This report aimed to investigate how chlorophyll-concentrations (Chl-a) in the water column and varved sediments were affected by changes in air temperature and precipitation and consequently how climate change will affect the sedimentation and productivity in boreal aquatic ecosystems. VRS (visible-reflectance-spectroscopy) was used to asses Chl-a and its derivates in sediment trap samples between 2002-2021 and in a series of freeze cores (1979-2021) from lake Nylandssjön, with annually laminated sediments. In order to evaluate how weather and climate change affected the sedimentation and productivity in the lake the results were compared with meteorological data from SMHI (Swedish Meteorological and Hydrological Institute) and Chl-a data from seperate depths in the water column. The results indicate that the majority of the yearly sedimentation occur either in May or June, where a higher cumulative amount of precipitation in May lead to a higher sedimentation rate in May (r=0,49; p=0,03). The amount of precipitation in spring also had a significant impact on the primary production in spring and summer (r=0,59; p=0,01; r=0,73; p=0,002). Water column Chl-a and spectrally inferred Chl-a in sediments show similar trends in concentrations with deeper water sampling, however, water column Chl-a displayed significant differences in values between various depths (p=0,0004). Consequently, climate change will much likely increase the productivity of boreal aquatic ecosystems within years and the amount of sedimentation that occurs between years due to higher temperatures. An increased amount of precipitation will also enhance the primary productivity and the transportation of allochthonous- and minerogenic material to the lake.

In this thesis a robust Python based software for controlling a Chlorophyll-a Pulse-Amplitude-Modulated (PAM) fluorescence microscope and analysing subsequent data has been developed and validated. The automation software, called PACMan (PAM Automation Control Manager) was made for the purpose of increasing the amount of single cell data generated per experiment. PACMan includes an autofocus algorithm and the ability to vary experimental parameters during experiments. The analysis software, called PAMalysis, processes and facilitates interpretation of PAM experimental data, printing both text files and creating graphical output. PACMan was used on two different phytoplankton species of the Symbiodiniacae family to characterize them under thermal stressors while immobilized on a microfluidic device. The heterogeneity of the phytoplanktons response to increasing thermal stress was evaluated and the best performers under heat stress have been removed using Laser Capture Microdissection for downstream cultivation. PACMan was also used to compare the response of 4 Symbiodiniacae species to increasing relaxation time between light pulses and to image the heterogeneity of response of the common eukaryotic model organism C. reinhartii to a chemical gradient of the common herbicide DCMU (3-(3,4-dichlorophenyl)-1,1-dimethylurea).