurel), and Rhododendron maximum (Rosebay Rhododendron) forest communities along southern-facing slopes provide suitable areas of cover, both of which are critical for spotted skunk survival and reproductive success. Our analysis provides insight into the relationships between landscape features and Eastern Spotted Skunk distributions across Virginia. Understanding these relationships is critical for the effective management and conservation of this vulnerable species.

Virginia↗

USGS2021

Demography of the Appalachian Spotted Skunk (Spilogale putorius putorius)

Spilogale putorius (Eastern Spotted Skunk) is a small, secretive carnivore that has substantially declined throughout the eastern United States since the mid-1900s. To better understand the current status of Eastern Spotted Skunks, we studied survival and reproduction of the S. p. putorius (Appalachian Spotted Skunk) subspecies across 4 states in the central and southern Appalachian Mountains from 2014 to 2020. Using encounter histories from 99 radio-collared Appalachian Spotted Skunks in a Kaplan–Meier known-fate survival analysis, we calculated a mean annual adult survival rate of 0.58. We did not find support for this survival rate varying by sex, predator cover (canopy cover and topographic ruggedness), or climate. Compared to estimates of survival from previous research, our data suggest that Appalachian Spotted Skunk survival is intermediate to the S. p. interrupta (Plains Spotted Skunk) and S. p. ambarvalis (Florida Spotted Skunk) subspecies of Eastern Spotted Skunk. We located 11 Appalachian Spotted Skunk natal dens and estimated mean litter size to be 2.8 juveniles per female. We used a Lefkovitch matrix to identify the most important demographic rates and found that adult survivorship had the largest impact on the population growth rate. These results provide important demographic information for future Eastern Spotted Skunk population viability analyses and can serve as a baseline for future comparative assessments of the effects of management interventions on the species.

Alabama, North Carolina, South Carolina, Virginia↗

USGS2017

Winter habitat associations of eastern spotted skunks in Virginia

Eastern spotted skunk ( Spilogale putorius ) populations have declined throughout much of their range in the eastern United States over recent decades. Declines have been attributed to habitat loss or change, increased competition with sympatric mesocarnivore species, or disease. To better understand the extant distribution of spotted skunks in the Appalachian Mountains of western Virginia, USA, we used a detection-non-detection sampling approach using baited camera traps to evaluate the influence of landscape-level environmental covariates on spotted skunk detection probability and site occupancy. We conducted camera trap surveys at 91 sites from January to May in 2014 and 2015. Spotted skunk occupancy was associated with young-aged forest stands at lower elevations and more mature forest stands at higher elevations. Both land cover types in this region can be characterized as having complex forest structure, providing cover that varies with stand age, species composition, elevation, and management regime. Our results provide insight into factors that influence spotted skunk spatial distribution and habitat selection, information that can be used to generate conservation assessments and inform management decisions.

Virginia↗