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.

Social networks for volunteered geographic information - A case study of OpenStreetMap

The world of mapping has changed. Earlier, only professional experts were responsible for map production, but today ordinary people without any training or experience can become map-makers. The number of online mapping sites, and the number of volunteer mappers has increased significantly. The development of the technology, such as satellite navigation systems, Web 2.0, broadband Internet connections, and smartphones, have had one of the key roles in enabling the rise of volunteered geographic information (VGI). As opening governmental data to public is a current topic in many countries, the opening of high quality geographical data has a central role in this study. The aim of this study is to investigate how is the quality of spatial data produced by volunteers by comparing it with the map data produced by public authorities, to follow what occurs when spatial data are opened for users, and to get acquainted with the user profile of these volunteer mappers. A central part of this study is OpenStreetMap project (OSM), which aim is to create a map of the entire world by volunteers. Anyone can become an OpenStreetMap contributor, and the data created by the volunteers are free to use for anyone without restricting copyrights or license charges. In this study OpenStreetMap is investigated from two viewpoints. In the first part of the study, the aim was to investigate the quality of volunteered geographic information. A pilot project was implemented by following what occurs when a high-resolution aerial imagery is released freely to the OpenStreetMap contributors. The quality of VGI was investigated by comparing the OSM datasets with the map data of The National Land Survey of Finland (NLS). The quality of OpenStreetMap data was investigated by inspecting the positional accuracy and the completeness of the road datasets, as well as the differences in the attribute datasets between the studied datasets. Also the OSM community was under analysis and the development of the map data of OpenStreetMap was investigated by visual analysis. The aim of the second part of the study was to analyse the user profile of OpenStreetMap contributors, and to investigate how the contributors act when collecting data and editing OpenStreetMap. The aim was also to investigate what motivates users to map and how is the quality of volunteered geographic information envisaged. The second part of the study was implemented by conducting a web inquiry to the OpenStreetMap contributors. The results of the study show that the quality of OpenStreetMap data compared with the data of National Land Survey of Finland can be defined as good. OpenStreetMap differs from the map of National Land Survey especially because of the amount of uncertainty, for example because of the completeness and uniformity of the map are not known. The results of the study reveal that opening spatial data increased notably the amount of the data in the study area, and both the positional accuracy and completeness improved significantly. The study confirms the earlier arguments that only few contributors have created the majority of the data in OpenStreetMap. The inquiry made for the OpenStreetMap users revealed that the data are most often collected by foot or by bicycle using GPS device, or by editing the map with the help of aerial imageries. According to the responses, the users take part to the OpenStreetMap project because they want to make maps better, and want to produce maps, which have information that is up-to-date and cannot be found from any other maps. Almost all of the users exploit the maps by themselves, most popular methods being downloading the map into a navigator or into a mobile device. The users regard the quality of OpenStreetMap as good, especially because of the up-to-dateness and the accuracy of the map.

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.

Management of multi-scale forest resource data over time

During the last decades there has been a global shift in forest management from a focus solely on timber management to ecosystem management that endorses all aspects of forest functions: ecological, economic and social. This has resulted in a shift in paradigm from sustained yield to sustained diversity of values, goods and benefits obtained at the same time, introducing new temporal and spatial scales into forest resource management. The purpose of the present dissertation was to develop methods that would enable spatial and temporal scales to be introduced into the storage, processing, access and utilization of forest resource data. The methods developed are based on a conceptual view of a forest as a hierarchically nested collection of objects that can have a dynamically changing set of attributes. The temporal aspect of the methods consists of lifetime management for the objects and their attributes and of a temporal succession linking the objects together. Development of the forest resource data processing method concentrated on the extensibility and configurability of the data content and model calculations, allowing for a diverse set of processing operations to be executed using the same framework. The contribution of this dissertation to the utilisation of multi-scale forest resource data lies in the development of a reference data generation method to support forest inventory methods in approaching single-tree resolution.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

Controls on trace metals in urban stream sediments : implications for pollution monitoring using sediment chemistry data

