Bioirrigation in marine sediments: numerical simulations and ecological conclusions O.S. Galaktionov, F.J.R. Meysman, B. Gribsholt, J.J. Middelburg(An engineer's view on benthic ecology)European Conference on Coastal Zone Research: an ELOISE approachPortoroz, Slovenia, November 14 18, 2004

Types of sediments: muddy (low permeability): solute transport is dominated by diffusion sandy (high permeability): advective transport by porewater flows may far exceed the magnitude of diffusive fluxesModelling (bio)-irrigation in permeable aquatic sediments(Bio)-irrigation: passive advection caused by the interaction of the overlying water flow with (biogenic) bedforms, i.e. ripples, mounds, protruding shells etc.diffusion through the burrow walls etc. active advection of porewater due to activity of benthic organisms: ventilation of burrows etc. Activity of benthic organisms may also enhance diffusive transport (through the tube walls)water columnsediment

Active bio-irrigation (by the lugworm Arenicola marina)Schematic drawing of Arenicola in its burrowImportance of the quicksand channel (higher permeability) should be examined

How complex the bio-irrigation model geometry should be?3D2D axisymmetric1D retains full spatial complexity computationally expensive necessarily low resolution faster FEM simulations allows high resolution retains sufficient complexity very fast simulations no downward advection no horizontal heterogeneity

Bio-irrigation by the Arenicola marina: importance of burrow insulationBurrow wall insulation helps to extend habitat towards less permeable sediments Active insulation: lining burrow walls with mucus, head banging etc. requires investment of resources Passive insulation: accumulation of iron oxides etc. is free but costs time may explain the semi-permanent nature of the burrowsInsulated burrow walls:only overlying water is drawn to the burrow Permeable burrow walls:flow shortcuts, anoxic pore water re-enters the burrow

3D, 2D and 1D models: meshes and streamlines3D2D axisymmetric1D*actual mesh and streamlinesactual mesh and streamlines* sketch

Flushing experimentInjection experimentSaturation ofpore waterwith tracer(NO3-)Br-Measure tracer appearance in pore waterrough sandaquiferNO3-?SO42-O2NO3-, O2seaorganic matterTracer addition (Br- )Measuring tracer appearance in overlying waterSaturating pore water with tracer (NO3- )Numerical models of bio-irrigation are applied to:Field study NO3-

Modelling Br- injection: coupled 2D axisymmetric model (unamended)Horizontally averaged tracer profilesComputed concentration patterns Overlying water column is assumed to be ideally mixed t = 96 min is actual incubation time; no tuning of the parameter values!

Reproducing the core incubation data with 3D, 2D and 1D modelsSmall feeding pocketAmended models (vertically enlarged feeding pocket) 2D model can be easily tuned by adjusting the feeding pocket geometry 1D model also requires strong additional non-mechanistic tuning: increasing the effective diffusivity (hydromechanical dispersion)

Approximating Timmermann (2002) results: large feeding pocket (?)

Experimental artifacts(?): flushing nitrate from the sediment core NO3- flushing test: sediment core saturated with nitrate solution; overlying water replaced (by clean water); one Arenicola marina introduced; nitrate concentration in water column monitoredConclusions: Concentration overshot (core 1) is reproduced by the model Presence of the overshot is controlled by the core geometry Flow is essentially 3D: layers below the burrow are efficiently flushed

Bio-irrigation and NO3- transport to the sea (NAME project)Field site (Denmark): rough sandaquiferNO3-?SO42-O2NO3-, O2seaorganic matterWhat is the role of bio-irrigation?

Bio-irrigation and NO3- transport to the sea (NAME project) organic matter oxygen sulfate nitrate H2SThe computed concentration patterns correspond to the discharge velocity 2 m/yr and worm density 8 m-2 (each pumping 1ml/min)Preliminary remarks Nitrate is prevented from the contact with the large part of organic matter Zone clear from nitrate is irrigated with abundant sulfate (sea water) Hydrogen sulfide production may result from bio-irrigation

NO3- transport to the sea: influence of discharge velocity from aquifer Advective bio-irrigation strongly affects the nitrate removal / discharge into the sea NO3- consumption is suppressed by mechanical separation of nitrate-rich aquifer water from reactive organic matter Reliable prediction of nitrate removal requires simultaneous knowledge of the aquifer discharge rate and animal density/activity

Bioirrigation in marine sediments: Concluding remarksSediment permeability is the key factor shaping the ecology of the marine sedimentsArenicola marina Burrow lining prevents flow short-circuits, extends habitat to less permeable sediments Advective bio-irrigation reaches the sediment layers below the burrow depthAdvective bio-irrigation: 3D 2D 1D(?) model 3D model is computationally expensive, prohibiting high resolution 2D axisymmetric model: captures important features of the flow, including advective flow below the burrow computationally efficient, still allowing high resolution 1D model requires excessive tuning: uses enhanced diffusion to mimic advective effects Application: advective bio-irrigation and NO3- removal Animal activity (bio-irrigation) may hinder the nitrate removal Reliable predictions require data on both aquifer discharge rate and animal density/activityThank you for attention!

