Environmental and economic implications of land management changes in agricultural watersheds
Bibliographic record
Abstract
This research developed and applied a GIS-based modelling framework that integrated a hydrologic model and a farm economic model to examine the environmental and economic implications of land management changes in terms of potential crop rotation in the Fairchild Creek watershed in southwestern Ontario. Model simulations that incorporated annual object-oriented landuse/landcover classifications revealed that both sediment loads and cropping returns are variable across space and time and that these patterns are not comparable. Furthermore, the spatial distribution of sediment load to economic output ratios are relatively stable and concentrated in areas with high sediment delivery or low crop-based economic output. These results provide practical references for watershed management agencies to understand the spatial and temporal dimensions of the tradeoffs between environmental impacts of agricultural nonpoint source pollution and economic output. Therefore, based on identifying high damage to benefit ratios, decision makers may prioritize areas to implement agricultural conservation practices such as conservation tillage and riparian buffer strips.
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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".