Application of Bayesian network including Microcystis morphospecies for microcystin risk assessment in three cyanobacterial bloom-plagued lakes, China
文献类型：期刊论文
| 作者 | Shan, Kun3,5 ; Shang, Mingsheng3,5; Zhou, Botian3,5; Li, Lin4; Wang, Xiaoxiao3; Yang, Hong2; Song, Lirong1,4
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| 刊名 | HARMFUL ALGAE
 |
| 出版日期 | 2019-03-01 |
| 卷号 | 83页码:14-24 |
| 关键词 | Bayesian network Cyanobacterial blooms Microcystis Eutrophication Microcystin Climate warming Lake Taihu Lake Chaohu Lake Dianchi |
| ISSN号 | 1568-9883 |
| DOI | 10.1016/j.hal.2019.01.005 |
| 通讯作者 | Shan, Kun(shankun@cigit.ac.cn) ; Song, Lirong(lrsong@ihb.ac.cn) |
| 英文摘要 | Microcystis spp., which occur as colonies of different sizes under natural conditions, have expanded in temperate and tropical freshwater ecosystems and caused seriously environmental and ecological problems. In the current study, a Bayesian network (BN) framework was developed to access the probability of microcystins (MCs) risk in large shallow eutrophic lakes in China, namely, Taihu Lake, Chaohu Lake, and Dianchi Lake. By means of a knowledge-supported way, physicochemical factors, Microcystis morphospecies, and MCs were integrated into different network structures. The sensitive analysis illustrated that Microcystis aeruginosa biomass was overall the best predictor of MCs risk, and its high biomass relied on the combined condition that water temperature exceeded 24 degrees C and total phosphorus was above 0.2 mg/L. Simulated scenarios suggested that the probability of hazardous MCs (>= 1.0 mu g/L) was higher under interactive effect of temperature increase and nutrients (nitrogen and phosphorus) imbalance than that of warming alone. Likewise, data-driven model development using a naive Bayes classifier and equal frequency discretization resulted in a substantial technical performance (CCI = 0.83, K = 0.60), but the performance significantly decreased when model excluded species-specific biomasses from input variables (CCI = 0.76, K = 0.40). The BN framework provided a useful screening tool to evaluate cyanotoxin in three studied lakes in China, and it can also be used in other lakes suffering from cyanobacterial blooms dominated by Microcystis. |
| 资助项目 | National Natural Science Foundation of China[51609229] ; National Natural Science Foundation of China[41701247] ; Chongqing Science and Technology Commission[cstc2017jcyjAX0241] ; National Key Scientific and Technological Project of China[2014ZX07104-006] ; National Basic Research Program of China[2008CB418006] |
| WOS研究方向 | Marine & Freshwater Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:000470940300002 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/8212]  |
| 专题 | 大数据挖掘及应用中心 |
| 通讯作者 | Shan, Kun; Song, Lirong |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Univ Reading, Dept Geog & Environm Sci, Reading RG6 6AB, Berks, England 3.Chinese Acad Sci, CAS Key Lab Reservoir Environm, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China 4.Chinese Acad Sci, Inst Hydrobiol, State Key Lab Freshwater Ecol & Biotechnol, Wuhan 430072, Hubei, Peoples R China 5.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Big Data Min & Applicat Ctr, Chongqing 400714, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shan, Kun,Shang, Mingsheng,Zhou, Botian,et al. Application of Bayesian network including Microcystis morphospecies for microcystin risk assessment in three cyanobacterial bloom-plagued lakes, China[J]. HARMFUL ALGAE,2019,83:14-24. |
| APA | Shan, Kun.,Shang, Mingsheng.,Zhou, Botian.,Li, Lin.,Wang, Xiaoxiao.,...&Song, Lirong.(2019).Application of Bayesian network including Microcystis morphospecies for microcystin risk assessment in three cyanobacterial bloom-plagued lakes, China.HARMFUL ALGAE,83,14-24. |
| MLA | Shan, Kun,et al."Application of Bayesian network including Microcystis morphospecies for microcystin risk assessment in three cyanobacterial bloom-plagued lakes, China".HARMFUL ALGAE 83(2019):14-24. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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