Ronald D. Lacewell

Optimum Effort and Rent Distribution in the Gulf of Mexico Shrimp Fishery

Traditional methods used to estimate fishing effort that maximizes rent to an open access resource have almost universally assumed all costs are directly proportional to effort. When crews receive a fixed share of gross returns, labor costs are proportional to catch; hence, rent accrues to crews as well as vessel owners under limited entry. A model that allowed costs to be proportional to effort and catch was applied to the Gulf of Mexico shrimp fishery. This study indicates that traditional analysis would result in management schemes that overtax vessels and ignore rent accruing to crews.

An Intraseasonal Dynamic Optimization Model to Allocate Irrigation Water between Crops

A dynamic programming model that allocates irrigations among competing crops, while allowing for stochastic weather patterns and temporary or permanent abandonment of one crop in dry periods, is presented. Fifteen intraseasonal irrigations are allocated between corn and sorghum fields on the southern Texas High Plains. Broad rules of thumb implied by the results suggest irrigating the driest field in any stage unless soil water is close to field capacity on both fields or below wilting point on corn. A crop simulation model is used to reduce the complicated decision rules into simpler strategies with similar net returns.

Economic Implications for the Biological Control of Arundo donax: Rio Grande Basin

Abstract. Giant reed, Arundo donax L., is a large, bamboo-like plant native to the Mediterranean region. It has invaded several thousand hectares of the Rio Grande riparian habitat in Texas and Mexico. The United States Department of Agriculture-Agricultural Research Service (USDA-ARS) is investigating four herbivore insects as potential biological control agents for giant reed. One of the most important reasons for targeting this invasive weed is to reduce its impact on available water supplies, especially in the Rio Grande Basin. This study examined selected economic implications of this program for agricultural water users in the U.S. The research included (a) estimating the value of the water saved (to agricultural purposes) by reduction of giant reed, (b) benefit-cost analyses, (c) regional economic impact analyses, and (d) an estimate of the per-unit life-cycle cost of water saved during a 50-year planning horizon (2009 through 2058). Positive results related to the benefit-cost ratio, economic impact analyses, and competitive results for the per-unit life-cycle cost of saving water are associated with the biological control project for giant reed. The benefit-cost ratio, calculated with normalized prices, indicates

Open-Loop Stochastic Control of Grain Sorghum Irrigation Levels and Timing

4.38 of benefits for every dollar of public investment. According to 2009 results for the economic impact analyses, economic output is

The Edwards Aquifer Water Resource Conflict: USDA Farm Program resource-use incentives?

22,000, value-added is

Economic impact of integrated pest management strategies for cotton production in the Coastal Bend Region of Texas

11,000, and no employment is supported by the water savings from giant reed. Additionally, the per-unit cost of water saved is

BOLL WEEVIL CONTROL STRATEGIES: REGIONAL BENEFITS AND COSTS

44.08, a value comparable to other projects designed to increase water supply for the region. These results indicate this program will have positive net economic implications for the U.S. and the Lower Rio Grande Valley of Texas.

A General Model for Evaluating Agricultural Flood Plains

Crop growth simulation models that consider the soil-plant-atmosphere continuum recently have become an important research tool. Examples of growth simulation models include those for corn (Curry and Chen), cotton (Baker, Hesketh, Duncan), alfalfa (Miles et al.), barley (Kallis and Tooming), wheat (Trenbath), and grain sorghum (Arkin, Vanderlip, Ritchie). This article investigates the utility of the grain-sorghum-growth simulation model of Arkin, Vanderlip, and Ritchie as an irrigation management tool on the Texas High Plains with economic criteria guiding decisions. Most water-use studies (e.g., Swanson and Thaxton; Jensen and Musick; Shipley, Regier, Wehrly) emphasize the need for coordinating irrigation with water requirements of the plant during critical stages of plant development. Yield response attributed to a specific irrigation depends upon several factors, including: (a) amount of soil moisture available at the time of irrigation; (b) stage of the plant development; and (c) interaction effect from previous or subsequent irrigations, or both, which reduce or eliminate moisture stress conditions. Normally, three or four irrigations are applied to grain sorghum in the Texas High Plains to meet water use requirements during the growing season. Applications may vary from only one preplant to as many as six postplant waterings (Shipley and Regier). Increasing concern for the declining groundwater supply and energy costs along with potential energy curtailments in the region emphasize the importance of improved irrigation planning and management. Potential fuel curtailments magnify the already existing degree of risk and uncertainty of farming in areas with low and unstable rainfall. This uncertainty results in production practices that depart from the optimal deterministic input-output combinations, even for risk-averse producers. Previous estimates of economically optimal irrigation water application rates, and estimates of the impact of rising energy costs were primarily based on the assumption that the producer knew in advance the state of the different future environments that would surround him (Casey, Jones and Lacewell; Lacewell; Condra and Lacewell). Climatic, institutional, and economic conditions throughout the production year were considered as known at the beginning of the year. To overcome these limitations, the computerized grain sorghum growth model was modified to consider stochastic situations in weather and/or institu-

Challenges and Opportunities for Water of the Rio Grande

This paper summarizes economic and hydrological analyses of the impacts of the 1990 and 1996 U.S. Department of Agriculture (USDA) farm programs on irrigation water withdrawals from the Edwards Aquifer in south central Texas and on aquifer-dependent spring flows that support threatened and endangered species. Economic modeling, a regional producer behavioral survey, as well as institutional and farm characteristic analyses are used to examine likely irrigation water-use impacts. Hydrologie modeling is used to examine spring flow effects. Study results show that 1990 USDA commodity programs caused producers to require less irrigation water, in turn increasing rather than decreasing aquifer spring flows. Market economic factors are the dominant criteria influencing producer irrigation decisions. Farm-tenure arrangements and aquifer management responsibilities of the Edwards Aquifer Authority indicate that the 1996 Farm Acts PFC payment program will not cause an increase in irrigation withdrawals. Broader actions such as long-term water supply enhancement/conservation programs, dry-year water-use reduction incentives and water markets all provide tools for Edwards water-use conflict resolution. USDA farm programs do not apparently play a material part in the total debate.

Regional Impact of Urban Water Use on Irrigated Agriculture

A long-season (160–180 days) cotton variety with a conventional production system was formerly grown in the Texas Coastal Bend Region. Cotton producers in the region used intensive insecticide applications throughout the growing season and harvested in August or September, and occasionally in October. In general, intensive insecticide applications for boll weevil and fleahopper control destroyed the beneficial insects and spiders. Late-season tobacco budworm infestations were thereby aggravated. These late-season insect infestations were a result of the relatively high rainfall during August and September. Moreover, high rainfall during this time not only interfered with harvest, but also reduced both the yield and quality of cotton (Lacewell et al.).