Hydrodynamic habitat influences suspension feeding by unionid mussels in freshwater ecosystems
Bibliographic record
Abstract
Summary Benthic suspension feeders play significant roles in aquatic ecosystems, but the influences of abiotic, especially hydrodynamic, factors on many of their activities remain largely unknown. This is especially true for freshwater unionid mussels, which are important inhabitants of rivers and lakes, often forming multispecies assemblages in the former. Our goal is to determine whether and how seston flux affects the suspension feeding of freshwater unionid mussels from different hydrodynamic habitats (i.e. lentic and lotic). Fluorometric measurements of algal depletion in a recirculating flow chamber were used to determine the clearance rate ( CR ) of four freshwater mussel species: E lliptio complanata , E lliptio dilatata , F usconaia flava and S trophitus undulatus . Clearance rate varied with algal flux ( J = UC , where U is velocity and C is algal concentration) for all species examined, resulting in a 41‐fold increase in CR for some species , compared with no‐flux controls. Importantly, the results from the no‐flux controls were consistent with published CR values obtained under static conditions. E lliptio dilatata from the fastest flowing lotic system (Grand River, Ontario) cleared up to four times more algae than any other species, including its conspecifics from a slower flowing river (Ausable River, Ontario) and the species from the lentic habitat ( E . complanata; Lake Opeongo, Ontario). Differences in CR s were also found among E . dilatata, F . flava and S . undulatus from the same lotic habitat at the highest algal flux examined, indicating that species may specialise to different hydrodynamic conditions. The impact of suspension feeding by unionid mussels has probably been underestimated, especially under lotic conditions with high seston flux. Mussels may have ecotypic responses to their hydrodynamic habitats, which affect their CR . Moreover, specialisation within a single habitat type is indicative of resource partitioning that could reduce competition in multispecies assemblages.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".