ELLENBOYLEN_THESIS_FOXFISH

Ellen Boylen
June 2015
This thesis is presented as part of the requirements for
the Degree of Bachelor of Science in Marine Science
with Honours at Murdoch University
Factors affecting the growth of the Foxfish
Bodianus frenchii on the south and lower west
coasts of Western Australia

1
Declaration
I declare that the work presented here is my own research conducted from March to
October 2014, and has not been submitted for the award of any other degree at another
tertiary institution.
Elle Boylen
June 2015
Cover photograph: "Curious Foxfish at Rottnest Island, Western Australia"
Taken by Ellen Boylen, 2014

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Abstract
The Foxfish Bodianus frenchii is a long-lived labrid that is endemic to Western
Australia, where it lives in shallow coastal reefs on the lower west and cooler south
coasts. A hybrid of sclerochronological techniques, Pearson’s correlation coefficient
and additive mixed modelling was used to determine whether the pattern of growth of
the otoliths of B. frenchii was related to temperature over the year, seasonally and or to
the warmer months of the year. Emphasis was placed on testing the hypothesis that the
strength of the relationships between otolith growth and temperature variables is greater
on the lower west than south coast as actual temperatures and temperature range in any
given month are greater on that coast and the temperatures varied more between years.
Focus was also placed on determining whether the pattern of otolith growth of B.
frenchii on the lower west coast was related to sea level height on that coast, an
indicator of the strength of the Leeuwin Current. No attempt was made to relate otolith
growth with sea level height on the south coast as the Leeuwin current flows well
offshore on that coast.
Successive growth increments in the transverse sections of the otoliths of 53
B. frenchii, comprising adjacent translucent and opaque zones, were measured and
aligned according to year, using the increment width for the year of capture as the
anchor. Visual examination of the time series of individual increment widths for all
otoliths of individuals for each coast separately was undertaken to determine whether
the widths of the increments, i.e. narrow or wide, of each otolith corresponded. The
widths of the sequential increments of the different otoliths did not match, a common
feature of otoliths in which all increment widths are very narrow. Further attempts to
cross date the increment widths in the time series for each otolith, i.e. aimed at matching
corresponding increment widths, was thus undertaken using a statistical approach. This

3
was also not entirely successful. Subsequent analyses thus continued to use the year of
capture as the anchor aligning the otolith width of the different years for individuals on
both coasts.
The next step was detrending, whereby age-related declines in otolith growth are
removed, while at the same time preserving any climate signals present in the increment
width time series. Various detrending techniques have been used in otolith-based
increment width studies. A visual assessment of the results of different types of
detrending procedures demonstrated that the double detrending method provided the
best fit for the B. frenchii increment width data.
The detrended time series for the increment widths for each otolith of B. frenchii
was used to calculate a mean index chronology (MIC) for otoliths from individuals from
both the south and lower west coast populations. These MICs were then employed to
determine whether the trends in the otolith increment widths were related to the
environmental variables given earlier. Note that year in this study corresponds to the
July (mid-winter) of one year to June (early-winter) of the following year so that each
year encompasses the main growth period, i.e. spring to autumn. As each year
encompasses the last two months of winter of one year and the first month of winter of
the next year, it is inappropriate to test for differences between winters.
The pattern of change in MICs with age for B. frenchii on the lower west and
south coasts were similar, demonstrating that although actual temperatures varied
appreciably between the two coasts, the pattern of growth was influenced by the similar
overall trends.
On the basis of Pearson’s correlation coefficient, the MIC for B. frenchii on the
south coast was positively correlated with mean annual SST (r = 0.32, P = 0.02) and, to
a slightly greater extent, for this species on the lower west coast (r = 0.37, P = 0.007).

4
The MIC for B. frenchii on the south coast was not related, however, to SST when
considered in the context of seasons or months. In contrast, the MIC for B. frenchii on
the lower west coast was related individually to spring, summer and autumn (r = 0.39, P
= 0.004) and thus to the times of year when temperatures were greatest and most growth
would be expected to occur.
The relationships between MICs and temperature were next explored using
generalized additive mixed modeling (GAMM), which permitted the age of each fish at
each increment and a random individual effect to be incorporated. The GAMM results
demonstrated that the MICs for B. frenchii were positively correlated with mean annual
SST for individuals on both the lower west and south coasts, with the relationship being
stronger for the former coast. These results parallel those of the Pearson’s correlation
coefficients.
Pearson’s correlation coefficients demonstrated that the MIC for B. frenchii was
not correlated with mean annual FSL for the population on the lower west coast and the
same was true for the MIC on both a seasonal and monthly basis. On the basis of
GAMM, the MIC for B. frenchii on the lower west coast was strongly (P = 0.008)
related to sea level height, contrasting the result of the Pearson’s correlation coefficient.
The results, derived from Pearson’s correlation coefficient, and by the use of
GAMM validate the hypothesis that otolith growth in B. frenchii are correlated with
water temperature and, to a slightly greater extent, on the lower west than south coasts.
They also demonstrate a relationship between otolith growth and sea level on the lower
west coast.

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Acknowledgements
I would like to thank my primary supervisors Peter Coulson and Ian Potter for their
guidance and patience.
I would also like to thank my "unofficial" supervisors Adrian Hordyk and Norm Hall
for their endless technical expertise and time.
Thank you to my parents Greg and Deb for their unwavering support and belief in my
abilities.
Special thanks to Justine Arnold and Nicholas Zebegew for the emotional support and
last minute advice.
Without all of you, I would not be where I am today.

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Table of Contents
Declaration........................................................................................................................1
Abstract .............................................................................................................................2
Acknowledgements...........................................................................................................5
Table of Contents..............................................................................................................6
List of Figures ...................................................................................................................8
List of Tables & Equations .............................................................................................10
Introduction.....................................................................................................................12
Objectives........................................................................................................19
Materials & Methods.......................................................................................................21
Sample collection............................................................................................21
Otolith preparation, imaging and increment measurement.............................22
Cross dating, detrending and otolith chronology construction .......................25
Analysis...........................................................................................................27
Data Exploration .........................................................................................29
Environmental Data ........................................................................................29
Results.............................................................................................................................31
Biological data ................................................................................................31
Cross dating and synchrony among individuals within ..................................31
Detrending.......................................................................................................35
Synchrony between regions ............................................................................38
Correlations with environmental variables .....................................................38
Sea Surface Temperature ............................................................................38
Fremantle sea level......................................................................................42

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Discussion .......................................................................................................................45
Selection of otoliths and sample sizes.............................................................45
Cross dating and synchrony among individuals .............................................46
Detrending.......................................................................................................48
Synchrony between regions ............................................................................49
Financial year vs. calendar year......................................................................50
Relationships between MIC and environmental variables..............................52
References.......................................................................................................................56
Appendix.........................................................................................................................66
List of figures ..................................................................................................66
Data Exploration .............................................................................................67
Outliers........................................................................................................67
Homogeneity...............................................................................................69
Normality ....................................................................................................70
Independence...............................................................................................71
Motivation for Modeling.............................................................................73
Power Analysis................................................................................................73

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List of Figures
Figure 1. Mean annual values for a) sea surface temperatures (°C) at Rottnest Island on
the lower west coast and at Esperance on the south coast of Western Australia and b)
sea level (cm) at Fremantle. .................................................................................. 18
Figure 2. Map of south-western Australia showing the location of where samples of
Bodianus frenchii were collected from waters near Rottnest, on the lower west coast,
and Esperance, on the south coast. Red dots denote the approximate location for which
sea surface temperature data was obtained. .......................................................... 22
Figure 3. a) The sectioned otolith of a 51 year old Bodianus frenchii and a b) higher
magnification image of part of the dorsal side of the otolith were increment
measurements were undertaken. In a) white dots indicate the first and every tenth
opaque zone and vertical black lines are indicative of the axis followed when measuring
increments. In b) horizontal white lines show the position of the outer edge of each
opaque zone........................................................................................................... 24
Figure 4. A visual representation of the successive increment widths of the 29 Bodianus
frenchii individuals from the south coast used to assist in visually identifying
synchronous patterns in those widths. Numbers on the left and right y-axis are
identifying codes for individual fish. .................................................................... 33
frenchii individuals from the lower west coast used to assist in visually identifying
identifying codes for individual fish. .................................................................... 33
Figure 6. A visual representation of the statistical cross-dating of the standardized raw
increment time series for the 29 individual Bodianus frenchii from the south coast. Blue
correlates well (p-values less or equal to the user-set critical value) while potential
dating problems are indicated by the red segments (p-values greater than the user set

