sediment out washing from the bering sea recorded by grain size using the laser diffraction particle...

8/14/2019 Sediment Out Washing From the Bering Sea Recorded by Grain Size Using the Laser Diffraction Particle Analyser

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Sediment transport from the Bering Sea(Meiji Drift) to the North Pacific Ocean

as recorded by grain size

O.M JINADU

Department of Geology & Petroleum Geology, School of Geosciences, University of Aberdeen, Aberdeen AB24 3UE, UK

ABSTRACT

A thick sediment body deposit known as the Meiji drift is located in the northwestern

Pacific Ocean. It was proposed to have been formed from deep water exiting the Bering Sea

under the influence of thermohaline circulation. The grain size of clay, silt and sandy layers

from the Ocean Drilling Programme (ODP) site 884 was determined using laser diffraction

grain analysis to investigate changes in palaeocurrent velocity and sediment source to the

Meiji drift over the last 10 myr, with emphasis on Quaternary glacial and interglacial

periods. There was a subtle change in mean grain size during the onset of Northern

Hemisphere Glaciation (~2.6 Ma). During the last 150 ka grain size show trends that

indicate the palaeocurrent velocity of deep water in the Meiji drift may have changed

through time.

Introduction

The Meiji sediment drift is up to 1800 m

thick, over 1000 km long and approximately 350

Km wide. The Meiji drift deposition was caused

by the connection between the bottom water and

the bearing sea circulation pattern. It is

suggested that the deposition is formed under

the influence of the thermohaline circulation

(THC) (Mammerickx 1985; Rea et al., 1995;

Scholl et al., 2003). It is thought that the

deposition first began in the Oligocene and

sediments are still being deposited to this day

(David w. Scholl et al; 1973 Rea et al 1995).

Diatoms have been observed at site 884 (Barron

and Gledenkov, 1995). The sources to the Meiji

Drift are Bering-derived material during

glacials and volcanic-arc material from the

nearby Aleutian and Kamchatkan volcanic

regions (VanLaningham et al., 2009). The

isotope recordings from the last Glacial

Maximum show that there were little or no

salinity changes (Keigwin, 1987 Keigwin et al;2003). It was also found that the current salinity

of the surface water at this time is not high

enough to cause THC in the Bering Sea

(Warren, 1983; Emile-Geay et al., 2003). There

are a number of possible explanations for this.

For example it is possible that the Asian

monsoon adds a large amount of fresh water to

the North Pacific via the western boundary

current.

The processes that cause a sediment drift

can be characterized by the documentation and

analysis of sources of the sediment, and also bythe examination of the changes in grain size.

Grain size analysis is a common sedimentologic

tool widely used for the study of marine

deposits, where particle sizes imitate the

processes that generated the clasts, including

weathering, erosion, transport, andsedimentation. Grain size analyses of marine

sediments have been effectively used in

combination with other paleoceanographic

proxies to document past changes in strength ofbottom currents and upwelling i.e. Warner and

Domak (2002) analysed glacial marine

sediments from the Antarctic as a

paleoenvironmental proxy and correlated it with

the downcore variations of magnetic

susceptibility. Modern tools such as X-ray

attenuation (sedigraph), coulter counter

(electroresistance) and photohydrometer are

automated instruments that estimate grain size

distribution. The laser diffraction particle size

analyser is the latest instrument that offers the

most effective way to perform rapid analyses of

very fine grained sediments on very small

samples.

Laser diffraction grain analysis was used

here to analyse the clay, silt and sandy layers of

the samples taken from the Ocean Drilling

Project Programme (ODP) site 884b (Rea et al.,

1995; Fig 1).Measurements were taken from

samples spanning the last 10 Ma with paying

particular attention to the last 150,000yrs so as

examine the Pliocene-Quaternary transition and

the potential influence of the Milankovitch

cycles. Fine grained samples were mostly

focused on because the platy shape of clayparticles gives them more area to be measured

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(Konert et al., 1997), making it easier to collect

accurate and relevant data. Furthermore, upto

40 samples can be run at the same time and data

can be collectively and rapidly.

Study area

The samples were taken from the Meiji Drift,

which is located on the eastern flanks of the

Emperor Seamount chain in the northwest Pacific

Ocean. Fig 1 and 2 show the proximal contributing

terrigenous sediment sources to the Bering/NW

Pacific region. The major rivers basins in the region

are the Anadyr, Yukon, Kuskokwim and

Kamchatka Rivers.

