| Silvicultural soil loss control has an impact on economic returns from forestry. A model presented here is a linear programming (LP) that maximizes the annual equivalent value from timber growing subject to soil loss and land availability in various soil groups and management regimes. The model shows the impact on income caused by efforts to comply with federal and state water acts by restricting soil loss. Soil loss is estimated using the Universal Soil Loss Equation. Results show that as soil loss restrictions get more stringent, the opportunity cost of reducing one more unit of soil loss from forestry practices increases. Analysis of various soil loss abatement measures, such as soil loss restriction standards, tax, and subsidy have been carried out and results compared. The results suggest there is little difference in the way forests would be managed with the imposition of taxes and subsidy at lower rates, but the difference may be significant at higher tax/subsidy rates.; In the second part of the analysis, efficiency and equity aspects of soil conservation are the main focus. The soil conservation measures are usually drawn up at the individual state level, and designed to apply uniformly across many types of forest land. That is, many environmental regulations and guidelines and many best management practices (BMPs) are not specified by soil type, physiographic region or other land classification. This analysis examines the impact of such a uniform guide in regions with forest lands of different productivity and erodibility classifications. The model shows that different soil conservation methods and standards have differing impacts depending on the region. On a county level, a uniformly applied soil conservation tends to most affect low productive and highly erosive forest lands more severely. A differentially applied soil conservation affects both low productive and highly erosive forest land equitably, but it is less efficient.; In the last part, stochastic nature of soil loss was incorporated into the model by using chance-constrained procedure. The analysis was done for 80, 90, and 95 percent confidence limits using a post-optimization procedure. |
