Browsing by study line "Physical Geography"
Now showing items 21-40 of 42
-
(2023)Bioklimaattinen mallinnus on keskeinen biogeografinen menetelmä, jolla tutkitaan lajilevinneisyyden ja ilmaston välistä yhteyttä. Tutkimuksessa tarkasteltiin, kuinka hyvin lämpö- ja kosteusolosuhteita kuvaavat bioklimaattiset muuttujat selittivät tundran putkilokasvilajien levinneisyyttä kahdella mittakaavatasolla ja mitkä muuttujat olivat suhteellisesti tärkeimpiä eri lajeille. Lisäksi tarkasteltiin muuttujien alueellista vaihtelua. Biogeografinen tutkimus on erityisen tärkeää tundralla – esimerkiksi Suomen tunturipaljakan putkilokasvilajeista 16 % on uhanalaisia, ja tämän luvun odotetaan kasvavan ilmaston lämpenemisen myötä. Tutkimus sijoittui Mallatuntureiden ja Ailakkavaaran alueille Luoteis-Lappiin. Mallinnettavia putkilokasvilajeja oli 26, joista kahdeksan on arktis-alpiinisia ja muut boreaalisia. Bioklimaattisia muuttujia johdettiin kahdesta ilmastoaineistoista: hienon mittakaavan mikroilmastoaineistosta sekä mesomittakaavan sääasemien mittauksista interpoloidusta aineistosta, joka kuvaa makroilmastollisia olosuhteita. Bioklimaattisten muuttujien alueellista vaihtelua tutkittiin karttatarkastelun avulla ja aineistojen erojen tilastollista merkitsevyyttä arvioitiin tilastollisin tunnusluvuin. Malleja rakennettiin kolmella menetelmällä: yleistetyt lineaariset ja addittiviset mallit sekä yleistetyt luokittelupuut. Mikroilmastomallien muuttujia olivat kasvukauden lämpöolosuhteita kuvaava tehoisa lämpösumma, talven olosuhteita kuvaava helmikuun minimilämpötila ja kesän kosteusolosuhteita kuvaava heinäkuun maaperän kosteus. Makroilmastomalleissa oli muuttujina lämpösumma, helmikuun minimilämpötila ja kesän sademäärä. Mallien suorituskykyä arvioitiin AUC-arvojen avulla ja muuttujien tärkeydet selvitettiin yleistetyt luokittelupuut -menetelmällä. Hienon mittakaavan bioklimaattiset muuttujat kuvasivat selkeästi tarkemmin lämpö- ja kosteusolosuhteiden alueellista vaihtelua lyhyillä etäisyyksillä kuin karkeamman mittakaavan muuttujat. Eri mittakaavojen muuttujien erot olivat myös tilastollisesti merkitseviä. Vaikka bioklimaattisten mallien suorituskyky oli keskimäärin heikko, mikroilmastomallien AUC 0,69 oli korkeampi kuin makroilmastomallien AUC 0,63. Ero suorituskyvyssä oli siis tilastollisesti merkitsevä. Mikroilmastomallit selittivät paremmin yksittäisten putkilokasvilajien levinneisyyttä kuin makroilmastomallit, sillä suorituskyvyltään hyviä tai erinomaisia malleja oli enemmän. Alle puolelle lajeista suhteellisesti tärkein bioklimaattinen muuttuja oli sama eri mittakaavoilla. Tehoisa lämpösumma oli tärkein muuttuja useimmille arktis-alpiinisille ja boreaalisille lajeille karkeammassa mittakaavassa, kun taas heinäkuun keskimääräinen maaperän kosteus oli tärkein muuttuja useimmille arktis-alpiinisille lajeille hienossa mittakaavassa. Tehoisa lämpösumma oli tärkein muuttuja useimmille boreaalisille lajeille myös hienossa mittakaavassa. Tutkimuksen perusteella tundran mikro- ja makroilmastolliset lämpö- ja kosteusolosuhteet eroavat merkittävästi toisistaan, millä on merkitystä esimerkiksi lajien suojelusuunnittelua kehitettäessä ilmaston lämmetessä. On tärkeää huomioida, millaisia ilmasto-olosuhteita bioklimaattisten mallien aineistot kuvaavat, kun tutkitaan tundran putkilokasvilajien suhdetta ympäristöönsä hienossa mittakaavassa.
