Individual-Based Ecological Modeling at Humboldt State University

Research on the use of individual-based models (IBMs) for applied and theoretical ecology is affiliated with the Mathematical Modeling Program, HSU Mathematics Department. This research is a collaboration of mathematicians, ecologists and biologists, environmental engineers, and software professionals. See below for our research goals.

Visit this new site to learn more about Humboldt State's Mathematical Modeling graduate program!

What's New

• New Individual- and agent-based modeling textbook. Steve Railsback and Volker Grimm are preparing a new text on individual-based (or "agent-based") modeling in science. The text is designed for courses in which instructors as well as students are new to this kind of modeling. The book is not specific to ecology, but general to all scientific fields. It teaches basic concepts of modeling, the design of individual-based models, how to program models in the NetLogo platform, and analysis of models to solve scientific problems and develop theory. Draft chapters are now available for download and evaluation at the book's web site.
  
  
• Summer short courses in individual- and agent-based modeling, 2008-2010. The Institute of Forest Growth and Forest Computer Sciences of Technical University Dresden, Germany, received funding to conduct one-week intensive courses in individual- and agent-based simulation modeling, in the summers of 2008, 2009, and 2010. The courses are taught in English at a lovely small town in the "Switzerland of Saxony" park area near Dresden. Instructors will include Uta Berger of TU Dresden, Volker Grimm, and Steve Railsback of our Humboldt State program. See the course web site for information.
  
  
• inSTREAM used in McCloud River Project instream flow studies. Our individual-based trout model was used as one of several instream flow assessment methods in the regulatory process to update the operating license of the McCloud River hydroelectric project. This was the first completely non-research application of inSTREAM. The model predicted that higher instream flows in summer could increase the relative abundance of brown vs. rainbow trout, but high winter flows could have the opposite effect.
  
  
• inSTREAM training opportunities. We occasionally provide training in our inSTREAM individual-based trout model. Classes are usually but not always here in Arcata. Contact Steve Railsback if you are interested.
  
  
• Evaluation of nonlinear, interactive effects of temperature, turbidity, and channel shape on trout populations. Bret Harvey conducted a simulation analysis of whether these three stressors have cumulative effects on trout populations that are stronger than we would expect if they acted independently. The study recently was published in Fisheries. See the Products and Publications page for details.
  
  
• Execution time improvements for inSTREAM completed and published. We implemented a minor change in formulation that reduces execution time of our individual-based trout model by about one third, with negligible effect on results. See the inSTREAM page for details.
  
  
• inSTREAM, our individual-based Stream Trout Research and Assessment Model, is available in new versions. Version 4.2 is designed for public use; the release includes software, example input, and a new, complete documentation set. Two other versions support alternative hydraulic simulation methods; one is inSTREAM-2D, which uses two-dimensional hydrodynamic modeling. See the inSTREAM page for additional information and downloads.
  
  
• Sensitivity Analysis Methods for large IBMs developed. For his MS thesis, Paul Cunningham developed a three-phase strategy for parameter sensitivity analysis of large, complex IBMs and demonstrated it on inSTREAM. A draft publication on the strategy is on our publications and products page.
  
  
• Trait-mediated indirect interactions and non-consumptive effects emerge from our approach to modeling adaptive behavior. TMIIs and NCEs are exciting new areas of ecological research because they illustrate the effects of individual adaptive behavior on population and community dynamics. In a new manuscript, we describe the approach to theory of adaptive behavior we use and illlustrate its ability to reproduce a wide range of TMIIs and NCEs observed in empirical experiments. See the publications and products page.
  
  
• "Pattern-oriented modeling of agent-based complex systems: lessons from ecology" appears in Science. This paper by Volker Grimm and others (including Steve Railsback) discusses the use of individual-based models and observed patterns in studying complex systems. Patterns can be used to design models, test theory for how system phenomena emerge from individual traits, and parameterize models. See our publications and products page for the citation and access to this paper.
  
  
• "Pattern-oriented modeling of agent-based complex systems: lessons from ecology" appears in Science.
  
  

Goals:

• Developing a conceptual and theoretical basis for individual-based ecology. Differential calculus provides the conceptual basis for classical ecological models, but IBMs lack such a basis. We find the new science of Complex Adaptive Systems to be a fruitful source of concepts for thinking about and designing IBMs.
• Applying fish IBMs to river management issues. We developed several generations of stream salmonid IBM to address such management questions as: How do the magnitude and timing of instream flow releases affect populations? What are the cumulative effects of changes in flow and temperature on fish populations? What effects do habitat alterations (e.g., loss of pools, increased turbidity), competition, predation, and habitat connectivity have on population dynamics?
• Using IBMs to test and develop ecological theory. We use IBMs as 'virtual ecosystems' for testing ecological theory and linking behavioral ecology to population ecology.
• Developing software and software engineering approaches for IBMs. Software engineering is much more important for IBMs than for other ecological models. We develop software engineering guidance, flexible and re-usable code for stream fish models, and a library of Swarm-based code for IBMs.
• Integrating individual-based approaches in ecological and modeling education. We integrate IBMs in ecological modeling courses at HSU, and gladly offer software and guidance to instructors at other institution

 

WebMASTER:  krf20@humboldt.edu
Last Updated:  23 Dec. 2009