Wolfgang Trutschnig

In view of the increasing digitalization of industry, data science and data visualization are assuming an increasingly pivotal role in numerous industry sectors, facilitating enhanced monitoring and analysis of production processes. This development is primarily driven by growing demands for product quality and sustainability. In a multitude of industrial contexts, large volumes of high-resolution sensor data are continuously recorded throughout production. To make this huge amount of data usable for technologists, an interactive visual analytics tool for the analysis of production data has been developed. The tool enables users to explore complex process data, identify relevant patterns, and derive data-driven insights for quality optimization. This, in turn, leads to reduced scrap rates, as well as improved plant utilization and delivery performance. The present paper demonstrates the effectiveness of the proposed approach using a selected industrial use case and highlights key insights gained from its application in practice.

Summary: The insurance hypothesis of biodiversity assumes that biodiversity increases ecosystem stability when functionally redundant species exhibit distinct responses to environmental changes, allowing some species to compensate for the loss of others. However, empirical evidence remains scarce. Using a novel approach to quantify the responses of 96 plant species to land use, we tested the hypothesis combining field data with a common garden experiment. By subjecting transplanted grassland plant communities to different land‐use intensities, we quantified response diversity (defined as the variability of responses among species to the same environmental factor), species composition, and functionality from spectral data before and after experimental changes. Our results show that land‐use intensification reduced response diversity of plant communities in the field and the common garden. Moreover, our results indicate that response diversity increases functional stability but decreases stability in terms of species composition (temporal β‐diversity), that is, response‐diverse communities tended to lose species with fewer replacements while response‐depleted communities mainly experienced species turnover. Our work highlights that response diversity underlies multiple dimensions of ecosystem stability as it stabilizes functionality but destabilizes species composition. We further discuss future research directions to adapt the concept of response diversity under global change scenarios.

We tackle the natural question of whether it is possible to estimate conditional distributions via Sklar's theorem by separately estimating the conditional distributions of the underlying copula and the marginals. Working with so-called empirical checkerboard/Bernstein approximations with suitably chosen resolution/degree, we first show that uniform weak convergence to the true underlying copula can be established under very mild regularity assumptions. Building upon these results and plugging in the univariate empirical marginal distribution functions we then provide an affirmative answer to the afore-mentioned question and prove strong consistency of the resulting estimators for the conditional distributions. Moreover, we show that aggregating our estimators allows to construct consistent nonparametric estimators for the mean, the quantile, and the expectile regression function, and beyond. Some simulations illustrating the performance of the estimators and a real data example complement the established theoretical results.

Recently established, directed dependence measures for pairs (X,Y) of random variables build upon the natural idea of comparing the conditional distributions of Y given X=x with the unconditional distribution of Y. They assign pairs (X,Y) values in [0,1], where the value is 0 if and only if X,Y are independent, and it is 1 exclusively for Y being a measurable function of X. Here we show that comparing randomly drawn conditional distributions with each other instead or, equivalently, analyzing how sensitive the conditional distribution of Y given X=x is on x, opens the door to constructing novel families of dependence measures Λφ induced by general convex functions φ:R→R, containing, e.g., Chatterjee’s coefficient of correlation as special case. After establishing additional useful properties of Λφ we focus on continuous (X,Y), translate Λφ to the copula setting, consider the Lp-version and establish an estimator which is strongly consistent in full generality. A real data example and a simulation study illustrate the chosen approach and the performance of the estimator. Complementing the afore-mentioned results, we show how a slight modification of the sensitivity idea underlying Λφ can be used to define new measures of explainability generalizing the fraction of explained variance.

Being uniquely adapted to extreme environmental conditions, rock‐dwelling lecideoid lichens are a diverse and major component of terrestrial vegetation in Antarctica. Climate change is reshaping Antarctic ecosystems, forcing cold‐adapted species to migrate to maintain their climatic niche. The study surveyed the circum‐Antarctic lecideoid lichen diversity and modeled the impacts of two climate change scenarios on their distributional range shifts across Antarctica. Fungal and algal symbionts of lecideoid lichen species from a circum‐Antarctic sampling were classified using classical barcoding methods. The climatic niches of nine common fungal (mycobiont) species and four algal (photobiont) OTUs were predicted, and spatial range shifts were projected across four Antarctic bioregions under three Shared Socioeconomic Pathways: (1) SSP1‐2.6: sustainable development, (2) SSP3‐7.0: medium–high reference scenario with high methane emissions and (3) SSP5‐8.5: continued dependence on fossil fuels. DNA‐barcoding revealed altogether 34 species of lecideoid lichens associated with 9 photobiont OTUs for the Antarctic continent. In addition to the already known lichen species in Antarctica, three newly detected species of the genus Lecidella could be identified. The calculated climate change scenarios across bioregions predict overall range expansion for mycobiont species and photobiont OTUs. While a reduction in suitable habitat size is expected in maritime Antarctica, species distributions are predicted to expand in continental regions, primarily due to inland shifts. These inland areas may serve as emerging climatic refugia for certain mycobiont species. Overall, these results suggest that, under future warming, lecideoid lichens undergo an overall range expansion, particularly in previously uncolonized inland areas in continental Antarctica.