-
(2021)Eutrophication and climate change are considered to be the worst threats to the Baltic Sea ecosystem. The goal of this work is to understand, what are the consequences of environmental change to the distribution of Fucus spp., one of the key species of the Baltic Sea. Of particular interest here is to find the role of light and water turbidity in defining Fucus spp. distribution since scenario models of the effect of water turbidity defining the distribution has yet remained less studied. Nemo-SCOBI model of physical and biogeochemical conditions of the Baltic Sea calibrated according to different eutrophication and climate change scenarios were used in species distribution modelling (SDM) to predict future distribution of Fucus spp. The SDM method that was used was a regression-tree-based machine-learning generalized boosting method (GBM). In the modelling over 30 000 species presence and absence observations and six environmental variables (temperature, salinity, light attenuation, depth attenuated wave exposition and two seafloor types) were used. Water turbidity decreased in all scenarios in the areas where Fucus spp. occur but the BSAP was more beneficial scenario than the worst case scenario. Salinity decreased more and temperature increased less in the RCP8.5 scenario than in the RCP4.5 scenario. On top of that temperature decreased in the west coast of Finland in the RCP8.5 scenario. Suitable area for Fucus spp. declined in all scenarios so that the average occurrence probability decreased 11–30 percentage points. If no climate and eutrophication objectives (the Baltic Sea Action Plan and the RCP4.5) were met the average occurrence probability declined 25 percentage points. The situation for Fucus spp. is quite alarming because even if all the objectives would be achieved the suitable environment will nevertheless decline. If no actions will be taken in order to reduce nutrients the average occurrence probability declines 11–25 percentage points. Temperature decline in the RCP8.5 scenarios is thought to be caused by increasing upwelling events in the future, which may increase nutrient amounts in the coastal waters. The weak response to light and temperature and strong response to salinity and the fact that salinity decreased in all scenarios may explain why suitable areas decreased in all scenarios. There were some inconsistencies between the results and literature since the most optimistic scenario was the RCP4.5 & worst case, where BSAP goals are not achieved. This can be due to lack of species observations in the whole environmental gradients. The prediction results in the areas where water will be clearer in the future are not reliable and presumably more positive than these results show. While the BSAP scenarios may be too pessimistic the results of worst case scenarios are more reliable.
-
(2022)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.
-
(2020)A warming trend of annual average surface temperatures since pre-industrial times has been observed globally. High-arctic area of Svalbard, Norway is undergoing amplified change of annual average temperatures when compared to the global average. Decline of glaciers in western Svalbard has been ongoing for several decades, and in the recent past, rapid biological successions have taken place. These changes have likely had effect on regional scale carbon dynamics at Svalbard’s moss tundra areas. Possibly indicating onset of paludification process of these areas. However, palaeoecological studies from the area are scarce, and the response of high-latitude moss tundra areas to past or ongoing climate change, are still not fully understood. This thesis aimed to bring forward information of changes in recent organic matter and carbon accumulation rates at Svalbard, Norway. Soil profiles were collected from four moss tundra sites, located on coastal areas and fjords descending towards Isfjorden, on the western side of Spitsbergen island. Radiocarbon (14C) and lead (210Pb) dating methods with novel age-depth modelling and soil property analyses, were used to reconstruct recent organic matter and carbon accumulation histories from 1900 AD to 2018 AD. Accumulation histories were supported by meteorological measurements from the area. In addition, annual maximum value Normalized Difference Vegetation Indices for 1985 AD till 2018 AD period were produced, to study vegetation succession in the recent past. Lastly, possibility to predict spatiotemporal variation of soil carbon accumulation with satellite derived vegetation indices was assessed. Development from predominantly mineral soils to organic soils was distinguishable within multiple soil profiles, pointing to potential paludification. Recent apparent carbon accumulation rates showed an increasing trend. Supporting meteorological data and literature suggest that regional abiotic and biotic factors in synergy with weather and climate are contributing to this observed trend. Vegetation indices pointed to major changes in vegetation composition and productivity. However, investigation of relationship between recent carbon accumulation rates and vegetation indices did not produce reliable results. Spatiotemporal heterogeneity of carbon soil-atmosphere fluxes presently imposes large challenges for such modelling. To alleviate this problem, efforts for more efficient synergetic use of field sampling and remote sensing -based material should be undertaken, to improve modelling results.
-
(2019)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.
