ABSTRACT TAYLOR, RICHARD STANLEY. Evaluating the Effects Of

ABSTRACT

TAYLOR, RICHARD STANLEY. Evaluating the Effects of Regional Climate Trends Along the West Antarctic Peninsula Shelf Based on the Distributions of Naturally Occurring Radiochemical Tracers within the Seabed. (Under the direction of Drs. David DeMaster and Christopher Osburn).

Measurements of 230Th, 210Pb and 234Th activities were made on sediment

cores collected along a N-S transect (exhibiting a sea-ice gradient) off the West

Antarctic Peninsula. The resultant data, together with existing 14C sediment data,

were used to evaluate the effects of regional warming on particle flux reaching the

seabed on timescales from millennial to seasonal. Shelf samples were collected at

five stations, over three cruises, between February 2008 and March 2009, as part of

the FOODBANCS-2 Project. Sea-ice conditions (the number of days ice-free prior to core collection) were evaluated at the five stations to understand the relationship between ice abundance and particle flux. Based on the millennial tracer, 14C, particle

flux along the peninsula decreases southward, consistent with the observed sea-ice

gradient. 230Th data provide evidence that sediment focusing (i.e., lateral transport)

occurs to a greater extent in the northern reaches of the study area as compared to

the southernmost stations. 210Pb-based particle flux measurements (representing centurial trends) display a similar trend as 14C, showing higher particle flux in the

northern study area stations (where sea-ice conditions are diminished) and lower flux southward as sea-ice conditions increase. Additionally, 210Pb data suggest that

lateral transport plays an important role in sediment distributions on hundred-year

timescales, which is explainable by the relatively short circulation times of peninsular

waters relative to 210Pb’s half-life. On seasonal and annual time scales, 234Th data

show an increase in particle flux at the southernmost stations. The observed increase in particle flux on seasonal and annual time scales is consistent with the

increased warming trend along the peninsula and the reduction in sea-ice conditions

over the past decade. However, a significant statistical relationship could not be

established between sea-ice free days and 234Th-derived particle flux to the seabed.

Thus, the fluxes/distributions of long-lived particle-reactive tracers (14C, 230Th, and

210Pb) off the West Antarctic Peninsula appear to be controlled primarily by the long- term pattern of increasing sea ice in the southward direction, whereas the fluxes of the short-lived tracer (234Th) appear to be affected most by the more recent

decreases in sea ice extent (associated with Climate Change) that have occurred

over the past decade primarily in the southern stations.

by Richard Stanley Taylor

A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the degree of Master of Science

Marine, Earth and Atmospheric Sciences

Raleigh, North Carolina

2015

APPROVED BY:

______Dr. David J. DeMaster Dr. Christopher L. Osburn (Co-Chair of Advisory Committee) (Co-Chair of Advisory Committee)

______Dr. Elana L. Leithold Dr. Carrie J. Thomas

DEDICATION

For Science!

BIOGRAPHY

Richard was born in Columbus, Mississippi on November 23, 1979. His

parents provided boundless support for his insatiable curiosity in everything he did - from exploring the sciences, to sports, to creative endeavors and beyond. His only

limits have been those of personal safety (and those were pushed by the author

often). Over the years he has worn many hats — to better his understanding of the

unknown.

In August 2009, after a long academic hiatus, Richard enrolled in the Marine

Sciences program at North Carolina State University to finish his Bachelor’s Degree.

The path to eventual success was long, but along the way he was rewarded with

great gifts, each better than the last. Firstly, he was given the opportunity to assist in

field and laboratory research —endeavors that further fueled his interest in the

unknown. His newly gained field experience allowed his path to cross with that of his

mentor, and eventual friend, Dave DeMaster. It was Dr. DeMaster who, through

his inspiring work in Antarctica and his well-taught course on chemical

oceanography, opened Richard’s eyes to the boundlessly interesting world

of marinechemistry and radioisotopes. Lastly (and definitely the best), Richard met

his future wife while completing his degree. Richard started his graduate career at

North Carolina State University in the fall of 2012 under the guidance of Drs.

DeMaster and Osburn. Upon completion of his master’s degree, he will be

continuing on with Dr. DeMaster in pursuit of his doctorate.

iii

ACKNOWLEDGEMENTS

The author would like to express his gratitude for the many people who contributed feedback and support throughout the writing process. In particular, he would like to thank his committee members: Doctors Carrie Thomas, Lonnie Leithold, Dave

DeMaster and Chris Osburn for keeping his writing focused and honest. Financial support was provided by the National Science Foundation (Grant no. ANT-0636773,

David J. DeMaster, Craig R. Smith and Carrie J. Thomas, principal investigators).

The author also wishes to thank his friends Jen Dixon-Brown and Robert

Duke for their open office doors (and the much needed breaks). Lastly, he would like to express his gratitude for his family and for their endless support (especially his wife - Emily Winchester Taylor).

TABLE OF CONTENTS

LIST OF TABLES ...... vii

LIST OF FIGURES ...... viii

Chapter 1 Overview of Study Area and Overall Research Objective ...... 1

1. The West Antarctic Peninsula – Background ...... 1 2. General Circulation ...... 1 3. Sediment Transport ...... 4 4. Ecology ...... 7 5. Climate Change ...... 10 6. Overall Research Objective ...... 11

Chapter 2 Documenting the Seabed Response to Climate Change Trends on the West Antarctic Peninsula Based on Naturally Occurring Radiochemical Tracers ...... 13

1. Introduction ...... 13 2. Methods ...... 18 2.1 Study Sites ...... 18 2.2 Radiochemical Analysis ...... 19 2.3 Sea-Ice Metric ...... 21 3. Results ...... 22 3.1 Radiochemical ...... 22 3.2 Millennial Trends ...... 25 3.3 Decadal-Centurial Trends ...... 28 3.4 Seasonal Trends ...... 31 3.5 Annual Trends ...... 33 3.6 Sea-Ice Trends ...... 34 4.1 Discussion ...... 37 4.2 Summary of Temporal Trends in Particle Flux...... 45 5. Conclusions ...... 48

References ...... 50

Appendices ...... 56 Appendix A ...... 57 Appendix B ...... 58 Appendix C ...... 59 Appendix D ...... 60 Appendix E ...... 61 Appendix F ...... 64 Appendix G ...... 72

LIST OF TABLES

Table1: Geochemical results from radioisotopic analyses. 14C data are from DeMaster et al., 2015 (in prep). Cruise information: FB2-1 is Summer 2008, FB2-2 is Winter 2008 and FB2-3 is Summer 2009. CRS IDs are core identification numbers. Absolute error is determined from counting statistics. Annual mean 234Th inventories presume the winter contribution was the same for 2008 and 2009. For 14C SAR parenthetical values (± ) represent a 95% confidence interval. For calculated mean inventories, parenthetical values represent standard deviations (1σ). ND = not determined. * 230Th activities from Station AA were at detector limits and were not considered when evaluating trends along the WAP. ** 230Th data from Station B were interpolated from 0-10 cm...... 24

Table 2: Focusing factors (Ψ) for 230Th, 210Pb, and 234Th. 230Th Psi values were calculated based on a water column production rate of 26.7dpm m-3 ky-1 (Francois et al., 2004). The estimated 226Ra activity was 0.14 dpm/kg (Ku and Lin, 1976), and the estimated 238U activity was 2.4 dpm/kg(Pilson, 1988). 234Th Psi ranges were based on the minimum and maximum observed inventories. na = not analyzed...... 28

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LIST OF FIGURES

Figure 1: 6 year mean (red) and standard error (blue) ADCP velocities between 40 and 200m depth along the WAP (Savidge and Amft, 2009). For (a) South Shetland Islands (SM=Smith Island, SN=Snow Island, LI=Livingston Island, KG=King George Island), BY=Boyd Strait, BT=Brabant Island, and (b) southern WAP (AX=Alexander Island, Mg Bay=Marguerite Bay, Mg Tr= Marguerite Trough, AD=Adelaide Island, AV=Anvers Island) net outer shelf flow is NNE with a cyclonic gyre between the peninsula and KG (a) and south of AD (b)...... 3

Figure 2: Clay mineral assemblages in sediments west of the Antarctic Peninsula (Hillenbrand et al., 2005). The general trend within the Bransfield Strait (smectite provenance) is for sediment to collect within deep basins, but stronger bottom currents do transport sediment off shelf as mounds along the continental slope to the south and west of the Strait. South of Anvers Island (chlorite-illite provenance), sediment is derived from glacialprocesses and transported offshore by tidal and wind induced circulation (Hillenbrand et al., 2005)...... 5

Figure 3: Schematic of the ice-dependent (top) biological community along the WAP and the potential implications of current warming trends along the peninsula (bottom) (McClintock et al., 2008). Sea-ice plays an important role in sustaining the foodweb by supporting (but not limited to) ice-algae, diatoms, krill and some penguins. ). The upper figure illustrates the biota dominating the coastal environment when sea-ice is well established (i.e., much of the recent past), whereas the lower figure shows the biota dominating the coastal environment when sea-ice is no longer prevalent. Increased warming will continue to decrease sea-ice, potentially leading to a change in the pelagic ecosystem structure as has been documented in the northern WAP by the increase in warm-water tolerant cryptophytes and salps coastward (McClintock et al., 2008)...... 9

Figure 4: Palmer LTER sea-ice extent (km2). The minimum extent of sea-ice occurs in March and the mean winter maximum occurs in August. Trend lines show autumn advance occurring later and spring retreat occurring earlier with time (Stammerjohn et al., 2008)...... 11

Figure 5: Map of study sites for FOODBANCS-2 Project. Contour lines represent shelf bathymetry. Stations (red dots) were occupied during Austral Summer and Winter 2008, and Austral Summer 2009...... 16

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Figure 6: Sediment accumulation rates (SAR) along the 550km N-S transect (DeMaster et al., 2015 in prep). On millennial timescales, there is decreasing particle flux as distance from AA (farther south) increases. Error bars represent the 95% confidence limits on the SAR from linear regression...... 26

Figure 7: 210Pb inventories from all sampled cores denoted by their Station-FB cruise. Station G had 2 cores (a and b) analyzed from cruise FB2-3. Error bars represent absolute errors (calculated from counting statistics)...... 30

Figure 8: 210Pb inventory weighted regression analysis. The centurial trend is that of decreasing particle flux from north to south (p-values < 0.0001)...... 30

Figure 9: 234Th inventories from the three FB-2 cruises. Points are mean core inventories (n=5) and error bars are standard deviations of the means. Each cruise (season) had decreasing inventories from Stations AA to E, but increased inventories from E to G. Cruise FB2-3 (Summer 2009) had higher inventories than either previous cruise, consistent with documented inter-annual variability in 234Th (McClintic et al., 2008)...... 32

Figure 10: Annual 234Th inventory regression as a function of distance from Station AA. The weighted linear regression equation was derived using the inverse of the squared absolute errors as weights. The data suggest that no linear correlation (p- value = 0.192) between latitude and inventory exists, possibly due to differences in the nature of particle origin on short timescales...... 34

Figure 11: The log transformed 234Th inventories at Station E (Figure 11a), Station F (Figure 11b) and Station G (Figure 11c) relative to ice cover 120 days prior to core recovery (120 days represents 5 half-lives of 234Th and thus the typical detection limit). Station E showed a positive, linear trend between 234Th inventory and ice-free days. Station G, however, had a negative linear trend. Station F showed high inter- annual variability between summer 2008 and 2009 and thus no correlation between ice-free days and 234Th inventory...... 36

Figure 12: Conceptual model from Smith et al. (1999), showing the dynamic relationship between benthic and pelagic ecosystems and how fluxes might be impacted based on changing sea-ice conditions along the WAP as a result of climate change...... 38

Figure 13: Millennial (14C in cm/ky - black), centurial/decadal (210Pb dpm/cm2 - red) and annual/seasonal (234Th in dpm/cm2x10 – green) flux proxies for the WAP. The long-term climatological trend is that of decreasing particle flux from N-S along the 550km transect. On short time scales (seasonal to annual), there is an increase in particle flux at Stations F and G, relative to longer-term proxies, i.e., southern stations look (radiochemically) similar to the northern stations at the alpha level of 0.05. Error bars represent standard deviations of the arithmetically averaged core inventories...... 47

Chapter 1

Overview of Study Area and Overall Research Objective

1. The West Antarctic Peninsula – Background

The West Antarctic Peninsula (WAP) extends approximately 1500km north from the continent into the Southern Ocean and is the northernmost extension of

Antarctica into the Southern Ocean. The major bodies of water that border the west side of the Antarctic Peninsula are the Bellingshausen Sea to the west and the

Bransfield Strait to the north.

