Festuca paniculata meadows in Ticino (Switzerland) and their Alpine environment

Festuca paniculata (L.) Schinz & Thellung locally dominates montane and subalpine meadows of the Alps and other mountains of southern Europe. Vegetation releves were carried out in Switzerland and northern Italy to study the site conditions under which Festuca paniculata meadows occur in this part of the Alps, their species composition and phytosociological status, and their relationship to Festuca paniculata meadows described previously from the French Alps (Centaureo-Festucetum spadiceae) and Austrian Alps (Hypochaerido uniflorae-Festucetum paniculatae). The Swiss meadows were found to have a similar ecology to those in France and Austria. They occur mostly between 1600 and 2100 m a.s.l on steep slopes with southern aspect, generally on crystalline rocks, but sometimes on calcareous rocks if soils have been decalcified. The species composition of the Swiss meadows is closer to the Austrian than to the French communities, and we attribute them to the association Hypochaerido uniflorae-Festucetum paniculatae with the new subassociation polygaletosum chamaebuxi. Climate is probably the main factor separating vegetation units in the Alps: the Centaureo-Festucetum spadiceae occurs where summers are dry, whereas the Hypochaerido uniflorae-Festucetum paniculatae occurs where rainfall is not a limiting factor in summer

Les pelouses à Festuca paniculata du Tessin (Suisse) dans un contexte Alpin

Abstract.: Vittoz P., Selldorf P., Eggenberg S. and Maire S. 2005. Festuca paniculata meadows in Ticino (Switzerland) and their Alpine environment. Bot. Helv. 115: 33-48. Festuca paniculata (L.) Schinz & Thellung locally dominates montane and subalpine meadows of the Alps and other mountains of southern Europe. Vegetation relevés were carried out in Switzerland and northern Italy to study the site conditions under which Festuca paniculata meadows occur in this part of the Alps, their species composition and phytosociological status, and their relationship to Festuca paniculata meadows described previously from the French Alps (Centaureo-Festucetum spadiceae) and Austrian Alps (Hypochaerido uniflorae-Festucetum paniculatae). The Swiss meadows were found to have a similar ecology to those in France and Austria. They occur mostly between 1600 and 2100 m a.s.l on steep slopes with southern aspect, generally on crystalline rocks, but sometimes on calcareous rocks if soils have been decalcified. The species composition of the Swiss meadows is closer to the Austrian than to the French communities, and we attribute them to the association Hypochaerido uniflorae-Festucetum paniculatae with the new subassociation polygaletosum chamaebuxi. Climate is probably the main factor separating vegetation units in the Alps: the Centaureo-Festucetum spadiceae occurs where summers are dry, whereas the Hypochaerido uniflorae-Festucetum paniculatae occurs where rainfall is not a limiting factor in summe

On the trails of Josias Braun-Blanquet II : first results from the 12th EDGG Field Workshop studying the dry grasslands of the inneralpine dry valleys of Switzerland

The 12th EDGG Field Workshop took place from 11 to 19 May 2019, organised by the Vegetation Ecology Group of the Institute of Natural Resource Sciences (IUNR) of the Zurich University of Applied Sciences (ZHAW). Like in the 11th Field Workshop in Austria, the main target was the "Inneralpine Trockenvegetation" (Festuco-Brometea and Sedo-Scleranthetea), which was first extensively sampled by Josias Braun-Blanquet and collaborators during the 1950s. We visited the Rhône valley in the cantons of Vaud and Valais, one of the most ex-treme xerothermic islands of the Alps and the Rhine and Inn valleys in the canton of Grison. In total, 30 nested-plot series (EDGG biodi-versity plots) of 0.0001 to 100 m² and 82 plots of 10 m² were sampled in meso-xeric, xeric and rocky grasslands of 25 different sites, rang-ing from 500 to 1,656 m a.s.l., under different topographic, bedrock and landuse conditions. All vascular plants, bryophytes and lichens were recorded in each plot, along with their cover values. We found on average 28.9 vascular plants on 10 m²; which was the lowest mean species richness of any previous EDGG Field Workshop. These values are comparable to the average species richness values of dry grasslands of the Aosta valley in Italy. The data sampled will be used to understand the biodiversity patterns regionally and in the Palae-arctic context as well as to place the Swiss dry grasslands in the modern European syntaxonomic system

