Climatic, topographic, and anthropogenic factors determine connectivity between current and future climate analogs in North America
Bibliographic record
Abstract
As climatic conditions shift in coming decades, persistence of many populations will depend on their ability to colonize habitat newly suitable for their climatic requirements. Opportunities for such range shifts may be limited unless areas that facilitate dispersal under climate change are identified and protected from land uses that impede movement. While many climate adaptation strategies focus on identifying refugia, this study is the first to characterize areas which merit protection for their role in promoting climate connectivity at a continental extent. We identified climate connectivity areas across North America by delineating paths between current climate types and their future analogs that avoided nonanalogous climates, and used centrality metrics to rank the contribution of each location to facilitating dispersal across the landscape. The distribution of connectivity areas was influenced by climatic and topographic factors at multiple spatial scales. Results were robust to uncertainty in the magnitude of future climate change arising from differing emissions scenarios and general circulation models, but sensitive to analysis extent and assumptions concerning dispersal behavior and maximum dispersal distance. Paths were funneled along north-south trending passes and valley systems and away from areas of novel and disappearing climates. Climate connectivity areas, where many potential dispersal paths overlapped, were distinct from refugia and thus poorly captured by many existing conservation strategies. Existing protected areas with high connectivity values were found in southern Mexico, the southwestern US, and western and arctic Canada and Alaska. Ecoregions within the Isthmus of Tehuantepec, Great Plains, eastern temperate forests, high Arctic, and western Canadian Cordillera hold important climate connectivity areas which merit increased conservation focus due to anthropogenic pressures or current low levels of protection. Our coarse-filter climate-type-based results complement and contextualize species-specific analyses and add a missing dimension to climate adaptation planning by identifying landscape features which promote connectivity among refugia.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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 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".