Interannual variability (2000–2013) of mesopelagic and bathypelagic particle fluxes in relation to variable sea ice cover in the eastern Fram Strait
Bibliographic record
Abstract
The Fram Strait connects the Atlantic and Arctic Oceans and is a key conduit for sea ice advected southward by the Transpolar Drift and northward inflow of warm Atlantic Waters. Continued sea ice decline and “Atlantification” are expected to influence pelagic–benthic coupling in the Fram Strait and Arctic as a whole. However, interannual variability and the impact of changing ice conditions on deepwater particle fluxes in the Arctic remain poorly characterized. Here, we present long-term sediment trap records (2000–2013) from mesopelagic (200 m) and bathypelagic (2,300 m) depths at two locations (HGIV and HGN) in the Fram Strait subjected to variable ice conditions. Sediment trap catchment areas were estimated and combined with remote sensing data and a high-resolution model to determine the ice cover, chlorophyll concentration, and prevailing stratification regimes. Surface chlorophyll increased between 2000 and 2013, but there was no corresponding increase in POC flux, suggesting a shift in the efficiency of the biological carbon pump. A decrease in particulate biogenic Si flux, %opal, Si:POC, and Si:PIC at mesopelagic depths indicates a shift away from diatom-dominated export as a feasible explanation. Biogenic components accounted for 72% ± 16% of mass flux at 200 m, but were reduced to 34% ± 11% at 2,300 m, substituted by a residual (lithogenic) material. Total mass fluxes of biogenic components, including POC, were higher in the bathypelagic. Biomarkers and ∂ 13 C values suggest both lateral advection and ice-rafted material contribute to benthic carbon input, although constraining their precise contribution remains challenging. The decadal time series was used to describe two end-members of catchment area conditions representing the maximum temperatures of Atlantic inflow water in 2005 at HGIV and high ice coverage and a meltwater stratification regime at HGN in 2007. Despite similar chlorophyll concentrations, bathypelagic POC flux, Si flux, Si:POC, and Si:PIC were higher and POC:PIC was lower in the high-ice/meltwater regime. Our findings suggest that ice concentration and associated meltwater regimes cause higher diatom flux. It is possible this will increase in the future Arctic as meltwater regimes increase, but it is likely to be a transient feature that will disappear when no ice remains.
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 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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".