A computer model newly developed by researchers combines ocean current simulations and genetic forecasting to help scientists predict animal dispersion patterns and details of the ecology of coral reefs across the Caribbean Sea. The work is reported by Heather M. Galindo and Stephen R. Palumbi of Stanford University, and Donald B. Olson of the University of Miami, and appears in the August 22nd issue of Current Biology, published by Cell Press.
Effective marine management and conservation planning require a better understanding of the movement of young marine animals, including small larvae, in part because such movements facilitate normal biological connections among geographically separate populations. Although tiny larvae are impossible to follow directly, advances in modeling ocean currents have made it possible to predict larval movements. However, until now it has remained difficult to test these movement predictions in the field by comparing the model to data from population genetic studies.
The new work enables scientists to field-test such predictions and thereby hone our understanding of how marine larvae disperse in the environment and influence the structure of adult populations. In their study, the researchers coupled two types of models: One model predicts the movements of "virtual" coral larvae in the Caribbean Sea based on ocean currents, while the second model gives the virtual larvae a genetic tag. The researchers then tested this new approach by comparing the new model's predictions to empirical genetic data for threatened staghorn corals.
This test showed that combining the oceanographic and genetic models allowed the researchers to successfully predict genetic patterns on a regional scale. This breakthrough approach to integrating genetic and oceanographic models helps predict genetic links among several locations and is an important new tool for the management and ecological study of marine protected areas.
The researchers include Heather M. Galindo and Stephen R. Palumbi of Stanford University in Pacific Grove, California; Donald B. Olson of University of Miami in Miami, Florida.
The authors were supported through the Bahamian Biocomplexity Project sponsored by the National Science Foundation (NSF OCE-0119976), NOAA-FL Sea Grant NA16RG-2195, and grants from the David and Lucille Packard and Gordon and Betty Moore Foundations to PISCO. In addition, this material is based upon work supported under a National Science Foundation Graduate Research Fellowship awarded to H.M.G.
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