According to Google Scholar in August 2015, the products listed here have been cited
over 6300 times.
“Modeling potential river management conflicts between frogs and salmonids” Railsback, S. F., B. C. Harvey, S. J. Kupferberg, M. M. Lang, S. McBain, and H. H. Welsh, Jr.
Canadian Journal of Fisheries and Aquatic Sciences, in press. We describe FYFAM, our new model of river management effects on yellow-legged frog breeding, and use the model to compare unregulated flows and temperatures vs. those managed primarily for salmon populations. The abstract:
Management of regulated rivers for yellow-legged frogs and salmonids exemplifies potential conflicts among species adapted to different parts of the natural flow and temperature regimes. Yellow-legged frogs oviposit in rivers in spring and depend on declining flows and warming temperatures for egg and tadpole survival and growth, whereas salmonid management can include high spring flows and low-temperature reservoir releases. We built a model of how flow and temperature affect frog breeding success. Its mechanisms include adults selecting oviposition sites to balance risks of egg dewatering by decreasing flow versus scouring by high flow, temperature effects on development, habitat selection by tadpoles, and mortality via dewatering and scouring. In simulations of a regulated river managed primarily for salmonids, below-natural temperatures delayed tadpole metamorphosis into froglets, which can reduce overwinter survival. However, mitigating this impact via higher temperatures was predicted to cause adults to oviposit before spring flow releases for salmonids, which then scoured the egg masses. The relative timing of frog oviposition and high flow releases appears critical in determining conflicts between salmonid and frog management.
“Effects of spatial extent on modeled relations between habitat and salmon spawning success” Railsback, S. F., B. C. Harvey, and J. L. White.
Transactions of the American Fisheries Society, in press. The abstract:
We address the question of spatial extent: how model results depend on the amount and type of space represented. For models of how stream habitat affects fish populations, how do the amount and characteristics of habitat represented in the model affect its results and how well do those results represent the whole stream? Our analysis used inSalmo, an individual-based model of salmon spawning, incubation, and juvenile rearing. The model was applied to 12 sites, totaling 4.0 km length, on Clear Creek, California, treating the simulated 4.0 km as a synthetic whole stream. Simulation experiments examined responses of salmon spawning and rearing success to habitat variables such as flow and temperature, when the model included each individual site, all sites, and random combinations of two to nine sites. Some responses, such as temperature effects on egg incubation, were insensitive to spatial extent. Other responses, including effects of flow on production of large juveniles, varied sharply among sites and varied with spatial extent. Most small sites had little effect on overall results, but one small site provided exceptionally good juvenile rearing habitat and strongly affected responses of the entire stream. Larger sites (length > 15 channel widths) in distinct habitat types (e.g., highly disturbed and recently restored) also had strong effects. Including more or longer sites generally increased model representativeness but not consistently. Results highly representative of the entire stream could also be obtained by combining large sites in typical habitat with "hot spots" of especially productive habitat. Finally, sites lower in the watershed appear to be more important to model results and salmon spawning success because more juveniles migrate through them.
“InSTREAM-Gen: modelling eco-evolutionary dynamics of trout populations under anthropogenic environmental change” Ayllón, D., S. F. Railsback, S. Vincenzi, J. Groeneveld, A. Almodóvar, and V. Grimm.
Ecological Modelling, in press.
This paper describes the NetLogo implementation of inSTREAM, the addition of genetic evolution in several trout traits, and the model's simulated response to land use and climate change. The abstract:
Current rates of environmental change are exceeding the capacity of many populations to adapt to new conditions and thus avoid demographic collapse and ultimate extinction. In particular, cold-water freshwater fish species are predicted to experience strong selective pressure from climate change and a wide range of interacting anthropogenic stressors in the near future. To implement effective management and conservation measures, it is crucial to quantify the maximum rate of change that cold-water freshwater fish populations can withstand. Here, we present a spatially explicit eco-genetic individual-based model, inSTREAM-Gen, to predict the eco-evolutionary dynamics of stream-dwelling trout under anthropogenic environmental change. The model builds on a well-tested demographic model, which includes submodels of river dynamics, bioenergetics, and adaptive habitat selection, with a new genetic module that allows exploration of genetic and life-history adaptations to new environments. The genetic module models the transmission of two key traits, size at emergence and maturity size threshold. We parameterized the model for a brown trout (Salmo trutta L.) population at the warmest edge of its range to validate it and analyse its sensitivity to parameters under contrasting thermal profiles. To illustrate potential applications of the model, we analysed the population's demographic and evolutionary dynamics under scenarios of (1) climate change-induced warming, and (2) warming plus flow reduction resulting from climate and land use change, compared to (3) a baseline of no environmental change. The model predicted severe declines in density and biomass under climate warming. These declines were lower than expected at range margins because of evolution towards smaller size at both emergence and maturation compared to the natural evolution under the baseline conditions. Despite stronger evolutionary responses, declining rates were substantially larger under the combined warming and flow reduction scenario, leading to a high probability of population extinction over contemporary time frames. Therefore, adaptive responses could not prevent extinction under high rates of environmental change. Our model demonstrates critical elements of next generation ecological modelling aiming at predictions in a changing world as it accounts for spatial and temporal resource heterogeneity, while merging individual behaviour and bioenergetics with microevolutionary adaptations.
