Ecological Variability and Carbon Stock Estimates of Mangrove Ecosystems in Northwestern Madagascar
Bibliographic record
Abstract
Mangroves are found throughout the tropics, providing critical ecosystem goods and services to coastal communities and supporting rich biodiversity. Despite their value, world-wide, mangroves are being rapidly degraded and deforested. Madagascar contains approximately 2% of the world’s mangroves, >20% of which has been deforested since 1990 from increased extraction for charcoal and timber and conversion to small to large-scale agriculture and aquaculture. Loss is particularly prominent in the northwestern Ambaro and Ambanja bays. Here, we focus on Ambaro and Ambanja bays, presenting dynamics calculated using United States Geological Survey (USGS) national-level mangrove maps and the first localized satellite imagery derived map of dominant land-cover types. The analysis of USGS data indicated a loss of 7659 ha (23.7%) and a gain of 995 ha (3.1%) from 1990–2010. Contemporary mapping results were 93.4% accurate overall (Kappa 0.9), with producer’s and user’s accuracies ≥85%. Classification results allowed partitioning mangroves in to ecologically meaningful, spectrally distinct strata, wherein field measurements facilitated estimating the first total carbon stocks for mangroves in Madagascar. Estimates suggest that higher stature closed-canopy mangroves have average total vegetation carbon values of 146.8 Mg/ha (±10.2) and soil organic carbon of 446.2 (±36.9), supporting a growing body of studies that mangroves are amongst the most carbon-dense tropical forests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".