9
critical value). Green lines show segments that do not completely overlap the time
period and thus have no correlations calculated (Bunn 2010). ............................. 34
increment time series for the 24 individual Bodianus frenchii from the lower west coast.
Blue correlates well (p-values less or equal to the user-set critical value) while potential
dating problems are indicated by the red segments (p-values greater than the user set
critical value). Green lines show segments that do not completely overlap the time
period and thus have no correlations calculated (Bunn 2010). ............................. 34
Figure 8. Comparisons of the a, b) raw chronologies, c, d) negative exponential and e, f)
cubic smoothing spline g, h) double detrending methods for individuals of Bodianus
frenchii (grey lines) from the south (blue lines) and lower west (red lines) coasts of
Western Australia.................................................................................................. 37
Figure 9. a) A comparison of the mean index chronologies (MIC) for Bodianus frenchii
from the south (blue line) and lower west coasts (red line) and a comparison of the MIC
for B. frenchii from the b) south and c) lower west coasts and mean annual sea surface
temperature (black line) in those regions and comparison of the MIC for Bodianus
frenchii from the lower west and d) mean annual Fremantle sea level (black line) for the
years between 1954 and 2005. .............................................................................. 39
Figure 10. Three dimensional visualizations of the generalised additive mixed models
displaying the relationship between a) the otolith growth of Bodianus frenchii on the
south coast and SST and otolith growth of B. frenchii on the lower west coast and b)
SST and c) FSL. x, environmental variable; y, mean increment chronology; z, smoother
of age..................................................................................................................... 44

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List of Tables & Equations
Table 1. Examples of the different detrending methods employed in otolith based
increment width chronology studies on fish species with varying times series length and
sample size. ........................................................................................................... 15
Table 2. Length and age range, method of capture and sex of the individuals of
Bodianus frenchii from the south and lower west coasts of Western Australia used in the
this study. .............................................................................................................. 32
Table 3. Time series range, mean increment size, interseries correlation, mean
sensitivity and standard deviation in the individual time series for Bodianus frenchii
chronologies for the south and lower west coasts and both coasts combined. n = sample
size......................................................................................................................... 32
Table 4. The expressed population signal (EPS) and 𝑟 values for the raw chronologies,
and the increment widths for Bodianus frenchii on the south and lower west coasts of
Western Australia after the negative exponential, spline and double detrending methods
were applied. ......................................................................................................... 36
Table 5. Pearson’s correlation coefficients (r) and their P values (in parentheses) for the
relationships between the MICs of Bodianus frenchii from the south and lower west
coasts and mean annual (financial year) and mean seasonal sea surface temperatures
(°C) in waters off those coasts and mean annual and mean seasonal Fremantle sea level
(cm). ...................................................................................................................... 40
Table 6. Pearson’s correlation coefficients (r) and their P values (in parentheses) for the
relationships between the MICs of Bodianus frenchii from the south and lower west
coasts and mean monthly sea surface temperatures (°C) in those waters, and between
the MIC of Bodianus frenchii from the lower west coast and mean monthly Fremantle
sea level (cm). * denotes significant correlations at 0.05, ** denotes significant
correlation at 0.01.................................................................................................. 40

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Table 7. Results of generalised additive mixed models of the effect of increasing sea
surface temperature on the growth of otoliths of Bodianus frenchii on the south and
lower west coasts................................................................................................... 42
Table 8. Results of generalised additive mixed models of the effect of increasing
Fremantle sea level (a proxy for Leeuwin Current strength) on the growth of otoliths of
Bodianus frenchii on the lower west coast............................................................ 43
Equation 1. Generalised additive mixed model formula for B. frenchii biochronologies
............................................................................................................................... 28

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Introduction
The otoliths, ear bones of fish, consist of calcium carbonate and an organic matrix,
which are used for sensory purposes such as balance and hearing (Campana & Neilson
1985, Popper et al. 2005). Of the three pairs of otoliths, including the lapilli and
asterisci, the largest, the sagittae, have been routinely used by researchers to age
individual fish (Campana 2001). The density at which calcium carbonate material is
deposited, which varies during the year (Pannella 1971), results in the production of
alternating opaque (slow winter growth, densely deposited material) and translucent
(faster summer growth, sparsely deposited material) growth zones in the otolith. One of
the unique properties of otoliths is the consistency of which calcium carbonate and an
organic matrix is deposited (Campana & Thorrold 2001). As this material is deposited
regularly, even during times of stress or starvation and after somatic growth has largely
ceased, the growth zones in otoliths are very valuable for determining the age of fish
(Morrongiello et al. 2012).
Otoliths contain more information than simply the age of a fish. Early
researchers showed that the distances between successive daily growth bands in otoliths
could vary by manipulating the environmental conditions under which fish were held in
aquaria (Pannella 1971, Campana & Neilson 1985), and that historical annual time
series of growth could be obtained by measuring the widths of annuli in otoliths, as a
proxy for annual fish growth (Boehlert 1985, Pereira et al. 1995, Lehodey &
Grandperrin 1996). More recently, trends in the widths of successive growth increments
have been used to investigate how inter-annual fluctuations in environmental variables,
such as water temperature and the strength of major ocean current systems, influence
the growth of fish species (Black et al. 2011a, Black et al. 2013a, Rountrey et al. 2014,
Morrongiello & Thresher 2015). It is hypothesized that variations in increment widths

13
are produced by a number of intrinsic and extrinsic factors (Miller et al. 2010,
Morrongiello et al. 2012).
Intrinsic factors include genetic predispositions (Morrissey 2011), biological or
physiological factors, while extrinsic factors include inter- and intra-species competition
and environmental influences, such as large scale oceanographic systems such as the El
Nino Southern Oscillation (Lehodey & Grandperrin 1996). The aim of previous
sclerochronological (sclero = hard part, chronos = time series) work employing otoliths
has been to detect relationships between the trends displayed by successive increment
widths in otoliths with extrinsic factors such as air temperature (Black et al. 2013b), sea
surface temperature (Coulson et al. 2014), sea bottom temperature (Black 2009), wind
direction (Black et al. 2011a), oceanic upwelling (Black et al. 2011b), the El Nino
Southern Oscillation (Meekan et al. 1999) and hydrological regimes of freshwater
environments (Morrongiello et al. 2011, Black et al. 2013b). The relationships
established between growth and environmental variables can then be used to make
ecological inferences about populations, and population interactions and to forecast
ecological reactions to those environmental drivers (e.g. Rountrey et al. 2014).
The methods for constructing biochronologies from increment width
measurements obtained from otoliths in many recent studies (i.e. Black et al. 2005,
2008a; Matta et al. 2010 Gillanders et al. 2012) have been heavily borrowed from those
used to construct chronologies from annual banding in the trunks of trees (Douglass
1920, 1941), which have been developed over the past 95 years. Special emphasis has
been placed, by dendrochronology (dendro = tree, chronos = time series), on the
importance of the process of cross dating, i.e. ensuring that each increment is assigned
correctly to the year of formation (Fritts 1976, Cook & Kairiukstis 1990, Maxwell et al.
2011). Cross dating, which is traditionally carried out by visually inspecting the

14
individual increment series and matching conspicuously wide and or narrow increments,
is possible on these otoliths for those species that display such trends (e.g. Matta et al.
2010; Coulson et al 2014; Tao et al. 2015). However, when increments are only 40-µm
wide, visually detecting patterns of wide and narrow increments is very difficult
(Rountrey et al. 2014, Nguyen et al. 2015). In these cases, statistical cross dating, a
process which mimics visual cross dating using correlation analyses, has become
increasingly important.
In order to tease out any climate signals in otolith increment time series,
detrending, i.e. the process of standardizing growth ring widths in chronologies to a
mean of one, is used to remove age-related growth declines while preserving as much
environmentally-induced variability as possible to better illustrate climate-driven
anomalies in ring widths (Cook 1985). The most common method of detrending in
otolith-based biochronology studies is a modified exponential or curvilinear method
(Table 1). Other detrending methods used include smoothing splines, double detrending
and regional curve standardization (Table 1). Historically, curvilinear standardization
has been used in dendrochronological studies carried out in the north-west of America,
where the trees exhibit exponential growth (Cook 1985). Curvilinear standardization is
inappropriate in those cases where the trend in the increment time series is not perfectly
exponential or linear (Cook 1985). The smoothing spline represents a highly flexible
technique, which represents a major improvement in standardizing ring-width series
compared to linear or curvilinear fits (Cook & Peters 1981). Double detrending is the
combination of negative exponential and smoothing spline detrending techniques,
where the data are detrended with a spline, then a negative exponential function, hence
it is detrended twice (Rountrey et al. 2014). Regional curve standardization is a
detrending technique whereby a single increment is standardized by taking the average

