IAGLR19 session on "Harmful algal blooms and their toxicity"
We are pleased to inform you that we are hosting a session at
IAGLR's 62nd annual Conference on Great Lakes Research to be held at SUNY, The College at Brockport, New York (10-14 June 2019) about
Harmful algal blooms (HABs) and their toxicity.
We would like to encourage submission to this session described below (Deadline Feb. 1):
#24. Harmful algal blooms (HABs) and their toxicity: Remote sensing and modeling approaches
Harmful Algal Blooms (HABs) are a worldwide problem that has been widely recognized over the past several decades. While freshwater HABs can occur naturally, human activities leading
to increased eutrophication as well as climate change have been linked to the increased occurrence and intensity of HABs. HABs can be both non-toxic or toxic. While non-toxic HABs can negatively impact water quality, fisheries and recreational facilities,
toxic blooms may additionally cause illness and death in humans and wildlife. Therefore, it is vital to be able to understand and predict the toxicity of HABs. Though a variety of physical, chemical and biological variables have been suggested as factors triggering
HAB toxicity, much remains to be done to improve our predictive and response capabilities, including the early detection and tracking of blooms, monitoring of HAB toxicity, and the development of scale-adaptive modeling tools. The primary goal of this session
is to create a valuable opportunity for the interdisciplinary exchange of ideas and experiences between the lake modeling, remote sensing, and Earth System Modeling communities. The session will facilitate in-depth discussions of emerging concepts, field and
satellite observations, as well as statistical and mechanistic modeling approaches. We particularly welcome presentations on field observations of HABs, predictive modeling studies, statistical analyses of the environmental factors that control algal and nutrient
dynamics in lakes, and recent advances in estimating Chl-a and other relevant variables using field and remotely-sensed observations for seasonal and inter-annual forecasting of HABs.
Homa Kheyrollah Pour, Serghei Bocaniov, Philippe Van Cappellen (University of Waterloo, Waterloo, ON, Canada)
Dr. Homa Kheyrollah Pour, PhD.
Department of Earth and Environmental Sciences
University of Waterloo
Waterloo, Ontario, Canada N2L 3G1,