Caractérisation des chutes de litière et des apports au sol en nutriments dans une mangrove de Guyane française
Bibliographic record
Abstract
Litter falls and their contributions to soil nutriments were measured in five distinct facies of a mangrove in French Guyana. These facies were characterized by their distance from the sea, their floral composition (Laguncularia racemosa (L.), Avicennia germinans (L.) Stearn, Rhizophora spp.), and their structural features. Data were analyzed according to facies and to species for litters, as well as to seasons for the nutriments. This mangrove produced respectively 8.8 and 8.7 t·ha1·year1of litter at the pioneer and senescent stages submitted to strong environmental constraint and 12.5 and 12.6 t·ha1·year1for young and mature stages where developmental conditions are optimum. Nitrogen and carbon inputs were estimated to 1.3 × 102and 6.4 t·ha1·year1, respectively. Litter appeared rich in phosphorous, corresponding with the high concentrations characterizing the sediments. For a given species, magnesium and calcium concentrations were constant between facies, whereas potassium and sodium concentrations varied according to the distance from the sea. Differences were perceived between species for all nutriments except sodium. Results are discussed in relation with the ecophysiological characteristics of the mangrove trees and the specific sedimentology of Guyana coast and are replaced in the perspective of an improved knowledge of the carbon and mineral balances in tropical coastal ecosystems.Key words: mangrove, French Guyana, litter, carbon balance, mineral nutriments, spatial variations.[Journal translation]
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".