Influence of oceanographic conditions on coastal zooplankton assemblages at three IMOS National
Reference Stations in Western Australia
Erin McCosker
This thesis is presented for the degree of Master of Environmental Science of Murdoch University
November 2016
i
Declaration
I declare that this thesis is my own account of my research and contains as as its main
content, work which has not previously been submitted for a degree at any tertiary
education institution.
Erin McCosker
ii
iii
Abstract
Despite the importance of zooplankton in providing vital information about ocean-climate
forcing in marine systems, knowledge of the planktonic zoogeography of the south-east
Indian Ocean is limited. The dominant oceanographic feature in this region is the
anomalous poleward flowing Leeuwin Current, which transports warm, tropical waters
south along the Western Australian coast, and follows a trajectory that crosses thirteen
degrees of latitude, from the tropical north to the temperate south. This study examined two
years of data collected by Australia’s Integrated Marine Observing System at three unique
locations in Western Australian coastal ocean waters between 22°S and 34°S. Spatial and
temporal patterns in zooplankton abundance, composition and diversity were investigated,
with a focus on copepods, and differences in assemblage structure were related to
oceanographic conditions. Clear distinctions in copepod assemblages were observed,
becoming weaker in winter due to enhanced connectivity driven by alongshore and cross-
shelf transport of species in the Leeuwin Current. Both physical and biogeochemical factors
were revealed to be significant in shaping copepod assemblages, with seawater density, an
indication of water mass, exerting the greatest influence. The results suggest that both
broad scale latitudinal gradients and mesoscale events contribute to variation in
dissimilarities of zooplankton assemblages in these waters. This study provides the first
detailed comparison of zooplankton assemblages in the northwest, southwest and southern
coastal waters of Western Australia, and enhances understanding of the processes
influencing zooplankton distribution and structure.
iv
Acknowledgements
I must extend my sincerest thanks to my primary supervisor, Prof Lynnath Beckley, for her
advice, patience and enthusiasm throughout the year, and for coercing the powers that be
into allowing me to act as a demonstrator at the Ecology Field Camp at Jurien Bay in 2016,
which was a valuable learning experience in many ways, but especially in methods of
zooplankton sampling and identification. What I have achieved this year, being on the
opposite side of the country to the university, has been very much helped by Lynnath. My
thanks also go to my co-supervisor, Claire Davies, at CSIRO Oceans and Atmosphere, for
her support, plankton expertise and valuable input into this research project. Claire was
also a great source of information and guidance. I am also grateful for Dr Alicia Sutton’s
assistance in understanding and applying various techniques and tools for analysis in
PRIMER, some of which are presented in this thesis.
My family and partner also get a mention for their support and patience over the past two
years. Finally, thanks also go to my colleagues for allowing me to work flexibly around my
Masters program of study.
The data used in this study were sourced from the Integrated Marine Observing System
(IMOS). IMOS is supported by the Australian Government through the National
Collaborative Research Infrastructure Strategy and the Super Science Initiative.
v
Table of Contents
1. Introduction ................................................................................................................... 1
2. Materials and methods ................................................................................................ 5
2.1 Study sites .......................................................................................................... 5
2.2 Data sources and sampling methods ................................................................. 7
2.2.1 Mooring-based oceanographic data ....................................................... 7
2.2.2 Physical and chemical data from vessel-based sampling ..................... 7
2.2.3 Other oceanographic data ...................................................................... 8
2.2.4 Biological data ........................................................................................ 8
2.3 Statistical analyses ............................................................................................. 9
3. Results ......................................................................................................................... 12
3.1 Oceanographic conditions at the three NRS ................................................... 12
3.1.1 Physical oceanography ........................................................................ 12
3.1.2 Biogeochemical oceanography ............................................................ 17
3.1.3 Principal component analysis of environmental variables ................... 20
3.2 Zooplankton at the three NRS .......................................................................... 22
3.2.1 Zooplankton abundance and biomass ................................................. 22
3.2.2 Zooplankton composition ...................................................................... 24
3.2.3 Taxonomic distinctness of copepod assemblages .............................. 28
3.3 Comparison of copepod assemblages ............................................................. 29
3.3.1 Characteristic and discriminating copepod species ............................. 31
3.4 Influence of oceanographic conditions on the copepod assemblages ............ 34
4. Discussion .................................................................................................................. 36
4.1 Oceanographic characteristics at the three NRS ............................................. 36
4.2 Zooplankton abundance, biomass and composition at the three NRS ........... 37
4.3 Dissimilarities in copepod assemblages at the three NRS .............................. 39
4.4 Oceanographic factors explaining the variability in copepod assemblage structure at the three NRS ................................................................................ 41
4.5 Limitations and future research ........................................................................ 43
5. Conclusion .................................................................................................................. 45
6. References .................................................................................................................. 46
1
1. Introduction
Zooplankton, as dominant primary consumers in marine systems, play an essential
role in the transfer of energy, and in the recycling of nutrients and carbon in these systems
(Longhurst, 1985; Beaugrand, 2005; Hays et al., 2005, Suthers and Rissik, 2009). As they
can have short generation times and complex life cycles, and are largely at the mercy of
ocean currents, zooplankton are sensitive to relatively small changes in ocean climate and
environmental forcing, making them useful indicators of change in marine ecosystems
(Richardson, 2008; Suthers and Rissik, 2009; Gonzalez-Gil et al., 2015). Copepods, due to
their diversity and dominance within the zooplankton, are particularly useful to understand
oceanographic influences on patterns of distribution and composition in mesozooplankton
assemblages (Longhurst, 1985; Hays et al., 2005, Suthers and Rissik, 2009; Dias et al.,
2015).
Numerous studies have revealed that patterns of zooplankton distribution,
abundance, biomass and diversity reflect ocean-climate processes at various spatial and
temporal scales, from global warming to coastal upwelling (e.g., Verheye and Richardson,
1998; Mackas et al., 2001; Beaugrand et al., 2002b; Muhling and Beckley, 2007;
Richardson 2008; Mackas et al., 2012a; Gonzalez-Gil et al., 2015). The association of
patterns in zooplankton distribution and productivity to ocean currents (Beaugrand et al.,
2002a), and boundary currents, such as the Benguela (Verheye et al., 2016), Humboldt
(Ayon et al., 2008) and East Australian Current (EAC) (Booth et al., 2007; Johnson et al.,
2011; Kelly et al., 2016) have been observed. Relationships between zooplankton and
large scale weather systems, such as El Niño Southern Oscillation (ENSO), have been
identified (Fromentin and Planque, 1996; Ayon et al., 2008), as have biogeographical shifts
in zooplankton, for example, in the North Sea as a consequence of global warming
(Beaugrand et al., 2002b). As the impacts of environmental influences are not uniform
across the entire pelagic ecosystem (Gaughan et al., 2009), the abundance and
composition of zooplankton assemblages are typically dynamic.
Understanding long term trends and shifts in marine zooplankton provides
information about changes in ocean-climate forcing (Hays et al., 2005), the importance of
which is demonstrated by the more than thirty countries that hold multi-decadal
zooplankton time-series. Long-term monitoring programs include the Continuous Plankton
Recorder (CPR) surveys, which operate in the Atlantic, Pacific and Southern oceans and in
Australian and South African waters (Richardson et al., 2006), the California Cooperative
2
Oceanic Fisheries Investigations (CalCOFI) program (Edwards et al., 2010) and the Hawaii
Ocean Time-series program (Karl and Lukas, 1996). These programs build on the
knowledge base provided by the early significant interdisciplinary ocean surveys, such as
the Southern Ocean Discovery Investigations surveys and the International Indian Ocean
Expedition (IIOE).
In Australia, the Integrated Marine Observing System (IMOS) is the national
observation system responsible for long term, systematic monitoring of ocean variability
and the physical and biological responses in the marine environment (Proctor et al., 2010;
Lynch et al., 2011; Lynch et al., 2014). The IMOS infrastructure includes seven (previously
nine) National Reference Stations (NRS) located in coastal ocean waters and distributed
across Australia’s various bioregions. The relatively recent establishment (2009) of a
comprehensive zooplankton monitoring program undertaken at the NRS by IMOS, means
that in comparison to other countries, Australia lacks a continuous long-term zooplankton
time series. Consequently, comparatively less is known about the zooplankton of coastal
Australian waters (Strzelecki et al, 2007; Muhling et al., 2008).
Australia’s oceanography is unique in having two poleward flowing currents. The
EAC flows south along the eastern coast of Australia, while the western coast is
characterised by the southward flowing Leeuwin Current (LC). The LC originates off the
North West (NW) Shelf off Western Australia (WA) and transports warm, lower salinity,
tropical water south, mostly along the shelf break, and around Cape Leeuwin at 35⁰S,
before turning eastward to flow along the southern coast towards Tasmania, a distance of
approximately 5,500 km (Cresswell and Golding, 1980; Pearce, 1991; Ridgeway and
Condie, 2004; Cresswell and Domingues, 2009; Weller et al., 2011). The LC’s poleward
flow is driven by geostrophic transport from the Indonesian Throughflow that creates an
alongshore height gradient strong enough to overcome equatorward wind stress and
dampen Ekman driven upwelling (Cresswell and Golding, 1980; Cresswell, 1991). Unlike
other eastern boundary currents, the LC is downwelling favourable, resulting in an
oligotrophic, low productivity region in the south-east Indian Ocean (Pearce, 1991; Hanson
et al., 2005; Twomey et al., 2007; Thompson et al., 2011).
The LC varies in intensity, temperature and salinity, and its profile is gradually
modified along its southward trajectory (Waite et al., 2007; Weller et al., 2011), creating a
longshore gradient in oceanographic conditions across 13 degrees of latitude. The LC flow
is at a maximum in the austral autumn-winter (Cresswell, 1991; Pearce and Pattiaratchi,
3
1999; Ridgeway and Godfrey, 2015). In summer, when the LC is weaker, wind-driven
cooler, coastal currents, such as the Ningaloo Current (22°S - 24°S), and the Capes
Current (34⁰S - 35⁰S), have been observed to flow northward in surface waters (Gersbach
et al., 1999; Pearce and Pattiaratchi, 1999; Woo et al., 2006; Woo and Pattiaratchi, 2008).
Inter-annual variation is linked to the ENSO cycle, with stronger LC flow occurring during
La Niña years (Pearce and Phillips, 1988; Huang and Feng, 2015). Localised physical
processes such as coastal upwelling, eddies and meanders add further complexity to the
environment (Pearce, 1991; Lourey et al., 2006; Waite et al., 2007; Thompson et al., 2011;
Holliday et al., 2011). The location, extent and magnitude of these temporal changes in the
LC along the coast vary, such that different regional responses in marine biota are
observed.
Although the physical and chemical properties of the LC are well-studied, little is
known about oceanographic influences on spatial and temporal patterns of biota, especially
zooplankton. This is largely a result of the long WA coastline, isolation of study locations
and logistical constraints, which have restricted research efforts (Hays et al., 2005; Lynch
et al., 2014). Some of the first descriptions of zooplankton in waters offshore of WA were
undertaken by Tranter along the 110˚E IIOE transect in the early 1960s (e.g., Tranter,
1962; Tranter and Kerr, 1969; Tranter and Kerr, 1977). Since that time, studies have
described zooplankton assemblages at various locations in the LC system, such as the NW
Shelf (McKinnon et al., 2003; Wilson et al., 2003; McKinnon et al., 2015), LC eddies in the
southwest (Strzelecki et al., 2007; Muhling et al., 2007; Sawstrom et al., 2014, Sutton et al.,
2015) and the southern shelf waters (Gaughan and Potter, 1994; Gaughan and Fletcher,
1997).
A few studies have examined the influence of the LC on pelagic biota distribution
and composition, including that of larval fishes (Gaughan et al., 1990; Meekan et al., 2006;
Muhling and Beckley, 2007; Muhling et al., 2008; Beckley et al, 2009; Holliday et al., 2012),
krill (Sutton and Beckley 2016), macrozooplankton (Gaughan et al., 2009); chaetognaths
(Buchanan and Beckley, 2016), copepods (McKinnon and Ayukai, 1996; McKinnon and
Duggan, 2003; McKinnon et al., 2008), microzooplankton (Paterson et al., 2007) and
western rock lobster puerulus (Pearce and Phillips, 1998; Caputi, 2008). However, to date,
there have been no comparative descriptions of the zooplankton assemblages in WA
coastal waters from 22⁰S to 34⁰S, a region that is highly influenced by the LC.
4
The aim of this study is to describe the spatial and temporal variation in zooplankton
assemblages in WA coastal waters, at three sites, Ningaloo (22°S), Rottnest (32°S) and
Esperance (34°S), during the period 2011 to 2012. The study also addresses questions
regarding the influence of oceanographic conditions on the zooplankton assemblages. The
data for the analyses have been sourced from observational monitoring conducted by
IMOS, and provides the opportunity to compare oceanographic conditions and zooplankton
assemblages between three unique coastal ocean locations along a vast coastline. During
the period in which this study is focused, a strong La Niña event occurred and affected
approximately 2,000 km of the WA coast. This dataset thus also allows some evaluation of
changes in oceanographic conditions and zooplankton assemblages during an ocean
climate perturbation.
This study has focused on four research questions:
1. What are the oceanographic conditions at the three WA NRS?
2. What are the zooplankton assemblages at the three WA NRS?
3. Do the copepod assemblages at the three WA NRS differ?
4. Which oceanographic factors explain the variability in copepod assemblage
structure between the three WA NRS?
5
2. Materials and methods
2.1 Study sites
The WA coast is approximately 5,000 km long and spans 22 degrees of latitude.
The three IMOS NRS are located along this coast near Ningaloo (22°S), Rottnest Island
(32°S), and Esperance (34°S), at a depth of approximately 50 m, in waters that range from
tropical to temperate (Figure 1). The characteristics of the three NRS are summarised in
Table 1.
Figure 1. Location of the IMOS National Reference Stations currently in use (filled circles) and those that have been decommissioned (unfilled circles) off the coast of Australia.
6
Table 1. Details of the three NRS located off the coast of WA (adapted from Lynch et al., 2014). Bioregions as per Commonwealth of Australia (2006).
NRS Location
in WA Latitude
(⁰S) Longitude
(⁰E)
Distance offshore
(nm)
Depth (m)
Start (year)
End (year)
Frequency of sampling
Bioregion
Ningaloo NW 21⁰52’ 113⁰56’ 3.5 55 late-2010 mid-2013 Seasonally, 4 per year
Tropical
Rottnest SW 32⁰00’ 115⁰25’ 13.5 50 late-2009 ongoing Monthly Transition
Esperance S 33⁰56’ 121⁰51’ 1.5 50 mid-2009 mid-2013 Seasonally, 4 per year
Warm Temperate
Figure 2. Plankton and biogeochemical sampling regime at the three NRS. The shaded area indicates the focus period of this study.
NingalooRottnest
EsperanceJ F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D
20132009 2010 2011 2012
7
2.2 Data sources and sampling methods
Data used in this study were sourced from the IMOS Australian Ocean Data
Portal (AODN) (https://portal.aodn.org.au/). Data were derived from observations of
physical, biogeochemical and biological variables at the NRS, which were collected from
a combination of in situ moored sensors and vessel-based sampling.
