| Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network | |
| Hou, Guoxiang; Li, Hongbin; Recknagel, Friedrich; Song, Lirong; Song, LR, Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China | |
| 2006-12-01 | |
| Source Publication | JOURNAL OF FRESHWATER ECOLOGY
 |
| ISSN | 0270-5060 |
| Volume | 21Issue:4Pages:639-647 |
| Abstract | A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms.; A radial basis function neural network was employed to model the abundance of cyanobacteria. The trained network could predict the populations of two bloom forming algal taxa with high accuracy, Nostocales spp. and Anabaena spp., in the River Darling, Australia. To elucidate the population dynamics for both Nostocales spp. and Anabaena spp., sensitivity analysis was performed with the following results. Total Kjeldahl nitrogen had a very strong influence on the abundance of the two algal taxa, electrical conductivity had a very strong negative relationship with the population of the two algal species, and flow was identified as one dominant factor influencing algal blooms after a scatter plot revealed that high flow could significantly reduce the algal biomass for both Nostocales spp. and Anabaena spp. Other variables such as turbidity, color, and pH were less important in determining the abundance and succession of the algal blooms. |
| Subtype | Article |
| Keyword | Blue-green-algae Nakdong River Cyanobacteria Prediction Blooms Murray Korea |
| Department | Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China; Huazhong Univ Sci & Technol, Dept Ocean Sci & Engn, Wuhan 430074, Peoples R China; Univ Adelaide, Sch Earth & Environm Sci, Adelaide, SA 5005, Australia |
| Subject Area | Ecology ; Limnology |
| WOS Headings | Science & Technology ; Life Sciences & Biomedicine |
| Indexed By | SCI |
| Language | 英语 |
| WOS Research Area | Environmental Sciences & Ecology ; Marine & Freshwater Biology |
| WOS Subject | Ecology ; Limnology |
| WOS ID | WOS:000242201300011 |
| WOS Keyword | BLUE-GREEN-ALGAE ; NAKDONG RIVER ; CYANOBACTERIA ; PREDICTION ; BLOOMS ; MURRAY ; KOREA |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.ihb.ac.cn/handle/152342/8776 |
| Collection | 期刊论文 |
| Corresponding Author | Song, LR, Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China |
| Affiliation | 1.Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China 2.Huazhong Univ Sci & Technol, Dept Ocean Sci & Engn, Wuhan 430074, Peoples R China 3.Univ Adelaide, Sch Earth & Environm Sci, Adelaide, SA 5005, Australia |
| Recommended Citation GB/T 7714 | Hou, Guoxiang,Li, Hongbin,Recknagel, Friedrich,et al. Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network[J]. JOURNAL OF FRESHWATER ECOLOGY,2006,21(4):639-647. |
| APA | Hou, Guoxiang,Li, Hongbin,Recknagel, Friedrich,Song, Lirong,&Song, LR, Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China.(2006).Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network.JOURNAL OF FRESHWATER ECOLOGY,21(4),639-647. |
| MLA | Hou, Guoxiang,et al."Modeling phytoplankton dynamics in the River Darling (Australia) using the radial basis function neural network".JOURNAL OF FRESHWATER ECOLOGY 21.4(2006):639-647. |
| Files in This Item: | ||||||
| File Name/Size | DocType | Version | Access | License | ||
| Modeling phytoplankt（525KB） | 开放获取 | -- | View Application Full Text | |||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment