Validation of the water content of the digestive gland as an indicator of nutritional condition in the American lobster<i>Homarus americanus</i>(H. Milne Edwards, 1837) (Decapoda: Nephropidae)
Bibliographic record
Abstract
Abstract Simple nutritional condition indicators are needed to provide information on the influence of ecosystem changes on the populations of the American lobster Homarus americanus (H. Milne Edwards, 1837) on various timescales. This study validates the use of the water content (% wet mass) of the digestive gland as an indicator of nutritional condition in the lobster (carapace length 65–127 mm) by assessing its capacity to estimate digestive-gland lipid reserves under variable environmental and physiological conditions. The validation was completed using samples from wild lobsters dissected shortly after being captured during different seasons and in various locations in the St. Lawrence Estuary and Gulf of St. Lawrence (GSL), and data from an environmentally realistic laboratory study on post-ovigerous females from the southern and the northern GSL sampled at different stages of their molt cycle. In both wild and experimental lobsters, water content was the best predictor of lipid reserves compared to other condition indicators (i.e., condition factor, various digestive-gland indices, and hemolymph Brix index). A strong linear relationship was found between lipid and water contents. Lipid content and interrelated molting status were identified as two important factors leading to the variations in water-fat regression equations among groups of wild or experimental lobsters. As lipid content could vary spatiotemporally in unexpected ways in a changing environment, it is recommended to use a sampling event-specific regression line to estimate digestive-gland lipid content from measured water content in field monitoring programs. Combining water content with molt status indicators such as Brix index is recommended to support interpretation of the observed variations in condition.
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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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".