Assessing Reef Fish Assemblages in a Temperate Marine Park Using Baited Remote Underwater Video

University of Wollongong Theses Collection University of Wollongong Theses Collection

University of Wollongong Year 

Assessing reef ﬁsh assemblages in a temperate marine park using baited remote underwater video James A. Wraith University of Wollongong

Wraith, James A, Assessing reef ﬁsh assemblages in a temperate marine park using baited remote underwater video, MSc thesis, School of Biological Sciences, University of Wollongong, 2007. http://ro.uow.edu.au/theses/12

This paper is posted at Research Online. http://ro.uow.edu.au/theses/12

Assessing Reef Fish Assemblages in a Temperate Marine Park Using Baited Remote Underwater Video

A thesis submitted in fulfilment of the requirements for the Award of the degree

Master of Science Research

from

University of Wollongong

James A. Wraith BA, BSc

Biological Sciences 2007

CERTIFICATION

I, James A. Wraith, declare that this thesis, submitted in fulfilment of the requirements for the award of Master of Science (Research), in the Department of Biological Sciences,

University of Wollongong, is wholly my own work unless otherwise referenced or acknowledged. The document has not been submitted for qualifications at any other academic institution.

……………………………………

James A. Wraith

15 January 2008

Table of Contents

Abstract v

Acknowledgements vii

List of Figures viii

List of Tables x

Chapter 1: Introduction 1 Background 1 BRUV 3 Applications and advantages of BRUV 6 Limitations of BRUV 8 Aims of the study 10

Chapter 2: Baited Underwater Video – Does Bait Matter? 12 Introduction 12 Methods 17 Study Site 17 Sampling Design 20 Bait 21 BRUV Components 22 Analysis of video footage 26 Statistical Analysis 27 Results 30 Fish Species Richness and Abundance 30 Fish Assemblage 35 Discussion 37

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video 42 Introduction 42 Methods 45 Analysis of video footage 47 Statistical Analysis 47 Results 49 Species Richness and Abundance 50 Assemblage Structure 52 Discussion 56

iii

Chapter 4: Discussion 61

Appendix 84 Appendix 1. Mean number of individuals surveyed at three locations in Jervis Bay Marine Park: Callala, Huskisson, and Plantation Point, in two years of sampling: 2005 (n=3), and 2006 (n=4). Individuals were recorded using baited remote underwater video, which was baited with either: abalone, pilchard, or urchin. 85 Appendix 2. Number of individuals recorded (n=8) in 2005 and 2006 on six temperate rocky reefs: Little Beecroft Peninsula (LBC), Long Nose Point (LN), Honeymoon Bay (HB), Lobster Rock (LR), Middle Ground (MG), and Sir John Young Banks (SJY), using baited remote underwater video. Two reefs were sampled in three habitats: coastal deep (CD), coastal shallow (CS), and patch deep (PD). 87

Abstract

Baited remote underwater video (BRUV) is becoming an increasing popular tool for examining reef fish assemblages in depths less than 100m. This sampling technique is relatively new in the literature and several gaps remain to be filled. Scientists using this technique have selected bait based on results from trapping experiments. Therefore the first objective of the study was to compare commonly used baits and test if different fish species and fish assemblages were recorded. I planned to apply results from the first study towards further research using BRUV. Management at Jervis Bay Marine Park, located in southeast Australia, have applied a strategy to protect a comprehensive and representative sample of local habitats and associated flora and fauna. In doing so, sanctuary “no take” zones have been put in place. Surprisingly, there are no patch reefs afforded this protection. My second objective was to provide the Jervis Bay Marine Park management with baseline data on deep patch reef locations and to draw comparisons between deep patch, deep coastal, and shallow coastal reefs.

I compared three different baits (pilchard, abalone, and urchin) at three locations in two separate years. A total of 63 “drops” (30 min recordings) were conducted in two years and a total of 47 species were recorded. There were no differences in the diversity and abundance of fish recorded while baited with pilchard and abalone. In contrast, in the second year of sampling I detected a greater species richness and abundance using pilchard, compared to urchin, at most locations (p<0.05). The two most speciose families recorded in the study were Labridae and Monacanthidae. These families, as well as several individual fish species, were examined but there were no significant differences

in their relative abundance among bait treatments. Additionally, in the second year of sampling I detected differences in H′ and time of first arrival among locations (p<0.05).

