Research Provides Answers to Mitigate Impacts of Energy Development to Wildlife
Bibliographic record
Abstract
Energy development and other anthropogenic disturbances have resulted in lost, degraded, and fragmented wildlife habitats in many portions of the western United States and Canada. These compromised habitats have in turn led to declines in some wildlife populations. Furthermore, conservation of wildlife populations in the West is very challenging given that populations of many species migrate across large landscapes to access seasonal resources. Research that seeks to identify the direct and indirect impacts of energy development to wildlife habitats and populations plays a critical role in identifying potential steps to mitigate these impacts. The purpose of my presentation is to showcase findings from studies that have yielded information that can be used to make energy development more harmonious with wildlife populations. The case studies I will present include examples from elk (Cervus elaphus), greater sage-grouse (Centrocercus urophasianus), and other focal taxa that inhabit the western North American landscape. Findings from research that can be applied to form beneficial mitigation steps are particularly important given the rapid pace of energy development across the West and the need to provide industry and natural resource managers with useful information to restore the quality and effectiveness of wildlife habitats in disturbed systems. Jeffrey L. Beck, Rangeland Wildlife Habitat Restoration Ecologist, Department of Ecosystem Science and Management, University of Wyoming, Dept. 3354, 1000 E. University Ave, Laramie, WY, 82071, jlbeck@ uwyo.edu Jeffrey L. Beck is an assistant professor of wildlife habitat restoration ecology in the Department of Ecosystem Science and Management at the University of Wyoming. His research interests focus on restoring the quality and effectiveness of wildlife habitats in disturbed systems, particularly sagebrush habitats. The research questions that Dr. Beck’s lab addresses are guided by ecological concepts that are used as a framework to evaluate conservation questions. Two general areas of emphasis that Dr. Beck’s lab is pursuing include: (1) evaluating the direct and indirect impacts of anthropogenic disturbance on vertebrates (greater sage-grouse and ungulates as model taxa), and (2) assessing the efficacy of mitigation techniques and conservation practices intended to enhance habitat conditions or mitigate effects of anthropogenic development in sagebrush habitats. Dr. Beck and his students seek to understand responses of habitat restoration efforts across a range of spatial and temporal scales to better inform conservation practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".