-
Pohjoisboreaalisen järven ja sen valuma-alueen puron metaanivuon alueellinen ja ajallinen vaihtelu (2021)Methane is an important greenhouse gas in the global atmosphere and its concentration has more than doubled compared to preindustrial times. Fresh water lakes and streams are substantial sources of methane. However, the estimations of their role in the global methane budget vary significantly and not until the 21st century has the understanding of their role as substantial methane sources increased. In the boreal zone, lakes produce as much as 30 % of the methane emissions. In this study, we examine spatial and temporal changes in methane fluxes from northern boreal lake Pallasjärvi and from a small stream located in its catchment area between June and November of 2020. We also examine the factors that explain the spatial and temporal changes in the methane fluxes, both lake and stream. Lake and stream methane fluxes were measured every other week between June and August, once a week in September, and once in the beginning of November using the chamber method. During the chamber measurements we also measured water surface temperature. Furthermore, at the stream sites we measured the water flow rate. At the lake measurement points we measured the water depth in November, which we calibrated to apply to the entire measurement period using water pressure logger. In March 2021, we measured the depth of the sediment layer at the lake sites. We also used CORINE-landcover data to model stream methane fluxes and for the lake, we used Finnish Meteorological Institute’s wind speed and direction dataset. We used these variables in order to explain the spatial and temporal variation of the lake and the stream methane fluxes using correlation analysis and linear mixed models. In this study, we find that water surface temperature, water depth, and wind were significant variables in explaining the lake methane fluxes. Respectively, landcover and surface water temperature explained the stream methane flux. From a temporal perspective, the strongest fluxes were measured between June and July at the lake sites and August and the beginning of September at the stream sites. Methane fluxes were divided spatially in two different groups at both lake and stream sites. At the lake sites, the strongest fluxes were measured in the shallow Pallaslompolo area and the weakest at the larger and deeper main basin of the lake. At the stream sites, the fluxes were also divided in two groups, the upstream’s weak fluxes and the downstream’s strong fluxes. According to the results, the temporal change of flux in the lake area is controlled by the changes in the factors underlying the methane production, and the differences in the lake basin depth control the spatial change of flux. The temporal change of stream methane flux depends on the changes in the methane production in the stream and its catchment area, while the spatial change depends on the changes in the landcover along the stream. However, more research and data are needed about the lake sediment layer temperature and oxygen levels, the water methane concentration, and stream catchments with different landcovers, which all impact the methane fluxes.
-
(2024)Deforestation is an ongoing issue worldwide, and the loss of forests, coupled with climate change, is causing significant changes in global biodiversity and ecosystem functioning. Currently, forests cover approximately 13% of the land area in the United Kingdom, making it one of the least forested countries in Europe. Reforestation efforts aim to increase forest area, ensuring the provision of ecosystem services, biodiversity, carbon storage, and species conservation. The goal in United Kingdom is to increase forest cover from 13% to 17% nationwide by 2050. However, research focusing on the impacts of climate change largely relies on large-scale climates over areas greater than 1 km². Broad-scale climates also called macroclimates affect large areas on a long-term and are spatially very broad scale. Many species, however, experience significantly different temperatures and weather conditions from macroclimates. These microrefugias created by microclimates can provide habitats for species requiring cooler conditions in changing climates. Microclimates have a lot of impact for forest ecology, as they enhance carbon sequestration, microbial activity, and decomposition processes in forests. Many different factors influence the formation of microclimates, such as solar radiation, air temperature, precipitation, soil temperature, humidity, and wind. Vegetation affects radiation and wind near the ground, creating the characteristic microclimate of each area. Buffering refers to the ability of forests to absorb or resist changes in temperature, thereby maintaining more stable temperature conditions compared to temperatures outside the forest. This study aims to find answers on the questions 1. How well can forests buffer macroclimate temperatures and create microclimates? 2.What kind of forest structures create microclimates that differ from the macroclimate? 3.Which types of forests planted in Scotland best support the creation of microrefugia? For this study, microclimate measurements and remote sensing data (TLS) were collected from 21 forest sites in England and Scotland. Macroclimate temperatures were determined using ERA5-Land data and nearby weather stations temperature data. By using linear models and statistical analyses, slope values were made for each forest plot to represent buffering. The results indicate what types of forests enhance temperature buffering and create microclimate conditions. The results indicate that broadleaf and coniferous forests effectively buffer temperatures during the leaf-on period, while their effectiveness diminishes during the leaf-off period. Broadleaf forests showed buffering during the leaf-on period but showed reduced buffering during the leaf-off period. Coniferous forests maintained better buffering during the leaf-on period and low buffering during the leaf-off period. Monoculture forests provided consistent buffering, while older and multi-age forests performed best in both periods, demonstrating the importance of structural complexity and diversity. Certain species, such as spruce, Scots pine, and oak, showed strong buffering capabilities year-round. The linear mixed-effects model confirmed that forest structural traits such as, Foliage Height Diversity and Relative Height and other factors such as hillslope, elevation, and tree type significantly influence temperature buffering. Maintaining diverse and structurally complex forests with a mix of species like spruce, Scots pine, and oak is essential for optimizing temperature buffering and creating stable microclimates and microrefugia. These forests can better withstand temperature fluctuations and provide habitats for species affected by climate change. The study highlights the importance of long-term forest growth and diverse understories in enhancing forest resilience and ecological stability. Further research is needed to understand the broader implications of forest management practices on biodiversity and ecosystem functioning. Further research is also needed in the planning of reforestation in Scotland to understand where reforestation can be most effectively implemented.