Contamination of urban streams is a rising topic worldwide, but the assessment and investigation of stormwater induced contamination is limited by the high amount of water quality data needed to obtain reliable results. In this study, stream bed sediments were studied to determine their contamination degree and their applicability in monitoring aquatic metal contamination in urban areas. The interpretation of sedimentary metal concentrations is, however, not straightforward, since the concentrations commonly show spatial and temporal variations as a response to natural processes. The variations of and controls on metal concentrations were examined at different scales to increase the understanding of the usefulness of sediment metal concentrations in detecting anthropogenic metal contamination patterns. The acid extractable concentrations of Zn, Cu, Pb and Cd were determined from the surface sediments and water of small streams in the Helsinki Metropolitan region, southern Finland. The data consists of two datasets: sediment samples from 53 sites located in the catchment of the Stream Gräsanoja and sediment and water samples from 67 independent catchments scattered around the metropolitan region. Moreover, the sediment samples were analyzed for their physical and chemical composition (e.g. total organic carbon, clay-%, Al, Li, Fe, Mn) and the speciation of metals (in the dataset of the Stream Gräsanoja). The metal concentrations revealed that the stream sediments were moderately contaminated and caused no immediate threat to the biota. However, at some sites the sediments appeared to be polluted with Cu or Zn. The metal concentrations increased with increasing intensity of urbanization, but site specific factors, such as point sources, were responsible for the occurrence of the highest metal concentrations. The sediment analyses revealed, thus a need for more detailed studies on the processes and factors that cause the hot spot metal concentrations. The sediment composition and metal speciation analyses indicated that organic matter is a very strong indirect control on metal concentrations, and it should be accounted for when studying anthropogenic metal contamination patterns. The fine-scale spatial and temporal variations of metal concentrations were low enough to allow meaningful interpretation of substantial metal concentration differences between sites. Furthermore, the metal concentrations in the stream bed sediments were correlated with the urbanization of the catchment better than the total metal concentrations in the water phase. These results suggest that stream sediments show true potential for wider use in detecting the spatial differences in metal contamination of urban streams. Consequently, using the sediment approach regional estimates of the stormwater related metal contamination could be obtained fairly cost-effectively, and the stability and reliability of results would be higher compared to analyses of single water samples. Nevertheless, water samples are essential in analysing the dissolved concentrations of metals, momentary discharges from point sources in particular.

Spatial and temporal determinants of Finnish farmland bird populations

During the past decades agricultural intensification has caused dramatic population declines in a wide range of taxa related to farmland habitats, including farmland birds. In this thesis, I studied how boreal farmland landscape characteristics and agricultural land use affect the abundance and diversity of farmland birds using extensive field data collected by territory mapping of breeding farmland birds in various parts of Finland. My results show that the area and openness of agricultural areas are key determinants of farmland bird abundance and distribution. A landscape composition with enough open farmland combined with key habitats such as farmyards and wetland is likely to provide essential prerequisites for the occurrence of a rich farmland avifauna. In Finland, the majority of large areas suitable for open habitat specialists are located in southern and western parts of the country. However, the diversity of the species with an unfavourable conservation status in Europe (SPECs) had notable hotspot areas in northern and north-western agricultural areas. I found that in boreal agroecosystems farmland birds favour fields with springtime vegetative cover, especially agricultural grasslands and set-asides. Hence, in the spring cereal dominated Finnish agroecosystems it is the absence of field vegetation that may limit populations of many farmland bird species. It is likely that the decrease of crops providing vegetative cover in the spring, such as permanent grasslands, cultivated grass, and autumn-sown cereals, has greatly contributed to the declines of Finnish farmland birds. Grass crops have persistently declined in Finland as a consequence of specialization in crop production and the large-scale decline in livestock husbandry. Small-scale non-crop habitats, especially ditches and ditch margins, are also important for many bird species in the Finnish agroecosystems, but have dramatically declined during the last decades. A major problem for farmland bird conservation in Finland is the conflict between landscape structure and agricultural management. Areas with mixed and cattle farming are virtually absent from the large agricultural plains of southern and south-western Finland, where the landscape structure is more likely to be favourable for rich farmland bird assemblages. On the other hand, mixed and cattle farming is still rather frequent in northern and central parts of the country, where the landscape structure is not suitable for many farmland specialist birds requiring open landscapes. My results provide useful guidelines for farmland bird conservation, and imply that considerable attention needs to be paid to landscape factors when selecting areas for various conservational management actions, such as agri-environment schemes. Actions promoting the abundance of set-asides, grass crops, and ditches would markedly benefit Finnish farmland bird populations. Organic farming may benefit farmland birds, but it is not clear how general its beneficial effect is in boreal agroecosystems. The most urgent action aiming to preserve farmland biodiversity would be to support re-introducing and sustaining cattle farming by environmental subsidies. This would be especially beneficial in the southern parts of Finland, where the landscape characteristics and abundance of agricultural areas are most suitable for farmland birds and where cattle farming is currently rare.

