Invasive mussels modify the cycling, storage and distribution of nutrients and carbon in a large lake
Bibliographic record
Abstract
Summary This study examined the effect of invasive dreissenid mussels on nutrient and carbon dynamics in a large lake (Lake Simcoe, Ontario). We measured rates of nutrient (phosphorus and nitrogen) and carbon excretion and biodeposition by zebra and quagga mussels and the P, N and C content of their soft tissues and shells at different depths throughout the open‐water season. Measurements were combined with detailed information about dreissenid biomass and lakewide distribution to examine the impacts of dreissenids on whole‐lake dynamics of P, N and C. Mussel tissue P, N and C content and rates of excretion and biodepositon varied among species, seasons and depths, apparently driven by metabolic and stoichiometric factors. Dreissenid mussels excreted, deposited and stored large quantities of P, N and C when compared to lake standing stocks and loadings, and represent an important driver of nutrient cycling in the lake. Living and discarded mussel shell material is shown to represent a potentially important, and hitherto largely overlooked, long‐term sink for P, N and C. The concentration of dreissenid biomass in the well‐mixed and illuminated littoral portion of L. Simcoe results in redirection of nutrients and carbon from offshore areas to the nearshore zone of the lake. Changes in nutrient and carbon distribution and cycling patterns caused by dreissenid establishment in L. Simcoe and other ecosystems can have implications for the distribution of primary and secondary production and should be considered in the context of water quality and nutrient input management.
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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".