MEPS 531:221-239 (2015)  -  DOI: https://doi.org/10.3354/meps11349

ABSTRACT: Marine diseases are a strong selective force that can have important economic and ecological consequences. Larval dispersal patterns, selective mortality and individual growth rates can modulate metapopulation responses to disease pressure. Here, we use a modeling framework that includes distinct populations, connected via larval transport, with varying disease selection pressure and connectivity to examine how these dynamics enhance or inhibit the evolution of disease resistance in metapopulations. Our system, oysters and MSX disease, is one in which disease resistance is highly and demonstrably heritable. Simulations show that under conditions of population isolation (i.e. local retention of larvae) and strong disease selection, populations rapidly evolve genetic disease resistance. Varying the patterns of larval dispersal alone doubles the time for evolution of disease resistance. Spatially varying disease in the absence of larval dispersal leaves some populations unable to respond to the disease, whereas adding larval dispersal slows the response of populations under strong selection and speeds the response in populations under low selection when fitness is based on relatively limited genetic structure (‘juvenile fitness’ in our simulations). Under spatially variable disease pressure, larval dispersal generates a fourfold greater variance in fitness outcomes across the dispersal patterns tested. In a metapopulation, populations experiencing lower selection pressure will tend to slow the development of other, more heavily selected populations. This suggests that conservation efforts aimed at improving overall metapopulation resistance in the face of marine diseases should target those populations under modest or high disease pressure, rather than protecting those experiencing low selective pressure.

KEY WORDS: Larval dispersal · Metapopulation dynamics · Connectivity · Disease · Oyster · Resistance · Structured population model · Genetic adaptation · Evolution