Biophysical Drivers of Spawning Dynamics in Estuarine Fish

Home , Acanthopagrus butcheri, Coastal fish, Estuary perch, Percomorpha, Sand whiting, Sparisoma cretense

Biophysical drivers of spawning dynamics in estuarine fish

Dylan E. van der Meulen

A thesis in fulfilment of the requirements for the degree of Doctor of Philosophy

School of Biological, Earth & Environmental Sciences Faculty of Science University of New South Wales

September 2018

THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet

Surname or Family name: van der Meulen

First name: Dylan Other name/s: Edward

Abbreviation for degree as given in the University calendar: PhD

School: Biological, Earth and Environmental Sciences Faculty: Faculty of Science

Title: Biophysical drivers of spawning dynamics in estuarine fish

Abstract: Determining links among estuarine variability, habitat and spawning of estuary-dependent fish is essential for understanding population processes and directing conservation efforts. I used acoustic telemetry, habitat mapping and egg sampling, in the Shoalhaven and Clyde rivers (New South Wales, Australia), to examine biophysical drivers of habitat use and spawning dynamics in estuarine-dependent fish:, Estuary Perch, Percalates colonorum, Sand Whiting, Sillago ciliata , Yellowfin Bream, Acanthopagrus australis, Black Bream, Acanthopagrus butcheri and the Yellowfin Bream and Black Bream hybrid complex.

Spawning activity of Estuary Perch was restricted to areas of structurally complex large wooden debris and a concrete ferry landing, adjacent to deep water. Eggs were released at night during the first 2 h of the run-out tide.

Spawning movements of Sand Whiting were typified by regular, swift migrations from upstream resident sites to specific areas adjacent to river entrances and deep water. Spawning movements coincided with high water temperatures linked to coastal winds and down- welling oceanographic conditions. Similarly to Estuary Perch, spawning occurred after nocturnal high tides. This strategy increases offshore dispersal and exports eggs and larvae onto coastal waters. At upstream residences, Sand Whiting displayed small core home ranges and high site fidelity to habitat characterised by sediment containing benthic invertebrates. These locations are likely used to maintain reproductive growth between spawning movements.

Large-scale tracking of Yellowfin Bream, Black Bream and their hybrids showed high levels of residency and site-fidelity, with peak distributions occurring in the lower and upper-middle estuary. Estuarine movements were correlated with freshwater flow, temperature, and genetic classification. Distinct repetitive spawning migrations were not observed. The data suggests that spawning may occur within estuaries, with inter-estuarine migrations playing a significant role in genetic dispersal and mixing.

This study highlights the complex interrelationships between movement, spawning, physicochemical variation and habitat availability. Spawning and recruitment success may be dependent on the selection of spawning locations and the timing of spawning events, which influences dispersal of eggs and larvae within and between estuaries, and can act to isolate populations or facilitate inter-estuarine connectivity and genetic relatedness.

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Preface

ORIGINALITY STATEMENT

‘I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.’

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Date …12/9/18…………….………

van der Meulen, D.E. 3 Preface

‘I hereby grant the University of New South Wales or its agents the right to archive and to make available my thesis or dissertation in whole or part in the University libraries in all forms of media, now or here after known, subject to the provisions of the Copyright Act 1968. I retain all proprietary rights, such as patent rights. I also retain the right to use in future works (such as articles or books) all or part of this thesis or dissertation. I also authorise University Microfilms to use the 350 word abstract of my thesis in Dissertation Abstract International (this is applicable to doctoral theses only). I have either used no substantial portions of copyright material in my thesis or I have obtained permission to use copyright material; where permission has not been granted I have applied/will apply for a partial restriction of the digital copy of my thesis or dissertation.'

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AUTHENTICITY STATEMENT

‘I certify that the Library deposit digital copy is a direct equivalent of the final officially approved version of my thesis. No emendation of content has occurred and if there are any minor variations in formatting, they are the result of the conversion to digital format.’

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Date ……12/9/18………………………………......

van der Meulen, D.E. 4 Preface

Photo 1 Spawning aggregation of Estuary Perch Percalates colonorum on large wooden debris, Shoalhaven River, New South Wales (Photo: D.E. van der Meulen).

van der Meulen, D.E. 5 Preface

Publications

The information in this thesis is entirely the result of investigations conducted by the author with guidance from supervisors Dr Matthew D. Taylor, Dr Nicholas L. Payne, Dr

Charles A. Gray, Professor Iain Suthers and Dr Christopher T. Walsh, and has not been submitted in part, or otherwise, for any other degree or qualification. This thesis consists of six chapters, including four data chapters prepared as standalone manuscripts, and therefore there may be some repetition of background and methods.

One data chapter has been accepted and two others are in review in peer-reviewed journals, as detailed below.

Chapter 2: van der Meulen, D.E., Walsh, C.T., Taylor, M.D., and Gray, C.A. (2014) Habitat requirements and spawning strategy of an estuarine-dependent fish, Percalates colonorum. Marine and Freshwater Research 65, 218-227.

Chapter 3: van der Meulen, D.E., Walsh, C.T., Reinfelds, I., Payne, N.L., Ives, M.C., Roberts, D.G., Craig, J. Gray, C.A., and Taylor, M.D. (In Review) Estuarine movements in a sparid hybrid complex. PLoS ONE.

Chapter 4: van der Meulen, D.E., Walsh, C.T., Payne, N.L., Gray, C.A., Reinfelds, I., Gannon, R., Suthers, I.M., and Taylor, M.D. (In Review) Temperature mediates repeated and extensive spawning migrations of Sand Whiting, Sillago ciliata. Estuaries and Coasts.

Chapter 5: van der Meulen, D.E., Payne, N.L., Rowland, D., Gray, C.A., Walsh, C.T., Suthers, I.M., and Taylor, M.D. (In Prep) High precision homing during spawning migrations of a soft sediment fish. Target Journal: Biology Letters.

van der Meulen, D.E. 6 Acknowledgements

Acknowledgements

Firstly, I would like to express my sincere gratitude to my supervisors Dr Matthew

Taylor, Dr Iain Suthers, Dr Nicholas Payne, Dr Charles Gray and Dr Chris Walsh for your knowledge, guidance, support, enthusiasm and encouragement. I am additionally grateful to Dr Charles Gray and Dr Chris Walsh, for providing me with the opportunities to undertake this research.

This project was supported by the Recreational Fishing Trust, the Caring for Country program and the Australian Research Council (LP100100367) in collaboration with

NSW Department of Primary Industries, Fisheries and the University of New South

Wales. All research was conducted under a Section 37 permit (Fisheries Management

Act 1994) issued by NSW Department of Primary Industries. This study complied within the requirements of the Animal Research Act 1985 (ACEC # 06/03).

Thank you to the NSW Department of Primary Industries, University of New South

Wales and University of Wollongong for providing the equipment, facilities and expertise required. A project of this scale would not have been possible without the continued support from colleagues from NSW DPI, NSW Office of Water and the

University of NSW. In particular I would like to thank Dr Matt Ives for his modelling skills and everything R related, to Lachlan Barnes for his comradery and R insight, to

James Craig for database assistance, to Jerom Stocks and Grant Clark for their willingness to follow me in the field with a fishing rod at all hours, to Ivars Reinfelds for his hydrology expertise and support throughout and to Nicholas Payne for coming onboard with fresh eyes, showing us what can be done with an accelerometer tag, and for providing unbelievably valuable guidance, I am truly grateful for your help. From van der Meulen, D.E. 7 Acknowledgements

the university, I especially thank my fellow students, Ruan Gannon for his tireless enthusiasm and commitment to the project, to Gwenal Cadiou for his assistance in the field and in the water and to Teagan Marzullo. Other NSW DPI staff members that provided advice and technical assistance included Daniel Johnson, Martin Jackson,

Heath Folpp, Isabelle Theorbeld, Michael Rodgers, Justin McKinnon, Amy Smoothey,

Caitlin Kesby, Garry Rielly, Geoff Barrett, James McLeod and Justin Stanger.

Many thanks to all the fishers who helped capture fish for this project. I especially thank

Jerom Stocks, Grant Clark, Ruan Gannon, Nicholas Payne, Martin Jackson, Jim Barrie,

Tim Francis, Steve Johnson, Chris Neville, Warren Ganderton, John Wilson, Bobby

Russo, Dean Dawson, Rod Stockton, Jason Wheeler, Mitch van der Meulen, Kyle van der Meulen, Dave Clark, Steve Starling, Dan Selby, Clint Thorpe and Ettien DeCelis.

Thank you to everyone from the Basin Lure and Fly Anglers Club and Southern Bass

Fishing Club for your support and assistance.

Finally and most importantly, to my amazing wife, Karlee, I thank you most of all. Your endless love, constant support and tireless encouragement throughout this process and the countless sacrifices you have made has enabled me to reach this point. To my two beautiful girls, Alba and Elani, you are my sunrise over the sea and you fill my heart with joy, you have helped me to reach the end of this thesis, more than you will ever know. My Parents, Susan and Daniel, deserve special thanks for their support and for instilling in me their love of the water, which has steered me down the path I am on today.

van der Meulen, D.E. 8 Thesis Abstract

Thesis Abstract

Determining links among estuarine variability, habitat and spawning of estuary- dependent fish is essential for understanding population processes and directing conservation efforts. I used a combination of acoustic telemetry, habitat mapping, environmental data collection and egg sampling, in the Shoalhaven and Clyde rivers

(New South Wales, Australia), to examine biophysical drivers of spawning dynamics in four key estuarine-dependent fish: Estuary Perch, Percalates colonorum, Sand Whiting,

Sillago ciliata, Yellowfin Bream, Acanthopagrus australis and the hybrid complex of

Yellowfin Bream and Black Bream, Acanthopagrus butcheri.

Estuary Perch have been found to move to estuary entrances during the winter spawning season. Fine-scale spatio-temporal patterns in movement activity of Estuary Perch within this suggested spawning location, was restricted to areas of structurally complex large wooden debris and a concrete ferry landing. Spawning was confirmed at this location through the collection of Estuary Perch eggs. Hourly sampling over two 48 hour periods showed egg abundances peaked at night during the first 2 h of the run-out tide.

Spawning movements of Sand Whiting were typified by regular, swift migrations from specific upstream resident sites to areas adjacent to river entrances. Spawning movements coincided with high water temperatures, while individual migrations appeared to be triggered by fluctuations in coastal water temperature, linked to coastal winds and down-welling oceanographic conditions, and increased freshwater flow. Sand

Whiting displayed high levels of site fidelity and site attachment at upstream resident sites, with little overlap between individual fish. Preferred habitat was characterised by sediment containing benthic invertebrates and the presence of predator holes. These van der Meulen, D.E. 9 Thesis Abstract

predator holes are characterised by depressions in the sediment which are left behind after a fish or ray prey on a benthic organism. Downstream, sand whiting form spawning aggregations centred about one location, adjacent to the river entrance and deep water to aid in offshore dispersal. Similar to Estuary Perch, egg abundances peaked after nocturnal high tides.

Large-scale tracking of Yellowfin Bream and Yellowfin Bream backcross hybrids showed high levels of residency and site-fidelity, with peak distributions occurring in the lower and upper-middle estuary. Estuarine movement patterns were correlated with freshwater flow, temperature, and genetic classification (analysis of genotypes to identify pure Yellowfin Bream or Yellowfin Bream backcross hybrids). Distinct repetitive spawning migrations were not observed for either Yellowfin Bream or hybrids. The data suggests that Yellowfin Bream and hybrids may be capable of spawning within estuaries, but irregular inter-estuarine migrations by adults appear to play a significant role in the genetic mixing of populations of this species complex.

van der Meulen, D.E. 10 Contents

Table of Contents

Biophysical drivers of spawning dynamics in estuarine fish ...... 1 Publications ...... 6 Acknowledgements ...... 7 Thesis Abstract ...... 9 Table of Contents ...... 11 List of Figures ...... 13 List of Tables...... 17

Chapter 1: General Introduction ...... 19 1.1 Estuarine Ecosystems ...... 20 1.2 Biophysical drivers of fish movement ...... 22 1.3 Spawning dynamics of fish ...... 26 1.4 Estuarine-dependent fishes ...... 28 1.4.1 Estuary Perch ...... 29 1.4.2 Yellowfin Bream, Black Bream and their hybrids ...... 31 1.4.3 Sand Whiting ...... 33 1.5 Thesis objectives ...... 35

Chapter 2: Habitat requirements and spawning strategy of an estuarine- dependent fish, Percalates colonorum ...... 36 Abstract ...... 36 2.1 Introduction ...... 37 2.2 Methods ...... 39 2.2.1 Study site ...... 39 2.2.2 Mapping subtidal habitat ...... 40 2.2.3 Tagging ...... 41 2.2.4 Fish tracking ...... 42 2.2.5 Percalates colonorum egg abundance ...... 43 2.2.6 Data analysis ...... 44 2.3 Results ...... 47 2.3.1 Home range and habitat selection ...... 47 2.3.2 Percalates colonorum egg abundance ...... 50 2.4 Discussion ...... 52 2.4.1 Habitat requirements ...... 52 2.4.2 Spawning strategy ...... 55

Chapter 3: Estuarine movements in a sparid hybrid complex ...... 59 Abstract ...... 59 3.1 Introduction ...... 60 3.2 Methods ...... 63 3.2.1 Study Region ...... 63 3.2.2 Acoustic Array and Monitoring ...... 64 3.2.3 Ethics Statement ...... 66 3.2.4 Tagging ...... 66 3.2.5 Genetic analysis ...... 67 3.3 Data Analysis ...... 67 van der Meulen, D.E. 11 Contents

3.4 Results ...... 71 3.4.1 Movement Patterns...... 72 3.4.2 Movements in response to environmental variables ...... 76 3.4.3 Spawning Period Movements ...... 80 3.4.4 Depth Distributions ...... 81 3.5 Discussion ...... 82 3.5.1 Movements in response to environmental variables ...... 84 3.5.2 Spawning-related Movements ...... 86 3.5.3 Conclusions ...... 88

Chapter 4: Temperature mediates repeated and extensive spawning migrations of Sand Whiting, Sillago ciliata ...... 90 Abstract ...... 90 4.1 Introduction ...... 91 4.2 Methods ...... 93 4.2.1 Study locations ...... 93 4.2.2 Fish capture and tagging ...... 94 4.2.3 Ethics statement ...... 95 4.2.4 Acoustic array and data collection ...... 97 4.2.5 Data analysis ...... 98 4.2.6 Egg sampling ...... 100 4.3 Results ...... 102 4.3.1 Spawning movements ...... 103 4.3.2 Egg abundances ...... 108 4.4 Discussion ...... 109 4.4.1 General spawning movements ...... 109 4.4.2 Role of temperature on spawning dynamics ...... 112 4.4.3 Role of currents in temperature-mediated spawning ...... 115 4.4.4 Management implications ...... 118 4.4.5 Conclusion ...... 119

Chapter 5: High precision homing during spawning migrations of a sediment- specialist ...... 120 Abstract ...... 120 5.1 Introduction ...... 121 5.2 Methods ...... 123 5.3 Results ...... 126 5.4 Discussion ...... 129

Chapter 6: Key findings, management implications and future research ...... 132 6.1 Spawning dynamics of estuarine fish ...... 132 6.2 Management recommendations ...... 138 6.3 Future research and conclusions ...... 140

References ...... 144

Appendix ...... 168

van der Meulen, D.E. 12 Contents

List of Figures

Figure 1.1 Estuary Pech, Percalates colonorum. ©B.Yau...... 30

Figure 1.2 Yellowfin Bream, Acanthopagrus australis. ©B.Yau...... 32

Figure 1.3 Sand Whiting, Sillago ciliata. ©B.Yau...... 34

Figure 2.1 (a) Study-site location and detailed map of the Shoalhaven River, showing

(b) bathymetry, (c) subtidal habitat, (d) July new moon tracking period-weighted population utilisation distributions and (e) August full moon tracking period-weighted population. Habitats are not to scale and were enlarged for display purposes...... 46

Figure 2.2 Mean (± s.e.) habitat-selection index (core 50% and total 90% utilisation distribution, UD) for new moon and full moon sampling periods...... 49

Figure 2.3 Mean (±s.e.) number of eggs captured per m3 (column) for each sampling time in relation to tidal height (line) for the full moon and new moon sampling periods.

...... 51

(Station 10), Nowra Bridge (Station 16), Ski Park (Station 22) and Gypsy Point (27).

Tide data was collected for Greenwell Point (Station 3) and Nowra Bridge (Station 16).

...... 64

Figure 3.2 Average hourly distance from sea of six representative Acanthopagrus australis and six Acanthopagrus hybrids. Transmitter serial number displayed in each plot...... 76

van der Meulen, D.E. 13 Contents

Figure 3.3 Population averaged distance from sea for a) Acanthopagrus australis and b)

Acanthopagrus hybrids. Population averaged movement rate for c) Acanthopagrus australis and d) Acanthopagrus hybrids. Individual hourly averaged distance from sea for fish with tag serial numbers e) 1060789, f) 1060944 and g) 1060946 plotted with environmental variables: flow, temperature and conductivity respectively. Note: all figures are plotted with the same x-axis scale so that environmental variables can be compared against movements...... 78

Figure 3.4 Total population, spawning/non-spawning and wet/dry year two dimensional kernel density estimates plotted for Acanthopagrus australis and Acanthopagrus hybrids...... 79

Figure 3.5 Average depth (+-SD) at each receiver station (black line) and maximum river depth adjacent to each receiver (grey line) shown in relation to distance from sea.

...... 81

Figure 3.6 (A) Relative depth distributions of fish, with depth data averaged against log flow. (B) Salinity depth profiles (PSU) conducted using a Sea-Bird CTD for station 7 conducted during low flow (normal) conditions and high flow (fresh) conditions...... 82

Australia is shown in yellow. S1-5 and C1-C2 represent tagging locations in the

Shoalhaven River and Clyde rivers respectively. Dashed line indicates the area below which is classified as the spawning location (<7km from the estuary entrance)...... 94

Figure 4.2 Average hourly distance from sea of four representative Sand Whiting plotted against freshwater flows, conductivity, temperature and female GSI (inferred from 2004-05 St. Georges Basin DPI Data) from the Shoalhaven and Clyde rivers. van der Meulen, D.E. 14 Contents

Transmitter serial number is displayed in each plot. Grey shaded areas represent the spawning season...... 103

Figure 4.3 Relationship between fork length (FL) and the average number of movements towards the river entrance observed during the spawning season for Sand

Whiting in the Shoalhaven River (closed circle, dashed line) and Clyde River (open circle, solid line)...... 105

Figure 4.4 Influence of temperature on Sand Whiting rate of movement (km/hr) and distance from sea (km) for the Shoalhaven (a,c) and Clyde (b,d) rivers, with data averaged for each 0.1°C increment in water temperature. Dashed line represents the temperature above which spawning movements towards the entrance of the river commence. Note: temperatures are not directly comparable between rivers, nor do they represent temperatures encountered by the fish, as temperature was recorded from a single location in each estuary...... 107

Figure 4.5 Spawning movements of fish 1066621. This data is plotted against river temperature (recorded at a fixed point 6.9km from the river entrance) to demonstrate how short term temperature fluctuations correlate with downstream movements of this species...... 108

Figure 4.6 Mean (± S.E.) number of Sand Whiting eggs captured per m3 from the Clyde

River in relation to tidal height and day (white), night (grey). Start date was 11th

February 2012...... 109

van der Meulen, D.E. 15 Contents

(c) Conceptual figure showing the direction of summer trade winds and the corresponding net water movement caused by Ekman’s transport...... 116

Figure 5.1 Study locations in the Clyde River, NSW, Australia. a) Upstream residence tracking array, showing all subtidal habitat present. b) Core area (50% utilization distribution) for Sand Whiting in the upstream residence array. c) Downstream spawning tracking array, showing all subtidal habitat present. d) Core area (50% utilization distribution) for Sand Whiting in the downstream spawning array. e) Large scale movements of Sand Whiting 11 for the duration of the tracking period. Shaded areas show the detection coverage of the VPS arrays, and the linear array in the estuary is shown in the bottom left panel (filled circles)...... 124

Figure 5.2 Mean habitat selection index (±S.E.) determined for the core area (50% utilisation distribution) of Sand Whiting within the upstream residence and the downstream spawning tracking arrays. Images display the different habitat types present. Sediment with predator holes image shows ghost shrimp burrows present only in the upstream residence location...... 127

Figure A.1 Average hourly ocean, river and air temperature. Air temperature was recorded at Nowra (-34.94, 150.55), river temperature was collected 6.9km from the river entrance and ocean temperature was collected adjacent to the Shoalhaven River.

...... 168

Figure A.2 Bathymetry at a) the upstream residence array and b) the downstream spawning array...... 169

van der Meulen, D.E. 16 Contents

List of Tables

Table 2.1 Summary of Percalates colonorum tagging data and home range from downstream spawning grounds within the Shoalhaven River for the July new moon and

August full moon tracking periods. Core and total utilisation distributions (UD) represent the area and number of 50% and 90% kernel density isopleth, respectively. Nc

= the number of separate core UD areas, Nt = the number of separate total UD areas. FL, fork length; F, female; M, male...... 48

Table 3.1 Summary of Acanthopagrus australis and Acanthopagrus hybrids tagged in the Shoalhaven River ...... 75

Explanatory variables include log transformed river flow (LFlow), highest 5% of river flow (HighFlow), Fork Length (FL), genetic class (Genetics), spawning season

(Spawn), capture location (Capture), water temperature (Temp), conductivity (Cond). 80

Table 3.3 Summary statistics for the most parsimonious model fit to tagged

Acanthopagrus spp. mean distance from sea, using twelth order autoregression (AR12) on quarter-day data split into dawn, day, night and dusk. AR φ's are the autoregression parameters. Capture locations are relative to Ferry...... 80

Table 4.1 Summary of Sand Whiting tagged in the Shoalhaven and Clyde rivers...... 96

Table 5.1 Summary of Sand Whiting tagging and home range data from the upstream residence and downstream spawning tracking arrays...... 128

van der Meulen, D.E. 18 Chapter 1: General Introduction

Chapter 1: General Introduction

Defining environmental drivers and interrelationships between biotic and abiotic variables associated with home range, movement and migration patterns is central to understanding the ecology or an organism. Theories surrounding the home range and homing abilities of fish have been well developed for freshwater riverine environments

(Gerking 1953; Gerking 1959; Gowan et al. 1994; Rodriguez 2002). Many studies have found that individual movements are generally small, with fish displaying high levels of site fidelity, good homing abilities and periodic long-term shifts in location (Crook

2004; Gerking 1953).There is limited information about the movements of many estuarine fish species, and the relationship between these movements and key spatial elements of a fish’s life cycle are poorly understood. Reproductive strategies and the timing of spawning events undertaken by fish are highly variable, but ultimately contribute to reproductive success (Lowerre-Barbieri et al. 2011b). Many fish migrate to spawn at predictable locations and times, and can form large aggregations (Claydon

2004; Dean et al. 2014; Lowerre-Barbieri et al. 2016). These migrations and aggregations can be linked to environmental and physical conditions, with fish matching spawning events with optimal conditions for egg and larvae survival.

Fisheries are known to target spawning aggregations due to predictably high yields for a given unit of effort (Claydon 2004). Fish are generally more vulnerable during this period, and the resultant disruption to spawning can have detrimental consequences on fish populations (Claydon 2004; Sadovy and Domeier 2005; Sala et al. 2001). In addition, other environmental and anthropogenic disturbances can impact spawning van der Meulen, D.E. 19 Chapter 1: General Introduction

events and affect subsequent recruitment (Dean et al. 2012; Strydom et al. 2002). There is a need to better understand the links between environmental drivers and fish movements and distribution, to enhance science-based and adaptive management of fish populations. Specifically, this includes protection of spawning processes, identification, protection and enhancement of important structural and physicochemical habitats, and accounting for the way in which environmental variability affects fish distribution. The development of acoustic telemetry, data logging equipment and substrate mapping technology has allowed us to gain an increasingly detailed understanding of the movements of fish and other marine animals (Hussey et al. 2015).

The overall objective of the current research is to apply acoustic telemetry to define and quantify the factors driving movements and spawning dynamics of key commercially or recreationally important, large bodied, estuarine fish, particularly in respect to biophysical drivers. In this introductory chapter, I provide a general background of estuarine ecosystems of south-eastern Australia, the potential biophysical drivers of fish movements in these systems, and an overview of current knowledge of spawning dynamics for the study species. The chapter concludes with the research objectives addressed by the thesis.

