nitrate measurement and dynamics in the solitary islands ... · such as nutrient enriched river...

Nitrate Measurement and Dynamics

in the Solitary Islands Marine Park

Adam Davies

June 2011

Supervised by: Professor Anya Waite, Dr. Vincent Rossi and Dr. Peter Thompson

School of Environmental Systems Engineering

The University of Western Australia

1

Special Thanks

This project could not have come together without the support of some very important, and

particularly excellent people.

Professor Anya Waite (UWA), for creating to opportunity for me to undertake this research.

Dr. Vincent Rossi (UNSW), or his support in both collection and analysis of the data.

Dr. Peter Thompson (CSIRO), for lending me the ISUS unit.

Dr. Moninya Roughan, Dr. Brad Morris, Julie Wood, Helen Macdonald and Dianne Krikke

for their assistance in the field, and willingness to share their knowledge and expertise.

Peter Hughes at CSIRO Floreat for analysing the collected water samples

Stan and Mick from Wooli Dive Charters for the use of their boat.

My friends, family, house mates, band mates and everyone else who has supported me

through this project.

Twinings, for making Irish Breakfast Tea.

Adam Davies June 2011

2

AbstractNitrogen is a critical nutrient for the growth of primary producers in coral reef systems.

While historically nitrate has been measurable only through bottle sampling and subsequent

laboratory analysis, recent advances in spectrophotometry have enabled the in-situ profiling

of nitrate as a function of depth, creating data sets of both higher resolution and increased

accuracy. The In-Situ Ultraviolet Spectrophotometer (ISUS) device has proven to be

extremely accurate and reliable in deep ocean surveys, where nitrate concentration is

typically 20 – 50 μM. The objectives of this study were twofold – firstly to investigate the

practical detection limits and accuracy margins of the ISUS device in a very low

concentration (≤10 μM), near shore, shallow water environment, and, secondly, to use the

collected data as a mechanism to better understand the dynamics of the region.

A series of transects gathering both continuous depth-nitrate data and discrete Niskin Bottle

samples were performed across the continental shelf (depth 20-110m) around North Solitary

Island in late spring. The dominant features of the region are the southward flowing Eastern

Australian Current, upwelling driven by Ekman Transport and a well mixed surface layer.

Data from both the ISUS and bottle sample units suggest a deep nitrate maximum, consistent

with a deep water upwelling scenario. The noise associated with operating near the

detection limit of the spectrophotometer makes the very low concentration, near surface data

relatively unreliable when compared to bottle sample results. The distribution of ISUS

measured concentrations was much wider than expected, showing a standard deviation in

sampling of three times the expected accuracy.

Operating the ISUS unit in well mixed, extremely low nitrate concentration (≤2 μM) surface

waters produces data of no value. The device outpt is useful however in determining the

larger scale distributions of nitrate and the depth of the well mixed surface layer, if not the

specific concentrations for nitrate bugeting. The ISUS also successfully identified a low

concentration zone associated with the wake of North Solitary Island.

3

Table of ContentsAbstract.......................................................................................................................................3Glossary......................................................................................................................................5List of Tables...............................................................................................................................6List of Figures.............................................................................................................................6Introduction.................................................................................................................................7Literature Review........................................................................................................................9

Nitrate in the Marine Environment........................................................................................9ISUS Function......................................................................................................................11ISUS Limitations..................................................................................................................12The Study Site......................................................................................................................12

Solitary Islands Marine Park...........................................................................................12East Australian Current....................................................................................................13Climate change and oceanic nitrate.................................................................................13El-nino and the Southern Oscillation Index.....................................................................13Outcomes from accurate nitrate reporting.......................................................................14

Methods.....................................................................................................................................15Field Study Methodology.....................................................................................................15

Study Stations..................................................................................................................15Rosette Deployment.........................................................................................................17Bottle Sample Collection.................................................................................................19Error Sources...................................................................................................................19

Alternate data sources..........................................................................................................23Wind speed data...............................................................................................................23Sea Surface Temperature.................................................................................................23CTD/Fluorometer Data....................................................................................................24

Laboratory Analysis.............................................................................................................24Results.......................................................................................................................................26

Isus Output Calibration........................................................................................................26ISUS Function......................................................................................................................27Mixing Depth.......................................................................................................................27ISUS output vs. Laboratory Analysis...................................................................................31

Discussion.................................................................................................................................36ISUS data compared to Laboratory Data.............................................................................36Interesting Features..............................................................................................................36Upwelling Mechanisms........................................................................................................38

Ekman Transport..............................................................................................................38EAC acceleration.............................................................................................................38Topographical Upwelling................................................................................................38Rossby Radius of Deformation........................................................................................39

Conclusions and Recommendations.........................................................................................40References.................................................................................................................................41Appendices................................................................................................................................43

Appendix A: Sample ISUS Data..........................................................................................43Appendix B: LAB Data........................................................................................................44

4

GlossaryCSIRO Commonwealth Scientific and Industrial Research Organisation

CTD Conductivity, Temperature and Depth Sensor

EAC Eastern Australian Current

ENSO El Niño Southern Oscillation Index

ISUS In-situ Ultraviolet Spectrophotometer

Niskin Bottle A water capturing device designed to close at a programmed depth, holding

a 4L sample.

SIMP Solitary Islands Marine Park

SST Sea Surface Temperature

UV Ultraviolet

UNSW The University of New South Wales

UWA The University of Western Australia

5

List of TablesTable 1: Study Station Summary...............................................................................................17Table 2: Sampling Regime for 25-Nov-2011............................................................................20Table 3: Sampling Regime for 26-Nov-2011............................................................................20Table 4: Sampling Regime for 28-Nov-2011............................................................................21Table 5: Sampling Regime for 29-Nov-2011............................................................................22Table 6: Lab Analysis Results: A Transect................................................................................44Table 7: Lab Analysis Results, B Transect................................................................................45Table 8: Adjusted 2-point average samples...............................................................................45Table 9: Lab Analysis Results, E Field.....................................................................................46

