Mathematically modeling eelgrass population ecology: growth and response to hydrogen sulfide.
Committee: JJ Apodaca, Alisa Hove, Mark Brenner
Eelgrass (Zostera marina) is a marine angiosperm that provides habitat for culturally- and economically-important species including Dungeness crab and juvenile salmon, stabilizes sediments, protects coastlines, and may sequester carbon. In its Pacific Northwest distribution, eelgrass has experienced instances of localized population decline, which may be due to several site-specific stressors. Elevated hydrogen sulfide concentrations have been hypothesized as a stressor contributing to eelgrass decline in the Salish Sea. Previous studies have demonstrated detrimental effects of sulfide on both individual adult vegetative shoots and seedlings, revealing potential differences in sulfide tolerance across life stages. Variable sulfide tolerance may ultimately dictate the ability of a population to resist or naturally recover from sulfide stress. However, the population-level functional response to sulfide is unknown. In this study, we develop a stage-based matrix population model to explore the functional response of eelgrass populations to sulfide. The eelgrass lifecycle was mathematically defined by three stages (vegetative shoots, flowering shoots, and seeds) and the vital rates describing transitions between stages (branching rate, flowering rate, fecundity, germination rate, seedling survival rate). The model was constructed with population growth and stage composition defined as functions of the vital rates on an annual time scale. Data was collected for each stage-specific vital rate in response to hydrogen sulfide concentrations and defined as functions of sulfide where correlation existed or at low-medium- high intervals where no correlation occurred. The model was run across a range of sulfide concentrations, and the population growth (λ), demographic composition, and λ sensitivity to changes in vital rates were analyzed. Branching rate had the largest effect on population growth, survival rate had a moderate effect, and fecundity had a negligible effect. Population growth was positive (>1) for the majority of conditions. This model can identify populations at risk and inform effective conservation and restoration strategies.