1.1 Estuarine Ecosystems

Pritchard (1967) defined an estuary as a semi-enclosed coastal body of water which is connected with the open sea and within which sea water is measurably diluted by fresh water from land drainage. Estuaries generally represent the interface between catchment and the coast, and are spatially and temporally complex systems (Gillanders van der Meulen, D.E. 20 Chapter 1: General Introduction

et al. 2011; Rochford 1951). Freshwater inflow to the estuary determines many of the abiotic characteristics of the ecosystem, and also drives variability in estuarine productivity (Kimmerer 2002). Estuaries are among the most productive ecosystems in the world, and can support large biomass of fish, crustaceans and water birds. They also represent important refuge, spawning and nursery grounds for many of these species, and contain much of the biodiversity present within the coastal ecosystems (Whitfield et al. 2012). There is some concern for the health of estuaries worldwide, as a large proportion of the global population resides in urban areas adjacent to these systems, and as a result estuaries and the organisms that rely on them are exposed to a broad range of stressors arising from anthropogenic activities (Kennish 2002).

The south-eastern Australian coasts includes a large number of estuarine ecosystems, all of which are inherently complex, dynamic and variable (Roy et al. 2001). Over 950 water bodies adjoin the ocean along the New South Wales (NSW) coast, with the majority of these being small and intermittently closed (Williams et al. 1998). Over 130 estuaries have been documented with a size greater than 0.05 km2, and have been categorised into three main groups: 1) tide-dominated, drowned valley estuaries with entrances unchanged; 2) wave-dominated barrier estuaries, with trained entrances, that are permanently open or are untrained but are kept partially open; and 3) smaller saline intermittently open, mostly closed lakes and lagoons (Roy et al. 2001).

The Batemans Bay bioregion stretches from Shellharbour to Tathra, and has the highest density of estuaries across the state. Natural estuarine habitats in this region consist largely of macrophytes (including mangroves, saltmarsh and seagrass), algae, rocky reefs, wooden debris and sediment (Creese et al. 2009). Much of this habitat has been van der Meulen, D.E. 21 Chapter 1: General Introduction

lost or degraded through anthropogenic activities such as land clearing, forestry, farming, urbanization, river regulation, dredging and removal of large wooden debris

(de-snagging). In addition, bridges, jetties, oyster infrastructure, training walls and other hard structures have further modified natural shoreline and subtidal habitat.

Within NSW, many fish and invertebrates are dependent on estuaries for at least part of their lifecycle, and use them for reproduction (Gray and Barnes 2015; Walsh et al.

2013b), larval development (Neira et al. 1998; Trnski 2001), juvenile nurseries (West and King 1996), or as a migration pathway between freshwater and marine environments (Crook et al. 2010; Crook et al. 2014). NSW estuaries have been found to contain in excess of 100 different species of fish, but the number and status of estuarine- dependent fishes is still not fully known. A number of these species are commercially or recreationally important (Rowling et al. 2010b; West et al. 2015), supporting a diverse range of fisheries. Some of these species have recorded declines in commercial landings and catch per unit effort over the past decades (Rowling et al. 2010b), highlighting the need to better understand more aspects of their biology and ecology. The synthesis of spatial data on movement, habitat extent and fish distribution will provide an increasingly powerful tool to quantify aspects of the life history and ecology of coastal and estuarine species. This will aid in evaluating stock status and spatial management required for their sustainable harvest and effective conservation (Curley et al. 2013).

1.2 Biophysical drivers of fish movement

The interaction between biophysical variability and spatial and temporal patterns in fish distribution underpins many of the functional characteristics of estuarine ecosystems van der Meulen, D.E. 22 Chapter 1: General Introduction

(Gillanders et al. 2003; Green et al. 2006; Irlandi and Crawford 1997; Winemiller and

Jepsen 1998). Biophysical drivers of fish movement can include physico-chemical conditions, habitat extent and quality and biotic factors. These factors concomitantly affect habitat and space use, the distribution of individuals along the estuary (Gannon et al. 2015; Moles and Norcross 1995; Payne et al. 2013; Payne et al. 2015a), and reproductive timing and locations (Dahl et al. 2004; Lowerre-Barbieri et al. 2013; van der Meulen et al. 2014). For example the influence of freshwater inflow to estuaries may produce a cascade of effects on estuarine fisheries harvest (Gillson et al. 2009).

Movements and spatial distribution of individuals often vary in conjunction with ontogenetic changes and important life history phases, including reproduction, feeding, and predation or mortality. Animals show preference for physical and ecological environments which increase an individual’s chances of survival and reproductive success (Doligez et al. 1999; Orians and Wittenberger 1991; Saucier and Baltz 1993).

Therefore, site fidelity can be present in both resident and migrating species and can include association with locations that are used for residence, staging, moulting and reproduction. Fish may display ontogenetic shifts in movement and distribution which generally occurs with the onset of sexual maturity (Childs et al. 2008a; Childs et al.

2008c; Taylor et al. 2006), and this may indicate variability in behaviour and interactions within populations (Nilsson 2006). Additionally, fish size can also affect the impact of environmental variables on movement (Taylor et al. 2006). One of the biological factors with the greatest influence on movement and distribution is reproduction or reproductive season (Danylchuk et al. 2011; Dean et al. 2014; Domeier and Colin 1997; Lowerre-Barbieri et al. 2014; Lowerre-Barbieri et al. 2016). During this time many estuarine fish have been found to migrate or alter their position in the van der Meulen, D.E. 23 Chapter 1: General Introduction

estuary (Crook et al. 2010; Reinfelds et al. 2013; Walsh et al. 2013b), and/or form aggregations (Lowerre-Barbieri et al. 2014; Parsons et al. 2009). The location and timing of spawning events ultimately impacts the environmental conditions to which eggs and larvae are exposed, and their overall reproductive success (Lowerre-Barbieri et al. 2017).

Environmental variables have been found to influence the distribution of fish within estuaries (Childs et al. 2008b; Sakabe and Lyle 2010; Walsh et al. 2013b). For example: thermal and osmoregulatory optima of fish can directly influence the distributions through range limitations (Payne et al. 2016; Serrano et al. 2010; Walsh et al. 2013b).

Seasonal changes in temperature can impact fish activity and energetics (Gannon et al.

2014) and reproductive timing (Taylor et al. 2014). Tidal flow can trigger movements and timing of spawning events (Childs et al. 2008c; Garratt 1993; Gibson 2003; Næsje et al. 2012). One of the greatest disruptions to the abiotic conditions within estuarine systems is large, short-term influxes of freshwater from heavy rainfall events. These large freshwater flow events can rapidly decrease salinity, alter temperature and pH, increase water velocities, nutrient load, organic input and turbidity and alter dissolved oxygen concentrations and olfactory cues (Payne et al. 2013; Whitfield 2005).

Responses to increased freshwater flow include, migration downstream towards the estuary entrance (Sakabe and Lyle 2010; Taylor et al. 2014; Walsh et al. 2013a), reversal of circadian rhythms (albeit temporarily) (Payne et al. 2013), altered predatory behaviour in response to altered prey behaviour and distributions (Payne et al. 2015b), and conducting spawning migrations (Reinfelds et al. 2013).

van der Meulen, D.E. 24 Chapter 1: General Introduction

Human beings have had an increasing impact on earth’s ecosystems and natural ecological processes (Alberti et al. 2003). Fish movements and distributions can be adversely impacted by fishing practices, pollution inflow, habitat alteration, introduced species, river regulation and climate change (Aarts et al. 2004; Booth et al. 2011;

Cloern 2001; Gillanders et al. 2011; Lindley et al. 2011). This may further modify interactions within and among species, which can alter processes such as hybridisation

(Roberts et al. 2010; Seehausen et al. 2008), and affect predator-prey interactions

(Payne et al. 2015a), competitive interactions (Westley et al. 2010), and spawning success (Dean et al. 2012).

Fishing and habitat alteration can have major impacts on spawning and population structure in aquatic environments (Palm et al. 2007; Pedersen et al. 2009; Sala et al.

2001). This is particularly evident in modified and heavily urbanised estuaries where shoreline modification and habitat degradation commonly occur. Degradation of spawning habitat has resulted in the significant decline of fish populations worldwide

(Collins et al. 2000; Lindley et al. 2011; Madenjian et al. 2011; Renaud 1997; Sear

1993). The implications of altering key spawning habitat of fish include increased stress

(Schreck et al. 2001), altered predator–prey interactions (Crowder and Cooper 1982), decreased spawning success (Hickford and Schiel 2011) and reduced habitat carrying capacity (MacKenzie et al. 2003). Alternatively, the presence of quality habitat has been linked to the increased success of spawning events and improved recruitment of juveniles for several fish species (Palm et al. 2007; Pedersen et al. 2009).

Ultimately, the drivers of fish movement and distribution are both interactive and complex, but our appreciation of these factors is improving through the development van der Meulen, D.E. 25 Chapter 1: General Introduction

and application of technologies that can resolve positional information for aquatic biota over large temporal and spatial scales (Hussey et al. 2015). This provides the data necessary to define species home range, habitat preferences and site fidelity, and contributes to our understanding of ecosystem function (Donaldson et al. 2014), as well as the consequences of environmental and anthropogenic disturbances (Dean et al.

2012; Payne et al. 2015a; Rice 2005) and the design of effective spatial management measures (Curley et al. 2013; Kramer and Chapman 1999; Palumbi 2004; Zeller 1997).

1.3 Spawning dynamics of fish

Successful spawning involves a wide range of reproductive strategies and behaviours, and appropriate environmental conditions. Fish stocks naturally display high levels of inter-annual variability, which is mostly driven by variation in recruitment. During the early 19th century, Hjort (1914) proposed the “Critical Period” hypothesis which proposed that recruitment magnitude was largely driven by a critical time window during which newly hatched larvae must acquire food. This was supported by the

“Aberrant Drift” hypothesis, which highlights the potential impact of unfavourable dispersal of larvae and juveniles by currents on recruitment. This work paved the way for a number of subsequent hypotheses that contribute to models of population dynamics and fish stock variation. It is now generally acknowledged, that not one but a combination of different biological and physical factors combine to influence juvenile recruitment into the adult population (see review by Houde 2008). For example, the timing of spawning events and the selection of spawning habitat can influence the biotic, hydrographic and physicochemical conditions to which eggs and larvae are exposed (Bilton et al. 2002; Epifanio and Garvine 2001; Jenkins et al. 2015; Sponaugle van der Meulen, D.E. 26 Chapter 1: General Introduction

et al. 2002; van der Meulen et al. 2014). This in turn affects hatching success, larval survival, predator/prey interactions and advection, and overall recruitment success, connectivity, genetic diversity and population structure (Checkley et al. 1988; Houde

2008; Lowerre-Barbieri et al. 2014; Rohrs et al. 2014; Sponaugle et al. 2002).

Larval dispersal of estuarine fishes may be simplified into two core strategies: 1) larval retention, in which larvae are retained within their estuary of origin; or 2) larval export, where eggs and newly hatched larvae are exported from the estuary to coastal regions, and return to estuarine waters in the late larval, early post larval and juvenile stages (see review by Bilton et al. 2002). These strategies are achieved through timing and location of spawning, egg buoyancy, larval stage duration, vertical and horizontal swimming behaviour of larvae, and the use of various abiotic cues to stimulate certain behaviours

(Sponaugle et al. 2002). This can contribute to the flow of genetic material between estuaries, or influence speciation (Bilton et al. 2002). Examples highlighting the timing and location of spawning events have been described for fish (Garratt 1993; Gladstone

2007) and crustaceans (Lynch and Rochette 2007; Paula 1989), often in relation to rhythmic fluctuations such as lunar, tidal and circadian rhythms. Ultimately, species have evolved these strategies to aid the survival and recruitment of offspring.

In estuaries, temperature and freshwater inflow are thought to be particularly important in larval survival and recruitment success (Ferguson et al. 2008; Houde 1987; Walsh et al. 2010; Whitfield 1994). However, the exact mechanisms driving recruitment are poorly understood. Recruitment variability has been suggested to be caused by variation in the numbers of spawning adults (Hughes et al. 2000), the condition of adults

(McDermott et al. 2011), egg and larval survival (Richmond and Woodin 1996), van der Meulen, D.E. 27 Chapter 1: General Introduction

predation (Bailey and Houde 1989), larval transport (Melville-Smith et al. 1981), larval cues directing larvae towards nursery grounds (McDowall and Eldon 1980; Sponaugle et al. 2002), and the location or distribution of spawning sites (Begg and Marteinsdottir

2002). Defining adult spawning dynamics and behaviour will aid in developing a clearer understanding of these interacting factors in dispersal and recruitment of estuarine- dependent organisms.

The identification of the spatio-temporal aspects of spawning events can assist the development of sustainable harvest and conservation strategies that help maintain the abundance and distribution of aquatic organisms in the wild. Protection measures specifically targeted at spawning individuals have been shown to have positive effects on population structure (Palm et al. 2007; Pedersen et al. 2009; Taylor et al. 2012); however, evaluation of the effects of such strategies are rare. Such measures include habitat protection and rehabilitation (Langler and Smith 2001), spatial and temporal fishing closures (Domeier and Colin 1997; Lindeman et al. 2000) and marine protected areas (Berkeley et al. 2004; Sala et al. 2002), and should be prioritised where anthropogenic activities have been shown to disrupt spawning dynamics.

1.4 Estuarine-dependent fishes

This project focused on fish species that are estuarine-dependent, having both juvenile and adult dependency on estuarine ecosystems, and for which there is little known about their spawning dynamics or general movement patterns throughout the spawning period.

The study species also had to be large enough to carry an acoustic transmitter as adults.

In addition, all species studied were of recreational or commercial importance. van der Meulen, D.E. 28 Chapter 1: General Introduction

1.4.1 Estuary Perch

Estuary Perch, Percalates colonorum (Figure 1.1), are a catadromous percichthyid,

(previously Macquaria colonorum Near et al. 2012), which inhabit estuaries of south- eastern Australia (SE). The species is a popular recreational sport-fish (McDowall

1996), and resides in estuarine waters from northern New South Wales around the south eastern coastline to South Australia (but has also been recorded from northern

Tasmania). Estuary Perch feed primarily on decapods and teleost as well as aquatic and terrestrial invertebrates (Howell et al. 2004). The species spawns throughout the Austral winter (June–August) and displays a group synchronous, multiple batch, broadcast spawning strategy (Walsh et al. 2011). Estuary Perch reach maturity (L50) at a size of

25.05 cm and 22.21 cm FL and an age of 3.75 and 3.28 years for females and males respectively (Walsh et al. 2011). Throughout this period, individuals generally make large-scale (up to 50 km) multiple putative spawning migrations from upstream residencies to specific marine-dominated locations close to river entrances (McCarrager and McKenzie 1986; Walsh et al. 2012a; Walsh et al. 2013b; Williams 1970). Estuary

Perch aggregate and exhibit high levels of site fidelity at these downstream locations, however it is unknown what specific habitats are used by aggregating Estuary Perch, and whether and when spawning occurs in these areas. These factors are essential for defining the spawning strategy for this species.

van der Meulen, D.E. 29 Chapter 1: General Introduction

Figure 1.1 Estuary Pech, Percalates colonorum. ©B.Yau.

van der Meulen, D.E. 30 Chapter 1: General Introduction

1.4.2 Yellowfin Bream, Black Bream and their hybrids

Yellowfin Bream, Acanthopagrus australis (Günther) (Figure 1.2), are an estuarine- dependent sparid endemic to the east coast of Australia, with a distribution ranging from northern Queensland to central Victoria. It is a protandrous hermaphrodite (Buxton and

Garratt 1990) and likely spawns in shallow coastal waters (Pollock 1982a; Pollock

1984). They feed on molluscs, crustaceans, worms, fish and ascidians. Juvenile and adults reside within estuaries, with both life-stages occupying a wide range of habitats, including rocky reefs, soft sediment, large woody debris, mangroves and seagrass, from freshwater reaches of rivers to the estuary channel opening to the ocean. However, there is a paucity of information regarding movements and distributions of Yellowfin Bream within estuaries across annual time-scales. Tag-recapture studies on Yellowfin Bream suggest limited movement of both adults and juveniles (Pollock, 1982a), however small numbers of Yellowfin Bream have been observed to travel large distances, often corresponding with spawning periods (Pollock 1982a; Pollock 1982b). Yellowfin

Bream have been shown to all reach maturity by the size of 20.5 cm within Morton Bay in southern Queensland (Pollock 1982a). The spawning period is variable along the east coast of Australia, with spawning occurring between May and September in Moreton

Bay (Pollock 1982b). In contrast, based on timing of juvenile recruitment to seagrass beds, a spawning period of June to December is assumed in the southern parts of the species range (Gray et al. 2000; Griffiths 2001; McNeill et al. 1992; Rotherham and

West 2002).

van der Meulen, D.E. 31 Chapter 1: General Introduction

Figure 1.2 Yellowfin Bream, Acanthopagrus australis. ©B.Yau.

The closely related congener, Black Bream (Acanthopagrus butcheri), is morphologically similar to Yellowfin Bream (Roberts et al. 2009), but is distributed from southern New South Wales to south-western Western Australia (as far north as the

Murchison River). This species is strictly estuary-dependent as it is thought to complete its entire lifecycle within a single estuary, and is known to thrive in intermittently closed and open estuarine systems. Black Bream within the Swan River, Western Australia, have been found to reach maturity (L50) at 21.8 and 21.2 cm for females and males, respectively (Sarre and Potter 1999). Spawning occurs from August to January, within smaller creeks located towards the upper reaches of estuaries (Haddy and Pankhurst

1998; Hindell et al. 2008; Ochwada-Doyle et al. 2012; Walker and Neira 2001).

Co-occurring Yellowfin Bream and Black Bream are known to hybridise (Roberts et al.

2009; Roberts et al. 2010), especially within systems in southern NSW and eastern van der Meulen, D.E. 32 Chapter 1: General Introduction

Victoria that experience intermittent estuary-mouth opening and closing to the ocean.

Estuaries in this area support predominantly Acanthopagrus spp. hybrid complexes, with fewer purebred Black Bream (Roberts et al. 2011a) (D.G. Roberts, unpublished data). These fish have been found to reach sexual maturity (L50) at 15.88 cm for both sexes (Ochwada-Doyle et al. 2012). Hypothesised implications for purebred Black

Bream is that isolated populations may be genetically swamped through Yellowfin

Bream introgression. Primary causes are thought to be anthropogenic changes to population sizes of Black Bream from fishing pressure and modification to estuary opening and closing regimes (Roberts et al. 2010). Nevertheless, there is the possibility that hybridisation between these species is a natural and ancient phenomenon unrelated to anthropogenic impacts. Characterising divergent movement patterns within this hybrid complex will provide novel insights into the dynamics of hybridisation.

1.4.3 Sand Whiting

Sand Whiting Sillago ciliata (Cuvier, 1829) (Figure 1.3), is an estuarine-dependent sillaginid with a broad distribution encompassing the tropical and temperate regions along the entire east coast of mainland Australia, as well as Tasmania, Lord Howe

Island, New Caledonia, Woodlark Islands, and southern Papua New Guinea (Fishbase

2015). The species primarily inhabits inshore and estuarine sediment environments, and is heavily exploited by both recreational and commercial fisheries (Henry and Lyle

2003; Rowling et al. 2010a; West et al. 2015). Sand whiting prey on benthic crustaceans and polychaetes. Their light yellow and silver colouration and elongated body enables them to hunt in shallow sediment habitats, while reducing the risk of predation. Sand Whiting reach maturity (L50) at a size of 19.13 cm and 17.07 cm FL van der Meulen, D.E. 33 Chapter 1: General Introduction

and an age of 1.63 and 1.1 years for females and males respectively (Ochwada-Doyle et al. 2014). In south-eastern Australia, Sand Whiting have an optimum temperature for reproductive growth and locomotor performance of ~26°C (Payne et al. 2016), and this equates to an optimal spawning period that encompasses the austral summer. The spawning period varies with latitude, from eight months in the northern NSW to < four months in southern NSW (Burchmore et al. 1988; Cleland 1947; Ochwada-Doyle et al.

2014; Payne et al. 2016). Commercial harvest tends to peak during summer for Sand

Whiting (Rowling et al. 2010a), which coincides with peak spawning activity. The targeting of spawning aggregations has been found to have detrimental consequences for recruitment, population structure, and aggregation distributions in fishes (Dean et al.

2012; Sadovy and Domeier 2005); however, there is no information available on the ecology of Sand Whiting to assess this.

Figure 1.3 Sand Whiting, Sillago ciliata. ©B.Yau.

van der Meulen, D.E. 34 Chapter 1: General Introduction

1.5 Thesis objectives

The main objective of this thesis was to examine how biophysical variables impact the movements and spawning dynamics of estuarine fish by integrating acoustic telemetry with biological, physical and environmental data. The specific objectives of this thesis were:

1. Investigate the habitat requirements and spawning dynamics of Estuary Perch,

Percalates colonorum during the breeding season in an area identified as a

putative spawning ground.

2. Combine genetic analysis of Acanthopagrus spp. and acoustic tracking of fish

movements to understand several aspects of the spatial ecology of this species

complex. These findings are interpreted in the context of understanding

hybridisation dynamics through interbreeding and large-scale movements.

3. Determine adult movements and spatial and temporal patterns of Sand Whiting

spawning in relation to physico-chemical variation within two major estuaries in

southern New South Wales.

4. Investigate the fine-scale habitat requirements and movement characteristics of

Sand Whiting, during and outside of the breeding season at areas identified as

downstream spawning grounds and upstream resident locations.

van der Meulen, D.E. 35 Chapter 2: Habitat and spawning of Percalates colonorum

Chapter 2: Habitat requirements and spawning strategy of an

estuarine-dependent fish, Percalates colonorum

Abstract

Determining the links among estuarine hydrography, habitat and spawning of estuarine- dependent fish is essential for understanding reproductive dynamics, recruitment processes and directing conservation efforts. Acoustic tracking was used to evaluate fine-scale spatial and temporal patterns in spawning activity of Percalates colonorum

(Estuary Perch) within the Shoalhaven River, south-eastern Australia. Plankton tows were used to determine the timing of spawning events. Tagged P. colonorum exhibited movements restricted to areas of structurally complex large wooden debris and a concrete ferry landing. Egg counts confirmed that spawning events coincided with adult aggregations, whereas egg abundances peaked at night during the first 2 h of the run-out tide. I postulate that spawning and recruitment success of P. colonorum is attributable to its selective spawning habitats that are (1) structurally complex to provide refuge and protection from predation, as well as congregate prey items, (2) adjacent to deep water of high velocities to maximise egg dispersal and (3) in close proximity to river entrance to facilitate coastal dispersal of eggs and inter-estuarine connectivity of larvae.

van der Meulen, D.E. 36 Chapter 2: Habitat and spawning of Percalates colonorum

2.1 Introduction

The identification of the timing, duration and habitats of fishes during spawning events is important in understanding ecological processes that underpin a species population dynamics (Sponaugle et al. 2002). Such knowledge can assist the development of conservation strategies, including habitat protection and rehabilitation (Langler and

Smith 2001), spatial and temporal fishing closures (Domeier and Colin 1997; Lindeman et al. 2000) and marine protected areas (Berkeley et al. 2004; Sala et al. 2002), that help maintain the abundance and distribution of aquatic organisms in the wild. Protection measures specifically targeted at spawning individuals have been shown to have positive effects on population structure (Palm et al. 2007; Pedersen et al. 2009; Taylor et al. 2012); however, evaluation of the effects of such strategies are rare. Effective protection of fish habitat is particularly important where anthropogenic activities can disrupt spawning dynamics.

Fishing and habitat alteration have been found to have major impacts on spawning and population structure of organisms in aquatic environments (Palm et al. 2007; Pedersen et al. 2009; Sala et al. 2002). This is particularly evident in modified and heavily urbanised estuaries where shoreline modification and habitat degradation commonly occur. Degradation of spawning habitat has resulted in the significant declines of populations worldwide (Collins et al. 2000; Lindley et al. 2011; Madenjian et al. 2011;

Renaud 1997; Sear 1993). The implications of altering key spawning habitat of fish include increased stress (Schreck et al. 2001), altered predator–prey interactions

(Crowder and Cooper 1982), decreased spawning success (Hickford and Schiel 2011) and reduced habitat carrying capacity (MacKenzie et al. 2003). Alternatively, the van der Meulen, D.E. 37 Chapter 2: Habitat and spawning of Percalates colonorum

presence of quality habitat has been linked to the increased success of spawning events and subsequent recruitment of juveniles for several fish species (Palm et al. 2007;

Pedersen et al. 2009).

