Habitat mapping for bird conservation in North America
Bibliographic record
Abstract
In view of the continuing appropriation and conversion of natural land areas in North America for human uses, there is growing concern about the impacts of changing land use on terrestrial bird species. In order to promote conservation of critical remaining habitats for birds, Partners in Flight (PIF) initiated a project in 1997 in which bird conservation plans were prepared by members in each of 60 ecologically defined physiographical areas throughout the United States. Accurate, nationwide information on the location and extent of vegetative cover types, as well as lands under state and federal management, are critically important elements in the creation of effective bird conservation plans. The National Fish and Wildlife Foundation (NFWF) awarded a challenge grant to The Nature Conservancy's (TNC) Wings of the Americas Program to assist Partners in Flight in acquiring land cover data to serve as the foundation of the planning effort. Canon U.S.A., Inc. and the American Bird Conservancy also contributed support toward this goal. The Center for Advanced Spatial Technology at the University of Arkansas was contracted to produce the needed land cover maps and associated tabular products. Digital land cover databases created by the U.S. Forest Service, the U.S. Geological Survey, the Canada Centre for Remote Sensing, the University of California-Santa Barbara Department of Geography, and the U.S. Department of Transportation, Bureau of Transportation Statistics were used in this project. The final spatial products were produced during 1998–1999 and are described in this paper. This effort represents the first nationwide habitat mapping project in the United States aimed at supporting and enhancing conservation of terrestrial bird species.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".