Population Connectivity of Peltorhamphus Novaezeelandiae Between the Neighbouring Otago and Southland Regions of New Zealand

Population connectivity of Peltorhamphus novaezeelandiae between the neighbouring Otago and Southland regions of New Zealand.

Patricia Mary Mockett

A thesis submitted for the degree of Master of Science at the University of Otago, Dunedin, New Zealand.

July 2013 ii

Abstract

Connectivity among subpopulations of organisms is a primary focus in marine ecology and this knowledge is particularly imperative to the development of regulations in the management of fisheries (Cowen et al., 2007). The structure of local populations can be identified using intrinsic markers such as morphological and life history characteristics, as well as genetic markers (Bailey, 1997, Begg and Waldman, 1999). Genetic techniques are limited in that they cannot detect low levels of exchange (Thresher, 1999). Life history, morphological and meristic characteristics have been regularly employed to identify differentiation between local populations and in order to create a robust study it is reccomended that a combination of traits be examined (Begg and Waldman, 1999).

The objective of the present study is to determine the level of connectivity among subpopulations of the flatfish species Peltorhamphus novaezeelandiae in the neighbouring Otago and Southland regions of New Zealand. I endeavoured to determine whether these fish form a single panmictic population over this geographical landscape or, are in fact segregated into discrete subpopulations. Flatfish as a group are an important component in New Zealand’s annual commercial catch particularly in the Otago and Southland regions, yet there is little biological information available on each species including Peltorhamphus novaezeelandiae. Fish from each region were sampled by otter trawl and morphological, stable isotope, stomach content and age determination analyses were conducted. As a result of these analyses I concluded that Peltorhamphus novaezeelandiae exhibit a complex population structure within the Otago and Southland regions of New Zealand. These subpopulations experience connectivity whether it be via the dispersal and recruitment of eggs, larvae or juveniles or through the migration of adults. Subpopulations are subject to enough separation over spatial and temporal scales to enable and maintain significant differences in life history characteristics. It is evident that the population structure of P.novaezeelandiae occurs at smaller spatial scales than is currently recognised by the Quota Management System and it is hoped that the knowledge gained through the completion of this study enables more informed management decisions and the sustainability of this important fish stock.

iii

Acknowledgements

Firstly, I would like to thank my supervisor Steve Wing for the extensive knowledge you have imparted on me during the development and completion of my thesis and to the University of Otago’s Marine Science Department which has given me the opportunity to meet some amazing people of whom I hope to never lose contact with. Early on in my thesis work I had the opportunity to travel to the National Fish Collection unit at Te Papa museum in Wellington where I was fortunate to meet collection manager, Andrew Stewart and visiting flatfish researcher from NOAA, Thomas Monroe. I would like to extend my sincere thanks to Tom as his knowledge and training in Peltorhamphus identification was invaluable. Your enthusiasm for the amazing world of flatfishes was very contagious.

A special thanks to all staff at the Portobello Marine Lab, it was nice to see your smiling faces when I was getting frustrated with my work! To the Marine Studies Centre staff, I am grateful to have had the opportunity to work with you all and to be able to pursue my passion for all marine creatures while working in the aquarium. I even discovered that I enjoyed teaching much to my amazement. A big thank you to Ant Smith of the F.V Aurora, who went to immense trouble to collect fish required for this study, all of which were donated to me.

And finally, to all of my family and friends who had lost hope that they would ever see the day that I finally submitted this thesis, my parents Debbie and Bruce Mockett, my In-laws Viv and Colin Adam. Thank you for your never ending support, there were times when I wanted to quit but you kept me going. To my dad Bruce, thank you for all your help in the field and the never ending discussions and requests for progress reports. To my loving husband Scott Adam, your ongoing enthusiasm for all marine creatures is my greatest encouragement of all and my involvement in your varied work history in the commercial fishing sector has enabled me to have some incredible experiences that I wouldn’t have had the opportunity to otherwise. Thank you for all of the hours you spent assisting me in fish collections, transporting animals back to the lab and frequent visits out to Portobello to feed them. This is just the beginning of many more adventures together.

Table of contents

Abstract ...... iii Acknowledgements ...... iiv Table of contents...... v List of figures ...... ixx List of tables ...... xi

Chapter 1: GENERAL INTRODUCTION 1 1.1 Marine populations ...... 1 1.2 Population connectivity ...... 1 1.3 Identification of fish stocks ...... 2 1.4 Techniques for identifying population connectivity and structure ...... 3 1.5 Flatfish biology ...... 4 1.6 Peltorhamphus species ...... 5 1.7 Commercial interest and management ...... 5 1.8 Study Sites ...... 8 1.8.1 Otago ...... 8 1.8.2 Southland ...... 9 1.9 Objectives ...... 10

Chapter 2: AGE AND GROWTH ...... 11 2.1 Introduction ...... 11 2.1.1 The importance of age and growth in fisheries management...... 11 2.1.2 Age determination using otoliths ...... 12 2.1.3 Forms of aging error ...... 13 2.2 Objectives ...... 15 2.3 Materials and Methods ...... 16 2.3.1 Sample collection ...... 16 2.3.2 Otolith preparation for aging ...... 18

2.3.3 Age estimation...... 1919 2.3.4 Freezing Effects...... 1919 2.4 Data Analysis ...... 2222 2.4.1 Von Bertalanffy growth function 23

2.4.2 Growth curve comparison ...... 23 2.5 Results ...... 23 2.5.1 Length frequency and sex ratio ...... 23 2.5.2 Analysis of precision between readers ...... 26 2.5.3 Von Bertalanffy growth model ...... 27 2.6 Discussion ...... 31 2.6.1 Aging precision between readers ...... 31 2.6.2 Length frequency and sex ratios...... 31 2.6.3 Spatial variation in growth ...... 33 2.6.4 Limitations of growth estimates from length at age data ...... 35 2.6.5 Implications for management ...... 35 2.7 Conclusions ...... 37

Chapter 3: STABLE ISOTOPES AND DIET 38 3.1 Introduction ...... 38 3.1.1 Methods of diet analysis ...... 38 3.1.2 Stable Isotopes, what are they? ...... 3939 3.1.3 Isotopic fractionation...... 41 3.1.4 The use of stable isotopes in biological studies ...... 42 3.2 Objectives ...... 44 3.3 Materials and Methods ...... 45 3.3.1 Sample Collection ...... 45 3.3.2 Stomach Content Processing ...... 45 3.3.3 Stable Isotope Processing ...... 45 3.4 Data analysis ...... 47 3.4.1 Diet ...... 47 3.4.2 Stable Isotopes...... 48

3.5 Results ...... 4949 3.5.1 Peltorhamphus novaezeelandiae diet from stomach contents ...... 4949 3.5.2 PCO analysis ...... 5151 3.5.3 PERMANOVA...... 51 3.5.4 Natural stable isotope signatures ...... 5353 3.5.5 IsoError mixing model ...... 5656 3.6 Discussion ...... 58 3.6.1 Spatial variation in isotopic signatures...... 5959 3.6.2 Utilising complementary techniques ...... 62 3.6.3 Ontogenetic trophic shift ...... 62 3.7 Conclusions ...... 64

Chapter 4: MORPHOLOGY 65 4.1 Introduction ...... 65 4.1.1 Morphology in relation to population connectivity...... 65 4.1.2 Identification of fish stocks using morphometric characters ...... 65 4.1.3 The limitations of morphometrics ...... 6666 4.2 Objectives ...... 67 4.3 Materials and Methods ...... 6868 4.3.1 Sample collection ...... 6868 4.4 Data Analysis ...... 70 4.4.1 Standardising morphometric measurements ...... 70 4.4.2 Morphological analysis ...... 70 4.5 Results ...... 72 4.5.1 Principle coordinate analysis (PCO) ...... 72 4.5.1 PERMANOVA...... 73 4.5.2 Canonical analysis of principal components (CAP) ...... 75 4.6 Discussion ...... 7878 4.6.1 Population structure...... 7979 4.7 Conclusions ...... 81

vii

Chapter 5: GENERAL DISCUSSION AND CONCLUSIONS 82 5.1 Implications of spatial scale on population studies ...... 82 5.2 Summary of findings ...... 83 5.2.1 Growth ...... 83 5.2.2 Stable isotopes and diet ...... 85 5.2.3 Morphological characteristics ...... 8686 5.3 Population spatial structure and connectivity inferred from growth, stable isotopes, morphological characteristics...... 8888 5.4 Implications for management ...... 8989 5.5 Final conclusions ...... 93

References ...... 94 Appendix 1: Peltorhamphus taxonomic key ...... 102 Appendix II: IRI Index Values ...... 103

viii

List of figures

Figure 1.1 Map of New Zealand showing the five quota management area’s (QMA’s) for flatfish (FLA). The Otago and Southland regions are indicated by shading ...... 7

Figure 2.1 Sampling locations within the Southland (A) and Otago (B) regions as indicated by the solid points ...... 17

Figure 2.2 Peltorhamphus novaezeelandiae otoliths aged 1+ (A), 2+ (B) and 3+(C) ...... 20

Figure 2.3 Peltorhamphus novaezeelandiae otoliths aged 4+(A), 5+ (B) and 6+ (C) ...... 2123

Figure 2.4 Length frequency distribution by sex for Peltorhamphus novaezeelandiae from the Otago region (n=47) ...... 25

Figure 2.5 Length frequency distribution by sex for Peltorhamphus novaezeelandiae from the Southland region (n=99) ...... 25

Figure 2.6 Age bias plot showing the precision between readers ...... 26

Figure 2.7 Von Bertalanffy growth models for the Otago (n=47) and Southland (n=99) regions of southern New Zealand ...... 28

Figure 2.8 Von Bertalanffy growth models for males (n=14) and females (n=33) from the Otago region ...... 28

Figure 2.9 Von Bertalanffy growth models for males (n=63) and females (n=36) from the Southland region ...... 29

Figure 2.10 Von Bertalanffy growth models for males from the Otago (n=14) and Southland (n=63) regions ...... 29

Figure 2.11 Von Bertalanffy growth models for females from the Otago (n=33) and Southland (n=36) regions ...... 30

Figure 2.12 Von Bertalanffy growth models for all males (n=77) and females (n=69) from both the Otago and Southland regions ...... 30

Figure 3.2 Principal co-ordinates analysis (PCO) plot comparing taxonomic groupings between regions ...... 52

Figure 3.3 Principal co-ordinates analysis (PCO) plot comparing feeding strategy between regions ...... 52

Figure 3.4 Mean stable carbon (δ13C) and nitrogen (δ15N) values from muscle samples taken from the dorsal region of individual Peltorhamphus novaezeelandiae from Otago (n=25) and Southland (n=25) regions of New Zealand ...... 53

Figure 3.6 Trophic level versus proportion of diet derived from suspended particulate organic matter (SPOM) for individual Peltorhamphus novaezeelandiae originating from the Otago and Southland regions of New Zealand ...... 55

Figure 3.7 Trophic level versus length (mm) for individual Peltorhamphus novaezeelandiae originating from the Otago and Southland regions of New Zealand ...... 56

Figure 4.1 Blind side of Peltorhamphus novaezeelandiae indicating the morphometric character pectoral fin length blind side (PBS) ...... 68

Figure 4.2 Morphometric measurements taken from the eye side of 150 Peltorhamphus novaezeelandiae ...... 69

Figure 4.3 PCO graph with respect to region ...... 74

Figure 4.4 PCO graph with respect to sex ...... 74

Figure 4.5 Constrained ordination of principle components (CAP) showing the relationship between the Otago and Southland regions along canonical axes ...... 7777

Figure 4.6 Constrained ordination of principle components (CAP) showing the relationship between male and female Peltorhamphus novaezeelandiae along canonical axes ...... 7777

List of tables

Table 2.1 Mean shrinkage value of total length (cm) for Peltorhamphus novaezeelandiae following death and freezing. From the University of Otago master of science thesis submitted by Gavin James (1969) on The escapement of flatfish from trawl nets and studies on the biology of Peltorhamphus novaezeelandiae pg 18...... 22

Table 2.2 Summary of size and sex data for Peltorhamphus novaezeelandiae collected for growth analysis from the Otago and Southland regions during 2009, 2010 and 2011...... 24

Table 3.1 Summary of Peltorhamphus novaezeelandiae collected for carbon and nitrogen stable isotope processing...... 46

Table 3.2 Summary of permutational analysis of variance (PERMANOVA) and test for homogeneity of dispersion (PERMDISP) using the program PERMANOVA+ version 1.0.2 as an add on to PRIMER v6. Tests of statistical significance are indicated in bold type...... 57

Table 4.1 Results of PERMANOVA using a 2-factor design (region, sex) to test differences in morphology. Differences according to region obtained a significant P-value (P<0.0001)...... 73

Table 4.2 Allocation success results for up to 8 PCO axes (m) for CAP analyses according to region and sex. A maximum of eight axes can be used as the number of axes must not equal more than the number of variables of which there are eight morphometric characters in this analysis...... 75

Table 4.3 Leave one out allocation of observations according to a) region and b) sex from the canonical analysis of principal coordinates (CAP) analysis in PRIMER...... 76

Peltorhamphus novaezeelandiae, the New Zealand sole. Photographs by Patricia Mockett

xii

Chapter 1

GENERAL INTRODUCTION

1.1 Marine populations

A primary objective of marine ecology is to gain an understanding of the processes that regulate the abundance and distribution of marine populations (Cappuccino and Price, 1995). A key process driving and maintaining population dynamics (including abundance and distribution) is the connectivity among subpopulations of organisms (Cowen and Sponaugle, 2009). The objective of the present study is to determine the level of connectivity among subpopulations of the flatfish species Peltorhamphus novaezeelandiae in the neighbouring Otago and Southland regions of New Zealand. This will allow us to determine whether these fish form a single panmictic population over this geographical landscape or, are in fact segregated into discrete sub-populations. Flatfish as a group are an important component in New Zealand’s annual commercial catch particularly in the Otago and Southland regions, yet there is little biological information available on single species. The Peltorhamphus genus is a group of four species of sole, which despite consisting of one commercial species (P. novaezeelandiae) has had little scientific research. As public awareness of environmental sustainability increases and fish stocks around the world continue to decline it is important that I have all the necessary information needed to make appropriate decisions in fisheries management. Therefore, a comprehensive understanding of the population dynamics of Peltorhamphus novaezeelandiae is needed to ensure stocks are managed at the appropriate spatial scale, hereby reducing the risk of localised depletion.

1.2 Population connectivity

Population connectivity can be defined as the exchange of individuals between distinct, geographically separated subpopulations and is important for population replenishment, genetic mixing and habitat colonisation (Cowen et al., 2007, Pineda et al., 2007). Populations that have no

1 movement of individuals in or out are known as ‘closed’ populations and are completely seperate from other populations of the same species. Most marine populations are considered ‘open’ due to the lack of physical barriers in the marine environment (Pinsky et al., 2012). Movement in the marine environment is dominated by passive or weakly swimming early life stages such as eggs, larvae and juveniles. A stable, regional population may be compiled of many unstable local (sub) populations. The unstable subpopulations experience cycles of colonisation (as a result of dispersal by individuals) and eventually extinction, yet the population persists at the regional level; known as a metapopulation (Hanski, 1998). Some subpopulations may not be self-sustaining (the number of deaths are greater than the number of births) but are maintained by dispersal from another population (connectivity) in a source – sink configuration (Hanski, 1998). A source subpopulation is one which maintains another subpopulation by supplying individuals, usually larvae and juveniles; while a sink sub-population is one which exists through recruitement from external sources (Gonzalez et al., 1998). Movement occurs between subpopulations or between habitats utilized for different activities such as spawning and wintering grounds and juvenile habitat (Gibson, 1997).

Population connectivity occurs as an artefact of physical pathways for transport and dispersion, such as water currents and hydrographic features; coupled with biological processes such as the timing of spawning and larval behaviour (Gawarkiewicz et al., 2007). Field studies to quantify population connectivity are difficult due to the complex range of physical processes that act upon the final destination of organisms; such as tidal and wind driven currents, tidal jets and eddies. Dispersal and therefore connectivity may be inferred from biological studies by comparing differences in characteristics which are influenced by environmental and genetic factors (Cowen and Sponaugle, 2009, Gawarkiewicz et al., 2007).

1.3 Identification of fish stocks

Fish ‘stocks’ are an important concept in the management of fisheries (Begg and Waldman, 1999). They can be defined as groups of fish large enough to be self-reproducing which are adapted to their local environment, with each individual displaying similar life history characteristics (Begg and Waldman, 1999, Swain and Foote, 1999). The term ‘population’ and ‘stock’ are often used interchangeably but refer to different objectives. Generally, a ‘population’ is genetically distinct while

2 a ‘stock’ is often distinct in environmentally induced characteristics which are not heritable. Ideally, a stock would refer to a descrete population as is the assumption for many fisheries models, however is rarely the case in practice (Begg and Waldman, 1999).

1.4 Techniques for identifying population connectivity and structure

The structure of local populations can be identified using intrinsic markers such as morphological and life history characteristics, as well as genetic markers including mitochondrial DNA, nuclear DNA and protein variation (Bailey, 1997, Begg and Waldman, 1999). Genetic techniques are widely used to discriminate between marine populations (Bailey, 1997, Fairclough et al., 2013, Knutsen et al., 2003), however this technique is limited in that it cannot detect low levels of exchange between populations, nor can it measure exchange rates or origin of the individuals (Thresher, 1999). Genetic differentiation assumes reproductive isolation of stocks which have become separated over evolutionary timescales. In the marine environment however, there are fewer barriers between stocks and only a small level of migration is required to maintain genetic homogeneity which may be less than one individual per generation (Pawson and Jennings, 1996). Alternative methods such as tagging, morphometrics and life history characteristics provide small-scale resolution due to their sensitivity to the effects of short term environmental and population change (Pawson and Jennings, 1996).

Life history characteristics include growth rates, age at maturity, time of spawning, sex ratios, fecundity and trophic level (Begg et al., 1999b, Pawson and Jennings, 1996). These characteristics are expressions of genetic (intrinsic) and environmental (extrinsic) factors and are used to delineate fish stocks as they indicate geographic or reproductive isolation of populations (Begg et al., 1999b). For example, the time of spawning may differ between fish populations as subpopulations maximise potential for larval dispersal by adapting to local hydrological conditions, hydrological features such as currents and eddies may restrict the mixing of eggs and larvae between populations or alternatively may allow mixing of eggs, larvae and juveniles with re-segregation in the adult population (Begg et al., 1999b).

Morphological techniques examine the physical characteristics of an organism (Begg and Waldman, 1999). Linear measurements or ratios are used to quantify morphological differences; this

3 method has proven to be effective in discriminating between individual fish stocks (Dwivedi and Dubey, 2012, Marques et al., 2006, Turan, 1999, Turan, 2004). Morphometrics should be applied using a holistic approach due to the large intra-population variation which can obscure any inter- population differences (Pawson and Jennings, 1996). Morphological techniques are valuable as they are controlled by both environmental and genetic factors (Begg and Waldman, 1999).

Employing a holistic approach (using a combination of techniques) when investigating population structure is critical for accurately differentiating between subpopulations; no single characteristic will neccesarily reveal dissimilarities (Begg and Waldman, 1999). The intergration of several methods provides confirmation of the results from each technique and allows discrepancies within each technique to be resolved. Other methods which have not been mentioned here include, mark-recapture, commercial catch data, the use of parasites and otolith microchemistry (Begg and Waldman, 1999).

1.5 Flatfish biology

Flatfish belong to the monophyletic order Pleuronectiformes with over 700 species described in 15 family level taxa. The total species diversity for this order is unknown (Gibson, 2008). Pleuronectiformes are generally deep-bodied and laterally compressed with both eyes present on the same side of the head. Larval stages of all flatfish species start off as pelagic, bilaterally symmetrical organisms but during larval development undergo ontogenetic metamorphosis during which one eye migrates from one side of the head to the other. Whether the left or right eye migrates is dependent on the species, in some species it is random while in others it is fixed. After ontogenetic metamorphosis the larvae settle out of the water column and assume a benthic lifestyle as juveniles in habitats of soft substratum particularly silt, mud, sand and sand-shell mixtures (Gibson, 2008).

Flatfish perform ontogenetic habitat shifts as their morphology and requirements change during their different life stages (Ramos et al., 2009). Juveniles are thought to congregate in sheltered inshore waters (nursery grounds) such as estuaries and shallow mud and sand flats, where they remain for up to two years. They often dominate coastal nurseries in comparison with other benthic fish species (Gibson, 2008). Juveniles move offshore at 2-3 years of age for first spawning which occurs during winter and spring. They subsequently recruited into the adult population and often perform a ‘dummy

4 run’ with the adults to the spawning grounds. Previous studies have suggested that during this time specific cues are learnt which will allow individuals to navigate and recognise the grounds for future spawning events (Metcalfe et al., 2006). Flatfish are shallow water species which can be found from the intertidal zone to the continental slope, at depths to approximately 100 metres (Gibson, 2008).

Most New Zealand flatfish species are fast growing and short lived, only surviving to 5-6 years of age (Francis, 1988) with very few surviving 15-20 years (Stevens et al., 2005). They are highly fecund; Rhombosolea plebeia for example, can produce from 0.2 million to over 1 million eggs during a single spawning event (Colman, 1973).

1.6 Peltorhamphus species

New Zealand flatfish include the genera Rhombosolea, Pelotretis, Colistium and Peltorhamphus. The Peltorhamphus family is commonly known as the New Zealand sole, english sole or common sole and consists of three species, P. novaezeelandiae, P. latus and P. tenuis (James, 1972). A new species has recently been identified from the Otago / Southland regions and is currently being described. P. novaezeelandiae is a commercial species while the other species are not known to grow large enough to be of commercial value. There is little known about the biology or population dynamics of the Peltorhamphus species. It has therefore been assumed that the characteristics of these species are similar to that of other flatfish. This study aims to shed some light on the unknown characteristics of Peltorhamphus novaezeelandiae.

