Ecological determinants of intertidal recruitment and metacommunity structure on the Atlantic coast of Nova Scotia
Bibliographic record
Abstract
Rocky-intertidal species are often distributed as metacommunities along marine shores, as rocky habitats are patchy. Nearshore pelagic conditions often explain variation among the local communities, but most studies have been done on eastern ocean boundary coasts. We investigated potential drivers of intertidal metacommunity structure on the Atlantic coast of Nova Scotia. We studied the high intertidal zone of nine wave-exposed bedrock locations spanning 425 km of coastline. At each location in the spring, we measured the recruitment of barnacles and mussels, the two predominant sessile invertebrates. Satellite data on coastal phytoplankton abundance and particulate organic carbon (food supply for intertidal filter-feeders) and in-situ data on coastal seawater temperature explained to varying degrees the geographic structure of recruitment. In turn, the summer abundance of both filter-feeders was positively related to their spring recruitment. Ultimately, predator (dogwhelk) abundance increased with the recruitment and abundance of barnacles and mussels (the main prey of dogwhelks), suggesting that bottom-up forcing influences metacommunity structure on this coast. Sea ice constituted an overlapping source of variation. Drift ice leaving the Gulf of St. Lawrence in late winter disturbed intertidal communities in the northern locations, limiting local biodiversity compared with central and southern locations.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".