An investigation of selection cutting as a viable alternative to clear-cutting practices in Nova Scotia's spruce and fir forests
Bibliographic record
Abstract
Forestry in the province of Nova Scotia has been dominated by clear- cutting for the past several years. Only recently, as forests of harvest potential have become scarce and diminishing returns have become evident for Nova Scotia, has concern been expressed as to the sustainability of this practice and the need for alternatives. Using the three concepts of sustainability; economics, community, and environment, this thesis attempts to contrast selection cutting and clear-cutting, with a concentration on the Acadian spruce and fir forests of the province of Nova Scotia. A Sustainability Prediction Model and a Sustainability Measures Model are presented to help classify practices in terms of sustainability. These practices are then loosely classified according to Kerry Turner's (expanded by Glyn Bissix) sustainability model. In addressing these three sustainability concepts, a combination of literature reviews from industry, government, environmentalists, and others, past experimental research, field work, along with careful interpolation and prediction have been used to construct a powerful case in favour of selection cutting as a viable, sustainable alternative to clear-cutting in Nova Scotia Acadian spruce and fir forests. Economic data has been reviewed for both practices in the province. Other measures to increase value derived from harvesting to meet demand such as log sorting, expansion of the value-added industry, certification, etc. are also discussed. The impact on communities in terms of employment, values, tourism, aesthetics, recreation, etc, has been established through research of past studies and personal contacts. The ecological impact of both practices was investigated through literature, and past experimentation. Using case study sites, and the general information of impacts applicable to the province, both practices were classified using Bissix's extended version of Turner's Sustainability Classifications. Finally, predictions were made about the sustainability of Nova Scotia forests and the forestry industry following these two practices using the Sustainability Prediction Model and a means of testing these predictions suggested. The main conclusions based on this thesis suggest selection cutting to be a definite possibility to alleviate many of the critical concerns associated with clear- cutting as our main forestry practice. Economically profits may drop slightly, but are much more evenly distributed and will continue to generate revenue into the future. Ecologically much less damage in done to habitat and feeding sources. In terms of community a greater, more diverse skill-orientated employment base opens up allowing for more opportunities for a diverse local population with much more longevity in terms of job stability. Selection cutting also allows for a more multiple-use approach to forest management, including recreation, tourism, and harvesting forest products other than timber. Overall, selection cutting was predicted to be of strong sustainability with clear-cutting predicted to be in the weak to exploitive range. This conclusion was further substantiated using Turner's Sustainability Classifications with the expansion to this system made by Glyn Bissix. Using this classification, clear-cutting was determined to be a weak to very weak sustainable practise. Selection cutting was determined to be a strong sustainable practise.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".