event sedimentation, bioturbation, and preserved...
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EVENT SEDIMENTATION, BIOTURBATION, AND PRESERVED SEDIMENTARY
FABRIC: FIELD AND MODEL COMPARISONS IN THREE CONTRASTING MARINE
SETTINGS
Samuel Jackson Bentley, Sr.
Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge,
Louisiana 70803 USA, [email protected], 225-578-2954 (corresponding author)
Alexandru Sheremet
Department of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge,
Louisiana 70803 USA, [email protected]
John M. Jaeger
Department of Geological Sciences, University of Florida, Gainesville, USA,
ABSTRACT
A model for the emplacement, bioturbation, and preservation of fine scaled sedimentary strata
has been used to evaluate the impact of interacting physical and biological sedimentary processes
on preserved sedimentary fabric in three contrasting shelf and estuarine depositional settings:
Eckernförde Bay, German Baltic Sea; the Eel Shelf, northern California, USA; and the northern
Gulf of Alaska continental shelf, USA. We have compared field measurements of sedimentation
and bioturbation (from 7Be, 234Th, 210Pb, and 137Cs measurements), and observations of
sedimentary fabric derived from core X-radiographs with model predictions of preserved
sedimentary fabric. The one-dimensional model is forced by fluctuations in the instantaneous
sedimentation rate, which deposits sediment with primary sedimentary fabric. Primary
sedimentary fabric is then modified by bioturbation, which is represented as a first-order depth-
limited reaction term, the rate of which is derived from radioisotopic and time-series estimates of
bioturbation depth and intensity. Model output includes depth in seabed and corresponding
preservation quotient, a measure of relative primary versus biogenic fabric. Although measured
rates and depth scales of sedimentation and bioturbation vary across the three study areas by
more than a factor of ten, model results strongly resemble actual sedimentary fabric in core X-
radiographs in each case. Our results support and expand on concepts that invoke episodic
sedimentation and depth-dependent bioturbation as important competing factors in the
preservation or destruction of primary depositional fabric, and also suggest that radioisotopic
estimates of bioturbation rates can adequately portray natural conditions.
Keywords: shelf sedimentation, bioturbation, model, stratigraphy, event layer, preservation potential
Regional terms: USA, California, Eel Shelf, Gulf of Alaska, Germany, Baltic Sea, Eckernförde Bay
1.0 INTRODUCTION
The goals of this study are to synthesize concepts that relate depositional processes,
bioturbation, and resultant sedimentary fabric, then to evaluate these concepts in contrasting
depositional environments using a recently published approach for modeling the preservation
potential of sedimentary fabric undergoing bioturbation (Bentley and Sheremet, 2003). Fabric
and structures contained in sedimentary strata record environmental processes in the benthic
boundary layer near the time of sediment deposition. Specifically, preserved sedimentary fabric
records the competing processes of bioturbation, by which primary sedimentary fabric and
structures are replaced by biogenic fabric and structures, and sediment burial, which transports
sediments below depths of physical and biological reworking, thus preserving the resultant
fabric. Relations between physical and biological components of sedimentary fabric in both
ancient and recent sediments have been used to evaluate patterns of biological succession and
evolution (over timescales of seasons [Gingras et al., 2002] to eras [McIlroy et al., 1997]),
relative frequency and magnitude of depositional events (Howard, 1975), and the impact of other
environmental perturbations, such as anoxia (Savrda and Bottjer, 1986), and even benthic
response following the Cretaceous/Tertiary Impact Event (Ekdale et al., 1998). In studies of both
ancient and modern sedimentary strata, such interpretations have often been restricted to relative
interacting rates of depositional and biological processes, because absolute estimates of relevant
rates and timescales have been lacking. For example, Figure 1A shows a sandy event layer in the
Plio-Pleistocene Rio Dell Formation (northern California, USA) that displays a crossbedded sand
layer with a sharp basal contact, grading upward into bioturbated mudstone, with similar
bioturbated mudstone below. We recognize that the layer was deposited as a single event that
differed significantly from conditions before and after the event, and we can see that upper
portions of the event layer were slowly disrupted by bioturbation before being buried and
preserved. However, we have no way of knowing the exact timescales over which subsequent
burial and bioturbation occurred.
During the past four decades, important tools for the quantitative study of processes in the
benthic boundary layer have evolved, and have allowed us to estimate absolute rates and
timescales of interacting physical and biological sediment transport, accumulation (burial) and
mixing. Availability of these tools now allows us to take a more quantitative look and the
emplacement and evolution of sedimentary fabric. Key milestones include the advent and
application of geochronological tools based on short-lived particle reactive radioisotopes, such as
210Pb, 137Cs, 234Th , and 7Be, among others (Aller and Cochran, 1976; Nittrouer et al., 1979;
Sommerfield et al., 1999, and many others), new tools for imaging seafloor sediments (X-
radiography, and more recently, CT imaging), and the development of instruments and modeling
approaches for studying sediment and flow dynamics in the bottom boundary layer (Sternberg
and Creager, 1965; Sternberg and Larsen, 1975; Wright, 1995, and many others).
From these process studies of interacting sedimentation and bioturbation in the benthic
boundary layer, we have gained insights that are relevant to the study of both modern and ancient
sedimentary strata. One such important concept relates the character of preserved sedimentary
fabric (i.e., whether it is dominantly biogenic or physical in origin) to the competing processes of
bioturbation and sediment burial (Moore and Scruton, 1957; Howard, 1975; Nittrouer and
Sternberg, 1981, Wheatcroft, 1990, and many others). Specifically, we can hypothesize that
biogenic sedimentary fabric will tend to overprint physical sedimentary fabric (i.e., produced
during deposition or physical reworking) in sediments where and when the volumetric
bioturbation rate significantly exceeds the net combined rates of physical reworking and
deposition, when both biogenic and physical rates are measured over comparable depth and
timescales. The likelihood that a particular sediment layer will escape total disruption by
bioturbation before final burial is referred to as the preservation potential of the event layer
(Wheatcroft, 1990). The relevant length scales include the bioturbation depth Lb, which is the
depth in the seabed at which the bioturbation rate decreases to zero, and the thickness of an
individual sedimentary event layer, Ls (Fig. 1B). One important time scale is the length of time
required to bury a layer below depth Lb, which has been referred to as both the transit time
(Wheatcroft, 1990) and the residence time Tr (Bentley and Sheremet, 2003).
