Adaptive dynamics with interaction structure

Evolutionary dynamics depend critically on a population's interaction structure - the pattern of which individuals interact with which others, depending on the state of the population and the environment. Previous research has shown, for example, that cooperative behaviors disfavored in well-mixed populations can be favored when interactions occur only between spatial neighbors or group members. Combining the adaptive dynamics approach with recent advances in evolutionary game theory, we here introduce a general mathematical framework for analyzing the long-term evolution of continuous game strategies for a broad class of evolutionary models, encompassing many varieties of interaction structure. Our main result, the "canonical equation of adaptive dynamics with interaction structure", characterizes expected evolutionary trajectories resulting from any such model, thereby generalizing a central tool of adaptive dynamics theory. Interestingly, the effects of different interaction structures and update rules on evolutionary trajectories are fully captured by just two real numbers associated with each model, which are independent of the considered game. The first, a structure coefficient, quantifies the effects on selection pressures, and thus on the shapes of expected evolutionary trajectories. The second, an effective population size, quantifies the effects on selection responses, and thus on the expected rates of adaptation. Applying our results to two social dilemmas, we show how the range of evolutionarily stable cooperative behaviors systematically varies with a model's structure coefficient

Analysis of a spatial Lotka-Volterra model with a finite range predator-prey interaction

We perform an analysis of a recent spatial version of the classical Lotka-Volterra model, where a finite scale controls individuals' interaction. We study the behavior of the predator-prey dynamics in physical spaces higher than one, showing how spatial patterns can emerge for some values of the interaction range and of the diffusion parameter.Comment: 7 pages, 7 figure

Red Queen Coevolution on Fitness Landscapes

Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve ex- ploring their fitness landscapes. Coevolution involves the coupling of species fit- ness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution com- menting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.Comment: 40 pages, 12 figures. To appear in "Recent Advances in the Theory and Application of Fitness Landscapes" (H. Richter and A. Engelbrecht, eds.). Springer Series in Emergence, Complexity, and Computation, 201

Aggregate structure of hydroxyproline-rich glycoprotein (HRGP) and HRGP assisted dispersion of carbon nanotubes

Hydroxyproline-rich glycoproteins (HRGP) comprise a super-family of extracellular structural glycoproteins whose precise roles in plant cell wall assembly and functioning remain to be elucidated. However, their extended structure and repetitive block co-polymer character of HRGPs may mediate their self-assembly as wall scaffolds by like-with-like alignment of their hydrophobic peptide and hydrophilic glycopeptide modules. Intermolecular crosslinking further stabilizes the scaffold. Thus the design of HRGP-based scaffolds may have practical applications in bionanotechnology and medicine. As a first step, we have used single-molecule or single-aggregate atomic force microscopy (AFM) to visualize the structure of YK20, an amphiphilic HRGP comprised entirely of 20 tandem repeats of: Ser-Hyp4-Ser-Hyp-Ser-Hyp4-Tyr-Tyr-Tyr-Lys. YK20 formed tightly aggregated coils at low ionic strength, but networks of entangled chains with a porosity of ~0.5–3 μm at higher ionic strength. As a second step we have begun to design HRGP-carbon nanotube composites. Single-walled carbon nanotubes (SWNTs) can be considered as seamless cylinders rolled up from graphene sheets. These unique all-carbon structures have extraordinary aromatic and hydrophobic properties and form aggregated bundles due to strong inter-tube van der Waals interactions. Sonicating aggregated SWNT bundles with aqueous YK20 solubilized them presumably by interaction with the repetitive, hydrophobic, Tyr-rich peptide modules of YK20 with retention of the extended polyproline-II character. This may allow YK20 to form extended structures that could potentially be used as scaffolds for site-directed assembly of nanomaterials

Eco-evolutionary dynamics on deformable fitness landscapes

Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem. We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner. We observe that this model can exhibit either of the two behavioural modes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change. We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution

Endbericht der wissenschaftlichen Begleitung des SeWo-LWL-Programms für selbständiges und technikunterstütztes Wohnen im Quartier

