Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Assessment of Coastal Bird Populations and Habitats on the Finnish Coast of the Baltic Sea: Implications for Monitoring and Management

Coastal birds are an integral part of coastal ecosystems, which nowadays are subject to severe environmental pressures. Effective measures for the management and conservation of seabirds and their habitats call for insight into their population processes and the factors affecting their distribution and abundance. Central to national and international management and conservation measures is the availability of accurate data and information on bird populations, as well as on environmental trends and on measures taken to solve environmental problems. In this thesis I address different aspects of the occurrence, abundance, population trends and breeding success of waterbirds breeding on the Finnish coast of the Baltic Sea, and discuss the implications of the results for seabird monitoring, management and conservation. In addition, I assess the position and prospects of coastal bird monitoring data, in the processing and dissemination of biodiversity data and information in accordance with the Convention on Biological Diversity (CBD) and other national and international commitments. I show that important factors for seabird habitat selection are island area and elevation, water depth, shore openness, and the composition of island cover habitats. Habitat preferences are species-specific, with certain similarities within species groups. The occurrence of the colonial Arctic Tern (Sterna paradisaea) is partly affected by different habitat characteristics than its abundance. Using long-term bird monitoring data, I show that eutrophication and winter severity have reduced the populations of several Finnish seabird species. A major demographic factor through which environmental changes influence bird populations is breeding success. Breeding success can function as a more rapid indicator of sublethal environmental impacts than population trends, particularly for long-lived and slowbreeding species, and should therefore be included in coastal bird monitoring schemes. Among my target species, local breeding success can be shown to affect the populations of the Mallard (Anas platyrhynchos), the Eider (Somateria mollissima) and the Goosander (Mergus merganser) after a time lag corresponding to their species-specific recruitment age. For some of the target species, the number of individuals in late summer can be used as an easier and more cost-effective indicator of breeding success than brood counts. My results highlight that the interpretation and application of habitat and population studies require solid background knowledge of the ecology of the target species. In addition, the special characteristics of coastal birds, their habitats, and coastal bird monitoring data have to be considered in the assessment of their distribution and population trends. According to the results, the relationships between the occurrence, abundance and population trends of coastal birds and environmental factors can be quantitatively assessed using multivariate modelling and model selection. Spatial data sets widely available in Finland can be utilised in the calculation of several variables that are relevant to the habitat selection of Finnish coastal species. Concerning some habitat characteristics field work is still required, due to a lack of remotely sensed data or the low resolution of readily available data in relation to the fine scale of the habitat patches in the archipelago. While long-term data sets exist for water quality and weather, the lack of data concerning for instance the food resources of birds hampers more detailed studies of environmental effects on bird populations. Intensive studies of coastal bird species in different archipelago areas should be encouraged. The provision and free delivery of high-quality coastal data concerning bird populations and their habitats would greatly increase the capability of ecological modelling, as well as the management and conservation of coastal environments and communities. International initiatives that promote open spatial data infrastructures and sharing are therefore highly regarded. To function effectively, international information networks, such as the biodiversity Clearing House Mechanism (CHM) under the CBD, need to be rooted at regional and local levels. Attention should also be paid to the processing of data for higher levels of the information hierarchy, so that data are synthesized and developed into high-quality knowledge applicable to management and conservation.

Spatial and Spectral Separability of Grasslands in the inner Turku Archipelago using Landsat Thematic Mapper Satellite Imagery

The present study investigates the spatial and spectral discrimination potential for grassland patches in the inner Turku Archipelago using Landsat Thematic Mapper satellite imagery. The spatial discrimination potential was computed through overlay analysis using official grassland parcel data and a hypothetical 30 m resolution satellite image capturing the site. It found that Landsat TM imagery’s ability to retrieve pure or near-pure pixels (90% purity or more) from grassland patches smaller than 1 hectare was limited to 13% success, compared to 52% success when upscaling the resolution to 10 x 10 m pixel size. Additionally, the perimeter/area patch metric is proposed as a predictor for the suitability of the spatial resolution of input imagery. Regression analysis showed that there is a strong negative correlation between a patch’s perimeter/area ratio and its pure pixel potential. The study goes on to characterise the spectral response and discrimination potential for the five main grassland types occurring in the study area: recreational grassland, traditional pasture, modern pasture, fodder production grassland and overgrown grassland. This was done through the construction of spectral response curves, a coincident spectral plot and a contingency matrix as well as by calculating the transformed divergence for the spectral signatures, all based on training samples from the TM imagery. Substantial differences in spectral discrimination potential between imagery from the beginning of the growing season and the middle of summer were found. This is because the spectral responses for these five grassland types converge as the peak of the growing season draws nearer. Recreational grassland shows a consistent discrimination advantage over other grassland types, whereas modern pasture is most easily confused. Traditional pasture land, perhaps the most biologically valuable grassland type, can be spectrally discriminated from other grassland types with satisfactory success rates provided early growing season imagery is used.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Mathematics inspired by Darwin. Adaptive dynamics of dispersal and cooperation

