Geospatial environmental data modelling applications using remote sensing, GIS and spatial statistics

This thesis presents novel modelling applications for environmental geospatial data using remote sensing, GIS and statistical modelling techniques. The studied themes can be classified into four main themes: (i) to develop advanced geospatial databases. Paper (I) demonstrates the creation of a geospatial database for the Glanville fritillary butterfly (Melitaea cinxia) in the Åland Islands, south-western Finland; (ii) to analyse species diversity and distribution using GIS techniques. Paper (II) presents a diversity and geographical distribution analysis for Scopulini moths at a world-wide scale; (iii) to study spatiotemporal forest cover change. Paper (III) presents a study of exotic and indigenous tree cover change detection in Taita Hills Kenya using airborne imagery and GIS analysis techniques; (iv) to explore predictive modelling techniques using geospatial data. In Paper (IV) human population occurrence and abundance in the Taita Hills highlands was predicted using the generalized additive modelling (GAM) technique. Paper (V) presents techniques to enhance fire prediction and burned area estimation at a regional scale in East Caprivi Namibia. Paper (VI) compares eight state-of-the-art predictive modelling methods to improve fire prediction, burned area estimation and fire risk mapping in East Caprivi Namibia. The results in Paper (I) showed that geospatial data can be managed effectively using advanced relational database management systems. Metapopulation data for Melitaea cinxia butterfly was successfully combined with GPS-delimited habitat patch information and climatic data. Using the geospatial database, spatial analyses were successfully conducted at habitat patch level or at more coarse analysis scales. Moreover, this study showed it appears evident that at a large-scale spatially correlated weather conditions are one of the primary causes of spatially correlated changes in Melitaea cinxia population sizes. In Paper (II) spatiotemporal characteristics of Socupulini moths description, diversity and distribution were analysed at a world-wide scale and for the first time GIS techniques were used for Scopulini moth geographical distribution analysis. This study revealed that Scopulini moths have a cosmopolitan distribution. The majority of the species have been described from the low latitudes, sub-Saharan Africa being the hot spot of species diversity. However, the taxonomical effort has been uneven among biogeographical regions. Paper III showed that forest cover change can be analysed in great detail using modern airborne imagery techniques and historical aerial photographs. However, when spatiotemporal forest cover change is studied care has to be taken in co-registration and image interpretation when historical black and white aerial photography is used. In Paper (IV) human population distribution and abundance could be modelled with fairly good results using geospatial predictors and non-Gaussian predictive modelling techniques. Moreover, land cover layer is not necessary needed as a predictor because first and second-order image texture measurements derived from satellite imagery had more power to explain the variation in dwelling unit occurrence and abundance. Paper V showed that generalized linear model (GLM) is a suitable technique for fire occurrence prediction and for burned area estimation. GLM based burned area estimations were found to be more superior than the existing MODIS burned area product (MCD45A1). However, spatial autocorrelation of fires has to be taken into account when using the GLM technique for fire occurrence prediction. Paper VI showed that novel statistical predictive modelling techniques can be used to improve fire prediction, burned area estimation and fire risk mapping at a regional scale. However, some noticeable variation between different predictive modelling techniques for fire occurrence prediction and burned area estimation existed.

Enhanced processing of SPOT multispectral satellite imagery for environmental monitoring and modelling

