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Effects of breeding for short-tailedness in sheep on parameters of reproduction and lamb development
(2025) Hümmelchen, Hannah; Wagner, Henrik; Brügemann, Kerstin; König, Sven; Wehrend, Axel
Background: Sheep's tail docking is a widespread practice, which is banned or critically discussed in some countries to improve animal welfare. Objective: The aim was to determine the influence of breeding for short-tailedness (ST) or long-tailedness (LT) in sheep on the development of reproduction parameters and lamb performance. Method: One hundred forty-nine ewes were mated with four rams according to tail length. Pregnancy and pregnancy loss rates were calculated. During pregnancy, the progesterone levels (P4) of the ewes were measured. The weight and length of the 254 lambs were recorded up to 14 weeks of life. Litter size, placenta weight, sex, stillbirths, vitality, morbidity and mortality of the lambs were also documented. Results: No significant differences were found for P4 and placental weight for the two mating groups (ST and LT). Although the pregnancy rate for ST was slightly lower (75.71%) than for LT (87.34%), there was only a low significant difference (p = 0.07). The sex distribution was 61 (48.80%) male and 64 (51.20%) female lambs in the ST group and 67 (51.94%) male and 62 (48.06%) female lambs in the LT group. The twinning rate was not significantly different (ST 75.20%; LT 75.97%), and no significant difference was found in the average body length and vitality of the lambs. However, LT lambs showed better weight gains that were marginally significant (p = 0.09). Conclusion: This study found no evidence that reproductive parameters or lamb performance were affected by selective breeding based on tail length.
Pig tail length is associated with the prevalence of tail malformations but not with inflammation of the tail
(2025) Egerer, Christiane; Gerhards, Katharina; Becker, Sabrina; Engel, Petra; König, Sven; Reiner, Gerald
Evaluating hydrological model performance using varying amounts of participatory monitoring water level data
(2025) Mitze, Fabian; Jacobs, Suzanne Robin; Breuer, Lutz; Zeballos, Jazmin Campos; Weeser, Björn
In the context of participatory monitoring projects in hydrology, the collection of water level data by laypersons is used as a simple and cost-effective alternative to automatic water level sensors, especially in poorly gauged catchments in remote areas of countries in the Global South. Such data can be used for the development of hydrological models to support water resources management. However, a common problem with participatory monitoring approaches is the irregularity of data collection and its decreasing frequency over time. Determining the amount and timing of data collection required for satisfactory model calibration is critical. To investigate this further, we examined daily water levels from a four-year project in western Kenya. We set up scenarios that represented datasets of different lengths and seasonal starting points for measurements. These scenarios were then used to calibrate a simple rainfall-runoff model. The data were supplemented with satellite data on evapotranspiration to improve the simulated water balance. The model runs were filtered using a water balance filter, and the Kling-Gupta-Efficiency (KGE) was used to compare model efficiencies. While a single month of water level data collected during the rainy seasons was sufficient to achieve good model performance (KGE ≥ 0.75), several months of data were required for simulations starting in the dry seasons. Similar results were found for the validation period, with lower overall model performance (KGE ≥ 0.6). Water level data collected during high flows generally led to an improvement in model performance compared to data collected during low flows. However, after a certain threshold, more water level data did not lead to further substantial model improvement. Based on the analysis of different datasets, this study demonstrated that short-term participatory monitoring programs that collect water level data during the wet season have the potential to provide sufficient input to calibrate a hydrological model.
The effect of vection on the use of optic flow cues
(2025) McManus, Meaghan; Fiehler, Katja
When we move objects move past us in a relative pattern of motion referred to as optic flow. Modulations in optic flow can impact both our perception of self-motion (e.g. perceived distance travelled) and our feeling of self-motion, referred to as vection (e.g. speed of self-motion). The perception and feeling of self-motion have so far been studied independently, leaving open whether and how the two relate to each other. In the current study, stationary participants performed a self-motion task in virtual reality where they moved to previously indicated distances using constant velocity optic flow. The perception of self-motion was measured as the ratio between the distance to travel and the distance travelled, where stopping sooner indicates that the optic flow cues were more effective in creating the perception of self-motion. Vection experience was measured via a questionnaire. When participants felt vection, there was a correlation between stopping distance (reflecting the perception of self-motion) and the felt speed of vection (reflecting the feeling of self-motion), i.e. the faster participants felt they were moving the sooner they stopped. These results show that the perception and feeling of self-motion are linked and that treating the two concepts independently can lead to misinterpretations.
Analyzing conflicts, crime and violence through complexity
(2026-04-21) Rodriguez Prieto, Maykol
Conflicts over natural resources, environmental crimes, and illicit markets constitute interconnected phenomena that reinforce one another through complex interactions involving armed groups, organized crime, institutional weaknesses, and legal actors. These dynamics generate violence, environmental degradation, biodiversity loss, and significant economic and social costs while creating self-reinforcing systems sustained by illicit financial flows and criminal networks. Despite the growing literature on these issues, their clandestine nature, heterogeneous actors, and nonlinear interactions make them difficult to analyze using conventional approaches. This thesis applies the framework of complexity theory to examine the interdependence between conflict, environmental crime, and organized crime. Drawing on concepts such as emergence, adaptation, and nonlinearity, it combines game theory, network theory, and agent-based modeling to investigate how interactions among heterogeneous agents produce systemic outcomes. The research is organized into three complementary studies. The first study develops a two-stage network game to analyze rent dissipation in conflicts over natural resources, demonstrating how network structures, alliances, rivalries, and power asymmetries shape economic losses. The model is calibrated using the Sudanese gold conflict. The second study employs an agent-based model to simulate cocaine trafficking through container shipping between South America and Europe, evaluating the effects of corruption, inspection capacity, and ship size on trafficking outcomes. Simulation results reveal that corruption substantially weakens enforcement efforts and creates opportunities for organized crime. The third study presents a theoretical network model to examine the relationship between enforcement costs, coordination, and social acceptability in interventions designed to sustain cooperation and prevent corruption, showing that effective enforcement depends on both network topology and the distribution of influential actors. Taken together, the findings demonstrate that conflicts, environmental crimes, and illicit markets should be understood as components of an adaptive complex system rather than as isolated phenomena. By integrating multiple complexity-based methodologies, this thesis provides new theoretical and quantitative tools to better understand these interactions and offers insights for designing more effective policies to reduce violence, environmental degradation, and organized criminal activity.