Surprisingly, large differences between the baits were greatly reduced at one location -

Plantation Point. I interpret this finding as there being a high density of fish at Plantation

Point that masks the differences in the attraction of these baits. I concluded that as the behaviour and structure of the fish assemblage can vary in space, pilchard was the best choice of bait for consistently detecting species richness and abundance.

A total of 144 BRUV “drops” (30 min recordings) in 9 locations in 2005 and 2006 were completed in the second study. The composition of fish assemblage at shallow and deep water habitats was different (p<0.05). Indeed, depth related differences for temperate reef fish are well documented and my findings emphasise the need for the Marine Park management to maintain protection of reef habitats across abroad range of depths. I did not detect any differences in the composition of the fish assemblage or the relative abundance of fish between the two deep habitats (p>0.05), although the presence of several rarely encountered species including Bodianus unimaculatus, Coris sandageri,

Meuschenia scaber, Caesioperca lepidoptera, and Eubalichthys mosaicus were recorded in the deep patch reef habitat. I concluded that the inclusion of the deep habitat in the sanctuary zoning plan is important for protecting fish biodiversity. By generating permanent baseline data, this study aims to assist Marine Park management in making sound decisions on future zoning plans.

Acknowledgements

I would like to thank my supervisors, Andy Davis and Todd Minchinton for their tireless efforts. Andy and Todd provided hours of consultation and advice on all aspects of this thesis, including experimental design, sampling, and presentation. I would also like to acknowledge Tim Lynch and Ian Osterloh for countless hours of assistance in the field.

Many thanks to everyone else who provided assistance in the field including: Jeremy,

Mark, Ben, and Caitlin.

Thanks to Marine Parks Authority for entrusting me with the funding, equipment, boat usage, and resources that made this research possible.

I would also like to thank the crew in the University of Wollongong Workshop, Geoff

Hurt and Steve Cooper, for successfully applying numerous design changes to produce four BRUV stands and camera housings.

I give thanks to my family and friends for their love, guidance, and support during this endeavor. I am grateful to my parents for their encouragement to pursue my dreams.

Special thanks to my wife Lisa, for her patience and understanding during the months I spent away from home, and during the long hours I spent at the University analyzing tapes and doing all the work associated with putting together this final document.

vii

List of Figures

Figure 1. Two commonly used baited remote underwater video designs: a) horizontal (Cappo et al. 2004) and b) vertically positioned recording platforms (Willis & Babcock 2000)...... 4

Figure 2. Jervis Bay Marine Park is located within the Bateman’s Shelf Bioregion, approximately 180 km south of Sydney, NSW, Australia. Study sites include: Callala Bay Reef (C), Huskisson Reef (H), and Plantation Point (P)...... 19

Figure 3. Preparation and deployment of BRUV: a) inserting camera through forward end port; b) baiting the canister; c) deploying BRUV; and d) deploying floats after BRUV has settled on the ocean floor...... 25

Figure 4. Mean (± SE) species richness, relative abundance (Total Max n), Shannon-Weiner Diversity Index (H′), and first time of first arrival (t1st1) of fish in the presence of three baits (pilchard , abalone , and urchin ) at three locations (Callala (C), Huskisson (H), and Plantation Point (PP) in 2005 (n=3) and 2006 (n=4) ...... 31

Figure 5. nMDS plot comparing fish assemblages attracted to baits: pilchard ( ), abalone ( ), and urchin ( ) at locations: Callala (black), Huskisson (white), and Plantation Point (Grey) for years 2005 and 2006. Centroids are displayed for 2005 (n=3) and 2006 (n=4). 2005 centroids have been indicated with a hash mark through the middle of the symbol...... 36

Figure 6. Jervis Bay Marine Park Boundary, Bathymetry, and Study Locations. Study locations include: 1.Sir John Young Banks, 2. Lobster Rock , 3. Little Beecroft Peninsula, 4. Long-nose Point, 5. Honeymoon Bay, and 6. Middle Ground. Park boundary extends from Kinghorn Point in the north to the northern shore of Sussex Inlet in the south, to mean high water mark around the shores of Jervis Bay and to the limit of the tidal influence in the estuaries...... 46

