Title page for ETD etd-07062007-155333

Type of Document Dissertation
Author Sable, Shaye Ellen
Author's Email Address ssable1@lsu.edu
URN etd-07062007-155333
Title A Comparison of Individual-Based and Matrix Projection Models Applied to Fish Population and Community Dynamics
Degree Doctor of Philosophy (Ph.D.)
Department Oceanography & Coastal Sciences
Advisory Committee
Advisor Name Title
Kenneth A. Rose Committee Chair
Gregory Stone Committee Member
James H. Cowan, Jr. Committee Member
James P. Geaghan Committee Member
Megan K. Lapeyre Dean's Representative
  • community
  • simulation
  • fish population
  • individual-based model
  • matrix projection model
Date of Defense 2007-06-12
Availability unrestricted
Matrix projection models and individual-based models (IBM) are commonly used for the

analysis and management of fish populations. Matrix models break down the population into

age or stage classes, while IBMs track individuals. I perform a series of quantitative

comparisons between the predictions of the two modeling approaches using the IBM as the

standard of comparison to demonstrate when individual variation, species interactions, and

spatial heterogeneity adversely affect matrix model performance. I first evaluate the matrix

approach for predicting yellow perch population responses when perch are involved in size-specific

predator-prey interactions with walleye. I created density-dependent and stochastic age-structured and stage-within-age matrix models from an Oneida Lake walleye-yellow perch IBM,

and then changed perch survival rates within the matrix models and IBM and compared their

predicted responses. The matrix models simulated yellow perch responses reasonably well when

density-dependent YOY survival was correctly defined. At least 20 years of data (IBM output)

were needed to correctly estimate the density-dependent relationships in the matrix models.

Second, I developed a 2-species matrix model by linking the elements between perch and

walleye matrix models. The 2-species model simulated yellow perch prey responses reasonably

well, but was unable to correctly predict walleye predator responses. Third, I developed a new

IBM that simulated a 6-species tidal marsh community on a fine-scale spatial grid of habitat

cells. The IBM was used to scale individual-level effects of lowered dissolved oxygen and

habitat degradation to population-level responses, and used to estimate relatively simple stage-based matrix models for grass shrimp and gulf killifish populations. Equilibrium analysis of the simple matrix models was insufficient for predicting population responses. This study showed

that stochastic, density-dependent matrix projection models were able to mimic density-

dependent survival processes and species interactions relatively well, while equilibrium analysis of simple matrix models was inadequate. The matrix approach consistently had trouble

estimating density-dependent and inter-specific growth relationships that were important for

accurate model predictions. I recommend the use of IBMs and relatively complicated matrix

models (stage-within-age, stochastic, density-dependent, multispecies) for simulation of fish

population and community dynamics.

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