Final Report to the National Science Foundation on Grant BIR-9318160 to
The University of Tennessee, Knoxville
Parallel Processing for Individual-Based Ecological Models
Submitted by: Louis J. Gross (gross@tiem.utk.edu)
The Institute for Environmental Modeling and Departments of Ecology
and Evolutionary Biology and Mathematics University of Tennessee,
Knoxville, TN 37996-1610
July 24, 1997
Part II - Summary of Completed Project
Individual-based models in ecology track the behavior, growth and
reproduction of many individuals in a population or community,
requiring substantial computational resources for which parallelization
methods can be appropriate. This project dealt with three types of
ecological models. For a spatially-explicit rule-based model of
white-tailed deer and Florida panther in South Florida, which tracks
the behavior of individual organisms on realistic landscapes, we
developed parallel implementations using a 32 processor Connection
Machine CM-5, a 4000 processor Maspar MP-2, and a network of
workstations using the Message Passing Interface MPI. A second model
investigated was for a structured population tracking the dynamics of
many cohorts of individuals within the populations making up a
community. As an example, a Daphnia model was linked to a fish model,
and parallel implementations were developed using the CM-5, Parallel
Virtual Machine (PVM) run over a network of workstations, and a 40
processor IBM SP-2. A third model involved a community of mussel
species along linear arrays of cells representing different spatial
cells of a river, implemented on the MP-2. In all cases, a general
result was that parallel implementations require different underlying
biological assumptions than those used in serial versions of the
models, and thus do not necessarily produce exactly the same model
behavior as a serial implementation.
Part III - Technical Information
Investigators and their affiliations:
L. J. Gross, T.G. Hallam, H-K. Luh and S. Ramachandramurthi, The
Institute for Environmental Modeling, UTK;
D. DeAngelis, Department of Biology, University of Miami;
M. Leuze, Joint Institute for Computational Science, UTK;
M. Berry, Computer Science Department, UTK;
M. McKinney, Mathematics Department, NC State Univ.;
C. Abbott and L. Mellott, Grad Students, Computer Science
Department, UTK;
J. Nichols, Grad Student, Mathematics Department, UTK;
H-L. Lee, Grad Student, Ecology Program, UTK.
The award period for this project was initially 5/94-4/96 and was
extended to 4/97. Over the time period of the award, it has supported
in part the following individuals on post-doctoral or student research
assistant positions:
Dr. Hang-Kwang Luh, Ph.D. Zoology. Research Assistant Professor, August
1994-September 1996 (currently on staff of the Entymology Department,
Oregon State University)
Dr. Siddharthan Ramachandramurthi, Ph.D. Computer Scinece. Research
Assistant Professor, August 1994-September 1996 (currently on the staff
of LSI Logic, Inc., Boston, MA)
Dr. Hooi-Ling Lee, Ph.D. Ecology, Graduate Research Assistant, August
1994 - August 1996 (currently in a visiting position at University
Sains Malaysia)
Catherine Abbott, M.S. Computer Science, Graduate Research Assistant,
December 1994 - August 1995 (currently working for Resource Technology,
Longwood, FL)
John Dempsey, Graduate Research Assistant, August 1994 - November 1994
(currently pursuing M.S. in Computer Science at Univ. of Albany)
Linda Mellott, M.S. Computer Science, Graduate Research Assistant,
August 1995 - December 1996 (currently employed in Washington, D.C.)
Jeffrey Nichols, Graduate Research Assistant, August 1994 - December
1996 (currently completing Ph.D. in Mathematics, degree expected
December 1997)
Publications acknowledging support from this award:
Abbott, C. A., M.W. Berry, E. J. Comiskey, L. J. Gross and H.-K. Luh.
Computational models of white-tailed deer in the Florida Everglades.
IEEE Computational Science and Engineering (accepted, to appear 1997)
Lee, H. L. and D. L. DeAngelis. A simulation study of the
spatio-temporal dynamics of the Unionid mussels. Ecological Modeling
(accepted, to appear 1997)
Luh, H.-K., C. Abbott, M. Berry, E.J. Comiskey, J. Dempsey, and L. J.
Gross. 1997. Parallelization in a spatially-explicit individual-based
model (I) Spatial data interpolation. Computers and Geosciences 1997.
23:293-304
Luh, H.-K., J. J. Mineskey and H. Bozdogan. Choosing the best
predictors in regression analysis via the genetic algorithm with
informational complexity as the fitness function. Computational
Statistics & Data Analysis (submitted).
