Scientists at Northern Arizona University and the National Center for Ecological Analysis and Synthesis have developed a model that uses circuit theory to predict gene flow across landscapes. Their approach could give managers a better way to identify the best spots for wildlife corridors, which are crucial to protecting biodiversity.
There are a lot of similarities between circuit theory and ecological connectivity, said Brad McRae, head of the project. Its a powerful tool.
A 2005 doctoral graduate from the NAU School of Forestry, McRae, now a scientist at the National Center for Ecological Analysis and Synthesis in Santa Barbara, Calif., with his adviser Paul Beier of NAU School of Forestry, published this innovation in the Dec. 11 issue of Proceedings of the National Academy of Sciences of the USA.
McRae first hit on the idea while working with Beier on a study of genetic relationships of cougars across the southwest United States. We had good maps of habitat and good maps of genetic data, he said, and no way to see how one might affect the other.
Using experience from his previous career as an electrical engineer, he reasoned that gene flow across a complex landscape should follow the same rules as electrical conductance in a complex circuit board.
The result was what McRae calls the Isolation by Resistance model. The model represents patches of habitat as nodes in an electrical circuit and the genes of animals and plants as the current that flows between the nodes. Flow occurs across multiple pathways, encountering more resistance in some areaspoor habitats or human-made barriersand flowing preferentially through better habitats.
I predict Brads model will become the standard way of modeling gene flow, and in a few years it will be seen as so intuitively appropriate that scientists will wonder why no one had seen the analogy before, Beier said. As a conservation biologist, I am most excited abo
'/>"/>
| Contact: Paul Beier Paul.Beier@nau.edu Northern Arizona University Source:Eurekalert |
Related biology news :
1. Novel 3-D cell culture model shows selective tumor uptake of nanoparticles
2. A new kind of rat model
3. JILA finds flaw in model describing DNA elasticity
4. Smithsonian researchers develop models to assess wetland health
5. Prediction of RNA pseudoknots using heuristic modeling with mapping and sequential folding
6. Simulating kernel production influences maize model accuracy
7. MIT model could improve some drugs effectiveness
8. Model for the assembly of advanced, single-molecule-based electronic components developed at Pitt
9. Improving detection of nuclear smuggling goal of computer model of mechanical engineer
10. New chimeric mouse model for human liver diseases, drug testing
11. Study finds first-ever genetic animal model of autism
| Copyright © 2003-2012 Bio-Medicine. All rights reserved. ABOUT | CONTACT US | DISCLAIMER | PRIVACY POLICY | TERMS AND CONDITIONS |  |