List of FiguresFigure 1: Fundamentals of the Nitrogen Cycle.........................................................................10Figure 2: ISUS Design featuring: A-Spectrometer, B-UV Light Source, C-UV Fiber for reference detector, D- High pressure endcap, E- Retroreflective Probe, F- Reference channel board, G-Control Unit, H-UV Fiber to Spectrometer, I-Battery Pack (Johnson & Coletti 2002)..........................................................................................................................................11Figure 3: Study Site Location and Sample Stations..................................................................15Figure 4: Sample Stations and regional bathymetry (Rossi 2010)............................................16Figure 5: Rosette showing: A-CTD with Fluorometer, B-Niskin Bottles, C-ISUS Sensor......18Figure 6: Wind Intensity and Stress over the study period. Boxed sections indicate sampling times (Rossi 2010)....................................................................................................................23Figure 7: 3 day average SST on 22-Nov-2011 (Macdonald 2010)...........................................24Figure 8: 3 day average SST on 26-Nov-2011 (Macdonald 2010)...........................................24Figure 9: ISUS calibration curve, linear regression showing colour as depth (Rossi 2011).....26Figure 10: Nitrate Concentrations at station A8........................................................................27Figure 11: A Transect Temperature Profiles..............................................................................28Figure 12: A Transect Thermocline and Cast Depths................................................................28Figure 13: B Transect Temperature Profiles.............................................................................29Figure 14: B Transect Thermocline and Cast Depths...............................................................29Figure 15: E Field Temperature Profiles...................................................................................30Figure 16: Mixing depths in E field: E02, E03 and E04 Subset...............................................30Figure 17: Mixing depths in E field: E05, E06 and E07 Subset...............................................31Figure 18: Mixing depths in E field: E09 and E10 Subset........................................................31Figure 19: A Transect Nitrate Curves (A02-A05).....................................................................31Figure 20: A Transect Nitrate Curves (A06-A08).....................................................................32Figure 21: B Transect Nitrate Curves (B01-B03).....................................................................32Figure 22: B Transect Nitrate Curves (B04-B06).....................................................................33Figure 23: B Transect Nitrate Curves (B07-B09).....................................................................33Figure 24: E Field Nitrate Curves (E02-E04)...........................................................................34Figure 25: E Field Nitrate Curves (E05-E07)...........................................................................34Figure 26: E Field Nitrate Curves (E09 & E10).......................................................................35Figure 27: North Solitary Island Wake Zone............................................................................37

6

IntroductionNitrogen is a very important element. It makes up most of the atmosphere and is critical to

the production of proteins, amino acids and DNA. In the ocean it is often a limiting nutrient

for primary producers – the photosynthetic phytoplankton that form the foundation of the

oceanic food hierarchy (Kamykowski & Zentara 2005). Unfortunately, historically, nitrate has

been labour intensive to measure, with bottle samples and laboratory titration or colorimetry

the only way to accurately determine nitrate and nitrite concentrations in the ocean. The

need to freeze and thaw samples, or analyse immediately to prevent degradation is costly,

potentially inaccurate and resource intensive. A recently developed in-situ method for nitrate

measurement is making data collection significantly easier (Johnson & Coletti 2002). As a

continuous sensor, the ISUS unit enables simultaneous CTD and Nitrate measurement,

creating a contiguous data set while reducing the need for post processing and costly lab

analysis.

Present research has been focused on the use of the ISUS unit in the deep ocean, where

gradients are typically gentle, and concentrations relatively high. The challenge addressed in

this study is determining the usefulness of the ISUS output in near shore and surface waters,

where concentrations are at, close to, or below the quoted limit of detection of the device.

The upwelling favourable conditions of the SIMP study site should present an ideal scenario

for testing the accuracy of the ISUS near it's limits – these conditions should induce a nitrate

peak at depth, as the nutrient rich deep water intrudes along the continental shelf.

A team of eight researchers from UWA and UNSW conducted the study between the 24th and

30th of November, 2010. In all 24 of the targeted 30 stations were cast, collecting data for

conductivity, temperature, depth, fluorescence and ISUS nitrate, with water samples taken to

measure chlorophyll, nitrate, silicate, phosphate and ammonia. While the primary focus of

this study is to compare the nitrate outputs from ISUS and bottle samples, the other data is

useful in establishing the dynamics of the region to give a better understanding of the

complete system.

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This study will hopefully determine the practical limit of nitrate detection by the ISUS unit in

shallow coastal waters, at least under the conditions at the time of the study. If the practical

limit is sufficient, one day the standard CTD sensor may be improved to include ISUS

functionality. As the ISUS unit can also be calibrated for other species, this could greatly

enhance the spectrum of data available to oceanographers.

The importance of nitrate as a limiting reagent in primary productivity has long been

established (Dugdale 1967; Dugdale & Goering 1967). Modern models of nitrate uptake by

these primary producers incorporate cell acclimation to regional conditions. Such models are

robust in predicting the change in productivity of coastal systems to either pulse events -

limited change in productivity due to response times - or a steady state regime where

response to sustained nitrate increase occurs on the order of hours (Smith et al. 2009).

The SIMP study area has been identified as a region of diverse species assemblages (tropical,

subtropical and temperate) due to the convergence of East Australian Current and local

temperate waters (Marine Parks Authority 2008). This diversity makes the region ideal for

investigating the response to nitrate influx of different types of reef communities. This study

aims to identify a mush less labour intensive and significantly more cost effective method of

establishing nitrate distribution, variation, accumulation and transport from the deep ocean

into these near shore communities.

8

Literature Review

Nitrate in the Marine EnvironmentThere are many processes at work in the coastal ocean that make use of nitrogen. The

nitrogen cycle is possibly the most complex (and least understood) mechanism of interest to

biological oceanographers. Nitrogen exists in many oxidation states in the ocean, including

nitrate, nitrite, ammonia, nitrous oxide and molecular nitrogen. The interaction of the

nitrogen cycle with the carbon and oxygen cycles creates a further layer of system

complexity (Capone et al. 2008). It is doubtful that any model will ever be able to account for

the complexities of these interactions, especially once large scale forces like ocean currents,

seasonal variability, climate evolution (either natural or anthropogenic) and local scale forces

such as nutrient enriched river discharges, localised deep water upwelling, pollution plumes

and undersea volcanic activity are accounted for. All is not lost however, as the discerning

oceanographer can look closely at the important mechanisms for a particular site, and

hopefully draw some valuable conclusions based on established long term data sets, targeted

field work and logical critical thought.

At its simplest, there are three fundamental components of the nitrogen cycle in the marine

environment. First is fixation, the conversion of atmospheric or river deposited nitrogen into

the biologically available forms (such as nitrate, nitrite and ammonium) by photosynthetic

micro-organisms in the euphotic zone. The second component is that of organic matter,

closely related to carbon availability. This part of the nitrogen cycle involves the direct use of

nitrogen in primary production organisms and the transmission of nitrogen up the trophic

levels of the food chain into higher order organisms. Finally the return of decaying organic

matter to biologically available nitrogen in the aphotic zone is the process of denitrification

(Gruber & Galloway 2008; Chester 2000).

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This simple model has many other inputs and outputs, the importance of each being very

site specific. The surface of the open ocean will be unconcerned with river influxes, sediment

deposition and resuspension or benthic nitrification, and conversely near-shore nitrogen

cycles become much more complicated with factors such as industrial activity, coastal

currents, continental shelf upwelling and surface runoff becoming potentially significant.