15
increment width of a calendar year over the average increment width for an age class
(Briffa et al. 1996, Melvin & Briffa 2008) and preserves low frequency variance but
removes the overall trends in long time series (Melvin & Briffa 2008). This present
study determined the best method for detrending chronologies for the Bodianus frenchii.
hom
Table 1. Examples of the different detrending methods employed in otolith based
increment width chronology studies on fish species with varying times series length and
sample size.
Detrending method Species Time series
length
Sample
size
Curvilinear
standardization
red snapper Lutjanus campechanus1
gray snapper Lutjanus griseus 1
lake trout Salvelinus namaycush2
freshwater drum Aplodinotus grunniens3
28
31
21
22
30
24
17
1351
Smoothing splines splitnose rockﬁsh Sebastes diploproa4
yelloweye rockﬁsh Sebastes ruberrimus5
49
50
50
66
Double detrending western blue groper Achoerodus gouldii6
51 56
Regional curve
standardization
rock flathead Platycephalus laevigatus7
longhead flathead Leviprora inops 7
yellowfin sole Limanda aspera8
14
12
21
96
120
17
Black et al. 4
2005, 5
2008a,1
2011a, 2
2013b, 8
2013a, 3
Davis-Foust, 2012; 6
Rountrey et al. 7
2014; Coulson et
al. 2014
The Foxfish Bodianus frenchii is a medium-sized, shallow-water, temperate reef
fish of considerable longevity, attaining a maximum age of 78 years (Cossington et al.
2010), making it the longest-lived species within the speciose Labridae family. A
comprehensive study of the biology of B. frenchii collected over reefs on the lower west
and south coasts of Western Australia demonstrated that this protogynous
hermaphroditic labrid attains a greater length and body mass at age throughout life in
waters on the cooler south coast than on the warmer lower west coast and that females
mature at an earlier age on the former coast and that those females exhibit substantially
greater fecundity (Cossington et al. 2010). Bodianus frenchii, endemic to temperate
Australian waters, is most common off the lower west and south coasts of Western

16
Australia, where it co-occurs with another long-lived, but much larger labrid, the
Western Blue Groper Achoerodus gouldii (Cossington et al. 2010).
The otolith growth of A. gouldii, a species which attains a maximum age of 70
years, was shown to be positively and significantly correlated with sea surface
temperatures (SST) off the south coast of Western Australia in the months from
November to May i.e. the time of year of increasing and elevated water temperatures
and thus the main growing period (Rountrey et al. 2014). This is similar to the period
for which there is a positive relationship between SST and otolith growth for two
species of flathead (Platycephalidae) in the same region (Coulson et al. 2014, Rountrey
et al. 2014). In deep water off south-western Australia, the growth of Hapuku Polyprion
oxygeneios was found to also have a significant, positive relationship with SST in
winter and spring months of the previous year (Nguyen et al. 2015). In neither the study
involving A. gouldii nor the two platycepahlids was there any correlation between
otolith growth and the strength of the Leeuwin Current, a dominant oceanographic
feature along the west Australian coast. However, Nguyen et al. (2015) found a lagged
positive relationship between the growth of Hapuku Polyprion oxygeneios and Leeuwin
Current strength in the previous calendar year. The lag in the effect of the Leeuwin
Current on the growth of P. oxygeneios was thought to be a result of the time required
for their main (> 50%) prey, squid, most likely arrow squid Nototodarus gouldi, to
attain a size where they form a substantial part of the hapuku diet (Nguyen et al. 2015).
The near shore waters of the lower west and south coasts of Western Australia
differ markedly in their habitat structures, reef types and water depths. It is generally
accepted that the habitat structure within a region affects the biological community
structure and that habitat structure is driven by physical oceanography within a region
(Carter & Woodroffe 1994, List & Terwindt 1995). The near-shore waters of the west

17
coast are protected by a semi-continuous, limestone-based reef and barrier island
system, which moderates wave energy (Howard 1989, Wells et al. 1993, Sanderson et
al. 2000). In contrast, granite boulder reefs and headlands dominate near-shore waters of
the south coast which is fully exposed to the southern ocean and is a high wave-energy
coast (Wells & Keesing 1990, Wells et al. 1993, Kendrick 1999, Sanderson et al. 2000).
In addition, the waters of the south coast increase in depth far more rapidly with
distance from shore than is the case with waters off the lower west coast (Kendrick
1999, Sanderson et al. 2000).
Another important difference between the two coasts is their temperature
regimes, with average temperature, and the range in average temperature, on the lower
west coast being greater than on the south coast (Kendrick 1999, Sanderson et al. 2000)
(Figure 1). An important contributor to this difference is not only lower latitude, but
also the influence of the pole-ward flowing, warm waters of the Leeuwin Current on
this coast. The Leeuwin Current has a strong influence on the distribution and
abundance of marine flora and fauna in south western Australia (Pearce & Phillips
1988, Caputi et al. 1996), and in recent years has led to marine heat wave-like
conditions in waters off the lower west coast (Pearce & Feng 2011, Rose et al. 2012,
Feng et al. 2013, Pearce & Feng 2013). Fremantle sea level (FSL) has been used as a
proxy for the strength of the Leeuwin Current, i.e. strong current strength results in
higher FSL while weak current strength results in lower FSL, which, until recently, has
been closely correlated with the recruitment of rock lobster to reefs along the lower west
coast (Pearce & Phillips 1988, Caputi et al. 2001).

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Figure 1. Mean annual values for a) sea surface temperatures (°C) at Rottnest Island on
the lower west coast and at Esperance on the south coast of Western Australia and b)
sea level (cm) at Fremantle.
Objectives
The species that is the focus of this thesis is a long-lived, temperate fish species that
lives in a region experiencing increases in temperature (Pearce & Feng 2007, Pearce &
Feng 2011). Previous otolith-based biochronology studies have demonstrated that water
temperature during the summer months, and thus those when the majority of growth is
occurring, has an important influence on the growth of fish in Western Australia

19
(Coulson et al. 2014; Rountrey et al. 2014). Those studies were restricted, however, to
fish populations along the south coast of Western Australia. The current study thus
investigates otolith growth of B. frenchii from the lower west as well as south coast
waters, it also employs the otoliths of this species caught in waters off the lower west
coast, where temperatures are greater and have increased since 1970. Furthermore, the
influence of the Leeuwin Current is greater on the lower west coast and occurs more
inshore than on the south coast.
The first aim of this study was to develop a biochronology, using growth
increment widths in otoliths, for the long-lived B. frenchii on both the south and lower
west coasts in south-western Australia, which could be used for the following purposes.
1) Determine whether the patterns of otolith growth of the two populations are
synchronized, thereby implying that the growth of individuals of this species in these
two distantly-located populations respond similarly to environmental influences.
2) Test the hypotheses that, the waters off the lower west coast of Australia exhibit
greater inter-annual fluctuations in temperature than off the south coast of Western
Australia, the relationship between the otolith increment width chronology for B.
frenchii will be stronger in the waters of the former coast.
3) Test the hypotheses that, as the Leeuwin Current exhibits a substantial influence on
waters along the west coast of Australia as far south as the lower west coast, it will have
an effect on the pattern of otolith growth of B. frenchii in these waters.

20
Materials & Methods
Sample collection
Bodianus frenchii, whose otoliths were used in this current study, were collected
between April 2004 and 2006 as part of an earlier study on the biological characteristics
of this species in south-western Australia (Cossington et al. 2010). In that study,
individuals were collected from numerous locations in marine waters between Jurien
Bay at ~ 30°18’S, 115°02’E on the lower west coast and from Esperance at ~ 33°51’S,
121°53’E on the south coast (Figure 2). To enable the current study to investigate the
influence of environmental variables on the growth of B. frenchii at the northern and
southern extent of this species distribution for which sufficient samples were available,
B. frenchii sampled from Rottnest Island at ~ 32°00’S, 115°52’E (hereafter referred to
‘lower west coast’) and Esperance (hereafter referred to ‘south coast’) were selected for
otolith increment analysis. Bodianus frenchii from Rottnest Island were sampled by rod
and line angling and spear fishing while SCUBA diving, whereas those from Esperance
where sampled by spear fishing while snorkeling and collected from recreational line
and commercial gillnet fishers (Table 2).
One of the aims of this study is to investigate the influence of fluctuating
environmental conditions on the growth of B. frenchii (see earlier). In order to
maximize temporal resolution of the data and the greater certainty of resultant
correlation tests that is afforded by using long time series (Wigley et al. 1984), i.e. a
series of successive increment measurements from an individual, the sectioned otoliths
from the oldest individuals from each of the two coasts were preferentially selected. In
addition, only those otoliths from the oldest fish, whose increment boundaries could be
clearly defined, allowing for the most precise increment measurements, were employed
for otolith chronology construction.