Where and how to conserve: Extending the scope of spatial reserve network design

Ongoing habitat loss and fragmentation threaten much of the biodiversity that we know today. As such, conservation efforts are required if we want to protect biodiversity. Conservation budgets are typically tight, making the cost-effective selection of protected areas difficult. Therefore, reserve design methods have been developed to identify sets of sites, that together represent the species of conservation interest in a cost-effective manner. To be able to select reserve networks, data on species distributions is needed. Such data is often incomplete, but species habitat distribution models (SHDMs) can be used to link the occurrence of the species at the surveyed sites to the environmental conditions at these locations (e.g. climatic, vegetation and soil conditions). The probability of the species occurring at unvisited location is next predicted by the model, based on the environmental conditions of those sites. The spatial configuration of reserve networks is important, because habitat loss around reserves can influence the persistence of species inside the network. Since species differ in their requirements for network configuration, the spatial cohesion of networks needs to be species-specific. A way to account for species-specific requirements is to use spatial variables in SHDMs. Spatial SHDMs allow the evaluation of the effect of reserve network configuration on the probability of occurrence of the species inside the network. Even though reserves are important for conservation, they are not the only option available to conservation planners. To enhance or maintain habitat quality, restoration or maintenance measures are sometimes required. As a result, the number of conservation options per site increases. Currently available reserve selection tools do however not offer the ability to handle multiple, alternative options per site. This thesis extends the existing methodology for reserve design, by offering methods to identify cost-effective conservation planning solutions when multiple, alternative conservation options are available per site. Although restoration and maintenance measures are beneficial to certain species, they can be harmful to other species with different requirements. This introduces trade-offs between species when identifying which conservation action is best applied to which site. The thesis describes how the strength of such trade-offs can be identified, which is useful for assessing consequences of conservation decisions regarding species priorities and budget. Furthermore, the results of the thesis indicate that spatial SHDMs can be successfully used to account for species-specific requirements for spatial cohesion - in the reserve selection (single-option) context as well as in the multi-option context. Accounting for the spatial requirements of multiple species and allowing for several conservation options is however complicated, due to trade-offs in species requirements. It is also shown that spatial SHDMs can be successfully used for gaining information on factors that drive a species spatial distribution. Such information is valuable to conservation planning, as better knowledge on species requirements facilitates the design of networks for species persistence. This methods and results described in this thesis aim to improve species probabilities of persistence, by taking better account of species habitat and spatial requirements. Many real-world conservation planning problems are characterised by a variety of conservation options related to protection, restoration and maintenance of habitat. Planning tools therefore need to be able to incorporate multiple conservation options per site, in order to continue the search for cost-effective conservation planning solutions. Simultaneously, the spatial requirements of species need to be considered. The methods described in this thesis offer a starting point for combining these two relevant aspects of conservation planning.

Spatial ecology of an oak-associated herbivore community : A metacommunity of herbivores

Habitat fragmentation is currently affecting many species throughout the world. As a consequence, an increasing number of species are structured as metapopulations, i.e. as local populations connected by dispersal. While excellent studies of metapopulations have accumulated over the past 20 years, the focus has recently shifted from single species to studies of multiple species. This has created the concept of metacommunities, where local communities are connected by the dispersal of one or several of their member species. To understand this higher level of organisation, we need to address not only the properties of single species, but also establish the importance of interspecific interactions. However, studies of metacommunities are so far heavily biased towards laboratory-based systems, and empirical data from natural systems are urgently needed. My thesis focuses on a metacommunity of insect herbivores on the pedunculate oak Quercus robur a tree species known for its high diversity of host-specific insects. Taking advantage of the amenability of this system to both observational and experimental studies, I quantify and compare the importance of local and regional factors in structuring herbivore communities. Most importantly, I contrast the impact of direct and indirect competition, host plant genotype and local adaptation (i.e. local factors) to that of regional processes (as reflected by the spatial context of the local community). As a key approach, I use general theory to generate testable hypotheses, controlled experiments to establish causal relations, and observational data to validate the role played by the pinpointed processes in nature. As the central outcome of my thesis, I am able to relegate local forces to a secondary role in structuring oak-based insect communities. While controlled experiments show that direct competition does occur among both conspecifics and heterospecifics, that indirect interactions can be mediated by both the host plant and the parasitoids, and that host plant genotype may affect local adaptation, the size of these effects is much smaller than that of spatial context. Hence, I conclude that dispersal between habitat patches plays a prime role in structuring the insect community, and that the distribution and abundance of the target species can only be understood in a spatial framework. By extension, I suggest that the majority of herbivore communities are dependent on the spatial structure of their landscape and urge fellow ecologists working on other herbivore systems to either support or refute my generalization.

