An inverse model was developed to quantify the depth distributions of bioir
rigation intensities in sediments based on measured solute concentration an
d reaction rate profiles. The model computes statistically optimal bioirrig
ation 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 aga
inst 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 optimizatio
n algorithm. A quality function allows identification of depth intervals wh
ere bioirrigation coefficients are not well constrained. The inverse model
was applied to four different depositional environments (Sapelo Island, Geo
rgia; Buzzards Bay, Massachusetts; Washington Shelf; Svalbard, Norway) usin
g total CO2 production, sulfate reduction, and Rn-222/Ra-226 disequilibrium
data. Calculated bioirrigation coefficients generally decreased rapidly as
a function of depth, but distinct subsurface maxims were observed for site
s in Buzzards Bay and along the Washington Shelf. irrigation fluxes of O-2
computed with the model-derived bioirrigation coefficients were in good agr
eement with those obtained by difference between total benthic O-2 fluxes m
easured with benthic chambers and diffusive fluxes calculated from O-2 micr
oprofiles.