The extent, density, and biomass carbon of eelgrass (Zostera marina) meadows in Clayoquot Sound, British Columbia
Bibliographic record
Abstract
Seagrass habitats have recently been characterized by their ability to capture and store organic carbon, known as ‘blue carbon.’ However, the geospatial extent and carbon storage capacity of these habitats are largely unknown on the Pacific Coast of Canada. This research quantified the areal extent of three eelgrass (Zostera marina) meadows in southern Clayoquot Sound on the Pacific Coast of Canada using remote sensing technologies and assessed the above- and belowground biomass (AGB; BGB) and living carbon content of the intertidal and subtidal zones. AGB estimates ranged from 11 ± 4 to 92 ± 51 g DW m-2, which translated into carbon stocks of 4 ± 1 to 33 ± 18 g C m-2 and are consistent with global estimates for Z. marina. BGB estimates were much lower than values for Z. marina in other regions (45 - 285 g DW m-2), ranging from 5 ± 4 g DW m-2 (2 ± 1 g C m-2) to 26 ± 20 g DW m-2 (9 ± 7 g C m-2). Low BGB in Clayoquot Sound is likely a response to sub-optimal environmental conditions, resulting in the eelgrass’ shallow root system. The intertidal zone of two of our meadows, Robert Point (22,414 m2) and Grice Bay (186,468 m2), made up approximately 70% of their total meadow area (31,886 m2 and 261,667 m2, respectively), whereas the subtidal dominated at Kennedy Cove (4,318 m2), making up 80% of the meadow (5,343 m2). Mapping the intertidal and subtidal portions of each meadow allowed for biomass and living carbon estimates to be scaled up to their respective zone. After accounting for the size of each meadow, the more marine-influenced meadows, Robert Point and Kennedy Cove, had significantly higher density, biomass, and living carbon content values. Given the scarcity of data available on the extent of eelgrass meadows in Canada, regionally specific quantification of these habitats’ areal extent, biomass, and carbon storage dynamics are required to accurately assess seagrasses climate change mitigation potential.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".