Issues in Computational Ecology
Submitted to the Workshop on Computational Ecology,
San Diego Supercomputer Center, University of California, San Diego
September 22-23, 1995

Louis J. Gross
Professor of Mathematics and Ecology
Departments of Mathematics and 
Ecology and Evolutionary Biology
University of Tennessee
Knoxville, TN 37996-1300
gross@math.utk.edu
http://www.math.utk.edu/~gross/ (My Home Page)
http://archives.math.utk.edu/mathbio/  (Our Math Archives Life Sciences Page)

While there are hosts of significant open questions in ecology that are and 
will continue to be be affected by the availability of computational 
technology, I focus here on only a few that I consider of great relevance to 
the more applied concerns of the field. Specifically, these deal with 
management of resources, and the interface between the science of ecology 
and the politics of decision-making. Much of my comments arise from ongoing 
research to provide detailed scientific input, based upon observational 
biology and the application of computer models, to water management decisions 
in South Florida. This research is part of the ATLSS project (Across Trophic 
Level System Simulation) supported by the National Biological Service (see 
my Home Page for details).

Landscape-scale Management:
    Much of applied resource management occurs at the landscape scale, and 
has the potential to make use of spatially-explicit information (often 
included in some form of GIS data base) to analyze current and past trends 
and effects (e.g. on animal population sizes, vegetation community structure, 
etc.) and make predictions about effects of possible management scenarios. 
This can involve linking models for landscape change at various scales to 
the economic impacts of such changes. As of yet, we have experience with 
very few such approaches (for one example involving a Markov-transition 
approach to landscape change see the LUCAS Home Page at 
http://www.cs.utk.edu/~lucas/index.html), and yet regional assessment 
programs aimed towards comparing various management plans require the type 
of fairly detailed analysis provided by extensions of such approaches.
    
Multimodeling:
    Historically, much of modeling in both theoretical and applied ecology 
has dealt with models that aggregate across a variety of scales (temporal, 
spatial, and organismal). Thus classical models have been dynamical systems 
with state variables being the densities of species, and these have served 
as the basis for much of ecosystem modeling. Taking account of spatially-
heterogeneous systems, with different trophic levels having different inherent 
spatial and temporal scales, requires a mixture of modeling approaches rather 
than a single one-model-fits-all view. Thus, we have been developing (in the 
ATLSS project) the methodology for a multimodel (for non-biological examples 
see the site http://www.cis.ufl.edu/~fishwick/research/node2.html) which 
combines process-oriented compartment models for the lower trophic levels, 
structured population models for intermediate trophic levels, and individual-
based models for higher-level consumers. Procedures for developing and 
analyzing such ecosytem-scale multimodels in combination with economic and 
social impact models remains an area of great future importance.

Spatially-explicit control: 
    Management that occurs at landscape scale (e.g. forest harvesting, water 
flow management, conservation preserve design, etc.) is not an all-or-nothing 
affair that occurs uniformly in space. Rather, realistic management scenarios 
must take account of spatial heterogeneity in underlying resources, as well 
as how such heterogeneity interacts with management through time (local 
ecological succession for example). Given that there are a variety of 
potential criteria which affect the system management, so that the underlying
non-spatial issue may be viewed as a multiple criteria optimization problem, 
how should the "control" of the system be applied spatially in order to carry 
out the optimization? This is a little-developed area of applied mathematics, 
particularly in systems in which there are stochastic factors which interact 
with the management scheme. Yet it lies at the heart of much of applied 
ecology today.


Brief Biography:
Dr. Louis Gross is currently a Professor of Mathematics and Ecology at UTK.
He completed his Ph.D. in Applied Mathematics at Cornell University in 1979 
and has been on the faculty of the University of Tennessee at Knoxville since
that time. His areas of research include mathematical modeling in biology, 
plant physiological ecology, behavioral ecology, and landscape ecology. 
Current projects include the development of an across trophic level modeling 
framework for the Everglades region of South Florida, individual-based models 
for animal populations, application of massively parallel computers to 
ecological models, and development of a quantitative curriculum for life 
science students. He has served on the Editorial Boards of all three journals 
of the Ecological Society of America, as well as co-directing several 
Courses and Workshops in Mathematical Ecology at the International Centre for 
Theoretical Physics in Trieste, Italy.