A structure-function-diversity model of grassland ecosystems (Gemini) has been developed. For a potentially unlimited number of clonal plant populations, it explicitly simulates competition for two key resources (light and nitrogen) along vertical canopy and soil profiles. Population turnover, shoot and root morphogenesis, photosynthesis, respiration, transpiration, N acquisition by uptake, allocation of assimilates between structural compartments, and reserve storage and remobilization, are simulated for each plant population. The object-oriented structure of the modeling framework allows to couple, or not, the simulated plant populations to other sub-models describing climate variables, soil functioning, grazing behavior and grassland management. Partitioning of growth between shoot structures, leaf photosynthetic proteins and roots is based on two assumptions: (i) functional balance between root and shoot activity, (ii) coordination of leaf photosynthesis. The model was parameterized from plant functional trait measurements of 13 native perennial pasture grass species grown in monocultures at high N availability and low cutting frequency in a field trial. Predicted and measured annual dry-matter yields were highly correlated without bias across species, N supply and cutting frequency treatments in monocultures and in mixtures of six species. Results show the ability of this mechanistic model to simulate without bias nitrogen and disturbance responses of net primary productivity and of plant community structure. (C) 2012 Elsevier B.V. All rights reserved

International audienceGemini, a mechanistic model linking plant functional traits, plant populations, community dynamics, and ecosystem scale fluxes in grasslands has been reported in a companion paper (Soussana et al., 2012). For monocultures and six species mixtures of perennial grass species, this model has been successfully evaluated against experimental data of above-ground net primary productivity (ANPP) and plant community structure across nitrogen and disturbance (cutting frequency) gradients. The Gemini model combines two categories of processes: (i) C and N fluxes, (ii) morphogenesis and architecture of roots and shoots and demography of clonal plant axes. These two process categories constrain the form and function of the simulated clonal plants within plastic limits. We show here that the plasticity of the simulated plant populations accounts for well-established empirical laws: (i) root:shoot ratio, (ii) self-thinning, (iii) critical shoot N content, and (iv) role of plant traits (specific leaf area and plant height) for population response to environmental gradients (nitrogen and disturbance). Moreover, we show that model versions for which plasticity simulation has been partly or fully suppressed have a reduced ANPP in monocultures and in binary mixtures and do not capture anymore productivity and dominance changes across environmental gradients. We conclude that, along environmental and competition gradients, the plasticity of plant form and function is required to maintain the coordination of multiple resource capture and, hence, to sustain productivity and dominance

When using optimization techniques based on mathematical models, we often need to make important simplifications. The solution thus provided, even if proven to be theoretically one of the best, might not be so good in practice. Simulation can be used to evaluate the actual performance of the solution. We propose here a coupling between optimization and simulation that tries to improve the solution provided by a mathematical model. This approach, named "model enhancement" here, still focuses on optimizing the theoretical objective function, contrary to the common optimization-simulation coupling that focuses on improving the objective function evaluated from simulation. We propose to illustrate this approach on a routing problem, and present numerical results on the quality of the solution and the efficiency of both coupling approaches.

We present briefly some results we obtained with known methods to solve minimum cost tension problems, comparing their performance on non-specific graphs and on series-parallel graphs. These graphs are shown to be of interest to approximate many tension problems, like synchronization in hypermedia documents. We propose a new aggregation method to solve the minimum convex piecewise linear cost tension problem on series-parallel graphs in O(m 3 ) operations.

The development of hypermedia/multimedia systems requires the implementation of an element, usually known as formatter, which is in charge of receiving the specification of a document and controlling its presentation. Adjustments over the duration of media objects is one of the most important adaptation techniques that hypermedia formatters should implement in order to maintain document spatio-temporal relationships. Elastic time computation accomplishes this goal by stretching or shrinking the ideal duration of media objects. This paper presents new elastic time algorithms for adjusting hypermedia document presentations. The algorithms explore the flexibility offered by some hypermedia models in the definition of media-object durations, choosing objects to be stretched or shrunk in order to obtain the best possible quality of presentation. Our proposals are based on the "out-of-kilter" method for minimum-cost flow problems on temporal graphs. An aggregation procedure enhances the basic algorithm offering more flexibility in modeling real-life situations in comparison with other previous work based on linear programming.

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Some hypermedia synchronization issues request the resolution of the minimum convex piecewise linear cost tension problem (CPLCT problem) on directed graphs that are close to two-terminal series-parallel graphs (TTSP-graphs), the so-called quasi-k series-parallel graphs (k-QSP graphs). An aggregation algorithm has already been introduced for the CPLCT problem on TTSP-graphs. We propose here a reconstruction method, based on the aggregation and the wellknown out-of-kilter techniques, to solve the problem on k-QSP graphs. One of the main steps being to decompose a graph into TTSP-subgraphs, methods based on the recognition of TTSP-graphs are thoroughly discussed.

Abstract. In generic programming, software components are parameterized on types. When available, a static specialization mechanism allows selecting, for a given set of parameters, a more suitable version of a generic component than its primary version. The normal C++ template specialization mechanism is based on the type pattern of the parameters, which is not always the best way to guide the specialization process: type patterns are missing some information on types that could be relevant to define specializations.The notion of a concept, which represents a set of requirements (including syntactic and semantic aspects) for a type, is known to be an interesting approach to control template specialization. For many reasons, concepts were dropped from C++11 standard, this article therefore describes template metaprogramming techniques for declaring concepts, modeling relationships (meaning that a type fulfills the requirements of a concept), and refinement relationships (meaning that a concept refines the requirements of another concept).From a taxonomy of concepts and template specializations based on concepts, an automatic mechanism selects the most appropriate version of a generic component for a given instantiation. Our purely library-based solution is also open for retroactive extension: new concepts, relationships, and template specializations can be defined at any time; such additions will then be picked up by the specialization mechanism.