The influence of biophysical processes on plankton distribution in the Swan River Estuary. Gemma Bertrand Supervisors: Anas Ghadouni and Chari Pattiaratchi School of Environmental Systems Engineering, The University of Western Australia November 2010 .
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The influence of biophysical processes on plankton
distribution in the Swan River Estuary.
Gemma Bertrand
Supervisors: Anas Ghadouni and Chari Pattiaratchi
School of Environmental Systems Engineering,
The University of Western Australia
November 2010
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1 Executive Summary
The spatial and temporal distribution and productivity of plankton in aquatic environments
varies depending on the scales at which they are assessed and is affected by the tendency of
communities to occur in patches. To understand the mechanisms affecting plankton patchiness
and to model aquatic ecosystems, high resolution observations of plankton need to be
combined with physical and chemical parameters at a range of scales (Brentnall et al. 2003).
The development of the Laser Optical Plankton Counter (LOPC) by ODIM Brooke Ocean in
recent years, has allowed high-resolution quantification of zooplankton community size
structure and biomass.
The aims of this study are:
1) To assess the suitability of the LOPC for use in estuarine and shallow water conditions
given that it was designed for use in the deep ocean;
2) To quantify vertical changes in plankton community size structure over a period of 24
hours at one location in the Swan River Estuary; and
3) To quantify horizontal changes in plankton community size structure between the lower
and upper Swan River Estuary.
There were several practical components of this project including pre-field work construction of
an instrument housing frame, field sampling, laboratory comparison of sampling techniques
and data analysis methodologies. Two separate field trips were conducted in the Swan River
Estuary to obtain the required high-resolution data set of biological, chemical and physical
properties by taking vertical profiles in the estuarine water using a FluoroProbe, LOPC, CTD,
PAR sensor and integrated plankton tows.
The first field trip assessed vertical profile differences between the lower and middle estuary
and the second field trip was conducted at one station over a 24-hour period, sampling every
half hour where possible. To assess the suitability of the LOPC to estuarine conditions vertical
plankton tows were compared to microscopic identification of zooplankton species and then
run through the LOPC in lab circulator mode.
From the results gained, it was shown that there were vertical gradations in both
phytoplankton and zooplankton communities both during the spatial sampling along the
gradients of the estuary as well as over a period of 24 hours. The vertical profiles during the 24
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hour sampling period demonstrated that the proportion of macrozooplankton was greater at
the same depths as the deep chlorophyll maximum. This coincides with the location of the
density gradient between the less saline surface water and denser ocean water at the bottom.
Results from the spatial sampling showed variations between the lower and middle estuary,
with higher plankton abundance in the upper estuary at locations with brackish water at the
surface. The proportion of macrozooplankton was also higher at these stations in comparison
to the lower estuary.
The LOPC provided good quality information on community size structure and the vertical
variations with depth. The LOPC results could be further enhanced by coupling the device with
a depth sensor for vertical casts.
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2 Acknowledgements
I want to thank those who have helped me in the preparation of this thesis.
Firstly to my supervisor Anas Ghadouani, for all your help in the lab, the field and your
support and guidance along the way.
To Chari Pattiaratchi for providing advice on physics of the Swan River and helping to make
the tough calls to delay fieldwork due to bad weather.
To the Swan River Trust, who provided a Swan Canning Research Initiative Program grant,
which has allowed this study to occur and for access to field data.
To Conor Mines who has provided advice and help with the use of the LOPC. Conor’s help
has saved lots of time and frustration for which I am very grateful.
To Dani Barrington for skippering the Scorpion, even on the coldest of nights and providing
help with the use of the FluoroProbe and field work preparation.
To Dianne Krikke for helping in the lab; particularly with preparations for fieldwork and for
skippering the Scorpion.
To Dennis Stanley for helping get the flow circulator working and other bits and pieces in
the lab, especially the loan of your imperial tools.
To Elke Reichwaldt for saving the day during our first lot of field work bringing us the
valuable starter caps and cables that were left behind and helping drive the trailer around
in far from ideal conditions.
To Liah Coggins and Alexandra Young for helping me in the lab, the field and ongoing
support. To Liah thank you for editing, it is much appreciated. To Alex thank you for taking
some great photos in the field.
To my fellow SESE colleagues and friends for providing welcome distractions and support
when needed.
To all my fieldwork helpers, including Dani, Conor, Liah, Alex, Dianne, Charlene, Elke and
Anas. A big thanks for putting up with cold weather, long days and nights. I would not have
any results or data without you.
And finally to Mum and Dad for helping to make and design the frame for the equipment,
making muffins, supporting us in the field, editing my work and being there for me.
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Contents Page
1 Executive Summary ................................................................................................................ 3
2 Acknowledgements ............................................................................................................... 5
3 Abbreviations ....................................................................................................................... 10
4 Introduction ......................................................................................................................... 11
5 Literature Review ................................................................................................................. 14
5.1 Plankton Patchiness .................................................................................................... 14
5.2 River and Estuary Hydrodynamic Influences on Plankton Ecology .............................. 15
5.3 Plankton Size Distribution – Why size matters? .......................................................... 15
5.4 Plankton Sensing Technologies ................................................................................... 16
5.4.1 Laser Optical Plankton Counter ............................................................................ 17
5.4.2 FluoroProbe ......................................................................................................... 20
5.5 Field Site: The Swan River Estuary ............................................................................... 21
5.5.1 Hydrodynamics .................................................................................................... 22
5.5.2 Oxygen Availability ............................................................................................... 22
5.5.3 Light Climate ........................................................................................................ 23
5.5.4 Phytoplankton ..................................................................................................... 24
5.5.5 Zooplankton ......................................................................................................... 25
5.5.6 Current Monitoring .............................................................................................. 26
6 Aims and Objectives ............................................................................................................. 28
6.1 Aim 1 ........................................................................................................................... 28
6.2 Aim 2 ........................................................................................................................... 28
6.3 Aim 3 ........................................................................................................................... 28
7 Methodology ....................................................................................................................... 29
7.1 Frame Construction ..................................................................................................... 29
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7.2 Site Location ................................................................................................................. 30
7.3 Spatial Fieldwork .......................................................................................................... 31
7.4 Temporal Fieldwork ..................................................................................................... 31
7.5 Laboratory Circulator ................................................................................................... 32
7.6 Project Management ................................................................................................... 33
7.7 Data Analysis ................................................................................................................ 34
7.7.1 LOPC ..................................................................................................................... 34
7.7.2 CTD ....................................................................................................................... 36
7.7.3 Irradiance ............................................................................................................. 36
7.7.4 FluoroProbe .......................................................................................................... 37
8 Results ................................................................................................................................. 38
8.1 Microscopic Observations ............................................................................................ 38
8.2 FluoroProbe Calibration ............................................................................................... 39
8.3 Spatial Fieldwork .......................................................................................................... 39
8.3.1 Physical Environment ........................................................................................... 39
8.3.2 Light Climate ......................................................................................................... 42
8.3.3 Phytoplankton ...................................................................................................... 43
8.3.4 Zooplankton ......................................................................................................... 44
8.4 Temporal Fieldwork ..................................................................................................... 48
8.4.1 Physical Environment ........................................................................................... 48
8.4.2 Phytoplankton ...................................................................................................... 50
8.4.3 Light Climate ......................................................................................................... 52
8.4.4 Zooplankton ......................................................................................................... 53
9 Discussion ............................................................................................................................ 57
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9.1 Suitability of LOPC in Estuary Conditions ..................................................................... 57
9.2 Spatial Sampling .......................................................................................................... 57
9.2.1 Physical and Chemical Environment .................................................................... 57
9.2.2 Phytoplankton ..................................................................................................... 58
9.2.3 Zooplankton Abundance ...................................................................................... 58
9.2.4 Zooplankton Biomass ........................................................................................... 59
9.3 Temporal Sampling ...................................................................................................... 59
9.3.1 Physical and Chemical Environment .................................................................... 59
9.3.2 Zooplankton Abundance ...................................................................................... 59
9.3.3 Zooplankton Biomass ........................................................................................... 60
9.3.4 Phytoplankton ..................................................................................................... 60
9.3.5 Vertical Migration ................................................................................................ 61
9.4 General Discussion ...................................................................................................... 61
10 Conclusion ........................................................................................................................... 62
10.1 Future Work and Recommendations ........................................................................... 62
11 References ........................................................................................................................... 64
12 Appendices .......................................................................................................................... 69
12.1 Appendix 1 – Field Work Plan Including JSEA .............................................................. 69
12.2 Appendix 2 – Swan River Trust - Physical-Chemical Profiles ........................................ 71
12.3 Appendix 3 – LOPC results from spatial fieldwork ....................................................... 73
12.4 Appendix 4 – LOPC results from temporal fieldwork ................................................... 83
12.5 Appendix 5 – Dominant Phytoplankton Species .......................................................... 87
12.6 Appendix 6 – Dominant Zooplankton Species ............................................................. 88
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Table of Figures
Figure 5-1 Variation in plankton concentration at large scales from Abraham (1998). ............... 14
Figure 5-2 A Standard Tunnel Laser Optical Plankton Counter. ................................................... 18
Figure 5-3 Schematic diagram of the laser, mirror and processing system used in the LOPC. ..... 18
Figure 5-4 The Data Logger used for storing data during LOPC deployment. .............................. 19
Figure 5-5 The excitation spectra of different plankton groups (BBE Moldaenke 2007). ............ 21
Figure 5-6 Winter profile during year of low rainfall from SRT. ................................................... 23
Figure 5-7 Dominant taxonomic groups from A) 1980-81 and B)1994-5 from (Twomey & John
2001). .......................................................................................................................................... 25
Figure 5-8 SRT monitoring stations location and estuary division. .............................................. 27
Figure 7-1 The instrument frame with the data logger, FluoroProbe and LOPC attached from left
to right. ....................................................................................................................................... 29
Figure 7-2 Sampling locations for both temporal and spatial fieldwork. ..................................... 30
Figure 7-3 Laboratory Circulator setup to analyse plankton samples with the LOPC. ................. 33
Figure 8-1 CTD vertical profiles from Station 1 to 11 during spatial sampling. ............................ 41
Figure 8-2 Phytoplankton spectral group concentrations at different stations. .......................... 43
Figure 8-3 Zooplankton size distribution profiles from the LOPC during the spatial sampling. ... 44
Figure 8-4 Tidal elevation during 24 hour sampling period. ........................................................ 48
Figure 8-5 Salinity profile from temporal sampling. .................................................................... 49
Figure 8-6 Dissolved oxygen variations during the temporal sampling. ...................................... 50
Figure 8-7 Temperature variations during the temporal sampling. ............................................. 51
Figure 8-8 Phytoplankton spectral group concentration profiles during the 24 hour sampling. . 53
Figure 8-9 Zooplankton size distribution profiles from the LOPC during the 24 hour sampling. . 54
Figure 8-10 Integrated zooplankton size structure. The x-axis shows ESD in μm. ....................... 55
Figure 8-11 Biomass from the same cast as Figure 8-10 ............................................................. 55
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3 Abbreviations
BOD Biological oxygen demand
CDOM Chromophoric dissolved organic matter
CTD Conductivity, temperature and depth
ESD Equivalent spherical diameter
DOW Department of Water
DVM Diel vertical migration
Kd Attenuation coefficient
LOPC Laser optical plankton counter
MEP Multi element plankter
NBSS Normalised biomass size spectra
OPC Optical plankton counter
PAR Photosynthetically active radiation
RCC River continuum concept
SEP Single element plankter
SPM Suspended particulate matter
SRE Swan River Estuary
SRT Swan River Trust
TVM Tidal vertical migration
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Introduction
The Swan River Estuary
The health of the Swan River Estuary (SRE) is very important to the community living around it
and using it for recreational purposes such as fishing, sailing and rowing. The decline in water
quality has been recognised as having the potential to cause problems to the commercial and
recreational values of the upper estuary (Twomey & John 2001). Estuaries also provide
important environmental services such as habitat for estuarine organisms, visual aesthetics and
essential ecosystem processes, including nutrient cycling and organic matter decomposition. In
order to maintain these values, and prevent the quality of the SRE from degrading further we
need to manage the water quality.
SRE Water Quality
Water quality management requires understanding of the physical processes that influence
plankton ecology, such as circulation and hydrodynamics, nutrient supply and oxygen
availability. It is therefore important to the local communities that an understanding of physical
processes influencing ecology is developed. The SRE is undergoing a period of significant
pressure as a result of climatic changes leading to reductions in rainfall, high nutrient loads,
and increased use and demands from a growing population (Thompson 1998). Algal blooms
have been a cause for concern of the health in the SRE since the mid 1990’s as they indicate the
health status of the SRE (Stephens & Imberger 1996). Such stress on the Swan River has been
reflected by the occurrence of plankton blooms, fish kills (Hamilton 2000) and the death of
dolphins.
Historical Water Quality Changes
The hydrology and nutrient loading in the SRE have changed significantly since European
settlement as a result of land clearing, agriculture developments, the establishment of weirs
and reservoirs (Chan et al. 2002; Thompson & Hosja 1996) and the opening of the river mouth
at Fremantle as directed by CY O’Connor (Hodgkin 1998). These changes to the system are likely
to have caused shifts in the aquatic organism assemblage and have directly impacted on the
health of the estuary today.
Water Quality Management
Water quality management of the SRE has been hindered by a lack of knowledge in a number of
important areas, including, the microbial system dynamics of bacteria and zooplankton . To
improve water quality management, it is also desirable to be able to model ecosystem
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dynamics through understanding and quantification of ecosystem functions. One important
aspect of modelling is to understand the processes that affect the distribution and abundance
of plankton in the environment, including the influences that their patchiness can have on
productivity and biomass.
Plankton Ecology
The distribution and abundance of plankton in the environment is dependent on physical,
chemical and biological factors. Important physical factors include salinity and temperature, as
well as movements of water masses or circulation involving mixing due to wind and tidal
movements, or stratification effects. The availability of nutrients is also important and uptake
depends on both concentration and plankton size. The irradiance of photosynthetically active
radiation (PAR) is particularly important for photoautotrophs and dissolved oxygen levels are
important for respiration of heterotrophic plankton in particular. Biological influences include
grazing pressure by zooplankton and small prey and properties of the plankton themselves such
as density, size and motility.
Plankton Sensing Technology
Traditional assessment of plankton community health has been heavily based on
phytoplankton, particularly by measurement of chlorophyll concentration. However, to assess
changes to an aquatic system, a more informative approach is to assess the food web at more
than one trophic level (Yurista, Kelly & Miller 2005). Particle counters, specifically those that can
analyse the size distribution of zooplankton over a large range of sizes such as the LOPC, can be
used to determine the biomass of different size groups, therefore providing information on
energy transfer between trophic levels. Coupling these technologies with techniques such as
fluorometry, allowing in-situ assessment of chlorophyll from phytoplankton as well as spectral
group determination with high resolution (Beutler et al. 2002) improving our understanding of
the ecosystem dynamics.
Study Aims and Approach
This study aims to develop a better understanding of zooplankton dynamics in the SRE.
Understanding the processes that affect zooplankton populations in the SRE requires an
approach that assesses the physical and chemical environment as well as the phytoplankton on
which they graze.
This thesis presents the importance of assessing aquatic systems at more than one trophic level
alongside collection of physio-chemical parameters. It then discusses current technologies that
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can be used to asses plankton communities with particular detail on the application and
function of the LOPC. The end of the literature review focuses on the field site of the SRE paying
attention to hydrodynamics, oxygen levels and plankton.
