Assessing net primary production in the northwestern Barents Sea using in situ, remote sensing and modelling approaches
Bibliographic record
Abstract
The northwestern Barents Sea (NW-BS) is a highly productive region within the transitional zones of an Atlantic to Arctic-dominated marine ecosystem. The steep latitudinal gradients in sea ice concentration, Atlantic and Arctic Water, offer an opportunity to test hypotheses on physical drivers of spatial and temporal variability of net primary production (NPP). However, quantifying NPP in such a large ocean region can be challenging by the lack of in situ measurements with high spatial and temporal resolution, and gaps in remote sensing estimates due to the presence of clouds and sea ice, and assumptions regarding the depth distribution of biomass. Without reliable data to evaluate models, filling these gaps with numerical models is limited by the model representation of the physical environment and its assumptions about the relationships between NPP and its main limiting factors. Hence, within the framework of the Nansen Legacy Project, we combined in situ measurements, remote sensing, and model simulations to constrain the estimates of phytoplankton NPP in NW-BS. The region was subdivided into Atlantic, Subarctic, and Arctic subregions on the basis of different phytoplankton phenology. In 2004 there was a significant regime change in the Atlantic subregion that resulted in a step-increase in NPP in tandem with a step-decrease in sea ice concentration. However, neither region experienced significant long term trends in NPP despite changes in the physical environment. Mixing was the main driver of simulated annual NPP in the Atlantic subregion, while light and nutrients drove annual NPP in the Subarctic and Arctic subregions. The multi-source estimate of annual NPP ranged 79–118 gC m−2 yr−1 in the Atlantic, 74–82 gC m−2 yr−1 in the Subarctic, and 19–47 gC m−2 yr−1 in the Arctic. The total NPP in the NW-BS region was estimated between 15 and 48 Tg C yr−1, which is 15–50% of the total NPP needed to sustain three of the most harvested fish species north of 62°N (roughly 90 Tg C yr−1). This research shows the importance of continuing to strive for better regional estimates of NPP.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".