Open Access

Urban areas are prone to climate change impacts. Simultaneously the world’s population increasingly resides in cities. In this light, there is a growing need to equip urban decision makers with evidence-based climate information tailored to their specific context, to adequately adapt to and prepare for future climate change. To construct climate information high-resolution regional climate models and their projections are pivotal, to provide a better understanding of the unique urban climate and its evolution under climate change. There is a need to move beyond commonly investigated variables, such as temperature and precipitation, to cover a wider breath of possible climate impacts. In this light, the research presented in this thesis is centered around enhancing the understanding about regional-to-local climate change in Berlin and its surroundings, with a focus on humidity. More specifically, following a regional climate modelling and data analysis approach, this research aims to understand the potential of regional climate models, and the possible added value of convection-permitting simulations, to support the development of high-quality climate information for urban regions, to support knowledge-based decision-making. The first part of the thesis investigates what can already be understood with available regional climate model simulations about future climate change in Berlin and its surroundings, particularly with respect to humidity and related variables. Ten EURO-CORDEX model combinations are analyzed, for the RCP8.5 emission scenario during the time period 1970 ̶ 2100, for the Berlin region. The results are the first to show an urban-rural humidity contrast under a changing climate, simulated by the EURO-CORDEX ensemble, of around 6 % relative humidity, and a robust enlarging urban drying effect, of approximately 2 ̶ 4 % relative humidity, in Berlin compared to its surroundings throughout the 21st century. The second part explores how crossing spatial scales from 12.5 km to 3 km model grid size affects unprecedented humidity extremes and related variables under future climate conditions for Berlin and its surroundings. Based on the unique HAPPI regional climate model dataset, two unprecedented humidity extremes are identified happening under 1.5 °C and 2 °C global mean warming, respectively SH>0.02 kg/kg and RH<30 %. Employing a double-nesting approach, specifically designed for this study, the two humidity extremes are downscaled to the 12.5 km grid resolution with the regional climate model REMO, and thereafter to the 3 km with the convection-permitting model version of REMO (REMO NH). The findings indicate that the convection-permitting scale mitigates the SH>0.02 kg/kg moist extreme and intensifies the RH<30 % dry extreme. The multi-variate process analysis shows that the more profound urban drying effect on the convection-permitting resolution is mainly due to better resolving the physical processes related to the land surface scheme and land-atmosphere interactions on the 3 km compared to the 12.5 km grid resolution. The results demonstrate the added value of the convection-permitting resolution to simulate future humidity extremes in the urban-rural context. The third part of the research investigates the added value of convection-permitting models to simulate humidity related meteorological conditions driving specific climate change impacts, for the Berlin region. Three novel humidity related impact cases are defined for this research: influenza spread and survival; ragweed pollen dispersion; and in-door mold growth. Simulations by the regional climate model REMO are analyzed for the near future (2041 ̶ 2050) under emission scenario RCP8.5, on the 12.5 km and 3 km grid resolution. The findings show that the change signal reverses on the convection-permitting resolution for the impact cases pollen, and mold (positive and negative). For influenza, the convection-permitting resolution intensifies the decrease of influenza days under climate change. Longer periods of consecutive influenza and mold days are projected under near-term climate change. The results show the potential of convection-permitting simulations to generate improved information about climate change impacts in urban regions to support decision makers. Generally, all results show an urban drying effect in Berlin compared to its surroundings for relative and specific humidity under climate change, respectively for the urban-rural contrast throughout the 21st century, for the downscaled future extreme conditions, and for the three humidity related impact cases. Added value for the convection-permitting resolution is found to simulate humidity extremes and the meteorological conditions driving the three impacts cases. The research makes novel contributions that advance science, through demonstrating the potential of regional climate models, and especially the added value of convection-permitting models, to understand urban rural humidity contrasts under climate change, supporting the development of knowledge-based climate information for urban regions.