2. General Circulation

The continental margin of the WAP is influenced by the Antarctic Circumpolar

Current (ACC) as it flows northward (Smith et al., 1999; Klinck et al., 2004; Savidge and Amft, 2009; Martinson et al., 2008). Due to topographic changes, as the ACC moves around the continental margin, warmer Circumpolar Deep Water (CDW) intrudes onto the inner shelf (Smith et al., 1999; Smith and Klinck, 2002; Martinson et al., 2008; Savidge and Amft, 2009).

Figure 1 shows that Antarctic Surface Water (AASW) flows eastward through the Bransfield Strait where it meets westerly flowing waters from the Weddell Sea, to form a cyclonic gyre (Savidge and Amft, 2009; Gulin, 2014).

Along the WAP, south of Bransfield Strait, AASW flows in an overall southerly direction and forms a cyclonic gyre and several sub-gyres (Smith et al., 1999;

Martinson et al., 2008; Savidge and Amft, 2009; Hopkins, 2011 and references therein). As AASW moves southward past Adelaide Island, it forms another gyre within Marguerite Bay (Figure 1) (Klinck et al., 2004; Moffat et al., 2008; Savidge and

Amft, 2009).

3. Sediment Transport

Within the water column along the WAP continental shelf, sediment is derived from either in situ biological activity or terrestrial weathering. The biological component on the shelf peaks during austral summer and is the net product of primary production, secondary grazing, microbial degradation and excretory products. Terrestrial inputs are derived from sub-glacial runoff, ice sheet basal flow and ice rafted debris (Pudsey et al., 1994; McGinnis et al., 1997; Fabres et al., 2000;

Khim et al, 2007; Masque et al., 2002; Garcia et al, 2011; Weston et al., 2013). In general, the terrestrial component is indicative of source rock (Figure 2) (Hillenbrand et al., 2003; Hillenbrand and Ehrmann, 2005).

Circulation dynamics along the shelf, in part, control the distribution of sediment spatially (Hillenbrand et al., 2003). Coastal discharge of terrestrial sediment gets resuspended via tidal currents and wind induced circulation and a nephloid layer is created, facilitating transport seaward (Figure 2) (Fabres et al.,

2000; Hillenbrand et al., 2003; Khim et al., 2007; Garcia et al., 2011). On the inner shelf of the WAP, surface gyres tend to transport suspended fine-grained particles southward of the origin point (Figure 1). Net bottom transport is seaward as noted from sediment cores and clay provenance studies along the WAP (Hillenbrand et al,

2003; Hillenbrand and Ehrmann, 2005).

In Bransfield Strait, most seabed sediment is derived from terrestrial glacial

discharge during spring – summer melting. This discharge is moved seaward via

resuspension and bottom currents as well as gravity flows, where it collects in

deeper basins (Masque et al., 2002; Isla et al., 2004). Some sediment is exported

west of Bransfield Strait and is deposited as mounds located on the continental rise

(Hillenbrand et al., 2003; Hillenbrand and Ehrmann, 2005).

Sediment in Marguerite Bay is mostly terrestrial, and glaciomarine processes

control its distribution (McGinnis et al., 1997; Hillenbrand et al., 2008). The intrusion

of CDW onto the shelf brings warmer waters that increase ice-shelf melting within

embayments, increasing suspended sediment concentrations in the water column

(Taylor et al., 2001; Gilbert et al., 2003). Within Marguerite Bay, deposited sediment

moves offshore via turbidity currents and gravitational flow via the Marguerite Trough

(Hillenbrand et al., 2008). The understanding of sediment transport dynamics along

the WAP is limited to evidence from geological deposits and inference from the limited circulation studies.

4. Ecology

The West Antarctic Peninsula exhibits a wide ranging and complex

ecosystem, and much of the marine ecosystem dynamics are coupled to seasonal

sea-ice parameters, e.g., the timing of sea-ice advance/retreat, or sea-ice extent

(McClintock et al., 2008; Montes-Hugo et al., 2009; Hopkins, 2011; Ducklow et al.,

2012; Huang et al., 2012; Smith et al., 2012). As a result, many pelagic species have evolved to have life cycles synchronized with sea-ice growth and retreat (Figure 3)

(Ducklow et al., 2012). Surface waters along the peninsula are generally replete with respect to macronutrients. Micronutrients (Fe mostly) and light availability tend to be limiting factors to primary productivity (Ducklow et al., 2012).

Primary productivity peeks in early Spring when winds decrease, the upper mixed layer shallows and the water column stabilizes, due to ice melt and effluent micronutrient supply (Ducklow et al., 2008; Vernet et al., 2008; Montes-Hugo et al.,

2009; Hopkins, 2011; Ducklow et al., 2012; Huang et al., 2012). There is high diversity within the phytoplankton community along the shelf with diatoms generally dominating seasonal blooms in the southern extent of the peninsula and cryptophytes to the north (Hopkins, 2011; Ducklow et al., 2012; Huang et al., 2012).

Zooplankton distribution is similarly influenced by latitudinal and cross-shelf sea-ice distributions. Krill dominate the zooplankton assemblage along the colder, inner to mid-shelf waters of the peninsula, while salps dominate in the warmer outer shelf and slope waters (Ducklow et al., 2012).

Along the WAP, productivity is highest in summer and lowest in winter with high inter-annual variability (Isla et al., 2002; Ducklow et al., 2008; McClintic et al.,

2008; Vernet et al., 2008; Ducklow et al., 2012; Smith et al., 2012; Weston et al.,

2013). Pelagic productivity, and organic matter cycling dynamics play a critical role in the benthic ecosystem structure. Shelf depths are on average 450m, well outside the euphotic zone, and food/nutrient availability is largely driven by water column export (Ducklow et al., 2008; McClintic et al., 2008; Smith et al., 2012; Weston et al.,

2013).

5. Climate Change

The West Antarctic Peninsula occupies a climatic gradient from the warmer, sub-polar north to the permanent ice of the south. Over the last 50 years, the nature of this gradient has been changing. In some parts of the WAP, annual average air temperatures have risen approximately 3 degrees Centigrade over this time period

(Vaughan and Doake, 1996; Vaughan et al., 2003; Meredith and King, 2005;

Mulvaney et al., 2012), with winter temperatures more than 5 degrees Centigrade higher (Stammerjohn et al., 2008; Mayewski et al., 2009; Turner et al., 2013). During this same time period, sea surface temperatures have increased approximately 1 degree (Meredith and King, 2005).

Heat retention has been linked to increased wind intensity along the peninsula, which negatively impacts sea-ice, initiating a positive feedback loop along the WAP (Meredith and King, 2005; Harangozo, 2006; Stammerjohn et al., 2008;

Fan et al., 2014). Westerly winds during spring/summer push ice eastward.

Increased intrusion of UCDW onto the shelf increases heat flux and further promotes the extent of sea-ice loss. Reduced ice extent increases the area of open-ocean and subsequently heat exchange with the atmosphere into the fall. Northerly winds in the fall increase in intensity due to the higher heat flux, which pushes ice eastward against the continent, further perturbing the system by delaying winter sea-ice advance. The net result is a reduction in ice extent, later ice advance and earlier retreat (Figure 4) (Vaughan et al., 2003; Meredith and King, 2005; Harangozo, 2006;

Stammerjohn et al., 2008; Turner et al., 2013).

6. Overall Research Objective

High latitude climate changes are poised to have profound impacts on WAP

ecosystems, which as mentioned earlier, have biological assemblages whose

lifecycles are mainly tied to ice parameters. As a result, changes in the pelagic

ecosystem, brought on by climate change, are likely to impact benthos and the

nature of the seabed. Because the benthic environment acts to integrate time,

changes in the benthic environment may be less abrupt and could even go

unnoticed on short to medium time scales (annual to decadal).

In light of the evidence of climate change along the WAP, I propose to investigate several parameters that will aid in the understanding of the linkage

between the pelagic and benthic coupling in regards to climate perturbations. The

aim is to understand particle flux dynamics over multiple timescales in order to

evaluate how the benthic environment of the WAP responds to climate change. An

additional goal is to link particle flux to seasonal sea-ice dynamics along the WAP.

Chapter 2

Documenting the Seabed Response to Climate Change Trends on the West

Antarctic Peninsula Based on Naturally Occurring Radiochemical Tracers

1. Introduction

Global warming is a non-local phenomenon that is impacting nearly every part of the planet. However, not all regions are impacted equally. High-latitude, polar- regions are experiencing some of the greatest increases in air and water temperatures (Mulvaney et al., 2012; Meredith and King, 2005), and the Antarctic

Peninsula is warming as fast as (or faster than) any region on the planet (Doney et al., 2012). Vaughan et al. (2003) and Mayewski et al. (2009) reported several degrees of atmospheric warming along the northern and western portions of the

Antarctic Peninsula between 1951 and 2000. Specifically, the air temperatures during the West Antarctic Peninsula (WAP) winters have warmed over 5 degrees

Centigrade in the same time period (Mayewski et al., 2009), and the annually averaged air temperature have risen about 3°C (Ducklow et al., 2007; Meredith and

King, 2005; Vaughan et al., 2003; McClintock et al., 2008).

As a consequence of global heat retention, westerly wind intensity has increased around Antarctica (Mayewski et al., 2009; Fan et al., 2014), and this is negatively impacting sea-ice extent along the WAP, i.e., producing decreased sea-

ice coverage (Harangozo, 2006; Stammerjohn et al., 2008). On the WAP, the

increased air temperature has translated into a one degree Centigrade increase in

the surface ocean temperature along the peninsula (Meredith and King, 2005). The

increased sea temperature also has been shown to be a contributing factor in the

decrease of sea-ice on the WAP (Vaughan et al., 2003; Jacobs and Comiso, 1993;

Fan et al., 2014; Stammerjohn et al., 2008). Sea ice extent has diminished along the

WAP by 40% since satellite measurements began in 1978, and there has been a 90-

day decrease in average sea-ice days (over the last thirty years) within the Palmer

LTER area (Stammerjohn et al., 2008; Ducklow et al., 2013).

Sea ice is vital to the health of the pelagic ecosystem on the peninsula.

Phytoplankton and zooplankton rely on ice seasons for their sustained growth and

development. These planktonic organisms serve as the foundation of the greater

food web on the WAP shelf (Ducklow et al., 2013). Ultimately, phytoplankton are

ingested by zooplankton and detritivores, with the resulting organic-rich fecal pellets

and organic debris raining downward, providing food for the benthic environment

(Mincks et al., 2005).

