Pd/a Crsp Eighteenth Annual Technical Report

This study deals with development of decision support tools for warmwater pond aquaculture. Efforts are directed at refining the POND© software and developing a new farm-level decision support tool. Refinements to POND© focus on general issues related to program maintenance, enhancements to the enterprise budgeting tool within POND©, and a task-oriented interface for assisting users in accomplishing specific activities within the tool related to educational and extension application. A brief summary of AquaFarm©, a new aquaculture decision support tool developed in part with PD/A CRSP support, is presented. EIGHTEENTH ANNUAL TECHNICAL REPORT 162 the model optionally generates supplementary feeding schedules. Level 2 models provide a substantially more sophisticated view of pond dynamics, allowing prediction of phytoplankton, zooplankton, and nutrient dynamics (carbon, nitrogen, and phosphorus), in addition to fish growth and water temperature. This modeling level is intended for detailed pond analysis, management optimization, and numerical experimentation. Fish can feed from natural and/or artificial food pools. Consumption of natural food (phytoplankton and zooplankton pools) by fish is predicted on the basis of a resource competition model and also depends on fish appetite. At this level a constant user-specified concentration of pond nitrogen, phosphorus, and carbon is assumed. Mass balance accounting for each of these variables is maintained, allowing estimation of fertilizer requirements necessary to maintain steady-state levels. Both fertilization and feeding schedules are generated by the models. An important aspect of POND© is the ability to incorporate the results from the pond dynamics simulations, with additional information, into an enterprise budget. These budgets allow for the accumulation of various types of costs and incomes, summarized and coupled with interest and depreciation expressions, to assess the overall economic viability of a particular production enterprise. Current efforts for POND© development are focusing on enhancing the economic capabilities of ponds. The first of these is the support of partial budgeting. The second is the inclusion of time-based costs. These can include periodic costs (i.e., costs that recur at specific periodic intervals) and costs that are scheduled to occur only at specific times and with specific durations. The inclusion of such costs has allowed POND© to be used to more directly simulate the mediumto long-term dynamics of production facilities, as well as to facilitate the examination of the economics of facility production during specific production windows. Additional efforts are focusing on creating task-oriented user interfaces. We started this recently with the inclusion of “wizards” for automating key simulation tasks. We are now extending this metaphor for the development of design and analysis tasks. For example, wizards are being developed to size ponds to meet specific production targets under particular climatic and production regimes, provide optimized feeding schedules to hit particular production targets, and develop nutrient budgets for specific production strategies. We will be continuing to develop these wizards over the next year in collaboration with our cooperators. In addition to these activities related to the POND© software, we are releasing this year an additional decision support tool, AquaFarm©. AquaFarm© provides simulation of physical, chemical, and biological unit processes, facilities, and management systems for a broad class of aquaculture systems, including semi-intensive and intensive systems. It incorporates and extends many of the components of the POND© model, including economic analyses but further provides more detailed unit process descriptions and more robust analytical capabilities. It allows simulation of broodfish maturation, egg production, and grow-out of finfish or crustaceans in cage, single pass, serial reuse, recirculation, or solar-algae pond systems. AquaFarm© allows the iterative refinement of design specifications for a production facility by simulating production dynamics with feedback when production goals are not satisfied, allowing users to rapidly fine-tune facility design and management to meet specific criteria. A more complete description of AquaFarm© is given by Ernst et al. (2000).