Additional sides

Bio-irrigation by the Arenicola marina: importance of burrow insulationStreamlines of the porewater flow, computed in the assumption of uniform sediment properties.Numerical simulations show the importance of the burrow lining: it allows to extend habitat to less permeable sedimentsInsulated burrow walls

only overlying water is drawn to the burrow Permeable burrow walls:

flow shortcuts,anoxic pore water re-enters the burrow

Bio-irrigation (by the lugworm Arenicola marina): quicksand importance?Comparing the computed passive tracer profiles in the cylindrical core with and without quicksand column (10 times higher permeability) Computed depth profile for the concentration of passive tracer (laterally integrated from 3D-simulations) compared to the experimental data obtained by Timmermann et al., (2002)

Bio-irrigation by the Arenicola marina: importance of burrow geometryBy placing a finite size source at the axis of axisymmetric sediment core the dependence of the sediment resistance of the burrow geometry was evaluatedFacts, revealed by simulations: resistance slowly grows with the burrow depth (most of it happens near the source) burrow opening (size of feeding pocket) plays a larger role We may speculate that: burrow depth is likely determined by other factors (food availability, predator avoidance), while it is advantageous for a worm to enlarge the feeding pocket to facilitate pumping.

Alternative (complementary?)description of bio-irrigation:active irrigation (advection)Classical description of bio-irrigation:tube model (Aller, 1980) passive irrigation (diffusion)Diffusive versus advective bio-irrigation combination of these models?

Simple model of advective bioirrigation: source in the cylindrical domainThe velocity field (described by Darcys law) in the cylindrical domain with open upper side that contains a point source at the axis may be obtained analytically:Whereand k are the roots of the Bessel function:Comparison (pressure contours) of the analytical and FEM solutions (FEMLAB):J and I are Bessel functions and modified Bessel function of the 1st kindCoefficients an, b0 and bk are defined so that the boundary conditions are fulfilled on the walls

Bio-irrigation and reactive tracers: 3D effects versus 1D approximationsFrom 3D to 1D: flow patterns in axisymmetric core with a small source steady state distribution of decaying tracer averaging concentration field horizontally to obtain 1D profileNext step:Can the resulting concentration profile vs. depth be reproduced in the 1D reactive transport model?

Linearly decaying tracer: Gaussian distributed source in 1D Horizontal averaging preserves the linear relation between concentration and reaction rate:Tracer concentration profile averaged from axisymmetric simulations is well matched by 1D Gaussian distributed source

1D vs. 3D (linearly decaying tracer): effective width of 1D source The problem of the best-fit source width includes five parameters: source width [L], source depth X0 [L], core radius Rc [L], reaction rate constant k [T-1] and source intensity F* [L3T-1] with two independent dimensionalities (length L and time T). According to Buckinghams theorem non-dimensional source width = / X0 should depend on only two independent non-dimensional parameters: Note: the approx. formula represents merely a good fit and was not analytically derived

1D vs. 3D, (nearly) zero-order reaction: more questions than answers Zero-order reaction rate is approximated by the monod-type expression Reference case: Horizontal averaging (3D 1D) leads to a gross overestimation of the total reaction rate Secondary effect: shift of the concentration maximum towards sediment-water interface Adjustment of the reaction rate constant is required for the 1D model The best fit is achieved with a more linearized dependence of R(c)

Bio-irrigation (by the lugworm Arenicola marina): quicksand importance?Better fitting (Timmerrmann, 2002; core 2e) using quicksand: Diameter of the column with higher permeability and the change in permeability are merely fitting parameters (not properly observed or measured) Not all cases are properly described using only this assumption

Flushing tracer from the sediment core: numerical predictions Screen snapshot:

Passive (bio)-irrigation: porewater flow under the seabed form (ripple)Pressure variations, arising around the obstacle in the near-bottom flow drive the porewater fluxes under the obstacleExperimental images from Huettel M. et al , Limn. And Ocean. 41 (2), 1996:The images above were taken at the intermediate range of Re (near transition to turbulence)The porewater flow under the ripple at different flow regimes can be simulated numerically

Passive irrigation: porewater flow under the seabed form (ripple)Pressure variations, arising around the obstacle in the near-bottom flow drive the porewater fluxes under the obstacleLaminar flow (Re 200) v ~ 1 cm/s:Turbulent flow (Re 5000) v ~ 25 cm/s : Porewater velocity at z=0 under the ripple crest is aprox. 0.036 mm/hPorewater velocity at z=0 under the ripple crest is aprox. 5 cm/hlog U

Simple model of advective bioirrigation: source in the cylindrical domainhas the solution in the formwith the coefficients:where

Bio-irrigation and NO3- transport to the sea (NAME project)Chem. species: O2, Fe2+, SO42-, HS-, CH4, HCO3-, NO3-, N2, Cl-, DOM ; CH2O, FeOOH, FeSReactions set:Conservation equations have a form:Di diffusion/bioturbation coefficient, ui advection/burial velocity, Ri reaction ratemineralization