As with any modelling endeavour, the best way to approach a complex system is to identify

the components that can be isolated from the interference of other variables. Different

components of the nitrogen cycle have already been explored. The dynamics of oxygen-

nitrogen cycle interactions during denitrification, rates of denitrification by specific species of

cyanobacteria and identifying genetic variability in nitrogen fixation mechanisms of bacteria

are all examples of narrow focus of particular components of the nitrogen cycle (Neubacher,

Parker & Trimmera 2011; Zehr 2011; Zehr & Kudela 2011).

For this study, the areas of focus are twofold – can we more efficiently and accurately

determine the concentrations of the nitrate species in the coastal ocean, and what can we

deduce about the mixing of nitrogen (as nitrate) to the euphotic zone from the data we

collect.

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Figure 1: Fundamentals of the Nitrogen Cycle

NitrificationBiological Use

Denitrification

Euphotic ZoneAphotic Zone

Mixing

ISUS FunctionThe In-Situ Ultraviolet Spectrophotometer (ISUS) Device was developed over 2000-2001 by

Kenneth Johnson and Luke Coletti at the Monterey Bay Aquarium Research Institute in

California. The device was designed to measure nitrate, bisulfide and bromide in deep (up

to 2000m) water at high temporal and spatial resolutions with sufficient accuracy to be useful

for research endeavours (Johnson & Coletti 2002). The major components of the device are

identified in Figure 2. Light from the UV source travels along either the retroreflective probe,

exposed to the seawater, and the reference or 'dark' probe, before entering the spectrometer.

The dark probe is used to periodically determine a reference spectra with no seawater

interaction for internal calculation of concentrations, and is used to account for any

instabilities in either UV lamp operation or spectrometer function, as every dark sample is

effectively a device recalibration. Processing and data storage occurs in the control unit. Data

can also be output to an external storage device such as a CTD sensor or computer. The

device is powered either externally or by a series of lithium batteries.

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Figure 2: ISUS Design featuring: A-Spectrometer, B-UV Light Source, C-UV Fiber for reference detector, D- High pressure endcap, E- Retroreflective Probe, F- Reference channel board, G-Control Unit, H-UV Fiber to Spectrometer, I-Battery Pack (Johnson & Coletti 2002).

The device takes advantage of the differences in ultraviolet absorption spectra of common

aquatic species, identifying the 217nm peak associated with nitrate, and using an internal

calculation to eliminate background interference, and absorbency spectra from other

inorganic species. The relative concentration value is output as one voltage, and the 'dark'

reference voltage as a second signal. The 'dark' voltage is an orphan from the periodic

internal recalibration function, but may be useful when troubleshooting to ensure the UV

lamp is functioning continuously and correctly. Post processing can be used to calibrate the

voltages into nitrate concentrations (Johnson & Coletti 2002).

ISUS LimitationsThe ISUS unit has some important limitations, especially in the low concentration, near

surface zone. High accuracy requires a longer scan (~30 samples in 30 seconds per station) to

achieve a 95% confidence interval of ±0.2µM. As this study employs a continuous casting

profile methodology, accuracy is reduced to ±1µM, with a detection limit of 1.5µM (Johnson

& Coletti 2002).

The Study Site

Solitary Islands Marine ParkThe Solitary Islands Marine Park (SIMP) is located on the eastern coast of Australia,

approximately half way between the major population centres of Sydney and Brisbane. The

71 000 hectare park is characterised by a group of five islands and a diverse array of reef

communities at varying depths (Marine Parks Authority 2008).

The reef systems are composed of a mix of tropical, subtropical and temperate assemblages,

a function of diverse temperature and cross shelf current dynamics (Zann 2000).

Given the apparent paradox of coral reef communities, having high productivity and species

diversity with typically nutrient poor surroundings, identifying the source of a critical

nutrient like nitrate could greatly help in identifying sensitivity of coastal reef communities

to changes in wider ocean dynamics (Hoegh-Guldberg 1999).

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East Australian CurrentThe Eastern Australian Current is the dominant oceanographic feature in the region of the

marine park. The study area is prone to topographically induced upwelling. The acceleration

of the EAC in the region of the marine park forms a region of high stress at the bottom

boundary layer, creating upwelling favourable conditions (Oke & Middleton 2000). It should

be noted that during the study period high winds and swell were observed. It is possible that

turbulent mixing during the field work may have removed any observable stratification and

upwelling nutrient signal. Coastal upwelling of nitrate is typically accompanied by high

levels of chlorophyll, and as such the chlorophyll data collected during the survey may be a

useful signal for validation of nitrate data (Capone et al. 2008).

The EAC is seasonally variable, with peak flow occurring during the late summer months

(Ridgway & Hill 2009). As such a weaker than maximum current induced upwelling signal

may be observed during the study period.

Climate change and oceanic nitrateWhile there is no long term data set for nitrate availability within the marine park, research

based on sea surface temperature correlated availability of nitrate and the subsequent

response to change in climate and temperature has shown a significant decrease in SIMP

spring (October) nitrate availability (Kamykowski & Zentara 2005). The decrease in surface

nitrate availability in temperate waters is directly related to an increase in local sea surface

temperatures.

El-nino and the Southern Oscillation IndexThe EAC has been shown to be forced on a decadal scale by the action of baroclinic Rossby

waves, with a three year dynamic lag evident between Southern Oscillation peaks and EAC

forcing peaks (Holbrook et al. 2011). This large time scale forcing enables the prediction of

periods of higher EAC forcing and benthic stress, potentially resulting in a stronger

upwelling signal in the region of the marine park.

13

Outcomes from accurate nitrate reportingMany fields of study benefit from accurate reporting of oceanic nitrate and nitrogen

concentrations. Potential applications include the management of nitrate budgets for coastal

water quality, investigating competitive dynamics of species in nitrate rich or deficient

environments and changes to oceanic geochemistry in the wake of events such as

phytoplankton blooms (Whitehouse et al. 1996; DiMilla et al. 2011; Cermeno et al. 2011).

14

Methods

Field Study Methodology

Study StationsSite selection for sampling casts had to satisfy a number of criterion. First the sites must all be

sufficiently proximal to harbour to enable sampling many stations and returning daily.

Secondly the sites needed to provide an accurate transect of the reef for identification of cross

shelf variability in species concentrations.

Transects were selected along lines of latitude to enable ease of data processing. The A

transect consists of eight stations across the shelf to the north of North Solitary Island. The B

transect is a series of nine stations south of the island, and the group of E stations was

selected to investigate both the very near shore dynamics and the effect (if any) of the island

wake. Stations along the A and B transects are 3-4 kilometres apart along each transect, and

18km apart longitudinally. Maximum sampling depth was estimated as 200m based on

isobath data (Figure 4), in-situ depth at station B09 proved to be significantly less (125m) on

15

Figure 3: Study Site Location and Sample Stations

30km

the shoulder of the continental shelf.

