Simulation models are valuable for making predictions that may be tested in natural systems and for understanding observed patterns. The simulation model developed for this thesis evaluates the effects of spatial network architecture, including organism dispersal patterns and isolation of habitats, on metapopulations. Two fields were merged throughout this project: metapopulation biology and small-world network theory. Small-world networks are characterized in their extremes as scale-free or single-scale. These models potentially simulate the networks of habitats and corridors in which metapopulations operate. Small-world network theory has been used to describe systems as diverse as rivers, the world-wide-web, and protein interactions, but has not been used as an experimental treatment for metapopulation dynamics. I tested the effects of growth rate, dispersal pattern, network architecture (scale-free and single-scale), attack type (targeted or random), and attack severity (0, 5, 10, 20, or 40% attacked populations) on metapopulation size and inter-population variation in a simulated system designed to be relevant to conservation biology and ecology. Metapopulation size and inter-population variation changed due to combinations of dispersal pattern, growth rate, and attack severity. Specifically, metapopulations were most affected by a combination of unidirectional dispersal and low growth rate in both metapopulation number and inter-population variation. However, a significant difference between scale-free and single-scale metapopulations was not found due to a low connectivity in the modeled networks as well as limitations of experimental assumptions. However, future studies that alter the model's assumptions could improve understanding of the influence of landscape structure on at-risk metapopulations.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-4083 |
| Date | 01 January 2007 |
| Creators | Bernard, Alaina Brooke |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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