Figure 7. Mean (± SE) species richness, relative abundance (Total Max n), species diversity index (H′) (Shannon-Weiner Diversity Index), and first time of first arrival (t1st1) of fish within three habitat types: coastal deep (CD: ), coastal shallow (CS: ), and patch deep (PD: ). Two locations were sampled in each habitat. Locations included: Little Beecroft Peninsula (LB), Long-nose Point (LN), Honeymoon Bay (HB), Lobster Rock (LR), Middle

viii

Ground (MG), and Sir John Young Banks (SJY). In 2005 and 2006 (n=8)...... 51

Figure 8. nMDS plot comparing fish assemblages between three habitat types represented by two locations each: coastal deep (LB = , LN= ), coastal shallow (HB = , LR = ), and patch deep (MG = , SJY = ) for years 2005 and 2006. Symbols representing 2005 locations are filled in with colour. Centroids are displayed for both years (n=8)...... 54

List of Tables

Table 1. Fish families captured from trawl and not recorded using BRUV in a comparison of sampling techniques (Cappo et al. 2004). The number of species (n spp) in each family is indicated in brackets...... 8

Table 2. Two-factor ANOVA for four variables: species richness, relative abundance (Total Max n), Shannon-Weiner Diversity Index (H′), and time of first species to arrive in seconds (t1st1) in 2005 (n=3) and 2006 (n=4). Significant differences at α = 0.05 are indicated by bold type...... 32

Table 3. Two factor ANOVA examining relative abundance (Total Max n) for 2 families and 13 individual species among baits and among locations in two separate years. Significant differences at α = 0.05 are indicated by bold type...... 34

Table 4. PERMANOVA differences in fish assemblage among baits and among locations for 2005 (n=3) and 2006 (n=4). Significant differences at α = 0.05 are indicated by bold type...... 36

Table 6. PERMANOVA differences in fish assemblage between habitat and location for 2005 and 2006...... 54

Table 7. SIMPER results for overall dissimilarity in fish assemblages between habitats: coastal deep (CD), coastal shallow (CS), and patch deep (PD). Species regarded as being important contributors to the assemblage dissimilarity are shown in bold. Habitats with greater average abundance are in parentheses. Values shown for each location in the pairwise comparisons are the Max n for the species...... 55

Chapter 1: Introduction

Understanding processes that influence the dynamics and structure of marine fish

assemblages is the main focus of marine fish ecologists. The building block for

understanding these processes is quantifying observations in nature (Andrew & Mapstone

1987, Underwood et al. 2000). However, observations of marine fish can be quite

challenging due to the physical constraints of the marine environment. The advent of

remote sampling technology has made it possible for researchers to make observations in

marine environments previously beyond their reach. Remote technology is now

commonly employed by marine ecologists to both quantitatively and qualitatively observe marine organisms and marine habitats in locations previously unattainable

(Starmans et al. 1999, Hovland et al. 2002, Parry et al. 2003).

Background

Traditional sampling techniques that have been used to quantify marine fish abundance

and diversity can be classified into two general categories: (1) underwater visual census

(UVC) obtained by snorkel or SCUBA; and (2) remote capture (i.e. angling, long-lining,

or gill netting). UVC is commonly used in shallow water habitats because it is a

relatively inexpensive sampling technique and does not require extracting fish from the

population. However, UVC has several biases which are well documented, including

observer error and variation in behavioural responses of fish to divers (Thresher & Gunn

1986, Thompson & Mapstone 1997). These biases have been problematic in studies that

examine fish abundance within marine reserves, because in these locations fish behaviour

can vary markedly in response to human activities (Cole 1994). UVC has also been

Chapter 1: Introduction shown to underestimate cryptic species (Willis 2001) and moreover, divers are limited in their ability to sample in areas because of no-decompression limits.

Remote capture techniques have an advantage over UVC because they can be used to examine fish at depths beyond the reach of people on SCUBA. However, remote capture techniques also have several noted disadvantages. For example, remote capturing involves removing individuals from the population and can be destructive to the environment (Wassenberg et al. 2002). This practice is understandably controversial, particularly when conservation of sensitive areas or protected species is the aim of the research. In addition, estimates of abundance and diversity can be imprecise (Arreguin-

Sanchez 1996) or biased (Millar & Fryer 1999) when employing capture techniques.

Moreover, complex bathymetry precludes some capture techniques (Collins et al. 2002), making it difficult to sample many benthic organisms. Therefore, in response to many of the problems associated with traditional sampling techniques, new sampling techniques involving photographic or video sampling have been developed and are continually being updated and improved.

