The impact of geography and climate on the population structure and local adaptation in a wild bee
Bibliographic record
Abstract
Abstract Deciphering processes that contribute to genetic differentiation and divergent selection of natural populations is useful for evaluating the adaptive potential and resilience of organisms faced with various anthropogenic stressors. Insect pollinator species, including wild bees, provide critical ecosystem services but are highly susceptible to biodiversity declines. Here, we use population genomics to infer the genetic structure and test for evidence of local adaptation in an economically important native pollinator, the small carpenter bee ( Ceratina calcarata ) . Using genome‐wide SNP data ( n = 8302), collected from specimens across the species' entire distribution, we evaluated population differentiation and genetic diversity and identified putative signatures of selection in the context of geographic and environmental variation. Results of the analyses of principal component and Bayesian clustering were concordant with the presence of two to three genetic clusters, associated with landscape features and inferred phylogeography of the species. All populations examined in our study demonstrated a heterozygote deficit, along with significant levels of inbreeding. We identified 250 robust outlier SNPs, corresponding to 85 annotated genes with known functional relevance to thermoregulation, photoperiod, and responses to various abiotic and biotic stressors. Taken together, these data provide evidence for local adaptation in a wild bee and highlight genetic responses of native pollinators to landscape and climate features.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".