Reduced habitat suitability and landscape connectivity in a songbird migratory divide
Bibliographic record
Abstract
Abstract Aim Seasonal migration is a common phenomenon in animals and connects geographically distant ecosystems. Considerable variation has been documented in this behaviour and migratory divides (contact zones between populations that use different routes to navigate around ecological barriers) are an example of this. Migratory divides could have important implications for ecological speciation as hybrids in divides take intermediate routes and it has been predicted that these routes will be ecologically inferior as they bring hybrids over barriers that parental forms avoid. We provide the first test of this prediction here using a well‐characterized divide between coastal and inland subspecies of Swainson’s thrushes. Location North, Central and South America. Time period 2006–2013. Major taxa studied Birds. Methods We used ecological niche models and analyses of landscape connectivity to predict suitable habitat for coastal and inland thrushes on migration and identify optimal migratory routes. We compared estimates of habitat suitability and landscape connectivity along the actual migratory routes of birds tracked with light‐level geolocators. Results Consistent with predictions for migratory divides, niche models estimated lower habitat suitability in the intermediate range between the migratory ranges of parental forms. Furthermore, our models of landscape connectivity predicted optimal routes that circumvent this intermediate area. Birds taking intermediate routes used stopover sites of lower predicted habitat suitability than birds migrating on either side of the divide and overlapped less with optimal paths. Main conclusions Our results support the prediction that intermediate routes of hybrids in migratory divides are ecologically inferior to those of parental forms. This finding suggests ecological differences are helping to maintain divides and could have broad implications, with divides shaping the distribution and maintenance of species boundaries globally and across many taxonomic groups.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".