Phase Synchronization in Railway Timetables

Timetable construction belongs to the most important optimization problems in public transport. Finding optimal or near-optimal timetables under the subsidiary conditions of minimizing travel times and other criteria is a targeted contribution to the functioning of public transport. In addition to efficiency (given, e.g., by minimal average travel times), a significant feature of a timetable is its robustness against delay propagation. Here we study the balance of efficiency and robustness in long-distance railway timetables (in particular the current long-distance railway timetable in Germany) from the perspective of synchronization, exploiting the fact that a major part of the trains run nearly periodically. We find that synchronization is highest at intermediate-sized stations. We argue that this synchronization perspective opens a new avenue towards an understanding of railway timetables by representing them as spatio-temporal phase patterns. Robustness and efficiency can then be viewed as properties of this phase pattern

Functional Effects of Parasites on Food Web Properties during the Spring Diatom Bloom in Lake Pavin: A Linear Inverse Modeling Analysis

This study is the first assessment of the quantitative impact of parasitic chytrids on a planktonic food web. We used a carbon-based food web model of Lake Pavin (Massif Central, France) to investigate the effects of chytrids during the spring diatom bloom by developing models with and without chytrids. Linear inverse modelling procedures were employed to estimate undetermined flows in the lake. The Monte Carlo Markov chain linear inverse modelling procedure provided estimates of the ranges of model-derived fluxes. Model results support recent theories on the probable impact of parasites on food web function. In the lake, during spring, when ‘inedible’ algae (unexploited by planktonic herbivores) were the dominant primary producers, the epidemic growth of chytrids significantly reduced the sedimentation loss of algal carbon to the detritus pool through the production of grazer-exploitable zoospores. We also review some theories about the potential influence of parasites on ecological network properties and argue that parasitism contributes to longer carbon path lengths, higher levels of activity and specialization, and lower recycling. Considering the “structural asymmetry” hypothesis as a stabilizing pattern, chytrids should contribute to the stability of aquatic food webs

Evolving Clustered Random Networks

We propose a Markov chain simulation method to generate simple connected random graphs with a specified degree sequence and level of clustering. The networks generated by our algorithm are random in all other respects and can thus serve as generic models for studying the impacts of degree distributions and clustering on dynamical processes as well as null models for detecting other structural properties in empirical networks

Googling Food Webs: Can an Eigenvector Measure Species' Importance for Coextinctions?

A major challenge in ecology is forecasting the effects of species' extinctions, a pressing problem given current human impacts on the planet. Consequences of species losses such as secondary extinctions are difficult to forecast because species are not isolated, but interact instead in a complex network of ecological relationships. Because of their mutual dependence, the loss of a single species can cascade in multiple coextinctions. Here we show that an algorithm adapted from the one Google uses to rank web-pages can order species according to their importance for coextinctions, providing the sequence of losses that results in the fastest collapse of the network. Moreover, we use the algorithm to bridge the gap between qualitative (who eats whom) and quantitative (at what rate) descriptions of food webs. We show that our simple algorithm finds the best possible solution for the problem of assigning importance from the perspective of secondary extinctions in all analyzed networks. Our approach relies on network structure, but applies regardless of the specific dynamical model of species' interactions, because it identifies the subset of coextinctions common to all possible models, those that will happen with certainty given the complete loss of prey of a given predator. Results show that previous measures of importance based on the concept of “hubs” or number of connections, as well as centrality measures, do not identify the most effective extinction sequence. The proposed algorithm provides a basis for further developments in the analysis of extinction risk in ecosystems

Biodiversity and the Functioning of Ecosystems in the Age of Global Change: Integrating Knowledge Across Scales

The dramatic decline of biodiversity worldwide has raised a general concern on the impacts this process could have for the well-being of humanity. Human societies strongly depend on the benefits provided by natural ecosystems, which are the result of biogeochemical processes governed by species activities and their interaction with abiotic compartments. After decades of experimental research on the biodiversity-functioning relationship, a relative agreement has been reached on the mechanisms underlying the impacts that biodiversity loss can have on ecosystem processes. However, a general consensus is still missing. We suggest that the reason preventing an integration of existing knowledge is the scale discrepancy between observations on global change impacts and biodiversity-functioning experiments. The present chapter provides an overview of global change impacts on biodiversity across various ecological scales and its consequences for ecosystem functioning, highlighting what is known and where knowledge gaps still persist. Furthermore, the reader will be introduced to a set of tools that allow a multi-scale analysis of how global change drivers impact ecosystem functioning

Ascendency as Ecological Indicator for Environmental Quality Assessment at the Ecosystem Level: A Case Study

Previous studies have shown that when an ecosystem consists of many interacting components it becomes impossible to understand how it functions by focussing only on individual relationships. Alternatively, one can attempt to quantify system behaviour as a whole by developing ecological indicators that combine numerous environmental factors into a single value. One such holistic measure, called the system ‘ascendency’, arises from the analysis of networks of trophic exchanges. It deals with the joint quantification of overall system activity with the organisation of the component processes and can be used specifically to identify the occurrence of eutrophication. System ascendency analyses were applied to data over a gradient of eutrophication in a well documented small temperate intertidal estuary. Three areas were compared along the gradient, respectively, non eutrophic, intermediate eutrophic, and strongly eutrophic. Values of other measures related to the ascendency, such as the total system throughput, development capacity, and average mutual information, as well as the ascendency itself, were clearly higher in the non-eutrophic area. When the whole-system properties of the three areas were compared, however, the values associated with the intermediate eutrophic area turned out to be the lowest, which possibly could be attributed to the unstable nature of this area. The current study provided an example of how the measures arising out of?network analysis might lead to an improved understanding of the system functioning and of the eutrophication process itself