The sampling regime is summarised in Table 1 below.

16

Figure 4: Sample Stations and regional bathymetry (Rossi 2010)

Rosette DeploymentThe apparatus used to collect both data and water samples was a combination of a six bottle

Seabird niskin rosette with an attached Seabird CTD measuring conductivity, temperature,

pressure (depth) and fluorescence. The ISUS unit was attached to the rosette and interfaced

with the CTD to enable data convergence into a single file.

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Table 1: Study Station Summary

CTD Cast Station Date Time Depth Latitude Longitude1.0 A02 25/11/2010 07:20:00 35.0 -29.834 153.3502.0 A03 25/11/2010 08:01:00 40.0 -29.834 153.3903.0 A04 25/11/2010 08:37:00 45.0 -29.834 153.433

13.0 A05 28/11/2010 07:55:00 70.0 -29.832 153.47512.0 A06 28/11/2010 07:30:00 76.0 -29.832 153.51611.0 A07 28/11/2010 07:00:00 85.0 -29.832 153.55810.0 A08 28/11/2010 06:35:00 95.0 -29.833 153.60016.0 B01 29/11/2010 06:40:00 20.0 -29.994 153.25117.0 B02 29/11/2010 07:10:00 27.0 -29.995 153.27418.0 B03 29/11/2010 07:40:00 39.0 -29.994 153.30419.0 B04 29/11/2010 08:15:00 51.0 -29.995 153.34120.0 B05 29/11/2010 08:50:00 56.0 -29.994 153.38221.0 B06 29/11/2010 09:30:00 77.0 -29.995 153.42522.0 B07 29/11/2010 10:15:00 85.0 -29.994 153.46223.0 B08 29/11/2010 11:05:00 89.0 -29.995 153.50524.0 B09 29/11/2010 12:10:00 125.0 -29.994 153.5537.0 E02 26/11/2010 10:08:00 33.0 -29.904 153.322

14.0 E03 28/11/2010 09:35:00 40.0 -29.901 153.41615.0 E04 28/11/2010 11:05:00 65.0 -29.901 153.4666.0 E05 25/11/2010 13:26:00 20.0 -29.934 153.2855.0 E06 25/11/2010 13:03:00 35.0 -29.934 153.3244.0 E07 25/11/2010 12:36:00 40.0 -29.934 153.3659.0 E09 26/11/2010 11:05:00 29.0 -29.967 153.2828.0 E10 26/11/2010 10:40:00 37.0 -29.967 153.325

Once the boat was navigated onto the appropriate station, it was oriented to drift downwind

from the rosette deployment davit, to prevent the upcast from bringing the apparatus up

under the boat. A sonar depth sounding provided the water column height to be divided for

sampling. The deepest niskin bottle firing depth was set at least 5m above the ocean floor to

prevent bottoming out, and then intervals on the order of 20m across the column depth to

give a reasonable resolution on a single cast. Selected depths were then uploaded into the

niskin rosette and the system armed for downcast firing. Closing the niskin bottles on the

downcast serves to both limit the nautical drift off station and avoid collecting downcast

mixed water on the upcast.

Once in the water the apparatus was left barely submerged to equilibrate for one minute,

before being cast downwards at a rate of ~1m/s. Casts were paused at niskin firing depths to

ensure closure of both bottles. Bottle firing was monitored via cast line vibration, and when

maximum depth firing was confirmed, the rosette was reeled in. CTD and ISUS datasets

were downloaded from the CTD data bank daily and sample records (sample identification

numbers, locations, depths, anomoly notes) were transfered from paper into a digital

spreadsheet.

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Figure 5: Rosette showing: A-CTD with Fluorometer, B-Niskin Bottles, C-ISUS Sensor

A

B

C

Bottle Sample CollectionTwo niskin bottles were fired at each depth to collect a combined total of 8L of water, with

the exception of stations B08 and B09, where chlorophyl filtrate replicates were sacrificed for

a greater vertical water column resolution from a single cast. Surface water samples were

collected directly. The Niskin bottles were decanted into 8L carboys that had been triple

rinsed with station water between uses. Under inclement weather conditions, the carboys

were stowed until a safe haven (either in the lee of North Solitary Island, or back at the dock

in Wooli) would allow processing. 6L of each sample was vacuum filtered for chlorophyll-a

determination, with the remaining 2L avaialble for processing to be sent for nutrient analysis.

The water was used to triple rinse a syringe and 0.45 micron filter, before triple rinsing and

75% filling three 10mL sample tubes per station depth, which were labelled and frozen.

These samples were collated and packed with dry ice to be sent to CSIRO Floreat for

analysis. Tables 1-4 describe the sampling depths for each station.

Error SourcesOn Station drift during casts was typically on the order of 150m. Given this drift occurs

during both down and up casts, it is reasonable to assume downcast drift is typically less

than 100m laterally, which is approximately 3% of the distance between stations, small

enough to be negligible.

Another notable error source is the sampling of stations on different days, most notably

stations A2, A3 and A4 three days before A5 A6 and A7. Given the consistency of wind

forcing across the study period (Figure 6) and that changes in the large scale processes that

would induce a shift in the coastal dynamics happen on the order of seasons, years and

decades, this discontinuity is considered negligible (Ridgway & Hill 2009).

19

Rough seas prevented significant data and sample collection on the 26th of November. The

significance of wind forcing is discussed in more detail below. The surface mixing during a

high shear stress wind period is evident in the SST plots in the week before field work dates

shown in Figure 7 and Figure 8.

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Table 2: Sampling Regime for 25-Nov-2011

Station Date Time Zone Depth Sounding Sample DepthA2 25-Nov 7:20:00 EST 10A2 25-Nov 7:20:00 EST 20A2 25-Nov 7:20:00 EST 35A2 25-Nov 7:38:00 EST 1A3 25-Nov 8:01:00 EST 15A3 25-Nov 8:01:00 EST 30A3 25-Nov 8:01:00 EST 45A3 25-Nov 8:15:00 EST 1A4 25-Nov 8:37:00 EST 60A4 25-Nov 8:53:00 EST 19A4 25-Nov 8:53:00 EST 38A4 25-Nov 8:53:00 EST 54A4 25-Nov 8:57:00 EST 1E7 25-Nov 12:36:00 EST 1E7 25-Nov 12:32:00 EST 10E7 25-Nov 12:32:00 EST 20E7 25-Nov 12:32:00 EST 35E6 25-Nov 13:03:00 EST 0E6 25-Nov 13:00:00 EST 10E6 25-Nov 13:00:00 EST 20E6 25-Nov 13:00:00 EST 30E5 25-Nov 13:26:00 EST 2E5 25-Nov 13:26:00 EST 10E5 25-Nov 13:26:00 EST 19