2.2.1 Mooring-based oceanographic data
Continuous observations of water column properties were collected at the NRS
by pairs of in situ Water Quality Monitors (WQM) deployed in shallow (18 – 25 m) and
deep (48 – 55 m) parts of the water column. The WQMs consist of a number of sensors
to measure temperature and salinity (Conductivity-Temperature-Depth (CTD) sampler),
oxygen (Seabird sensor) and fluorescence and turbidity (EcoPuk FLNTU). Data were
collected from the WQMs at one-second intervals across one minute of continual
sampling every 15 minutes and logged internally. Data were harvested from the WQMs
when moorings were serviced, which occurred three times per year at Esperance and
Rottnest, and twice annually at Ningaloo (Lynch et al., 2014).
2.2.2 Physical and chemical data from vessel-based sampling
Physical water column properties
The in situ moored sensors were capable of collecting high resolution data for
many water properties, but it required supplementing by vessel-based biogeochemical,
phytoplankton and zooplankton sampling, and laboratory analyses. The commencement
date and frequency of vessel-based sampling varied between the NRS (Figure 2), and
typically occurred at monthly intervals at Rottnest Island, and seasonally at Ningaloo
and Esperance (Lynch et al., 2014).
Field sampling involved conducting CTD casts to obtain a water column profile
from the surface to near the seabed (~50 m). The CTD recorded data at one second
intervals and the resulting data were binned to measurements of every 1 m of the water
column (IMOS, 2012). Temperature (⁰C), practical salinity (psu), density (kg m-3) and
dissolved oxygen concentration (µmol kg-1) were measured from the CTD profiles.
Nutrients
Water was collected in 5 L Niskin bottles at discrete 10 m intervals from just
below the surface to 50 m. Triplicate water samples for the nutrients (µmol L-1) nitrate,
phosphate, and silicate, were extracted from the Niskin bottles. Samples were analysed
by the CSIRO laboratory located in Tasmania (IMOS, 2012).
8
Chlorophyll a
A combined water column sample of water from all Niskin bottles taken at 10 m
depth intervals was prepared for phytoplankton pigment analysis. The composition and
concentration of phytoplankton pigments (mg m-3) were determined by an established
High Performance Liquid Chromatography procedure performed in the CSIRO Oceans
and Atmosphere laboratory in Tasmania (IMOS, 2012).
2.2.3 Other oceanographic data
Monthly mean Fremantle sea level data and monthly mean Southern Oscillation
Index (SOI) data were sourced from the Australian Bureau of Meteorology (BOM)
website (http://www.bom.gov.au/ntc/IDO70000/IDO70000_62230_SLD.shtml, accessed
September 2016). Sea surface temperature (SST) and geostrophic current velocity
images were sourced from the IMOS Ocean Current website
(http://oceancurrent.imos.org.au/, accessed May 2016).
2.2.4 Biological data
Zooplankton
Vessel-based mesozooplankton (0.2 – 2 mm) samples were collected using a
standard 100 µm mesh plankton drop net of 60 cm internal diameter based on the
design by Heron (1982). The drop net was deployed from the side of a small boat and
collected a sample from the surface to just above the seabed. Two plankton drop net
samples were taken and separately preserved with formalin and seawater. One sample
was for analysis of biomass, the second for zooplankton composition and abundance.
Laboratory analyses of the zooplankton samples were undertaken by CSIRO
Oceans and Atmosphere staff employed on the IMOS program. Dry weight was
determined by placing the filtered zooplankton samples on pre-weighed petri dishes and
drying overnight (or for 24 hours) in an oven at 60⁰C. Following the drying procedure, the
sample was re-weighed and the biomass determined as mg per m3 of water sampled.
Zooplankton assemblage composition analysis was carried out by microscopic
identification of specimens. Taxonomic identification was to the best level possible,
guided by an assembled taxonomic library, and by expert zooplankton analysts if
required. Copepods were generally identified to species level, so more data analyses
were possible for this group. Data were recorded as number of individuals per m3.
9
2.3 Statistical analyses
Statistical analyses in this study were performed using data from 2011 – 2012,
which included a complete set of seasonal data for the three NRS (Figure 2). CTD data
for temperature, salinity, dissolved oxygen and density, and nutrient concentration data
were averaged over the water column, as examination of temperature-salinity profiles
over depth for each sample confirmed that there was little to no stratification (refer to
Figure 4 in Results). These data were used in all statistical analyses. Statistical analyses
were performed in PRIMER-E v6 with the PERMANOVA+ v1 add-on (Anderson, 2005;
Clarke and Warwick, 2005). Prior to analyses, examination of draftsman plots
determined the most appropriate transformation method of data for use in subsequent
analyses. Seasons were considered by grouping data from December to February
(summer); March to May (autumn); June to August (winter); and September to
November (spring).
(Q1) What are the oceanographic conditions at the three NRS?
Water column profiles for temperature-salinity and nutrients (nitrate, phosphate
and silicate) were examined using the vessel-based sampling data. High temporal
resolution temperature and salinity data measured by the WQMs were used for finer
detail time series analysis of these water properties.
Principal component analysis (PCA) was performed to explore patterns in the
environmental variables: temperature, salinity, density, dissolved oxygen, nutrients, and
chlorophyll a. Prior to analysis, variables were standardised by square root
transformation to reduce skewness, and normalised. A Euclidean-distance based
resemblance matrix was constructed, and a PC plot was generated from the PC scores
to visualise variation in the environmental data from the three NRS. A fixed, three-factor
permutational analysis of variance (PERMANOVA) (Anderson et al., 2008) was used to
determine if there were significant differences in environmental parameters because of
the a priori factors of NRS, season and year, and to investigate any interaction effect.
Following PERMANOVA, analysis of similarity (ANOSIM) with a one-way design was
used to conduct pair wise comparisons of environmental parameters for within factor
differences (Clarke and Warwick, 2001).
(Q2) What are the zooplankton assemblages at the three NRS?
Zooplankton abundance and biomass data were examined for spatial and
temporal patterns. A fixed, three-factor PERMANOVA based on Euclidean distance was
performed (on fourth root transformed data) to determine if there were significant
10
differences in zooplankton total abundance and biomass due to the a priori factors of
NRS, season and year, or any interaction of these factors. ANOSIM was used to
examine the within factor differences in abundance and biomass. Two diversity indices,
Margalef’s richness (Margalef, 1958) and Shannon-Weiner diversity (Shannon, 1948)
were computed using abundances of copepods identified to at least genus, to reduce
bias. Subsequently, species accumulation curves were plotted to investigate the effect
of sampling effort.
Analysis of average taxonomic distinctness (∆+) was carried out for copepod
assemblages. The ∆+ value is a measure of the overall taxonomic spread of an
assemblage (Clarke and Warwick, 1998), based on presence/absence data and
incorporating taxonomic relatedness information. The ∆+ value represents the average
taxonomic path length between two randomly chosen species in a sample, through
performing tests based on random simulations from a reference list of species (Clarke
and Warwick, 1998). High ∆+ values show that assemblages are less similar to each
other, because they have a greater number of higher taxonomic categories, while
conversely, lower ∆+ values indicate less taxonomic diversity. The analysis produces a
funnel plot that displays the calculated ∆+ values, the interval in which 95% of the values
occur, and identifies any departures from expectations of ∆+ values of assemblages
(Warwick and Clarke, 1998).
(Q3) Do the copepod assemblages at the three NRS differ?
Analyses of assemblages were performed on a reduced dataset of copepods
identified to at least genus level. Abundance data were fourth-root transformed to
reduce the weight of contribution of dominant taxa (Clarke and Warwick, 2001). A fixed,
three-factor PERMANOVA based on a Bray-Curtis resemblance matrix was used to
examine if there was significant variation in copepod assemblages between NRS,
seasons, years or if there was an interaction between these a priori factors. ANOSIM
was performed for pairwise comparisons of a priori factors.
Cluster analysis constructed a dendogram using group-average linkages that
displayed the similarities among copepod assemblages. Non-metric multi-dimensional
scaling (nMDS) ordination was used to arrange the copepod assemblages in two
dimensional space, based on similarities. To determine the species that characterised or
distinguished copepod assemblages at the three NRS, the similarity percentage
(SIMPER) (Clarke and Ainsworth, 1993) procedure was applied.
11
(Q4) Which oceanographic factors explain the variability in copepod assemblage
structure between the three NRS?
Multivariate patterns in copepod assemblages were explored using a distance-
based linear model (DistLM), which fits the abundance data to a multiple regression
model to find the set of predictor variables that best explains the variation in
assemblages (McArdle and Anderson, 2001). Examination of draftsmen plots revealed
that temperature and salinity were covariates, and seawater density was included in the
DistLM as a combination of these variables. Dissolved oxygen and silicate were
subsequently removed from the analysis due to their strong positive and negative
correlations (R = 0.92, R = -0.82), respectively, with density. A stepwise regression
selection procedure with the adjusted R2 selection criterion was used to choose the best
combination of predictor variables in the model. Results of the DistLM were represented
in a distance-based redundancy analysis (dbRDA) bi-plot (Legendre and
Anderson,1999), where the variables chosen by the DistLM were used to constrain the
ordination.
12
3. Results
3.1 Oceanographic conditions at the three NRS
3.1.1 Physical oceanography
A clear distinction in oceanographic conditions was observed at the three NRS
along the latitudinal gradient (22° – 34°S) of the WA coast (Figure 3). As temperature
decreased from north to south, there were corresponding increases in salinity, dissolved
oxygen and seawater density (Table 2). Along the coast, temperature decreased by
~8°C, and salinity increased by ~0.7 psu, with a corresponding difference in density of
~3 kg m-3.
Figure 3 Mean temperature, mean salinity and depth-integrated chlorophyll a at the three NRS, and their location on the WA coast
13
The water columns at the NRS were well-mixed throughout 2011 and 2012
(Figure 4a-c), signifying the presence of only one water mass on each sampling
occasion (Appendix 1). Warm, fresh, Tropical Surface Water (TSW) (>22°C, <35 psu,
<1024 kg m-3) was apparent at Ningaloo. As the LC transported this water south to
Rottnest, it became cooler (21°C), more saline (>35 psu) and more dense
(>1024 kg m-3) (Table 2). Here, the influence of cooler (19°C), more saline (>35.5 psu)
Capes Current water was revealed in late spring-summer. On the southern shelf, at
Esperance, the dominant water mass was cool, saltier and more dense, although waters
remained relatively warm, and became less saline (>20°C, ~35.5 psu) in autumn, when
LC water penetrated around Cape Leeuwin and along the south coast.
Table 2 Mean, minimum and maximum values of the abiotic variables at the three NRS in 2011 – 2012.
Ningaloo Rottnest Esperance
Mean (min-max) Mean (min-max) Mean (min-max)
Temperature (⁰C) 25.3 (22.2 - 29.2) 21.1 (18.3 - 24.6) 18.8 (16.2 - 20.9)
Salinity (psu) 34.8 (34.5 - 35.0) 35.3 (35.0 - 35.7) 35.6 (35.4 - 35.9)
Dissolved oxygen (µmol L-1) 207 (193 - 217) 219 (198 - 232) 230 (221 - 241)
Density (kg m-3) 1023 (1022 - 1024) 1025 (1024 - 1026) 1026 (1025 - 1026)
Chlorophyll a (mg m-3) 0.34 (0.19 - 0.54) 0.26 (0.13 - 0.56) 0.38 (0.23 - 0.72)
Silicate (µmol L-1) 3.38 (2.80 - 4.20) 1.96 (0.70 - 2.90) 0.03 (<0.01 - 0.10)
Nitrate (µmol L-1) 0.30 (<0.01 - 2.00) 0.24 (<0.01- 1.60) 0.06 (<0.01 - 0.13)
Phosphate (µmol L-1) 0.10 (0.05 - 0.18) 0.08 (0.01 - 0.19) 0.07 (0.02 - 0.39)
All three NRS presented well-defined seasonal patterns of water temperature
and salinity (Figure 5a-b and Figure 6a-b), reaching maxima in summer-early autumn
and gradually decreasing to a minimum in late winter-early spring before rising again.
The effect of the strong La Niña event during 2011-2012 was evidenced by above
average temperatures along the WA coast (Figure 7a-b). In 2011, water temperatures
were >1°C higher in summer at Ningaloo, >0.7°C higher in autumn at Rottnest, and
>0.7°C in late autumn-early winter at Esperance, relative to 2012. Coinciding with the
La Niña event, and persisting for several months, there were close to record-high
positive SOI values (Bureau of Meteorology (BOM), 2012), and high sea levels at
Fremantle, indicative of an intensified LC (Figure 8a-b).
14
Summer 2011
Temperature (°C) D
epth
(m
)
Salinity (psu)
Winter 2011
Temperature (°C)
Dep
th (
m)
Salinity (psu)
Figure 4. Temperature and salinity profiles (0 – 50 m) for summer and winter 2011 at (a).Ningaloo (b) Rottnest (c) Esperance. Solid line indicates temperature (⁰C) and dashed line indicates salinity (psu).
a b c
15
a
b
Figure 5. Time series of (a) mean daily temperature and (b) mean daily salinity collected by the shallow (18-25 m) deployed WQMs at the NRS. Dates at which vessel-based zooplankton sampling occurred are indicated by black circles.
2011 2012
2011 2012
16
a
b
Figure 6. Time series of (a) mean daily temperature and (b) mean daily salinity collected by the deep (45-55 m) deployed WQMs at the NRS. Dates at which vessel-based zooplankton sampling occurred are indicated by black circles.
2011 2012
2011 2012
17
Figure 7. Satellite imagery of the WA coast during the peak of the 2010/2011 La Niña marine heat wave. (a) Thirty day monthly mean sea level anomaly for March 2011 (b) Monthly average SST anomaly and geostrophic velocity for March 2011. Images courtesy of IMOS.
Figure 8. (a) Monthly mean Southern Oscillation Index (SOI) values (b) Monthly mean sea level at Fremantle for 2011 and 2012. Data sourced from BOM.
3.1.2 Biogeochemical oceanography
Dissolved oxygen concentration was strongly negatively correlated with water
temperature, and increased with latitude. Chlorophyll a concentrations were low across
the three NRS, generally < 0.4 mg m-3 (Figure 9a-c). Similar seasonal patterns were
observed for Rottnest and Esperance, with an increase in chlorophyll a concentration in
autumn/winter of ~0.2 - 0.4 mg m-3 from summer. The seasonal signal at Ningaloo was
a bNingaloo
Rottnest
Esperance
Ningaloo
Rottnest
Esperance
b a
18
less marked in comparison. No relationship between chlorophyll a concentration and
zooplankton biomass was observed (Figure 9d).
Figure 9. Seasonal mean depth-integrated chlorophyll a concentrations for (a) Ningaloo (b) Rottnest (c) Esperance. (d) Relationship between total zooplankton biomass and depth-integrated chlorophyll a concentration. Error bars represent the standard error of the mean over the monthly samples for Rottnest.
