Geology topics

Ashley L. Whipple

Publications and source records attributed to Ashley L. Whipple.

6 recordsLinked to original sources

USGS2026

Modeling chronic wasting disease transmission risk in mule deer related to habitat characteristics

Chronic wasting disease (CWD) is a prion disease of cervids that spreads to uninfected individuals through direct transmission (contact with infected individuals), vertical transmission (from mother to offspring), or indirect transmission (exposure to contaminated environments). The risk of indirect transmission is unevenly distributed on the landscape, and risk levels are expected to be controlled by patterns of habitat use by infected and uninfected individuals as well as environmental properties that alter the length of time prions remain infectious and available for uptake. Despite evidence from controlled or laboratory studies identifying environmental properties likely to affect patterns of CWD prion locations on the landscape, it remains difficult to connect mechanisms to realized increased or decreased risk of disease transmission, and few studies have attempted to detect patterns of different CWD risk in different environments. Using data from GPS-collared mule deer in Wyoming that were CWD-tested annually, we constructed models predicting annual probability of disease transmission contingent on environmental properties extracted from GPS use points. We compared models that emphasized different pathways of disease transmission by including or excluding sets of covariates that described deer density, habitat selection, and covariates expected to affect prion persistence in the environment. Results indicated that key habitat characteristics often selected by mule deer, such as proximity to secondary roads, were also associated with higher risk of testing positive for CWD, which supports the hypothesis that disease risk was correlated to patterns of habitat use by deer. We also found increased risk associated with spatial properties that were not selected-for by deer, such as areas where topography collects moisture, suggesting that prion retention mechanisms also play a role in risk. Incorporating these spatially-varying risk factors into our understanding of CWD transmission and outbreak progression can support managers in designing data collection and disease management strategies.

Wyoming↗

USGS2025

Greater sage-grouse seasonal habitat associations: A review and considerations for interpretation and management applications

Habitat features needed by wildlife can change in composition throughout the year, particularly in temperate ecosystems, leading to distinct seasonal spatial-use patterns. Studies of species-habitat associations therefore often focus on understanding relationships within discrete seasonal periods with common goals of prediction (e.g., habitat mapping) and inference (e.g., interpreting model coefficients). Across the range of the greater sage-grouse ( Centrocercus urophasianus ) of western North America, the increasing use of high-frequency tracking devices has led to a surge in habitat association studies covering multiple temporal periods and spatial extents. We reviewed the literature for seasonal habitat association studies corresponding to the second and third orders of selection (Johnson 1980). Our objectives were to summarize the methodological approaches used to estimate habitat associations to aid understanding in cross-study comparisons and identify common habitat features reported as selected or avoided within different seasonal periods. We reviewed 71 second- and third-order studies published from 2007–2023 that evaluated covariates collected in a geographic information system (GIS) and modeled probability of selection or intensity of use. The most common study design evaluated a single level of selection (third-order) and was multi-scale (i.e., covariates were measured at varying spatial grains). The most common model approach estimated habitat associations using resource selection functions (RSFs) fit with logistic regression. Studies mostly focused on the breeding periods and winter, but all seasons throughout the annual cycle were covered. There was clear support for selection of sagebrush and avoidance of trees and rugged terrain across seasons, and strong selection of mesic conditions in summer. However, habitat associations for most covariates were mixed, with proportionally equivalent selection and avoidance reported, even within the same seasons. Different factors hampered cross-study comparisons, including variation in study design, but additional contributors likely included important context-dependent habitat associations, such as functional responses to changing habitat availability. We suggest collaborative studies leveraging multiple datasets can help improve seasonal habitat inference by removing the effects of variable study designs.

Journal of Wildlife Management↗

USGS2025

A compilation pipeline for wildlife tracking datasets collected from ground-based and satellite-based telemetry transmission devices

Wildlife conservation planning increasingly requires collaboration and integration of research from discrete studies spanning large geographic areas. Tracking datasets are essential for analyzing animal movements and species distributions in relation to environmental conditions and combining them can enable powerful analyses to further aid planning efforts. However, combining datasets necessitates addressing variation in study designs, tracking methodologies, location uncertainty, and data attributes. We outline a compilation pipeline to integrate ground-based and satellite-based telemetry tracking datasets, motivated from our work with greater sage-grouse ( Centrocercus urophasianus ), a highly imperiled species of western North America. Our objective was to create a database with a standardized set of attributes to facilitate filtering locations for spatial analyses. Our pipeline phases are: (1) dataset pre-processing, (2) formatting individual datasets to a common template, (3) dataset binding, (4) error checking, and (5) filtering. Our pipeline includes additional functionality to identify coordinates from recurrently visited locations (e.g., nest sites), which may be of special interest. The final compiled sage-grouse database included nearly 5 million locations collected from 53 datasets and over 19,000 birds tracked from 1980 to 2022, including over 11,000 nest locations. Our error checks flagged 3.9 % of locations as likely errors, predominantly collected from satellite-based telemetry transmissions. We demonstrate the ability of our pipeline to identify nest locations and flag erroneous locations by applying it to simulated tracking datasets. Overall, our workflow offers a transferable approach for researchers aiming to standardize wildlife telemetry datasets and conduct ecological analyses for both individual studies and large-scale collaborations.

