Terrestrial and coloured dissolved organic matter in Arctic waters: Towards in-situ sensor based monitoring of Arctic-Atlantic organic carbon exchange at major Arctic gateways

With accelerating global warming, air temperatures around the globe are increasing and the highest increase has been observed over the past decades, particularly in the Arctic region. An increase in air temperatures for the Arctic region will not only affect the rate of sea ice melting, but will also increase river discharge and erosion of riverbanks and coastlines. The latter processes will lead to more terrestrial dissolved organic matter (tDOM) being transported from land to the Arctic Ocean in the future. The fate of dissolved organic carbon (DOC) supplied as tDOM is of great concern, since it potentially can be transformed to carbon dioxide (CO₂) and be exchanged with the atmosphere.

The aim of this Ph.D. thesis was to study the fate of tDOM in the Arctic Ocean and to develop an analytical method to quantify and trace its distribution from different sources. To understand the continuum of tDOM, the fate of the dissolved material was first investigated in the Arctic coastal zone (ACZ), where it is released, and later in Arctic major gateway, the Fram Strait, where it is exported to the Atlantic Ocean.

My studies found that the fate of tDOM from coastal erosion depends on the permafrost soil type being dissolved into the coastal waters. The derived tDOM from three different permafrost types led to the development of three distinct marine bacterial communities, which also led to three different bacterial growth efficiencies. The difference in bacterial growth efficiency ultimately means that the carbon processing of the derived DOC, and the remineralization to CO₂, from coastal erosion is greatly dependent on which permafrost soil type will erode into coastal waters. However, it was found that most of the DOC was likely refractory to rapid mineralization and may survive passage through the coastal zone.

The refractory part of tDOM that survives the coastal zone will be exported to the open ocean, where it will follow ocean currents across the Arctic Ocean and under the sea ice. The water masses circulating in the Arctic Ocean will eventually get exported through one of two major Arctic gateways, either side of Greenland, to the Atlantic Ocean. Once in the Atlantic Ocean, the exported tDOM and associated DOC may be sequestered into the deep ocean and despite eventual mineralization with time, be kept away from interaction with the atmosphere. To follow how the carbon cycle is responding to climate change it is therefore important to trace this pathway. One approach to obtain a quantitative measure of the distribution and fate of tDOM, is to use the biopolymer lignin as a biomarker. Lignin only exists in terrestrial plants and when found in the ocean reflects tDOM distribution. Besides that, lignin character has also been shown to be able to provide information on source and diagenesis of the lignin material.

During this project, I developed a machine-learning assisted method to quantify lignin phenols in seawater with the aim of improving the sensitivity and specificity of high-pressure liquid chromatography (HPLC) coupled with absorbance detection. This new method circumnavigates current limitations with this instrumentation and substantially reduces seawater needed for measurement. The method was applied to seawater from the Fram Strait and the total concentration of dissolved lignin was clearly higher for Arctic surface waters being exported, than Atlantic waters being imported, reflecting the tDOM supplied from landmasses around the Arctic Ocean and persisting to reach the Fram Strait and thereby exported to the North Atlantic. Additionally it was found that multiple sources of terrestrial material could be differentiated in the exported water masses.

Finally, I investigated the relationship between DOM fluorescence and lignin phenol concentrations in seawater using N-way Partial Least Squares (N-PLS) regression. The goal was to predict the essential lignin parameters from spectral fluorescence measurements which are much less time consuming to make and for which there is a time series of data for in the Fram Strait. The N-PLS model derived successfully replicated the measured trends in the water masses sampled and could be used to predict lignin phenol ratios and thereby differentiate between tDOM sources. The developed N-PLS model was further reduced to predict lignin phenols based on only four excitation wavelengths in order to investigate the potential of designing in situ sensors for the purpose. Despite the large reduction in excitations wavelengths, the model still performed well. This indicates that the approach holds promise as a proxy for estimating lignin concentrations, greatly extending potential spatial and temporal coverage, and paving the way for development of sensors which can be used on profiling (automated) systems and help monitor and quantify the effect of climate change on the ocean’s carbon budget more closely in the future.