@phdthesis{Malchow2023,
  author    = {Malchow, Anne-Kathleen},
  title     = {Developing an integrated platform for predicting niche and range dynamics},
  doi       = {10.25932/publishup-60273},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-602737},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiv, 169},
  year      = {2023},
  abstract  = {Species are adapted to the environment they live in. Today, most environments are subjected to rapid global changes induced by human activity, most prominently land cover and climate changes. Such transformations can cause adjustments or disruptions in various eco-evolutionary processes. The repercussions of this can appear at the population level as shifted ranges and altered abundance patterns. This is where global change effects on species are usually detected first. To understand how eco-evolutionary processes act and interact to generate patterns of range and abundance and how these processes themselves are influenced by environmental conditions, spatially-explicit models provide effective tools. They estimate a species' niche as the set of environmental conditions in which it can persist. However, the currently most commonly used models rely on static correlative associations that are established between a set of spatial predictors and observed species distributions. For this, they assume stationary conditions and are therefore unsuitable in contexts of global change. Better equipped are process-based models that explicitly implement algorithmic representations of eco-evolutionary mechanisms and evaluate their joint dynamics. These models have long been regarded as difficult to parameterise, but an increased data availability and improved methods for data integration lessen this challenge. Hence, the goal of this thesis is to further develop process-based models, integrate them into a complete modelling workflow, and provide the tools and guidance for their successful application. With my thesis, I presented an integrated platform for spatially-explicit eco-evolutionary modelling and provided a workflow for their inverse calibration to observational data. In the first chapter, I introduced RangeShiftR, a software tool that implements an individual-based modelling platform for the statistical programming language R. Its open-source licensing, extensive help pages and available tutorials make it accessible to a wide audience. In the second chapter, I demonstrated a comprehensive workflow for the specification, calibration and validation of RangeShiftR by the example of the red kite in Switzerland. The integration of heterogeneous data sources, such as literature and monitoring data, allowed to successfully calibrate the model. It was then used to make validated, spatio-temporal predictions of future red kite abundance. The presented workflow can be adopted to any study species if data is available. In the third chapter, I extended RangeShiftR to directly link demographic processes to climatic predictors. This allowed me to explore the climate-change responses of eight Swiss breeding birds in more detail. Specifically, the model could identify the most influential climatic predictors, delineate areas of projected demographic suitability, and attribute current population trends to contemporary climate change. My work shows that the application of complex, process-based models in conservation-relevant contexts is feasible, utilising available tools and data. Such models can be successfully calibrated and outperform other currently used modelling approaches in terms of predictive accuracy. Their projections can be used to predict future abundances or to assess alternative conservation scenarios. They further improve our mechanistic understanding of niche and range dynamics under climate change. However, only fully mechanistic models, that include all relevant processes, allow to precisely disentangle the effects of single processes on observed abundances. In this respect, the RangeShiftR model still has potential for further extensions that implement missing influential processes, such as species interactions. Dynamic, process-based models are needed to adequately model a dynamic reality. My work contributes towards the advancement, integration and dissemination of such models. This will facilitate numeric, model-based approaches for species assessments, generate ecological insights and strengthen the reliability of predictions on large spatial scales under changing conditions.},
  language  = {en}
}
@phdthesis{Kraus2021,
  author    = {Kraus, Sara Milena},
  title     = {A Systems Medicine approach for heart valve diseases},
  doi       = {10.25932/publishup-52226},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-522266},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xi, 186},
  year      = {2021},
  abstract  = {In Systems Medicine, in addition to high-throughput molecular data (*omics), the wealth of clinical characterization plays a major role in the overall understanding of a disease. Unique problems and challenges arise from the heterogeneity of data and require new solutions to software and analysis methods. The SMART and EurValve studies establish a Systems Medicine approach to valvular heart disease -- the primary cause of subsequent heart failure. With the aim to ascertain a holistic understanding, different *omics as well as the clinical picture of patients with aortic stenosis (AS) and mitral regurgitation (MR) are collected. Our task within the SMART consortium was to develop an IT platform for Systems Medicine as a basis for data storage, processing, and analysis as a prerequisite for collaborative research. Based on this platform, this thesis deals on the one hand with the transfer of the used Systems Biology methods to their use in the Systems Medicine context and on the other hand with the clinical and biomolecular differences of the two heart valve diseases. To advance differential expression/abundance (DE/DA) analysis software for use in Systems Medicine, we state 21 general software requirements and features of automated DE/DA software, including a novel concept for the simple formulation of experimental designs that can represent complex hypotheses, such as comparison of multiple experimental groups, and demonstrate our handling of the wealth of clinical data in two research applications DEAME and Eatomics. In user interviews, we show that novice users are empowered to formulate and test their multiple DE hypotheses based on clinical phenotype. Furthermore, we describe insights into users' general impression and expectation of the software's performance and show their intention to continue using the software for their work in the future. Both research applications cover most of the features of existing tools or even extend them, especially with respect to complex experimental designs. Eatomics is freely available to the research community as a user-friendly R Shiny application. Eatomics continued to help drive the collaborative analysis and interpretation of the proteomic profile of 75 human left myocardial tissue samples from the SMART and EurValve studies. Here, we investigate molecular changes within the two most common types of