Deep sea biodiversity hotspots: Time series image data acquisition from challenging ecosystems with affordable open source hardware and software.
During the last three years the Alfred Wegener Institute for Polar and Marine Research (AWI), have in collaboration with the Max Planck Institute for Marine Microbiology (MPI) and GEOMAR been developing cost effective imaging platforms for deployment in remote ecosystems. These are based around the use of the popular ‘maker community’ family of Raspberry Pi computers, off-the-shelf components and the use of radio transparent sapphire glass and plastic housings. The Raspbian and Python programming languages have been used to develop deployment solutions capable of taking images across a range of frequencies for deployments of hours to more than a year.
Following prototyping we have developed a ~$150 camera design for use at depths of less than ~200 m utilising a plastic housing. Additionally, we have also developed a camera design for deployment at depths of <6000 m with a sapphire glass housing (~$300 build cost). Here we present images taken with these systems from a range of remote hotspot ecosystems and poorly sampled regions of the world ocean, as well as preliminary scientific findings based on these data. Ecosystems surveyed with these platforms thus far include the deep under-ice seafloor, cold-water coral reefs, polymetallic nodule fields and the deep under-ice pelagic. By keeping the build cost of the camera systems low, scaling up the number which can be deployed for a given period becomes a financial possibility for mid-size research projects, supporting statistical approaches difficult to achieve with the majority of current time series camera deployment strategies.
This study is part of the Arctic long-term observatory FRAM, the HACON-FRINATEK project and HGF-project ARCHES.
Full build plans, 3D printer files, schematics and software are freely available from the projects Github page.