Land suitability analysis for harvest species using a multi -criteria and GIS approach in northern Saskatchewan
Bibliographic record
Abstract
For sustainable plant harvesting, a land suitability analysis is essential to maximize the use of existing land resources. In the study area, the most urgent problem was finding the most suitable place that will support chanterelles and junipers, this is because among the most economically relevant plants in northern Saskatchewan, chanterelle and juniper are very under-harvested due to inadequate strategic harvesting (Boreal heartland 2021). Through the application of geospatial technology, this study developed a suitability map for the harvest of chanterelle and juniper in specific zones.\nTherefore, to overcome this challenge, a geospatial approach involving the Analytical Hierarchy Process (AHP), Weighted Overlay Analysis (WOA) and the Pairwise Comparison Matrix method (PCM) were applied. In accordance with reclassification and weight overlay analyses by Food and Agricultural Organizational guidelines (FAO, 1993), the study area was divided into five appropriate chanterelle and juniper zones. Based on the analysis of the study area, the individual factors indicated the most important factors to the growth of both species are edaphological (soil texture) 30.1%, climatological (rainfall) 29.4%, topological (elevation and slope) 22% and physiological (fire history and landcover) 18.4%. Consequently, this shows that, 58% of the land (12,378.60 km2) was determined to be highly suited, 31% (6,654.82 km2) to be moderately suited, and 11% of the study area (2,449.27 km2) to be poorly suited for juniper growth. Furthermore, the analyzed results indicate that 36% of the land area (7,641.72 km2) was assessed as highly suited for the growth of chanterelle mushrooms, 56% (12,136.62 km2) was assessed as moderately suited, and 8% (1,724 km2) was assessed as poorly suited. At the local level, this study provided information about chanterelle and juniper farming land and suitability. This information could be used by the boreal heartland of northern Saskatchewan, farmers, investors, and governments to determine the most promising areas for chanterelle and juniper farming to maximize export earnings.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".