Modeling population connectivity by ocean currents, a graph-theoretic approach for marine conservation
The dispersal of individuals among marine populations is of great importance to metapopulation dynamics, population persistence, and species expansion. Understanding this connectivity between distant populations is key to their effective conservation and management. For many marine species, population connectivity is determined largely by ocean currents transporting larvae and juveniles between distant patches of suitable habitat. Recent work has focused on the biophysics of marine larval dispersal and its importance to population dynamics, although few studies have evaluated the spatial and temporal patterns of this potential dispersal. Here, we show how an Eulerian advection-diffusion approach can be used to model the dispersal of coral larvae between reefs throughout the Tropical Pacific. We illustrate how this connectivity can be analyzed using graph theory-an effective approach for exploring patterns in spatial connections, as well as for determining the importance of each site and pathway to local and regional connectivity. Results indicate that the scale (average distance) of dispersal in the Pacific is on the order of 50-150 km, consistent with recent studies in the Caribbean (Cowen, et al. 2006). Patterns in the dispersal graphs highlight pathways for larval dispersal along major ocean currents and through island chains. A series of critical island 'stepping stones' are discovered providing potential pathways across the equatorial currents and connecting distant island groups. Patterns in these dispersal graphs highlight possible pathways for species expansions, reveal connected upstream/downstream populations, and suggest areas that might be prioritized for marine conservation efforts. © 2007 Springer Science+Business Media B.V.
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- Ecology
- 41 Environmental sciences
- 37 Earth sciences
- 31 Biological sciences
- 06 Biological Sciences
- 05 Environmental Sciences
- 04 Earth Sciences
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Ecology
- 41 Environmental sciences
- 37 Earth sciences
- 31 Biological sciences
- 06 Biological Sciences
- 05 Environmental Sciences
- 04 Earth Sciences