Using HYDROTEND model by Syvisky et al

(2003) it was noted that approximately 2-8million

metric (Mt) is delivered to the Meiji drift each year

from three rivers (Kuskokwim, Anadyr and

Kamchatka) while Eberl (2004) predicted the

Yukon has delivered 55 Mt of sediments per year to

the ocean during historic times. Most of the

sediments input to the Meiji Drift are from fluvial

sources but some other materials may be adverted

to the Meiji region by the Kuroshio Current and the

Alaskan Stream (Figure 1). Deposits such as ice-

rafted debris (IRD) are found in this region

Krissek, 1993; Bigg et al., 2008) and were seen in

the core therefore, they were avoided

(VanLaighman et al 2009).

Sampling and Analytical method

Site 884 sediments over the last ten millions

years are characterized by mostly clay, silt andclayey diatom-rich layers (Rea et al., 1993).

Looking at some of the samples, they contain

materials that resemble ash. These were commonly

found throughout the core sediments.

The samples analysed for this study were taken

from the of the ODP hole 884b and 884c with

depth ranging from 0-472.5 meters below the

seafloor (mbsf). Most of the samples were takenfrom the finer-grained intervals although there are

few occasional samples that were taken from coarse

(IRD?) units.

In total 53 samples were analysed. Dry samples

were gently disaggregated with a mortar and pestle

but with modest pressure to avoid breaking the

individual grains. About 1-2 grams was weighed

and placed into a 250 ml bottle. To further

disaggregate the samples ~50ml of Sodium

Dodecyl Sulphate was added to every sample to

remove organic matter and isolate the terrigenous

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Figure 1.Bering Sea and North Pacific Ocean with ocean currents and contributing sediment source areas. White

arrows show surface currents, while light gray arrows show present deep water currents are known to exist in the

present day (Owens and Warren, 2001). River Basins: YB = Yukon River Basin; KuB = Kuskokwim River Basin;

AB = Anadyr River Basin; KaB = Kamchatka River Basin. Undifferentiated river basins contributing to the Bering

Sea/Meiji Drift: SWA = southwest Alaska; EA = Eastern Aleutians; WA = Western Aleutians; FN = Far northeast

Russia; KC = Koryak coastal basins; NK; Northern Kamchatka; SK = Southern Kamchatka. Sample and Core

Locations: 884 = ODP Site 884. Figure from VanLaningham et al (2009).


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Fractions. Samples were shaken and left for ~3-

4 days to allow all grains > 0.1 microns to settle.

Distilled water (~100ml) was added to the samples

to remove the chemical and to require optical

concentrations (also known as obscuration) of 5-

10% as described by Pape (1996) and Buurman et

al. (1997). Obscuration is the percentage oflight

that is attenuated because of extinction (scattered or

absorbed) by the particles.We calculated thissettling time using Stokes law in terms of particles

settling down- If particles are falling in the

viscous fluid together by their own weight due togravitythen a terminal velocity also known as thesettling velocity is reached when this friction force

combined with buoyant force exactly balance the

gravitational force. This allowed us to calculate

how long it takes for the particles to settle down in

the distilled water. Extraneous water (supernatant)

was drained off carefully. Samples were washed

three times to achieve the best result and

obscuration of 10%. Samples were stirred and

transferred to the rotary auto preparation station of

the laser grain size analyzer.

Laser diffraction particle size analyzer technique:

Measurements were carried out with Coulter LS

13 320. The laser diffraction particle size analyzer

(LDPSA) is based on the principle of light beam

scattering by small particles. The scatter beam is

divided into two, with each focused into 126

detectors by a reverse Fourier lens. The diffraction

pattern formed by laser beam scattering from the

samples suspended in a liquid medium (aqueous

mode) is caught by the detector rings of the

analyser. Diffraction patterns are interpreted using

the Fraunhofer or Mie theory to calculate grain size

from the intensity of the diffracted light. The

instrument measures 118 grain size classes in theranges of 0.04m-2000m. The lower class

boundary is 0.04m and each following boundary

is 1.098 times the preceding one (LS 320 Coulter

manual). Particles smaller than the minimum are

ignored by the instrument. We note, however, that

even though the instrument specifications suggests

it can analyse fine clay particles, McCave et al.,

(1995) have shown that LDPSA are not effective

below 0.1 microns.

