Kenneth Thorø Martinsen:
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Freshwater ecosystems play an important role in the global carbon cycle. In recent decades, researchers have shown that lakes and streams are active sites of carbon processing and release large quantities of greenhouse gases including carbon dioxide (CO2). Estimates of carbon emissions from freshwater ecosystems have steadily increased with ongoing research but the estimates remain uncertain. Of particular interest are small lakes which traditionally have been overlooked, are highly abundant, and are in close contact with the terrestrial environment. This thesis investigates carbon cycling in small lakes and stream networks and contains four chapters addressing methodology, environmental drivers, and upscaling.
Chapter I describes a novel floating chamber designed to perform automatic measurements of lake CO2 fluxes. The chapter describes how simple modifications can be added to improve existing designs. The suggested solution is easy to assemble and cheap making it attractive for studies of lake CO2 fluxes.
Chapter II examines the influence of drought on carbon cycling and CO2 fluxes from small lakes and the air-exposed sediments surrounding them. The chapter shows the high CO2 fluxes from lake sediments that have recently been exposed to air and highlight the impact of drought on system-scale carbon processes in small lakes. As the frequency of drought events is expected to increase as a consequence of climate change, these findings question the long-term conservation of carbon deposits in small lakes.
Chapter III investigates the contribution of in-lake metabolic processes to the CO2 flux in small forest lakes during the annual cycle. The chapter shows that aerobic lake metabolism alone cannot account for the observed CO2 flux. The discrepancy can be explained by potential contributions from anaerobic metabolism or groundwater input. Furthermore, a national analysis reveals that the discrepancy is most pronounced in small lakes. This highlights the influence of lake size on the contributions of different processes occurring within or outside the lake to the CO2 flux.
Chapter IV uses national stream monitoring data from Denmark, Sweden, and Finland combined with catchment characteristics to predict CO2 partial pressure in the entire stream network. The chapter presents a framework that uses machine learning and geospatial data to improve predictive performance. The most influential drivers were catchment elevation, permanent water cover, and slope, highlighting the importance of wetlands and catchment geomorphometry on stream CO2 partial pressure.