Humans have affected the Swedish forests for a long time, mainly through agriculture and forestry. Since the beginning of the 20th century, a lot of changes have taken place in forest policy, which have affected the structures of our forests, such as tree age, size and species distributions. By using information from different types of historical data, we can increase our understanding of the earlier structures of forests and how to manage them in the future. This study investigated changes in annual growth and changes in age, diameter, height and tree species distribution in the forests of Östergötland from year 1927 to the period 1983-2017, using data from the Swedish National Forest Inventory. Six tree species where used, Picea spp, Pinus spp, Quercus robur, Betula spp, Alnus spp and Populus tremula. There was an increase in the proportion of Picea spp, and a decrease in the proportion of Pinus spp since 1927. The proportion of deciduous trees also increased but not as much. Interestingly, the proportion of Betula spp had fallen since 1927, but the now larger proportion of young trees indicate that the proportion of Betula spp is increasing again. Q. robur, P. tremula, Picea spp and Pinus spp also had a larger proportion of younger trees in the more recent period. There was a significantly higher proportion of tall trees during the latter period for all tree species. For growth rate in width, the results varied among tree species. For Betula spp it had decreased and for Q. robur it had increased. For the coniferous trees there was hardly any difference between the periods. Overall, the results show that Östergötland's forests have been influenced by forestry and increased ungulate populations since the first inventory 1927 and that there have been changes in the composition of the forests. / Människan har länge påverkat de svenska skogarna. Sedan 1900-talets början har en hel del förändringar skett inom skogspolitiken, vilket har påverkat bland annat skogarnas ålder- och storleksfördelning, samt trädslagsfördelning. Genom att använda information från olika typer av historiska data kan vi öka vår förståelse om hur skogar såg ut förr och vad som har påverkat dem. Denna studie undersökte skillnader i tillväxt, höjd-och diameterfördelning, samt åldersfördelning i Östergötlands skogar från år 1927 till perioden 1983–2017, med hjälp av data från riksskogstaxeringen. Sex trädslag användes; gran (Picea spp), tall (Pinus spp), ek (Quercus robur), björk (Betula spp), al (Alnus spp) och asp (Populus tremula). En kraftig ökning av andelen gran hade skett sedan 1927, medan andelen tall hade minskat. För lövträden hade det endast skett en liten ökning i andel. Intressant var också att andelen björk hade minskat sedan 1927 och att andelen björkar yngre än 50 år var större den senare perioden, vilket indikerar att björkens andel kan vara på väg att öka igen. Ek, asp, gran och tall hade också en större andel yngre träd under den senare perioden. För alla trädslag fanns det en betydligt mindre andel höga träd år 1927. För årlig tillväxt i bredd varierade resultaten trädslagen emellan. För björk hade årsringsbredden minskat sedan 1927, medan den hade ökat för ek. För barrträden var det knappt någon skillnad mellan perioderna. Resultaten visar att Östergötlands skogar har påverkats mycket av skogsbruket, samt klövviltsbete, sedan 1927 och att det har skett flera strukturella förändringar i skogarnas sammansättning.