For this study the LDPA was used as follows:

The samples were placed in the rotary autosampler attached to the Coulter LS 320. Calgon

dispersant was used to enhance dispersal of the

3

Figure 2. The proximal contributing terrigenous sediment sources to the Bering/NW Pacific region. The major rivers

basins in the region are the Anadyr, Yukon, Kuskokwim and Kamchatka Rivers. The numbers in black circle represent

the amount of sediment load deposited to the Meiji drift each year. From VanLaningham et al 2009


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grains. The samples were sonicated for ~3 seconds

immediately before analysis using the built in

ultrasonicator. This is a final step to disperse any

clusters formed while the samples are in line. The

sample tubes were emptied automatically for ~ 5

sec with an additional flushing by a 3-second water

stream. The speed of the pump was set to 100 forall analyses. Some of the samples were analysed

twice to check the reproducibility of the analyses.

The optical model chosen for grain sizedetermination is the Fraunhofer model,based on the Fraunhofer theory of lightscattering.

Calculation of statistical parameters

Statistical parameters are calculated using both

arithmetic and geometric algorithms. The

approaches used most commonly are methods of

moments (Krumbien and PettiJohn, 1938) and thegraphical methods (Folk and Ward, 1957) to

calculate mean, median, skewness, sorting

(Standard deviation), coefficient of variation and

Kurtosis. These statistical parameters were derived

using the software programme (GRADISTAT)

(Blott and Pye, 2000) provide with the instrument.

Result

The data over the entire record (i.e. from 0 ka to

10 Ma- see appendix table 1 for raw data) was

plotted (Figures 3A to 3J). The last 150 ka was

zoomed in so as to examine the potential influence

from the Milankovitch cycle variability (Figures3A, 3C, 3E, 3G and 3I). Outliers were observed on

the plot, especially the higher frequency plot (150

ka) therefore a three point moving average

(appendix table 2) i.e. for each point the smoothing

technique takes one point on each side plus its own

value and calculates the average of the three. This

was used to observe the trends.

The Last Ten Million Years at the Meiji Drift

The mean and median over the last 10 Ma

shows tremendous scatter with outliers but there is

a subtle reduction in grain size around 2.5 Ma. Themean (fig 3a and 3b) and median (fig 3c and 3d)

grain size showed an increase at 3 Ma to 5 Ma i.e.

mean sizes increased from 10.5m (7 ) to 32m

(5 ) while the median showed an increase of

13.4m to 51.6m. Using the Udden, (1914);Wentworth, (1922) grain size scale, itcan noted that samples increased frommedium silt to coarse silt.

Kurtosis measures the peakness of distribution

of grain size. Using Krumbien and PettiJohn (1938)

descriptive terminology as the depth of the core

increase i.e. from 0-10 Ma (fig 3H); the values for

kurtosis are small compared to the high frequency

plot (0-150 ka-fig 3G). The highest value (2.8) is

seen at 10 Ma and lowest value (0.1) seen at ~5Ma.

Based on this observation, it can be considered that

the kurtosis grain size at the end of the core are

platykurtic to very leptokurtic.

D10 (fig 3e and 3f) show the cumulative

percentile at which a specified percentage of grain

size diameter samples are finer. Over the 10 Ma adecreasing d10 particle size trend between 1.49-2.7

Mas can be seen. The lowest point is at 2.5 Ma, this

shows that 10% of the particles are finer than

0.5m. From 3-5.5 Ma there was an increase in d10

grain size, the samples shows that 10% of the

samples are finer than 1m i.e. an increase from

1m (3 Ma) to 3.5m (5.5 Ma). Towards the end of

the core i.e. 6 Ma to 10 Ma a decrease was in grain

d10 grain size was seen. Most sample exhibit grain

size is finer than 2m (averagely) except the outlier

observed at 10 Ma.

All samples are positively skewed (Fig 3I and3J) over the last 10ma. Sizes ranges from

0.5(lowest) to 2.5(highest). Smaller size are

observed from 1 Ma-10 Ma compared to 0-150 ka

which showed better trends of grain size. The 0-10

Ma plot (fig 3J) only showed a reasonable trend at

1 to 2.5 Ma where it can be seen that the skewness

grain size increased slightly i.e. sizes increased

from +1.0-1.99. Better trends at observed on the 0-

150 Ka plot (Fig 3I).

Based on Krumbien and PettiJohn (1938)

Standard deviation (sorting) show that all sample

grain sizes are greater than are 4m. This make

them relatively poorly sorted.

The Last 150,000 Years at the Meiji Drift

The mean and median grain size over the last

150 ka show a few outliers but generally a

decreasing trend in size can seen i.e. grain size

went from coarse grain to fine grain silt. From 0-52

ka the mean have lower grain size i.e. size are in the

range of 6-7m. Higher grain size can be seen at

around 56-65 ka (higher than 20m). A subtle

reduction can be seen at 73 ka (7m). From 75-83

ka mean grain size increased from 11m to 20 m.

