Browsing by study line "Naturgeografi"

Diatoms (Bacillariophyta) are unicellular microalgae inhabiting nearly all aquatic environments on Earth. Some taxa are endemic to certain regions, whereas some are widely spread or even cosmopolitan. Diatoms’ species diversity and habitat selection support their use as bioindicators, and traditional water quality indices are based on species composition and index species. However, trait-based indices have gained interest in recent years and researchers believe that traits could potentially act as a useful tool in environmental assessment. Traits refers to the morphological, physiological and phenological properties of species, and they are closely linked to the species’ capacity to grow and reproduce in certain circumstances. Morphological variation in diatoms varies significantly between taxa and species. The possibilities of a diatom to adapt into changing habitat is a result of its capacity to alter its morphological properties. Urban and agricultural land use affect water resources negatively, and climate change acts as a reinforcing factor creating complex and mixed effects on aquatic environments. Global warming is and will proceed to be strongest near the poles and its unique and harsh habitats. Climate change by anthropogenic activities and environmental pollution has affected and will affect microbial communities and primary producers everywhere. Diatoms have a central role in global productivity and biogeochemical cycle, and changes in microbial cell size could have severe implications for food webs and energy transition of energy in the trophic system. The aim of this thesis was to monitor the morphological properties, including the size, shape and striae density, of G. parvulum and its link to different combinations two stressors: nutrient solution (PO4 and NO3) and limited light availability. Shading treatment had a clear effect on average cell width, but average cell length did not correlate with shading. Nutrient treatment did not alter the cell length but had some effect on striae density. However, it was concluded that striae count or head shape are not most suitable for indicator purposes, as they are affected by cell size. In conclusion, no clear variation patterns according to the nutrient or shading treatment were detected, but result suggest that the increased availability of light could alter the size of G. parvulum. Results could be blurred by the small sample size or the presence of cryptic or semi-cryptic species.

The stability of local organism communities is affected by multiple variables from historical dispersal factors of broad spatiotemporal scale to more local variables of ecosystem trophic level and disturbance variables. Streams are a very a unique living environment in this regard, as their hydrological circumstances and nutrient balance vary substantially throughout the year, disturbances reflect from upstream locations to downstream relatively fast and the dispersal created by current causes microorganism communities to resemble one another along upstream-downstream gradient. As such, stream habitats are temporally remarkably variable by their environmental conditions and on the other hand subject to continuous one-way migration from upstream sites. The population dynamics of stream micro-organisms differs greatly from lentic systems as a result. In this thesis the temporal stability of six Southern Finnish diatom communities was studied during the summer 2017. A clear gradient from urban to natural environments, characterized by their catchment’s land use variables was sought after in the initial study setting. The aim of the study was to recognize the most important variables affecting the stability of diatom communities as well as to study how the stability of communities differed between varying habitats characterized by their pwater quality and physical environment. In addition, the stability and performance of diatom indices IPS and TDI was studied. The sampling period of the study was conducted between 17th of May 2017 and 18th of October 2017, covering the majority of Southern Finnish growing period. In total eight samples were collected per site, primarily following the temporal cycle of 21 days. In addition to diatom samples the physicochemical water quality and physical environmental variables were studied from the sampling locations. These were used to recognize the central environmental variables affecting the changes observed in diatom communities. Linear regression analysis and a variety of multivariable analyses, such as non-metric multidimensional scaling (NMDS), canonical correspondence analysis (CCA) and generalized linear mixed models (GLMM) were utilized as statistical methods. The results indicated that the sampling sites differed significantly by their physicochemical water quality as well as their diatom communities. The diversity and structure of diatom communities was affected most strongly by variables representing the overall environmental stress and disturbance level, trophic level and local hydrology. The local species count was most strongly correlated with electrical conductivity, total phosphorus concentration and time elapsed since the onset of sampling period. The stability of diatom communities was mainly affected by environmental variables representing anthropogenic activity and trophic level of the ecosystem. The communities were generally most temporally stable in urban sampling locations, although they were temporally more variable than their natural habitat counterparts over short observation time span. The values of both studied diatom indices differed significantly between sampling locations. According to the results the IPS-index failed to reflect differences in physicochemical water quality. By contrast, the TDI-index was temporally relatively stable and also correlated better with physicochemical water quality variables. The results were mostly in accordance with the most crucial reference frame of the study field as well as the results of previous studies. As such, they can be seen to further reinforce the view that diatom communities are most species diverse in high trophic level and low environmental stress habitats. The temporal stability of the communities followed the same principles with the most stable communities being present in high environmental stress, low trophic level habitats.