Knowledge of the timing and location of spawning events is essential to understand the biological, physical, environmental and ecological processes that underpin spawning success. The timing and location of spawning events, combined with knowledge of local transport mechanisms, are required to understand larval dispersal (Bilton et al.

2002). Timing and location of spawning events have been described in fish (Garratt

1993; Gladstone 2007) and crustaceans (Lynch and Rochette 2007; Paula 1989) and have been linked to lunar, tidal and circadian rhythms. The timing and location of these events have evolved for each species to benefit survival and recruitment of offspring.

However, the exact mechanisms driving recruitment are poorly understood. Recruitment variability has been suggested to be caused by variation in the numbers of spawning adults (Hughes et al. 2000), the condition of adults (McDermott et al. 2011), egg and larvae survival (Richmond and Woodin 1996), predation (Bailey and Houde 1989) larval transportation (Melville-Smith et al. 1981) and larval cues directing larvae towards nursery grounds (McDowall and Eldon 1980; Sponaugle et al. 2002). Further understanding of adult spawning dynamics and behaviour will aid in developing a clearer understanding of these interacting factors in dispersal and recruitment of estuarine-dependent organisms.

The catadromous percichthyid, Percalates colonorum (commonly known as Estuary

Perch), previously Macquaria colonorum (Near et al. 2012), inhabits estuaries of south- eastern Australia (SE) where it is a key recreational sport-fishing species (McDowall van der Meulen, D.E. 38 Chapter 2: Habitat and spawning of Percalates colonorum

1996). The species spawns throughout the Austral winter (June–August) and displays a multiple broadcast spawning strategy (Walsh et al. 2011). Throughout this period, individuals generally make large-scale (up to 50 km) multiple putative spawning migrations from upstream residencies to specific marine-dominated locations close to river entrances (McCarrager and McKenzie 1986; Walsh et al. 2012a; Walsh et al.

2013b; Williams 1970). P. colonorum aggregates and exhibits high levels of site fidelity at these downstream locations. However, it is unknown what habitats are utilised by aggregating P. colonorum, and whether and when spawning occurs, or takes place in these areas. An understanding of these characteristics is needed to determine specific spawning requirements and subsequent spawning success for this species.

The present study investigated the habitat requirements and spawning dynamics of P. colonorum during the breeding season in an area identified as a putative spawning ground. Specifically, this study evaluated (1) fine-scale spatial and temporal distribution of P. colonorum to identify their key habitat usage; and (2) the spawning strategy of P. colonorum by examining temporal variations in abundance of eggs in spawning grounds.

2.2 Methods

2.2.1 Study site

The present study was conducted in the Shoalhaven River (34°53′S, 150°45′E), SE

Australia (Figure 2.1). The river consists of a 48-km estuary between the entrance and the tidal limit, and an upper 27-km freshwater section to the base of the Tallowa Dam. van der Meulen, D.E. 39 Chapter 2: Habitat and spawning of Percalates colonorum

Since European settlement, the river has had extensive modification. First, during the

1800s, the river course was altered by connecting the Shoalhaven River to the adjacent

Crookhaven River, which resulted in the progressive closing of the original Shoalhaven

River entrance. Today the Shoalhaven River flows to the sea via the Crookhaven River entrance. Second, Tallowa Dam was constructed in 1976, which resulted in a reduced, and regulated, river flow regime. Much of the lands adjacent to the estuary section have been cleared for agriculture and small industrial and urban areas. The lower estuary section has very minimal natural riparian vegetation and because of extensive erosion, much of the riverbank consists of rock training walls (Figure 2.1).

The present study focused on the putative spawning grounds for P. colonorum identified by Walsh et al. (2012a), which are located between 3.5 and 6.9 km of the river entrance.

This section of river is typically marine dominated, except during large freshwater flows. It contains about a 1-km area of natural vegetation, some small patches of mangrove and salt marsh, and a cable ferry crosses the river within this area.

2.2.2 Mapping subtidal habitat

Maps of subtidal habitat throughout the sampling area (Figure 2.1) were produced using multiple data sources, including existing bathymetric (New South Wales Office of

Water, Unpubl. Data) and macrophyte maps (New South Wales Department of Primary

Industries, Fisheries Spatial Database: https://webmap.industry.nsw.gov.au), aerial imagery, depth sounding and side scan sonar data (Lowrance HDS-5, Navico, Lysaker,

Norway), as well as visual GPS surveys. Data were combined using ArcGIS v. 9.3

(ESRI, Redlands, California) to provide a composite representation of the main habitat van der Meulen, D.E. 40 Chapter 2: Habitat and spawning of Percalates colonorum

types present in the study area during the tracking periods. All data was compared and any differences between habitats were updated from the most recently acquired data.

Subtidal habitats represented a mosaic of simple and complex natural and artificial habitats. The main river channel was dominated by soft sediment, and surrounding littoral habitats included rock training walls in the upstream half on the study area, and localised areas of seagrass, mangrove and salt marsh, in a descending order of area

(Figure 2.1). A small section of subtidal habitat directly adjacent to the only remaining riparian vegetation within the study area consisted of fallen trees, which were classified as either large wooden debris (LWD) or small wooden debris (SWD) with a surface area greater than or less than 4 m2, respectively. Additional artificial habitat was provided by a cable ferry that crossed the river in the upstream section of the study area and consisted of two large concrete landings and the ferry itself. Other artificial habitat present included moored boats, mooring blocks and navigation buoys.

2.2.3 Tagging

Twenty Percalates colonorum individuals were captured using hook and line (artificial lure) and tagged with acoustic transmitters. These included 14 internally implanted 69- kHz Vemco V13-1L (dimensions = 36 mm × 13 mm Ø, weight = 11 g) or V13TP-1L

(dimensions: 45 mm × 13 mm Ø, weight = 12 g) coded transmitters (Amirix Systems,

Halifax, Nova Scotia, Canada), and six externally attached Sonotronics IBT 96-1

(dimensions: 25 mm × 8 mm Ø, weight = 1.5 g) continuous transmitters (Sonotronics,

Tuscon, Arizona, USA). Coded Vemco transmitters were surgically implanted in fish between September 2007 and December 2008 (for large-scale movements and surgery van der Meulen, D.E. 41 Chapter 2: Habitat and spawning of Percalates colonorum

details, see Walsh et al. 2012). Continuous Sonotronics transmitters (IBT-96-1) used frequencies between 73 and 78 kHz and a unique ping sequence and ping space to identify individuals. Each Sonotronics transmitter (IBT-96-1) was mounted to a

Hallprint (TBA-2) T-bar (Hallprint, Hindmarsh Valley, South Australia) external tag with nylon thread, and coated in epoxy resin (Roberts et al. 2011b). External tagging was conducted between 18 July and 5 August 2009. Fish were anesthetised using 23mg

L–1 of Aqui-S (Aqui-S New Zealand Ltd., Lower Hutt, New Zealand) and external tags were attached to the dorsal margin between the lateral line and the dorsal fin, in line with approximately the 4th or 5th dorsal spine by using an Avery Dennison Tagfast III tagging gun (Avery Dennison Corporation, California, USA). External tagging was chosen over surgical implantation of continuous transmitters to reduce recovery times

(owing to short battery life) and to minimise potential impacts on behaviour of imminently spawning fish. Fish tagged included 10 males, seven females and three unsexed, with mean (± s.e.) fork length (FL) of 322.8 mm (± 8.6 mm). All fish tagged were above mean size at maturity (male L50 = 22.21cm, female L50 = 25.05cm; Walsh et al. 2011).

2.2.4 Fish tracking

Fish with coded and continuous transmitters were monitored using active tracking.

Signals were received and decoded using a Vemco VR100 acoustic receiver and a

VH110 directional hydrophone (Amirix Systems, Halifax, Nova Scotia, Canada; automatic gain setting) mounted on the side of an open-hull aluminium boat. Tracking of fish was undertaken between 21 July and 12 August 2009, over two continuous 48-h tracking periods occurring around the new moon and full moon (commencing on 21 van der Meulen, D.E. 42 Chapter 2: Habitat and spawning of Percalates colonorum

July and 5 August, respectively). Tracking was restricted to an area determined from a previous telemetry study as a potential winter spawning aggregation site and was conducted over the new moon and full moon periods as this was when peak abundances of fish occurred (Walsh et al. 2013b). Continuous tracking involved surveying the length of the study area by using a linear search pattern, driving mid-river until an individual was identified. A position fix for individuals was determined by manoeuvring the boat and rotating the directional hydrophone until the strongest signal

(dB measured on the VR100) was achieved. Individual identification, date, time and

GPS coordinates were recorded for each fish. This process was repeated until all fish within the tracking area were located. In total, 50 runs of the tracking area were conducted continuously during each 48 h sampling period.

2.2.5 Percalates colonorum egg abundance

Temporal variation in the relative abundance of P. colonorum eggs adjacent to aggregation sites (as determined from the active tracking) was investigated. A circular plankton net (1-m Ø × 1.5 m length, 50 µm mesh, towed at a speed of 6 kn for 15 s at 3 m depth) was used to sample eggs. Five replicate tows were made each hour over 48 h periods during the full moon and new moon, commencing at 12:00 p.m. on 26 July and

10 August 2010, respectively. Tow depths were selected from examination of mean P. colonorum depths within the study area derived from long-term passive tracking

(unpublished data) and because P. colonorum spawns neutrally buoyant pelagic eggs

(Gunasekera and De Silva 2000). Start and finish locations were determined using GPS, and flow meter readings were used to standardise tows. Samples were stored on ice in sample jars and all P. colonorum eggs were identified, counted, staged (Jones et al. van der Meulen, D.E. 43 Chapter 2: Habitat and spawning of Percalates colonorum

1978) and measured. Depth-stratified environmental variables (temperature, salinity, dissolved oxygen) were recorded hourly at a fixed location central to plankton tows at the deepest section of the river.

2.2.6 Data analysis

Position data derived from tracking was projected into Universal Transverse Mercator

(Zone 56) geographic coordinate system. Weighted kernel density (KD) distributions were estimated for each fish during each tracking period by the kernel density estimate

(kde) routine in Geospatial Modelling Environment (Beyer 2012; R Development Core

Team 2013), using a Gaussian (bivariate normal) kernel estimator and the plug-in bandwidth estimator. Four bandwidth estimators were trialled, including (1) least- squares cross-validation (LSCV), (2) biased cross-validation (BCV), (3) plug-in and (4) smoothed cross-validation (SCV). Resulting distributions were inspected, and the plug- in estimator (Jones et al. 1996) was found to best represent the distribution of the position data and was used for the full analysis. Core and total utilisation areas of tracked fish were calculated from the 50% and 90% KD isopleths, respectively (Börger et al. 2006, calculated using ArcGIS v. 10), and are subsequently referred to as utilisation distributions (UD). Counts were made of the number of core and total UDs which were determined as having distinct, separation between the calculated areas for each tracked fish.

The area of each habitat within core and total UDs were calculated from habitat maps using ArcGIS v. 10. A habitat selection index (HI) was derived for each fish as a ratio of the habitat present within the UD’s and the total habitat present within each tracking van der Meulen, D.E. 44 Chapter 2: Habitat and spawning of Percalates colonorum

area (Manly et al. 2002). Habitat selection was evaluated using a single-factor ANOVA, which compared HI across the habitats described above (fixed; five levels: LWD, rockwall habitat, sediment, SWD and ferry). Habitat-selection indices from three fish were randomly selected for each level of habitat, to maintain sample independence among factor levels and separate ANOVAs were used for core and total UD, and lunar period.

Any significant differences among levels of habitat were evaluated using Student–

Neumann–Keuls (SNK) tests.

Percalates colonorum egg-abundance data were expressed as egg density for each individual plankton tow. Egg density was compared between lunar phases (fixed; 2 levels: full and new) and among tidal periods (fixed; four levels: low tide, high tide, incoming tide and outgoing tide). Data were log(x + 1) transformed and a Euclidian similarity matrix was calculated from sample data. Data were analysed according to the above design, using a two-factor permutational analysis of variance (PERMANOVA,

Anderson 2001).

van der Meulen, D.E. 45 Chapter 2: Habitat and spawning of Percalates colonorum

Figure 2.1 (a) Study-site location and detailed map of the Shoalhaven River, showing (b) bathymetry, (c) subtidal habitat, (d) July new moon tracking period-weighted population utilisation distributions and (e) August full moon tracking period-weighted population. Habitats are not to scale and were enlarged for display purposes. van der Meulen, D.E. 46 Chapter 2: Habitat and spawning of Percalates colonorum

2.3 Results

Fifteen and sixteen fish were detected within the study area during the new moon and full moon intensive tracking periods, respectively. Of these, 11 fish were common to both tracking periods. Individuals occasionally moved into and out of the study area during both intensive tracking periods, which resulted in tracking durations ranging from 2.3 to 46.5 h and 11.7 to 45.6 h for the new moon and full moon periods, respectively. Mean (± s.e.) detections for all individual fish tracked equalled 17.27 (±

4.00, n = 15) and 25.44 (± 3.89, n = 16) for the new moon and full moon tracking periods, respectively.

2.3.1 Home range and habitat selection

Individual core and total UD areas were highly variable across the new moon and full moon tracking periods (Table 2.1). Core and total UD areas averaged (± s.e.) 1924 m2

(± 157) and 5132 m2 (± 805) for the new moon tracking period and 1614 m2 (± 125) and

3465 m2 (± 462) for the full moon tracking period, respectively. During the new moon period, only 20% of P. colonorum displayed more than one core UD, whereas 50% displayed more than one during the full moon tracking period (Table 2.1). No apparent relationship was found between UD area and lunar phase (Core UD: F1,13 = 2.397, p >

0.05; Total UD: F1,13 = 3.655, p > 0.05), sex (Core UD: F1,13 = 0.794, p > 0.05; Total

UD: F1,13 = 0.237, p > 0.05) or core UD for tag type (F1,14 = 4.667, p > 0.05) There was a significant difference between total UD area for the different tag types (F1,14 = 5.19, p

< 0.05).

van der Meulen, D.E. 47 Chapter 2: Habitat and spawning of Percalates colonorum

Table 2.1 Summary of Percalates colonorum tagging data and home range from downstream spawning grounds within the Shoalhaven River for the July new moon and August full moon tracking periods. Core and total utilisation distributions (UD) represent the area and number of 50% and 90% kernel density isopleth, respectively. Nc = the number of separate core UD areas, Nt = the number of separate total UD areas. FL, fork length; F, female; M, male. Fish FL Sex Tag Type July new moon August full moon ID (mm) Core UD Total UD Core UD Total UD Area Area Area Area 2 2 2 2 (m ) Nc (m ) Nt (m ) Nc (m ) Nt 1 290 M Continuous 1923.81 1 8761.82 2 1680.04 1 5563.99 5 2 260 M Continuous 2113.41 1 8311.30 2 833.00 1 1072.56 1 3 294 M Continuous 1986.98 1 9462.70 1 4 395 F Continuous 2107.15 2 9325.01 2 1781. 12 2 2973.36 1 5 295 M Continuous 1801.62 1 2478.67 1 6 366 F Continuous 2444.68 1 4738.71 1 7 358 M Coded 2219.30 2 8819.31 2 2458.20 2 7712.66 1 8 366 M Coded 1410.71 1 1954.65 1 1362.50 2 3289.96 3 9 327 U Coded 323.90 1 412.39 1 10 276 M Coded 2440.51 1 5220.92 2 1247.07 2 1963.10 2 11 382 F Coded 2320.37 1 5592.12 2 2120.34 4 4942.19 1 12 321 M Coded 2000.24 1 3049.55 1 983.18 1 1437.00 1 13 312 F Coded 2226.97 1 3317.91 1 1199.32 2 1988.28 1 14 314 M Coded 1143.73 1 1562.36 1 15 294 U Coded 2621.97 2 4950.82 1 3 5283.86 2 16 304 F Coded 1486.88 1 2173.46 1 17 300 U Coded 2531.11 1 4069.71 1 1488.45 3 2645.91 1 18 376 F Coded 1846.60 1 4967.38 4 19 326 F Coded 1310.12 1 1979.50 2 20 300 M Coded 1648.17 1 2394.48 2

Fish were not randomly distributed through the tracking area, but were clustered around the following two main areas: (1) the LWD and (2) western ferry landing (Figure 2.1).

Individuals generally associated only with either the LWD or the western ferry landing, rarely associating with both during the tracking periods. Multiple core UDs were observed more often for individuals that associated with the area of LWD.

Habitat-selection indices were generally greatest for LWD, SWD and the ferry and lowest for the rockwall and sediment for core and total UD during the new moon and full moon (Figure 2.2). Seagrass, mangroves, saltmarsh, boat hulls, mooring weights and navigational aids were not associated within any of the UDs during both tracking van der Meulen, D.E. 48 Chapter 2: Habitat and spawning of Percalates colonorum

periods. Significant differences between selection indices for the different habitat types were found for core (F4,10 = 13.43, P < 0.05) and total (F4,10 = 11.92, P < 0.05) UD new moon and the core (F4,10 = 28.95, P < 0.05) and total (F4,10 = 14.50, P < 0.05) UD full moon periods. Post hoc SNK test revealed that selection indices were significantly greater for LWD and the ferry than for all other habitat types, for the core UD during the new moon and total UD during the full moon. However, total UD showed that only

LWD was significantly greater than the other habitat types during the new moon.

Similarly, during the full moon tracking period, core UD selection indices for LWD were significantly higher than those for the ferry, which was significantly higher than those for all the other habitat types.

Figure 2.2 Mean (± s.e.) habitat-selection index (core 50% and total 90% utilisation distribution, UD) for new moon and full moon sampling periods.

van der Meulen, D.E. 49 Chapter 2: Habitat and spawning of Percalates colonorum

2.3.2 Percalates colonorum egg abundance

Peak egg abundances occurred approximately 1 h after high tide at night for both the full moon and new moon sampling periods, after which they progressively decreased to a minimum 3 h later (Figure 2.3). Low numbers of eggs were captured at other times throughout sampling. All P. colonorum eggs captured were in early development, which indicated that they were recently spawned. No late-stage embryos were captured.

Analyses revealed a significant Lunar phase × Tide interaction term (PERMANOVA,

P= 0.02), and pairwise comparisons revealed that this was due to a significantly greater amount of eggs in the water column during the outgoing tide during the full moon

(PERMANOVA, P < 0.05) than during the incoming, low and high tides. A significantly (P < 0.01, PERMANOVA) larger number of eggs was collected during the full moon than the new moon.

van der Meulen, D.E. 50 Chapter 2: Habitat and spawning of Percalates colonorum

Figure 2.3 Mean (±s.e.) number of eggs captured per m3 (column) for each sampling time in relation to tidal height (line) for the full moon and new moon sampling periods.

van der Meulen, D.E. 51 Chapter 2: Habitat and spawning of Percalates colonorum

2.4 Discussion

The current study, in conjunction with a longer-term acoustic-tracking study (Walsh et al. 2012a), successfully identified a spawning location of P. colonorum in a large regulated river. All individuals tracked were assumed to exhibit behaviour typical of that within a spawning population, because their residency, home range and large-scale migrations were similar to those recorded from other studies (Walsh et al. 2012a; Walsh et al. 2013b). The present study revealed clear habitat requirements for P. colonorum within this location, as well as the timing of spawning and location of recently released eggs.

2.4.1 Habitat requirements

Percalates colonorum displayed high levels of site fidelity and small home ranges within the downstream spawning location. Specific areas of wooden debris and the ferry landing were identified as important habitat. Although both habitats differ in the actual structure, they represent the most structurally complex habitats available within the specific area studied. The use of structurally complex habitat as a nesting medium is well known for some substrate spawners. Largemouth bass, Micropterus salmoides, shows preference for structurally complex wooden habitat around which to nest

(Lawson et al. 2011). Similarly, other diadromous fish such as salmonids select areas of increased structural complexity by spawning on gravel beds as opposed to sandy areas

(Coulombe-Pontbriand and LaPointe 2004; Magee et al. 1996). Although structural complexity is a key selection criterion for substrate spawners (Lawson et al. 2011; Nash van der Meulen, D.E. 52 Chapter 2: Habitat and spawning of Percalates colonorum

et al. 1999; Snickars et al. 2010), this has not previously been demonstrated for broadcast spawners such as P. colonorum. There are several reasons why P. colonorum may use structurally complex habitats for spawning and other ecological requirements.

Structurally complex aquatic habitats often provide greater refuge from predators and increased prey densities relative to non-complex habitats (Crook and Robertson 1999;

Crowder and Cooper 1982). In particular, structures identified in association with P. colonorum residency could, therefore, provide refuge from predation as well as a feeding location. P. colonorum has been observed feeding within spawning aggregations because they are targeted by recreational fishers in these areas. Such complex structures can also alter laminar flows, creating pressure waves and eddies of low flow (Crook and Robertson 1999; Fausch 1993; Ottevanger et al. 2012). Therefore, fish may utilise such habitats as resting areas, to conserve energy before spawning and between spawning events. Attraction to heterogeneous complex structures may occur by recognising chemical cues from conspecifics or alternatively, following response to cues emitted by the structures themselves (Marsden et al. 1995; Ueda et al. 1998;

Werner and Lannoo 1994). For example, salmonids are known to follow visual and olfactory cues for homing towards specific habitat to spawn (Ueda et al. 1998).

Therefore, it is possible that structurally complex habitats may provide essential cues or homing markers that enable aggregation of P. colonorum in spawning condition.

Degradation of river-bank habitat, particularly riparian vegetation, and its negative impacts on aquatic organisms is of worldwide concern (Nagayama and Nakamura

2010). Land clearing and development along river shoreline mean that there is very little recruitment of new large wooden debris (fallen trees) into many riverine systems, and the removal of large wooden debris to mitigate flood damage, clear fishing grounds and van der Meulen, D.E. 53 Chapter 2: Habitat and spawning of Percalates colonorum

reduce boating hazards still continues around the world. Extensive habitat modification has occurred within P. colonorum spawning grounds in the Shoalhaven River, and the long-term impacts of this modification are unknown. The area and quality of spawning habitat could be a limiting factor for the number of fish within spawning grounds.

Although not all P. colonorum individuals inhabit the spawning grounds simultaneously

(Walsh et al. 2013b), spawning output may be limited by the number of fish that can physically fit into the area of preferred habitat present within a spawning ground. In situ diver observations suggest that numbers of adult P. colonorum adjacent to large wooden debris far exceed the numbers of fish capable of seeking refuge within them. Moreover, larger individuals were observed to be more common within LWD, with smaller individuals occurring in adjacent less complex structures (D. van der Meulen, pers. obs.). This suggests a potential hierarchy within the preferred habitat where smaller individuals are displaced to lower-quality spawning habitat. Also, the largest aggregations of spawners were observed adjacent to habitat with the largest area and highest structural complexity. By increasing the amount of preferred habitat available to spawners may increase spawning success and subsequent recruitment to P. colonorum populations. However, this depends on whether spawning habitat is the nexus for successful recruitment, relative to other factors such as predation, advection or food supply. Restoration of spawning habitat has been found to have significant effects on the survival and recruitment of juveniles (Palm et al. 2007; Pedersen et al. 2009).

Because of the high level of habitat selection, limited critical habitat and evidence of selection of modified man-made structures, it’s suggested that P. colonorum is a prime candidate for habitat-restoration projects and studies.

van der Meulen, D.E. 54 Chapter 2: Habitat and spawning of Percalates colonorum

I suggest that not only the actual type of habitat and its complexity, but also its specific location, is important as a spawning area for P. colonorum. First, these habitats are adjacent to deep water and releasing eggs in the deepest section of the river potentially reduces the risk of eggs being transported to non-optimal areas such as shallow, low- flow areas, where increased egg mortality could potentially occur (Nicholson et al.

2008). Second, the proximity of these specific spawning habitats to the river entrance provides salinities between 20 and 30 during dry periods. This corresponds to optimal conditions for hatching and development of fertilised P. colonorum eggs (Beckman

1999; Gunasekera and De Silva 2000). Moreover, in SE Australia during winter, higher water temperatures are observed in the ocean- and marine-dominated estuarine areas than in upstream riverine environments (NSW Department of Primary Industries, unpubl. data). Such thermal conditions may also result in faster development of eggs and larvae and enhance potential survival and subsequent recruitment of P. colonorum.

