Naturally low seston concentration and the net energy balance of the greenshell mussel ( <i>Perna canaliculus</i> ) at Island Bay, Cook Strait, New Zealand
Bibliographic record
Abstract
Abstract This paper describes an investigation of the physiological energetics of the New Zealand greenshell mussel, Perna canaliculus (Gmelin, 1791), which is aimed at determining if mussels are absent from many shores of Cook Strait as a consequence of a negative energy balance resulting from ambient low seston quantity and quality. Seston characteristics and mussel physiological functions were measured under ambient summer conditions at Island Bay, a site in Cook Strait. Estimates of total particulate matter (TPM in mg litre −1 ), particulate organic matter (POM in mg litre −1 ), and particulate organic carbon (POC in |ig litre −1 ) were low but of a similar magnitude to values reported for many comparable temperate regions. However, seston % organic matter (% OM) values were consistently low (<25%) and resulted in negative net absorption efficiency (AE) values and concomitant negative scope for growth (SFG = net energy balance) values. We suggest that the ongoing costs of energy loss associated with extra‐and intracellular digestion (termed metabolic faecal loss) are greater than the energy derived from seston of such low organic matter. Our data indicate that ambient levels of seston % OM of ≤25% are insufficient to promote a positive net energy balance in P. canaliculus , and as such probably play a major role in explaining the almost complete absence of mussels from many Cook Strait shores.
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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 | 0.001 | 0.001 |
| 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".