Not only does climate (and sea-ice) factor into the biogenic component of particle flux, but the regional climate also plays a role in the lithogenic fraction of flux.

It is the interplay between the glaciological setting and shelf circulation of the WAP that drives the lithogenic component of particle flux (Hillenbrand et al., 2003), which is mainly derived from terrestrial sources, e.g., sub-glacial runoff, ice sheet basal

flow and ice-rafted debris (Harden et al., 1992; Pudsey et al., 1994,; McGinnis et al.,

1997; Fabres et al., 2000; Khim et al., 2007; Garcia et al., 2011; Weston et al.,

2013). The lithogenic flux is enhanced during the relatively warmer spring and

summer seasons along the peninsula (Garcia et al., 2011; Weston et al., 2013).

Given the sea-ice decline over the past few decades (Stammerjohn et al.,

2008) and the tightly coupled interaction between pelagic productivity and benthic

food webs (Mincks et al., 2005), it was postulated that any changes in the pelagic

ecosystem function and structure would translate into changes in the benthic

environment. To test this theory, the second phase of the FOODBANCS Project,

FOODBANCS-2, was initiated. The focus of FOODBANCS-2 research was to observe and document changes in the benthic environment along a climatically sensitive, N-S transect on the WAP that exhibited a gradient in sea-ice coverage

(Figure 5). Investigators proposed to examine particle flux dynamics and benthic ecology in the context of changes in sea-ice coverage (a possible result of regional climate forcing) for this sensitive, high-latitude environment.

There have been numerous flux studies employing particle traps along the peninsula, e.g., FRUELA96 (Anandon and Estrada, 2002; Palanques et al., 2002), the Palmer LTER (Ducklow et al., 2007; 2012) and FOODBANCS (Smith et al.,

2008a; McClintic et al., 2008). However, there may be some inherent biases associated with particle traps, i.e., under-sampling in time and space (Buessler et al., 2010 ).

Figure 5: Map of study sites for FOODBANCS-2 Project. Contour lines represent shelf bathymetry. Stations (red dots) were occupied during Austral Summer and Winter 2008, and Austral Summer 2009.

As a result, net flux to the benthic environment has large uncertainties and is poorly

understood. In order to get a better understanding of particle flux,

sediment cores retrieved from along the peninsula can help to illuminate particle flux dynamics along the WAP, because the seabed is an integrator of net water column processes.

To evaluate the influence of climate change on the WAP and to understand the nature of particle flux over a range of time scales, a suite of radiochemical

tracers (230Th, 14C, 210Pb and 234Th), with variable half-lives (75.2 ky, 5730 y, 22.3 y and 24.1 days, respectively), were measured on sediment samples from regional basins (shelf depths >400m), where (fine-grained) sediment more likely to scavenge radiochemical tracers from the water column accumulates. By comparing the distributions of these varying tracers in the seabed (representing time scales ranging from millennia to months), the effects of regional warming on the Antarctic Peninsula over the past few decades can be resolved from long-term conditions extending back centuries to millennia.

The goal of this research is to evaluate trends in the radioisotopic flux/inventories of four particle flux proxies, and to determine if there is any evidence to support the hypothesis that the southernmost stations along the 550km N-S WAP transect are exhibiting enhanced particle fluxes (comparable to the northernmost stations). Specifically, it is hypothesized that the inventories of 234Th (characterizing

monthly time scales) collected from the southernmost stations, during 2008 and

2009, are suggestive of a temporal increase in particle flux relative to the northern

stations of the transect and the long-term (centurial to millennial) trend of decreasing particle flux with increasing latitude. The fundamental belief is that as warming trends along the West Antarctic Peninsula persist, there should be an increase in particle flux, both lithogenic and biogenic.

2. Methods

2.1 Study Sites

The West Antarctic Peninsula was sampled along a 550 km N-S transect between 63°S and 68°S (Figure 5). Three cruises were completed using the RV

Lawrence M. Gould during the austral summers of 2008 and 2009 and the RV

Nathaniel B. Palmer during the austral winter of 2009. These cruises were timed to coincide with periods of highest and lowest primary production (and presumably particle flux), summer and winter, respectively. Five stations were selected along the

WAP shelf, each at water depths of ~600m (where the seabed exhibits accumulation of fine-grained sediments – Harden et al., 1992). Station selection coincided with a

natural gradient in sea-ice coverage and duration: Station AA, the northernmost station, being ice-free more than nine months of the year, in contrast to Station G, the southernmost station, being ice free about three months of the year (Smith et al.,

2012). Stations were occupied multiple times during each cruise, and each time a station was occupied, a 12-barrel, 9cm diameter megacore was collected.

Cores having the least disturbed sediment-water interfaces were sampled for

radiochemical analysis (at 0.5cm intervals down to 2cm, every centimeter from 2-10 cm, every other centimeter from 10-20 cm and at 2cm intervals from 20 cm to the bottom of the core). A kasten core was collected at each of the five stations and subsampled over 3cm intervals, at 5-8 depths throughout the 1-3 meter cores.

Sediments used to measure 14C were dried at 100°C on board ship. All other

radiochemical samples were stored at 4°C and dried just prior to analysis. Of the

megacores collected from each cruise, 3-5 cores from each station were analyzed

for 234Th activity. 210Pb was measured on one core from each station per cruise.

230Th analyses were run on four kasten cores (Stations AA, B, F, and G), three of which had previously been analyzed for 14C activity (DeMaster et al., 2015, in prep.).

2.2 Radiochemical Analysis

Analyses for 234Th, 210Pb, and 230Th were accomplished by chemical digestion

of approximately 5g of dried, homogenized sediment in near-boiling 6M hydrochloric and 7M nitric acids following the methods of Aller and DeMaster (1984). All three radiochemical analyses were made on separate sediment samples from the same core. An analyte-appropriate spike of known activity was introduced prior to initial digestion: 230Th (for 234Th), 209Po (for 210Pb) and 228Th (for 230Th). For the thorium

analyses (and their uranium parents), thorium and uranium fractions, after initial

digestion, were isolated using anion exchange resin (AG1-X8, 200-400 mesh, Cl-

form). Thorium and uranium activities were further purified using 0.4M

thenoyltrifluoroacetone (TTA - in benzene) extractions followed by dry deposition

onto stainless steel planchettes on a heated chimney (Aller and DeMaster, 1984).

Activities of 232Th, 230Th, and 228Th were determined using alpha spectroscopy,

whereas the activity of 234Th was determined via anti-coincidence beta counting.

210Pb analyses were made by isolating its daughter, 210Po, in 1.5M HCl, followed by

deposition of the polonium isotopes on 1cm2 silver planchettes. After plating,

samples were counted using surface barrier detectors and alpha spectroscopy.

Detector counting efficiency was approximately 30% for all radioisotopic analysis.

The statistical uncertainties inherent in observing decay events were propagated

throughout the various data calculations (see Absolute error - Table 1).

14C activity was determined on the organic carbon fraction of the kasten core

sediments. Particulate inorganic carbon was removed using an overnight, 1M HCl

pretreatment. Thirty to 90 mg sediment samples were combusted on an elemental

analyzer (Flash EA 1112), followed by CO2 isolation into glass tubing using

cryogenic techniques (DeMaster et al. 2015, in prep.). The CO2 samples were

analyzed for 14C activity using the accelerator mass spectrometer at the NOSAMS facility (Woods Hole Oceanographic Institution).

Geochemical data were handled as discrete observations (and arithmetically

averaged when pooled values were used) in statistical analyses. For seasonal and

annual trends, 234Th data were pooled for each station and evaluated spatially and temporally using a linear model, treating both station (spatial) and cruise (temporal) effects as fixed.

2.3 Sea-Ice Metric

Annual sea-ice trends along the WAP were evaluated from the Bootstrap-2

passive microwave dataset available through the National Sea Ice Data Center

(NSIDC) in Colorado. The five stations were geocoordinated with Interactive Data

Language (IDL) using modified source code provided by NSIDC. Each of the five

stations was represented by a single 25 km2 cell of the satellite data matrix. Binary

satellite data were input into Matlab and the resultant daily concentrations were used

to derive the sea-ice statistic used in this study. The parameter of interest, sea-ice

free days, was quantified by counting the number of days that had ice

concentrations less than 15% (Stammerjohn et al., 2008). For annual trend analysis,

a year was defined as occurring from March 15th of the initial year to March 14th of the subsequent year. Due to incomplete data, 1987 was excluded from analysis.

To evaluate seasonal trends in sea-ice coverage at each station and spatial trends per cruise (FB2-x), the sea-ice free days were counted for the 120 days

(approximately 5 half-lives of the shortest lived tracer, 234Th) prior to collection of each megacore sample. The ratio of observed sea-ice free days out of 120 was treated as binomial count data and run as a generalized linear model treating both

station and cruise as fixed effects. The ratios of ice-free days out of total days were

transformed in order to account for the use of count data when evaluating ice trends.

All statistical analyses were performed using SAS v. 9.4 at the alpha significance

level of 0.05.

3. Results

3.1 Radiochemical

Excess activities were calculated by subtracting the supported activities from the total activities for each isotope. For both thorium isotopes, the uranium parent was directly measured, but for 210Pb, the (effective) parent (226Ra) activity was

approximated by the asymptotic activity of the total activity profile at depth. To

understand particle flux along the peninsula, inventories of excess activity for each

of the three radioisotopes were calculated using the equation

= (1) ∗ * 푑푑 where A is the excess activity at depth퐼 ∑ interval퐴 휌 횫 푧Δz and ρdb is the dry bulk density

(Table 1). Under steady-state conditions, the radiochemical flux of a particular

radioisotope to the seabed can be calculated by multiplying the seabed inventory by

its decay constant.

Observed fluxes, subsequently, can be used to resolve the relative

contributions of vertical settling and lateral transport. The production of each tracer

in the water column is known; therefore, a focusing factor (Psi) can be derived by

comparing observed seabed fluxes to the expected water column production for particular radioisotopes (Bacon, 2004). Values equal to one indicate vertical settling as the predominant component of sediment flux. Values greater than one indicate contributions from both vertical supply and lateral transport to the sediment flux.

Values less than one indicate sediment is transported laterally away from the station area (or for isotopes with short half-lives, as is the case for 234Th, decay within the water column).

