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According to Google Scholar, the products listed here have been cited over 2000 times.
Please email Steve Railsback for papers not available here.

“Trait-mediated trophic interactions: is foraging theory keeping up?” Railsback, S. F. and B. C. Harvey. Trends in Ecology & Evolution, Available online 17 September 2012, ISSN 0169-5347, 10.1016/j.tree.2012.08.023. Available at Science Direct. This review resulting from our work developing foraging theory for individual-based models. The abstract: Many ecologists believe that there is a lack of foraging theory that works in community contexts, for populations of unique individuals each making trade-offs between food and risk that are subject to feedbacks from behavior of others. Such theory is necessary to reproduce the trait-mediated trophic interactions now recognized as widespread and strong. Game theory can address feedbacks but does not provide foraging theory for unique individuals in variable environments. "State- and prediction-based theory" (SPT) is a new approach that combines existing trade-off methods with routine updating: individuals regularly predict future food availability and risk from current conditions to optimize a fitness measure. SPT can reproduce a variety of realistic foraging behaviors and trait-mediated trophic interactions with feedbacks, even when the environment is unpredictable.
“The Evolution of Agent-based Simulation Platforms: A Review of NetLogo 5.0 and ReLogo” Lytinen, S. L. and S. F. Railsback. To appear in Proceedings of the Fourth International Symposium on Agent-Based Modeling and Simulation, at the 21st European Meeting on Cybernetics and Systems Research (EMCSR 2012), Vienna, Austria, April 2012. This paper compares the programming experience, documentation, and execution speed of two software platforms. NetLogo has continued to steadily increase in suitability for scientific applications since our 2006 review in Simulation (below). ReLogo is a new product of the Repast program; it implements NetLogo's primitives so they can be used in models programmed in the languages Groovy or Java, within the Eclipse development environment. Overall we found ReLogo to be substantially more cumbersome to use, lacking in documentation, and slower in execution than NetLogo. It was not clear how ReLogo could combine NetLogo-like code with Repast's libraries that are more specialized or general than NetLogo. This review is available here.
“Agent-based and individual-based modeling: A practical introduction” (textbook), Railsback, S. F., and V. Grimm. Princeton University Press, Princeton, New Jersey. 2012. This is the first hands-on textbook for learning individual-based modeling. It uses the NetLogo modeling platform. More information here.
“Pattern-oriented modeling of bird foraging and pest control in coffee farms”, Railsback, S. F., and M. D. Johnson. Ecological Modelling 222:3305-3319, 2011. This paper describes development and testing of an IBM of pest insect suppression by migratory songbirds on coffee plantations in Jamaica. (The model's interface is shown here.) The paper (1) describes nine patterns observed in the field by Matt Johnson and his students, which characterize bird foraging and pest consumption; (2) describes the IBM designed so these patterns could emerge from it; and (3) tests four alternative theories for bird foraging behavior and identifies one that best reproduces the observed patterns. Some classical foraging theory is shown not to be useful at the level of realism of this model.
“An individual based larval dispersion model for the Hawaiian hawskbill sea turtle in the Hawaiian archipelago” (MS thesis), Falbo, K. R., 2011. A summary and the thesis are here.
“An individual-based model for the dispersal of the South African wild dog population in the KwaZulu-Natal Province” (MS thesis), Arnold, E. G., 2010. A summary and the thesis are here.
“ Importance of fish behaviour in modelling conservation problems: food limitation as an example”, Railsback, S. F., and B. C. Harvey. Journal of Fish Biology 79:1648-1662, 2011. This paper, based on a keynote talk by S. Railsback at the 2011 meeting of the Fisheries Society of the British Isles, uses inSTREAM to investigate the concept of "food limitation": at what level of food availability does a fish population no longer benefit from more? In the simulation experiments, when fish were assumed to use behavior to trade off feeding and predation avoidance, the traditional notion of food limitation was completely contradicted.
