Salt marshes, mangroves, and seagrass, coral reefs play a role in the sequestration of atmospheric \(CO_2\) , leading to the concept of “blue carbon”. Routinely assessing such blue-carbon ecosystems requires labour-intensive diver surveys. To alleviate the analysis of the video footage recorded by our team of divers, we introduce an automated weakly supervised computer vision pipeline that turns commodity 1080P underwater video into per-species distribution maps and coarse seafloor \(CO_2\) indices. First, the method prompts the Segment Anything in High Quality (HQ-SAM) with a handful of user clicks to generate pseudo-masks for ten ecologically indicative benthic taxa. These masks bootstrap four class-specific nnU-Net models that refine species boundaries. Finally, the carbon content, as low/medium/high concentration indicators, was estimated in each frame, producing site-level heatmaps suitable for temporal comparison. Experiments were run on 412 manually curated frames from coastal sites in Northland, Aotearoa New Zealand. The final image segmentation results showed mean Intersection-over-Union (mIoU) and Dice coefficients of 0.55 and 0.83, respectively.