Will the introduced mussel Mytilus galloprovincialis outcompete the native mussel M. trossulus in Puget Sound? A study of relative survival and growth rates among different habitats
Bibliographic record
Abstract
The Mediterranean mussel (Mytilus galloprovincialis = Mg) has become established throughout Puget Sound and the effects of this species introduction on the native mussel M. trossulus (Mt) are unknown. Mg and hybrids between Mg and Mt (Mgt) are abundant on floating docks and large Mg and Mgt mussels also occur at low frequencies in the intertidal zone and in areas of low salinity. A variety of factors (e.g., growth/survival rates, predation, larval recruitment) may be causing these observed distribution patterns. In this study we performed three field experiments to examine the relative survival and growth rates of Mg and Mt: 1) at different tide heights on pilings vs subtidal locations on docks, 2) when grown in single-species groups and mixed-species groups, and 3) at locations with different salinities. Individuals of Mg had higher survival and growth than Mt in all areas except the high intertidal. Each species had similar growth rates when grown in single and mixed-species groups. Mg had higher survival and growth rates than Mt under both high and low salinity. These results indicate that the introduced Mg has superior growth and survival to the native Mt, and Mg has the potential to outcompete Mt under certain environmental conditions.
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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".