Bioturbation has been described as both a diffusive process, parameterized by the
biodiffusion coefficient Db (units of length2 time-1) (Boudreau, 1986; Wheatcroft et al., 1989, and
many others) and a reaction rate α (units of time-1) (Bentley and Sheremet, 2003). The diffusive
analogue is most useful in describing the redistribution of a particular sediment tracer (Guinasso
and Schink, 1975; Aller and Cochran, 1976; Nittrouer et al., 1984, and many others), whereas the
reaction rate concept can be more easily applied to the irreversible transformation of primary
depositional fabric to biogenic fabric (Bentley, 1998; Bentley and Sheremet, 2003) or
“ichnofabric” (e.g., Droser and Bottjer, 1986), which is the focus of this paper.
From observational studies, general rules have been developed in order to allow broader
comparison and generalization of the above bioturbation-sedimentation hypothesis. Four of the
more significant resulting concepts are:
Concept 1. Bioturbation is generally most rapid closest to the sediment-water interface, decreases
with increasing depth in the substrate, reaching zero at a finite depth (Berner, 1980, Boudreau,
1994, and many others). In many settings, but not all, this bioturbation depth (Lb) is significantly
greater than typical depths of hydrodynamic erosion (e.g., Wiberg, 2000; Wheatcroft and Drake,
2002).
Concept 2. Rapid sediment accumulation, whether in the form of many small frequent pulses, or
larger less frequent pulses, leads to greater preservation of primary sedimentary fabric (Moore
and Scruton, 1957; Howard, 1975; Nittrouer and Sternberg, 1981).
Concept 3. Deposition of event layers thicker than the depth of mixing allows complete
preservation of basal portions of the event layers, and event layers thinner than the depth of
mixing are likely to show signs of biological reworking (Nittrouer and Sternberg, 1981;
Wheatcroft, 1990; Wheatcroft and Drake, 2002).
Concept 4. Episodic sediment deposition leads to greater preservation potential for primary
sedimentary structure, because of reduced transit times in the mixed layer (Wheatcroft and
Drake, 2002; Wheatcroft et al., 2005; Wheatcroft, in press). This also implies that steady-state
sedimentation, with bioturbation, leads to lower preservation potential for primary sedimentary
fabric.
These generalizations, developed in the studies cited above, have been derived mostly from
relationships among spatially and temporally averaged accumulation and bioturbation rates,
bioturbation depths, and bed thicknesses. However, these same concepts point to the importance
of spatial and temporal variability in enhancing preservation potential of sedimentary fabric.
Accordingly, several recent studies have developed computational models of interacting
bioturbation and varying sedimentation, to test the aforementioned conceptual hypotheses
(Boudreau et al., 2001; Bentley and Sheremet, 2003; Keen et al., 2004). In the remainder of this
paper, we investigate the stratigraphic results of interacting bioturbation and unsteady
sedimentation in three contrasting depositional environments using the model of Bentley and
Sheremet (2003). The study areas are the Eel Shelf off Northern California, USA, a flood-
dominated open-shelf setting; Eckernförde Bay, a fjord-like bay in the German Baltic Sea; and
the mid continental shelf in the northern Gulf of Alaska, a wave-dominated open-shelf setting
with seasonally pulsed glacifluvial sediment supply. Model parameters and forcing for each
setting are derived from published studies of sedimentation and bioturbation rates and depths,
and modeled fabric will be compared with X-radiographs and other quantifications of biogenic
and physical sedimentary fabric.
2.0 MODEL AND METHODS
The model used herein to evaluate concepts 1-4 estimates the preservation quotient q (a
dimensionless measure for the fractional volume of sediment characterized by primary physical
sedimentary fabric) as a function of depth-limited bioturbation and time-dependent
sedimentation rate (Bentley and Sheremet, 2003). The local form of the general equation is:
,bqzt
=⎟⎠⎞
⎜⎝⎛
∂∂
+∂∂ ω
Eq. 1 subject to the boundary conditions
bLzatzq
zatqtqJ
==
==
0
0),(
∂∂
ω Eq. 2
where z = depth in sediment, ω = burial rate (cm y-1), q is the preservation quotient, J is the flux
of new sediment with q (0, t) = q0, and b is the local bioturbation rate. A simple relationship for
bioturbation rate that satisfies these conditions is
,)(),( qzzqb α−= Eq. 3
where α(z) is a first-order volumetric bioturbation rate constant α (y-1, or cm3 cm-3 y-1) with a
depth dependency described by
bLzforzz ≤−= )exp()( 0 βαα
bLzforz >= 0)(α Eq. 4
where α0 is the rate constant at z=0, and β is a depth-attenuation coefficient (cm-1) (Fig. 1B). The general solution to this equation along the trajectory z(z0, t) is:
.)()(exp),(
00 ⎥
⎦
⎤⎢⎣
⎡−= ∫
z
zdz
tzqtzq
ωα Eq. 5
Once a layer of sediment is buried below z = Lb, q(z,t) ceases to evolve, fabric is thus preserved,
and q(z,t) = qp, a constant value. This solution ignores erosion, which is an acceptable
assumption for the cases we are considering here, where erosion depths are generally much less
than Lb or Ls (e.g., Wiberg, 2000).