2.4.2 Spawning strategy

The results indicated that P. colonorum populations spawn a large proportion of eggs within 1 h of high tide at night. Alternatively, a diurnal signal may cause spawning to occur at midnight. Tide and time-of-night tend to co-correlate with lunar phase (i.e. the largest tides are nocturnal during the winter full and new moons) which can be an important driver for spawning. Additionally, variation in day length would likely alter the timing of egg releases out of synchronisation with midnight between the sampling events. Caution should be taken in interpreting these results as sampling was only conducted over two lunar events, further sampling throughout the spawning season would provide better insight into the timing of egg releases by this species. Night-time van der Meulen, D.E. 55 Chapter 2: Habitat and spawning of Percalates colonorum

ebb tides present during the Austral winter provide the largest tidal range of any tidal cycle during the identified P. colonorum spawning season (Miller et al. 2006).

Therefore, dispersal may be maximised by spawning during nocturnal high tides. Eggs were captured in progressively lower numbers during the following 2 h, which was probably due to eggs drifting into the sampling area from the other potential spawning site at the ferry landing, just upstream from the egg sampling area. Alternatively, it could be attributed to lower levels of spawning occurring following the peak period.

The low numbers of eggs encountered at other sampling times could be attributed to anomalies in the transport of eggs by back eddies, low flow areas and tidal movement.

P. colonorum eggs generally hatch ~55 h post fertilisation (Gunasekera and De Silva

2000) and it, therefore, appears that dispersal was sufficient to prevent a corresponding peak in egg abundance during the return daytime flood tide.

Variability in spawning output between full moon and new moons could not be determined here because this study sampled only one of each moon phase. Nevertheless, captures of eggs during the July full moon were significantly higher than the August new moon captures. Lunar reproductive cycles and rhythms in larval release have been described in fish and crustacean species (Bueno and Flores 2010; Gladstone 2007; Paula

1989; Takemura et al. 2004), and may account for the variation observed here. It is possible that the lower numbers of eggs captured on the August new moon may have been due to lower abundances of spawning fish. This coincides with observed peaks in the proportion of long-term passively tagged fish within the spawning area during the

July full moon, with lower numbers present during the August new moon (Walsh et al.

2013b).

van der Meulen, D.E. 56 Chapter 2: Habitat and spawning of Percalates colonorum

The locality of the spawning grounds, combined with the timing of spawning, suggests that P. colonorum uses the ebb tide as a primary mechanism to facilitate offshore dispersal of offspring. This corresponds with the larval export strategy (see review of

Bilton et al. 2002), where estuarine organisms migrate to the entrances of estuaries to spawn on nocturnal high tides. Other examples of teleosts using this strategy include

Pagrus auratus (Wakefield 2010) and the estuarine-dependent Acanthopagrus berda

(Garratt 1993). Spawning at the top of the high tide maximises the potential for eggs to be transported to coastal shelf regions, where prevailing currents, tides and winds interact with larval swimming behaviours to disperse pelagic larvae (Bilton et al. 2002;

Sponaugle et al. 2002).

Two distinct genetic populations of P. colonorum have been recorded north and south of Jervis Bay, New South Wales, with little genetic variability within each group

(Shaddick et al. 2011). Moreover, no offshore movements of adult P. colonorum were detected during long-term telemetry studies (Walsh et al. 2012a), although anecdotal offshore movements of adults have been reported in conjunction with large freshwater- flow events (Trinski et al. 2005). Interestingly, the closely related Australian bass,

Percalates novemaculeata, exhibits increasing genetic isolation by distance, particularly at the northern and southern distributions (Jerry and Baverstock 1998; Shaddick et al.

2011). This species has been shown to reside further upstream during its spawning period (Walsh et al. 2012a), which would reduce the possibility of offshore dispersal and increase larval retention (Bilton et al. 2002). Therefore, for the more estuarine- dependent P. colonorum, I suggest that genetic mixing between rivers is likely to occur through dispersal of eggs and larvae and not via adult migrations.

van der Meulen, D.E. 57 Chapter 2: Habitat and spawning of Percalates colonorum

It is generally hypothesised that freshwater flows provide cues for larvae of estuarine species, and the timing and magnitude of freshwater flows can have an impact on rates of recruitment and subsequent fishery yields (Ferguson et al. 2008; Kingsford and

Suthers 1994; McDowall and Eldon 1980; Staunton-Smith et al. 2004; Trnski 2001).

Laboratory experiments have shown selection for estuary and river water over sea water by larval estuarine fish species (James et al. 2008). Indeed, episodic recruitment of P. colonorum has been positively linked to freshwater flows (Walsh et al. 2010).

Therefore, a greater understanding of the implications of the spawning and larval export strategy of P. colonorum, the roles of freshwater flows and their intrusions into nearshore waters, on dispersal and rates of survival of eggs and larvae and subsequent recruitment levels of young-of-the-year back into estuaries is required.

van der Meulen, D.E. 58 Chapter 3: Movements of Acanthopagrus Species Complex

Chapter 3: Estuarine movements in a sparid hybrid complex

Abstract

The movements of purebred and hybrid complexes of species reveal the interactions that facilitate hybridisation and lead to genetic introgression. Acanthopagrus australis

(Yellowfin Bream) and the Acanthopagrus hybrid complex of A. australis and

Acanthopagrus butcheri (Black Bream)were tracked using acoustic telemetry within a south-east Australian estuary. All fish displayed high levels of residency and site- fidelity, with peak distributions occurring in the between 15 and 32km upstream of the river entrance. Offshore movements were recorded for 43% of A. australis and 38% of

Acanthopagrus spp. hybrids but this followed ≈1-2 years of continuous residence within the river. Estuarine movement patterns in A. australis and A. spp. hybrids were significantly related to conductivity, freshwater flow, temperature, genetic classification, and capture location. Distinct repetitive spawning migrations were not observed for either A. australis or A. spp. hybrids. The data suggests that A. australis and A. spp. hybrids may be capable of spawning within estuaries, and irregular adult inter-estuarine migrations appear to play a significant role in the genetic mixing of populations. Future research aimed at identifying spawning locations could help to explain the spawning mechanisms that lead to hybridisation.

van der Meulen, D.E. 59 Chapter 3: Movements of Acanthopagrus Species Complex

3.1 Introduction

Identifying the interaction between estuarine variability and spatial and temporal patterns in fish distribution is important for understanding the functional characteristics of estuarine ecosystems (Gillanders et al. 2003; Green et al. 2006; Irlandi and Crawford

1997; Winemiller and Jepsen 1998). Estuarine fish have flexible behaviours to respond to environmental variability, including variations in water flow, salinity, temperature and habitat (Childs et al. 2008b). One of the greatest disruptions to the abiotic conditions within estuarine systems is large volume, short-term influxes of freshwater driven by large rainfall events. These large freshwater flow events, rapidly decrease salinity and alter temperature and pH, as well as increasing water velocities, nutrient load and turbidity (Payne et al. 2013). In response, fish have been shown to migrate downstream towards the estuary entrance (Sakabe and Lyle 2010; Taylor et al. 2014;

Walsh et al. 2013a), reverse circadian rhythms (albeit temporarily) (Payne et al. 2013) and alter their predatory behaviour in response to altered prey behaviour and distributions (Payne et al. 2015b). Also, studies have shown that seasonal changes in temperature impact fish activity and energetics (Gannon et al. 2014) and reproductive timing (Taylor et al. 2014). Concomitantly, these factors affect habitat and space use by different species, the overall distribution of individuals (Kynard et al. 2000; Moles and

Norcross 1995; Taylor et al. 2006; van der Meulen et al. 2014) and may produce cascading effects on fisheries harvest (Gillson et al. 2009).

While most fish react to biophysical variation in some way, responses are often species- specific and can represent links between important life history stages. Commercial fishing, pollution, habitat destruction and river regulation can impact fish movements van der Meulen, D.E. 60 Chapter 3: Movements of Acanthopagrus Species Complex

and distributions (Aarts et al. 2004; Cloern 2001; Lindley et al. 2011).

Anthropogenically altered distributions may modify interactions between species which could result in changes to hybridisation rates (Roberts et al. 2010; Seehausen et al.

2008). Understanding the movement dynamics and interactions between different species allows improved spatial management of both fish stocks and estuarine ecosystems, and reveal interactions within and between species (Goethel et al. 2011;

Palumbi 2004; Roberts et al. 2009).

Acanthopagrus australis (Günther) (Yellowfin Bream) is an estuarine-dependent species endemic to the east coast of Australia, with a distribution ranging from northern

Queensland to central Victoria. It is a protandrous hermaphrodite (Buxton and Garratt

1990) and likely spawns in shallow coastal waters (Pollock 1982a; Pollock 1984).

Juvenile and adults reside within estuaries, with both life-stages occupying a wide range of habitats, including rocky reefs, unvegetated soft sediment, large woody debris, mangroves and seagrass, from freshwater reaches of rivers to the estuary channel opening to the ocean. However, there is a paucity of information regarding continuous movements and distributions of A. australis within estuaries across annual time-scales.

Tag-recapture studies on A. australis suggest limited movement of both adults and juveniles (Pollock 1982a). However, small numbers of A. australis have been observed to travel large distances, often corresponding with spawning periods (Pollock 1982a;

Pollock 1982b). The spawning period is variable along the east coast of Australia

(Sheaves 2006), with spawning occurring between May and September in Moreton Bay,

Southern Queensland (Pollock 1982b). In contrast, based on the timing of recruitment of juveniles into seagrass beds, a spawning period of June to December is assumed in

van der Meulen, D.E. 61 Chapter 3: Movements of Acanthopagrus Species Complex

the southern parts of the species range (Gray et al. 2000; Griffiths 2001; McNeill et al.

1992; Rotherham and West 2002).

The closely related congener, Acanthopagrus butcheri (Black Bream), is a morphologically similar species to A. australis (Roberts et al. 2009) and is distributed from southern New South Wales to south-western Western Australia, where it occurs as far north as the Murchison River. This species is estuary-dependent in the strictest sense because it is thought to complete its entire lifecycle within a single estuary, and is known to thrive in intermittently closed and open estuarine systems. Spawning occurs from August to January, within smaller creeks located towards the upper reaches of estuaries (Haddy and Pankhurst 1998; Hindell et al. 2008; Ochwada-Doyle et al. 2012;

Walker and Neira 2001).

Where Acanthopagrus australis and A. butcheri co-occur they have been shown to hybridise (Roberts et al. 2009; Roberts et al. 2010), especially within systems in southern NSW and eastern Victoria that experience intermittent estuary-mouth opening and closing to the ocean. Estuaries in this area support predominantly Acanthopagrus spp. hybrid complexes, with fewer purebred A. butcheri (Roberts et al. 2011a) (D.G.

Roberts, unpublished data). Hypothesised implications for purebred A. butcheri are that isolated populations may be genetically swamped through A. australis introgression.

Primary causes are thought to be anthropogenic changes to population sizes of A. butcheri from fishing pressure and modification to estuary opening and closing regimes

(Roberts et al. 2010). Nevertheless, there is the possibility that hybridisation between these species is a natural and ancient phenomenon unrelated to anthropogenic impacts.

Understanding divergent movement patterns within this hybrid complex may provide van der Meulen, D.E. 62 Chapter 3: Movements of Acanthopagrus Species Complex

novel insights into the dynamics of hybridisation. In particular, it is of interest as to whether initial A. australis introgression into A. butcheri is dependent on contact between pure A. australis and A. butcheri, with later generation Acanthopagrus spp. hybrids displaying site attachment or residency within estuaries, or through the migration and interbreeding of introgressed hybrid bream with resident purebred A. butcheri.

This study combines genetic analysis of Acanthopagrus spp. and acoustic tracking of fish movements to understand several aspects of the spatial ecology of this species complex. Specifically, the study investigates spatial and temporal variation in movements, residency, site fidelity, and linear space utilisation along the estuary; and the potential for biophysical variation to influence movements and distributions of each group within the species complex. These findings are interpreted in the context of understanding hybridisation dynamics.

3.2 Methods

3.2.1 Study Region

The Shoalhaven River (-34.900°S, 150.763°E) is a river-dominated estuary with a wave-dominated delta located in south-east Australia (Roy et al. 2001). The estuary is

48 km long from the entrance to the tidal limit (Walsh et al. 2012a), draining a catchment of 7,326 km2 (shoreline land-use is primarily agriculture) and supports a large aquaculture (oyster farming) industry. The mouth of the estuary has been heavily modified, with a canal being cut to join the Shoalhaven River and the adjacent van der Meulen, D.E. 63 Chapter 3: Movements of Acanthopagrus Species Complex

Crookhaven River, which has subsequently altered the mouth of the Shoalhaven River such that it exits to the sea through the Crookhaven River (with the original mouth of the Shoalhaven River closed by sand deposition for the duration of this study, Figure

3.1).

Figure 3.1 Shoalhaven River study site. Black circles represent receiver locations with large black circles showing the location of temperature and conductivity data loggers paired with a receiver (Station numbers: 1, 7, 16, 27 and 30). Fish tagging was conducted at five sites: Berry’s Canal (Station 7), the entrance to Broughton Creek (Station 10), Nowra Bridge (Station 16), Ski Park (Station 22) and Gypsy Point (27). Tide data was collected for Greenwell Point (Station 3) and Nowra Bridge (Station 16).

3.2.2 Acoustic Array and Monitoring

Thirty-five Vemco VR2W acoustic receivers (Vemco, Nova Scotia, Canada) were deployed between the estuary entrance and the tidal limit (Figure 3.1), in a configuration that was optimised to examine large-scale linear movements of fishes van der Meulen, D.E. 64 Chapter 3: Movements of Acanthopagrus Species Complex

within the estuary (Walsh et al. 2012b). Ten receivers were deployed along the coast to monitor offshore movements of tagged fish (Figure 3.1). Receivers recorded time, date, fish identity and station name as well as fish body temperature and swimming depth

(from sensor tags; see below). Temperature and conductivity variation within the array were monitored using five Odyssey data loggers (Dataflow Systems Pty. Ltd.

Christchurch, New Zealand) which were evenly distributed throughout the length of the estuary (Figure 3.1). The river height gauging station (GS 215216) located at Grassy

Gully (54km from river entrance) in the freshwater reach of the river was used to determine freshwater flow input. Meteorological data was obtained from the Australian

Government - Bureau of Meteorology for station number 68072 located at Nowra, NSW

(34.94°S, 150.55°E). Astrological data was obtained from Geoscience Australia

(Geoscience Australia, 2012) and tidal data came from the National Tide Centre

(Bureau of Meteorology) and Manly Hydraulics Laboratory (Manly Vale, NSW) for gauging stations at Greenwell Point (3km from river entrance) and Nowra Bridge

(19km from river entrance). Water quality depth profiles were conducted monthly and coordinated with freshwater flow events at each receiver station using a Sea-Bird CTD profiler (SBE 19-plus V2; Sea-Bird Electronics, www.seabird.com). Additional acoustic receivers were deployed to monitor inter-estuarine movement at the entrances of major estuaries systems north and south of the Shoalhaven River including: Hunter River,

Lake Macquarie, Tuggerah Lake, Hawkesbury River, Sydney Harbour, Georges River,

Cooks River, Port Hacking, Lake Illawarra, Minnamurra River, Currambeen Creek, St.

Georges Basin, Lake Conjola, Burrill Lake, Clyde River and Moruya River.

van der Meulen, D.E. 65 Chapter 3: Movements of Acanthopagrus Species Complex

3.2.3 Ethics Statement

This study was carried out in strict accordance with the recommendations in the Guide to Acceptable Procedures and Practices for Aquaculture and Fisheries Research, 3rd

Edition (Barker et al. 2009). The protocol for capture, handling and surgery was approved by the Animal Care and Ethics Committee of the New South Wales

Department of Primary Industries (Animal Research Permit 09/01). All surgery was performed under anaesthesia, and all efforts were made to minimize suffering. Capture and tagging of fish in the Shoalhaven River during this study was permitted under

Section 37 of the NSW Fisheries Management Act 1994, under Scientific Research

Permit number P01/0059 (issued by NSW Department of Primary Industries).

3.2.4 Tagging

All fish were captured on hook-and-line between December 2008 and November 2009 at five locations ranging from the entrance to upper reaches of the estuary and externally tagged with a unique ID (Hallprint T-bar anchor tags, Hindmarsh Valley, Australia) to determine their capture location. A total of 29 fish were surgically implanted with

Vemco V9-2L/2L TP (containing temperature and pressure sensors, 759-959d tag life) or V13-1L (1123d tag life) acoustic transmitters with a pseudorandom delay of between

60 and 300s (Walsh et al. 2012a). Surgery was conducted either on-location and the fish were released immediately after recovery, or fish were transported to the Shoalhaven

Marine and Freshwater Centre where surgery was conducted and fish were released up to two weeks post-surgery. Surgery was conducted following techniques outlined in

Walsh et al. (2012a). Sex was determined by macroscopically staging the gonads, where van der Meulen, D.E. 66 Chapter 3: Movements of Acanthopagrus Species Complex

possible, during surgery. All fish were released at the location of capture, and fork length (FL), total length (TL), weight, and sex were recorded.

3.2.5 Genetic analysis

A small biopsy from each fish’s caudal fin provided cells for DNA extraction and subsequent genetic analysis to determine each fish’s specific genetic identity.

Admixture analysis based on the 8-loci (microsatellite) nuclear genotype of each fish was used to estimate a qi-value (the mean posterior proportion of ancestry ± 95%).

Thresholds of qi ≤0·05, 0·05< qi <0·95 and qi ≥0·95 were used to identify pure A. australis, hybrids and pure A. butcheri, respectively. Hybrid fish were further classified;

0·05 < qi < 0.40 for A. australis-like hybrids (a class of A. australis backcross) and 0·60

< qi < 0.95 for A. butcheri-like hybrids (A. butcheri backcross). Further details of the analysis and discussion of the dynamics of hybridisation and classes of hybrids in estuaries can be found in Roberts et al. (2009) and Roberts et al. (2010).

3.2.6 Data Analysis

Telemetry data from receivers were downloaded at regular intervals and stored in a

Microsoft Access database. Prior to analysis all single detection data and "false" detections were discarded from the dataset (Clements et al. 2005). Spatial and temporal movement patterns were initially expressed as distance-to-sea measurements, which were measured for each receiver. Data were summarised in hourly bins, by calculating the average distance-to-sea from detection positions for the fish during that hour period.

For hours when fish were not detected an assumed distance-to-sea was assigned using van der Meulen, D.E. 67 Chapter 3: Movements of Acanthopagrus Species Complex

the calculated slope between the hourly distance-to-sea and the number of lapsed hours.

This was only possible due to the low number of missed detections that occurred when fish passed receivers allowing a complete dataset to be formed that could be compared against environmental variables. Movement rate was determined as the distance travelled per hourly calculated fish position. Daily average positions were calculated from these data, to reduce problems associated with detection variability due to biological and environmental noise (Payne et al. 2010) and ensured the data were comparable among individuals. Temperature and conductivity logger data were examined in the context of fish movement data, and reference station 27 was selected as it had the most complete data set and the highest correlation (Figure 3.1). Data from this single location was used as the aim was to examine how fish reacted to environmental variation, not how well they managed to minimise exposure to this variation through movement.

Depth data, determined from pressure sensing tags, were used to define the spatial differences in the swimming depths of Acanthopagrus spp. within the river in relation to environmental variables. Data may be compared against longitudinal distributions to aid in determining drivers of movement. Data was standardised by randomly selecting equal numbers of detections for each individual fish across all receivers. Swimming depths were averaged for each receiver and swimming depth in relation to flow was determined by averaging log flow for each 0.1m increment in swimming depth.

Maximum depth adjacent to the receivers were determined from detailed bathymetric surveys conducted by NSW Department of Land and Water.

van der Meulen, D.E. 68 Chapter 3: Movements of Acanthopagrus Species Complex

3.2.6.1 Kernel Density Estimation

One-dimensional kernel density estimates (KDE) were constructed using R 3.0.2 (R

Development Core Team 2013) dens function. Hourly fish locations were used to determine the distributions of Acanthopagrus spp. at both the individual and population level. KDE’s were used to calculate the number of modes and total linear river distance occupied by individual fish within the core (50th percentile) and total (90th percentile) utilisation distributions (UD). To determine spatial and temporal variation in linear space utilisation along the estuary single factor ANOVA’s were used to examine variation between modal distribution counts and core and total UD’s for A. australis and

A. spp. hybrids; simple linear regressions were used to examine the relationships between fork length (FL) versus core and total UD’s and modal distributions, as well as any relationships between capture distance from sea and modal distributions. KDE's were also used to show variation in the distributions of fish populations throughout the study; between dry (2008-2009) and wet years (2010-2011) and between spawning

(August to December) and non-spawning periods (January to July). Individuals with less than 400 detections were considered to provide insufficient data and were removed from the analysis, as they generally had short detections periods which did not allow comparison against variables across a relevant time period or were detected infrequently, suggesting a tag transmission error had occurred. All KDE's were weighted so that each fish gave equal weight towards the distribution regardless of the length of time the fish was detected. The total sum of the distributions was adjusted to equal “1”, allowing comparison of distributions at the same scale.

van der Meulen, D.E. 69 Chapter 3: Movements of Acanthopagrus Species Complex

3.2.6.2 Analysis of movement and biological and environmental variables

The study investigated the influence of biological and environmental factors on the distribution of fish identified as A. australis and A. australis hybrid backcrosses in the river using autoregressive (AR) models. The dependent variable used for distribution was the mean distance of individual fish from the sea (DistanceFromSea).

Environmental explanatory variables tested in the model included mean water temperature (Temp), conductivity (Cond), loge river flow (LFlow) and a boolean variable to examine the effect of high river flow (HighFlow) events (e.g. flow > highest

5% of flows (Devlin et al. 2010)). Although inherently correlated with river flow, the

HighFlow variable was included to test the hypothesis that high river discharge events are the only changes in flow that are relevant to the movement of Acanthopagrus spp.

Genetic classification (Genetics) was included to test the hypothesis that distribution within the river (DistanceFromSea) varies between A. australis and A. australis hybrid backcrosses. Biological variables included a genetic classification (Genetics), FL (FL), capture location (Capture) and a boolean variable for spawning season (Spawn) which indicated the period of maximum spawning for A. australis spp. (August to December).

AR models were attempted against various levels of aggregated data, using generalised least squares fit by maximum likelihood (gls function in nlme library of the R software, (Pinheiro et al. 2014)). A quarter-day dataset constituted the finest scale of the data for which an AR analysis could be completed using a dual core i7 PC with 16GB of RAM. This dataset was aggregated over six hourly blocks that were loosely referred to as dawn (03:00-09:00), day (09:00-15:00), dusk (15:00-21:00), and night (21:00-

03:00). Using data at the finest scale possible was important as fish were capable of van der Meulen, D.E. 70 Chapter 3: Movements of Acanthopagrus Species Complex

making significant movements and returning to their original location within a day, by using only daily average data there was concern that important movements would be lost within the dataset. The best AR model was chosen based on AIC values using backward elimination (or top-down) stepwise regression (Aarts et al. 2008; Zuur et al.

2009). A twelfth order AR model was used, as this order was found to be optimum using the acf and ar functions (R Development Core Team 2013).

The complete model included:

DistanceFromSeai = α + β1 · Condi + β2 · Tempi + β3 · HighFlowi + β4 · LogFlowi +

β5 · Capturei + β6 · Geneticsi + β7 · FLi + β8 · Spawni + εi,

where α is the intercept term, the β1- β8 are the parameter coefficients and εi represents the model residuals. An interaction term Genetics:Spawn was also included in the investigation to incorporate the different spawning and location characteristics found in the analysis of movement patterns for the different species.

3.3 Results

A total of 29 Acanthopagrus spp. were tagged between December 2008 and November

2009. Genetic analysis revealed 17 A. australis and nine A. australis hybrid backcrosses were tagged, as well as one A. butcheri hybrid backcross, one F1 hybrid and one fish that was not identified (because of missing genetic data, Table 3.1). Both the putative A. butcheri hybrid backcross and F1 hybrid types, which were tagged within Broughton Creek (a major tributary within the Shoalhaven River), it is suggested van der Meulen, D.E. 71 Chapter 3: Movements of Acanthopagrus Species Complex

that these fish survived, yet only moved within the boundaries for this tributary and as a result were only detected on the main Shoalhaven River array on one receiver at the entrance to Broughton Creek. This was consistent with the idea that A. butcheri are generally resident in their natal estuary. Acoustic receivers were not placed throughout

Broughton Creek so it was not possible to determine and compare the longitudinal movements of these fish. Thus, they were excluded from the global data analysis.

