Interpreting marine benthic ecosystem functioning in coastal waters: validating the biological trait concept

Coastal areas harbour high biodiversity, but are simultaneously affected by rapid degradations of species and habitats due to human interactions. Such alterations also affect the functioning of the ecosystem, which is primarily governed by the characteristics or traits expressed by the organisms present. Marine benthic fauna is nvolved in numerous functions such as organic matter transformation and transport, secondary production, oxygen transport as well as nutrient cycling. Approaches utilising the variety of faunal traits to assess benthic community functioning have rapidly increased and shown the need for further development of the concept. In this thesis, I applied biological trait analysis that allows for assessments of a multitude of categorical traits and thus evaluation of multiple functional aspects simultaneously. I determined the functional trait structure, diversity and variability of coastal zoobenthic communities in the Baltic Sea. The measures were related to recruitment processes, habitat heterogeneity, large-scale environmental and taxonomic gradients as well as anthropogenic impacts. The studies comprised spatial scales from metres to thousands of kilometres, and temporal scales spanning one season as well as a decade. The benthic functional structure was found to vary within and between seagrass landscape microhabitats and four different habitats within a coastal bay, in papers I and II respectively. Expressions of trait categories varied within habitats, while the density of individuals was found to drive the functional differences between habitats. The findings in paper III unveiled high trait richness of Finnish coastal benthos (25 traits and 102 cateogries) although this differed between areas high and low in salinity and human pressure. In paper IV, the natural reduction in taxonomic richness across the Baltic Sea led to an overall reduction in function. However, functional richness in terms of number of trait categories remained comparatively high at low taxon richness. Changes in number of taxa within trait categories were also subtle and some individual categories were maintained or even increased. The temporal analysis in papers I and III highlighted generalities in trait expressions and dominant trait categories in a seagrass landscape as well as a “type organism” for the northern Baltic Sea. Some initial findings were made in all four papers on the role of common and rare species and traits for benthic community functioning. The findings show that common and rare species may not always express the same trait categories in relation to each other. Rare species in general did not express unique functional properties. In order to advance the understanding of the approach, I also assessed some issues concerning the limitations of the concept. This was conducted by evaluating the link between trait category and taxonomic richness using especially univariate measures. My results also show the need to collaborate nationally and internationally on safeguarding the utility of taxonomic and trait data. The findings also highlight the importance of including functional trait information into current efforts in marine spatial planning and biomonitoring.

Model-based testing of software systems : functionality and performance

Software is a key component in many of our devices and products that we use every day. Most customers demand not only that their devices should function as expected but also that the software should be of high quality, reliable, fault tolerant, efficient, etc. In short, it is not enough that a calculator gives the correct result of a calculation, we want the result instantly, in the right form, with minimal use of battery, etc. One of the key aspects for succeeding in today's industry is delivering high quality. In most software development projects, high-quality software is achieved by rigorous testing and good quality assurance practices. However, today, customers are asking for these high quality software products at an ever-increasing pace. This leaves the companies with less time for development. Software testing is an expensive activity, because it requires much manual work. Testing, debugging, and verification are estimated to consume 50 to 75 per cent of the total development cost of complex software projects. Further, the most expensive software defects are those which have to be fixed after the product is released. One of the main challenges in software development is reducing the associated cost and time of software testing without sacrificing the quality of the developed software. It is often not enough to only demonstrate that a piece of software is functioning correctly. Usually, many other aspects of the software, such as performance, security, scalability, usability, etc., need also to be verified. Testing these aspects of the software is traditionally referred to as nonfunctional testing. One of the major challenges with non-functional testing is that it is usually carried out at the end of the software development process when most of the functionality is implemented. This is due to the fact that non-functional aspects, such as performance or security, apply to the software as a whole. In this thesis, we study the use of model-based testing. We present approaches to automatically generate tests from behavioral models for solving some of these challenges. We show that model-based testing is not only applicable to functional testing but also to non-functional testing. In its simplest form, performance testing is performed by executing multiple test sequences at once while observing the software in terms of responsiveness and stability, rather than the output. The main contribution of the thesis is a coherent model-based testing approach for testing functional and performance related issues in software systems. We show how we go from system models, expressed in the Unified Modeling Language, to test cases and back to models again. The system requirements are traced throughout the entire testing process. Requirements traceability facilitates finding faults in the design and implementation of the software. In the research field of model-based testing, many new proposed approaches suffer from poor or the lack of tool support. Therefore, the second contribution of this thesis is proper tool support for the proposed approach that is integrated with leading industry tools. We o er independent tools, tools that are integrated with other industry leading tools, and complete tool-chains when necessary. Many model-based testing approaches proposed by the research community suffer from poor empirical validation in an industrial context. In order to demonstrate the applicability of our proposed approach, we apply our research to several systems, including industrial ones.