Kinetic and Dynamic Delaunay tetrahedralizations in three dimensions

We describe the implementation of algorithms to construct and maintain three-dimensional dynamic Delaunay triangulations with kinetic vertices using a three-simplex data structure. The code is capable of constructing the geometric dual, the Voronoi or Dirichlet tessellation. Initially, a given list of points is triangulated. Time evolution of the triangulation is not only governed by kinetic vertices but also by a changing number of vertices. We use three-dimensional simplex flip algorithms, a stochastic visibility walk algorithm for point location and in addition, we propose a new simple method of deleting vertices from an existing three-dimensional Delaunay triangulation while maintaining the Delaunay property. The dual Dirichlet tessellation can be used to solve differential equations on an irregular grid, to define partitions in cell tissue simulations, for collision detection etc.Comment: 29 pg (preprint), 12 figures, 1 table Title changed (mainly nomenclature), referee suggestions included, typos corrected, bibliography update

Species Interactions - From Phenotypes to Ecosystems

Interactions between species can structure populations and communities, affect the flow of energy and matter within and across ecosystem boundaries, and shape the biotic and abiotic environment. Thereby, species interactions can also feed back on the participating species themselves, and on other members of the community. Complex interaction networks can arise that may influence the stability of ecosystems and potentially make them resilient against external perturbation. However, species interactions are not static: through endlessly recurring interplay with their environment, species, and thus, their interactions with other species, are subject to evolutionary change. It is therefore widely acknowledged that species interactions are not only the foundation for the functioning of all ecosystems, but also contribute to the emergence and maintenance of biological diversity on earth. In the face of rapid global environmental change it is critical to learn more about the nature of species interactions, for example, in the context of their strength (effect sizes), temporal stability (variation, within and between generations) or dimensionality (number of, interactions per species). For this dissertation I have conducted a series of experiments to explore the role of species interactions within different levels of ecological organization and across a range of ecological contexts. Specifically, I investigated i) how species interactions can shape phenotypic distributions of populations, ii) how species interactions shape developmental trajectories of phenotypes, and iii) how species interactions affect resistance and resilience of ecosystems in response to external disturbance. In four chapters I addressed these questions with a series of outdoor and laboratory experiments, which provided compelling evidence for strong effects of species interactions on phenotypes, populations, communities and ecosystems

phenopype : A phenotyping pipeline for Python

Digital images are an intuitive way to capture, store and analyse organismal phenotypes. Many biologists are taking images to collect high-dimensional phenotypic information from specimens to investigate complex ecological, evolutionary and developmental phenomena, such as relationships between trait diversity and ecosystem function, multivariate natural selection or developmental plasticity. As a consequence, images are being collected at ever-increasing rates, but extraction of the contained phenotypic information poses a veritable analytical bottleneck. phenopype is a high-throughput phenotyping pipeline for the programming language Python that aims at alleviating this bottleneck. The package facilitates immediate extraction of high-dimensional phenotypic data from digital images with low levels of background noise and complexity. At the core, phenopype provides functions for rapid signal processing-based image preprocessing and segmentation, data extraction, as well as visualization and data export. This functionality is provided by wrapping low-level computer vision libraries (such as OpenCV) into accessible functions to facilitate scientific image analysis. In addition, phenopype provides a project management ecosystem to streamline data collection and to increase reproducibility. phenopype offers two different workflows that support users during different stages of scientific image analysis. The low-throughput workflow uses regular Python syntax and has greater flexibility at the cost of reproducibility, which is suitable for prototyping during the initial stages of a research project. The high-throughput workflow allows users to specify and store image-specific settings for analysis in human-readable YAML format, and then execute all functions in one step by means of an interactive parser. This approach facilitates rapid program-user interactions during batch processing, and greatly increases scientific reproducibility. Overall, phenopype intends to make the features of powerful but technically involved low-level CV libraries available to biologists with little or no Python coding experience. Therefore, phenopype is aiming to augment, rather than replace the utility of existing Python CV libraries, allowing biologists to focus on rapid and reproducible data collection. Furthermore, image annotations produced by phenopype can be used as training data, thus presenting a stepping stone towards the application of deep learning architectures

Filtering joystick data for shooter design really matters

Designing satisfactory, quick and precise control schemes for shooters on consoles remains one of the major game play programming challenges today. Besides the application of game situation specific control aids like soft locking even simple and game unspecific filtering approaches can improve the control quality significantly. In this paper we will objectify and quantify this effect that is well known among game developers as heuristic knowledge

Dietary-based developmental plasticity affects juvenile survival in an aquatic detritivore

Developmental plasticity is ubiquitous in natural populations, but the underlying causes and fitness consequences are poorly understood. For consumers, nutritional variation of juvenile diets is probably associated with plasticity in developmental rates, but little is known about how diet quality can affect phenotypic trajectories in ways that might influence survival to maturity and lifetime reproductive output. Here, we tested how the diet quality of a freshwater detritivorous isopod (Asellus aquaticus), in terms of elemental ratios of diet (i.e. carbon: nitrogen: phosphorus; C: N: P), can affect (i) developmental rates of body size and pigmentation and (ii) variation in juvenile survival. We reared 1047 individuals, in a full-sib split-family design (29 families), on either a high- (low C: P, C: N) or low-quality (high C: P, C: N) diet, and quantified developmental trajectories of body size and pigmentation for every individual over 12 weeks. Our diet contrast caused strong divergence in the developmental rates of pigmentation but not growth, culminating in a distribution of adult pigmentation spanning the broad range of phenotypes observed both within and among natural populations. Under low-quality diet, we found highest survival at intermediate growth and pigmentation rates. By contrast, survival under high-quality diet survival increased continuously with pigmentation rate, with longest lifespans at intermediate growth rates and high pigmentation rates. Building on previous work which suggests that visual predation mediates the evolution of cryptic pigmentation in A. aquaticus, our study shows how diet quality and composition can generate substantial phenotypic variation by affecting rates of growth and pigmentation during development in the absence of predation