Moreover, an additional four fish (3 A. australis and one A. australis hybrid backcross) provided insufficient data for analysis to proceed. Data may have been lacking for these fish due to tag failure, mortality, predation, tag rejection or due to the fish rapidly exiting the river system. As only A. australis and A. australis hybrid backcrosses were used for analysis I will refer to A. australis hybrid backcrosses as A. hybrids hereafter, unless specifically stated.

3.3.1 Movement Patterns

Individual A. australis and A. hybrids displayed similarities in their movement patterns

(Figure 3.2). Both A. australis and A. hybrids showed high levels of site fidelity and moved within distinct home ranges, from which they would undertake large-scale movements within the estuary or migrations beyond the estuary mouth. The period of time that fish would remain committed to a specific location (~1.5 km linear river distance) in the estuary was variable; at the extreme, this period of time was in excess of two years for five of the tagged fish.

Tagged A. australis and A. hybrids were found to be distributed from the river entrance to 45 and 41 km upstream, respectively. The distribution of A. australis and A. hybrids van der Meulen, D.E. 72 Chapter 3: Movements of Acanthopagrus Species Complex

in the estuary overlapped (Figure 3.4). Distributions of A. australis were centred on three main modal peaks between 16 and 32 km from the entrance of the river, whereas,

A. hybrid distributions were centred about a single modal peak, 17 to 26 km from the entrance of the river (Figure 3.4). Core UDs averaged 4.8 km (S.E. ± 1.8 km) and 4.6 km (S.E. ± 0.5 km) for A. australis and A. hybrids, respectively (Table 3.1). Eighty one percent of A. australis and 63% of A. hybrids displayed multimodal core UDs. There was no significant difference between the number of core (F1,22 = 0.79, P = 0.38) and total UD (F1,22 = 0.87, P = 0.36) for A. australis and A. hybrids. Similarly there was no significant difference between the size of the core (F1,22 = 0.78, P = 0.38) and total (F1,22

= 0.85, P = 0.37) UD for A. australis and A. hybrids. There was also no significant

2 relationship between FL and modal distance from sea (F1,14 = 1.21, P = 0.29, R = 0.08),

2 2 core (F1,14 = 0.06, P = 0.81, R = 0.01) or total UD (F1,14 = 0.03, P = 0.85, R = 0.002) for A. australis, and similarly there was no significant relationship between FL and

2 modal distance from sea (F1,7 = 2.44, P = 0.18, R = 0.32), core (F1,7 = 0.15, P = 0.71,

2 2 R = 0.02) or total UD (F1,7 = 0.13, P = 0.73, R = 0.02) for A. hybrids. There was a significantly positive relationship found between the tagging location and the modal

2 distance from sea for A. australis (F1,13 = 6.31, P = 0.027, R = 0.35) and A. hybrids

2 (F1,7 = 55.47, P = 0.0003, R = 0.90). Caution should be taken when interpreting these results as the increased number of individual analysis can increase the likelihood of type one error.

Nine (64%) A. australis and three (38%) A. hybrids made short term (<24 h) offshore movements after which they returned to the estuary. Six (43%) A. australis (fish IDs:

1060789, 1060790, 1060944, 1060947, 1060951, 1061912) and three (38%) A. hybrids

(fish IDs: 1060795, 1060942, 1060945) were found to make what appeared to be van der Meulen, D.E. 73 Chapter 3: Movements of Acanthopagrus Species Complex

offshore movements at the conclusion of their detection period. Two of these fish were detected on receivers placed at estuary entrances on the Minnamurra River (fish ID

1060944) and Port Hacking (fish ID 1060790), travelling a distance of 32 km (368 days between detections) and 99 km (13 days between detections) north (straight line distance) respectively, and did not return to the Shoalhaven River. An additional two fish were captured by recreational fishermen at Jervis Bay (fish ID 1060942) and Port

Stephens (fish ID 1060951), a straight line distance of 22 km south (438 days between last detection and capture) and 278 km north (127 days between last detection and capture) respectively. These offshore movements coincided with large freshwater flow events that occurred from early to late summer 2010 and 2011. There was no significant difference in the fork length of the fish that made these inter-estuarine movements and the fish that remained resident to the Shoalhaven River (F1,22 = 0.19, P = 0.67).

van der Meulen, D.E. 74 Chapter 3: Movements of Acanthopagrus Species Complex

Table 3.1 Summary of Acanthopagrus australis and Acanthopagrus hybrids tagged in the Shoalhaven River

Capture Release Fork Length Weight Days No Core UD Total UD Ave Dist Fish ID Sex1 Tag Type Genetic Classification Location Date (mm) (g) Tracked Detections Dist2 Dist3 Sea4 1060794 Berry's Canal 21/01/2009 242 278 M 706 V9-2L 666 A. australis 1172 4571 13053 1060800* Berry's Canal 21/01/2009 237 250 F 46 V9-2L 360 A. australis - - - 1060923 Berry's Canal 29/11/2009 286 482 U 359 V9TP-2L 9311 A. australis 1272 1845 19320 1060924 Berry's Canal 29/11/2009 328 734 U 931 V9TP-2L 58111 A. australis backcross 3357 10788 6535 1060928* Berry's Canal 29/11/2009 294 525 U 32 V9TP-2L 87 A. australis backcross - - - 1060929 Berry's Canal 29/11/2009 349 995 F 167 V9TP-2L 10164 A. australis backcross 1274 7013 4732 1060958* Broughton Creek 29/11/2009 346 1035 F 777 V9-2L 3770 A. butcheri backcross - - - 1061917* Broughton Creek 15/03/2009 368 1020 F 362 V13-1L 79 F1 - - - 1060790 Nowra Bridge 17/02/2009 258 386 U 761 V9TP-2L 25527 A. australis 2023 20051 16043 1060930* Nowra Bridge 29/11/2009 358 895 M 376 V9TP-2L 69 A. australis 1447 2990 - 1060941 Nowra Bridge 17/02/2009 258 395 F 208 V9-2L 8267 A. australis 473 1533 18855 1060948 Nowra Bridge 17/02/2009 245 291 F 164 V9-2L 3833 A. australis backcross 3068 14572 14888 1060951 Nowra Bridge 15/03/2009 295 550 U 357 V9-2L 39893 A. australis 24320 43776 23620 1061912 Nowra Bridge 15/03/2009 333 780 U 269 V13-1L 146945 A. australis 1419 8433 23566 1066623 Nowra Bridge 15/03/2009 285 500 F 893 V9-2L 26659 A. australis 1565 7823 15855 1060926 Ski Park 29/11/2009 327 832 M 406 V9TP-2L 48079 A. australis 922 2976 23613 1060942 Ski Park 17/02/2009 242 331 F 315 V9-2L 37265 A. australis backcross 1277 2364 21748 1060943 Ski Park 17/02/2009 262 395 F 308 V9-2L 93419 A. australis 5381 15636 23226 1060944 Ski Park 17/02/2009 256 351 U 671 V9-2L 81869 A. australis 9032 33854 19618 1060945 Ski Park 17/02/2009 244 312 M 472 V9-2L 16514 A. australis backcross 785 2770 20317 1060946 Ski Park 17/02/2009 251 333 U 664 V9-2L 20064 A. australis backcross 2820 11005 14076 1060947 Ski Park 17/02/2009 252 332 M 364 V9-2L 79095 A. australis 1172 4571 21010 1060789 Gypsy Point 15/03/2009 297 338 F 735 V9TP-2L 97819 A. australis 16477 29584 19497 1060795 Gypsy Point 11/12/2008 286 495 U 143 V9-2L 14904 A. australis backcross 2928 4676 22583 1060796 Gypsy Point 11/12/2008 290 476 F 769 V9-2L 7028 A. australis backcross 5781 22489 22447 1060797 Gypsy Point 11/12/2008 262 373 U 515 V9-2L 34687 A. australis 596 9609 30809 1060798 Gypsy Point 11/12/2008 242 337 U 453 V9-2L 10891 A. australis 243 827 29101 1060799 Gypsy Point 11/12/2008 236 287 U 508 V9-2L 10940 - 3400 8830 21264 1061913 Gypsy Point 15/03/2009 318 360 U 1195 V13-1L 151159 A. australis 5936 24944 22048 1 Sex is male (M), female (F) or unidentified (U) 2 Core UD Dist refers to the linear distance (m) along the estuary encompassed by the core utilisation distribution (50% kernel density distribution). 3 Total UD Dist refers to the linear distance (m) along the estuary encompassed by the total utilisation distribution (90% kernel density distribution). 4Ave Dist Sea refers to the average linear distance (m) from the estuary entrance, determined from hourly positions. * Fish provided insufficient data (<400 detections) or were from a genetic classification with limited replication and were not used in data analysis. van der Meulen, D.E. 75 Chapter 3: Movements of Acanthopagrus Species Complex

Figure 3.2 Average hourly distance from sea of six representative Acanthopagrus australis and six Acanthopagrus hybrids. Transmitter serial number displayed in each plot.

3.3.2 Movements in response to environmental variables

The impacts of environmental variables on fish movements and distributions were variable (Figure 3.3 and Figure 3.4). Weather conditions were relatively dry in 2009 whereas the start of 2010 corresponded with the end of long-term drought conditions, van der Meulen, D.E. 76 Chapter 3: Movements of Acanthopagrus Species Complex

with increased rain, large-scale flooding, and a switch from El Niño to La Niña weather conditions. All fish displayed downstream movement in relation to increased freshwater flows with the degree of displacement variable. Initial displacement was correlated with the strength of flow, after which fish were quick to return to their original residences.

Prolonged periods of freshwater flow throughout 2010 saw some individuals of both A. australis and A. hybrids adjust their upstream residences to locations closer to the river entrance. The population distance from sea (averaged by hour) changed from ~25 km upstream from the river entrance to 17 km upstream for A. australis and from 22 km upstream to 15 km upstream for A. hybrids (Figure 3.3) between 2009 and 2010. Some individuals did maintain their relative position between the wet and dry years which is evident in the peak modal distributions remaining similar, but there was also a substantial increase in the time fish spent in the lower estuary between 0 and 10 km from the river entrance (Figure 3.4). The average rate of movement of the population increased with peak freshwater flows (Figure 3.3). In addition to flow, temperature also had an impact on the average rate of movement for both A. australis and A. hybrids with activity based on large-scale movements increasing to a maximum at 21°C after which activity decreased.

The most parsimonious 12th-order autoregressive model using average quarter-day data contained the variables Temp, Cond, LFlow, Genetics, Capture and Spawn (Table 3.2 and Table 3.3, AIC = 715952). High correlation between successive fish-location time steps was found for this model (Table 3.3, φ1 = 1.07). Despite the high level of autocorrelation the model indicated that conductivity, log flow, genetic classification, capture location and spawning season all had a significant influence on fish location

(Table 3.3). van der Meulen, D.E. 77 Chapter 3: Movements of Acanthopagrus Species Complex

Figure 3.3 Population averaged distance from sea for a) Acanthopagrus australis and b) Acanthopagrus hybrids. Population averaged movement rate for c) Acanthopagrus australis and d) Acanthopagrus hybrids. Individual hourly averaged distance from sea for fish with tag serial numbers e) 1060789, f) 1060944 and g) 1060946 plotted with environmental variables: flow, temperature and conductivity respectively. Note: all figures are plotted with the same x-axis scale so that environmental variables can be compared against movements. van der Meulen, D.E. 78 Chapter 3: Movements of Acanthopagrus Species Complex

Figure 3.4 Total population, spawning/non-spawning and wet/dry year two dimensional kernel density estimates plotted for Acanthopagrus australis and Acanthopagrus hybrids.

van der Meulen, D.E. 79 Chapter 3: Movements of Acanthopagrus Species Complex

Table 3.2 Comparison of models constructed for estimating the influence of environmental factors on the mean distance of Acanthopagrus spp. from the sea using twelfth order autoregressive with quarter-day aggregated data. The models with the lowest AIC value indicates the best fitting and most parsimonious models (in bold). Explanatory variables include log transformed river flow (LFlow), highest 5% of river flow (HighFlow), Fork Length (FL), genetic class (Genetics), spawning season (Spawn), capture location (Capture), water temperature (Temp), conductivity (Cond). Model AIC ∆ AIC 1200 Genetics + FL + Capture + Spawn + Temp + Cond + LFlow + HighFlow 715955 - 1201 Genetics + Capture + Spawn +Temp + Cond + LFlow + HighFlow 715953 1.9 1202 Genetics + Capture + Spawn + Temp + Cond + LFlow 715952 0.7 1203 Genetics + Capture + Spawn + Cond + LFlow 715953 1.3 1202B Genetics:Spawn + Capture + Temp + Cond + LFlow 715984 30.7

Table 3.3 Summary statistics for the most parsimonious model fit to tagged Acanthopagrus spp. mean distance from sea, using twelth order autoregression (AR12) on quarter-day data split into dawn, day, night and dusk. AR φ's are the autoregression parameters. Capture locations are relative to Ferry. Coefficients Estimate s.e. t p (Intercept) 14797.94 742.83 19.92 <0.001 Genetics -5117.40 583.84 -8.77 <0.001 Spawn 953.46 199.75 4.77 <0.001 Temp -31.57 17.38 -1.82 0.0693 Cond -15.66 6.90 -2.27 0.0232 LFlow -64.52 32.78 -1.97 0.0491 CaptureGypsy 12345.82 780.64 15.81 <0.001 CaptureNowra 5878.24 821.69 7.15 <0.001 CaptureSkiPark 7730.64 769.23 10.05 <0.001 AR φ's:1.07,-0.21,0.04,0.02,0.03,-0.01,0.02,0.01,0.01,-0.01,-0.01,0.01

3.3.3 Spawning Period Movements

There was significant movement observed during the spawning season for both A. australis and A. hybrids. During this period, both short-term upstream and downstream movements were observed. These were generally singular movements to non-common locations and they did not appear to coincide with environmental variables. There was also little variation in the population based kernel density estimates between spawning and non-spawning periods (Figure 3.4). van der Meulen, D.E. 80 Chapter 3: Movements of Acanthopagrus Species Complex

3.3.4 Depth Distributions

Individual swimming depths of fish (n = 6) ranged from the surface to 16.1 m. Mean swimming depths (± SE) were 4.1 m (± 0.31). Maximum average swimming depth at each receiver was 7.5 m. Depth distributions were related to the maximum depth of water present adjacent to receivers, with the exception being that fish were generally not located at depths >10min locations where the maximum river depth exceeded 10 m. For locations where the maximum depth adjacent to receivers was less than 10 m fish were generally distributed in the bottom 39% of the water column (Figure 3.5). Freshwater flow events above log 1.5 ML/day resulted in decreased average population swimming depths (Figure 3.6). During normal flow conditions salinity was found to be well mixed with similar salinity measurements recorded at all depths (Figure 3.6). During freshwater flow events, salinity was lower at the surface than it was at depth (Figure

3.6).

Figure 3.5 Average depth (+-SD) at each receiver station (black line) and maximum river depth adjacent to each receiver (grey line) shown in relation to distance from sea.

van der Meulen, D.E. 81 Chapter 3: Movements of Acanthopagrus Species Complex

3.4 Discussion

Acanthopagrus australis and A. hybrid were both distributed throughout the estuary, occupying a variety of overlapping physical and hydrographic habitats. Genetic classification was found to influence the distance of fish from the sea within the estuary, with A. australis found further upstream than A. hybrids. While genetic classification did influence individual fish location, population distributions overlapped, with both A. australis and A. hybrids displaying similarities in their movement patterns. Individual

A. australis and A. hybrids were found to display small UDs and high levels of site fidelity associated with specific locations. Following large-scale movements and displacement by environmental disturbances, these fish generally returned to these places of residence. Peak distributions occurred in the lower and upper middle estuary.

The patterns of distribution detected here are consistent with findings from other movement studies on Acanthopagrus congeners. Acanthopagrus butcheri (Hindell et al.

2008; Sakabe and Lyle 2010) and goldsilk seabream, Acanthopagrus berda (Sheaves et van der Meulen, D.E. 82 Chapter 3: Movements of Acanthopagrus Species Complex

al. 1999) displayed a high degree of localised movements with larger scale migrations linked to spawning seasons.

Within the distribution of each group of fish, individuals occupied an average core UDs of 4.1 km (linear river distance), which was smaller than that found for mulloway,

Agryrosomus japonicus, (Taylor et al. 2014) but larger than that of estuary perch,

Percalates colonorum, (Walsh et al. 2012a) during the same time period in the

Shoalhaven estuary. This indicates variability in space use between different species.

Fish also displayed high levels of site attachment or site fidelity, suggesting that within their broader population, individual distributions are characterised by multiple smaller activity centres that could function to reduce direct competition. High levels of site fidelity have been suggested to reduce predation and increase feeding efficiency through familiarization with specific locations (Childs et al. 2008a; Kramer and Chapman

1999). Fish length has been found to be positively related to home range area and movement rates (Andrews et al. 2007; Taylor et al. 2014). However, no relationship was found between fish length and UD for either A. australis or A. hybrids. The results of this study are supported by studies on A. butcheri (Hindell et al. 2008), spotted grunter, Pomadasys commersonnii (Næsje et al. 2007), Mediterranean parrotfish,

Sparisoma cretense (Afonso et al. 2008) and Roman seabream, Chrysoblephus laticeps

(Kerwath et al. 2007) and may be a trait displayed only by social and territorial species.

Large-scale offshore movements of distance >20 km were recorded for both A. australis and A. hybrids. Interestingly, none of the fish were detected returning to the Shoalhaven

River (although this may be a product of the expiration of the tag battery), with fish recorded moving up to 278 km, predominantly in a northward direction. Conventional van der Meulen, D.E. 83 Chapter 3: Movements of Acanthopagrus Species Complex

tag-recapture studies have documented that a small number of A. australis make large- scale (typically northward) migrations, but the majority of recaptures generally occur in the estuary in which they were tagged (Pollock 1982a; Roberts and Ayre 2010;

Thomson 1959). These inter-estuarine movements did not appear to be linked to any biological relationship and caused some of the variation in monitoring periods between fish. The general northward directionality of these inter-estuarine movements may be a result of fish seeking locations with mean temperatures that are closer to their thermal optimum (Payne et al. 2016). Alternatively, reproductively mature fish may migrate in a northward direction across the length of the NSW coast as a compensatory mechanism for the southward entrainment of larvae by the East Australian Current (Booth et al.

2007; Gray et al. 2012). Initiation of offshore movements coincided with large freshwater flow events. Large freshwater discharges from rivers to the near-shore coastal environment may act as a coastal buffer and facilitate inter-estuarine movements

(Gillanders and Kingsford 2002). This suggests that anthropogenic alteration of flow regimes may impact adult dispersal mechanisms.

3.4.1 Movements in response to environmental variables

Abrupt downstream movements in response to large rainfall events and corresponding freshwater flows were observed for both A. australis and A. hybrids. Downstream movements coincided with decreased conductivity alongside increased flow but return movements generally occurred prior to the return of conductivity to pre-flow conditions.

This suggested that fish either quickly recovered from changes in salinity, or movements were driven by changes in other biophysical conditions. Large freshwater flows represent one of the most disruptive events that occur in river systems and can van der Meulen, D.E. 84 Chapter 3: Movements of Acanthopagrus Species Complex

directly influence the estuarine morphology, water temperature, salinity, pH, turbidity, nutrient status, organic input, dissolved oxygen concentrations and olfactory cues

(Whitfield 2005). A wide range of estuarine-dependent species have displayed similar responses to flow events (Sakabe and Lyle 2010; Taylor et al. 2010; Taylor et al. 2014;

Walsh et al. 2013b). However, a number of other factors may influence movements and distribution associated with freshwater flows including, but not limited to osmoregulatory stress (Sangiao-Alvarellos et al. 2005), thermoregulation (Hight and

Lowe 2007; Nay et al. 2015; Newell and Quinn 2005), loss of homing cues (Drinkwater and Frank 1994; Lürling and Scheffer 2007), spawning season (Reinfelds et al. 2013) and predator/prey distributions (Payne et al. 2015b).

A number of individual A. australis and A. hybrids displayed a shift in their upper estuarine spatial distribution as a result of increased and prolonged freshwater flows associated with above average rainfall and a shift to La Nina weather patterns on the

East Coast of Australia. Fish can be quick to adjust to initial changes in salinity by temporarily increasing osmoregulatory load (1-3 days); however, for longer periods fish may need to move to a location that has a higher salinity (Dalla Via et al. 1998;

Sangiao-Alvarellos et al. 2005). Alternatively, fish may rapidly alter their position along the estuary to compensate for the change in salinity, and thereby avoid a major osmoregulatory load (Serafy et al. 1997; Serrano et al. 2010). These distributional shifts probably occur due to increased survival benefits (Childs et al. 2008a; Kramer and

Chapman 1999). Hydrographic habitats, such as the saline structure of the estuary shift with increases and decreases of freshwater flow (Miller et al. 2006). These hydrographic habitats may have shifted beyond the physiologically tolerable or preferred range of this species in the upper reaches (Serrano et al. 2010). An upstream van der Meulen, D.E. 85 Chapter 3: Movements of Acanthopagrus Species Complex

distribution shift would be expected as salinity returned to pre-flow conditions.

However, monitoring further distribution shifts were not possible due to expiration of the tags.

Fish were found to move to shallower depths in response to large freshwater flows, and unlike alongshore movements, vertical distributions were slow to recover. These findings corroborate the results of Payne et al. (2013). This suggests that different mechanisms may be driving vertical distributions. During the peak of large freshwater flow events, stratification of the water column occurs with freshwater present on the surface and denser saline water at depth (Figure 3.6). If fish were actively selecting salinities close to their preferred salinity, then fish would be expected to move deeper during flows. Therefore, it’s inferred that salinity is not driving vertical distribution.

Biophysical variables that alter depth distributions and behaviour in relation to flow include turbidity (Payne et al. 2013), light intensity (Reebs 2002), dissolved oxygen

(Payne et al. 2013) and changes in predator and prey distributions (Payne et al. 2015b;

Strange 2013).

3.4.2 Spawning-related Movements

There were large-scale movements observed during the spawning season, with both A. australis and A. hybrids displaying similar behaviours. Increases in short-term upstream and downstream movements were observed, but these were generally singular movements to non-common locations and they did not coincide with other environmental variables, nor were they synchronised. Additionally, the distributional overlap between A. australis and A. hybrids suggests they have similar biophysical van der Meulen, D.E. 86 Chapter 3: Movements of Acanthopagrus Species Complex

requirements during the spawning season. All the fish used in this study were above the size of maturity, and it’s assumed that they are reproductively active (Ochwada-Doyle et al. 2012). Using conventional tagging Pollock (1982a), showed that while some A. australis moved to coastal surf zones to spawn, fish that did not move to coastal surf zones generally didn’t spawn during that season and instead reabsorbed their oocytes

(Pollock 1984). It is plausible that A. australis and A. hybrids remaining in the estuary in any given year do not partake in spawning. However, some fish need to spawn within the estuary to facilitate hybridisation with the estuarine restricted A. butcheri (Roberts et al. 2010). Future attempts to identify spawning behaviour at different locations (e.g. van der Meulen et al. 2014) could help to explain the spawning mechanisms that contribute to hybridisation and introgression.

Estuarine populations of A. butcheri are thought to be genetically subdivided (Burridge and Versace 2007; Burridge et al. 2004; Chaplin et al. 1998) whereas A. australis is genotypically diverse and genetically homogeneous over several tens-to-hundreds of kilometers (Roberts and Ayre 2010). For A. australis, this implies there is increased dispersal, and is consistent with the perceived mobility of adult fish (confirmed herein by the movement data), and the species long pelagic larval phase under the influence of the East Australian Current (Roberts and Ayre 2010) . This mobility not only maintains genetic interconnection of the A. australis population but may also provide opportunities for hybridisation and introgression with its estuary-restricted congener, A. butcheri. Interestingly, the movement data also revealed large-scale inter-estuarine movements of A. hybrids. Thus, the dispersal mechanisms of A. hybrids appear similar to purebred A. australis, in that they provide an additional potential source of introgression of A. australis alleles into A. butcheri. Indeed, introgression of A. australis van der Meulen, D.E. 87 Chapter 3: Movements of Acanthopagrus Species Complex

genes into A. butcheri probably proceed via matings between pure A. australis and A. butcheri, with subsequent backcrossing between early generations of hybrids and A. butcheri within estuaries, or through introgression resulting from the migration and interbreeding of introgressed hybrid bream (that are more genetically aligned with A. australis than with resident purebred A. butcheri, or A. butcheri backcrosses). Although in planning, this study aimed to tag and monitor the movements of A. butcheri hybrid backcrosses – the most abundant bream in many intermittently open-and-closed southern NSW lakes and lagoons – small sample sizes and general lack of movement precluded analysis. A future study specifically targeting A. butcheri hybrid backcrosses through tagging fish from known hybridisation hotspots (e.g. Coila or Brou Lakes,

Roberts et al. 2010) may provide further insights into the dynamics of this hybridising species complex.