230Th 14C 210Pb 234Th Ice-free CRS Station Inventory absolute SAR Inventory absolute mean Inventory absolute cruise annual Days ID Cruise (dpm/cm2) error (cm/ky) (dpm/cm2) error (dpm/cm2) error mean mean 120 932 2.4 0.1 175.5 2.3 120 935 5.9 0.1 5.5 FB2-1 120 937 8.2 0.1 (2.1) 120 938 5.1 0.1 * 69 184.3 120 944 6.3 0.1 11.2 AA 0.3 0.03 (17) (13.3) 120 1111 2.2 0.1 3.9 (2.5) (0.1) 120 1120 4.4 0.1 FB2-2 199.6 2.9 120 1123 5.0 0.2 (1.5) 120 1230 11.6 0.2 9.0 177.7 2.0 120 1235 8.6 0.2 FB2-3 120 1239 6.9 0.1 (2.4) 70.3 2.8 120 963 2.4 0.1 120 965 4.0 0.1 1.9 FB2-1 120 966 1.4 0.1 (1.4) 120 971 1.2 0.1 120 973 0.5 0.0 119 1107 1.7 0.1 4.4** 28 84.2 1.7 5.1 B 0.3 88.7 2.0 119 1141 3.4 0.1 FB2-2 (0.3) (24) (12.3) 119 1142 1.0 0.1 (1.2) (2.1) 119 1144 0.7 0.0 93.7 2.0 120 1160 2.2 0.1 120 1254 5.7 0.1 4.9 120 1256 4.9 0.1 FB2-3 120 1258A 6.0 0.2 (1.5) 120 1258B 5.6 0.2 65.4 1.7 119 1035 1.3 0.0 0.4 FB2-1 116 978 0.0 0.0 (0.8) 116 982 0.0 0.0 22 69.4 2.6 65.2 114 1084 0.8 0.0 0.6 2.8 E ND ND 114 1086 0.6 0.0 FB2-2 (17) (4.4) 113 1096 0.4 0.0 (0.2) (2.5) 120 1210 4.9 0.1 4.0 120 1218 3.1 0.1 FB2-3 60.7 1.7 120 1221 4.0 0.1 (0.9) 120 1004 5.1 0.1 2.1 118 996 1.2 0.0 FB2-1 97.3 2.6 118 998 0.0 0.0 (2.7) 7.2 66.4 107 1063 2.2 0.1 2.3 11.5 F 1.6 ND FB2-2 (1.6) (26.9) 106 1073 3.0 0.1 (10.0) 53.8 2.9 106 1077 1.7 0.0 (0.7) 48.1 2.3 119 1167 11.8 0.1 16.3 119 1170 14.6 0.1 FB2-3 119 1171 22.3 0.1 (5.4) 102 1014 1.2 0.0 102 1015 2.7 0.1 4.0 33.1 0.9 102 1019 7.1 0.3 FB2-1 103 1022 3.1 0.1 (2.4) 103 1023 5.8 0.1 104 1040 2.8 0.1 30.2 6 46.1 104 1041 2.5 0.1 2.9 9.5 G 1.0 64.2 1.8 103 1049 4.5 0.1 FB2-2 (1.0) (3) (13.9) 103 1053 2.8 0.1 (0.9) (3.6) 102 1059 2.1 0.0 100 1196 16.1 0.1 37.5 0.7 100 1197 6.1 0.1 9.1 49.4 1.3 100 1198 4.9 0.1 FB2-3 100 1199 12.9 0.1 (5.1) 100 1201 5.5 0.1

3.2 Millennial Trends

The sedimentary distribution of 14C is not influenced to a significant extent by

particle mixing (bioturbation) along the WAP; therefore, this long-lived radioisotope is an effective tracer of sediment accumulation rates on the WAP shelf (Harden et al.,

1992). Sediment accumulation rates (SAR) along the peninsula were derived from the 14C data from DeMaster et al. (2015, in prep.). The calculated SARs presume

that the surface age of bulk organic matter is constant over time. The data show

Station AA having the highest sediment accumulation rate (69 cm/ky) and Station G

the lowest (5.8 cm/ky). The sediment accumulation rates decrease from N to S along

the transect, and there is an 11-fold greater flux of sediment, on millennial time

scales, at Station AA as compared to Station G (Figure 6). The SAR for Station F

was not reported due to an unresolved, down-core 14C sediment profile (DeMaster,

personal comm.).

230Th inventories are listed in Table 1 and were integrated to the bottom of the kasten core (Stations AA, B and F) or to a depth horizon of approximately 7ky

(Station G). Excess activity was very small (near detector limits) for Station AA, probably due to the high sediment accumulation rate and subsequent dilution of the thorium signal. Station G had the highest (measurable) inventory, 31.6 dpm/cm2,

and Station AA the lowest, 0.2 dpm/cm2. There was an increase in inventory along

the transect, southward of Stations AA, which can be attributed to the increased time

over which the sediments at the southern stations (especially Station G) integrated, because of the decreased sediment accumulation rates to the south (69 cm/ky at

Station AA versus 5.8 cm/ky at Station G – Table 1).

100

Sediment(cm/ky) Rate Accumulation

0 AA B E F G Station

230Th, which is highly particle reactive, is produced at a constant rate from its more soluble parent, 234U. 230Th has a short residence time in the water column (<40

years in deep water) relative to its half-life (Francois et al., 2004). These properties

result from the nearly complete scavenging of 230Th from the water column. 230Th

inventories were used to calculate a sediment-focusing factor (Psi) following the method of Francois et al. (2004) based on the formula:

= ∗ (2) 퐴 휌푑푑푧 휓 ∫ 훽230ℎ푠 where A* is the age corrected excess activity of the depth horizon z, rho is the dry

bulk density, is the water column production of 230Th over water depth h, and s

230 is the dated age훽 of depth horizon z. Age correction and tie-points used in the Psi

calculation were based on 14C sediment accumulation rates. In the calculation of Psi,

230Th activity was only integrated to a time horizon of at most 7 thousand years, a

period of relatively uniform sedimentation in this high-latitude environment (Heroy

and Anderson, 2007; Bentley et al., 2011). Stations AA and B had Psi values > 2,

suggesting that sediment focusing plays more of a role at the northern stations.

Southern stations had 230Th Psi values slightly greater than one (1.3-1.6), suggesting vertical particle scavenging predominates and less lateral sediment focusing/lateral transport (Table 2).

Table 2: Focusing factors (Ψ) for 230Th, 210Pb, and 234Th. 230Th Psi values were calculated based on a water column production rate of 26.7dpm m-3 ky-1 (Francois et al., 2004). The estimated 226Ra activity was 0.14 dpm/kg (Ku and Lin, 1976), and the estimated 238U activity was 2.4 dpm/kg (Pilson, 1988). 234Th Psi ranges were based on the minimum and maximum observed inventories. na = not analyzed.

3.3 Decadal-Centurial Trends

Because of its 22.3 year half-life, 210Pb can be useful in understanding

sedimentary processes integrated over 5 half-lives, or ~110 years (Table 1). During the FOODBANCS-2 Project, Station AA had the highest inventory of the five stations

(mean inventory of 184 dpm/cm2), and there was a decrease in radiochemical inventory/flux moving to the south, where Station G had the lowest inventory (46.1 dpm/cm2, Table 1 and Figure 7). Stations E and F had similar inventories, 65.2 and

66.4 dpm/cm2, respectively (Table 1). At Station AA, one near-surface sample had

an activity of 150 dpm/g, which was higher than any other recorded activity at any of

the stations. If this sample were excluded from the inventory calculations as an

outlier, the conclusions drawn from the statistical tests remain the same; therefore,

the sample was included in the final analysis. A one-way ANOVA was significant when comparing mean 210Pb inventories among the stations (n=16, p-value <

0.0001). Further, a post-hoc test (Tukey multiple comparisons correction) showed

that the mean 210Pb inventory at Station AA was significantly different than the other

4 stations’ means (p-value < 0.0001). There is a significant trend of decreasing 210Pb inventory from north to south (Figure 8, p-value < 0.0001).

250

200 ) 2

150

100

(dpm/cm PbInventory 210 50

0 AA-1AA-2AA-3 B-1 B-2 B-3 E-1 E-2 E-3 F-1 F-2 F-3 G-1 G-2 G-3aG-3b

Station-Cruise

220

200 180 ) 2 160 AA 140 120

100

Pb Inventory (dpm/cm PbInventory 80 B G

210 E 60 F 40

20 0 100 200 300 400 500 600 Distance from Station AA (km)

Figure 8: 210Pb inventory weighted regression analysis. The centurial trend is that of decreasing particle flux from north to south (p-values < 0.0001).

3.4 Seasonal Trends

Due to its short half-life of 24 days, 234Th is an ideal tracer to understand particle dynamics over seasonal timescales (~120 days). For cruise FB2-1, mean

234Th inventories ranged from 0.4 – 5.6 dpm/cm2. The general trend along the peninsula was that of decreasing inventory from Station AA to E with an increase in inventory at Stations F and G (Figure 9). Mean 234Th inventories from FB2-2, ranged from 0.6 – 3.9 dpm/cm2. Austral winter (mean) inventories exhibited the same latitudinal trend as observed the previous summer. Summer 2009, FB2-3, had 234Th inventories as high as 22.3 dpm/cm2 at Station F, and as low as 4.0 dpm/cm2 at

Station E; the same general trend observed during the previous two cruises was observed during cruise FB2-3 (Table 1 and Figure 9).

A two-way ANOVA test showed a significant interaction between the Station and Cruise effects (n=58; p-value = 0.0022). A post-hoc test (Tukey multiple comparisons correction) showed that the only contrasts that produced significant differences in mean 234Th inventories occurred at the southernmost stations

(Stations F and G). For cruise FB2-3, mean inventory at Station F differed significantly compared to mean inventories at Stations B, E and G. The other contrasts that produced significant differences in mean inventories occurred when investigating either Stations F or G for cruise FB2-2 to FB2-3.

20 )

5 Th Inventory (dpm/cm ThInventory

234 0

-5 AA B E F G AA B E F G AA B E F G FB2-1 FB2-2 FB2-3

Seasonal variability in particle flux has been well documented along the

peninsula (McClintic et al., 2008; Smith et al., 2008b; Buessler et al., 2010; Ducklow

et al., 2007; 2012). While the magnitude of the 234Th inventory differed from season

to season, consistent station to station trends in the inventory (high-low-high) were observed during the 12 month study period (Figure 9). For the WAP, the inventories were approximately the same along the N-S transect during each cruise. There was

no statistically significant linear trend along the transect for any of the three cruises

(weighted linear regressions, p-values > 0.132).

3.5 Annual Trends

Annual 234Th inventories were calculated based on the assumption that the

winter inventory (FB2-2) was constant from year-to-year; i.e., 2008 inventory is equivalent to FB2-1 plus FB2-2 and 2009 inventory is FB2-2 plus FB2-3. Annual

234Th inventories were highest at Station AA for 2008 (9.4 dpm/cm2) and highest at

Station F for 2009 (18.6 dpm/cm2). For both 2008 and 2009, inventories were lowest at Station E (1.1 and 4.6 dpm/cm2, respectively), and increasing away from Station

E, both northward and southward (similar to the observed seasonal patterns –

Figure 10). The observed inventories at every station for Summer 2009 were the

same as or greater than 234Th inventories for all of 2008.

25 Inventory = 0.968 + 0.003*distance 2 adj. R = 0.014 p-value = 0.1923 20 ) 2 15

5 (dpm/cm ThInventory 234 0

0 100 200 300 400 500 600 Distance from Station AA (km)

Figure 10: Annual 234Th inventory regression as a function of distance from Station AA. The weighted linear regression equation was derived using the inverse of the squared absolute errors as weights. The data suggest that no linear correlation (p-value = 0.192) between latitude and inventory exists, possibly due to differences in the nature of particle origin on short timescales.

3.6 Sea-Ice Trends

Table 1 shows the counts of ice-free days (up to 120 days) prior to sediment core retrieval. The number of ice-free days observed were lower in the winter compared to the summer for southern Stations E, F and G. Stations AA and B were ice-free for 120 days regardless of season. Over all, Station G had the fewest ice- free days observed for every cruise. Based on satellite ice trends (Appendix B)

Stations B, E, F and G appear to have an increase in the number of ice-free days over the last 35 years. Stations E, F and G show the largest percentage increase in ice-free days (due to the natural decrease in ice-free days with increasing latitude).

When comparing the relationship between ice-free days and 234Th

inventories, no statistical correlation existed when using the pooled inventories

(excluding observations of zero inventories) across stations (n=56, p-value = 0.147).