Other potential depth-distributions of α(z) could be used as well, such as linear, stepwise,
or parabolic distributions (for example, the evaluation of Db by Boudreau, 1986). However,
because so few observations exist on the depth distribution of volumetric bioturbation rates, we
suggest that to simply specify that α decreases with increasing depth is an appropriate starting
point.
Three separate computational approaches are used to evaluate q(z,t) for different model
scenarios in this paper. Solution 1 (Bentley and Sheremet, 2003) is an analytical solution for
equations 1-5, and allows evaluation of q(z,t) where a steady-state background burial rate ω0 is
episodically enhanced by a pulse of more rapid sedimentation, as in the formation of a storm or
flood deposit. Solution 2 is a numerical version of Solution 1, written in Matlab, used for
conditions where more than two episodic pulses and/or regular seasonal pulses are desired. For
Solution 2, the value of q(z,t) is integrated numerically.
Solution 3 uses the integration scheme of Solution 2, adapted to allow random fluctuations
of the burial rate typical of natural environments. The thickness of individual event layers is
specified by selection from a random exponential distribution of event-layer thicknesses,
following the approach of Niedoroda et al. (1989) and Bentley and Nittrouer (1999). The model
generates one depositional event per month for the duration of the model run. The random-
number generator in Matlab produces a uniform distribution of 0 ≤ ru < 1, where ru is the random
value generated. This value is converted to a random value re in an exponential distribution
(Hahn and Shapiro, 1967) by the relationship:
re = (-ln (1-ru))/B, Eq. 6
where B is the coefficient of an exponential probability density function (Swan and Sandilands,
1995) given by:
f(re) = B exp(-B re). Eq. 7
The probability (Pr) that a random value (re) will exceed some specified threshold (x) during a
specified time interval (such as the model’s monthly storm) is (from Swan and Sandilands,
1995):
Pr(re ≥ x) = exp(-B x), Eq. 8
which is also the mean recurrence frequency of x. The monthly random value re is converted to a
bed thickness (Ls) with an empirical formula:
Ls = C re3, Eq. 9
where C is an adjustable coefficient > 0. The coefficients B and C can be tuned so that the time-
averaged burial rate is a known near-constant value ω , but is produced by the integrated
deposition of many individual layers of random thickness and estimated return period (Bentley,
1998; Bentley and Nittrouer, 1999). (The Gumbel or Extreme Event Distribution is also
commonly used to relate magnitude and return period of natural events; however, so few relevant
data exist that we retain the basic exponential distribution for simplicity.) Solutions 2 and 3
follow user-specified timesteps of 0.01-0.04 y, and performance of each model has been verified
through comparisons with analytical solutions for steady-state conditions.
3.0 MODEL PARAMETERS AND MODEL-DATA COMPARISON
Values of model parameters used herein are derived from case studies of the three study
areas (Table 1). In each case, previous studies have estimated time-averaged accumulation rates
using 210Pb/137Cs geochronology. These observations provide constraints for accumulation rates
produced by model runs (ω ). For the Eel Shelf and Eckernförde Bay, observations exist that
describe known event layer thicknesses, dates, and possible return periods, and seasonal
variability of sediment supply has been documented for the Gulf of Alaska shelf (see Jaeger and
Nittrouer, this volume, Figs. 3 and 4), thus allowing for the estimation of ω(t) or B and C, as
needed. Also available for all cases are estimates of the biodiffusion coefficient Db (derived from
234Th profiles of multiple cores), the bioturbation depth Lb, and, for the Eel Shelf, estimates of
the depth-attenuation of bioturbation intensity.
We have used two separate approaches to estimate the values of α0 and β (Eq. 4). Studies
of the Eel Shelf and Gulf of Alaska shelf have produced estimates of the sediment bioturbation
timescale Tb (from X-radiographic and radioisotope data; Bentley and Nittrouer, 2003; Jaeger
and Nittrouer, this volume), which we consider to be the inverse of a depth-averaged
bioturbation rate constant,α . For the Eel Shelf, estimates of Tb are made for both rapid, shallow
bioturbation, as well as for deeper, slower bioturbation. For the Gulf of Alaska, no depth
dependence of bioturbation rate is considered, and estimates of Tb integrate bioturbation for the
entire mixed layer. For each of these cases, we have selected reasonable values of α0 and β such
that, over appropriate depth ranges, α ≅ 1/Tb (Table 1). In the case of Eckernförde Bay, we
follow a similar procedure, with the additional step of estimating Tb from the relationship Db =
L2/2t (Boudreau, 1986), wherein we assume that Lb ~ L, and t ~ Tb (Bentley, 1998; Bentley and
Sheremet, 2003).
For each study area, biogenic and physical sedimentary fabric observed in core X-
radiographs have been described in detail, and have been summarized in the form of maps of
lithofacies assemblages (Gulf of Alaska) or spatial and depth-distribution of fabric types and
sedimentary structures (Eckernförde Bay and Eel Shelf). Thus, the observations used to force
model simulations (i.e., sedimentation rates and bioturbation rates and depths) are generally
independent of the X-radiographic data to which we compare model results.
3.1 Eckernförde Bay
Eckernförde Bay is a fjord-shaped embayment in the southwestern German Baltic Sea that
was the subject of intense investigation through the Coastal Benthic Boundary Layer Project
(CBBL), an interdisciplinary investigation of continental shelf sediments (Richardson, 1994) (Fig.
2). The bay is a sink for fine sediments of high organic content, and has a history of seasonal
hypoxia and anoxia extending back over a century (Rumohr, 1986; Wiegelt, 1991). The region is
microtidal, and other significant elements of the hydraulic regime include oscillations of the
Baltic seiche (vertical excursions to ~25 cm) (Friedrichs and Wright, 1995) and currents and
waves from winter storms (Milkert and Werner, 1995), which can transport sediment from the
bay coastline into the central basin. The resulting deposits have sedimentary characteristics
similar to tempestites observed in the North Sea and elsewhere (Aigner and Reineck, 1982).