3.4.3 Conclusions

This is one of the first studies to examine the comparative movement patterns within a hybridised species complex, while our findings are based on relatively small sample sizes, several patterns were detected that may reflect patterns from the broader population This study highlights the complexity of estuarine movement patterns in A. australis and A. hybrids as they appear to be dependent on freshwater flow, temperature, and ancestry. Nevertheless, several patterns were evident. In particular, freshwater flows caused vertical and horizontal movements within the estuary, and may well have contributed to inter-estuarine migrations. In contrast to other estuarine- dependent species, there was a lack of obvious spawning migrations. Further work is required to determine spawning-related movement patterns within this species complex, van der Meulen, D.E. 88 Chapter 3: Movements of Acanthopagrus Species Complex

although clearly, adult inter-estuarine migrations play a significant role in the genetic interconnection of populations of this species complex.

van der Meulen, D.E. 89 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Chapter 4: Temperature mediates repeated and extensive

spawning migrations of Sand Whiting, Sillago ciliata

Abstract

Environmental variability plays a major role in the spawning and recruitment success of fishes. Reproductive dynamics of many estuarine fishes can be related to temperature variation, but the links between reproductive ecology and thermal landscapes are complex and often poorly understood. This study explored how temperature variation influences the movements and spawning behaviour of Sand Whiting, Sillago ciliata through the combination of acoustic telemetry and plankton sampling in two estuaries in south-eastern Australia. Spawning, which was confirmed by egg sampling at the putative spawning locations, was typified by regular, rapid migrations from upstream residences to habitats adjacent to river entrances. Over a spawning season

(approximately four months), individuals would undertake between five and 30 return migrations across return distances of up to 80 km, and travelling a total of almost 1000 km per season. Movements to the spawning location coincided with higher water temperatures in the estuary. These movements appear to be linked to fluctuations in coastal water temperature driven by down-welling oceanic conditions and increased freshwater flow. As these populations are nearer the poleward extent of the species distribution, both fish movement and spawning behaviour appears to be very closely regulated by the highest available temperatures. The results demonstrate the role of temperature for spawning dynamics in Sand Whiting, and highlight how the synthesis of acoustic telemetry and biological information can give meaningful insight to the elements underlying observed fish behaviours. van der Meulen, D.E. 90 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

4.1 Introduction

Successful spawning involves a broad range of strategies and behaviours in fishes.

Some species lay demersal eggs in nests occupied for their entire life (Buston 2004;

Fricke 1979), while others migrate thousands of kilometres to specific spawning locations and release pelagic eggs into the water column for dispersal (Arai 2014;

Beguer-Pon et al. 2015; Domeier and Speare 2012). The timing of spawning events and the selection of spawning habitat determines the hydrographic and physicochemical conditions to which eggs and larvae are exposed (Epifanio and Garvine 2001; Jenkins et al. 2015; Sponaugle et al. 2002; van der Meulen et al. 2014). The resultant effects on hatching success, larval survival and advective dispersal will in turn influence overall recruitment success and connectivity (Able et al. 2011; Checkley et al. 1988; Rohrs et al. 2014; Sponaugle et al. 2002), and quantifying these patterns is essential for effective management of populations (Lowerre-Barbieri et al. 2017).

Larval dispersal of estuarine fishes can be categorised into two core strategies: 1) larval retention, in which larvae are retained within their estuary of origin; and 2) larval export, where eggs and newly hatched larvae are exported from the estuary to coastal regions, and return to estuarine waters in the late larval and early post larval stages (see review by Bilton et al. 2002). Fish can achieve these strategies through selective timing and location of spawning, egg buoyancy, larval stage duration, vertical and horizontal swimming behaviour of larvae, and the use of various abiotic cues to stimulate certain behaviours (Sponaugle et al. 2002). In estuarine environments, the location and timing of spawning events in relation to temperature and freshwater inflow have a particularly

van der Meulen, D.E. 91 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

large impact on larval survival and recruitment success (Ferguson et al. 2008; Ferguson et al. 2013b; Houde 1987; Walsh et al. 2010; Whitfield 1994).

Sand Whiting (Sillago ciliata, Cuvier, 1829) are estuarine-dependent sillaginids with a broad distribution encompassing the tropical and temperate regions along the entire east coast of mainland Australia, as well as Tasmania, Lord Howe Island, New Caledonia,

Woodlark Islands, and southern Papua New Guinea (Burchmore et al. 1988; McKay

1992; Morton 1985). The species primarily inhabits inshore and estuarine sediment environments, and is heavily exploited by both recreational and commercial fisheries

(Henry and Lyle 2003; Rowling et al. 2010a; West et al. 2015). Sand Whiting in south eastern Australia have an optimum temperature for reproductive growth and locomotor performance of ~26°C (Payne et al. 2016), with the spawning period centred around the warmer months in that region (Burchmore et al. 1988; Cleland 1947; Ochwada-Doyle et al. 2014; Payne et al. 2016). With the commercial harvesting of Sand Whiting also peaking in summer in southern Australia (Rowling et al. 2010a), there is a need to better understanding spawning dynamics of this species.

Acoustic telemetry and egg sampling were combined to measure spatial and temporal patterns of Sand Whiting spawning in relation to abiotic variation, particularly temperature, within two large estuaries in south-eastern Australia. Specifically, the objectives were to: (1) Determine putative spawning movements of Sand Whiting within two separate estuaries in New South Wales; (2) Identify environmental mechanisms that trigger putative spawning movements of Sand Whiting; and (3) confirm the timing of Sand Whiting spawning events through egg sampling.

van der Meulen, D.E. 92 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

4.2 Methods

4.2.1 Study locations

This study was conducted in the Shoalhaven (-34°53’, 150°45’) and Clyde rivers (-

35°42’, 150°10’), in south-eastern Australia (Figure 4.1). The Shoalhaven River is a permanently open, semi-mature, wave dominated barrier estuary (Roy et al. 2001). The river consists of a 48 km estuary between the entrance and the tidal limit and an upper

27 km freshwater section to the base of the Tallowa Dam (total lenght of 327km, total catchment area of 7326 km2, Roy et al. 2001). The river is regulated and has a heavily modified estuarine reach surrounded by a predominantly agricultural catchment, with some residential and industrial areas. The upper estuary and freshwater catchment is dominated by wet and dry sclerophyll forest, and the headwater section is largely agricultural.

The Clyde River is a permanently open, intermediate, tidal dominated, drowned valley estuary that flows into an ocean embayment at the town of Batemans Bay (Roy et al.

2001). The river consists of a 37 km estuarine reach and a total catchment area of 1837 km2. The majority of the catchment is heavily forested (90%), with the remaining catchment area consisting of small areas of residential, urban and agricultural land use.

van der Meulen, D.E. 93 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Figure 4.1 Shoalhaven (a) and Clyde River (b) study locations. Black circles represent receiver locations with large black circles showing the location of temperature and conductivity data loggers paired with a receiver. Sand Whiting distribution in eastern Australia is shown in yellow. S1-5 and C1-C2 represent tagging locations in the Shoalhaven River and Clyde rivers respectively. Dashed line indicates the area below which is classified as the spawning location (<7km from the estuary entrance).

4.2.2 Fish capture and tagging

Fourteen and 20 adult Sand Whiting were internally tagged in the Shoalhaven River, during November 2009 and April 2011 respectively (Table 4.1). A further 17 and 21 individuals were tagged in the Clyde River during April 2011 and November 2012 van der Meulen, D.E. 94 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

respectively (Table 4.1). Fish were primarily captured using hook-and-line, with some fish contributed by commercial haul netting operations. Fish were held in boat-based tanks prior to surgery and released at the capture location. Surgical implantation of

Vemco (Amirix Systems Inc., Halifax, Nova Scotia Canada) acoustic transmitters (V9-

2L, low power, 180-300s delay, 759-959d estimated tag life) was conducted following techniques outline in Walsh et al. (2012a). Location, fork length (FL) and sex were recorded, with sex determined, where possible, by macroscopically identification of gonads during implantation of the transmitter. Fish were released on location as soon as they had fully recovered from the anaesthetic. Data was excluded for a period of 14 days post-surgery to allow fish to return to regular behaviour. Due to multiple tagging cohorts and the tag life of the transmitters, not all fish are exposed to the same environmental conditions. Caution needs to be taken when interpreting the results due to this.

4.2.3 Ethics statement

This study was carried out in strict accordance with the recommendations in Barker et al. (2009), and handling of animals was permitted under New South Wales Department of Primary Industries Animal Research Permit (09/01). All surgery was performed under anaesthesia, and all efforts were made to minimize suffering. Capture and tagging of fish in the Shoalhaven and Clyde rivers during this study was permitted under

Section 37 of the NSW Fisheries Management Act 1994 through Scientific Research

Permit number P01/0059 (issued by NSW Department of Primary Industries).

van der Meulen, D.E. 95 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Table 4.1 Summary of Sand Whiting tagged in the Shoalhaven and Clyde rivers.

Serial No. Capture Date River Location Capture Location Fork Length (mm) Sex n Detections Days Detected 1060955 25/11/2009 Shoalhaven River S1 311 M 9894 635

1066613 25/11/2009 Shoalhaven River S1 295 U 2793 384

1066614 25/11/2009 Shoalhaven River S1 295 U 11168 419

1066617 25/11/2009 Shoalhaven River S1 305 U 9557 416

1060952 25/11/2009 Shoalhaven River S4 310 F 18974 424

1060961 # 25/11/2009 Shoalhaven River S4 297 M 58 1 1066608 25/11/2009 Shoalhaven River S4 311 U 293 168

1066621 25/11/2009 Shoalhaven River S4 293 M 8657 709

1060933 23/11/2009 Shoalhaven River S5 302 U 674 85

1060935 # 23/11/2009 Shoalhaven River S5 328 M 339 11 1060938 23/11/2009 Shoalhaven River S5 301 M 600 79

1060939 23/11/2009 Shoalhaven River S5 302 M 3464 341

1060940 23/11/2009 Shoalhaven River S5 330 M 5912 256

1066615 23/11/2009 Shoalhaven River S5 324 U 9104 420

1107849 5/04/2011 Shoalhaven River S1 335 M 9840 146

1107850 5/04/2011 Shoalhaven River S1 333 M 57617 811

1107851 # 5/04/2011 Shoalhaven River S1 337 F 63 1 1107852 * 5/04/2011 Shoalhaven River S1 326 M 474 3 1107857 5/04/2011 Shoalhaven River S1 325 M 9716 812

1107865 * 5/04/2011 Shoalhaven River S1 320 M 172 6 1083462 * 7/04/2011 Shoalhaven River S2 308 M 326 5 1083458 6/04/2011 Shoalhaven River S3 308 F 56691 939

1101281 6/04/2011 Shoalhaven River S3 330 M 16495 353

1101282 * 6/04/2011 Shoalhaven River S3 336 F 117 2 1101283 * 6/04/2011 Shoalhaven River S3 327 F 228 4 1083446 * 6/04/2011 Shoalhaven River S5 329 F 245 4 1083452 6/04/2011 Shoalhaven River S5 310 F 24143 329

1101289 6/04/2011 Shoalhaven River S5 333 F 63810 325

1107843 * 6/04/2011 Shoalhaven River S5 316 F 82 1 1107844 # 6/04/2011 Shoalhaven River S5 295 M 1887 13 1083451 5/04/2011 Shoalhaven River S5 276 M 16402 135

1083456 5/04/2011 Shoalhaven River S5 327 F 283005 938

1083503 * 5/04/2011 Shoalhaven River S5 329 F 211 7 1083507 5/04/2011 Shoalhaven River S5 311 F 32498 222

1083438 27/01/2011 Clyde River C1 297 F 46776 727

1083440 14/01/2011 Clyde River C1 290 M 7217 790

1083461 * 9/05/2011 Clyde River C1 306 M 546 4 1083466 # 21/04/2011 Clyde River C1 335 F 3717 27 1083501 27/01/2011 Clyde River C1 406 F 65938 461

1083505 27/01/2011 Clyde River C1 270 F 7590 742

1101267 14/01/2011 Clyde River C1 320 F 4788 221

1101277 * 17/10/2010 Clyde River C1 372 F 562 5 1101284 9/01/2011 Clyde River C1 391 F 119556 626

1101285 14/01/2011 Clyde River C1 330 F 30260 949

1101286 # 14/01/2011 Clyde River C1 417 F 282 49 1083441 # 19/04/2011 Clyde River C2 324 M 464 887 1083455 23/04/2011 Clyde River C2 294 F 163785 939

1101287 * 19/04/2011 Clyde River C2 347 M 406 2 1083447 21/04/2011 Clyde River C2 340 F 1779 147

1083448 # 20/04/2011 Clyde River C2 320 M 9111 28 1101288 * 22/04/2011 Clyde River C2 331 F 469 4 1060964 29/11/2012 Clyde River C1 270 M 1678 247

1083464 * 29/11/2012 Clyde River C1 287 M 432 14 1101290 # 29/11/2012 Clyde River C1 315 F 54 211 1101292 22/11/2012 Clyde River C1 270 F 19585 519

1146395 # 14/11/2012 Clyde River C1 265 U 398 411 1146397 21/11/2012 Clyde River C1 265 M 802 277

1146398 * 12/12/2012 Clyde River C1 370 M 229 4 1146400 21/11/2012 Clyde River C1 274 M 2720 309

1146401 21/11/2012 Clyde River C1 294 M 444 254

1146402 # 12/12/2012 Clyde River C1 300 F 87 198 1146403 14/11/2012 Clyde River C1 262 F 4630 370

1146404 15/11/2012 Clyde River C1 250 M 1584 412

1148484 # 15/11/2012 Clyde River C1 361 F 810 8 1148485 15/11/2012 Clyde River C1 333 F 1289 224

1148486 12/12/2012 Clyde River C1 382 U 252 169

1148487 14/11/2012 Clyde River C1 308 M 435 210

1148488 * 14/11/2012 Clyde River C1 355 F 450 3 1148490 22/11/2012 Clyde River C1 375 F 1065 210

1148491 # 29/11/2012 Clyde River C1 360 F 89 51 1148492 14/11/2012 Clyde River C1 356 F 325 210

1148493 # 14/11/2012 Clyde River C1 346 F 24 5 * Fish detected making offshore movement soon after tagging.

# Fish not used in data analysis due to insufficient detections.

M=Male, F=Female, U=Unidentified. van der Meulen, D.E. 96 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

4.2.4 Acoustic array and data collection

Two linear acoustic arrays were established between the estuary entrance and the tidal limit in the Shoalhaven and Clyde rivers, comprising 39 and 34 Vemco VR2W acoustic receivers respectively (Figure 4.1). The arrays were optimised to examine large-scale linear movements of fish species within the estuary (Taylor et al. 2014; Walsh et al.

2012b). Receivers recorded time, date, fish identity and station name. Temperature and conductivity were recorded using five Odyssey data loggers (Dataflow Systems Pty.

Ltd. Christchurch, New Zealand) which were evenly distributed throughout the length of each estuary (Figure 4.1). Odyssey data loggers were configured to record data every hour, and were downloaded at regular intervals along with the acoustic receivers using the Odyssey Data Logging Software (Dataflow Systems Pty. Ltd. Christchurch, New

Zealand). Data was further processed in Microsoft Excel and stored in a Microsoft

Access 2007 database. Loggers located at fixed locations of 6.9 km and 10.8 km (for the

Shoalhaven and Clyde rivers respectively) from the estuary mouth were used for analysis as they provided the most complete and comparable data sets between the estuaries. Direct comparisons between rivers could not be made due to variation in the loggers locations exposing them to different temperature regimes. River height gauging stations located at Grassy Gully (NSW Office of Water gauge station 215216,-34.845,

150.432) in the Shoalhaven River and Brooman (NSW Office of Water gauge station

216002, -35.4681, 150.2394) in the Clyde River were used to determine freshwater flow input. Meteorological data was obtained for Nowra, NSW (Australian Government-

Bureau of Meteorology station number 68072, -34.94, 150.55) for the Shoalhaven River and Moruya, NSW (Australian Government-Bureau of Meteorology station number

69148, -35.91, 150.14) for the Clyde River. Astrological data was obtained from van der Meulen, D.E. 97 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Geoscience Australia (Geoscience Australia, 2012) and tidal data came from the

National Tide Centre (Bureau of Meteorology) and Manly Hydraulics Laboratory

(Manly Vale, NSW). The spawning season of Sand Whiting was classified as 1st

December to 31st March, based on the gonadosomatic index (GSI) determined from a centrally located estuary, St. Georges Basin, NSW (-34.13, 150.60) in 2004-05 (NSW

DPI unpublished data).

4.2.5 Data analysis

Raw data from the acoustic receivers (VR2W) was downloaded at regular intervals using Vemco User Environment (VUE) software and stored in a Microsoft Access 2007 database. Data produced in this study was also stored on the Integrated Marine

Observing System – Animal Tracking Facility (IMOS-ATF) database on the Australian

Ocean Data Network (AODN) portal (https://animaltracking.aodn.org.au/). A linear distance from sea was determined for each receiver station using ArcGIS ArcMap v10.2.2 (ESRI, Redlands, California USA), based on the nearest distance of the receiver station to the river midline, and a value was assigned to each detection accordingly.

Data were summarised in hourly bins, by calculating the average distance from sea from detection positions for the fish during that hour period. For hours when fish were not detected an assumed distance from sea was assigned using the calculated slope between the hourly distance from sea and the number of lapsed hours. This was only possible due to the low number of missed detections that occurred when fish passed receivers allowing a complete dataset to be formed that could be compared against environmental variables. Movement rate was determined as the distance travelled per hourly calculated fish position. Repetitive distance from sea and movement rate calculations were van der Meulen, D.E. 98 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

conducted using R v. 3.0.2 (R Development Core Team 2013). Daily average positions were calculated from hourly fish positions. This process was conducted to address problems associated with detection variability due to biological and environmental noise (Payne et al. 2010; Stocks et al. 2014) and ensured the data was comparable across individuals.

Temperature (Temp, °C) and conductivity data (Cond, mS/cm), meteorological data (air temperature, rainfall, humidity, barometric pressure, wind speed and direction), astronomical data (day/night/dusk/dawn, where dusk and dawn are determined as one hour before and after sunset or sunrise, respectively; moon phase), tidal data (river height, flow direction) river flow data and spawning season (Spawn, December to

March) were converted into hourly averages and matched to hourly position data

(DistSea, m) in the database for each fish to be used in further data analysis. Flow information was used to calculate the Boolean variable HighFlow , which represented the top 5% of flow rates detected at the logging station across the duration of the study

(Devlin et al. 2010).

Initially, general trends in the data were explored using parametric tests to examine the relationship between the number of spawning migrations with fork length (linear regression) or sex (1-factor ANOVA). Furthermore, the length of time Sand Whiting spent within the spawning location was compared between estuaries (1-factor

ANOVA), and the average daily movements inside and outside of spawning periods

(paired t-test).

van der Meulen, D.E. 99 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

A linear mixed-effects model was used to examine the effect of HighFlow, Temp, Cond and Spawn on DistSea , with individual fish included as a random effect (Payne et al.

2013). How Temp impacted DistSea during the spawning season was important, so an interaction term, Temp:Spawn, was included. Predictors were scaled to range from -1 to

1 (Kleijnen 1997) and centred (Aitken and West 1991). Inclusion of predictors were assessed on the basis of Bayesian Information Criterion (BIC, which generally provides a simpler parsimonious model), and significant interaction terms were interpreted using

‘simple slopes’ parameter estimates (Aitken and West 1991).

4.2.6 Egg sampling

Temporal variation in the relative abundance of Sand Whiting eggs adjacent to aggregation sites was investigated. A circular plankton net (1 m Ø x1.5 m length, 50 μm mesh) was used to sample eggs by deploying the net to the substrate and vertically hauling the net to the surface. Five replicate lifts were made each hour over a 36-h period during the full moon, commencing at 09:00 hrs (Eastern Daylight Savings Time) on 11th February 2012. The sampling site was selected based on the location of Sand

Whiting aggregation within the proposed spawning site from this study. Sample locations were recorded using GPS, and water depth was used to standardise plankton lifts. Samples were immediately stored on ice in sample jars and later photographed and measured. Sand Whiting eggs were identified as a transparent pelagic egg (0.68-

0.72mm Ø) with a marginally opaque oil globule (~0.18mm Ø) with black edging

(Neira et al. 1998; Tosh 1902). Eggs were identified, counted and staged (Jones et al.

1978), with egg stage greater than morula excluded from analysis as they were likely

van der Meulen, D.E. 100 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

spawned outside of the one hour sampling period. Egg abundance was plotted against tide and diel period to determine the timing of the spawning event.

van der Meulen, D.E. 101 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

4.3 Results

A total of 651,307 and 482,498 detections were analysed from 22 Sand Whiting tagged in the Shoalhaven River and 21 Sand Whiting tagged in the Clyde River respectively

(Table 4.1). From 72 fish originally tagged, 14 fish provided insufficient data and 15 fish made offshore movements soon after release, so were excluded from analysis

(Table 4.1). The short tag duration of some fish could be caused by mortality, predation, tag rejection or tag failure. Tracked Sand Whiting in the Shoalhaven and

Clyde rivers were detected within the study area for 78-939 days and 146-949 days respectively ( Table 4.1). Sand Whiting movements were characterised by long periods spent in upstream residences during April to November (autumn, winter and spring) each year (Figure 4.2). From December to March (summer), the majority of fish undertook multiple rapid migrations from their upstream residences to a common location at the estuary entrance (Figure 4.2). These rapid migrations coincided with the spawning season for this species and are subsequently termed “spawning movements”.

van der Meulen, D.E. 102 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

4.3.1 Spawning movements

During the spawning season, individual Sand Whiting were observed to conduct up to

26 (11.03 ± 1.52, mean ± S.E.) and 25 (9.34 ± 1.51, mean ± S.E.) spawning movements from their upstream residences to a common location at the entrance of the river van der Meulen, D.E. 103 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

systems, travelling up to a maximum total linear distance of 936 km (440.23 ± 29.91, mean ± S.E.) and 385 km (161.22, ±17.43, mean ± S.E.) for the Shoalhaven and Clyde rivers respectively (Figure 4.2).

Table 4.2 Summary of linear mixed-effects models (individual fish ID included as a random effect) of Distance-from-sea (DistSea) explained by biological and environmental factors for both the Shoalhaven and Clyde rivers. Shoalhaven Value SE DF t p (Intercept) 0.133 0.059 149263 2.241 0.025 HighFlow -0.101 0.005 149263 -21.782 0.000 Temp 0.256 0.003 149263 81.986 0.000 Cond 0.060 0.003 149263 21.566 0.000 Spawn -0.183 0.004 149263 -49.043 0.000 Temp:Spawn -0.336 0.009 149263 -39.485 0.000

Clyde Value SE DF t p (Intercept) 0.029 0.006 151859 4.746 0.000 HighFlow -0.101 0.003 151859 -34.191 0.000 Temp 0.088 0.002 151859 46.095 0.000 Cond -0.026 0.002 151859 -11.734 0.000 Spawn 0.065 0.003 151859 24.724 0.000 Temp:Spawn -0.291 0.005 151859 -54.697 0.000

Fish only spent a short period of time at the spawning locations during each migration in the Shoalhaven River (2.15 ± 0.35 days, mean ± S.E.) and Clyde River (1.47 ± 0.28 days, mean ± S.E.) before returning to their original residences. There was a significant positive relationship between fork length and the number of spawning movements for

2 Sand Whiting in the Shoalhaven River (β = 0.24, F1,16 = 5.47, P = 0.03, R = 0.26), this relationship was not significant within the Clyde River (β = 0.02, F1,17 = 0.40, P = 0.54,

R2 = 0.02)(Figure 4.3). Also, there was no significant difference observed in the number of spawning movements conducted by males and females in the Shoalhaven

(F1,10 = 0.67, P = 0.43) or Clyde rivers (F1,16 = 0.47, P = 0.51), or the number of

van der Meulen, D.E. 104 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

spawning movements conducted by fish between the Shoalhaven and Clyde rivers (F1,35

= 0.62, P = 0.44).

