Notes on Grimm and Railsback Chapter 1,
“Individual-based modeling and ecology”
March 18, 2009
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Why IBM in ecology?
• Compared to physics (atoms), in ecological
systems, entities:
• Grow and develop
• Need resources
• Modify their environment
• Are adaptive
• Seek fitness
• Influence their environment and others and vice
versa
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Sucessful example-Green Woodhoopoe
• RQ: How does a green woodhoope (bird) decide to
migrate in order to achieve social staus sufficient to
reproduce?
• “We cannot of course ask the birds how they decide and
we do not have enough data on individual birds and
their decisions to answer these questions empirically”
• Migration heuristic accounting for age and social rank
better explained population-level group size distributions
better than a random migration rule.
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Sucessful example-beech forests
• Goal was to model late-succession beech forests that
historically covered Northern Europe
• RQ- How large should protected stands be? How
long would they take to establish? What indicators of
“naturalness” of forests should be used?
• Target system-level mosaic patterns and vertical
stand structure
• Use individual tree growth model--well established
• Model produced independent predictions not used for
calibration, could be validated; success attributed to
multiple patterns used for model development
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Successful example: river flow and fish
• How is fish survival affected by river flow?
• Assume that fish select habitat to maximize fitness,
considering both food intake and predation risk
• Applied to study effect of stream turbidity, which
decreases food availability and predation risk
• Model concluded net effects on populations were
negative
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Individual-based ecology, characteristics
• Systems are modeled as collections of individuals
• IBM is the primary modeling tool for IBE
• IBE should be based on theoretical models of individual
behavior, developed from both empirical and theoretical
models, that must reproduce behavior from real-world
systems
• Observed patterns are the main target for model
development and testing
• Models are framed in complexity-theoretic concepts
• Model are implemented via computer simulations
• Field and lab studies
are
forLecture
IBE4 theoretical
Spatial
ABM crucial
H-E Interactions,
Dawn Parker, George Mason University
development
Four criteria for IBM:
• IBMs have to consider growth and development in
some way
• Must be local feedback between individuals and
resource availability
• Individuals must be modeled as discrete entities
(important implications for complex behavior)
• Individuals must be able to differ within age, size, or
stage distributions
Note that these criteria are stronger that those used by
me and other social scientists.
Also note their emphasis on adaptation and fitnessseeking
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Status and Challenges of the IBM
approach
• Grimm found whole less than sum of parts; individual
applications were useful, but group did not further
ecology as a field as much as expected.
• Issues related to pop.ecology theory like persistence,
resilience, and regulation (definitions?) not
addressed.
• Complexity-theoretic issues like self-organization and
emergence not addressed either.
• Applications developed for “pragmatic, not
paradigmatic” reasons.
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Problems cont.
“Most IBMs were:
1. Developed for specific species with no attempt to
generalize results;
2. Rather complex, but lacking specific techniques to
deal with that complexity;
3. Too elaborate to be described completely in a single
paper, making communication of the model to the
scientific community incomplete”
(G-R 2005, chapter 1, p. 16)
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Challenges, cont.
Two closely linked problems have been
underestimated:
• Complexity of IBMs imposes a heavy cost (sound
familiar?)
• Lack of theoretical and conceptual framework leads
to ad-hoc assumptions
• “Do not panic! This book shows us how to meet
these challenges!” (p. 16)
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University
Where do challenges lie?
• Development due to added complexity
• Analysis and understanding
• Communication
• Data requirements
• Uncertainty and error propagation
• Generality
• Lack of standards
Lots of this sounds familiar as well!
Spatial ABM H-E Interactions, Lecture 4
Dawn Parker, George Mason University