Optical monitoring and forecasting systems for harmful algal blooms: Possibility or pipe dream?

Monitoring programs for harmful algal blooms (HABs) are currently reactive and provide little or no means for advance warning. Given this, the develop ment of algal forecasting systems would be of great use because they could guide traditional monitoring programs and provide a proactive means for res ponding to HABs. Forecasting systems will require near real-time observatio nal capabilities and hydrodynamic/biological models designed to run in the forecast mode. These observational networks must detect and forecast over e cologically relevant spatial/temporal scales. One solution is to incorporat e a multiplatform optical approach utilizing remote sensing and in situ moo red technologies, Recent advances in instrumentation and data-assimilative modeling may provide the components necessary for building an algal forecas ting system, This review will outline the utility and hurdles of optical ap proaches in HAB detection and monitoring. In all the approaches, the desire d HAB information must be isolated and extracted from the measured bulk opt ical signals. Examples of strengths and weaknesses of the current approache s to deconvolve the bulk optical properties are illustrated. After the phyt oplankton signal has been isolated, species-recognition algorithms will be required, and we demonstrate one approach developed for Gymnodinium breve D avis, Pattern-recognition algorithms will be species-specific, reflecting t he acclimation state of the HAB species of interest. Field data will provid e inputs to optically based ecosystem models, which are fused to the observ ational networks through data-assimilation methods. Potential model structu re and data-assimilation methods are reviewed.