Growth rate, prey preference, and feeding rate of Evasterias troschelii
Bibliographic record
Abstract
The outbreak of sea star wasting disease along the Pacific Northwest in 2013 is associated with a shift in sea star community structure, with the normally abundant Pisaster ochraceus decreasing in abundance relative to Evasterias troschelii in and around Vancouver, BC. This change in relative abundance could directly affect the abundance and distribution of important prey species such as Mytilus trossulus (mussels) and Balanus glandula (barnacles), with Mytilus observed to exclude and decrease species richness of additional prey species in the intertidal. Previous research indicates that Pisaster prefers mussels over barnacles, however with Evasterias being understudied, these preferences are unknown. The goal of this research project was to improve our understanding of Evasterias prey preferences, feeding rates, and whether diet affects sea star growth. We conducted a lab experiment using organisms collected from Burrard Inlet, BC, and provided Evasterias with a diet of mussels, barnacles, or both, and recorded prey consumption and predator growth rate. Additionally, we conducted a feeding rate experiment between Evasterias and Pisaster. Results show the growth rate of Evasterias was higher when mussels were available. However, the proportion of mussels or barnacles consumed did not differ when sea stars were presented with only one or both prey species, suggesting that they did not have a strong prey preference. The number of mussels consumed overall was lower than that of barnacles, but tissue mass consumed was higher in mussels than that of barnacles. The feeding rates between Pisaster and Evasterias showed similarity. Although the strength of dietary preferences of Evasterias and Pisaster may differ, our results suggest that Evasterias may nevertheless play a similar ecological role when it becomes abundant on rocky shores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".