Plant transpiration is a key element in the hydrological cycle. Widely used methods for its assessment comprise sap flux techniques for whole-plant transpiration and porometry for leaf stomatal conductance. Recently emerging approaches based on surface temperatures and a wide range of machine learning techniques offer new possibilities to quantify transpiration. The focus of this study was to predict sap flux and leaf stomatal conductance based on drone-recorded and meteorological data and compare these predictions with in-situ measured transpiration. To build the prediction models, we applied classical statistical approaches and machine learning algorithms. The field work was conducted in an oil palm agroforest in lowland Sumatra. Random forest predictions yielded the highest congruence with measured sap flux (r\(^2\) = 0.87 for trees and r\(^2\) = 0.58 for palms) and confidence intervals for intercept and slope of a Passing-Bablok regression suggest interchangeability of the methods. Differences in model performance are indicated when predicting different tree species. Predictions for stomatal conductance were less congruent for all prediction methods, likely due to spatial and temporal offsets of the measurements. Overall, the applied drone and modelling scheme predicts whole-plant transpiration with high accuracy. We conclude that there is large potential in machine learning approaches for ecological applications such as predicting transpiration.

The culture of human induced pluripotent stem cells (hiPSCs) at large scale becomes feasible with the aid of scalable suspension setups in continuously stirred tank reactors (CSTRs). Innovative monitoring options and emerging automated process control strategies allow for the necessary highly defined culture conditions. Next to standard process characteristics such as oxygen consumption, pH, and metabolite turnover, a reproducible and steady formation of hiPSC aggregates is vital for process scalability. In this regard, we developed a hiPSC-specific suspension culture unit consisting of a fully monitored CSTR system integrated into a custom-designed and fully automated incubator. As a step towards cost-effective hiPSC suspension culture and to pave the way for flexibility at a large scale, we constructed and utilized tailored miniature CSTRs that are largely made from three-dimensional (3D) printed polylactic acid (PLA) filament, which is a low-cost material used in fused deposition modelling. Further, the monitoring tool for hiPSC suspension cultures utilizes in situ microscopic imaging to visualize hiPSC aggregation in real-time to a statistically significant degree while omitting the need for time-intensive sampling. Suitability of our culture unit, especially concerning the developed hiPSC-specific CSTR system, was proven by demonstrating pluripotency of CSTR-cultured hiPSCs at RNA (including PluriTest) and protein level.

The recently observed consistent loss of β-diversity across ecosystems indicates increasingly homogeneous communities in patches of landscapes, mainly caused by increasing land-use intensity. Biodiversity is related to numerous ecosystem functions and stability. Therefore, decreasing β-diversity is also expected to reduce multifunctionality. To assess the impact of homogenization and to develop guidelines to reverse its potentially negative effects, we combine expertise from forest science, ecology, remote sensing, chemical ecology and statistics in a collaborative and experimental β-diversity approach. Specifically, we will address the question whether the Enhancement of Structural Beta Complexity (ESBC) in forests by silviculture or natural disturbances will increase biodiversity and multifunctionality in formerly homogeneously structured production forests. Our approach will identify potential mechanisms behind observed homogenization-diversity-relationships and show how these translate into effects on multifunctionality. At eleven forest sites throughout Germany, we selected two districts as two types of small ‘forest landscapes’. In one of these two districts, we established ESBC treatments (nine differently treated 50x50 m patches with a focus on canopy cover and deadwood features). In the second, the control district, we will establish nine patches without ESBC. By a comprehensive sampling, we will monitor 18 taxonomic groups and measure 21 ecosystem functions, including key functions in temperate forests, on all patches. The statistical framework will allow a comprehensive biodiversity assessment by quantifying the different aspects of multitrophic biodiversity (taxonomical, functional and phylogenetic diversity) on different levels of biodiversity (α-, β-, γ-diversity). To combine overall diversity, we will apply the concept of multidiversity across the 18 taxa. We will use and develop new approaches for quantification and partitioning of multifunctionality at α- and β- scales. Overall, our study will herald a new research avenue, namely by experimentally describing the link between β-diversity and multifunctionality. Furthermore, we will help to develop guidelines for improved silvicultural concepts and concepts for management of natural disturbances in temperate forests reversing past homogenization effects.

Farmland tree cultivation is considered an important option for enhancing wood production. In South India, the native leaf-deciduous tree species Melia dubia is popular for short-rotation plantations. Across a rainfall gradient from 420 to 2170 mm year\(^{–1}\), we studied 186 farmland woodlots between one and nine years in age. The objectives were to identify the main factors controlling aboveground biomass (AGB) and growth rates. A power-law growth model predicts an average stand-level AGB of 93.8 Mg ha\(^{–1}\) for nine-year-old woodlots. The resulting average annual AGB increment over the length of the rotation cycle is 10.4 Mg ha\(^{–1}\) year\(^{–1}\), which falls within the range reported for other tropical tree plantations. When expressing the parameters of the growth model as functions of management, climate and soil variables, it explains 65% of the variance in AGB. The results indicate that water availability is the main driver of the growth of M. dubia. Compared to the effects of water availability, the effects of soil nutrients are 26% to 60% smaller. We conclude that because of its high biomass accumulation rates in farm forestry, M. dubia is a promising candidate for short-rotation plantations in South India and beyond.