1.7 Commercial interest and management

Flatfish occur in all of the world’s oceans, with a high diversity of species in various shapes and sizes. In several regions around the world flatfish populations are large enough to support major fisheries and constitute a valuable resource (Gibson, 2008). Major flatfish fisheries are mostly found in the northern hemisphere in both the Atlantic and Pacific Oceans (Families Pleuronectidae, Scophthalmidae, Soleidae and Paralichthyidae). Commercial fisheries in the temperate southern regions target other groups including the Rhombosoleidae (Australia, New Zealand) and Paralichthyidae (South America) (Gibson, 2008).

There are 15 species of flatfish found in New Zealand coastal waters, eight of which are harvested commercially by an inshore domestic trawl fleet. This is a highly valuable fishery with 3629 tonnes (of a total allowable commercial catch (TACC) of 5409 tonnes) caught in the 2007/2008 year. Approximately 38% of this was landed in area 3 (FLA3) which encompasses the Otago and Southland regions (Fig. 1.1). During this time the TACC for customary and recreational take was set at 5 and 150 tonnes respectively (MFish, 2009).

The flatfish stocks are managed by the Ministry of Primary Industries (previously known as the Ministry of Fisheries) through New Zealand’s individual transferable quota management system. All flatfish species are combined in one generic code (FLA) in order to simplify management of landings (2009). Flatfish are managed through five management areas (Fig. 1), each of which is assigned a portion of the annual commercial quota relative to previous landings. Little is known about flatfish in New Zealand with few biological parameters available and no estimates of abundance or biomass for these taxa. The boundaries of the five management areas have been set with reference to tagging and morphological studies (2009, Colman, 1973, Francis, 1988) most of which took place in Canterbury or on the west coast of the South Island (2009).

Management Area 3 (FLA3) is the largest of the management areas and encompasses a large portion of the South Island coastline (Fig. 1.1). Fish within this zone are considered a single population. The 2006/2007 quota year saw a 47% reduction in commercial quota (from 2681 tonne to 1430 tonne) for FLA3 due to evidence of stock depletion (MFish, 2009).

In order to effectively manage fish stocks at the level of species, as well as at the level of populations it is paramount that we understand the role they play in the ecosystem and how they function as a population (Bailey, 1997). This includes indentifying subpopulations and determining the degree of connectivity between them. Flatfish in particular are important at both a social and economic level in the South Island of New Zealand as they account for a noteworthy proportion of the commercial, recreational and customary catch.

Figure 1.1 Map of New Zealand showing the five quota management areas (QMA’s) for flatfish (FLA). The Otago and Southland regions are indicated by shading. Flatfish management area 3 extends from the northern banks of the river on the east coast to the northern side of Big Bay on the west coast.

1.8 Study Sites

Although Otago and Southland are neighbouring regions covering a relatively short portion of the South Island coastline of New Zealand; they are distinct from one another in their topographical and hydrodynamic features. Both regions encounter the Southland current and both have large natural harbours which are presently and historically major fishing ports.

1.8.1 Otago

The Otago coastline is characterised by its many rocky headlands and deep inlets (Elliott, 1958). Noteworthy features include the Clutha river and its tributaries which are the major source of freshwater and provide the coast with fine sands through high country erosion of shist rock. These sands are transported up the coast in a northerly direction by the longshore Southland Current (Elliott, 1958). The Southland Current is of subtropical origins and contributes to the hydrological complexity of coastal Otago in its interaction with the inflow of major rivers (Hawke, 1989). There are three significant water masses which lie off the Otago coast: the nearshore neritic water, the subtropical Southland Current and Sub-Antarctic Surface Water. The Neritic water is low salinity as a result of freshwater runoff from the land while the Southland Current is of high temperature and salinity due to its subtropical origins. At the break in the narrow continental shelf (only 10km wide at the narrowest point) the Southland Front defines the beginning of the Sub-Antarctic Surface Water which is characterised by low temperatures and low salinities (Hawke, 1989). The Otago Peninsula is a large headland which juts out into the path of the offshore currents causing them bend out around the headland. They move back inshore north of the peninsula creating a counter clockwise eddy in Blueskin Bay that is enhanced by certain winds and tidal conditions (Murdoch, 1989). The Blueskin Bay eddy in the lee of Otago Peninsula acts as a mechanism to both retain and recruit pelagic larvae. A study by Murdoch (1989) found that the distribution of flatfish (Pleuronectidae) eggs was often confined to the eddy especially in spring. The author concluded that the eddy system may be responsible for maintaining local populations of crustaceans and coastal fishes.

1.8.2 Southland

The Southland region is the most southern region of New Zealand and includes Stewart Island. As with Otago the Southland region is in the path of the Southland Current. The Southland Current originates from the Tasman Current; upon reaching the west coast of the South Island it becomes the north flowing Westland Current and the South flowing Southland Current. The Southland current flows around the bottom of the South Island and is deflected around Stewart Island and through Foveaux Strait, finally proceeding in a northerly direction up the eastern seaboard (Jillett, 1969). The Foveaux Strait itself is Southland’s most distinct feature. The Foveaux Strait is a narrow and at times treacherous stretch of water which separates Stewart Island from the mainland, it is approximately 80km long and 23-53 km wide, sloping from a depth of 50m in the east to 20m in the west (Cranfield et al., 1999). The Strait is at latitude 46º South within an area known as the ‘roaring forties’ due to the extreme conditions generated by the prevailing westerly winds which are unimpeded by landmasses at this latitude (Pickrill and Mitchell, 1979). The tidal current runs anticlockwise around New Zealand and is intensified as it flows through the Strait from west to east. The velocity of the tidal streams is typically less than 80 cm s-1 but can reach 120 cm s-1 during periods of spring tides. Extreme wave conditions are created when the west to south west storm swells and tidal streams combine (Cranfield et al., 1999).

1.9 Objectives

The principal aim of this thesis is to investigate the inter-relationships of Peltorhamphus novaezeelandiae populations from two adjacent regions of New Zealand, Otago and Southland. I will do this by examining the differences in growth, trophic level, food web structure of prey base (as resolved by stable isotopes), sex ratio and morphometrics. This will allow me to determine whether Peltorhamphus novaezeelandiae populations in the Otago and Southland regions form a single panmictic population, or are in fact subpopulations separated by less preferable habitat. This research was approved by the animal ethics committee and conducted in accordance with the University of Otago Code of Ethical Conduct and all necessary laboratory compliance permits. The following specific objectives will be addressed in the subsequent chapters:

1. To determine if there is spatial variability in growth patterns among Peltorhamphus novaezeelandiae from the Otago and Southland regions.

2. To determine whether there are differences in trophic level by comparing the stomach contents and natural stable isotope signatures of δ13C and δ15N of the muscle tissue.

3. To investigate the differences in sex ratio between Peltorhamphus novaezeelandiae from Otago and Southland regions.

4. To determine whether there are morphological differences between Otago and Southland Peltorhamphus novaezeelandiae.

5. To investigate whether P. novaezeelandiae utilise sheltered coastal inlets as juvenile habitat.

Chapter 2

AGE AND GROWTH

2.1 Introduction

2.1.1 The importance of age and growth in fisheries management

The aging of fish and other marine animals provides vital data to inform the management of fisheries around the world (Paul, 1992). Age estimations are employed in the extrapolation of the most basic of population parameters such as maximum yield, growth, mortality and recruitment. The management of a fishery is often dependent of the reliability of this information in order to set quota’s, size limits and overall to increase the likelihood of a fishery’s sustainability (Morison et al., 2005). Since the beginning of mechanised commercial fishing there has been a need for information pertaining to the age of fish, whether it be to understand variable year class strengths, the dynamics of fish stocks or how a population reacts to fishing mortality (Paul, 1992). Many species of finfish live in excess of 20 years, some beyond 100, and therefore age and age composition are important features at both the individual and population levels (Campana and Thorrold, 2001).

Fast growth is a preferable species trait for a fishery as it often indicates that the species also exhibits early maturity and devotes a large portion of their resources into annual reproductive output (Denney et al., 2002). Growth is influenced by a variety of abiotic and biotic factors including population density, water temperature, prey availability and quality, habitat quality and fishing pressure, many populations also exhibit differential growth rates between the sexes (Nash et al., 2005). Species which are distributed over a wide geographical range experience different abiotic and biotic factors at the local level and it has long been recognised that sub-populations exist within a matrix of preferable habitats (Bailey, 1997).

Peltorhamphus novaezeelandiae are documented to grow to 510 mm total length and live to seven years of age (Stevens et al., 2004). James (1969) attempted a recapture experiment and to hold

11 live fish for a period of time in order to determine growth but was unsuccessful in both accounts. When comparing lengths and ages of fish caught by bottom trawl he concluded that growth was fastest in the first two years of life.

2.1.2 Age determination using otoliths

The aging of marine fishes began around the turn of the 20th century with use of length- frequency relationships, rings / bands present on scales and check marks on otoliths and other bones such as fin rays and vertebrae. This coincided with the decline of the European fisheries and a need for an understanding of age, growth and variability of year class strengths (Paul, 1992). Initial work on the aging of marine fish has continued to evolve with the recognition of the wealth of information which otoliths contain. Otoliths contain information on life history characteristics such as growth and age at maturity, as well as movement and environmental data such as population connectivity and natal origins, all of which form the fundamental basis of fisheries science today (Begg et al., 2005, Nash et al., 2005).

In teleost fish, otoliths are the most commonly used structure for estimating age and this is particularly true for flatfish with the exception of summer flounder and yellowtail flounder which are aged using scales (Nash et al., 2005). Otoliths are commonly known as fish ‘earbones’ or ‘earstones’ and there are three pairs found directly behind the brain, the sagittae, lapilli and asterisci, of which the sagittae are the largest and most commonly used (Popper and Lu, 2000). Each otolith is contained within its own chamber known as an otolithic end organ in the inner ear where it is suspended in endolymphatic fluid surrounded by bundles of sensory hair cells. The otolith is approximately three times denser than the body of the fish and mechanical stimulus in the form of vibration or movement causes the otolith to come into contact with the sensory hair cells enabling a fish to detect sound, acceleration and orientation (Popper et al., 2005).

The unique properties of the otoliths allow for precise aging and the relative ease of sample preparation makes them a popular tool in fisheries science with more than 800,000 otoliths aged in 1999 alone (Campana and Thorrold, 2001). Otolith properties include continual growth, isolation from the environment, no reabsorbtion and an aragonite crystalline structure. Continual growth, even during periods of adversity is unique in comparison to bone and scales where growth will slow or stop

12 altogether (Maillet and Checkley Jr, 1990). A continual record is essential for an accurate age estimate. Otoliths are formed in isolation to the environment unlike scales or teeth, they are also more protected than bone which is exposed to blood plasma which is less stable than endolymphatic fluid. Most importantly the otolith cannot be reabsorbed unlike any other calcified structure (Campana and Neilson, 1985), ensuring a complete record. Finally, the manner of calcification in aragonitic otoliths is unique to any other biomineralized structure creating a superior time keeper (Suga et al., 1991, Campana and Thorrold, 2001).

Determining the age of a fish involves counting the number of hyaline (translucent) and opaque zones which surround the nucleus (Fig. 1.1). A single hyaline and opaque zone are deposited annually and are known as annuli. The hyaline zone is deposited during periods of slower growth while the opaque zone is deposited during fast growth; it is richer in calcium carbonate and is therefore much denser than the hyaline zone (Jennings et al 2009). Daily increments are also present in otoliths and this has enabled remarkably precise aging of larval fish and juveniles (Campana and Neilson, 1985). Otolith morphology is species specific with an incredible range of shapes and sizes. Therefore different techniques are required in order to view the annuli. Preparation techniques may include leaving the otolith whole, grinding and polishing the otolith to remove the overburden or sectioning. Thin sections must be across the nucleus to ensure a complete increment sequence (Campana and Neilson, 1985). Flatfish otoliths tend to be flat and oval in shape due to the twisting of the skull during larval metamorphosis and therefore simply require grinding and polishing (Nash et al., 2005).

2.1.3 Forms of aging error

Despite the value of otoliths to provide vital growth and environmental information, there are some limitations. A mix of pattern recognition and knowledge and experience is required for otolith aging of any given species (Morison et al., 2005). Age determination is subject to two main forms of error: (1) process error, and (2) subjectivity error (Campana and Thorrold, 2001). A process error refers to the structure itself, bony structures in fish do not always exhibit continual growth and therefore a complete historical record. Otoliths do feature continual growth, however a complete record is not visible on all axes within the otolith structure. Subjectivity error refers to the preparation and interpretation of samples which can vary markedly between readers (Campana and Thorrold,

2001). Inaccurate aging can have disastrous consequences for fisheries management especially when generating population parameters such as yield, growth, mortality and recruitment (Morison et al., 2005). New Zealand is certainly not immune to such disasters as can be demonstrated by the over- exploitation of the orange roughy (Hoplostethus atlanticus) fishery on the Chatham Rise (Tracey and Horn, 1999). Examples of over-exploitation due to aging error highlight the need for age validation.

Age validation has often been mistaken for validation of the increment periodicity and does not confirm the age of the fish itself. These errors are known as accuracy and precision errors. Accuracy errors refer to the proximity of the age estimate to the true value while precision errors refer to the periodicity of repeated measurements on a given structure (Campana and Thorrold, 2001). Determining absolute age is the ultimate goal in any age validation study, however this is beyond the scope of the present study. There has been very few studies to date focused on Peltorhamphus novaezeelandiae with the exception of the Master of Science thesis submitted by Gavin James in 1969 and a research report for the Ministry of Fisheries (Stevens et al., 2004). James validated his method of age determination and concluded that the hyaline and opaque zones in the otoliths of P.novaezeelandiae were laid down annually. In order to also validate the interpretation of the age readers and therefore increase accuracy it is important to control for bias and systematic errors. This can be done by monitoring consistency both within and among age readers with the use of a mean coefficient of variance (CV) and age bias plots for randomly selected fish (Campana and Thorrold, 2001), as will be incorporated into this study.

2.2 Objectives

The objective of this chapter is to compare the growth and condition indices of P.novaezeelandiae from the Otago and Southland regions. The Otago and Southland regions differ significantly in geology and subsequently hydrology. Therefore it is reasonable to assume that individuals residing in these regions may experience differential growth rates and condition indices due to exposure to different abiotic and biotic factors. The specific aims of this chapter are:

1. To determine growth using the Von Bertalanffy growth function for Peltorhamphus novaezeelandiae from the Otago and Southland regions.

2. To compare population growth rates (k) and growth curves of Peltorhamphus novaezeelandiae and from the Otago and Southland regions.

3. To determine whether any differentiation in growth exists between the sexes.

2.3 Materials and Methods

2.3.1 Sample collection

Peltorhamphus novaezeelandiae individuals were collected by otter trawl from commercial fishing vessels in the Otago and Southland coastal regions between January 2010 and June 2012 (Fig. 2.1). The fishing vessels were inshore vessels which towed nets of a maximum wing mesh size of 6 inches and a cod end mesh size of 4 inches. Specimens were identified to species level using the Peltoramphus identification key developed in 2010 by Thomas Munroe of the National Oceanic and Atmospheric Administration (NOAA) (appendix I). The number of sites sampled was greater in the Otago region due to the accessibility to participating fishing vessels but the total number of fish captured was greater for the Southland region due to a greater capture success. A selection of individuals representing the total size range caught were used to determine the growth of the species. The fish were stored whole on ice and then frozen at the Portobello Marine Laboratory (PML) awaiting further processing.

Figure 2.1 Sampling locations within the Southland (A) and Otago (B) regions as indicated by the solid points.

During 2010 juvenile P. novaezeelandiae were unsuccessfully targeted from the shore in inlets surrounding the targeted regions, including the Otago Harbour and Riverton Estuary using a 25 metre beach seine net with mesh size of 0.4cm. A small number of juvenile P. novaezeelandiae were captured on the commercial fishing vessels.

The fish (n=146) were defrosted overnight in running seawater at PML. Each fish was weighed (g), measured for total length (mm) and the saggital otoliths extracted. The otoliths are located in a cavity below and to the rear of the brain. They were removed by slipping a knife under the operculum and making a horizontal cut across the top of the head. Once the otoliths were removed they were cleaned in Milli-Q purified water using forceps to remove any membranous material and air dried for a minimum of 48 hours, before being stored in 2 ml Eppendorf tubes.

2.3.2 Otolith preparation for aging

One otolith from each pair was mounted on a standard 3 inch glass microscope slide using CrystalbondTM 509 Amber thermoplastic cement. The otolith was initially fixed to the slide sulcus side down. Each mounted otolith was polished using 800–1200 µm wet and dry sandpaper in order to fully reveal the growth increments. The slide was then heated for a second time and the otolith was turned and ground / polished on the opposite side. Otoliths were viewed at frequent intervals during the polishing process under a compound microscope to determine whether the polishing plane was near the primordial plane. The amount of refocusing required to move between the polishing plane and the primordial plane was used to indicate the amount of polishing still necessary. As the polishing plane neared the primordial plane only the finer grit paper was used and a high magnification was needed to ensure that the polishing plane stopped just short of the primordial plane (the otolith was not destroyed due to overpolishing).

Due to their multidimensional structure, each otolith was viewed under both reflected and transmitted light at several different magnifications in order to obtain a satisfactory reading. The polished specimens were aged three times, once by reader1 and twice by reader2. The otoliths were read in a random order and the readers had no information as to the weight or length of the fish from which they originated. Final age estimates were obtained by averaging the 3 readings for each fish.

2.3.3 Age estimation

At the centre of the otolith is the nucleus which is then surrounded by a hyaline zone and further alternating opaque and hyaline zones depending on the age of the fish. As described in James (1969), the nucleus in otoliths from Peltorhamphus novaezeelandiae is highly variable in size suggesting that the first annuli may be fused with, and therefore indistinguishable from the nucleus. Thus following conclusion regarding the position of the nucleus, age was determined by counting the surrounding opaque zones. For example a 1+ fish has a nucleus, a hyaline zone, an opaque zone and then may or may not have a further hyaline zone.

2.3.4 Freezing Effects

The phenomenon of shrinkage in flatfish following death and freezing is well documented in the literature (Lavety, 1987, Lockwood and Daly, 1975, Halliday and Roscoe, 1969). To account for this a sample of 25 fish of various sizes were measured for total length immediately following capture and then again in a thawed state, after a minimum of two weeks frozen at -20ºC. The shrinkage value (mm) was found to be in agreement with James’ (1969) Master of Science thesis and all length measurements from this point on have been altered accordingly (Table 2.1).

A.) B.)

C.)

Figure 2.2 Peltorhamphus novaezeelandiae otoliths aged 1+ (A), 2+ (B) and 3+ (C). Vertical white arrows on each photograph indicate the position of the outer edge of each opaque zone.

A.) B.)

C.)

Figure 2.3 Peltorhamphus novaezeelandiae otoliths aged 4+ (A), 5+ (B) and 6+ (C). Vertical white arrows on each photograph indicate the position of the outer edge of each opaque zone.

Length at capture (cm) Shrinkage (cm) Length at capture (cm) Shrinkage (cm)

8.0 – 11.9 0.1 32.0 – 35.9 0.7

12.0 – 15.9 0.2 32.0 – 39.9 0.8

16.0 – 19.9 0.3 40.0 – 43.9 0.9

20.0 – 23.9 0.4 44.0 – 47.9 1.0

24.0 – 27.9 0.5 48.0 – 51.9 1.1

28.0 – 31.9 0.6

2.4 Data Analysis

Data was analysed in Microsoft Excel 2007. Fish which had otoliths that were deemed unreadable by either reader1 or reader2 were removed from analysis (n=9). Consistency of age estimates by the two readers were tested with an age bias plot and precision was estimated by a coefficient of variation (CV) value (Campana et al., 1995). Growth curves were constructed and growth parameters were estimated in regards to region and sex using the Von Bertalanffy growth function (Bertalanffy, 1938) as described by Haddon (2001).

2.4.1 Von Bertalanffy growth function

Growth curves were constructed from age at total length data using the Von Bertalanffy growth model (Haddon, 2001):

L  L 1 eK[tt0 ] t   

Where L∞ is the estimated average maximum length of an individual, k is the growth rate coefficient and t0 is the hypothetical age at which the species has zero length. The curves were fitted using the least squares function in Microsoft EXCEL.

2.4.2 Growth curve comparison

Growth curves were compared between region and between sex. Due to the non-linear nature of the Von Bertalanffy growth function, differences were analysed using the residual sum of squares method (ARSS). The ARSS is a total comparison, meaning it does not compare the parameters individually but simply tests whether two or more curves are statistically different overall (Haddon, 2001). The analysis of the residual sum of squares calculates an F-statistic and a p-value for the F- statistic.

2.5 Results

2.5.1 Length frequency and sex ratio

A total of 146 Peltorhamphus novaezeelandiae were collected from the Otago and Southland regions for analysis of growth (Table 2.2). 47 of these were from the Otago region and 99 from the Southland region. P. novaezeelandiae from the Otago region ranged from 155mm in length and 161 g in weight to 504 mm and 1425 g, while the Southland region ranged from 111 mm and 12 g to 436 mm and 865 g respectively. For both regions males were smaller than females in both length and weight. The length frequency data for Otago showed that the larger size classes (>400mm) were exclusively female while fish smaller than 250 mm in length were exclusively male (Fig. 2.4). Both

23 males and females were present in the middle size classes. An overall ratio of 1.8 females to every 1 male (sex ratio’s were compiled from the entire data set not just the individuals which were suitable for age estimation in order to give a more accurate depiction of the population).

The length frequency data for the Southland region contrasted that of the Otago region with a higher ratio of males and an overall smaller length (Fig. 2.5). Fish less than 150 mm were more frequently male while fish in the 150mm–200mm size range are exclusively female. As with Otago the middle size classes (200mm–400mm) were a mix of both male and females. In contrast to the Otago region, males were present in higher numbers than females with 1.75 males to every 1 female. The maximum age assigned to a fish in this study was 6+ which was in agreement with James (1969). Stevens, James et al. (2004) concluded that the maximum age of Peltorhamphus novaezeelandiae was 7+ years.