The last 150 ka (Fig 3g) showed that most of thesamples vary from extremely leptokurtic to

leptokurtic. The highest point observed at ~30 ka

with kurtosis value of 7.57m, this can be

considered as been extremely leptokurtic. A sharp

decrease can be seen at 38 ka and 61 ka, both

showing a size of 2.5m (very leptokurtic) and

1.4um (leptokurtic). From ~88 ka to150 ka most of

the samples are very leptokurtic (i.e. grain size are

between 1.50m to 3.00m).

Using the three point moving average, d10 for

the last 150ka (fig 3e) showed a decrease in size.

From ~85 ka to 140 ka most of the samples areappear to be finer than 1.5 m. A minor increase in

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size can be seen at 80-82 ka i.e. samples increased

from 1.5m to 2.2m. A subtle reduction can be

seen at 72 ka, the d10 grain size shows that 10% of

the samples are finer than 0.5m. The overall trend

from 0-55 ka showed roughly the same d10 value

i.e. ~ 0.6m to 0.8m. From ~150 ka to 82 ka the

skewness grain size appears to be constant i.e. onan average of +1.60. A slight increase can be

observed around 70 ka. There was a subtle

reduction at ~60.30 ka (+1.25) and 38 ka (+1.6).

Towards the top of the core i.e. 0-30 ka most of the

samples show a higher skewness value i.e. most

sizes are greater than +2.0.

Microsoft_Office_Excel_Worksheet1




5

0

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Age (ka) vs skewness

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Age (ka) vs d10E

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Age (ka) vs Median grain size

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Meangrainsize(m)

Age (ka) vs Mean grain size

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1 23 4

A

Onset of

N.Hemisphere

glaciation

Onset of

N.Hemisphere

glaciation


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6

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0.5

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Age(Ma) vs Skewness

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Age (Ma) vs Mean grain size

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Age(Ma) vs Kurtosis

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Age (Ma) vs d10

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Age (ka) vs Kurtosis

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0 1 2 3 4 5 6 7 8 9 10 11 12Mediangrainsize(m)

Age (Ma) vs Median grain size

Figure 3: Graphs showing data plot over the entire record (i.e. from 0 ka to 10 Ma). A: age (ka) against the mean grain size

(m); B shows age (Ma) against the mean grain size (m);C show plot of age (Ka) against median ;D show age (Ma) against

median grain size; E: age(ka) against d10; F: age(Ma) against d10;G:age(ka) against Kurtosis; H:age(Ma) against Kurtosis;

I:age(ka) against skewness; J:age(Ma) against skewness. On the higher frequency plot (C, E, G, and I) the dotted lines are the

raw value data and the smooth line represent three point moving average. Number 1-6 on the higher frequency plot represent

the Marine Isotope Stages (MIS; MIS 1, 3 and 5 represents interglacial periods while 2, 4, and 6 represent the glacial period.

The arrows on plot B, D and F represent the onset of Northern Hemisphere Glaciation that occurred around ~2.6Ma.

Onset of

N.Hemisphere

glaciation

B

F

H


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Discussion

The results of the grain size analysis of the

Meiji drift show a lot of scatter with a few trends

illuminated. I first focus attention to the median,

mean, and d10 data sets over the last 10 Ma. Each

shows a change at around 2.5 Ma to 5.5 Ma. It was

noted by Rea and Snoeckx (1995) that physicalweathering and erosion suddenly increased the

amount of IRD and terrigeneous sediments to the

north pacific to 2.6 Ma. The change from preglacial

to glacial sediments occurred very rapidly i.e. as

little as 1000-2000 years (Pruher and Rea 1998). A

decrease in d10 and mean grain (~2m) at ~2.6 Ma

are especially striking because this period

corresponds to the onset of northern hemisphere

glaciation (~2.6 Ma). Glacial erosion and

weathering can be use to explain why the sediment

at 2.6 Ma is fine grained. During glacial erosion

forms powered rock flour which tends to be veryfine grained (less than 2m).

The overall decreasing trend over the last 150 ka

is odd as I expected the variation to track MIS

stages 6-1(glacial-interglacial variation).

VanLaningham et al. (2009) showed that the source

of sediment to the drift changed with the MIS

stages (Fig 4). But the grain size analyses did not

show this. There are several possible explanations

for this is. Either the LDPSA is not a good

technique to use on silt sized particles (McCave et

al; 2006) or the sample preparation i.e. chemical

disaggregation of samples was not done properly.

Another explanation is that the change in sediment

source to the Meiji drift (VanLaningham et al.,

2009) might have caused the decrease in grain size.