Luh, H.-K., J. L. Gittleman, H. Bozdogan, and C. G. Anderson.
Phylogeny and multivariate correlated traits: an information-based
approach. Evolution (submitted).
Mellott, L. E., M. W. Berry, E. J. Comiskey and L. J. Gross. The design
and implementation of an individual-based predator-prey model for a
distributed computing environment. J. of Supercomputing (submitted)
Ramachandramurthi, S., T. G. Hallam, and J. A. Nichols. Parallel
simulation of individual-based, physiologically structured populations.
Mathematical and Computer Modelling 25 (12) (to appear 1997).
Ramachandramurthi, S., J. A. Nichols and T. G. Hallam. Ecological
Assessment in watersheds:Individual-based modeling and parallel
simulations. Mission Earth Proceedings. . Proceedings, Mission
Earth:Modeling and Simulation for a Sustainable Global System, Society
for Computer Simulation 1996, 193-198.
Theses and Dissertations:
Abbott, Catherine Ann M.S. (Computer Science) A Parallel
Individual-Based Model of White-Tailed Deer in the Florida Everglades.
August 1995.
Lee, Hooi-Ling Ph.D. (Ecology) Use of a Spatially-Explicit Model to
Study the Distributional Dynamics of Unionid Mussels. December 1996.
Mellott, Linda M.S. (Computer Science) A Distributed Implementation of
an Individual-Based Predator-Prey Model. May 1997.
Presentations made related to this project:
An Invited Minisymposium on Environmental Modeling and Computation was
organized at the Annual Meeting of the Society for Industrial and
Applied Mathematics in Charlote, NC in October 1995. This Symposium
focused on results from this project and included talks on
ecotoxicology models utilizing partial differential equations for
population structure and landscape-scale models using
spatially-explicit simulation of individual organisms. For each
application, one speaker described the underlying modeling problems,
and the second speaker discussed the related computation issues, with
emphasis on parallelization methods. The talks were:
Dr. Thomas Hallam: Risk Assessment for Chemically Stressed Populations
and Communities
Dr. Siddharthan Ramachandramurthi: Parallel Computation in Structured
Population and Community Models
Dr. Louis J. Gross: Modeling the Everglades: Integrating Alternative
Methodologies across Scales
Dr. Hang-Kwang Luh: Parallel Computation for Individual-based
Ecological Models at Landscape-scale
Other presentations (not all of which required financial support from
this award) include:
1995 Logan, UT. Conference on Mathematical Models in Population
Dynamics. L. Gross and T. Hallam (2 presentations)
1995 San Diego, CA. San Diego Supercomputer Center Workshop on
Computational Ecology. L. Gross
1996 Orlando, FL. Sixth Symposium on Environmental Toxicology and
Risk Assessment: Modeling and Risk Assessment. L. Gross and T.
Hallam (2 presentations)
1996 San Diego, CA. Mission Earth: Modeling and Simulation for a
Sustainable Global System. S. Ramachandramurthy
1996 Lubbock, TX. Departments of Biology and Mathematics, Texas
Tech University. L. Gross
1996 Providence, RI. Session on Advanced Technologies in Ecological
Science, Annual Meeting of the Ecological Society of America. L. Gross
1996. Providence, RI. Symposium on The Interface between Theoretical
Ecology and Conservation Biology, Annual Meeting of the Society for
Conservation Biology. L. Gross
1996 Hamburg, Germany. Prodynamics: A workshop on progress in dynamics
of ecological models. T. Hallam
1996 Trieste, Italy. Third Autumn Workshop on Mathematical Ecology. L.
Gross and T. Hallam (2 presentations)
1996 Athens, Greece. International Society of Nonlinear Analysts.
T. Hallam
1997 Lafayette, LA. Mathematics Department, University of Southwestern
Louisiana. T. Hallam
1997 Lafayette, LA. National Wetlands Laboratory. T. Hallam
1997 Amsterdam, Holland. Department of Theoretical Biology, Vrije
University. T. Hallam
1997 London, UK. Zeneca Chemical Company. T. Hallam
1997 Winrock, AR. Workshop on Aquatic Ecosystem Modeling and
Assessment Techniques, Army Corps of Engineers, Waterways Experiment
Station. L. Gross and T. Hallam (2 presentations)
Brief description of research carried out during this project:
There were three major subprojects included in this project, all
of which involve the development of parallelization schemes for
ecological models which track the behavior of individual organisms,
making use of a variety of architectures and platforms. The three
components (spatially-explicit rule-based models, structured
population models derived from partial differential equations, and
spatially-explicit community models) are each discussed briefly below,
though much more of the details of each project component are included
in the various papers which are available upon request from L. Gross,
the Lead P.I. for this award.
