Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Bioremediation

Bioremediation

Bioremediation is the use of prokaryotes, fungi, or plants to remove pollutants from the environment. This process has been used to remove harmful toxins in groundwater as a byproduct of agricultural run-off and also to clean up oil spills.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Rainstorm regimes modulate cyanobacterial bloom dynamics in deep reservoirs: Synergistic effects of nutrient pulses and hydrological perturbations.

Limnology and oceanography·2026

Same author

CyanoHABs and CAPs: assessing community-based monitoring of PM<sub>2.5</sub> with regional sources of pollution in rural, northeastern North Carolina.

Environmental science: atmospheres·2025

Same author

Harmful algal blooms in inland waters.

Nature reviews. Earth & environment·2025

Same author

Global lake phytoplankton proliferation intensifies climate warming.

Nature communications·2024

Same author

Wetland phosphorus dynamics and phosphorus removal potential.

Water environment research : a research publication of the Water Environment Federation·2022

Same author

Global divergent trends of algal blooms detected by satellite during 1982-2018.

Global change biology·2022

Search research articles

Related Experiment Video

Updated: May 23, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

A Practitioner-Informed Decision Tree for Selecting Harmful Cyanobacteria Bloom Control and Mitigation Techniques.

Desirée Tullos¹, Megan M Skinner², Hans W Paerl³

¹Department of Biological and Ecological Engineering, Oregon State University, Corvallis, Oregon, USA.

Wires. Water

|March 10, 2025

Summary

Harmful cyanobacterial blooms (HCBs) are increasing globally. This study presents a decision tree to help select effective HCB control strategies for various water bodies, considering factors like nutrient sources and water body characteristics.

Keywords:

cyanobacteria decision tree harmful algal bloom mitigation and control in-lake restoration methods nutrient management

More Related Videos

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Published on: February 7, 2017

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Published on: August 14, 2020

Related Experiment Videos

Last Updated: May 23, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Published on: February 7, 2017

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation

Published on: August 14, 2020

Area of Science:

Environmental Science
Ecology
Water Resource Management

Background:

Harmful cyanobacterial blooms (HCBs) pose significant ecological and human health risks, with increasing global incidence.
Existing HCB control techniques lack clear guidance on selection and effectiveness across diverse water bodies.
There is a need for a systematic framework to evaluate and choose appropriate HCB mitigation strategies.

Purpose of the Study:

To develop a decision tree framework for selecting effective in situ Harmful Cyanobacterial Bloom control techniques.
To synthesize scientific literature and practitioner experience for HCB management guidance.
To address the lack of clear, evidence-based strategies for HCB control in different aquatic environments.

Main Methods:

A comprehensive review of peer-reviewed and gray literature on HCB control techniques.
A national survey of practitioners regarding HCB control methods and their application.
Development of a decision tree based on literature review and survey data, incorporating key influencing factors.

Main Results:

Key factors for HCB control feasibility include nutrient load source (external vs. internal), treatment area size, and water body regulations.
The decision tree framework categorizes HCB control techniques based on environmental conditions and effectiveness.
Survey results revealed significant regional variations in HCB control technique application.

Conclusions:

The developed decision tree provides a science-based framework to guide the selection of appropriate and effective HCB control strategies.
Understanding site-specific factors is crucial for successful Harmful Cyanobacterial Bloom mitigation.
The framework aids water resource managers in making informed decisions for HCB management, supported by case studies and a review of current techniques.