The Taita Hills in southeastern Kenya form the northernmost part of Africa’s Eastern Arc Mountains, which have been identified by Conservation International as one of the top ten biodiversity hotspots on Earth. As with many areas of the developing world, over recent decades the Taita Hills have experienced significant population growth leading to associated major changes in land use and land cover (LULC), as well as escalating land degradation, particularly soil erosion. Multi-temporal medium resolution multispectral optical satellite data, such as imagery from the SPOT HRV, HRVIR, and HRG sensors, provides a valuable source of information for environmental monitoring and modelling at a landscape level at local and regional scales. However, utilization of multi-temporal SPOT data in quantitative remote sensing studies requires the removal of atmospheric effects and the derivation of surface reflectance factor. Furthermore, for areas of rugged terrain, such as the Taita Hills, topographic correction is necessary to derive comparable reflectance throughout a SPOT scene. Reliable monitoring of LULC change over time and modelling of land degradation and human population distribution and abundance are of crucial importance to sustainable development, natural resource management, biodiversity conservation, and understanding and mitigating climate change and its impacts. The main purpose of this thesis was to develop and validate enhanced processing of SPOT satellite imagery for use in environmental monitoring and modelling at a landscape level, in regions of the developing world with limited ancillary data availability. The Taita Hills formed the application study site, whilst the Helsinki metropolitan region was used as a control site for validation and assessment of the applied atmospheric correction techniques, where multiangular reflectance field measurements were taken and where horizontal visibility meteorological data concurrent with image acquisition were available. The proposed historical empirical line method (HELM) for absolute atmospheric correction was found to be the only applied technique that could derive surface reflectance factor within an RMSE of < 0.02 ps in the SPOT visible and near-infrared bands; an accuracy level identified as a benchmark for successful atmospheric correction. A multi-scale segmentation/object relationship modelling (MSS/ORM) approach was applied to map LULC in the Taita Hills from the multi-temporal SPOT imagery. This object-based procedure was shown to derive significant improvements over a uni-scale maximum-likelihood technique. The derived LULC data was used in combination with low cost GIS geospatial layers describing elevation, rainfall and soil type, to model degradation in the Taita Hills in the form of potential soil loss, utilizing the simple universal soil loss equation (USLE). Furthermore, human population distribution and abundance were modelled with satisfactory results using only SPOT and GIS derived data and non-Gaussian predictive modelling techniques. The SPOT derived LULC data was found to be unnecessary as a predictor because the first and second order image texture measurements had greater power to explain variation in dwelling unit occurrence and abundance. The ability of the procedures to be implemented locally in the developing world using low-cost or freely available data and software was considered. The techniques discussed in this thesis are considered equally applicable to other medium- and high-resolution optical satellite imagery, as well the utilized SPOT data.

Coastal environmental gradients – Key to reproduction habitat mapping of freshwater fish in the Baltic Sea

Habitat requirements of fish are most strict during the early life stages, and the quality and quantity of reproduction habitats lays the basis for fish production. A considerable number of fish species in the northern Baltic Sea reproduce in the shallow coastal areas, which are also the most heavily exploited parts of the brackish marine area. However, the coastal fish reproduction habitats in the northern Baltic Sea are poorly known. The studies presented in this thesis focused on the influence of environmental conditions on the distribution of coastal reproduction habitats of freshwater fish. They were conducted in vegetated littoral zone along an exposure and salinity gradient extending from the innermost bays to the outer archipelago on the south-western and southern coasts of Finland, in the northern Baltic Sea. Special emphasis was placed on reed-covered Phragmites australis shores, which form a dominant vegetation type in several coastal archipelago areas. The main aims of this research were to (1) develop and test new survey and mapping methods, (2) investigate the environmental requirements that govern the reproduction of freshwater fish in the coastal area and (3) survey, map and model the distribution of the reproduction habitats of pike (Esox lucius) and roach (Rutilus rutilus). The white plate and scoop method with a standardized sampling time and effort was demonstrated to be a functional method for sampling the early life stages of fish in dense vegetation and shallow water. Reed-covered shores were shown to form especially important reproduction habitats for several freshwater fish species, such as pike, roach, other cyprinids and burbot, in the northern Baltic Sea. The reproduction habitats of pike were limited to sheltered reed- and moss-covered shores of the inner and middle archipelago, where suitable zooplankton prey were available and the influence of the open sea was low. The reproduction habitats of roach were even more limited and roach reproduction was successful only in the very sheltered reed-covered shores of the innermost bay areas, where salinity remained low (< 4‰) during the spawning season due to freshwater inflow. After identifying the critical factors restricting the reproduction of pike and roach, the spatial distribution of their reproduction habitats was successfully mapped and modelled along the environmental gradients using only a few environmental predictor variables. Reproduction habitat maps are a valuable tool promoting the sustainable use and management of exploited coastal areas and helping to maintain the sustainability of fish populations. However, the large environmental gradients and the extensiveness of the archipelago zone in the northern Baltic Sea demand an especially high spatial resolution of the coastal predictor variables. Therefore, the current lack of accurate large-scale, high-resolution spatial data gathered at exactly the right time is a considerable limitation for predictive modelling of shallow coastal waters.

