Studying the diurnal and seasonal acclimation of photosystem Ii using chlorophyll-a fluorescence

A small fraction of the energy absorbed in the light reactions of photosynthesis is re-emitted as chlorophyll-a fluorescence. Chlorophyll-a fluorescence and photochemistry compete for excitation energy in photosystem II (PSII). Therefore, changes in the photochemical capacity can be detected through analysis of chlorophyll fluorescence. Chlorophyll fluorescence techniques have been widely used to follow the diurnal (fast), and the seasonal (slow) acclimation in the energy partitioning between photochemical and non-photochemical processes in PSII. Energy partitioning in PSII estimated through chlorophyll fluorescence can be used as a proxy of the plant physiological status, and measured at different spatial and temporal scales. However, a number of technical and theoretical limitations still limit the use of chlorophyll fluorescence data for the study of the acclimation of PSII. The aim of this Thesis was to study the diurnal and seasonal acclimation of PSII in field conditions through the development and testing of new chlorophyll fluorescence-based tools, overcoming these limitations. A new model capable of following the fast acclimation of PSII to rapid fluctuations in light intensity was developed. The model was used to study the rapid acclimation in the electron transport rate under fluctuating light. Additionally, new chlorophyll fluorescence parameters were developed for estimating the seasonal acclimation in the sustained rate constant of thermal energy dissipation and photochemistry. The parameters were used to quantitatively evaluate the effect of light and temperature on the seasonal acclimation of PSII. The results indicated that light environment not only affected the degree but also the kinetics of response of the acclimation to temperature, which was attributed to differences in the structural organization of PSII during seasonal acclimation. Furthermore, zeaxanthin-facilitated thermal dissipation appeared to be the main mechanisms modulating the fraction of absorbed energy being dissipated thermally during winter in field Scots pine. Finally, the integration between diurnal and seasonal acclimation mechanisms was studied using a recently developed instrument MONI-PAM (Walz GmbH, Germany) capable of continuously monitoring the energy partitioning in PSII.

Fluorescence properties of Baltic Sea phytoplankton

To obtain data on phytoplankton dynamics with improved spatial and temporal resolution, and at reduced cost, traditional phytoplankton monitoring methods have been supplemented with optical approaches. In this thesis, I have explored various fluorescence-based techniques for detection of phytoplankton abundance, taxonomy and physiology in the Baltic Sea. In algal cultures used in this thesis, the availability of nitrogen and light conditions caused changes in pigmentation, and consequently in light absorption and fluorescence properties of cells. In the Baltic Sea, physical environmental factors (e.g. mixing depth, irradiance and temperature) and related seasonal succession in the phytoplankton community explained a large part of the seasonal variability in the magnitude and shape of Chlorophyll a (Chla)-specific absorption. The variability in Chla-specific fluorescence was related to the abundance of cyanobacteria, the size structure of the phytoplankton community, and absorption characteristics of phytoplankton. Cyanobacteria show very low Chla-specific fluorescence. In the presence of eukaryotic species, Chla fluorescence describes poorly cyanobacteria. During cyanobacterial bloom in the Baltic Sea, phycocyanin fluorescence explained large part of the variability in Chla concentrations. Thus, both Chla and phycocyanin fluorescence were required to predict Chla concentration. Phycobilins are major light harvesting pigments for cyanobacteria. In the open Baltic Sea, small picoplanktonic cyanobacteria were the main source of phycoerythrin fluorescence and absorption signal. Large filamentous cyanobacteria, forming harmful blooms, were the main source of the phycocyanin fluorescence signal and typically their biomass and phycocyanin fluorescence were linearly related. Using phycocyanin fluorescence, dynamics of cyanobacterial blooms can be detected at high spatial and seasonal resolution not possible with other methods. Various taxonomic phytoplankton pigment groups can be separated by spectral fluorescence. I compared multivariate calibration methods for the retrieval of phytoplankton biomass in different taxonomic groups. Partial least squares regression method gave the closest predictions for all taxonomic groups, and the accuracy was adequate for phytoplankton bloom detection. Variable fluorescence has been proposed as a tool to study the physiological state of phytoplankton. My results from the Baltic Sea emphasize that variable fluorescence alone cannot be used to detect nutrient limitation of phytoplankton. However, when combined with experiments with active nutrient manipulation, and other nutrient limitation indices, variable fluorescence provided valuable information on the physiological responses of the phytoplankton community. This thesis found a severe limitation of a commercial fast repetition rate fluorometer, which couldn t detect the variable fluorescence of phycoerythrin-lacking cyanobacteria. For these species, the Photosystem II absorption of blue light is very low, and fluorometer excitation light did not saturate Photosystem II during a measurement. This thesis encourages the use of various in vivo fluorescence methods for the detection of bulk phytoplankton biomass, biomass of cyanobacteria, chemotaxonomy of phytoplankton community, and phytoplankton physiology. Fluorescence methods can support traditional phytoplankton monitoring by providing continuous measurements of phytoplankton, and thereby strengthen the understanding of the links between biological, chemical and physical processes in aquatic ecosystems.