Soil moisture influences various environmental and climatological processes and is an important part of the hydrological cycle. The processes influencing its spatial and temporal variation are complex and linked with each other as well as influenced by soil moisture itself which makes observing them challenging. This is especially true in cold regions where soil moisture has shown strong fine scale variation and influences numerous ecosystem processes. To test different hypotheses related to soil moisture and to simulate its variation, several hydrological process-based models have been developed. Understanding how these models differ from each other and how they describe soil moisture is crucial in order to use them effectively. For this study, three process-based models representing varying model approaches and answering different research questions were chosen and used to simulate the spatial and temporal variation of soil moisture in a small study area in northwestern Finland. JSBACH is a global-scale land surface model that simulates various geophysical and geochemical processes over land and in the boundary layer between land surface and the atmosphere. SpaFHy is a catchment scale hydrological model developed to simulate water balance and evapotranspiration in boreal forests. Ecohydrotools is a hydrological model used to study fine scale spatial variation in soil hydrology. The model results show clear similarities as well as differences when compared with each other and with field measurements of soil moisture. The strongest similarities are in distinguishing wetter and drier areas in the study area, although the actual moisture content estimations vary between the models. All models show difficulties in simulating finer scale spatial variation, particularly in drier areas. Temporal variation shows more similarities between the models, although there are also clear discrepancies with measurements and the models. These simulations show that there are several things influencing a model’s capability to simulate soil moisture variation. Varying data requirements, included processes as well as model design and purpose all influence the results, leading to varying estimations of soil moisture. Improving model predictions in cold environments requires better understanding of the underlying processes as well as more detailed information on the environmental variables influencing soil moisture.

Arctic soils store significant amounts of carbon deposited by plants and litter. Carbon is released from the soil in respiration due to plant roots and decomposition by microbes. In the northern hemisphere, carbon inputs from photosynthesis have exceeded releases of carbon to atmosphere via respiration. Arctic soils have been a globally remarkable carbon sink due to cold and waterlogged conditions. However, rising global temperatures and changes in hydrology have caused the carbon fluxes in soil-atmosphere interface to alter. Arctic areas are considered especially vulnerable to climate change and alterations in the arctic soil carbon pools could create powerful feedbacks to warming. Furthermore, drivers controlling soil respiration flux remain poorly known, especially their contributions in different environments and their dynamics in time. Thus, understanding soil respiration as a process is vital in understanding future changes in the global carbon cycle.The aim of this study was to identify environmental drivers of soil respiration in tundra at landscape-scale and their relative importance in different stages of growing season. The study area was a valley between two fells at Kilpisjärvi, Finland. Soil respiration was measured using the chamber method in 100 study sites on the 3 x 2 km landscape three times during the summer of 2018. Environmental data on soil microclimate and vegetation properties was gathered fromthe area as well. The impact of environmental conditions to respiration flux was studied using multiple generalized linear models with different explanatory variable combinations.Results suggest that abundant vegetation causes high respiration by providing resources for belowground microbes and creating extensive root network. Highest respiration was measured in peak growing season, when elevated temperatures stimulated respiration exclusively in tundra meadows. It seems that vegetation and soil parameters also define the temperature response of respiration. The flux increased with elevated temperatures only on soils that are assumed to have adequate nutrient and carbon composition to support higher respiration. This study suggests that onlandscape-scale, the resources provided by vegetation are of bigger importance to respiration than climatic changes both spatially and temporally.Moving forward, more empiricaldata is needed in order to accurately model future changes in respiration. Intense sampling efforts from the Arctic tundra areasthatcover the large spatial and temporal variabilityof respiration are necessary.

Microclimate research is an important part of research about our warming earth. Microclimate refers to a local climate that is partially independent of the free atmosphere formed in an area of a few square meters to a few square kilometers. In this study, the level of consideration of the microclimate is the air layer in the immediate vicinity of the earth's surface. Microclimates are characterized by air temperature, air humidity, timing of the seasons, and the variety of organisms that thrive in the area, which differ from the wider climate. Local microclimates arise from the interaction of atmospheric processes and environmental factors in the area. The thesis examines how the extreme temperatures of microclimates vary in different vegetation zones in Finland. Two research areas are located in the tundra vegetation zone in the northern parts of Finland, and the remaining five research areas are in the boreal vegetation zone. The research questions are: 1) How do the extreme temperatures (minimum and maximum temperatures) of the warmest month of the growing season, July, vary in the study areas? 2) Which environmental factors affect the extreme temperatures of the research areas? Environmental factors to be considered are ground level above sea level, relative ground level, slope, distance to the nearest bodies of water, canopy cover, solar radiation and windiness. According to the results, the minimum temperatures were statistically significantly affected by the canopy coverage mainly negatively, the absolute ground level mainly negatively and the slope, with the trend varying between negative, positive and unimodal depending on the study area. The environmental factors that had the greatest influence on the maximum temperatures were the absolute ground level, negatively in the south and positively in the north, the canopy coverage mostly negatively, and the relative ground level mostly positively. The research results were largely in line with the hypotheses. In the south, abundant forest vegetation lowered the maximum temperatures of forest environments and raised the minimum temperatures. In central Finland, in the study area covered by wetlands, lakes and fragmented forests, especially the distance to water bodies affected the extreme temperatures. In northern Finland, the tundra vegetation led to the strongest temperature fluctuations. The maximum temperatures of the research areas varied less than the minimum temperatures. The maximum temperatures in July remained between 21.3 and 31.7˚C degrees, the range was 10.4˚C. The minimum temperatures remained between -3.3 and 5.2 ˚C degrees, the range was 8.5 ˚C degrees. In the future, microclimate-related research in the Nordic countries could focus even more precisely on the interannual variations of micro-level temperature observations over a longer period of time, as well as on the specification of the characteristics that affect the temperatures in different vegetation zones.

