Background
Objectives
Significance
Anticipated Benefits
Beneficiaries
Methods
Deliverables
Schedule
References

Background

Predictive modeling can be a useful tool for making decisions relevant to aquaculture development (Pillay, 1992). Previous pond modeling and decision support activities have focused on individual pond (e.g., Piedrahita, 1990) or facility-level analysis (e.g., Nath et al., 1995). Analyzing the role of pond aquaculture as a component of larger or 'macro-level' systems (Fig. 2) requires consideration of issues beyond those relating to pond management per se. For example, the UC Davis component of the DAST is involved in the development of an agroecological model to examine material flow between terrestrial agriculture and pond aquaculture activities. Similarly, the OSU-DAST is presently involved in a collaborative effort with the FAO to assess aquaculture potential and resource requirements in different agroecological zones by the use of POND^© models. The POND^© framework supports capabilities for simulating arbitrary objects or entities (e.g., ponds, fish lots); these capabilities can be extended to enable simulation of terrestrial crops. Because POND^© already considers the effects of the biophysical environment on pond production and includes economic analysis functionality, linkages between aquacultural and associated agricultural systems models will enable considerations of potential synergies (e.g., farm yields per unit of fertilizer used) and conflicts of resource use (e.g., water, fertilizers) between the two systems, and the assessment of economic benefits of alternate production systems based on local conditions. Such analyses will ultimately aid the design and implementation of sustainable farming systems. Macro-level systems models must also take into account the socioeconomic implications of new or improved pond aquaculture and/or integrated farming technologies, if long-term adoption of such technologies is to occur.

Objectives

1) To incorporate agroecological models of integrated farms into the POND^© framework,

2) To enhance the POND^© framework for macro-level systems analysis,

3) To develop capabilities for conducting socioeconomic analyses in conjunction with macro-level systems analysis, and

4) To examine the combined use of macro-level systems models, economic analyses and socioeconomic tools as a mechanism for studying the interactions between pond aquaculture and the surrounding social and biophysical environment.

Significance

Integrating results from macro-level systems models, economic and socioeconomic analysis tools will allow for improved understanding of the interactions between pond aquaculture and its surrounding environment.

Anticipated Benefits

Improved tools for designing integrated farming systems and assessing the impacts of pond aquaculture development.

Beneficiaries

Integrated farming researchers, socioeconomic scientists, technical assistance agencies, and international donors.

Methods

POND^© will be modified to include terrestrial crop models developed by the UC DAST as an additional simulation object. This object will be linked to other capabilities already available in the POND^© software (e.g., fertilizer optimization and economic analyses tools) to enable simulations of integrated farms to be conducted. Additional decision support functionality will be provided in POND^© to perform constraint analysis of different factors influencing farm production. Simulation output from the pond aquaculture and terrestrial agriculture components will be automatically fed to the economic analyses package within POND^© thereby enabling "what-if" scenarios to be explored. Results of such simulations will be examined by the use of socioeconomic analysis tools to predict constraints on resource use and availability, improved productivity, and possible shifts in farming practices due to the perception of a higher value (economically and/or culturally) product.

Deliverables

A terrestrial crop modeling component integrated with pond facility-level models and the economic analysis package in the POND^© framework; a report summarizing results obtained by integrating macro-level systems model output and socioeconomic tools.

Schedule

1/1/97 to 4/30/98

Report Submittal: 4/30/98

References

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Bolte, J. P., S. S. Nath, and D.H. Ernst. 1995. POND^©: A decision support system for pond aquaculture. Twelfth Annual Administrative Report, PD/A CRSP, Corvallis, OR:48-67.

Boyd, C. E. 1994. Bottom soils, sediment and pond aquaculture. Chapman and Hall, New York. 348pp.

Colman, J. A. and A. R. Jacobson. 1991. Review and development of aquaculture models for predicting solute flux at the sediment-water interface. In: D. E. Brune and J. R. Tomasso (Editors). Aquaculture and Water Quality, Advances in World Aquaculture, Volume 3, The World Aquaculture Society, Baton Rouge, LA: 460-488.

Ernst, D. H., J. P. Bolte, and S. S. Nath. 1993. A decision support system for finfish aquaculture. In: J-K. Wang (Editor), Techniques for Modern Aquaculture Symposium: Proceedings of an Aquacultural Engineering Conference, 21-23 June 1993, Spokane, WA. ASAE, St. Joseph, MI.

Jorgensen, S.E., L. Kamp-Nielsen, and H. F. Mejer. 1982. Comparison of a simple and a complex sediment phosphorus model. Ecol. Modeling 16:99-124.

Kamp-Nielsen, L. 1975. A kinetic approach to the aerobic sediment-water exchange of phosphorus in Lake Esrom. Ecol. Modeling 1:153-160.

Michalewicz, Z. 1992. Genetic algorithms + Data Structures = Evolution Programs. Springer-Verlag. 250pp.

Nath, S. S., J. P. Bolte, and D. H. Ernst. 1995. Decision support for pond aquaculture planning and management. Sustainable Aquaculture '95, PACON International, 11-14 June 1995, Honolulu, Hawaii.

Piedrahita, R. H. 1990. Calibration and validation of TAP, an aquaculture pond water quality model. Aquacultural Engg. 9:75-96.

Pillay, T. V. R. 1992. Aquaculture and the environment. Fishing News Books, Oxford, England. 189pp.

Schroeder, G. L. and E. Berner-Samsonov. 1986. The pond ecosystem and its control. In: R. Billard and J. Marcel (Editors). Aquaculture of cyprinids, INRA, Paris:243-256.

Smits, J. G. C. and D.T. van der Molen. 1993. Application of SWITCH, a model for sediment-water exchange of nutrients, to Lake Veluwe in The Netherlands. Hydrobiologia 253:281-300.

Tilman, D. 1982. Resource competition and community structure. Princeton University Press, NJ. 296 pp.