“Effects of passage barriers on demographics and stability properties of a virtual trout population”, Harvey, B. C., and S. F. Railsback. River Research and Applications, DOI: 10.1002/rra.1574. 2011. Do barriers to upstream passage (low-head dams; culverts) affect trout population characteristics such as abundance and frequency of local extinction? How do such effects depend on the density and location of barriers? This simulation study, using inSTREAM to represent a large network of small to medium-sized stream reaches, produced a few surprising answers.
“Pattern-oriented modelling: a 'multiscope' for predictive systems ecology”, Grimm, V., and S. Railsback. Philosophical Transactions of the Royal Society B 367:298-310, 2012. This paper (based on a presentation to the Royal Society by V. Grimm) provides an excellent overview of the "pattern-oriented modeling" strategy for designing and testing IBMs.
“inSTREAM: the individual-based stream trout research and environmental assessment model”, Railsback, S. F., B. C. Harvey, S. K. Jackson, and R. H. Lamberson. General Technical Report PSW-GTR-218, U. S. Department of Agriculture Forest Service, Pacific Southwest Research Station, Albany, California. 254 pages. This document can be downloaded here.
"Exploring the persistence of stream-dwelling trout populations under alternative real-world turbidity regimes with an individual-based model", Harvey, B. C., and S. F. Railsback. Transactions of the American Fisheries Society 138: 348-360, 2009. Laboratory studies have shown that turbidity reduces the ability of trout to see and capture food, yet also reduces risk because the trout are more difficult for predators to see. What are the overall consequences of these opposing effects on trout populations? Sub-lethal effects of turbidity are difficult to evaluate, in part because turbidity varies widely and in part because effects on mortality, growth, and reproduction are very difficult to measure in rivers. We used the individual-based trout model, in combination with laboratory studies, to examine these issues and predict population-level consequences of individual-level turbidity effects. This paper is available from Bret Harvey's web site.
“Model the real, artificial, or stylized iguana? Artificial life and adaptive behavior can be linked through pattern-oriented modeling”, Grimm, V., and S. F. Railsback. Adaptive Behavior 17(4): 309-312, 2009. This invited commentary muses on the applicability of "artificial life" (computer simulations that are life-like but not explicitly related to any particular organism) to biological research. Pattern-oriented modeling (see Grimm et al. 2005 below) provides a way to learn about the adaptive behavior of real organisms from artificial life studies.
“Estimating multi-factor cumulative watershed effects on fish populations with an individual-based model”, Harvey, B. C., and S. F. Railsback. Fisheries 32(6): 292-298, June, 2007. This paper uses inSTREAM to investigate cumulative impacts and interactions among three stressors: elevated wet-season turbidity, elevated dry-season temperature, and loss of pools. Simulated effects were non-linear and non-additive: at high stress levels, cumulative effects were worse than predicted by assuming each stress acts alone. Such interacting effects are especially interesting for temperature and turbidity because they operated at different times of year. This paper is available from Bret Harvey's web site.
"Adaptive Behavior in the Face of Uncertainty: Prediction-based Theory Reproduces Trait-mediated Trophic Interactions" Railsback, S. F., and B. C. Harvey. Manuscript in preparation. IBMs are natural for representing effects of individual behaviour on population and community ecology, but to be productive IBMs need general theory for how individuals make adaptive decisions when conditions are variable, unpredictable, and subject to feedback from behaviour. We describe "state- and prediction-based theory" (SPT), which resembles state-based dynamic modelling except that individuals use a rough prediction of future conditions to identify good choices. An IBM using SPT reproduced a variety of non-consumptive effects and trait-mediated indirect interactions that characterise effects of behaviour on food webs. Examples include: as predation risk increased, anti-predator behaviour limited mortality but produced strong non-consumptive effects on prey and their food resource; as food was reduced, predation mortality increased; and predator avoidance strongly affected density dependence in growth. Contact Steve Railsback for a draft.
