Wildlife Crossings in North America: The State of the Science and Practice
Bibliographic record
Abstract
In this paper we present results from a telephone survey as part of a National Cooperative Highway Research Program (NCHRP) project, Evaluation of the Use and Effectiveness of Wildlife Crossings (NCHRP 25-27). Specifically, we present a summary of North American efforts to mitigate road effects for wildlife. We stress the need to provide multiple wildlife passages along transportation corridors to begin to accommodate the movement of the full complement of species in an area. We surveyed over 250 transportation professionals in the United States and Canada by telephone to learn more about efforts to make roads more permeable for wildlife. We asked questions about both the practice and science associated with road ecology. Participants employed by agencies, private organizations, and academic institutions answered questions concerning wildlife crossings, planning for wildlife and ecosystems, animal-vehicle collision information, and past, current, and future research activities related to roads and wildlife. As of September 2005, we found that there were at least 460 terrestrial and 300 aquatic crossings in North America. Trends in practice over time since wildlife passages began to be installed in the 1970s appear to show an increased number of target species in mitigation projects, increased numbers of endangered species used as target species for mitigation, increasing involvement of municipal and state agencies, an increase in the number of passages and accompanying structures constructed, and a continent-wide trend of neglect of maintenance of these passages. The trends in the science revealed a tendency for a broadening of the scope of research in terms of the number of species considered, an increase in the length of time monitoring projects were conducted, and an increase in the number of participants in scientific monitoring of mitigation projects and in general road ecology research. There are several projects in North America where multiple crossings have been or will be installed to accommodate a large suite of species and their movement needs. These include Albertaâs Trans Canada Highway mitigation efforts, Montanaâs U.S. Highway 93 mitigation projects, Arizonaâs projects along U.S. 93 and on State Route 260, Floridaâs I-75 Alligator Alley project, and Vermontâs future Route 78 and US 7-SR 9 projects. These projects may be models for how road construction activities can increase the permeability of the roaded landscape. We also present recommendations to assist in the research, design, placement, monitoring, and maintenance of crossings. We summarize the state of the practice and science of road ecology with respect to wildlife with suggestions to increase permeability of transportation corridors, and to increase communication and cooperation among those who would be involved in the mitigation of roads and other travel corridors
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.008 |
| 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".