Table 2.2 Summary of size and sex data for Peltorhamphus novaezeelandiae collected for growth analysis from the Otago and Southland regions during 2009, 2010 and 2011.

Mean Length (mm), Mean Weight (g), Sex n (Range) (Range)

Otago Male 14 315, (155 - 388) 369, (161 - 596)

Female 33 362, (276 - 504) 557, (218 - 1425) Total 47 339, (155 - 504) 463, 161 - 1425) Southland Male 63 299, (111 - 402) 292, (12 - 699) Female 36 301, (149 - 436) 331, (28 - 865) Total 99 300, (111 - 436) 311, (12 - 865) Total 146

14 Female Male

Frequency 6

0 200 250 300 350 400 450 500 550 Length (mm)

Figure 2.4 Length frequency distribution by sex for Peltorhamphus novaezeelandiae from the Otago region (n = 47).

60 Female 50 Male

30 Frequency Frequency

0 150 200 250 300 350 400 450 Length (mm)

Figure 2.5 Length frequency distribution by sex for Peltorhamphus novaezeelandiae from the Southland region (n = 99).

2.5.2 Analysis of precision between readers

An age bias plot was constructed by taking reader2’s average age for all fish of a given age by reader1 (Fig. 2.6). For example, for all fish which were aged as 1 year old by reader1, reader2’s estimates (two estimates for each individual) were averaged to give a single value for each of the 6 age groups present. The line represents the ideal situation where both readers were in agreement for all age estimations. The error bars represent the 95% confidence interval of the mean age given by reader2. Precision between the two readers was very good overall however a small amount of bias is apparent. Reader2 tended to give an estimated age a little higher than that of reader1 for age classes 1, 2 and 3, and slightly lower for the 5 year old age class. The mean CV between readers was 21.8 %.

Mean age estimated by reader 2 reader by estimated age Mean 0 0 1 2 3 4 5 6 7 8 Age estimated by reader 1

Figure 2.6 Age bias plot showing the precision between readers. The line represents the ideal situation where both readers are in agreement for each age estimation. The error bars represent the 95% confidence interval for the mean age estimated by reader2.

2.5.3 Von Bertalanffy growth model

An individual Von Bertalanffy growth model was fitted to both the Otago and Southland regions in order to determine whether there was differential population growth overall (Fig. 2.7). The growth parameters as determined by the model for Otago were L∞ = 423.1 mm, k = 0.57, n = 47 and for Southland were L∞ = 367.4 mm, k = 0.73, n = 99. The growth curves were not significantly different where F = 2.28 and p-value = 0.08.

To determine whether differential growth was present between the sexes, Von Bertalanffy growth models were fitted to the data for each sex by region (Figs. 2.8 and 2.9). Figure 2.8 demonstrates growth curves for males and females from Otago. The growth parameters for females were L∞ = 451.7 mm, k = 0.48, n = 33 and for males were L∞ = 371.8 mm, k = 0.77, n = 14. Although the length frequency graph (Fig. 2.4) indicated that the larger size classes were dominated by females there was no significant difference between the male and female growth models (F = 0.706, p-value = 0.55).

Growth curves for male and females from the Southland region (Fig. 2.9) showed no significant differences F = 0.093, p-value = 0.96. Male growth parameters were L∞ = 344.6 mm, k = 0.90, n = 63 and for females L∞ = 347.3, k = 0.82, n = 36.

Growth curves were also compared between region for each sex. Figure 2.10 shows the growth models for males from each region and figure 2.11 shows the growth models for females from each region. Neither comparisons indicated any significant difference in growth with F = 0.38, p-value = 0.77 for males and F = 2.02, p-value = 0.12 for females.

600

500

400 Otago 300 Otago Von Bert 200 Southland

Total Length (mm) Length Total Southland Von Bert 100

0 0 1 2 3 4 5 6 Age (Years)

Figure 2.7 Von Bertalanffy growth models for the Otago (n = 47) and Southland (n = 99) regions of southern New Zealand. The two models were not significantly different with an F statistic of 2.28 and a p-value of 0.08.

600

500

400 Otago Female 300 Female Von Bert 200 Otago Male

Total Length (mm) Length Total 100 Male Von Bert

0 0 1 2 3 4 5 6 Age (Years)

Figure 2.8 Von Bertalanffy growth models for males (n = 14) and females (n = 33) from the Otago region. The models did not show any significant difference with an F statistic = 0.706 and p-value = 0.55.

500 450

400

350 300 Southland Female 250 Female Von Bert 200 150 Southland Male

Total Length (mm) Length Total 100 Male Von Bert 50 0 0 1 2 3 4 5 6 Age (Years)

Figure 2.9 Von Bertalanffy growth models for males (n = 63) and females (n = 36) from the Southland region. The models did not show any significant difference with an F statistic = 0.093 and p-value = 0.96.

450 400

350

300 250 Otago Male 200 Otago Von Bert 150 Southland Male

Total Length (mm) Length Total 100 Southland Von Bert 50 0 0 1 2 3 4 5 6 Age (Years)

Figure 2.10 Von Bertalanffy growth models for males from the Otago (n = 14) and Southland (n = 63) regions. The models did not show any significant difference with an F statistic = 0.38 and p-value = 0.77.

600

500

400 Otago Female 300 Otago Von Bert 200 Southland Female

Total Length (mm) Length Total Southland Von Bert 100

0 0 1 2 3 4 5 6 Age (Years)

Figure 2.11 Von Bertalanffy growth models for females from the Otago (n = 33) and Southland (n = 36) regions. The models did not show any significant difference with an F statistic = 2.02 and p-value = 0.12.

600

500

400 Female 300 Female Von Bert 200 Male

Total Length (mm) Length Total 100 Male Von Bert

0 0 1 2 3 4 5 6 Age (Years)

Figure 2.12 Von Bertalanffy growth models for all males (n = 77) and females (n = 69) from both the Otago and Southland regions. The models did not show any significant difference with an F statistic = 1.37 and p-value = 0.25.

2.6 Discussion

2.6.1 Aging precision between readers

Some bias was apparent in the aging of whole Peltorhamphus novaezeelandiae otoliths between readers 1 and 2. Reader2 tended to assign the younger fish with a slightly higher age estimate than reader1 and the 5 year old age class slightly lower. The coefficient of variance for aging precision was not within the accepted 5 – 10% range with a value of 21.8%. This reflects the difficulty of aging whole P.novaezeelandiae otoliths especially for the younger age classes where zones are not always well defined, many check marks may make up a single zone and therefore there is increased subjectivity and bias between readers.

Both James (1969), and Stevens, James et al. (2004) also reported difficulty in zone resolution due to the thick, opaque and dense nature of the otoliths. They noted that the sulcus was very shallow on the proximal surface, making it difficult to manually create a thin section in thicker otoliths without compromising the otolithic structural integrity. That finding was also true in this study, suggesting that otoliths from older fish could easily be inappropriately assigned to a younger age group and therefore the maximum age of P. novaezeelandiae could be older than currently thought. The report completed by the National Institute of Water and Atmospheric Research (NIWA) into the maximum age of Peltorhamphus novaezeelandiae (Stevens et al., 2004) did not calculate a coefficient of variation between readers in order to analyse aging precision, they did however state that 46.5% of age estimates between readers were identical (72.6% of age estimates were identical between readers in the current study).

2.6.2 Length frequency and sex ratios

The ratio of males to females for the Southland region (1.75 males to 1 female) was consistent with previous studies by James (1969) and Graham (1956) who gave ratios of 1.67 and 1.5 males to every female. The male to female ratio for the Otago region however, was reversed with more females to males (1.8 females to every 1 male). The given ratio by James (1969) is based on P.novaezeelandiae collected from the Otago region which is in stark contrast of the Otago results given in this study. The bias toward larger sized individuals in the Otago sample may explain this discrepancy as the larger fish

31 were observed to be typically female although comparison of male and female growth curves showed no significant differentiation. The mean fish length in Otago was 362 mm for females and 315 mm for males while in Southland the mean for females was 301 mm and for males the mean was 299 mm. It is common in the flatfish fishery for catches to consist of one or two age classes (MFish, 2009) and therefore consist of a narrow size range. The size of individuals can vary from day to day and within relatively small distances (pers. Comm.), suggesting that individuals from similar age classes or of similar developmental stages tend to congregate together.

An alternative explanation may be that P.novaezeelandiae exhibit sequential hermaphroditism, where at some point in their life they change sex. Sex change can be induced by both social and environmental cues, if the change is male to female it is known as protandry and female to male is protogyny (Warner, 1975, Sadovy and Shapiro, 1987, Grober and Bass, 2002). Sequential hermaphroditism is prevalent in teleost fishes, particularly in reef dwelling species (Chopelet et al., 2009, Godwin et al., 2003). It is not however, a common occurrence in flatfish (pleuronectiformes) (Luckenbach et al., 2009, Godwin et al., 2003). An example of hermaphroditism in flatfish is a species from the Bothidae family, Citharichthys cornutus (Gutherz, 1969). Gutherz (1969) describes this species as sexually dimorphic which includes a hermaphroditic form that exhibits intermediate characteristics of males and females as well as ‘normal’ males and females.

A more likely scenario is that Peltorhamphus novaezeelandiae display sexual dimorphism in growth (and likely maturation); and that as mentioned above the method of collection has resulted in a bias towards smaller fish from the Southland region and larger fish from the Otago region skewing the sex ratio data. Higher female growth is a common trait of flatfish species and is a product of delayed maturation (Lozán, 1992, Imsland et al., 1997). Energy is channelled towards growth as opposed to reproduction which eventually results in larger females which have the ability to produce a larger number of eggs (Imsland et al., 1997). This has interesting implications for aquaculture as sex is determined by temperature, many studies have subsequently focused on the effect of temperature on sex determination for different flatfish species in a bid to produce all female offspring (Luckenbach et al., 2009, Luckenbach et al., 2003, Baroiller and D'cotta, 2001). In order to rule out sequential hermaphroditism in P.novaezeelandiae examination of the gonadal tissue would be required as described by Sadovy and Shapiro (1987).

2.6.3 Spatial variation in growth

There is no significant spatial variability in growth among males and females or between the neighbouring Otago and Southland regions of southern New Zealand suggesting that the external factors which regulate growth are constant throughout the Otago and Southland coastal zones. Past studies of growth in other New Zealand flatfish species have returned contrasting results. Differential growth between males and females was detected in both yellow belly flounder, Rhombosolea leporina and sand flounder, Rhombosolea plebeia (Colman, 1974, Francis, 1988). These studies concluded that females grew larger and faster than males, as did Stevens, Francis et al. (2005) when examining the growth of brill, Colistium guntheri and turbot, Colistium nudipinnis. Francis (1988) recalculates the growth rate of Canterbury sand flounder from historical tagging data (Mundy, 1968). He identified that sand flounder from Akaroa Harbour grew significantly slower than those from Lyttelton Harbour or the Avon-Heathcote Estuary. Several discrepancies between the two interpretations of the data were detected which Francis concluded was due to errors in Mundy’s aging method, highlighting the necessity of robust methodology to avoid potentially disastrous errors in fisheries management. Similar to the present study, an investigation into the growth of the fringed flounder, Etropus crossotus in South Carolina, USA found no significant difference between the growth of males and females (Reichert, 1998). Females are generally larger than males in most flatfish species with exceptions being stone flounder (Platichthys bicoloratus) and wide eyed flounder (Bothus podus) (Gibson, 2008).

Although none of the growth curves in the present study show any significant differentiation there was some indication that differences do exist, such as with the Otago males and females. As shown in figure 2.4, the larger size classes are dominated by females and reach a large asymptotic maximum size of 451.7 mm with a growth rate of 0.48, this can be contrasted against the Otago males which attain an asymptotic maximum length of 371.8 mm with a growth rate of 0.77. It is possible that the sample size for Otago males (n = 14) may be too small to allow any true differences to be detected. Alternatively, The length frequency distribution for Southland (Fig. 3.2) shows a mix of males and females at all size classes which is supported by the non-significant comparison of growth curves and an asymptotic maximum length of 344.6 mm and 347.3 mm and growth rates of 0.90 and 0.82 respectively.

For all given growth models the larger the value for L∞, the slower the growth rate (k). This does not appear to be the case for brill, turbot, sand flounder or lemon sole based on the Von Bertalanffy growth parameters given in the Ministry of Fisheries (NZ) plenary document (2009). Brill and turbot grow slowly with a growth rate of between 0.10 and 0.39 (MFish, 2009), with a maximum age of 21 years (Stevens et al., 2005). Lemon sole grow at a fast rate of between 1.29 and 1.85 (MFish, 2009), living for only 5+ years (Rapson, 1940). With a growth rate of 0.57 for Otago and 0.73 for Southland as determined by the current study I can conclude that Peltorhamphus novaezeelandiae are one of the fastest growing commercial flatfish species with a short life span, second only to lemon sole, Pelotretis flavilatus.

2.6.4 Limitations of growth estimates from length at age data

The use of length-at-age data can present challenges, especially in exploited populations such as the commercially harvested Peltorhamphus novaezeelandiae. The selectivity of fishing gear or avoidance by fisherman can result in a biased estimate of mean length-at-age and consequently result in incorrect growth curves. Data obtained from historical fisheries landings can likewise be biased due to the selectivity of the fishery as a whole (Gibson, flatfish biology and exploitation chapter 7). The flatfish fishery on the southern east coast of New Zealand selects for flatfish above the legal minimum size of 25cm by using trawl nets which have a mesh size of approximately 4 inches in the cod end (collection point at the base of the net) allowing smaller fish to escape. During periods of intense fishing effort, especially during times of the year when P.novaezeelandiae are less abundant there is potential for skewed length–at-age data.

2.6.5 Implications for management

Values of k (growth rate) show that Peltorhamphus novaezeelandiae grow quickly to reach a maximum asymptotic length of approximately 395mm. Living to a maximum age of between 6+ years (as determined by the current study and James’ (1969) Master of Science thesis) and 7+ years (MFish, 2009), suggests that P.novaezeelandiae employ a strategy of fast growth particularly in the first 2 – 3 years to attain maximum asymptotic length, high abundance, high fecundity, reproduce frequently and have relatively short generation times. This is the ideal situation for a sustainable fishery and can be explained in terms of r and K (Reznick et al., 2002).

K- selection describes a population which exhibits a relatively constant population size over time, density dependent mortality, inter- and intraspecific competition, slow development but with

35 increased competitive ability, reproduce later, larger body size and a longer lifespan. Populations which exhibit these characteristics are able to maintain population size and to survive periods of unfavourable conditions but are less able to recover from catastrophic events (Pianka, 1970).

Fisheries management favours species which display r- selected life history characteristics. The level of sustainable harvest is much higher than that of the slower growing and reproducing K- selected species and populations have a greater ability to absorb periods of intense fishing effort (Charles, 2008). Most flatfish fall under the banner of r- selection with the noteable exception of New Zealand’s brill, Colistium guntheri and turbot, Colistium nudipinnis (Stevens et al., 2005) with an international example being that of halibut, Hippoglossus stenolepis (Casey et al., 1995).

2.7 Conclusions

 The sex ratio of 1.75 males to every 1 female is consistent with the existing literature.

 There were no spatial dissimilarities in growth detected between the Otago and Southland regions of New Zealand for the common sole Peltorhamphus novaezeelandiae.

 No sex specific variation in growth was detected. However, although statistical significance was not reached, females from Otago were consistently larger than their males counterparts. A larger sample size may resolve this issue.

 Peltorhamphus novaezeelandiae exhibit fast growth and a relatively small body size indicating that their life history is based on r- selection making them an ideal commercial fishery in terms of sustainable management.

The ultimate aim of this chapter was to determine whether differences in growth existed between the neighbouring Otago and Southland populations of P. novaezeelandiae. No such dissimilarities were detected and thus I must conclude that the extrinsic conditions which regulate growth are constant throughout the Otago and Southland regions. The following chapters describe the life history characteristics morphology and diet all of which will be critically examined to determine the population connectivity of P. novaezeelandiae between the Otago and Southland regions.

Chapter 3

STABLE ISOTOPE SIGNATURES AND DIET

3.1 Introduction

Differential productivity over large spatial scales often leads to a patchy habitat matrix in terms of the quality and quantity of available food resources. This may result in contrasting emphasis on specific prey items at local scales and contribute to the maintenance of subpopulations within a species geographic range (Pickett and White, 1985). The spatial heterogeneity of prey species across fragmented habitats may result in the localised exploitation of different trophic levels and consequently the employment of adaptive feeding strategies (Huxel et al., 2004). The food webs supporting localised populations may reflect the relative availability of sources of basal organic matter and fluctuations in resources may result in a diversification of prey species thus increasing the temporal stability of local populations (Vander Zanden and Vadeboncoeur, 2002, Fry et al., 1999, Wing et al., 2012).

3.1.1 Methods of diet analysis

In order to determine whether dissimilarities in diet exist at large spatial scales, I must firstly establish whether the consumption of specific prey groups occurs at all sites and secondly the prevalence of specific prey group consumption at each site (Schlosser, 1991). The analysis of stomach contents may be achieved by occurrence, numerical, volumetric or gravimetric methods (Hyslop, 1980). The occurrence method gives a percentage of all fish which have a specific prey species present in their gut. In the numerical method the number of individuals in each food category is recorded and the volumetric method records prey items in relation to their volume, often found by using a graduated measuring cylinder and displacement techniques. The gravimetric method refers to the weight of a food category in relation to the total weight of the stomach contents and is to be employed in the present study (Hyslop, 1980).

The analysis of stomach contents alone has its problems, stomach contents only reveal what the animal has consumed during recent foraging and results can be highly variable as available prey items may be influenced by time of year, tidal cycle and time of day, as well as predator density and competition (Rudnick and Resh, 2005).

Another method is the use of stable isotopes, which can be used to determine the proportional contribution of food sources to an animal’s diet, some of which may not be represented in the gut content analysis due to rapid digestion (Phillips and Gregg, 2001). Coupled with stable isotope techniques, gut content analysis can be used to determine whether differences in isotopic values are due to true dietary differences or to variation of isotopic values for basal carbon sources (Wing et al., 2012, Layman et al., 2012). Gut content analysis is useful in delineating diet in the short term and resolution of prey consumption to the species level, while the analysis of stable isotopes is useful for longer term diet studies and the inference of trophic level. A combination of these techniques allows maximum resolution of the data (Rudnick and Resh, 2005).

3.1.2 Stable Isotopes, what are they?

Stable isotopes occur naturally in the environment and as their name suggests do not decay spontaneously like radioactive isotopes. They have become a prominent feature of ecological studies as they provide both source – sink (tracer) and process information (Peterson and Fry, 1987). The application of stable isotopes to food web studies is valuable due to the predictable way that stable isotope ratios in the proteins of animal tissue reflect those of the proteins in their diet, thus enabling researchers to investigate trophic relationships pertaining to time and space and develop models of trophic structure (Layman et al., 2012, Bearhop et al., 2004). In ecological studies nitrogen (N) and carbon (C) are the most commonly used elements however, sulphur (S), oxygen (O) and deuterium (D) may also be used for particular applications (Layman et al., 2012). The relative abundances of the heavier isotopic species are very low with 13C occurring at 1.11% and 15N at 0.37% (Ehleringer and Rundel, 1989), these isotopes tend to persist in metabolically active tissues (such as muscle and blood) for weeks to months and indefinitely in metabolically inert tissues (such as otoliths and bone) (Hobson, 1999).

Isotopic compositions are expressed in standard delta notation (δ), where each unit is parts per thousand (‰) from a chosen standard and is determined by the following equation:

In this equation R is the heavy to light isotope ratio in respect to the sample and the standard which in the case of nitrogen and carbon is 15N:14N and 13C:12C respectively. The internationally recognised standard for carbon is the PeeDee limestone and for nitrogen is atmospheric air (Peterson and Fry, 1987).

3.1.3 Isotopic fractionation

Isotopic fractionation occurs when one isotope is enriched or depleted in relation to another through chemical and physical process (Peterson and Fry, 1987). In the case of food webs isotopic fractionation refers to the change in the ratio of heavy to light isotopes between a consumer and its prey (Vander Zanden and Rasmussen, 2001). The ratio of δ15N to δ14N exhibits stepwise enrichment with increasing trophic levels (2‰ - 5‰) and is thus useful in determining a consumers trophic position (Layman et al., 2012, Vander Zanden and Rasmussen, 2001). In contrast to nitrogen isotopes, ratios of carbon isotopes change very little with trophic level but exhibit substantial variation among different primary producers and thus are good indicators of the original source of dietary carbon (Layman et al., 2012). Food webs may differ between locations and subsequently carry distinct isotopic signatures as a product of the processes occurring within the ecosystems (Peterson and Fry, 1987, Layman et al., 2012).

The oceanic carbon cycle

Carbon enters the ocean as dissolved organic carbon (DOC), dissolved inorganic carbon (DIC) and particulate organic carbon (POC) via the addition of terrestrial vegetation, rocks and sediments and by molecular diffusion of CO2 across the air-sea interface (Sabine, 2001). Primary producers utilise DIC creating organic compounds, making nutrients available to consumers within the system (Segar, 1998). Inter- and intra-specific variation occurs in the isotopic values of primary producers as well as variation due to differential environmental conditions. Despite this, carbon isotopic signatures can be used to effectively discriminate between primary producers which employ different photosynthetic pathways as a result of differential fractionation and the utilization of a different species of inorganic carbon (Farquhar et al., 1989). Photosynthetic pathways include C3 metabolism,

C4 metabolism and the Crassulacean acid metabolism with most aquatic plants and algae utilising the

C3 carbon assimilation pathway (Farquhar et al., 1989). In generalist terms, aquatic macroalgae is relatively enriched in δ13C, phytoplankton is intermediary and terrestrial organic matter is relatively depleted (Fry and Sherr, 1989).

