A first look at megabenthic community responses to seasonal change using the new Holyrood Subsea Observatory in Conception Bay, NL
Bibliographic record
Abstract
Sub-Arctic seafloor communities rely on seasonal phytoplankton blooms for food, revealing a tight benthic-pelagic coupling. To maximize resource availability for offspring, organisms such as snow crabs, sea stars, and sea cucumbers synchronize their reproductive and feeding behaviours with spring blooms. Due to climate change, spring blooms are occurring earlier in sub-Arctic regions, leading to a possible mismatch between timing of resource availability and important life-history behaviours. Here, we utilize high-frequency time-series observations from the Holyrood Subsea Observatory, a new cabled seafloor observatory deployed in Conception Bay, Newfoundland. We use hourly data collected from environmental sensors (Conductivity-Temperature-Depth, Acoustic Doppler Current Profiler, fluorometer), a near-surface mooring (fluorometer), and a video camera to identify and quantify abundance and diversity of benthic megafauna, and to determine how community composition changed from pre-bloom to full bloom conditions. Data analysis revealed striking temporal changes in benthic activity, with the notable emergence of Psolus cf. phantapus sea cucumbers (up to 289.9 indiv./m2) coinciding with increased chlorophyll-a concentration and seawater temperature. At least three dense schools of forage fish, two Atlantic herring (79 and 144 indiv. frame-1) and one capelin (91 indiv. frame-1), were observed during the main bloom between May 5 and June 16. This study provides the first high-frequency in situ observations of benthic community response to seasonal food input in the region. The high temporal resolution made it possible to record the precise timing of the of Psolus cf. phantapus emergence in relation to the timing of food input to the seafloor, which will provide a baseline to monitor phenology as climate change progresses. Changes to the timing of spring blooms have implications for sub-Arctic fisheries productivity and ecosystem functioning, making continuous long-term monitoring of seafloor communities essential.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".