Nutrient concentrations (silicate, nitrate and phosphate) decreased along a north
to south latitudinal gradient, and were generally low, providing a clear demonstration of
the oligotrophic nature of WA coastal waters (Figure 10). Silicate concentrations were
highest in the source waters of the LC at Ningaloo (up to ~4 µmol L-1) and moving south
along the coast, this declined rapidly, with concentrations reduced by half at Rottnest,
and barely detectable in Esperance waters. Nitrate concentrations rarely exceeded
0.5 µmol L-1, and were particularly depleted at the surface, with surface concentrations
generally about half those at depths > 30 m. In spring 2012, the nitrate concentration at
Ningaloo rose to 1.2 µmol L-1, which was considerably higher than the overall mean for
the site. The waters at the three NRS contained very little phosphate, and
concentrations rarely exceeded 0.3 µmol L-1.
c
a b
d
19
Figure 10. Relationship between mean annual nutrient concentrations and depth for (a) Ningaloo (b) Rottnest (c) Esperance. Error bars represent standard error of the mean. Unfilled circles: 2011, filled: 2012.
a b c
20
3.1.3 Principal component analysis of environmental variables
The principal component analysis (PCA) identified three main components which
together accounted for 84% of the variance in the environmental data (Figure 11). The
first axis of variability (PC1) represented temperature, salinity, dissolved oxygen
concentration, density and silicate and explained 54% of the variance. The PCA plot
revealed a clear spatial separation of the oceanographic characteristics of the three
NRS along the first PC axis, which reflected the north to south gradient of decreasing
temperature and silicate, and increasing salinity and dissolved oxygen, and hence,
density (Figure 11). The second axis of variability (PC2) was represented by chlorophyll
a and phosphate. This PC was less significant, did not show clear separation between
NRS, and explained only 17% of the variation.
Figure 11. Principal component analysis (PCA) plot showing the variation in the abiotic variables in relation to NRS site and season. The vectors indicate the direction and strength of each environmental factor’s contribution to the overall variation. Symbol colour denotes NRS: Ningaloo (red), Rottnest (turquoise), Esperance (blue).
21
PERMANOVA revealed significant variation in environmental factors between
the three NRS (P = 0.001) and with seasons (P = 0.001) (Table 3). PERMANOVA did
not reveal a significant variation in environmental factors across years, or a significant
interaction effect of factors. ANOSIM showed that dissimilarities were greatest between
Ningaloo and Esperance (R = 0.99, P = 0.001), but were also significant between
Ningaloo and Rottnest (R = 0.77, P = 0.001) and Esperance and Rottnest
(R = 0.76, P = 0.001). ANOSIM found that, averaged across all NRS, there was
significant variation in environmental factors between seasons, however this was
revealed for autumn and spring only (R = 0.21, P = 0.023).
ANOSIM confirmed that temperature was significantly warmer, and that salinity
and dissolved oxygen were significantly lower at Ningaloo than at Esperance
(R = 0.77 - 0.99, P = 0.001) and at Rottnest (R = 0.37 - 0.93, P = 0.001). This
corresponded to less dense seawater at Ningaloo compared to Esperance
(R = 0.97, P = 0.001), and Rottnest (R = 0.80, P = 0.001), while seawater density was
also significantly lower at Rottnest than Esperance (R = 0.35, P = 0.001).
Ningaloo waters were significantly richer in nitrate and silicate than Esperance
waters (R = 0.43, R = 1, respectively, P = 0.001) and were also more silicate-rich than
Rottnest waters (R = 0.96, P = 0.001), but silicate was more abundant at Rottnest than
at Esperance (R = 1, P = 0.001). ANOSIM did not reveal any significant differences in
chlorophyll a or phosphate concentrations between NRS.
Table 3. PERMANOVA based on the Euclidean distance matrix of the normalised environmental variable data (square root transformed) for 2011-2012 in response to NRS location, year, season of the year, and the interaction between the three factors. * indicates significance at P < 0.05.
Source of variation df MS pseudo-F P
NRS 2 75.55 29.18 0.001*
Year 1 2.38 0.92 0.457
Season 3 10.93 4.22 0.001*
NRS x Year 2 4.79 1.85 0.094
NRS x Season 6 3.75 1.45 0.133
Year x Season 3 3.98 1.54 0.141
NRS x Year x Season 6 3.42 1.32 0.220
Residuals 14 2.59
22
3.2 Zooplankton at the three NRS
3.2.1 Zooplankton abundance and biomass
A high degree of spatio-temporal variability in zooplankton abundance was
observed in this study, and was an effect of zooplankton sampling using a 100 µm mesh
size net, which resulted in the collection of a wide range of taxa, from copepod nauplii
(< 1 mm) to medusa (> 20 mm). There was no clear effect of latitude on overall
zooplankton abundance, and values ranged from <1000 to >14000 ind m-3 (Figure 12a).
Seasonal patterns in abundance were observed for Ningaloo and Esperance, but the
timing of abundance maxima differed, occurring in summer and autumn, respectively
(Figure 12a and Appendix 2). Zooplankton abundances were relatively evenly
distributed throughout the year at Rottnest.
PERMANOVA indicated that although there was no significant difference in total
zooplankton abundance between the NRS, years or seasons, there was a significant
interaction effect of NRS and season (P = 0.006) (Table 4). ANOSIM revealed that
zooplankton abundance was significantly greater at Ningaloo than Rottnest
(R = 0.78, P = 0.036) in summer, but no other significant differences in abundances
were found for these two NRS. While ANOSIM did not find any significant difference in
total zooplankton abundance between Esperance and Ningaloo, it was revealed that
abundance was significantly greater at Esperance than Rottnest, but only in autumn
(R = 0.87, P = 0.048).
Table 4. PERMANOVA based on Euclidean distance for significant differences in total zooplankton abundance for the factors NRS, year and season. * indicates significance at P < 0.05.
Source of variation df MS pseudo-F P
NRS 2 2.50 2.10 0.182
Year 1 1.09 0.91 0.369
Season 3 1.68 1.41 0.296
NRS x Year 2 0.67 0.57 0.581
NRS x Season 6 5.80 4.87 0.006*
Year x Season 3 0.93 0.78 0.533
NRS x Year x Season 6 0.89 0.74 0.648
Residuals 14 1.19
Zooplankton total biomass at the three NRS ranged from <4 mg - ~60 mg m-3.
Biomass maxima generally corresponded to abundance maxima, and occurred in
summer at Ningaloo, and in autumn at Rottnest and Esperance (Figure 12b). Biomass
23
was exceptionally high at Ningaloo in summer 2011, being >50% higher than at any
other period. PERMANOVA revealed that zooplankton total biomass differed
significantly between the three NRS (P = 0.002), and that there was a significant
interaction effect between NRS and season (P = 0.009) (Table 5). ANOSIM confirmed
that zooplankton total biomass was significantly greater at Ningaloo than Rottnest
(R=0.78, P = 0.048) in summer, but there were no other significant differences in
seasonal biomass between these two NRS. ANOSIM found no significant differences in
zooplankton total biomass between Ningaloo and Esperance, or Rottnest and
Esperance for any season.
Figure 12 Seasonal variation of (a) mean zooplankton abundance and (b) mean zooplankton biomass for 2011-2012 at the three NRS. Error bars represent the standard error of the mean.
Table 5. PERMANOVA based on Euclidean distance for significant differences in total zooplankton biomass for the factors NRS, year and season. * indicates significance at P < 0.05.
Source of variation df MS pseudo-F P
NRS 2 0.38 14.60 0.002*
Year 1 0.05 2.06 0.159
Season 3 0.07 2.84 0.085
NRS x Year 2 0.06 2.42 0.127
NRS x Season 6 0.13 4.91 0.009*
Year x Season 3 0.07 2.67 0.072
NRS x Year x Season 6 0.05 1.90 0.125
Residuals 14 0.03
a b NingalooRottnestEsperance
NingalooRottnestEsperance
24
3.2.2 Zooplankton composition
A total of 226 zooplankton taxa were identified at the three NRS during the study
period (Appendix 3). Taxa included both mero- and holoplanktonic fauna, and
represented 12 phyla and 14 classes. Single zooplankton samples collected at the NRS
contained up to 75 zooplankton taxa.
Crustaceans made up the bulk of the zooplankton, and contributed to ~80% of
total abundance at each NRS (Figure 13). The contribution of the other zooplankton
groups to assemblages varied. North to south along the coast, the contribution of
Appendicularia (predominantly Oikopleuridae) and Chaetognatha (family Sagittidae) to
the zooplankton assemblages declined. Conversely, the relative abundance of Mollusca
increased at higher latitudes. Seasonal blooms in taxa occurred: Appendicularia were
numerous in autumn at Ningaloo, while blooms of Bivalvia and Gastropoda occurred at
this NRS in summer 2012, at Rottnest in autumn 2012, and in autumn-winter at
Esperance. Zooplankton assemblages also comprised a diverse range of
meroplanktonic Polychaeta, Bryozoa, Decapoda and Echinodermata.
Figure 13 Summary of zooplankton composition for (a) Ningaloo (b) Rottnest (c) Esperance.
Within the Crustacea, Copepoda contributed most to the NRS zooplankton
assemblages, both in terms of abundance and diversity, and comprised 66-77% of
abundance, and 149 of the total 226 zooplankton taxa identified. The numerically
Crustacea Non-CrustaceaCalanoida copepods MolluscaCyclopoida copepods AppendiculariaHarpacticoida copepods BryozoaCladocera ChaetognathaCrustacea, other Annelida
Non-crustacea, other
a b c
25
dominant copepod order at Rottnest and Esperance was Calanoida, but it was co-
dominant with Cyclopoida at Ningaloo (Figure 13). Copepodites, predominantly
Calanoida and Cyclopoida, almost consistently outnumbered adult copepods. Their
abundances increased episodically at the three NRS, and contributed up to 55% of the
sampled zooplankton abundance. Amongst the other Crustacea, Cladocera was
relatively important at Esperance, particularly Penilia avirostris, with the species’
abundance regularly exceeding seasonal total abundances of Cyclopoida and
Harpacticoida copepods.
Within the copepods, the family Oithonidae (Cyclopoida) was the most numerous
(Figure 14) and a suite of Oithonid copepods were amongst the most abundant
zooplankton taxa across all three NRS (Table 6). The order Calanoida was well
represented in assemblages by abundances of the families Paracalanidae, Acartidae
and Clausocalanidae, however, their distribution varied. Paracalanidae copepods were
more numerous at Ningaloo and Rottnest, while copepods of the families Acartidae and
Clausocalanidae were generally more numerous at Esperance (Figure 14 and
Figure 15).
Table 6. Mean abundance of the dominant zooplankton taxa at the three NRS in 2011 – 2012
Ningaloo Rottnest Esperance
Group Family Taxon ind. m-3 ind. m-3 ind. m-3
Copepoda Oithonidae Oithona spp. 1,117 382 814
Oithonidae Oithona nana 138
Euterpinidae Euterpina acutifrons 130 50
Oncaeidae Oncaea spp. 97 106
Paracalanidae Parvocalanus crassirostris 88
Paracalanidae Paracalanus indicus 63 67
Oithonidae Oithona simplex 62
Chaetognatha Sagittidae Zonosagitta pulchra 49
Copepoda Oithonidae Dioithona rigida 47 51 107
Paracalanidae Bestiolina similis 45
Acartiidae Acartia spp. 60 112
Acartiidae Acartia tonsa 37 66
Cladocera Sididae Penilia avirostris 120 780
Copepoda Clausocalanidae Clausocalanus furcatus 110 92
Cladocera Podonidae Pseudevadne tergestina 62
Copepoda Ectinosomatidae Microsetella norvegica 167
Clausocalanidae Clausocalanus spp. 133
Thaliacea Doliolidae Doliolum spp. 45
Copepoda Oithonidae Oithona similis 40
26
Figure 14. The composition of copepod families at the three NRS. Also shown is the contribution of the two highly abundant groups of copepods not identified to family level, juvenile calanoid copepods and nauplii copepods.
Figure 15. Shade plot of fourth-root transformed seasonal abundance of the twenty most abundant copepod taxa across the three NRS. The shading is proportional to abundance, with white space indicating the taxon was not present. Taxa are ordered from most to least abundant.
Oithonidae Paracalanidae CorycaeidaeEuterpinidae Oncaeidae AcartiidaeClausocalanidae Ectinosomatidae Juvenile calanoid
Nauplii copepod Other
27
Of the 116 copepod species identified in the study region, 34 were identified at
all three NRS, many of which are known to be cosmopolitan species (Figure 16).
Overall, the greatest number of copepod species was recorded at Rottnest (88), slightly
more than Ningaloo (80) but considerably more than Esperance (53) (Table 7). Rottnest
had both the greatest number (22) and proportion (25%) of copepod species recorded
exclusively at the site, although none were abundant. The number of copepod species
shared exclusively by Ningaloo and Rottnest (24) was considerably higher than the
number found exclusively at Ningaloo and Esperance (4) or at the two southern NRS
sites only (7) (Figure 16). Margalef’s species richness and Shannon-Weiner diversity
values for copepods were similar at Ningaloo and Rottnest, and were higher than
Esperance values (Table 7). However, uneven sampling efforts at the NRS must be
taken into account when considering these results (Ningaloo and Esperance, n = 8;
Rottnest, n = 22).
Figure 16 Venn diagram depicting the numbers of copepod species exclusive to each of the NRS, and the number of species common among NRS. Numbers in brackets indicate number of zooplankton samples.
Table 7 Diversity indices for copepods at the three NRS.
Number of Species
Margalef’s Species Richness
Shannon-Weiner Diversity Index
Ningaloo 80 8.9 3.24
Rottnest 88 9.3 3.25
Esperance 53 5.9 2.96
28
Species accumulation curves were examined to provide further insight into the
observed differences in species richness, taking into account uneven zooplankton
sampling efforts (Figure 17). A plateau in the Esperance species accumulation curve at
the sixth sampling effort, and a relatively plateaued species accumulation curve for
Rottnest following the ninth sampling effort at this NRS, indicated that these levels of
sampling effort were sufficient to detect the copepod species pool at these NRS. In
contrast, the Ningaloo curve showed a continued upward trajectory at the eighth
sampling effort, which indicated that species richness was underestimated at the end of
the sampling period for this NRS (Figure 17).
Figure 17. Species accumulation curves based on presence/absence of copepod species for each NRS during the 2011 – 2012 sampling period.
3.2.3 Taxonomic distinctness of copepod assemblages
Taxonomic distinctness analysis of copepods at the NRS revealed that all
assemblages had relatively high values of average taxonomic distinctness (∆+). The
funnel plot showed that ∆+ for assemblages ranged from 82 – 90, and did not strongly
vary between the NRS or seasons (Figure 18). Generally, ∆+ values fell within the 95%
confidence limits, which indicated that the copepod assemblages contained the
expected level of species diversity for the region, with some exceptions. Higher ∆+ did
not necessarily correspond with a greater number of species: the winter and spring
Rottnest assemblages which were more taxonomically diverse than would have been
expected, as indicated by the location above the funnel simulation boundary, varied in
number of species from 22 – 39 (Figure 18).
NingalooRottnestEsperance
29
Figure 18. Simulated distribution of average taxonomic distinctness for copepod species at the NRS, and the 95% confidence limits.
