Metacommunity dynamics may result from life history trade-offs associated with movement. Inter-specific variation of movement strategies such as random and directed movement may promote biodiversity via local coexistence and species partitioning; however, few studies have directly quantified the movement types of several coexisting species. We documented the colonization patterns following hydrological disturbance using a 20-year time series of marsh fish and investigated how both speed and directedness influenced these patterns. The critical swimming speed (UCRIT) for six common marsh fish were estimated using endurance tests in a Blazka-style swim tunnel. We then incorporated both speed and direction into several Agent Based Models (ABM’s) to simulate dispersal in a homogenous landscape. Six virtual “species”, with varying levels of directedness, were simulated to swim in an artificial environment for 12 hours in simulated time to reach a refuge habitat located 1-km north. Six different speeds were tested to explore the interaction between direction and speed to produce 46,656 different combinations. The time of first arrival for each species was saved at the end of each run and used to calculate the probability of arrival order. We then compared both our UCRIT estimates and simulated results to field observed field patterns.
Results/Conclusions
Over 500 drying events were analyzed and revealed consistent patterns of species recolonization that were independent of density. Species also arrived in a consistent pattern (first to last: Jordanella floridae, Gambusia holbrooki, Fundulus chrysotus, Lucania goodei, Heterandria formosa, and Poecilia latipinna) following re-inundation of the habitat. Swim tunnel results revealed that fast (high UCRIT) estimates were characteristic of early colonizing species (J. floridae, G. holbrooki, F. chrysotus); whereas, slow (low UCRIT) estimates were characteristic of late colonizing species (L. goodei, H. formosa, P. latipinna). Further investigation revealed that fast, directed individuals are more likely to reach a habitat first compared to slow, undirected ones. However, directional bias was revealed to be more important than speed alone. This pattern was indicative of L. goodei, a species with low estimates of UCRIT, but which moves in a directed fashion. Our simulated results generated predictions on order of arrival consistent with field data and observed colonization patterns in our long-term dataset. This reveals that recolonization patterns can be predicted using a simple model that includes only directional bias and speed. Furthermore, this study demonstrated the importance of incorporating observations from both field and laboratory data into ABMs when trying to describe ecological phenomena.