The main aims and objectives of this project will be followed by the methodologies used to
obtain and analyse the data to answer the projects questions. Results and discussion will cover
both fieldwork and laboratory work and will draw conclusions on the main findings. Some
recommendations for future sampling with the LOPC in the SRE will be made, along with
possible ways of improving the quality of the data collected.
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4 Literature Review
4.1 Plankton Patchiness
The heterogeneous distribution of plankton in the environment, termed plankton patchiness, is
an important consideration in understanding the structure and function of aquatic ecosystems
(Pinel-Alloul 1995; Pinel-Alloul & Ghadouani 2007), biogeochemical cycling, fisheries and the
response to changes in climate (Daly & Smith 1993). Patterns of plankton patchiness across
spatial and temporal scales can be caused by forcing at different scales (Levin 1992) and
according to the ‘multiple driving forces hypothesis’ is caused by the combination and
interactions of biotic and abiotic processes (Pinel-Alloul 1995). Physical effects on plankton
distribution tend to be most important on larger scales with biological effects being more
important on shorter scales (Pinel-Alloul & Ghadouani 2007; Pinel-Alloul 1995).
When determining plankton productivity from large scale, ‘mean field’ dynamics can cause
estimates to differ greatly from actual productivity due to the patchiness of plankton (Brentnall
et al. 2003). This has important implications when modelling systems at large scales, greater
than a kilometre, as variability caused by small-scale processes can greatly affect productivity
estimates. It is therefore important to understand the dynamics affecting plankton at a range of
scales and be able to use high resolution observations coupled with physical and chemical
parameters (Brentnall et al. 2003).
Figure 4-1 Variation in plankton concentration at large scales from Abraham (1998).
Abraham (1998) described phytoplankton as having less variability at shorter length scales
whereas zooplankton were almost as variable on short scales as on long scales. Figure 4-1
shows this variability of phytoplankton and zooplankton at large scales. In this figure, the blue
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line represents the carrying capacity, the green line phytoplankton and the red line
zooplankton. Abraham (1998) postulated that patchiness may be generated by non-diffusion
advection, as diffusion processes are unable to create the fine scaled variability as diffusion
transfers variability from short to large spatial scales. Turbulent diffusion, however, transfers
variability from the large scale to the small scale and this turbulent advection is able to create
the fine scale structures seen in zooplankton distributions. Overall, Abraham found that the
lifetime of zooplankton is an important factor affecting their spatial distribution.
4.2 River and Estuary Hydrodynamic Influences on Plankton Ecology
The River Continuum Concept (RCC), developed by Vannote et al (1980), describes how the
function and structure of ecology changes with the physical gradients of a river as a result of
geomorphological processes. For instance, the concept describes the upstream to downstream
shifts in the proportions of heterotrophic to autotrophic organisms, with heterotrophic
processes being dominant in headwaters and closer to the river mouth. Vannote et al (1980)
discusses that over temporal scales such as seasons, a section of a river may shift energy
dependency from autotrophic organisms to detritus, but in summer months, autotrophy is
generally dominant. The RCC may not be as applicable to floodplain rivers, especially where
both autotrophic organic matter and organic matter derived from terrestrial systems are
extremely important for food webs (Thorp et al. 1994).
Hydrodynamic conditions such as the water flow rate and residence time are important to
planktonic development in river environments, particularly to zooplankton as they have longer
generation times (Basu & Pick 1996). Basu and Pick (1996) suggested that slower reproducing
zooplankton may be susceptible to advective loss. From their study of Canadian Rivers Basu and
Pick concluded that whilst phytoplankton biomass in rivers was related to nutrient availability,
zooplankton biomass was more strongly correlated to water residence time. This influenced the
species of zooplankton in rivers, resulting in systems being dominated by rotifers and small
crustaceans (Basu & Pick 1996).
4.3 Plankton Size Distribution – Why size matters?
Plankton size is an important property as size affects physiological processes and can therefore
have important implications for ecological processes (Ray et al. 2001). The biological production
of a system is also affected by size due to its influence on the metabolic rates of organisms
(Dickie, Kerr & Boudreau 1987). The density of biomass in an ecosystem is also dependent
upon the size of the organisms within the community structure (Ray et al. 2001; Dickie, Kerr &
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Boudreau 1987). Size distribution of a community can be used for comparison of an ecosystem
at different times and locations (Ray et al. 2001).
Yurista, Kelly and Miller (2005) suggested that zooplankton biomass is analogous to chlorophyll
as an indicator, and that biomass and the size structure of zooplankton assemblages are
therefore potentially important indicators (Yurista, Kelly & Miller 2005; Herman & Harvey 2006;
Zhou & Huntley 1997 ).
The slope of biomass size spectra has been used as a measure for comparing different aquatic
systems and it has been proven by Ahrens and Peters (1991, in Gaedke 1992) that the slope of
normalized spectra becomes less negative with increasing eutrophication (Gaedke 1992) . The
spectral shape or slope shows when the distribution of zooplankton differs from mean
conditions and can be used to indicate if a particular trophic group has changed in abundance
affecting the flow of energy in the ecosystem (Herman et al. unpublished).
4.4 Plankton Sensing Technologies
Methods to capture and or assess plankton communities have been available for hundreds of
years and methods of analysis have changed as technology has advanced. The invention of
fluorometric techniques, using light emitting diodes to quantifying fluorescence at particular
wavelengths and the use of coulter counters and laser optics have both made a significant
impact. A summary of some of the newer technologies sensing plankton, bacteria, other
properties of water and the spatial scales that they can be used at are summarised in Table 4-1.
Older methods such as plankton net tows and hauls are still important allowing microscopic
identification of species and evaluation of techniques. However, the use of plankton nets must
be used with caution as material can be expelled from the net, fragile particles can be
destroyed and zooplankton that are more mobile can avoid being captured (Checkley et al.
2008).
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Technology Variable
measured/sampled Spatial scale Depth
range (m)
Flow cytometry (FCM) Bacteria Macro to
small Subsurface
Airborne remote sensing (CAMS, AISA) Chl-a Large to small Surface
Ocean colour (SeaWiFS) Chl-a Macro to
global Surface
Fluorescence Chl-a Micro to
small 0–200
Spectrofluorescence Chl-a + other
pigments Micro to
small 0–100
Continuous Plankton Recorder (CPR) Plankton Small to meso 0–10
Continuous Plankton and Environmental Recorder (CPER)
Plankton, Chl-a, T, Cond., PAR, depth Small to meso 0–10
Longhurst–Hardy plankton recorder (LHPR) Plankton Small to meso 0–10
Fast Continuous Plankton Recorder (FCPR) Plankton Small to meso 0–10
Undulating oceanographic recorder (UOR)
Plankton, Chl-a, T, Cond., PAR, depth Small to meso 0–120
Bioacoustic techniques Zooplankton Large to meso 0–120
Video plankton recorder (VPR) Plankton Micro 0–130
Digital in-line holographic microscopy (DIHM)
Plankton and bacteria size and
tracks Micro 0–15
(prototype)
Optical plankton counter (OPC) Particle size M
Micro to meso 0–1000
Laser optical plankton counter (LOPC)
Particle size and shape
Micro to meso 0-660
Long-range autonomous underwater vehicle: seaglider
Chl-a, T, Cond., PAR, depth
Micro to macro 0-200
Table 4-1 New plankton sensing technologies adapted from (Pinel-Alloul & Ghadouani 2007)
4.4.1 Laser Optical Plankton Counter
The Laser Optical Plankton Counter (LOPC) is a development of the Optical Plankton Counter
developed by ODIM Brooke Ocean. The standard LOPC can be used up to depths of 660 m and
is shown in Figure 4-2 from ODIM Brooke Ocean (2008b). The LOPC detects particles from 100
to 35,000 μm in diameter and has a high scan rate of 35 μs allowing continuous high-resolution
sampling with minimal coincidence counts (Herman, Beanlands & Phillips 2004; ODIM Brooke
Ocean).
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Figure 4-2 A Standard Tunnel Laser Optical Plankton Counter.
The device works by emitting a linear beam which is 1 mm deep and 3.5 cm high across a 7 cm
wide tunnel to a reflecting prism and back to a group of 35 photo diode detectors, each 1 mm
in size (Herman, Beanlands & Phillips 2004). A schematic of the laser as adopted by Herman,
Beanlands and Phillips (2004) can be seen in Figure 4-3. Water flows through the main tunnel
and passes across the laser beam. As particles flow across the beam, they occlude the light
depending on their size and opacity. The area of light blocked in an individual photo diode is
used to determine the equivalent spherical diameter(ESD) of the particle in the beam (ODIM
Brooke Ocean 2008b).
Figure 4-3 Schematic diagram of the laser, mirror and processing system used in the LOPC.
Data from the LOPC can either be stored in the Data Logger, see Figure 4-4 from ODIM Brooke
Ocean (2008b), or connected to a deck unit and personal computer. Data is output from the
LOPC in two forms: 1) single element plankters (SEPs) are from particles which obscure only
one photo diode element each, and 2) multi element plankters (MEPs) which are greater than
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approximately 1500 μm which obscure multiple elements (Herman, Beanlands & Phillips 2004).
The data from SEP counts are sorted according to their ESD into 15 μm bins from 90 μm to 1920
μm (Herman, Beanlands & Phillips 2004). For data from MEP counts, the area obscured of each
element is transmitted individually and can then be used to create shape profiles (ODIM Brooke
Ocean 2008b; Herman, Beanlands & Phillips 2004). The area from each MEP count is then
summed and added to the size distribution of SEP counts. Shape profiles can be used for
taxonomic species identification of larger particles.
The purpose for upgrading the optical plankton counter (OPC), was to reduce the number of
coincidence events: i.e. when more than one particle in the beam at the same time, is counted
as one particle. The LOPC is able to deal with particle concentrations of up to 106 m-3 before the
detection limit is exceeded which is approximately 80 times better than the OPC. The LOPC is
also able to measure a larger size range of particles due to the increased number of detection
elements (Herman, Beanlands & Phillips 2004).
Figure 4-4 The Data Logger used for storing data during LOPC deployment.
The LOPC processing software developed by Alex Herman uses the ESD of particles to
determine the spherical volume which is then corrected using an ellipsoid shape ratio as shown
in Equation 4-1 and Equation 4-2 below (Herman & Harvey 2006; Herman 2009). The density of
the particles are assumed to be approximately that of water at 1 mg mm-3.
Equation 4-1 Simplified Particle Biomass Calculation
R is the ratio of length to width of zooplankton used as a correction factor in the calculation to
prevent overestimation of biomass as these particles generally tend not to be spherical
(Herman & Harvey 2006).
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Equation 4-2 Particle Biomass Calculation
Normalised Biomass Size Spectra (NBSS) is a method that can be used to compare between
biomass size spectra of zooplankton at different locations. The linear slope or the curve of the
quadratic function fitted to the size spectra is used to compare the relative amounts of biomass
contributed by different size fractions. There are other devices that can be used to create NBSS
from measurement of the size distribution of particles, such as the LOPC and Zooscan. Care
must be taken when comparing slopes determined with different devices as they each have
different methods and limitations when assessing plankton communities (Schultes & Lopes
2009). Similar limitations are found when comparing net samples under the microscope to the
LOPC, due to the inherently different sampling techniques (Schultes & Lopes 2009). As a result,
these methods, instead of being compared, are best used in combination.
4.4.2 FluoroProbe
The BBE-Moldaenke FluoroProbe is a device which uses fluorescence to measure the
concentration of different phytoplankton classes either in situ or in vivo (Beutler et al. 2002).
The different phytoplankton groups are differentiated by their fluorescence spectra which are
dependent on the proportion of different pigments as discussed by Beutler (2002).
The FluoroProbe uses five different wavelength light emitting diodes which are used in series to
determine concentration of pigments in the water and can then be used to determine relative
abundance of each ‘spectral group’. Using the FluoroProbe software enables four groups of
plankton to be differentiated based on their fluorescence spectrums, see Figure 4-5. These
include:
Group 1 - chlorophyta and euglenophyta;
Group 2 - phycocyanin rich cyanobacteria;
Group 3 - heterokontophyta and dinophyta; and
Group 4 - cryptophyta and phycoerythrin rich cyanobacteria (Twiss & MacLeod 2008;
Beutler et al. 2002; Beutler et al. 2003).
Group 3 contains two unique plankton groups that cannot be separated due to their relatively
similar fluorescence spectrum.
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Figure 4-5 The excitation spectra of different plankton groups (BBE Moldaenke 2007).
Yellow substances can influence the signal received by the FluoroProbe as they can also
fluoresce, influencing the amount of algae measured in a sample. Emitting light at 370 nm
allows quantification of the amount of yellow substances in the water (BBE Moldaenke 2007).
This however cannot be converted to a concentration as the range of yellow substance varies
greatly (BBE Moldaenke 2007).
4.5 Field Site: The Swan River Estuary
The Swan River Estuary (SRE), located on the Swan Coastal Plain in South Western Australia, is a
micro-tidal estuary that connects to the ocean at Fremantle. Located in a Mediterranean
climate, the catchment receives the majority of its rainfalls between May and September,
influencing the hydrodynamics of the river. This seasonally varying estuary is driven by multiple
forcing, including gravitational circulation and tidal and sub-tidal oscillations from low-pressure
systems and cyclones (O'Callaghan, Pattiaratchi & Hamilton 2007). The Swan-Canning estuary
experiences a partially mixed tidal signal that is predominantly diurnal with a mean amplitude
of 0.6 m experienced at Fremantle Harbour (O'Callaghan, Pattiaratchi & Hamilton 2007;
Stephens & Imberger 1996). Note that the use of SRE is a generic name for the Swan and
Canning River systems.
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During winter time, freshwater inflows mainly from the Avon River (Chan et al. 2002) induce
longitudinal gradients in salinity along the estuary resulting in gravitational circulation and
stratification (Stephens & Imberger 1996). Sub-tidal oscillations acting on the SRE cause
movement of the salt wedge, transporting anoxic waters upstream, and this has been
associated with fish kills in the upper reaches (O'Callaghan, Pattiaratchi & Hamilton 2007).
4.5.1 Hydrodynamics
The processes causing mixing and circulation in estuaries have important consequences for
hydrodynamic features and other properties of the water body such as light penetration,
particulate suspension and plankton communities. Micro-tidal estuaries which are classified
according to their low mean tidal range, have low levels of tidal mixing with dominant mixing
forces associated with wind, waves and freshwater inflow and demonstrate typical
hydrodynamics which often include salt wedge features (Kurup, Hamilton & Patterson 1998).
Hydrodynamic classification of the SRE varies seasonally due to the changes in relative
importance of freshwater inflows, sub-tidal oscillations, wind and tidal driven circulation. The
SRE can be divided into three main areas, the lower estuary from Fremantle to the Narrows
Bridge, the middle estuary being between the Narrows Bridge and Ron Courtney Island and the
upper estuary being upstream of Ron Courtney Island.
During summer, the lower SRE is filled with Indian Ocean water, and the main basins of the
lower estuary are well mixed. The middle estuary typically has brackish surface waters
underlain by denser saltier water and the upper estuary is brackish to fresh. In winter and
autumn the majority of freshwater flows into the SRE are from the Avon River catchment,
pushing the salt wedge downstream into the middle or lower estuary, depending on the
amount of rainfall and resulting river flow (Twomey & John 2001). During spring, as the river
flow from catchments reduces with rainfall, salt water intrudes up the river, which over time
and into summer can reach up to 60 km inland (Thompson 2001).
