Open Access

One of the major challenges for humanity is related to biodiversity conservation. This can be reflected by the fact that there exist institutionally induced instruments that most nations have adopted for this purpose such as "pay to conserve" programs, in which a compensation is provided to landowners for engaging in conservation and/or biodiversity-friendly activities on their lands. These payments are proportional to the conserved areas. Another associated strategy would be the agglomeration bonus, which involves extra payment on top of the initial base for the conservation of areas next to those that have already been conserved, so as to promote continuity and agglomeration for improving biodiversity. Over the past two decades, these conservation strategies have received significative attention from researchers, which have used ecological and economic models to analyze the performance of such strategies. On this background, this master's thesis particularly focuses on the evaluation of communication among landowners in coordination of their future decisions, in the context of the afore mentioned conservation strategies. More precisely, this is explored as a feature within one of the previously proposed models to evaluate its potential correlation and/or causality with the performance of the conservation scheme. Simulations were run using an agent-based model, whereby a large dataset was generated. Statistical and interpretable machine learning methods were then applied on the dataset to investigate correlations and possible causations between state variables of the model and chosen predictors including the feature on communication. Relevant results have been obtained so far to indicate that indeed, communication does affect most of the state variables of the conservation model. Although the strength may not be equal to other predictors, communication features structured as the number of chat rounds among landowners were shown to be statistically significant in most cases. It was also found that having at least three chat rounds among landowners could give results similar to those obtained when the model reaches a stable state in terms of time, which it found to be with eleven or more timesteps. Other significative observations viewed in respect to the predictors were that the slope value of the curve utilized within the sigmoid function for the model comes out to exert a considerable influence and needs further research to redefine its real values.

Satzung zur Sicherung guter wissenschaftlicher Praxis und zum Umgang mit Verdachtsfällen wissenschaftlichen Fehlverhaltens an der Brandenburgischen Technischen Universität Cottbus–Senftenberg vom 20. Juli 2023

Neurodegenerative diseases (NDs) are characterized by abnormalities within neurons of the brain or spinal cord that gradually lose function, eventually leading to cell death. Upon examination of affected tissue, pathological changes reveal a loss of synapses, misfolded proteins, and activation of immune cells all indicative of disease progression before severe clinical symptoms become apparent. Early detection of NDs is crucial for potentially administering targeted medications that may delay disease advancement. Given their complex pathophysiological features and diverse clinical symptoms, there is a pressing need for sensitive and effective diagnostic methods for NDs. Biomarkers such as microRNAs (miRNAs) have been identified as potential tools for detecting these diseases. We explore the pivotal role of miRNAs in the context of NDs, focusing on Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, Huntington’s disease, and Amyotrophic Lateral Sclerosis. The review delves into the intricate relationship between aging and NDs, highlighting structural and functional alterations in the aging brain and their implications for disease development. It elucidates how miRNAs and RNA-binding proteins are implicated in the pathogenesis of NDs and underscores the importance of investigating their expression and function in aging. Significantly, miRNAs exert substantial influence on post-translational modifications (PTMs), impacting not just the nervous system but a wide array of tissues and cell types as well. Specific miRNAs have been found to target proteins involved in ubiquitination or deubiquitination processes, which play a significant role in regulating protein function and stability. We discuss the link between miRNA, PTM, and NDs. Additionally, the review discusses the significance of miRNAs as biomarkers for early disease detection, offering insights into diagnostic strategies.

The holistic characterization of different microbiomes in anaerobic digestion (AD) systems can contribute to a better understanding of these systems and provide starting points for bioengineering. The present study investigates the microbiome of 80 European full-scale AD systems. Operational, chemical and taxonomic data were thoroughly collected, analysed and correlated to identify the main drivers of AD processes. The present study describes chemical and operational parameters for a broad spectrum of different AD systems. With this data, Spearman correlation and differential abundance analyses were applied to narrow down the role of the individual microorganisms detected. The authors succeeded in further limiting the number of microorganisms in the core microbiome for a broad range of AD systems. Based on 16S rRNA gene amplicon sequencing, MBA03, Proteiniphilum, a member of the family Dethiobacteraceae, the genus Caldicoprobacter and the methanogen Methanosarcina were the most prevalent and abundant organisms identified in all digesters analysed. High ratios for Methanoculleus are often described for agricultural co-digesters. Therefore, it is remarkable that Methanosarcina was surprisingly high in several digesters reaching ratios up to 47.2%. The various statistical analyses revealed that the microorganisms grouped according to different patterns. A purely taxonomic correlation enabled a distinction between an acetoclastic cluster and a hydrogenotrophic one. However, in the multivariate analysis with chemical parameters, the mainclusters corresponded to hydrolytic and acidogenic microorganisms, with SAOB bacteria being particularly important in the second group. Including operational parameters resulted in digester-type specific grouping of microbes. Those with separate acidification stood out among the many reactor types due to their unexpected behaviour. Despite maximizing the organic loading rate in the hydrolytic pretreatments, these stages turned into extremely robust methane production units. From 80 different AD systems, one of the most holistic data sets is provided. A very distinct formation of microbial clusters was discovered, depending on whether taxonomic, chemical or operational parameters were combined. The microorganisms in the individual clusters were strongly dependent on the respective reference parameters.

Disturbances can be any discrete events that significantly affect ecosystem components, they can be natural events such as wildfires and floods, or anthropogenic events like farming, mining, and deforestation. Disturbances are the most important source of temporal and spatial heterogeneity and shape the composition and dynamics of natural communities. However, after many years of research, it is still difficult to predict the response patterns of natural communities to disturbances accurately. This dissertation aimed to investigate the taxonomic, functional, and trophic response of beetle communities to three types of disturbances in field studies. Chapter 3 is based on an experiment in an unmanaged heathland area that was affected by a severe wildfire (natural disturbance). Emergence tents and wild boar carcasses were used to analyse the impact of wildfires on re-colonization and emergence of carrion-associated scavenging beetle species from local soils. Chapter 4 focused on effects of fallows at the local scale and proportions of permanent agricultural grasslands at the landscape scale on the taxonomic and functional diversity of the emerging ground beetles in intensively managed cereal fields (anthropogenic disturbance). Chapter 5 addressed the trophic links between the prey (dipterans emerging from lakes or terrestrial collembolans) and predators (ground beetles) at a post-mining lakeshore (anthropogenic disturbance) and compared the patterns of their isotopic niches (δ13C and δ15N) with data from a natural lakeshore. Overall, species composition, trait diversity and trophic interactions were more sensitive to indicate the disturbance conditions than traditional diversity indices, independent on the nature of disturbance (natural or anthropogenic). When the intensity and frequency of disturbance is moderate, the habitat complexity can be maintained, and the taxonomic and functional diversity of beetle communities could even be promoted by the disturbance, rare species with specialized preferences could be conserved. Disturbances, however, do not just affect consumers at higher trophic levels (e.g. predators or scavengers), but may have even greater impact on communities at basal trophic levels (e.g. aquatic dipterans, Collembola, herbivorous beetles) and could further affect the feeding preferences of predatory beetles that utilize such organisms as prey. The findings not only provided unique data and novel insights to effects of land-use and management on the conservation of beetle communities in disturbed landscapes, but also highlighted the need to better understand the impacts of disturbances on integrated aspects of the ecological communities.