Optimizing sea urchin gonad enhancement and gastrointestinal parameters with newly formulated feeds at different temperatures with green (Strongylocentrotus droebachiensis) and red (Mesocentrotus franciscanus) sea urchins in British Columbia, Canada
Bibliographic record
Abstract
Sea urchins are an ecologically important species that can drastically alter marine communities due to their consumption and destruction of macroalgal beds (e.g. kelp forests). These beds form highly productive ecosystems that provide shelter and nursery habitat for many benthic and pelagic species. When their populations explode, due to a lack of predators and/or various environmental conditions, sea urchins can overgraze and decimate macroalgal beds. This creates areas called sea urchin barrens, which is a problem seen around the world. Sea urchin aquaculture is a method to remove these over-populated sea urchins from the environment, feed them either a prepared or macroalgal diet for approximately 12-weeks to produce a marketable roe product in a process termed roe or gonad enhancement. Two feeding trials were conducted on two species of sea urchins that are native to the waters off Vancouver Island, British Columbia, Canada: the green (Strongylocentrotus droebachiensis) and red (Mesocentrotus franciscanus) sea urchin. There were nine treatments per feeding trial, where three diets (two prepared diets; V10.1.9 and V10.1.10, and one natural bull kelp (Nereocystis luetkeana) diet and three different temperatures (8, 12, and 16oC; which are temperatures commonly found in the waters around Vancouver Island) were examined to assess the feasibility of a sea urchin gonad enhancement operation with these species and diets. \nOverall, green sea urchins fed V10.1.9 at 8 and 12°C produced the highest gonad yields (mean ± SE: 29.4 ± 1.1% and 29.4 ± 1.5%, respectively) while V10.1.9 at 12°C also had the highest gonad yield increase per week (mean ± SE: 2.2 ± 0.2%) and the lowest FCR-G (mean ± SE: 1.0E-2 ± 9.0E-4 feed g gonad increase g-1). Green sea urchins fed V10.1.10 at 12°C, however, produced the most preferred gonad taste, gonad yields still above market minimum (mean ± SE: 25.6 ± 1.5%), and the third lowest FCR (mean ± SE: 1.5E-2 ± 1.9E-3 feed g gonad increase g-1), while urchins fed V10.1.10 at 16°C had the best colour (mean degree of colour difference ± SE: 6.0 ± 0.9). Therefore, it can be suggested that optimal conditions moving forward for green sea urchins would be feeding V10.1.10 at 12°C. For red sea urchins, those fed V10.1.10 produced the highest gonad yields at 12°C (mean ± SE: 12.7 ± 1.5%) and the best colour at 16°C (mean degree of colour difference ± SE: 30.3 ± 3.1), while red sea urchins fed V10.1.9 at 16°C produced the second highest gonad yields (mean ± SE: 11.0 ± 0.4%), the lowest FCR-G (1.9E-3 ± 2.8E-4 feed g gonad increase g-1), the most preferred gonad taste, and a low degree of colour difference (mean ± SE: 32.3 ± 2.1). Therefore, it can be suggested that optimal conditions moving forward for red sea urchins would be feeding V10.1.9 at 16°C.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".