| CHO Hong-Yeon,PARK Kwang-Soon,KIM Sung. 2016. Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data. Acta Oceanologica Sinica, 35(2):39－45 |
| Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data |
| Global parameter estimation of the Cochlodinium polykrikoides model using bioassay data |
| Received:July 20, 2015 Revised:September 21, 2015 |
| DOI：10.1007/s13131-016-0806-0 |
| Key words:global and local estimation gain and loss parameters Cochlodinium polykrikoides bioassay data model performance |
| 中文关键词: global and local estimation gain and loss parameters Cochlodinium polykrikoides bioassay data model performance |
| 基金项目:The part of the project “Development of Korea Operational Oceanographic System (KOOS), Phase 2”, funded by the Ministry of Oceans and Fisheries, Korea; the part of the project entitled “Cooperative Project on Korea-China Bilateral Committee on Ocean Science”, funded by the Ministry of Oceans and Fisheries, Korea and China-Korea Joint Research Ocean Research Center. |
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| Abstract: |
| Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide (a.k.a algal bloom) model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%-50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required. As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions. |
| 中文摘要: |
| Cochlodinium polykrikoides is a notoriously harmful algal species that inflicts severe damage on the aquacultures of the coastal seas of Korea and Japan. Information on their expected movement tracks and boundaries of influence is very useful and important for the effective establishment of a reduction plan. In general, the information is supported by a red-tide (a.k.a algal bloom) model. The performance of the model is highly dependent on the accuracy of parameters, which are the coefficients of functions approximating the biological growth and loss patterns of the C. polykrikoides. These parameters have been estimated using the bioassay data composed of growth-limiting factor and net growth rate value pairs. In the case of the C. polykrikoides, the parameters are different from each other in accordance with the used data because the bioassay data are sufficient compared to the other algal species. The parameters estimated by one specific dataset can be viewed as locally-optimized because they are adjusted only by that dataset. In cases where the other one data set is used, the estimation error might be considerable. In this study, the parameters are estimated by all available data sets without the use of only one specific data set and thus can be considered globally optimized. The cost function for the optimization is defined as the integrated mean squared estimation error, i.e., the difference between the values of the experimental and estimated rates. Based on quantitative error analysis, the root-mean squared errors of the global parameters show smaller values, approximately 25%-50%, than the values of the local parameters. In addition, bias is removed completely in the case of the globally estimated parameters. The parameter sets can be used as the reference default values of a red-tide model because they are optimal and representative. However, additional tuning of the parameters using the in-situ monitoring data is highly required. As opposed to the bioassay data, it is necessary because the bioassay data have limitations in terms of the in-situ coastal conditions. |
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