21
Figure 2. Map of south-western Australia showing the location of where samples of
Bodianus frenchii were collected from waters near Rottnest, on the lower west coast,
and Esperance, on the south coast. Red dots denote the approximate location for which
sea surface temperature data was obtained.
Otolith preparation, imaging and increment measurement
The otoliths employed during the current study were previously sectioned for
age determination (Cossington et al. 2010). This involved embedding one otolith from
each individual in clear epoxy resin before cutting a thin, ~ 300 μm thick transverse
section, using a low-speed diamond saw (Buehler), through the otolith primordia. The
surface of the sections were then lightly polished using fine wet and dry carborundum
paper (grade 1200) and mounted on slides using DePX mounting medium with a cover
slip. Multiple images of the dorsal side of the sectioned otoliths were taken at a

22
magnification of 10X using an Olympus DP70 12.0 megapixel digital camera mounted
on an Olympus BX51 stereo microscope. These images were then stitched together
using the stitch function in Leica Application Suite V. 4.3 (Leica Microsystems).
The measurement of the widths of successive growth increments on the digital
images of sectioned otoliths was carried out using ImageJ V. 1.47 (Abràmoff et al.
2004) and employing the plugin ‘IncMeas’ (Rountrey 2009). As the width of an
increment at one particular location on an otolith may vary from the width of that same
increment measured elsewhere, increments were measured along three to five transects
in order to obtain a more precise, otolith-wide measurement of that increment. The
average of these transects was used as the time series for an individual. Increments were
measured to the nearest 1 µm along transects that were drawn perpendicularly to the
otolith increments on the digital images of the sectioned otoliths, i.e. parallel to growth
direction (Figure 3a). Starting at the outermost opaque zone, the outer edge of each
individual opaque zone was marked until the edges of those opaque zones where no
longer clearly defined, after which increment measurement ceased (Figure 3b). This
often meant that the increments representing the growth undertaken in the first 5 years
of life were not measured. Partial increments on the peripheral side of the outermost
opaque zone were not measured.

23
Figure 3. a) The sectioned otolith of a 51 year old Bodianus frenchii and a b) higher
magnification image of part of the dorsal side of the otolith were increment
measurements were undertaken. In a) white dots indicate the first and every tenth
opaque zone and vertical black lines are indicative of the axis followed when measuring
increments. In b) horizontal white lines show the position of the outer edge of each
opaque zone.

24
Cross dating, detrending and otolith chronology construction
Cross dating is an important process that relies on the assumption that there are
synchronous growth patterns in multiple individuals due to the influence of common
environmental drivers of growth (Black et al. 2005). By matching growth patterns
among individuals, missing or false increments can be identified and taken into account
when assigning calendar years, ensuring that each increment is assigned to the correct
year of formation (Kastelle et al. 2011). While visual cross dating has been possible for
some fish species (Black et al. 2005, Gillanders et al. 2012, Coulson et al. 2014), it was
not possible for B. frenchii, as was the case for Achoerodus gouldii (Rountrey et al.
2014), due to the very small increment widths, ~ 10-20 µm, thus making it difficult to
visually detect any changes in those widths. As the date of capture of the individuals
used in this study was known, this served as an anchor for each increment measurement
series and accordingly back-dated. Statistical cross-dating was performed using the
dendrochronology program library dplR in R (Bunn 2010) following the methods
outlined in Bunn et al. (2015). This cross dating program was used to fit each series of
increment measurements with a highly flexible cubic smoothing spline using a 15-year
moving window. Each time series was then divided by the values predicted by the
spline function, removing low-frequency variability and standardizing all measurement
time series to a mean of one. The detrended time series for each individual was then
correlated, at segment lengths of 20 years, with a lag of 10 years, with the average for
all other standardised time series of measurements for all individuals. The mean,
calculated as a Tukey's biweight robust mean, was reported as the inter-series
correlation. This approach of isolating only the high frequency, serially-independent
growth pattern mathematically mimicked the process of visual cross-dating (Holmes
1983, Grissino-Mayer 2001). dplR also calculated the mean sensitivity, a measure of

25
the relative change in increment width between successive years that ranges from a
minimum of zero, i.e. two increments with the same width, to a theoretical maximum of
two, i.e. a pair of increments in which one value is zero (Fritts 1976). The
corresponding otoliths whose time series were highlighted in the output by the dplR
program to have potential errors, were visually expected, and if no error was found the
increment measurement was not adjusted.
To develop the mean index chronology (MIC) for climate analysis, each set of
the original growth-increment measurement time series was detrended employing
double detrending method outlined in Rountrey et al. (2014). The detrending effectively
removed the rapid ontogenetic decline in growth rate that occurs in early life, and
removed other low frequency variation including departures from the negative
exponential fit. Additional detrending techniques were also explored such as negative
exponential detrending (Black 2009, Black et al. 2010, Matta et al. 2010, Black et al.
2011a, Gillanders et al. 2012) and cubic smoothing splines (Black et al. 2005). All
detrending analyses were carried out employing the R package dplR (Bunn 2008) and
only those years with a sample depth of > five individuals were retained to ensure a true
mean is calculated (Matta et al. 2010, Black et al. 2013a).

26
Analysis
For the analysis the chronologies of B. frenchii a hybridization of sclerochronology
techniques, Pearson's correlation analysis and additive mixed-effects modeling was
used, similar to Rountrey et al (2014), who investigated the relationship between otolith
growth of the co-occurring A. gouldii and environmental variables on the south coast.
The analysis can be broken down into three parts: 1) data exploration, 2) Pearson's
correlation analyses, and 3) modeling otolith growth, via mean index chronology
(MIC), using a generalized additive mixed model, with age as a smooth function and an
individual random effect. Reasoning for using the GAMM approach is outlined in the
Appendix.
To determine a parsimonious predictive relationship between the MICs for B.
frenchii on the south and lower west coasts and the mean annual sea surface temperature
in waters of those regions and Fremantle sea level, generalised additive mixed models
(GAMMs) were used. This resulted in three models, each model was created, using one
predictor, either mean annual sea surface temperature (for both the south coast and
lower-west coast) or mean annual Fremantle sea level (lower-west coast). Models were
created using gamm4 in R (Wood et al. 2014).

27
To investigate the effects of variations in sea surface temperature on B.
frenchii growth, we created a generalised additive mixed model in the form of:
Equation 1. Generalised additive mixed model formula for B. frenchii
biochronologies
𝑔(𝑀𝐼𝐶𝑖,𝑗
𝑏
) = 𝛽0 + 𝑓1(𝐴𝑔𝑒𝑖,𝑗) + 𝑋𝑗 + 𝑧𝑖
𝑇
𝑏
where:
𝑔(𝑀𝐼𝐶𝑖,𝑗
𝑏
) is a monotonic differential link function of fish otolith
width, where MIC(i, j) where i is the MIC increment and j
is year relating to increment;
𝛽0 is the intercept parameter;
𝑓1(𝐴𝑔𝑒𝑖𝑗) is a centered twice-differentiated smooth function for fish
age;
𝑋𝑗 is the average annual (financial calendar) environmental
variable for year j;
𝑧𝑖
𝑇
𝑏 is an error term; where 𝑏 are random effects, assumed to be
distributed
~𝑁{0, 𝐷( 𝜃)} where 𝜃 is a 𝑐 × 1 vector of variance components

28
Data Exploration
Data exploration is the first step in data analysis (Tukey 1977, Zuur et al. 2010) with the
objective of summarizing the dataset's main characteristics, often with visual methods.
Data exploration is described as "graphical detective work" (Tukey 1972) of factors,
such as outliers, unequal variance, or dependence structures, which affect the type of
analysis which can be performed. The results of the data exploration can be found in the
Appendix.
Environmental Data
A range of environmental variables and climate indices (i.e. bottom temperature, wind
direction, oceanic upwelling, El Nino Southern Oscillation Index or Multivariate ENSO
Index, and Dipole Mode Index) were considered in order to determine their influence on
the growth of B. frenchii in south-western Australia. However, many of these variables
were not available throughout much of the early years of the MIC on both the west and
south coasts. The variables which were selected, were also the most likely to influence
the growth of fish in south-western Australia, were sea surface temperature (SST) and
Fremantle sea level (FSL), a measure of the strength of the Leeuwin Current. No
attempt was made to relate otolith growth with sea level height on the south coast as the
Leeuwin current flows well offshore on that coast.
Mean monthly SST data was collected from Hadley Satellites and obtained from
the Met Office Marine Data Bank (Rayner 2003). Mean monthly SST data was obtained
for every month between January 1938 and December 2005 from the grid cell off the
lower-west coast (-32°, 116’E) and south coast (-35°, 119’E). Fremantle sea level was
obtained from the Bureau of Meteorology. Pearson’s correlation coefficients (r) were
tested to determine whether there was a significant relationship between the B. frenchii

29
MIC and mean annual, seasonal and monthly SST data for each coast and mean annual,
seasonal and monthly FSL.
In the present study, correlation tests between otolith increment widths and
environmental variables were conducted with those variables organized on a financial
year scale, rather than calendar year. The financial year is preferred to the calendar year,
because it follows more closely the biological growth year of teleosts in the southern
hemisphere (Coulson et al. 2014), i.e. the peak growing period is summer (December -
February) which would be divided if the traditional calendar year scale was employed.