We are in a phase of an alarming biodiversity loss, by scientist already referred to as Earth’s sixth mass extinction. According to estimations, the current extinction rates are 100 to 1000 times higher than those predicted from fossil records. To counteract species loss and preserve the remaining biodiversity, with its important ecosystem functioning and services essential to human well-being, there is an urgent need to develop promising and long-term conservation strategies. In order to achieve these goals, extensive research to gain a better understanding of the general mechanisms underlying community diversity is of greatest importance. Especially, the identification of intrinsic ecological and distributional species traits is receiving increased attention in ecology and conservation biology research. Depending on the expression of their traits, species perform particular ecosystem functions and respond in a specific manner to environmental conditions. The identification of the effect of certain traits on community compositions can therefore significantly improve our understanding of species extinction processes and help to develop valuable and appropriate recommendations for conservation management. As trait-based analyses are applicable to different geographical, temporal and taxonomical scales, they may even allow for a broader generalization if similar results are found on different scales, i.e. for local species pools, the complete species pools of different habitat types or the entire species pool across several habitat types including different climatic regions. Although insects make up the largest part of animal diversity and provide essential ecosystem services in form of e.g. pollination, pest control, and decomposition, the majority of studies on extinctions have mainly focused on vertebrates. Among invertebrates either charismatic taxa or those targeted by conservation laws have been investigated until now (e.g. butterflies or saproxylic beetles). Being highly species-rich and trait-diverse, ground beetles (Coleoptera: Carabidae) should be even more suitable for conducting trait-based analyses. Thus, using ground beetles as a model taxon, four case studies focusing on the analyses of traits form the basis of this doctoral thesis. The work of this thesis was conducted with the aim of gaining general insights on the influence of species traits on ground beetle community compositions, such as habitat occupancy and species vulnerability to extinction, for instance. An important aspect when investigating species traits is the consideration of confounding factors which could influence the results, such as dependent relations between the different traits. Compiling a large dataset of 566 Central European species, I identified that dependent relations between the six tested traits of ground beetles (distribution range size, habitat specialization, body size, hind-wing morphology, breeding season and trophic level) are highly common. Across all identified dependent trait relations, the relation between body size and hind wing morphology or range size and hind wing morphology showed the strongest significant dependencies. Since the consideration of trait relations is necessary to provide reliable interpretations, all analyses of this thesis tested several traits simultaneously and considered possible trait interactions. Studies on local communities found specific traits characterizing the local species pools of certain habitat types. Here, the species pools of seven different habitat types (coastal, forest, mountain, open, riparian, wetland and special habitat) were used to determine habitat-specific trait filters. The identified traits, characteristic for certain habitat types, were in most cases in accordance with the previous findings on local communities. Across Germany, the species of frequently disturbed habitat types, namely coastal, riparian and wetland habitats were characterized by small body size, high amount of macroptery, intermediate to high habitat specialization, spring breeding, and predatory feeding behavior. The species of stable habitat types (forest, mountain, and open habitats), however, were found to be generally larger in body size and more frequently breeding in autumn, further displaying greater variations in the other traits. The gained knowledge on the habitat-specific filtering of traits improve our understanding of the organization and assembly of communities, and can thereby help to detect alterations in the habitat-specific species pool due to natural or human-induced environmental changes. Furthermore, traits can provide evidence on species occurrences and vulnerability to extinction. Three case studies of this thesis aimed to gain new insights on this topic, through the investigations on the following research questions; I. Which traits drive species extinction risks of Central European ground beetle species, II. How traits influence the species occurrences of 28 forest species within a large area in Central Europe, and III. Whether certain traits are related to long-term population trends of the species pool from an ancient forest in northern Germany. The results indicated, that depending on the habitat type and tested species pool, different traits prove to be good predictors for the vulnerability of species. Nevertheless, across different geographical and taxonomical scales, especially species with small range sizes and high habitat specialization faced a greater risk of extinction. Therefore, the two traits distributional range size and habitat specialization emerge as reliable predictors of ground beetles vulnerability to extinction. Interestingly, body size did not display a consistent response; while increasing body size led to higher extinction risk in riparian, wetland and open habitats and large macropterous species showed higher extinction risks across the entire species pool, smaller species showed long-term population declines in an ancient forest. To summarize, this thesis presents a comprehensive picture of ground beetle species traits, providing valuable insights and a better understanding of the mechanisms driving changes in ground beetle diversity. On the basis of the results presented in this work, the efficiency of biodiversity protection can be increased by developing appropriate management and recovery plans, especially targeting species of threatened habitat types or ‘functional groups’ of species, exhibiting trait values strongly associated with a greater vulnerability to extinction.