Louis Boutan (1893) is credited for taking the first underwater photographs towards the end of the last century, although the development of underwater photography as an oceanographic tool took off in the 1940s with the work of Maurice Ewing and his associates in the United States (see Holme & McIntryre 1984). Around the same time, video recording was also starting to be used by marine ecologists (see Barnes 1963).

Video recording had the advantage over underwater photography because it provided

Chapter 1: Introduction researchers with data sets that covered more time, without having to balance proportionally large field costs with data quality (Willis et al. 2003). Marine scientists have since discovered several ways to incorporate these remote sampling technologies into robust sampling techniques. Cameras and video recorders have all been deployed from various platforms including boats (Willis et al. 2000), manned submersibles

(Ralston et al. 1986), or remotely operated vehicles (Norcross & Mueter 1999).

Moreover, they have been hand-held by divers (Harvey et al. 2002), lowered to a stationary position on the substrate (Cappo et al. 2004), and towed (Barker et al. 1999).

BRUV

Baited Remote Underwater Video (BRUV) is one type of remote sampling technique that

is becoming more prevalent in the literature because it is a non-destructive, non-intrusive

sampling technique that can be deployed to variable depths in various habitats including those with complex topography (Willis & Babcock 2000). There is some variation in the

BRUV technique (Babcock et al. 1999, Cappo et al. 2004) but the principle is the same: bait is used to attract fish and the observations are recorded. BRUV normally consists of one or two (stereo) high-resolution video cameras aimed at a container filled with bait.

The video camera is held within a watertight housing, which is mounted onto a stainless steel frame. The frame provides stability and also protects the housing from any damage in the event the BRUV has some movement from strong currents or is attacked by a large predator. The BRUV can be lowered or raised manually or remotely to variable depths with relative ease. The bait holder is positioned either out in front of the frame for horizontal viewing or directly beneath the video camera for vertical viewing (Fig. 1).

Chapter 1: Introduction

The two main differences between the current BRUV designs are the number of cameras and their alignment relative to the substratum. In each case the differences are important and justified in their own right. It is well documented that stereo BRUV is more effective for measuring fish length than single video BRUV (Harvey et al. 2002). However, this advantage comes at a cost. The increase in the effectiveness of stereo-video requires advanced training and costly technology. The stereo-vision is only possible with precise calibration of the two cameras, which requires software programs with inbuilt algorithms to carry out this function (Harvey & Shortis 1998). Moreover, the calibration can be compromised by the movement of either of the two cameras. Time is another cost to consider when comparing stereo BRUV compared to single camera. Stereo BRUV requires additional laboratory time for researchers to obtain fish lengths using stereo- computer software. Finally, stereo-video BRUV requires a minimum of two cameras, thereby doubling the cost of the camera equipment when compared to single camera

BRUV. One of the advantages of BRUV is that it provides researchers with a “rapid assessment” technique and in some cases as many as five BRUV have been deployed at once (Cappo et al. 2004). Therefore, retaining this advantage would require up to ten cameras for a multiple stereo-video survey.

The second main difference between the current BRUV designs - the orientation of the camera relative to the substrate - can have implications for the abundance and composition of the species recorded. The horizontal design allows better observation of the surrounding habitat. It is more commonly used for multiple species comparisons because it is better at detecting species that may be reluctant to approach the bait bag due

Chapter 1: Introduction to fish behaviour or competition for the bait (Armstrong et al. 1992). Researchers employing the horizontal design have indicated that this sampling technique detects species attracted to the bait plume, species attracted to the commotion caused by other species feeding at the station, and species incidentally passing the field of view (Cappo et al. 2004). In contrast, vertically designed BRUV are useful because the bottom of the stand provides a good reference for estimating the size of the fish. This design has been used in several studies comparing sizes and abundance of carnivorous fish (Babcock et al.

1999, Willis & Babcock 2000).

Applications and advantages of BRUV

BRUV studies can be generally grouped into two categories: 1) measurements of fish

abundance and 2) observations of foraging behaviour of deep-water scavengers. Studies

that examine fish abundance are more common in the literature, and in many cases

authors have argued that BRUV provides higher estimates than traditional sampling

techniques (Babcock et al. 1999, Cappo et al. 2004). For example, Ellis and DeMartini

(1995) found that BRUV was a useful alternative to bottom long-line sampling for

estimating abundances of juvenile pink snapper Pristipomoides filamentosus. Priede and

Merrett (1996) used BRUV to examine scavengers below 1500 m because acoustic

methods provided limited information and conventional trawlers were inadequate

because few vessels carried gear that was capable of fishing at this depth. In fact, BRUV

has been used to estimate fish abundance at depths below 5000 m (Wilson & Smith 1984,

Priede & Merrett 1998).

