King Harbor in the City of Redondo Beach, California was the site of massive fish kills during 2005 following intense and prolonged red tide events. Weekly monitoring since early 2006 revealed the presence of an abundant and diverse community of potentially harmful dinoflagellate and raphidophyte species in the harbor with highly heterogeneous spatial and temporal distributions. Vertical migration and photoacclimation of dinoflagellates and raphidophytes were investigated as mechanisms for dealing with changing light levels in the King Harbor marina over a 24-hour cycle on 19-20 June 2007. PAR, CTD, chlorophyll fluorescence, dissolved oxygen concentrations, active chlorophyll fluorescence, backscattering, and light absorption and attenuation data were measured every four hours using sensor arrays. Discrete water samples were analyzed for pigment concentrations, particulate and dissolved inorganic nutrients, and phytoplankton community composition using both microscopical and molecular techniques. The overall phytoplankton community composition changed significantly during the 24-hour cycle, and the depth of the chlorophyll maximum moved from shallow waters to deeper depths, and possibly all the way to the sediment interface, during the evening hours. These data suggest a high degree of small-scale heterogeneity in vertical distribution of harmful algal populations and provide important insights into mechanisms that impact community composition within red tide assemblages in King Harbor.

Through the NAMOS project, our team of biologists and engineers are assisting municipalities in understanding the underlying causes and effects of harmful microalgal blooms. Since early 2007, we have been studying system-level dynamics of the chemical, physical, and biological processes in King Harbor, a shallow, semi-enclosed urban harbor in Redondo Beach, California. For the last two years a network of dock-based water quality sensors in the harbor has continuously provided data on the environmental parameters relevant to bloom formation. Additionally, intensive human-mediated studies of the phytoplankton community distribution and structure are testing several hypotheses on the biological and physical factors affecting algal growth in this system. Recent field experiments have sought to explain the roles of tidal forcing and phytoplankton behavior and physiology in the structuring and distribution of bloom-forming algal communities.

Harmful algal blooms (HAB) have been a recurring problem in King Harbor of the City of Redondo Beach in recent years. In 2005, a red tide resulted in a massive fish kill, and created a nuisance for commercial and recreational use of the harbor. It took several weeks for the incident to subside and for the ecosystem to return to normal. Several potentially problematic species of algae again bloomed during 2006, and seven bloom-forming species were isolated and cultured. Beginning in January 2007, the Networked Aquatic Microbial Observing System (NAMOS), which is comprised of both mobile and static sensing platforms, has been employed periodically in the harbor area to monitor phytoplankton population dynamics. A robotic boat is able to provide vertical profiles of critical environmental data including chlorophyll, temperature, salinity and dissolved oxygen throughout the harbor, while continuous recordings of chlorophyll concentration, dissolved oxygen, CTD, and turbidity are gathered by sensors at both surface and near bottom in different locations in the harbor.The combined use of static and mobile nodes constitutes an effective monitoring and early warning system for HABs. NAMOS has proven an excellent tool for providing excellent contextual data for experimental studies of bloom-forming species of phytoplankton. Field and lab experiments were conducted in conjunction with the deployment of the sensor network in order to examine environmental triggers for algal blooms in the harbor.

This poster presents an overview of our technique to create detailed 3 dimensional bathymetric and contour maps of marine environments. We use an occupancy grid based representation for the map. The maps are constructed using information gathered by an automated robotic boat mounted with an Imagenex 881L pencil beam sonar. We also present some preliminary work on intelligent exploration strategies for map construction, given the set of constraints on our robotic boat (time, distance, energy, physical constraints). Provision of accurate maps provides invaluable information to marine biologists including water volume, volume changes due to tidal cycles which indicate the amount of bio mass present in the water body and its changes. Using the maps, scientists can determine interesting locations for deployment of sensors for environmental monitoring.

When a scalar field, such as temperature, is to be estimated from sensor readings corrupted by noise, the estimation accuracy can be improved by judiciously controlling the locations where the sensor readings (samples) are taken. Following is the problem we are solving: given a set of static sensors and a group of mobile robots equipped with the same sensors, how to determine the data collecting paths for the mobile robots so that the reconstruction error of the scalar field is minimized. In our scheme, the static sensors are used to provide an initial estimate and the mobile robots refine the estimate by taking additional samples at critical locations. Unfortunately, it is computationally expensive to search for the best set of paths that minimizes the field estimation errors and hence the field reconstruction errors as well). In the case of single mobile robot, we propose an Approximate Breadth First Search to find a 'good' path for the robot. We have validated the path planning algorithm both in simulation and with the NAMOS system. In the case of multiple mobile robots, our approach first partitions the sensing field into equal gain subareas and then we use the single robot planning algorithm to generate a path for each robot separately. The properties of this approach are studied in simulation.

The overarching theme of the Center’s Aquatic application area continues to be the creation and application of a new genre of wireless sensing systems that will provide real-time monitoring capabilities of chemical, physical and biological parameters in freshwater and coastal marine ecosystems. High-resolution temporal and spatial measurements are essential for understanding the highly dynamic nature of aquatic ecosystems and the rapid response of microbial communities to environmental driving forces. Our unique approach to aquatic sensing and sampling, Networked Aquatic Microbial Observing Systems (NAMOS), employs coordinated measurements between stationary sensing nodes (buoys and pier-based sensors) and robotic vehicles (surface robotic boats and autonomous underwater vehicles) to provide in-situ, real-time presence for observing plankton dynamics (e.g. phytoplankton abundance, dissolved oxygen), and linking them to pertinent environmental variables (e.g. temperature, light, nutrients, etc.). Specific projects undertaken in this application area involve the development and deployment of sensor networks to examine harmful algal blooms within King Harbor, City of Redondo Beach, and the construction of mobile sensor networks in open coastal waters off southern California. The latter research involves deployments of autonomous surface and underwater vehicles, and the development of hardware and software for coordinated activities of these robotic vehicles.

Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatio-temporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.