Soil moisture plays a key role in ecosystems. Soil moisture varies spatially and temporally, and the variations are influenced by many different factors. On a large scale, climate has a large effect on soil moisture, but more locally, especially topography, soil and vegetation become important factors. In addition, mean soil moisture content affects whether soil moisture variations are greatest when soil is dry or moist. Climate change will significantly affect soil moisture around the world, and effects will also be visible in the boreal forest. Therefore, it is important to study soil moisture more comprehensively in boreal environment. The purpose of this thesis is to find out how soil moisture varies spatially and temporally, and how topography, soil and vegetation explain this variation in different parts of the boreal forest and in different environments. Study area covers eight areas of varying size (3,5–37 km2) in the boreal forest around Finland. Each study area has 44–96 study points from which soil moisture has been measured every 15 minutes during July 2020. Mean and standard deviation of soil moisture (response variables) of each research point were calculated from the measurements, of which the mean describes the spatial variation of soil moisture and the standard deviation the temporal variation. The response variables were explained by environmental variables. Variables explaining topography’s effect were altitude, SAGA wetness index (SWI), topographic position index (TPI) and radiation. Vegetation was explained by canopy cover and site fertility class, and soil was explained by soil class. The effect of environmental variables on spatial and temporal variations of soil moisture was analysed using a generalized additive model (GAM), which was fitted for each study area and for both response variables separately. Explanatory power of the models was examined with an adjusted R2 value using the bootstrap method. Relative importance of the individual environmental variables in the model was examined by randomizing the variables, and the direction of the effect of the environmental variables was examined using response curves. Soil moisture varied considerably spatially and temporally within the study areas and between the areas. Soil moisture was generally high in study areas with a lot of peatlands, and moisture varied most spatially usually in topographically heterogeneous areas. Often, the temporal variation of moisture was highest on dryer study areas and lowest on moister areas. Indeed, it was found that when the mean soil moisture was high, the standard deviation was often small and vice versa. Topographic factors influenced to the mean and standard deviation of soil moisture more in the northern than in the southern regions, while the role of canopy cover was emphasized in the southern regions when explaining the mean moisture. Soil influenced to the moisture more in the northern than in the southern areas. From all variables, SWI clearly explained the best both the mean and standard deviation of moisture. Canopy cover and radiation also explained well the mean moisture in a part of the study areas. In addition to SWI, the standard deviation of moisture was best explained by site fertility class and soil class. Altitude and TPI rarely explained the mean and standard deviation of moisture well. SWI often increased moisture and decreased moisture’s temporal variability in the study areas, but the directions of the effects of other environmental variables varied a lot between areas. This study shows that the large spatial and temporal variability of soil moisture in different environments of the boreal forest is dominated by different factors, and even the same environmental factors affect soil moisture in very different ways between areas. Research must be continued to get a better general picture of the factors affecting soil moisture variations in the boreal forest, and to be able to prepare better for the environmental changes caused by climate change.