Chapter 1: Introduction

BRUV has several other advantages. This technique is non-destructive and non- extractive, making it appropriate for sampling in marine protected areas (e.g. Willis &

Babcock 2000, Westera et al. 2003, Willis et al. 2003, Cappo et al. 2004). The species exploited in marine fisheries are usually top-level predators (Pauly et al. 1998), and

BRUV is an effective technique for monitoring these species because the bait plume from the BRUV often attracts large, mobile predatory fish (Cappo et al. 2004). These large mobile species are often the first to return to marine protected areas, providing a good measure of the effectiveness of the protection (Polunin & Roberts 1993, Russ & Alcala

1996a). Furthermore, behavioral responses of some fish to SCUBA divers means that commonly used underwater visual census techniques may be of limited utility in making statistically rigorous comparisons of abundance, particularly inside marine protected areas where fish can become diver-friendly or diver-negative depending on the location

(Cole 1994).

In addition to estimating fish abundance, a number of qualitative studies using BRUV have looked at swimming technique and movement rates of both invertebrate (Yau et al.

2002) and vertebrate benthic scavengers (Armstrong et al. 1991, Collins et al. 1999, He

2003). These studies have contributed to our understanding of the foraging behaviour of several deep-sea scavenging species leading to predictions of how these mobile creatures are able to distribute organic material to other benthic groups (Yau et al. 2002). Indeed, the baited underwater video technique is an excellent non-intrusive tool, which has contributed to a better understanding of the marine benthic environment.

Chapter 1: Introduction

Limitations of BRUV

There are several limitations to BRUV. For instance, BRUV can preclude some species from visiting the station. Cappo et al. (2004) reported that many “lie and wait” predators and cryptic and sedentary species were less likely to search out the source of the bait plume. In their study, several species sampled by trawling were not recorded using

BRUV (Table 1). In fact, they did not record any flatfish or flathead (bothids, psettodids, and platycephalids) even though these families were major components of the trawl catch in terms of diversity and abundance. The arrival of certain species can also preclude the arrival of other species attracted to the bait plume through intraspecific and interspecific competition, and this can bias estimates of abundance and composition of species

(Armstrong et al. 1992).

Family(n spp.) Platycephalidae (4) Bothidae (9) Callionymidae (3) Priacanthidae (1) Triglidae (1) Scorpaenidae (3) Caesionidae (1) Plotosidae (1) Gobiidae (1) Triacanthidae (1) Ostracidae (2) Antennaridae (3) Psettodidae (1) Gerreidae (1) Dactylopteridae (1) Pseudochromidae (1) Centriscidae (1)

Chapter 1: Introduction

Although BRUV relies on fish attraction to bait, there have been no studies investigating the bias that different baits might have on estimates of fish abundance and diversity. For example, interspecific competition could be occurring around the bait because most of the baits used in BRUV studies attract large mobile predators (Cappo et al. 2004). Most

BRUV studies have used some type of oily bait fish, such as pilchard (Babcock et al.

1999, Willis et al. 2000, Watson et al. 2005), mackerel (Ellis & DeMartini 1995) or sardines (Stobart et al. 2007) as an attractant because their oily properties are good for retaining the scent in the water column. Indeed, the composition of a reef fish assemblage includes fish of all trophic guilds, and the diets of these fish can vary substantially

(Russell 1983).

Fish abundance and fish density can be difficult to estimate using BRUV. For example, fish abundance can be underestimated in areas with high densities of fish because there is an upper limit to the number of fish that can simultaneously occur in the BRUV field of view. Calculating fish density is also extremely difficult using BRUV as the area sampled can be difficult to quantify. Models of bait plumes have been used to convert fish sightings to density estimates (Priede et al. 1994, Priede & Merrett 1996, Collins et al. 2002), although these models make several assumptions. The speed and direction of the current must be accurately measured and assumed to maintain these parameters throughout the entire sampling area. The odour from the bait is assumed to be retained in the water column and species are assumed to be stationary until sensing the bait, then respond immediately to the odour (Sainte-Marie & Hargrave 1987). These assumptions

Chapter 1: Introduction are precarious and as Yau and co-workers (YAU et al. 2001) noted, small differences in arrival time of some species will cause major fluctuations in density estimates. Indeed, the benefits of BRUV can be increased by developing and employing a consistent methodology, which will reduce biases and enable broader comparisons within the literature.

