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Amy Kristine Wray

Publications and source records attributed to Amy Kristine Wray.

5 recordsLinked to original sources

Evaluating evidence of changing regional occupancy of four bat species in response to forest management practices

Coordinated, regional strategies to guide effective management and conservation of forests can be used to balance conservation with management for other objectives such as timber, scenic viewsheds, and fire. A key part of these regional strategies is incorporating knowledge of how management actions may affect certain species, especially those that are sensitive or are of concern. However, knowledge of how management actions may affect species is inferred from studies conducted across small areas where the species’ behavior and forest conditions are easily assessed. Here, we examine how occupancy of four bat species responds to forest management across the eastern United States at regional scales. We used range-wide capture and stationary acoustic surveys from the North American Bat Monitoring Program from 2010 to 2020 to estimate yearly summer occupancy for four bat species of conservation concern identified in the U.S. Department of Agriculture Forest Service (USFS) Southern and Eastern Regions Bat Conservation Strategy: little brown bat ( Myotis lucifugus ), northern long-eared bat ( Myotis septentrionalis ), Indiana bat ( Myotis sodalis ), and tricolored bat ( Perimyotis subflavus ), and assessed the degree to which occupancy of each species changed after different vegetation management actions were implemented on USFS lands. We identified 78 different management actions that were hypothesized to influence summer bat occupancy at two spatial scales (5-km and 10-km) across the eastern United States from the Forest Service Activity Tracking System and grouped these management actions into four vegetation management types: clear-cutting, fire, thinning, and ground vegetation management. To evaluate potential effects of these vegetation management types on bat occupancy, we created a yearly management metric representing the average number of years that had passed since any one of the included management actions in each management type had been implemented in each 5-km or 10-km grid cell, weighted by the proportion of the grid cell covered by the management treatment history. We chose these metrics to ask if more management or management done recently had a larger effect on bat occupancy than less management or management done long-ago. We then fit Bayesian hierarchical multi-scale occupancy models for each species to assess how occupancy changed in response to the amount and time since implementation of each vegetation management type. Using the estimated relationships between the yearly metrics of management and bat occupancy, we created predictions for how bat occupancy responded at 1- and 5- years after implementation. We found substantial differences in the response of the four species to the four vegetation management types. Ground vegetation management provided the greatest increase in expected occupancy at 1 year after implementation for little brown bat, long-eared bat, and tricolored bat, while fire provided the greatest increase in expected occupancy for Indiana bat. Thinning provided increases for all species at 1 year after implementation, but even greater increases at 5 years after implementation. Clear-cutting, on the other hand, tended to result in decreased occupancy at both 1- and 5-years after implementation for each species and had the greatest effect on tricolored bat at 1 year after implementation. Clear evidence for how management types like these may be affecting bat populations can be used at regional scales to help private and public forest managers achieve their strategic goals.

eastern United States↗

Multi-scale predictors of Northern Long-eared Bat (Myotis septentrionalis) occupancy in the United States

Historically, Myotis septentrionalis (Northern Long eared Bat) was among the most common forest-interior species in North America. Largely due to high mortality from white-nose syndrome, this species has experienced severe population declines across its range. To create an updated species distribution map representing summer occupancy probabilities from 2017 to 2022, we integrated stationary acoustic data with live-capture data from the database of the North American Bat Monitoring Program into a multi-scale, multi-method occupancy modeling framework. Our results provide data-driven predictions with quantified uncertainty for summer occupancy probabilities for Northern Long-eared Bats at 2 spatial scales across the range of the species, while also accounting for inherent observation biases (e.g., imperfect detection).