4.5.2 Oxygen Availability
Anoxic waters can cause regeneration of nutrients from the benthos, as changes in oxygen
concentration can modify the cycling of nitrogen and change the adsorption and desorption of
phosphorus (Hamilton et al. 2001). Circulation patterns in the SRE which control the movement
of oxygen depleted waters (O'Callaghan, Pattiaratchi & Hamilton 2007) may therefore have
important implications for the spatial distribution of plankton communities in the estuary due
to the influence on nutrient availability.
23
Inspection of vertical profiles of physical and chemical parameters show that near anoxic and
hypoxic waters are common in the middle and upper estuary. A winter profile before heavy
rains where the salt wedge in the middle estuary preventing mixing of oxygen throughout the
water column can be seen in Figure 5-6 below. These conditions are associated with brackish to
fresh surface water underlain by dense salty water. These low oxygen conditions can alter
biogeochemical cycling and increase supply of nutrients to plankton communities (O'Callaghan,
Pattiaratchi & Hamilton 2007; Hamilton et al. 2001). The hydrodynamic interplay with biological
oxygen demand (BOD) from the catchment can lead to anoxic conditions that are particularly
common in the upper estuary during winter or after large rainfall events. The effect of low
oxygen waters on the plankton of the SRE have not been assessed, although links have been
made between anoxic waters and fish kills in the Swan (Stephens & Imberger 1996).
Figure 4-6 Winter profile during year of low rainfall from SRT.
4.5.3 Light Climate
Suspended particulate matter (SPM), both biotic and abiotic, is a contributor to the attenuation
of light along with Gelbstoff or yellow substance and water molecules (Kirk 1977; Kostoglidis,
Pattiaratchi & Hamilton 2005). Kirk (1977) suggests that all these factors are important,
however, for the purpose of measuring light influence on plankton, measurement of the total
attenuation of photosynthetically active radiation (PAR) is considered satisfactory.
A study conducted by Kostoglidis Pattiaratchi & Hamilton (2005) indicates that the main
contributor to the attenuation of incident irradiance in the Swan River is due to absorbance by
chromophoric dissolved organic matter (CDOM). After continuous heavy rainfall periods by the
end of winter the colour of water in the lower SRE is normally a brown colour in contrast to
much clearer water at the end of summer.
24
4.5.4 Phytoplankton
Phytoplankton studies in the SRE have included Chan et al. (2002) and Chan &Hamilton’s (2001)
studies on hydrological influences, Twomey and John’s (2001) study on the influence of salt
wedge dynamics on phytoplankton assemblage, Rosser and Thompson (2001) and Thompson
and Hosja’s (1996) studies on nutrients and nutrient limitation, Thompson’s studies on spatial
and temporal variations (1998; 2001) and Karandonis’s study of light attenuation effects (2004).
Plankton blooms in the SRE are generally of non-toxic species including blooms of diatoms,
cryptophytes, chlorophytes and phytoflagellates (Thompson & Hosja 1996). Figure 5.7 below
shows how the phytoplankton assemblage of the major taxon changes throughout two
different years. Chlorophytes are more abundant in 1994-1995, with a decreased abundance of
cryptophytes compared to 1980-1981. Even though these two years are 14 years apart, it
cannot be assumed that this is the general trend due the large inter-annual variability in
phytoplankton assemblage (Twomey & John 2001).
Some species, however, have the ability to form harmful toxins that can persist in the
environment causing severe water management problems. One example in the SRE was the
Microcystis aeruginosa bloom in the summer of 2000, when high January rainfall provided ideal
conditions for a bloom (Orr, Jones & Douglas 2004). This bloom caused closure of large regions
of the SRE and had the potential to cause infection in animals and humans due to the presence
of microsystin, a persistent biological toxin, in the river (Orr, Jones & Douglas 2004; Jones & Orr
1994). Fish kills are also often associated with bloom events. Whilst this was an unusually rare
event, it highlights the sort of problems that managers of water resources, particularly estuaries
and coastal water bodies, have to deal with.
Phytoplankton distribution in the environment is closely linked to physical properties such as
water temperature and salinity (Abraham 1998). In the SRE the salt wedge and gradients of
salinity are important for phytoplankton distribution and the composition of species (Twomey
& John 2001). In the past it has been suggested that salinity is the ‘master factor’ controlling
the phytoplankton assemblage and succession in the SRE, however, Thompson (2001)suggests
that instead the focus should be on rainfall as it influences salinity, river flow and nutrient
concentrations.
25
Figure 4-7 Dominant taxonomic groups from A) 1980-81 and B)1994-5 from (Twomey & John 2001).
4.5.5 Zooplankton
Very little is known about the zooplankton of the SRE and this is acknowledged by the Swan
River Trust (SRT) (Swan River Trust 2008). Zooplankton have been the subject of fewer studies
than phytoplankton, with the most notable being Griffin and Rippingale’s (2001) study of top-
down controls of phytoplankton by zooplankton grazing. Shifts in zooplankton biomass were
found to vary as phytoplankton species composition shifted, with decreasing biomass occurring
as zooplankton shifted from copepod assemblages to rotifers (Brachionus sp.) (Griffin &
Rippingale 2001). However, this may have been caused by a shift in phytoplankton species over
the same time because of changes in the physical environment.
26
In 1943, Thomson (1946) collected crustaceans amongst algae in Freshwater Bay of the SRE.
Crustacea ranged from marine Mesochra, estuarine Carophium to freshwater Gladioferens
(Thomson 1946). The amphipod Corophium minor was found from March to early July, Munna
brevicornis and Gladioferens imparipes were found from July to December, the isopod
Cruranthura simplicia was found from June to September, and Mesochra parva of the order
Hapicticoida was found from October to November (Thomson 1946). Thomson (1946)
concluded that in summer the fauna were generally marine and estuarine forms and in winter
were estuarine and freshwater.
It has been shown that zooplankton of the SRE are unable to survive in low dissolved oxygen
conditions (Griffin & Rippingale 2001). This is supported by other studies of estuaries and
continental shelves that have found the abundance of nauplii and copepods decreased or were
not present in waters with oxygen concentrations less than 1 mgL-1 (Roman et al. 1993).
One important zooplankton dynamic that affects the vertical distribution is diel vertical
migration (DVM) (Lalli & Parsons 1997). DVM can be either nocturnal migration, twilight
migration or reverse migration. The reasons for such migrations are not satisfactorily known,
however, the implications that such migrations can have on phytoplankton interactions is
important (Lalli & Parsons 1997). Tidal vertical Migration (TVM) is another mechanism used by
some zooplankton species in parts of estuaries influenced by tidal movements to maintain their
position to prevent being exported out of the system (Ueda, Kuwatani & Suzuki 2010). To
maintain their position, during ebb tides zooplankton tend to distribute in the lower water
column and in flood tides tend to distribute in the upper water column (Ueda, Kuwatani &
Suzuki 2010).
4.5.6 Current Monitoring
Under the Swan and Canning Rivers Management Act 2006, the SRT is required to prepare a
River Protection Strategy (Swan River Trust 2009). Action Area 5 of this report is dedicated to
monitoring the health of the river and reporting this information to the community. The current
monitoring of the SRE is managed by the SRT and the DOW which, involves sampling both the
Swan and Canning Estuaries on a weekly basis. Sampling includes collection of physical,
chemical and biological samples and measurements. The focus of the SRT in the analysis of
grab samples has been phytoplankton with no quantification or identification of zooplankton
species (observation of complete data sets from sampling conducted by DOW and SRT).
27
Very little is also known about the vertical structure of plankton communities in the SRE, with
current sampling techniques involving samples that are grabbed either from the surface or at
depths up to 6 m, or integrate the water column up to a maximum depth of 6 m.
Figure 4-8 SRT monitoring stations location and estuary division.
To maintain some consistency with the sampling conducted by the SRT and the fieldwork in this
study, the lower estuary refers to sites sampled between Blackwall Reach and the Narrows
Bridge, the middle estuary refers to sites sampled above the Narrows Bridge, as shown in Figure
4-8 5-8. Only one station above Ron Courtney Island was sampled and thus this will be included
in the meaning middle estuary.
28
5 Aims and Objectives
To gain a better understanding of the processes affecting zooplankton in the SRE requires
quantification of the physical, chemical and biological environment. Phytoplankton assemblage
and concentration can control zooplankton as well as zooplankton influencing phytoplankton
through grazing, therefore assessing both populations is important.
5.1 Aim 1
Assess the suitability of using the LOPC in estuarine conditions. The LOPC was designed to be
used in the ocean and large lakes. To ensure that the LOPC is suited to use in the SRE a series of
LOPC field results were compared to integrated vertical plankton tows. These samples where
then used to identify the presence of zooplankton species and sediment under the microscope
and then run through the flow circulator setup of the LOPC.
5.2 Aim 2
To quantify vertical changes in plankton community size structure between the lower and
middle SRE. Planktonic assemblage is influenced by physical, chemical and biological forces that
vary between locations in the estuary. Gradients in physical-chemical forcing along the estuary
are therefore expected to influence the spatial distribution of plankton.
5.3 Aim 3
To quantify vertical changes in plankton community size structure over a period of 24 hours.
The ecology of plankton is influenced by physical, biological and circadian cycle effects that can
alter the vertical distribution of plankton. Sampling every half hour over a period of 24 hours
allowed temporal changes in the vertical distribution of plankton to be evaluated. The purpose
of this was to determine how temporal influences, such as diel vertical migration of
zooplankton and changes in tidal currents moving water masses with different salinity and
oxygen, affect plankton patchiness, and therefore plankton populations.
29
6 Methodology
There were a number of practical components of this project which are detailed here and
include pre-field work construction of a frame to house instruments, laboratory and field work
and data analysis methodologies.
6.1 Frame Construction
To enable the LOPC, data logger and FluoroProbe to be lowered through the water column
together in a controlled manner a metal frame was constructed. A frame had to be used as the
data logger and LOPC are both bulky and heavy requiring a winch to pull them to the surface
after each cast. The design of the frame had to allow the devices to profile the water column
vertically, whilst remaining balanced and ideally acting as a housing to protect the instruments.
Two main designs were considered with the final design being a rectangular box made of
aluminium angle shown in Figure 6-1.
Figure 6-1 The instrument frame with the data logger, FluoroProbe and LOPC attached from left to right.
The weight of the data logger, LOPC and FluoroProbe are 11 kg, 11.4 kg and 4.5 kg respectively
giving the frame a total weight with the instruments attached just less than 30 kg.
30
6.2 Site Location
Site locations for spatial sampling were selected to coincide with sampling stations of the SRT’s
fortnightly sampling. These locations can be seen in Figure 6-2 as the blue dots. Sampling at the
same locations as the SRT allowed comparison of results to data obtained from the Department
of Water and provided some further information such as nutrient analysis and phytoplankton
species counts. Sites for spatial sampling were only chosen in the lower and middle estuary due
to depth limitations of using the LOPC in shallow conditions such as the upper estuary.
The site chosen for temporal sampling was a public mooring located at a depth of 11 m that
enabled high resolution profiling using the LOPC, FluoroProbe and CTD. The use of a mooring
was necessary as anchoring a boat would have prevented sampling at the same location
throughout the 24 period and would have caused sediment disturbance. This site is the red dot
as seen in Figure 6-2 and is located in Freshwater Bay just north of Royal Freshwater Bay Yacht
Club.
Figure 6-2 Sampling locations for both temporal and spatial fieldwork.
31
6.3 Spatial Fieldwork
The first field trip was conducted over two days in early July involving sampling from Blackwall
Reach in the lower estuary to Kingsley Street in the middle estuary. At each station, a vertical
profile was conducted using the LOPC and FluoroProbe in the frame and the CTD. The frame
was lowered through the water column falling under its own weight and then raised to the
surface using an electronic winch connected to a davit arm on the boat. A Seabird CTD SBE
19plus SEACAT Profiler was used at each station to collect a vertical profile of changes in
physical and chemical properties of the water column. The CTD was held at the surface for
about 60 seconds to allow priming before being lowered at a rate of about 1 metre per 5
seconds.
Downwelling light was measured at each station on the sunny side of the boat using a LI-Cor LI-
192SA Underwater Quantum Sensor just below the surface (2-5 cm) and then every 50 cm from
the surface until 5 m depth, then every metre to 8 m (extent of measuring cable) or til just
above the bottom of the river. Three readings were recorded at each depth using a LI-Cor LI-
1400 reader using a 15-second average with a calibration constant of -286.95 applied to the LI-
192 quantum sensor data. The LI-192 sensor was attached to a 2009S Lowering Frame that was
weighted using a 1.5 kg lead dive weight, to keep the frame vertical in the water.
Vertical plankton tows were performed at each station using 53 μm mesh plankton net that was
weighted at the bottom. The depth of water for each sampling tow was recorded. Plankton
matter collected in the net was backwashed into a sample jar and fixed at 4% w/v
formaldehyde solution using a base formaldehyde solution of 36% concentration.
6.4 Temporal Fieldwork
A 24 hour field trip was conducted from the 18th to the 19th of August to assess temporal
changes in the vertical distribution of plankton. A site in the lower estuary was chosen with a
depth of about 11 m was chosen to allow high resolution of vertical trends. Sampling was
conducted from a permanent mooring to prevent disruption of sediments with an anchor and
to maintain sampling position. Sampling was conducted using the FluoroProbe and LOPC on the
Frame every half hour, CTD every hour, LI-Cor four times during sunshine hours and integrated
vertical plankton tow four times during the 24 hours focussing on dawn, morning, afternoon
and dusk. Unforeseen circumstances saw the breakdown of the electronic winch between the
11:15 am and 12:15 pm. Once the winch was fixed, sampling continued. Problems also occurred
with the FluoroProbe not recording a number of casts due to a damaged circuit connection in
the starter plug.
32
Each time sampling was conducted using the frame, two faster casts were conducted to allow
required flow rates for LOPC function and then one slower cast was conducted using the
FluoroProbe only to provide higher spatial resolution data from the FluoroProbe. This was
required due to the slower scan rate of the FluoroProbe. Integrated plankton tows, vertical
tows from the bottom to the surface using a plankton net, were conducted in the same manner
as the spatial fieldwork. LI-Cor readings were collected every 0.5 m starting from just below the
surface of the water to a depth of 8.5 m. A 15 second average of downwelling irradiance was
measured at each depth.
6.5 Laboratory Circulator
Integrated plankton tow samples collected from both the temporal and spatial field work were
observed under the microscope to determine the dominant zooplankton groups present in
samples before analysis with the Laboratory Circulator.
The Laboratory Circulator and LOPC Flow tube conversion were set up in the laboratory
according to instructions in the operation and maintenance manual (ODIM Brooke Ocean
2008a) with some changes necessary to the pump input connection from the main water
storage tank. The original connection between the tank and pump was placing a lateral loading
on the pump shaft, preventing it from turning. These fittings were replaced with a section of
flexible hose to allow the pump to operate. The final set up of the Laboratory Circulator can be
seen in Figure 6-3.
Approximately 25 litres of water placed in the Laboratory Circulator and the water was passed
through the 75 μm mesh filter for 4 hours and then through a 20 μm mesh filter for about a
further 10 hours. This resulted in background counts on average of less than 10 counts per
second. To prevent unnecessarily large volumes of water being added to the Laboratory
Circulator from the plankton two samples, the samples were concentrated by passing the
solution through a 54 μm section of mesh and then backwashed with deionised water into a
smaller sample jars. The samples were then added to the Laboratory Circulator through the
sample hatch and results from the LOPC were captured with the LOPC software. The data files
were then processed in the same way as they were during field work.
33
Figure 6-3 Laboratory Circulator setup to analyse plankton samples with the LOPC.
6.6 Project Management
The field work was managed to ensure that all activities were conducted safely and efficiently.