Rannansiirtyminen ja ihmisen toimintaympäristön muutos Mätäjokilaakson alueella esihistoriallisella ajalla

In this thesis, I study the changing ladscape and human environment of the Mätäjoki Valley, West-Helsinki, using reconstructions and predictive modelling. The study is a part of a larger project funded by the city of Helsinki aming to map the past of the Mätäjoki Valley. The changes in landscape from an archipelago in the Ancylus Lake to a river valley are studied from 10000 to 2000 years ago. Alongside shore displacement, we look at the changing environment from human perspective and predict the location of dwelling sitesat various times. As a result, two map series were produced that show how the landscape changed and where inhabitance is predicted. To back them up, we have also looked at what previous research says about the history of the waterways, climate, vegetation and archaeology. The changing landscape of the river valley is reconstructed using GIS methods. For this purpose, new laser point data set was used and at the same time tested in the context landscape modelling. Dwelling sites were modeled with logistic regression analysis. The spatial predictive model combines data on the locations of the known dwelling sites, environmental factors and shore displacement data. The predictions were visualised into raster maps that show the predictions for inhabitance 3000 and 5000 years ago. The aim of these maps was to help archaeologists map potential spots for human activity. The produced landscape reconstructions clarified previous shore displacement studies of the Mätäjoki region and provided new information on the location of shoreline. From the shore displacement history of the Mätäjoki Valley arise the following stages: 1. The northernmost hills of the Mätäjoki Valley rose from Ancylus Lake approximately 10000 years ago. Shore displacement was fast during the following thousand years. 2. The area was an archipelago with a relatively steady shoreline 9000 7000 years ago. 8000 years ago the shoreline drew back in the middle and southern parts of the river valley because of the transgression of the Litorina Sea. 3. Mätäjoki was a sheltered bay of the Litorina Sea 6000 5000 years ago. The Vantaanjoki River started to flow into the Mätäjoki Valley approximately 5000 years ago. 4. The sediment plains in the southern part of the river valley rose from the sea rather quickly 5000 3000 years ago. Salt water still pushed its way into the southermost part of the valley 4000 years ago. 5. The shoreline proceeded to Pitäjänmäki rapids where it stayed at least a thousand years 3000 2000 years ago. The predictive models managed to predict the locations of dwelling sites moderately well. The most accurate predictions were found on the eastern shore and Malminkartano area. Of the environment variables sand and aspect of slope were found to have the best predictive power. From the results of this study we can conclude that the Mätäjoki Valley has been a favorable location to live especially 6000 5000 years ago when the climate was mild and vegetation lush. The laser point data set used here works best in shore displacement studies located in rural areas or if further specific palaeogeographic or hydrologic analysis in the research area is not needed.

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.

Understanding solid-state transformations during dehydration: new insights using vibrational spectroscopy and multivariate modelling

Many active pharmaceutical ingredients (APIs) have both anhydrate and hydrate forms. Due to the different physicochemical properties of solid forms, the changes in solid-state may result in therapeutic, pharmaceutical, legal and commercial problems. In order to obtain good solid dosage form quality and performance, there is a constant need to understand and control these phase transitions during manufacturing and storage. Thus it is important to detect and also quantify the possible transitions between the different forms. In recent years, vibrational spectroscopy has become an increasingly popular tool to characterise the solid-state forms and their phase transitions. It offers several advantages over other characterisation techniques including an ability to obtain molecular level information, minimal sample preparation, and the possibility of monitoring changes non-destructively in-line. Dehydration is the phase transition of hydrates which is frequently encountered during the dosage form production and storage. The aim of the present thesis was to investigate the dehydration behaviour of diverse pharmaceutical hydrates by near infrared (NIR), Raman and terahertz pulsed spectroscopic (TPS) monitoring together with multivariate data analysis. The goal was to reveal new perspectives for investigation of the dehydration at the molecular level. Solid-state transformations were monitored during dehydration of diverse hydrates on hot-stage. The results obtained from qualitative experiments were used to develop a method and perform the quantification of the solid-state forms during process induced dehydration in a fluidised bed dryer. Both in situ and in-line process monitoring and quantification was performed. This thesis demonstrated the utility of vibrational spectroscopy techniques and multivariate modelling to monitor and investigate dehydration behaviour in situ and during fluidised bed drying. All three spectroscopic methods proved complementary in the study of dehydration. NIR spectroscopy models could quantify the solid-state forms in the binary system, but were unable to quantify all the forms in the quaternary system. Raman spectroscopy models on the other hand could quantify all four solid-state forms that appeared upon isothermal dehydration. The speed of spectroscopic methods makes them applicable for monitoring dehydration and the quantification of multiple forms was performed during phase transition. Thus the solid-state structure information at the molecular level was directly obtained. TPS detected the intermolecular phonon modes and Raman spectroscopy detected mostly the changes in intramolecular vibrations. Both techniques revealed information about the crystal structure changes. NIR spectroscopy, on the other hand was more sensitive to water content and hydrogen bonding environment of water molecules. This study provides a basis for real time process monitoring using vibrational spectroscopy during pharmaceutical manufacturing.

