Projecting a spatial shift of Ontario's sugar maple habitat in response to climate change: A GIS approach
Bibliographic record
Abstract
Canada is the world's largest producer of maple syrup. Syrup production depends on weather and climatic conditions of the sugarbush. However, forest ecosystems are highly sensitive to climate change. The effect of rapidly changing precipitation and temperature patterns on tree species is of concern as these long‐lived organisms cannot quickly adapt to the new environmental conditions in which they find themselves. As temperatures increase it is expected that there will be a change in species' ranges poleward. This study uses Multi‐Criteria Decision Making (MCDM) and Geographic Information System (GIS) weighted sum analysis to project near future (2050) and distant future (2100) suitability maps of sugar maple (Acer saccharum) habitat in Ontario associated with three different Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) scenarios. Our maps project an overall decrease in the amount of suitable habitat within the current sugar maple range under the scenarios modelled, which intensifies in the later time period. Furthermore there is a projected shift in central and southern Ontario from a region dominated by suitable habitat to one dominated by unsuitable habitat.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".