30
Results
Biological data
The ages of individuals used in this chronology study ranged from 39 - 78 years for the
south coast and 41 - 62 years for the west coast, which corresponded to lengths ranging
from 372 - 435 and 315 - 446 mm, respectively (Table 2). As B. frenchii is a
protogynous hermaphrodite that changes sex at ~ 29 years (Cossington et al. 2010), all
but one of the individuals from each coast that were used in this chronology study were
male (Table 2).
Cross dating and synchrony among individuals within
The increments measured encompassed years between 1938 and 2005 for the south
coast and 1947 and 2005 for the west coast. A sample depth of at least six occurred in
those years between 1954 and 2005 and 1954 and 2004 on south and lower west coasts,
respectively. Visually, there is no pattern of variation in the widths of the increments in
the otoliths of B. frenchii within and between the otoliths of the individuals on both
coasts (Figure 4, Figure 5). As visual cross dating was not possible due to the very small
increment widths (Table 3) increasing the difficultly in identifying synchrony in
conspicuously wide and/or narrow increments, statistical cross dating was employed,
with the capture year used as the anchor for this process. Although there was some
synchrony among a few individuals on each coast (indicated by the blue segments in
Figure 6 and Figure 7) shown by the statistical cross dating, on the whole, this process
also demonstrated a lack of synchrony among those same individuals (indicated by the
red segments in Figure 6 and Figure 7).
Despite this apparent lack of synchrony identified by statistical cross dating, the
interseries correlation (ISC), a measure of how much correlation exists amongst the

31
increment widths (Grissino-Mayer 2001), demonstrates that there is synchrony among
the standardised increment time series for those individuals of B. frenchii on the south
coast, and to a lesser extent, the lower west coast (Table 3). The very low mean
sensitivity values, a measure of the change in increment width between successive
years, of 0.14 for the south coast and 0.01 for the lower west coast indicate that there is
very little variation between successive increment widths, which is probably why visual
and statistical cross dating failed to find any synchrony (Table 3).
Table 2. Length and age range, method of capture and sex of the individuals of
Bodianus frenchii from the south and lower west coasts of Western Australia used in the
this study.
Length range
(mm)
Age range
(years)
Method of capture Sex
Gillnet Line Spear F M
South 372-435 39-78 8 10 11 1 28
Lower west 315-446 41-62 20 4 1 23
Table 3. Time series range, mean increment size, interseries correlation, mean
sensitivity and standard deviation in the individual time series for Bodianus frenchii
chronologies for the south and lower west coasts and both coasts combined. n = sample
size.
Time series
(years)
Mean
increment
size (µm)
Interseries
correlation
Mean
sensitivity
Standard
deviation
n
South 33-68 46 0.32 0.14 4.87 29
Lower west 33-58 42 0.17 0.11 3.02 24
Combined coasts 31-59 44 0.19 0.12 4.15 53

32
frenchii individuals from the south coast used to assist in visually identifying
identifying codes for individual fish.
frenchii individuals from the lower west coast used to assist in visually identifying
identifying codes for individual fish.

33
increment time series for the 29 individual Bodianus frenchii from the south coast. Blue
correlates well (P less or equal to the user-set critical value) while potential dating
problems are indicated by the red segments (P greater than the user set critical value).
Green lines show segments that do not completely overlap the time period and thus
have no correlations calculated (Bunn 2010).
increment time series for the 24 individual Bodianus frenchii from the lower west coast.
Blue correlates well (P less or equal to the user-set critical value) while potential dating
problems are indicated by the red segments (P greater than the user set critical value).
Green lines show segments that do not completely overlap the time period and thus
have no correlations calculated (Bunn 2010).

34
Detrending
A range of detrending methods that are most commonly used in otolith increment
width-based chronology studies were employed in order to determine which of these
was most suitable to apply to the B. frenchii increment width data.
The negative exponential detrending method is a rigid function that removes age
related growth declines in the increment series that are more prevalent in tree ring data,
for which it was developed. The negative exponential detrending method does not
appear to have has not completely removed the age-related decline in the otolith
increment-width data for B. frenchii, as there is still a declining trend in the time series
(Figure 8c, d). The cubic smoothing spline method (often termed 'spline'), which is by
far the most common in dendrochronology, but not so in otolith sclerochronology,
works by taking a mean of the surrounding four data points, in front, behind, above and
below. Double detrending also employs a cubic-smoothing spline after the increment
width data is initially detrended by applying a negative exponential function (Cook &
Kairiukstis 1990). When applied to the increment width data for B. frenchii from each
coast, both the spline and double detrending methods have largely removed any age
related decline in the increment width data (Figure 8e, f, g, h). In addition, the detrended
time series also display a homogeneous variance around a mean of 1. Furthermore,
these detrending methods, while eliminating the age related decline in otolith growth,
have preserved the high frequency climate effects, which is particularly evident in the
south coast B. frenchii data where there is conspicuous decrease in increment width in
the early 1990s (Figure 8e, g).
The higher expressed population signal (EPS), a measure of how well the
sample means represent the mean of the theoretical population (Wigley et al. 1984),
provided by negative exponential detrending suggests that this best detrending option
for the B. frenchii increment width data (Table 4). Chronologies with EPS values above

35
the theoretical threshold of 0.85 or high 𝑟̅ values are generally considered to be
acceptable; however, detrending with the aim of maximizing these indicator parameters
may result in the retention of aspects of an ontogenetic trend (Nguyen et al. 2015).
Thus, despite the negative exponential detrending option providing the highest EPS and
𝑟̅ values, visually it was still shown to retain an ontogentic decline and was therefore
discarded. The EPS and 𝑟̅ values for the spline and double detrending methods for the
increment data for south coast population were identical (Table 4). As the EPS and
𝑟̅ values for double detrending of the increment data for lower west coast population
were marginally higher than those obtained employing the spline detrending, and to
enable comparisons with the previous otolith chronology study of the Western Blue
Groper Achoerodus gouldii in the same region (Rountrey et al. 2014), double detrending
was chosen as the detrending method for B. frenchii on the south and lower west coasts.
Table 4. The expressed population signal (EPS) and 𝑟̅ values for the raw chronologies,
and the increment widths for Bodianus frenchii on the south and lower west coasts of
Western Australia after the negative exponential, spline and double detrending methods
were applied.
Raw Negative
Exponential
Spline Double
Detrending
South
EPS 0.854 0.878 0.697 0.697
𝑟̅ 0.221 0.259 0.100 0.100
Lower West
EPS 0.741 0.821 0.421 0.433
𝑟̅ 0.131 0.195 0.037 0.039

36
Figure 8. Comparisons of the a, b) raw chronologies, c, d) negative exponential and e, f) cubic smoothing spline g, h) double detrending methods for individuals
of Bodianus frenchii (grey lines) from the south (blue lines) and lower west (red lines) coasts of Western Australia.