A área de pesquisa denominada Informática para Biodiversidade enfrenta o desafio de suprir a demanda por tecnologia de apoio à conservação da biodiversidade. Dentre as áreas da ecologia que se beneficiam de recursos tecnológicos, a modelagem de distribuição de espécies se destaca pelo número de ferramentas e de algoritmos desenvolvidos para os pesquisadores da área. No entanto, estudos demostram que a modelagem tem se tornado mais complexa, bem como, a necessidade por melhorias da aplicação de novas técnicas e soluções computacionais. A interoperabilidade computacional para os dados de biodiversidade, que incluem os modelos gerados pelas ferramentas de modelagem, é citada pelos autores e pesquisadores da área como uma preocupação que demanda estudos, definição de melhores práticas e soluções de computação. Cada tópico que envolve a modelagem como, algoritmos, parâmetros, dados de ocorrência, camadas ambientais, ferramentas e técnicas para a elaboração de modelos, além dos padrões de metadados e perfis de aplicação, são objetos de estudo para que seja possível a interoperabilidade nesse campo de pesquisa. Este trabalho apresenta, portanto, uma estratégia computacional para apoiar a interoperabilidade entre os modelos gerados pelas ferramentas de modelagem de distribuição de espécies, através do uso de padrões de metadados e pelo desenvolvimento de um perfil de aplicação que apoie essa interoperabilidade. São apresentados dois estudos de caso com o objetivo de validar essas estratégias e uma arquitetura computacional para apoiar comunidades de desenvolvimento de ferramentas de modelagem a buscarem essa interoperabilidade entre os dados fornecidos e processados por elas. As contribuições deste trabalho envolvem a disponibilização de um perfil de aplicação voltado para a área de modelagem de distribuição de espécies, um protótipo de software para processar os modelos gerados pelas ferramentas de modelagem, o incentivo e o uso do digital objetct identification para disponibilização dos dados, além do processo de pesquisa e da validação de metodologias que foram utilizadas para se alcançarem os resultados desta pesquisa. / The research area called Informatics for Biodiversity faces the challenge of meeting the demand for technology to support biodiversity conservation. Among the areas of ecology that benefit from technological resources, the modeling of species distribution is notable for the number of tools and algorithms developed to researchers in this area. However, studies have shown that modeling has become more complex, as well as the need for improvements in the application of new techniques and computational solutions. The computational interoperability for biodiversity data, which includes models generated by modeling tools, is cited by authors and researchers in the field as a concern that demands studies, definition of best practices and computing solutions. Each topic that involves modeling such as algorithms, parameters, occurrence data, environmental layers, tools, techniques for the elaboration of models, standards of metadata and application profiles are objects of study of this dissertation. This thesis presents a computational strategy to support the interoperability between the models generated by the modeling tools of species distribution, through the use of metadata standards and the development of an application profile that supports this interoperability. Two case studies are presented with the objective of validating these strategies and we also present a computational architecture to support communities to develop of modeling tools to seek this interoperability between the data supplied and processed by them. The contributions of this work involve the provision of an application profile for the area of species distribution modeling, a software prototype to process the models generated by the modeling tools, the incentive and use of the digital objetct identification to make data available, and in addition to the process of research and validation of methodologies that were used to summarize the results of this research.

Several aspects of plant-pollinator interactions are presented in the thesis. It contains a review on the open questions of plant-pollinator interactions from single species to complex networks. The following sections document novel results. Firstly, the conservation of complex pollination networks is addressed through the hierarchy of species' importance. In addition, the habitat requirements and interactions of a threatened rare pollinator species are explored. In the following chapters, the results from manipulative approaches applied in the field to plant-pollinator interactions are presented. The effect of pollinator's population decline on pollinators' foraging for pollen is investigated. Moreover, the way plant species loss impact several aspects of pollinator visitation is presented. Lastly, the impact of species removal on plant-pollinator network topology and on species ability of establishing new interactions is investigated.

Accounts of species’ range shifts in response to climate change, most often as latitudinal shifts towards the poles or upslope shifts to higher elevations, are rapidly accumulating. These range shifts are often attributed to species ‘tracking’ their thermal niches as temperatures in their native ranges increase. Our objective was to estimate the degree to which climate change-driven shifts in water temperature may increase the exposure of West Virginia’s native freshwater fishes to mountaintop removal surface coal mining. Mid-century shifts in habitat suitability for nine non-game West Virginia fishes were projected via Maximum Entropy species distribution modeling, using a combination of physical habitat, historical climate conditions, and future climate data. Modeling projections for a high-emissions scenario (Representative Concentration Pathway 8.5) predict that habitat suitability will increase in high elevation streams for eight of nine species, with marginal increases in habitat suitability ranging from 46-418%. We conclude that many West Virginia fishes will be at risk of increased exposure to mountaintop removal surface coal mining if climate change continues at a rapid pace.