“A strategy for parameter sensitivity and uncertainty analysis of individual-based models”, Railsback, S. F., P. M. Cunningham, and R. H. Lamberson. Manuscript in preparation. Traditional parameter sensitivity and uncertainty methods are infeasible for large, complex IBMs. This paper describes a strategy for making analysis adequately comprehensive yet computationally feasible. The phases include individual-parameter sensitivity analysis; pairwise analysis of interactions among key parameters; and analysis of the robustness of management results from a model to uncertainty in key parameters. A draft is here.
"Pattern-oriented modeling of agent-based complex systems: lessons from ecology", Grimm, V., E. Revilla, U. Berger, F. Jeltsch, W. M. Mooij, S. F. Railsback, H.-H. Thulke, J. Weiner, T. Wiegand, and D. L. DeAngelis (2005). Science 310:987-991. Individual-based (or agent-based) models are an important tool for understanding complex systems, but science still needs a general strategy for designing, testing, and learning from such bottom-up models. This paper reviews examples of a strategy we call "pattern-oriented modeling". Using a variety of observed patterns helps scientists design and parameterize IBMs and to develop "algorithmic" theory for how system properties arise from characteristics of individuals and their environment. There is a link to this paper from Volker Grimm's web site.
"Agent-based simulation platforms: review and development recommendations", S. F. Railsback, S. L. Lytinen, and S. K. Jackson (2006). Simulation 82: 609-623. Which software platform is best for your individual-based model? This article reviews the most popular software platforms for individual- and agent-based modeling: MASON, NetLogo, Repast, and the Objective-C and Java versions of Swarm. The primary basis of the review is the authors' experience implementing a series of example models (available at Steve Lytinen's site) and teaching several platforms. The paper also compares the execution speed of the example models implemented in the different platforms. Conclusions include recommendations for future development of platforms for agent-based simulation. A pre-publication version is here.
"A standard protocol for describing individual-based and agent based models", Grim, V., U. Berger, F. Bastiansen, S. Eliassen, V. Ginot, J. Giske, J. Goss-Custard, T. Grand, S. Heinz, G. Huse, A. Huth, J. U. Jepsen, C. Jørgensen, W. M. Mooij, B. Müller, G. Pe'er, C. Piou, S. F. Railsback, A. M. Robbins, M. M. Robbins, E. Rossmanith, N. Rüger, E. Strand, S. Souissi, R. A. Stillman, R. Vabø, U. Visser, and D. L. DeAngelis (2006). Ecological Modeling 198: 115-126. Individual-based models are much more difficult to describe and understand than are simple equation-based models. This paper addresses this problem by proposing a standard format for describing IBMs. The paper's appendices include descriptions of about 20 IBMs in the standard format
"How does individual behavior affect population resilience and stability in virtual trout?", S. F. Railsback and B. C. Harvey. Presentation at the 2006 Ecological Society of America meeting, August 7-11, Memphis. This paper was presented in the symposium Revisiting the "stability" icon: Upstart approaches to modeling resilience, organized by Volker Grimm, Donald DeAngelis, Uta Berger, and Steve Railsback.
"A sensitivity analysis of an individual-based trout model", P. M. Cunningham. Presentation at SwarmFest 2006, the Swarm Development Group agent-based modeling conference, July 23-24, University of Notre Dame.
"Juvenile Salmon Movement through the Sacramento-San Joaquin Delta: Challenges in Using Field Data to Validate Models", A. M. Dodd. Poster presentation at the 2006 World Conference on Natural Resource Modeling, June 25-28, Norwegian School of Economics and Business Administration. Poster available here.