37
Synchrony between regions
The MIC’s for the two B. frenchii populations were significantly correlated (r =
0.15, P= 0.005), indicating that there is a high level of synchrony in the otolith
growth of the individuals of these two populations (Figure 9a). This finding
suggests that B. frenchii on the south and lower west coasts respond in a similar
way to variations in temperature, despite the fact that these two populations are
spatial separated (~1200km) and occur on coasts that are markedly different in
terms of their reef types and the environmental conditions experienced. Even
though synchrony in the trends of increment widths is present between the two B.
frenchii populations, in order to investigate the relationships between otolith
growth of individuals in those two populations and region specific environmental
variables, the MICs have not been combined to generate a single MIC.
Correlations with environmental variables
Sea Surface Temperature
On the basis of Pearson’s correlation coefficient, the MIC for B. frenchii on the
south coast was weakly and positively correlated with mean annual (financial
year) SST (r = 0.32, P = 0.02) in those years between 1954 and 2005 (Table 5).
There was a stronger positive relationship (r = 0.37, P = 0.007) between the MIC
for B. frenchii on the lower west coast mean annual (financial year) SST (Table
5). This positive relationship on an annual level for the lower west coast was
largely driven by the significant positive correlation (r = 0.39, P = 0.004) with
mean seasonal SST for summer, the time of year when temperature is highest and
when the majority of growth is expected to occur (Table 6).

38
Figure 9. a) A comparison of the mean index chronologies (MIC) for Bodianus
frenchii from the south (blue line) and lower west coasts (red line) and a
comparison of the MIC for B. frenchii from the b) south and c) lower west coasts
and mean annual sea surface temperature (black line) in those regions and
comparison of the MIC for Bodianus frenchii from the lower west and d) mean
annual Fremantle sea level (black line) for the years between 1954 and 2005.

39
Table 5. Pearson’s correlation coefficients (r) and their P values (in parentheses)
for the relationships between the MICs of Bodianus frenchii from the south and
lower west coasts and mean annual (financial year) and mean seasonal sea surface
temperatures (°C) in waters off those coasts and mean annual and mean seasonal
Fremantle sea level (cm).
South West
Financial SST Annual 0.32 (0.0216*) 0.37 (0.0075**)
Spring 0.06 (0.6725) 0.30 (0.0355*)
Summer 0.20 (0.1532) 0.39 (0.0042**)
Autumn 0.22 (0.1172) 0.32 (0.0204*)
Financial FSL Annual 0.18 (0.2309)
Spring -0.01 (0.9334)
Summer 0.18 (0.2154)
Autumn 0.11 (0.4387)
Table 6. Pearson’s correlation coefficients (r) and their P values (in parentheses)
for the relationships between the MICs of Bodianus frenchii from the south and
lower west coasts and mean monthly sea surface temperatures (°C) in those
waters, and between the MIC of Bodianus frenchii from the lower west coast and
mean monthly Fremantle sea level (cm). * denotes significant correlations at 0.05,
** denotes significant correlation at 0.01.
South West
SST July 0.14 (0.3136) 0.30 (0.0316*)
August 0.10 (0.4827) 0.27 (0.0575)
September 0.09 (0.5398) 0.29 (0.0419*)
October 0.11 (0.4502) 0.41 (0.0026**)
November 0.21 (0.1331) 0.29 (0.0409*)
December 0.15 (0.2769) 0.19 (0.1793)
January 0.14 (0.3360) 0.37 (0.0081**)
February 0.23 (0.1054) 0.35 (0.0110*)
March 0.25 (0.0683) 0.29 (0.0357*)
April 0.19 (0.1769) 0.29 (0.0366*)
May 0.16 (0.2487) 0.30 (0.0347*)
June 0.25 (0.0712) 0.28 (0.0450*)
FSL July -0.01 (0.9494)
August 0.05 (0.7482)
September 0.15 (0.2832)
October 0.15 (0.2934)
November 0.15 (0.2832)
December 0.05 (0.7330)
January 0.22 (0.1306)
February 0.14 (0.3399)
March 0.11 (0.4582)
April 0.16 (0.2555)
May 0.03 (0.8158)
June 0.14 (0.3224)

40
Generalised additive mixed models employing a smoother for age at which
the increment was formed and a random intercept for each individual
demonstrated that there is a significant relationship between mean annual SST and
otolith growth of B. frenchii on both the south (P = 0.003, Figure 9b) and lower
west (P = 0.0006, Figure 9c) coasts. Although, the relationship has a higher
significance on the lower-west coast, there was a higher estimated effect for the
south coast. Thus, for B. frenchii on the south coast, it is estimated that for any
given year, every 1°C increase in SST the width of the increment corresponding to
that year will be 1.25µm (SE ± 0.42) wider, while the width of this increment in
the otolith of an individual off the lower west coast is estimated to be 1.18µm (SE
± 0.35) wider (Table 7).
Both the south (-14.5 ± 2.9) and lower west (-14.6 ± 2.8) coasts had
similar estimates for the smoother of age (Table 7). This equates to the otolith
increment width decreasing at a rate of -14.5 and -14.6 μm for the south and lower
west coasts, respectively, for every increasing year of age of the fish. The GAMM
combines both the effects of the predictor and the smoother of the age to model
the growth of B.frenchii otolith increments. This can be better visualized using 3D
models (south coast: Figure 10b, lower-west coast: Figure 10c).

41
sea surface temperature on the growth of otoliths of Bodianus frenchii on the
south and lower west coasts.
South coast
Random effects Variance SD
FishID (Intercept) 6.483 2.546
Penalized component of age smooth 30832.695 175.592
Residual 11.912 3.451
Fixed effects Estimate SE t P
Intercept -3.7223 7.6025 -0.490 0.625
Annual (financial year) SST 1.2538 0.4214 2.975 0.003 **
Unrealized component of age smooth -14.5241 2.8546 -5.088 <2e-16 ***
Lower west coast
Residual 15.78 3.973
Intercept -4.113 7.018 -0.586 0.557917
Annual (financial year) SST 1.183 0.346 3.419 0.000648***
Fremantle sea level
Pearson’s correlation coefficients demonstrated that the MIC for the B. frenchii
population on the lower west coast was not correlated with mean annual, mean
seasonal or mean monthly FSL (Tables 5, 6). In contrast, on the basis of GAMM,
the MIC for B. frenchii on the lower west coast was positively related to mean
annual FSL (Table 8). This model also estimated that, for every given year, every
1 cm increase in mean annual Fremantle sea level will result in a 6.34µm increase
in the width of the increment for that year, for individuals on the lower-west coast.

42
Fremantle sea level (a proxy for Leeuwin Current strength) on the growth of
otoliths of Bodianus frenchii on the lower west coast.
t Coast
Residual 15.64 3.955
Intercept 14.875 1.891 7.866 8.44e-15 ***
Financial Annual FSL 6.339 2.377 2.667 0.00777 **
Visualizing GAMMs
GAMMs combine both the effects of the predictor (i.e. the respective
environmental variables = x), the smoother of the age (z) to model the growth of
B.frenchii otolith increments (y = MIC). This can be better visualized using three
dimensional visualizations of the models (south coast SST model: Figure 10a,
lower west coast SST model: Figure 10b, and lower west coast FSL model: Figure
10c).

43
Figure 4. Three dimensional visualizations of the generalised additive mixed models displaying the relationship between a) the otolith growth of
Bodianus frenchii on the south coast and SST and otolith growth of B. frenchii on the lower west coast and b) SST and c) FSL. x, environmental
variable; y, mean increment chronology; z, smoother of age.

44
Discussion
Selection of otoliths and sample sizes
Bodianus frenchii is a protogynous labrid of exception longevity, attaining a
maximum age of 78 years (Cossington et al. 2010). For this study, in order to
maximize the chronology length, which increases the strength and validity of
potential correlations with environmental variables, the otoliths of the oldest
individuals were preferentially selected. The final number of otoliths, whose
increment widths were measured for the analyses, were selected, largely, on the
basis of the clarity of increment boundaries across a broad region of the dorsal
side of the sectioned otolith allowing for multiple transects along which
increments were measured (Table 2). Similar selection criteria have been used for
freshwater, lake trout Salvelinus namaycush and Selincuo naked carp
Gymnocypris selincuoensis (Black et al. 2013b, Tao et al. 2015) and marine
teleosts aurora rockfish Sebastes aurora, northern rock sole Lepidopsetta
polyxystra, yellowfin sole Limanda aspera and Alaska plaice Pleuronectes
quadrituberculatus (Matta et al. 2010, Thompson & Hannah 2010). Clarity of
growth increment boundaries is an important feature to be taken into account
when considering a species for otolith-based chronology studies. When
investigating relationships between otolith (fish) growth and environmental
variables, imprecise increment measurements may lead to a result of no
correlation or, worse, false correlations with those variables.
For this study, the clearest sectioned otoliths from the oldest individuals
were retained for increment measurement. The resultant sample sizes were of 29
and 24 for the south and lower west coast, respectively, were consistent with the