For both field trips a minimum of three people were required onboard the vessel to undertake
sampling. As part of the UWA Boat and Safety Policy, a skipper with Restricted Coxswain
Certificate was required. Preparation to ensure that the boat and its equipment, including davit
arm and winch, were in working order required communications with the UWA Boat and Safety
Officer. Field work plans for both field trips were prepared to ensure that no damage would
result to people or equipment. A copy of the field work plan prepared is in APPENDIX 1.
34
Crew rosters and sampling equipment had to be prepared for both the spatial and 24 hour
sampling. Crew exchanges meant that changeover times and place had to be communicated
clearly to all members. Due to the cold weather, it was the responsibility of both individuals and
the fieldwork leader to ensure that crew had adequate warm clothes and were provided with
warm food and drinks throughout the fieldwork. Not only were the crew needed to help sample
during the field trip but to assist during launch and retrieval of the boat.
During the second field trip, the boat was moored using a SRT Public mooring. Details of this
mooring had to be obtained to ensure that the mooring had undergone required safety checks
and maintenance in accordance with the UWA Boating Policy. Due to the 4 hour limit on these
moorings, registration information about the boat also had to be sent to the Department of
Transport and Water Police, to prevent a fine being given for overstaying the required time
limit.
The passing of a cold weather front during the first planned time window for the temporal
sampling resulted in delaying this field trip by one week. It was decided that due to the
predicted strong winds forecast that operation of equipment on the boat would not have been
safe. This decision meant that field work plans had to be altered and hiring of boat and car had
to be extended and rebooked.
Due to the large amount of time out in the field, a laptop with long battery life was required to
download data from the FluoroProbe after each station or time sampling. Lighting was also
required to allow each individual to see what they were doing at night and for safety reasons.
Communication with the SRT and Department of Water was required to obtain information
from their estuary sampling program that was conducted on the same day as the spatial
sampling and two days prior to the temporal sampling.
6.7 Data Analysis
Data from both Field Trip 1 and Field Trip 2 were analysed according to the methodology below.
6.7.1 LOPC
Files stored on the data logger during field work were created as .bin files that were
transformed to .dat files using the LOPC software. Software, created by Alex Herman was used
to process these files. To gain high resolution temporal data, plankton ESD bin sizes had to be
selected prior to processing. As very little was known about the zooplankton of the Swan River,
the correct bin sizes to quantify different zooplankton abundance were unknown so an initial
35
set of bin sizes was selected. After this data was processed the cumulative size distribution,
which has higher size resolution, was used to determine more appropriate ESD bin sizes of 90-
150 μm, 151-250 μm, 251-500 μm, 501-1000 μm and 1001-3750 μm. These bin sizes were then
used for the second processing of LOPC data files.
Some difficulty was experienced with processing the cast files from station 5 of the spatial
sampling, possible due to high MEP counts (Schultes & Lopes 2009). Because of this, LOPC data
from station 5 has not been presented in this study. All other casts using the LOPC in the spatial
field work were successfully processed.
During the temporal sampling, for reasons unknown, the LOPC failed to initialise and collect
data correctly throughout some casts. Combining this issue with the unreliability of the
FluoroProbe meant that there were not as many sampling periods as anticipated which
collected both phytoplankton and zooplankton results.
Because the LOPC has no depth sensor, accurate determination of sampling depth was not
possible. The depth however was compared to the depth of the FluoroProbe at the same time
as the devices were synced prior to sampling. The LOPC is able to estimate the flow rate of
water by measuring the time for particles of particular size range to pass through the laser
beam. However, in the mode of processing used, the flow rate was not used as validation and
could not be directly compared to a depth or acceleration sensor.
It was difficult to quantify the relative total abundance of zooplankton over the water column,
due to lack of knowledge of the flow rate, or exact depth in relation to particle counts. As a
result, conclusions will only be drawn from the ratio of different zooplankton size groupings,
and the vertical variations as well as values integrated over the water column. Depth averaged
biomass can be used to compare biomass between stations.
Biomass of cells were calculated for each of the size fractions above according to Equation 4-2
with an R value of 3 as a part of the processing of the data with Alex Herman’s software. These
results were integrated over each downcast conducted in the field. Because of the difficulties in
estimating the volume of water flow, in this project biomass will be represented as either
milligrams integrated over the whole cast, or milligrams per metre. Biomass at each station was
only calculated from in situ counts collected in the field. For the purpose of this study
zooplankton size classes will be grouped as: microzooplankton, between 90-250 μm,
mesozooplankton 250-1000 μm, and macrozooplankton > 1000 μm, unless otherwise stated.
36
NBSS were not be created for this study as further research into the best R factor, length to
width ratio, for the species present in SRE is required to ensure that accurate biomass estimates
are made. This does not mean that the data collected is not useful, instead, it is anticipated that
with further microscopic identification and measurement of zooplankton samples, that NBSS
shall be created. This will allow improved understanding of the zooplankton communities
within the SRE with LOPC at different times and locations by comparison of the slope.
6.7.2 CTD
CTD data was downloaded from the SBE 19plus SEACAT Profiler using SEATERM. Due to the
priming time required for the CTD pump, the first 60 seconds of data from each cast was
deleted, or the top of the cast prior to the drop. Down cast data was then extracted and
imported into MATLAB. Salinity values were calculated using SEAWATER, which is a series of
MATLAB scripts developed by Phil Morgan at the CSIRO. These conversions were according to
UNESCO standards for salt water developed by Fofonoff and Millard (1983).
For the temporal sampling, average values of salinity, temperature and dissolved oxygen were
calculated at the surface and bottom of each station from a minimum of 10 data points and an
integrated average was calculated over the whole water column.
6.7.3 Irradiance
To determine the attenuation coefficient of light at each station the natural log of (the
ratio of downwelling PAR at depth (E) to downwelling PAR at the surface (Eo) ) was plotted
against depth (z). A linear regression line was then fitted by the least squares regression
method and the slope of this line is the attenuation coefficient in a manner suggested by (Kirk
1977). This method is in accordance to the Lambert-Beer Equation for attenuation of light
through a medium. To determine the significance of the Kd value, a t-test was conducted on
the linear regression of depth vs. Kd.
Equation 6-1 Attenuation of light (Kirk 1977).
Equation 6-2 Calculating the attenuation coefficient (Kd).
37
6.7.4 FluoroProbe
The FluoroProbe uses a pressure sensor to measure the depth in the water column. Because
atmospheric pressure can vary over short time scales (~hours) this can influence the depth
readings recorded by the FluoroProbe. To overcome this atmospheric pressure was obtained
from the Bureau of Meteorology and linearly interpolated over the sampling period.
Atmospheric pressure data from the spatial field trip was obtained at 9 am and 3 pm each day
out in the field, whereas data from the temporal field trip was higher resolution, every half
hour. This information was then used to alter the atmospheric pressure parameter in the
‘Parameters of Measurement’ of the FluoroProbe program. This automatically altered the
depth readings according to the Equation 6-3. The depth sensor of the FluoroProbe located on
the base of the meant that concurrent measurements of depth and absorbance were occurring
at different heights within the water column. The measured distance between the depth sensor
and the measurement window was 20 cm and this distance was deducted from all depth
readings so that depths indicate the height of the water column being sampled by the
FluoroProbe.
Equation 6-3 Influence of atmospheric pressure on the depth calculation from the FluoroProbe. Pressure is
measured in bar and depth is in metres (BBE Moldaenke 2007).
38
7 Results
The results from both the spatial and temporal field trips, including laboratory analysis of
plankton tow samples using the flow circulator are presented in this section.
7.1 Microscopic Observations
Appendix 6 – Dominant Zooplankton Species, shows the dominant zooplankton species
observed from plankton net samples. Samples from both temporal and spatial fieldwork were
observed under the microscope to check that particles being counted were plankton. During
the temporal sampling, nauplii were the most abundant species present, with high observation
of tintinnids and calanoids. During the spatial sampling, tintinnids were most abundant, with
varying proportions of nauplii, rotifers, ceratium and other minor species.
There was only a small amount of sand found in a few samples and it is most likely that this was
a result of the plankton net disturbing sediment.
Rotifer Calanoid Rotifer
Tintinnid Nauplii
* Note these images
are not to scale. The
purpose of these
photos are to illustrate
dominant zooplankton
taxon.
Table 7-1 Dominant zooplankton species observed in the SRE.
The dominant zooplankton species observed under the microscope from plankton net samples
showed a variety of groups. Tintinnids were the most abundant group over the whole estuary
sampled. There appears to be a gradient in species from calanoid and nauplii being dominant in
the first two stations to ceratium and tintinnids from Heathcote to the Narrows Bridge.
Tintinnids, rotifers and nauplii were most dominant in the middle estuary. A similar assemblage
of zooplankton was noted at Freshwater Bay to stations 1 and 2, with nauplii being more
dominant than tintinnids.
39
7.2 FluoroProbe Calibration
Average chlorophyll a measured by the FluoroProbe during the temporal sampling at
Freshwater Bay was 2.7 μg/L. The sites either side of this location monitored by the Swan River,
Blackwall Reach and Armstrong Spit, two days prior had 1.0 and 3.1 μg/L of chlorophyll. Table 8-
2 Below shows the difference between chlorophyll a measured in the field with the
FluoroProbe and measured by the SRT from grab samples. Measurements collected by the SRT
in the middle estuary were on the day before the FluoroProbe sampling, which may explain
some of the larger variations.
Site Name Depth
(m) Chlorophyll a (by vol) (μg/L)
FluoroProbe average Chlorophyll a (μg/L)
ARMSTRONG SPIT 6.0 1.3 2.56
Surf 0.9
NARROWS BRIDGE 3.5 2.1 3.63
Surf 0.8
NILE ST 2.5 9.1 6.43
Surf 8.5
ST JOHN OF GOD HOSPITAL
4.0 5.4 15.12
Surf 11
MAYLANDS SWIMMING POOL
3.0 6.6 15.95
Surf 5.8
RON COURTNEY ISLAND
4.0 4.5 6.72
Surf 11 Table 7-2 Comparison of SRT and FluoroProbe chlorophyll a concentrations.
7.3 Spatial Fieldwork
This section presents information on the physical, chemical and biological environment gained
from the field and laboratory analysis of data collected during sampling over two days from the
lower and middle estuary.
7.3.1 Physical Environment
The depth and distance of each site sampled during the spatial fieldwork is shown in Table 7-3
below. The deepest sites sampled were at Blackwall Reach and Armstrong with depth generally
decreasing with distance upstream, with the main exception of Ron Courtney Island. It should
be noted that station 5 is upstream of station 6 due to the order of sampling.
40
Station
Number Station Name
Distance Upstream
From Fremantle (km)
Depth
(m)
1 Blackwall Reach 7
15.40
2 Point Walter 8.5 7.00
3 Armstrong 10.5 10.10
4 Heathcote 13 3.50
6 Matilda Bay 15.5 4.40
5 Narrows 18 3.80
7 Nile Street 23 2.60
8 St John of God 28 2.00
9 Maylands 29 2.30
10 Ron Courtney Island 34 4.60
11 Kingsley 36.5 1.40
Table 7-3 Information on spatial field work sampling sites.
A summary of the physical and chemical climate in Figure 7-1 shows the CTD data that was
collected at each station. General trends at each station show that surface water was cooler
and less saline than water at depth with surface water having higher levels of dissolved oxygen.
With increasing distance from Fremantle, from the lower to the middle estuary, there was a
negative gradient of salinity from approximately 34 ppt to 23-25 ppt respectively. Each station
had slightly different physico-chemical properties with particular vertical variations evident in
some upstream locations, see Figure 7-1 and
Table 7-4 . Station 9 had the greatest vertical difference in salinity between the surface water
and at depth with a ∆S of 6.4. Station 10 also has some interesting vertical changes with
dissolved oxygen decreasing from 5.08 mg/L at the surface to 1.1 mg/L at the bottom, the
lowest dissolved oxygen level of all sites and the deepest of the upstream sites. The cast of
station 11 only has one metre of data that was accurate due to a short priming period. As a
result the surface readings at this station are not included in Table 8-4.
The dynamics at station 10 in particular are quite interesting as shown Figure 7-1, where the
salt wedge causes change from the brackish surface waters to 27.8 by 3 m and remains high
until near the bottom of the cast where at 4.9 m salinity decreases to 21.5.
Physical and chemical properties were also recorded by the SRT on the first day of our two day
spatial sampling campaign. These profiles created by the SRT can be seen in Appendix 2 – Swan
River Trust - Physical-Chemical Profiles. Vertical gradients due to the position of the salt wedge
are strongest in the middle estuary.
41
Figure 7-1 CTD vertical profiles from Station 1 to 11 during spatial sampling.
Lower Estuary Middle Estuary
Station 1 2 3 4 6 5 7 8 9 10 11*
Average over total depth
Temperature (oC) 14.98 14.44 14.64 13.93 14.58 14.22 14.98 15.72 15.67 15.21 16.32
Salinity 33.65 32.95 33.12 32.26 32.63 31.42 29.81 27.53 27.19 25.88 24.86
Dissolved Oxygen (mg/L) 8.56 8.88 8.17 8.48 7.97 7.57 7.51 6.46 6.59 2.62 3.46
Surface
Temperature (oC) 14.08 14.30 13.75 13.78 13.33 12.41 14.59 15.61 14.96 16.04 n/a
Salinity 32.46 32.30 31.90 31.79 31.17 28.38 27.69 27.55 22.95 23.78 n/a
Dissolved Oxygen (mg/L) 9.33 9.13 8.79 8.55 8.45 8.58 8.44 6.76 7.40 5.08 n/a
Bottom
Temperature (oC) 15.71 15.50 15.97 14.91 15.59 15.39 15.59 15.82 15.98 16.50 16.51
Salinity 34.47 33.96 34.27 33.07 33.52 32.91 30.72 28.00 29.36 21.51 25.91
Dissolved Oxygen (mg/L) 7.98 7.98 6.89 8.27 6.62 6.16 6.35 6.22 5.30 1.11 2.90
Table 7-4 Average, surface and depth measurements of temperature, salinity and dissolved oxygen.
42
Station 1 2 3 4 6 5 7 8 9 10 11
Average total chlorophyll (μg/L) n/a 4.20 3.20 3.20 2.80 3.40 7.90 13.80 16.10 5.80 9.20
Kd, (m-1) 0.54 0.45 0.48 0.46 0.64 0.39 0.90 1.14 1.01 1.03 1.24
Correlation Coefficient 0.99 0.98 0.98 0.94 0.97 0.97 0.99 1.00 0.99 0.99 0.98
p -value 0.0001 0.0001 0.0001 0.011 0.008 0.002 0.048 0.103 0.049 0.002 0.241
Table 7-5 Chlorophyll and light attenuation data from spatial sampling.
7.3.2 Light Climate
Water in the lower estuary in comparison to the middle estuary was clearer. Light attenuation
in the lower estuary from stations 1 to 6 had an average of 0.49 m-1 and in the middle estuary,
average light attenuation was 1.06 m-1, see
Table 7-5. The number of PAR readings at stations 8 and 11 were limited due to shallow depth,
resulting in p-values above the 5% confidence limit.
43
Figure 7-2 Phytoplankton spectral group concentrations at different stations.
7.3.3 Phytoplankton
Phytoplankton concentration and spectral group composition from the FluoroProbe changes
between the lower and middle estuary. Figure 7-2 shows the vertical profile of phytoplankton
species concentration at each site from Station 1 at Blackwall Reach to Station 11 at Kingsley
Street. The scale on the x-axis changes for the plots at stations 8 and above in this figure.