The nitrogen cycle

78% of the earth’s atmosphere consists of nitrogen however this nitrogen has a restricted availability for biological use and many biological process can be described as nitrogen limited (Segar, 1998). Nitrogen enters the ocean by precipitation, land runoff and diffusion of atmospheric nitrogen

(N2) at the ocean surface but requires fixation mainly by cyanobacteria to be available for primary + production (Alongi et al., 1992). NH4 is the preferential form of fixed nitrogen as it requires little energy in its assimilation, however NO3 is much more abundant and therefore most primary producers have the ability to utilize both nitrogen sources (Knapp, 2012). Biologically available nitrogen varies considerably in time and space with areas of upwelling and/or areas of high rainfall and land runoff having a higher supply than others (Peterson and Fry, 1987). δ15N is useful for estimating trophic level as a consumer exhibits an average enrichment of 3.4‰ in relation to its diet due to catabolic pathways that favour the excretion of the lighter isotope through urine (Post, 2002, Schoeninger and DeNiro, 1984).

3.1.4 The use of stable isotopes in biological studies

The use of stable isotopes in animal ecology has become increasingly popular over the past few decades in both terrestrial and marine applications (Gannes et al., 1997). Marine applications of stable isotopes may include analysis of localised foodwebs, characterising and differentiating among populations and determining population connectivity (Griffiths, 1991, Layman et al., 2012).

Historically, foodweb studies relied on observations of gut contents which provided short term information on the presence and importance of prey species in an animal’s diet. Stable isotope analyses now allows for an insight into long term dietary habits (Schmidt et al., 2006, Hobson et al., 1996). Variation in the metabolic activity of different tissues within a single animal dictates the length of the record due to turnover rate of the isotopic signatures stored within the tissues. For example the liver has a high turnover rate of days to weeks; white muscle has a turnover rate of weeks to months and metabolically inert structures such as bone may maintain an isotopic record for several years or indefinitely (Perga and Gerdeaux, 2005, Sotiropoulos et al., 2004, Rubenstein and Hobson, 2004).

Little fractionation of carbon isotopes occur between a consumer and its prey but carbon isotopic signatures differ between groups of primary producers and therefore it is possible to identify basal carbon sources and to trace the movement of carbon through the foodweb (Farquhar et al., 1989). By combining gut content analysis and stable isotope techniques it is possible to identify the cause of differential isotope signatures and circumstances where the two techniques do not agree may indicate seasonal or ontogenetic dietary shifts (de la Moriniere et al., 2003).

Spatial and temporal differentiation of biologically available nitrogen in the ocean and the availability of different carbon sources may result in isotopic signatures which are specific to local habitats allowing for the discrimination of local populations (Graham et al., 2010). The movement of an individual between habitats or population connectivity can be assessed by comparing the average isotopic signature of a population with an individual signature to determine whether the isotopic characteristics of that individual is significantly different and thus whether or not it is an immigrant (Graham et al., 2010). The isotopic signature carried by an individual is a record of diet and therefore the position an individual occupies in the local foodweb. Additionally, the combination of stable isotopes and biochemical markers have been employed to assess marine pollution and water quality, trace the origins and migrations of wildlife as well as having applications in microbial science (Hobson, 1999, Boschker and Middelburg, 2002, Deudero et al., 2011).

3.2 Objectives

The objective of this chapter was to use a combination of stomach content analysis and carbon and nitrogen stable isotope analyses to assess the dietary habits of Peltorhamphus novaezeelandiae from the Otago and Southland regions of New Zealand with the following specific aims:

1. To determine whether there are trophic level changes during the lifecycle of Peltorhamphus novaezeelandiae and if so whether this occurs within both Otago and Southland locations.

2. To use stomach-content analysis and stable isotope analysis as complementary techniques to describe the diet of Peltorhamphus novaezeelandiae.

3. To characterize the δ13C and δ15N signatures of Otago and Southland common sole from muscle tissue to determine if they can be used to differentiate potential subpopulations and subsequently describe population spatial structure.

3.3 Materials and Methods

3.3.1 Sample collection

Peltorhamphus novaezeelandiae individuals were collected by bottom trawl from commercial fishing vessels in the Otago and Southland coastal regions between January 2010 and June 2012 (Fig. 2.1) as described in chapter 2. The fish were stored whole on ice and then frozen at the Portobello Marine Laboratory (PML) awaiting further processing. Fish were defrosted overnight in running seawater at PML. Each fish was weighed (g), measured (mm) (chapter 4) and the otoliths removed (chapter 2).

3.3.2 Stomach content processing

The stomach contents of 120 P. novaezeelandiae individuals were analysed in this study. The entire gut was collected, weighed and fixed in 10% seawater buffered formalin for 48 hours. Following overnight degassing, samples were preserved in 70% isopropyl alcohol awaiting sorting and identifying of the contents.

Material from within the gut was removed and the gut itself discarded. Stomach contents were identified to the lowest classification possible and placed into ten taxonomic groupings. The blotted wet eight of each group was weighed to 0.001g. The taxonomic groupings consisted of Amphipoda, Isopoda, Decapoda, Euphausicea, Nemata, Annelida, Cephlapoda, Bivalvia & Gastropoda, Teleost and Bryazoa (Appendix II). These groupings were then further categorised by feeding strategy in order to best reflect patterns of basal carbon sources.

3.3.3 Stable isotope processing

A sample of muscle tissue was collected where possible from the dorsal area on the eye side of each specimen (Fig. 4.1), ensuring that it was not contaminated by any blood, skin, scales or bone. 50 muscle samples were selected for stable isotope analysis, these samples represented P. novaezeelandiae from the entire size range captured during this study for both the Otago and Southland regions (Table 3.1).

An initial wet sample of greater than 0.5 ml was preferred to ensure 0.8mg of residual material following dehydration at 45°C for 72 hours. Following dehydration the muscle tissue was homogenised to a fine powder with a mortar and pestle. The mortar and pestles were cleaned using Milli-Q water and dried in a drying oven at 45ºC between samples to avoid cross-contamination. 0.8mg (+/- 10%) of each sample was weighed and sealed into a tin canister for stable isotope analysis of δ13C and δ15N. The samples were analysed by Iso-trace Research New Zealand in the Department of Chemistry at the University of Otago using an Europa Hydra isotope ratio mass spectrometer (Europa Scientific, Crewe, UK) coupled to an Carlo Erba NC 2500 (Carlo Erba, Milan, Italy) elemental analyser (precision: 0.2‰ for δ13C and 0.3‰ for δ15N). Primary standards for analysis were calibrated to EDTA laboratory standard reference (Elemental Microanalysis, Cheshire, UK) and standardised against international standards (IAEACH-6 for carbon, IAEAN1 and IAEAN2 for nitrogen). The primary standard for δ15N was atmospheric air and Vienne PeeDee Belemnite was the standard for δ13C. The isotope ratio is expressed in standard delta notation (Peterson and Fry, 1987).

Table 3.1 Summary of Peltorhamphus novaezeelandiae collected for carbon and nitrogen stable isotope processing

Region Total length Number (mm) of samples Otago 50 – 100 2 101 – 200 4 201 – 300 6 301 – 400 7 401 - 500 5 500 + 1 Total 25 Southland 50 - 100 0 101 - 200 6 201 – 300 7 301 – 400 7 401 – 500 5 500 + 0 Total 25

3.4 Data analysis

3.4.1 Diet

Feeding intensity was inferred from a vacuity index (VI) where the number of empty stomachs was expressed as a proportion of total stomachs examined (Hyslop, 1980). Empty stomachs were not included in further dietary analyses.

An index of relative importance (IRI) was calculated for each taxonomic and feeding strategy grouping:

Where %W is the percent weight of the prey category and %F is the percent frequency of occurrence within the same category.

In order to determine whether significant differences exist between the taxonomic groupings or feeding strategies for the Otago and Southland regions, categories were treated as presence absence data and analysed in the program PERMANOVA+ version 1.0.2 as an add on to PRIMER v6. Comparisons were made between regions and the data was pre-treated via an initial square root transformation. The crossed ANOVA design was applied to a Bray Curtis resemblance matrix using a maximum of 9999 permutations with unrestricted permutation of the raw data.

Principle coordinate analysis (PCO) plots were constructed in order to visualise any multivariate patterns in diet. PCO allows visualisation of patterns in response to entire sets of variables by reducing the dimensionality of the data cloud and allowing the most prominent patterns to be observed (Anderson et al., 2008). A CAP analysis was also performed in order to determine diet specificity, with a leave one out allocation analysis allocating each P. novaezeelandiae individual to region.

3.4.2 Stable isotopes

Trophic level

Stable carbon (δ13C) and nitrogen (δ15N) values from 50 Peltorhamphus novaezeelandiae individuals were plotted relative to basal carbon and nitrogen values for predetermined benthic (macroalgae) and pelagic (suspended particulate organic matter (SPOM)) production as described by Jack and Wing (2011). The isotopic values of δ13C and δ15N for basal carbon sources were corrected for fractionation by increasing the values by five trophic levels. With each increasing trophic level isotopic signatures were increased by +0.4 for δ13C and +2.3 for δ15N as suggested for aquatic organisms by McCutchan et al. (2003). These values have been widely utilised in a range of previous studies pertaining to stable isotopes and the diet of marine animals (Rodgers and Wing, 2008, Jack and Wing, 2011, Wing et al., 2012). Five trophic levels were added in order to correct for the isotopic signatures of P. novaezeelandiae. the trophic level occupied by each individual was calculated by resolving the proportions of macroalgae and SPOM represented in each isotopic signature and using these proportions to calculate the corrected isotopic signature and number of fractionations each point sat above the basal source.

Analysis of δ13C and δ15N

Statistical analysis of carbon and nitrogen stable isotope signatures was accomplished using a permutational analysis of variance (PERMANOVA) with 9999 permutations for each term. Pre- treatment included conversion of data to a Euclidean distance similarity matrix. Using a two level design with the fixed factor being region and unrestricted permutation of raw data, a PERMANOVA was used to assess differences in δ13C and δ15N, trophic level, trophic level x length, trophic level x %SPOM. A further PERMANOVA was also performed for trophic level, δ13C and δ15N with fixed factors of region and sex in order to assess the influence of sex on the data. Each PERMANOVA was accompanied by a PERMDISP analysis in order to determine whether any significant results were being influenced by the dispersion of points within the data cloud.

IsoError mixing model

A mass balance model of δ13C and δ15N (Phillips and Gregg, 2001) was employed to determine the relative contributions of pelagic (SPOM) and benthic (macroalgae) basal carbon source pools. The average δ13C and δ15N values for all Peltorhamphus novaezeelandiae as well as for each region was determined and the standard error calculated. Mean trophic level was calculated as previously described and the average δ13C and δ15N values for Peltorhamphus novaezeelandiae were corrected by subtracting the trophic discrimination factor for each trophic level (McCutchan et al., 2003). The 2- source mixing model IsoError is freely available in a Microsoft Excel spreadsheet (Phillips and Gregg, 2001) and was used to determine the relative contributions of pelagic and basal carbon source pools for P.novaezeelandiae as a whole and also for each region.

3.5 Results

3.5.1 Peltorhamphus novaezeelandiae diet from stomach contents

For the combined Otago and Southland regions, 11.9% of Peltorhamphus novaezeelandiae had empty stomachs and were emitted from further diet analyses. In order to determine the importance of each taxonomic grouping the index of relative importance (IRI) was calculated and results are shown for each region in Figure 3.1. Ten taxonomic groupings were identified and of these four occurred regularly in terms of both frequency and mass. Prey species from the phylum Amphipoda were most common representing 72.5% of the total IRI values for Otago and 89.8% for Southland. The phylum Annelida represented 19.3% and 5.9% for Otago and Southland respectively, Decapoda 7.2% and 3% and Nemata 0.1% and 1.3%. The remaining taxonomic groupings represented 0.9% of the total IRI values for the Otago region. It is interesting to note that 9.5% of Otago individuals had the beaks of the pacific bobtail squid Sepioloidea pacifica present in their stomachs but the flesh of the squid had already been digested and therefore that particular prey item was not fully represented.

(a)

100 90 80

70 Other

60 Annelida 50 Nemata % IRI % 40 Decapoda 30 Amphipoda 20 10 0 Otago Southland

(b)

100 90

80 Secondary Consumer 70

60 Benthic Suspension 50 Feeder

% IRI % 40 Deposit Feeders 30 20 Pelagic Suspension Feeder 10 0 Otago Southland

Figure 3.1 Index of relative importance (IRI) values displayed as a percentage of the total defined by (a) the four major taxonomic groupings, with the remaining six categories of lesser importance grouped as ‘other’ and (b) feeding strategy. The phylum Amphipoda was the most exploited prey grouping with 72.5% IRI for the Otago region and 89.8% IRI for the Southland region (a). When grouped by feeding strategy deposit feeders and secondary consumers were most dominant with 95% and 4.8% respectively for the Otago region and 98.4% and 1.6% respectively for the Southland region.

3.5.2 PCO analysis

The principal coordinates analysis (PCO) plot with respect to taxonomic groupings (Fig. 3.2) shows that data from the Otago and Southland regions are overlapping, while the PCO with respect to feeding strategy (Fig. 3.3) shows the regions as two distinct groups in the data from the two dimensional viewpoint. Each vector is in relation to a specific variable (taxonomic grouping or feeding strategy) and begins at the centre of the unit circle and ends at the coordinates (x,y). This indicates the correlations between said variable and the two PCO axes. Vector length and direction show how each vector effects the spread of the data (Anderson et al., 2008). The length of the vector is indicative of the weight of the variable in the data cloud. In figure 3.2, PCO axis 1 explains 56.1% of the total variation and PCO axis 2 explains 38.6%. The taxonomic groups Decapoda, Annelida, Nemata and Amphipoda have the most influence over the spread of the data. The PCO axis for figure 3.3 explains 78.8% and 32.5% respectively with deposit feeders, benthic suspension feeders and secondary consumers influencing the spread of the data.

3.5.3 PERMANOVA

In order to test whether or not there were differences between regions for taxonomic groupings or feeding strategy, a permutational MANOVA was performed. Both analyses for taxon groupings and feeding strategies between regions were significant with P-values of 0.0309 (t = 1.896) and 0.0027 (t = 2.832) respectively (Table 3.2). A leave one out allocation of observations to groups resulted in 63.79% successful allocations for taxonomic groupings and 64.29% successful allocations for feeding strategy.

Figure 3.2 Principal co-ordinates analysis (PCO) plot comparing taxonomic groupings between regions. Data was presence absence, square root transformed and based on a Bray Curtis similarity matrix. The data does not indicate any differences at the regional level.

Figure 3.3 Principal co-ordinates analysis (PCO) plot comparing feeding strategies between regions. Data was presence absence, square root transformed and based on a Bray Curtis similarity matrix. The two regions are clearly identifiable with the Otago region having a wider spread than Southland.

3.5.4 Natural stable isotope signatures

Muscle samples from 50 Peltorhamphus novaezeelandiae individuals were analysed for stable carbon (δ13C) and nitrogen (δ15N) isotopes in order to determine long term dietary characteristics. Overall the mean δ13C value for was -17.06 with a standard deviation of 0.6 and mean δ15N value was 13.81 also with a standard deviation of 0.6. The mean δ13C and δ15N for the Otago region (n = 25) were -17.26 and 14.01 respectively, with standard deviations of 0.59 and 0.50. The Southland region (n = 25) had mean δ13C and δ15N values of -16.81 and 13.62 with respective standard deviations of 0.44 and 0.65. Figure 3.4 shows the mean values for each region, the standard error is indicated by the error bars.

14.8 Southland 14.6 Otago 14.4 14.2

δ 14.0 15

13.8 13.6 13.4 13.2 13.0 -18.0 -17.5 -17.0 -16.5 -16.0 δ13C

Figure 3.4 Mean stable carbon (δ13C) and nitrogen (δ15N) values from muscle samples taken from the dorsal region of individual Peltorhamphus novaezeelandiae from the Otago (n = 25) and Southland (n = 25) regions of New Zealand. The error bars represent standard error.

20.0 Otago 18.0 Southland 16.0 14.0

12.0 δ

10.0 15 N

8.0 SPOM 6.0 Macroalgae 4.0 2.0 0.0 -22.0 -21.0 -20.0 -19.0 -18.0 -17.0 -16.0 -15.0 -14.0 δ13C

Figure 3.5 δ13C and δ15N values for Peltorhamphus novaezeelandiae individuals from the Otago and Southland regions of New Zealand plotted with predetermined mean values for source pools suspended particulate organic matter (SPOM) and macroalgae. Basal values have been corrected to five trophic levels in accordance with stepwise fractionation values of 2.3 (δ15N) and 0.4 (δ13C) for each level and error bars represent one standard error.

Predetermined mean δ13C and δ15N values for basal carbon sources, macroalgae and suspended particulate organic matter (SPOM) were corrected to four trophic levels in accordance to stepwise fractionation values of 2.3 (δ15N ) and 0.4 (δ13C) and plotted along with δ13C and δ15N values for the Otago and Southland regions (Fig. 3.5). Both regions appear to be more dependent on the macroalgal source pool. PERMANOVA analysis revealed a significant difference in δ13C and δ15N signatures between the Otago and Southland regions with a p-value of 0.0002 (Psuedo-F = 7.3957). A PERMDISP did not show any statistical significance (p = 0.9181, t = 0.10627). The calculated trophic levels for each P. novaezeelandiae individual were also compared between regions and this showed statistical significance with a p-value of 0.0005 (Pseudo-F = 16.501), dispersion of points within the data cloud was not a factor in the significant result from the PERMANOVA as a PERMDISP analysis showed a p-value of 0.2672 (t = 1.1072). When length was included in PERMANOVA analysis with trophic level a non significant result was returned (p>0.05), as was the case with PERMANOVA analyses which included sex (Table 3.2).

Figure 3.6 shows trophic levels for individual P. novaezeelandiae plotted against proportion of diet derived from SPOM for each region. A PERMANOVA analysis revealed that there is a significant difference in trophic level and proportion SPOM between the Otago and Southland regions (p-value = 0.002, Pseudo-F = 11.559). Dissimilarities in the dispersion of points within the data cloud were not significant between regions (p > 0.05). In order to determine whether shifts in trophic level occurred with increasing length, the trophic level of individual P. novaezeelandiae were plotted against total fish length (mm) (Fig. 3.7). No relationship is evident in the figure and this was supported by the PERMANOVA which returned a non significant result (p-value = 0.9428).

4.5 4

3.5

3 2.5 2

1.5 Otago Trophic Level Trophic 1 Southland 0.5 0 0 20 40 60 80 % SPOM

4.5 4

3.5

3 2.5 2 Otago 1.5

Trophic Level Trophic Southland 1 0.5 0 0 100 200 300 400 500 600 Length (mm)

Figure 3.7 Trophic level versus length (mm) for individual Peltorhamphus novaezeelandiae originating from the Otago and Southland regions of New Zealand.

3.5.5 IsoError mixing model

Peltorhamphus novaezeelandiae appear to occupy the third average trophic level of the foodweb with an overall average trophic level (for both regions combined) of 3.2, and an average trophic level of 3.43 and 3.06 for Otago and Southland respectively. Isotopic signatures of P. novaezeelandiae appear to be more dependent on benthic primary production as can be seen in Figure 3.5. The isoerror mixing model was used to estimate the proportional contribution of pelagic (SPOM) and benthic (macroalgae) basal carbon source pools to P. novaezeelandiae diet. The mixing model confirmed that benthic production was most important in the sole foodweb, accounting for 90% (± 0.034) of the basal carbon source pool for the combined P. novaezeelandiae population leaving only 10% (± 0.034) to pelagic production. Similar results were obtained when the regional δ13C signatures were run in separate mixing models with 82% (± 0.894) benthic production for Otago and 99% (± 0.047) for Southland.

Table 3.3 Summary of permutational analysis of variance (PERMANOVA) and test for homogeneity of dispersion (PERMDISP) using the program PERMANOVA+ version 1.0.2 as an add on to PRIMER v6. Tests of statistical significance are indicated in bold type.

PERMANOVA PERMDISP Stomach Content Analysis P t

Taxonomic Groupings x Region 0.0309 1.896

Feeding Strategy x Region 0.0027 2.832

Stable Isotopes P Pseudo-F P t

δ13C, δ15N x Region 0.0002 7.3957 0.9181 0.10627

Trophic Level x Region 0.0005 16.501 0.2672 1.1072

Trophic Level, Length x Region 0.9428 5.00E-03 0.3062 1.0682

Trophic Level, %SPOM x Region 0.0002 11.559 0.4729 0.78526

δ13C, δ15N, Trophic Level x Region, Sex 0.2834 1.2706 0.8328 0.21469

δ13C, δ15N, Trophic Level x Sex 0.0722 2.6397

3.6 Discussion

The study of fish diets has historically been undertaken via the examination of stomach contents providing important insight into dietary preference, seasonal prey availability, and trophic position which are useful characteristics in the management of fisheries (Hyslop, 1980). It is however, recognised that this method has some significant limitations including the loss of resolution due to the differential rates of digestion between taxa, the limited snapshot in time of a particular individuals last meal and the high variability between individuals whom are influenced by differential external controls (Layman et al., 2012). The use of stable isotopes have become a popular method of dietary analysis, providing information on a much longer timescale from several days to several years depending on the turnover rates of the tissues analysed (Peterson and Fry, 1987). The ability to acquire time and space integrated information on the trophic relationships among organisms has resulted in critical advances in our understanding of food webs and our ability to manage fish stocks accordingly (Layman et al., 2012).