45
majority of other otolith increment width chronology studies in which the otoliths
from fewer than 50 individuals were used. A post hoc power analysis (Appendix,
Power Analysis) corroborated that a sample size of 50 is sufficient to gain
adequate statistical power for our B. frenchii chronologies. Although there is no
research standard to determine how many samples should be used when
constructing otolith-based biochronologies, sample size is likely to vary based on
the question being asked and or the geographic area over which samples are
collected. For example, Gillanders et al. (2012) used the otoliths from as few as
16 Luderick Girella tricuspidata collected over a restricted region from waters off
northern New Zealand, while Morrongiello and Thresher (2015) employed the
otoliths of 6143 Tiger Flathead Platycephalus richardsoni collected from six
fishing regions spanning eight degrees of latitude. As the samples of B. frenchii
used in the current study are from distantly populations located waters on two
coasts, the interpretation of the results have been restricted to generalities on the
influences of environmental variables on the otolith growth of individuals in those
two populations and how conditions on these two coasts drive differences in the
response in otolith growth.
Cross dating and synchrony among individuals
Cross-dating is the process of ensuring that each increment is assigned correctly to
the year of formation (Fritts 1976, Cook & Kairiukstis 1990, Maxwell et al.
2011). This is accomplished by visually inspecting the time series and looking for
conspicuously wide and/or narrow increments (Black et al. 2005). This process is
relatively easily applied in those species that are particularly sensitive to
fluctuations in environmental conditions which also is captured by conspicuous

46
variations in growth increment widths in their otoliths (e.g. Matta et al. 2010;
Coulson et al 2014; Tao et al. 2015). As in the case of A. gouldii (Rountrey et al.
2014), it may not always be possible in the case of those species, such as of B.
frenchii, whose increments have mean widths of 42-46 µm. In addition, B.
frenchii and A. gouldii are known as complacent, in that they do not show
significant response to any environmental change. In the case of such species, the
ability to visually align increments on the basis of their widths is not possible.
Statistical cross dating provides an avenue for the increment width time
series of individuals of such complacent, and non-complacent, species to be
statistically checked. The results of cross dating, such as the interseries correlation
and mean sensitivity, provide an indication of the quality and level of synchrony
within the increment width data. The interseries correlation (ISC), is the mean
correlation of the standardised individual series with the mean of all the others.
Values of 0.32 and 0.17 for the south and lower west coast populations indicate
that individuals of B. frenchii on the south coast respond similarly to fluctuations
in environmental conditions resulting in greater synchrony amongst their
increment widths. The ISC values for both B. frenchii populations are very low in
comparison to those values obtained in other studies, such as 0.76 for grey
snapper Lutjanus griseus (Black et al. 2011a) and 0.88 for largemouth bass
Micropterus salmoides (Rypel 2009). In the case of the south coast B. frenchii
population, the ISC value is markedly higher than 0.11 obtained for A. gouldii in
the same waters (Rountrey et al. 2014), but far less than 0.64 and 0.62 obtained
for P. laevigatus and L. inops from shallow, inshore waters along the same coast
(Coulson et al. 2014). This perhaps indicates that B. frenchii are less complacent
towards fluctuating environmental variables than A. gouldii and that, in shallow

47
water environments where variables such as water temperature exhibit greater
extremes, the individuals of species living in such waters are likely to all respond
in a similar way. This is also demonstrated by very high ISC values (0.49-0.88)
for fish in shallow, freshwater environments (Rypel 2009, Black et al. 2013b, Tao
et al. 2015).
The mean sensitivity is a measure of the range of increment width
variation. The very low values of 0.14 and 0.11 for south and lower west coast
populations indicate that the increment widths of B. frenchii do not differ
markedly between years. While these values are low are at the lower end of the
spectrum in comparison to the results from other studies, mean sensitivity values
for otolith increment width studies are typically <0.25. Like B. frenchii, the
increment widths of hapuku Polyprion oxygeneios, a deep water species found off
southern Western Australia, do not vary markedly (mean sensitivity = 0.14)
between years of formation (Nguyen et al. 2015).
Detrending
Detrending is a process, which standardises growth ring widths in chronologies to
a mean of one. The aim of detrending is to remove the age-related growth declines
in the increment width time series while preserving as much environmentally-
induced variability as possible to better illustrate climate driven anomalies in
increment widths of (Cook 1985). The type of detrending that is applied to the
increment width data will influence the final MIC and potentially any correlations
with the selected environmental variables. One of the most common types of
detrending used in otolith biochronologies is the cubic smoothing spline (Black et
al. 2005, Black et al. 2008b). In this study, three detrending methods were applied

48
and compared to determine the optimal detrending method for B. frenchii. Based
on visual inspection of detrended chronologies along with expressed population
signals it was decided that double detrending is the best detrending method for B.
frenchii. This method was also used for developing the otolith chronology for the
Western Blue Groper Achoerodus gouldii, another long-lived labrid species that
co-occurs with B. frenchii. Double detrending involves detrending the increment
width data, firstly, with a smoothing spline and then, secondly, with a negative
exponential function techniques (Rountrey et al. 2014). As separate, stand-alone
detrending methods, double detrending and cubic smoothing splines were visually
very similar and produced similar expressed population signal values. However,
upon closer inspection, the cubic smoothing spline flattened the individual
increment series for the individuals off the lower-west coast, particularly in the
early years of the chronology. The application of a negative exponential function
in conjunction with a smoothing spline greatly improved the chronology as the
double detrended chronology followed the trends in the increment widths of the
individuals off the south coast.
Synchrony between regions
Cossington et al. (2010) found regional differences between the B. frenchii
populations on the south coast and lower west coast, with those individuals on the
south coast growing faster and attaining a larger size and mass at age and
maturing earlier in life compared to those individuals on the lower west coast.
Despite these biological differences and the that fact that these two populations
are spatially separated (~1200km) and occur on coasts that are markedly different
in terms of their reef types and the environmental conditions, the response of

49
otolith growth of the individuals in those two populations to regional specific SST
was remarkably similar (Figure 9a). This demonstrates, particularly of B. frenchii
on the lower west coast close to its northern limit of distribution, that historical
increases in water temperature have only positively influenced otolith growth.
Modeling of future otolith growth of A. gouldii off the south coast of Western
Australia by Rountrey et al. (2014) demonstrated that predicted future increases in
water temperate throughout this century are only expected to positively influence
otolith growth. While Morrongiello et al. (2015) demonstrated that, throughout
the majority of its geographic range on the south east coast of Australia, the
growth of the temperate tiger flathead, P. richardsoni, responded positively to
temperature, at the northern limit of its distribution, warming waters are having a
negative impact on the growth of this species (Morrongiello & Thresher 2015).
The results from Morrongiello et al. (2015) suggest that, if future climate change
was to continue to result in increasing water temperature, the otolith growth of
typically cool-temperate species such as B. frenchii is likely to respond negatively
those future increases. Given that B. frenchii is restricted to a narrow latitudinal
range, with Rottnest Island being close to their northern limit, and recent marked
increases in water temperature off the lower west coast (Pearce & Feng 2013), the
population in this region is susceptible to future increases in water temperatures.
Financial year vs. calendar year
The main growing season for fish species in south-western Australia and, indeed,
other regions of the Southern Hemisphere at similar latitudes, extends from
approximately mid-spring (October) to early autumn (March). Therefore, the
growing period extends from the end of one calendar year to the beginning of

50
another and thus otolith growth occurs over the period that straddles two calendar
years. In contrast, the main growing period in the Northern Hemisphere falls in
the middle of the calendar year and thus the growth increment is formed over the
period of an individual calendar year. Thus, relationships between otolith
increment width chronologies constructed for fish species in the Northern
Hemisphere and environmental variables in those regions on an annual scale
(Matta et al. 2010, Black et al. 2011b, Black et al. 2013b) are correlations on over
the same temporal scale. If this same approach is taken for studies carried out in
the Southern Hemisphere, increment widths would be correlated with
environmental variables that occur after the increment has begun forming. It
therefore appears logical that, in the Southern Hemisphere, increment widths
should be correlated environmental variables on a financial year (July to June)
scale which would encompass the main growing period (October to March).
Coulson et al. (2014) used this approach when investigating relationship
between the growth of the otoliths two species of Platycephalidae and SST in
waters off southern Western Australia. While correlation tests between the MIC
for both species and mean annual (financial year) SST were significant, this was
not the case when mean annual SST was calculate on a calendar year scale. Other
studies in southern Western Australian and New Zealand waters have
demonstrated that there is a positive relationship between otolith growth and SST
in those months between mid-spring and late autumn of the previous calendar year
(Gillanders et al. 2012, Rountrey et al. 2014, Nguyen et al. 2015). However, these
researchers did not acknowledge the use of SST on a financial year scale and
instead referred to such relationships as lagged correlations with SST in months
and or seasons of the previous year. It is clear from the results of the current study