Station Date Time Zone Depth Sounding Sample DepthE2 26-Nov 10:08:00 EST 33 1E2 26-Nov 10:08:00 EST 33 15E2 26-Nov 10:08:00 EST 33 28E10 26-Nov 10:39:00 EST 37 1E10 26-Nov 10:39:00 EST 37 15E10 26-Nov 10:39:00 EST 37 32E9 26-Nov 11:04:00 EST 29 2E9 26-Nov 11:04:00 EST 29 20

21


Station Date Time Zone Depth Sounding Sample DepthA8 28-Nov 6:36:00 EST 1A8 28-Nov 6:36:00 EST 30A8 28-Nov 6:43:00 EST 60A8 28-Nov 6:43:00 EST 80A7 28-Nov 7:00:00 EST 1A7 28-Nov 7:00:00 EST 30A7 28-Nov 7:00:00 EST 50A7 28-Nov 7:00:00 EST 75A6 28-Nov 7:23:00 EST 1A6 28-Nov 7:23:00 EST 20A6 28-Nov 7:35:00 EST 45A6 28-Nov 7:35:00 EST 68A5 28-Nov 7:53:50 EST 0A5 28-Nov 7:53:50 EST 20A5 28-Nov 7:53:50 EST 40A5 28-Nov 7:53:50 EST 62E03 28-Nov 9:36:30 EST 2E03 28-Nov 9:36:30 EST 15E03 28-Nov 9:36:30 EST 30E04 28-Nov 11:06:00 EST 1E04 28-Nov 11:06:00 EST 25E04 28-Nov 11:06:00 EST 50

22


Station Date Time Zone Depth Sounding Sample DepthB01 29-Nov 6:42:00 EST 20 2B01 29-Nov 6:42:00 EST 20 17B02 29-Nov 7:10:00 EST 27 2B02 29-Nov 7:10:00 EST 27 26B03 29-Nov 7:39:00 EST 39 2B03 29-Nov 7:39:00 EST 39 20B03 29-Nov 7:39:00 EST 39 35B04 29-Nov 8:12:00 EST 51 2B04 29-Nov 8:12:00 EST 51 25B04 29-Nov 8:12:00 EST 51 45B05 29-Nov 8:49:00 EST 56 2B05 29-Nov 8:49:00 EST 56 30B05 29-Nov 8:49:00 EST 56 50B06 29-Nov 9:33:00 EST 77 0B06 29-Nov 9:28:00 EST 77 25B06 29-Nov 9:30:00 EST 77 50B06 29-Nov 9:32:00 EST 77 70B07 29-Nov 10:17:00 EST 85 0B07 29-Nov 10:12:00 EST 85 25B07 29-Nov 10:14:00 EST 85 50B07 29-Nov 10:16:00 EST 85 78B08 29-Nov 11:05:00 EST 89 1B08 29-Nov 10:59:00 EST 89 20B08 29-Nov 11:00:00 EST 89 40B08 29-Nov 11:02:00 EST 89 60B08 29-Nov 11:04:00 EST 89 80B09 29-Nov 12:08:00 EST 125 1B09 29-Nov 12:08:00 EST 125 30B09 29-Nov 12:10:00 EST 125 60B09 29-Nov 12:12:00 EST 125 80B09 29-Nov 12:14:00 EST 125 110

Alternate data sources

Wind speed dataWind speed data was collated by Vincent Rossi of UNSW. The dataset shows maximum

wind intensities and stresses during study excursion times. The consistent direction (NNE)

of the prevailing winds may be a significant driver of Ekman transport, which will be

investigated in the discussion section of this paper.

Sea Surface TemperatureLarge scale sea surface temperature values, remotely sensed via satellite were graphed by

Helen Macdonald (2010). They clearly show localised surface mixing after the period of high

onshore wind intensity during the week leaing up to the field work, and a heterogeneous

distribution of surface water. The SST plots imply the prescence of a very well mixed surface

layer.

23

Figure 6: Wind Intensity and Stress over the study period. Boxed sections indicate sampling times (Rossi 2010).

CTD/Fluorometer DataWhile not specifically of interest in this study, the broader data set from the survey

incorporating conductivity, temperature, fluorescence, other nutrient (silicate, ammonia,

phosphate) and chlorophyll-a values for each station and depth may prove useful in

valdating the nitrate based analysis of hydrodynamics.

Laboratory AnalysisThe bottle samples were analysed by flow injection analysis colorimetry using a Lachat

QuikChem Colorimeter. The instrument uses a cadmium reduction column to convert the

nitrate into nitrite, and the subsequent nitrate (nitrate + nitrite) values are reported (Diamond

1999). Given that nitrate concentrations in the near surface ocean are typically below the

detection limit for colorimetry of 0.2 μM, it has been assumed that nitrite is proportionally

negligible and as such insignificant (Capone et al. 2008).

As there were three samples taken at each depth at each station, these could be averaged and

statistically assessed for accuracy. The data show a high correlation between samples (± 0.08

μM). Given the 95% confidence interval of ISUS output has been established at 1μM, the lab

data are sufficiently accurate for us to draw comparisons between the data sets. Complete lab

data can be found at Appendix B: LAB Data.

24

Figure 7: 3 day average SST on 22-Nov-2011 (Macdonald 2010)

Figure 8: 3 day average SST on 26-Nov-2011 (Macdonald 2010)

Three sample points have been identified as potential outliers. These data points have

disproportionately large standard deviations relative to the rest of the data. They are Station

B04 at 25m depth, B06 at the surface and B09 at 60m depth. Given the narrow sample space

(just three replicates) it is difficult to determine if these are errors, or just a high local

heterogeneity in nitrate distribution. In each case, two of the three values were very (<6%

difference) close to each other, implying that the third offending value is likely to be an

artifact of some error in experimental procedure. As such, these values were calibrated to the

mean of the two close values before any data analysis The adjusted values can be found in

Table 8.

25

Results

Isus Output CalibrationThe ISUS output voltages were fit against the bottle sample concentration values to convert

them into concentrations. The breakdown of spectrophotometer function near the limit of

detection is clearly evident in the distribution (Figure 9).

The regression equation:

C NO3=V ISUS ×17.5771−16.6632

Was applied to the raw ISUS dataset to convert voltages into concentrations. Sample output

below shows the calibrated ISUS concentration curve and lab sample curve for station A8

(Figure 10).

26

Figure 9: ISUS calibration curve, linear regression showing colour as depth (Rossi 2011)

ISUS Breakdown

ISUS FunctionThe reference voltages for each cast were very stable about the 3 volt standard implying

correct function of the ISUS unit in terms of operating power, lamp function and

spectrometer function.