Figure 4.3 Relationship between fork length (FL) and the average number of movements towards the river entrance observed during the spawning season for Sand Whiting in the Shoalhaven River (closed circle, dashed line) and Clyde River (open circle, solid line).

Sand Whiting spent significantly more time within the spawning location in the

Shoalhaven as opposed to the Clyde River (F1,34 = 4.56 , P = 0.04). Average daily rate of movement was significantly higher during the spawning periods compared to the non-spawning periods for both the Shoalhaven (t14 = 7.57, P < 0.001) and Clyde rivers

(t17 = 4.83, P < 0.001). In the Shoalhaven, Sand Whiting moved 4.46 ± 0.27 km (mean

± SE) per day during the spawning period and 2.15 ± 0.94 km (mean ± SE) during the non-spawning periods and in the Clyde River moved 1.53 ± 0.20 km (mean ± SE) during the spawning period and 0.30 ± 0.26 km (mean ± SE) during the non-spawning period (Figure 4.2).

van der Meulen, D.E. 105 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Water temperatures exceeding 20°C in the Shoalhaven River and 22°C in the Clyde

River recorded at the logger locations coincided with the onset of distinct spawning movements along the estuary (Figure 4.2 and Figure 4.4). The terms, HighFlow, Temp,

Cond, Spawn, Temp:Spawn were found to significantly influence the Distance-from-sea

(DistSea) of tagged Sand Whiting for both the Shoalhaven and Clyde rivers (Table

4.2). Further interpretation of the interaction term indicated that during the spawning season, Sand Whiting were found to move closer to the entrance of the river as temperatures increased. However, the reverse was true outside of the spawning period, with decreasing upstream temperatures associated with movement towards the river entrance (Figure 4.4 c,d). Thus, Sand Whiting movements during the spawning season positively correlated with increasing water temperature for both the Shoalhaven and

Clyde rivers, but did not correlate with temperature outside of this period (Figure 4.4).

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Visual inspection of data collected during the spawning period suggested that movements towards the entrance of the river coincided with short-term fluctuations in water temperature. As temperature increased during the spawning season, fish were found to migrate to the entrance of the river and then would return to upstream residences as the temperature decreased again (Figure 4.5). This relationship did not van der Meulen, D.E. 107 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

appear to rely on a threshold temperature, but rather was dependent on the changing thermograph.

4.3.2 Egg abundances

Egg sampling conducted in the Clyde River revealed that the mean number of eggs in the water column peaked at 48.24 ± 6.69 (mean ± SE) eggs per m3. Specifically, egg abundance was higher during the nocturnal high tide, peaked one hour after the high tide, and abruptly decreased within three hours following the high tide (Figure 4.6). All eggs captured were in early stages of development, indicating that they were recently spawned.

van der Meulen, D.E. 108 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Figure 4.6 Mean (± S.E.) number of Sand Whiting eggs captured per m3 from the Clyde River in relation to tidal height and day (white), night (grey). Start date was 11th February 2012.

4.4 Discussion

4.4.1 General spawning movements

Factors affecting the spatial and temporal selection of spawning sites are complex and poorly understood, but ultimately contribute to the reproductive success and resilience of many marine and estuarine fishes. Furthering our knowledge of the spatial ecology related to the spawning dynamics of estuarine-dependent fish is needed for the integration of larger conceptual life-history and population models, and to increase our ability to effectively and spatially manage fish stocks (Lowerre-Barbieri et al. 2017;

Lowerre-Barbieri et al. 2014). Acoustic telemetry enables us to observe spawning- related movements and behaviors in-situ, which can in-turn increase our knowledge of cues for movements, locations and timing of spawning events and dispersal of eggs and larvae. Sand Whiting within both the Shoalhaven and Clyde rivers displayed abrupt van der Meulen, D.E. 109 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

changes in their movement patterns which corresponded with the onset and completion of the spawning season. Tagged individuals would conduct multiple, rapid movements between a distinct upstream location to an area at the river entrance and in some cases offshore, displaying high levels of site fidelity and attachment within the range of the receivers (1-2 km). That tagged individuals initially distributed throughout the river congregated on a single location at the entrance of the river when and where Sand

Whiting eggs were captured suggests these movements are indeed spawning migrations.

Intra-estuarine spawning migrations towards river entrances have been observed in other estuarine-dependent fish species distributed along Australia’s east coast including

Estuary Perch, Percalates colonorum (van der Meulen et al. 2014; Walsh et al. 2013b), and Mulloway, Argyrosomus japonicus (Taylor et al. 2014). In addition, this behaviour is observed in species in other regions, such as Common Snook, Centropomus undicimalis (Adams et al. 2009; Lowerre-Barbieri et al. 2014) and Whitemouth

Croaker, Micropagonias furnieri (Acha et al. 1999). However, no species have been observed making migrations to and from the spawning grounds as frequently and across such distances as Sand Whiting.

Despite the lack of research on the spawning frequency for this species, observed multimodal egg size distributions (Cleland 1947; Morton 1985) are consistent with those of multiple-batch broadcast spawners. Histological examination of ovarian tissue suggests that multiple-batch broadcast spawners are capable of repeat spawning at high frequencies. For example, Yellow Sea Bream Dentex hypselosomus, were capable of spawning on 2-3 consecutive days throughout the spawning season (Yoda and Yoneda

2009), Queenfish, Seriphus politus. spawn on average every 7.4 days (Demartini and van der Meulen, D.E. 110 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Fountain 1981) and spawning frequency of Common Snook, Centropomus undecimalis, was found to be every 1-2.5 days (Taylor et al. 1998). It is possible that, for Sand

Whiting, each movement towards the river entrance may coincide with at least one spawning event. The high frequency spawning strategy suggested here is in contrast to an earlier study which only found two discrete peaks in juvenile abundance across a single recruitment period (Smith and Sinerchia 2004). Smith and Sinerchia (2004) suggest that juvenile abundance either reflects the timing of spawning events or the timing of favorable recruitment conditions to which the larvae are exposed. Based on the assumption that each spawning movement represents at least one spawning event, it would appear that episodic recruitment events may be a result of favourable conditions for egg and larval survival and not reflective of episodic spawning. These results are supported by Cushing’s match-mismatch hypothesis, which explains that variation in stock recruitment can be driven by matching (or not matching) spawning timing with favorable biotic and abiotic conditions (see Cushing 1990).

Downstream migrations occurred throughout the spawning period, with larger individuals conducting more migrations than smaller individuals. While this study was unable to determine that each movement corresponds to a spawning event, the results do suggest that larger individuals are more active during the spawning season. In multiple- batch spawners, age has been found to be positively related to both the number of batches an individual can produce, and the duration of spawning (Lowerre-Barbieri et al. 2009; Wright and Trippel 2009). Additionally, batch fecundity has been found to increase significantly with size for other sillaginid species (Gray et al. 2014).

Demographic trends in spawning behavior can influence the reproductive resilience of fish populations (Lowerre-Barbieri et al. 2015; Lowerre-Barbieri et al. 2017). The van der Meulen, D.E. 111 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

presence of older, larger individuals in the spawning population may have important implications for reproductive output and success, and needs to be further investigated.

The results suggest that Sand Whiting may spawn within 1 h of nocturnal high tides.

However, caution should be taken when interpreting these results as sampling was only conducted over a short period in one river system. Similar timing of spawning events, occurring within the first hour after a high tide, have been observed in Estuary Perch

(van der Meulen et al. 2014). By coinciding spawning with high tides and positioning at the entrance of rivers, Sand Whiting may export fertilized oocytes offshore, onto the nearshore coastal shelf regions. Sand Whiting larvae have been found in coastal waters and entrained in anthropogenic plumes (Gray 1996), have been caught entering estuaries on incoming tides (Miskiewicz 1987; Neira et al. 1998) and found recruiting into estuarine nursery habitats (Hannan and Williams 1998). This larval export strategy, disperses larvae via coastal winds, waves and currents and allows genetic mixing and inter-estuarine connectivity in the absence of large-scale adult movements (see Bilton et al. 2002).

4.4.2 Role of temperature on spawning dynamics

Temperature was found to play a significant role in the reproductive dynamics of Sand

Whiting. While freshwater flows were correlated with downstream shifts in fish distributions, these events were infrequent and did not impact the high frequency spawning movement patterns. Additionally, the drivers of movements of estuarine fish in relation to flows have been well studied and show direct similarities to my findings

van der Meulen, D.E. 112 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

(Payne et al. 2013; Payne et al. 2015b; Sakabe and Lyle 2010; Taylor et al. 2014;

Walsh et al. 2013b).

The onset of the spawning season coincided with distinct movements towards the river entrance and abrupt increases in the rate of movement. These movement patterns occurred when water temperatures approached the thermal optimum for swimming activity and reproductive growth of this species (Payne et al. 2016). This result is unsurprising, because such temperatures have been found to be a predictive factor for the onset of reproductive activity (Anguis and Cañavate 2005; Hilder and Pankhurst

2003; Pankhurst and Porter 2003; Payne et al. 2016; Shimizu 2003), presumably because they allow fish to operate at the peak efficiency while undertaking such energy- intensive spawning events. Sand Whiting are distributed throughout the tropics and sub- tropics, and this biogeography may explain why fish, in this temperate study site, select the highest available temperatures for spawning and activity.

Rapid movements towards and away from the spawning grounds located at the entrance of the river, in some cases, coincided with short term increases and decreases in temperature, respectively (see Fig 4.5). As a result, fish distributed throughout the river may synchronize movements to a common location. For successful spawning to occur within multiple-batch spawners, fish need to synchronize gamete maturity and release within and between genders (Wright and Trippel 2009). Documented spawning cues include moon phase (Gladstone 2007; Park et al. 2006; Takemura et al. 2004), tidal cycle (Garratt 1993; van der Meulen et al. 2014; Yamahira 2001), diel period

(Danylchuk et al. 2011), currents (Lobel 1989) and temperature (Danilowicz 1995;

Hilder and Pankhurst 2003; Sheaves 2006; Sims et al. 2004), all of which likely play a van der Meulen, D.E. 113 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

role in spawning output and fertilization success. Although, studies assessing individual cues for multiple spawning movements within spawning seasons are rare, there is evidence that suggests this movement behavior is not unique among species within the study area (Walsh et al. 2013b). While temperature appears to be correlated with the rapid movements observed for Sand Whiting, the underlying factors driving movements are likely complex. The high levels of site fidelity and the rapid movements observed between the upstream residence locations and the downstream spawning locations suggest that the benefits of moving between locations outweigh the benefits of remaining at the one location. Sand Whiting maximised time spent at familiar upstream locations which are not only warmer, during summer, but also likely to contain the abundant prey required to feed high metabolic demands. In addition, high levels of site fidelity are believed to reduce predation and increase feeding efficiency because of familiarity with the chosen location (Childs et al. 2008a; Kramer and Chapman 1999).

This aggregation of individuals at specific locations potentially increases spatial vulnerability to predation and fishing pressures (Claydon 2004; Coleman et al. 1996;

Sadovy and Domeier 2005), but while synchronised spawning did occur, spawning movements differed among individuals. This combined with the short time that individuals would spend in the spawning ground, should spread the risk for both the spawners and the subsequent larvae.

Behavioral thermoregulation has been suggested to occur for a number of different species during their spawning season or while carrying offspring. For example, adult

Sockeye Salmon, Oncorhynchus nerka, move vertically to optimal temperatures within stratified lakes prior to spawning (Newell and Quinn 2005), Leopard Sharks, Triakis semifasciata, move into warmer shallow water for extended periods which may aid in van der Meulen, D.E. 114 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

digestion, somatic growth and or reproduction (Hight and Lowe 2007) and Bluefin

Tuna, Thunnus thynnus, change their diving behavior and thermal biology during different stages of their spawning migrations (Teo et al. 2007). This behaviour increases metabolic outputs and development of gametes, allowing fish to be ready to spawn sooner than if they were to remain at single locations. Similarly, by coinciding spawning with increasing temperature, egg development, egg survival and larval growth are optimized (Caputi et al. 1996).

4.4.3 Role of currents in temperature-mediated spawning

During summer, Sand Whiting move towards downstream spawning grounds when coastal temperatures increase and retreat upstream as temperatures decrease.

Temperature variation within the river is more closely linked to oceanic temperature conditions than air temperature (Figure A.1), it is likely that turbulent mixing in the middle to lower estuarine reaches by powerful tidal currents rapidly disperses oceanic temperature conditions to upstream locations. Conditions in the marine environment that coincide with short-term episodic increases in temperature (Figure 4.5) are likely to favour spawning and survival of offspring. The driving factors behind the short-term episodic fluctuations in water temperature are related to the prevailing winds (from NE and SE) that occur during summer on the east coast of NSW. Ekman transport drives net water movement 90 degrees to the left of the wind direction in the southern hemisphere (Gibbs et al. 1998; Griffen and Middleton 1991), and thus a south-easterly wind transports surface water towards the coast and drives warm clear water of the East

Australian Current westward (Figure 4.7). When the wind blows from the NE, the net water transport is offshore, moving surface water away from the coast and drawing up van der Meulen, D.E. 115 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

Figure 4.7 (a) Wind rose for summer winds (2011) displaying the number of hours the wind was greater than 15 knots recorded at Nowra, NSW. (b) Average (±SE) ocean water temperature for each wind direction (>15knts) during summer 2011, displayed with a two day delay to allow for lag between wind and change in water temperature. (c) Conceptual figure showing the direction of summer trade winds and the corresponding net water movement caused by Ekman’s transport. van der Meulen, D.E. 116 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

deeper cooler water near the coast (Figure 4.7). The cycle between the NE and SE winds is approximately three to seven days (Griffen and Middleton 1991), and the variation in summer water temperature between upwelling and down-welling conditions was found to be from 14 to 22°C, respectively. The effects of this process can be variable and depends on wind-fetch, duration and strength (see Sponaugle et al. 2002 for Ekman transport examples).

These results suggest temperature variation determines the general timing of spawning movements, and that these events appear to coincide with down-welling oceanographic conditions and warmer coastal temperatures. Spawning output has been found to vary with the strength and direction of the current, and this may contribute to variation in recruitment (Lobel 1989). Additionally, Sand Whiting presumably favour these current conditions because they provide an ecological or physiological benefit which increases reproductive fitness and recruitment. For example, timing and location of spawning may occur to distribute larvae at locations with reduced numbers of predators and high food availability (Castro et al. 2000). For Sand Whiting, spawning during down-welling conditions may deliver eggs and larvae to clear, warm water with decreased numbers of predator. The periodic switching to high nutrient upwelling conditions along the coast may deliver trophic benefits by increasing food availability at a time after which yolk sac feeding will have ceased.

The strength and direction of currents influence recruitment and fishery landings worldwide (Caputi et al. 1996; Gaughan 2007; Griffin et al. 2001; Morgan et al. 2012;

Roughgarden et al. 1988). For example, the strength of the Leeuwin Current off the coast of Western Australia can influence the recruitment of various coastal fish and van der Meulen, D.E. 117 Chapter 4: Temperature mediates spawning migrations of Sand Whiting

crustacean species (Caputi et al. 1996). Similarly, in years when the California Current is strong and flowing towards the equator, recruitment of Rockfish (Sebastes spp.) increases (Ralston et al. 2013). While there is a good understanding of how current processes are linked to recruitment, there is a need to determine how the timing of spawning events may be interconnected. The wind-driven processes that influence temperature fluctuations on the south-eastern coast of Australia may not be present throughout the large distribution of Sand Whiting, so further work to understand the spawning dynamics across a broader geographical range should be considered.

4.4.4 Management implications

The increased rate of movement observed during the spawning season and the high site fidelity to both spawning and non-spawning grounds increases the susceptibility of Sand

Whiting to capture by both gill net and haul net fisheries. Sand Whiting landings peak during the summer months (Rowling et al. 2010a), which coincides with the spawning season of the species. There is worldwide concern over the targeting of spawning aggregations of fish because it can lead to rapid depletion of fish stocks (Sadovy and

Domeier 2005). I suggest that future spatial management arrangements could consider both the spawning locations and residence locations of the species, to effectively reduce fishing pressure. The temporary closure of such locations may help ensure that natural breeding processes can proceed, which should in turn lead to enhancement of recruitment and productivity.

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4.4.5 Conclusion

Sand Whiting conducted intra-estuarine spawning movements prompted by temperature fluctuations driven by coastal wind and current conditions, spawning on nocturnal high tides adjacent to river entrances. Additionally, Sand Whiting movements were consistent with behavioral thermoregulation, taking advantage of environmental temperature heterogeneity to access temperatures closer to their thermal optimum.

Presumably, this behavior optimizes reproductive output, increasing survival of eggs and larvae, and recruitment into the adult population. Because movement and reproduction in this species appears very closely regulated by temperature, future changes in environmental conditions may strongly influence the timing, duration, and success of spawning in Sand Whiting.

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Chapter 5: High precision homing during spawning migrations

of a sediment-specialist

Abstract

The homogeneous landscape of sediment substrates supports the belief that sediment specialised fish would display low levels of site attachment and site fidelity due to the lack of distinct features in the environment to associate with. This study examined the fine-scale movements, habitat association and spawning dynamics of Sand Whiting,

Sillago ciliata, within upstream residential and downstream spawning grounds using two dimensional passive acoustic tracking. Sand whiting were found to have extremely small core home ranges for most of the year, with almost no overlap between tagged individuals in their upstream habitats. Furthermore, they displayed high levels of site attachment and site fidelity, generally occupying the same distinct location for the entire

8-month study period. The affinity to such small core home ranges upstream was particularly striking given sand whiting would conduct up to 15 migrations over the 4- month spawning season, to spawning habitat ~8km away where they would form aggregations, and return each time to the same location from which they initiated their migration. This study shows that fish can exhibit strong site attachment to relatively featureless environments such as sediment substrates and that these areas should be considered for fish conservation and restoration programs.

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5.1 Introduction

Site fidelity, or philopatry, is the tendency of an organism to stay in or habitually return to a particular area. This strategy can increase survival through association with habitats where food is abundant (Prange et al. 2003), competition is limited and the likelihood of predation is reduced (Heithaus and Dill 2002); and can contribute to reproductive success by repeating events that lead to the survival of offspring (Bollinger and Gavin

1989). Detailed knowledge of a species home range, habitat preferences and site fidelity is essential to developing a complete understanding of marine ecosystems (Donaldson et al. 2014), determine impacts from environmental and anthropogenic disturbances (Dean et al. 2012; Payne et al. 2015a) and is imperative for effective spatial management (Rice

2005).

For fishes, there is a wealth of information about species that interact with structurally complex marine environments such as reefs (Ferguson et al. 2013a; Meyer and Holland

2005; Piraino and Szedlmayer 2014), or broad scale movement of coastal and pelagic species (Jorgensen et al. 2009; Lowerre-Barbieri et al. 2016). However, limited work has been conducted on fish that associate with more homogeneous environments, such as sediment specialised fish (Furey et al. 2013). Areas of shallow water sediment are responsible for a large proportion of the primary production in estuaries (Underwood and Kromkamp 1999). This supports a large biomass of benthic invertebrates, including crustaceans, polychaetes and molluscs, each of which are preyed on by fish, rays and shore birds which have evolved to take advantage of this distinct ecological niche

(Kalejta and Hockey 1991). The marine benthos is subject to erosion and deposition processes and, as such, can be altered by dredging (Nitsche et al. 2007), implementation van der Meulen, D.E. 121 Chapter 5: Spawning and homing of Sand Whiting

of rock training walls, sea walls and groines (Levings 1980) and sediment inputs from land-clearing practices (Wood and Armitage 1997) and natural events such as floods

(Miller et al. 2002). There is a clear need to better understand how fish associate with soft sediments from both an ecological and management perspective.

Sand Whiting, Sillago ciliata, are a sediment-specialised sillagnid that inhabit nearshore and estuarine environments (Henry and Lyle 2003; Rowling et al. 2010a) where they prey primarily on benthic crustaceans and polychaetes. They have been found to make rapid, large-scale spawning migrations from specific upstream, middle estuarine locations to estuary entrances and offshore based on temperature and flow cues (Chapter

4). Sand whiting are exploited by both commercial and recreational fishers with peaks in commercial harvest occur during summer (Henry and Lyle 2003; Rowling et al.

2010a), which coincides with spawning (Morton 1985; Ochwada-Doyle et al. 2014).

There is a need to further develop our understanding of the fine-scale movements and spawning dynamics of this species to sustainably manage this resource.

To address this, the habitat requirements and movement characteristics of Sand Whiting were investigated using fine-scale passive acoustic telemetry. This was conducted during and outside of the breeding season at areas identified as downstream spawning grounds and upstream resident locations (Chapter 4). Specifically, this study evaluated

(1) fine-scale spatial and temporal distribution of Sand Whiting; (2) key habitat selection of Sand Whiting; and (3) temporal changes of activity in Sand Whiting.

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5.2 Methods

This study was conducted within the Clyde River, NSW Australia (35.698°S,

150.155°E; Figure 5.1). The Clyde River is a permanently open, intermediate, tidal dominated, drowned valley estuary that flows into an ocean embayment at the town of

Batemans Bay (Roy et al. 2001). Two separate Vemco Positioning System (VPS) arrays of acoustic receivers were deployed to monitor the fine-scale movements of whiting. Locations were chosen based on large-scale acoustic tracking of whiting conducted during 2011 and 2012. These arrays were located 2.5 km and 9 km from the river entrance, and consisted of 23 and 15 Vemco (Amirix Systems, Halifax, Nova

Scotia, Canada) VR2W acoustic receivers and co-located synchronising transmitters, respectively (Figure 5.1). The array was optimised to ensure that for each tag transmission, detections would occur on a minimum of three receivers, allowing fine- scale position estimates. Twenty four Sand Whiting were tagged within the upstream array using baited hook and line and were surgically implanted with Vemco acoustic transmitters (V9, low power, 180-300s random delay, 759-959d estimated tag life).

Surgery was conducted in situ, onboard the research vessel and fish were returned to the water as soon as they had recovered from anaesthetic. Sex was determined, where possible, by macroscopically identification of gonads during surgery and implantation of the transmitter. Surgery procedures were conducted as per Walsh et al. (2012a).

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All data was analysed by Vemco using the VPS position algorithm which returned for each transmission; a fish location estimate, time of transmission and a horizontal position error (HPE) estimate (Smith 2013). Fish location data were imported into

ArcGIS 10.2 (ESRI, Redlands, California). A comparison between the HPE and the known distance error based on stationary transmitters (synchronising and reference tags), was used to filter fish detections with HPE > 15 (equivalent to ~5m ø for both arrays), retaining sufficient detections while increasing the accuracy of the data (Smith

2013). Kernel Density Estimates (KDE) were processed for each fish using Geospatial

Modelling Environment (Beyer 2012; R Development Core Team 2013), using a plugin bandwidth estimator (Jones et al. 1996) and a Gaussian kernel type. A cell size of 5 m was used as this was the average error associated with the positioning system. Positions were time weighted to account for areas within the array where the probability of detection was lower. Core and total utilisation distributions (UD) areas were derived from the 50% and 90% KDE isopleths, respectively. Core and total UDs were calculated for each fish within the upstream residence and downstream spawning locations.

Subtidal habitats were defined using macrophyte maps (New South Wales Department of Primary Industries, Fisheries Spatial Database: https://webmap.industry.nsw.gov.au), aerial imagery, depth soundings and side scan sonar data (Lowrance Gen2 HDS10,

Navico, Tulsa, Oklahoma, USA) (Figure 5.1). A Habitat selection index was calculated for individual Sand Whiting within the downstream and upstream spawning locations during and outside of the spawning season for both core and total UD’s. Habitat

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selection index (HI) was derived for each fish as a ratio of the habitat present within the

UD’s and the total habitat present within each tracking area (Manly et al. 2002).

An aggregation index (AI) was used to determine the degree of overlap among UDs of fish. The aggregation index is calculated as the area of overlap between two fish UDs divided by the sum of the area of the UDs minus the overlap area. When averaged across all possible fish combinations this provided an index of overlap among tagged individuals, where a higher value suggests greater aggregation within the population

(Dean et al. 2012; Fieberg and Kochanny 2005). The aggregation index was calculated separately for each fish within the upstream residence and downstream spawning locations.

