Differences in wetland plant community establishment with additions of nitrate-N and invasive species (<i>Phalaris arundinacea </i>and <i>Typha</i> ×<i>glauca</i>)
Bibliographic record
Abstract
Restored prairie pothole wetlands in North America are often enriched by nitrate-N (NO3-N) that has been lost from surrounding agricultural systems. In addition, these wetlands are increasingly colonized by invasive taxa including Phalaris arundinacea L. and Typha ×glauca Godr. To explore the impacts of NO3-N enrichment, suppression by invasive species, and the interaction of these factors on restored communities, we grew native sedge meadow communities from seed in greenhouse mesocosms and subjected them to NO3-N and invasive species for 4 months. Typha ×glauca did not reduce overall native community biomass and actually enhanced Aster spp. biomass. Phalaris arundinacea suppressed growth of the native community to an equal relative extent across all NO3-N levels. The shoot biomass of the entire native community in untreated plots was similar to the P. arundinacea fraction of the treated plots. Phalaris arundinacea demonstrated greater plasticity in root-shoot allocation than the native community over the range of NO3-N inputs. Proportional allocation to root biomass was greater for P. arundinacea than for the native community at all but the highest NO3-N level. Both factors may be important in explaining dominance of P. arundinacea over the native community in a range of fertility conditions. Regardless of NO3-N inputs, the restoration of diverse native wetlands requires strict control of P. arundinacea during community establishment, as evidenced by the relatively rapid rate of suppression of native community biomass by P. arundinacea compared with T. ×glauca.Key words: restoration, agricultural impacts, prairie pothole, root/shoot ratio.
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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".