Ecological Restoration on Private Lands: An Assessment of TRCA's Planting Practices and Guideline for Conservation Authorites
Bibliographic record
Abstract
Since the early 1900s, tree planting has been a part of the restoration of Ontario's landscape. In central Ontario, there are many groups and efforts to plant trees on both public and private lands. The Toronto and Region Conservation Authority's (TRCA) Private Land Planting Program is an initiative with more than 50 years of planting and forest management experience, supporting landowners in restoration and improvement of their properties through the planting of native trees and shrubs. However, to ensure the survival of planted trees, planting practices must be optimized, including site selection and preparation, species selection, approach to planting, and monitoring. This paper aims to assess TRCA's planting practices on private lands, evaluate the success of restoration projects based on the review of private land quality and survival assessment data from 2019-2021, and identify potential tree planting improvement areas and suggest guidelines for tree planting restoration. Three planting sites were used to support the case study and project objectives.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".