Projections of suitable habitat under climate change scenarios: Implications for trans‐boundary assisted colonization
Bibliographic record
Abstract
PREMISE OF THE STUDY: Climate change may threaten endemic species with extinction, particularly relicts of the Arcto-Tertiary Forest, by elimination of their contemporary habitat. Projections of future habitat are necessary to plan for conservation of these species. METHODS: We used spline climatic models and modified Random Forests statistical procedures to predict suitable habitats for Brewer spruce (Picea breweriana), which is endemic to the Klamath Region of California and Oregon. We used three general circulation models and two sets of carbon emission scenarios (optimistic and pessimistic) for future climates. KEY RESULTS: Our procedures predicted present occurrence of Brewer spruce perfectly. For the decades 2030, 2060, and 2090, its projected range within the Klamath Region progressively declined, to the point of disappearance in the decade 2090. The climate niche was projected to move north to British Columbia, the Yukon Territory, and southeastern Alaska. CONCLUSION: The results emphasize the necessity of assisted colonization and trans-boundary movement to prevent extinction of Brewer spruce. The projections provide a framework for formulating conservation plans, but planners must also consider regulations regarding international plant transfers.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".