Inoculating rhizome-propagated <i>Sporobolus pumilus</i> with a native mycorrhizal fungus increases salt marsh plant growth and survival
Bibliographic record
Abstract
Salt marshes are ecosystems of significant ecological importance for coastal stability and fundamental roles in marine ecosystems. Salt marshes are declining due to anthropogenic and natural causes including sea level rise. Coastal restoration efforts have increased worldwide, but many fail in long-term coastal stability. We used a naturally occurring arbuscular mycorrhizal fungus (AMF) to test whether survival and early growth of the salt marsh grass Sporobolus pumilus (formerly Spartina patens) improved under simulated salt marsh conditions. Using a tidal mesocosm bench, we grew inoculated plants with varying AMF treatments under simulated tidal regimes to determine if AMF could aid in establishment of healthy Sporobolus communities. Rhizome-derived S. pumilus had greater survival and grew faster than seed-derived plants. Plants inoculated with propagated AMF consistently outperformed both sterile and native sediment controls in terms of plant survival and growth. Use of rhizome-derived Sporobolus inoculated with propagated Funneliformis geosporum showed the most promise in producing successful plant populations for salt marsh restoration. This may be due to plant life stage and improved plant nutrient status, allowing rhizome-derived plants to grow more quickly than seed-derived plants. Using these plants in future large-scale restoration may increase re-establishment of salt marsh ecosystems.
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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".