-
(2019)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.
-
(2020)Soils are important stocks of carbon and the soil-atmosphere CO2 flux is the second largest carbon flux between ecosystems and the atmosphere. Soil respiration is in previous studies considered to be mostly controlled by soil moisture and temperature, but also the activity of soil macrofauna. In African semi-arid savannas these parameters are controlled by seasonality. Mound-building termites are abundant in these savannas and in addition to the carbon cycle, they affect soil properties when building mounds and foraging outside them. Gas exchange and heat transfer in mounds is a complex phenomenon that varies depending on mound architecture and environment variables. Mound ventilation brings the CO2 generated in termite and their nest metabolism outside the mounds. CO2 emissions of termites, especially outside their mounds, should be studied to clarify their impact on the savanna soil respiration. In attempt to understand soil respiration around termite mounds, soil respiration rates was measured from surrounding area of six mounds of fungus-growing termite species Macrotermes michaelseni and Macrotermes subhyalinus using closed static chamber method in Tsavo ecosystem, southern Kenya. Measurements were made during the three assumed rainy seasons, in November 2016, April 2017, and December 2017. Research focused whether CO2 emissions come from the soil or from termites. The effect of prevailing wind was also studied to understand the role of mound ventilation better. Soil moisture, soil temperature, and the amount of rainfall were also measured and their effect on respiration was studied. The results show that a single reason for the changes in soil respiration rates around termite mounds is difficult to find. Most of the variation between measurement sites and measurement periods were due to changes in soil moisture. Prevailing wind direction was also found to be possible reason for changes in soil respiration rates. Soil respiration rates were higher near the mounds, so termite activity or changes in soil properties caused by them are assumed to be a contributing factor. Due to limited amount of data, many of the uncertainties on the subject should be further researched.
-
(2020)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.
-
(2024)Boreal soils are vital carbon reservoirs for the Earth, playing a crucial role in the global carbon cycle. The boreal landscape is a combination of small-scale variation of forests and wetlands with widely varying total carbon stocks. To understand these carbon dynamics, it is important to examine the factors that drive the C stock sizes. This thesis examines the variability of soil organic carbon, the environmental factors that explain it and the reliability of different modelling methods for SOC variation. The data consists of environmental data produced by the BioGeoClimate Modelling Lab, 129 soil samples collected from the study area, and their annealing results. SOC stocks have been modelled using three different methods: Generalized Linear Models, Generalized Additive Models, Generalized Boosted Methods. The results of the study show that the main factors explaining the variation in soil carbon are soil moisture and the presence of wetlands, and to a moderate extent slope, potential incoming solar radiation and canopy height. The estimated total carbon stock of the 130 km² study area is estimated to be about 1 858 620 016.3 Kg, with the largest stocks located in wetlands and GAM having the best predictive performance. Although the amount of carbon is not directly comparable to other studies, the results show similarities in the spatial distribution of carbon compared to other studies.
