GeoComputation - GeoComputation - page 139

annual migration, very little is known about the routes they take or, indeed, where in Africa they
spend the winter months. If scientists can pinpoint areas of geographical importance, then one can
start to look at whether or not there are ecological pressures at such places which might explain their
subsequent observed losses in Britain.
6.4 CONCLUSIONS
For GC, many application areas in biology require no more than the application of existing methods
to data sets that happen to represent biological phenomena. However, the data explosion in biology
and the nature of the available data opens up many avenues for the development of GC methods.
These use non-standard (for GIS software) data structures such as trees and matrices, representing
phenomena such as phylogenies and genetic similarities.
The topics covered in this chapter demonstrate how biological applications espouse the core
organising concepts and techniques of GC and that computationally intensive modelling of biologi-
cal systems is very much at the cutting edge of biology research. Much biologically oriented GC
research has already begun, but there remains a wealth of opportunity for researchers in GC to
utilise and explore biological data and applications.
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