However, Friedrichs and Wright (1995) suggest that particle resuspension during storms in the
deep central basin of the bay should be negligible, due to water depth and fetch limitations. This
conclusion is consistent with the character of distal storm deposits (fine-grained, thin beds, rare
cross-stratification) observed by Milkert and Werner (1995) in box cores taken following major
winter storms.
Sediments are accumulating in the central basin of the bay at ~0.4 cm y-1, due to
combination of storm sedimentation, that delivers ~ 0.25 cm y-1 of sediment (Milkert, 1996;
Bentley and Nittrouer, 1999), and estuarine-like processes (~ 0.15 cm y-1), whereby sediments
resuspended in the open Baltic are advected into the bay and are deposited, due to weak currents
in fair-weather conditions (Friedrichs and Wright, 1995). These sediments are then mixed by the
small-bodied opportunistic macrofaunal community (bodies < 10 mm), composed largely of
capitellid polychaetes and tellinid bivalves (D’Andrea et al., 1996). Profiles of 234Th from the
bay suggest a value for Lb of ~1 cm, and Db ~ 0.7 cm2 y-1 (Bentley and Nittrouer, 1996, 1999).
The interaction of bioturbation with combined fair-weather depositional processes and episodic
event-layer deposition produces alternating pelletal beds and physically stratified laminations of
fine sediment (Fig. 3). Bioturbation can totally rework depositional sedimentary fabric
conditions of fair-weather sediment deposition, even though mixing is restricted to the upper
centimeter of the seabed and bioturbation is periodically interrupted by anoxic events. Under
storm conditions, deposition of event layers thicker than the depth of bioturbation overwhelms
the macrofauna, and results in at least partial preservation of event-layer stratification. The
recurrence interval of events producing preserved stratification is ~10 years or greater, suggested
by both historical data (Milkert and Werner, 1995) (Figure 3) and Monte Carlo simulations of
storm sedimentation (Bentley and Nittrouer, 1999). This mechanism for producing laminations
in anoxic sediments differs from conclusions of previous studies in oxygen-stressed settings,
which offer anoxic bottom water and cessation of bioturbation as the primary formative process
for fine-scale physical stratification.
In order to test this conceptual model of stratal formation for Eckernförde Bay, we
conducted simulations of sedimentation and bioturbation using Solution 2 of Equation 1 , as well
as Solution 3 of Equation 1 (Figs. 4 and 5). Two separate bioturbation regimes were evaluated,
based on 234Th profiles of Bentley and Nittrouer (1999), which suggest relatively slow time-
averaged bioturbation, and a more rapid rate suggested by the deliberate-tracer mesocosm study
of D’Andrea et al. (1996). Figure 4 displays the results of these two bioturbation regimes acting
on identical time series of pulsed and background sediment deposition. For comparison, the
interpreted X-radiograph in Figure 3 shows a partially bioturbated event layer at ~ 18 cm depth
in seabed (characteristic of numerous cores described by Bentley and Nittrouer, 1999),
suggesting that the actual bioturbation regime in the bay is weak enough to allow recognizable
preservation of event layers thinner than Lb. In turn, this observation suggests that the slower
bioturbation regime (Figure 4, right panel) is probably closest to actual conditions in the bay,
because of the higher values of qp associated with the 1-cm event layer (i.e., the 1-cm event layer
in Figure 4B is partially bioturbated, but would probably be recognizable in an X-radiograph).
To simulate longer-term processes, the slower bioturbation regime was then applied in
simulations using Solution 3, whereby all annual sedimentation is deposited in the form of event
layers of random thickness that are sampled from an exponential probability density function
(Eq. 7). The values of B and C, used to tune the event-sedimentation regime (Eqs. 6-9), are very
close to those tested in the Monte Carlo simulations of Bentley and Nittrouer (1999). These
parameters generate a mean accumulation rate of ~0.4 cm y-1 from individual monthly beds up to
~2 cm thick over model runs of 60 y. Simulation results shown in Figure 5 suggest that basal
portions of four event layers should be recognizable (for these layers, Ls > Lb, and q=1 for the
basal contact), and at least four thinner layers have values of qp >~0.5, suggesting that the upper
and lower contacts would be bioturbated, but recognizable (Figs. 3 and 5). These results thus
support the conceptual model of Bentley and Nittrouer (1999), and provide examples of the
importance of thick event layers (Concept 3) and pulsed sedimentation (Concept 4) on the
character of preserved sedimentary fabric, even where mixing depths and event layer thicknesses
are minimal.
3.2 Eel Shelf
The Eel Shelf is a reentrant on the northern California coast, bounded by Cape Mendocino to the
south, and Trinidad Head to the north (Fig. 6), and has been the location of extensive
investigations into shelf-sediment transport, bioturbation, and accumulation during recent years,
primarily through the Office of Naval Research STRATAFORM program (Wheatcroft et al.,
1996; Cacchione et al., 1999; Sommerfield and Nittrouer, 1999; Wright et al., 1999; Cutter and
Diaz, 2000; Traykovski et al., 2000; Wheatcroft and Borgeld, 2000; Bentley and Nittrouer,
2003). Most sediment reaching the shelf (~90%) is supplied by winter floods on the Eel River,
which has a highly seasonal flow and is the largest single source of sediment to the California
margin (Griggs and Hein, 1979). The same storms that create flooding on the Eel River also
produce large waves (> 8 m, with bottom-orbital velocities > 50 cm s-1 at 60 m water depth) and
northward coastal currents. During periods of flooding, muddy plumes of river discharge are
confined initially to the sandy innermost shelf (< 30 m depth), but gravity-forced density flows
of fluid mud trapped within the wave boundary layer (Traykovski et al., 2000) eventually
transport flood sediment to the middle shelf where mud is accumulating at rates of 0.5-1 cm y-1
(based on 210Pb and 14C geochronology; Sommerfield and Nittrouer, 1999) (Fig. 6). Field
observations between February 1995 and July 1998 documented the formation of shelf-mud
layers to ~10 cm thick following two major floods (January 1995; January 1997) (Wheatcroft et
al., 1996; Drake, 1999; Cutter and Diaz, 2000; Wheatcroft and Borgeld, 2000; Bentley and
Nittrouer, 2003). During the same period, non-flood “dry storms” resulted in reactivation and
seaward transport of coarse inner-shelf sand and silt (Cacchione et al., 1999; Drake, 1999;
Ogston and Sternberg, 1999).
