Developing and using a Controlled, Agile and Novel Observing Network (CANON)

Under the Controlled, Agile and Novel Observing Network (CANON) project, we work to develop technology to observe traditionally understudied but ecologically important ephemeral features in the ocean and evaluate their impacts on ecosystem dynamics.

The Importance and Challenge of Sampling Transient Events in the Ocean

How can researchers understand ocean biogeochemistry when the subject of study varies constantly over time and space? MBARI’s Controlled, Agile, and Novel Observing Network (CANON) Initiative is an interdisciplinary effort that utilizes smart, autonomous devices designed to cooperate with each other to collect oceanographic information. Having time-varying spatial information relative to upwelling plumes, associated fronts, and chemical features can greatly improve our understanding of Monterey Bay and the California Current Ecosystem.

Moving from Shipboard to Autonomous Observations

Using robots to find the feature or process of interest rapidly is key to directing the activities of devices so they can sample effectively. Autonomous vehicles that can collect samples for laboratory analyses and provide information about zooplankton, fish, and marine mammals will help scientists to develop a realistic picture of the relationships between oceanographic processes and life in the sea. Our hope is that with these new tools, researchers will be able to better predict what lies in the future for ocean ecosystems.

Observational Campaigns

During previous field experiments in Monterey Bay, long-range autonomous underwater vehicles have been used to follow a subsurface patch of seawater rich in ammonium, target sampling along an upwelling front, drift within an upwelling isotherm, and target vertically migrating layers of fish above an upward facing echosounder. CANON seeks to combine different novel technologies together to gain a better understanding of processes that wouldn’t be possible through one technology alone. Through these efforts we can determine how best to combine technologies to the greatest effect.