California, Colorado, Idaho, Montana, Nevada, Nort↗

USGS2024

Imperiled Great Basin terminal lakes: Synthesizing ecological and hydrological science gaps and research needs for waterbird conservation

Terminal lakes are declining globally because of human water demands, drought, and climate change. Through literature synthesis and feedback from the resource and conservation community, we review the state of research for terminal lakes in the Great Basin of the United States, which support millions of waterbirds annually, to prioritize ecological and hydrologic information needs. From an ecological perspective, research priorities include measuring the underlying differences in waterbird resource selection and distribution, migratory connectivity, abiotic factors that interact with prey densities to affect prey availability, and waterbird fitness or demography. Integrated links between water availability, water quality, and food webs are lacking in the literature. Scarce water availability data hinder the current knowledge of water extraction and evapotranspiration rates. Research that can address these priorities would help advance our understanding of how the Great Basin terminal lakes function as an interrelated system and support conservation efforts to reverse the decline of these critical lakes.

California, Nevada, Oregon, Utah↗

USGS2024

Remote sensing for monitoring mine lands and recovery efforts

Under the Bipartisan Infrastructure Law Ecosystem Restoration Program, the U.S. Department of the Interior has invested in assessing and recovering degraded ecosystems to promote healthy human communities and wildlife habitats. One priority established by the program is the need to address degraded ecosystems associated with mine lands, including active, inactive, and abandoned mines. Mine lands occur in every State of the United States and present a range of environmental hazards and safety risks to human communities and wildlife habitats. However, limited information compiled across the United States exists on the whereabouts of mining activities and their potential environmental effects on landscapes. Remote sensing is the process of acquiring information about the landscape from ground platforms, aircraft, or satellites to assess surface characteristics such as topography, vegetation, and soil properties and can therefore provide important cost-effective methods for identifying mining sites and assessing their environmental effects. Based on a literature review of remote sensing applications that assessed land health conditions and monitoring of mine lands, this report highlights important approaches, capabilities, considerations, and case studies using a breadth of techniques. The report identifies considerations for setting appropriate vegetation recovery targets and demonstrates how remote sensing can inform the prioritization, recovery design, and long-term assessments of recovery to help support decision makers and land managers. Applications of remote sensing to mine recovery will be most effective when recovery targets are clearly defined and quantifiable from data collected before mining activity, per the Surface Mining Control and Reclamation Act of 1977 and similar laws. Additionally, the collected data would need to be accessible and maintained in databases for baseline references used to establish these recovery targets.

continental United States↗

USGS2022

Spatial scale selection for informing species conservation in a changing landscape

Identifying the relevant spatial scale at which species respond to features in a landscape (scale of effect) is a pressing research need as managers work to reduce biodiversity loss amid a variety of environmental challenges. Until recently, researchers often evaluated a subset of potential scales of effect inferred from previous studies in other locations, often based on different biological responses and environmental variables. These approaches, however, can create uncertainty as to whether relevant spatial scales were identified, and whether the effects of environmental variables at scale were accurately estimated. Identifying scales of effect is particularly relevant for the greater sage-grouse ( Centrocercus urophasianus ), a sagebrush-obligate species of conservation concern requiring large areas of intact sagebrush cover ( Artemisia spp.) for habitat. We demonstrate the application of a scale selection approach that jointly estimates the scale of effect and the effect of sagebrush cover on trends in population size using counts from 584 sage-grouse leks in southwestern Wyoming (2003–2019) and annual estimates of sagebrush cover from a remote sensing product. From this approach, we estimated a positive effect of mean sagebrush cover with a 95% probability that the scale of effect occurred within 5.02 km of leks. In an average year, we found that lower levels of sagebrush cover within these estimated scales could support increasing trends in sage-grouse population size when populations were small, but higher levels of sagebrush cover were needed to sustain growing populations when populations were larger. With standardized monitoring and annual estimates of vegetation from remote sensing, this scale selection approach can be applied to identify relevant scales for other populations, species, and biological responses such as demography and movement.

Wyoming↗