The macrofaunal community can mix the upper ~5 cm of the seabed completely over
periods of weeks to months (Bentley and Nittrouer, 2003), and shows little evidence of
disturbance resulting from flood layer deposition (Wheatcroft, in press). As a result, only event-
layers >5 cm thick (thickest fine-grained flood layers) are likely to escape erasure by
bioturbation, and thinner layers (thinner flood layers and sand/silt layers deposited from
wave/current transport) are rapidly reworked (Wheatcroft and Drake, 2003). Where preserved,
however, clay-rich flood layers contrast distinctly with the enclosing matrix of coarser
bioturbated strata.
Although thick event layers appear to be deposited commonly on the Eel Shelf, in all cases
observed to date, Ls< Lb, suggesting that all portions of each event layer should be at least
partially disrupted by bioturbation, and for cases when Ls << Lb, all primary depositional fabric
might be destroyed. Nevertheless, partially preserved event layers are evident in piston cores
from the shelf (Sommerfield et al., 2002; Bentley and Nittrouer, 2003). As discussed by
Wheatcroft and Drake (2003) and Wheatcroft (in press), only under exceptional cases is
significant event layer preservation likely, when either Ls >Lb, or when the event-layer residence
time Tr is shortened due to subsequent deposition of another event layer.
As noted above, two thick event layers were deposited on the middle Eel Shelf in 1995 and
1997, enhancing preservation potential for basal portions of the older layer, as shown in Figure 7.
In this case, Ls (1995) + Ls (1997) ~ 15 cm, approximately the same as Lb, and as a result,
Wheatcroft and Drake (2003) and Bentley and Nittrouer (2003) have suggested that preservation
of basal portions of the 1995 event layer is likely. We have evaluated this possibility using
Solution 2 for Equation 1, and parameters shown in Table 1, to compare modeled q(z,t) and
actual fabric evident in X-radiographs of the Eel Shelf depocenter (specific run conditions are
listed in the Figure 7 caption). Values of q in the X-radiograph were estimated by placing a 1-cm
grid across the image scaled to actual size, and tabulating the number of vertices at each depth
where primary stratification was evident (scatter plot in Figure 7), similar to point counting of
petrographic thin sections. Model and tabulated results compare favorably, except for near the
seabed, where the model overpredicts q(z,t), suggesting that (1) mixing processes at the seabed
(possibly physical and biological) are more rapid than the model accounts for, but (2) modeled
bioturbation deeper in the seabed is a reasonable portrayal of actual conditions.
The model-data comparison in Figure 7 represents only one point in a relatively vast
parameter space that could represent long-term conditions on the Eel Shelf. In order to conduct a
more in-depth study of this parameter space, we have conducted simulations for qp using
Solution 1 for a range of bioturbation, sedimentation regimes (Table 1), and pulse separations
(Figure 8). For individual model runs, two event layers of Ls = 7 cm are deposited on the seabed
with pulse separations varied from 0 to 10 y, and are buried by background sedimentation rates
of 0.1 cm y-1 (left side) or 0.3 cm y-1 (right side) until the top of the second event layer is buried
below depth Lb. The final profile of (qp, z) for each run has been combined with others profiles
of identical Ls, α0, β, and ω0, but different pulse separations to create each individual plot. The
range of model-generated time-averaged sedimentation rates (including ω0 and Ls) is ~0.2-0.6
cm y-1 over 60-200 y, depending on the model run, and is on the lower side of the range for
210Pb accumulation rates measured for the Eel Shelf depocenter (Sommerfield and Nittrouer,
1999). 210Pb geochronology averages accumulation rates over timescales of ~ 100y, comparable
to our model runs.
Our model simulations demonstrate that the timing of depositional events does exert strong
control on the preservation potential of the first event layer, but bioturbation rate near the base of
the bioturbated zone is also an important determinant in the final value of q. For β = 0.2, α over
the depth interval 10-15 cm is ~10% of α0, with corresponding α /α0 ratios of 0.2% and 0.001%
for β = 0.5 and 1, respectively. Bentley and Nittrouer (2003) state that timescales of bioturbation
near depth Lb are 30-300 y, suggesting that β~0.2-0.5 is most representative of present
conditions. In any case, results in Figure 8 are indicative of the important roles that both deep,
slow mixing (Concept 1) and episodic sediment deposition (Concept 4) play in the preservation
potential of primary depositional fabric.
3.3 Northern Gulf of Alaska
In the northern Gulf of Alaska, Jaeger and Nittrouer (this volume) investigate processes of
shelf stratal formation along the glaciated, mountainous coastline of south-central Alaska from
the Alsek River to Prince William Sound (Fig. 9). Radioisotope-derived sediment accumulation
rates in the open-shelfal areas are highest ( > 1 cm y-1) at mid-shelf depths and are >2 cm y-1 on
the Copper River delta and near rivers draining the Bering Glacier. Similar spatial patterns in
sediment accumulation between centennial and Holocene time scales reflect the dominance of
the Copper River and Bering and Malaspina glaciers as sediment sources. The formation of
lithofacies was investigated using short-lived tracers 234Th and chlorophyll-a and X-radiography
of cores. Five lithofacies can be identified for the study area: an inner shelf sand facies, a
partially laminated bioturbated mud facies, a bioturbated mud facies, a gravelly mud facies, and
a tertiary bedrock facies. The bioturbated and partially laminated mud facies are dominant,
representing over 75% of the shelf area, and roughly equal volumes of both facies are preserved.
