Dynamic energy budget (DEB) parameter estimation for the globally invasive Quagga Mussel (Dreissena rostriformis bugensis)

Abstract

Impacts of Dreissena spp. on infrastructure, nutrient cycling, and productivity in invaded ecosystems have been well-documented. These effects are influenced by mussel density, growth, and reproduction; therefore, there is a need to parameterize a dreissenid bioenergetic model that can be incorporated into lake management decision support tools. Since Quagga Mussels (D. rostriformis bugensis) are the most common dreissenid species in the Laurentian Great Lakes, we compiled existing data from the past 20 years of literature to estimate Dynamic Energy Budget (DEB) model parameters for Quagga Mussels to predict mussel growth, filtration, temperature dependence, and nutrient fluxes. Our estimations for shape coefficient, maximum reserve density, Arrhenius temperature, surface area-specific ingestion rate, and surface area-specific searching rate were within the range of previously published DEB parameters for bivalves, with key differences that we relate to Quagga Mussel success in the Great Lakes through growth model simulations. Additionally, since dreissenids feed differentially on available prey, selectivity coefficients for common taxonomic algal groups and sizes were estimated which can be used to calculate effective food concentrations and estimate the environmentally available food density for Quagga Mussels. Finally, we developed an initial calibration of a DEB model in order to predict Quagga Mussel clearance rates in response to varying environmental conditions. Since field-collected data are not designed for precise parameter estimation, significant uncertainties in parameter estimates currently persist, highlighting the need for well-controlled laboratory experiments. The components of this model hold potential for integration into biogeochemical models to elucidate mussel effects on nutrient cycling and their response to future environmental changes. This integration enhances our understanding of ecosystem dynamics and can inform effective management strategies for invasive species in aquatic environments.