Climate change effects on native fauna of northeastern forestsThis article is one of a selection of papers from NE Forests 2100: A Synthesis of Climate Change Impacts on Forests of the Northeastern US and Eastern Canada.
Bibliographic record
Abstract
We review the observed and potential effects of climate change on native fauna of forests in northeastern North America by focusing on mammals, birds, amphibians, and insects. Our assessment is placed in the context of recent regional-scale climate projections. Climate change, particularly in recent decades, has affected the distribution and abundance of numerous wildlife species. Warming temperatures, alterations to precipitation regimes, seasonality, and climatic extremes are projected to affect species directly or indirectly in each of the focal taxa. Greatest climate change will occur during winter, and the survival of winter-active species as well as the survival, distribution, and abundance of hibernating mammals, amphibians, resident birds, and diapausing insects may be altered. Even under low emissions scenarios, effects on native fauna may be profound, affecting iconic species, endangered species, and species that provide economically valuable services, such as pollination and regulation of insect populations. However, much research that is essential to assessing the effects of climate change on the native fauna of northeastern forests remains to be done. Research that reveals causal mechanisms and relates these findings to population and community level processes will be most valuable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".