3.3 Comparison of copepod assemblages
PERMANOVA confirmed that copepod assemblages differed significantly among
NRS (P = 0.001), between seasons (P = 0.04) and that there was a significant
interaction effect between NRS and season (P = 0.01) (Table 8). There was no
significant difference in assemblages between years (P = 0.05). ANOSIM showed that
assemblages at the NRS all were significantly different from each other. Ningaloo and
Esperance assemblages were the most distinct from each other (R = 0.59, P = 0.001),
and Rottnest and Esperance the least distinct (R = 0.38, P = 0.001), with the
distinctness between Rottnest and Ningaloo falling in between (R = 0.46, P = 0.001).
ANOSIM found that in summer, there were significant differences between
copepod assemblages at Ningaloo and Rottnest (R = 0.98, P = 0.036) and Rottnest and
Esperance (R = 0.79, P = 0.036), but not at Ningaloo and Esperance (P = 0.33).
Differences in copepod assemblages between the NRS in autumn were somewhat
weaker, but there were significant differences between copepod assemblages at
Ningaloo and Rottnest (R = 0.71, P = 0.048) and Rottnest and Esperance (R = 0.60, P =
0.048). ANOSIM found no significant differences between copepod assemblages at the
three NRS in winter or spring (P > 0.05).
30
Table 8. PERMANOVA based on the Bray-Curtis similarity of copepod abundance data (fourth-root transformed) for the factors NRS, year and season. * indicates significance at P < 0.05.
Source of variation df MS pseudo-F P
NRS 2 4013.0 4.46 0.001*
Year 1 1830.3 2.03 0.050
Season 3 1424.8 1.58 0.043*
NRS x Year 2 1091.1 1.21 0.237
NRS x Season 6 1412.7 1.57 0.015*
Year x Season 3 860.5 0.96 0.547
NRS x Year x Season 6 945.5 1.05 0.388
Residuals 14 899.9
Cluster analysis arranged the copepod assemblages in a spatial pattern that
approximately reflected their distribution along the WA coast (Figure 19). The analysis
divided the assemblages into three major groupings that separated the Ningaloo and
Esperance assemblages from the Rottnest assemblages.
Figure 19 Bray-Curtis similarity dendogram of the NRS copepod assemblages, based on (fourth-root transformed) abundance. Red lines connect assemblages that are not statistically unique (P<0.05). Symbol colour denotes NRS: Ningaloo (red), Rottnest (turquoise), Esperance (blue).
31
The nMDS ordination of copepod assemblages showed the relatively clear
separation of NRS assemblages (Figure 20). Esperance assemblages, coupled with two
spring Rottnest assemblages, were closely grouped. The remainder of the Rottnest
assemblages were relatively well arranged together and were separated from the
Esperance assemblages. Ningaloo assemblages were less closely arranged. However,
the high nMDS ordination stress value of 0.24 meant that the ordination was an
imperfect representation of the assemblages in multidimensional space.
Figure 20. A two-dimensional nMDS ordination of copepod assemblages at the three NRS: Symbol colour denotes NRS: Ningaloo (red), Rottnest (turquoise), Esperance (blue). Groupings are shown at the 60% similarity level.
3.3.1 Characteristic and discriminating copepod species
SIMPER revealed the average similarity of copepod assemblages within a NRS
site was greatest at Esperance (61%) and least at Ningaloo (44%) (Table 9).
Oithona spp. contributed the most to all within-NRS similarities in copepod
assemblages. This group of species dominated the assemblages and had a strong
influence on their structuring, demonstrating no seasonal pattern and fluctuations in
abundance from <100 ind m-3 to >4000 ind m-3.
32
There were latitudinal patterns in the relative abundance of many of the other
ubiquitous and highly abundant copepods. Species that increased in relative abundance
with latitude included Microsetella norvegica, Diothona rigida, and Acartia tonsa
(Figure 21). SIMPER identified two of these species as characteristic of Esperance
assemblages (Table 9). Species that decreased in abundance with latitude included
E. acutifrons, O. simplex and O. nana (Figure 21). O. nana was typical of Ningaloo
assemblages. Species characteristic of Rottnest copepod assemblages were also
characteristic of either Ningaloo or Esperance assemblages: C. furcatus and
Acartia spp. characterised both Rottnest and Esperance assemblages, with Oncaea
spp. and P. indicus characteristic of both Rottnest and Ningaloo assemblages (Table 9).
Species that distinguished Esperance and Rottnest copepod assemblages from
Ningaloo were similar, with C. furcatus and D. rigida being good discriminators. The
tropical species Parvocalanus crassirostris, together with O. simplex and O. nana,
distinguished Ningaloo copepod assemblages from the other NRS assemblages.
Greater abundances of Clausocalanus spp. and Diothona oculata at Esperance, and
the presence of Oncaea media and Calocalanus spp. only in the Rottnest assemblage,
distinguished the two southern NRS assemblages from each other.
Figure 21. Contribution to percentage abundance of copepods only by the numerically dominant copepod species at the three NRS in 2011 - 2012.
33
Table 9. Summary of SIMPER results for the three NRS averaged across seasons. Results for within NRS similarities list taxon which contributed at least 2% to the similarity. Results for dissimilarity between NRS assemblages show taxon that contributed > 5% to the dissimilarity. Percentage contributions are shown in brackets next to taxon names. (Av. = average).
Ningaloo Rottnest Esperance
Ningaloo Av. similarity: 44% Oithona spp. (14%) Oithona nana (8%) Paracalanus indicus (7%) Oncaea spp. (7%) Paracalanus aculeatus (6%)
Rottnest Av. dissimilarity: 53% Clausocalanus furcatus (3%) Dioithona rigida (2%) Parvocalanus crassirostris (2%) Euterpina acutifrons (2%) Oithona simplex (2%)
Av. similarity: 54% Oithona spp. (11%) Oncaea spp. (8%) Paracalanus indicus (7%) Oithona nana (6%) Clausocalanus furcatus (6%) Acartia spp. (6%) Microsetella norvegica (5%)
Esperance Av. dissimilarity: 58% Clausocalanus furcatus (3%) Clausocalanus spp.(3%) Oithona nana (2%) Acartia spp. (2%) Dioithona rigida (2%) Oithona brevicornis (2%) Calocalanus spp. (2%)
Av. dissimilarity: 49% Clausocalanus spp. (3%) Oithona brevicornis (3%) Dioithona oculata (2%) Oncaea media (2%) Calocalanus spp. (2%) Oncaea venusta (2%) Temora spp. (2%) Diothona rigida (2%)
Av. similarity: 61% Oithona spp. (11%) Clausocalanus spp. (7%) Acartia spp. (7%) Acartia tonsa (6%) Clausocalanus furcatus (6%) Diothona rigida (5%) Oithona similis (5%)
The average dissimilarity between the three NRS was greatest in summer (56%)
and weakest in winter (50%) (Table 10). A greater number of copepod species were
common to all three NRS in winter (26 of 101) compared to summer (19 of 91).
Copepod species that increased in importance in winter at Rottnest and Esperance that
were typically characteristic of Ningaloo assemblages included Paracalanus aculeatus,
P. indicus and Canthocalanus pauper (Table 11). The distinction between Ningaloo and
Esperance assemblages was greatest in spring, when the assemblages had few (15 of
56) copepod species in common. Ningaloo and Rottnest assemblages were most
dissimilar in summer, due to dominance by inshore species (Paracalanid and
Harpacticoid copepods) at Ningaloo and offshore species (Oncaeid and Clausocalanid
copepods) at Rottnest. No pattern was observed for Rottnest and Esperance.
34
Table 10 Dissimilarity percentage between copepod assemblages at the three NRS on a seasonal basis, as determined by the SIMPER analysis.
Ningaloo:Rottnest Rottnest:Esperance Ningaloo:Esperance
Summer 58 % 49 % 59 %
Autumn 52 % 50 % 61 %
Winter 48 % 48 % 54 %
Spring 54 % 48 % 63 %
Table 11. Key copepod taxon characteristic of the winter assemblages at the three NRS and their percentage contribution to the similarity at each NRS.
Ningaloo Rottnest Esperance
Oithona spp. (9%) Paracalanus indicus (5%) Paracalanus aculeatus (4%) Delibus nudus (4%) Canthocalanus pauper (4%)
Oithona spp. (9%) Paracalanus indicus (7%) Paracalanus aculeatus (5%) Delibus nudus (1%) Canthocalanus pauper (6%) Euterpina acutifrons (6%) Temora turbinata (6%)
Oithona spp. (10%) Paracalanus indicus (4%) Paracalanus aculeatus (6%) Euterpina acutifrons (6%) Temora turbinata (6%)
3.4 Influence of oceanographic conditions on the copepod assemblages
In the distance-based linear model (DistLM) for copepod assemblage structures,
marginal tests from the DistLM revealed that of the four environmental variables (mean
seawater density, and depth-integrated nitrate, phosphate and chlorophyll a) included in
the model, all but phosphate were significant in explaining some of the variation in
copepod assemblages (P < 0.05). The DistLM procedure selected mean seawater
density, depth-integrated nitrate and chlorophyll a for inclusion in the best model
explaining copepod assemblage structure (r2 = 0.17). The model explained just 17% of
the overall variation, and only seawater density and chlorophyll a were significant
explanatory variables in the model (Table 12).
Table 12. Results of the distance-based linear model (DistLM) showing the percentage of variation in copepod assemblage structure at the three NRS explained by each of the environmental variables. * indicates significance at P < 0.05.
Environmental variable SS pseudo-F P % variation explained
Mean seawater density 4133.9 3.5 0.0001* 9.7
Depth-integrated chlorophyll a 1965.5 1.7 0.0346* 4.8
Depth-integrated nitrate concentration 1732.9 1.5 0.0817 2.3
35
For the fitted model, the distance-based redundancy (dbRDA) bi-plot showed the
first and second axes to explain 87% of the variation (Figure 22). Seawater density
explained the most variation in the fitted model (57.8%) and was correlated with the first
axis of the dbRDA bi-plot. Chlorophyll a concentration was associated with the second
axis of the dbRDA bi-plot and explained a further 28.7% of the total variation in
assemblage structures. Nitrate concentration was correlated with the third axis and was
responsible for <3% of the overall variation. The spatial arrangement of the
assemblages in the bi-plot can be interpreted as a relationship between less dense
seawater and Ningaloo copepod assemblages, and higher density seawater with
Esperance copepod assemblages. Higher chlorophyll a also drives copepod
assemblage structure seasonally at Esperance, and higher nitrate concentration
sporadically influences Ningaloo and Rottnest copepod assemblages.
Figure 22. Distance-based redundancy (dbRDA) biplot of copepod assemblage data. The ordination is based on the best DistLM model with the three variables shown as vectors on the bi-plot, indicating the direction and strength of the factor’s influence on the copepod assemblage structure. Symbol colour denotes NRS: Ningaloo (red), Rottnest (turquoise), Esperance (blue).
36
4. Discussion
This is the first detailed study to use IMOS data to analyse spatial and temporal
variability in zooplankton abundance, biomass, and composition, and copepod
assemblage structure in waters off WA between 22°S and 34°S. This study revealed
clear dissimilarities in the oceanographic environments at the three NRS, and in the key
taxa that shaped their zooplankton assemblages. It also identified environmental
variables that influenced copepod assemblage structures, with seawater density
showing the strongest relationship, while short-term and seasonal changes in
oceanographic conditions were also important drivers of variation in assemblages.
4.1 Oceanographic characteristics at the three NRS
The three NRS had distinct oceanographic conditions, characterised by a north
to south latitudinal gradient of change in physical and biogeochemical properties. The
predominant water mass at Ningaloo was TSW, with the exception of spring 2012, when
more dense water characterised by higher nitrate was present, and was possibly
upwelled water (Rossi et al., 2013a). The water mass at Rottnest comprised modified
LC water, which was cooler (~21°C) and saltier due to the inflow of offshore water, and
air-sea heat and freshwater fluxes (Weller et al., 2011). The influence of the Capes
upwelling was occasionally seen at Rottnest when waters cooled and more nitrate was
found at depth (Lourey et al., 2013; Rossi et al., 2013b). However, the LC was generally
strong enough to suppress the Capes Current flow, and SST imagery revealed the LC to
frequently flood the shelf here (Appendix 1). Waters at Esperance were relatively warm
(20°C) in summer, becoming cooler and denser in winter due to wind forcing and heat
loss (Middleton and Bye, 2007). Here, oceanographic conditions in autumn 2011 and
winter 2012 differed, and consisted of unseasonably warm (~21°C), lower density
(~1025 kg m-3), chlorophyll a enriched water, a reflection of the LC’s seasonal influence
along the southern shelf of WA.
The strong La Niña event that occurred during 2011 -2012 resulted in a highly
intensified LC, and an overall net heat flux into the ocean, which caused warmer water
temperatures to be sustained for longer periods along the WA coast (Pearce and Feng,
2013; Feng et al., 2013; Benthuysen et al., 2014). The unusually strong LC, coupled
with weakening of usually opposing southerly winds, was sufficient to largely prevent the
northward flowing, summer coastal Ningaloo and Capes Currents (Pearce and
Pattiaratchi, 1999; Woo et al., 2006; Huang and Feng, 2015).
37
In addition to their physical characteristics, there was also variability in the
biogeochemical properties of the NRS waters. Chlorophyll a values were within the
typical range (~0.1 – 0.8 mg m-3) previously observed for Western Australian shelf
waters (e.g. Wilson et al., 2003; Koslow et al., 2008). Chlorophyll a maxima at Rottnest
and Esperance coincided with the autumn-winter shelf-wide phytoplankton bloom known
to occur (Muhling et al., 2007; Koslow et al., 2008; Thompson et al., 2009; Rosseaux et
al., 2012; Lourey et al., 2013), however a less consistent pattern was observed for
Ningaloo. Waters were generally nutrient-poor, and were especially depleted at
Esperance. These conditions are typical of the oligotrophic nature of WA coastal waters,
and are a consequence of the downwelling favourable LC which suppresses nutrient
enrichment, in addition to a lack of terrestrial sources of nutrients (Hanson et al., 2005;
Lourey et al., 2006; Thompson et al., 2011).
4.2 Zooplankton abundance, biomass and composition at the three NRS
Zooplankton abundance and composition at the three NRS were dynamic, and
variation was driven by the seasonal responses of a diverse range of large and small
zooplankton. Zooplankton total abundances varied by orders of magnitude between
consecutive sampling at the three NRS, and this high degree of variability means that no
site was clearly the most zooplankton rich. The temporal pattern in abundance consisted
of maxima coinciding with the warmest water temperatures at the three NRS, and the
annual autumn-winter phytoplankton bloom on the southwest and southern coasts
(Lourey et al., 2006; Koslow et al., 2008; Lourey et al., 2013). The rapid depletion of
zooplankton at Ningaloo and Esperance that followed the maxima may have been a
response to heavy predation, natural mortality, or dispersal by a strengthened LC, of the
large populations of nauplii and copepodites that characterised these assemblages
(Fletcher et al., 1994).