Studies of solar and stellar flares using multi-instrument data

Solar flares were first observed by plain eye in white light by William Carrington in England in 1859. Since then these eruptions in the solar corona have intrigued scientists. It is known that flares influence the space weather experienced by the planets in a multitude of ways, for example by causing aurora borealis. Understanding flares is at the epicentre of human survival in space, as astronauts cannot survive the highly energetic particles associated with large flares in high doses without contracting serious radiation disease symptoms, unless they shield themselves effectively during space missions. Flares may be at the epicentre of man s survival in the past as well: it has been suggested that giant flares might have played a role in exterminating many of the large species on Earth, including dinosaurs. Having said that prebiotic synthesis studies have shown lightning to be a decisive requirement for amino acid synthesis on the primordial Earth. Increased lightning activity could be attributed to space weather, and flares. This thesis studies flares in two ways: in the spectral and the spatial domain. We have extracted solar spectra using three different instruments, namely GOES (Geostationary Operational Environmental Satellite), RHESSI (Reuven Ramaty High Energy Solar Spectroscopic Imager) and XSM (X-ray Solar Monitor) for the same flares. The GOES spectra are low resolution obtained with a gas proportional counter, the RHESSI spectra are higher resolution obtained with Germanium detectors and the XSM spectra are very high resolution observed with a silicon detector. It turns out that the detector technology and response influence the spectra we see substantially, and are important to understanding what conclusions to draw from the data. With imaging data, there was not such a luxury of choice available. We used RHESSI imaging data to observe the spatial size of solar flares. In the present work the focus was primarily on current solar flares. However, we did make use of our improved understanding of solar flares to observe young suns in NGC 2547. The same techniques used with solar monitors were applied with XMM-Newton, a stellar X-ray monitor, and coupled with ground based Halpha observations these techniques yielded estimates for flare parameters in young suns. The material in this thesis is therefore structured from technology to application, covering the full processing path from raw data and detector responses to concrete physical parameter results, such as the first measurement of the length of plasma flare loops in young suns.

Modeling of Surface UV Radiation Using Satellite Data

Solar UV radiation is harmful for life on planet Earth, but fortunately the atmospheric oxygen and ozone absorb almost entirely the most energetic UVC radiation photons. However, part of the UVB radiation and much of the UVA radiation reaches the surface of the Earth, and affect human health, environment, materials and drive atmospheric and aquatic photochemical processes. In order to quantify these effects and processes there is a need for ground-based UV measurements and radiative transfer modeling to estimate the amounts of UV radiation reaching the biosphere. Satellite measurements with their near-global spatial coverage and long-term data conti-nuity offer an attractive option for estimation of the surface UV radiation. This work focuses on radiative transfer theory based methods used for estimation of the UV radiation reaching the surface of the Earth. The objectives of the thesis were to implement the surface UV algorithm originally developed at NASA Goddard Space Flight Center for estimation of the surface UV irradiance from the meas-urements of the Dutch-Finnish built Ozone Monitoring Instrument (OMI), to improve the original surface UV algorithm especially in relation with snow cover, to validate the OMI-derived daily surface UV doses against ground-based measurements, and to demonstrate how the satellite-derived surface UV data can be used to study the effects of the UV radiation. The thesis consists of seven original papers and a summary. The summary includes an introduction of the OMI instrument, a review of the methods used for modeling of the surface UV using satellite data as well as the con-clusions of the main results of the original papers. The first two papers describe the algorithm used for estimation of the surface UV amounts from the OMI measurements as well as the unique Very Fast Delivery processing system developed for processing of the OMI data received at the Sodankylä satellite data centre. The third and the fourth papers present algorithm improvements related to the surface UV albedo of the snow-covered land. Fifth paper presents the results of the comparison of the OMI-derived daily erythemal doses with those calculated from the ground-based measurement data. It gives an estimate of the expected accuracy of the OMI-derived sur-face UV doses for various atmospheric and other conditions, and discusses the causes of the differences between the satellite-derived and ground-based data. The last two papers demonstrate the use of the satellite-derived sur-face UV data. Sixth paper presents an assessment of the photochemical decomposition rates in aquatic environment. Seventh paper presents use of satellite-derived daily surface UV doses for planning of the outdoor material weathering tests.

