Bibliographic record
Abstract
In partnership with the Colorado Department of Transportation, the Federal Highway Administration, the Nature Conservancy, and Colorado State University, the Southern Rockies Ecosystem Project (SREP) launched Linking Colorado’s Landscapes in fall 2003. Linking Colorado’s Landscapes is a multifaceted collaboration to promote wildlife linkages in the context of long-range planning. Phase I consisted of a statewide analysis of wildlife linkages, the objective of which was to identify broad linkage zones that facilitate movement for Colorado’s diverse array of wildlife species and to prioritize amongst them. Building upon linkage assessment methodologies used elsewhere, we developed a science-based approach integrating local and regional expertise (via a series of workshops) and computer modeling. Recognizing that connectivity is a function of individual species’ perceptions of suitable habitat and barriers in the landscape, a focal species approach was employed as the basis for linkage identification in both the workshops and the modeling. By integrating both qualitative and quantitative processes, we were able to produce a comprehensive biological assessment of the most critical wildlife linkages in the state. In total, 176 linkages were identified via expert workshops, with additional linkages modeled for Canada lynx, gray wolf, and pronghorn. In prioritizing linkages for further analysis in Phase II, we also considered: the presence of local partners; stretches of roadway with frequent animal-vehicle collisions; planned transportation projects projected by CDOT through 2030; and the distribution of linkages across the state and their complementary contributions to landscape connectivity. Twenty-three linkages were selected and were grouped into 12 high-priority linkage complexes based on similarities in species usage patterns and geography. Phase II of Linking Colorado’s Landscapes provides an in-depth assessment of each high-priority linkage. Based on this compilation of site-specific information, we will next provide recommendations for possible crossing structures, management alternatives, and other measures to improve permeability in these linkage areas. Phase II analyses include: an assessment of additional species that utilize the linkage; identification of specific crossings; an assessment of land ownership and management within the linkage; and an evaluation of existing natural or man-made features that facilitate or impair movement. The resulting linkage assessment packages and recommendations will be distributed in spring 2006 and will serve as a guide for the Colorado Department of Transportation (CDOT) and other local and regional transportation planners, community leaders, and conservationists working to develop more wildlifefriendly landscapes and transportation networks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.024 |
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; both teacher heads agree on what is shown here.
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".