Zooplankton biomass at the three NRS was comparable to values reported for
shelf waters of other boundary currents, including the EAC (Tranter, 1962; Young et al.,
1996) and the Agulhas Current (Pretorius et al., 2016). Seasonal patterns in
zooplankton biomass in boundary current systems, such as the Southern Benguela,
have been linked to the cycle of primary production (Pillar, 1986; Pretorius et al., 2016),
however, no such relationship was observed in this study. This is in agreement with
previous findings in Australian waters (McKinnon and Duggan, 2003; McKinnon et al.,
2005), and may be a reflection of the dominance of carnivorous zooplankton, such as
Oithonid and Oncaeid copepods.
38
Despite the oligotrophic nature of WA coastal waters, they were characterised by
a diverse range of zooplankton fauna. Spatio-temporal patterns in the distribution of
zooplankton groups reflected water mass properties and seasonal oceanography. This
included the distribution of Chaetognatha species, including an association of
Zonosagitta pulchra to the tropical waters at Ningaloo, which concurred with previous
findings (Buchanan and Beckley, 2016). Similarly, the importance of Cladocera on the
southern shelf agrees with earlier studies (Gaughan and Potter, 1994), as do the
seasonal blooms of this group observed at Esperance, which have also been reported
for other temperate marine systems (Kane, 2013). Fluctuations in meroplankton
abundances, including Bivalvia and Gastropoda larvae, coincided with chlorophyll a
maxima and may be attributed to spawning in response to food availability (Van Ruth
and Ward, 2009).
The dominance of copepods (~70%) in the zooplankton assemblages is typical
of marine systems (Longhurst, 1985). The 116 copepod species identified in the study
region was considerably less than the 977 species identified for the entire Indian Ocean
(Razouls et al., 2005 -2016). However, the number and groups of species observed
corresponded to previous studies of WA coastal waters (eg. McKinnon and Ayukai,
1996; McKinnon and Duggan, 2003; McKinnon et al., 2008; McKinnon et al 2015) and
eastern Australian coastal waters at similar latitudes (Kimmerer and McKinnon, 1985;
Kimmerer and McKinnon, 1987; McKinnon et al., 2005).
The most important copepod families in terms of abundance were Oithonidae,
Paracalanidae, Clausocalanidae and Acartiidae. Dominance by Paracalanidae and
Oithonidae copepods is typical of Australian tropical coastal waters (McKinnon and
Thorrold, 1993; McKinnon et al., 2005) but appears to be more widespread along the
WA coast. Oithona spp was the most numerous taxon at all three NRS, which is not
surprising, considering this genus is speciose, widely distributed, and highly tolerant of
oceanographic conditions (Gallienne and Robins, 2001; Dahms et al., 2015; Chew and
Chong, 2016). Amongst the other dominant copepods, Paracalanus indicus was
important at Ningaloo and Rottnest. This copepod species is typically dominant in the
zooplankton in other boundary currents at similar latitudes (Hidalgo et al., 2010).
Proportions of Acartia spp. and Clausocalanid copepods such as Clausocalanus
furcatus were greater in Rottnest and Esperance assemblages, and are commonly
associated with the mesozooplankton in other oligotrophic, subtropical-temperate
regions (Kouwenberg, 1994; Mazzocchi and Paffenhöfer, 1998; Schnack-Schiel et al.,
2010).
39
A comparison of species accumulation curves for copepods provided evidence of
a latitudinal decline in copepod species richness along the WA coast, corresponding
with the globally recognised pattern of declining species richness towards the poles in
marine systems (Hillebrand, 2004). This pattern of declining species richness has also
been observed for marine crustaceans and fish along both the west and east coasts of
Australia (O’Hara and Poore, 2000; Fox and Beckley, 2005) and off the coast of South
Africa (Turpie et al., 2000). However, despite the observed latitudinal decline in copepod
species richness, no evidence was found to support a relationship between declining
copepod species diversity and latitude that has been observed for the global oceans
(Rombouts et al., 2009). This study’s findings correspond with observed lack of
latitudinal patterns of species diversity for fish larvae in both southwestern and in
southeastern Australian waters, which similarly found no evidence of declining species
diversity with increasing latitudes (Keane and Neira, 2008; Holliday et al., 2012).
On a temporal scale, a seasonal trend of autumn-winter maxima in copepod
species richness was observed, coincident with a stronger LC, and is likely related to
poleward transport of species in the LC. Positive relationships between zooplankton
species richness and LC strength have previously been revealed, although not across
the entire assemblage (Caputi et al.,1996; Gaughan and Fletcher, 1997; Gaughan et al.
2009). At Rottnest and Esperance, greater species richness also coincided with a peak
in chlorophyll a, which may provide a further explanation for an increase in the number
of copepod species recorded at these sites in autumn-winter.
The average taxonomic distinctness (∆+) test was selected to provide a
complementary view of copepod assemblage biodiversity. An advantage of the test,
which is relevant to this study, is its robustness to different levels of sampling effort and
species numbers (Clarke and Warwick, 1998; Warwick and Clarke, 2001). The test
revealed high similarity in ∆+ values, and little derivation from the mean, which suggests
that, as expected, copepod assemblages had similar levels of complexity but different
compositions. It is also an indication that assemblages were a good representation of
the copepod species pool for WA coastal waters between 22°S and 34°S.
4.3 Dissimilarities in copepod assemblages at the three NRS
Dissimilarities in copepod assemblages between the three NRS were high, and
clear distinctions were observed. This is despite many species’ wide distributions and
apparent lack of preference for oceanographic conditions, inhabiting waters that were
highly oligotrophic, with wide ranging temperatures (16°C – 29°C) and salinities
(34 - 36 psu). Thus, dissimilarities were largely due to differences in proportions and
40
abundances of species, rather than the presence of discriminating species, and was
demonstrated by the fact that >40 species were required to account for 70% of the
dissimilarity between NRS assemblages. The identification of copepod taxa common or
exclusive to NRS suggests a gradual change in composition from north to south, with
the greatest distinctions between copepod assemblages between two NRS most
spatially isolated from each other, Ningaloo and Esperance.
Dissimilarities between the NRS assemblages were weakest in winter and
reflected an enhanced connectivity of WA coastal waters. Alongshore transport of warm
water and its tropical species further south along the WA coast occurs in autumn-winter
when the LC is at maximum strength (Hutchins and Pearce, 1994). This is enhanced by
the low retentive nature of the shelf in the north near Ningaloo, due to nearshore
influence of the LC (Hanson and McKinnon, 2009; Feng et al., 2010). Inundation of the
shelf by the LC results in entrainment of species that are dispersed poleward or across
the shelf (Gaughan et al., 2009; Holliday et al., 2012), influencing the bioregional affinity,
and offshore/inshore component of pelagic assemblages.
Evidence of these processes included a greater number of copepod species
common to all three NRS in winter, coupled with enhanced species richness and
diversity, including of offshore species on the shelf, and tropical species in the south.
Similarly, enhanced species richness and a tropicalisation of macrozooplankton
(Gaughan and Fletcher, 1997) and larval fish assemblages (Muhling and Beckley, 2007;
Holliday et al., 2012) in southwestern and southern shelf waters of WA has been
attributed to advection in the LC. The EAC’s influence in alongshore distribution of
zooplankton and reduced assemblage dissimilarities in southeastern Australian waters
has also been demonstrated (Harris et al., 1991; Booth et al., 2007; Keane and Neira,
2008; Kelly et al., 2016). Like the EAC, the injection of warm, subtropical, low salinity LC
water may be responsible for the increase and persistence of warm water copepod
species at higher latitudes on the WA coast (Gaughan and Fletcher, 1997).
Copepods have been useful in demonstrating changes in marine systems,
particularly in relation to warming trends (Verheye et al., 2016). In this study, tropical
and subtropical affinity copepods appeared as resident populations in southwest and
southern shelf waters. These copepods could be representative of a broad trend of
range extensions and increased abundances of warm-water copepods, and assemblage
shifts towards their dominance in other temperate regions, such as Tasmania (Johnson
et al., 2011), the East China Sea (Tseng et al., 2008), the Southern Benguela (Verheye
and Richardson, 1998; Huggett et al., 2009) and Chesapeake Bay (Kimmel et al., 2012),
as well as the large ocean basins (Beaugrand et al., 2002a; Batten et al., 2011). This
41
may in part be due to behavioural and physiological traits of warm water copepods
which allow them to out-compete other species (Mazzocchi and Paffenhöfer, 1998;
Peralba and Mazzocchi, 2004; Turner, 2004; Duggan et al., 2008; Mackas et al., 2012b).
Observations of tropical pelagic species in WA waters existing beyond their normal
range are not new (eg. Maxwell and Cresswell, 1981). However, a continuous trend of
range extension by tropical species may result in a shift towards a more homogenous
copepod assemblage along the entire WA coast. Continued long-term monitoring is
required to investigate such patterns.
4.4 Oceanographic factors explaining the variability in copepod
assemblage structure at the three NRS
In this study, physical oceanography properties at the NRS (temperature, salinity,
and dissolved oxygen, represented by seawater density, as an indicator of water mass)
were more influential than biogeochemical variables (nutrients and chlorophyll a) in
shaping copepod assemblage structures. DistLM revealed a separation of copepod
assemblages along a gradient of increasing seawater density with latitude, and this was
a significant, but not strong, influence on assemblages. Previous studies of various
plankton groups in WA waters, including larval fish (Muhling and Beckley, 2007; Muhling
et al., 2008; Holliday et al., 2012), krill (Sutton and Beckley, 2016), chaetognaths
(Buchanan and Beckley, 2016) and other macrozooplankton (Sawstrom et al., 2014),
have also observed patterns in assemblage structures that reflected the latitudinal
changes in oceanography and links to water masses.
The latitudinal dissimilarities in copepod assemblage structures were observed to
correspond relatively well to the pelagic bioregions delineated by Lyne and Hayes
(2005), with a gradual change from a mostly tropical-copepod assemblage at Ningaloo,
to a mixed assemblage in the transition zone at Rottnest, and an assemblage with a
stronger warm-temperate component at Esperance. While Ningaloo’s TSW was
generally characterised by high abundances of tropical copepod species, the degree of
dissimilarity among copepod assemblages at the site points to frequent fluctuations in
relative species abundances. This variation may be linked to short-term oceanographic
events that occurred at this NRS during the study period. At Ningaloo, conditions
produced by the La Niña-generated heat wave, and the spring upwelling that appeared
to occur, may have favoured some species of the copepod assemblage. Greater
variance in assemblages at Ningaloo is likely a reflection of species’ varying and
relatively rapid responses to oceanographic forcing.
42
The distribution of Indo-Pacific origin copepod species typically associated with
warm, tropical waters among the three NRS sites varied. While some of these species
were exclusively found at Ningaloo, others did not appear past the tropical-temperate
transition zone at Rottnest. A further group of Indo-Pacific species displayed no
discernible north to south gradient, and appeared to be tolerant of the cooler, denser,
temperate waters at Esperance. This included the copepod species Dioithona oculata,
Dioithona rigida and Temora turbinata in the assemblage at Esperance. Despite this,
fewer tropical species and lower abundances at Esperance, relative to the other NRS
sites, is probably an indication of species’ temperature tolerance limits being reached.
The waters at this NRS were characterised by a predominantly subtropical-temperate
copepod assemblage that consisted of species more typical of the cooler, denser
subtropical waters at Rottnest, than those species found in Ningaloo’s TSW.
The mixed assemblage of tropical, subtropical and temperate copepod species
at Rottnest is a reflection of its location in a region where the LC intrusion occurs (Weller
et al., 2011), and sporadic seasonal Capes upwelling may occur, resulting in variation in
water mass properties that influence the distribution of biota (Lourey et al., 2013). In this
tropical-temperate transition zone, opposing currents cause waters from the north and
south to merge, resulting in an intersection of entrained pelagic species. Similar
overlaps of tropical, subtropical and temperate pelagic fish biota occur in the EAC-
Tasman Sea transition zone on the east coast of Australia, where the convergence of
those waters creates a distinctly mixed pelagic assemblage (Keane and Neira, 2008).
Chlorophyll a also explained some of the variation in copepod assemblage
structure, although its influence was less significant. Species compositions of
assemblages associated with the increased chlorophyll a did not differ markedly, but
were characterised by greater abundances of herbivorous copepods, such as
Clausocalanus spp, Temora spp., Temora turbinata and Paracalanus indicus
(Kouwenberg, 1994), which may be a response to food resources. Previous studies of
copepod assemblages in coastal waters have revealed that opportunistic herbivorous
species can achieve rapid growth rates in response to blooms of chlorophyll a (eg.
Guenther et al., 2008; Rosa et al., 2016), and may also be the case in these waters.
43
4.5 Limitations and future research
Although the DistLM identified statistically significant explanatory variables for
copepod assemblage structure, a high proportion of unexplained variation in the data
remained. Possible explanations for the high degree of unexplained variation, some of
which have been discussed as potential limiting factors in similar studies (eg. Wilson et
al., 2003; Holliday et al., 2011), include highly variable abundance, ubiquitous species,
identification of key taxa to genus level only, uneven sampling effort, lagged responses
by assemblages to oceanographic change, or that other abiotic and biotic factors not
investigated were important influencers.
While further studies may mitigate some of the identified potential model
deficiencies, by, for example, including additional environmental (e.g. wind velocity or
current strength) or biological variables (e.g. predator or phytoplankton abundance) to
investigate additional sources of influence on assemblages, this study highlights the
importance of both the methods and continuity of biological sampling undertaken by
IMOS in coastal waters. The use of a 100 µm mesh sized net by IMOS in its vessel-
based zooplankton sampling is consistent with standardised methods for
mesozooplankton sampling, because it ensures a complete representation of the
assemblage. However, this method can also present challenges for taxonomic
identification due to the collecting of large numbers of copepodites and nauplii, which
are rarely identified to higher taxonomic levels, and thus were excluded from analyses in
this study. However, IMOS quality assurance methods for laboratory analysis, including
the use of expert plankton analysts, ensures high quality level biological data is
maintained (Lynch et al., 2015). The data includes species-level taxonomic identification
for the majority of copepod specimens, and this ultimately provided a sufficiently detailed
data set that enabled robust analyses of this important zooplankton group in this study.
Further limitations in the study were the uneven sampling size and gaps in data,
which are largely a consequence of logistical constraints in carrying out long term,
regular vessel-based sampling of geographically isolated locations (Lynch et al., 2015),
such as Ningaloo and Esperance. The low frequency and short temporal scale of
sampling at these two NRS sites, compared to the more easily accessible Rottnest
NRS, means that these data only represent a snapshot of the assemblages and
oceanographic conditions at these sites in each of the seasons of the year, and does not
capture the subtle changes that may be occurring at these sites. Nonetheless, the data
provided by IMOS for these two relatively under-studied coastal locations, provided
valuable insight into seasonal and interannual variation in their zooplankton and
oceanography.
44
Despite the described challenges, the sustained continuous IMOS ocean
monitoring and vessel-based physical and biological sampling program at Rottnest NRS
provides opportunities to use data as it becomes available to undertake further
investigations into environment-zooplankton relationships in coastal WA waters. The
location of the Rottnest NRS in the tropical-temperate zone provides advantages for
studying these relationships, such as the diversity of its pelagic assemblage and the
complexity of factors influencing the NRS site’s oceanographic conditions. The IMOS
NRS at Rottnest, and more broadly in Australian waters, aligns with a globally
acknowledged necessity for continuous long-term observations of oceans and their biota
to allow comprehensive and robust investigations of abiotic-biotic relationships in marine
systems, and further our understanding of these interactions.
