The comparison of four dynamic systems-based software packages: Translation and sensitivity analysis
Environmental Modeling and Software, 21, 1491-1502, 2006
Abstract: Dynamic model development for describing complex ecological systems continues to grow in popularity. For both academic research and project management, understanding the benefits and limitations of systems-based software could improve the accuracy of results and enlarge the user audience. A Surface Wetness Energy Balance (SWEB) model for canopy surface wetness has been translated into four software packages and their strengths and weaknesses were compared based on ‘novice’ user interpretations. We found expression-based models such as Simulink and GoldSim with Expressions were able to model the SWEB more accurately; however, stock and flow-based models such as STELLA, Madonna, and GoldSim with Flows provided the user a better conceptual understanding of the ecologic system. Although the original objective of this study was to identify an ‘appropriate’ software package for predicting canopy surface wetness using SWEB, our outcomes suggest that many factors must be considered by the stakeholders when selecting a model because the modeling software becomes part of the model and of the calibration process. These constraints may include user demographics, budget limitations, built-in sensitivity and optimization tools, and the preference of user friendliness vs. computational power. Furthermore, the multitude of closed proprietary software may present a disservice to the modeling community, creating model artifacts that originate somewhere deep inside the undocumented features of the software, and masking the underlying properties of the model.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).