Conservation efforts that involve habitat protection, population augmentation, and species reintroductions require knowledge of the habitat requirements, distribution, and abundance of a species—information that can be challenging to acquire, especially for rare organisms with patchy distributions. In this thesis, I develop a protocol for the use of environmental DNA (eDNA) and create a Species Distribution Model for the endangered James spinymussel, Parvaspina collina (Unionidae). The results of this work show that eDNA is a robust tool for identifying species presence but not for estimating the relative abundance of populations. This study found that P. collina’s distribution is influenced by abiotic habitat characteristics related to sedimentation and runoff rather than by the distribution of its host fishes. The predicted habitat suitability was used to identify locations of priority conservation concern and these results can be used to direct future sampling efforts, identify potential dispersal routes, and inform conservation decisions.

Invasive plant species impact ecosystems by altering native plant community composition and modifying ecosystem properties such as fire and nutrient cycles. We used species distribution models to address both theoretical and applied questions regarding invasive plants in an ecosystem particularly vulnerable to invasion, riparian areas. In our first study, we asked whether a native species is closer to equilibrium than a functionally similar invasive species and determined drivers of invasion for an aggressive invader of riparian areas, Phalaris arundinacea (reed canarygrass). We modeled the presence of P. arundinacea and a comparable native species using four techniques and compared model fit between species and between models with and without dispersal processes incorporated. Non-dispersal model fit for our invasive species was lower than for the native species and improvement in fit with the addition of the dispersal constraint was greater for the invasive species than the native species. These results provide evidence that invasive species are further from equilibrium than native species and suggest that dispersal processes should be considered when modeling invasive species. In our second study, we addressed whether there was a set of site traits that make some sites more prone to invasion by non-native plants than others. We used Random Forests to individually model the presence of 11 invasive plant species that are designated as noxious weeds in our study area. We used model results to identify general patterns of invasion and to provide management recommendations for the study area. We found that a particular site type was more likely to be invaded by the majority of study species: hot, dry sites with high grass or shrub cover near roads with high nutrient levels and high stream baseflow values. Management recommendations to combat invasion by P. arundinacea in particular and invasive species in general are the same: limiting species’ spread along roads, lowering site nutrient levels, and anticipating increased spread with climate change.

The distribution of the cliff chipmunk in Idaho was previously considered to include only the Raft River Valley and the Goose Creek Basin. A pilot study was conducted in 2003 and 2004. Thirty-five cliff chipmunk presence locations and 124 absence locations were recorded. Habitat variables of elevation, slope, deviation from south, distance to water, and vegetation type were extracted for all of the absence and presence points by means of GIS analysis. The data were analyzed by implementing a classification tree, and a "GIS habitat association model" was created. The model was tested in 2005, and the overall model accuracy was 77.5%. The study extended the known cliff chipmunk range in Idaho west to Rock Creek, Twin Falls County, east to Weston Canyon, Franklin County, and north to the Cotterel Mountains, Cassia County. Monitoring current known locations and searching for new locations to further refine 11 understanding of the species' distribution and to determine the actual population status of cliff chipmunks in Idaho are recommended.

