Outbreeding depression from physiological refugia limits adaptation of a native gastropod to an invasive predator
Bibliographic record
Abstract
Biological invasions have caused the loss of freshwater biodiversity worldwide. The interplay between adaptive responses and demographic characteristics is expected to be important for the resilience of populations to biological invasions, but the interaction between these factors is poorly understood. The native freshwater gastropod Amnicola limosa is distributed along spatial variation in impact from an invasive molluscivorous fish (Neogobius melanostomus), as well as calcium concentrations, limiting the distribution of this invader (refuges). We investigated the potential for genetic adaptation of A. limosa to the invasive predator and the low calcium habitats. We conducted pooled whole-genome sequencing of twelve gastropod populations from the Upper St. Lawrence River, complemented with a laboratory reciprocal transplant of wild F0 A. limosa to measure survival and fecundity in treatments of water calcium concentration (low/high) and round goby cue (present/absent). We quantified gene flow between the habitat types to test how population structure might interact with adaptation. We found that low calcium, uninvaded habitats could act as refugia for the gastropods from the invasive fish and provide migrants to declining invaded gastropod populations through strong gene flow (i.e., demographic rescue), which also maintained genetic diversity (i.e., genetic rescue). However, we also detected signatures of divergent selection between habitat types and evidence of low fitness of individuals from refuge populations in both habitat types. This suggests that migrants from refuges could introduce maladapted alleles to recipient populations in high calcium, invaded habitats, thereby reducing fitness via outbreeding depression and producing conflict between demographic, genetic, and evolutionary rescue.
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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 | 0.000 | 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) | 0.001 | 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".