Allelopathic effects of filamentous cyanobacteria on phytoplankton in the Baltic Sea

Eutrophication and enhanced internal nutrient loading of the Baltic Sea are most clearly reflected by increased late-summer cyanobacterial blooms, which often are toxic. In addition to their toxicity to animals, phytoplankton species can be allelopathic, which means that they produce chemicals that inhibit competing phytoplankton species. Such interspecific chemical warfare may lead to the formation of harmful phytoplankton blooms and the spread of exotic species into new habitats. This is the first report on allelopathic effects in brackish-water cyanobacteria. The experimental studies presented in this thesis showed that the filamentous cyanobacteria Anabaena sp., Aphanizomenon flos-aquae and Nodularia spumigena are capable of decreasing the growth of other phytoplankton species, especially cryptophytes, but also diatoms. The detected allelopathic effects are rather transitory, and some co-occurring species show tolerance to them. The allelochemicals are excreted during active growth and they decrease cell numbers, chlorophyll a content and carbon uptake of the target species. Although the more specific modes of action or chemical structures of the allelochemicals remain to be studied, the results clearly indicate that the allelopathic effects are not caused by the hepatotoxin, nodularin. On the other hand, cyanobacteria stimulated the growth of bacteria, other cyanobacteria, chlorophytes and flagellates in a natural phytoplankton community. In a long-term data analysis of phytoplankton abundances and hydrography of the northern Baltic Sea, a clear change was observed in phytoplankton community structure, together with a transition in environmental factors, between the late 1970s and early 2000s. Surface water salinity decreased, whereas water temperature and the concentration of dissolved inorganic nitrogen increased. In the phytoplankton community, the biomass of cyanobacteria, chrysophytes and chlorophytes significantly increased, and the late-summer phytoplankton community became increasingly cyanobacteria-dominated. In contrast, the biomass of cryptophytes decreased. The increased temperature and nutrient concentrations probably explain most of the changes in phytoplankton, but my results suggest that the possible effect of chemically mediated biological interactions should also be considered. Cyanobacterial allelochemicals can cause additional stress to other phytoplankton in the nutrient-depleted late-summer environment and thus contribute to the formation and persistence of long-lasting cyanobacterial mass occurrences. On the other hand, cyanobacterial blooms may either directly or indirectly promote the growth of some phytoplankton species. Therefore, a further increase in cyanobacteria will probably shape the late-summer pelagic phytoplankton community by stimulating some species, but inhibiting others.

Aerosol size distribution and its connection to cloud droplet number concentration

In order to predict the current state and future development of Earth s climate, detailed information on atmospheric aerosols and aerosol-cloud-interactions is required. Furthermore, these interactions need to be expressed in such a way that they can be represented in large-scale climate models. The largest uncertainties in the estimate of radiative forcing on the present day climate are related to the direct and indirect effects of aerosol. In this work aerosol properties were studied at Pallas and Utö in Finland, and at Mount Waliguan in Western China. Approximately two years of data from each site were analyzed. In addition to this, data from two intensive measurement campaigns at Pallas were used. The measurements at Mount Waliguan were the first long term aerosol particle number concentration and size distribution measurements conducted in this region. They revealed that the number concentration of aerosol particles at Mount Waliguan were much higher than those measured at similar altitudes in other parts of the world. The particles were concentrated in the Aitken size range indicating that they were produced within a couple of days prior to reaching the site, rather than being transported over thousands of kilometers. Aerosol partitioning between cloud droplets and cloud interstitial particles was studied at Pallas during the two measurement campaigns, First Pallas Cloud Experiment (First PaCE) and Second Pallas Cloud Experiment (Second PaCE). The method of using two differential mobility particle sizers (DMPS) to calculate the number concentration of activated particles was found to agree well with direct measurements of cloud droplet. Several parameters important in cloud droplet activation were found to depend strongly on the air mass history. The effects of these parameters partially cancelled out each other. Aerosol number-to-volume concentration ratio was studied at all three sites using data sets with long time-series. The ratio was found to vary more than in earlier studies, but less than either aerosol particle number concentration or volume concentration alone. Both air mass dependency and seasonal pattern were found at Pallas and Utö, but only seasonal pattern at Mount Waliguan. The number-to-volume concentration ratio was found to follow the seasonal temperature pattern well at all three sites. A new parameterization for partitioning between cloud droplets and cloud interstitial particles was developed. The parameterization uses aerosol particle number-to-volume concentration ratio and aerosol particle volume concentration as the only information on the aerosol number and size distribution. The new parameterization is computationally more efficient than the more detailed parameterizations currently in use, but the accuracy of the new parameterization was slightly lower. The new parameterization was also compared to directly observed cloud droplet number concentration data, and a good agreement was found.

