|Title||Nitrogen transformations and fluxes in fish ponds: a modelling approach|
|Source||Wageningen University. Promotor(en): E.A. Huisman; J.A.J. Verreth; M.C.J. Verdegem. - S.l. : S.n. - ISBN 9789058084019 - 185|
Aquaculture and Fisheries
|Publication type||Dissertation, internally prepared|
|Keyword(s)||visteelt - aquacultuur - visvijvers - stikstof - stikstofretentie - stikstofkringloop - stikstofmetabolisme - visvoeding - modellen - fish culture - aquaculture - fish ponds - nitrogen - nitrogen retention - nitrogen cycle - nitrogen metabolism - fish feeding - models|
|Categories||Aquaculture Nutrition and Feeding|
Nitrogen is a key element in aquatic environments, and in Aquaculture it is an important pond management variable. In current aquaculture research two important goals are to maintain the water quality within the system, and to improve the retention of nutrients applied to the system in order to minimize the discharge. The principal objectives of this study were to integrate the information available of nitrogen processes in fish ponds into a predictive model, and to investigate further the nitrogen dynamics between the water, the sediments and the biota present in this systems. First, a nitrogen balance in fish ponds was followed along a growing cycle; by combining estimates of the deposition rates of uneaten feed, faeces and dead phytoplankton with measurements of nitrogen accumulation in the sediment, the rate of decomposition of organic matter in the sediment was evaluated. The cumulative recovery at the end of the experiment was almost 100%, meaning that the nitrogen budget in the system studied can be fully explained without any consideration of nitrogen volatilisation, due to either denitrification or ammonia volatilisation. The interactions between various N-species are complex and difficult to integrate. A model that calculates the amounts of various N-compounds in the water column and in the sediment was constructed, and used to gain insight into the relative importance of transformation processes between the various N-compounds. The model was divided into three modules: fish, phytoplankton and sediment-water.
All concentrations of the various N-species present were simulated well except the N retained in organic matter in the sediment. To improve our understanding of the bottom organic matter dynamics, and make the model a more comprehensive predictive tool, an estimation of the principal sources of organic matter that accumulate in fish pond bottoms was assessed. Organic matter accumulation in fish ponds was quantified, and the data was used to construct, to calibrate and to validate a dynamic simulation model of organic matter deposition/decomposition in fish ponds. Besides, the rates of sedimentation and resuspension were measured along a growing cycle, following the influence of nutrient input, water parameters, fish biomass and fish size on these processes. Using a dilution analysis method to differentiate between sedimented and resuspended particles, sedimentation and resuspension rates were calculated. The rate of material collected in sediment traps increased from 88.5 to 330 g/m 2 per day along the growing cycle, but the relative resuspension did not change significantly, being always in the range of 42 to 47% of the total collected material. The processes of sedimentation of organic matter and resuspension were included in the original model. The proportion of three principal sources of organic matter that accumulate in the pond bottom were also included as parameters of the sedimentation process. A logistic equation relating the rate of resuspension and the fish biomass was calculated; and seepage, as a potential loss of nitrogen from the system, was also considered. The additions to the model represented a substantial improvement to model simulations.