45
5. Conclusion
This study is the first to relate differences in oceanographic conditions to
dissimilarities in coastal zooplankton abundance, biomass and composition in the
northwest, southwest and southern coastal waters off WA. Zooplankton abundance and
biomass varied spatially and temporally, and there were distinct differences in the key
taxa. A latitudinal gradient of change in copepod assemblage composition from tropical
through to more temperate, was related to a gradual change in water mass
characteristics from north to south along the WA coast. Seasonal fluctuations in species
compositions were considerable, and the distribution of species was likely influenced by
LC transport of TSW along the coast. The pelagic assemblages of this region of the
southeast Indian Ocean are vastly understudied compared to other coastal ocean
environments, and there is a large scope for future research in this area, using the
significant amount of environmental and biological data becoming available through
IMOS.
46
6. References
Anderson, M. J. (2005) PERMANOVA: a FORTRAN computer program for
permutational multivariate analysis of variance. Department of Statistics, University of
Auckland.
Anderson, M. J., Gorley, R. and Clarke, K. P. (2008) PRIMER: guide to software and
statistical methods. PRIMER-E, Plymouth, UK, 2008
Australian Bureau of Meteorology (2012) Record-breaking La Niña events. Retrieved
from http://www.bom.gov.au/climate/enso/history/La-Nina-2010-12.pdf, [accessed
August 2016].
Ayon, P., Criales-Hernandez, M. I., Schwamborn, R. and Hirche, H.-J. (2008)
Zooplankton research off Peru: A review. Progress in Oceanography, 79: 235-255.
Batten, S. D. and Walne, A. W. (2011) Variability in northwards extension of warm water
copepods in the NE Pacific. Journal of Plankton Research, 33: 1643-1653.
Beaugrand, G., Ibanez, F., Lindley, J. A., and Reid, P. C. (2002a) Diversity of calanoid
copepods in the North Atlantic and adjacent seas: species associations and
biogeography. Marine Ecology Progress Series, 232: 179-195.
Beaugrand, G., Reid, P. C., and Ibanez, F. (2002b) Major reorganisation of North
Atlantic pelagic ecosystems linked to climate change. GLOBEC International Newsletter,
8: 30-33.
Beaugrand, G. (2005) Monitoring pelagic ecosystems using plankton indicators. ICES
Journal of Marine Science, 62: 333-338.
Benthuysen, J., Feng, M. and Zhong, L. (2014) Spatial patterns of warming off Western
Australia during the 2011 Ningaloo Niño: Quantifying impacts of remote and local
forcing. Continental Shelf Research, 91:232-246.
Booth, D.J., Figueira, W.F., Gregson, M.A., Brown, L. and Beretta,
G. (2007) Occurrence of tropical fishes in temperate southeastern Australia: role of the
East Australian Current. Estuarine and Coastal Shelf Science. 72:102–114.
Buchanan, P. J. and Beckley, L. E. (2016) Chaetognaths of the Leeuwin Current
system: oceanographic conditions drive epi-pelagic zoogeography in the south-east
Indian Ocean, Hydrobiologia, 763 (1), 81-96.
47
Caputi, N., Fletcher, W. J., Pearce, A. and Chubb, C. F. (1996) Effect of the Leeuwin
Current on the recruitment of fish and invertebrates along the Western Australian Coast.
Marine and Freshwater Research, 47, 147–155.
Caputi, N. (2008) Impact of the Leeuwin Current on the spatial distribution of the
puerulus settlement of the western rock lobster (Panulirus cygnus) and implications for
the fishery of Western Australia. Fisheries Oceanography, 17 (2): 147-152.
Chew, L. L. and Chong, V. C. (2016) Response of marine copepods to a changing
tropical environment: winners, losers and implications. PeerJ 4:e2052.
Clarke, K. R. and Ainsworth, M. (1993) A method of linking multivariate community
structure to environmental variables. Marine Ecology Progress Series, 92: 205-219.
Clarke, K. R. and Warwick, R. M. (1998) A taxonomic distinctness index and its
statistical properties. Journal of Applied Ecology, 35: 523–531.
Clarke, K. R. and Warwick, R. M. (2001) Change in Marine Communities: An Approach
to Statistical Analysis and Interpretation, 2nd ed. PRIMER-E, Plymouth.
Clarke, K. R. and Warwick, R. M. (2005) Primer-6 computer program. Natural
Environment Research Council, Plymouth.
Commonwealth of Australia (2006) A guide to the Integrated Marine and Coastal
Regionalisation of Australia Version 4.0. Department of Environment and Heritage,
Canberra, Australia.
Cresswell, G.R. and Golding, T. J. (1980) Observations of a southward flowing current in
the south-eastern Indian Ocean. Deep-Sea Research 27A: 449-466.
Cresswell, G. R. 1991 The Leeuwin Current - observations and recent models. Journal
of the Royal Society of Western Australia 74:1-14.
Cresswell, G. R. and Domingues, C. M. (2009) The Leeuwin Current south of Western
Australia. Journal of the Royal Society of Western Australia, 92: 83–100.
Dahms, H.-U., Tseng, L.-C. and Hwang, J.-S. (2015) Biogeographic distribution of the
cyclopoid copepod genus Oithona – from mesoscales to global scales. Journal of
Experimental Marine Biology and Ecology, 467: 26-32.
Dias, C. O., Araujo, A. V., Vianna, S. C., Loureiro-Fernandes, L. F. Paranhos, R. Suzuki,
M. S. and Bonecker, S. L. C.. (2015) Spatial and temporal changes in biomass,
production and assemblage structure of mesozooplanktonic copepods in the tropical
48
south-west Atlantic Ocean. Journal of the Marine Biological Association of the United
Kingdom, 95(3): 483-496.
Duggan, S., McKinnon, A. D. and Carleton, J. H. (2008) Zooplankton in an Australian
tropical estuary. Journal of the Coastal and Estuarine Research Federation, 31: 455-
467.
Edwards, M., Beaugrand, G., Hays, G. C., Koslow, J. A. and Richardson, A. J. (2010)
Multi-decadal oceanic ecological datasets and their application in marine policy and
management. Trends in Ecology and Evolution, 25 (10): 602 - 610.
Feng, M., Slawinkski, D., Beckley, L. E. and Keesing, J. K. (2010) Retention and
dispersal of shelf waters influenced by interactions of ocean boundary current and
coastal geography. Marine and Freshwater Research, 61: 1259-1267.
Feng, M., McPhaden, M. J., Xie, S. and Hafner, J. (2013) La Niña forces unprecedented
Leeuwin Current warming in 2011. Scientific Reports, 3 (1277).
Fletcher, W. J., Tregonning, R. J. and Sant, G. J. (1994) Interseasonal variation in the
transport of pilchard eggs and larvae off southern Western Australia. Marine Ecology
Progress Series 111, 209–224.
Fox, N. J. and Beckley, L. E. (2005) Priority areas for conservation of Western
Australian coastal fishes: A comparison of hotspot, biogeographical and complementary
approaches. Biological Conservation, 125: 399-410.
Fromentin, J.- M. and Planque, B. (1996) Calanus and environment in the eastern North
Atlantic. II. Influence of the North Atlantic Oscillation on C. finmarchicus and C.
helgolandicus. Marine Ecology Progress Series, 134: 111–118.
Gallienne, C. P. and Robins, D. B. (2001) Is Oithona the most important copepod in the
world's oceans? Journal of Plankton Research, 23: 1421–1432.
Gaughan, D. J., Neira, F. J., Beckley, L. E, and Potter, I. C. (1990). Composition,
seasonality and distribution of ichthyoplankton in the Lower Swan Estuary, south-
western Australia. Australian Journal of Marine and Freshwater Research, 41: 529-543.
Gaughan, D. J. and Potter, I. C. (1994) Relative abundance and seasonal changes in
the macrozooplankton of the Lower Swan Estuary in south-western Australia. Records
of the Western Australian Museum, 16 (4): 461-474.
49
Gaughan, D. J. and Fletcher, W. J. (1997) Effects of the Leeuwin Current on the
distribution of carnivorous macrozooplankton in the shelf waters of southern Western
Australia. Estuarine, Coastal and Shelf Science, 45: 89-97.
Gaughan, D. J., Pearce, A. F. and Lewis, P. D. (2009) Does the poleward boundary
current off Western Australia exert a dominant influence on coastal chaetognaths and
siphonophores? Estuarine, Coastal and Shelf Science, 83 (4): 443-450.
Gersbach, G. H., Pattiaratchi, C. B., Ivey, G. N. and Cresswell, G. R. (1999) Upwelling
on the south-west coast of Australia—source of the Capes Current? Continental Shelf
Research, 19 (3): 363–400.
Gonzalez-Gil, R., Gonzalez Taboada, F., Hofer, J. and Anadon, R. (2015) Winter mixing
and coastal upwelling drive long-term changes in zooplankton in the Bay of Biscay
(1993–2010). Journal of Plankton Research, 37(2): 337–351.
Guenther, M., Gonzalez-Rodriguez, E., Carvalho, W. F., Rezende, C. E.; Mugrabe, G.
and Valentin, J. L. (2008) Plankton trophic structure and particulate organic carbon
production during a coastal downwelling-upwelling cycle. Marine Ecology Progress
Series, 363: 109-119.
Hanson, C. E., Pattiaratchi, C. B., and Waite, A. M. (2005) Seasonal production regimes
off south-western Australia: influence of the Capes and Leeuwin Currents on
phytoplankton dynamics, Marine and Freshwater Research, 56, 1011-1026.
Hanson, C. E. and McKinnon, A. D. (2009) Pelagic ecology of the Ningaloo region,
Western Australia: influence of the Leeuwin Current. Journal of the Royal Society of
Western Australia, 92: 129-137.
Harris, G. P., Griffiths, F. B., Clementson, L. A., Lyne, V. and Der Doe, H. (1991)
Seasonal and interannual variability in physical processes, nutrient cycling and the
structure of the food chain in Tasmanian shelf waters. Journal of Plankton Research, 13:
109-131.
Hays, G. C., Richardson, A. J. and Robinson, C. (2005) Climate change and marine
plankton. Trends in Ecological Evolution, 20: 337–344.
Heron, A. C. (1982) A vertical free fall plankton net with no mouth obstructions.
Limnology & Oceanography, 27(2): 380-383.
50
Hidalgo, P., Escribano, R., Vvergara, O., Jorquera, E., Donoso, K. and Mendoza, P.
(2010) Patterns of copepod diversity in the Chilean coastal upwelling system. Deep Sea
Research Part II: Topical Studies in Oceanography, 57 (24-26): 2089-2097.
Hillebrand, H. (2004) Strength, slope and variability of marine latitudinal gradients.
Marine Ecology Progress Series, 273: 251–267.
Holliday, D., Beckley, L. E., Weller, E. and Sutton, A. L. (2011) Natural variability of
macro-zooplankton and larval fishes off the Kimberley, north-western Australia:
Preliminary findings. Journal of the Royal Society of Western Australia, 94(2): 181-195.
Holliday, D., Beckley, L. E., Millar, N., Olivar, M. P., Slawinski, D., Feng, M. and
Thompson, P. A. (2012) Larval fish assemblages and particle back-tracking define
latitudinal and cross-shelf variability in an eastern Indian Ocean boundary current.
Marine Ecology Progress Series, 460: 127-144.
Huang, Z. and Feng, M. (2015) Remotely sensed spatial and temporal variability of the
Leeuwin Current using MODIS data. Remote Sensing of Environment, 166: 214-232.
Huggett, J., Verheye, H., Escribano, R., and Fairweather, T. (2009) Copepod biomass,
size composition and production in the Southern Benguela: Spatio-temporal patterns of
variation, and comparison with other eastern boundary upwelling systems. Progress in
Oceanography, 83: 197-207.
Hutchins, J. N. and Pearce, A. F. (1994) Influence of the Leeuwin Current on recruitment
of tropical reef fishes at Rottnest Island, Western Australia. Bulletin of Marine Science,
54(1): 245-255.
IMOS (2012) National Reference Stations Biogeochemical Operations - Practical
Handbook, a CSIRO Marine and Atmospheric Research Laboratories Report for
IMOS. IMOS Integrated Marine Observing System, Australia.
Johnson, C. R., Banks, S. C., Barrett, N. S., Cazassus, F., Dunstan, P. K., Edgar, G.
J., Frusher, S. D., Gardner, C., Haddon, M., Helidoniotis, F., Hill, K. L. , Holbrook, N.
J., Hosie, G. W., Last, P. R., Ling, S. D., Melbourne-Thomas, J., Miller, K., Pecl, G.
T., Richardson, A. J., Ridgway, K. R., Rintoul, S. R., Ritz, D. A., Ross, D. J.,
Sanderson, J. C., Shepherd, S. A., Slotwinski, A., Swadling, K. M. and Taw, N.
(2011) 'Climate change cascades: Shifts in oceanography, species' ranges and
subtidal marine community dynamics in eastern Tasmania. Journal of Experimental
Marine Biology and Ecology, 400 (1–2): 17-32.
51
Kane, J. (2013) Long-term abundance and distribution trends of the
Cladoceran Penilia avirostris in the US Northeast Shelf Ecosystem. Journal of the
Northwest Atlantic Fishery Science, 45: 1–10.
Karl, D. M. and Lukas, R. (1996) The Hawaii Ocean Time-series (HOT) program:
Background, rationale and field implementation. Deep Sea Research Part II: Topical
Studies in Oceanography, 43 (2–3): 129-156.
Keane, J. P. and Neira, F. J. (2008) Larval fish assemblages along the south-
eastern Australian shelf: linking meso-scale non-depth-discriminate structure and
water masses. Fisheries Oceanography, 17: 263-280.
Kelly, P., Clementson, L., Davies, C., Croney, S. and Swadling, K. (2016)
Zooplankton responses to increasing sea surface temperatures in the southeasters
Australia global marine hotspot. Estuarine, Coastal and Shelf Science, 180: 242-
257.
Kimmel, D. G., Boynton, W. R. and Roman, M. R. (2012) Long-term decline in the
calanoid copepod Acartia tonsa in central Chesapeake Bay, USA: an indirect effect
of eutrophication? Estuarine, Coastal and Shelf Science, 101: 76-85.
Kimmerer, W. J. and McKinnon, A. D. (1985) A comparative study of the
zooplankton in two adjacent embayments, Port Phillip and Westernport Bays,
Australia. Estuarine, Coastal and Shelf Science, 21: 145-159.
Kimmerer, W. J. and McKinnon, A. D. (1987) Zooplankton in a marine bay. I.
Horizontal distributions used to estimate net population growth rates. Marine Ecology
Progress Series, 41:43-52.
Koslow, J. A., Pesant, S., Feng, M., Pearce, A., Fearns, P., Moore, T., Matear, R. and
Waite, A. (2008) The effect of the Leeuwin Current on phytoplankton biomass and
production off southwestern Australia. Journal of Geophysical Research, 113: C07050.