It is difficult to determine which of these is the

most plausible and future work will have to use a

Sedigraph and more thorough disaggregating

treatment to eliminate these potential problems.

McCave et al; (2006) noted that LDPSA is not

the ideal instrument for analysing clay and silt

because coarse clay/ fine silt may be recorded as

medium to coarse silt i.e. the platy shape of smaller

grains can be dominated by larger area. At presentthe sedigraph is a good choice of instrument for

studying deep sea sediment as an analogue for

current intensity. The technique is based on the

settling principle of Stokes law which measures

grain size distribution in terms current velocity.

This can best be related to transport and

depositional process.Despite all of this grain size parameters in silt

(2-63m) can be used to interpret palaeocurrent

velocity and paleoceanography (McCave and

Manighetti; 1995). These authors noted that, based

on the dynamics of sediment erosion, depositionand aggregate breakup of the coarser silt (greater

than 10um) is non cohesive whereas the less than

10um fraction is cohesive. This means that size

sorting in response to hydrodynamic processes can

be used to determine the current velocity i.e. I

would except smaller fine grained (


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likely to be found in medium to coarse (10-63m)

silt fraction.

Conclusion:

We use laser diffraction particle analysis to

examine changes in grain size distribution over the

last 10 Myr to understand sediment transport to the

Meiji drift in the North Pacific Ocean. Overall, the

results showed that LDPSA is probably not the best

method for taking grain size measurements.

McCave and Syvisky (1991); McCave et al (1996)

discussed that the sedigraph is a better instrument,

especially for silt-sized particles. Acknowledging

that, I do recognize a few trends of interest. The

mean, median and d10 grain size show a reduction

at 2.6 Ma, which can be correlated with the onset

of Northern hemisphere glaciation. Previous studies

showed prior to 2.6 Ma, physical weathering and

erosion increased the rate of sedimentation

suddenly. Thus, the results obtained here are in

good agreement with this. A suggested

interpretation for this is that during glacial

weathering and erosion process, abrasion might

have ground the sediment to glacial flour, therefore

making a very fine particle size that was deposited

in the Meiji Drift. The result for mean grain size on

the higher frequency plot (0-150 ka) showed some

trends as well, but with a fair amount of scatter.

The grain size results do not agree with previous

studies because VanLaningham et al. (2009)

showed that the source of sediment to the drift

changed with the MIS stages i.e. stages 1-6. But if

these data are correct, then the lack of size can beused to infer that the velocity of deep water current

in the Meiji drift did not change very much over the

last 150 Ka.

Acknowledgement

Foremost I would like to thank Dr S.VanLaningham for his

discussion support and mostly for providing the core samples

used for this project. Furthermore I would like to show my

appreciation to Mr Collin Taylor at the Department of geology

and petroleum geology, University of Aberdeen for technical

support. Lastly, I would also like to thank Dr D. David K. Rea,

Professor Emeritus at the Department of Geological Sciences

University of Michigan for discussing his ideas on the project.

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Fig 4: Sediment source change to the Meiji

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VanLaningham, S., Pisias, N.G., Duncan, R.A., Clift, P.D.

Glacial-interglacial sediment transport to the Meiji Drift,

northwest Pacific Ocean: Evidence for timing of Beringian

outwashing ;2009;Earth and Planetary Science Letters277

(1-2), pp. 64-72.

Appendix

9

Appendix table 1: Show rawa data for the last 10 Ma. Leg= 145, Site=884, Hole= B and C, Core=1, Sec= 1, 0-2cm,

20cc
http://www.scopus.com/scopus/search/submit/author.url?author=Pisias,+N.G.&origin=resultslist&authorId=7003985012&src=shttp://www.scopus.com/scopus/search/submit/author.url?author=Duncan,+R.A.&origin=resultslist&authorId=7401604553&src=shttp://www.scopus.com/scopus/search/submit/author.url?author=Clift,+P.D.&origin=resultslist&authorId=7004449923&src=shttp://www.scopus.com/scopus/search/submit/author.url?author=Pisias,+N.G.&origin=resultslist&authorId=7003985012&src=shttp://www.scopus.com/scopus/search/submit/author.url?author=Duncan,+R.A.&origin=resultslist&authorId=7401604553&src=shttp://www.scopus.com/scopus/search/submit/author.url?author=Clift,+P.D.&origin=resultslist&authorId=7004449923&src=s


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Appendix Table 2. Show 3 point average value data for the last 10 Ma. Leg= 145, Site=884, Hole= B and C,

Core=1, Sec= 1, 0-2cm, 20cc.

sediment out washing from the bering sea recorded by grain size using the laser diffraction particle...

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