Transformative learning is increasingly set to become an essential component in sustainability transformation. This type of learning attracts considerable interest in studying and impulsing a paradigm change to transform our world into a more sustainable one, yet its underlying learning mechanisms have remained overlooked. Although there is an apparent relationship between transformative learning and sustainability transformation, little has been done to systematically explore the contribution to sustainability transformation. This learning theory developed decades ago independently of sustainability discourses; however, it provides an analytical framework for understanding the learning processes, outcomes and conditions in individual and social learning towards sustainability transformation. Against this background, the following research question arises: To which extent can transformative learning lead to sustainability transformation? This doctoral work aims to explore transformative learning processes, outcomes, and conditions occurring and advancing towards sustainability transformation of the textile-fashion industry in Mexico. Taking an exploratory approach, the methods employed were literature reviews to untangle concepts and to construct theoretical pillars to support the empirical research design and data analysis. For data collection, snowball-sampling techniques were used to explore the practice field of the textile-fashion industry in Mexico. Qualitative interviews were employed to gather data about the learning experiences of actors. Qualitative and quantitative methods were required to perform the respective data analysis, the qualitative codification of interviewees’ responses through MAXQDA being the most remarkable one. Analysis of social media content was also utilised to understand the communication and business practices of projects involved in the transformation of the textile-fashion sector. As a result, this work comprises three articles, one a systematic literature review and two empirical research articles, investigating the transformative learning processes of entrepreneurs in the development of sustainability niches. As for the findings of this doctoral work, the use of transformative learning in sustainability transformation requires a careful study of the theory and its conceptual elements. Regarding the case study, transformative learning is inherent in forming and developing sustainability niches as entrepreneurs venture into them: It is individual prior learning, expectations and actions that initiate the path of sustainability transformation while disorienting dilemmas, critical reflection, and discourse accelerate them. Through these stages, it is when individual learning turns into social learning. On the other hand, based on the multi-level perspective, the interplay between the niche, regime and landscape levels generates a space for sustainability transformation and transformative learning. This work contributes to deciphering the black box of learning in sustainability transformations. The principal endeavour was to build the theoretical bridges between this emerging area of inquiry and transformative learning theory, as a significant part of this theoretical construction required drawing upon other research fields such as sustainability transitions and sustainability entrepreneurship. The crosscutting feature of learning in those fields enabled the development of an awareness of boundary objects between those fields (e.g., expectations). Furthermore, this study is pioneering in exploring sustainability transformation processes of the textile-fashion industry in Latin American contexts. The findings of this work can also be extrapolated to other sectors in which entrepreneurs participate, such as local food production, sustainable mobility, among others

Water is vital for humankind and ecosystems alike. However, population growth, agricultural inten-sification, urbanization, and climate change embody potential hazards and pressures for water re-sources without existing long-term solutions. For two decades now, policy and governance literature has increasingly emphasised the role of learning in finding solutions to environmental policy prob-lems and effectively steering governance practices. Participation of non-state actors in decision mak-ing is widely considered to deliver learning products that support effective outcomes for environ-mental problems. Besides, the institutionalisation of participation through legislation opens up the necessity for (administrative) organizers to learn about participation as a governance mode in order to steer its effective working. Apart from participation, management approaches specifically aiming at driving learning, such as adaptive management (AM), are increasingly endorsed in water govern-ance. Despite the current prominence of learning in the environmental governance literature, evi-dence is lacking on which learning approaches function effectively regarding outcomes, whether participation aids learning, and how learning about successful governance arrangements is most effectively promoted. This doctoral dissertation aims to contribute to clarification of the potential of learning for water governance. The goal is to trace and understand the environmental impacts of learning through par-ticipation (research aim 1) and adaptive management (research aim 2), and the effect of learning on participation as a governance mode (research aim 3). For this goal, I engage in a predominantly qualitative research design following the case study method. For every specific research aim cases are selected and analysed qualitatively according to conceptual categories and mechanisms which are defined beforehand. Quantitative studies are used to corroborate the results for research aim 1 and 2 in a mixed-method approach to enhance the valid-ity of results. The empirical research context is European water governance, the implementation of the EU Water Framework and EU Floods Directive (WFD, FD) specifically. Eight cases of participa-tory decision-making across three European countries and five cases of AM in Northern Germany for WFD implementation are examined to identify whether learning in these processes enhanced envi-ronmental outcomes. To detect whether governance learning by public officials occurred, the design of participatory processes for FD implementation in ten German federal states is assessed. The findings of research aim 1, understanding learning through participation and its effects on water governance, reveal that participatory planning led to learning through improved understandings at an individual and group level. Learning did, however, hardly shape effective outcomes. In the AM cases (research aim 2) managers and participants of implementing networks improved their knowledge as well as capacities, and spread the results. Nonetheless, environmental improvement was not necessarily linked to ecological learning. Regarding learning about participation as a govern-ance mode (research aim 3) all interviewed public officials in German federal states reported some degree of governance learning, which emerged not systematically but primarily drawing on own experiences and intuition. These findings are condensed into three overarching lessons for learning in water governance: (1) Interactive communication seems to form the overall frame for participant and group learning. Framing of learning experiences turned out to play an important and potentially distorting role, for which professional facilitation and structured knowledge aggregation methods might be an im-portant counterbalance. (2) Learning did not automatically enhance environmental outcomes. It may thus not be an explanatory variable for policy outcomes, but a conditioning or intervening vari-able related to collective action, motivation for participation, and situating the issue at hand at wider societal levels. (3) The concepts of puzzling and powering might help understand learning as a source for effectiveness in the long-term when complemented with interest-based debates for creat-ing sufficient political agency of policy issues. Learning seen as puzzling processes might instruct acceptance and legitimization for new powering efforts. The perpetuation of learning in systematic ways and structures appears to characterize an alternative to this reflexive and strategic interplay, for which the water-related EU directives provide the basis. These insights are of practical and policy relevance, particularly for policy makers and practitioners in the pursuit of learning. They may further contribute to the academic understanding of learning in water governance and its potential contribution to transforming and adapting water governance re-gimes, as envisioned in the European water-related directives.

Siehe Inhaltsangabe der Diplomarbeit!