Land Use and Land Cover Change in the Crown of the Continent Ecosystem, Montana, USA from 1992-2011
Bibliographic record
Abstract
In recent decades land use and land cover change (LULCC) has occurred throughout the Intermountain West. The Crown of the Continent Ecosystem (CCE) extends along the Rocky Mountains adjacent to the Canada-U.S. International border. In the U.S. portion of the CCE, located in northwestern Montana, development has increased since the 1990s, largely because of urban to rural migration. The CCE has become an amenity-based destination, which in turn is likely to threaten its terrestrial and aquatic ecological diversity (Quinn and Broberg 2007). Specifically, development pressures on private lands surrounding federally protected lands, are intensifying and thus threatening core habitat of native species and connectivity of forested areas. By characterizing the spatial and temporal patterns of LULCC, we can better understand landscape-scale changes influenced by human-environment interactions. Using National Land Cover Database (NLCD) products, I identified areas that have experienced land cover change for three time periods: 1992-2001, 2001-2006, and 2006-2011. Additionally, I used case studies to further investigate LULCC in the study area. The findings suggest that the highest rates of development in proximity to Glacier National Park were dependent on existing urban land cover, meaning existing roadway infrastructure and established urban areas saw the greatest urban development. Additionally, communities adjacent to Glacier National Park were hotspots for urban development. Based on the results, areas in proximity to federally protected lands are likely to experience continued urban intensification over the next few decades.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".