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Open Access Publications from the University of California

Marine lakes as biogeographical islands: a physical model for ecological dynamics in an insular marine lake, Palau

  • Author(s): Blanchette, François
  • Montroy, Sydney
  • Patris, Sharon
  • Dawson, Michael N.
  • et al.

Marine lakes are emerging ecological and evolutionary natural experimental systems, with genetically isolated resident populations that exhibit extreme population dynamics and rapid phenotypic change. Marine lakes are posited to be marine islands, however, unlike terrestrial islands for which rich models have been developed over the past half-century, we know little of the mechanisms driving changes in marine lakes. This is a critical knowledge gap in efforts to reconcile theory on, or distinguish differences among, island and island-like systems. To reduce this critical knowledge gap, we present a mathematical model describing marine lakes based on a case study of Jellyfish Lake (Ongeim’l Tketau, Mecherchar: OTM), Palau. Empirical data show that marine lakes exhibit delayed and reduced tidal motions, suggesting exchange of a limited amount of water with the neighboring (‘mainland’) ocean. Our model tracks changes in lake level, allowing determination of an exchange rate that is a physical null model for biological colonization and a proxy for colonization distance in island biogeography theory. In addition, we track horizontally averaged in-lake quantities such as salinity and temperature (i.e., marine weather, climate) and stratification (i.e., habitat) — that are known to influence resident species’ distributions and population dynamics — by solving an advection-diffusion equation. We find that weather, ocean conditions, groundwater, and exchanges through tunnels determine the abiotic environment in OTM. By comparing simulations and data, we estimate the difficult-to-measure properties of the surrounding groundwater — the ‘matrix’ in the vernacular of habitat islands — and give a range of realistic values for the effective diffusion coefficient. This coefficient is found to increase in a tropical storm, suggesting that other drivers can be important during perturbations.

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