Die Selbstständige Wohnen gem. GmbH (SeWo) als Tochtergesellschaft des Landschaftsverbandes Westfalen-Lippe (LWL) fördert 15 Wohnprojekte für je 10-15 Menschen mit vergleichsweise höherem Hilfebedarf in Kommunen in Westfalen-Lippe. Die Mieter/innen leben mit Unterstützung in ihren eigenen Wohnungen. Durch sozialraum- bzw. quartiersbezogene Arbeit und technische Unterstützung soll die Teilhabe, die Selbstständigkeit und die Sicherheit der Mieter/innen mit Beeinträchtigungen nachhaltig verbessert werden. Die Evaluation des SeWo-LWL Programms für selbstständiges und technikunterstütztes Wohnen im Quartier umfasst die drei Themenbereiche: Bauen für das Wohnen von Menschen mit Behinderung; Sozialraumorientierung und soziale Inklusion; technikunterstütztes Wohnen. Für diese drei Themenbereiche werden abschließend aufgrund der im Projekt ausgewerteten Erfahrungen und unter Berücksichtigung der aktuellen Herausforderungen Empfehlungen ausgesprochen. Das Evaluationsprojekt hat die sozialraum- und quartiersbezogene Arbeit der Anbieter sowie die daraus resultierenden Teilhabemöglichkeiten der Mieter/innen multiperspektivisch erhoben und bewertet. Zudem werden die Barrieren und Förderer für die Realisierung der Wohngebäude analysiert sowie haustechnische Lösungen und die Chancen für Mieter/innen dargestellt. Die quartiers- und sozialraumbezogene Arbeit wird aus der Perspektive der Quartiers- und Teilhabgestalter/innen und aus der Perspektive der Mieter/innen mit Behinderung bewertet: - Qualitative Inhaltsanalyse der Anbieterkonzepte - Strukturierte Netzwerkkarte mit Kooperationsbeziehungen im Quartier - Workshop mit den Quartiers- und Teilhabegestalter/innen aus allen Wohnprojekten - Fokusgruppen mit den Mieter/innen in den Wohnprojekten - Strukturierter Dokumentationsbogen mit Eco-Map zur sozialraum- und quartiersbezogenen Teilhabe für jede Mieterin/ jeden Mieter zu drei Erhebungszeitpunkte - Qualitative Einzelinterviews mit Quartier- und Teilhabegestalter/inne

Sea ice CO2 flux in the Southern Ocean during mid-winter and early spring

There seems little doubt that sea ice is permeable to CO2 and other gases although air–sea ice gas flux is more or less inhibited at a brine volume fraction of less than 5% representing the threshold for fluid permeability of sea ice. Generally, air–sea ice CO2 flux is at its minimum in winter due to low sea ice temperatures and consequently reduced permeability despite the fact the partial pressure of CO2 in sea ice is usually high at that time and sea ice has therefore the potential to release CO2 to the atmosphere. Here, we present first evidence that snow laden Antarctic sea ice can act as source for atmospheric CO2 even during mid-winter and early spring. During a mid-winter cruise to the Weddell Sea (AWECS, 2013) and an early spring cruise off east Antarctica (SIPEX-2, 2012), due to thick insulating snow covers, the bottom of the snow and the surface of the sea ice were relatively warm (>–10°C) even though air temperature was sometimes below –30°C. In addition, in both areas, sea ice was characterized by high bulk-salinities, resulting in brine volume fractions that are generally higher than 5%. Automatic “open-closed” chamber measurements indicated positive CO2 fluxes of up to +2.5 mmol C m–2 day–1, illustrating that sea ice acted as a source of atmospheric CO2. Higher fluxes were measured at bare ice surfaces after removing the snow. However, generally low snow densities (mean: 339 kg m–3), indicating a permeable snow cover, facilitated degassing of CO2 at the snow-air interface. Our results therefore suggest that even in the winter and early spring, Antarctic sea ice can act as CO2 source for the atmosphere, particularly in areas with a thick insulating snow cover.Bigsout

EDGAR3.0: Comparative genomics and phylogenomics on a scalable infrastructure.

The EDGAR platform, a web server providing databases of precomputed orthology data for thousands of microbial genomes, is one of the most established tools in the field of comparative genomics and phylogenomics. Based on precomputed gene alignments, EDGAR allows quick identification of the differential gene content, i.e. the pan genome, the core genome, or singleton genes. Furthermore, EDGAR features a wide range of analyses and visualizations like Venn diagrams, synteny plots, phylogenetic trees, as well as Amino Acid Identity (AAI) and Average Nucleotide Identity (ANI) matrices. During the last few years, the average number of genomes analyzed in an EDGAR project increased by two orders of magnitude. To handle this massive increase, a completely new technical backend infrastructure for the EDGAR platform was designed and launched as EDGAR3.0. For the calculation of new EDGAR3.0 projects, we are now using a scalable Kubernetes cluster running in a cloud environment. A new storage infrastructure was developed using a file-based high-performance storage backend which ensures timely data handling and efficient access. The new data backend guarantees a memory efficient calculation of orthologs, and parallelization has led to drastically reduced processing times. Based on the advanced technical infrastructure new analysis features could be implemented including POCP and FastANI genomes similarity indices, UpSet intersecting set visualization, and circular genome plots. Also the public database section of EDGAR was largely updated and now offers access to 24,317 genomes in 749 free-to-use projects. In summary, EDGAR 3.0 provides a new, scalable infrastructure for comprehensive microbial comparative gene content analysis. The web server is accessible at http://edgar3.computational.bio