Mixing DepthMixed Layer depth is typically calculated as the thermocline at which temperature changes

from surface value by 0.5 degrees (Levitus 1982). Figure 11 shows the different temperature

profiles at the stations along the A transect. Figure 12 shows the interpreted thermocline

relative to the total cast depth along the A transect. In the well mixed surface layer we would

expect to see uniform distribution of nitrate concentrations. As such, only samples and ISUS

data from below the thermocline should be used when evaluating the comparative accuracy,

sensitivity and reliability of the different nitrate measurement methodologies. Following are

mixing depth evaluations for each of the stations, sorted into A and B transects and the E

field.

27

Figure 10: Nitrate Concentrations at station A8

0 2 4 6 8 1 0 1 2- 9 0

- 8 0

- 7 0

- 6 0

- 5 0

- 4 0

- 3 0

- 2 0

- 1 0

0

C o n c e n t r a t i o n ( m i c r o M )

Dep

th (

m)

S t a t i o n A 8 I S U S a n d B o t t l e s a m p l e N i t r a t e C o n c e n t r a t i o n s

T h e r m o c l i n e

L a b d a t aI S U S o u t p u t

28

Figure 11: A Transect Temperature Profiles

17 18 19 20 21 22 23 24

-10

0

10

20

30

40

50

60

70

80

90

Te mpe ra ture (De gre e s C e lcius )

Dep

th (m

)

Te mpe ra ture vs De pth a long the A tra ns e ct

A8A7A6A5A4A3A2

Figure 12: A Transect Thermocline and Cast Depths

1 5 3 . 3 1 5 3 . 3 5 1 5 3 . 4 1 5 3 . 4 5 1 5 3 . 5 1 5 3 . 5 5 1 5 3 . 6 1 5 3 . 6 5- 1 2 0

- 1 0 0

- 8 0

- 6 0

- 4 0

- 2 0

0

L o n g i t u d e ( D e g r e e s E a s t )

Dep

th (

m)

A T r a n s e c t T h e r m o c l i n e S u r f a c e M i x i n g D e p t h a n d M a x i m u m C a s t D e p t h

M a x i m u m C a s t D e p t h


29

Figure 13: B Transect Temperature Profiles

1 2 1 4 1 6 1 8 2 0 2 2 2 4

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

T e m p e r a t u r e ( D e g r e e s C e l c i u s )

T e m p e r a t u r e v s D e p t h A l o n g B T r a n s e c t

Dep

th (

m)

B 0 1B 0 2

B 0 3

B 0 4

B 0 5B 0 6

B 0 7

B 0 8B 0 9

Figure 14: B Transect Thermocline and Cast Depths

1 5 3 . 2 5 1 5 3 . 3 1 5 3 . 3 5 1 5 3 . 4 1 5 3 . 4 5 1 5 3 . 5 1 5 3 . 5 5 1 5 3 . 6- 1 4 0

- 1 2 0

- 1 0 0

- 8 0

- 6 0

- 4 0

- 2 0

0

L o n g i t u d e ( D e g r e e s )

Dep

th (

m)

B T r a n s e c t T h e r m o c l i n e S u r f a c e M i x i n g D e p t h a n d M a x i m u m C a s t D e p t h


M a x i m u m C a s t D e p t h

The E field of sample stations is divided into a series of three cross shelf transects

(E02,E03,E04) (E05,E06,E07) and (E09, E10). The surface mixing boundaries (blue) and

maximum cast depths (red) are demarcated below (Figure 16, Figure 17, Figure 18).

30

Figure 15: E Field Temperature Profiles

Figure 16: Mixing depths in E field: E02, E03 and E04 Subset

1 5 3 . 3 1 5 3 . 3 2 1 5 3 . 3 4 1 5 3 . 3 6 1 5 3 . 3 8 1 5 3 . 4 1 5 3 . 4 2 1 5 3 . 4 4 1 5 3 . 4 6 1 5 3 . 4 8 1 5 3 . 5- 8 0

- 6 0

- 4 0

- 2 0

0S t a t i o n E 0 2 t o E 0 4 M i x i n g a n d C a s t D e p t h


Dep

th (

m)

ISUS output vs. Laboratory AnalysisComparative plots of ISUS output and Bottle (Lab Analysed) samples were generated for

each station. Blue data are ISUS Values, red data are Lab samples and the black line denotes

the surface mixed layer thermocline at the particular station.

31

Figure 18: Mixing depths in E field: E09 and E10 Subset

1 5 3 . 2 8 1 5 3 . 2 8 5 1 5 3 . 2 9 1 5 3 . 2 9 5 1 5 3 . 3 1 5 3 . 3 0 5 1 5 3 . 3 1 1 5 3 . 3 1 5 1 5 3 . 3 2 1 5 3 . 3 2 5- 4 0

- 3 0

- 2 0

- 1 0



Dep

th (

m)

Figure 19: A Transect Nitrate Curves (A02-A05)

0 5 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 2


Dep

th (

m)

0 5 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 3


Dep

th (

m)

0 5 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 4


Dep

th (

m)

0 5 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 5


Dep

th (

m)

Figure 17: Mixing depths in E field: E05, E06 and E07 Subset

1 5 3 . 2 8 1 5 3 . 2 9 1 5 3 . 3 1 5 3 . 3 1 1 5 3 . 3 2 1 5 3 . 3 3 1 5 3 . 3 4 1 5 3 . 3 5 1 5 3 . 3 6 1 5 3 . 3 7 1 5 3 . 3 8- 4 0

- 3 0

- 2 0

- 1 0



Dep

th (

m)

32

Figure 20: A Transect Nitrate Curves (A06-A08)

0 2 4 6 8 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 6


Dep

th (

m)

0 2 4 6 8 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 7


Dep

th (

m)

0 2 4 6 8 1 0

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

A 0 8


Dep

th (

m)

Figure 21: B Transect Nitrate Curves (B01-B03)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 1


Dep

th (

m)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 2


Dep

th (

m)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 3


Dep

th (

m)

33


0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 4


Dep

th (

m)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 5


Dep

th (

m)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 6


Dep

th (

m)


0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 7


Dep

th (

m)

0 5 1 0 1 5

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 8


Dep

th (

m)

0 5 1 0 1 5 2 0

0

2 0

4 0

6 0

8 0

1 0 0

1 2 0

B 0 9


Dep

th (

m)

34

Figure 25: E Field Nitrate Curves (E05-E07)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 5


Dep

th (

m)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 6


Dep

th (

m)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 7


Dep

th (

m)

Figure 24: E Field Nitrate Curves (E02-E04)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 2


Dep

th (

m)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 3


Dep

th (

m)

0 2 4 6 8 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 4


Dep

th (

m)

In all, 3682 data points were collected using ISUS instrumentation. A further 252 data points

(triplicate samples at 84 individual locations) make up the laboratory analysed bottle sample

data set.

