The ICEX program would not be possible without fantastic international collaborators. This year, we are very grateful to Kasper Hancke, a post-doctoral fellow in Physiology and Marine Sciences at the Norwegian University of Science and Technology's Trondheim Biological Station (TBS) for his organization of this, our (much delayed!) trip to Norway. (Big thanks as well to Kasper's colleagues at NTNU!)
All of us are also quite excited about the scientific context of the work that we are doing with the IVER in the next few days. Our primary goal is to attach an oxygen sensor to the autonomous underwater vehicle and then to conduct various missions at the Bay of Hopavågen where the Trondheim Biological Station's Sletvik Field Station is located. This field station is approximately 120 km west of Trondheim and about 20 km west of the outlet of the Trondheimsfjord.
Today, as part of our first "work day" in Trondheim, we met with Kasper at 9 am this morning at TBS to learn more about why mapping oxygen level distributions is so important. The level of oxygen in the water at any given time and depth is determined by two competing processes: photosyntheis (which produces oxygen as a byproduct) and metabolism/respiration (which consumes oxygen and produces carbon dioxide). Measuring changes in oxygen levels across time allows researchers to monitor photosynthesis rates in the water column. Photosynthesis rates are impacted by the amount of micro- and macro-algae in the water as well as the amount and angle of light which is hitting the surface of the water, amongst other factors.
Our aim over the next few days, in Kasper's words, is to quantify the net community oxygen production (gross oxygen production via photosynthesis minus oxygen consumption via metabolism/respiration) of the Hopavågen enclosure and Trondheimsfjord. We will also aim to map the oxygen distribution in 3D and construct a related time-series. (NOTE: metabolism/respiration rates can be determined by taking water samples and running lab-based experiments in which the samples are exposed to no light - thus, removing photosynthesis from the equation.) This net community oxygen production data can then be used for various applications, including:
- monitoring the impact of human activity on coastal ecosystems (e.g., effects from nutrient run-off related to aquaculture and agriculture activities);
- monitoring the impacts of toxics (e.g., oil spills) on marine production;
- studying climate impacts on marine carbon turn-over; and,
- mapping kelp forest activity and health status.
[UPDATE by Alex:] Another exciting aspect of the technical side of our work consists of the confidence values we can associate with the data we collect. So for each data point, the confidence value for that data point depends on how long it has been since we last received a GPS measurement. In other words how much possible error in our location estimate has built up since the last GPS measurement, a high amount of possible error leads to a lower confidence value. For example, using data collected in Avila Bay, one area where there would be lower confidence values can be seen in the area labelled "A" in the picture below. Conversely, a low amount of possible error leads to a high confidence value. The area labelled "B" in the picture below corresponds to an area right after a GPS measurement was received and there would be a high confidence value for the data-points in that area.Therefore if, for example, part of the dataset seems different from the rest, we can look at the confidence values for that area and if there are low confidence values then we know that the data-points for that area might not be accurate.
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