However, trends in 234Th inventories developed when evaluating stations individually, but only south of Station B (Figure 11). To account for scaling effects in

the 234Th residual data, the inventories were log-transformed and zeros were padded

prior to regression analysis. The 234Th inventory at Station E increased as ice-free

days increased (p-value = 0.013 – Figure 11a). Station F demonstrated no statistical

correlation (Figure 11b, p-value = 0.326) between observed inventory and the

number of ice-free days, likely due to the large difference in 234Th inventory between

summer 2008 and 2009 or sampling timing (see discussion). Station G had a

statistically significant decrease in 234Th inventory as the number of ice-free days

increased (p-value = 0.019 –Figure 11c).

(a) 2.0 (c) 3.0 Station E Station G 1.8 ln(y) = 0.18x -20.31 ln(y) = -0.27x +29.32 2 2 1.6 R = 0.61 p-value = 0.013 2.5 R = 0.35 p-value = 0.019

1.4 2.0 1.2

1.0 1.5 0.8 ThInventory) ThInventory) 234 0.6 234 1.0 ln( ln( 0.4

0.2 0.5 0.0 0.0 112 114 116 118 120 122 99 100 101 102 103 104 105 Ice-free Days Ice-free Days

3.5 Station F 3.0 ln(y) = 0.06x -5.35 (b) R2 = .14 p-value = 0.326 2.5

2.0

1.5 ThInventory) 234 1.0 ln( 0.5 0.0

104 106 108 110 112 114 116 118 120 122 Ice-free Days

Figure 11: The log transformed 234Th inventories at Station E (Figure 11a), Station F (Figure 11b) and Station G (Figure 11c) relative to ice cover 120 days prior to core recovery (120 days represents 5 half-lives of 234Th and thus the typical detection limit). Station E showed a positive, linear trend between 234Th inventory and ice-free days. Station G, however, had a negative linear trend. Station F showed high inter-annual variability between summer 2008 and 2009 and thus no correlation between ice-free days and 234Th inventory.

4.1 Discussion In any marine environment, there are two main components of particle flux to

the seabed – vertical settling and lateral transport. The vertical component is

derived from particulate matter settling (primarily) vertically through the water column

overlying the seabed. Laterally transported sediment comes from outside the study

area, and transport is generally accomplished via currents, tides and (in shallower

environments) waves. The seabed acts to integrate these sources of particle flux.

The 230Th data suggest that sediment has been accreting at all stations on millennial timescales. Assertions about sediment focusing dynamics at the northern stations are approximate due to the high sediment accumulation rate at Station AA, leading to excess 230Th activities near detection limits. The 230Th data suggest that

sediment flux over millennial timescales (1-7ky) effectively scavenges all of the

thorium from the overlying water column.

The observed inventories provide some supportive evidence for sediment

focusing and lateral transport via currents on long-term time scales consistent with

ADCP derived physical oceanographic data reported for the peninsula by Savidge

and Amft (2009) and Moffat et al. (2008).A portion of sediment flux at Station AA,

with a 230Th Psi value > 2 (Table 2), is likely attributable to focusing via lateral

transport. Sediment focusing within Bransfield Strait has been documented in the

past (Yoon et al., 1992; Palanques et al., 2002). The (230Th) Psi values near one

(Table 2) along the southern reaches of the WAP transect indicate that vertical

scavenging of particle predominates and that minimal 230Th is being supplied from

surrounding waters, i.e., very little net lateral transport is occurring on millennial

timescales. The lack of lateral transport on millennial timescales indicates that 230Th

inventories in the seabed are not sensitive to recent changes in climate and particle

flux as suggested by Smith et al. (1999), who describe a warmer, maritime climate

moving southward along the peninsula over the past several decades (Figure 12).

The 14C derived sediment accumulation rates decrease along the N-S

FOODBANCS-2 transect (Table 1), coincident with the natural sea-ice gradient

along the peninsula (Table 3). SARs decreased from Station AA (69 cm/ky) to

Station B and E (30-37 cm/ky) to Station G (5.8 cm/ky). Similarly, 210Pb inventories

decrease along the WAP transect from north to south as shown in Figure 7. The

predicted 210Pb inventory (Ψ=1) can be calculated based on the water column

activity of its effective parent, 226Ra (see Table 2 above), and the overlying water

column height (yielding a value of ~8.0 dpm/cm2, which is ~20 times less than the

average 210Pb inventory at Station AA). The water column height necessary to

support the observed 210Pb inventories along the WAP transect ranged from 3 to 14

km (compared to the actual water depth of ~600 m). Clearly, there is a significant

mechanism by which excess 210Pb is laterally transported to all of the WAP study

sites on 100-year time scales.

Due to its 22.3y half-life, more than half of the observed 210Pb inventories

(and resultant Psi values >> 1) along the WAP can be attributed to sedimentary

process occurring when climate change effects were relatively diminished (>30

years ago). The high inventories likely reflect the sampling depth for the study area

(basins >500m) as well as circulation dynamics on the shelf. Fine grained sediments

(those more likely to scavenge radiochemical tracers from the water column) tend to accumulate below 400m on the WAP shelf (Harden et al., 1992). Basins along the

WAP shelf (water depth > 400m) are characteristic of approximately 30% of the total

shelf area. The sediments occurring at water depths < 400m are primarily reworked

sands containing very little or no fine-grained sediment (and thus, no associated

particle reactive tracers such as 210Pb). Therefore scavenging of nearby shelf 210Pb

production can explain a 210Pb Ψ value of approximately 3.

In addition, the high 210Pb inventories and large Psi values can (in part) be

explained by the short (relative to the half-life of 210Pb) residence time of the waters

along the WAP, as part of regional circulation. Harden et al. (1992) reported a

residence time for Marguerite Bay of approximately 8y and as short as 2y for

Gerlache Strait. The 100 year timescale that 210Pb integrates over is sufficiently long

compared to the water’s residence time that 210Pb produced in offshore

waters(where particle flux is very low) has time to be transported onto the shelf

where it can be scavenged by the enhanced fine-grained sediment fluxes (lithogenic

and biogenic) occurring on the shelf and deposited in the shelf basins (acting as

localized depocenters).

In Bransfield Strait, subglacial discharge is highest during the spring-summer melt, forming sediment rich plumes (Harden et al., 1992). These plumes move seaward via tidally induced resuspension events and density flows (Masque et al.,

2002; Isla et al., 2004). Continued warming trends would likely elevate the sediment load in this region resulting in enhanced particle scavenging, which would lead to future increases in seabed inventories of 210Pb.

Within Marguerite Bay, sediment is mainly lithogenic in origin and

glaciomarine processes control its distribution and rate of accumulation (McGinnis et

al., 1997; Hillenbrand et al., 2008). Intrusions of warmer circumpolar deep water

(CDW) have been shown to increase ice-shelf melt, resulting in increased

suspended sediment concentrations (Taylor et al., 2001; Gilbert et al., 2003). Again,

further warming within Marguerite Bay could lead to increases in sediment load to

the water column. Coupling the short residence time of water parcels within

Marguerite Bay to an increased sediment load would tend towards increasing the

seabed inventories of 210Pb in the future.

As sea-ice melts it produces a freshwater lens, promoting stratification and subsequently enhancing primary productivity (Smith and Nelson, 1985). The increased atmospheric temperatures and subsequent higher wind intensities have made the WAP sea-ice season shorter (Stammerjohn et al., 2008). Smith et al.,

(2008b) showed the decrease in the sea-ice season has the potential to increase the rates and duration of primary production along the WAP. It is reasonable to presume that as warming trends continue, particle flux will increase due to the increased biological activity. Coupled with the potential lithogenic material increase from increased basal flow, subglacial runoff and resuspension, the higher sediment load will effectively scavenge more particle reactive tracers from the water column, increasing seabed inventories. This enhanced radiochemical signal is likely to have

occurred over the past 1-2 decades; as such, the 234Th inventories in recent years are more likely to reveal this response to changing particle flux dynamics than are the 210Pb inventories (where more than 50% of the signal comes from times prior to

observed change).

The data from the N-S transect showed equal 234Th inventories for a given station from both FB2-1 and FB2-2, i.e., the austral summer and winter of 2008, respectively (Figure 9). There was no difference in inventories between the two seasons (p-value = 0.812). The flux observed at Station B during winter 2008 (488 dpm/m2/d) was similar to that observed at a nearby near-bottom sediment trap during the summer of 2000 (400 dpm/m2/d - McClintic et al., 2008). Presumably, little primary production occurs in the winter; as such, the observed winter inventories would more likely be explained by the resuspension and lateral transport of lithogenic material.

The observed 234Th inventories (0.1-2.5 dpm/cm2) in the seabed can be

explained by the complete scavenging of an approximately 10m column of water or

the incomplete scavenging of a taller column. During the winter, when resuspension

and near-bottom nepheloid transport are predominant, seabed inventories are likely the result of more complete scavenging of particles in near-bottom waters. During

the spring and summer, much of the 234Th produced in the euphotic zone is likely to

be scavenged by the organic matter sinking out of the surface waters. However,

significant particulate organic matter is recycled at depth (releasing the associated

234Th), i.e., scavenging during the summer is likely to occur in a vertical mode over a

greater part of the water column (but at much less than 100% removal). Thus, with

very different modes of scavenging and tracer transport during the different seasons,

it is fortuitous that the winter and summer 234Th inventories were so similar. It should

also be noted that during the spring and summer sampling periods, that much of the

234Th signal produced in surface waters, may temporarily reside in the water column

as suspended material (and not in the seabed), especially during times of plankton

blooms.

The 2009 summer’s data showed the southern stations (F and G) with the

highest (10-fold increase relative to the previous summer) 234Th inventories. These

data support the concept of inter-annual variability on the WAP when comparing the summers of 2008 and 2009 (McClintic et al., 2008; Smith et al., 2008b; Buessler et al., 2010). The 234Th inventories at Stations AA and B were (near) constant during

these two summers, whereas the inventories increased substantially (10 fold) at

Stations F and G over the same time period. The increased inventories at F and G

over the entire study period are consistent with an increase in particle flux along the

peninsula as a result of a reduction in ice days at the southern stations.

During the summer of 2009, Stations F and G experienced unusually high

234Th seabed inventories, possibly as a result of an interannual, high particle flux

event (McClintock et al., 2008). However, the high 234Th inventory observed at

Station G during the summer of 2009 corresponded with some of the fewest ice-free

days at this station. The high inventory at G can be explained in part by the timing of

the ice edge retreat at the station (sampling at Station G occurred at or near the ice

edge, enhancing biogenic particle flux, Smith and Nelson, 1985), and not the

absolute number of ice-free days (Fritsen et al., 2011). During the summer of 2009,

Station F exhibited the highest 234Th inventories observed in the study area during the project. In contrast to Station G (which had only 100 ice-free days prior to sampling, out of 120), Station F had 119 days of ice-free conditions (of 120) prior to sampling. The ice edge was likely situated between Stations F and G for a period of

2-3 weeks prior to the FB2-3 cruise.

The mean 234Th inventories were not only unusually high at Station F during

FB2-3, but were (nearly) twice as high as at Station G during the same period. The

enhanced 234Th seabed inventories (and by analogy particle flux) observed at

Station F relative to Station G is consistent with the longer time-period of open-

ocean conditions and the likelihood that Station F was near the ice edge for an

extensive and longer period of time (perhaps 2-3 weeks) than at Station G.

