Integrative assessment of intraspecific diversification in Loggerhead Shrike (<i>Lanius ludovicianus</i>) provides insight on the geographic pattern of phenotypic divergence and process of speciation
Bibliographic record
Abstract
Integrated studies of the geographical, ecological, and historical factors that shape intraspecific phenotypic and genetic variation can help us to decipher the processes leading to geographic patterns of population divergence and speciation. We quantify and compare morphological and genetic variation in the Loggerhead Shrike (Lanius ludovicianus Linnaeus, 1766), a broadly distributed passerine in North America with both migratory and non-migratory populations that occupy a diversity of habitats and topographies. The geographic distributions and patterns of differentiation among subspecies suggest that migration has strongly impacted population divergence, including the habit of migrating itself, but also dispersal. Patterns of mitochondrial and nuclear genetic differentiation can be attributed to female-biased dispersal and to increased dispersal rates and distances in migratory populations. Weak phenotypic differentiation among migratory versus migratory and non-migratory populations suggest that migration may more strongly affect morphology than adaptation to local habitats. Our results generally support previous subspecific designations with two notable exceptions. We found little genetic differentiation between two subspecies (Lanius ludovicianus gambeli Ridgway, 1887 and Lanius ludovicianus mexicanus C.L. Brehm, 1854), but identify a new, distinct subspecies, which we refer to as Lanius ludovicianus centralis ssp. nov.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".