Hybridization between the Rare Gray-headed Chickadee and the Abundant Boreal Chickadee in the Midst of Shifting Climate
Bibliographic record
Abstract
As species respond to changing climate, distributions and abundances may shift and alter species interactions. Hybridization, a relatively widespread phenomenon becoming more common with climate change, can have beneficial and detrimental effects on population growth rates and genetic integrity. Beneficial effects due to the introduction of advantageous alleles and increased genetic diversity may result from hybridization. Species may also accrue fitness costs associated with changing climates if mismatches occur between environmental variables and phenotypes. The gray-headed chickadee, Poecile cinctus lathami, is an extremely rare songbird that has experienced marked declines in recent decades within its restricted distribution in Alaska and northwestern Canada. The widespread boreal chickadee, Poecile hudsonicus, has conversely become more locally abundant. I investigated two hypotheses of mechanisms – hybridization and environmental change – that may have contributed to the apparent rapid decline of the gray-headed chickadee and influx of boreal chickadee using mitochondrial and reduced representation nuclear DNA sequence data. I analyze historical specimens of both species and contemporary boreal chickadees to investigate the occurrence of hybridization and trends of abundance and interspecific gene flow. Additionally, I test for genotype-environment associations using historical, present, and future climate data sets to explore the trajectory of boreal chickadee adaptation to their local environment. I detect evidence of hybrids backcrossing to boreal chickadee populations prior to recent declines, and signatures of later-generation hybrids among both historical and contemporary boreal chickadees. I find that boreal chickadee genetic isolation-by-environment exceeds isolation-by-distance. Further, I identify temperature and precipitation bioclimatic variables which have strong associations with allelic composition and predict areas with the highest risk of environmental-genetic mismatch due to climate change. This study identifies hybridization as playing a role in gray-headed chickadee declines despite the inability to sample any individuals today and provides evidence that environment-genetic mismatches may occur for boreal chickadees as a result of climate change across areas of sympatry and allopatry. Advisor: Sarah A. Sonsthagen
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 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 | 0.001 | 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 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".