基于赤潮控制要素识别的近海富营养化压力指数研究
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摘要
鉴于赤潮发生影响要素之间一般性逻辑关系模糊不清,且缺乏表征关键控制要素之间量化关系的解析式,造成当前赤潮预测预警与防控间关系不紧密甚至相脱节。为将二者密切连接,本文利用胶州湾1982—2015年的调查数据,在解析富营养化和赤潮发生关键控制要素基础上,建立了应用于赤潮预测预警的复合富营养化压力指数(compoundeutrophicationindex,CEI),同时将CEI应用于长江口赤潮高发区海域验证。结果表明,胶州湾赤潮发生关键控制要素有14种,CEI评价结果不仅与chl a吻合度较高(相似性指数为0.86),而且与赤潮发生时间匹配度较好(达93%),与统计方法预测预警准确度相当,其空间匹配度达77%,与生态动力学模型预测预警准确度相当。将CEI应用于长江口赤潮高发区,时间上与chl a吻合度(相似性指数)为0.74,达到较高的一致性;空间上与chl a吻合度(Kappa系数)为0.25,达到一般一致性。由于海域的特殊性,关键控制要素的遗失可能是一致性偏低的主要原因,未来研究基于长江口赤潮高发区进行CEI构建可能使问题改善。
The current forecasting and prevention methods of harmful algal bloom(HAB) are disjointed due to the ambiguity between the factors and the lack of a quantitative analysis. To connect them, this study established a compound eutrophication index(CEI) that can both forecast and reflect the relationship between factors based on the statistics calculated during 1982—2015 in Jiaozhou Bay. Meanwhile, CEI was applied to the Yangtze River estuary. Results showed that the CEI includes 14 key control factors. A higher degree of agreement was observed between CEI and chl a(SI = 0.86)than that of the current eutrophication method. The accuracy of CEI and the HAB occurrence time reached almost 93%,which was equivalent to that obtained from the statistical methods, and the spatial matching degree between CEI and HAB distribution was 77%, which was equivalent to that derived from the ecological dynamic model considering grade-3 as standard. After adjusting for regional factors, the similarity index(SI) of CEI and chl a was 0.74 in the Yangtze River estuary, reaching a high consistency. The spatial coincidence(kappa coefficient) of CEI and chl a was 0.25, reaching moderate and general consistency. The general consistency may have been caused by the loss of key control factors due to the particularity of the sea area. Future studies based on CEI construction in the Yangtze River estuary may solve this issue.
The current forecasting and prevention methods of harmful algal bloom(HAB) are disjointed due to the ambiguity between the factors and the lack of a quantitative analysis. To connect them, this study established a compound eutrophication index(CEI) that can both forecast and reflect the relationship between factors based on the statistics calculated during 1982—2015 in Jiaozhou Bay. Meanwhile, CEI was applied to the Yangtze River estuary. Results showed that the CEI includes 14 key control factors. A higher degree of agreement was observed between CEI and chl a(SI = 0.86)than that of the current eutrophication method. The accuracy of CEI and the HAB occurrence time reached almost 93%,which was equivalent to that obtained from the statistical methods, and the spatial matching degree between CEI and HAB distribution was 77%, which was equivalent to that derived from the ecological dynamic model considering grade-3 as standard. After adjusting for regional factors, the similarity index(SI) of CEI and chl a was 0.74 in the Yangtze River estuary, reaching a high consistency. The spatial coincidence(kappa coefficient) of CEI and chl a was 0.25, reaching moderate and general consistency. The general consistency may have been caused by the loss of key control factors due to the particularity of the sea area. Future studies based on CEI construction in the Yangtze River estuary may solve this issue.
引文
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