As sea ice recedes earlier in the season, the duration that open ocean

conditions dominate also increases. These waters are already high in nutrients, and

given that light is commonly the limiting factor, the increased number of ice-free days

increases the number of days when light can penetrate the water column and

increase primary production (Fritsen et al., 2011). Additionally, salps, which rapidly

export organic matter from surface waters, are occurring more landward due to the increase in open-ocean conditions along the southern WAP (McClintock et al.,

2008).

In the FOODBANCS-2 study area, Station G exhibited the largest difference in seasonal ice conditions (2008-2009), whereas Station AA appears to remain unchanged (Table 1). In fact, the northern regions of the WAP are much more climatically maritime versus the southern portions of the peninsula, which have been dominated by continental climate historically (Smith et al., 1999; Ducklow et al.,

2007). The sea-ice data (with the 234Th inventories) suggest that the northern stations, AA and B, are not likely influenced by the length of the sea-ice season nor the timing of the ice-edge retreat in recent years. However, the 234Th inventories at

Stations F and G support the idea that particle flux is increasing, possibly in response to the climate shift and the changing sea-ice dynamics along the peninsula.

4.2 Summary of Temporal Trends in Particle Flux

Millennial tracers, 14C and 230Th, suggest that particle flux along the WAP follows a long-term climatic gradient. Northern stations, ice-free most of the year, receive the most particle flux, whereas the southern stations, that are ice-bound most of the year, receive the least amount of particle flux (Figure 13).

Additionally, the particle reactive tracer, 230Th, is efficiently removed from the water column and indicates little net lateral transport on 1000-year timescales. On

100-year timescales, in contrast, the focusing factor derived from the 210Pb data

indicates that lateral transport does play an important role in scavenging particle-

reactive tracers from the water column. Although the trend of decreasing particle flux

with increasing latitude is maintained with the 210Pb inventory data, simple one-

dimensional flux (vertical component only) cannot explain the observed inventories.

Decadal sea-ice trends can help to explain observed particle fluxes along the

WAP (especially the southern stations) on annual and seasonal timescales as open-

ocean conditions increase in this area, allowing more primary production and

increasing particle export from the euphotic zone as well as resuspension and lateral

transport. The high 234Th seabed inventories at Stations F and G suggest that the

faster rate of change in sea-ice coverage brought on by warming oceans is more

important to flux dynamics in the southern, more continental stations, than at the

northern, more maritime, stations (AA and B).

) /

2 250

200

(dpm/cm Inventory Pb 150 210

x 10) / 2 100

Sediment C Accumulation (cm/ky) Rate Th Inventory (dpm/cm ThInventory 14 0

234 AA B E F G

5. Conclusions

Over the last 50 years, there has been an increase in global heat retention,

and this has led to an increase in surface ocean temperatures. Higher temperatures

have been recorded along the WAP, and these have been shown to correlate with

sea-ice dynamics. It has been observed that there is a significant increase in open

ocean area along the peninsula following the decline in sea ice over the past 30

years.

Evaluation of millennial, particle flux proxies (230Th- derived Psi values and

14C sediment accumulation rates) reveal a N-S trend of higher particle flux at Station

AA decreasing southward to Station G. Additionally, 210Pb inventories display a

similar gradient in particle flux along the peninsula, decreasing as latitude increases,

typifying particle flux on centurial time scales. The high 210Pb inventories, relative to

water column production, do suggest extensive sediment focusing via lateral

transport over the past 100 years. Seasonal and annual trends derived from 234Th

inventories along the peninsula show an increase in particle flux at the southern

stations (relative to the northern stations). Although there is a discordant correlation

between sea-ice days and 234Th at the southern stations, data collected along the

WAP suggest that the nature of particle flux has been changing in recent times, and

is consistent with changes in climate and sea-ice coverage. It would appear that the decrease of sea ice, associated with warming trends on the peninsula, is perturbing the long-term trends in particle flux, and leading to an increase in vertical transport

(higher primary productivity) and lateral transport (resuspension during winter storms) at southern stations on seasonal and annual time scales.

There appears to be a systematic increase in particle flux as sea-ice diminishes, which is linked to Stations F and G exhibiting the largest and most systematic changes in sea-ice coverage over the last 35 years. The data indicate some predictive power for radioisotope inventories (234Th) towards climatologically significant variables (ice coverage), but a robust model for either forecasting or reconstructing these variables has not been realized as of yet. Further investigation between ice coverage, radioisotope inventories and biogeochemical tracers, e.g., chlorophyll-a, or other satellite and laboratory derived organic biomarkers (CDOM, fatty acids, etc.) may help to understand natural and anthropogenic forcing on particle flux along the WAP and to aid in the development of a better model for understanding climate change effects on particle flux.

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APPENDICES

Appendix A: Spatial and Temporal 234Th Distributions

25 AA

20 )

2 F 15 AA G AAB 10 B AA B B F AA G AA AAB G F E AAB 5 E B Th Inventory (dpm/cm ThInventory E E G G E E B 234 G E AAE F F AA G F F AA AAE G B B F 0 F B

95 100 105 110 115 120 125 Ice-free Days

Figure 1: Scatter plot of 234Th inventories versus sea-ice free days. No station trend nor season trend was evident from the data for FB2-1 (red), FB2-2 (blue) or FB2-3 (black). The data suggest the timing/position of the ice edge is likely more important than number of ice-free days.

Appendix B: Annual Sea-ice Trends

13 9

12 8

11 7 10 6

9 5 Ice-free Months Ice-free Months Ice-free 8 4 Station AA Station F 3 7 y=0.04x-75.26 y=0.07x-140.66 2 R2 = 0.08 p-value = 0.101 R = 0.20 p-value = 0.009 6 2 1975 1980 1985 1990 1995 2000 2005 2010 2015 1975 1980 1985 1990 1995 2000 2005 2010 2015

14 8

12 6 10 4 8

2 Ice-free Months Ice-free 6 Months Ice-free

Station B 4 y=0.10x-195.07 0 Station G R2 = 0.27 p-value = 0.002 y=0.10x-193.49 R2 = 0.29 p-value = 0.001 2 1975 1980 1985 1990 1995 2000 2005 2010 2015 1975 1980 1985 1990 1995 2000 2005 2010 2015 12

Ice-free Months Ice-free

4 Station E . y=0.09x-174.87 R2 = 0.24 p-value = 0.003 2 1975 1980 1985 1990 1995 2000 2005 2010 2015

Figure 1: Least squares regressions for ice-free months during satellite record period for each of the FOODBANCS-2 stations. Stations B, E, F and G appear to have the largest increase in ice-free months over the last 35 years. Stations E, F and G show the largest percentage increase in the number of ice-free days

230 Appendix C: Thxs Profiles

230 Th (dpm/g) 230Th (dpm/cm) xs xs -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0 0 0 Station AA 20 20

40 40

60 60 80 80 Depth (cm) Depth Depth (cm) Depth 100 100

120 120

140 Station F 140

230 230 Thxs (dpm/cm) Thxs (dpm/cm) -1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 0 0 Station B 20 Station G 20 40 40 60 60 80 80 100 100 (cm) Depth (cm) Depth 120 120 140 140 160 160 180

230 Figure 1: Thxs (excess) activity versus depth profiles from kasten cores collected during FOODBANCS-2.

210 Appendix D: Pbxs Profiles

AA F 210Pb (dpm/g) 210 xs Pbxs (dpm/g) 0 20 40 60 80 100 120 140 160 0 10 20 30 40 50 0 0

5 5

10 10

15 15 Depth (cm) Depth (cm) Depth

20 20 FB2-1 FB2-1 FB2-2 FB2-2 FB2-3 FB2-3 25 average 25 average

B G 210 210 Pbxs (dpm/g) Pbxs (dpm/g) 0 10 20 30 40 50 60 0 5 10 15 20 25 30 35 0 0

5 5

10 10

15 15

(cm) Depth (cm) Depth

20 FB2-1 20 FB2-1 FB2-2 FB2-2 FB2-3 FB2-3 average FB2-3 25 25 average

E 210 Pbxs (dpm/g) 0 10 20 30 40 50 0

15 (cm) Depth 20 FB2-1 FB2-2 FB2-3 25 average

210 Figure 1: Pbxs (excess) versus depth profiles from the FOODBANCS-2 cores. Supported activity was estimated using an asymptotic approximation of 226Ra activity

234 Appendix E: Thxs Profiles

234 Figure 1: Thxs (excess) activity versus depth profiles from each core from the FOODBANCS-2 project. Rows represent the data from different stations, whereas columns represent station data from different cruises.

Appendix E Continued 234Th (dpm/g) 234Th (dpm/g) 234Th (dpm/g) xs xs xs 0 5 10 15 20 25 30 0 5 10 15 20 0 5 10 15 20 25 30

0 0 0

2 2 2

Station AA

Depth (cm) Depth 4 (cm) Depth 4 (cm) Depth 4 FB2-1 Station AA Station AA CRS 932 FB2-2 CRS935 FB2-3 CRS 937 CRS 1111 CRS 1230 6 CRS 938 6 CRS 1120 6 CRS 1235 CRS 944 CRS 1123 CRS 1239

234 234 234 Thxs (dpm/g) Thxs (dpm/g) Thxs (dpm/g) -2 0 2 4 6 8 10 12 14 16 18 -2 0 2 4 6 8 10 12 14 16 0 5 10 15 20 25 30 35 0 0 0

2 2 2

Station B Station B Depth (cm) Depth 4 (cm) Depth 4 (cm) Depth 4 FB2-1 Station B FB2-3 FB2-2 CRS 963 CRS 1254 CRS 965 CRS 1107 CRS 1256 CRS 966 CRS 1141 CRS 1258A 6 CRS 971 6 CRS 1142 6 CRS 1258B CRS 973 CRS 1144 CRS 1260 234Th (dpm/g) 234Th (dpm/g) 234Th (dpm/g) xs xs xs 0 5 10 15 20 25 30 -2 0 2 4 6 8 10 0 10 20 30 40 50 0 0 0

2 2 2

(cm) Depth 4 (cm) Depth 4 (cm) Depth 4 Station E Station E FB2-3 Station E FB2-2 FB2-1 CRS 1084 CRS 1210 6 6 6 CRS 1086 CRS 1218 CRS 1035 CRS 1096 CRS 1221

Appendix E Continued

234 234 234 Thxs (dpm/g) Thxs (dpm/g) Thxs (dpm/g)

-2 0 2 4 6 8 10 12 -2 0 2 4 6 8 10 12 14 0 20 40 60 80 100 120 140 160 180

0 0 0

2 2 2

Depth (cm) Depth 4 (cm) Depth 4 (cm) Depth 4 Station F Station F Station F FB2-1 FB2-2 FB2-3 CRS 996 CRS 1063 CRS 1167 6 6 6 CRS 998 CRS 1073 CRS 1170 CRS 1004 CRS 1077 CRS 1171

234 234 234 Thxs (dpm/g) Thxs (dpm/g) Thxs (dpm/g) -2 0 2 4 6 8 10 12 0 5 10 15 20 25 30 0 10 20 30 40 50 0 0 0

2 2 2

Station G Station G Depth (cm) Depth 4 Station G (cm) Depth 4 (cm) Depth 4 FB2-1 FB2-2 FB2-3 CRS 1014 CRS 1040 CRS 1996 CRS 1015 CRS 1041 CRS 1997 CRS 1019 CRS 1049 CRS 1998 6 6 6 CRS 1022 CRS 1053 CRS 1999 CRS 1023 CRS 1059 CRS 1201

Appendix F: Radiochemical Data

230 Table 1: Thxs is the salt corrected excess activity for a depth interval. Error terms were propagated from counting statistics and represent absolute errors. No negative values were used in the calculation of inventories.