In 1859, Charles Darwin published his theory of evolution by natural selection, the process occurring based on fitness benefits and fitness costs at the individual level. Traditionally, evolution has been investigated by biologists, but it has induced mathematical approaches, too. For example, adaptive dynamics has proven to be a very applicable framework to the purpose. Its core concept is the invasion fitness, the sign of which tells whether a mutant phenotype can invade the prevalent phenotype. In this thesis, four real-world applications on evolutionary questions are provided. Inspiration for the first two studies arose from a cold-adapted species, American pika. First, it is studied how the global climate change may affect the evolution of dispersal and viability of pika metapopulations. Based on the results gained here, it is shown that the evolution of dispersal can result in extinction and indeed, evolution of dispersalshould be incorporated into the viability analysis of species living in fragmented habitats. The second study is focused on the evolution of densitydependent dispersal in metapopulations with small habitat patches. It resulted a very surprising unintuitive evolutionary phenomenon, how a non-monotone density-dependent dispersal may evolve. Cooperation is surprisingly common in many levels of life, despite of its obvious vulnerability to selfish cheating. This motivated two applications. First, it is shown that density-dependent cooperative investment can evolve to have a qualitatively different, monotone or non-monotone, form depending on modelling details. The last study investigates the evolution of investing into two public-goods resources. The results suggest one general path by which labour division can arise via evolutionary branching. In addition to applications, two novel methodological derivations of fitness measures in structured metapopulations are given.

GIS assessing traditional and modern agricultural land use/land cover change. A case study 1959-2005: Rekijoki, Somero, SW-Finland

Finland’s rural landscape has gone through remarkable changes from the 1950’s, due to agricultural developments. Changed farming practices have influenced especially traditional landscape management, and modifications in the arable land structure and grasslands transitions are notable. The review of the previous studies reveal the importance of the rural landscape composition and structure to species and landscape diversity, whereas including the relevance in presence of the open ditches, size of the field and meadow patches, topology of the natural and agricultural landscape. This land-change study includes applying remote sensed data from two time series and empirical geospatial analysis in Geographic Information Systems (GIS). The aims of this retrospective research is to detect agricultural landscape use and land cover change (LULCC) dynamics and discuss the consequences of agricultural intensification to landscape structure covering from the aspects of landscape ecology. Measurements of LULC are derived directly from pre-processed aerial images by a variety of analytical procedures, including statistical methods and image interpretation. The methodological challenges are confronted in the process of landscape classification and combining change detection approaches with landscape indices. Particular importance is paid on detecting agricultural landscape features at a small scale, demanding comprehensive understanding of such agroecosystems. Topological properties of the classified arable land and valley are determined in order to provide insight and emphasize the aspect the field edges in the agricultural landscape as important habitat. Change detection dynamics are presented with change matrix and additional calculations of gain, loss, swap, net change, change rate and tendencies are made. Transition’s possibility is computed following Markov’s probability model and presented with matrix, as well. Thesis’s spatial aspect is revealed with illustrative maps providing knowledge of location of the classified landscape categories and location of the dynamics of the changes occurred. It was assured that in Rekijoki valley’s landscape, remarkable changes in landscape has occurred. Landscape diversity has been strongly influenced by modern agricultural landscape change, as NP of open ditches has decreased and the MPS of the arable plot has decreased. Overall change in the diversity of the landscape is determined with the decrease of SHDI. Valley landscape considered as traditional land use area has experienced major transitional changes, as meadows class has lost almost one third of the area due to afforestation. Also, remarkable transitions have occurred from forest to meadow and arable land to built area. Boundaries measurement between modern and traditional landscape has indicated noticeable proportional increase in arable land-forest edge type and decrease in arable land-meadow edge type. Probability calculations predict higher future changes for traditional landscape, but also for arable land turning into built area.