Kouwenberg, J. H. M. (1994) Copepod distribution in relation to seasonal hydrographics
and spatial structure in the north-western Mediterranean (Golfe du Lion). Estuarine,
Coastal and Shelf Science, 38: 69-90.
Legendre, P. and Anderson, M. J. (1999) Distance-based redundancy analysis: testing
multispecies responses in multifactorial ecological experiments. Ecological Monographs,
69:1–24.
52
Longhurst, A. R. (1985) The structure and evolution of plankton communities. Progress
in Oceanography, 15: 1–35.
Lourey, M. J., Dunn, J. R. and Waring, J. (2006) A mixed-layer nutrient climatology of
Leeuwin Current and Western Australian shelf waters: Seasonal nutrient dynamics and
biomass. Journal of Marine Systems, 59 (1–2), 25-51.
Lourey, M. J., Thompson, P. A., McLaughlin, M. J., Bonham, P. and Feng, M. (2013)
Primary production and phytoplankton community structure during a winter shelf-scale
phytoplankton bloom off Western Australia. Marine Biology, 160 (2), 355-369.
Lynch T. P., Morello, E. B., Evans, K., Richardson, A. J., Rochester, W. Steinberg, C.
R., Roughan, M., Thompson, P., Middleton, J. F., Feng, M. Sherrington, R., Brando, V.,
Tilbrook, B., Ridgway, K., Allen, S., Doherty, P., Hill, K. and Moltmann, T. C.. (2014)
IMOS National Reference Stations: A Continental-Wide Physical, Chemical and
Biological Coastal Observing System. PLoS ONE, 9 (12): e113652.
Lynch, T.P., Morello, E.B., Middleton, J. F., Thompson, P., Feng, M., Richardson, A.,
Doherty, P., Roughan, M., Morris, B., Tilbrook, B., Steinberg, C., James, C., Allen, S.,
Moltmann, T.C. and Hill K. L. (2011) IMOS National Reference Station (NRS) Network -
Rationale, Design and Implementation Plan. Retrieved from
http://imos.org.au/fileadmin/user_upload/shared/ANMN/NRS_rationale_and_implementa
tion_100811.pdf ;[accessed 17 March 2016].
Lyne, V. and Hayes, D. (2005) Pelagic Regionalisation: national marine
bioregionalisation integration project. CSIRO Report to the National Oceans Office.
CSIRO Marine Research, Hobart.
Mackas, D. L., Thomson, R. E. and Galbraith, M. (2001) Changes in the zooplankton
community of the British Columbia continental margin, 1985–1999, and their covariation
with oceanographic conditions. Canadian Journal of Fisheries and Aquatic Sciences, 58:
685–702.
Mackas, D. L., Pepin, P. and Verheye, H. (2012a) Interannual variability of marine
zooplankton and their environments: within- and between region comparisons. Progress
in Oceanography, 97: 1–14.
Mackas, D. L., Greve, W., Edwards, M., Chiba, S., Tadokoro, K., Eloire, D., Mazzocchi,
M. G., Batten, S., Richardson, A. J., Johnson, C., Head, E., Conversi, A. and Peluso, T.
(2012b) Changing zooplankton seasonality in a changing ocean: Comparing time series
of zooplankton phenology. Progress in Oceanography, 97–100: 31-62.
53
Margalef, R. (1958) Modern orientations in Hydrobiology. Scientia, 93 (2):41–46.
Maxwell, J. G. and Cresswell, G. R. (1981) Dispersal of tropical marine fauna to the
Great Australian Bight by the Leeuwin Current. Australian Journal of Marine and
Freshwater Research, 32: 493-500.
McKinnon, A. D. and Thorrold, S. R. (1993) Zooplankton community structure and
copepod egg production in coastal waters of the central Great Barrier Reef. Journal of
Plankton Research, 15 (12): 1387-1411.
Mazzocchi, M. G. and Paffenhöfer, G. A. (1998) First observation on the biology of
Clausocalanus fucastus (Copepoda, Calanoida). Journal of Plankton Research, 20 (2):
331-342.
McKinnon, A. D. and Ayukai, T. (1996) Copepod egg production and food resources in
Exmouth Gulf, Western Australia. Marine and Freshwater Research, 47, 595-603.
McArdle, B. H. and Anderson, M. J. (2001) Fitting multivariate models to community
data: a comment on distance-based redundancy analysis. Ecology, 82, 290–297.
McKinnon, A. D. and Duggan, S. (2003) Summer copepod production in subtropical
waters adjacent to Australia's North West Cape. Marine Biology, 143 (5), 897-907.
McKinnon, A. D., Meekan, M. G., Carleton, J. H., Furnas, M. J., Duggan, S. and
Skirving, W. (2003) Rapid changes in shelf waters and pelagic communities on the
southern Northwest Shelf, Australia, following a tropical cyclone. Continental Shelf
Research, 23: 93–111.
McKinnon, A. D., Duggan, S. and De’ath, G. (2005) Mesozooplankton dynamic in
nearshore waters of the Great Barrier Reef. Estuarine, Coastal and Shelf Science,
63:497-511.
McKinnon, A. D., Duggan, S., Carleton, J., H. and Bottger-Schnack, R. (2008) Summer
planktonic copepod communities of Australia’s North West Cape (Indian Ocean) during
the 1997-99 El Nino/La Nina. Journal of Plankton Research, 30 (7), 839-855.
McKinnon, A. D. and Duggan, S. (2014) Community ecology of pelagic copepods in
tropical coastal waters. In: Seuront, L. (ed). Copepods: Diversity, Habitat and Behaviour.
Nova Science Publishers Inc.,pp 25-49.
McKinnon, A. D., Duggan, S., Holliday, D. and Brinkman, R. (2015) Plankton community
structure and connectivity in the Kimberley-Browse region of NW Australia. Estuarine,
Coastal and Shelf Science, 153: 156-167.
54
Meekan, M. G., Carleton, J. H., Steinberg, C. R., McKinnon, A. D., Brinkman, R.,
Doherty, P. J., Halford, A., Duggan, S. and Mason, L. (2006) Turbulent mixing and
mesoscale distributions of late-stage fish larvae on the NW Shelf of Western Australia.
Fisheries Oceanography, 15(1): 44-59.
Middleton, J. F. and Bye, J. A. T. (2007) A review of the shelf-slope circulation along
Australia’s southern shelves: Cape Leeuwin to Portland. Progress in Oceanography, 75:
1–41.
Muhling, B. A. and Beckley, L. E. (2007) Seasonal variation in horizontal and vertical
structure of larval fish assemblages off south-western Australia, with implications for
larval transport. Journal of Plankton Research, 29 (11): 967-983.
Muhling, B. A., Beckley, L. E., Koslow, J. A. and Pearce, A. F. (2008) Larval fish
assemblages and water mass structure off the oligotrophic south-western Australian
coast, Fisheries Oceanography, 17 (1), 16-31.
O'Hara, T. D. and Poore, G. C. B. (2000) Patterns of distribution for southern Australian
marine echinoderms and decapods. Journal of Biogeography, 27: 1321-1335.
Paterson, H. L., Knott, B. and Waite, A. M. (2007) Microzooplankton community
structure and grazing on phytoplankton, in an eddy pair in the Indian Ocean off Western
Australia. Deep Sea Research Part II: Topical Studies in Oceanography, 54 (8–10):
1076-1093.
Pearce, A. F. 1991 Eastern boundary currents of the southern hemisphere. Journal of
the Royal Society of Western Australia 74:35-45.
Pearce, A. F. and Phillips, B. F. (1988) ENSO events, the Leeuwin Current, and larval
recruitment of the western rock lobster. Journal of Conservation, 45: 13-21.
Pearce, A. F. and Feng, M. (2013) The rise and fall of the “marine heat wave” off
Western Australia during the summer of 2010/2011. Journal of Marine Systems, 111-
112: 139-156.
Pearce, A. and Pattiaratchi, C. (1999) The Capes Current: a summer countercurrent
flowing past Cape Leeuwin and Cape Naturaliste, Western Australia, Continental Shelf
Research, 19 (3), 401-420.
Pearce, A., Slawinski, D., Feng, M., Hutchins, B. and Fearns, P. (2011) Modelling the
potential transport of tropical fish larvae in the Leeuwin Current. Continental Shelf
Research, 31 (19-20): 2018-2040.
55
Peralba, A. and Mazzocchi, M. G. (2004) Vertical and seasonal distribution of eight
Clausocalanus species (Copepoda: Calanoida) in oligotrophic waters, Journal of Marine
Science, 61 (4):645-653.
Pillar, S. C. (1986) Temporal and spatial variations in copepod and euphausiid biomass
off the southern and south-western coasts of South Africa in 1977/71. South African
Journal of Marine Science, 4: 219-229.
Pretorius, M., Hugget, J. A. and Gibbons, M. J. (2016) Summer and winter differences in
zooplankton biomass, distribution and size composition in the KwaZulu-Natal Bight,
South Africa. African Journal of Marine Science, 38: 155-168.
R Core Team (2013) R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. (http://www.R-project.org/.)
Razouls C., de Bovée F., Kouwenberg J. et Desreumaux, N., (2005-2016) Diversity and
Geographic Distribution of Marine Planktonic Copepods. Retrieved from
http://copepodes.obs-banyuls.fr/en [Accessed August 6, 2016].
Richardson, A. J., Walne, A. W., John, A. W. G., Jonas, T. D., Lindley, J. A., Sims, D.
W., Stevens, D. and Witt, M. (2006) Using continuous plankton recorder data. Progress
in Oceanography, 68: 27-74.
Richardson, A. J. (2008) In hot water: zooplankton and climate change. Journal of
Marine Science, 65: 279–295.
Ridgway, K. R. and Condie, S. A. (2004) The 5500 km long boundary flow off western
and southern Australia. Journal of Geophysical Research, 109: C04017.
Ridgway, K. R. and Godfrey, J. S. (2015) The source of the Leeuwin Current
seasonality. Journal of Geophysical Research: Oceans, 120: 6843 – 6864.
Rombouts, I., Beaugrand, G., Ibaňez, F., Gasparini, S., Chiba, S., and Legendre, L.
(2009) Global latitudinal variations in marine copepod diversity and environmental
factors. Proceedings of the Royal Society B: Biological Sciences, 276 (1670): 3053–
3062.
Rosa, J. C. L, Monteiro-Ribas, W. M. and Fernandes, L. D. A. (2016) Herbivorous
copepods with emphasis on dynamic Paracalanus quasimodo in an upwelling region.
Brazilian Journal of Oceanography, 64 (1): 67-73.
56
Rosseaux, C. S. G., Lowe, R., Feng, M., Waite, A. M. and Thompson, P. A. (2012) The
role of the Leeuwin Current and mixed layer depth on the autumn phytoplankton bloom
off Ningaloo Reef, Western Australia. Continental Shelf Research, 32: 22-35.
Rossi, V., Feng, M., Pattiaratchi, C., Roughan, M. and Waite, A. M. (2013a) Linking
synoptic forcing and local mesoscale processes with biological dynamics off Ningaloo
Reef. Journal of Geophysical Research: Oceans, 118: 1211-1225.
Rossi, V., Feng, M., Pattiaratchi, C., Roughan, M. and Waite, A. M. (2013b) On the
factors influencing the development of sporadic upwelling in the Leeuwin Current
system. Journal of Geophysical Research: Oceans, 118: 3608-3621.
Sawstrom, C., Beckley, L. E., Saunders, M. I., Thompson, P. A. and Waite, A. M. (2014)
The zooplankton prey field for rock lobster phyllosoma larvae in relation to
oceanographic features of the south-eastern Indian Ocean. Journal of Plankton
Research, 36 (4), 1003-1016.
Shannon, C. (1948) A mathematical theory of communication. Bell System Technical
Journal, 27: 379–423.
Schnack-Shiel, S. B., Mizdalski, E. and Cornils, A. (2010) Copepod abundance and
species composition in the Eastern subtropical/tropical Atlantic. Deep-Sea Research II,
57: 2062-2075.
Strzelecki, J., Koslow, J. A. and Waite, A. (2007) Comparison of mesozooplankton
communities from a pair of warm- and cold-core eddies off the coast of Western
Australia, Deep-Sea Research Part II, 54, 1102-1112.
Suthers, I. M. and Rissik, D. (2009) Plankton: A guide to their ecology and monitoring for
water quality. CSIRO Publishing, Collingwood. 272p.
Sutton, A. L. and Beckley, L. E. (2016) Influence of the Leeuwin Current on the
epipelagic euphausiid assemblages of the south-east Indian Ocean. Hydrobiologia, 774
(1): 193-207.
Thompson, P. A., Baird, M. E., Ingleton, T. and Doblin, M. A. (2009) Long-term changes
in temperate Australian coastal waters: implications for phytoplankton. Marine Ecology
Progress Series, 394:1-19.
Thompson, P. A., Wild-Allen, K., Lourey, M., Rousseaux, C., Waite, A. M., Feng, M. and
Beckley, L. E. (2011) Nutrients in an oligotrophic boundary current: evidence of a new
role for the Leeuwin Current. Progress in Oceanography, 91: 345–359.
57
Tranter, D. J. (1962) Zooplankton abundance in Australasian waters. Australian Journal
of Marine and Freshwater Research, 13: 106-142.
Tranter, D. J. and Kerr, J. D. (1969) Seasonal variations in the Indian Ocean along
110⁰E. Australian Journal of Marine and Freshwater Research, 20: 77-84.
Tranter, D. J. and Kerr, J. D (1977) Further studies of plankton ecosystems in the
Eastern Indian Ocean II. Numerical abundance and biomass. Australian Journal of
Marine and Freshwater Research, 28: 557-583.
Tseng, L.-C., Souissi, S., Dahms, H.-U., Chen, Q-C. and Hwang, J. S. (2008) Copepod
communities related to water masses in the southwest East China Sea. Helgoländer
Marine Research, 62, 153-165.
Turner, J. T. (2004) The importance of small planktonic copepods and their roles in
pelagic marine food webs. Zoological Studies, 432: 255-266.
Turpie, J. K., Beckley, L. E. and Katua, S. M. (2000) Biogeography and the selection of
priority areas for conservation of South African coastal fishes. Biological Conservation,
92 (1): 59-72.
Twomey, L. J., Waite, A. M., Pez, V. and Pattiaratchi, C. B. (2007) Variability in nitrogen
uptake and fixation in the oligotrophic waters off the south west coast of Australia. Deep-
Sea Research II, 54: 925-942.
Van Ruth, P. D. and Ward, T. M. (2009) Meso-zooplankton abundance, distribution and
community composition in the eastern Great Australian Bight. Transactions of the Royal
Society of South Australia, 133:2, 274-283.
Verheye, H. M. and Richardson, A. J. (1998) Long-term increase in crustacean
zooplankton abundance in the southern Benguela upwelling region (1951-1996):
bottom-up or top-down control? Journal of Marine Science, 55: 803-807.
Vreheye, H. M., Lamont, T., Hugget, J. A., Kreiner, A. and Hampton, I. (2016) Plankton
productivity of the Benguela Current Large Marine Ecosystem (BCLME). Environmental
Development, 17: 75-92.
