Potential impacts of climate change on neotropical migrants: management implications
Bibliographic record
Abstract
The world is warming. Over the last 100 years, the global average temperature has increased by approximately 0.7°C. The United Nations Intergovernmental Panel on Climate Change projects a further increase in global mean temperatures of between 1.4° - 5.8° C by the year 2100. How will climate change affect Neotropical migrants? Models of changes in the breeding distributions of North American birds predict that most species will undergo some shift in their ranges. In parts of northern Minnesota and southern Ontario, this could lead to an avifauna with as many as 16 fewer species of wood warblers than currently occur. Unless all components of the ecosystem change at the same rate, an unlikely prospect, this potential disruption of the ecosystem could lead to major impacts on forest health. Data show that many changes have already occurred with earlier arrival dates, breeding dates and changes in distributions. This includes preliminary results showing the average latitude of occurrence of some species of North American birds has shifted northward by almost 100 km in the last 20 years, and many species in Michigan arriving in the spring an average of 21 days earlier now than 30 years ago. Climate change will add more pressure to bird populations and greater challenges to conservation planners and land managers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".