Pp2a: At The Crossroads Between Growth and Defence In Plants

Living organisms manage their resources in well evolutionary-preserved manner to grow and reproduce. Plants are no exceptions, beginning from their seed stage they have to perceive environmental conditions to avoid germination at wrong time or rough soil. Under favourable conditions, plants invest photosynthetic end products in cell and organ growth to provide best possible conditions for generation of offspring. Under natural conditions, however, plants are exposed to a multitude of environmental stress factors, including high light and insufficient light, drought and flooding, various bacteria and viruses, herbivores, and other plants that compete for nutrients and light. To survive under environmental challenges, plants have evolved signaling mechanisms that recognise environmental changes and perform fine-tuned actions that maintain cellular homeostasis. Controlled phosphorylation and dephosphorylation of proteins plays an important role in maintaining balanced flow of information within cells. In this study, I examined the role of protein phosphatase 2A (PP2A) on plant growth and acclimation under optimal and stressful conditions. To this aim, I studied gene expression profiles, proteomes and protein interactions, and their impacts on plant health and survival, taking advantage of the model plant Arabidopsis thaliana and the mutant approach. Special emphasis was made on two highly similar PP2A-B regulatory subunits, B’γ and B’ζ. Promoters of B’γ and B’ζ were found to be similarly active in the developing tissues of the plant. In mature leaves, however, the promoter of B’γ was active in patches in leaf periphery, while the activity of B’ζ promoter was evident in leaf edges. The partially overlapping expression patterns, together with computational models of B’γ and B’ζ within trimeric PP2A holoenzymes suggested that B’γ and B’ζ may competitively bind into similar PP2A trimmers and thus influence each other’s actions. Arabidopsis thaliana pp2a-b’γ and pp2a-b’γζ double mutants showed dwarfish phenotypes, indicating that B’γ and B’ζ are needed for appropriate growth regulation under favorable conditions. However, while pp2a-b’γ displayed constitutive immune responses and appearance of premature yellowings on leaves, the pp2a-b’γζ double mutant supressed these yellowings. More detailed analysis of defense responses revealed that B’γ and B’ζ mediate counteracting effects on salicylic acid dependent defense signalling. Associated with this, B’γ and B’ζ were both found to interact in vivo with CALCIUM DEPENDENT PROTEIN KINASE 1 (CPK1), a crucial element of salicylic acid signalling pathway against pathogens in plants. In addition, B’γ was shown to modulate cellular reactive oxygen species (ROS) metabolism by controlling the abundance of ALTERNATIVE OXIDASE 1A and 1D in mitochondria. PP2A B’γ and B’ζ subunits turned out to play crucial roles in the optimization of plant choices during their development. Taken together, PP2A allows fluent responses to environmental changes, maintenance of plant homeostasis, and grant survivability with minimised cost of redirection of resources from growth to defence.

Effects of algal turbidity on foraging and antipredator behaviour of the three-spined stickleback (Gasterosteus aculeatus)