Landscape-scale soil erosion modelling and ecological restoration for a mountainous watershed in Sichuan, China

Sichuanissa Tiibetin ylängön metsäkato on pysähtynyt mutta eroosio-ongelmat jatkuvat Viikin tropiikki-instituutin tutkija Ping ZHOU kartoitti trooppisen metsänhoidon alaan kuuluvassa väitöskirjatyössään maaperän eroosioalttiutta ja sen riippuvuutta metsäkasvillisuudesta Jangtsen tärkeää sivuhaaraa Min-jokea ympäröivällä n. 7400 neliökilometrin suuruisella valuma-alueella Sichuanin Aba-piirikunnassa. Aineistonaan hän käytti muun muassa satelliittikartoitustietoja ja mittaustuloksia yli 600 maastokoealalta. Tutkimuksen nimi suomeksi on "Maaperän eroosion mallinnus ja vuoristoisen valuma-alueen ekologinen ennallistaminen Sichuanissa Kiinassa". Aikaisempien tutkimusten perusteella oli tiedossa että metsien häviäminen tällä alueella pysähtyi jo 1980-luvun alussa. Sen jälkeen on metsien pinta-ala hitaasti kasvanut etupäässä sen vuoksi, että teollinen puunhakkuu luonnonmetsissä kiellettiin kokonaan v. 1998 ja 25 astetta jyrkemmillä rinteillä myös maatalouden harjoittaminen on saatu lopetetuksi viljelijöille tarjottujen taloudellisten houkuttimien avulla. Täten myös pelto- ja laidunmaata on voitu ennallistaa metsäksi. Ping Zhou pystyi jakamaan 5700 metrin korkeuteen saakka kohoavan vuoristoalueen eroosioalttiudeltaan erilaisiin vyöhykkeisiin rinteen kaltevuuden, sademäärän, kasvipeitteen ja maalajin perusteella. Noin 15 prosentilla tutkitun valuma-alueen pinta-alasta, lähinnä Min-joen pääuomaa ympäröivillä jyrkillä rinteillä, eroosioriski oli suuri tai erittäin suuri. Eri tyyppisellä kasvillisuudella oli hyvin erilainen vaikutus eroosioalttiuteen, ja myös alueen sijainti vuoriston eri korkeuksilla vaikutti eroosioon. Säästyneet lähes luonnontilaiset havumetsät, joita on etupäässä vuoriston ylimmissä osissa 2600-4000 metrin korkeudella, edistävät tehokkaasti metsän luontaista uudistumista ja levittäytymistä vaurioituneille alueille. Säilyneiden metsien puulajikoostumus antoi tutkimuksessa mahdollisuuden ennustaa metsien tulevaa kehitystä koko tutkitulla valuma-alueella sen eri korkeusvyöhykkeissä ja eri maaperätyypeillä. Ennallistamisen kannalta ongelmallisimpia olivat alueet joilta metsäpeite oli lähinnä puiden teollisen hakkuun vuoksi kokonaan hävinnyt ja joilla maaperä yleisesti oli eroosion pahoin kuluttama. Näillä alueilla ei ole tehty juuri mitään uudistamis- tai ennallistamistoimenpiteitä. Niillä metsien ennallistaminen vaatii myös puiden tai pensaiden istuttamista. Tähän sopivia ovat erityisesti ilmakehän typpeä sitovat lajit, joista alueella kasvaa luontaisena mm. sama tyrnilaji joka esiintyy myös Suomessa. Työssä tutkittiin yli kahdeksankymmenen paikallisen luontaisen puulajin (joista peräti noin kolmannes on havupuulajeja) ekologisia ominaisuuksia ja soveltuvuutta metsien ennallistamiseen. Avainasemassa työn onnistumisen kannalta ovat nyt paikalliset asukkaat, joiden maankäytön muutokset ovat jo selvästi edistänet luonnonmetsän ennalleen palautumista. Suomen Akatemia rahoitti vuosina 2004-2006 VITRI:n tutkimushanketta, josta Ping Zhou'n väitöskirjatyö muodosti keskeisen osan. Kenttätyö Sichuanissa avasi mahdollisuuden hedelmälliseen monitieteiseen yhteistyöhön ja tutkijavaihtoon Kiinan tiedeakatemian alaisen Chengdun biologiainstituutin (CIB) kanssa; tämä tieteellinen kanssakäyminen jatkuu edelleen.