Aims of the study

The use of BRUV to estimate fish abundance and diversity in reef habitats is still in its infancy and several questions about the biases associated with this technique remain to be answered. Many of these questions surround the bait component of BRUV as many researchers employing this technique are using different types and amounts of bait, enclosed in various types of containers that provide fish with different levels of

accessibility (e.g. Ellis & DeMartini 1995, Babcock et al. 1999, Cappo et al. 2004,

Watson et al. 2005). We still do not know to what degree these factors affect the fish

assemblage surveyed. Additionally, the large variation in the techniques employed by

different researchers makes accurate comparisons within the literature difficult. My first

objective in this study was to compare three different baits – pilchard, abalone, and

urchin – by examining the differences in abundance and composition of the fish

assemblage recorded.

My main objective in the second data chapter was to compare fish assemblages in

different reef habitats in and around Jervis Bay Marine Park: coastal shallow, coastal

deep, and patch deep reefs. The Jervis Bay Marine Park was established in 1999, functioning to restore and protect marine floral and faunal diversity. To achieve this aim

Chapter 1: Introduction the Marine Park attempted to represent a full range of the available biological habitats

(ANZECC_TFMPA 1999). Surprisingly, patch reef, reef that is separated from the mainland by a body of sand, is currently not represented in the sanctuary zoning plan.

The sanctuary zone precludes all forms of fishing and I was surprised to find that no patch reef was given this level of protection considering that the composition of a temperate reef fish assemblage can vary between patch and coastal reef habitats

(Shepherd et al. 2005). Therefore, this research not only provides the Marine Park with valuable baseline data on fish abundance, richness and diversity in several reef habitats, but it also examines whether the fish assemblage in patch reefs differs from other habitats and therefore should be included in the Parks sanctuary zoning plan.

Chapter 2: Baited Underwater Video – Does Bait Matter?

Introduction

Reef fish play an ecologically important role in the function of temperate reefs

(Kingsford 1998). The reef fish assemblage has a direct effect on the structure and function of the reef ecosystem by having an impact on other organisms through predation and prey availability (Kingsford 1998, Witman & Dayton 2001). However, as a conspicuous component of the marine environment, reef fish are subject to human influence and many species are harvested for food, sport and bait (Kingsford et al. 1991).

Unfortunately, the heavy demand for these fish can have a negative effect on the dynamics of the reef ecosystem and dramatically change the structure of the reef community (Underwood et al. 1983, Shears & Babcock 2002).

Most reef ecological surveys are done using underwater visual census (UVC), although several recent studies estimating fish abundance and diversity within marine protected areas have employed baited remote underwater video (BRUV) as the monitoring technique (Babcock et al. 1999, Willis & Babcock 2000, Willis et al. 2000, Westera et al.

2003, Willis et al. 2003). Similar to UVC, BRUV is a non-extractive and non-destructive monitoring technique, undoubtedly an important quality for sampling within sensitive areas such as marine reserves. BRUV has several advantages over UVC in that it can be used in depths not suitable for SCUBA, it is not restricted by water temperature, and it can be operated in areas of high current and low visibility. Moreover, there are several biases associated with UVC, which are well documented (Thresher & Gunn 1986,

Chapter 2: Baited Underwater Video – Does Bait Matter?

Thompson & Mapstone 1997, Edgar et al. 2004). In particular, UVC has been problematic for obtaining accurate fish samples in marine protected areas where fish can become “diver-friendly” or “diver-negative” depending on the location (Cole 1994).

Until recently, few studies have used BRUV to examine reef communities in depths less than 100 metres. BRUV has predominantly been used to examine fish in depths ranging from 600 to 5000 m (Priede et al. 1990, Armstrong et al. 1991, Collins et al. 1999, Yau et al. 2002). Not surprisingly, all of the research attempting to ascertain biases associated with BRUV has been done in deeper habitats (Priede & Merrett 1996, 1998). Therefore, scientists using BRUV in much shallower water have only these extremely deep comparisons to make generalizations about the BRUV sampling technique. The problem with this is that the behaviour of the fish found in these very deep habitats, typically scavengers, is quite different because the conditions are typically unproductive compared to more shallow reefs (Jacob et al. 1998). Therefore, there is considerable scope for standardizing, and potentially improving, the effectiveness of BRUV for use on reefs in depths less than 100m. Nevertheless, as scientists become more familiar with this sampling technique, BRUV is fast becoming a standard monitoring tool in marine protected areas. In fact, within Australia BRUV monitoring programs have been put in place in all New South Wales marine parks, the Great Barrier Reef Marine Park in

Queensland, and Ningaloo Marine Park in Western Australia (T.Lynch pers. comm.).

