Assessing the ecological relationships of the orange-striped green sea anemone, Diadumene lineata, as a non-indigenous species in British Columbia, Canada
Bibliographic record
Abstract
The orange-striped green sea anemone, Diadumene lineata, is a widely distributed non-indigenous species that has been introduced to coastal habitats across the globe. Despite its now cosmopolitan distribution, little is known about its position in local food webs or its ecological impacts on indigenous species. To better understand the ecological role of D. lineata in intertidal communities, we conducted a series of feeding trials, stable isotope analyses, and correlative site abundance surveys to establish the trophic relationships for this species in British Columbia, Canada, where it is widely distributed and locally abundant. The strength of those linkages in the ecosystem were then examined through an anemone density manipulation in local tidepools, and the possible facilitative relationship between D. lineata and the indigenous mussel, Mytilus trossulus, was explored using a combination of field and laboratory experiments. Our findings suggest that D. lineata is a dietary generalist and is not limited by indigenous predators within the high shore range of the anemone. Mussels were found to facilitate the attachment of D. lineata in specific conditions but did not influence long-term retention in experimental tidepools. Despite observed and often dramatic increases in anemone abundance in the Salish Sea since 2016, we found no effect of elevated anemone density on benthic intertidal biodiversity through the density manipulation experiment. Further research is needed to determine whether D. lineata may influence other species interactions or ecosystem services before establishing whether this anemone should be classified as an invasive species in western Canada and elsewhere.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".