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1. Harmful algal blooms in inland waters

   https://doi.org/10.1038/s43017-024-00578-2  

   Feng, Lian; Wang, Ying; Hou, Xuejiao; Qin, Boqiang; Kutser, Tiit; Qu, Fan; Chen, Nengwang; Paerl, Hans W; Zheng, Chunmiao (September 2024, Nature Reviews Earth & Environment)

   Harmful algal blooms can produce toxins that pose threats to aquatic ecosystems and human health. In this Review, we outline the global trends in harmful algal bloom occurrence and explore the drivers, future trajectories and potential mitigation strategies. Globally, harmful algal bloom occurrence has risen since the 1980s, including a 44% increase from the 2000s to 2010s, especially in Asia and Africa. Enhanced nutrient pollution owing to urbanization, wastewater discharge and agricultural expansion are key drivers of these increases. In contrast, changes have been less substantial in high-income regions such as North America, Europe and Oceania, where policies to mitigate nutrient pollution have stabilized bloom occurrences since the 1970s. However, since the 1990s, climate warming and legacy nutrient pollution have driven a resurgence in toxic algal blooms in some US and European lakes, highlighting the inherent challenges in mitigating harmful blooms in a warming climate. Indeed, advancing research on harmful algal bloom dynamics and projections largely depends on effectively using data from multiple sources to understand environmental interactions and enhance modelling techniques. Integrated monitoring networks across various spatiotemporal scales and data-sharing frameworks are essential for improving harmful algal bloom forecasting and mitigation. 

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2. Modeling harmful algal blooms in a changing climate

   https://doi.org/10.1016/j.hal.2019.101729  

   Ralston, David K.; Moore, Stephanie K. (January 2020, Harmful Algae)
3. Multi-Modal Lake Sampling for Detecting Harmful Algal Blooms

   https://doi.org/10.1109/OCEANS47191.2022.9977137  

   Salman, Ibrahim; Karapetyan, Nare; Venkatachari, Archana; Quattrini Li, Alberto; Bourbonnais, Annie; Rekleitis, Ioannis (October 2022, OCEANS 2022, Hampton Roads)

   In this paper, we present a system for measuring water quality, with a focus on detecting and predicting Harmful Cyanobacterial Blooms (HCBs). The proposed approach includes stationary multi-sensor stations, Autonomous Surface Vehicles (ASVs) collecting water quality data, and manual deployments of vertical water sampling together with vertical water quality sensor data collection, in order to monitor the health of the lake and the progress of different types of algal blooms. Traditional water monitoring is performed by manual sampling, which is limited both in the spatial and the temporal domain. The proposed method will expand the range of measurements while reducing the cost. Human sampling is still included in order to provide a base of comparison and ground truth for the automated measurements. In addition, the collected data, over multiple years, will be analyzed to infer correlations between the different measured parameters and the presence of blooms. A detailed description of the proposed system is presented together with data collected during our first sampling season. 

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4. An engineered polysaccharide lyase to combat harmful algal blooms

   https://doi.org/10.1016/j.bej.2018.01.005  

   Eckersley, Evan; Berger, Bryan W. (April 2018, Biochemical Engineering Journal)
5. Harmful Algal Blooms (HABs): track them like a scientist

   https://doi.org/10.1080/00368121.2019.1691968  

   Curran, M.C.; Richlen, M.L. (December 2019, Science activities)