Long-term Land Use and Land Cover Changes Affected by the Conservation Reserve Program in the Minnesota River Valley
Bibliographic record
Abstract
The Conservation Reserve Program (CRP) is a cost-share and rental payment program signed into law byPresident Reagan in 1985 and administered by the Farm Service Agency (FSA) under the United StateDepartment of Agriculture (USDA). CRP aims to counteract erosion and protect the environment by encouragingagricultural landowners to convert highly erodible cropland and other environmentally sensitive lands to nativeor alternative permanent vegetative cover through the implementation of 10-year contracts paying annual rents.CRP has been actively implemented since the enactment of the Food Security Act of 1985. Re-authorized byCongress in 1996 with major modifications, the CRP has been renewed with minor alterations several times. In1998, the joint state/federal Conservation Reserve Enhancement Program (CREP) targeted the long-termretirement of an additional 40,469 ha (100,000 acres) of agricultural land in the Minnesota River basin toenhance water quality and wildlife habitat through permanent conservation easements.This research examines land use change from 1985 to 2013 in the Minnesota River Valley beginning with an eraof no long-term set-asides to the current era with two active long-term set-aside conservation reserve programs.Multi-temporal remote sensing images from 1985, 1995, 2005 and 2013 were analyzed to map the land usechanges in response to the CRP policy alterations. The results revealed more than 36,000 ha (89,000 acres)cropland have been converted to grassland or forest during this 28-year span. A persistent drop in croplandoccurred in spite of rising corn and soybean prices since 2002 associated with Minnesota’s biofuel industry andincreased foreign demand for these commodities, which indicates that the long-term nature of the CRP andCREP contracts are critical for maintaining the conversions of cropland to grassland or forest cover whileproviding stable farm income.
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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 | 0.001 | 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".