Topics in Spatial Econometrics - With Applications to House Prices

Topics in Spatial Econometrics — With Applications to House Prices Spatial effects in data occur when geographical closeness of observations influences the relation between the observations. When two points on a map are close to each other, the observed values on a variable at those points tend to be similar. The further away the two points are from each other, the less similar the observed values tend to be. Recent technical developments, geographical information systems (GIS) and global positioning systems (GPS) have brought about a renewed interest in spatial matters. For instance, it is possible to observe the exact location of an observation and combine it with other characteristics. Spatial econometrics integrates spatial aspects into econometric models and analysis. The thesis concentrates mainly on methodological issues, but the findings are illustrated by empirical studies on house price data. The thesis consists of an introductory chapter and four essays. The introductory chapter presents an overview of topics and problems in spatial econometrics. It discusses spatial effects, spatial weights matrices, especially k-nearest neighbours weights matrices, and various spatial econometric models, as well as estimation methods and inference. Further, the problem of omitted variables, a few computational and empirical aspects, the bootstrap procedure and the spatial J-test are presented. In addition, a discussion on hedonic house price models is included. In the first essay a comparison is made between spatial econometrics and time series analysis. By restricting the attention to unilateral spatial autoregressive processes, it is shown that a unilateral spatial autoregression, which enjoys similar properties as an autoregression with time series, can be defined. By an empirical study on house price data the second essay shows that it is possible to form coordinate-based, spatially autoregressive variables, which are at least to some extent able to replace the spatial structure in a spatial econometric model. In the third essay a strategy for specifying a k-nearest neighbours weights matrix by applying the spatial J-test is suggested, studied and demonstrated. In the final fourth essay the properties of the asymptotic spatial J-test are further examined. A simulation study shows that the spatial J-test can be used for distinguishing between general spatial models with different k-nearest neighbours weights matrices. A bootstrap spatial J-test is suggested to correct the size of the asymptotic test in small samples.

Markov random fields and spatial smoothing in improving of forest inventory estimates

Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.

Microbiological characterisation of soils : Evaluation of some critical steps in data collection and experimental design

The study of soil microbiota and their activities is central to the understanding of many ecosystem processes such as decomposition and nutrient cycling. The collection of microbiological data from soils generally involves several sequential steps of sampling, pretreatment and laboratory measurements. The reliability of results is dependent on reliable methods in every step. The aim of this thesis was to critically evaluate some central methods and procedures used in soil microbiological studies in order to increase our understanding of the factors that affect the measurement results and to provide guidance and new approaches for the design of experiments. The thesis focuses on four major themes: 1) soil microbiological heterogeneity and sampling, 2) storage of soil samples, 3) DNA extraction from soil, and 4) quantification of specific microbial groups by the most-probable-number (MPN) procedure. Soil heterogeneity and sampling are discussed as a single theme because knowledge on spatial (horizontal and vertical) and temporal variation is crucial when designing sampling procedures. Comparison of adjacent forest, meadow and cropped field plots showed that land use has a strong impact on the degree of horizontal variation of soil enzyme activities and bacterial community structure. However, regardless of the land use, the variation of microbiological characteristics appeared not to have predictable spatial structure at 0.5-10 m. Temporal and soil depth-related patterns were studied in relation to plant growth in cropped soil. The results showed that most enzyme activities and microbial biomass have a clear decreasing trend in the top 40 cm soil profile and a temporal pattern during the growing season. A new procedure for sampling of soil microbiological characteristics based on stratified sampling and pre-characterisation of samples was developed. A practical example demonstrated the potential of the new procedure to reduce the analysis efforts involved in laborious microbiological measurements without loss of precision. The investigation of storage of soil samples revealed that freezing (-20 °C) of small sample aliquots retains the activity of hydrolytic enzymes and the structure of the bacterial community in different soil matrices relatively well whereas air-drying cannot be recommended as a storage method for soil microbiological properties due to large reductions in activity. Freezing below -70 °C was the preferred method of storage for samples with high organic matter content. Comparison of different direct DNA extraction methods showed that the cell lysis treatment has a strong impact on the molecular size of DNA obtained and on the bacterial community structure detected. An improved MPN method for the enumeration of soil naphthalene degraders was introduced as an alternative to more complex MPN protocols or the DNA-based quantification approach. The main advantage of the new method is the simple protocol and the possibility to analyse a large number of samples and replicates simultaneously.