Threats to agriculture at the extensive and intensive margins : economic analyses of selected land-use issues in the U.S. West and British Columbia
Bibliographic record
Abstract
Key WordsAgriculture-environment interactions, economic modelling, sage grouse, yellow starthistle, urban-rural fringe, Geographic Information Systems (GIS), farmland conservation, direct marketingAgricultural land uses are frequently challenged by competing land demands for urban uses and for nature. Decisions made by private operators at the natural (extensive) and urban (intensive) margins of land use may not be socially desirable due to the externalities and public goods associated with agricultural land use and production. The objective of this research is to inform and determine the economic implications of land use policies and decisions in two agricultural systems – (1) rangeland of the arid U.S. west, and (2) the urban fringe of British Columbia, Canada – where competition for land use and associated spillovers threaten long-term agricultural sustainability. This research uses econometric methods and Geographic Information Systems (GIS) to accomplish this goal.At the extensive margin, we address an issue where wildlife conservation interests challenge agricultural range uses in Nevada and another where invasive weeds reduce grazing productivity in California. We investigate the factors influencing the decline of greater sage grouse (Centrocercus urophasianus) populations and, using regression analysis, find that annual weather variations are dominant. Still there is some evidence that cattle grazing negatively affects sage grouse populations. We assess agricultural losses and damages due to yellow starthistle (Centaurea solstitialis L.) by using a survey administered to ranchers. Data collected included infestation rates, loss of forage quality and control efforts. Total state-wide losses of livestock forage value are calculated at 6-7% of the annual harvested pasture value.Further, at the intensive margin, this research explores the economic implications of the Agricultural Land Reserve (ALR) in southwestern British Columbia. GIS technology is used to assemble spatial data of farmland near the city of Victoria. Hedonic models determine spatial, farm type and ALR protection impacts on farmland prices from 1974 through 2008, incorporating a total of 2211 parcel sales into the analysis. We find that ALR zoning reduced protected land prices over time, even though prices were impacted more by urban than agricultural production factors. Next, we analyze ALR exclusion applications from 1974 through 2006 using a logit regression model of re-zoning decisions, and find that, although approvals became more likely over time, agricultural capability is a key determinant in exclusion decisions. Finally, we explore the impact of niche- and direct-marketing on farm economic sustainability. Among farms surveyed, the majority (>80%) of farm area was devoted to vegetable and berry production, and more than 50% of total sales took place on-farm. Production intensity (gross revenue per unit of land) is positively related to recent farm investments, crop diversity, and greenhouse or nursery operations; and negatively related to university education, female operators, farm area and agri-tourism. Results suggest that direct marketing could improve long-term agricultural sustainability in this region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".