The aim of this thesis was to examine how aquatic organisms, such as fish, behave in an altered environmental condition. Many species of fish use vision as their primary tool to gain information about their surrounding environment. The visual conditions of aquatic habitats are often altered as a result of anthropogenic disturbance, such as eutrophication that initiates algal turbidity. In general, turbidity reduces the visibility and can be hypothesized to have an influence on the behaviour of fish. I used the three-spined stickleback (Gasterosteus aculeatus) as a model species and conducted four studies in the laboratory to test how algal turbidity affects its behaviour. In this thesis, two major behavioural aspects are discussed. The first is antipredator behaviour. In study I, the combined effects of turbidity and shoot density on habitat choice (shelter vs open) behaviour was tested on a group of sticklebacks (20 fish) in the presence and absence of piscivorous perch (Perca fluviatilis). In study II, I examined the behavioural responses of feeding sticklebacks when they were exposed to the sudden appearance of an avian predator (the silhouette of a common tern, Sterna hirundo). The study was done in turbid and clear water using three different groups sizes (1, 3 and 6 fish). The second aspect is foraging behaviour. Study III & IV focused on the effects of algal turbidity on the foraging performance of sticklebacks. In study III, I conducted two separate experiments to examine the effects of turbidity on prey consumption and prey choice of sticklebacks. In this experiment turbidity levels and the proportion of large and small prey (Daphnia spp.) were manipulated. In study IV, I studied whether a group of six sticklebacks can distribute themselves according to food input at two feeding stations in a way that provided each fish with the same amount of food in clear and turbid water. I also observed whether the fish can follow changes in resource distribution between the foraging patches. My results indicate an overall influence of algal turbidity on the antipredator and foraging behaviour of sticklebacks. In the presence of a potential predator, the use of the sheltered habitat was more pronounced at higher turbidity. Besides this, sticklebacks reduced their activity levels with predator presence at higher turbidity and shoot density levels, suggesting a possible antipredator adaptation to avoid a predator. When exposed to a sudden appearance of an avian predator, sticklebacks showed a weaker antipredator response in turbid water, which suggests that turbidity degrades the risk assessment capabilities of sticklebacks. I found an effect of group size but not turbidity in the proportion of sticklebacks that fled to the shelter area, which indicates that sticklebacks are able to communicate among group members at the experimental turbidity levels. I found an overall negative effect of turbidity on food intake. Both turbidity and changes in the proportion of prey sizes played a significant role in a stickleback’s prey selection. At lower turbidity levels (clear <1 and 5 NTU) sticklebacks showed preferences for large prey, whereas in more turbid conditions and when the proportion of large to small prey increased sticklebacks became increasingly random in their prey selection. Finally, my results showed that groups of sticklebacks disperse themselves between feeding stations according to the reward ratios following the predictions of the ideal free distribution theory. However, they took a significantly longer time to reach the equilibrium distribution in turbid water than in clear water. In addition, they showed a slower response to changes in resource distribution in a turbid environment. These findings suggest that turbidity interferes with the information transfer among group foragers. It is important to understand that aquatic animals are often exposed to a degraded environment. The findings of this thesis suggest that algal turbidity negatively affects their behavioural performance. The results also shed light on the underlying behavioural strategies of sticklebacks in turbid conditions that might help them adapt to an altered environmental situation and increase their survival. In conclusion, I hold that although algal turbidity has detrimental effects on the antipredator and foraging behaviour of sticklebacks, their behavioural adjustment might help them adapt to a changing environment.

Verkkopalveluiden jatkuvan ylläpidon kehittäminen: Case Aucor Oy ja WordPress

Verkkopalveluiden ylläpitovaiheessa halutaan varmistua, etteivät palveluun tehdyt muutokset aiheuta verkkopalvelussa virhetilanteita ja palvelu toimii moitteetta. Muutoksen hyväksyntätestaus voidaan tehdä regressiotestauksena vertaamalla palvelun tilaa ennen ja jälkeen muutoksen. Sisältöpainotteisessa verkkopalvelussa testaaminen keskittyy loppukäyttäjälle esitetyn sivun semanttiseen sekä visuaaliseen oikeellisuuteen sekä erilaisiin toiminnallisiin testeihin. Työssä tarkastellaan etenkin suositulla WordPress-julkaisujärjestelmällä toteutettujen verkkopalveluiden ylläpitoa. Keskeisenä osana julkaisujärjestelmillä toteutettujen verkkopalveluiden ylläpitoa on julkaisujärjestelmän ja sitä täydentävien lisäosien päivittämistä ajantasaisiin versioihin. Nämä päivitykset paitsi tuovat uusia ominaisuuksia verkkopalvelun kehittäjille, myös paikkaavat järjestelmän tietoturvahaavoittuvuuksia sekä korjaavat aiemmissa versioissa esiintyneitä virheitä. Tässä työssä kehitettiin kohdeyrityksen aiempia verkkopalveluiden ylläpitoprosesseja niissä tunnistettujen kehityskohteiden perusteella. Uudistettu kokonaisuus jakautuu kahteen kokonaisuuteen: päivitystarpeen seurantaan sekä päivitysten tekemiseen. Päivitystarpeen seurantaa varten kehitettiin uusi työkalu helpottamaan kokonaiskuvan hahmottamista. Päivitysten tekemisen osalta työssä keskityttiin automatisoidun regressiotestauksen kehittämiseen, missä tärkeimpänä testauskeinona käytetään verkkopalvelusta tallennettujen kuvankaappausten vertailuun perustuvaa visuaalista testausta. Uusien ylläpitoprosesseille määriteltiin myös seurannan kohteet uudistuksen onnistumisen ja jatkokehityksen arviointia varten.