-
(2022)The Arctic is facing a major turning point with climate change and the region's climate will experience a particularly sharp rise in temperature. Subarctic ponds are important habitats and shelters for many organisms in the area but are nevertheless poorly known compared to larger water bodies. Along with climate change, the importance of studying ponds becomes more important as they are the first to manifest a changing climate. Factors affecting the water properties of subarctic ponds include the characteristics of the catchment area, such as its location relative to the sea, altitude, bedrock, and soil. Of the climatic factors, the temperature in the summer months and the amount of precipitation are of great importance. The purpose of the thesis was to find out the factors influencing the water properties of ponds in the Kilpisjärvi region and how the water properties vary between ponds. Water samples were collected from 94 tundra ponds in and around Malla Strict Nature Reserve and in the areas around Ailakkavaara in August-September 2018 and 2019. The collected samples were later analyzed in the laboratory of the Department of Geosciences and Geography in University of Helsinki. The hydrochemical variables studied were metals dissolved in water, major ions, and total phosphorus and nitrogen. Variables describing catchment characteristics such as the Normalized Difference Vegetation Index (NDVI), TWI (Topographic Wetness Index) and climatic variables such as precipitation during the summer months and average temperature in July were collected from open spatial data sources. Based on the results of the principal component analysis (PCA), the chemical properties of pond waters vary slightly on average between Malla and Ailakkavaara, but there is more variation within the regions. The characteristics of the catchment areas and the climate clearly influenced the vegetation type surrounding the ponds, but these factors were not as strongly reflected in the characteristics of the pond waters. The absolute amounts of nutrients and water-dissolved metals are small, but the relative variation between ponds is substantial. Based on GAM-modeling, influence of groundwater (deuterium excess) was the single most significant factor influencing water quality, which was the explanatory variable for several water properties. The drier-than-average summer months in the study years emphasize the importance of runoff to water quality. Rainfall during the summer months, altitude, mean temperature in July, and amount of vegetation (NDVI) were the main factors influencing the subarctic ponds in the study. The increase in temperature caused by climate change will raise the temperature of pond waters and increased precipitation will increase the runoff of metals dissolved in ponds.
-
(2023)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.
-
(2023)Substratum and environmental variables influence benthic algal species richness and community composition. Benthic habitats form complex connections within and between communities leading to unique water ecosystems. In order to better understand substratum relationships and the effects of environmental covariates towards microorganisms, this study focused on benthic diatoms in subarctic mountain ponds living in different substrata. Moreover, methodological choices are important for field survey in freshwater environments and thus in this study, we also compared sponge and brush sampling techniques to examine possible differences in benthic diatom species richness and community composition. We sampled 23 subarctic ponds between July and August 2022 in northern Fennoscandia. The samples were taken from stones and sediment. To analyse the differences between species richness for substrata and methods, we used paired Wilcoxon signed-rank test and paired t-test. In order to find out the most significant environmental variables influencing diatom species richness, we used generalized linear models (GLM). Differences in diatom community compositions were analysed using non-metric multidimensional scaling (NMDS), analysis of similarities (ANOSIM), and Jaccard similarity index. Finally in order to visualise the variation in community composition between stone and sediment samples explained by environmental variables, a redundancy analysis (RDA) was used. Benthic diatom species richness significantly differed between rock and sediment substrata where sediment was the most species rich substratum. Local environmental variables were influential towards diatom species richness, where water pH was the major determinant for both substrata. Diatom community composition did not differ significantly between rock and sediment substrata but was defined by environmental variables such as pond surface area and water pH having a strong influence on both substrata. No significant differences were found between sampling methods in terms of diatom species richness or community composition. Our results support the theory that sediment substratum contains the highest diatom species richness. Furthermore, the study highlights the importance of water pH on benthic diatoms regardless of substratum, supporting diatom reliability as bioindicators for water pH.
-
(2023)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.
