SIMULATION: Transactions of The Society for Modeling and Simulation International

Hill, David R. C.; Komatsu, Teruhisa

doi: 10.1177/0037549706072484pmid: N/A

Cournède, Paul-Henry; Kang, Meng-Zhen; Mathieu, Amélie; Barczi, Jean-François; Yan, Hong-Pin; Hu, Bao-Gang; de Reffye, Philippe

doi: 10.1177/0037549706069341pmid: N/A

Numerical simulation of plant growth has been facing a bottleneck due to the cumbersome computation implied by the complex plant topological structure. In this article, the authors present a new mathematical model for plant growth, GreenLab, overcoming these difficulties. GreenLab is based on a powerful factorization of the plant structure. Fast simulation algorithms are derived for deterministic and stochastic trees. The computation time no longer depends on the number of organs and grows at most quadratically with the age of the plant. This factorization finds applications to build trees very efficiently, in the context of geometric models, and to compute biomass production and distribution, in the context of functional structural models.

Hoffmann, James P.

doi: 10.1177/0037549706069103pmid: N/A

The addition of two emerging technologies (evolutionary computation and ecoinformatics) to computational ecology can advance our ability to build better ecological models and thus deepen our understanding of the mechanistic complexity of ecological systems. This article describes one feasible approach toward this goal–the combining of inductive and deductive modeling techniques with the optimizing power of simple algorithms of Darwinian evolution that include information-theoretic model selection methods. Specifically, the author shows a way to extend classic genetic algorithms beyond typical parameter fitting of a single, previously chosen model to a more flexible technique that can work with a suite of possible models. Inclusion of the Akaike information-theoretic model selection method within an evolutionary algorithm makes it possible to accomplish simultaneous parameter fitting and parsimonious model selection.Experiments with synthetic data show the feasibility of this approach, and experiments with time-series field data of the zebra mussel invasion of Lake Champlain (United States) result in a model of the invasion dynamics that is consistent with the known hydrodynamic features of the lake and the motile life history stage of this invasive species.The author also describes a way to extend this approach with a modified genetic programming algorithm.

Wang, Dali; Berry, Michael W.; Carr, Eric A.; Gross, Louis J.

doi: 10.1177/0037549706068826pmid: N/A

Parallelization of a landscape fish population model (ALFISH) is an important effort towards high performance Across Tropic Level System Simulation (ATLSS) on a computing grid. ALFISH models the impacts of different water management strategies in the South Florida region on the freshwater fish population, providing estimates of the food resource available to wading birds. The parallel ALFISH model delivers similar results to those from a sequential implementation. Compared with the average simulation time of the sequential model, which is about 35 hours, the speed improvement of the parallel model on a symmetric multiprocessor (SMP) is substantial. Using 14 processors, the runtime of the parallel model with static partitioning is less than 4 hours, and that of the parallel model with dynamic load balancing is less than 3 hours.

Sasai, Yoshikazu; Ishida, Akio; Sasaki, Hideharu; Kawahara, Shintaro; Uehara, Hitoshi; Yamanaka, Yasuhiro

doi: 10.1177/0037549706068943pmid: N/A

Physical influences on a marine ecosystem in the open ocean are investigated using a simplified four-component ecosystem model embedded in an eddy-resolving ocean general-circulation model (OGCM). The annual cycle of temperature, nitrate, and phytoplankton in the upper ocean is well reproduced with the climatological monthly mean forcing.A comparison with satellite ocean color data shows that the model is capable of a realistic description of the annual mean and regional patterns of surface chlorophyll.Simulated chlorophyll distribution at the surface shows a pattern influenced by the western boundary current (Kuroshio) and meso-scale eddies.Nitrate distribution in the upper ocean in the northwestern Pacific is mainly controlled by physical processes, especially meso-scale variability, including many anticyclonic and cyclonic eddies, fine-scale fronts, and filaments.The warm-core eddy entrains high-nitrate water from the surrounding filaments, creating conditions for the high production in spring.

Goreaud, F.; Alvarez, I.; Courbaud, B.; de Coligny, F.

doi: 10.1177/0037549706070397pmid: N/A

Spatially explicit individual-based models are used more often in forest modeling, especially because they take into account the influence of the spatial structure on the dynamics. However, they are potentially very sensitive to the initial spatial structure used for a simulation, which can be problematic if the initial state is not known or is simulated in an unrealistic way.The aim of this article is to study this sensitivity to initial spatial structure in the case of the “Mountain” model, an individual-based model of irregular spruce stands implemented in the Capsis platform.To characterize the influence of the initial spatial structure on the dynamics of the model, the authors simulated different initial spatial structures and compared the results of long-term simulations. They showed that the initial spatial structure can highly influence the dynamics of the model, not only during the first cycle of the evolution but also in the very long term in the evolution of the next generations. They also illustrated how some disturbances, such as a periodic gap opening through storms, can modify both the long-term dynamics of the stand and the duration of the influence of the initial spatial structure.