Impacts of climate change on diversity in forested ecosystems: Some examples
Bibliographic record
Abstract
Ecological diversity (the product of ecosystem, species, and genetic diversity) will change significantly in the 21st Century in response to the combined influence of climate, human activities, the movement of indigenous and non-indigenous species, and natural disturbances like fire (also modified by climate). Many species will acclimate (phenotypic variation) and/or adapt (genotypic variation) to changing conditions. Many will not. Species with a high rate of reproduction that are able to move long distances, rapidly colonize new habitats, tolerate humans, and survive within a broad range of biophysical conditions will be most successful in finding new niches. Large changes in ecosystem composition, structure, and function are expected to occur at northern latitudes and higher altitudes. In some areas novel ecosystems likely will replace existing subalpine, alpine, boreal forest, and tundra ecosystems. Key words: climate change, ecodiversity, forest, ecosystem diversity, species diversity, genetic diversity
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".