-
(2021)As the climate warms tundra ecosystems will face changes that have an impact on their carbon cycle. Arctic tundra is already experiencing changes in plant species composition and distribution, and vegetation height expected to increase. Vegetation shifts such as shrubification can increase carbon uptake from the atmosphere to the tundra ecosystems but changes in soil microclimate and plant-microbe interactions related to vegetation shifts can also create feedbacks that increase carbon losses from the ecosystems to the atmosphere. To better understand changes in tundra carbon dioxide (CO2) fluxes related to climate change and vegetation shifts, it’s crucial to understand the factors controlling CO2 fluxes in the tundra in general and in the tundra environments that differ in their vegetation composition. We used environmental gradients created by late-lying snowbanks to collect the data and we used modelling to understand the factors controlling CO2 fluxes in the tundra and within four different vegetation types during the growing season. The vegetation types included in the study were barrens, meadow-like environments, prostrate shrub tundra (heat) and erect shrub tundra (shrub). Gross primary production (GPP) and ecosystem respiration (ER) were the highest in shrub plots, smaller in the heat and in meadow-like environments and the smallest in barrens. Net CO2 sink increased with vegetation cover and GPP, but also barrens with little vegetation were still mostly net CO2 sinks during the growing season due to low ER. The amount of vegetation measured in vegetation height and cover well explained the variation in GPP and net ecosystem exchange (NEE) in the whole data and within vegetation types. ER was also related to the amount of vegetation but was more affected by microclimate, mainly air temperature and soil moisture, than GPP and NEE. In shrub plots, variation in ER was explained by air temperature more than by vegetation cover or height. Microclimate variables were not important in explaining variation in GPP in the whole data or within vegetation types but air temperature in heath and in the whole data and soil temperature and soil moisture in barrens helped to explain variation in NEE. In the whole data, heat and shrub plots soil temperature was not related to higher ER. Depth of organic layer explained some variation in NEE and ER in the whole data and some variation in NEE in some of the vegetation types. Soil pH was not an important factor explaining CO2 fluxes, but it was related to vegetation type and vegetation distribution especially in the whole data. The main factor controlling CO2 fluxes in the tundra and within different vegetation types seemed to be the amount of vegetation. Air temperature and soil moisture help to explain the variation especially in ER. The ability of vegetation parameters to explain variation in ER may be partly because of a relatively small amount of heterotrophic respiration compared to autotrophic respiration in the system or because of a positive link between the amount of vegetation and the amount of decomposition. Drought during the field campaigns may have limited decomposition and decreased temperature sensitivity of decomposition which may partly explain the insensitivity of ER to soil temperature. In heat and in shrub plots the shading effect of vegetation lowered soil temperature and may have slowed decomposition. As the ability of vegetation, microclimate and soil variables to explain variation in CO2 fluxes differed between vegetation types, CO2 fluxes of different vegetation types may respond to changes in the tundra environment differently. The results imply that the effect of vegetation composition should be considered when estimating how tundra ecosystem CO2 fluxes will respond to climate change. Similarly, the role of factors controlling decomposition, such as drought and shading effect of shrub vegetation, may be important in determining the future carbon balance of the tundra.
-
(2021)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.
-
