Growth and photosynthesis responses of two co-occurring marsh grasses to inundation and varied nutrients
Bibliographic record
Abstract
For tidal marshes of the US Northeast, the late twentieth century decline of Spartina patens (Aiton) Muhl. has been attributed to increased flooding associated with accelerated sea level rise and nitrogen over-enrichment from cultural eutrophication. The objective of this study was to examine the impacts of inundation and nutrient availability on growth, photosynthesis, and interactions of S. patens and Distichlis spicata (L.) Greene, which co-occur and are common marsh species. Plants were grown in a factorial greenhouse experiment, where flow-through seawater was used to simulate semidiurnal tides. Field surveys were additionally conducted to relate plant distributions to environmental conditions. For S. patens grown in monoculture, nutrient additions did not enhance growth for the high inundation treatment. In addition, the combination of high nutrient availability and high inundation adversely affected S. patens tiller density, photosynthetic efficiency, and leaf CO 2 uptake. For D. spicata, nutrient additions enhanced growth for both inundation treatments with respect to aboveground biomass and tiller density. For species pairings, S. patens expanded relative to D. spicata under low inundation, low nutrient availability conditions, but declined relative to D. spicata under daily inundation in combination with nutrient amendments. These findings were additionally supported by field data, which indicated that D. spicata was more common than S. patens where nutrient availability was high. These results suggest that S. patens persistence is favored by low nutrient inputs and well-drained conditions, and supports the interpretation that this species is vulnerable to loss where high nutrient loads coincide with accelerated sea level rise.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".