Department Oceanography, Texas A&M University, College Station, TX, 77843, USA,
Environ Sci Pollut Res Int. 2013 Oct;20(10):6896-902. doi: 10.1007/s11356-012-1437-4. Epub 2013 Jan 11.
Monitoring programs for harmful algal blooms (HABs) typically rely on time-consuming manual methods for identification and enumeration of phytoplankton, which make it difficult to obtain results with sufficient temporal resolution for early warning. Continuous automated imaging-in-flow by the Imaging FlowCytobot (IFCB) deployed at Port Aransas, TX has provided early warnings of six HAB events. Here we describe the progress in automating this early warning system for blooms of Karenia brevis. In 2009, manual inspection of IFCB images in mid-August 2009 provided early warning for a Karenia bloom that developed in mid-September. Images from 2009 were used to develop an automated classifier that was employed in 2011. Successful implementation of automated file downloading, processing and image classification allowed results to be available within 4 h after collection and to be sent to state agency representatives by email for early warning of HABs. No human illness (neurotoxic shellfish poisoning) has resulted from these events. In contrast to the common assumption that Karenia blooms are near monospecific, post-bloom analysis of the time series revealed that Karenia cells comprised at most 60-75 % of the total microplankton.
有害藻类水华（HAB）监测计划通常依赖于耗时的手动方法来鉴定和计数浮游植物，这使得难以获得具有足够时间分辨率的预警结果。在德克萨斯州阿兰萨斯港部署的成像流式细胞仪（IFCB）持续进行自动成像，可以对六次 HAB 事件发出预警。在这里，我们描述了为小凯伦藻水华自动预警系统所取得的进展。2009 年，在 2009 年 8 月中旬对 IFCB 图像进行人工检查，为 9 月中旬出现的小凯伦藻水华发出了预警。利用 2009 年的图像开发了一个自动化分类器，该分类器在 2011 年投入使用。自动化文件下载、处理和图像分类的成功实施使得结果可以在采集后 4 小时内提供，并通过电子邮件发送给州机构代表，以预警 HAB 事件。这些事件没有导致人类疾病（神经毒性贝类中毒）。与小凯伦藻水华几乎是单一种群的常见假设相反，对时间序列的后 bloom 分析表明，小凯伦藻细胞最多占总浮游微生物的 60-75%。
