Quantifying bioirrigation in aquatic sediments: An inverse modeling approach

Abstract

An inverse model was developed to quantify the depth distributions of bioirrigation intensities in sediments based on measured solute concentration and reaction rate profiles. The model computes statistically optimal bioirrigation coefficient profiles; that is, profiles that best represent measured data with the least number of adjustable parameters. A parameter reduction routine weighs the goodness‐of‐fit of calculated concentration profiles against the number of adjustable parameters by performing statistical F‐tests, whereas Monte Carlo simulations reduce the effects of spatial correlation and help avoid local minima encountered by the downhill simplex optimization algorithm. A quality function allows identification of depth intervals where bioirrigation coefficients are not well constrained. The inverse model was applied to four different depositional environments (Sapelo Island, Georgia; Buzzards Bay, Massachusetts; Washington Shelf; Svalbard, Norway) using total CO2 production, sulfate reduction, and 222Rn/226Ra disequilibrium data. Calculated bioirrigation coefficients generally decreased rapidly as a function of depth, but distinct subsurface maxima were observed for sites in Buzzards Bay and along the Washington Shelf. Irrigation fluxes of O2 computed with the model‐derived bioirrigation coefficients were in good agreement with those obtained by difference between total benthic O2 fluxes measured with benthic chambers and diffusive fluxes calculated from O2 microprofiles.