Effective aerial monitoring of cyanobacterial harmful algal blooms is dependent on understanding cellular migration.
Mingzhi Qu, Stephen Anderson, Pin Lyu, Yasir Malang, Jizhou Lai, Jianye Liu, Bin Jiang, Feng Xie, Hugh H T Liu, Daniel D Lefebvre, Yuxiang S Wang
Author Information
Mingzhi Qu: Department of Biology, Queen's University, Kingston, ON, K7L 3N6, Canada.
Stephen Anderson: Department of Biology, Queen's University, Kingston, ON, K7L 3N6, Canada.
Pin Lyu: Institute for Aerospace Studies, University of Toronto, Toronto, ON, M3H 5T6, Canada; College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Yasir Malang: Institute for Aerospace Studies, University of Toronto, Toronto, ON, M3H 5T6, Canada.
Jizhou Lai: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Jianye Liu: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Bin Jiang: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China.
Feng Xie: School of Rail Transportation, Soochow University, Suzhou, 215131, China.
Hugh H T Liu: Institute for Aerospace Studies, University of Toronto, Toronto, ON, M3H 5T6, Canada.
Daniel D Lefebvre: Department of Biology, Queen's University, Kingston, ON, K7L 3N6, Canada.
Yuxiang S Wang: Department of Biology, Queen's University, Kingston, ON, K7L 3N6, Canada. Electronic address: yuxiangw@queensu.ca.
Cyanobacterial harmful algal blooms (CHABs) degrade water quality and may produce toxins. The distribution of CHABs can change rapidly due to variations in population dynamics and environmental conditions. Biological and ecological aspects of CHABs were studied in order to better understand CHABs dynamics. Field experiments were conducted near Hartington, Ontario, Canada in ponds dominated by Microcystis aeruginosa and CHABs floating experiments were conducted at Lake Taihu during the summers of 2015 and 2016. Single colonies composed of hundreds to thousands of cells with an average median of 0.2-0.5 mm in diameter were the basic form assumed by the Microcystis, and this remained the same throughout the growing season. Thorough mixing of the water column followed by calm conditions resulted in over 90% of the cyanobacteria floating after 1 h. Multiple colonies floated on the water surface in four types of assemblages: aggregates, ribbons, patches, and mats. It is the mats that are conventionally considered the blooming stage of cyanobacteria. Presence of CHABs on open water surfaces also depends on environmental influences such as direct and indirect wind effects. For example, field tests revealed that the surface coverage of CHABs can be reduced to half within an hour at wind speeds of 0.5 m/s. Because our findings indicated that blooming involves surface display of cyanobacteria essentially presenting as a two-dimensional plane under defined conditions, the use of surface imagery to quantify CHABs was justified. This is particularly important in light of the fact that traditional detection methods do not provide accurate distribution information. Nor do they portray CHABs events in a real-time manner due to limitations in on-demand surveillance and delays between sample time and analyzed results. Therefore, a new CHAB detection method using small unmanned aerial systems with consumer-grade cameras was developed at a maximum detection altitude of 80 m. When cyanobacteria were floating on the surface, CHABs detection through RGB band cameras and spectral enhancement techniques was efficient and accurate. Small unmanned aerial systems were capable of providing coverage up to 1 km per mission and the short intervals between sampling and results (approx. 2 h) allowed for the rapid analysis of data and for implementing follow-up monitoring or treatments. This method is very cost-effective at an estimate of as low as $100 CAD per mission with an average cyanobacterial detection accuracy of 86%. Thus, it is a good candidate method to fill the urgent need for CHABs detection, providing cost effective, rapid, and accurate information to improve risk management at a local level as well as to help quickly allocate resources for purposes of mitigation.
