Categorizing the severity of paralytic shellfish poisoning outbreaks in the Gulf of Maine for forecasting and management
Kleindinst, Judith L.
Anderson, Donald M.
McGillicuddy, Dennis J.
Stumpf, Richard P.
Fisher, Kathleen M.
Couture, Darcie A.
Hickey, J. Michael
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Development of forecasting systems for harmful algal blooms (HABs) has been a long-standing research and management goal. Significant progress has been made in the Gulf of Maine, where seasonal bloom forecasts are now being issued annually using Alexandrium fundyense cyst abundance maps and a population dynamics model developed for that organism. Thus far these forecasts have used terms such as “significant”, “moderately large” or “moderate” to convey the extent of forecasted paralytic shellfish poisoning (PSP) outbreaks. In this study, historical shellfish harvesting closure data along the coast of the Gulf of Maine were used to derive a series of bloom severity levels that are analogous to those used to define major storms like hurricanes or tornados. Thirty-four years of PSP-related shellfish closure data for Maine, Massachusetts and New Hampshire were collected and mapped to depict the extent of coastline closure in each year. Due to fractal considerations, different methods were explored for measuring length of coastline closed. Ultimately, a simple procedure was developed using arbitrary straight-line segments to represent specific sections of the coastline. This method was consistently applied to each year’s PSP toxicity closure map to calculate the total length of coastline closed. Maps were then clustered together statistically to yield distinct groups of years with similar characteristics. A series of categories or levels was defined (“Level 1: Limited”, “Level 2: Moderate”, and “Level 3: Extensive”) each with an associated range of expected coastline closed, which can now be used instead of vague descriptors in future forecasts. This will provide scientifically consistent and simply defined information to the public as well as resource managers who make decisions on the basis of the forecasts.
Author Posting. © The Author(s), 2013. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 103 (2014): 277-287, doi:10.1016/j.dsr2.2013.03.027.
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