35

Figure 26: E Field Nitrate Curves (E09 & E10)

0 1 2 3 4 5 6 7 8 9 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 0 9


Dep

th (

m)

0 1 2 3 4 5 6 7 8 9 1 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

4 0

E 1 0


Dep

th (

m)

Discussion

ISUS data compared to Laboratory DataComparison of the two nitrate measurement techniques yields some surprising and

interesting results. Most notably, the apparent accuracy of the ISUS device at low

concentration (≤10µM), with rapid sampling (cast at 1m/s) is much lower than the quoted

accuracy under a vertical profiling regime. Standard deviations of the ISUS profile data sets

are in the 1.5-2 µM range, over three times the expected spread of data points (Johnson &

Coletti 2002).

The higher than expected spread in ISUS nitrate data is likely a function of the fast decent

rate of the rosette breaking down the internal sample averaging functionality of the device.

The rate of decent and distribution of nitrate values is a relationship worthy of further

exploration.

Even though the ISUS output is insufficient to make any kind of evaluation of nitrate

budgets in the study region, the data is still useful in defining the broader scale dynamics of

nitrate across the continental shelf around North Solitary Island.

Interesting FeaturesBoth nitrate signals show deep nitrate maxima, supporting the presence of an upwelling

regime bringing deep, nutrient rich water into the coastal marine park. The nitrate signal is

evident along the complete shelf to the most westerly stations of the A and B transects,

supporting the high levels of productivity in the marine park through both the abundance

and long residence times of nitrate supply (Smith et al. 2009). The upwelling regime stability

is further supported by the distribution of sampling dates. Deep nitrate concentrations are of

comparable values along the A transect for the near shore (A2, A3, A4) stations, an the

remaining deeper stations that were sampled three days later.

In the absence of temperature or laboratory assessed data, the ISUS curves have proven very

accurate in predicting the depth of the surface mixed layer. The point at which post-

36

calibration nitrate concentration values become consistently non-negative is at or very close

to the thermocline at all A and B transect stations. The ISUS dataset may enable inferences

about the distribution of other parameters such as temperature and density.

Stations at equivalent isobaths along the A and B transects show similar nitrate concentration

profiles, supporting a largely homogeneous upwelling signal onto the shelf, with even

forcing across the shelf. The E field data provide clear evidence of a nitrate deficient region in

the wake of North Solitary Island (Figure 27). Stations E05, E06, E07 and E09 exhibit

particularly low nitrate concentrations across their entire depths, consistent with sheltering

from the prevailing upwelling and EAC transport signals .

There is a notable disagreement between the bottle sample results and ISUS output at station

E04, with lab results showing negligible nitrate at all three sampling depths, and the ISUS

signal reporting a deep maximum consistent with stations along the shelf at equivalent

isobaths (A05 and B05). As this station is beyond the zone of influence of the North Solitary

Island wake, this disparity likely describes an error in bottle sample collection.

37

Figure 27: North Solitary Island Wake Zone

Upwelling

EAC

Wake Zone

Upwelling MechanismsThree key mechanisms have been identified that may be responsible either individually or

collectively for the distribution of nitrate on the continental shelf at SIMP around North

Solitary Island. These mechanisms are: Wind driven Ekman Transport, high bottom

boundary layer stress associated with EAC acceleration, resulting in high bottom stress and

upwelling and topographically induced upwelling as a direct result of the EAC meeting

North Solitary Island or other ocean floor discontinuities.

Ekman TransportGiven the prevailing wind conditions from the north, in the southern hemisphere, surface

layer transport will be induced to the east (90 degrees to the left of prevailing winds). The

Ekman flow is a function of the balance between Coriolis forcing and wind induced drag on

the surface of the ocean (Mann & Lazier 2006). The flow offshore of the surface layer induces

the deep onshore flow to replace the surface water. Ekman flow does not fully develop in

shallower near surface waters (due to the length scales associated with Coriolis forcing), and

as such cycling in the island wake region is unlikely (Pond & Pickard 1983).

EAC accelerationA narrowing of the continental shelf causing acceleration of the EAC has been shown as a

mechanism for upwelling in the vicinity of SIMP (Oke & Middleton 2000). This process is

boundary stress induced and independent of Ekman transport. The acceleration of the

current causes a lag in geostrophic adjustment to equilibrium. The imbalance between

Coriolis forcing and pressure gradient forcing creates a region of high stress in the bottom

boundary layer of the shelf, driving an upwelling regime.

Topographical UpwellingA shallower maximum nitrate concentration may be evident along the north face of North

Solitary Island. As the EAC flows down from the north, the island face creates a region of

more intense mixing. Unfortunately no sampling stations were visited in this particularly

small region. As such it is difficult to say whether this process is occurring, or significant.

Given the large scale uniformity of the profile greater continental shelf in the region of the

marine park, any topographical effects are likely to be highly localised and of minimal

importance.

38

Rossby Radius of DeformationCalculation of the Rossby radius of deformation will give insight into the relative importance

of topographic, as the radius determines the length scale at which Coriolis forcing becomes

as important as buoyancy effects. Given the North Solitary Island length scale of 4km, the

Rossby radius can be calculated as:

LR≡ gD

f 0where g=gravity , D=depth , f 0=Lattitude specific Coriolis Parameter

for North Solitary Island:

LR≡9.8160

27.2921×10−5sin 29.9=166 km

The length of solitary island is extremely small relative to the Rossby radius (4km << 166km)

and as such any topographic effects on flow induced by North Solitary Island are negligible

compared to Coriolis driven forcing.

39

Conclusions and RecommendationsWhile the ISUS device has shown merit as a tool for identifying distributions of nitrate in the

coastal environment, output is simply too variable to use for any hard calculations of

nutrient budgets, at least in the region of SIMP. The survey data has provided an interesting

snapshot of the hydrodynamic regime of the park in spring during ideal Ekman transport

conditions.

The clear evidence of a sheltering wake behind North Solitary Island provides myriad

opportunities to target future research. Comparative study of reef productivities behind the

island and in regions exposed to the upwelling nitrate could prove very interesting.

The usefulness of data collected in this particular study could be greatly enhanced by some

auxiliary experiments. Testing the convergence of ISUS measurements under different

casting rates, long term monitoring of sample stations to determine seasonal, annual and

storm event variations in nitrate profiles are all valuable avenues for future research.

Monitoring the mid-shelf study stations during low wind forcing periods may provide

further insight into the significance of the two dominant upwelling forces in the region,

Ekman transport and geostrophic disequilibrium.

In the time since this study took place, Satlantic have released a smaller version of the ISUS

unit, able to be mounted in the science bay of a Slocum Ocean Glider. Deployment of a

Glider in this configuration in SIMP would enable a much greater horizontal resolution,

making identification of nitrate accumulation zones much more straightforward.

40

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42

Appendices

Appendix A: Sample ISUS DataISUS voltages were converted into concentrations by calibration against laboratory results.