Journal of North American Bat Research↗

Predicting bat roosts in bridges using Bayesian Additive Regression Trees

Human-built structures can provide important habitat for wildlife, but predicting which structures are most likely to be used remains challenging. To evaluate the predictive capabilities of data-driven ensemble modeling approaches, we conducted surveys for bats and signs of bat use, such as urine and guano staining, at bridges across the southwestern United States. We developed a bat roost discovery tool using Bayesian Additive Regression Trees (BART) and evaluated the predictive ability of this model against other commonly used approaches. We found that the lack of nearby water resources was associated with a lower predicted probability of bat presence or signs of bat use at bridges. While the presence of nearby water resources was associated with higher average predicted probability of bat presence or signs of bat use, high uncertainty surrounding these estimates indicates that other factors also play a role in determining which bridge roosts bats are more likely to use. As such, our model could be particularly useful for predicting which bridges can be excluded from survey efforts due to low probability of bat presence or signs of bat use. We extrapolated our model to unsurveyed bridges across the study region and provide an interactive dashboard application interface for the exploration of these results. Overall, this study demonstrates the application of BART as a predictive tool for prioritizing future bridge surveys for bats roosting in transportation structures.

Arizona, California, Nevada, New Mexico, Texas↗

Understanding gaps in early detection of and rapid response to invasive species in the United States: A literature review and bibliometric analysis

While concepts regarding invasive species establishment patterns and eradication possibilities have long been a topic of invasion biology, the specific terminology referring to early detection of and rapid response to (EDRR) invasive species emerged in scientific literature during the early 2000s. Since then, the EDRR approach has expanded to include a suite of detection, planning, and management tools. By conducting a systematic literature review, we attempt to characterize the field of EDRR in the United States and its territories as reflected by publication records. Specifically, we assessed publication data such as the number of publications per year, the most common journals where papers were published, and the relationship between author’s keywords for studies focusing on aquatic and terrestrial habitats. For publications that used invasive species occurrence or abundance data (whether collected for the purposes of the respective publication or acquired from another data source), we manually vetted additional information such as focal taxa, data collection years and locations, sources of other data used, and whether data or code were deposited in open access formats. We also conducted network analyses for the author institutions that coauthored papers together most frequently and for the references most cited by EDRR publications. Overall, we found that silos existed in terms of which author institutions worked together, which existing literature was cited, and which topics were frequently explored. We also found evidence of substantial gaps in data access and use. For example, although a wide variety of data sources for invasive species occurrences are available, these sources were seldom cited by published literature, and newly collected data was not often deposited into invasive species databases or other open-source data repositories. Considering the continued advocation for a centralized national EDRR information system, our study suggests that facilitating access to data, decision support tools, and other informational resources represents a key opportunity for improving EDRR capabilities.

Ecological Informatics↗

America's most wanted fishes: Cataloging risk assessments to prioritize invasive species for management action

Hundreds of fish species enter the United States through human intervention (e.g., importation) and some of these fishes pose a substantial risk to the nation’s assets and ecosystems. Prevention, early detection, and rapid response (EDRR) are vital to stop species invasions, but time and resources to manage the large suite of fish species that enter the nation are limited. Evaluating the risk of a species’ invasion in a location is one way to prioritize among many species for management action. Species risk assessments are often associated with information systems or are published within grey literature or peer-reviewed journal articles. Improving access to available risk assessments could help in prioritizing management action for the most potentially invasive fish species. We aggregated fish species risk assessments, synthesizing the current knowledge on the risk of fish invasions in the United States. To accomplish this, we searched information systems and conducted a literature review. We then summarized risk assessment results along with the importation statuses of fish species and identified if imported, high-risk species are managed under federal or state policy. Within the scope of the conterminous U.S., we found 98 high-risk fish species. Eighteen of these species are imported to the country, but only three species have been recently prohibited from importation according to the Lacey Act. We observed similar patterns at the scales of the Great Lakes region and Florida. Collectively, our work provides a baseline estimate of the high-risk fish invaders that enter the U.S. through importation, underscoring species to consider for priority management action, as well as a benchmark of species that lack risk assessments. Insights from this work can be enriched when joined with other invasive species information, which could be accomplished through a national EDRR information system, an information sharing hub in development by the U.S. Geological Survey.

Management of Biological Invasions↗