51
and previous research that, when investigating relationships between otolith
growth and environmental parameters in waters of the Southern Hemisphere,
those parameters should be considered on a financial year scale.
Relationships between MIC and environmental variables
Unlike other disciplines of sclerochronology, such as those based on the
growth bands in corals or the shells of bivalves, the results from studies
employing fish otoliths must take into consideration the fact that fish are mobile
and potentially inhabit a number of environments throughout their life cycle when
interpreting results (Morrongiello et al. 2012, Ong et al. 2015). Site fidelity and
home range estimates for the closely related California sheephead Semicossyphus
pulcher demonstrate that this species spends ~ 90% of total residence time within
a 600 m core area (Topping et al. 2006). Similarly, 10 out the 11 acoustically
tagged individuals of the co-occurring labrid, the western blue groper Achoerdus
gouldii, largely remained in a 1 km long by 40 m wide strip of coastal reef for the
12 month study period (Bryars et al. 2012). In addition, Fairclough et al. (2011)
demonstrated through otolith microchemistry analysis that, on the mid-west coast
of Western Australia, the movement of juvenile or adult baldchin groper
Choerodon rubescens occurs at relatively small spatial scales. The ability,
therefore, to detect responses in the otolith growth of B. frenchii to variations in
selected environmental variables is improved because of the likelihood that the
individuals, whose otoliths were employed in this study, have been resident in
those regions for the majority of their lives.
Because teleosts are polkiotherms, their body temperature is thus regulated
by the temperature of their surrounding environment, which has been shown to

52
positively influence otolith growth in a number of freshwater and marine species
(e.g. Rypel 2009; Matta et al. 2010; Gillanders et al. 2012; Black et al. 2013b),
including those species that inhabit south-western Australian waters (Coulson et
al. 2014; Nguyen et al. 2015). The results of the GAMMs demonstrated that,
while there was a significant, positive relationship between the MIC for the south
coast population with mean annual SST, the relationship with this variable was
more significant on the lower west coast (south P = 0.003, lower west P =
0.0006, Table 7). However, there was a higher estimated effect otolith increment
growth in increasing annual SST for the south coast population of B. frenchii
(estimate for increase of 1°C (±SE) = 1.25 µm ± 0.42) compared to the lower west
population (estimate for increase of 1°C (±SE) = 1.18 µm ± 0.35). Cossington et
al. (2010) stated that the cool south coast is more favourable for this species. As
expected, there is a higher estimated effect for otolith growth in increasing in this
area. The extent to which SST fluctuates from year to year is much greater on
along the lower west coast than the south coast (Figure 1) and, since ~ 1970, there
has been an increasing trend in the mean annual SST on that former coast.
The relationship between the MIC for B. frenchii on the south coast and
SST for is similar to the findings of Rountrey et al. (2014) for the co-occurring
A. gouldii, who found a weak, but significant influence of regional SST on the
otolith growth of A. gouldii in the south coast of Western Australia. Similarly,
Coulson et al. (2014) demonstrated that increasing water temperature has resulted
in increased otolith growth of two platycephalid species in inshore waters on the
same coast.

53
The effects of the Leeuwin Current in waters off the lower west coast of
Western Australia are well documented and Fremantle sea level (FSL) is
commonly used as a proxy for the Leeuwin Current through El Nino Southern
Oscillation cycles (Pearce & Phillips 1988, Caputi et al. 1996, Caputi et al. 2001,
Feng et al. 2008). Although there were no significant Pearson's correlations
between the MIC for the lower west coast population of B. frenchii and FSL, the
GAMM showed a highly significant relationship (P = 0.008) with an estimated
4.62 µm (SE = ± 2.05) increase in otolith increment size for every one cm
increase in Fremantle sea level. Nguyen et al. (2015) found that the Leeuwin
Current had a significant influence on the growth of hapuku Polyprion oxygeneios
in south-western Western Australia through its effect on primary productivity
eventually leading to increase prey resources for P. oxygeneios. The strength of
the Leeuwin Current weakens, as does its influence on the marine environment, as
it flows east along the south coast. It is thus not surprising that Coulson et al.
(2014) found no relationship between the otolith growth of two platycepahlids and
sea level in inshore waters along the south coast of Western Australia. The
influence of the Leeuwin Current on the otolith growth of B. frenchii is likely a
reflection of a combination of oceanographical and biological influences by the
strengthening of this current in this region.
Conclusion
In conclusion, two otolith increment-width chronologies were constructed for
Bodianus frenchii from the south and lower-west coasts of Western Australia.
While the otoliths for B. frenchii possess very clear growth increments, the lack of
conspicuous variability in widths required to undertake cross dating made this

54
process unsuccessful. The lack of synchrony in the trends displayed by the
increment widths between individuals demonstrates the insensitivity, as reflected
by the interseries correlation values, of B. frenchii to environmental fluctuations.
Despite the weak signal in the otolith increment widths, significant relationships
with regional SST and Leeuwin Current strength were present. Generalized
additive mixed modeling demonstrated that SST was an important driver of
otolith growth of B. frenchii on the south coast, while on the lower west coast, the
effects of a strong Leeuwin Current influence the otolith growth of B. frenchii in
these waters.

55
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65
Appendix
List of figures
A1. Dot plots for individual chronology time series for the 29 Bodianus frenchii
from the south coast. Each plot represents the individual points for each individual
with their identifying fish number at the top of each plot..................................... 67
A2. Dot plots for individual chronology time series for 24 Bodianus frenchii from
the lower west coast. Each plot represents the individual points for each individual
with their identifying fish number at the top of each plot..................................... 68
A3. Plots to visually assess homogeneity. Residuals vs. fitted values for the MICs
of a) south coast and c) lower west coast and box plots of individual Bodianus
frenchii increment width time series for the b) south coast and d) west coast...... 69
A4. QQ plots and residual histograms used to assess normality in the increment
width data for the B. frenchii from a, b) the south and c, d) lower west coasts.... 70
A5. Plot displaying the autocorrelation function (ACF) calculated for the
increment width data for B. frenchii on the a) south and b) lower west coasts at
lags of 0 to 30 years. The dotted line indicates the statistical significance at alpha
= 0.05. ................................................................................................................... 72

66
Data Exploration
Outliers
An "outlier" is an observation that has a relatively large or small value
(conventionally more than three standard deviations away from the mean)
compared to the majority of the data (Zuur et al. 2010). Typically, a box plot or
Cleveland dot plot (Cleveland 1993) is used to visually assess whether outliers are
present. If outliers are highlighted, the corresponding data need to be investigated.
To assess the outliers in the chronology dataset, the data was visually, inspected
for outliers. There does not appear to be any outliers in either the south (A1) or
the lower west coast samples (A2).
A1. Dot plots for individual chronology time series for the 29 Bodianus
frenchii from the south coast. Each plot represents the individual points for each
individual with their identifying fish number at the top of each plot.

67
A2. Dot plots for individual chronology time series for 24 Bodianus
frenchii from the lower west coast. Each plot represents the individual points for
each individual with their identifying fish number at the top of each plot.

68
Homogeneity
A basic assumptions for parametric statistical analyses, such as linear
regression, is that the data have equal variance or homogeneity. This can be
assessed using a residuals vs. fitted values plot (A3 a, c), or individual boxplots
(A3 b, d) to assess the spread of residuals. The spread of variances in the
B. frenchii chronology data look as though there might be a slight conical shape
(A3 a, c), caused most likely by a decrease in otolith increment width with
increasing age. This suggests that there is a variance structure present within the
data.
A3. Plots to visually assess homogeneity. Residuals vs. fitted values for
the MICs of a) south coast and c) lower west coast and box plots of individual
Bodianus frenchii increment width time series for the b) south coast and d) west
coast.

69
Normality
Normality, another assumption for parametric statistics, is assessed using
QQ plots (A4 a, c) or inspecting the spread of the residuals, to see if they are
normally distributed (A4 b, d). The normality visualization plots for the
chronology data show that the data are not normally distributed, as the data points
in QQ plots in both the south (A4 a) and lower west coast (A4 c) are up to 10
standard deviations away from the mean and the residual histograms are highly
skewed to the right (A4 b, d). Therefore, the assumption of normality for any
parametric modeling using the B. frenchii increment width data is violated.
A4. QQ plots and residual histograms used to assess normality in the
increment width data for the B. frenchii from a, b) the south and c, d) lower west
coasts.

ELLENBOYLEN_THESIS_FOXFISH

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