(2022)Subarktisten lampien vesikemia on muuttunut nopeasti viime vuosikymmeninä ympäristössä tapahtuneiden voimakkaiden muutosten johdosta. Subarktisten alueiden vesistötutkimuksissa on oltu erityisesti kiinnostuneita valuma-alueen kasvillisuuden muutoksista ilmaston lämpenemisen seurauksena. Maankamaran osalta huomio on ollut kallioperän kemiallisessa koostumuksessa. Tämän lopputyön keskiössä oli valuma-alueen tekijöistä maaperä. Lopputyön tavoitteena oli tarkastella, kuinka hyvin maaperämuuttujat selittävät lampien vesikemiaa. Maaperän kemiallisia ominaisuuksia kuvasi ICP-massaspektrometrillä määritetyt maaperänäytteiden helposti liukenevien alkuaineiden pitoisuudet. Lisäksi hehkutushäviömenetelmällä (LOI) määritettiin maaperän orgaanisen aineksen määrä. Maaperän rakennetta tarkasteltiin valuma-alueen maalajin ja maanpeiteluokkien peittävyysprosenttien avulla ja pohjavesivaikutteisuudella. Pääkomponenttianalyysin (PCA) mukaan vesikemian muuttujat eivät vaihdelleet kovinkaan yhdenmukaisesti; liuenneiden ionien kokonaismäärä ja runsaina esiintyneiden ionien pitoisuudet olivat kohtalaisen yhdenmukaisesti vaihtelevia. Valuma-aluetta kuvaavat muuttujat eivät sen sijaan PCA-analyysin mukaan olleet yhdenmukaisesti vaihtelevia. Yleistetyssä lineaarisessa mallissa (GLM) vesikemiaa kuvaavista muuttujista rinnejyrkkyys, varvikkojen ja heinikkojen laajuus sekä pohjavesivaikutteisuus selittivät tilastollisesti merkitsevästi lammen veden kemiaa. Pohjavesivaikutteisuus, jota mitattiin haihtuneisuutta kuvaavalla D-excess-arvolla, selitti ainoana muuttujana laajasti veden kemiallista vaihtelua. Se selitti pH:n sekä Al:n, Mn:n, Fe:n, Si:n ja TP:n vaihtelua. Yleisesti GLM-mallit olivat kuitenkin selitysvoimaltaan heikkoja. Ainoastaan veden Al:n ja Si:n pitoisuuksia selittävät mallit olivat selitysasteiltaan kohtalaisia. Tässä lopputyössä tutkittiin lisäksi sedimenttikivistä koostuvan Mallatunturien ja magmakivistä koostuvan Ailakkavaaran alueiden eroa lampien vesikemioissa. Samankaltaisuusanalyysissä (ANOSIM) löydettiin pieni ero alueiden välillä vesikemiassa. Maaperäominaisuuksien välillä ANOSIM-testissä löytyi myös heikko eroavaisuus alueiden välillä. Maaperissä oli yleisesti valuma-alueiden sisällä suurta vaihtelua, sillä maaperän alkuainepitoisuudet vaihtelivat merkittävästi eri puolilla lampea. Yleisesti tilastonanalyysien tulokset viittasivat siihen, että maaperä on tärkeä vesikemiaan vaikuttava tekijä valunnan tapahtuessa pohjavesikerroksen kautta. Lisäksi maaperän mineraaliaineksen koostumus selittää analyysin mukaan jonkin verran lampien vesikemian vaihtelua.
-
(2023)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.
-
(2022)Viimeisinä vuosikymmeninä pohjoisboreaalisella vyöhykkeellä on huomattu vesistöjen ruskeentumista eli väriluvun kasvua. Piilevät ovat vesistöissä eläviä yksisoluisia ruskeita leviä, joita käytetään laajasti veden laadun tutkimuksissa. Ne reagoivat herkästi ympäristömuuttujiin lajityypillisten sietoalueidensa puitteissa. Veden värin koostavat pääasiassa veteen liuenneet hiili- ja rautayhdisteet, joilla on sekä omat itsenäiset vaikutuksensa veden väriin että ne sitoutuvat herkästi toisiinsa. Veden väri vaikuttaa valon kulkeutumiseen vedessä absorboiden lähinnä lyhyitä aallonpituuksia ja muuttaen veteen tunkeutuvan valon spektriä. Veden värin vaikutuksesta piileviin on kuitenkin vain niukasti tutkimustietoa. Tässä tutkimuksessa olen kerännyt laajan ympäristömuuttuja- ja lajiaineiston 44 näytepisteeltä Keski-Suomen virtavesistä. Aineiston pohjalta selvitettiin veden värin vaikutusta piilevälajeihin ja lajistoa kuvaaviin indekseihin happamissa (pH ≤ 6,5) ympäristöissä. Tutkimuksessa käytettiin lineaarisia regressiomalleja (LM), yleistettyjä lineaarisia regressiomalleja (GLM) ja redundanssianalyysia (RDA). Tilastolliset analyysit toteutettiin R-tilasto-ohjelmalla. Tutkimuksessa selvisi, että veden väri vaikuttaa merkittävästi ja positiivisesti piileväyhteisön monimuotoisuuteen ja tasaisuuteen, mutta yhteyttä veden värin ja lajirunsauden välillä ei havaittu. Vaikutuksilla oli suurta suku- ja lajikohtaista vaihtelua. Yksittäisistä lajeista suurin yhteys veden väriin havaittiin Eunotia-suvun lajeilla ja Achnanthes minutissimalla, mutta myös muita lupaavia indikaattorilajeja havaittiin. Veden värin ohella tutkimuksessa havaittuja muita tärkeitä ympäristömuuttujia olivat veden happamuus ja tietyt hivenaine- ja ionipitoisuudet. Tutkimustulokset ovat pääsääntöisesti yhteneväisiä aiemman tutkimuskirjallisuuden kanssa, mutta tuovat arvokasta lisätietoa veden värin vaikutuksista ja nostavat esiin useita mahdollisuuksia jatkotutkimuksille. Tutkimuksen pohjalta veden värin huomioiminen piilevätutkimuksessa on tärkeää, varsinkin vesistöjen alati jatkuvan ruskeentumisen vuoksi.
Now showing items 21-40 of 42