摘要
掌握赤潮灾害时空分布规律是科学设计赤潮监控方案、提高防灾管理效率的基础和依据。本文统计分析了1990—2010年间山东海域的76次赤潮灾害事件数据。结果表明:赤潮灾害频率显著地分为4个波段,且峰值呈递增趋势;灾害面积呈现周期性倒U型曲线变化;每年的5—10月是赤潮灾害的多发期,其中,8月的灾害次数和灾害面积均占全年总数的30%以上;灾害空间分布集中在莱州湾海域、青岛近海、庙岛群岛的北隍城海域,烟台四十里湾的赤潮灾害最频繁;夜光藻(Noctiluca scintillans)和球型棕囊藻(Phaeocystis globosa)引发的赤潮灾害面积最高,夜光藻和红色裸甲藻(Gymnodinium sanguineum)致灾次数最多。本文从赤潮监测与信息采集、赤潮预报方法以及赤潮灾害预警报管理机制3个方面分析总结了山东海域赤潮灾害预警报业务化管理现状,结合山东海域赤潮灾害特征和预警报管理实践,提出了以控制污染和修复生态环境为根本的赤潮防控建议。
To understand the spatiotemporal distribution of harmful algal bloom （HAB） is the basis for the monitoring and prevention management of this disaster. In this paper, the data of 76 HAB events happened in Shandong coastal waters from 1990 to 2010 were analyzed, showing that the frequency of the disaster’s events could be evidently divided into four phases, and the peaks presented an increasing trend. The area this disaster happened appeared as periodic inverted U curve. The HAB happened frequently from May to October in each year, and the HAB events happened in August accounted for more than 30% of the total. Most of the events happened in Laizhou Bay, Qingdao coast, and Beihuangcheng waters, and the frequency of the events was the highest in Sishili Bay. The disaster caused by Noctiluca scintillans and Phaeocystis globosa occupied the largest area, and the frequency of the disaster caused by Noctiluca scintillans and Gymnodinium sanguineum was the highest. The early warning management of the HAB in Shandong Province was introduced from the aspects of monitoring system, forecasting methods, and management mechanism, and the prevention and control measures were proposed based on this study. It was suggested that the pollution control and ecological remediation could be the fundamental solution.
出处
《生态学杂志》
CAS
CSCD
北大核心
2012年第5期1272-1281,共10页
Chinese Journal of Ecology
基金
海洋公益性行业科研专项(200905019)
海洋公益性行业科研专项(201005018)
山东省908专项(SD90802014)
水生动物营养与饲料"泰山学者"岗位经费资助
关键词
赤潮
灾害特征
点聚图预报法
判别方程
预警报管理
harmful algal bloom （HAB）
disaster characteristics
scatter diagram forecasting technique
discriminant equation
early warning management