“New predictions from old theory: emergent effects of multiple stressors in a model of piscivorous fish ” Belarde, T. A., and S. F. Railsback.
Ecological Modelling, in press. The abstract:
Predicting cumulative effects is an important challenge of theoretical and management ecology. If a population will be exposed to multiple stressors (e.g., toxins, introduced competitors, climate change), will their cumulative effects be independent and hence multiplicative (the population survival rates due to each stressor can be multiplied together to determine the total reduction in abundance), synergistic (cumulative effects are greater than multiplicative), or antagonistic (stressors offset each other so cumulative effects are less than multiplicative)? Further, the effects of each stressor can vary with such factors as habitat quality, population density, and weather. It is difficult to predict cumulative effects with traditional population-level models because such models must assume the type and strength of stressor interactions a priori, and measuring stressor effects and interactions empirically is rarely practical. Instead, we used an individual-based model in which cumulative effects emerge from how each stressor affects the growth and survival of individuals, and how individuals interact. Our model is in fact based on theoretical concepts explored in the landmark 1980 paper of DeAngelis et al. (Cannibalism and size dispersal in young-of-the-year largemouth bass: experiment and model, Ecological Modelling 8:133-148): in a community of fish that eat each other, initial differences in size among individuals have strong effects on subsequent abundance and size distributions. We model survival and growth of juvenile Colorado pikeminnow (Ptychocheilus lucius) during their first year; these fish are subject to two stressors. The first stressor is a daily cycle of flow fluctuations imposed by an upstream hydroelectric dam; these fluctuations affect habitat area, food supply, and temperature, which then affect juvenile fish growth. Second is an introduced fish species that competes with pikeminnow for food, while both species can prey on each other via the size-based mechanism described by DeAngelis et al. We modeled a range of 30 strengths of these two stressors in each of 28 sites and weather year to produce 840 scenarios, using 7 weather year datasets as replicates. Emergent cumulative effects were multiplicative in 69% of these scenarios, synergistic in 22%, and antagonistic in 9%. Therefore, any a priori assumption about stressor interactions would be wrong in many situations. Synergistic effects were most common in deeper and larger habitats favorable to the introduced species; antagonistic effects were most common in smaller habitats where the introduced species had low growth because flow fluctuations further reduced the small food supply.
“The role of the geophysical template and environmental regimes in controlling stream-living trout populations. ” Penaluna, B. E., S. F. Railsback, J. B. Dunham, S. Johnson, R. E. Bilby, and A. E. Skaugset.
Canadian Journal of Fisheries and Aquatic Sciences, in press.
“Making predictions in a changing world: the benefits of individual-based ecology.” Stillman, R. A., S. F. Railsback, J. Giske, U. Berger, and V. Grimm.
BioScience 65: 140-150, 2015.
Our trout models and Richard Stillman's shorebird models illustrate how long-term individual-based modeling programs can make useful predictions of how management affects ecological resources. The abstract:
Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions-fitness maximization by individual organisms-is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research.
“Effects of land use on bird populations and pest control services on coffee farms” Railsback, S. F. and M. D. Johnson.
Proceedings of the National Academy of Sciences USA 111:6109-6114, 2014. DOI: 10.1073/pnas.1320957111.
This paper analyzes the coffee farm model described below (Railsback & Johnson 2011) to draw conclusions about how land management affects bird populations, pest infestation, and coffee production. The abstract:
Global increases in both agriculture and biodiversity awareness raise a key question: should cropland and biodiversity habitat be separated, or integrated in mixed land uses? Ecosystem services by wildlife make this question more complex. For example, birds benefit agriculture by preying on pest insects, but other habitat is needed to maintain the birds. Resulting land use questions include: what areas and arrangements of habitat support sufficient birds to control pests, whether this pest control offsets the reduced cropland, and what the benefits are of "land sharing" (mixed cropland and habitat) vs. "land sparing" (separate areas of intensive agriculture and habitat). Such questions are difficult to answer using field studies alone, so we use a simulation model of Jamaican coffee farms, where songbirds suppress the coffee berry borer (CBB). Simulated birds select habitat and prey in five habitat types: intact forest, trees (including forest fragments), shade coffee, sun coffee, and unsuitable habitat. The trees habitat type appears especially important: it provides efficient foraging and roosting sites near coffee plots. Small areas of trees (but not forest alone) could support enough birds to suppress CBB in sun coffee; the degree to which trees are dispersed within coffee had little effect. In simulations without trees, shade coffee supported sufficient birds to offset its lower yield. High areas of both trees and shade coffee reduced pest control because CBB was less often profitable prey. Because of the pest-control service by birds, land sharing was predicted more beneficial than land sparing in this system.
