Restoration Ecology of an Endangered Plant Species: Establishment of New Populations of <i>Cirsium pitcheri</i>
Bibliographic record
Abstract
Abstract We determined the effects of shade, burial by sand, simulated herbivory, and fertilizers on the survival and growth of artificially planted population of Cirsium pitcheri—an endangered plant species of the sand dunes along Lake Huron. Sand burial experiments showed that greenhouse grown plants should optimally be transplanted into areas receiving 5 cm of sand deposition: burial at this depth maximized emergence, survivorship, and below‐ground biomass. Under field conditions, simulated herbivory of up to 50% of the plant height produced a slight increase in biomass after one year of growth. Field observations showed that when white‐tailed deer removed more than 50% of the transplant's leaf tissue, the plant died. The application of a 20:20:20 (N:P:K) water‐soluble fertilizer produced a significant increase in the dry leaf biomass, total leaf area, and total dry biomass relative to control plants. We also tested for the presence or absence of a persistent seed bank. Few seeds were recovered from soil samples collected from Pinery Provincial Park and Providence Bay. However, C. pitcheri has the ability to form a persistent seed bank under field conditions but only at soil depths of 15 cm. Cirsium pitcheri seeds are able to germinate and seedlings can emerge from a burial depth of up to 6 cm. Thus, seeds planted in open, sunny areas will probably maximize emergence, growth, and survivorship of seedlings. Populations of C. pitcheri can be restored by planting seeds at shallow depths, transplanting greenhouse‐grown plants, applying water soluble fertilizers, and protecting plants from herbivores.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".