Are plantations changing the tree species composition of New Brunswick's forest?
Bibliographic record
Abstract
Forest plantations are viewed by some as a means to meet the world's escalating demand for wood, and by others as a threat to forest diversity and ecological function. With the purpose of improving planting practices, we analysed recently available data on 15- to 30-year-old plantations on public land in New Brunswick to identify tree species composition differences between plantations and the natural forest they replaced. Presently, 9% of the public forests in the province has been planted; at current planting rates, this will increase to 17% by the year 2030. Plantations established between 1967 and 1982 differ little from the natural forest they replaced in terms of total softwood content, but differ markedly by having much higher jack pine and much lower red spruce contents. There is evidence of reduced diversity evenness in plantations at the landscape level, but at the stand level few plantations are true monocultures and the abundance of high single-species dominance in plantations is very similar to that of the natural forests they replaced. All species composition comparisons between plantations and replaced natural forest vary strongly by ecoregion. To reduce the degree of difference between plantations and the natural forest, planting practices and prescriptions should (a) broaden the mix of species used, and use less jack pine and more red spruce and cedar, (b) employ a mix of species at the stand level, and (c) consider more fully the site conditions and natural species composition of ecological zones. Key words: plantations, tree species composition, forest simplification, tree species diversity, forest management
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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 teacher head, 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".