Stations 1 to 6 overall have lower total chlorophyll than stations 7 to 11, see
Table 7-4 which shows the average total chlorophyll from each profile. Stations 8 and 9 have
the highest total average concentrations over the water column of 13.80 and 16.10 μg/L.
Stations in the lower estuary have an average of less than 5 μg/L of chlorophyll, whereas
upstream concentrations in the middle estuary have a higher average of 10 μg/L of chlorophyll.
44
Phytoplankton species for station 2 to 6 are dominated by the spectral group of diatoms.
Whereas from station 7 upstream to station 11, green algae concentrations are much higher
but diatoms remain the most abundant spectral group. Station 6 was the only station to record
cryptophytes, which contributed about a third of chlorophyll in the surface water. Small
cryptophytes were also observed near this station the day before by the SRT along with
chlorophytes and diatoms species as seen in Appendix 5 – Dominant Phytoplankton Species.
Figure 7-3 Zooplankton size distribution profiles from the LOPC during the spatial sampling.
7.3.4 Zooplankton
Zooplankton abundance on average was higher in the lower estuary between stations 1 and 6
than in the middle estuary between stations 7 and 11, based on average cell counts per second.
Station 6 in particular had high total counts as seen in Figure 7-3. In this figure the y-axis shows
the depth bins where the first two bins are sampled in the first metre of the water column. The
cast rate is just over 1 m/s on average, so each remaining bin is integrated over approximately 1
m.
45
When looking at the average number of cell counts of a cast divided by the depth of the water
column, the average counts per metre over the whole estuary was close to 3000. Station 6, in
Matilda Bay, was significantly higher with depth averaged counts of nearly 4000 per metre.
Counts per metre were on average lower in the lower estuary at 2700 per metre when
excluding station 6 but were nearly 3000 per metre including station 6.
Field samples Laboratory Samples
Zooplankton Micro Meso Macro Micro Meso Macro
Lower Estuary
Average 75.35% 24.38% 0.27% 81.16% 18.82% 0.03%
Variance 0.0006 0.0006 0.000003 0.00236 0.00234 0.00000
Middle Estuary
Average 51.43% 46.84% 1.73% 92.97% 7.02% 0.01%
Variance 0.0007 0.0005 0.000029 0.00049 0.00048 0.00000
Table 7-6 Zooplankton size statistics. Comparison of five lower estuary and five middle estuary stations.
The abundance of zooplankton in particular size classes in the lower estuary sampled in July
was dominated by microzooplankton, between 90 and 250 μm. In the middle estuary,
microzooplankton were less abundant than in the lower estuary, with increasing abundance of
meso (250-1000 μm) and macro (>1000 μm) zooplankton. There was a significant change in size
abundances between station 6 and station 7. Station 6 was composed of 74% microzooplankton
whereas station 7 had only 53% microzooplankton counts. This change between the lower and
middle estuary is summarised in Table 7-3 and it is evident that there was a high degree of
similarity of zooplankton size structure between stations in each section of the estuary.
The lower estuary was dominated by microzooplankton counts, 75.35%, whereas the middle
estuary had more even count weighting between micro and meso zooplankton, 51.4% and
46.8% respectively. The number of counts from macrozooplankton was very low in both the
middle and lower estuary, composing less than 1% of all counts in the lower estuary and 1.73%
of counts in the middle estuary. The variation between sites was also very low, see Table 7-6.
In general, the proportion of each size group appears to have remained relatively constant
throughout the water column, see stations 6, 8, 9 and 11 in Figure 7-3. For some stations,
however, the abundance of different size classes changed with depth. At station 1 there was a
greater abundance of mesozooplankton above the ninth depth bin than there was below. At
station 2 there was a different pattern with more mesozooplankton at depth below the fifth
depth bin. At station 3 the proportion of micro to mesozooplankton remained similar over the
depth, except at the very bottom where there is a lack of mesozooplankton. Station 4
46
corroborated with the general pattern except in the middle of the cast where there appeared
to be a lack of meso and macrozooplankton. Interesting vertical variations are noted at station
10 where the first four depth bins are composed approximately equally of micro and meso
zooplankton, but below this microzooplankton dominated. At the surface of station 7, the first
depth bin is composed of nearly 50% microzooplankton to 50% mesozooplankton, but as depth
increases mesozooplankton tend to closer to one third of counts.
Appendix 3 shows a comparison of field to laboratory counts at each location and biomass
attributed to each size class. The relative abundance of counts in each class size for stations 1 to
4 when comparing laboratory and field counts is quite similar, see Table 7-6 . For the middle
estuary, however, the relationship is not as close. The use of the LOPC with the laboratory
circulator appears to reduce the number of mesozooplankton counts and increase the
proportion of counts in the microzooplankton class. This is particularly noticeable at stations 7
to 11 where the number of meso zooplankton is underestimated by the laboratory circulator
and the number of microzooplankton are overestimated. Less noticeable is at stations 4 and 6
where there is a slight underestimate of the number of mesozooplankton by the laboratory
circulator.
Depth Averaged Biomass (mg/L)
Station Micro Meso Macro Total
1 1.70 9.06 10.91 21.67
2 2.33 13.57 7.06 22.96
3 2.19 7.74 4.00 13.93
4 2.54 12.91 28.89 44.34
6 3.39 14.55 5.20 23.14
7 2.50 35.88 77.00 115.38
8 2.35 40.10 114.60 157.05
9 1.65 33.91 129.00 164.57
10 1.85 30.24 55.39 87.48
11 2.57 53.07 126.29 181.93
Table 7-7 Spatial sampling – Depth averaged biomass.
The weight of biomass appears to be inversely related to the number of counts in each size
class. The majority of biomass at each location is attributed to the macrozooplankton, which
tends to have the least number of counts, with the least amount of biomass being attributed to
the microzooplankton, which often has the greatest number of counts. This inverse
relationship of increasing total biomass as particle size increases, with macrozooplankton being
attributed to the greatest proportion of biomass, was particularly pronounced in the middle
estuary from station 7 to 11, see Table 7-7. In the lower estuary, however, the
mesozooplankton appear to be contributing a larger component of the overall biomass than
47
they did in the middle estuary. This was particularly evident from the biomass distribution at
stations 2, 3 and 6 and to a lesser extent at station 1.
48
7.4 Temporal Fieldwork
This section provides information on the physical, chemical and biological environment gained
from the field and laboratory analysis of data collected during the 24 hour sampling in
Freshwater Bay in the lower estuary.
7.4.1 Physical Environment
The physical and chemical properties of the water column during the temporal sampling
showed minimal variations at the surface and at depth during the 24 hour sampling except for
some slight warming and cooling of surface waters. A summary of the salinity, temperature
and dissolved oxygen conditions can be seen in Figure 7-4. A density gradient between surface
and bottom water exists throughout the duration of the sampling, but the height of the
gradient changes with time.
At the beginning of sampling, at 8.15 am, the tide in the river was ebbing until low tide, which
was reached at 5 pm at the site. The tide then rose slowly to high tide by about 7 am the
following morning. A plot of the tide over the 24 hours can be seen in Figure 7-4. This period of
sampling corresponded to just after the first quarter of the mood and thus a diurnal signal was
experienced in the river.
Figure 7-4 Tidal elevation during 24 hour sampling period.
Surface water of at the site in Freshwater Bay had a constant salinity of 29 ppt and dissolved
oxygen of 8 mg/L during the temporal sampling as shown in Figure 7-5 and Figure 7-6. The
temperature of surface water varied from 15 oC in the morning, warming to 15.5 oC during the
49
day, and then cooled overnight to 14.5 oC, seen in Figure 7-7, caused by low overnight air
temperature that reached a minimum of 2 oC.
The physical and chemical properties of bottom waters during the temporal field work differed
significantly from surface waters. Bottom waters were more saline that surface waters, with an
average salinity of 34.12. The temperature remained constant at 16.45 oC . Oxygen levels of the
bottom water were also lower than the surface water with an average value of 6.7 mg/L that
did not vary by greater than 0.25 mg/L. At the temperature and salinity levels this equated to
85% level of oxygen saturation.
Surface water and bottom water at this location in the Swan River were differentiated by the
presence of a density gradient between the two water masses. At the beginning of sampling the
density gradient is located at a depth of 3.5 m and deepens to 4.5 m as the tide reaches its
minimum height. As the tide floods back in during the evening and overnight the density
gradient rises to 3.5 m between 10 and 15 hours, falling to maximum of 4 m, before rising to a
minimum depth of 2.5 m at the end of the sampling period.
Figure 7-5 Salinity profile from temporal sampling.
50
Figure 7-6 Dissolved oxygen variations during the temporal sampling.
7.4.2 Phytoplankton
Phytoplankton abundance, composition and the depth of the chlorophyll maximum showed
fluctuations throughout the temporal sampling. The general pattern of phytoplankton spectral
groups showed an equal ratio of green algae to diatoms in the surface water shifting to
dominance in the diatom spectral group at depth, see Figure 7-8. At the surface, green algae
comprised 50% of the chlorophyll in the water column decreasing to 10 to 20% at the bottom.
As the depth of the chlorophyll maximum moved over the 24 hours, the total concentration of
chlorophyll also deviated. The total chlorophyll concentration at each depth is the sum of the
concentration of the phytoplankton groups, as seen in Figure 7-8. In the morning at the
beginning of the 24 hour sampling, the deep chlorophyll maximum was located at 5 metres
with a total chlorophyll concentration of 3.85 μg/L, which increased to 4.4 μg/L by 12.45 pm. By
3.45 pm the chlorophyll maximum had risen to 4 m with a total concentration of 4.81 μg/L. The
deep chlorophyll maximum concentration had decreased by 7:45 pm to 3.27 μg/L but remained
at a depth of 4 m. Overnight the deep chlorophyll maximum continued to fall to 5 m just before
midnight and to 7 m by 3:15 the following morning. Just after dawn, at 6:15 am the deep
chlorophyll maximum had lifted to 4 metres and the concentration increased to 3.53 μg/L. In
51
general overnight the total chlorophyll is more evenly distributed over the water column than it
is compared to profiles taken within day light hours.
At 9.45 am and 3:45 am low concentrations of cryptophytes were present in the first metre of
water. Cryptophytes were also present in sampling conducted by the SRT in this area of the
river, two days prior to sampling. At 9:45 am near the beginning of the temporal sampling
between 6 and 8 m there is green algae chlorophyll minimum, where the water at this depth is
dominated by green algae.
Figure 7-7 Temperature variations during the temporal sampling.
52
Average over water column
Average over 24 hours
Temperature (oC) 15.89
Salinity 31.94
Dissolved Oxygen (mg/L) 7.75
Surface Average over 24
hours
Temperature (oC) 15.09
Salinity 29.30
Dissolved Oxygen (mg/L) 8.63
Bottom Average over 24
hours
Temperature (oC) 16.45
Salinity 34.12
Dissolved Oxygen (mg/L) 6.69
Table 7-8 Temporal Sampling. Average water column physical and chemical properties.
LiCor 8:45 AM 12:53 PM 2:26 PM 4:26 PM
Kd (m-1) 2.55 2.54 2.23 1.98
Correlation 0.98 0.99 1.00 0.99
p-values 0.00002 0.00001 0.00001 0.00006
Table 7-9 Light attenuation variation during the day.
7.4.3 Light Climate
Sunrise and sunset during the temporal sampling were at 06:51 am and 17:51 pm respectively.
The attenuation of light caused by the water and other components resulted in an attenuation
coefficient of 2.55 m-1 in the morning, remaining constant until early afternoon and decreasing
to 2.23 and 1.98 m-1 by late afternoon, see Table 7-9. The attenuation coefficient had a high
correlation with depth, all which were supported by probabilities above the 99.9% confidence
limit.
Sample Time
Average Chlorophyll (μg/L)
9:45 AM 2.5
12:45 PM 2.7
3:45 PM 3.3
7:45 PM 2.2
11:45 PM 2.7
3:15 AM 2.8
6:15 AM 2.5
Table 7-10 Temporal sampling. Average FluoroProbe measurements of chlorophyll of the water column.
53
Figure 7-8 Phytoplankton spectral group concentration profiles during the 24 hour sampling.
7.4.4 Zooplankton
The abundance and proportion of different zooplankton size groups collected with the LOPC in
the field showed both vertical variations within profiles and changes with time. In general
within each profile there appeared to be less zooplankton in surface waters above the density
gradient, and more at depth. In the surface waters, the zooplankton were dominated by the
microzooplankton size class with the bottom waters being more evenly distributed between
micro and meso zooplankton, see Table 7-11. At the bottom of each cast there appeared to be
a reduction in the abundance of mesozooplankton particularly, between 500 and 1000 μm in
size.
The depth of the density gradient, as indicated by the temperature contour of 15.6 oC and a
salinity of 31 ppt, in reference to the times of casts shown in Figure 7-9, is located at a 3.7, 4.8,
4.3, 3.7, 4.0, 3.9 and 2.8 metres respectively. In Figure 7-9 the y-axis shows the depth bins
where the first two bins are sampled in the first metre of the water column. The cast rate is just
over 1 m/s on average, so each remaining bin represents approximately 1.2 m. Above the
54
density gradient microzooplankton on average comprised 84.8% of zooplankton counts,
whereas below the density gradient they comprised 56.8% of the counts, see Table 7-11. Below
the density gradient, mesozooplankton made up this disparity in counts, contributing 42.4% of
counts.
Figure 7-9 Zooplankton size distribution profiles from the LOPC during the 24 hour sampling.
A student’s paired t-test was conducted on the percentage abundance of microzooplankton and
mesozooplankton between the surface and bottom water masses of seven casts. From this it
was shown that there was above a 95% probability that the abundance of microzooplankton
and mesozooplankton was different between the surface and bottom waters.
Figure 8-10 is a plot of the size structure at the beginning of the spatial sampling. There is a
peak of zooplankton in the 90-115 μm size class which is cut off on the left due to the minimal
size of particles which the LOPC can distinguish. On the right hand side of the peak, the
abundance decreases rapidly with increasing size. This pattern was consistent throughout both
the temporal and spatial sampling. Figure 8-11 shows the biomass of this same cast.
Total Counts (number of counts per second)
Dep
th B
ins
55
Figure 7-10 Integrated zooplankton size structure. The x-axis shows ESD in μm.
Depth averaged biomass, as presented in Table 7-12, shows that even though micro and meso
zooplankton dominated the number of particle counts in the LOPC, macrozooplankton
comprised the largest proportion of biomass in the water column. Biomass from the
macrozooplankton was the most variable of the size groups. Mesozooplankton also
contributed a major proportion of biomass, whereas microzooplankton did not contribute more
than 4.1% of depth averaged biomass.
Figure 7-11 Biomass from the same cast as Figure 8-10
56
Appendix 4 – LOPC results from temporal fieldwork shows a comparison of the number of
counts in each size group, counted in the field and from plankton net samples in the laboratory
with the LOPC.
Average Surface Depth
Time Micro Meso Macro Micro Meso Macro Micro Meso Macro
9:45 AM 60.70% 38.62% 0.68% 84.35% 15.34% 0.30% 55.19% 44.04% 0.76%
12:45 PM 55.15% 28.99% 0.64% 87.28% 12.60% 0.12% 54.80% 44.16% 1.04%
3:45 PM 67.55% 34.01% 0.73% 85.07% 14.63% 0.30% 58.31% 40.81% 0.89%
7:45 PM 60.09% 34.89% 0.52% 83.48% 16.42% 0.10% 59.64% 39.75% 0.61%
11:45 PM 56.77% 42.55% 0.68% 83.29% 16.68% 0.04% 52.75% 46.47% 0.78%
3:15 AM 55.65% 39.48% 0.75% 88.84% 11.05% 0.12% 55.14% 44.02% 0.84%
6:15 AM 72.33% 40.79% 0.51% 81.54% 18.42% 0.04% 61.78% 37.73% 0.49%
Average 61.18% 37.05% 0.64% 84.83% 15.02% 0.15% 56.80% 42.42% 0.77%
Variance 0.0042 0.0022 9.33E-07 0.0006 0.0006 1.25E-06 0.0010 0.0009 3.31E-06
* Surface is taken as values above the density gradient and depth is taken as values beneath the density gradient.