“Trait-mediated trophic interactions:
is foraging theory keeping up?” Railsback, S. F. and B. C. Harvey.
Trends in Ecology & Evolution 48: 119-125, 2013.
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.
“Facultative anadromy in salmonids: linking habitat, individual life history decisions, and population-level consequences.” Railsback, S.F., B. C. Harvey, and J. L. White.
Canadian Journal of Fisheries and Aquatic Sciences 71:1270-1278, 2014. The abstract:
Modeling and management of facultative anadromous salmonids is complicated by their ability to select anadromous or resident life histories. Conventional theory for this behavior assumes individuals select the strategy offering highest expected reproductive success but does not predict how population-level consequences such as a stream's smolt production emerge from the anadromy decision and habitat conditions. Our individual-based population model represents juvenile growth, survival, and anadromy decisions as outcomes of habitat and competition. In simulation experiments that varied stream growth and survival conditions, we examined how many simulated juveniles selected anadromy vs. residence and how many of those choosing anadromy survived until smolting. Due to variation in habitat and among individuals, the within-population frequency of anadromy changed gradually with growth and survival conditions instead of switching abruptly. Higher predation risk caused more juveniles to select anadromy but fewer survived long enough to smolt. Improving growth appears a much safer way to increase smolt production compared to reducing freshwater survival. Smolt production peaked at high growth and moderately high survival, conditions that also produced many residents.
A pre-publication copy is here.
“Feeding modes in stream salmonid population models: Is drift feeding the whole story?” Harvey, B. C. and S. F. Railsback.
Environmental Biology of Fishes 97.5: 615-625, 2014.
This paper resulted in our participation at an American Fisheries Society symposium
on drift-feeding models. It draws two important conclusions. First, our inSTREAM
trout model successfully predicted differences in adult trout growth and how growth
was affected by stream flow, in a small stream. Second, the model was more accurate
when "search" feeding was included as an alternative to drift feeding; search feeding
appears to be important at least in low-flow situations.
“Contrast of degraded and restored stream habitat using an individual-based salmon model” Railsback, S. F., M. Gard, B. C. Harvey,
J. L. White, and J. K. H. Zimmerman.
North American Journal of Fisheries Management 33: 384-399, 2013.
This is one product of the inSALMO version of our salmonid IBMs. The abstract:
Stream habitat restoration projects are popular, but can be expensive, and can be difficult to evaluate. We describe inSALMO, an individual-based model designed to predict habitat effects on freshwater life stages (spawning through juvenile outmigration) of salmon. We used inSALMO in a demonstration evaluation of habitat restoration on Clear Creek, California, by simulating production of total and large (> 5 cm fork length) Chinook salmon Oncorhynchus tshawytscha outmigrants at a restored and an unrestored site. The calibrated model reproduced observed redd locations and outmigrant timing and size. In simulations, the restored site had much higher production of fry that established and grew before outmigration; its habitat appears to provide high survival and positive growth due to moderate velocities, shallow depths, and cover for feeding and hiding. However, the restored site did not produce more total outmigrants because at both sites spawning gravel was sufficient and the vast majority of fry moved downstream soon after emergence. Simulations indicated that at both sites increasing food and cover availability could further increase production of large, but not total, outmigrants; while spawning gravel, temperature, and flow appear near-optimal already. Further gravel addition was predicted to increase total fry production but have little or even negative effect on production of large outmigrants, illustrating that actions benefitting one life stage can negatively affect others. The model predicted that further enhancements (e.g., in cover availability) would be more beneficial at the restored site than at the unrestored site; restoration efforts may be most effective when concentrated in "hot spots" with good habitat for growth and predator-avoidance as well as spawning. In contrast to the traditional notion of "limiting factors", the model indicates that multiple factors have strong effects. The model, while uncertain, provided more understanding of restoration effects than can field studies alone and appears useful for designing projects to meet specific restoration objectives.
“The Evolution of Agent-based Simulation Platforms:
A Review of NetLogo 5.0 and ReLogo” Lytinen, S. L. and S. F. Railsback.
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.
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.
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
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
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.
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
"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. Jřrgensen, 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. Vabř,
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
"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,
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.
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
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.
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.
engineering considerations for individual-based models", G. E. P.
Ropella, S. F. Railsback, and S. K. Jackson (2002). Natural Resource
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.
"results": the pattern-oriented approach to analyzing natural
systems with individual-based models', S. F. Railsback (2001). Natural
Resource Modeling 14:
from Complex Adaptive Systems as a framework for individual-based modeling",
S. F. Railsback (2001). Ecological Modelling 139: 47-62. The pre-publication abstract
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.
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
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.
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).
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.
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.
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).
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).
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".
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.
Software for Individual-based Fish Models" presented by Steve Jackson,
Steve Railsback, and Glen Ropella at SwarmFest99
Thoughts on Individual-based Fish and Wildlife Models" presented
by Steve Railsback at SwarmFest99
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.
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.