Jaeger and Nittrouer propose that the differences in sedimentary fabric between these two
dominant facies (i.e., partially laminated versus fully bioturbated) are controlled by differing
sediment accumulation rates and bioturbation depth and intensity. The range of Db and Lb values
for this study area (5-10 cm2 y-1 and 4-7 cm, respectively) represent generally less intense
bioturbation than is typical of many accretionary shelf settings (e.g., Boudreau, 1994; Bentley
and Nittrouer, 2003; Jaeger and Nittrouer, this volume; Wheatcroft et al., in press). The lower
intensity and shallowness of bioturbation may reflect the relative lower organic matter
concentrations in sediments due to dilution from higher deposition rates of glacial rock flour.
Sediment flux to the shelf is controlled primarily by seasonal snowmelt and glacial meltwater
pulses that release most sediment from glacifluvial sources during the months of July-September
(Figure 2 in Jaeger and Nittrouer, this volume). Interannual variability in river discharge is less
than a factor of four (Fig. 2, Jaeger and Nittrouer, this volume), reflecting the modulating
influence of glacial melting on freshwater release, and is significantly less variable than non-
glacial rivers (e.g., Moorehead et al., 2003). Although these summer months are less stormy
than the winter season, mean wave heights remain relatively high, and resultant bottom orbital
velocities are sufficient to remobilize fresh sediment from the inner to middle shelf. Wave
energy thus creates the potential for seaward verging wave-enhanced gravity flows, similar to
those recently described for other wave-influenced accretionary shelf settings (Traykovski et al.,
2000; Wright et al., 2001; Friedrichs et al., 2003, among others). The resultant cross-shelf
sediment flux produces mud accumulation that can exceed 2 cm y-1 in water depths of 50-100 m,
with most sediment delivered during late summer months. These conditions of sediment supply
suggest relatively regular seasonal pulses of sediment, contrasting with the episodic flood-driven
sediment flux on the Eel Shelf, for example.
Jaeger and Nittrouer (this volume) state that, in general, the partially laminated mud facies
is characterized by both the most rapid sediment accumulation (> 1 cm y-1) and the deepest and
more intense bioturbation (Db ~10 cm2 y-1, Lb ~ 7 cm) in their study area. In order to evaluate
how this suite of seafloor processes influences preserved sedimentary fabric, we have conducted
simulations using Solution 2 of Equation 1, and the range of parameters for the Gulf of Alaska
Shelf (Table 1; Fig. 10). Conditions for slow, shallow bioturbation (α0 = 1, β = 0.5, Lb = 4) and
more rapid, deeper bioturbation were used (α0 = 1.5, β = 0.5, Lb = 7), based on the range of Lb
and Tb estimated by Jaeger and Nittrouer (this volume). For comparison, bioturbation conditions
typical of the Eel Shelf (α0 = 2.3, β = 0.5, Lb = 15) were also simulated (Fig. 10 B and C).
Sediment deposition was assumed to occur both as a background steady-state flux ω0, which was
set at ~10% of total annual accumulation, and as seasonal pulses for the remaining 90%. Three
sediment pulses were annually delivered with one each in July, August, and September in the
following manner: (1) as equal thickness for total annual accumulation rates of ~0.5 and 1.0 cm
y-1 (Fig. 10A, 0.15 or 0.3 cm each, respectively); (2) in decreasing thickness for accumulation
rates of 1.5 and 2.8 cm y-1 (0.8, 0.4, and 0.2 cm, or 1.2, 0.9, and 0.6 cm, respectively) (Figs. 10 B
and C); (3) as three monthly pulses with random normal distributions around mean thicknesses
of 0.8, 0.4, and 0.2 cm, or 1.2, 0.9, and 0.6 cm for average accumulation rates of ~1.5 and ~2.8
cm y-1, respectively (Fig. 10D).
For all simulations, values of q below Lb (i.e., q in preserved fabric) exceed 0.5 only in
settings with accumulation rates > 1 cm y-1 Fig. 10). For the non-random-pulse, 1.5 cm y-1 case
(Fig. 10B), q >0.5 only for the weakest bioturbation conditions. In addition, the simulations in
Figure 10D show that random variability in pulse thickness can increase episodic burial rates,
resulting in a higher value of q even when Ls << LB. These model conditions (Fig. 10D) are
probably most comparable to actual conditions in the partially laminated facies on the Gulf of
Alaska Shelf (Figs. 4, 7; Jaeger and Nittrouer, this volume), where time-averaged deposition is
characterized by relatively uniform, but nevertheless random, pulses of sediment deposition that
results in sporadic preservation of relatively thin beds. Model simulations thus agree with the
findings of Jaeger and Nittrouer (this volume), in that, regardless of the bioturbation conditions,
recognizable primary depositional fabric is only likely to be preserved in settings where
accumulation rates exceed ~1.5 cm y-1. However, lenses of bedded or laminated sediments not
readily identifiable in X-radiographs (but perhaps evident in thin section or outcrop) could be
preserved under annual accumulation rates of ~1 cm y-1 (i.e., where qp>~0.3).
4.0 CONCLUSIONS
In this paper, we have compared actual record of preserved primary depositional fabric
with model predictions of fabric for three contrasting marine depositional settings spanning a
>ten-fold range of average sediment accumulation rates, event-layer thicknesses, bioturbation
depths, and bioturbation rates. Our analysis of models and data for these three settings supports
and expands on important existing concepts of organism-sediment interactions. From this study,
we have the following major conclusions:
1. Concepts that relate preservation potential of primary depositional fabric to time-
averaged bioturbation rate and depth and episodic sedimentation rate are applicable
and scale independent over a wide range of rates and length scales.
2. The preservation potential of event layers in settings with deep bioturbation (Eel
Shelf) is highly sensitive to both the burial rate produced by episodic sedimentation
as well as the bioturbation rate at depths ~Lb.
