Effects of Landform and Other Environmental Variables on Forest Site Quality in the Appalachian Mountains
Bibliographic record
Abstract
Subregions are ecosystems of mesoscale size occurring between macroscale ecoregions of national extent and landscape units of subregional area within the U.S. Forest Service hierarchical classification framework of ecological units. The objective of this multi-disciplinary project was to develop a consistent national map of subregions from regional map products that had been developed independently by regional teams working with academic and conservation groups knowledgeable of ecosystems at local and state scales. Regional maps were joined and ecosystems were reviewed for consistency by a small national team consisting of representatives from each regional group. The national map received additional independent review for revision and refinement of ecosystems. The rationale and methodology for delineation of ecosystems shown on the map 'Ecological Subregions: Sections and Subsections of the Conterminous United States' is described in this report. Components of climate, geology, landform, soils and vegetation were integrated to form 190 sections and 1,234 subsection map units. This map represents the first approximation of ecological units at the subregions scale in the western U.S. and is a refinement of a 1995 map of Eastern subregions. Following its publication in 2007, the subregions map provides a basis for ecological mapping on Forest Service lands at the next lower finer scale: landtype associations. Case studies demonstrate use of the subregion map for ecosystem analysis in the Great Lakes Area and Appalachian Mountains in the southern United States. The 2007 map of subregions, supporting documents on methodology and databases of selected environmental data are available on CD. *Note: This abstract supplements and updates a preliminary report on the same topic that was presented, but not published, at the 2007 NAFEW, in Vancouver.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".