Station AA CRS 949 FB2-1 Station B CRS1138 FB2-2 Station F CRS 1175 FB2-3 Station G CRS 1011 FB2-1 230 230 230 230 Depth Thxs error Depth Thxs error Depth Thxs error Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) 0-3 0.05 0.01 10-13 0.69 0.06 0-2 2.31 0.27 0-3 1.32 0.09 5-7 -0.20 -0.02 25-28 -0.17 -0.02 45-47 -0.06 -0.01 20-23 1.43 0.10 17-19 -0.29 -0.03 40-43 -0.45 -0.04 110-112 -0.06 -0.01 40-43 0.30 0.03 29-31 -0.36 -0.04 55-58 0.18 0.02 150-152 -0.10 -0.02 60-63 -0.04 0.00 41-43 -0.76 -0.12 70-73 -0.25 -0.02 80-83 -1.29 -0.14 53-55 -0.33 -0.04 85-88 0.49 0.05 100-103 0.46 0.04 65-67 -0.39 -0.04 100-103 0.48 0.05 120-123 0.39 0.04 77-79 0.11 0.01 115-118 -0.47 -0.04 140-143 0.31 0.03 89-91 -0.48 -0.06 130-133 -1.02 -0.08 160-163 0.91 0.13 101-103 -0.58 -0.07 145-148 -0.49 -0.06 113-115 -0.46 -0.04 160-163 0.00 0.00 125-127 -0.48 -0.06 173-176 0.31 0.03

Appendix F Continued

210 Table 2: Pbxs is the salt corrected excess activity for a depth interval. Supported activity is asymptotic approximation of 226Ra activity. Error terms were propagated from counting statistics and represent absolute errors.

FB2-1 FB2-2 FB2-3 210 210 210 Station CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) AA 935 0-0.5 7.34 1.52 1123 0-0.5 38.73 6.40 1235 0.0-0.5 37.51 1.90 0.5-1 40.14 1.51 0.5-1 36.74 1.62 0.5-1 42.37 1.59 1-1.5 151.83 5.64 1-1.5 38.61 1.49 1-1.5 43.89 1.78 1.5-2 34.10 1.34 1.5-2 37.77 1.56 1.5-2 37.90 1.42 2-3 33.37 1.24 2-3 31.15 1.32 2-3 33.48 1.26 3-4 28.95 1.12 3-4 29.95 1.34 3-4 26.52 1.00 4-5 24.00 0.97 4-5 24.82 0.99 4-5 22.53 0.86 5-6 19.43 0.81 5-6 20.82 0.86 5-6 18.96 0.77 6-7 19.39 0.84 6-7 20.93 0.86 6-7 20.20 0.80 7-8 16.86 0.71 7-8 20.72 0.96 7-8 17.86 0.71 8-9 9.82 0.45 8-9 15.74 0.69 8-9 12.13 0.55 9-10 6.50 0.32 10-11 7.15 0.45 9-10 6.62 0.34 11-12 2.90 0.20 12-13 3.45 0.37 11-12 3.41 0.25 13-14 1.43 0.17 14-15 0.88 0.30 13-14 11.12 0.47 15-16 0.28 0.14 16-17 0.54 0.25 15-16 0.42 0.19 17-18 0.21 0.17 18-19 0.26 0.24 17-18 0.15 0.18 19-20 0.18 0.14 20-22 0.15 0.24 19-20 0.00 0.18 22-24 0.25 0.13 24-26 0.00 0.24 22-24 0.20 0.19 26-28 0.00 0.17

supported activity 0.86 1.02 1.14

Appendix F Continued

Table 2 Continued

FB2-1 FB2-2 FB2-3 210 210 210 Station CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) B 963 0-0.5 27.51 4.25 1141 0.0-0.5 34.68 1.97 1160 0-0.5 25.23 4.48 0.5-1 43.05 2.31 0.5-1 29.72 1.48 0.5-1 51.24 1.96 1-1.5 39.71 1.73 1-1.5 26.29 1.48 1-1.5 56.78 10.18 1.5-2 29.63 1.45 1.5-2 22.04 1.20 1.5-2 37.29 1.64 2-3 20.10 1.03 2-3 11.31 0.95 2-3 21.38 0.94 3-4 19.27 0.96 3-4 12.54 0.94 3-4 18.72 0.87 4-5 10.95 0.77 4-5 11.06 0.95 4-5 14.42 0.66 5-6 11.00 0.95 5-6 8.88 0.87 5-6 17.25 0.84 6-7 7.55 0.63 6-7 17.41 1.13 6-7 13.86 0.73 7-8 6.51 0.74 7-8 22.25 1.27 7-8 6.39 0.56 8-9 6.24 0.61 8-9 15.17 1.01 8-9 4.84 0.34 9-10 4.97 0.69 10-11 4.22 0.80 9-10 3.31 0.40 10-11 3.18 0.53 12-13 2.54 0.79 11-12 1.60 0.23 12-13 1.74 0.55 14-15 10.91 0.93 13-14 14.78 0.73 14-15 1.02 0.49 16-17 1.34 0.77 15-16 8.78 0.68 16-17 0.41 0.48 18-19 1.64 0.77 17-18 0.02 0.19 18-19 0.00 0.46 20-22 0.59 0.76 19-20 0.01 0.16 20-22 0.27 0.49 24-26 0.00 0.75 22-24 0.00 0.16

supported activity 3.32 3.47 3.23

FB2-1 FB2-2 FB2-3 210 210 210 Station CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) E 1035 0.0-0.5 34.36 4.06 1084 0.0-0.5 25.21 5.09 1221 0.0-0.5 41.85 2.12 0.5-1 38.61 1.96 0.5-1 45.79 2.01 0.5-1.0 27.60 7.48 1-1.5 26.82 1.25 1-1.5 33.32 2.84 1.0-1.5 37.35 2.51 1.5-2 23.56 1.20 1.5-2 28.40 2.18 1.5-2 17.88 0.92 2-3 19.09 1.02 2-3 23.58 1.69 2-3 33.87 1.45 3-4 10.16 0.75 3-4 19.11 1.72 3-4 15.46 0.95 4-5 11.53 0.85 4-5 14.48 1.45 4-5 10.26 0.76 5-6 9.22 0.72 5-6 9.64 1.17 5-6 7.54 0.65 6-7 12.16 0.79 6-7 7.07 1.09 6-7 7.34 0.69 7-8 9.59 0.73 7-8 8.20 1.10 7-8 9.64 0.73 8-9 6.64 0.74 8-9 8.53 1.09 8-9 8.60 0.73 9-10 10.21 0.89 10-11 3.81 1.04 9-10 6.71 0.65 10-11 5.95 0.63 12-13 3.38 1.01 11-12 4.13 0.59 12-13 2.24 0.57 14-15 2.17 1.02 13-14 1.89 0.55 14-15 1.15 0.62 16-17 0.77 0.99 15-16 1.16 0.55 16-17 0.23 0.55 18-19 0.26 1.00 17-18 0.88 0.54 18-19 0.00 0.56 20-22 0.00 0.99 19-20 0.00 0.52 20-22 0.27 0.55 22-24 0.75 0.53

supported activity 3.39 3.45 4.33

Appendix F Continued

Table 2 Continued

FB2-1 FB2-2 FB2-3 210 210 210 Station CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) F 998 0.0-0.5 5.49 4.90 1077 0.0-0.5 31.23 1.81 1167 0.0-0.5 46.93 3.00 0.5-1 19.17 1.00 0.5-1 20.66 1.27 0.5-1 27.59 1.67 1-1.5 17.42 0.98 1-1.5 19.16 1.23 1-1.5 18.71 1.24 1.5-2 16.70 0.97 1.5-2 14.03 1.01 1.5-2 11.87 1.17 2-3 11.90 0.87 2-3 5.04 0.85 2-3 10.14 1.05 3-4 9.74 0.74 3-4 3.76 0.83 3-4 7.11 1.14 4-5 11.08 0.89 4-5 2.91 0.83 4-5 6.00 1.00 5-6 7.13 0.67 5-6 2.97 0.83 5-6 3.79 1.06 6-7 7.43 0.73 6-7 2.23 0.84 6-7 3.87 0.97 7-8 8.90 1.00 7-8 3.84 0.83 7-8 4.16 0.97 8-9 11.16 0.78 8-9 5.31 0.87 8-9 4.38 0.97 9-10 12.31 0.82 10-11 5.80 0.96 9-10 5.24 0.98 10-11 14.33 0.85 12-13 2.79 0.82 11-12 1.99 0.95 12-13 10.88 0.78 14-15 1.29 0.83 13-14 2.39 0.95 14-15 5.14 0.62 16-17 1.68 0.80 15-16 1.45 0.94 16-17 2.38 0.58 18-19 1.92 0.83 17-18 0.00 0.94 18-19 0.99 0.63 20-22 0.76 0.79 19-20 1.89 0.97 20-22 0.76 0.55 24-26 0.00 0.79 24-26 0.00 0.55

supported activity 2.89 3.12 3.21

FB2-1 FB2-2 FB2-3 FB2-3 210 210 210 210 Station CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error CRS ID Depth Pbxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) G 1019 0.0-0.5 20.46 3.30 1049 0.0-0.5 31.72 5.85 1198 0.0-0.5 21.80 4.61 1197 0.0-0.5 28.18 1.48 0.5-1 19.41 0.79 0.5-1 29.00 1.24 0.5-1 19.74 1.18 0.5-1 20.69 0.95 1-1.5 15.50 0.74 1-1.5 21.75 1.19 1-1.5 18.70 0.92 1-1.5 12.09 0.58 1.5-2 13.83 0.64 1.5-2 16.64 0.87 1.5-2 17.42 0.84 1.5-2 8.83 0.47 2-3 8.02 0.46 2-3 14.69 0.75 2-3 10.88 0.61 2-3 4.74 0.35 3-4 4.71 0.34 3-4 8.91 0.61 3-4 5.98 0.51 3-4 3.85 0.34 4-5 2.84 0.30 4-5 4.26 0.49 4-5 5.35 0.46 4-5 2.74 0.29 5-6 2.58 0.26 5-6 3.53 0.49 5-6 4.15 0.45 5-6 3.98 0.32 6-7 2.78 0.27 6-7 2.98 0.47 6-7 4.28 0.47 6-7 3.87 0.32 7-8 3.17 0.27 7-8 3.18 0.49 7-8 5.66 0.49 7-8 3.79 0.32 8-9 2.27 0.27 8-9 4.44 0.50 8-9 6.40 0.52 8-9 7.65 0.43 9-10 1.48 0.23 9-10 5.21 0.54 9-10 7.40 0.52 9-10 9.04 0.47 10-11 1.42 0.23 10-11 7.64 0.58 10-11 4.80 0.49 10-11 4.52 0.15 11-12 1.00 0.21 11-12 5.33 0.55 11-12 2.19 0.42 11-12 0.00 0.21 12-13 0.57 0.20 12-13 3.02 0.49 12-13 1.47 0.40 12-13 0.50 0.15 13-14 0.42 0.19 13-14 2.07 0.46 13-14 0.74 0.39 13-14 1.00 0.24 14-15 0.26 0.19 14-15 1.12 0.44 14-15 0.68 0.43 15-16 0.15 0.18 15-16 0.95 0.44 15-16 0.62 0.43 16-17 0.03 0.17 16-17 0.77 0.44 16-17 0.41 0.42 17-18 0.09 0.18 17-18 0.70 0.44 17-18 0.21 0.38 18-19 0.16 0.18 18-19 0.62 0.43 18-19 0.10 0.38 19-20 0.08 0.18 19-20 0.59 0.44 19-20 0.00 0.38 20-22 0.00 0.18 20-22 0.56 0.44 22-24 0.00 0.42 supported activity 2.67 2.49 2.77 3.60

Appendix F Continued

234 Table 3: Thxs is the salt corrected excess activity at a given depth interval. Error terms were propagated from counting statistics and represent absolute errors. NVOAEB* = negative values outside analytic error bars. No negative values were used in the calculation of inventories.

