SYMP 13-1
An integrative investigation of larval dispersal and population connectivity using a coral reef fish
Understanding the patterns, causes and consequences of larval dispersal is a major goal of marine ecology. Patterns of dispersal determine the rates of larval exchange, or connectivity, between populations. Both physical factors (e.g., water movement) and biological factors (e.g., larval behavior) cause variation in population connectivity. Population connectivity, in turn, has major consequences for all aspects of an organism’s biology, from individual behavior to metapopulation dynamics, and from evolution within metapopulations to the origin and extinction of species. Further, understanding population connectivity is critical for designing effective networks of marine reserves – vital tools in the development of sustainable fisheries.
Over the last decade, three methods have emerged as the leading contenders to provide the greatest insights into the causes of population connectivity. First, genetic methods use parentage analyses, tracing recruits to specific adults, to measure population connectivity. Second, high-resolution oceanographic models make assumptions regarding water flow to predict population connectivity. Third, studies of animal behavior provide insight into how larval behavior might alter predictions of population connectivity. Despite advances, lack of integration means that we do not know the predictive skill of physical models or the extent to which incorporating larval behavior improves the skill of coupled bio-physical models.
Results/Conclusions
The overall objective of our research is to conduct an integrated investigation of population connectivity in one tractable system: the neon goby, Elacatinus lori, on the Belizean Barrier Reef. The research has three specific objectives: 1) to determine the relationship between distance and the probability of successful dispersal measured using genetic methods; 2) to determine the relationship between the probability of successful dispersal predicted by physical models and that measured using genetic methods; 3) to determine the extent to which incorporating larval behavior into coupled bio-physical models improves our ability to predict the probability of successful dispersal.
We have three major results to date. First, we have traced recruits back to their parents using parentage analysis and shown that the probability of successful dispersal declines rapidly with distance. Second, we have developed a coupled atmospheric-oceanographic model and shown that increasing the resolution of the atmospheric and oceanographic forcing improves its accuracy at predicting drifter trajectories. Third, we have conducted behavioral observations of the larvae and shown that they have well-developed swimming capabilities and orient non-randomly in the field. These findings lay solid foundations for integration, which will deepen our understanding of marine larval dispersal and population connectivity.