The growth of juvenile native mussels (<i>Elliptio complanata</i>) in lakes varies with sediment characteristics and site exposure
Bibliographic record
Abstract
Abstract Unionid mussels are among the largest and longest‐lived freshwater invertebrates and can play an important role in these ecosystems. They are also one of the most endangered groups of organisms. The juvenile stage is a particularly vulnerable part of mussel life history and is one of the most poorly known. I compared the growth of young Elliptio complanata at 17 nearshore sites, in shallow (polymictic) and stratified lake basins, along gradients of sediment characteristics and site exposure (effective fetch). At each site, the growth of six to 14 small (20–68 mm) mussels collected on the sediment surface was measured, using internal growth lines. The growth of very young endobenthic mussels (22–40 mm) was also measured on four to six mussels at each of two sites. Juveniles spend several years in the sediments, and I found that during this period growth is not constant but declines rapidly with age. Shifts in δ15N signatures suggest that juveniles change their habitat use towards a more planktonic baseline around the time of maturation, when they reach a length of 30–50 mm. Identical δ13C signatures in juveniles and adults suggest that both rely on food of planktonic origin, whether deposited or suspended. The growth of juvenile mussels varies in a complex but predictable manner with sediment characteristics and wind‐driven physical forces. Growth was highest in fine sediments with low organic content, in highly organic but coarse sediments, and in protected nearshore areas with low effective fetch. Interestingly, I also found high growth rates at exposed nearshore areas with fine sediments, suggesting that areas where bottom topography creates a refuge from currents and waves may provide particularly good conditions for the early growth of juvenile mussels. Some parts of the shoreline may be more important than others for native mussel populations, and if we can identify those, they may warrant additional protection.
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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 | 0.000 | 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".