Negative values are artifacts of sensor breakdown at very low concentrations near the

surface.

43

Station Longitude Depth ISUS Voltage ConcentrationA02 153.350 1.12 1.01 1.0317A02 153.350 1.37 1.01 1.0299A02 153.350 1.25 1.13 3.1972A02 153.350 1.26 1.13 3.1972A02 153.350 1.28 1.04 1.6680A02 153.350 1.14 1.01 1.1600A02 153.350 1.53 1.01 1.0985A02 153.350 1.85 1 0.9174A02 153.350 2.67 1 0.9157A02 153.350 3.4 1 0.9157A02 153.350 4.31 0.98 0.5008A02 153.350 5.26 0.91 -0.7454A02 153.350 6.24 0.91 -0.7454A02 153.350 6.85 0.91 -0.6593A02 153.350 7.78 0.91 -0.6329A02 153.350 8.73 0.95 -0.0317A02 153.350 9.12 0.98 0.5694A02 153.350 9.35 1.01 1.0053A02 153.350 10.29 1.08 2.3078A02 153.350 11.19 1.08 2.3113A02 153.350 12.21 1 0.9139A02 153.350 13.15 0.97 0.4481A02 153.350 14.07 1.08 2.3763A02 153.350 14.66 1.19 4.2992A02 153.350 15.32 1.17 3.9846A02 153.350 16.19 1.12 3.0548A02 153.350 16.84 1.12 3.0548A02 153.350 17.75 0.94 -0.1601A02 153.350 18.6 0.88 -1.2323A02 153.350 19.47 0.98 0.6133A02 153.350 20.29 1.09 2.4589A02 153.350 21.19 1.09 2.4589A02 153.350 22.19 1.09 2.4572A02 153.350 22.77 1.12 3.1005A02 153.350 23.22 1.23 5.0305A02 153.350 23.8 1.23 5.0287A02 153.350 24.64 1.22 4.7527A02 153.350 25.54 1.22 4.7527A02 153.350 26.43 1.23 4.9180

Appendix B: LAB DataLab results are sorted by station. Potential outlier values, identified by high proportional

standard deviations from the mean of the three samples are highlighted in red. Surface

samples have been recorded as 1m depth to prevent negative depths and function

breakdown under data post processing schemes.

44

Table 6: Lab Analysis Results: A Transect

CTD Cast Station Longitude NO3_NO2 ST DEV1 A02 153.3500 1 0.433 0.091 A02 153.3500 10 0.230 0.021 A02 153.3500 20 3.977 0.081 A02 153.3500 35 4.250 0.012 A03 153.3900 1 0.313 0.032 A03 153.3900 15 0.430 0.022 A03 153.3900 30 4.820 0.142 A03 153.3900 45 6.123 0.053 A04 153.4330 1 0.117 0.023 A04 153.4330 19 3.497 0.013 A04 153.4330 38 5.603 0.513 A04 153.4330 54 6.967 0.03

13 A05 153.4750 1 0.657 0.0113 A05 153.4750 20 1.060 0.0213 A05 153.4750 40 4.813 0.1413 A05 153.4750 62 7.583 0.1712 A06 153.5160 1 0.083 0.0312 A06 153.5160 20 0.200 012 A06 153.5160 45 4.913 0.0212 A06 153.5160 68 8.187 0.0811 A07 153.5580 1 1.717 0.0511 A07 153.5580 30 1.057 0.0111 A07 153.5580 50 4.940 0.0111 A07 153.5580 75 8.633 0.0410 A08 153.6000 1 0.500 0.0210 A08 153.6000 30 0.177 0.0310 A08 153.6000 60 6.340 0.1910 A08 153.6000 80 7.303 0.07

Depth (m)

45

Table 7: Lab Analysis Results, B Transect

CTD Cast Station Longitude NO3_NO2 ST DEV16 B01 153.2510 1 1.097 0.0316 B01 153.2510 17 5.373 0.0317 B02 153.2740 1 6.327 0.1317 B02 153.2740 26 8.290 0.2218 B03 153.3040 1 0.343 0.0418 B03 153.3040 20 3.730 0.0218 B03 153.3040 35 7.053 0.0119 B04 153.3410 1 0.203 0.0319 B04 153.3410 25 4.473 0.6719 B04 153.3410 45 8.040 0.0420 B05 153.3820 1 0.277 0.1420 B05 153.3820 30 7.007 0.0420 B05 153.3820 50 8.407 0.0321 B06 153.4250 1 1.760 0.7721 B06 153.4250 25 2.603 0.0721 B06 153.4250 50 7.897 0.0121 B06 153.4250 70 8.750 0.3822 B07 153.4620 1 1.840 0.0222 B07 153.4620 25 3.410 0.0222 B07 153.4620 50 7.230 0.0122 B07 153.4620 78 10.553 0.0823 B08 153.5050 1 6.190 0.0423 B08 153.5050 20 0.257 0.0223 B08 153.5050 40 3.680 0.0123 B08 153.5050 60 7.173 0.0423 B08 153.5050 80 8.797 0.0324 B09 153.5530 1 0.067 0.0624 B09 153.5530 30 2.900 0.0124 B09 153.5530 60 7.743 1.1824 B09 153.5530 80 9.870 0.5524 B09 153.5530 110 15.957 0.14

Depth (m)

Table 8: Adjusted 2-point average samples.

Station Depth NO3_NO2 ST DEVB04 25 4.1 0.25B06 1 1.32 0.01B09 60 7.06 0.06

46

Table 9: Lab Analysis Results, E Field

CTD Cast Station Longitude NO3_NO2 ST DEV7 E02 153.3220 1 0.530 07 E02 153.3220 15 0.313 0.017 E02 153.3220 28 4.603 0.15

14 E03 153.4660 1 0.060 014 E03 153.4660 15 1.340 0.0114 E03 153.4660 30 5.893 0.0515 E04 153.4160 1 0.0000 015 E04 153.4160 25 0.030 0.0315 E04 153.4160 50 0.020 0.02

6 E05 153.2850 1 0.390 0.016 E05 153.2850 10 0.920 0.016 E05 153.2850 19 1.913 0.125 E06 153.3240 1 0.197 0.015 E06 153.3240 10 0.213 0.015 E06 153.3240 20 0.240 0.015 E06 153.3240 30 0.643 0.14 E07 153.3650 1 0.593 0.044 E07 153.3650 10 0.980 0.034 E07 153.3650 20 0.650 0.014 E07 153.3650 35 4.090 0.239 E09 153.2820 1 0.020 09 E09 153.2820 20 0.603 0.028 E10 153.3250 1 0.020 08 E10 153.3250 15 0.357 0.018 E10 153.3250 32 3.663 0.01

Depth (m)

nitrate measurement and dynamics in the solitary islands ... · such as nutrient enriched river...

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