Note: Schedule has been revised. See Addendum to the Ninth Work Plan

Collaborating Institutions
Oregon State University

John Bolte
Marion McNamara

University of Arkansas at Pine Bluff

Steve Killian

Cooperating Institution
University of Georgia

Shree Nath

Objectives
1) To modify previously developed fish growth models so as to enable simulation of population growth of multiple fish lots in pond environments.
2) To develop methods for estimating fish biomass in ponds that are stocked and harvested at various time intervals in continuous production systems.
3) To implement software support for inventory management of fish stocks in operational farms.
4) To provide training to farmers on the use of decision support software for routine pond management.

Significance
Commercial, large-scale pond aquaculture operations (e.g., catfish, tilapia, and shrimp) are increasingly dependent on continually supplying fish to markets or to processors. Common to these operations is the practice of multiple stocking and harvesting, which results in several fish lots in a pond at any given time. Each lot tends to grow as a distribution (in terms of fish weights) because of genetic factors, sex differences, food competition, and behavioral changes. Distribution profiles of individual lots are also modified as a result of selective harvest practices (e.g., grading and sorting, and high-grade harvesting). Our previous growth modeling efforts (e.g., Nath, 1996; Nath and Bolte, 1998) assumed that all fish in a particular lot grew uniformly. Consequently, the POND^© software currently simulates mean fish weight for a given lot over time. The proposed study will involve refinement of POND^© models to enable prediction of fish weight distributions over time. This effort will draw upon current PD/A CRSP research at the University of California at Davis as well as previous work on modeling fish and shrimp distributions in ponds (e.g., Griffin et al., 1981; Cuenco et al., 1985; Leung and Shang, 1989). Methods will also be developed to estimate total fish biomass of multiple lots in ponds at different time intervals. Parameterization of the population growth models will be accomplished for tilapia (using CRSP data) and for channel catfish (using data from growth experiments and on-farm trials in the Southern US). Similar parameterization for shrimp will be undertaken in the future.

Users of the POND^© software have requested support for inventory management of fish lots. It is anticipated that addition of the above functionality within a decision support framework will be valuable to farmers in the context of accurately estimating fish biomass, scheduling pond harvests, and assessing feed conversion efficiency. Modifications to POND^© are also expected to be useful to extension agents and managers interested in projecting farm performance and assessing production risks.

Another important component of the proposed work is the training activity, which will involve a workshop to familiarize US farmers with application of pond management software developed by the PD/A CRSP. The workshop will be organized by the Education Development Component of the CRSP.

The proposed study falls primarily within the area of Social and Economic Aspects identified in the PD/A CRSP Continuation Plan 1996-2001. Specifically, the work is relevant to the Decision Support Systems research theme, and should generate recommendations that would assist farmers both overseas and in the US to optimize scheduling operations and fish supply to markets.

Anticipated Benefits
The proposed study is expected to result in the following benefits:

1) Models for projecting fish weight distributions over time, and estimating harvest events
2) Improved capabilities for managing multiple fish lots and their distributions in ponds
3) Support for inventory management of ponds and lots in existing facilities
4) Improved support for economic analysis of commercial pond operations
5) Farmers trained to apply decision support software for real-time management

Research Design
Activities proposed in this study include the following:

1) Models for Size Distribution Analysis: This activity will primarily involve refinements of the POND^© bioenergetics model to enable analysis of fish weight distributions in ponds. Refinements will include definition of size classes (bins) within statistical distributions, and capabilities of simulating differential fish growth (within and among bins) for individual lots between stocking and harvest intervals. Differential growth will be modeled as a function of both intrinsic factors (e.g., competition for food resources) and extrinsic factors (e.g., harvest events).
2) Decision Support for Scheduling Harvest Operations and Assessing Economic Outcomes: This activity will involve development of user interfaces and decision pathways to enable farmers to prescribe multiple stocking/harvest schedules for ponds, and to be able to interactively run various scenarios that result in economically optimal production. Economic analysis will be accomplished by linking the present enterprise budgeting functionality to the management scenarios prescribed by the user.
3) Inventory Management: This activity will involve considerable refinement of the databases in POND^© to enable farmers to enter and edit multiple stocking/harvest, feeding rate, and feed conversion data relevant to fish lots in ponds located at their facility. Capabilities will also be developed to enable farmers to modify these data in other types of software (e.g., spreadsheets) that they use on a routine basis. Finally, support will provided for farmers to manually modify predicted statistical distributions of fish weights based on harvest data.
4) Farmer Training: This activity will involve the development of training materials for a workshop on the use of software developed for size distribution and inventory management, coordination of the workshop (to be conducted at the University of Arkansas at Pine Bluff), and evaluation of software and training materials by farmers.

Regional Integration
Modifications to the POND^© software should be of benefit to users in all the CRSP sites. In terms of the level of effort among the four CRSP regions, it is anticipated that the study will be distributed evenly.

Schedule
Timelines for the proposed study and lead institutions for various activities are summarized in Table 1.

Report Submission
Quarterly progress reports and an annual report will be submitted consistent with the PD/A CRSP timelines for report submission.

References
Cuenco, M.L., R.R. Stickney, and W.E. Grant, 1985. Fish bioenergetics and growth in aquaculture ponds: III. Effects of intraspecific competition, stocking rate, stocking size and feeding rate on fish productivity. Ecol. Modelling, 28:73-95.
Griffin, W.L., J.S. Hanson, R.W. Brick, and M.A. Johns, 1981. Bioeconomic modeling with stochastic elements in shrimp culture. J. World Maricult. Soc., 12:94-103.
Leung, P. and Y.C. Shang, 1989. Modeling prawn production management system: A dynamic Markov decision approach. Agricultural Systems, 29:5-20.
Nath, S.S. 1996. Development of a decision support system for pond aquaculture. Ph.D. dissertation, Corvallis, Oregon: Oregon State University. 273 pp.
Nath, S.S. and J.P. Bolte, 1998. Advances in the POND© software: Wizard development and model refinements. In: D. Burke, J. Baker, B. Goetze, D. Clair, and H. Egna (Editors), Fifteenth Annual Technical Report, Pond Dynamics/Aquaculture CRSP, Oregon State University, Corvallis, OR, pp. 44-54.

Table 1. Timelines for project activities (OSU = Oregon State University; UAPB = University of Arkansas at Pine Bluff).

Activity	Institutions	Timeline
Models for Size Distribution Analysis	Lead: OSU Support: UAPB	July 1, 1988 to June 30, 1999
Decision Support for Scheduling Harvest Operations and Assessing Economic Outcomes	Lead: OSU Support: UAPB	January 1, 1999 to December 31, 1999
Inventory Management	Lead: OSU	July 1, 1999 to June 20, 2000
Farmer Training	Lead: OSU	May 2000