AIa,b = 100[overlapa,b/(areaa+areab-overlapa,b)] areaa = the UD50 for fish a areab = the UD50 for fish b overlapa,b = the overlap between the two areas

5.3 Results

Twelve Sand Whiting were detected in both arrays, for an average monitoring period of

237 days (total of ~ 130,000 position estimates; Table 5.1). All 12 individuals gave sufficient detections to estimate kernel density distributions in the upstream array, whereas data from only seven individuals was sufficient in the downstream array. Sand whiting spent the majority of time upstream (mean 84 ± 4.4% time spent in upstream array), but during the spawning season made repeated, rapid migrations to a common location downstream (mean of 5.7±1.4% time spent in downstream array), before returning to the upstream residences (Figure 5.1). Sand whiting from both sexes used van der Meulen, D.E. 126 Chapter 5: Spawning and homing of Sand Whiting

remarkably small core areas upstream (mean 182 ± 81 m2 for males, 551 ± 274 m2 for females), and larger areas downstream (mean 73519 ± 22121 m2 for males, 93998 ±

22000 m2 for females, Table 5.1). Note estimates of UDs are likely overestimates given position error of the acoustic array (mean position error for stationary transmitters 14.36

± 0.01m2 and 16.75 ± 0.01m2 for upstream and downstream arrays, respectively). The larger downstream core areas saw a far greater degree of spatial overlap between individuals (aggregation index 0.2 ± 0.0009) than upstream (8.33% overlap, aggregation index 0.0002 ± 2x10-7), where individuals tended to occupy discrete core areas (Figure

5.1; Table 5.1). Upstream, core habitats were dominated by sediment with predator holes (potential stingray feeding sites, Takeuchi and Tamaki 2014) throughout the study period, and to a lesser degree, bare sediment and seagrass (Figure 5.2). In contrast, most Sand Whiting selected the same shared location downstream, which was mostly seagrass, rock wall and reef, as well as some bare sediment (Figure 5.2).

Table 5.1 Summary of Sand Whiting tagging and home range data from the upstream residence and downstream spawning tracking arrays. Fish ID Fork Length (mm) Sex Days Tracked n Detections Residence Spawning Core UD Total UD Core Core UD Total UD Core Total Area (m2) Area (m2) AI Total AI Area (m2) Area (m2) AI AI 1 250 M 271 12343 68 3779 0.00 0.02 42823 194738.70 0.21 0.30 2 262 F 241 1129 551 4266 0.00 0.00 - - - - 3 265 M 240 5466 133 10874 0.00 0.03 90025 342656.86 0.16 0.33 4 270 F 121 2726 496 3004 0.00 0.00 133200 396202.08 0.20 0.44 5 270 F 271 44403 85 3018 0.00 0.00 91703 351275.80 0.21 0.41 6 270 M 263 16977 47 5679 0.00 0.01 128345 450908.33 0.18 0.48 7 274 M 271 17521 576 33951 0.00 0.03 32883 183045.73 0.18 0.27 8 294 M 254 4090 179 20040 0.00 0.01 - - - - 9 308 M 207 2036 88 846 0.00 0.01 - - - - 10 330 F 312 16979 1567 58093 0.00 0.02 57093 269678.67 0.25 0.34 11 356 F 208 5723 56 274 0.00 0.00 - - - - 12 382 ? 188 326 157 2286 0.00 0.02 - - - - Number of detections (n) providing position fixes throughout the study period. Area (m2) of core (50%) and total (90%) utilisation distributions (UD). Core and total aggregation index (AI) is determined as the area of overlap between two fish UDs divided by the sum of the area of the UDs minus the overlap area, averaged across all individuals.

van der Meulen, D.E. 128 Chapter 5: Spawning and homing of Sand Whiting

5.4 Discussion

Sand whiting were found to have extremely small core home ranges (average 10.3 m radius) for most of the year, with almost no overlap between tagged individuals in their upstream habitats. Furthermore, fish displayed high levels of site attachment and site fidelity, generally occupying the same distinct location for the entire 8-month study period. Due to the error associated with the tracking array these fish are likely occupying a significantly smaller area. The affinity to such small core home ranges upstream was particularly striking given Sand Whiting would conduct up to 15 migrations to spawning habitat ~8km away, over the 4-month spawning season, and each time return to the same location from which they initiated their migration.

Many animals display strong site fidelity; mammals, birds and reptiles are regularly shown to associate with spatially restricted habitats for extended durations (Börger et al.

2008; Potts and Lewis 2014). The concept of home range, site fidelity and homing in fish was originally developed in freshwater streams where the restricted-movement paradigm was developed (Crook 2004; Gerking 1953; Rodriguez 2002). The notion that some fish display high levels of site fidelity and long residences has similarly been shown for reef fish (Crook 2004; Gerking 1953; Meyer and Holland 2005; Piraino and

Szedlmayer 2014; Rodriguez 2002) and fish that associate with complex structural environments (Ferguson et al. 2013a), where they can use obvious physical features to associate with specific refuge and feeding locations. This study extends this paradigm to sediment habitats, and shows that fish can also exhibit strong site attachment to comparatively featureless environments such as soft sediment. van der Meulen, D.E. 129 Chapter 5: Spawning and homing of Sand Whiting

Shallow water sediment environments often support a large biomass of crustaceans, polychaetes and molluscs (Franca et al. 2009; Kalejta and Hockey 1991). Within the residence locations upstream, shallow water sediments (<4 m) were associated with ghost shrimp (Thalassinidea) burrows (a key Sand Whiting prey species) and larger predator holes (potential stingray feeding sites, Figure 5.2 and Figure A.2). Sand

Whiting may be selecting these individual predator holes as habitat, but it is difficult to prove that individuals use specific depressions. We suggest that these predator holes likely function as resting and reference points, to initiate foraging and as refuge to avoid predation (Payne et al. 2015b). There is clear spatial segregation between Sand Whiting and a potential predator Mulloway, Argyrosomus japonicas, generally in both the horizontal and vertical planes in the residence locations (Payne et al. 2015b)(NSW DPI unpublished data), which may not exist in the spawning areas. Additionally, by occupying small features in the sediment (such as predation holes), fish may be able to reduce swimming effort during tidal flow periods, and provide some form of refuge from predation.

During the spawning season Sand Whiting would conduct multiple short period migrations, leaving their residence locations to spawn at the entrance of the river. The cues that the fish use to move between these habitats are unknown, but likely include visual and or olfactory signals (Ueda et al. 1998), and suggests that these fish may have a cognitive map that allows them to navigate their environment (Börger et al. 2008).

The relatively large movements between residence locations and spawning habitat likely reflect the trade-offs between maximising reproductive output (aggregating at the river entrance where conditions for spawning and offspring survival are favourable), and foraging success while reducing predation risk (upstream). In combination with the van der Meulen, D.E. 130 Chapter 5: Spawning and homing of Sand Whiting

higher upstream temperatures that are closer to their thermal optimum (Chapter 4;

Payne et al. 2016) Sand Whiting have adapted an unique solution to the myriad environmental and biotic variation that exists in the estuarine environment.

Globally, estuarine fish populations are important for both the recreational and commercial fishing sectors, but reside in some of the world’s most degraded habitats

(Kennish 2002). Conservation and management efforts often focus on estuarine habitats such as seagrass beds or riparian vegetation, but this study highlights the importance of soft sediments for some economically significant fishes; a habitat that currently receives little attention in most fish conservation and restoration programs.

van der Meulen, D.E. 131 Chapter 6: Key Findings, Implications and Future Research

Chapter 6: Key findings, management implications and future

research

This chapter consolidates and compares the major findings of my thesis on the spawning dynamics of estuarine fish, to satisfy the main objectives outlined in Chapter

1. These findings are also discussed in relation to potential management and future research recommendations.

6.1 Spawning dynamics of estuarine fish

My research revealed complex and variable spawning strategies of the study species within the estuaries, which were linked to biophysical variability. These spatio-temporal aspects of spawning are essential for understanding reproductive dynamics, as well as factors influencing recruitment, in estuarine-dependent fish populations. The spatial distributions of fish, the habitat selected, the timing and duration of spawning movements, temporal scale of site fidelity, the timing of spawning events and the specific conditions experienced by eggs and larvae all play important roles in subsequent reproductive success.

Sand Whiting and Estuary Perch spawn at opposite times of the year (summer and winter respectively) (Ochwada-Doyle et al. 2014; Walsh et al. 2011). With the onset of the spawning season, both conduct multiple migrations from upstream residence locations to spawning grounds at the entrance of the river. Additionally, both spawn on nocturnal high tides, adjacent to deep water, using tidal flow to export fertilised eggs out of the estuary. While specific spawning migrations for Yellow-fin Bream were van der Meulen, D.E. 132 Chapter 6: Key Findings, Implications and Future Research

unable to be determined, Pollock (1982a) has shown offshore spawning movements occur. Similarly, Mulloway, Argyrosomus japonicas, have been found to move towards river entrances during the spawning season linked to freshwater flows (Taylor et al.

2014). Additionally, Common Snook, Centropomus undecimalis, (Lowerre-Barbieri et al. 2014; Young et al. 2016), Red Drum, Sciaenops ocellatus, (Lowerre-Barbieri et al.

2016) and Brand-marked flounder Platichthys flesus, (Dando 2011) have been found to conduct movements towards estuary entrances and offshore to spawn. This strategy allows eggs and larvae to be exported onto, or spawned within, coastal shelf waters, increasing genetic mixing and dispersal among river systems (Bilton et al. 2002). This work highlights the importance of estuary entrances as critical spawning locations for larval export strategy spawners.

During this study Yellow-fin Bream, Black Bream and their hybrids were found to reside within the estuary throughout the spawning season, which suggests that spawning may occur within estuaries for these species. Black Bream spawn in the upper reaches of estuaries (Hindell et al. 2008; Sakabe and Lyle 2010). Similarly, Australian Bass,

Percalates novamaculeata, reside within the middle estuary during the spawning season

(Reinfelds et al. 2013; Walsh et al. 2012a). By spawning at these locations eggs and larvae are more likely to be retained within the estuary reducing inter-estuarine dispersal

(Bilton et al. 2002). Both species display increased genetic variation by distance which is likely a result of this spawning strategy (Burridge and Versace 2007; Chaplin et al.

1998; Jerry and Baverstock 1998; Shaddick et al. 2011). Overlaps in distributions and behaviours between Yellowfin Bream and their backcross hybrids, particularly during the spawning season, suggests a mechanism for further introgression in this

Acanthopagrus population. This study shows how understanding the movement ecology van der Meulen, D.E. 133 Chapter 6: Key Findings, Implications and Future Research

and spawning dynamics of fish aids in interpreting genetic studies and the underlying mechanisms that drive genetic dispersal between rivers.

All of the study species were found to display high levels of site fidelity to specific habitats both during and outside of the spawning season (Chapter 5; Gannon et al. 2015; van der Meulen et al. 2014; Walsh et al. 2012a). Sand Whiting and Yellow-fin Bream have been found to display extreme site fidelity to upstream habitats (Chapter 5;

Gannon et al. 2015). Terrestrial animals have been found to display strong site fidelity; birds, reptiles and mammals are regularly shown to associate with spatially restricted habitats for extended durations for a variety to reasons (Börger et al. 2008; Potts and

Lewis 2014). The notion that fish display high levels of site fidelity and long residences orginated within freshwater fish studies (Gerking 1953; Gerking 1959). Understanding how fish interact and move between seemingly isolated or restricted populations has implications for management and research (Gowan et al. 1994). Reef fish (Meyer and

Holland 2005; Piraino and Szedlmayer 2014), freshwater riverine fish (Crook 2004;

Rodriguez 2002) and fish that associate with complex structural environments

(Ferguson et al. 2013a), have all been found to display high levels of site attachment, where they can use obvious physical features to associate with specific refuge and feeding locations. While Sand Whiting display an obvious exception to this concept, nonetheless, these upstream locations represent important habitat both during and outside of spawning periods, potentially functioning for foraging, refuge and thermoregulation.

During the spawning season both Sand Whiting and Estuary Perch displayed selection for specific locations and habitats. Estuary Perch selected structurally complex habitat van der Meulen, D.E. 134 Chapter 6: Key Findings, Implications and Future Research

such as large wooden debris and other man-made structures, while Sand Whiting were found to prefer areas of sediment, seagrass and rock wall. Common prerequisites for spawning habitat included proximity to the river entrance and access to deep water. The selection of the spawning locations allows access to areas of high tidal flow, this maximises the potential for eggs to be transported to coastal shelf regions.

Diversity in spatio-temporal reproductive behaviour such as spawning site variability may be a strategy that increases the reproductive resilience of fish populations

(Lowerre-Barbieri et al. 2016; Schindler et al. 2010). Life history diversity within a population (portfolio effect) can stabilise fish populations over the long term leading to increased benefits to the population (Schindler et al. 2010). Sand Whiting predominantly remained within the estuary during spawning migrations, however, some individuals were found to exit the systems, potentially spawning offshore at sites such as ocean beaches. While more work is needed to determine spawning sites for Yellow- fin Bream and their backcross hybrids there is a possibility that they also spawn at estuarine and offshore locations (Chapter 3; Pollock 1984). Although Estuary Perch remained within the estuary some individuals favoured spawning habitats near the ferry landing while other selected only large wooden debris (van der Meulen et al. 2014).

Spawning success may favour different locations under different conditions, by diversifying spawning locations fish may increase the probability of reproductive success and reduce that impacts of catastrophic events at the population level (Lowerre-

Barbieri et al. 2017). Maintenance of fish population diversity should be prioritised with fisheries management engaged to minimise homogenising impacts such as heavily targeting only individual stock components which may alter genetic diversity (Schindler et al. 2010). van der Meulen, D.E. 135 Chapter 6: Key Findings, Implications and Future Research

Episodic recruitment occurs within estuarine fish species and has been linked to environmental conditions (Ferguson et al. 2008; Jenkins 2005; Smith and Sinerchia

2004; Walsh et al. 2010). However, the physical and environmental mechanisms that lead to increased recruitment are poorly understood. The information presented here suggests that spawning likely occurs throughout the spawning season, for Estuary Perch and Sand Whiting. The episodic recruitment presented by Walsh et al. (2010) and Smith and Sinerchia (2004) is likely a result of continued spawning throughout the spawning season which matched with episodic favourable conditions for egg and larvae survival and or recruitment. In the case of Sand Whiting, the research presented suggests that spawning may be linked to temperature and changes in coastal winds and down-welling conditions. Sand Whiting may adaptively exploit these conditions as they are favorable for spawning and recruitment however more research is needed to determine if this is the case. Understanding of the physio-chemical conditions that eggs and larvae are exposed to as a result of specific spawning dynamics will aid in determining the conditions that need to align for these episodic recruitment events to occur.

Spawning movements of both Sand Whiting and Estuary Perch have been linked to temperature (Chapter 4; Walsh et al. 2013b), and thereby fish performance such as reproductive growth (Gannon et al. 2014; Payne et al. 2016). However, Sand Whiting movements correlate with the highest temperatures observed within the study area, whereas Estuary Perch correlate with low temperatures. This is likely related to their biogeography and the thermal optima of each study species. Estuary Perch have temperate biogeography while Sand Whiting have a tropical biogeography. Because movement and reproduction in these species appears very closely regulated by

van der Meulen, D.E. 136 Chapter 6: Key Findings, Implications and Future Research

temperature, future changes in environmental conditions may strongly influence the timing, duration, and success of spawning.

To compensate for temperature heterogeneity in the rivers fish also appear to use behavioural thermoregulation, moving upstream and downstream to gain access to temperature regimes that may increase growth in either adults or eggs and larvae

(Chapter 2; Chapter 4). By moving between upstream and downstream locations Sand

Whiting behaviorally thermoregulate to take advantage of environmental temperature heterogeneity and access warmer temperatures closer to their thermal optimum. This behaviour may increase metabolic outputs and development of gametes, allowing fish to be ready to spawn sooner than if they were to remain at single locations. Similarly, by coinciding spawning with specific temperatures, egg development, egg survival and larval growth are optimized (Caputi et al. 1996). The effect of coastal and estuarine environments on egg mortality remains an interesting question.

Further similarities in coastal movements were observed between Sand Whiting,

Yellowfin Bream and their backcross hybrids. All were found to make large scale migrations along the coast, predominantly in a northward direction. These movements may be a result of fish seeking locations with mean temperatures that are closer to their thermal optimum or may compensate for the southward entrainment of larvae by the

East Australian Current (Booth et al. 2007; Gray et al. 2012; Mullaney and Suthers

2013; Payne et al. 2016; Suthers et al. 2011). More research into the mechanism driving these movements is required. Additionally, the results also show that adult inter- estuarine migrations play a significant role in the genetic interconnection of populations of this species complex. van der Meulen, D.E. 137 Chapter 6: Key Findings, Implications and Future Research

The timing of spawning events and the selection of spawning sites influences the hydrographic and physicochemical conditions to which eggs and larvae are exposed

(Epifanio and Garvine 2001; Jenkins et al. 2015; Sponaugle et al. 2002; van der Meulen et al. 2014). The resultant effects on hatching success, larval survival and advection, will in turn influence overall recruitment success and connectivity (Checkley et al.

1988; Lowerre-Barbieri et al. 2011a; Rohrs et al. 2014; Sponaugle et al. 2002).

6.2 Management recommendations

Ecological and evolutionary factors related to spawning in marine fish are directly linked to stock productivity and are being increasingly recognised as important to properly manage fisheries resources (Kindsvater et al. 2016; Lowerre-Barbieri et al.

2017). Additionally, to effectively implement and evaluate spatial management of resources we need information on the movement ecology at both the population and ecosystem level, which will in turn allow investigation of impacts from anthropogenic disturbances.

The study species were found to display specific habitat requirements and exhibit high site fidelity to residence and spawning locations (Chapter 4; Chapter 5; Gannon et al.

2015; van der Meulen et al. 2014; Walsh et al. 2012a; Walsh et al. 2013b). Estuary ecosystems are often heavily modified (Thrush et al. 2008). Extensive habitat modification has occurred within spawning grounds, and the long-term impacts of this modification are unknown. The area and quality of spawning habitat could be a limiting factor for the number of fish within spawning grounds. The restoration of spawning habitat has been found to have significant effects on the survival and recruitment of van der Meulen, D.E. 138 Chapter 6: Key Findings, Implications and Future Research

juveniles (Palm et al. 2007; Pedersen et al. 2009) and could be implemented as a management tool to enhance fish stocks. Future management should focus on protecting important habitats and investigate habitat-restoration projects.

While spawning locations are undoubtedly important in terms of ensuring reproductive resilience, residence locations also need to be considered when developing management action. For example gill netting, haul netting and fish trapping occur at upstream residence locations throughout the year, targeting Sand Whiting and Bream. Due to the high site fidelity, long residency and small home ranges of these species there is potential for localised depletion at heavily fished areas and for the impacts of habitat modification to be exacerbated. Due to the complex nature of the movement ecology of these species, the spawning and residence locations and the migrations between them need to be considered in future spatial management, risk assessments and fisheries independent sampling.

During the spawning period, all study species showed changes in distributions, increased rates of movement, and high levels of site fidelity and residency.

Additionally, Estuary Perch and Sand Whiting were found to form large aggregations at predictable times and locations. These traits can increase susceptibility to capture which is often exploited by fishers, sometimes with detrimental impacts (Claydon 2004;

Sadovy and Domeier 2005). The aggregations observed around estuary mouths during specific periods certainly supports a case for these locations to be temporally protected.

Such protection of spawning fish will help ensure that natural breeding processes can proceed, which should in turn lead to enhancement of recruitment and productivity.

van der Meulen, D.E. 139 Chapter 6: Key Findings, Implications and Future Research

6.3 Future research and conclusions

Through the use of advancing technologies, such as acoustic telemetry, we are further quantifying the ecology of the aquatic environment. In future, we may be able to use information from studies such as this to model additional aspects of the life history of fish. This project has enhanced our understanding of the spawning dynamics of three important estuarine-dependent species found in south-eastern Australia. Future work should seek to expand the study species and the geographical range at which studies occur. Species of particular interest include: Dusky Flathead, Platycephalus fuscus,

Luderick, Girella tricuspidata, Mulloway, Argyrosomus japonicus, Australian Bass,

Percalates novemaculeata, Freshwater Mullet, Trachystoma petardi and Sea Mullet,

Mugil cephalus. As movements of more species are studied and geographical overlap of these species occurs, there is an opportunity to compare migration in the context of spawning dynamics among species and locations, which can aid in defining ecological and evolutionary drivers of these patterns.

Therefore future research should:

• Examine latitudinal variation in the spawning dynamics of fish (e.g. Gannon et

al. 2014). While this study attempted to conduct studies across multiple estuaries

there is a need to understand intra-estuarine movements and spawning dynamics

across the geographical distribution of species.

• Determine the drivers of inter-estuarine movements and assess the connectivity

of populations and increase our understanding of emigration and migration

within seemingly isolated stocks. This project has shown that inter-estuarine van der Meulen, D.E. 140 Chapter 6: Key Findings, Implications and Future Research

movements do occur, with both Bream spp. and Sand Whiting moving 100’s of

kilometres between estuaries.

• Examine spatial and temporal spawning output of Yellowfin Bream, Black

Bream and their hybrids, both within estuaries and offshore. Future attempts to

identify spawning locations could help to further explain the specific spawning

mechanisms that lead to hybridisation and introgression.

Researchers are gaining a better understanding of how environmental conditions influence recruitment and ultimately stock structure (Jenkins 2005). My research shows that it is possible to determine the timing and location of spawning events. Future research should, therefore, focus on linking spawning and recruitment. Understanding the mechanisms that lead to successful recruitment can ultimately benefit predictive models and enhance fisheries management. Suggested future research should strive to:

• Determine egg and larval dispersal across the entire spawning season based on

the location and timing of spawning of adults combined with mapping current

direction, temperature and strength (Leis et al. 2011).

• Determine cues that drive larval fish movement (horizontal and vertical) and

link these with successful recruitment to nursery grounds (field and laboratory

based experiments).

• Attempt to integrate spawning dynamic studies and recruitment quantification to

better understand the links between them (For example: does increasing

spawning output result in increased recruitment). This should involve, long term

surveys of spawning output and juveniles in known nursery grounds, combined

van der Meulen, D.E. 141 Chapter 6: Key Findings, Implications and Future Research

with daily ageing to back-calculate birth dates and determine when spawning

was successful.

While one potential spawning location was studied within the Clyde River it was also found that individuals were dispersing to other locations outside of the tracking area.

Sand whiting also spawn within the surf zone of coastal beaches (Morton 1985). It is likely that within the Clyde River population site fidelity to multiple spawning sites exist, which indicates a metapopulation structure. Future work should be focussed at gaining a better understanding of the spawning sites along the coast adjacent to river entrances and how spawning dynamics differ between these spawning strategies.

The evolution of selection processes for spawning locations is an exciting new area of research that can have implications for how organisms adapt to environmental, anthorpogenic and physical change. Future research should be focused at determining whether natal homing exists or whether favourable conditions may be imprinted at birth or genetically encoded into the biological cues of the offspring from the parents.

Additionally, research should aim to synthesise whether spawning behaviours are learned from other individuals (e.g. Atlantic Cod, Rose 1993) or if it is an innate response to environmental conditions.

The use of acoustic telemetry combined with habitat mapping, egg sampling and environmental monitoring considerably broadened the knowledge of the movement ecology and spawning dynamics of the study species. The selection of spawning locations and the timing of spawning events influences dispersal of eggs and larvae within and between estuaries, and can act to isolate populations or increases inter- van der Meulen, D.E. 142 Chapter 6: Key Findings, Implications and Future Research

estuarine connectivity and genetic dispersal. The act of spawning further increases the vulnerability of fish populations to anthropogenic impacts such as habitat degradation and fishing pressure. Spatial data has the potential to dramatically improve stock assessments and spatial management of our estuarine-dependent fish populations.

Management recommendations have been proposed to ensure the sustainability of fish populations taking into considerations their unique spawning dynamics and spatial ecology.

van der Meulen, D.E. 143 References

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van der Meulen, D.E. 167 Appendix

Appendix

van der Meulen, D.E. 168 Appendix

Figure A.2 Bathymetry at a) the upstream residence array and b) the downstream spawning array.

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