3. Episodic or periodic (e.g., seasonal) variations in the burial rate can allow for
significant preservation of primary fabric even when Ls << Lb (Gulf of Alaska).
4. The model approach utilized here provides a flexible and useful framework for
detailed analysis of sedimentary fabrics that result from interacting depositional and
bioturbation processes common to many aquatic settings. It provides numerical
results that can be readily compared to records of sedimentary fabric. This approach
also allows for evaluation of more complex process interactions than can be
accomplished with older methods that scale burial and mixing rates as relative
measures of preservation potential.
ACKNOWLEDGEMENTS
This effort was supported in part by National Science Foundation grant OCE-0093204 to
S.J.B., who also thanks Steven Chan and Angelina Freeman for building user interfaces
to code used for this study.
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TABLES
Table 1. Bioturbation and sedimentation parameters for model runs.
Location Lb Ls (max) Db ω α0 β Data Source Eel Shelf ~15 < 9 cm 10-100 0.6 0.8-2.3 0.2-
1.0 Bentley and Nittrouer, 2003;
Wheatcroft et al., 2005 Eckernförde Bay <1 < 1.5 0.7 0.4 2.8 0.5 Bentley and Nittrouer, 1999 Alaska Shelf 4-7 1.2 * 5-10 0.5-3 1, 1.5 0.5 Jaeger and Nittrouer, this
volume
* for purposes of evaluating the influence of seasonal, non-storm related event layers; episodic
event layers may be thicker (Jaeger and Nittrouer, this volume).
FIGURES
LB
LS
BioturbationRate α
Event Layer
Zone ofBioturbation
Historical Zone: Preserved Fabric
Sedimentation Rate ωA
B
Figure 1. A) This photograph of a storm bed from the Plio-Pleistocene Rio Dell Formation
(northern California, USA), illustrates important concepts in this paper, including: the depth of
bioturbation Lb; the thickness of the storm bed Ls; and that biological reworking of an event layer
is generally greatest near the top of the layer, where preservation of depositional fabric is
generally poorest. B) Schematic illustration of these concepts, showing an event layer of
thickness Ls that is thinner than bioturbation depth Lb. The layer is bioturbated at a rate α(z) until
it is buried below depth Lb, after which is it preserved in the “historical layer,” a term introduced
by Berger et al. (1979).
A
B
Nor
th
1 kmCI = 10 m
Mittelgrund
Core LocationsEckernförde BaySouthwestern Baltic SeaGermany
20
10
10 20
20 10
10
20
54° 27.5' N
54° 30' NEckernfördeNavy Base
Bocknis Eck
Kiel BightEckernförde
54°N
9°E
11°E
Nor
th S
ea
10°
E
Fig 2B
April '93
May '93
Figure 2. A) Location map of Eckernförde Bay, adapted from Bentley and Nittrouer (1999). B)
Steep walls and a sill near the bay mouth result in restricted fjord-like circulation that results in
seasonal hypoxia/anoxia, and thus impacts the macrofaunal community. The bay is also open to
the northeast, making fetch favorable for wave generation during winter storms (Milkert, 1996).
Depth Distributions of Burrows and Laminations
Number of Burrows and Laminations, All Cores (n=38)0 2 4 6 8 10 12 14 16 18 20
Dep
thin
Seab
ed(c
m)
0
5
10
15
20
25
Burrows
Laminations
1989
1976
1964
1950
1937
Sediment surfacePectinaria tube
Storm layers
Storm layer
Pelletal bed
Bivalve
Bioturbated storm layer
Bivalves
Cinders
cm-scale mottling
Partings from gas bubbles
Bioturbated storm layer
Cen
timet
ers
0
20
BS1-BC78
Figure 3. A) Plot of depth distributions for laminations and burrows, demonstrating partial
preservation of storm beds from historical storms that occurred in years shown on the plot. Data
were extracted from 38 X-radiographs of closely spaced boxcores taken in the bay. The age
model is derived from 210Pb/137Cs geochronology. B) Typical X-radiograph and interpretation
from the bay, showing partial preservation of basal portions for four storm layers. Vertical scales
are identical in (A) and (B). Data for A and B from Bentley and Nittrouer (1999) with
permission.
Simulations of q for Eckernförde Bay
q0.0 0.2 0.4 0.6 0.8 1.0
Dep
th in
Sea
bed
0
1
2
3
4
5
6
Instantaneous Burial Rate ω, cm y-10 5 10 15 20 25 30
0.0 0.2 0.4 0.6 0.8 1.0
0 5 10 15 20 25 30
ω ω
α0 = 10, β = 0.5, Lb = 1 α0 = 2.8, β = 0.5, Lb = 1
Figure 4. Model simulations of q(z,t) (shaded area plots) for identical sedimentation regimes (Ls
= 1 and 2 cm respectively, and ω0 = 0.4 cm y-1, shown by line plots) with rapid bioturbation on
the left (α0 = 10, based on the tracer study of D’Andrea and Lopez, 1996), and slower
bioturbation on the right (α0 = 2.8, derived from 234Th data of Bentley and Nittrouer, 1999). Lb =
1 and β = 0.5 for both cases. Based on patterns of bed preservation shown in Figure 3, α0= 2.8 is
probably most representative of conditions during the past 50-60 y. Note also that qp is enhanced
for strata immediately below the event layers, due to rapid burial below Lb.
Figure 5. A 60-y simulation of storm simulation and depth-limited bioturbation (α0 = 2.8, β =
0.5, and Lb = 1) in the central basin of Eckernförde Bay. The value of q(z,t) is indicated by the
color bar on the right, with q=100 for complete preservation of primary fabric. Sediment flux is
forced by sampling randomly from an exponential thickness-return period relationship described
in eqs. 6-9, where B = 6.0, and C = 1.2 cm. Individual beds are thus buried through time,
following a downward stepwise trajectory from left to right. The resulting mean sediment
accumulation rate for this run is 0.42 cm y-1, close to the mean of 0.4 cm y-1 estimated by
Bentley and Nittrouer (1999) from 210Pb/137Cs geochronology. Event layer properties and
preservation in this run (maximum Ls ~2 cm, qp ~ 1.0 in ~4 beds) are comparable to patterns in
core X-radiographs from the bay, shown in Figure 4.