The recent advances in stable isotope methods and analyses have resulted in a marked increase in their use in dietary studies over the last decade (Layman et al., 2012). However, manual stomach content analysis has not been made redundant. The combined use of these techniques provides a more robust result as the identification of prey items found in stomach contents are able to be used to support stable isotope findings; as well as provide information on specific prey items to the species level. Thus, as is in keeping with the theme of an holistic approach, this study utilised both techniques of manual stomach content analysis and stable isotope analysis to determine the dietary characteristics and trophic interactions of the New Zealand sole, Peltorhamphus novaezeelandiae over a broad geographic range. Spatial differences were found to occur in δ13C and δ15N signatures between the neighbouring Otago and Southland regions along the south-eastern coast of the South Island. Spatial differences were also found in the analysis of stomach contents from individuals collected from within the two locations during 2010 and 2011. These results suggest that a degree of separation occurs between the two geographic locations creating the existence of localised stocks between which mixing may occur via larval transport and transient individuals but movement is limited to enough of a degree that differential dietary characteristics are maintained both spatially and temporally.

3.6.1 Spatial variation in isotopic signatures

Characterising the δ13C and δ15N signatures of Otago and Southland New Zealand sole from muscle tissue.

Isotopic signatures of Peltorhamphus novaezeelandiae exhibited significant spatial variation between regions. P. novaezeelandiae from the Southland region displayed isotopic signatures δ13C and δ15N that were more depleted in the heavy isotope (13C and 15N) than those from the Otago region (Fig. 3.4). Both regions had a similar level of individual variation in δ13C and δ15N signatures with the Southland region having slightly more variability in δ13C indicating the consumption of a wider selection of prey items. Alternatively, it may be indicative of another basal carbon source, as can be seen in figure 3.5 there are a number of individuals that fall outside of the mean and standard error for macroalgae. This could indicate that either the fractionation values used in this study are not synonymous with the enrichment which is occurring between the prey and the consumer or another basal carbon source pool is operating in the region. A possible carbon source that has not been accounted for in this study is seagrass, Zostera capricorni which has a mean δ13C value of -12.3 (standard deviation of 0.1) (Leduc et al., 2006). As stomach content analysis indicates that it is in fact Otago with the wider prey base rather than Southland, the contribution of an alternative carbon source pool is likely. The significant result given by the permutational MANOVA shows that spatial variation in δ13C and δ15N signatures occur between the Otago and Southland regions. This, coupled with the non significant test for dispersion (PERMDISP) indicates that the dissimilarities detected by the PERMANOVA are true differences between region and not as a consequence of differences in the dispersion of points within the data cloud.

There is no existing literature on δ13C and δ15N signatures of New Zealand flatfish species to compare with the results found during the current study. It is difficult to compare the isotopic signatures of P.novaezeelandiae with international dietary studies on flatfish as δ13C values are affected by latitude, where basal δ13C values exhibit depletion at higher latitudes (Cherel and Hobson, 2007). Darnaude (2005) characterised the δ13C and δ15N signatures from the white muscle of five flatfish species seawards of the Rhone River Delta in the Mediterranean Sea. This study showed ontogenetic dietary changes with all species (Arnoglossus laterna, Buglossidium luteum, Citharus linguatula, Solea lascaris and S. solea) and these isotopic results were supported by stomach content

59 analysis. These results contrast those obtained during the present study where no dietary shifts where evident during growth of P.novaezeelandiae. This may be due to differential life history characteristics between species with the notable difference being that the other mentioned species are known to use estuarine habitat during the juvenile stage of their lifecycle, while there is evidence that P.novaezeelandiae do not. Therefore the observed ontogenetic dietary shifts may occur in accordance with habitat shifts and a change in available prey species. δ13C values reported in Darnaude (2005) for all flatfish species ranged between -16.95‰ and -20.14‰, while δ15N values ranged from 10.10‰ to 11.63‰. Peltorhamphus novaezeelandiae values were within this range for δ13C with an average of - 17.06‰ ± 0.6 but δ15N values were higher with an average of 13.81‰ ± 0.6. Examples of other species which occur within the same geographic range include blue cod Parapercis colias δ13C - 17.9‰ ± 0.1 and δ15N 13.0‰ ± 0.1 (Rodgers and Wing, 2008), rock lobster Jasus edwardsii δ13C - 17.2‰ ± 0.1 and δ15N 12.9‰ ± 0.1 (Jack and Wing, 2011) and the little neck clam Austrovenus stutchburyi δ13C -18.8‰ ± 0.3 and δ15N 10.7 ± 0.3 (Leduc et al., 2006).

δ15N as an indicator of dietary disparity over spatial scales

An enriched δ15N signature for the Otago region in relation to Southland indicated that Otago individuals fed at a higher average trophic level. Trophic level calculations confirmed this with an average trophic level of 3.4 for Otago and 3.1 for Southland. Although the dissimilarity appears negligible between regions a PERMANOVA was able to confirm that this difference between regions is in fact of statistical significance (p-value = 0.0005). The presence of pacific bobtail squid Sepiolodidea pacifica (category Crustacea/cephlapoda) and triplefin (Tripterygiidae, Category Teleost) (appendix II) remains in the stomachs of Otago individuals may account for the occupation of a higher trophic position.

Rodgers and Wing (2008) studied the spatial structure of blue cod Parapercis colias in Doubtful Sound, New Zealand and were able to elucidate dietary differences between the inner fiord and outer fiord. Blue cod diets were found to consist largely of crustaceans and molluscs. Fish from the inner fiord exhibited greater input of recycled carbon due from chemoautotrophic bacteria. Blue cod were concluded to occupy the fourth average trophic level.

δ13C as an indicator of dietary disparity over spatial scales

Variability in δ13C between regions indicates differential prey selection and consequently the differential exploitation of carbon source pools. Comparisons of δ13C signatures between regions were significant indicating that different proportions of benthic and pelagic production were being utilised. An isoError mixing model was employed to quantify the relative carbon source pools and results showed that as indicated by an initial plot (Fig. 3.5), macroalgal basal carbon sources were most important in the diets of all P. novaezeelandiae individuals. Benthic production was most important in the diets of Southland individuals with 99% and was slightly less utilised by the Otago population at 82%. This is supported by the results of the stomach content analysis which show a large proportion of consumed prey were deposit feeders as opposed to suspension feeders which would lead to a higher proportion of pelagic production incorporated into the diet.

Mass balance models such as the mixing model used here are known to be highly sensitive to the amount of trophic shift resulting from the assumed level of fractionation which occurs between prey and consumer. Fractionation of δ13C is relatively stable changing less than 1% as it travels through the food chain (DeNiro and Epstein, 1978) however, enrichment of δ15N is highly variable. Therefore, the level of assumed fractionation (2.3‰) as given by McCutchan et al. (2003) for aquatic organisms is not necessarily the true level of fractionation and subsequently affects the robustness of this method. Davis (2011) carried out a sensitivity analysis by performing the mixing model multiple times with different levels of fractionation ranging from 1.7‰ to 3.1‰. It was discovered that for every 2‰ change in assumed fractionation there was a 3% change in the estimated proportion of SPOM which was enough to reverse the estimated dominant source pool. Thus, this method is useful for estimating the relative proportions of carbon source pools but should be used in conjunction with other methods.

3.6.2 Utilising complementary techniques

Analysis of the stomach contents revealed that for both the Otago and Southland regions the dominant prey species of Peltorhamphus novaezeelandiae were members of the phylum Amphipoda. Amphipods were a more dominant feature in the stomachs of Southland individuals than for Otago, however the next most dominant phyla, Annelida, was more represented in the stomachs of Otago individuals. When looking at the feeding strategies of the species present in the stomach contents, over 95% were deposit feeders for both regions. A permutational MANOVA analysis confirmed that both the taxonomic groupings and feeding strategies were significantly distinct between region. These results are complemented by the stable isotope results which also revealed a significant difference in δ13C and δ15N between region. The high dependence on benthic production as the basal carbon source pool for both Otago and Southland regions can be directly linked to the high percentage of deposit feeders consumed by individuals from all areas. The leave one out allocation of observations to groups resulted in 63% success for taxonomic groupings and 64% success for feeding strategy, this suggests that while there is sufficient partitioning between fish stocks from each region a degree of mixing does occur.

3.6.3 Ontogenetic trophic shift

Ontogenetic trophic shifts occur in many fish species due to changes in body size, habitat and nutritional requirements (Davis et al., 2012). Flatfish species are generally believed to utilise shallow coastal inlets and estuaries during the juvenile phase of their lifecycle before making the migration out into coastal waters to spawning and feeding grounds (Gibson, 2008). Existing literature on Peltorhamphus novaezeelandiae however, suggests that this is not the case with this species. During sampling within the Otago Harbour and surrounding inlets it has been noted that juvenile P.novaezeelandiae are present in shallow coastal waters but not in the harbour or inlets. It is suggested that this species along with lemon sole (Pelotretis flavilatus), they bury into the sand in these shallow coastal waters in order to avoid being swept into the estuarine habitats during the incoming tide and periods of stormy weather (Roper and Jillett, 1981, James, 1969).

In order to test whether or not dietary shifts occur during the P.novaezeelandiae lifecycle which may indicate a significant ontogenetic event such as migration from estuarine to coastal waters,

62 the estimated trophic level for each individual was plotted against total length (mm) (Fig. 3.7). No relationship between trophic level and length was evident and this was supported by the PERMANOVA which returned a non-significant result (p-value = 0.9428).

3.7 Conclusions

This chapter aimed to investigate the dietary habits and trophic relationships of Peltorhamphus novaezeelandiae from the Otago and Southland regions. Complementary stable isotope and stomach content analysis techniques were used in order to obtain the maximum resolution possible. The following conclusions were reached:

 Both spatial and temporal dissimilarities in δ13C and δ15N signatures were present between the Otago and Southland regions, with Otago being slightly enriched in both δ13C and δ15N compared to that of Southland.

 Mean estimated trophic level was also significantly different between regions. As indicated by the higher mean δ15N, Otago individuals fed at a slightly higher trophic level than their Southland counterparts. Southland exhibited more variation in δ13C indicating a wider prey base.

 The combined methods of stomach content analysis and stable isotope analysis proved to be complementary to one another, and achieved a higher resolution of food web interactions and trophic positioning than if using just one method.

 The basal carbon source pool for both regions was predominantly benthic production. Otago was more dependent on pelagic production in comparison to Southland which was reflected by the higher mean trophic level.

 δ13C and δ15N signatures and trophic position did not differ between the sexes or between different size classes.

 The present results suggest that a degree of separation occurs between the two geographic locations creating the existence of localised stocks, between which mixing may occur via larval transport and transient individuals but movement is limited to enough of a degree that differential dietary characteristics are maintained both spatially and temporally.

Chapter 4

MORPHOLOGICAL CHARACTERISTICS

4.1 Introduction

4.1.1 Morphology in relation to population connectivity

Morphometric characters are those that describe aspects of body shape. Over a large geographic area, morphometric variation within a single species may be driven by intrinsic differences among stocks based on genetic distinctness or by environmental influences on growth and resource allocation within an individual (Swain and Foote, 1999). Localised biotic and abiotic factors such as salinity, turbidity, temperature, predation and fishing pressure, can influence differences in morphology corresponding to specific habitat and resource specialization (Webster et al., 2011). Specialization occurs when the selection pressures operating in different habitats select for different traits (Webster et al., 2011). Local features such as ocean currents and topography may limit gene flow to some extent by minimizing the mixing of eggs and larvae between neighbouring populations (Begg et al., 1999b, Marques et al., 2006). Populations therefore possess the capacity to evolve as an independent biological unit, however this is dependent on population dispersal or the rate of exchange of individuals between localised populations (Turan, 2004). Even a small amount of continuous connectivity between populations may be enough to allow genetic homogeneity to obscure the existence of multiple fish stocks (Metcalfe, 2006).

4.1.2 Identification of fish stocks using morphometric characters

Fish stocks can be defined as arbitrary groups of fish large enough to be essentially self- reproducing, with members of each group having similar life history characteristics (Hilborn and Walters, 1992). The terms ‘fish stock’ and ‘subpopulations’ are often used interchangeably however, there are many conflicting definitions for them in the literature (Begg and Waldman, 1999, Coyle,

1998). Regardless of precise definitions and biological underpinnings, from the perspective of fisheries management both terms essentially refer to units of individuals within a species range that can be characterised by non-heritable, environmentally induced similarities which over time results in genetic differentiation. These population units may exhibit varying degrees of temporal or spatial integrity (Begg and Waldman, 1999, Coyle, 1998). The concept of fish stocks varies with reference to timescale. Studies that focus on genetic differentiation refer to an evolutionary timescale during which less than one individual per generation may move between stocks in order to maintain genetic discreetness. On the other hand, studies that are interested in adaptive significance such as behaviour and life history refer to a much shorter timescale (Coyle, 1998). Investigations involving the analysis of morphometric characters such as body dimensions and body features (for example fin and head lengths) have often been used to differentiate among fish stocks (Marques et al., 2006, Swain and Foote, 1999, Turan, 2004). Morphometric characters are ideal for studies regarding adaptive significance as their expression is under simultaneous control of both genetic and environmental factors (Begg and Waldman, 1999). Morphometric characters often vary along a geographic gradient in wide-ranging coastal fish (Marques et al., 2006) such as Peltorhamphus novaezeelandiae, making morphology a useful tool in stock delineation.

4.1.3 The limitations of morphometrics

Morphological differences between fish stocks do not necessarily indicate discrete genetic stocks. Morphology and genetics are often akin to one another but in some instances morphological differentiation is purely environmentally induced (Swain and Foote, 1999). This may be referred to as phenotypic plasticity which is defined as ‘the ability of a single genotype to produce more than one alternative form of morphology, physiological state and/or behaviour in response to environmental conditions’ (West-Eberhard, 1989). Furthermore, morphometric characters generally express ontogenetic changes associated with growth and therefore are likely to be influenced by environmental variables for the entire life of the fish (Swain and Foote, 1999).

Utilisation of multiple techniques such as life history parameters, phenotypic characters and genetics may be applied in order to obtain a more accurate result (Begg et al., 1999b, Begg and Waldman, 1999, Coyle, 1998). Enquiry into a single characteristic will not necessarily reveal

66 dissimilarities between stocks even if a difference exists but by integrating different stock identification methods discrepancies arising from one method may be resolved by another (Begg and Waldman, 1999). Begg et al (1999) investigated the use of life history parameters as indicators of stock structure and concluded that while temporal differences among stocks were present, life history parameters were useful indicators of stock structure, particularly when combined in an holistic approach.

4.2 Objectives

The objective of the present chapter is to analyse morphological variability among stocks of Peltorhamphus novaezeelandiae originating from the Otago and Southland regions of New Zealand. This analysis is potentially useful to identify separation of discrete stocks. Furthermore, this information will be used as part of an holistic approach to stock identification and an estimation of population connectivity along with data collected on growth (chapter 2) and diet (chapter 3). Specifically the objectives for this chapter are:

1. To determine whether measurements of morphological characteristics differ between fish originating from Otago and Southland regions.

2. To investigate whether morphology can be used as a tool to differentiate between discrete subpopulations of Peltorhamphus novaezeelandiae.

4.3 Materials and Methods

4.3.1 Sample collection

Peltorhamphus novaezeelandiae were sampled by bottom trawl in the Otago and Southland regions (Fig. 2.1) as described in chapter 2 (section 2.3.1) and frozen at -20ºC awaiting further processing. 150 fish were captured in total, 54 from Otago and 96 from Southland. Measurements, to the nearest 0.1mm, of morphological features were taken from each thawed P.novaezeelandiae specimen prior to dissection (also see chapters 2 and 3, sections 2.3.1 and 3.3.1) using Vernier calipers. Total length was measured to the nearest mm using a measuring board. Ten morphological characteristics were measured which comprised of total length (TL), standard length (SL), blind side pectoral fin (PBS), eye side pectoral fin (PES), head length (H), snout length (S), caudal peduncle (CP), body width (BW), right side eye diameter (ED) and inter-orbital distance (IO) (Figs. 4.1 & 4.2).

PBS

Figure 4.1 Blind side of Peltorhamphus novaezeelandiae indicating the morphometric character pectoral fin length blind side (PBS). Peltorhamphus novaezeelandiae drawing from the Guide to the Sea Fishes of New Zealand by Tony Ayling and Geoffrey Cox, published in 1982.

Figure 4.2 Morphometric measurements taken from the eye side of 150 Peltorhamphus novaezeelandiae: body depth, caudal peduncle (CP), standard length, total length, pectoral fin length eye side, head length, snout length, right eye diameter (ED) and inter-orbital distance (IOD). The area which muscle samples were taken from is indicated by the broken line. Peltorhamphus novaezeelandiae drawing from the Guide to the Sea Fishes of New Zealand by Tony Ayling and Geoffrey Cox, published in 1982. 69

4.4 Data Analysis

4.4.1 Standardising morphometric measurements

In order to remove possible bias due to the effect of length from the analysis, each character (Figs. 4.1 & 4.2) was first standardised in Microsoft Excel (Lawton et al., 2010).

each character was standardised by:

Ŷ = 10K

where the exponent K is the log10 of the adjusted measurement e derived from:

e = log10Y - β(log10 X-log10 XSTL)

Where Y is the original measurement, β is the common regression slope of log10 Y against log10

X, X is the standard length of the individual, XSTL is the overall mean standard length. This transformation best reflects shape variation among groups independently of size factors (Reist, 1985).

4.4.2 Morphological analysis

Analysis of morphological data following standardisation of each character for length was performed using PRIMER version 6.1.1.2 and PERMANOVA + version 1.0.2. Morphological data was normalised and based on a Euclidean dissimilarity matrix.

In order to examine patterns across the entire data cloud, an initial unconstrained ordination was carried out in the form of a principal coordinates analysis (PCO). PCO allows visualisation of patterns in response to entire sets of variables by reducing the dimensionality of the data cloud and allowing the most prominent patterns to be observed (Anderson et al., 2008). Furthermore, A PCO

70 also allows any differences in variability or spread within groups to be examined (Anderson and Willis, 2003). Two PCO’s were done, in the first ‘region’ was selected as a factor in between Otago and Southland. In the second ‘sex’ was selected as a factor, this was to determine whether any apparent dissimilarities between the Otago and Southland regions were being driven by differences in sex.

To test the hypothesis that there is a morphological difference between P.novaezeelandiae individuals from the neighbouring Otago and Southland regions, a univariate PERMANOVA design was applied to the data set with ‘region’ as a factor. PERMANOVA refers to permutational ANOVA and MANOVA, “testing the simultaneous response of one or more variables to one or more factors in an analysis of variance experimental design, on the basis of any resemblance measure, using permutation methods” (Anderson et al., 2008). In order to visualise existing patterns P-values are obtained via the permutation method, ensuring robustness and validity (Anderson, 2006). Unrestricted permutation of the raw data was used for this analysis with 9999 permutations.

Complementary to PERMANOVA, morphological data was tested for homogeneity of dispersion using a PERMdisp analysis. PERMANOVA tests for location differences and is sensitive to differences in multivariate dispersion among groups, dictating that multivariate dispersion of the residuals should be homogeneous (Anderson et al., 2008). PERMdisp is a permutational analysis of multivariate dispersions which a) calculates the distance of observations from their centroids and b) compares the average distances among groups using ANOVA (Anderson et al., 2008). PERMdisp allows delineation of the output gained from PERMANOVA by determining whether any differences observed are truly due to differences in location in multivariate space or are due to differences in group dispersion (Anderson et al., 2008). PERMdisp may also be used to indicate changes in the variability of assemblages. It has been suggested that changes to the dispersion of ecological data may indicate stress in marine communities (Warwick and Clarke, 1993).

To determine which morphological characters are the most useful for discriminating among the Otago and Southland regions, a canonical analysis of principle coordinates (CAP) was applied to the data. CAP is a constrained ordination analysis and unlike PCO which is unconstrained, utilizes a priori hypothesis (Anderson et al., 2008, Anderson and Willis, 2003). The purpose of CAP is to draw axes through a multivariate data cloud that maximises the differences between groups (Anderson et al., 2008) and to indicate how distinct the groups are in multivariate space (Anderson and Willis, 2003). Cap is a useful tool in ecology as it permits us to view multivariate data in two dimensional space as opposed to PCO which is one dimensional, this may allow observations which were obscured at the one dimensional angle (Anderson et al., 2008). CAP requires the user to specify the number of PCO axes (m) to be used in the analysis. This was obtained by observing the percentage of correct allocations with increases in the number of axes. Six PCO axes were selected as this yielded the highest allocation success. Any number of axes below this may result in loss of ecologically important data and any above this would increase within group variability more than among group variability and therefore would not be useful for discriminating between groups (Anderson and Willis, 2003).

4.5 Results

4.5.1 Principle coordinate analysis (PCO)

The principal coordinates analysis (PCO) with respect to region (Fig. 4.3) shows two distinct groups which are slightly overlapping, while the PCO with respect to sex (Fig. 4.4) shows no pattern in the data from the two dimensional viewpoint. The first two PCO axes explain 33.5% and 16.8% of the total variation respectively. Each vector is in relation to a specific variable (morphological character) and begins at the centre of the unit circle and ends at the coordinates (x,y). This indicates the correlations between said variable and the two PCO axes. Vector length and direction show how each vector effects the spread of the data (Anderson et al., 2008). The length of the vector is indicative of the weight of the variable in the data cloud. Pectoral length eye side (PES) and inter-orbital distance (IOD) have a lot of weight in the data set and are causing the data the spread in near opposite directions. Body width (BW), head length (HL) and snout length (S) are also important variables. On the other hand eye diameter (ED), pectoral length blind side (PBS) and caudal peduncle (CP) have less of an effect on the distribution of the data in Euclidian space.

4.5.2 PERMANOVA

PERMANOVA using a 2-factor design (region, sex) revealed that differences in morphology according to region were highly significant (P < 0.0001) (Table 4.1). The factor sex and the interaction between factors region and sex, failed to obtain a significant result with P = 0.2202 and P = 0.1763 respectively. The pseudo-F statistic was highest for region at 26.971 while sex had 1.3491 and region x sex had 1.4662. The PERMDISP test for heterogeneity was not significant for either region or sex (region: F = 3.679, P > 0.05; sex: F = 0.287, P > 0.6).

