Seagrass community-level controls over organic carbon storage are constrained by geophysical attributes within meadows of Zanzibar, Tanzania
Bibliographic record
Abstract
Abstract. The aim of this work was to explore the feasibility of using plant functional traits to identify differences in sediment organic carbon (OC) storage within seagrass meadows. At 19 sites within three seagrass meadows in the coastal waters of Zanzibar, Tanzania, species cover was estimated along with three community traits hypothesized to influence sediment OC storage (above and belowground biomass, seagrass tissue nitrogen content, and shoot density). Sediments within four biogeographic zones (fore reef, reef flat, tidal channel, and seagrass meadow) of the landscape were characterized, and sediment cores were collected within seagrass meadows to quantify OC storage in the top 25 cm and top meter of the sediment. We identified five distinct seagrass communities that had notable differences in the plant traits, which were all residing within a thin veneer (ranging from 19 to 78 cm thick) of poorly sorted, medium to coarsely grained carbonate sands on top of carbonate rock. One community (B), dominated by Thalassodendron ciliatum, contained high amounts of above (972±74 g DW m−2) and belowground (682±392 g DW m−2) biomass composed of low-elemental-quality tissues (leaf C : N = 24.5; rhizome C : N = 97). While another community (C), dominated by small-bodied ephemeral seagrass species, had significantly higher shoot density (4178 shoots m−2). However, these traits did not translate into differences in sediment OC storage and across all communities the percentage of OC within sediments was similar and low (ranging from 0.15 % to 0.75 %), as was the estimated OC storage in the top 25 cm (14.1±2.2 Mg C ha−1) and top meter (33.9±7.7 Mg C ha−1) of sediment. These stock estimates are considerably lower than the global average (194.2±20.2 Mg C ha−1) reported for other seagrass ecosystems and are on the lower end of the range of estimates reported for the tropical Indo-Pacific bioregion (1.9 to 293 Mg C ha−1). The uniformly low OC storage across communities, despite large inputs of low-quality belowground tissues in community B, indicates that the geophysical conditions of the coarse, shallow sediments at our sites were not conducive to OC stabilization and outweighed any variation in the quantity or quality of seagrass litter inputs. These results add to a growing body of evidence showing that geophysical conditions of the sediment modulate the importance of plant traits in regards to retention of OC within blue carbon ecosystems and cautions against the use of plant traits as a proxy for sediment OC storage across all seagrass ecosystems.
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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 | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".