Waite, A. M., Thompson, P. A., Pesant, S., Feng, M., Beckley, L. E., Domingues, C.
M., Gaughan, D., Hanson, C. E., Holl, C. M., Koslow, T., Meuleners, M., Montoya, J. P.,
Moore, T., Muhling, B. A., Paterson, H., Rennie, S., Strzelecki, J. and Twomey, L.
(2007) The Leeuwin Current and its eddies: An introductory overview. Deep-Sea
Research II, 54: 789-796.
58
Warwick, R. M. and Clarke, K. R. (1998) Taxonomic distinctness and environmental
assessment. Journal of Applied Ecology, 35: 532–543.
Warwick, R. M. and Clarke, K. R (2001) Practical measures of marine biodiversity based
on relatedness of species. Oceanography and Marine Biology: An Annual Review, 39:
207–231.
Weller, E., Holliday, D., Feng, M., Beckley, L. and Thompson, P. (2011) A continental
shelf scale examination of the Leeuwin Current off Western Australia during the austral
autumn-winter. Continental Shelf Research, 31: 1858-1868.
Wilson, S. G., Carleton, J. H. and Meekan, M. G. (2003) Spatial and temporal patterns in
the distribution and abundance of macrozooplankton on the southern North West Shelf,
Western Australia. Estuarine, Coastal and Shelf Science, 56, 897-908.
Woo, M., Pattiaratchi, C. and Schroeder, W. (2006) Dynamics of the Ningaloo Current
off Point Cloates, Western Australia. Marine and Freshwater Research, 57: 291-301.
Woo, M. and Pattiaratchi, C. (2008) Hydrography and water masses off the Western
Australian coast. Deep-Sea Research I, 55:1090-1104.
Young, J. W., Bradford, R. W., Lamb, T. D. and Lyne, V. D. (1996) Biomass of
zooplankton and micronekton in the southern bluefin tuna fishing grounds off eastern
Tasmania. Australia, Marine Ecology Progress Series, 138: 1-14.
59
Appendix 1 – Sea surface temperature images corresponding to the IMOS
zooplankton sampling dates in 2011 and 2012.
Images sourced from the IMOS Ocean Current website, available at http://oceancurrent.imos.org.au/ [accessed May 2016].
Ningaloo
2011 2012
9/02/2011 29/02/2012
(Image for 26/02/2012 not available)
1/05/2011 9/05/2012
60
Ningaloo
2011 2012
6/07/2011 27/08/2012
7/11/2011 7/11/2012
61
Esperance
2011 2012
20/01/2011 9/03/2012
12/05/2011 12/06/2012
62
Esperance
2011 2012
18/08/2011 10/09/2012
30/11/2011 12/12/2012
63
Rottnest
2011
25/01/2011 24/02/2011
24/03/2011 27/05/2011
22/06/2011 25/07/2011
64
Rottnest
2011
26/08/2011 23/09/2011
20/10/2011 22/11/2011
21/12/2011
65
Rottnest
2012
30/01/2012 29/02/2012 (NB 21/02/2012 not available)
29/03/2012 4/05/2012
23/05/2012 27/07/2012
66
Rottnest
2012
24/08/2012 28/09/2012
19/10/2012 26/11/2012
19/12/2012
67
Appendix 2 – Seasonal mean zooplankton abundance and biomass
a b
c d
e) f)
Figure 23. Seasonal variation of mean zooplankton abundance and biomass recorded at a) and b) Ningaloo, c) and d) Rottnest, e) and f) Esperance. Error bars are standard error of the mean
68
Appendix 3 – List of all zooplankton taxa recorded by IMOS at the three NRS in 2011 and 2012
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Retaria 109 165 132
(Foraminifera) Unidentified Unidentified Unidentified Unidentified 109 138 132
(Radiolaria) Unidentified Unidentified Unidentified Unidentified 0 27 0
Ciliophora 192 36 46
Oligotrichea Tintinnida Ascampbelliellidae Ascampbelliella spp. 0 0 3
Cyttarocylididae Cyttarocylis spp. 184 4 0
Tintinnidae Unidentified 8 32 0
Undellidae Undella spp. 0 0 43
Cnidaria 152 283 123
Hydrozoa Anthoathecata Pandeidae Amphinema spp. 0 11 0
Calycophoraa Unidentified Unidentified 35 24 0
Narcomedusae Aeginidae Solmundella bitentaculata 21 8 0
Siphonophorae Abylidae Abylopsis eschscholtzii 4 0 0
Bassia bassensis 0 2 0
Diphyidae Eudoxoides spiralis 0 8 0
Lensia spp. 4 11 0
Unidentified 11 7 0
Unidentified Unidentified 0 61 8
Trachymedusae Rhopalonematidae Aglaura hemistoma 13 31 0
Anthomedusae Unidentified Unidentified 0 6 0
69
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Cnidaria Hydrozoa Unidentified Unidentified Hydroid, Hydromedusae, Medusa 66 114 115
Ctenophora 4 0
0
Unidentified Unidentified Unidentified Unidentified 4 0 0
Platyhelminthes 0 3 0
Unidentified Unidentified Unidentified Unidentified 0 3 0
Annelida 426 409 176
Polychaeta Unidentified Unidentified Unidentified 426 409 176
Bryozoa 127 1518 790
Unidentified Unidentified Unidentified 127 1518 790
Mollusca 3113 6954 6152
Bivalvia Unidentified Unidentified Unidentified 1471 4667 4240
Gastropoda Thecosomata Cavoliniidae Unidentified 9 38 35
Cliidae Clio spp. 21 0 8
Creseidae Creseis spp. 7 8 240
Limacinidae Limacina spp. 664 1913 0
Unidentified Unidentified Gastropod, Prosobranch 941 329 1629
70
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda 32267 61805 38988
(Crustacea) Branchiopoda Cladocera Podonidae Evadne spinifera 0 187 173
Podon intermedius 0 0 24
Pseudevadne tergestina 2 1365 79
Sididae Penilia avirostris 0 2641 6241
Cirripedia Unidentified Unidentified Unidentified 86 28 131
Arthropoda Copepoda Calanoida Acartiidae Acartia (Acanthacartia) fossae 20 248 0
(Crustacea) Acartia (Acanthacartia) sinjiensis 0 4 0
Acartia (Acanthacartia) tonsa 217 808 527
Acartia (Acartia) danae 28 6 0
Acartia (Acartia) negligens 6 6 0
Acartia (Acartiura) clausi 0 0 8
Acartia (Acartiura) simplex 2 32 8
Acartia (Odontacartia) pacifica 7 9 0
Acartia spp. 283 1326 893
Aetideidae Aetideus acutus 0 2 0
Augaptilidae Haloptilus longicornis 0 0 4
Calanidae Canthocalanus pauper 127 521 42
Cosmocalanus darwinii 17 1 0
Mesocalanus tenuicornis 22 13 0
Nannocalanus minor 44 53 8
71
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Calanoida Calanidae Neocalanus gracilis 6 0 0
(Crustacea) Undinula vulgaris 39 17 12
Calanoid juvenile 9024 8445 10006
Candaciidae Candacia bradyi 3 13 8
Candacia catula 0 0 31
Candacia discaudata 14 0 0
Candacia spp. 24 12 28
Candacia truncata 4 0 0
Centropagidae Centropages furcatus 10 0 8
Centropages orsinii 0 16 0
Centropages spp. 4 0 0
Clausocalanidae Clausocalanus arcuicornis 18 97 62
Clausocalanus furcatus 32 2424 736
Clausocalanus ingens 15 0 0
Clausocalanus jobei 6 58 0
Clausocalanus mastigophorus 0 8 0
Clausocalanus minor 0 8 0
Clausocalanus parapergens 6 8 0
Clausocalanus paululus 170 24 31
Clausocalanus pergens 6 0 0
Clausocalanus spp. 115 288 1064
Ctenocalanus vanus 0 4 4
Clausocalanus farrani/jobei 74 42 81
72
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Calanoida Eucalanidae Eucalanus spp. 0 94 8
(Crustacea) Pareucalanus attenuatus 7 11 0
Pareucalanus sewelli 0 8 0
Euchaeta concinna 0 1 0
Euchaeta marinella 0 4 0
Euchaeta spp. 98 60 16
Eucalanidae juvenile 31 52 0
Lucicutiidae Lucicutia spp. 11 8 0
Paracalanidae Acrocalanus gibber 27 55 0
Acrocalanus gracilis 28 81 55
Acrocalanus monachus 12 16 0
Acrocalanus spp. 3 2 0
Bestiolina similis 362 25 43
Calocalanus pavo 16 75 28
Calocalanus plumulosus 11 0 0
Calocalanus spp. 227 440 0
Calocalanus styliremis 0 4 12
Calocalanus tenuis 7 0 4
Delibus nudus 86 77 0
Mecynocera clausi 11 68 12
Mecynocera spp. 21 0 0
Paracalanus aculeatus 271 312 139
Paracalanus indicus 505 1483 147
73
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Calanoida Paracalanidae Paracalanus spp. 96 35 65
(Crustacea) Parvocalanus crassirostris 702 65 24
Parvocalanus spp. 14 0 0
Pontellidae Calanopia spp. 16 0 0
Labidocera farrani 0 8 0
Labidocera minuta 0 8 0
Labidocera spp. 14 8 0
Pontellidae Pontella spp. 0 0 16
Pontellopsis krameri 0 0 8
Unidentified 0 8 0
Rhincalanidae Rhincalanus cornutus 4 0 0
Scolecitrichidae Scolecithrix danae 4 8 0
Subeucalanus pileatus 6 0 0
Unidentified 0 8 0
Temoridae Temora discaudata 11 12 0
Temora spp. 46 227 275
Temora turbinata 14 723 115
Tortanus (Tortanus) barbatus 7 0 0
Tortanus spp. 0 8 85
Unidentified Copepod juvenile, Nauplii calanoid
2126 15233 5722
74
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Cyclopoida Corycaeidae Agetus flaccus 0 8 8
(Crustacea) Agetus limbatus 0 2 0
Agetus typicus 0 1 0
Corycaeus clausi 6 0 0
Corycaeus crassiusculus 0 31 0
Corycaeus speciosus 28 123 26
Corycaeus spp. 0 8 0
Corycaeus vitreus 0 4 0
Ditrichocorycaeus andrewsi 9 0 16
Ditrichocorycaeus anglicus 4 8 24
Ditrichocorycaeus asiaticus 6 39 0
Ditrichocorycaeus aucklandicus 0 0 39
Ditrichocorycaeus dahli 108 223 8
Ditrichocorycaeus erythraeus 34 55 0
Ditrichocorycaeus lubbocki 0 24 0
Ditrichocorycaeus minimus 0 0 16
Ditrichocorycaeus subtilis 0 16 0
Farranula carinata 0 16 8
Farranula concinna 38 43 0
Farranula curta 18 47 55
Farranula gibbula 20 24 0
Farranula rostrata 0 8 0
Farranula spp. 114 173 0
75
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Cyclopoida Corycaeidae Onychocorycaeus agilis 27 110 0
(Crustacea) Onychocorycaeus giesbrechti 0 16 0
Onychocorycaeus latus 35 0 26
Onychocorycaeus pacificus 0 11 0
Unidentified 715 897 313
Lubbockiidae Lubbockia spp. 42 0 0
Lubbockia squillimana 0 12 0
Oithonidae Dioithona oculata 57 0 242
Dioithona rigida 377 1120 853
Oithona atlantica 107 112 0
Oithona attenuata 66 9 279
Oithona australis 4 0 0
Oithona brevicornis 0 12 259
Oithona fallax 71 0 0
Oithona (“Grp3 (pointy head”) 0 0 24
Oithona longispina 0 61 0
Oithona nana 1102 740 151
Oithona plumifera 186 314 303
Oithona setigera 6 86 20
Oithona similis 81 259 0
Oithona simplex 495 259 31
Oithona spp. 8933 8406 6513
76
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Cyclopoida Oithonidae Oithona tenuis 62 146 0
(Crustacea) Paroithona spp. 11 0 0
Oithona decipiens/similis 122 283 324
Oncaeidae Oncaea clevei 44 55 0
Oncaea media 83 272 0
Oncaea mediterranea (“complex”) 20 67 0
Oncaea paraclevei 12 0 0
Oncaea scottodicarloi 20 166 28
Oncaea spp. 777 2330 198
Oncaea venusta (“complex”) 0 8 24
Oncaea venusta (“medium”) 0 12 0
Oncaea venusta (“medium no hump”) 11 8 24
Oncaea venusta typica 4 47 115
Oncaea venusta venella 0 20 17
Oncaea venusta venella (“hump”) 0 8 0
Oncaea venusta venella (“no hump”) 0 24 0
Oncaea waldemari 0 34 33
Triconia dentipes complex 4 0 0
Triconia spp. 0 48 8
Sapphirinidae Sapphirina scarlata 6 0 0
Unidentified Nauplii cyclopoid 863 1581 0
77
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Arthropoda Copepoda Harpacticoida Ectinosomatidae Microsetella norvegica 278 558 1335
(Crustacea) Microsetella rosea 77 359 177
Microsetella spp. 32 241 20
Euterpinidae Euterpina acutifrons 1037 1096 305
Miraciidae Macrosetella gracilis 38 130 16
Oculosetella gracilis 0 3 0
Peltidiidae Clytemnestra scutellata 7 4 3
Clytemnestra spp. 7 9 0
Unidentified Harpacticoid, Nauplii 60 390 84
Unidentified Unidentified Copepod nauplii 118 1647 0
Arthropoda Facetotecta Hansenocarididae Unidentified 0 11 0
(Crustacea)
Arthropoda Malacostraca Amphipoda Unidentified Unidentified 42 31 3
(Crustacea) Decapoda Luciferidae Lucifer spp. 4 39 0
Unidentified Unidentified 265 328 38
Euphausiacea Euphausiidae Unidentified 155 2 16
Isopoda Unidentified Unidentified 25 82 8
Mysida Mysidae Unidentified 0 2 8
Ostracoda Unidentified Unidentified Unidentified 171 551 16
78
Mean abundance (ind. m-3)
Phylum (Subphylum) Class Order Family Species / Taxon Ningaloo Rottnest Esperance
Echinodermata 125 136 427
Unidentified Unidentified Unidentified Unidentified 125 136 427
Chaetognatha 867 955 102
Sagittoidea Aphragmophora Sagittidae Flaccisagitta enflata 14 75 0
Zonosagitta pulchra 394 0 0
Unidentified 459 880 102
Chordata 3283 4901 1360
(Tunicata) Appendicularia Copelata Fritillaridae Fritillaria pellucida 15 0 0
Unidentified 238 251 8
Oikopleuridae Unidentified 3002 4313 989
Ascidiacea Unidentified Unidentified Unidentified 0 17 0
Thaliacea Doliolida Doliolidae Doliolum denticulatum 0 8 0
Doliolum nationalis 0 38 0
Doliolum spp. 24 153 363
Salpida Salpidae Thalia democratica 2 57 0
(Vertebrata) Teleostei Unidentified Unidentified Fish larvae 2 64 0