valvular heart disease: aortic valve stenosis (AS) and mitral valve regurgitation (MR). Through DE/DA analyses, we explore shared and disease-specific protein alterations, particularly signatures that could only be found in the sex-stratified analysis. In addition, we relate changes in the myocardial proteome to parameters from clinical imaging. We find comparable cardiac hypertrophy but differences in ventricular size, the extent of fibrosis, and cardiac function. We find that AS and MR show many shared remodeling effects, the most prominent of which is an increase in the extracellular matrix and a decrease in metabolism. Both effects are stronger in AS. In muscle and cytoskeletal adaptations, we see a greater increase in mechanotransduction in AS and an increase in cortical cytoskeleton in MR. The decrease in proteostasis proteins is mainly attributable to the signature of female patients with AS. We also find relevant therapeutic targets. In addition to the new findings, our work confirms several concepts from animal and heart failure studies by providing the largest collection of human tissue from in vivo collected biopsies to date. Our dataset contributing a resource for isoform-specific protein expression in two of the most common valvular heart diseases. Apart from the general proteomic landscape, we demonstrate the added value of the dataset by showing proteomic and transcriptomic evidence for increased expression of the SARS-CoV-2- receptor at pressure load but not at volume load in the left ventricle and also provide the basis of a newly developed metabolic model of the heart.},
  language  = {en}
}
@phdthesis{Kindermann2024,
  author    = {Kindermann, Liana},
  title     = {Trees, shrubs, and land-use change},
  doi       = {10.25932/publishup-64894},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-648943},
  school      = {Universit{\"a}t Potsdam},
  pages     = {X, 186},
  year      = {2024},
  abstract  = {The global drylands cover nearly half of the terrestrial surface and are home to more than two billion people. In many drylands, ongoing land-use change transforms near-natural savanna vegetation to agricultural land to increase food production. In Southern Africa, these heterogenous savanna ecosystems are also recognized as habitats of many protected animal species, such as elephant, lion and large herds of diverse herbivores, which are of great value for the tourism industry. Here, subsistence farmers and livestock herder communities often live in close proximity to nature conservation areas. Although these land-use transformations are different regarding the future they aspire to, both processes, nature conservation with large herbivores and agricultural intensification, have in common, that they change the vegetation structure of savanna ecosystems, usually leading to destruction of trees, shrubs and the woody biomass they consist of. Such changes in woody vegetation cover and biomass are often regarded as forms of land degradation and forest loss. Global forest conservation approaches and international programs aim to stop degradation processes, also to conserve the carbon bound within wood from volatilization into earth's atmosphere. In search for mitigation options against global climate change savannas are increasingly discussed as potential carbon sinks. Savannas, however, are not forests, in that they are naturally shaped by and adapted to disturbances, such as wildfires and herbivory. Unlike in forests, disturbances are necessary for stable, functioning savanna ecosystems and prevent these ecosystems from forming closed forest stands. Their consequently lower levels of carbon storage in woody vegetation have long been the reason for savannas to be overlooked as a potential carbon sink but recently the question was raised if carbon sequestration programs (such as REDD+) could also be applied to savanna ecosystems. However, heterogenous vegetation structure and chronic disturbances hamper the quantification of carbon stocks in savannas, and current procedures of carbon storage estimation entail high uncertainties due to methodological obstacles. It is therefore challenging to assess how future land-use changes such as agricultural intensification or increasing wildlife densities will impact the carbon storage balance of African drylands. In this thesis, I address the research gap of accurately quantifying carbon storage in vegetation and soils of disturbance-prone savanna ecosystems. I further analyse relevant drivers for both ecosystem compartments and their implications for future carbon storage under land-use change. Moreover, I show that in savannas different carbon storage pools vary in their persistence to disturbance, causing carbon bound in shrub vegetation to be most likely to experience severe losses under land-use change while soil organic carbon stored in subsoils is least likely to be impacted by land-use change in the future. I start with summarizing conventional approaches to carbon storage assessment and where and for which reasons they fail to accurately estimated savanna ecosystem carbon storage. Furthermore, I outline which future-making processes drive land-use change in Southern Africa along two pathways of land-use transformation and how these are likely to influence carbon storage. In the following chapters, I propose a new method of carbon storage estimation which is adapted to the specific conditions of disturbance-prone ecosystems and demonstrate the advantages of this approach in relation to existing forestry methods. Specifically, I highlight sources for previous over- and underestimation of savanna carbon stocks which the proposed methodology resolves. In the following chapters, I apply the new method to analyse impacts of land-use change on carbon storage in woody vegetation in conjunction with the soil compartment. With this interdisciplinary approach, I can demonstrate that indeed both, agricultural intensification and nature conservation with large herbivores, reduce woody carbon storage above- and belowground, but partly sequesters this carbon into the soil organic carbon stock. I then quantify whole-ecosystem carbon storage in different ecosystem compartments (above- and belowground woody carbon in shrubs and trees, respectively, as well as topsoil and subsoil organic carbon) of two savanna vegetation types (scrub savanna and savanna woodland). Moreover, in a space-for-time substitution I analyse how land-use changes impact carbon storage in each compartment and in the whole ecosystem. Carbon storage compartments are found to differ in their persistence to land-use change with carbon bound in shrub biomass being least persistent to future changes and subsoil organic carbon being most stable under changing land-use. I then explore which individual land-use change effects act as drivers of carbon storage through Generalized Additive Models (GAMs) and uncover non-linear effects, especially of elephant browsing, with implications for future carbon storage. In the last chapter, I discuss my findings in the larger context of this thesis and discuss relevant implications for land-use change and future-making decisions in rural Africa.},
  language  = {en}
}