Landscape Integrated Soil and Water Conservation (LISWC) System for Sloping Landscapes in Atlantic Canada
Bibliographic record
Abstract
Soil and water are fundamental and precious resources for agriculture. In Atlantic Canada (AC), intensive agricultural production systems have led to detrimental environmental effects such as soil erosion and the contamination of receiving waters, posing significant threats to the resilience and sustainability of the agro-ecosystem. Although many beneficial management practices (BMPs) have been developed, they all have their shortcomings and there are often trade-offs for each individual BMP. In this paper, a new paradigm is proposed for soil and water conservation—landscape integrated soil and water conservation (LISWC), a system designed to conserve and reuse soil and water within the landscape by integrating multiple BMPs based on an understanding of the landscape processes and knowledge about the BMPs. On a typical sloping field in AC, an LISWC system can be established by integrating BMPs such as diversion terraces and grassed waterways, tile drainage, water retention structures, supplemental irrigation, conservative tillage practices and soil–landscape restoration. Each individual BMP is designed to enhance one aspect of soil and water conservation but working on their own, they are all insufficient for the landscape as a whole and sometimes even have negative impacts. However, once integrated in the landscape, they complement each other: water erosion is reduced by diversion terraces and grassed waterway and conservative tillage, field drainage condition is enhanced by tile drainage, runoff and tile drained water is stored in the retention structure and reused for irrigation, and most eroded soil is returned to the soil loss area with soil–landscape restoration. This holistic landscape perspective can be used to develop LISWC systems for other landform types or applied at watershed or regional scales. Future studies are needed for the connections and interactions between individual BMPs, and analysis on the overall economic benefit of an LISWC system.
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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 | 0.000 | 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) | 0.000 | 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".