Spatially-explicit rule-based models track the behavior of
individual organisms on realistic landscapes, including rules for
foraging, movement, growth, mortality, and reproduction. As an
example of this type of model, this project supported the development
of parallel implementations of a model for white-tailed deer
and Florida panther in South Florida, coupled to spatially-varying
water levels and vegetation models. Parallelization was developed
using a 32 processor Connection Machine CM-5, a 4000 processor
Maspar MP-2, and a network of workstations using the Message
Passing Interface MPI. In all cases, extensive reworking of a serial
version of the model was necessary to the parallelization, with
somewhat different assumptions about individual behavior needed
relative to the randomized sequential procedure used in the serial
version. One published paper from this project focused on data-parallel
procedures for spatial interpolation of the hydrology and vegetation
components, comparing performance statistics for the CM-5 and the MP-2
and indicated that speed improvements were very much a function of the
architecture as well as the particular method used for spatial data
interpolation. Another paper focused on alternative methods to handle
hydrology, vegetation, and the coupling to deer foraging, with a
parallel code developed using spatial grid partitioning on the CM-5
showing significant speedups (ranging from 9 to 27) achievable relative
to a sequential version on a single processor. An additional paper
discusses a parallelization of the full deer/panther model using a
distributed network of workstations and the Message Passing Interface.
The resulting model behavior was similar, though not identical to that
from the sequential version of the model, due to somewhat different
assumptions about individual movements needed in the parallel version.
Moderate speedups (3 to 4) were obtainable on a network of up to 12
processors, with a major speedup limitation being the communication
costs due to the need for synchronization across processors.
Structured population models derived from partial differential
equations track the behavior of many cohorts of individuals within
a population, where each cohort may include many individuals. This
project supported the development of parallel implementations of a
Daphnia model, designed in part to be applied to analyze the
effects of toxicants on population levels and structure, as well
as the linkage of this model to a structured population model for
fish, thus making a simple community model. The focus of these
efforts were on the CM-5 and using PVM over a network of workstations,
though the Intel iPSC/860 and the IBM SP-2 have been utilized as well.
The papers published on this aspect of the project describe a general
scheme for parallel simulation of individual-based, structured
population models, with the development of algorithms to simulate such
models. The simulation model consists of an individual model and a
population model that incorporates the individual dynamics. The
individual model is a continuous time representation of organism life
history for growth with discrete allocations for reproductive
processes. The population model is a continuous time simulation of a
nonlinear partial differential equation of extended McKendrick-von
Foerster type. As a prototypical example, the Daphnia population model
results indicate that individual-based, physiologically structured
models are is well suited for parallelization and significant speed-ups
can be obtained by using efficient algorithms. Because the parallel
algorithms are applicable to generic structured populations, and these
serve as the building blocks for more detailed community-level or
food-web models, parallel computation appears to be a valuable tool for
ecological modeling and simulation.
A spatially-explicit community model for freshwater mussels was
developed as part of this project to analyze changes in community
composition through time along various reaches of a river/lake
system. The model includes age-structured populations of 35 species
of mussels along linear arrays of cells representing different
spatial cells of a river. This has been implemented on the MP-2, in
which each river cell is handled by a single processor element. During
dispersal phase, the front-end of the computer is used to combine
dispersing larvae from many cells and then redistributing them back to
respective processors as appropriate. The model used in the study is
based on the concept of a single open marine population with
space-limited recruitment, with each species of mussel in each cell
having up to a maximum of 15 different age classes, and the
physiological growth of the mussels is described by a deterministic
function that is parameterized individually for each species. As the
mussel species involved are transported by fish hosts for part of their
life cycle, movements of fish need to be taken into consideration to
analyze museel community dynamics. Parallelization involved the MP-2
splitting up the spatial region into cells with dispersal between
neighboring cells. A typical speedup was 4 to 6 for the MP-2 relative
to a single processor version run on a SUN Sparcstation 5. The key
difficulty in setting up a parallel structure for this model was the
tree-like structure of branching rivers. This project supported one
dissertation which describes one set of methods to deal with
parallelization of spatial branching patterns for models with
populations or communities moving within the branching structure.