Agronomic and economic effects of wetlands on crop yields using precision agriculture data
Bibliographic record
Abstract
Wetland drainage has become an increasingly important conservation issue in the Prairie Pothole region of North America. Financial incentives for annual crop production have driven wetland drainage for decades, and the removal of wetlands has detrimentally impacted key wetland ecosystem services such as wildlife habitat and carbon sequestration. Past studies which model the farmer's decision to drain wetlands often operate on the assumption that drained wetlands will produce similar yields to upland regions of the field. Our objective is to estimate the effects of wetlands and their buffer zones on crop yields, farm financial performance, and incentives for wetland drainage in the Prairie Pothole Region. We combine precision yield data and detailed wetland mapping data from 36 fields in the Black and Dark Brown soil zones of Saskatchewan, Canada to estimate the agronomic impacts of wetlands and their buffer areas on crop yields. Then, we incorporate these yield effects into a farm accounting model with three wetland drainage scenarios to estimate the annual per cultivated acre net benefits of wetland drainage in the study area, and compare these results to those estimated without wetland yield effects. We find that yields in wetland basins are relatively lower than the field's average yield, with substantial variability with respect to crop type, soil zone, and annual precipitation. Wetland drainage can mitigate these yield effects, but yields in drained wetland basins still fail to meet the field average yield. These yield effects can extend more than 50 m beyond the wetland boundary. We find that these effects substantially impact the net benefits of wetland drainage. The returns from wetland drainage increase when yield effects are considered. On average, full wetland drainage within the study area increases net benefits by $17 to $33 per cultivated acre relative to full wetland restoration. The results demonstrate the importance of considering wetland and buffer zone yield effects in wetland drainage decisions, improve our understanding of wetland costs, and potentially inform policy development and the design of incentives for wetland conservation in agricultural landscapes. • The agronomic effects of wetlands have rarely been considered in previous studies of wetland conservation costs in the PPR. • Precision yield and wetland mapp data is used to estimate the effects of wetlands on crop yields and farm finances. • Wetlands and their buffer zones have substantial negative effects on crop yields in the Prairie Pothole Region. • Wetland drainage can mitigate these yield effects, providing further incentive for drainage in the PPR. • The financial incentives for wetland drainage vary with respect to soil zone, technology use, and annual precipitation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".