Mathematical and computational challenges in population biology and ecosystems science.
Mathematical and computational approaches provide powerful tools in the study of problems in population biology and ecosystems science. The subject has a rich history intertwined with the development of statistics and dynamical systems theory, but recent analytical advances, coupled with the enhanced potential of high-speed computation, have opened up new vistas and presented new challenges. Key challenges involve ways to deal with the collective dynamics of heterogeneous ensembles of individuals, and to scale from small spatial regions to large ones. The central issues-understanding how detail at one scale makes its signature felt at other scales, and how to relate phenomena across scales-cut across scientific disciplines and go to the heart of algorithmic development of approaches to high-speed computation. Examples are given from ecology, genetics, epidemiology, and immunology.
Levin
S A
SA
Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA.
Grenfell
B
B
Hastings
A
A
Perelson
A S
AS
D000163:Acquired Immunodeficiency Syndrome / Q000821:virology; D000486:Allergy and Immunology; D000818:Animals; D005075:Biological Evolution; D003141:Communicable Diseases / Q000635:transmission; D019295:Computational Biology; D003198:Computer Simulation; D004463:Ecology; D004813:Epidemiology; D005823:Genetics; D006801:Humans; D008954:Models, Biological; D014773:Virology