Wind is often difficult to include in microclimatic research due to its high spatial and temporal variability. The development of wind speed and direction measurement methods together with the increase in available surface wind models and computational resources enable wind field simulation on a high temporal and spatial resolution. Winds were measured during summer 2018 in a topographically varying landscape of mostly low vegetation in Finnish Lapland. Six ultrasonic anemometers were placed to measure wind speed and direction in positions of varying topography and vegetation. Based on June 2018 data, topography has a clear effect on wind speeds but the effect of vegetation was not visible from the data. The highest average wind speeds measured on the study area varied between 6.3 m/s – 13.2 m/s, and highest gust wind speeds between 10.1 m/s – 17.1 m/s. The anemometers' data was used in modeling wind fields with WindNinja application to study areas of both topographic and vegetational variation and also to a larger area surrounding the study site. WindNinja is a diagnostic wind model, into which the data were applied as virtual weather stations. The modeling results were compared to measured wind speeds by leave-one-out validation. Spearman correlation coefficients between measured and simulated average wind speeds varied between 0.28 – 0.59, RMSE values between 1.1 – 2.6 m/s and MAE values between 0.8 – 2.0 m/s. The respective values for gust wind simulations were 0.42 – 0.63, 1.6 – 2.7 m/s and 1.2 – 2.1 m/s. Overall WindNinja underpredicted high wind speeds and overpredicted low speeds. In modeling results, topography had a clear effect on regional and local wind fields on all modeling areas Winds were strongest on top of ridges and weakest in depressions. Vegetation had very local effects to wind speed by increasing and lowering it. The results give a good overview of the small-scale windiness variability in the modeling areas. To further examine the micro- and mesoclimatic effects of windiness, the results of this thesis should be combined with other research conducted in the area. WindNinja has potential to further use in high resolution wind modeling, which is an important factor of microclimatic research in the changing climate. However, the software’s graphical user interface is not optimal for modeling longer periods of wind data.

Maankäytön muutokset sekä lisääntynyt ihmistoiminta ovat muokanneet ympäristöä merkittävästi viimeisten vuosikymmenien aikana. Nämä muutokset näkyvät ympäristön tilan heikkenemisenä, ja vaikuttavat myös vesistöjen tilaan. Vaikutukset ovat suurimpia kaupunkialueilla, jossa ihmistoiminta on voimakkainta. Kaupunkialueiden vedenlaatuun sekä hulevesikuormitukseen on alettu kiinnittää yhä enemmän huomiota, sillä vedenlaatu vaikuttaa niin ihmisten, ympäristön kuin eliöstönkin hyvinvointiin. Vedenlaadun tutkimuksessa hyödynnetään yhä enemmän erilaisia paikkatietoaineistoja sekä tilastollisia keinoja varsinaisten vedenlaadun mittaustulosten ohella, kuten tässäkin tutkielmassa on tehty. Hyödynnettäviä paikkatietoaineistoja on saatu Espoon kaupungilta, sekä internetin avoimen datan palveluista. Tässä tutkielmassa keskitytään tarkastelemaan vedenlaatua Espoon Lippajärveen ja Pitkäjärveen laskevissa ojissa, puroissa, sekä sadevesiviemäreissä. Erillisiä näytteenottopisteitä tutkielmassa oli 26, ja näytteenottokierroksia neljä tutkimusjakson aikana. Tutkimuksen 26 valuma-alueesta pienin on alle 0,01 km2, ja suurin yli 30km2. Yleisin valuma-alueiden kokoluokka oli 0,1-0,4 km2 välillä. Tutkimuksen tavoitteena oli arvioida vedenlaatua ja suurimpia hulevesikuormituksen lähteitä vedenlaadun mittaustulosten, paikkatietoanalyysien sekä tilastollisten keinojen avulla. Tutkielma on osa Espoon kaupungin Lippajärven ja Pitkäjärven kunnostushanketta. Tutkielmassa vedenlaatua arvioidaan kokonaisravinteiden, raskasmetallien sekä ainespitoisuuden osalta. Näiden yhteyttä ympäristömuuttujiin arvioitiin korrelaatioanalyysien sekä vedenlaadun tulosten luokittelun avulla. Tutkimustuloksissa ilmeni selkeitä korrelaatioita maankäytön, valuma-alueiden koon, vettä läpäisemättömän pinnan sekä uomien tiheyden välillä. Korrelaatioanalyysissä metsät korreloivat negatiivisesti useamman (3) vedenlaadun muuttujan kanssa, eli niillä oli vedenlaatua parantava vaikutus. Rakennetut alueet sekä vettä läpäisemätön pinta korreloivat yhteensä positiivisesti neljän vedenlaadun muuttujan kanssa, eli niillä oli vedenlaatua heikentävä vaikutus. Maatalousalueet korreloivat positiivisesti fosforin sekä kiintoaineen kanssa. Tutkimustulokset vastasivat osittain aiempia tieteenalan tutkimustuloksia, kuten fosforin sekä maatalousalueiden positiivisia korrelaatioita, rakennettujen alueiden ja raskasmetallien positiivisia korrelaatioita, sekä metsien ja vedenlaadun muuttujien negatiivisia korrelaatioita. Vedenlaatu vaihteli huomattavasti valuma-alueiden välillä, mutta molemmilta järviltä erottui heikomman vedenlaadun keskittymiä. Pitkäjärvellä heikoimman vedenlaadun alue oli Laaksolahdenrannan ja Jupperin välillä, sekä Vanhakartanon alueella, ja Lippajärvellä järven länsipuolella. Näillä alueilla hulevesien hallintaan tulisi kiinnittää erityistä huomiota, esimerkiksi hulevesien hallintakeinojen sijoittamista suunniteltaessa.