Table 7-11 Temporal sampling - Zooplankton size classes statistical abundance percentages.
Depth Averaged Biomass (mg/L)
Time Micro Meso Macro Total
9:45 AM 1.69 17.79 27.31 46.79
1:15 PM 1.45 16.16 20.14 37.75
6:45 PM 1.37 16.82 21.52 39.71
3:45 AM 1.80 18.04 23.42 43.25
Table 7-12 Depth Averaged Biomass (mg/L)
57
8 Discussion
This section discusses the results and investigates relationships observed and possible causes.
8.1 Suitability of LOPC in Estuary Conditions
The LOPC has provided invaluable insight into the vertical structure of zooplankton
communities in the SRE. Clear vertical structures were shown to be present during both the
temporal and spatial sampling, with the LOPC able to resolve the different size particles in the
water.
Comparison of size distributions determined from the laboratory with the field demonstrates
that the laboratory circulator more closely mirrors field observations in the lower estuary than
the middle estuary. The differences between field and laboratory size spectrums is likely
influenced by sample collection with the plankton net and concentration of samples. If larger
aggregates were present in the middle estuary these may have been broken by the plankton
net (Checkley et al. 2008). Despite this, in most locations, the size distribution plots collected in
the field and the laboratory were reasonably similar.
Because the method of processing does not use flow estimation, connecting the LOPC to a flow
meter and pressure sensor could help to improve depth resolution of data and improve
accuracy of biomass calculations. Towing the LOPC or affixing it to a boat may provide greater
spatial resolution of plankton abundance and biomass. However, both these methods have
their limitations and depth is the main limitation of the LOPC in a shallow estuary like the SRE.
This study assessed vertical structure of plankton communities both temporally and at different
locations using vertical casts. The required flow rate for the LOPC and shallow depths prevented
the acquisition of high resolution counts in comparison to deep sea casts.
8.2 Spatial Sampling
Spatial sampling of the phytoplankton and zooplankton communities of the SRE displayed
distinctly different patterns between the lower and middle estuary and these are likely to be
influenced by the location of hydrodynamic features.
8.2.1 Physical and Chemical Environment
In the week prior to the spatial sampling total rainfall experienced in the Perth region was 0.2
mm as reported by the SRT in Appendix 2. The salt wedge resulted in the strongest vertical
gradients of salinity, temperature and dissolved oxygen in the middle estuary near Maylands,
58
Ron Courtney Island and upstream. Interesting patterns of the physical environment were
noted particularly in the middle estuary due to the presence of the salt wedge. The greatest
stratification was noted at stations 9 and 10, with station 10 also showing a small pocket of
brackish water beneath the salt wedge. This water was also the least oxygenated water
recorded of all stations in the fieldwork, reaching near anoxic conditions at 11% saturation.
8.2.2 Phytoplankton
The distribution of phytoplankton in the estuary increased in concentration from the lower to
the middle estuary. This pattern of high average total chlorophyll held for most stations in the
middle estuary except at station 7 and in particular station 10. The total chlorophyll at station 7
is between the average values for the lower and middle estuary. The gradient in physical
parameters, such as salinity, between the lower and middle estuary was likely to be controlling
the plankton concentration. The concentration of phytoplankton at station 10 was below the
average trend of 10 μg/L of the middle estuary. This may be related to the unique physico-
chemical environment at this station, where low oxygen levels appear to be influencing the
biology.
During the spatial sampling, vertical structure was more consistent over the cast depth at
individual stations compared to the temporal sampling with variations noted between stations
as discussed above.
8.2.3 Zooplankton Abundance
Percentage composition of different zooplankton size fractions were shown to depend on the
chosen size range for each size class. Despite this, the results show that zooplankton greater
than 500 μm in size were more abundant in the middle estuary. This coincided with an increase
in the average chlorophyll concentration and it therefore appears that the zooplankton
distribution appears to be strongly influenced by the location of food. Grazing by zooplankton is
often dependent upon the phytoplankton species present with zooplankton often exhibiting a
preference for smaller diatoms and avoiding other species(Deeley & Paling 1999). In the lower
estuary microzooplankton were most dominant, whereas, in the middle estuary there were
increasing quantities of meso and macrozooplankton. Shifts in zooplankton assemblages from
macrozooplankton-sized copepods to microzooplankton, have been related to an increase in
eutrophication events (Uye 1994 in Griffin and Rippingale 2001). If eutrophication events have
lead to such changes in zooplankton assemblage of the SRE, this may explain the overall
abundance of microzooplankton throughout the estuary.
59
8.2.4 Zooplankton Biomass
Over the lower and middle estuary the microzooplankton are the smallest component of
biomass. Mesozooplankton in the lower estuary sometime comprise more biomass than the
macrozooplankton (> 1000 μm), but in the middle estuary macrozooplankton always comprise
the largest proportion.
8.3 Temporal Sampling
8.3.1 Physical and Chemical Environment
Rainfall in Perth the week prior to the temporal sampling was 41.4 mm resulting in increased
river flow, which freshened water in the upper estuary and increased stratification in the
middle estuary compared to the previous week. Because of this rainfall and the limited rainfall
in the previous month, hypoxic bottom waters from the upper estuary propagated further
downstream. The anoxic conditions, however, had minimal influence on the site sampled for
the temporal sampling in the lower estuary. At Freshwater Bay the water column was partially
stratified as suggested by the results. This stratification appears to have reduced the diffusion
of oxygen from the surface waters, which were about 100% saturated decreasing to 85%
saturation at the bottom. This is still considered to be well oxygenated with ample oxygen for
normal aquatic organism function. Only when oxygen levels are below 4.5 mg/L is it likely to be
detrimental to the health of organisms (Griffin & Rippingale 2001).
The density gradient between the surface and bottom water masses moved vertically
throughout the 24 hours most likely due to tidal and sub-tidal oscillations. The height of the
salinity gradient appeared to be most strongly influenced by the tidal components. Some
fluctuations appeared to be acting on a shorter time scale than the dominant diurnal tidal
constituents acting at this phase of the moon. This may have been related to the passing of a
small cold front on the evening prior to the 24 hour field trial.
8.3.2 Zooplankton Abundance
Not only does the density gradient appear to have acted as a barrier reducing oxygen diffusion,
it also appears to have acted as a barrier that is dividing the two different zooplankton
communities. The percentage abundances of microzooplankton and macrozooplankton in the
surface water compared to the bottom waters was statistically significant as discussed in the
results. The differences between the proportion of microzooplankton and macrozooplankton
above and below the density gradient was vividly evident that surface water had a clear lack of
60
zooplankton greater than 500 μm, and a high proportion of macrozooplankton located just
below the density gradient possibly caused by the co-location of the deep chlorophyll
maximum.
The movement of larger zooplankton from bottom waters during the ebb tide to surface layers
during the flood tide, however, may be related to the TVM mechanism that has been observed
in copepods, amphipods and other zooplankton, although not all studies support the retention
ability of copepods (Ueda, Kuwatani & Suzuki 2010).
8.3.3 Zooplankton Biomass
Biomass of zooplankton during the temporal sampling showed minimal change with time with
macrozooplankton being the largest contributor. Microzooplankton contributed the least.
The use of R=3 in calculating zooplankton biomass may have created an overestimation of
biomass in some size groups. Whilst this factor may have been appropriate for the largest
biomass group (>1000 μm), as R=3 is the appropriate length to width ratio for developed
copepods, it is unlikely that this factor is representative for the biomass of other zooplankton
groups such as the tintinnids, nauplii and ceratium.
Even though the selection of R chosen needs further adjustment, it is still evident from plots in
Appendix 4 that the majority of zooplankton biomass is controlled by the largest zooplankton
greater than 1000 μm.
8.3.4 Phytoplankton
Results obtained from the FluoroProbe indicate high concentration of the diatom and green
algae spectral groups. The diatom spectral group, however, incorporated more than one
plankton group. Data of phytoplankton species from the SRT supports that the diatom spectral
group was most likely to be composed of diatoms with the species Skeletonema costatum being
the most dominant phytoplankton species at Armstrong Spit and Chaetoceros spp./
Thalassionema, other diatom species were relatively common at Blackwall Reach prior to the
temporal sampling. The green spectral group was most likely composed of chlorophytes as they
were the dominant taxonomic green group from SRT data. During 1995 the most dominant
phytoplankton taxonomic group observed in the lower SRE were diatoms and throughout the
whole estuary during the winter months of July and August diatoms and chlorophytes were the
most abundant taxonomic groups (Twomey & John 2001)
61
8.3.5 Vertical Migration
From the results obtained during the temporal sampling, it is not clear whether the
zooplankton have undergone a form of diel vertical migration. From the early evening until the
next morning the tide was flooding and the location of the density gradient and plankton
community shifted with the tide. To confirm if there was a form of vertical migration, sampling
at different times during tidal movements could provide more information.
8.4 General Discussion
Some similarities between the distributions of zooplankton measure in the spatial and temporal
sampling have been noted between different sites. The size structure of the zooplankton in the
middle estuary had equal abundance of micro (90-250 μm) and meso (250-1000 μm)
zooplankton, which correlates to the size structure observed in the temporal sampling in
Freshwater Bay beneath the density gradient.
The gradients in zooplankton groups noted as most dominant across the estuary may have
been related to the lifetime of the different zooplankton groups. Basu and Pick (1996), found
that the zooplankton assemblage in Canadian rivers was influenced by the water residence
time. At warm temperatures, the regeneration time of tintinnids is short at less than 24 hours
(Blanchot, Charpy & Borgne 1989).
Comparison of the FluoroProbe measurements of chlorophyll a and chlorophyll a measured
from SRT samples are correlated well for the temporal sampling, but not quite as well for the
spatial sampling. This however is expected as the samples were not taken concurrently but they
suggest that readings are not excessively different.
62
9 Conclusion
Results from both field trips suggest that there were clear vertical patterns in the abundance of
plankton in the SRE that were related to hydrodynamic features of the estuary. The use of the
LOPC in the SRE provided good information on the zooplankton community size structure and
their vertical variations.
The vertical distribution of plankton at different locations in the SRE during the spatial sampling
showed higher abundances of zooplankton, greater than 500 μm in the middle estuary, which
were associated with higher concentrations of green algae and diatoms. Gradients in the
physical environment from upstream to downstream appear to have influenced the distribution
of both phytoplankton and zooplankton.
During the temporal sampling, zooplankton greater than 500 μm also appear to have collocated
at higher concentrations of phytoplankton. This distribution of plankton appears to have been
influenced by the depth of the density gradient. As the depth of the density gradient rose over
the evening the height of the deep chlorophyll maximum and peak in zooplankton abundance
rose as well. This movement of the zooplankton may also be related to the TVM mechanism.
9.1 Future Work and Recommendations
Some modifications to the group of equipment used could help to provide beneficial
information and improve quality of current data such as Combing the LOPC with a pressure
sensor and more accurate flow metre. This will provide better quality information on flow rate
and improve estimates of biomass, as well as improve spatial resolution of data that will
improve understanding of vertical changes at a location.
It is recommended in future work that there be an increase in both temporal and spatial
sampling. This would preferably occur during different seasons of the year, particularly when
different hydrodynamic conditions in the estuary occur, such as summer when flow is minimal
and middle estuary becomes quite stagnant. Ideally, the study of zooplankton could be
incorporated into the SRT's weekly sampling program, which would greatly improve
understanding of spatial trends in response to changes in physical gradients and show how
communities change in time.
Future work in the SRE should be used to determine a suitable value of R, used to calculate the
biomass of zooplankton particles. Making the R-value appropriate for the species composition
in the SRE will improve biomass estimation and therefore allow accurate calculation of the
63
slope of the NBSS. This will allow assessment of the zooplankton community at different trophic
levels giving a better indication of the health of zooplankton communities.
64
10 References
Abraham, ER 1998, 'The generation of plankton patchiness by turbulent stirring', Nature, vol. 391,
no. 6667, pp. 577-580.
Basu, BK & Pick, FR 1996, 'Factors regulating phytoplankton and zooplankton biomass in temperate
rivers', Limnology and Oceanography, vol. 41, no. 7, pp. 1572-1577.
BBE Moldaenke 2007, bbe FluoroProbe User Manual, version 1.9 E5, Kiel.
Beutler, M, Wiltshire, K, Meyer, B, Moldaenke, C, Lüring, C, Meyerhöfer, M, Hansen, UP & Dau, H
2002, 'A fluorometric method for the differentiation of algal populations in vivo and in situ',
Photosynthesis Research, vol. 72, no. 1, pp. 39-53.
Beutler, M, Wiltshire, KH, Arp, M, Kruse, J, Reineke, C, Moldaenke, C & Hansen, UP 2003, 'A reduced
model of the fluorescence from the cyanobacterial photosynthetic apparatus designed for
the in situ detection of cyanobacteria', Biochimica et Biophysica Acta (BBA) - Bioenergetics,
vol. 1604, no. 1, pp. 33-46.
Blanchot, J, Charpy, L & Borgne, R 1989, 'Size composition of particulate organic matter in the
lagoon of Tikehau atoll (Tuamotu archipelago)', Marine Biology, vol. 102, no. 3, pp. 329-339.
Brentnall, SJ, Richards, KJ, Brindley, J & Murphy, E 2003, 'Plankton patchiness and its effect on
larger-scale productivity', Journal of Plankton Research, no. 25, pp. 121-140.
Chan, T, Hamilton, D, Robson, B, Hodges, B & Dallimore, C 2002, 'Impacts of hydrological changes on
phytoplankton succession in the Swan River, Western Australia', Estuaries and Coasts, vol.
25, no. 6, pp. 1406-1415.
Chan, TU & Hamilton, DP 2001, 'Effect of freshwater flow on the succession and biomass of
phytoplankton in a seasonal estuary ', Marine and Freshwater Research, vol. 52, no. 6, pp.
869-884
Checkley, DM, Davis, RE, Herman, AW, Jackson, GA, Beanlands, B & Regier, LA 2008, 'Assessing
plankton and other particles in situ with the SOLOPC', Limnology and Oceanography, vol. 53,
no. 5, pp. 2123-2136.
Daly, KL & Smith, WO, Jr. 1993, 'Physical-Biological Interactions Influencing Marine Plankton
Production', Annual Review of Ecology and Systematics, vol. 24, pp. 555-585.
Deeley, DM & Paling, EI 1999, Assessing the ecological health of estuaries in Australia, Marine and
Freshwater Research Laboratory & Institute for Environmental Science Murdoch University,
Land and Water Resources Research and Development Corporation, Occasional Paper 17/99
(Urban Subprogram, Report No. 10)
Dickie, LM, Kerr, SR & Boudreau, PR 1987, 'Size-Dependent Processes Underlying Regularities in
Ecosystem Structure', Ecological Monographs, vol. 57, no. 3, pp. 233-250.
65
Fofonoff, NP & Millard, RC 1983, 'Algorithms for computation of fundamental properties of
seawater', Unesco Technical Papers in Marine Science, vol. 44.
Gaedke, U 1992, 'The Size Distribution of Plankton Biomass in a Large Lake and its Seasonal
Variability', Limnology and Oceanography, vol. 37, no. 6, pp. 1202-1220.