"Hydraulic simulations for regional fish modeling", G. P. Butcher and M. A. Parrish (2006). MS thesis, Department of Mathematics, Humboldt State University. Garth Butcher and Mark Parrish develop an approach and models for synthesizing site-specific to inSTREAM (two-dimensional channel shapes; relationships for how cell depth and velocity vary with flow; cell habitat variables) to represent any location within a watershed stream network. The approach uses widely available data, including stream habitat surveys. These methods were used to examine how sensitive inSTREAM is to site-specific input, and to synthesize 99 simulation sites throughout a watershed for regional impact assessment. The thesis is here (PDF, 3.6 MB).
"Tests of theory for diel variation in salmonid feeding activity and habitat use", S. F. Railsback, B . C. Harvey, J. Hayse, and K. LaGory (2005). Ecology 86:947-959. Can we model how individual animals decide whether to forage during the day or at night, and what habitat to use during day vs. night? This paper is an example of individual-based ecological theory, developed using pattern-oriented analysis. The theory for individual decision-making is tested by how well it reproduces, in an individual-based model, a wide variety of patterns observed in real animals at the individual and population levels. Available as PDF here.
Natural Resource Modeling special issue on individual-based models, now available. This issue contains papers from all speakers in our special symposium at the 2000 Ecological Society of America conference. Publication is in book format, with a price of $25. The Table of Contents and Introduction of this book, along with purchasing information, are available here
"What can habitat preference models tell us? Tests using a virtual trout population", S. F. Railsback, H. B. Stauffer, and B. C. Harvey (2003). Ecological Applications 13:1580-1594. What do empirical observations of habitat selection (e.g., animal density) tell us about habitat quality? Which is a better predictor of population response to habitat alteration - an empirical model of density as a function of habitat, or a mechanistic understanding of how intrinsic habitat quality varies with habitat? In this paper we use our stream trout IBM as a virtual ecosystem to address these questions, with surprising results. The paper (PDF) is here.
"Analysis of habitat selection rules using an individual-based model ", S. F. Railsback and B. C. Harvey (2002). Ecology 83: 1817-1830. Available from Redwood Sciences Lab on-line publications. Digital appendices, including description of the trout IBM and animations of simulation experiments, are published in Ecological Archives here.
"Software engineering considerations for individual-based models", G. E. P. Ropella, S. F. Railsback, and S. K. Jackson (2002). Natural Resource Modeling 15: 5-22.
"Population-level analysis and validation of an individual-based cutthroat trout model", S. F. Railsback, B. C. Harvey, R. R. Lamberson, D. E. Lee, N. J. Claasen and S. Yoshihara (2002). Natural Resource Modeling 15: 83-110.
'Getting "results": the pattern-oriented approach to analyzing natural systems with individual-based models', S. F. Railsback (2001). Natural Resource Modeling 14: 465-474.
"Concepts from Complex Adaptive Systems as a framework for individual-based modeling", S. F. Railsback (2001). Ecological Modelling 139: 47-62. The pre-publication abstract is here.
"Movement rules for individual-based models of stream fish", S. F. Railsback, R. H. Lamberson, B. C. Harvey, and W. E. Duffy (1999). Ecological Modelling 123: 73-89, 1999. Available from Redwood Sciences Lab on-line publications.
"Modelling changes in migration patterns of herring: collective behaviour and numerical domination", Geir Huse, Steve Railsback, and Anders Fernø (2002). Journal of Fish Biology 60: 571-582. This paper uses simulations from our fish schooling simulator to pose emergent behavior from (a) schooling and (b) directed movement by a few individuals as an explanation for major changes in migration patterns observed in herring. An abstract is on the fish schooling simulator page. Contact Dr. Huse at the Institute of Marine Resources, Bergen, Norway, for additional information.
"Fish populations as complex adaptive systems", Geir Huse and Steve Railsback. Draft Manuscript. This paper discusses the new science of Complex Adaptive Systems and its application to understanding population ecology. It provides an introduction to key concepts of CAS and examples of how these concepts could change how we study marine and freshwater fisheries. This paper is the primary product of Dr. Huse's visit to HSU in the fall of 2000.