600500
400300200
10090 70 50
3010
30
5090 70100
150200
900
Arcata
Eureka
Trinidad
Cape Mendocino
150
41° 00'
40° 30'
124° 00'
124° 30'
Mad River
Humboldt Bay
EelRiver
..
600
S Transect
0 km 10
.
San Francisco
StudyArea
Eel Shelf Study Area
N. CaliforniaIsobaths in metersN
Figure 6. Location map of the Eel Shelf, northern California, USA, showing the typical coastal
trajectory of buoyant flood plumes from the Eel River (gray pattern along the coast), the location
of the mid-shelf depocenter identified by Wheatcroft et al. (1996) and Sommerfield and Nittrouer
(1999), and the stations discussed by Bentley and Nittrouer (2003) and this paper (S-transect).
Modeled and measured q
q
0.0 0.2 0.4 0.6 0.8 1.0
0
5
10
15
20
25
Figure 7. Modeled q(z,t) (line plot) for conditions at the S-60 station on the Eel Shelf (Table 1,
Bentley and Nittrouer, 2003) and measured q (scatter plot) from a typical X-radiograph from that
station. Error bars for measured q (q ± 0.1 and z±1 cm) reflect measurement resolution,
described in the text. This core was collected in June 1997, approximately 5 months after the
second of two major floods on the Eel River that occurred during the STRATAFORM study
period (see Wheatcroft and Drake, 2003, for discussion). In the X-radiograph, evident are the
presence of both large, discrete biogenic structures (produced by deep deposit feeders), as well as
fine-scale mottling produced near the sediment surface by shallow/surface deposit feeders.
Approximate boundaries for the 1995 and 1997 flood layers are indicated by arrows to the left of
the X-radiograph. Parameters for the model run are: α0 = 2.3, β = 0.5, Lb = 15, ω0 = 0.6,
simulation duration 12.5 y, with pulses of Ls = 9 and 6 cm in year 10, month 1, and year 12,
month 1. Note that, as of June 1997, only the basal portion of the 1995 flood layer was buried
below depth Lb ~ 15 cm.
α ω0 0=0.8 y , =0.3 cm y-1 -1 α ω0 0=0.8 y , =0.1 cm y-1 -1
β0=0.5 cm-1
β0=0.2 cm-1
β0=1.0 cm-1
Figure 8. Simulations of qp for two event layers, showing the effects of time lag between events,
as well as varied background sedimentation rate and depth-attenuation of bioturbation. Model
conditions are Ls = 7 cm for each event, lags of 0-10 y between pulses and α0 = 0.8 y-1 (all
plots), ω0 = 0.3 cm y-1 (left column), ω0 = 0.1 cm y-1 (right column), and β = 0.2 cm-1 (top row),
β = 0.5 cm-1 (middle row), β = 1.0 cm-1 (bottom row). Color contours represent final “preserved”
value of q after both event layers for each run are buried below depth Lb, as discussed in the text.
Upper and lower contacts of the event layers are indicated by blue lines. For comparison, the Eel
Shelf event layers shown in Figure 7 were separated by a lag of 2 y, and were both mostly still
within the bioturbated zone in 1997, when the core shown was collected, and as simulated in
Figure 7.
Figure 9. Map of lithofacies on the northern Gulf of Alaska continental shelf, adapted from
Jaeger and Nittrouer, this volume. The two dominant lithofacies include the partially laminated
bioturbated mud facies, which is generally located close to major glacifluvial sediment sources
and near storm wave base, and the homogeneous bioturbated mud facies, which is more distal to
sediment sources, and is below wave base.
Gulf of Alaska Shelf q model profiles
0.0 0.3 0.6 0.9
Dep
th in
Sea
bed
(cm
)0
2
4
6
8
10
12
14
0.0 0.3 0.6 0.9q
0.0 0.3 0.6 0.9
0.5, 1 cm/y 1.5 cm/y2.8 cm/y
0.0 0.3 0.6 0.9
1.5 and 2.8 cm/y
A B C D
Figure 10. Simulation of q(z,t) for a range of conditions observed on the northern Gulf of Alaska
shelf; for comparison, Figures 10B and 10C also include more intense bioturbation conditions
comparable to the Eel Shelf depocenter. For all runs, β = 0.5. A) Left and middle, Ls = 0.15 cm
month-1 for three months each year, ω0 = 0.05 cm y-1, ω =0.5 cm y-1, α0 = 1.5 y-1 and Lb = 7 cm
(left) and α0 = 1 y-1 and Lb = 4 cm (middle); right, Ls = 0.3 cm month-1 for three months, ω0 =
0.1 cm y-1, ω =1.0 cm y-1, α0 = 1 y-1 and Lb = 4 cm. B) Ls = 0.8, 0.4 , 0.2 cm month-1 over three
months, ω0 = 0.1 cm y-1, ω =1.5 cm y-1, Lb = 15, 7, 4 cm (left to right, respectively), and α0 =
2.3, 1.5, 1.0 cm-1. C) Ls = 0.9, 0.6 , 0.3 cm month-1 over three months, ω0 = 0.1 cm y-1, ω =2.8
cm y-1, with Lb and α0 same as (B). D) Lb = 7 and α0 = 1.5 for both; sediment pulses are
randomized around monthly means of (left) Ls = 0.8, 0.4, 0.2 cm month-1 (ω =1.5 cm y-1) and
(right) Ls = 0.9, 0.6 , 0.3 cm month-1(ω =2.8 cm y-1).