Soil carbon modelling as a tool for carbon balance studies in forestry

Soils represent a remarkable stock of carbon, and forest soils are estimated to hold half of the global stock of soil carbon. Topical concern about the effects of climate change and forest management on soil carbon as well as practical reporting requirements set by climate conventions have created a need to assess soil carbon stock changes reliably and transparently. The large spatial variability of soil carbon commensurate with relatively slow changes in stocks hinders the assessment of soil carbon stocks and their changes by direct measurements. Models therefore widely serve to estimate carbon stocks and stock changes in soils. This dissertation aimed to develop the soil carbon model YASSO for upland forest soils. The model was aimed to take into account the most important processes controlling the decomposition in soils, yet remain simple enough to ensure its practical applicability in different applications. The model structure and assumptions were presented and the model parameters were defined with empirical measurements. The model was evaluated by studying the sensitivities of the model results to parameter values, by estimating the precision of the results with an uncertainty analysis, and by assessing the accuracy of the model by comparing the predictions against measured data and to the results of an alternative model. The model was applied to study the effects of intensified biomass extraction on the forest carbon balance and to estimate the effects of soil carbon deficit on net greenhouse gas emissions of energy use of forest residues. The model was also applied in an inventory based method to assess the national scale forest carbon balance for Finland’s forests from 1922 to 2004. YASSO managed to describe sufficiently the effects of both the variable litter and climatic conditions on decomposition. When combined with the stand models or other systems providing litter information, the dynamic approach of the model proved to be powerful for estimating changes in soil carbon stocks on different scales. The climate dependency of the model, the effects of nitrogen on decomposition and forest growth as well as the effects of soil texture on soil carbon stock dynamics are areas for development when considering the applicability of the model to different research questions, different land use types and wider geographic regions. Intensified biomass extraction affects soil carbon stocks, and these changes in stocks should be taken into account when considering the net effects of forest residue utilisation as energy. On a national scale, soil carbon stocks play an important role in forest carbon balances.

Molecular Modelling of Estrogen-Producing Enzymes CYP450 Aromatase and 17beta-Hydroxysteroid Dehydrogenase Type 1

Breast cancer is the most common cancer in women in the western countries. Approximately two-thirds of breast cancer tumours are hormone dependent, requiring estrogens to grow. Estrogens are formed in the human body via a multistep route starting from cholesterol. The final steps in the biosynthesis include the CYP450 aromatase enzyme, converting the male hormones androgens (preferred substrate androstenedione ASD) into estrogens(estrone E1), and the 17beta-HSD1 enzyme, converting the biologically less active E1 into the active hormone 17beta-hydroxyestradiol E2. E2 is bound to the nuclear estrogen receptors causing a cascade of biochemical reactions leading to cell proliferation in normal tissue, and to tumour growth in cancer tissue. Aromatase and 17beta-HSD1 are expressed in or near the breast tumour, locally providing the tissue with estrogens. One approach in treating hormone dependent breast tumours is to block the local estrogen production by inhibiting these two enzymes. Aromatase inhibitors are already on the market in treating breast cancer, despite the lack of an experimentally solved structure. The structure of 17beta-HSD1, on the other hand, has been solved, but no commercial drugs have emerged from the drug discovery projects reported in the literature. Computer-assisted molecular modelling is an invaluable tool in modern drug design projects. Modelling techniques can be used to generate a model of the target protein and to design novel inhibitors for them even if the target protein structure is unknown. Molecular modelling has applications in predicting the activities of theoretical inhibitors and in finding possible active inhibitors from a compound database. Inhibitor binding at atomic level can also be studied with molecular modelling. To clarify the interactions between the aromatase enzyme and its substrate and inhibitors, we generated a homology model based on a mammalian CYP450 enzyme, rabbit progesterone 21-hydroxylase CYP2C5. The model was carefully validated using molecular dynamics simulations (MDS) with and without the natural substrate ASD. Binding orientation of the inhibitors was based on the hypothesis that the inhibitors coordinate to the heme iron, and were studied using MDS. The inhibitors were dietary phytoestrogens, which have been shown to reduce the risk for breast cancer. To further validate the model, the interactions of a commercial breast cancer drug were studied with MDS and ligand–protein docking. In the case of 17beta-HSD1, a 3D QSAR model was generated on the basis of MDS of an enzyme complex with active inhibitor and ligand–protein docking, employing a compound library synthesised in our laboratory. Furthermore, four pharmacophore hypotheses with and without a bound substrate or an inhibitor were developed and used in screening a commercial database of drug-like compounds. The homology model of aromatase showed stable behaviour in MDS and was capable of explaining most of the results from mutagenesis studies. We were able to identify the active site residues contributing to the inhibitor binding, and explain differences in coordination geometry corresponding to the inhibitory activity. Interactions between the inhibitors and aromatase were in agreement with the mutagenesis studies reported for aromatase. Simulations of 17beta-HSD1 with inhibitors revealed an inhibitor binding mode with hydrogen bond interactions previously not reported, and a hydrophobic pocket capable of accommodating a bulky side chain. Pharmacophore hypothesis generation, followed by virtual screening, was able to identify several compounds that can be used in lead compound generation. The visualisation of the interaction fields from the QSAR model and the pharmacophores provided us with novel ideas for inhibitor development in our drug discovery project.