Table 4.1 Results of PERMANOVA using a 2-factor design (region, sex) to test differences in morphology. Differences according to region obtained a significant P-value (P<0.0001). Source DF SS MS Pseudo-F P(perm) Unique perms Region 1 178.2 178.2 26.971 0.0001* 9932 Sex 1 8.9136 8.9136 1.3491 0.2202 9958 Region x Sex 1 9.6866 9.6866 1.4662 0.1763 9952 Residuals 146 964.6 6.6068 Total 149 1192

Figure 4.3 PCO graph with respect to region, the two regions can be easily identified with some overlap. The vectors represent the morphometric measurements pectoral eye side (PES), eye diameter (ED), pectoral blind side (PBS), caudal peduncle (CP), body width (BW), head length (HL), snout length (SL) and inter-orbital distance (IOD).

Figure 4.4 PCO graph with respect to sex, there are no obvious patterns in the data. The vectors represent the morphometric measurements pectoral eye side (PES), eye diameter (ED), pectoral blind side (PBS), caudal peduncle (CP), body width (BW), head length (HL), snout length (SL) and inter-orbital distance (IOD). 74

Allocation Success % Allocation Success % m Region Sex 1 86.0 58.7 2 86.0 61.3 3 84.0 61.3 4 83.3 60.7 5 82.7 59.3 6 88.7 62.7 7 88.7 62.0 8 91.3 63.3

4.5.3 Canonical analysis of principal components (CAP)

A total of eight PCO axes (m) were selected for both region and sex as this yielded the highest allocation success (Table 4.2). Inclusion of all 8 axes allowed for 100% of the original variation (prop.G = 1) to be explained. Leave one out analyses were very successful for region (Table 4.3a) where 91.3% of individuals (8.7% misclassification error) were able to be correctly identified to their region of origin based on the chosen morphometric characters. Leave one out analyses were less successful for sex (Table 4.3b) with only 63.3% correct allocations (36.7% misclassification error) .

Figuess 4.5 and 4.6 show the relationship between the Southland and Otago regions and male and females respectively. The distinctness of one group from another is shown by the amount of horizontal overlap. Figure 4.5 shows that the regions Southland and Otago are overlapping slightly yet are distinct from one another as indicated by the values in table 4.3. Conversely, figure 4.6 shows almost complete overlap along the CAP1 axes.

Table 4.3 Leave one out allocation of observations according to a) region and b) sex from the canonical analysis of principal coordinates (CAP) analysis in PRIMER. Eight morphometric characters were included in the analysis (Table 4.1), where sample size n = 150 and PCO axes m = 8. A total of 137 out of 150 P.novaezeelandiae individuals (91.3%) were correctly identified to their region of origin based on the eight morphometric characters with 13 misclassifications (8.7%). Only 95 out of 150 fish (63.3%) were correctly classified according to sex with 55 misclassifications (36.7%)

Southland Otago Total Allocation Success (%) Southland 87 9 96 90.6 Otago 4 50 54 92.6

Accumulative Total 137/150 91.3 % Misclassification Error 8.7 %

Male Female Total Allocation Success (%) Male 56 24 80 70.0 Female 31 39 70 55.7

Accumulative Total 95/150 63.3% Misclassification Error 36.7 %

Figure 4.5 Constrained ordination of principle components (CAP) showing the relationship between the Otago and Southland regions along a canonical axes. The figure shows two distinct groups which are slightly overlapping.

Figure 4.6 Constrained ordination of principle components (CAP) showing the relationship between male and female Peltorhamphus novaezeelandiae along a canonical axes. 77

4.6 Discussion

Morphological differentiation between arbitrary groups of fish can provide useful information about population structure and has been used in many past studies to differentiate between fish stocks (Begg and Waldman, 1999, Marques et al., 2006). Significant differences in the morphological characteristics of Peltorhamphus novaezeelandiae were obtained during this investigation between the neighbouring Otago and Southland regions of southern New Zealand providing evidence for a degree of separation between these groups. 91.3% of the P.novaezeelandiae sampled were correctly identified according to their region of origin during a CAP analysis in the statistical program PRIMER (Table 4.3).

The ordination plot arising from the principal coordinates analysis (PCO) suggests that morphological differences exist at the regional level but morphology is homogenous between the sexes (Figs. 4.3 & 4.4). This is supported by the PERMANOVA and PERMDISP analysis. The highly significant result of PERMANOVA (P < 0.0001) in accordance to region, coupled with the non significant PERMDISP analysis (P > 0.05) infers that there are morphological differences between the Otago and Southland regions and the differentiation seen is caused by location differences only and not by dispersion effects (Anderson et al., 2008). There was no morphological differentiation observed between the sexes, both PERMANOVA and PERMDISP returned a non significant result (P > 0.2 and P > 0.6 respectively) indicating that there were no location or dispersion effects for sex. Morphological differences are often seen between sexes of the same species, Cadrin and Silva (2005) investigated morphometric variation of yellowtail flounder (Limanda ferruginea) at 8 geographic locations and in doing so found the species exhibited significant sexual dimorphism. By ruling out the effect of sexual dimorphism I can confidently conclude that the observed dissimilarities are a product of region.

The vectors inter-orbital distance (IOD), pectoral length eye side (PES), body width (BW), head length (HL) and snout length (S) (Fig. 4.1), are the most dominant morphological characteristics driving the differentiation between the two regions. While the aforementioned vectors are slightly more dominant than the others, all of the vectors measured had a strong influence on the distribution of the data in multi dimensional space. Morphological differentiation can often be related to adaptation to localised environmental conditions (Jørgensen et al., 2008). Kinsey, Orsoy et al. (1994) used both

78 morphometric and genetic techniques to investigate the population structure of the Spanish sardine (Sardinella aurita) in coastal waters of Florida. They were unable to detect dissimilarities at the genetic level but identified several morphological types demonstrating how phenotypic plasticity allows individuals to adapt to localised environmental conditions.

One hypothesis for the differences observed here may be contrasting foraging behaviour between regions due to differences in prey availability, predator density or environmental conditions such as temperature / light intensity and substrate type. Light intensity is acknowledged to be a major environmental factor which dictates feeding behaviour, at low light levels flatfish will often change to alternative foraging modes using sensory techniques rather than sight (Gibson 1997). Inter-orbital distance, head length and snout are likely to be related to prey and foraging behaviour where a greater or narrower inter-orbital distance alters the field of view. Head length and snout length are closely related and a larger head length and snout length may indicate a larger mouth gape and the ability to consume larger prey.

During this investigation eight adult Peltorhamphus novaezeelandiae were held in an outdoor circular tank and it was observed that during movement across the bottom of the tank, particularly at feeding time they would often have their eye side pectoral fin raised. This induces the question of functionality, what is the reason for this behaviour? Gibson (1997) states that in flatfish the eye side pectoral fin is employed as a rudder enabling fish to change direction in the horizontal plane, this would be particularly important for visual predators. Therefore it is fair to suggest that morphological differentiation of these vectors may be a product of environmental conditions where one group of P.novaezeelandiae relies more heavily on sensory foraging techniques while the other utilises sight.

4.6.1 Population structure

Species such as Peltorhamphus novaezeelandiae which encompass a broad geographic range often exhibit a patchy rather than even distribution (Metcalfe, 2006). The morphometric dissimilarities detected in this study between P.novaezeelandiae from the Otago and Southland regions provide evidence for the existence of two semi-discrete fish stocks which experience a low level of transfer of individuals. Morphometric characters have been used routinely in the past to discern population structure. James’ (1969) master of science thesis employed meristic and morphological techniques to

79 compare Peltorhamphus novaezeelandiae individuals from Blueskin Bay north of Otago Peninsula with individuals sourced from Auckland after observing morphometric variation in the fish he was studying. Results from the current study revealed that while there were no significant dissimilarities between larger sized P.novaezeelandiae from Otago and Auckland, there were two distinct smaller sized groups present in Otago of which James later went on to describe as separate species (James, 1972).

Ellis, Howell and Hayes (1997), compared morphological differences between hatchery reared and wild caught turbot Scophthalmus maximus, both of which originated from Irish Sea stock. Results from this study demonstrated strong phenotypic plasticity where morphological differences arose not from genetic differentiation but from various environmental conditions. Haddon and Willis (1995) found significant morphological differences between orange roughy Hoplostethus atlanticus from the Puysegur Bank and Lord Howe Rise where previous genetic studies had failed to detect dissimilarities. The concept of biological stocks implies that the integrity of the group is able to be maintained through space and time and that the stock also possesses other individual characteristics such as growth rates, recruitment and prey composition. The stock is able to persist over time by recruitment either from the stock itself or from other nearby stocks, indicating discrete localised populations which are important at the level of fisheries management (Haddon and Willis, 1995). Morphometric results of the current study indicate that the use of morphometric characters to discern stocks is ideal in short term studies and is a useful tool for fisheries management.

4.7 Conclusions

The aim of this chapter was to analyse various morphological characteristics of Peltorhamphus novaezeelandiae from the neighbouring Otago and Southland regions of southern New Zealand in order to identify discrete fish stocks and furthermore as part of an holistic approach to estimate population connectivity. The following conclusions were reached:

 There is a significant difference (P < 0.0001) in the morphological characters of Peltorhamphus novaezeelandiae between the Otago and Southland regions indicating the presence of localised fish stocks.

 The morphological differences observed between regions are not a product of sexual dimorphism.

 Morphological dissimilarities are a result of adaptation to localised environmental conditions.

 The use of morphometric characters to discern Peltorhamphus novaezeelandiae stocks is ideal for short term studies and is a useful tool for fisheries management.

Chapter 5

GENERAL DISCUSSION

The main aim of this thesis was to analyse different aspects of the life history of the New Zealand sole Peltorhamphus novaezeelandiae, in order to determine population connectivity between the neighbouring South Island regions, Otago and Southland. The Otago and Southland regions are influenced by a range of environmental conditions due to local geography, most notably Southland’s Foveaux Strait which is notoriously treacherous due to its depth, latitude and tidal flow and Otago’s nutrient rich water sourced from upwelling in the nearby deep sea canyons; as well as the large eddy created in the lee of the Otago Peninsula headland. Previous studies on P.novaezeelandiae are limited, with the most prominent works completed by Gavin James with his Master of Science thesis which briefly described the biology of the species (James, 1969). James then went on to later describe two new species in the Peltorhamphus genus as a result of anomalies observed during his Masters research (James, 1972). More recently New Zealand’s National Institute of Water and Atmospheric Research (NIWA) completed a study on the maximum age of New Zealand sole on behalf of the governments Ministry of Fisheries (now the Ministry of Primary Industries (MPI)) (Stevens et al., 2004). The results of the present study build on what little information that we have had to work with previously, providing a better insight into the life history characteristics of the species and the population dynamics, ultimately allowing more informed fisheries management decisions.

5.1 Implications of spatial scale on population studies

Species persist over broad spatial scales, yet each individual is shaped and influenced by their immediate environment which may differ to that of another individual of the same species living elsewhere (Tilman and Kareiva, 1997). Spatial scale has become recognised as an important part of investigative design in population ecology. The spatial scale at which an individual interacts with, and influences its environment and other organisms is dependent on the biology of the individual. A sessile organism interacts with its environment at much smaller spatial scales than a mobile organism, and the

82 range at which an organism may travel determines the spatial scale required for the design of a study and the patterns which can be observed (Tilman and Kareiva, 1997, Wiens, 1989). As a result of small scale environmental interactions, localised variation may occur in traits which include but are not limited to growth, diet, mortality, morphology and fecundity (Begg et al., 1999b)

Processes such a meta-population dynamics which occur at large spatial scales have been attributed to the stability of populations within a species range. The population as a whole is allowed to persist in less favourable habitat by dispersal and colonisation of individuals from more favourable conditions. Physical and biological barriers often exist between these subpopulations, determining the level of dispersal or ‘connectivity’ which may occur (Taylor et al., 1993). Higher levels of connectivity between fragmented habitat patches results in homogeneity of demographic traits (Begg et al., 1999b). Connectivity is a multifaceted process which affects population structure through physical and biological translocation of nutrients, ontogenetic, life history, spawning and feeding migrations, food-web dynamics and predator–prey interactions, among others (Sheaves, 2009).

Flatfish as a group are known to utilise a variety of habitats during their life histories, including the use of estuaries as nursery areas for juveniles and designated spawning and feeding grounds (Cyrus and Martin, 1991, Secor and Rooker, 2005). Tagging studies have revealed the movement of individuals across relatively large geographic distances (Francis, 1988, Alverson and Chatwin, 1957, Gibson, 1997). It is unlikely that Peltorhamphus novaezeelandiae uses estuarine waters as juvenile nursery grounds as previous investigations have noted the absence of both adults and juveniles during collections, yet they were present in shallow coastal waters as was consistent with the observations made during this study (James, 1969). Nothing is known of other habitats which are utilised by P.novaezeelandiae but it is acceptable to assume that long distance migrations over a scale of 100’s of kilometres would be possible when compared to the known behaviours of similar species.

5.2 Summary of findings

5.2.1 Growth

A total of 146 Peltorhamphus novaezeelandiae were collected from the Otago and Southland regions of New Zealand for analysis of growth (Table 2.2). 47 of these were from the Otago region

83 and 99 from the Southland region. Females were more prolific in the Otago region with a sex ratio of 1.8 females to every male, the opposite was true for the Southland region with a sex ratio of 1.75 males to every female. Previous studies have also reported sex ratio’s consistent with that of Southland (James, 1969, Graham, 1956) and the high female to male sex ratio obtained during this study for Otago is believed to be an artefact of the small sample size for the region. To confound the matter further, a bias existed toward larger sized individuals in the Otago sample compared to that of Southland. The larger fish were observed to be typically female however comparison of male and female growth curves showed no significant differentiation. A larger sample size and a more representative size range for both regions is required to reveal whether this discrepancy is genuine. Sampling which does not accurately represent the population as a whole is a common problem in population ecology and is often difficult to resolve (Pawson and Jennings, 1996).

The present investigation builds on early attempts to estimate age and growth by James (1969) and Finlay (in Thomson, 1928).This is the first study to employ the Von Bertalanffy growth function to model the growth of this species and to calculate the growth parameters L∞ (maximum asymptotic length) and k (growth rate). No spatial variation in growth was detected between the Otago and Southland regions suggesting that the external factors which regulate growth are constant throughout the Otago and Southland coastal zones. Variation in growth rates was also absent between the sexes. The existing literature shows that flatfish as a group often exhibit sexual differences in growth however it varies from species to species (Francis, 1988, Reichert, 1998, Gibson, 2008).

The current study gives growth rates of k = 0.57 for Otago and k = 0.73 for Southland and concludes that Peltorhamphus novaezeelandiae are one of the fastest growing commercial flatfish species with a short life span, second only to lemon sole Pelotretis flavilatus, which has a growth rate of k = 1.5 and lives for a maximum of 5+ years. Values of k (growth rate) show that P.novaezeelandiae grow quickly to reach a maximum asymptotic length of approximately 395mm and living to a maximum age of around 6+ years. The maximum age obtained in this study is in accordance with studies by James (1969) and New Zealand’s Ministry of Fisheries (2009). The available biological information suggests that P.novaezeelandiae employ a strategy of fast growth particularly in the first 2 – 3 years to attain maximum asymptotic length, high abundance, high fecundity, reproduce frequently and have relatively short generation times. This is the ideal situation for a sustainable fishery and can be explained in terms of r and K (Reznick et al., 2002).

r- selection describes a population which exhibits a variable population size over time, density independent mortality rates, little inter- or intraspecific competition, rapid development, early reproduction, a relatively small body size and a short lifespan. Populations with a life history which fits this description are productive, they have the ability to not only maintain population size but to exceed it when the conditions are favourable. The opposite situation is true for K- selected populations which are less equipped to recover from catastrophic events (Pianka, 1970). Fisheries management favours species which display r- selected life history characteristics. The level of sustainable harvest is much higher than that of the slower growing and reproducing K- selected species and populations have a greater ability to absorb periods of intense fishing effort (Charles, 2008). Most flatfish fall under the banner of r- selection with the noteable exception of New Zealand’s brill, Colistium guntheri and turbot, Colistium nudipinnis (Stevens et al., 2005) with an international example being that of halibut, Hippoglossus stenolepis (Casey et al., 1995).

5.2.2 Stable isotopes and diet

Complementary methods of stomach content and stable isotope analysis were employed to examine the dietary characteristics of Peltorhamphus novaezeelandiae. Historically the examination of stomach contents has been the primary method of dietary analysis however, advances in stable isotope techniques and its analysis has resulted in a marked increase in their use. Both techniques have their advantages and disadvantages but when combined can greatly improve the resolution of the results. 120 stomach samples and 50 stable isotope samples were analysed. The contents of the stomach samples were identified to species level where possible and then placed in to taxonomic groupings and also grouped by feeding strategy. When analysed in the program PERMANOVA+ version 1.0.2 (add on to PRIMER v6), both groupings returned significant results when compared between the Otago and Southland regions indicating differential prey selection or availability on a spatial scale. Statistical significance was also found during analysis in the aforementioned program for stable isotopes. Both stable carbon (δ13C), stable nitrogen (δ15N) and trophic level showed dissimilarities between region but trophic shifts did not occur with an increase in total length of any given individual fish and nor was δ13C, δ15N or trophic level affected by sex. The combined results from the stomach content analysis and stable isotope analysis provide good evidence the existence of localised stocks between which

85 mixing may occur via larval transport and transient individuals but movement is limited to enough of a degree that differential dietary characteristics are maintained both spatially and temporally.

Predetermined mean δ13C and δ15N values for basal carbon sources, benthic (macroalgae) and pelagic (suspended particulate organic matter (SPOM)) (Jack and Wing, 2011) were used along with mean fractionation values for aquatic organisms as determined by McCutcheon et al. (2003) to determine the trophic level for each P.novaezeelandiae individual and to create a 2-source mass balance mixing model IsoError (Phillips and Gregg, 2001). Basal carbon source pools were estimated to be mostly benthic production with 82% macroalgal contribution for Otago and 99% for Southland. This supports the findings of the stomach analysis which found that the prey consumed within both regions were predominantly deposit feeders.

Ontogenetic trophic shifts occur in many fish species due to changes in body size, habitat and nutritional requirements (Davis et al., 2012). Flatfish species are generally believed to utilise shallow coastal inlets and estuaries during the juvenile phase of their lifecycle before making the migration out into coastal waters to spawning and feeding grounds (Gibson, 2008). Existing literature on Peltorhamphus novaezeelandiae however, suggests that this is not the case with this species. During sampling within the Otago Harbour and surrounding inlets it has been noted that juvenile P.novaezeelandiae are present in shallow coastal waters but not in the harbour or inlets. It is suggested that this species along with lemon sole, Pelotretis flavilatus bury into the sand in these shallow coastal waters in order to avoid being swept into the estuarine habitats during the incoming tide and periods of stormy weather (James, 1969, Roper and Jillett, 1981). This supports the results of the present study as no evidence of ontogenetic trophic shift was detected.

5.2.3 Morphological characteristics

Significant differences in the morphological characteristics of Peltorhamphus novaezeelandiae were obtained during this investigation between the neighbouring Otago and Southland regions of southern New Zealand providing evidence for a degree of separation between these groups. 91.3% of the P. novaezeelandiae sampled were correctly identified according to their region of origin during a CAP analysis in the statistical program PRIMER. Statistical analyses reveal that morphological differences exist at the regional level (P < 0.0001) but morphology is homogenous between the sexes.

The morphological differences observed between Otago and Southland are a result of location and are not affected by the dispersion of the data (Anderson, Gorley et al. 2008). Morphological differences are often seen between sexes of the same species; Cadrin and Silva (2005) investigated morphometric variation of yellowtail flounder (Limanda ferruginea) at 8 geographic locations and in doing so found the species exhibited significant sexual dimorphism. By ruling out the effect of sexual dimorphism I can confidently conclude that the observed dissimilarities are a product of region.

The vectors inter-orbital distance (IOD), pectoral length eye side (PES), body width (BW), head length (HL) and snout length (S) (Fig 4.1), are the most dominant morphological characteristics driving the differentiation between the two regions. While the aforementioned vectors are slightly more dominant than the others, all of the vectors measured had a strong influence on the distribution of the data in multi dimensional space. Morphological differentiation can often be related to adaptation to localised environmental conditions (Jørgensen et al., 2008). Kinsey, Orsoy et al. (1994) used both morphometric and genetic techniques to investigate the population structure of the Spanish sardine (Sardinella aurita) in coastal waters of Florida. They were unable to detect dissimilarities at the genetic level but identified several morphological types demonstrating how phenotypic plasticity allows individuals to adapt to localised environmental conditions.

There are many examples of morphological variation within a single species in relation to different geographic locations (Ellis et al., 1997, Haddon and Willis, 1995). Genetic studies often fail to observe differences due to the plastic nature of morphological characteristics. Morphological differentiation due to phenotypic plasticity does not necessarily have the ability to discern stocks as a single measure because the ability to adapt to local conditions remains throughout the life of the fish. It does however indicate that there is sufficient separation between the two regions for a length of time which has allowed individuals in a specific location to adapt to local environmental conditions and therefore morphological variation is useful for indicating short term stock structure.

5.3 Population spatial structure and connectivity inferred from growth, stable isotopes, morphological characteristics.

The existence of a single, panmictic population within the geographic range of a fish species is rare, with most forming local subpopulations or ‘stocks’, between which, differing levels of interconnectivity occur (Metcalfe, 2006). The inference of connectivity between marine populations is an important but often inadequately understood issue from both a conservation and fisheries management perspective. The degree of connectivity between subpopulations determines the spatial scales over which population dynamics and spatial structure operate (Gibson et al., 2011). Differing levels of interconnectivity consequently mean subpopulations have different capacities to generate genetic and phenotypic differences which are often employed to elucidate fish stocks. Therefore knowledge of life history characteristics such as ontogenetic habitat shifts, morphology, growth and diet; as well as others the current study did not extend to, such as reproduction, larval development and seasonal distributions are important in understanding movement and behaviour and consequently population structure on temporal and spatial scales (Metcalfe, 2006).