Super Star Clusters in the Blue Dwarf Galaxy UM 462

I present optical observations of the Blue Compact Dwarf Galaxy UM 462. The images of this galaxy show several bright compact sources. A careful study of these sources has revealed their nature of young Super Star Clusters. The ages determined from the analysis of the stellar continuum and $H\alpha$ are between few and few tens Myr. The total star formation taking place into the clusters is about 0.05 $\mathrm{M_{\odot}/yr}$. The clusters seem to be located at the edges of two large round-like structures, possibly shells originated in a previous episode of star formation. The sizes of the shells compare well with the ages of the clusters. Evidence for the presence of an evolved underlying stellar population is found.Comment: 8 pages, 6 figure

Combining robustness and recovery for airline schedules

In this thesis, we address different aspects of the airline scheduling problem. The main difficulty in this field lies in the combinatorial complexity of the problems. Furthermore, as airline schedules are often faced with perturbations called disruptions (bad weather conditions, technical failures, congestion, crew illness…), planning for better performance under uncertainty is an additional dimension to the complexity of the problem. Our main focus is to develop better schedules that are less sensitive to perturbations and, when severe disruptions occur, are easier to recover. The former property is known as robustness and the latter is called recoverability. We start the thesis by addressing the problem of recovering a disrupted schedule. We present a general model, the constraint-specific recovery network, that encodes all feasible recovery schemes of any unit of the recovery problem. A unit is an aircraft, a crew member or a passenger and its recovery scheme is a new route, pairing or itinerary, respectively. We show how to model the Aircraft Recovery Problem (ARP) and the Passenger Recovery Problem (PRP), and provide computational results for both of them. Next, we present a general framework to solve problems subject to uncertainty: the Uncertainty Feature Optimization (UFO) framework, which implicitly embeds the uncertainty the problem is prone to. We show that UFO is a generalization of existing methods relying on explicit uncertainty models. Furthermore, we show that by implicitly considering uncertainty, we not only save the effort of modeling an explicit uncertainty set: we also protect against possible errors in its modeling. We then show that combining existing methods using explicit uncertainty characterization with UFO leads to more stable solutions with respect to changes in the noise's nature. We illustrate these concepts with extensive simulations on the Multi-Dimensional Knapsack Problem (MDKP). We then apply the UFO to airline scheduling. First, we study how robustness is defined in airline scheduling and then compare robustness of UFO models against existing models in the literature. We observe that the performance of the solutions closely depend on the way the performance is evaluated. UFO solutions seem to perform well globally, but models using explicit uncertainty have a better potential when focusing on a specific metric. Finally, we study the recoverability of UFO solutions with respect to the recovery algorithm we develop. Computational results on a European airline show that UFO solutions are able to significantly reduce recovery costs

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

Robust scheduling and disruption recovery for airlines

Airline planning include complex and structured operations that must be planned in advance in order to exploit the available resources, provide a reliable and competitive service and forecast system's performances. Decisions regarding operations are based on data which is frequently due to uncertainty. Moreover, unpredicted events may disrupt the current schedule and force managers to take reactive decisions to recover to an operational state. On the other hand, proactive decisions, i.e. decisions which take into account the uncertainty of the data, tend to robust solutions which are able to absorb data deviation and small disruptions. In this talk we address the aircraft routing problem from both reactive and proactive point of view and suggest ways to integrate the two approaches to reach what we call a robust recoverable approach for aircraft routing, i.e. a proactive strategy which accounts for the presence of a disruption recovery strategy. We validate our ideas with a computational study based on real world data provided by a major european airline

A column generation algorithm for disrupted airline schedules

We consider the recovery of an airline schedule after an unforeseen event, called {\em disruption}, that makes the planned schedule unfeasible. In particular we consider the aircraft recovery problem for a heterogeneous fleet of aircrafts, made of regular and reserve planes, where the aircrafts' maintenances are planned in an optimal way in order to satisfy the operational regulations. We propose a column generation scheme, where the pricing problem is modeled as a commodity flow problem on a dedicated network, one for each plane of the fleet. We present a dynamic programming algorithm to build the underlying networks and a dynamic programming algorithm for resource constrained elementary shortest paths to solve the pricing problem. We provide some computational results on real world instances

Uncertainty Feature Optimization for the Airline Scheduling Problem

Uncertainty Feature Optimization is a framework to cope with optimization problems due to noisy data, using an implicit characterazation of the noise. The Aircraft Scheduling Problem (ASP) is a particular case of such problems, where disruptions randomly perturbate the original flight schedule. This study uses the UFO framework to generate more robust and recoverable schedules, in the sense that more delays are absorbed and when re-optimization is required, the corresponding recovery costs are reduced. We provide computational results for the public data of an European airline provided for the ROADEF Challenge 2009 footnote{\texttt{http://challenge.roadef.or /2009/index.en.htm}}; new schedules are computed with different models, and we compare the a posteriori results obtained by the application of a recovery algorithm