FB2-1 FB2-2 FB2-3 234 234 234 Station CRS ID Depth Thxs error CRS ID Depth Thxs error CRS ID Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) AA 932 0-0.5 10.73 0.10 1111 0-0.5 11.69 0.12 1230 0-0.5 23.50 0.12 1-1.5 0.35 0.11 1-1.5 -0.63 0.14 1-1.5 4.68 0.10 2-3 0.12 0.07 2-3 -0.59 0.13 2-3 1.11 0.08 4-5 -0.84 0.10 4-5 -0.15 0.07 4-5 1.15 0.10 6-7 -0.69 0.10 6-7 -0.64 0.07 6-7 0.47 0.08

935 0-0.5 24.40 0.12 1120 0-0.5 17.58 0.11 1235 0-0.5 13.80 0.11 1-1.5 4.29 0.11 1-1.5 0.28 0.10 1-1.5 5.51 0.12 2-3 0.30 0.08 2-3 NVOAEB* 2-3 2.85 0.08 4-5 -0.58 0.11 4-5 NVOAEB* 4-5 -0.24 0.11 6-7 -0.36 0.10 6-7 NVOAEB* 6-7 0.73 0.13

937 0-0.5 25.20 0.10 1123 0-0.5 15.22 0.09 1239 0-0.5 24.86 0.09 1-1.5 4.59 0.10 1-1.5 1.13 0.09 1-1.5 2.15 0.11 2-3 0.49 0.08 2-3 -0.70 0.10 2-3 1.32 0.08 4-5 -0.17 0.10 4-5 1.43 0.09 4-5 -0.16 0.11 6-7 -0.17 0.10 6-7 NVOAEB* 6-7 -0.17 0.10

938 0-0.5 20.89 0.10 1-1.5 0.00 0.11 2-3 0.46 0.09 4-5 -0.43 0.10 6-7 -0.03 0.10

944 0-0.5 10.51 0.11 1-1.5 4.60 0.13 2-3 0.89 0.08 4-5 -0.59 0.10 6-7 -0.47 0.10

Appendix F Continued

Table 3 Continued

FB2-1 FB2-2 FB2-3 234 234 234 Station CRS ID Depth Thxs error CRS ID Depth Thxs error CRS ID Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) B 963 0-0.5 15.25 0.10 1107 0-0.5 13.29 0.11 1160 0-0.5 11.34 0.11 1-1.5 1.67 0.08 1-1.5 0.27 0.11 1-1.5 0.64 0.10 2-3 0.03 0.09 2-3 -0.92 0.10 2-3 0.23 0.09 4-5 -0.44 0.09 4-5 NVOAEB* 4-5 0.03 0.10 6-7 0.20 0.09 6-7 NVOAEB* 6-7 1.76 0.11

965 0-0.5 10.79 0.07 1141 0-0.5 12.41 0.11 1254 0-0.5 10.22 0.14 1-1.5 2.85 0.07 1-1.5 4.87 0.12 1-1.5 2.46 0.10 2-3 0.20 0.09 2-3 -1.01 0.11 2-3 5.60 0.10 4-5 1.51 0.08 4-5 -1.76 0.12 4-5 0.17 0.09 6-7 0.71 0.08 6-7 0.28 0.13 6-7 1.00 0.12

966 0-0.5 6.75 0.09 1142 0-0.5 6.98 0.11 1256 0-0.5 30.65 0.11 1-1.5 1.10 0.08 1-1.5 0.36 0.10 1-1.5 4.52 0.16 2-3 NVOAEB* 2-3 -0.59 0.09 2-3 1.05 0.10 4-5 -0.25 0.10 4-5 NVOAEB* 4-5 1.80 0.11 6-7 -0.76 0.09 6-7 0.36 0.11 6-7 -0.78 0.11

971 0-0.5 7.29 0.08 1144 0-0.5 5.34 0.10 1258A 0-0.5 9.54 0.10 1-1.5 -0.76 0.09 1-1.5 -1.58 0.10 1-1.5 1.83 0.11 2-3 0.06 0.10 2-3 -0.23 0.09 2-3 1.58 0.10 4-5 0.08 0.10 4-5 0.74 0.11 4-5 3.80 0.13 6-7 0.55 0.10 6-7 -0.48 0.11 6-7 -0.14 0.11

973 0-0.5 4.12 0.09 1258B 0-0.5 19.64 0.11 1-1.5 -0.65 0.08 1-1.5 0.92 0.09 6-7 -0.84 0.08 2-3 0.08 0.10 4-5 2.39 0.10 6-7 1.84 0.14

Appendix F Continued

Table 3 Continued

FB2-1 FB2-2 FB2-3 234 234 234 Station CRS ID Depth Thxs error CRS ID Depth Thxs error CRS ID Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) E 978 1-1.5 -0.10 0.11 1084 0-0.5 8.01 0.11 1210 0-0.5 13.51 0.18 2-3 -0.91 0.09 1-1.5 -0.54 0.11 1-1.5 3.34 0.11 4-5 NVOAEB* 2-3 -0.53 0.08 2-3 0.43 0.09 6-7 NVOAEB* 4-5 NVOAEB* 4-5 1.75 0.10 6-7 -0.06 0.07 6-7 3.09 0.06

982 1-1.5 -0.15 0.10 1086 0-0.5 6.41 0.11 1218 0-0.5 38.15 0.15 2-3 -0.34 0.08 1-1.5 -0.88 0.12 1-1.5 2.11 0.10 2-3 NVOAEB* 2-3 1.46 0.07 4-5 NVOAEB* 4-5 NVOAEB* 6-7 -0.05 0.08 6-7 1.29 0.08

1035 0-0.5 24.13 0.16 1096 0-0.5 7.68 0.12 1221 0-0.5 34.06 0.10 1-1.5 1.09 0.10 0.5-1.5 0.47 0.11 1-1.5 0.59 0.11 2-3 -0.16 0.07 1.5-2 -0.46 0.09 2-3 1.09 0.07 4-5 -0.59 0.06 2-3 NVOAEB* 4-5 -0.12 0.08 6-7 -0.23 0.05 4-5 NVOAEB* 6-7 0.26 0.08 6-7 -0.43 0.08

FB2-1 FB2-2 FB2-3 234 234 234 Station CRS ID Depth Thxs error CRS ID Depth Thxs error CRS ID Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) F 996 0-0.5 4.24 0.09 1063 0-0.5 11.95 0.10 1167 0-0.5 54.68 0.10 1-1.5 0.92 0.08 1-1.5 -0.10 0.08 1-1.5 5.94 0.09 2-3 NVOAEB* 2-3 0.27 0.07 2-3 1.07 0.08 4-5 NVOAEB* 4-5 0.67 0.08 4-5 0.20 0.09 6-7 0.68 0.07 6-7 -0.41 0.07 6-7 2.14 0.08

998 0-0.5 0.11 0.11 1073 0-0.5 9.61 0.06 1170 0-0.5 13.81 0.08 1-1.5 NVOAEB* 1-1.5 -0.04 0.07 1-1.5 1.03 0.08 2-3 NVOAEB* 2-3 0.65 0.06 2-3 18.72 0.10 4-5 NVOAEB* 4-5 0.98 0.07 4-5 0.48 0.08 6-7 -0.59 0.07 6-7 0.22 0.09 6-7 1.84 0.08

1004 0-0.5 10.61 0.09 1077 0-0.5 10.23 0.06 1171 0-0.5 166.28 0.09 1-1.5 0.22 0.09 1-1.5 -0.14 0.08 1-1.5 8.13 0.08 2-3 NVOAEB* 2-3 -0.28 0.10 2-3 0.12 0.06 4-5 6.11 0.11 4-5 -0.39 0.07 4-5 1.44 0.08 6-7 0.28 0.07 6-7 -0.06 0.07 6-7 2.40 0.09

Appendix F Continued

Table 3 Continued

FB2-1 FB2-2 FB2-3 234 234 234 Station CRS ID Depth Thxs error CRS ID Depth Thxs error CRS ID Depth Thxs error (cm) (dpm/g) (±) (cm) (dpm/g) (±) (cm) (dpm/g) (±) G 1014 0-0.5 10.04 0.09 1040 0-0.5 11.67 0.07 1196 0-0.5 13.45 0.10 1-1.5 -0.29 0.09 1-1.5 0.52 0.07 1-1.5 4.07 0.07 2-3 -0.70 0.06 2-3 0.06 0.05 2-3 10.14 0.06 4-5 0.32 0.06 4-5 0.63 0.05 4-5 3.05 0.05 6-7 0.54 0.06 6-7 0.19 0.05 6-7 1.62 0.06

1015 0-0.5 9.31 0.08 1041 0-0.5 17.08 0.07 1197 0-0.5 18.43 0.10 1-1.5 0.76 0.08 1-1.5 0.53 0.07 1-1.5 3.56 0.08 2-3 0.92 0.06 2-3 -0.51 0.08 2-3 0.97 0.05 4-5 -0.40 0.06 4-5 0.08 0.06 4-5 1.82 0.05 6-7 -0.14 0.07 6-7 0.45 0.06

1019 0-0.5 5.85 0.08 1049 0-0.5 25.12 0.07 1198 0-0.5 44.51 0.15 1-1.5 0.02 0.08 1-1.5 0.80 0.07 1-1.5 1.61 0.09 2-3 0.55 0.06 2-3 0.00 0.06 2-3 -0.06 0.07 4-5 1.51 0.05 4-5 0.05 0.06 4-5 -0.01 0.07 6-7 2.46 0.05 6-7 0.08 0.06 6-7 4.42 0.05

1022 0-0.5 9.70 0.08 1053 0-0.5 13.83 0.07 1199 0-0.5 12.43 0.09 1-1.5 -0.04 0.08 1-1.5 0.38 0.07 1-1.5 3.88 0.08 2-3 0.13 0.08 2-3 0.30 0.05 2-3 1.24 0.07 4-5 0.27 0.06 4-5 0.70 0.08 4-5 2.71 0.06 6-7 2.08 0.05 6-7 6.87 0.05

1023 0-0.5 8.64 0.08 1059 0-0.5 16.67 0.07 1201 0-0.5 14.84 0.10 1-1.5 0.59 0.08 1-1.5 0.15 0.08 1-1.5 2.07 0.08 2-3 -0.68 0.06 2-3 -0.27 0.06 2-3 0.22 0.06 4-5 0.71 0.05 4-5 0.08 0.06 4-5 0.49 0.06 6-7 4.87 0.06 6-7 0.25 0.06 6-7 4.00 0.05

Appendix G: FOODBANCS Sediment Trap Data

Table 1: Near-bottom (150-175 mab) sediment trap data (1999 – 2001) from FOODBANCS project (McClintic et al, 2008). Traps were deployed at Station B,64 48.00’S 65 21.30’W , (within 0.5km of Station B occupied during FOODBANCS-2). Trap flux is derived from 234Th.