Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks
文献类型：期刊论文
| 作者 | Li, Hongbin; Hou, Guoxiang; Dakui, Feng; Xiao, Bangding; Song, Lirong; Liu, Yonyding |
| 刊名 | ECOLOGICAL INFORMATICS
 |
| 出版日期 | 2007-06-01 |
| 卷号 | 2期号:2页码:184-192 |
| 关键词 | algal dynamics algal bloom neural network pH sensitivity analysis |
| ISSN号 | 1574-9541 |
| 通讯作者 | Hou, GX, Chinese Acad Sci, Inst Hydrobiol, Wuhan 430072, Peoples R China |
| 中文摘要 | Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration. |
| 英文摘要 | Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration. |
| WOS标题词 | Science & Technology ; Life Sciences & Biomedicine |
| 学科主题 | Ecology |
| 类目[WOS] | Ecology |
| 研究领域[WOS] | Environmental Sciences & Ecology |
| 关键词[WOS] | CROSS-VALIDATION ; MODEL ; BLOOMS ; ANNA |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000249940600015 |
| 公开日期 | 2010-10-13 |
| 源URL | [http://ir.ihb.ac.cn/handle/152342/8402]  |
| 专题 | 水生生物研究所_中科院水生所知识产出（2009年前）_期刊论文 |
| 作者单位 | 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 |
| 推荐引用方式 GB/T 7714 | Li, Hongbin,Hou, Guoxiang,Dakui, Feng,et al. Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks[J]. ECOLOGICAL INFORMATICS,2007,2(2):184-192. |
| APA | Li, Hongbin,Hou, Guoxiang,Dakui, Feng,Xiao, Bangding,Song, Lirong,&Liu, Yonyding.(2007).Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks.ECOLOGICAL INFORMATICS,2(2),184-192. |
| MLA | Li, Hongbin,et al."Prediction and elucidation of the population dynamics of Microcystis spp. in Lake Dianchi (China) by means of artificial neural networks".ECOLOGICAL INFORMATICS 2.2(2007):184-192. |
入库方式： OAI收割
来源：水生生物研究所
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