Modelling boreal forest CO2 exchange and seasonality

Man-induced climate change has raised the need to predict the future climate and its feedback to vegetation. These are studied with global climate models; to ensure the reliability of these predictions, it is important to have a biosphere description that is based upon the latest scientific knowledge. This work concentrates on the modelling of the CO2 exchange of the boreal coniferous forest, studying also the factors controlling its growing season and how these can be used in modelling. In addition, the modelling of CO2 gas exchange at several scales was studied. A canopy-level CO2 gas exchange model was developed based on the biochemical photosynthesis model. This model was first parameterized using CO2 exchange data obtained by eddy covariance (EC) measurements from a Scots pine forest at Sodankylä. The results were compared with a semi-empirical model that was also parameterized using EC measurements. Both of the models gave satisfactory results. The biochemical canopy-level model was further parameterized at three other coniferous forest sites located in Finland and Sweden. At all the sites, the two most important biochemical model parameters showed seasonal behaviour, i.e., their temperature responses changed according to the season. Modelling results were improved when these changeover dates were related to temperature indices. During summer-time the values of the biochemical model parameters were similar at all the four sites. Different control factors for CO2 gas exchange were studied at the four coniferous forests, including how well these factors can be used to predict the initiation and cessation of the CO2 uptake. Temperature indices, atmospheric CO2 concentration, surface albedo and chlorophyll fluorescence (CF) were all found to be useful and have predictive power. In addition, a detailed simulation study of leaf stomata in order to separate physical and biochemical processes was performed. The simulation study brought to light the relative contribution and importance of the physical transport processes. The results of this work can be used in improving CO2 gas exchange models in boreal coniferous forests. The meteorological and biological variables that represent the seasonal cycle were studied, and a method for incorporating this cycle into a biochemical canopy-level model was introduced.

Water quality estimation by optical remote sensing in boreal lakes

In lake-rich regions, the gathering of information about water quality is challenging because only a small proportion of the lakes can be assessed each year by conventional methods. One of the techniques for improving the spatial and temporal representativeness of lake monitoring is remote sensing from satellites and aircrafts. The experimental material included detailed optical measurements in 11 lakes, air- and spaceborne remote sensing measurements with concurrent field sampling, automatic raft measurements and a national dataset of routine water quality measurements from over 1100 lakes. The analyses of the spatially high-resolution airborne remote sensing data from eutrophic and mesotrophic lakes showed that one or a few discrete water quality observations using conventional monitoring can yield a clear over- or underestimation of the overall water quality in a lake. The use of TM-type satellite instruments in addition to routine monitoring results substantially increases the number of lakes for which water quality information can be obtained. The preliminary results indicated that coloured dissolved organic matter (CDOM) can be estimated with TM-type satellite instruments, which could possibly be utilised as an aid in estimating the role of lakes in global carbon budgets. Based on the results of reflectance modelling and experimental data, MERIS satellite instrument has optimal or near-optimal channels for the estimation of turbidity, chlorophyll a and CDOM in Finnish lakes. MERIS images with a 300 m spatial resolution can provide water quality information in different parts of large and medium-sized lakes, and in filling in the gaps resulting from conventional monitoring. Algorithms that would not require simultaneous field data for algorithm training would increase the amount of remote sensing-based information available for lake monitoring. The MERIS Boreal Lakes processor, trained with the optical data and concentration ranges provided by this study, enabled turbidity estimations with good accuracy without the need for algorithm correction with field measurements, while chlorophyll a and CDOM estimations require further development of the processor. The accuracy of interpreting chlorophyll a via semi empirical algorithms can be improved by classifying lakes prior to interpretation according to their CDOM level and trophic status. Optical modelling indicated that the spectral diffuse attenuation coefficient can be estimated with reasonable accuracy from the measured water quality concentrations. This provides more detailed information on light attenuation from routine monitoring measurements than is available through the Secchi disk transparency. The results of this study improve the interpretation of lake water quality by remote sensing and encourage the use of remote sensing in lake monitoring.