The current study employed a holistic approach during which the population and life history characteristics of growth, diet and morphology were examined. An holistic approach is recommended in population studies as often the patterns of a single characteristic can be misleading and bring about incorrect conclusions which can be detrimental if not fatal to a stock or species (Begg et al., 1999a, Begg and Waldman, 1999, Tracey and Horn, 1999). Conclusions drawn from a range of different approaches are more robust than those inferred from a single characteristic, with increased reliability and a lower risk of a misleading result.

The differences in diet and morphology detected in this study revealed that Peltorhamphus novaezeelandiae exhibits a complex population structure over its geographic range. There is evidence for stock structure among regions however, I are unable to conclude how much connectivity remains open. Although no significant dissimilarities in growth rates were detected between the Otago and Southland regions, crucial knowledge of growth characteristics were gained; which in itself is useful for understanding the life history of this species. This conclusion is consistent with other flatfish studies where the existence of subpopulations have been detected over large spatial scales (Metcalfe, 2006, Hoarau et al., 2002, Mollet et al., 2012). Subpopulations are thought to be created and

88 maintained by physical barriers such as ocean currents, water temperatures and fragmentation of suitable habitat (Bailey, 1997). Connectivity between subpopulations may be achieved via immigration and emigration of adults or through larval dispersal and recruitment. Consequently low levels of connectivity may be enough to maintain genetic homogeneity over large spatial scales obscuring the existence of local populations (Hanski, 1998). Subpopulations may occur in a metapopulation arrangement where one population acts as a ‘sink’ recruiting larvae and individuals from a ‘source’ population. This configuration can allow a species to persist over a large geographic area despite a lack of optimal habitat (Hanski, 1998).

In order for a true panmictic population to exist over large spatial scales, the species must be highly mobile with extensive mixing occurring over the entire geographic range. Significant differences in life history characteristics would not occur as an individual would not be able to develop adaptations to small-scale localised conditions. Conclusions cannot be drawn in this study on whether a metapopulation configuration exists as further information such as larval and juvenile movement, reproduction and genetics is required. The advancement of biochemical techniques such as trace element analysis of otoliths in recent years is also a promising tool in understanding population dynamics on a spatial and temporal dimension. Functional connectivity refers to how the geography and hydrology facilitates the movement of individuals between areas of habitat. Organisms respond to the spatial structure of the seascape at a number of spatial scales and alter their movements according to individual costs or benefits creating differential characteristics between localised populations, as well as differences in population viability and stability (Bélisle, 2005).

5.4 Implications for management

The findings of this study suggest that Peltorhamphus novaezeelandiae form distinct subpopulations at smaller spatial scales than currently recognised by the quota management areas (QMA’s) implemented through New Zealand’s quota management system (QMS). Therefore the potential exists for the over-exploitation of localised populations which could ultimately lead to their collapse. Finfish species tend to exhibit a complex population structure which requires management at the appropriate spatial scales in order to preserve stock complexity and behaviour (Stephenson, 1999). This is especially true for flatfish, which as a group are known to utilise a variety of habitats for

89 different functions and life stages such as juvenile rearing, feeding, wintering and spawning. Indications of stock complexity are difficult to obtain from historical data on commercial fish landings which is often how management areas and total allowable commercial catches (TACC) are set in the absence of biological data. Further complications are added when taking into account connectivity between semi-discrete populations and therefore management boundaries are often politically driven by commercial interests and ease of administration rather than as a reflection of population structure (Stephenson, 1999).

The Otago and Southland areas are both encompassed by Flatfish Management Area 3 (FLA3) which stretches from the northern banks of the Clarence River on the upper east coast of the South Island, down through Foveaux Strait and up the west coast to the northern side of Big Bay, a total of 5260 kilometres of coastline. Due to the nature of the species, pressure from recreational fisherman is much lower than that of estuarine flatfish which are able to be caught in a set net, such as yellow belly Rhombosolea leporina or greenback flounder Rhombosolea tapirinia; or finfish which are successfully captured using hook and line such as blue cod Parapercis colias or sea perch Helicolenus percoides. It is however, a primary fishery for the south-east coast commercial fisherman in the small inshore fishing fleet. The flatfish management areas comprise all eight commercial flatfish species and while each species has its own TACC they are all captured as part of a mixed bag trawl fishery where many species are targeted at the same time and often unwanted species are inadvertently captured. Therefore, mortality repeatedly occurs outside of the regulations of the TACC and often goes unreported either as discarded fish which are under-sized or illegal dumping of fish for which a vessel does not have the required quota (Rijnsdorp et al., 2007). As TACC’s are often set based on commercial catch statistics, scientific advice on sustainable levels of catch can be severely affected by illegal or misreported landings or by the discarding of under-sized fish (Rijnsdorp et al., 2007).

One management option which is not new but is increasing in popularity to some extent is that of community based coastal management of local fisheries. While this option is not ideal on its own, allowing more management decisions to incorporate a local community component increases both awareness of local issues and a sense of personal responsibility to maintain local fisheries at sustainable levels. It also allows issues which develop to be identified and remedied quickly. New Zealand Maori already employ a similar idea in their communities with mataitai and taiapure reserves, a concept which was developed as part of the Maori Fisheries Act 1989 in order to allow local

90 communities to protect and enhance inshore waters (Kallqvist, 2009). A mataitai reserve excludes commercial fisheries, while a Taiapure allows both recreational and commercial activity. Both reserves are able to have temporary closures (rahui) enforced in them if the committee which is nominated by local Iwi and approved by the Ministry of Fisheries (now the Ministry of Primary Industries) are concerned with the decline a of species. Catch limits are also subject to change depending on how the stocks within the management area are doing (Kallqvist, 2009). Although this particular example relates mostly to the recreational sector, a similar concept could be applied to the commercial sector; though as in any similar activity vested personal interests would need to be mitigated. While the implementation of Mataitai and Taiapure is a step towards community based co- management it is designed first and foremost to meet the needs of Maori, local people who are not of Maori decent often feel discriminated against and of lesser importance in such situations and a more inclusive structure would be required to get the entire community on board.

Experts in fisheries management are beginning to recognise that addressing the underlying relationships of fisheries with human welfare and conserving the resources for further generations brings about lasting changes to ensure the sustainability of both fisheries and habitats (Pomeroy, 1995). In order for laws and regulations surrounding fisheries resources to work effectively, a level of co-operation is needed from the fishers themselves as enforcement is often difficult due to the isolated nature that many stakeholders operate in. Community based co-management gives the community more power and responsibility, allowing it to become self-regulating to some degree (Pomeroy, 1995).

The level of connectivity between subpopulations within a species geographic range ascertains the spatial scales over which population dynamics operate. In addition to the spatial scales over which fisheries should be managed and the way in which marine protected areas should be designed and implemented. (Gibson et al., 2011). The implementation of marine protected areas (MPA’s) can be a crucial component in sustainable fisheries management, particularly in the protection of critical habitat such as spawning and nursery grounds or temporary closures of a particular fishery at certain times of the year (Ballantine, 1995). It is becoming increasingly apparent that despite intensive management of many key fisheries that stocks are still in decline and that the preservation of habitat is just as important as the management of fishing pressure. Management limitations are inevitable as one cannot account for all incidental mortality or the misreporting of catches and therefore MPA’s are invaluable in the rehabilitation of depleted stocks (Lauck et al., 1998). In order for MPA’s to have the desired

91 effect, they must encompass the appropriate spatial scales at which the population dynamics of a species operates. The design of an MPA is dependent on the specific goals that it is set to achieve, whether it be habitat conservation, protection of critical life stages or conservation of rare species (Botsford et al., 2003). MPA design often has to account for a multitude of species, all with varying life histories and population dynamics which has led to extremely complex modelling and there is suggestion that a network of MPA’s of moderate sizes is more effective than one MPA which covers a large geographic area (Halpern and Warner, 2003).

5.5 Final conclusions

The management of exploited fisheries is a complex issue as species comprise of spatially and temporally varying stocks. Additionally, individual species do not operate as a discrete unit but are influenced and have influence on co-occurring species. Biological information on life histories and population dynamics are crucial in effective management. This information however, is not always available and other information sources such as historical catch data is often used. The information acquired in the present study is not a complete view of the Peltorhamphus novaezeelandiae life history characteristics or population dynamics by any means, but is important knowledge which can be utilised its effective management and the bid to achieve and maintain the sustainability of this important resource.

The final conclusions of the present investigation are summarised in the following points:

 The overall combined results of investigations into the growth, dietary characteristics and morphology of Peltorhamphus novaezeelandiae indicate that a complex population structure exists within the Otago and Southland regions of New Zealand. This does not imply reproductive isolation or genetic differentiation.

 These subpopulations experience a degree of connectivity whether it be via the dispersal and recruitment of eggs, larvae or juveniles or through the migration of adults. However, subpopulations are subject to enough separation over spatial and temporal scales to enable and maintain significant differences in life history characteristics.

 It is evident that the population structure of P.novaezeelandiae occurs at smaller spatial scales than is currently recognised by the quota management system.

 Further research into the population dynamics of this species would be greatly beneficial toward increasing the efficacy of management efforts and to achieve sustainability of this fishery. In particular the utilisation of different habitats during significant life events such as spawning, feeding and juvenile rearing.

References

ALONGI, D. M., BOTO, K. & ROBERTSON, A. 1992. Nitrogen and phosphorus cycles, American Geophysical Union. ALVERSON, D. L. & CHATWIN, B. M. 1957. Results from tagging experiments on a spawning stock of petrale sole, Eopsetta jordani (Lockington). Journal of the Fisheries Board of Canada, 14, 953-974. ANDERSON, M., GORLEY, R. N. & CLARKE, K. R. 2008. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods, PRIMER-E. ANDERSON, M. J. 2006. Distance-based tests for homogeneity of multivariate dispersions. Biometrics, 62, 245- 53. ANDERSON, M. J. & WILLIS, T. J. 2003. CANONICAL ANALYSIS OF PRINCIPAL COORDINATES: A USEFUL METHOD OF CONSTRAINED ORDINATION FOR ECOLOGY. Ecology, 84, 511-525. BAILEY, K. M. 1997. Structural dynamics and ecology of flatfish populations. Journal of Sea Research, 37, 269- 280. BALLANTINE, W. 1995. Networks of" no-take" marine reserves are practical and necessary. Marine protected areas and sustainable fisheries. Science and Management of Protected Areas Association, Wolfville, Nova Scotia, Canada, 13-20. BAROILLER, J. & D'COTTA, H. 2001. Environment and sex determination in farmed fish. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, 130, 399-409. BEARHOP, S., ADAMS, C. E., WALDRON, S., FULLER, R. A. & MACLEOD, H. 2004. Determining trophic niche width: a novel approach using stable isotope analysis. Journal of Animal Ecology, 73, 1007-1012. BEGG, G. A., CAMPANA, S. E., FOWLER, A. J. & SUTHERS, I. M. 2005. Otolith research and application: current directions in innovation and implementation. Marine and Freshwater Research, 56, 477-483. BEGG, G. A., FRIEDLAND, K. D. & PEARCE, J. B. 1999a. Stock identification and its role in stock assessment and fisheries management: an overview. Fisheries Research, 43, 1-8. BEGG, G. A., HARE, J. A. & SHEEHAN, D. D. 1999b. The role of life history parameters as indicators of stock structure. Fisheries Research, 43, 141-163. BEGG, G. A. & WALDMAN, J. R. 1999. An holistic approach to fish stock identification. Fisheries Research, 43, 35-44. BÉLISLE, M. 2005. MEASURING LANDSCAPE CONNECTIVITY: THE CHALLENGE OF BEHAVIORAL LANDSCAPE ECOLOGY. Ecology, 86, 1988-1995. BERTALANFFY, L. V. 1938. A quantitative theory of organic growth (inquiries on growth laws II). Human biology, 10, 181-213. BOSCHKER, H. & MIDDELBURG, J. 2002. Stable isotopes and biomarkers in microbial ecology. FEMS Microbiology Ecology, 40, 85-95. BOTSFORD, L. W., MICHELI, F. & HASTINGS, A. 2003. Principles for the design of marine reserves. Ecological Applications, 13, 25-31. CADRIN, S. X. & SILVA, V. M. 2005. Morphometric variation of yellowtail flounder. ICES Journal of Marine Science: Journal du Conseil, 62, 683-694. CAMPANA, S. E., ANNAND, M. C. & MCMILLAN, J. I. 1995. Graphical and statistical methods for determining the consistency of age determinations. Transactions of the American Fisheries Society, 124, 131-138. CAMPANA, S. E. & NEILSON, J. D. 1985. Microstructure of fish otoliths. Canadian Journal of Fisheries and Aquatic Sciences, 42, 1014-1032. CAMPANA, S. E. & THORROLD, S. R. 2001. Otoliths, increments, and elements: keys to a comprehensive understanding of fish populations? Canadian Journal of Fisheries and Aquatic Sciences, 58, 30-38. CAPPUCCINO, N. & PRICE, P. W. 1995. Population dynamics: new approaches and synthesis, Academic Press.

CASEY, K. E., DEWEES, C. M., TURRIS, B. R. & WILEN, J. E. 1995. The effects of individual vessel quotas in the British Columbia halibut fishery. Marine Resource Economics, 10. CHARLES, A. T. 2008. Sustainable fishery systems, Wiley-Blackwell. CHEREL, Y. & HOBSON, K. A. 2007. Geographical variation in carbon stable isotope signatures of marine predators: a tool to investigate their foraging areas in the Southern Ocean. Marine Ecology Progress Series, 329, 281-287. CHOPELET, J., WAPLES, R. S. & MARIANI, S. 2009. Sex change and the genetic structure of marine fish populations. Fish and Fisheries, 10, 329-343. COLMAN, J. A. 1973. Spawning and fecundity of two flounder species in the Hauraki gulf, New Zealand. New Zealand Journal of Marine and Freshwater Research, 7, 21-43. COLMAN, J. A. 1974. Growth of two species of flounders in the hauraki gulf, New Zealand. New Zealand Journal of Marine and Freshwater Research, 8, 351-370. COWEN, R. K., G GAWARKIEWICZ, J PINEDA, SR THORROLD & WERNER, F. 2007. Population connectivity in marine systems. Oceanography, 20, 14-21. COWEN, R. K. & SPONAUGLE, S. 2009. Larval dispersal and marine population connectivity. Ann Rev Mar Sci, 1, 443-66. COYLE, T. 1998. Stock identification and fisheries management: the importance of using several methods in a stock identification study. Taking Stock: defining and managing shared resources. Edited by DA Hancock. Australian Society for Fishery Biology, Sydney, 173-182. CRANFIELD, H. J., MICHAEL, K. P. & DOONAN, I. J. 1999. Changes in the distribution of epifaunal reefs and oysters during 130 years of dredging for oysters in Foveaux Strait, southern New Zealand. Aquatic Conservation: Marine and Freshwater Ecosystems, 9, 461-483. CYRUS, D. & MARTIN, T. 1991. The importance of estuaries in life histories of flatfish species on the southern coast of Africa. Netherlands Journal of Sea Research, 27, 255-260. DARNAUDE, A. M. 2005. Fish ecology and terrestrial carbon use in coastal areas: implications for marine fish production. Journal of Animal Ecology, 74, 864-876. DAVIS, A. M., BLANCHETTE, M. L., PUSEY, B. J., JARDINE, T. D. & PEARSON, R. G. 2012. Gut content and stable isotope analyses provide complementary understanding of ontogenetic dietary shifts and trophic relationships among fishes in a tropical river. Freshwater Biology, 57, 2156-2172. DAVIS, J. 2011. Niche partitioning in the Fiordland Wrasse Guild. Master of Science, University of Otago. DE LA MORINIERE, C., POLLUX, B., NAGELKERKEN, I., HEMMINGA, M., HUISKES, A. & VAN DER VELDE, G. 2003. Ontogenetic dietary changes of coral reef fishes in the mangrove-seagrass-reef continuum: stable isotopes and gut-content analysis. Marine Ecology Progress Series, 246, 279-289. DENIRO, M. J. & EPSTEIN, S. 1978. Influence of diet on the distribution of carbon isotopes in animals. Geochimica et Cosmochimica Acta, 42, 495-506. DENNEY, N. H., JENNINGS, S. & REYNOLDS, J. D. 2002. Life–history correlates of maximum population growth rates in marine fishes. Proceedings of the Royal Society of London. Series B: Biological Sciences, 269, 2229-2237. DEUDERO, S., BOX, A., SUREDA, A., TINTORE, J. & TEJADA, S. 2011. Combining stable isotopes and biochemical markers to assess organic contamination in transplanted mussels Mytilus galloprovincialis. In: MCGEVIN, L. (ed.) Mussels: Anatomy, Habitat and Environmental impact. DWIVEDI, A. K. & DUBEY, V. K. 2012. Advancements in morphometric differentiation: a review on stock identification among fish populations. Reviews in Fish Biology and Fisheries, 1-17. EHLERINGER, J. R. & RUNDEL, P. W. 1989. Stable isotopes: history, units, and instrumentation. Stable isotopes in ecological research. Springer. ELLIOTT, E. L. 1958. SANDSPITS OF THE OTAGO COAST. New Zealand Geographer, 14, 65-74. ELLIS, T., HOWELL, B. R. & HAYES, J. 1997. Morphological differences between wild and hatchery-reared turbot. Journal of Fish Biology, 50, 1124-1128.

FAIRCLOUGH, D., EDMONDS, J., JACKSON, G., LENANTON, R., KEMP, J., MOLONY, B., KEAY, I., CRISAFULLI, B. & WAKEFIELD, C. 2013. A comparison of the stock structures of two exploited demersal teleosts, employing complementary methods of otolith element analysis. Journal of Experimental Marine Biology and Ecology, 439, 181-195. FARQUHAR, G. D., EHLERINGER, J. R. & HUBICK, K. T. 1989. Carbon isotope discrimination and photosynthesis. Annual review of plant biology, 40, 503-537. FRANCIS, R. I. C. C. 1988. Recalculated growth rates for sand flounder, Rhombosolea plebeia, from tagging experiments in Canterbury, New Zealand, 1964–66. New Zealand Journal of Marine and Freshwater Research, 22, 53-56. FRY, B., MUMFORD, P. L., TAM, F., FOX, D. D., WARREN, G. L., HAVENS, K. E. & STEINMAN, A. D. 1999. Trophic position and individual feeding histories of fish from Lake Okeechobee, Florida. Canadian Journal of Fisheries and Aquatic Sciences, 56, 590-600. FRY, B. & SHERR, E. B. 1989. δ13C Measurements as Indicators of Carbon Flow in Marine and Freshwater Ecosystems. In: RUNDEL, P. W., EHLERINGER, J. R. & NAGY, K. A. (eds.) Stable Isotopes in Ecological Research. Springer New York. GANNES, L. Z., O'BRIEN, D. M. & DEL RIO, C. M. 1997. Stable isotopes in animal ecology: assumptions, caveats, and a call for more laboratory experiments. Ecology, 78, 1271-1276. GAWARKIEWICZ, G., S. MONISMITH & LARGIER, J. 2007. Observing larval transport processes affecting population connectivity: Progress and challenges. Oceanography, 20, 40-53. GIBSON, R. N. 1997. Behaviour and the distribution of flatfishes. Journal of Sea Research, 37, 241-256. GIBSON, R. N. 2008. Flatfishes: Biology and Exploitation, Wiley. GIBSON, R. N., ATKINSON, R., GORDON, J., SMITH, I. & HUGHES, D. 2011. Estimating connectivity in marine fish populations: what works best? Oceanography and Marine Biology: An Annual Review, 49, 193-234. GODWIN, J., LUCKENBACH, J. A. & BORSKI, R. J. 2003. Ecology meets endocrinology: environmental sex determination in fishes. Evolution & development, 5, 40-49. GONZALEZ, A., LAWTON, J. H., GILBERT, F. S., BLACKBURN, T. M. & EVANS-FREKE, I. 1998. Metapopulation Dynamics, Abundance, and Distribution in a Microecosystem. Science, 281, 2045-2047. GRAHAM, B. S., KOCH, P. L., NEWSOME, S. D., MCMAHON, K. W. & AURIOLES, D. 2010. Using isoscapes to trace the movements and foraging behavior of top predators in oceanic ecosystems. Isoscapes. Springer. GRAHAM, D. 1956. A Treasury of New Zealand Fishes, Wellington, Reed. GRIFFITHS, H. 1991. Applications of stable isotope technology in physiological ecology. Functional Ecology, 5, 254-269. GROBER, M. S. & BASS, A. H. 2002. Life history, neuroendocrinology, and behavior in fish. Hormones, brain and behavior, 2, 331-348. GUTHERZ, E. J. 1969. Hermaphroditism in Citharichthys cornutus (Heterosomata, Family Bothidae). Copeia, 352-356. HADDON, M. 2001. Modelling and quantitative methods in fisheries, CRC Press. HADDON, M. & WILLIS, T. J. 1995. Morphometric and meristic comparison of orange roughy (Hoplostethus atlanticus: Trachichthyidae) from the Puysegur Bank and Lord Howe Rise, New Zealand, and its implications for stock structure. Marine Biology, 123, 19-27. HALLIDAY, R. & ROSCOE, B. 1969. The Effects If Icing and Freezing on the Length and Weight of Groundfish Species, International Commission for the Northwest Atlantic Fisheries. HALPERN, B. S. & WARNER, R. R. 2003. Review paper. Matching marine reserve design to reserve objectives. Proceedings of the Royal Society of London. Series B: Biological Sciences, 270, 1871-1878. HANSKI, I. 1998. Metapopulation dynamics. Nature, 396, 41-49.