Human activities in the form of land use changes, urbanisation and infrastructure developments are major threats to biodiversity. The loss and fragmentation of natural habitats are great obstacles for the long term preservation of biodiversity and nature protection measures alone may not be sufficient to tackle the problem. Environmental impact assessment (EIA) and strategic environmental assessment (SEA) play a central role in identifying, predicting and managing the impacts of human activities on biodiversity. The review of current practice suggests that the complexity of the task is underestimated and that new methodological approaches encompassing the entire landscape are needed. Spatial aspects of the assessment and the lack of information on scale-related issues are particular problems affecting the appropriate assessment of cumulative effects. In parallel with the development and establishment of EIA and SEA, spatial modelling is an expanding field in ecology and many derived applications could be suitable for the prediction and assessment of biodiversity-related impacts. The diversity of modelling methods suggests that a strategy is needed to identify prediction methods appropriate for EIA and SEA. The relevance and potential limitations of GIS-based species distribution and habitat models in predicting impacts on biodiversity were examined in three studies in the greater Stockholm area. Distinct approaches to habitat suitability modelling were compared from the perspective of environmental assessment needs and requirements. The results showed that model performance, validity and ultimate suitability for planning applications were strongly dependent on empirical data and expert knowledge. The methods allowed visual, qualitative and quantitative assessment of habitat loss, thus improving decision support for assessment of impacts on biodiversity. The proposed methods allowed areas of high ecological value and the surrounding landscape to be considered in the same assessment, thereby contributing to better integration of biodiversity issues in physical planning. / QC 20100727

Statistical modelling is often used to relate the presence or abundance of species to environmental predictors, thereby providing a basis for predictive mapping of species or biodiversity. The variables included must thus be relevant and reflect actual changes in the environment. Therefore, the quantification of species–environment relationships is an important aspect of predictive modelling. This thesis examines how phytobenthic species or communities in the Baltic Sea relate to environmental gradients, and if different aspects of phytobenthic species distribution in the Baltic Sea could be explained by spatial or temporal variation in environmental factors. Predictive distribution modelling usually focuses on how environmental variables control the distribution of species or communities. Thus the relative weight of the predictor variables on different scales is of importance. In this thesis, I show that the relative importance of environmental variables depends both on geographic scale and location, and that it also differs between species or species groups. There are no simple explanations to the temporal variability in species occurrence. I here show that the temporal changes in species distribution within the phytobentic zone varies in a spatial context. I also try to find temporal and spatio-temporal patterns in species distribution that could be related to changes in climate or anthropogenic disturbance. However, the findings in this thesis suggest that single factor explanations are insufficient for explaining large-scale changes in species distribution. A greater understanding of the relationship between species and their environment will lead to the development of more sensitive models of species distributions. The predictions can be used to visualise spatial changes in the distribution of plant and animal communities over time. / At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 2: Submitted. Paper 3: Manuscript. Paper 4: Manuscript. Paper 5: Manuscript.

Conservation strategies are mainly focused on species existing in an environment shaped by natural and anthropogenic pressures. Yet, evidence shows that climate is changing faster than ever and expected to continue to change in the near future, which can be devastating for plants with restricted ranges. Turkey harbors many endemic species that might be affected from these changes. However, available data is scarce and biased, complicating the anticipation of future changes. Aim of this study is to improve our understanding of endemic species distributions and forecasting effects of climate change via species distribution modelling (SDM). The study is based on two Anatolian (Crocus ancyrensis and Crataegus tanacetifolia) and two Ankara (Salvia aytachii and Centaurea tchihatcheffii) endemics. Independent presence and absence data (ranging between 19-68 and 38-61, respectively) for each species was collected through fieldwork in and around the Upper Sakarya Basin in 2008 and 2009. With the software Maxent, SDMs were performed by using 8 least correlated environmental features and random presence records (of which 25% were used for confusion matrix). SDMs for current distributions of C. ancyrensis, C. tchihatcheffii and C. tanacetifolia were reliable enough for future extrapolations despite errors originating from scale, non-equilibrium status and biotic interactions, respectively. The model for S. aytachii failed due to absence of limiting factor (soil type) in the model. Future projections of those three species modelled using CCCMA-CGCM2 and HADCM3 climate models indicated three possible responses to climate change: (1) Extinction, especially for habitat specialists / (2) Range expansion, especially for generalist species / and (3) Range contradiction, especially for Euro-Siberian mountainous species. Species modelling can be used to understand possible responses of plant species to climate change in Turkey. Modelling techniques should to be improved, however, especially by integrating other parameters such as biotic interactions and through a better understanding of uncertainties.