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“inSTREAM: the individual-based
stream trout research and environmental assessment model”, Railsback,
S. F., B. C. Harvey, S. K. Jackson, and R. H. Lamberson. Submitted
for publication as a General Technical Report, USDA Forest Service, Pacific
Southwest Research Station, Albany, California. See the inSTREAM
page to download a draft.
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“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.
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"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.
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“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.
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"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.
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"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.
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"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
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“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.
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“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.
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"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.
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“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).
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"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.
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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
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"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.
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"Elevated
turbidity reduces abundance and biomass of stream trout in an individual-based
model", B. C. Harvey and S. F. Railsback. In preparation. 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 notoriously
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 to examine
these issues, using it to predict population-level consequences of individual-level
turbidity effects. The draft submitted to Canadian Journal of Fisheries
and Aquatic Sciences is here.
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"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.
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"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.
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"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.
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'Getting
"results": the pattern-oriented approach to analyzing natural
systems with individual-based models', S. F. Railsback (2001). Natural
Resource Modeling 14:
465-474.
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"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.
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"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.
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"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.
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"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.
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"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).
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"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.
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"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.
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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).
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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).
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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".
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"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
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"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.
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"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.
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"A
Swarm-based System for Developing Individual-based Fish Models",
proceedings of the 1999 EcoHydraulics conference, Salt Lake City,
Utah. Available upon request.