Invasive <i>Phragmites</i> Increases Blue Carbon Stock and Soil Volume in a St. Lawrence Estuary Marsh
Bibliographic record
Abstract
Abstract Our study of a St. Lawrence Estuary marsh reveals that, compared to native Spartina patens‐dominated vegetation, invasive Phragmites australis makes a greater contribution to soil volume and carbon stock (referred to as blue carbon). Phragmites' contributions to soil volume enhance marsh sustainability in face of sea level rise, and its greater contribution to soil carbon helps to reduce the atmospheric concentration of CO2. Phragmites australis (common reed) is a cosmopolitan species growing in fresh to brackish wetlands. An invasive genetic strain, introduced from Europe or Asia, has expanded extensively along the St. Lawrence River in the last few decades but has been little studied on the estuarine portion. We collected soil cores from three sites within an invasive Phragmites stand and one site within S. patens‐dominated stand in a St. Lawrence Estuary salt marsh near la Pocatiere, Quebec. We measured the bulk density, carbon content, volume, and mass of belowground organic matter in 2‐cm‐thick soil layers of three cores at each Phragmites site. Bulk density and carbon content were measured in 5‐cm‐thick soil layers of three cores at S. patens site. Results showed that soil in the Phragmites stands held 37–77% more blue carbon than in the S. patens‐dominated marsh. Based upon their diameter size, Phragmites rhizomes could be contributing 7.4–10.2 cm to the thickness in the upper 20 cm of soil. We suggest that any management of invasive Phragmites include consideration of its role in increasing blue carbon stocks and marsh resilience along with other ecosystem services.
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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 | 0.000 | 0.000 |
| 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".