Harmful cyanobacteria bloom science is currently in the global spot light due to recent large-scale toxic blooms. Although cyanobacteria researchers generally believe toxin-producing blooms are becoming more frequent on an ever-expanding geographical scale, the data to address this question on a global scale has not yet been aggregated. Microcystin has been one of the most frequently detected cyanotoxins throughout the last 20+ years of cyanotoxin research. Thus, compiling global microcystin occurrence and concentration data from lakes and reservoirs will allow researchers to determine if toxic cyanobacterial blooms are indeed becoming more frequent and/or changing in concentration worldwide.
The goal of the Global Microcystin Aggregation (GMA) project is to compile a global spatial/temporal dataset of freshwater microcystin and associated physicochemical water quality (e.g., TN, TP, Chl, Secchi, temperature, etc.), lake morphology (e.g., mean depth, volume, surface area), and watershed (e.g., land use metrics, watershed area) data to:
1- Describe the occurrence and concentrations of microcystins on a global spatial scale.
2- Examine temporal trends of microcystin concentrations on a global scale.
3- Develop global predictive and forecasting models for microcystin occurrence and concentrations based on (a) TN,TP, Chl, Secchi, temperature and other widely sampled limnology variables, (b) lake morphology variables such as depth, volume, surface area, etc., (c) watershed variables such as land use, watershed area, and soil type, and (d) possibly climate conditions and weather patterns.
We are looking for cyanobacteria researchers, algal/metabolite ecologists, ecological modelers, and database managers to: help find data in the literature and/or request microcystin and associated water quality data from colleagues at governmental and non-profit agencies, aggregate microcystin and associated water quality data with different sampling and analytical methods, and analyze a large database of global microcystin and associated water quality data for temporal and spatial trends.
If you are interested in the project or have data to contribute, please contact Ted Harris (Ted.Daniel.Harris@gmail.com)
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