Coastal waters are highly productive and diverse ecosystems, often dominated by marine submerged aquatic vegetation (SAV) and strongly affected by a range of human pressures. Due to their important ecosystem functions, for decades, both researchers and managers have investigated changes in SAV abundance and growth dynamics to understand linkages to human perturbations. In European coastal waters, monitoring of marine SAV communities traditionally combines diver observations and/or video recordings to determine, for example, spatial coverage and species composition. While these techniques provide very useful data, they are rather time consuming, labor‐intensive, and limited in their spatial coverage. In this study, we compare traditional and emerging remote sensing technologies used to monitor marine SAV, which include satellite and occupied aircraft operations, aerial drones, and acoustics. We introduce these techniques and identify their main strengths and limitations. Finally, we provide recommendations for researchers and managers to choose the appropriate techniques for future surveys and monitoring programs. Integr Environ Assess Manag 2022;18:892–908. © 2021 SETAC

Benthic vegetation is arguably one of the most important indicators of the state of marine environment. Assessment of the status of eelgrass (Zostera marina) is commonly done using various remote sensing methods such as aerial photography or satellite images. These methods often fail to capture the true scenario beneath the surface of the water if the water is turbid or the satellite image is masked by cloud cover which makes it impossible to see beneath them. As a second line of defense, researchers have used under water videos (obtained either with scuba,snorkel or other visual observations) to assess the ground truth. Lots of man-hours are spent browsing through many hours of video data manually by an expert and assessing the status (presence/absence) which is a very common practice. Here we propose two methods for detection of eelgrass (presence/absence) from under water videos obtained from Roskilde Fjord in Denmark. We extend these methods to show that it can be used as a proxy to estimate coverage of eelgrass in a given area which match well with an expert's estimation. The benefit of using this method is that it is objective, less biased, cost efficient, robust to noisy environment, does not require pixel-level annotated ground truth images and can be used on existing video transects. This method can also detect rare errors from domain expert's visual estimation.

The dietary vitamin D intake of the Danish population is low, and food fortification is a strategy to increase intake. This paper explores the possibility of vitamin D fortification on the current population food intake in Denmark, such that the population receives adequate amounts of vitamin D without having to change current dietary patterns. A mixed-integer programming approach is used to arrive at a solution for the optimal fortification required at each food group level so that the majority of the population receive the minimum intake of average requirement (AR) and do not exceed the tolerable upper intake level (UL). The method shows a significant increase in vitamin D intake compared to the current scenario, keeping a neutral approach towards preferences of one food group over others. The method can also be fine-tuned in different scenarios where certain food group preferences are known, which can be encoded into the model in the form of constraints.