We are currently seeking a student from the MIT Media Lab to collaborate on the technology development, testing, and deployment.

Challenge

Globally, the number of Marine Protected Areas (MPAs) has increased dramatically in recent years, partially driven by high-level policy commitments (e.g., the Convention on Biological Diversity’s commitment to protect 10% of the oceans by 2020). However, adequate data does not exist to assess whether these MPAs are effective and how their management could or should be improved. There is little baseline data, let alone the robust, long-term monitoring data needed to ensure MPAs achieve their potential.

Approach

Sea CLAM (Citizen-Leveraged Augmented Monitoring) will:

  1. Capitalize on emerging technology and automated data analysis (including artificial intelligence) methods to develop sensor technology and a data platform;

  2. Create a low-cost/long-term MPA monitoring program by empowering recreational boats to become research vessels and recreational scuba divers to become researchers; and

  3. Provide a low cost tool that can be deployed by scientists, MPA managers, scientists, and (most notably) trained volunteers across the world.

Our mission is to create long-term data series of fish, habitats, and water quality both inside and adjacent to MPAs all over the world that will be used to measure efficacy of the MPAs and improve management. It is critical that the monitoring be long-term as ecosystem responses to policy change can take years, and data on trends provides more valuable insights into effectiveness of policy than snapshot ecological assessments.

  • Conservify will build a sensor that can capture photo, video and water quality data including GPS-correlated pH, conductivity/salinity, temperature, depth, and acceleration in 3-dimensional space. This platform will be available as a diver-held configuration, a ship-mounted configuration, and for seafloor mounting (BRUV).

  • Adventure Scientists will recruit/screen, train, and manage volunteers from their network of volunteer divers and boaters (including locals) to collect data using these sensors at set locations both inside and outside of MPAs on a quarterly basis.

  • Working with the Big Data, Big Ocean group, we will use automated video analysis to extract fish counts from video logs and include our environmental metadata.

  • Ocean Collectiv will design policy and management recommendations triggered by the data analysis.

All data collection will be done in partnership with local management authorities, who will receive the data and training in data collection and interpretation. The scope of this initial project can be scaled depending on available funding, and will include sensor development, testing, and some level of deployment.

Technology

The technology developed under this grant will include engineering and development of the device and mounting configurations, validation of the data collected, and a data visualization mechanism to review the data that will plug into the interface provided by the Big Data, Big Ocean group.

Policy Integration

Effective monitoring is only the first step. We must also ensure that data is used to inform policymaking. We will develop policy recommendations to accompany our scientific findings. For example, a reduction in key herbivores that help keep algae levels low on coral reefs, would trigger a suggestion to consider a ban/quota on the catch of herbivores or a restriction in the use of the fishing gears that that target them. Ocean Collectiv will work closely with local stakeholders to ensure these policy triggers are effectively targeted.

Unknowns

  • Location(s): Based on our existing relationships with MPA managers, we are exploring opportunities in Indonesia, Hawaii, Barbuda, and Mozambique. The location(s) will depend on discussions with local partners and project funding.

  • Automated Video Analysis: We plan to use Big Ocean, Big Data’s automated video analysis to extract fish counts and habitat data from the video we collect. However, if their software is not ready in time, we will use manual coding in collaboration with local partners.

  • Volunteer Effort Required: The required number of volunteer divers and boaters is dependent on the pilot location(s). Once the MPAs are selected, Adventure Scientists will create a volunteer profile and determine the number of volunteers needed.  

Resources/Team

Our team brings significant organizational resources to support this project.

  • Conservify is a 501(c)3 nonprofit based in Los Angeles, CA that develops open source conservation technology solutions for scientists, conservationists, governments, and NGOs globally. (Lead: Shah Selbe)

  • Adventure Scientists is a 501(c)3 nonprofit organization based in Bozeman, MT that equips partners with data collected from the outdoors that are crucial to addressing environmental challenges. By leveraging the skills of the outdoor adventure community we are able to gather difficult-to-obtain data at any scale, in any environment. (Lead: Gregg Treinish)

  • Ocean Collectiv is a consulting firm for ocean conservation strategy. Our diverse collaborative of experts designs, builds, and implements fresh ideas on policy, science, commerce, and communications. (Lead: Ayana Elizabeth Johnson)

  • MIT Media Lab: We are seeking a student from the Media Lab to collaborate on technology development and testing. (Lead: Katy Croff Bell)

  • University of Miami (Lead: Annie Brett, J.D.)

  • Blue Water Metrics (Lead: Matt Merighi)

  • Financial Resources: Beyond this initial pilot phase, we are prepared to raise additional capital as needed.  

Timeline

Our initial pilot project will be deployable within 6 months of project funding. We will then continue quarterly monitoring of our MPA sites.

Months 1-3

  • Technology development: build prototypes. Once complete, we will do a run of small batch manufacturing.

  • Research protocol developed

  • Project leads at Adventure Scientists assigned

  • MPAs scoped and selected, partnerships developed  

Months 3 & 4

  • Volunteer recruitment and training: In tandem, we will develop the research protocol and customize the training and data collection tools we will use (apps, checkin/checkout systems, etc.)

  • Testing: We will test and hone our sensors, protocol, and data platform.

Months 5 & 6

  • Deployment: Fieldwork at one or more MPAs in partnership with local managers

  • Sharing: Assessment of pilot, and sharing of lessons learned

  • Planning: Improve the system/methods for taking this work beyond the pilot

  • Policy integration: This component will be developed and integrated into the reports generated by the data platform