Environmental factors influencing the seasonal dynamics of spring algal blooms in and beneath sea ice in western Baffin Bay
Why this work is in the frame
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Bibliographic record
Abstract
Arctic sea ice is experiencing a shorter growth season and an earlier ice melt onset. The significance of spring microalgal blooms taking place prior to sea ice breakup is the subject of ongoing scientific debate. During the Green Edge project, unique time-series data were collected during two field campaigns held in spring 2015 and 2016, which documented for the first time the concomitant temporal evolution of the sea ice algal and phytoplankton blooms in and beneath the landfast sea ice in western Baffin Bay. Sea ice algal and phytoplankton blooms were negatively correlated and respectively reached 26 (6) and 152 (182) mg of chlorophyll a per m2 in 2015 (2016). Here, we describe and compare the seasonal evolutions of a wide variety of physical forcings, particularly key components of the atmosphere–snow–ice–ocean system, that influenced microalgal growth during both years. Ice algal growth was observed under low-light conditions before the snow melt period and was much higher in 2015 due to less snowfall. By increasing light availability and water column stratification, the snow melt onset marked the initiation of the phytoplankton bloom and, concomitantly, the termination of the ice algal bloom. This study therefore underlines the major role of snow on the seasonal dynamics of microalgae in western Baffin Bay. The under-ice water column was dominated by Arctic Waters. Just before the sea ice broke up, phytoplankton had consumed most of the nutrients in the surface layer. A subsurface chlorophyll maximum appeared and deepened, favored by spring tide-induced mixing, reaching the best compromise between light and nutrient availability. This deepening evidenced the importance of upper ocean tidal dynamics for shaping vertical development of the under-ice phytoplankton bloom, a major biological event along the western coast of Baffin Bay, which reached similar magnitude to the offshore ice-edge bloom.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it