"Complex Adaptive Systems meets the real world: Making agent-based simulation work for ecological management and research". This seminar on our methods for building, testing, and doing science with individual-based models was presented by Steve Railsback to the Santa Fe Institute and the Center for Nonlinear Studies at Los Alamos National Laboratory. Download the presentation slides here (Acrobat format; 1330 kb).
"Individual-based Model Formulation for Cutthroat Trout, Little Jones Creek, California", Steve Railsback and Bret Harvey (2001). General Technical Report PSW-GTR-182, Pacific Southwest Research Station, Forest Service, U. S. Department of Agriculture, Albany, California. This Forest Service research report documents the full formulation of the Little Jones Creek trout model. It includes more detail than previous reports on our modeling philosophy, field methods, and future research priorities. The report is available in part or whole from this Forest Service site.
"Advancing the Individual-based Modeling Approach: New Tools and Concepts ". Special symposium at the Ecological Society of America annual meeting, Snowbird, Utah, August 10, 2000. We organized this symposium, which presented progress on theoretical and software aspects of individual-based modeling. A special issue of the journal Natural Resource Modeling (see above) will include papers from the symposium. The symposium handout "References on Complex Adaptive Systems, Artificial Life, and Individual-based Modeling" is here.
Presentations at SwarmFest 2002, the annual Swarm users conference, March 29-31, Seattle, Washington. Steve Railsback presented several examples of using individual-based models to test ecological theory. Steve Railsback and Tamara Grand presented an ecological perspective in a discussion of how agent-based simulation can contribute to theory in ecological and social sciences; download the presentation slides (Acrobat; 280 kB).
Presentations at SwarmFest 2001, the annual Swarm users conference, April 28-30, Santa Fe, New Mexico. Steve Jackson presented concepts for implementing simulations with multiple model swarms (separate models with differing time and space scales, and agents that pass among models). Steve Railsback led a panel discussion on publication of research based on agent-based simulation; download the presentation slides (Acrobat; 270 kB).
Presentations at SwarmFest 2000, March 11-13, Utah State University. Steve Jackson presented our method for automated experiment management (generating replicate simulations and scenario comparisons) in a discussion of alternative approaches. Steve Railsback presented the paper "Getting 'Results': The Pattern-oriented Approach to Analyzing Complex Systems with Agent-based Models".
"Individual-based Models: Progress Toward Viability for Fisheries Management", S. F. Railsback, R. H. Lamberson, and S. Jackson. Presentation at Spatial Processes and Management of Fish Populations, 17th Lowell Wakefield Symposium, Anchorage, Alaska, October 1999.
"Swarm Software for Individual-based Fish Models" presented by Steve Jackson, Steve Railsback, and Glen Ropella at SwarmFest99
"Emerging Thoughts on Individual-based Fish and Wildlife Models" presented by Steve Railsback at SwarmFest99
"Tools for Individual-based Stream Fish Models", report prepared by Steve Railsback and Steve Jackson. EPRI TR-114006, Electric Power Research Institute, Palo Alto CA, 1999. This document was developed in conjunction with the software to provide CIFSS users with guidance on building, testing, and using models. The report documents our conceptual approach to IBMs, and contains a complete user's guide to our trout model software. It outlines the software's structure and provides guidance on formulating models, implementing changes in model formulation in the CIFSS software, building input files, running and testing models, and conducting research and management experiments with CIFSS models.
"California Individual-based Fish Simulation System, Trout Instream Flow Model Formulation", Report prepared by Steve Railsback, Bret Harvey, Steve Jackson, Roland Lamberson, and Walt Duffy. This report documents the formulation of our first stream trout model, including how we simulate stream habitat and trout spawning and reproduction, movement, foraging and growth, and mortality. August, 1999.
"A Swarm-based System for Developing Individual-based Fish Models", proceedings of the 1999 EcoHydraulics conference, Salt Lake City, Utah. Available upon request.