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Using SeaWiFS and In Situ Data for HAB Prediction in the Northern Gulf of Mexico: Decision Tree Analysis

Dan Holiday¹ and Greg Carter¹

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1. USM

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Document Type:

Poster

Date:

Received 14 August 2009 16:11 UTC; Posted 14 August 2009

Subjects:

Ecology, Earth & Environment

Tags:

• remote sensing
• SeaWiFS
• HABs
• Pseudo-nitzschia
• Gulf of Mexico
• decision tree

Abstract:

To date, 13 potential HAB species have been detected in coastal waters of Mississippi and Alabama, including representatives of the diatom genera Pseudo-nitzschia and Chaetoceros, and dinoflagellate genera Karenia, Gonyaulax, Akashiwo, Karlodinium, and Prorocentrum. This study investigates the potential of satellite remote sensing (SeaWiFS) to predict environmental conditions leading to the formation of HABs in these turbid coastal waters. Phytoplankton populations and water quality were monitored in situ at 3 to 6 week intervals and 17 locations in Mobile Bay and the Mississippi Sound from December, 2004, through June, 2006. SeaWiFS imagery corresponding with in situ collections was acquired. Non-parametric multivariate analyses determined relationships between phytoplankton cell counts and in situ or satellite-derived water properties, including surface temperature, salinity, concentrations of chlorophyll, total suspended solids, colored dissolved organic material, and nutrient levels. This paper will describe an expert system decision tree analysis approach to prediction of ecological conditions necessary for the formation of HABs. The model assumes unique ranges of remote sensing reflectance ratios, Chl a, and total suspended solids must exist within the environment are conducive for the formation of HABs.

Collection:

2009 Annual Meeting of the Ecological Society of America

Presented at:

Ecological Society of America - 2009 Annual Meeting, Albuquerque, NM, 02 August 2009

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This document is licensed to the public under the Creative Commons Attribution 3.0 License

How to cite this document:

Holiday, Dan and Carter, Greg. Using SeaWiFS and In Situ Data for HAB Prediction in the Northern Gulf of Mexico: Decision Tree Analysis. Available from Nature Precedings <http://dx.doi.org/10.1038/npre.2009.3607.1> (2009)

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