Phragmites australis invasion and herbicide-based control changes primary production and decomposition in a freshwater wetland
Bibliographic record
Abstract
Abstract Wetlands are important global carbon sinks, an increasingly important ecosystem service. Invasive plants can disrupt wetland carbon budgets, although efforts to suppress invasive plants may also have unintended effects. InvasivePhragmites australissubsp.australis(European common reed) produces extensive monocultures that displace resident plant communities. In Long Point (Ontario, Canada), a glyphosate-based herbicide was used to control over 900 ha ofP. australis. We determined how this ongoing management, and different environmental conditions, influence net primary productivity and decomposition rates. We compared above- and below-ground biomass, belowground:aboveground biomass ratios, standing dead stems, and litter in un-treatedP. australisstands, in herbicide-treated areas, and in reference vegetation. We also conducted a reciprocal transplant experiment to measure the decomposition rates of plant litter. One-year post-treatment, control efforts dramatically reduced aboveground biomass (122 g/m2 ± 133 SD) compared to un-treatedP. australis(1254 g/m2 ± 449 SD) and reference habitat (821 g/m2 ± 335 SD). An interaction between the plant community of the site and water depth predicted litter decomposition rates, with litter loss ranging from 5.75 to 74.65% across all species, and submerged litter decomposing faster. These results emphasize that secondary treatment, such as rolling, burning, or cutting, encourages the decomposition of deadP. australisstems, opening up space for the recovery of native plants. While herbicide-treated sites had low biomass immediately following treatment, aquatic vegetation began rapidly colonizing treated areas, suggesting that plant community recovery may restore the wetland carbon uptake in subsequent years.
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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) | 0.000 | 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 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".