Spatial and temporal variability in midge (Nematocera) assemblages in shallow Finnish lakes (60−70 °N) : community-based modelling of past environmental change

Multi- and intralake datasets of fossil midge assemblages in surface sediments of small shallow lakes in Finland were studied to determine the most important environmental factors explaining trends in midge distribution and abundance. The aim was to develop palaeoenvironmental calibration models for the most important environmental variables for the purpose of reconstructing past environmental conditions. The developed models were applied to three high-resolution fossil midge stratigraphies from southern and eastern Finland to interpret environmental variability over the past 2000 years, with special focus on the Medieval Climate Anomaly (MCA), the Little Ice Age (LIA) and recent anthropogenic changes. The midge-based results were compared with physical properties of the sediment, historical evidence and environmental reconstructions based on diatoms (Bacillariophyta), cladocerans (Crustacea: Cladocera) and tree rings. The results showed that the most important environmental factor controlling midge distribution and abundance along a latitudinal gradient in Finland was the mean July air temperature (TJul). However, when the dataset was environmentally screened to include only pristine lakes, water depth at the sampling site became more important. Furthermore, when the dataset was geographically scaled to southern Finland, hypolimnetic oxygen conditions became the dominant environmental factor. The results from an intralake dataset from eastern Finland showed that the most important environmental factors controlling midge distribution within a lake basin were river contribution, water depth and submerged vegetation patterns. In addition, the results of the intralake dataset showed that the fossil midge assemblages represent fauna that lived in close proximity to the sampling sites, thus enabling the exploration of within-lake gradients in midge assemblages. Importantly, this within-lake heterogeneity in midge assemblages may have effects on midge-based temperature estimations, because samples taken from the deepest point of a lake basin may infer considerably colder temperatures than expected, as shown by the present test results. Therefore, it is suggested here that the samples in fossil midge studies involving shallow boreal lakes should be taken from the sublittoral, where the assemblages are most representative of the whole lake fauna. Transfer functions between midge assemblages and the environmental forcing factors that were significantly related with the assemblages, including mean air TJul, water depth, hypolimnetic oxygen, stream flow and distance to littoral vegetation, were developed using weighted averaging (WA) and weighted averaging-partial least squares (WA-PLS) techniques, which outperformed all the other tested numerical approaches. Application of the models in downcore studies showed mostly consistent trends. Based on the present results, which agreed with previous studies and historical evidence, the Medieval Climate Anomaly between ca. 800 and 1300 AD in eastern Finland was characterized by warm temperature conditions and dry summers, but probably humid winters. The Little Ice Age (LIA) prevailed in southern Finland from ca. 1550 to 1850 AD, with the coldest conditions occurring at ca. 1700 AD, whereas in eastern Finland the cold conditions prevailed over a longer time period, from ca. 1300 until 1900 AD. The recent climatic warming was clearly represented in all of the temperature reconstructions. In the terms of long-term climatology, the present results provide support for the concept that the North Atlantic Oscillation (NAO) index has a positive correlation with winter precipitation and annual temperature and a negative correlation with summer precipitation in eastern Finland. In general, the results indicate a relatively warm climate with dry summers but snowy winters during the MCA and a cool climate with rainy summers and dry winters during the LIA. The results of the present reconstructions and the forthcoming applications of the models can be used in assessments of long-term environmental dynamics to refine the understanding of past environmental reference conditions and natural variability required by environmental scientists, ecologists and policy makers to make decisions concerning the presently occurring global, regional and local changes. The developed midge-based models for temperature, hypolimnetic oxygen, water depth, littoral vegetation shift and stream flow, presented in this thesis, are open for scientific use on request.