Growth and competition among understory plants varies with reclamation soil and fertilization
Bibliographic record
Abstract
Following oil sands mining in Alberta, Canada, the main land management goal is to establish a functioning boreal forest ecosystem, including the understory plant community. One of the challenges with restoring the understory is the presence of non-native species that compete with desirable native species for resources. In a greenhouse experiment, we studied the growth of two native understory species ( Galium boreale and Vicia americana ) and a non-native invasive species ( Matricaria perforata ) grown with either intra- or interspecific neighbors across three common land reclamation soils and a nitrogen fertilizer treatment. When grown by itself, V. americana aboveground biomass did not differ among soil or fertilizer treatments, likely due to its ability to fix nitrogen. Growth of M. perforata was directly related to soil nitrogen, and it had the greatest increase in biomass with fertilization. Growth and biomass of G. boreale was less than the other species, and it had the highest mortality in the nitrogen-poor soil. When grown together, the proportional biomass of M. perforata and V. americana varied with soil treatment such that M. perforata was dominant in the high-nitrogen forest floor-mineral mix treatment while V. americana was dominant in the low-nitrogen peat-mineral mix. Operationally, care should be taken when applying fertilizer to reclamation areas, as it may have an unwanted positive effect on growth for undesirable non-native plants at the expense of native species. In terms of seed mixtures, V. americana may be a good option for low inorganic nitrogen resource soils and G. boreale for high nitrogen resource soils.
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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".