We conducted three series of experiments in laboratory and natural streams to evaluate effects of various physical factors on seston (particulate organic matter) retention, entrainment, and transport. Results of laboratory experiments showed that substrate characteristics were important in determining retention of all sizes of seston. Retention increased with roughness and substrate complexity. During simulated storms in laboratory streams, seston concentrations were not generally correlated with discharge. However, we found strong correlation between seston concentration and the rate of increase in discharge during rising hydrographs, and, after peak discharge, seston concentration dropped exponentially independent of discharge. Simulated storms conducted in a natural stream channel supported those findings. Results of these experiments and published field studies suggest that existing sediment transport models have little application to seston transport in small streams primarily because of limited availability of seston. During baseflow, seston transport depends on the rate of biological particle generation and retention characteristics of the streambed. Seston transport during storms depends on the rate of increase in discharge, streambed retention, and the availability of particulate organic material on the streambed.

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A multinominal Iogit model was estimated and used to analyze the impact of variousproducer characteristics on the adoption of flow-through and recirculating technology in soft-shelled crab production. Because of the industry's geographic isolation and high turnover rate, data was collected by personal interviews in 1991. The results suggest that increased adoption might be fostered by targeting education programs towards full time, family operated businesses in nontraditional production regions. However, development of effective education programs may be hindered by the lack of a significant relationship between producer adoption decisions and the information provided by university or extension personnel.

For simulation to be truly useful for investigating many problems in agricultural economics, nonsimplifying optimization techniques need to be employed. General methods for simulation optimization that do not inhibit system characterization or analysis are available, and they would appear to provide much of the mathematical and optimizing rigor demanded by economists. This paper describes the theory and algorithm of a robust and efficient simulation optimization approach, the Complex Method. An example of implementing the algorithm is illustrated using a pest management problem.

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