Nitrogen cycling in the Cape Verde Frontal Zone (NW Africa): Elemental and isotopic characterization
Bibliographic record
Abstract
Despite the scientific interest on nitrogen (N) in the marine environment and its key role in \nglobal biogeochemical cycles, there are still uncertainties about the mechanisms that \ncontrol its cycle and how to quantify them. N fluxes to and within the ocean are likely to \nincrease in the future due to anthropogenic activities. To understand the consequences of \nthese anthropogenic perturbations in the ocean, natural fluctuations in the N cycle must be \nunderstood. In this context, the general objective of this PhD thesis is to characterize \nelemental and isotopically the inorganic and organic (dissolved and suspended) N pools, in \nthe Cape Verde Frontal Zone (CVFZ) from the information collected during two \noceanographic cruises carried out in summer and autumn 2017. This highly dynamic zone \nis located at the southern end of the Eastern Boundary Upwelling Ecosystem of the Canary \ncurrent. In the CVFZ, convergence of tropical and subtropical Atlantic waters occurs, \nforming the thermohaline Cape Verde front (CVF). In addition, this region is characterised \nby large vertical and horizontal export fluxes of organic matter and inorganic nutrients, due \nto the interaction of the CVF with the Mauritanian coastal upwelling and its Cape Blanc \nGiant Filament. \nWe observed that the distributions of inorganic and organic N species, and the -O2:N:Si:P \nstoichiometric ratios in the epipelagic layer of the CVFZ were dictated by the position of \nthe CVF and its interaction with meso- and submeso-scale structures (meanders, eddies, \nfilaments). This stoichiometry reflected severe N limitation at surface mixed layer, and \npreferential N mineralisation in the water below pycnocline and in meso- and bathypelagic \nlayers. Geographical heterogeneity in dissolved (DON) and suspended particulate (PON) \norganic nitrogen distributions and their stoichiometry were also observed within each of \nthe different water masses of contrasting origin present in the study area (North and South \nAtlantic Central Water, Subpolar Mode Water, Mediterranean Water, Antarctic \nIntermediate Water, Labrador Sea Water and North East Atlantic Deep Water). \nNevertheless, our analysis indicates that DON and suspended PON have a minor impact on \nlocal mineralisation processes, suggesting that regenerated nitrate in CVFZ was mainly \nderived from sinking POM. This higher contribution of sinking POM was also supported \nby the distribution of δ15NNO3 \n− and δ18ONO3 \n− and the average values obtained for each water \nmass in the CVFZ.
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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 | 0.000 | 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 | 0.005 | 0.002 |
| 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 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".