Griffin, SL & Rippingale, RJ 2001, 'Zooplankton grazing dynamics: top-down control of
phytoplankton and its relationship to an estuarine habitat', Hydrological Processes, vol. 15,
no. 13, pp. 2453-2464.
Hamilton, DP 2000, 'Record summer rainfall induced first recorded major cyanobacterial bloom in
Swan River', Journal of Environmental Engineerng Society, Institute of Engineers, vol. 1, no.
25.
Hamilton, DP, Chan, T, Robb, MS, Pattiaratchi, CB & Herzfeld, M 2001, 'The hydrology of the upper
Swan River Estuary with focus on an artificial destratification trial', Hydrological Processes,
vol. 15, no. 13, pp. 2465-2480.
Herman, AW 2009, LOPC Data Analayses - Standard LOPC, ODIM Brooke Ocean.
Herman, AW, Beanlands, B & Phillips, EF 2004, 'The next generation of Optical Plankton Counter:
the Laser-OPC', Journal of Plankton Research, vol. 26, no. 10, pp. 1135-1145.
Herman, AW, D.M. Checkley, J, Powell, JR & Jackson, GA unpublished, 'Separation and Estimation of
Zooplankton and Non-Living Transparent Particles Using Optical Measurements '.
Herman, AW & Harvey, M 2006, 'Application of normalized biomass size spectra to laser optical
plankton counter net intercomparisons of zooplankton distributions', Journal of Geophysical
Research-Oceans, vol. 111, no. C5, p. 9.
Hodgkin, EP 1998, 'The future of the estuaries of south-western Australia', Journal of the Royal
Society of Western Australia, vol. 81, pp. 225 - 228.
Horner Rosser, SMJ & Thompson, PA 2001, 'Phytoplankton of the Swan-Canning Estuary: a
comparison of nitrogen uptake by different bloom assemblages', Hydrological Processes,
vol. 15, no. 13, pp. 2579-2594.
Jones, GJ & Orr, PT 1994, 'Release and degradation of microcystin following algicide treatment of a
Microcystis aeruginosa bloom in a recreational lake, as determined by HPLC and protein
phosphatase inhibition assay', Water Research, vol. 28, no. 4, pp. 871-876.
Karandonis, A 2004, Light and phytoplankton interactions in a shallow, micro-tidal, south-west
Australian estuary. , The University of Western Australia.
Kirk, JTO 1977, 'Use of a quanta meter to measure attenuation and underwater reflectance of
photosynthetically active radiation in some inland and coastal south-eastern Australian
waters', Marine and Freshwater Research, vol. 28, no. 1, pp. 9-21.
66
Kostoglidis, A, Pattiaratchi, CB & Hamilton, DP 2005, 'CDOM and its contribution to the underwater
light climate of a shallow, microtidal estuary in south-western Australia', Estuarine, Coastal
and Shelf Science, vol. 63, no. 4, pp. 469-477.
Kurup, GR, Hamilton, DP & Patterson, JC 1998, 'Modelling the Effect of Seasonal Flow Variations on
the Position of Salt Wedge in a Microtidal Estuary', Estuarine, Coastal and Shelf Science, vol.
47, no. 2, pp. 191-208.
Lalli, C & Parsons, T 1997, Biological Oceanography: An Introduction, Second Edition, Elsevier,
Vancouver, Canada.
Levin, SA 1992, 'The problem of pattern and scale in ecology', Ecology, vol. 73, no. 6, pp. 1943-1967.
O'Callaghan, J, Pattiaratchi, C & Hamilton, D 2007, 'The response of circulation and salinity in a
micro-tidal estuary to sub-tidal oscillations in coastal sea surface elevation', Continental
Shelf Research, vol. 27, no. 14, pp. 1947-1965.
ODIM Brooke Ocean, Laser Optical Plankton Counter, ODIM Brooke Ocean. Available from:
http://www.brooke-ocean.com/profile.html.
ODIM Brooke Ocean 2008a, Laboratory Circulator Operation and Maintenance Manual, Department
of Fisheries and Oceans, Ocean Sciences Division, Bedford Ocean Institute, Dartmouth, Nova
Scotia.
ODIM Brooke Ocean 2008b, Laser Optical Plankton Counter: Operation and Maintenance Manual,
Department of Fisheries and Oceans, Ocean Sciences Division, Bedford Ocean Institute,
Dartmouth, Nova Scotia.
Orr, PT, Jones, GJ & Douglas, GB 2004, 'Response of cultured Microcystis aeruginosa from the Swan
River, Australia, to elevated salt concentration and consequences for bloom and toxin
management in estuaries', Marine and Freshwater Research, vol. 55, no. 3, pp. 277-283.
Pinel-Alloul, B & Ghadouani, A 2007, 'Spatial heterogeneity of planktonic microorganisms in aquatic
systems ', in The spatial distrbution of microbes in the environment, eds RB Franklin & AL
Mills, Springer, Dordrecht, The Netherlands.
Pinel-Alloul, P 1995, 'Spatial heterogeneity as a multiscale characteristic of zooplankton community',
Hydrobiologia, vol. 300-301, no. 1, pp. 17-42.
Ray, S, Berec, L, Straskraba, M & Jørgensen, SE 2001, 'Optimization of exergy and implications of
body sizes of phytoplankton and zooplankton in an aquatic ecosystem model', Ecological
Modelling, vol. 140, no. 3, pp. 219-234.
Roman, M, Gauzens, A, Rhinehart, W & White, J 1993, 'Effects of low oxygen waters on Chesapeake
Bay zooplankton', Limnology and Oceanography, vol. 38, no. 8, pp. 1603 - 1614.
Schultes, S & Lopes, RM 2009, 'Laser Optical Plankton Counter and Zooscan intercomparison in
tropical and subtropical marine ecosystems', Limnology and Oceanography-Methods, vol. 7,
pp. 771-784.
67
Stephens, R & Imberger, J 1996, 'Dynamics of the Swan River Estuary: The seasonal variability',
Marine and Freshwater Research, vol. 47, no. 3, pp. 517-529.
Swan River Trust 2008, Swan Canning Research and Innovation Program (SCRIP) Swan River Trust,
East Perth, Western Australia.
Swan River Trust 2009, Health Rivers Action Plan : An Action Plan to improve water quality in the
Swan Canning river system, Swan River Trust, East Perth, Western Australia.
Thompson, PA 1998, 'Spatial and Temporal Patterns of Factors Influencing Phytoplankton in a Salt
Wedge Estuary, The Swan River, Western Australia', Estuaries, vol. 21, no. 4B, pp. 801 - 817.
Thompson, PA 2001, 'Temporal variability of phytoplankton in a salt wedge estuary, the Swan-
Canning Estuary, Western Australia', Hydrological Processes, vol. 15, no. 13, pp. 2617-2630.
Thompson, PA & Hosja, W 1996, 'Nutrient limitation of phytoplankton in the upper Swan River
estuary, Western Australia', Marine and Freshwater Research, vol. 47, no. 4, pp. 659-667.
Thomson, JM 1946, 'New Crustacea From the Swan River Estuary', Journal and Proceedings of the
Royal Society of Western Australia, vol. 30, pp. 35 - 53.
Thorp, JH, Black, AR, Haag, KH & Wehr, JD 1994, 'Zooplankton Assemblages in the Ohio River -
Seasonal, Tributary, and Navigation Dam Effects', Canadian Journal of Fisheries and Aquatic
Sciences, vol. 51, no. 7, pp. 1634-1643.
Twiss, MR & MacLeod, IR 2008, 'Phytoplankton community assessment in eight Lake Ontario
tributaries made using fluorimetric methods', Aquatic Ecosystem Health & Management,
vol. 11, no. 4, pp. 422-431.
Twomey, L & John, J 2001, 'Effects of rainfall and salt-wedge movement on phytoplankton
succession in the Swan-Canning Estuary, Western Australia', Hydrological Processes, vol. 15,
no. 13, pp. 2655-2669.
Ueda, H, Kuwatani, M & Suzuki, KW 2010, 'Tidal vertical migration of two estuarine copepods:
naupliar migration and position-dependent migration', Journal of Plankton Research, vol.
32, no. 11, pp. 1557-1572.
Vannote, RL, Minshall, GW, Cummins, KW, Sedell, JR & Cushing, CE 1980, 'River Continuum
Concept', Canadian Journal of Fisheries and Aquatic Sciences, vol. 37, no. 1, pp. 130-137.
Yurista, PM, Kelly, JR & Miller, S 2005, 'Evaluation of optically acquired zooplankton size-spectrum
data as a potential tool for assessment of condition in the Great Lakes.', Environmental
Management, vol. 35, no. 1, pp. 34 - 44.
Zhou, M & Huntley, M 1997 'Population dynamics theory of plankton based on biomass size
spectra', Marine Ecology Progress Series, vol. 159, pp. 61 - 73.
68
69
11 Appendices
11.1 Appendix 1 – Field Work Plan Including JSEA
70
UWA FIELD WORK PLAN - The influence of physical processes on plankton distribution in the Swan River Estuary.
This form may contain confidential information and must be kept secure Field Work Supervisor/ Principal Investigator
Anas Ghadouani
Field Work Leader/ Dive Supervisor
Gemma Bertrand
Unit of study/Research/Project etc
Environmental Engineering Final Year Thesis Fieldwork
Field work description or title This field work endeavors to investigate the temporal distribution of plankton in the Swan River Estuary using high resolution equipment including a Laser Optical Plankton Counter (zooplankton), FluoroProbe (phytoplankton), CTD (conductivity, temperature, depth, oxygen, fluorescence) a PAR sensor (photosynthetic photon flux or irradiation), biological and physical observations from the field will enable us to quantify variations of plankton size structure distribution in terms of biological and physical forcing at a range of scales.
Dates of field work 18/8/2010-26/8/2010 is the time window in which the one day,
24 hour sampling will be conducted.
Transport arrangements UWA vehicle will be used to tow boat to boat ramp along the Swan River. The boat we will be used to sample at a mooring in freshwater bay and to pick up and return people to a jetty.
What will be the contact arrangement with the University or other reputable contact? (ie shore contact)
Anas Ghadouani will be the University shore contacts. Contact will only be made if an incident occurs since all field work will be conducted on the Swan River in the metropolitan area of Perth.
What shall University staff/reputable contact do if no contact is made?
If concerned, contact should be attempted to the numbers listed below.
DETAILS OF PARTICIPANTS
NAME
STATUS Researcher, student, volunteer
PARTICIPANT’S FORM ATTACHED? (Mandatory) (Y/N)
VOLUNTEER’S INSURANCE FORM ATTACHED?
Dianne Krikke Staff (Employee) In office N/A Gemma Bertrand Student Y N/A Dani Barrington Post Grad – Student
(Employee) Y N/A
Conor Mines Post Grad - Student(Employee)
Y N/A
Alexandra Young Student Y Y Liah Coggins Student (Employee) Y N/A Shian Min Liau Student (Employee) Y N/A
ITINERARY DETAILS
DATE/ TIMES LOCATION ACCOMMODATION CONTACT DETAILS 18/8/2010-26/8/2010 is the time window in which the one day, 24 hour sampling will be conducted. Intending to sample on the 18
th to 19
th of
August.
Swan River, Fresh Water Bay at a Swan River Trust Mooring just north of
N/A
Gemma Bertrand Dani Barrington Conor Mines Liah Coggins Alexandra Young
ITEMS THAT WILL BE COMPLETED PRIOR TO THE FIELD WORK
Tick as appropriate
Participants briefed on details of proposed field work; relevant safety policies, procedures and expected conduct whilst on the field work
�
Field work information sheet provided to all participants �
All equipment, vehicles and tools will be checked for safety compliance prior to field work commencing
�
I have made the necessary provisions for emergency situations such as the appropriate level of first aid, emergency contact telephone numbers; e.g., air and sea rescue, police rangers etc
�
I have checked with participants whether they have any medical conditions that should be disclosed
�
I have checked that appropriate licenses, permits and agreements with land owners etc have been obtained and are up to date for the use of specialized equipment and/or plant
�
Field Work Procedures in Rural and Remote Areas
Job Safety Environmental Analysis (JSEA) Part (A) JSEA No:1
Revision No: 1 Name of person preparing JSEA. Gemma Bertrand Signature: Date:
Date issued: 29/06/2010 Approval: Head of School/ Director of Centre: Charithra Pattiarachi Signature: Date:
Job Description: Sampling biological, physical and chemical parameters in the Swan River using specially designed marine probes and machines. The Scorpion a 5.7m boat is being used to reach the sites required and a Davit Arm and winch will be used to lower the combined frame of the LOPC, Data Logger and FluoroProbe into the water together. The CTD probe will be lowered over the side of the boat individually. Water samples will be collected for calibration purposes.
Location: Swan River between Blackwall Reach and Success Hill.
PERSONAL QUALIFICATIONS AND EXPERIENCE: Recreational Skippers Ticket, over 10 years yachting experience, fieldwork participant of 4 previous fieldtrips of similar nature.
PLANT/EQUIPMENT: Laser Optical Plankton Counter, Data Logger, FluoroProbe, CTD, Electrical Winch, LiCor Light sensor.
REFERENCES: none required.
Determine the Consequence (C )
Risk Matrix 5 4 3 2 1
People Local treatment with short recovery
- minor short term health effects.
Medical treatment required or short term acute health effects.
Lost Time Injury (off work recovery
required) or short / medium term health
issues.
Extensive injuries or chronic health issues. Single fatality or permanent disability.
Environment Onsite release, containable with
minimal damage. Localised impact
on energy usage.
Major onsite release with some damage, no
offsite damage. Numerous and/or
widespread but small scale impacts on
energy and waste. Remediation in terms of
days..
Offsite release, no significant
environmental damage. Remediation in
terms of weeks.
Major offsite release, short to medium term
environmental damage. Remediation in terms of
months.
Major offsite release, long term environmental
damage. Remediation in terms of years.
Community Workforce concern Local community concern Regional concern Widespread reputation loss to single business
unit, widespread community outcry.
Widespread reputation loss to more than one
business unit, extreme community outcry
nationally.
Dete
rm
ine t
he
Lik
eli
hoo
d (
L)
A Almost certain
Medium High Very High Very High Very High
B Probable Medium Medium High Very High Very High
C Possible Low Medium Medium High Very High
D Unlikely Low Low Medium Medium High
E Very unlikely
Low Low Low Medium Medium
Step 1 Determine the severity of the consequences
Step 2 Determine the likelihood that the hazard will cause an incident
Step 3 Analyse the TRUE RISK (Very High, High, Medium, Low
Step 4 Develop control measures, using hierarchy of control
Step 5 Determine RESIDUAL RISK (Steps 1-3 above)
Note: Significant risks are those determined as being Very High or High
Risk Levels (R) Actions
Very High Very High: Risks are intolerable for OHS. Do not commence or continue at this risk level for OHS risks. Implement control measures to ensure the risk level is reduced. Communicate and consult thoroughly on non-HSEC risks to
ensure the positive benefits outweigh the negative impacts.
High High risk: Risk is undesirable. Verify, and where possible quantify, the accuracy and certainty for the existing risk level. Implement control measures to ensure risk level is reduced to or is confirmed to be As Low As Reasonably
Practicable (ALARP). Operation at this level requires management approval.
Medium Medium risk: Are only tolerated if examination proves them to be ALARP. Implement management plans to prevent the occurrence and monitor for changes. Reduce to Low Risk if the benefits outweigh the cost.
Low Low risk: Are acceptable. Review at next review interval.