HAWKE, D. J. 1989. Hydrology and near‐surface nutrient distribution along the South Otago continental shelf, New Zealand, in summer and winter 1986. New Zealand Journal of Marine and Freshwater Research, 23, 411-420. HILBORN, R. & WALTERS, C. J. 1992. Quantitative Fisheries Stock Assessment: Choice, Dynamics, and Uncertainty, Chapman and Hall. HOARAU, G., RIJNSDORP, A., VAN DER VEER, H., STAM, W. & OLSEN, J. 2002. Population structure of plaice (Pleuronectes platessa L.) in northern Europe: microsatellites revealed large‐scale spatial and temporal homogeneity. Molecular Ecology, 11, 1165-1176. HOBSON, K. A. 1999. Tracing origins and migration of wildlife using stable isotopes: a review. Oecologia, 120, 314-326. HOBSON, K. A., SCHELL, D. M., RENOUF, D. & NOSEWORTHY, E. 1996. Stable carbon and nitrogen isotopic fractionation between diet and tissues of captive seals: implications for dietary reconstructions involving marine mammals. Canadian Journal of Fisheries and Aquatic Sciences, 53, 528-533. HUXEL, G. R., HASTINGS, A., POLIS, G. A. & HOLT, R. D. 2004. At the frontier of the integration of food web ecology and landscape ecology. In: POLIS, G. A., POWER, M. E. & HUXEL, G. R. (eds.) Food Webs at the Landscape Level: The Ecology of Trophic Flow across Habitats

University of Chicago Press. HYSLOP, E. 1980. Stomach contents analysis—a review of methods and their application. Journal of fish biology, 17, 411-429. IMSLAND, A., FOLKVORD, A., GRUNG, G., STEFANSSON, S. & TARANGER, G. 1997. Sexual dimorphism in growth and maturation of turbot, Scophthalmus maximus (Rafinesque, 1810). Aquaculture Research, 28, 101- 114. JACK, L. & WING, S. R. 2011. Individual variability in trophic position and diet of a marine omnivore is linked to kelp bed habitat. Marine Ecology Progress Series, 443, 129-139. JAMES, G. D. 1969. The escapement of flatfish from trawl nets and studies on the biology of Peltorhamphus novaezeelandiae. Master of Science, University of Otago. JAMES, G. D. 1972. Revision of the New Zealand flatfish genus Peltorhamphus with descriptions of two new species. Copeia, 345-355. JILLETT, J. B. 1969. Seasonal hydrology of waters off the Otago peninsula, South‐Eastern New Zealand. New Zealand Journal of Marine and Freshwater Research, 3, 349-375. JØRGENSEN, H. B., PERTOLDI, C., HANSEN, M. M., RUZZANTE, D. E. & LOESCHCKE, V. 2008. Genetic and environmental correlates of morphological variation in a marine fish: the case of Baltic Sea herring (Clupea harengus). Canadian Journal of Fisheries and Aquatic Sciences, 65, 389-400. KALLQVIST, E. 2009. Who is catching what? A survey of recreational fishing effort and success ontaiāpure and mātaitai management areas. Master of science, University of Canterbury. KINSEY, S. T., ORSOY, T., BERT, T. M. & MAHMOUDI, B. 1994. Population structure of the Spanish sardine Sardinella aurita: natural morphological variation in a genetically homogeneous population. Marine Biology, 118, 309-317. KNAPP, A. N. 2012. The sensitivity of marine N2 fixation to dissolved inorganic nitrogen. Frontiers in microbiology, 3. KNUTSEN, H., JORDE, P. E., ANDRE, C. & STENSETH, N. C. 2003. Fine-scaled geographical population structuring in a highly mobile marine species: the Atlantic cod. Mol Ecol, 12, 385-94. LAUCK, T., CLARK, C. W., MANGEL, M. & MUNRO, G. R. 1998. Implementing the precautionary principle in fisheries management through marine reserves. Ecological applications, 8, S72-S78. LAVETY, J. 1987. Variability in the lengths of Dover sole (Solea solea) after death. Marine Policy, 11, 319-320.

LAWTON, R. J., WING, S. R. & LEWIS, A. M. 2010. Evidence for discrete subpopulations of sea perch (Helicolenus ercoides) across four fjords in Fiordland, New Zealand. New Zealand Journal of Marine and Freshwater Research, 44, 309-322. LAYMAN, C. A., ARAUJO, M. S., BOUCEK, R., HAMMERSCHLAG-PEYER, C. M., HARRISON, E., JUD, Z. R., MATICH, P., ROSENBLATT, A. E., VAUDO, J. J., YEAGER, L. A., POST, D. M. & BEARHOP, S. 2012. Applying stable isotopes to examine food-web structure: an overview of analytical tools. Biological Reviews, 87, 545- 562. LEDUC, D., PROBERT, P. K., FREW, R. D. & HURD, C. L. 2006. Macroinvertebrate diet in intertidal seagrass and sandflat communities: A study using C, N, and S stable isotopes. New Zealand Journal of Marine and Freshwater Research, 40, 615-629. LOCKWOOD, S. J. & DALY, C. D. B. 1975. Further observations on the effects of preservation in 4% neutral formalin on the length and weight of 0-group flatfish. Journal du Conseil, 36, 170-175. LOZÁN, J. 1992. Sexual differences in food intake, digestive tract size, and growth performance of the dab,< i> Limanda limanda L. Netherlands journal of sea research, 29, 223-227. LUCKENBACH, J. A., BORSKI, R. J., DANIELS, H. V. & GODWIN, J. Sex determination in flatfishes: mechanisms and environmental influences. Seminars in cell & developmental biology, 2009. Elsevier, 256-263. LUCKENBACH, J. A., GODWIN, J., DANIELS, H. V. & BORSKI, R. J. 2003. Gonadal differentiation and effects of temperature on sex determination in southern flounder (< i> Paralichthys lethostigma). Aquaculture, 216, 315-327. MAILLET, G. & CHECKLEY JR, D. 1990. Effects of starvation on the frequency of formation and width of growth increments in sagittae of laboratory-reared Atlantic menhaden Brevootia tyrannus larvae. Fishery Bulletin, 88, 155-165. MARQUES, J. F., TEIXEIRA, C. M. & CABRAL, H. N. 2006. Differentiation of commercially important flatfish populations along the Portuguese coast: Evidence from morphology and parasitology. Fisheries Research, 81, 293-305. MCCUTCHAN, J. H., LEWIS, W. M., KENDALL, C. & MCGRATH, C. C. 2003. Variation in trophic shift for stable isotope ratios of carbon, nitrogen, and sulfur. Oikos, 102, 378-390. METCALFE, J. D. 2006. Fish population structuring in the North Sea: understanding processes and mechanisms from studies of the movements of adults. Journal of Fish Biology, 69, 48-65. METCALFE, J. D., HUNTER, E. & BUCKLEY, A. A. 2006. The migratory behaviour of North Sea plaice: currents, clocks and clues. Marine and Freshwater Behaviour and Physiology, 39, 25-36. MFISH 2009. Flatfish (FLA). In: ZEALAND, M. O. F. N. (ed.). MOLLET, F. M., ENGELHARD, G. H., VAINIKKA, A., LAUGEN, A. T., RIJNSDORP, A. D. & ERNANDE, B. 2012. Spatial variation in growth, maturation schedules and reproductive investment of female sole Solea solea in the Northeast Atlantic. Journal of Sea Research. MORISON, A., BURNETT, J., MCCURDY, W. & MOKSNESS, E. 2005. Quality issues in the use of otoliths for fish age estimation. Marine and freshwater research, 56, 773-782. MUNDY, A. R. 1968. A study of the biology of the sand flounder, Rhombosolea pleabeia (Richardson), off the Canterbury coast. PhD, University of Canterbury. MURDOCH, R. C. 1989. The effects of a headland eddy on surface macro-zooplankton assemblages North of Otago Peninsula, New Zealand. Estuarine, Coastal and Shelf Science, 29, 361-383. NASH, R. D., GEFFEN, A. J. & GIBSON, R. 2005. Age and growth. Flatfishes: Biology and Exploitation. Blackwell Science, Oxford, 138-163. PAUL, L. 1992. Age and growth studies of New Zealand Marine fishes, 1921-90: A review. Marine and Freshwater Research, 43, 879-912. PAWSON, M. G. & JENNINGS, S. 1996. A critique of methods for stock identification in marine capture fisheries. Fisheries Research, 25. PERGA, M. & GERDEAUX, D. 2005. ‘Are fish what they eat’all year round? Oecologia, 144, 598-606.

PETERSON, B. J. & FRY, B. 1987. Stable isotopes in ecosystem studies. Annual review of ecology and systematics, 18, 293-320. PHILLIPS, D. L. & GREGG, J. W. 2001. Uncertainty in source partitioning using stable isotopes. Oecologia, 127, 171-179. PIANKA, E. R. 1970. On r- and k-Selection. The American Naturalist, 104, 592-597. PICKETT, S. T. A. & WHITE, P. S. 1985. The ecology of natural disturbance of natural patch dynamics, Academic Press. PICKRILL, R. A. & MITCHELL, J. S. 1979. Ocean wave characteristics around New Zealand. New Zealand Journal of Marine and Freshwater Research, 13, 501-520. PINEDA, J., HARE, J. A. & SPONAUGLE, S. 2007. Larval transport and dispersal in the coastal ocean and consequences for population connectivity. Oceanography, 20, 22-39. PINSKY, M. L., PALUMBI, S. R., ANDREFOUET, S. & PURKIS, S. J. 2012. Open and closed seascapes: where does habitat patchiness create populations with high fractions of self-recruitment? Ecol Appl, 22, 1257-67. POMEROY, R. S. 1995. Community-based and co-management institutions for sustainable coastal fisheries management in Southeast Asia. Ocean & Coastal Management, 27, 143-162. POPPER, A. N. & LU, Z. 2000. Structure–function relationships in fish otolith organs. Fisheries research, 46, 15- 25. POPPER, A. N., RAMCHARITAR, J. & CAMPANA, S. E. 2005. Why otoliths? Insights from inner ear physiology and fisheries biology. Marine and freshwater Research, 56, 497-504. POST, D. M. 2002. Using stable isotopes to estimate trophic position: models, methods, and assumptions. Ecology, 83, 703-718. RAMOS, S., RÉ, P. & BORDALO, A. A. 2009. Environmental control on early life stages of flatfishes in the Lima Estuary (NW Portugal). Estuarine, Coastal and Shelf Science, 83, 252-264. RAPSON, A. M. 1940. The reproduction, growth, and distribution of the lemon soles (Pelotretis flavilatus Waite) of Tasman Bay and Marlborough Sounds.

. New Zealand Marine Department, Fisheries Bulletin, 7, 56. REICHERT, M. J. M. 1998. Etropus crossotus, an annual flatfish species; age and growth of the fringed flounder in South Carolina. Journal of Sea Research, 40, 323-332. REIST, J. D. 1985. An empirical evaluation of several univariate methods that adjust for size variation in morphometric data. Canadian Journal of Zoology, 63, 1429-1439. REZNICK, D., BRYANT, M. J. & BASHEY, F. 2002. r-and K-selection revisited: the role of population regulation in life-history evolution. Ecology, 83, 1509-1520. RIJNSDORP, A., DAAN, N., DEKKER, W., POOS, J. & VAN DENSEN, W. 2007. Sustainable use of flatfish resources: addressing the credibility crisis in mixed fisheries management. Journal of Sea Research, 57, 114-125. RODGERS, K. L. & WING, S. R. 2008. Spatial structure and movement of blue cod Parapercis colias in Doubtful Sound, New Zealand, inferred from delta^ 1^ 3C and delta^ 1^ 5N. MARINE ECOLOGY-PROGRESS SERIES-, 359, 239. ROPER, D. S. & JILLETT, J. B. 1981. Seasonal occurrence and distribution of flatfish (Pisces: Pleuronectiformes) in inlets and shallow water along the Otago coast. New Zealand Journal of Marine and Freshwater Research, 15, 1-13. RUBENSTEIN, D. R. & HOBSON, K. A. 2004. From birds to butterflies: animal movement patterns and stable isotopes. Trends in Ecology & Evolution, 19, 256-263. RUDNICK, D. & RESH, V. 2005. Stable isotopes, mesocosms and gut content analysis demonstrate trophic differences in two invasive decapod crustacea. Freshwater Biology, 50, 1323-1336. SABINE, C. L. 2001. Global Carbon Cycle. eLS. John Wiley & Sons, Ltd. SADOVY, Y. & SHAPIRO, D. Y. 1987. Criteria for the diagnosis of hermaphroditism in fishes. Copeia, 136-156. SCHLOSSER, I. J. 1991. Stream fish ecology: a landscape perspective. BioScience, 41, 704-712.

SCHMIDT, K., ATKINSON, A., PETZKE, K.-J., VOSS, M. & POND, D. W. 2006. Protozoans as a food source for Antarctic krill, Euphausia superba: Complementary insights from stomach content, fatty acids, and stable isotopes. Limnology and Oceanography, 51, 2409-2427. SCHOENINGER, M. J. & DENIRO, M. J. 1984. Nitrogen and carbon isotopic composition of bone collagen from marine and terrestrial animals. Geochimica et Cosmochimica Acta, 48, 625-639. SECOR, H. & ROOKER, J. R. 2005. Connectivity in the life histories of fishes that use estuaries. Estuarine Coastal and Shelf Science, 64, 1-3. SEGAR, D. A. 1998. Introduction to ocean sciences, Wadsworth Pub. SHEAVES, M. 2009. Consequences of ecological connectivity: the coastal ecosystem mosaic. Mar Ecol Prog Ser, 391, 107-115. SOTIROPOULOS, M., TONN, W. & WASSENAAR, L. 2004. Effects of lipid extraction on stable carbon and nitrogen isotope analyses of fish tissues: potential consequences for food web studies. Ecology of Freshwater Fish, 13, 155-160. STEPHENSON, R. L. 1999. Stock complexity in fisheries management: a perspective of emerging issues related to population sub-units. Fisheries Research, 43, 247-249. STEVENS, D. W., FRANCIS, M. P., SHEARER, P. C., MCPHEE, R. P., HICKMAN, R. W. & TAIT, M. J. 2005. Age and growth of two endemic flatfish (Colistium guntheri and C. nudipinnis) in central New Zealand waters. Marine and Freshwater Research, 56, 143-151. STEVENS, D. W., JAMES, G. D. & FRANCIS, M. P. 2004. Maximum age of New Zealand sole (Peltorhamphus novaezeelandiae) from the west coast South Island, Final Research Report for Ministry of Fisheries Research Project FLA2003-01. National Institute of Water and Atmospheric Research. SUGA, S., NAKAHARA, H. & KAIGI, N. G. 1991. Mechanisms and phylogeny of mineralization in biological systems, Springer-Verlag. SWAIN, D. P. & FOOTE, C. J. 1999. Stocks and chameleons: the use of phenotypic variation in stock identification. Fisheries Research, 43, 113-128. TAYLOR, P. D., FAHRIG, L., HENEIN, K. & MERRIAM, G. 1993. Connectivity is a vital element of landscape structure. Oikos, 68, 571-573. THRESHER, R. E. 1999. Elemental composition of otoliths as a stock delineator in fishes. Fisheries Research, 43, 165-204. TILMAN, D. E. & KAREIVA, P. M. E. 1997. Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions, Princeton University Press. TRACEY, D. M. & HORN, P. L. 1999. Background and review of ageing orange roughy (Hoplostethus atlanticus, Trachichthyidae) from New Zealand and elsewhere. New Zealand Journal of Marine and Freshwater Research, 33, 67-86. TURAN, C. 1999. A note on the examination of morphometric differentiation among fish populations: the Truss System. Turkish Journal of Zoology, 23, 259-264. TURAN, C. 2004. Stock identification of Mediterranean horse mackerel (Trachurus mediterraneus) using morphometric and meristic characters. ICES Journal of Marine Science: Journal du Conseil, 61, 774-781. VANDER ZANDEN, M. J. & RASMUSSEN, J. 2001. Variation in 15N and 13C trophic fractionation: Implications for aquatic food web studies. Limnology and Oceanography, 46, 2061-2066. VANDER ZANDEN, M. J. & VADEBONCOEUR, Y. 2002. Fishes as integrators of benthic and pelagic food webs in lakes. Ecology, 83, 2152-2161. WARNER, R. R. 1975. The adaptive significance of sequential hermaphroditism in animals. American Naturalist, 61-82. WARWICK, R. M. & CLARKE, K. R. 1993. Increased variability as a symptom of stress in marine communities. Journal of Experimental Marine Biology and Ecology, 172, 215-226.

100

WEBSTER, M. M., ATTON, N., HART, P. J. B. & WARD, A. J. W. 2011. Habitat-Specific Morphological Variation among Threespine Sticklebacks (Gasterosteus aculeatus) within a Drainage Basin. PLoS ONE, 6, e21060. WEST-EBERHARD, M. J. 1989. Phenotypic plasticity and the origins of diversity. Annual review of Ecology and Systematics, 20, 249-278. WIENS, J. A. 1989. Spatial Scaling in Ecology. Functional Ecology, 3, 385-397. WING, S. R., BEER, N. A. & JACK, L. 2012. Resource base of blue cod Parapercis colias subpopulations in marginal fjordic habitats is linked to chemoautotrophic production. Marine Ecology Progress Series, 466, 205-214.

101

Appendix 1: Peltorhamphus taxonomic key

Developed in March 2010 by Thomas Munroe of the National Oceanic Atmospheric Administration (NOAA), in preparation. .Contact: [email protected].

1a. Ocular-side pectoral-fin ray longer than (for specimens 130 mm standard length (SL) or less), or equal to (specimens >130 mm SL) maximum body depth; no papillary operculum; larger specimens (usually >80 mm SL) with several small, ctenoid scales on blind sides of dorsal- and anal- fin rays, 41-42 total vertebrae Peltorhamphus tenuis

1b. Ocular-side pectoral-fin ray usually less than maximum body depth; papillary operculum present or absent; no scales on blind sides of dorsal- and anal-fin rays; less than 40 total vertebrae 2

2a. Anterior ventral margin of ocular-side opercle with 1-4 fleshy filaments; (following characters for fish >40 mm SL) more than 2 (usually 4-5) scales in diagonal row between ventral margin at middle of lower eye to upper margin of mouth opening; eye relatively small, eye diameter usually equal to or less than interorbital space and less than distance between ventral margin of lower eye and dorsal margin of mouth opening; posterior margin of mouth opening usually at vertical through anterior nostril 3

2b. Anterior ventral margin of ocular-side opercle without fleshy filaments; only 1-2 scales in diagonal row between ventral margin of mouth opening; posterior margin of mouth opening usually at vertical through anterior margin of lower eye Peltorhamphus latus

3a. Entire inner lining of ocular-side opercle and roof of mouth black; body stocky with short trunk length; gill raker on first arch on blind side long and of uniform thickness throughout their lengths and with tips recurved distally, gill rakers on upper limb of first arch on blind side slightly shorter than those on lower arch; fish larger than approx 80 mm SL with ctenoid scales on blind-side mid-body region and on blind-side pre- and subopercle Peltorhamphus n.sp*

3b. Inner lining of ocular-side opercle black only on dorso-posterior region, roof of mouth without black pigmentation; body more elongate with long trunk length; gill takers on first arch on blind side shorter, with their bases wider than distal regions, and distal tips not recurved, gill rakers on upper limb of first arch on blind side noticeably shorater and rounder than those on lower arch; fish larger than about 80 mm SL with cycloid scales on blind-side mid-body region and on blind side pre- and subopercle Peltorhamphus novaezeelandiae

*n.sp denotes a recently identified new species which is in the process of being described.

102

Appendix II: IRI Index Values

Appendix 1.1 Classification of diet items found in stomach content analysis. Items were grouped by taxon and feeding strategy.

% IRI Taxon Grouping Feeding Strategy Otago Southland Crustacea/Amphipoda Deposit Feeder 72.5 89.8 Crustacea/Isopoda Deposit Feeder 0.3 0.0 Cruatacea/Decapoda Secondary Consumer 7.2 3.0 Crustacea/Euphausiacea Pelagic Suspension Feeder 0.0 0.0 Nemata Deposit Feeder 0.1 1.3 Annelida Deposit Feeder 19.3 5.9 Mollusca/Cephlapoda Secondary Consumer 0.0 0.0 Mollusca/Gastropod + Bivalve Benthic Suspension Feeder 0.5 0.0 Teleostei Secondary Consumer 0.1 0.0

Appendix 1.2 Percent frequency (%F), percent weight (%W) and revised index of relative importance (IRI) for prey categories from the Otago region.

Otago Taxon Grouping % F % W IRI Crustacea/Amphipoda 37.2 53.0 1975 Crustacea/Isopoda 4.3 2.2 9 Cruatacea/Decapoda 13.8 14.2 197 Crustacea/Euphausiacea 0.0 0.0 0 Nemata 8.5 0.4 3 Annelida 19.1 27.4 524 Mollusca/Cephlapoda 3.2 0.0 0 Mollusca/Gastropod/Bivalve 12.8 1.1 13 Teleostei 1.1 1.7 2

103

Appendix 1.3 Percent frequency (%F), percent weight (%W) and revised index of relative importance

(IRI) for prey categories from the Otago region.

Southland Taxon Grouping % F % W IRI Crustacea/Amphipoda 73.2 37.2 2727 Crustacea/Isopoda 0.0 0.0 0 Cruatacea/Decapoda 9.4 9.6 90 Crustacea/Euphausiacea 0.6 1.1 1 Nemata 1.4 27.7 38

Annelida 15.3 11.7 179 Mollusca/Cephlapoda 0.0 1.1 0 Mollusca/Gastropod/Bivalve 0.0 0.0 0 Teleostei 0.1 1.1 0

104