Field Work Procedures in Rural and Remote Areas
Job Safety Environmental Analysis (JSEA) Part (B)
JSEA No: 1
Stage 1 Break the activity into steps. Each of the stage should be logical and describe the step in simple terms.
Stage 2 Identify the hazards associated with each step. Consider uncontrolled sources such as Gravity, Electrical, Mechanical, Manual Handling, Pressure, etc.
Stage 3 Using the risk ranking as defined in Part A. Rank the Consequence and Likelihood of the hazard becoming actual. C =Consequence: L =Likelihood: R = Risk.
Stage 4 Develop controls necessary to manage the hazards. Consider the Hierarchy of Controls starting at Elimination to Personnel Protective Equipment.
Stage 5 Using the risk rankling as defined in Part A Re-rank the Consequence and Likelihood to determine if the controls have reduced the risk to an acceptable level.
Stage 6 Nominate the person responsible for managing / working to the controls as nominated
S3: RISK
RATING S5:RISK RATING
Stage 1 Job Step
Stage 2 EHS Hazards
C L R Stage 4
Solution / Control Measures C L R
Stage 6 Res: person
Travel to and from launching facilities Traffic Accident / Incident 3 C M Follow safe driving practices and ensure competent drivers. Ensure that driver is not overtired.
5 D L Car Driver
Launching and retrieving boat on boat ramp.
Slipping on boat ramp, trouble with boat winch (crushed fingers).
4 C M Launch boat s slowly and ensure firm footing and no rushing around on ramp. Keep clear of winch.
4 E L Individuals
People getting on and off boat Slipping or falling into water/boat. 4 C M Ensure that boat is secure before boarding or departing and help each other to get on/off boat.
5 D L Participants
Departing and coming alongside Jetty Crushed hands/Limbs 4 C M Ensure that approach to jetty is slow and at usual 45 degrees. Follow skippers directions when securing or undoing ropes to jetty.
5 D L Skipper and participants
Travelling between jetty and between sampling stations
Traffic Accident / Incident 4 D L Follow required speed limitations on the River and follow navigation signals. Be cautious around other vessels.
5 D L Skipper : Dani Barrington and Dianne Krikke
Lowering equipment into the water with ropes and or winch and bringing equipment back on board.
Rope burns to hands or trouble moving/holding equipment. Potential foot/hand damage.
4 C M Ensure that gloves are provided for those handling ropes on the winch and that everyone is wearing enclosed shoes or steel cap boots. Two people operating the davit arm and retrieving devices.
5 C L Team Leader: Gemma Bertrand and Participants
Loading and unloading boat with equipment.
Back damage from living heavy equipment
4 B M Ensure that heavy equipment is lifted by more than one person and where possible use of a small trolley will be made available.
5 D L Individuals and Gemma Bertrand to ensure trolley available
Exposure to elements on boat. Mild hypothermia, illness from being cold.
5 B M Ensure all participants have adequate clothes, rain jackets, provide warm drink and food.
5 D L Participants and Gemma Bertrand
Rough weather/waves on boat Objects moving around, generally unsafe boating weather
4 C M If weather gets too rough or forecast is extreme, cancel field work, return to uni.
5 D L Skipper: Dani Barrington and Dianne Krikke.
Field Work Procedures in Rural and Remote Areas
4. Boat details - University of Western Australia boat Boat name: Scorpion Department for Planning and Infrastructure registration: C948 Boat size and type: 6.7m Boat trailer and registration: 1TKH336 Engines size and capacity: Main: 115hp Mercury, Auxiliary: 30hp Mercury Marine radios and call sign: 27Mhz radio (ch 88 safety), call sign VNW 3548 Fuel capacity: 90L Echo sounder: Garmin Fish Finder 250c GPS / plotter: Lowrance Global Nav 310 GPS Survey Class: Survey Exempt Licensed carrying capacity: 5 people Other equipment: Flares, life ring, fire extinguisher, torch, life jackets, fire extinguisher, dual batteries, hand held air horn, first aid kit Owner and contact#: UWA (contact UDBSO Alex Grochowski: 0403 761 333)
5. Boat and Safety Equipment: The boat has all the required safety equipment (see above). Prior to the first day of field work, all divers will be made familiar with:
• boat safety equipment and its location on the vessel
• boat operation
• marine radio operation
• first aid kit
• sampling procedures
Radio Contacts for Sea rescue State Wide.
Marine 27MHz Band: 27.90 & 27.88
Marine VHF: Ch 16 & Ch 73
6. Emergency Evacuation Plan EMERGENCY CONTACT AND RESPONSE INFORMATION
Fremantle Marine Sea Search and Rescue 9335 1332
Port Authority N/A
Ambulance 000 / 112
Nearest hospital Sir Charles Gardener, Nedlands or Royal Perth Hospital, Perth.
Nearest hyperbaric N/A
Mobile phone N/A
Emergency Services 000 / 112
DES/DAN N/A
Marine Radio Channels Channel 88 on Scorpions Radio for Emergency
Emergency Procedure - Remember
1. Don’t Panic, slow down and think clearly 2. Do not endanger yourself or others 3. Provide First Aid to patient, assessing ABC’s, call for help if possible 4. If at sea, return patient to shore, as soon as possible 5. Notify the emergency services (Ambulance, Police and Sea Rescue) immediately
using VHF (Ch. 16) or 27 MHz radios (Ch. 88), or phone (000/112) 6. Notify the emergency services (Ambulance and Police) immediately
→ 000 (landline) or 112 (mobile) Follow the Emergency Services instructions
7. Evacuate patient, to closest hospital (see above). 8. Keep record of patients diving details.
Field Work Procedures in Rural and Remote Areas
7. Relevant Sea Rescue Groups
Fremantle Sea Rescue Fremantle Fishing Boat Harbour Call sign – VN6DI VHF: channel 73 (or 16 emergency) 27Mhz: channel 90 (or 88 emergency) Telephone: 9335 1332 (24 hours)
A full list of Sea Rescue groups is appended to this document Contacts Centre for Marine Futures personnel must be contacted ASAP if any situation occurs that requires emergency procedures. Contacts are, in prioritized order: Eg:
o Jessica Meeuwig: 6488 1464
o Alexander Grochowski 6488 7825 (office) / 6488 2835 (lab)
• SWAN RIVER TRUST contact: Chief Scientist- Jeff Cosgrove 08 9278 0955
PEOPLE RESPONSIBLE FOR SUBMISSION AND APPROVAL NAME SIGNATURE DATE
Field Work Supervisor Anas Ghadouani
Field Work Leader Gemma Bertrand
UDBSO Alex Grochowski
Head of School/Administrative Unit Chari Pattiaratchi Head of SESE Based upon the information in the above Field Work Plan I:- □ Approve □ Do not approve □ Grant conditional approval
Conditions if relevant
NOTE:-
• A copy of this Field Work Plan and associated Field Work participant forms must be left with the School/Unit office.
• A copy must also be always availably in the field in case of emergency.
• A copy shall be forwarded to the Dean/Senior Manager if the Head of School/Administrative Unit deems that the proposed Field Work involves potential hazards that are complex or have a higher than normal level of risk.
• Volunteer insurance details are to be retained by the School/Unit office.
71
11.2 Appendix 2 – Swan River Trust - Physical-Chemical Profiles
72
__________________________________________________________________________________________ Page 1 of 2
Environmental Monitoring and Reporting Swan River Estuary ~ Weekly profile
by
Water Science Branch, Department of Water
Date: Monday 5th July 2010 Weather & tide conditions: Conditions were dry with 0-70% cloud cover and east to north easterly winds up to 7 knots. The tide was ebbing becoming stationary during the period of sampling. Perth recorded 0.2 mm rainfall during the week prior to sampling (Bureau of Meteorology). Oxygenation: The upper Swan Guildford oxygenation plant was in operation for the week prior to sampling. Lower Swan/Canning Estuary (BLA to NAR): The lower estuary was saline and mostly well oxygenated throughout with the exception of moderately oxygenated bottom water at HEA and NAR. Water temperature ranged from 12.1 to 16.8°C. Middle Swan Estuary (NIL to MAY): The middle Swan Estuary had well oxygenated surface water overlying moderately (NIL) to hypoxic (STJ and MAY) bottom waters with brackish surface water overlying saline bottom water. Water temperature ranged from 13.7 to 16°C. Upper Swan Estuary (RON to POL): The upper Swan Estuary was mostly brackish throughout with the exception of saline bottom water at RON to KMO. Surface water was well oxygenated overlying hypoxic and near anoxic bottom water. Water temperature ranged from 9.3 to 16.4°C.
Definitions: Salinity – fresh <5ppt, brackish 5-25ppt, saline 25-35ppt, hypersaline >35ppt Dissolved oxygen – supersaturated >100% saturation, well oxygenated 100-80%, moderately oxygenated 80-60%, poorly oxygenated 60-40% saturation; hypoxic <40% saturation, near anoxic <10% saturation
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-15
-10
-5
0
0 10 20 30Salinity (ppt)
-15
-10
-5
0
0 5 10 15Dissolved Oxygen (mg/L)
-15
-10
-5
0
0 50 100 150 200Dissolved Oxygen (%Sat'n)
0 5 10 15 20 25 30 35 40 45 50
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-5
0
10 15 20 25 30Temperature (°C)
Swan River Estuary - Physical-chemical Profile - 5th July 2010
Distance from entrance (km)
Dep
th (m
)
*Data for sites FP1 (Harbour entrance) and FP7 (Fremantle Bridge) are supplied courtesy of the Fremantle Port Authority
FP1* FP7* BLA ARM HEA NAR NIL STJ MAY RON KIN SUC MEA MUL WMP CAV REG MSBJBC POL
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Environmental Monitoring and Reporting Swan River Estuary ~ Weekly profile
by
Water Science Branch, Department of Water
Date: Monday 16th August 2010 Weather & tide conditions: Conditions were fine with 80 to 100% cloud cover and an easterly to north easterly wind up to 8 knots. The tide was ebbing and the river flowing during the period of sampling. Perth recorded 41.4 mm rainfall during the week prior to sampling (Bureau of Meteorology). Oxygenation: The upper Swan Guildford oxygenation plant was not in operation during the week prior to sampling. Lower Swan/Canning Estuary (FP1 to NAR): The lower estuary was saline throughout, with the exception of brackish surface water at NAR. Surface water was well oxygenated throughout and bottom water ranged from well oxygenated in the lower estuary to poorly oxygenated at HEA and NAR. Water temperature ranged from 15.2 to 16.6°C. Middle Swan Estuary (NIL to MAY): The middle estuary was stratified with brackish, well to moderately oxygenated surface water and saline, hypoxic bottom water. Water temperature ranged from 15 to 17.4°C. Upper Swan Estuary (RON to POL): The upper estuary from RON to WBRP was strongly stratified with fresh or slightly brackish, moderately oxygenated surface water overlying brackish, hypoxic to near anoxic bottom water. Further upstream, from CAV to POL the water column was fresh and well oxygenated throughout. Water temperature ranged from 12.9 to 16.7°C.
Definitions: Salinity – fresh <5ppt, brackish 5-25ppt, saline 25-35ppt, hypersaline >35ppt Dissolved oxygen – supersaturated >100% saturation, well oxygenated 100-80%, moderately oxygenated 80-60%, poorly oxygenated 60-40% saturation; hypoxic <40% saturation, near anoxic <10% saturation
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-15
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-5
0
0 10 20 30Salinity (ppt)
-15
-10
-5
0
0 5 10 15Dissolved Oxygen (mg/L)
-15
-10
-5
0
0 50 100 150 200Dissolved Oxygen (%Sat'n)
0 5 10 15 20 25 30 35 40 45 50
-15
-10
-5
0
10 15 20 25 30Temperature (°C)
Swan River Estuary - Physical-chemical Profile - 16th August 2010
Distance from entrance (km)
Dep
th (m
)
*Data for sites FP1 (Harbour entrance) and FP7 (Fremantle Bridge) are supplied courtesy of the Fremantle Port Authority
FP1* FP7* BLA ARM HEA NAR NIL STJ MAY RON KIN SUC MEA MUL WMP CAV REG MSBJBC POL
73
11.3 Appendix 3 – LOPC results from spatial fieldwork
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78
79
80
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11.4 Appendix 4 – LOPC results from temporal fieldwork
Field time indicates the time of the LOPC cast, Lab time indicates time of the integrated
plankton tow sample for comparison.
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85
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11.5 Appendix 5 – Dominant Phytoplankton Species
Phytoplankton Identification -Swan River Trust
Temporal Sampling
Station # Station Name Dominant Species Harmful Species
1 Blackwall Reach Flagellated chloro/prasinophytes, Plagioselmis, Chaetoceros spp./ Thalassionema.
Fibrocapsa @ 3/mL; Heterosigma akashiwo @ 7/mL.
2 Armstrong Spit Skelotonema Costatum most dominant. Small Cryptophytes, Plagioselmis
Fibrocapsa @ 3/mL; Heterosigma akashiwo @ 10/mL.
Spatial Sampling
Station # Station Name Most Dominant Group
Other notable Groups and comment
1 Blackwall Reach Skeletonema costatum; Plagioselmis; small cryptophytes.
GKC @ 10/mL; Heterosigma akashiwo @ 51/mL; haptophyte @ 10/mL.
2 Armstrong Spit Skeletonema costatum; Plagioselmis; small cryptophytes.
GKC @ 6/mL; Heterosigma akashiwo @ 13/mL.
5 Narrows Bridge Flagellated chlorophytes; Skeletonema costatum; small cryptophytes.
GKC @ 3/mL; Heterosigma akashiwo @ 10/mL; Fibrocapsa @ 17/mL.
7 Nile Street Passive pico-like chlorophytes; flagellated chloro/prasinophytes; small cryptophytes.
Dinophysis acuminata @ 5/mL; Fibrocapsa @ 275/mL; GKC @ 165/mL; Heterosigma akashiwo @ 18/mL.
8 St John of God Heterocapsa; passive pico-like chlorophytes; small cryptophytes.
Dinophysis acuminata @ 15/mL; Fibrocapsa @ 126/mL; GKC @ 25/mL.
9 Maylands SP Passive pico-like chlorophytes; small cryptophytes; Heterocapsa.
Fibrocapsa @ 126/mL; Dinophysis acuminata @ 20/mL.
10
Ron Courtney
Island Passive pico-like chlorophytes; small cryptophytes; Apedinella.
GKC @ 51/mL; Dinophysis acuminata @ 21/mL.
88
11.6 Appendix 6 – Dominant Zooplankton Species
Zooplankton Identification
Temporal Sampling
Sample # Time Most Dominant Group Other notable groups and
comments
1 8:45 AM Nauplii, Tintinnid, calanoid
2 1:00 PM Tintinnid, nauplii and calanoid fish larvae, hairy worm
3 7:00 PM Nauplii, Tintinnid, calanoid hairy worm, fish larvae
4 4:00 AM Nauplii, Tintinnid, calanoid
Zooplankton Identification
Spatial Sampling
Station # Most Dominant Group Other notable groups and
comments
1 Calanoid, tintinnid, nauplii
2 Tintinnid, nauplii, calanoid
3 Tintinnid, ceratium
4 Tintinnid, ceratium calanoid
5 Tintinnid, ceratium, nauplii Rotifer, few calanoid
6 Tintinnid, ceratium, nauplii Rotifer, lack of calanoid
7 Tintinnid, nauplii, ceratium Not much in sample
8 Tintinnid, nauplii, rotifers calanoid
9 Tintinnid, rotifer Nauplii
10 Tintinnid, nauplii Few calanoid
11 Tintinnid, rotifers, nauplii No calanoid
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