Surprisingly, there has not been a single BRUV study examining differences among baits to attract fish. Indeed, a reef fish assemblage constitutes fish of different trophic levels

Chapter 2: Baited Underwater Video – Does Bait Matter? and the food and feeding behaviour of reef fish varies considerably (Russell 1983).

Scientists have been catching and monitoring animals by attracting them to bait for centuries and there have been numerous studies examining bait preference to attract the greatest numbers (Ernst 1965, Stein et al. 1990, Kutka et al. 1992, Spurr 1995,

Krushelnycky & Reimer 1998, Saunders & Harris 2000). Therefore, it seems logical to examine the most effective bait for attracting the greatest number of fish to a BRUV. In fact, researchers currently using BRUV have not blindly chosen the type of bait for sampling, yet have drawn on studies from similar survey techniques, namely fish trapping, to determine the bait of choice (Cappo & Brown 1996). Bait effectiveness is well documented in trapping experiments (Wolf & Chislett 1974, High 1980, Munro

1983, Dalzell & Aini 1987, Whitelaw et al. 1991), and researchers using this technique have found that using oily baitfish such as pilchard (Scardinops sp.) is more effective for catching a greater abundance of fish than white-fleshed baits such as Lethrinus choerorhynchus (Whitelaw et al. 1991) and octopus (High 1980). There is no question that these findings have spurred the popular decision to use a soft-fleshed, oily baitfish in

BRUV experiments. In a survey of BRUV studies done in depths less than 100m, all but two used mackerel (Scomber sp.) or pilchard to attract fish (Babcock et al. 1999, Willis &

Babcock 2000, Westera et al. 2003, Willis et al. 2003, Cappo et al. 2004, Watson et al.

2005, Harvey et al. in press). The exceptions are Ellis and DeMartini (1995) who attached a single squid to the outside of the bait container filled with mackerel, and

Stobart and associates (2007) who combined sardines with an effervescent bait pellet. In fact, pilchard (Sardinops sp.) has been the only bait used in shallow BRUV studies within

Chapter 2: Baited Underwater Video – Does Bait Matter?

Australian and New Zealand waters (Babcock et al. 1999, Willis & Babcock 2000, Cappo et al. 2004, Watson et al. 2005).

Although it might seem sensible and cost effective for researchers using BRUV to base their choice of bait on trapping experiments, there are differences between trapping and

BRUV techniques. The most significant difference between these techniques is the soak time. Most BRUV studies use 30 minute sampling periods because 30 minutes was found to be the most cost effective time interval that produced consistent estimates of relative density (Willis & Babcock 2000). In contrast, fish trapping is normally done in intervals of days (Munro 1983, Dalzell & Aini 1987, Blanc 1988), which requires use of bait that will retain its odour for long durations. Since researchers using BRUV can change bait after short sampling periods, they could potentially benefit from selecting different bait to that which has been found to be the most effective for trapping.

I set out to compare two different types of fish baits - abalone gut (Haliotis spp.) and urchin (Heliocidaris erythrogramma) - to the commonly used pilchard bait in order to examine if there would be a difference in the fish abundance and fish assemblage recorded using BRUV. Abalone gut was chosen because it was recognised in an

Australian national survey, conducted by Kiwigama Research (2002), as one of the top eight most commonly used types of bait and berley by recreational fisherman in

Australia. This bait is easy to obtain and can found in most bait and tackle shops.

Urchin, in contrast, is not found in most fish and tackle shops although it is ubiquitous in local waters of NSW and can be gathered with little effort. I chose to examine this bait

Chapter 2: Baited Underwater Video – Does Bait Matter? based on my personal observation that scuba divers are often successful in attracting fish by breaking open the urchins and exposing the intestines. The aim of this experiment was to test the hypothesis that there is no difference in the fish assemblage visiting the

BRUV station when using pilchard, abalone, or urchin bait to attract fish. As the response of fish species may vary with space and time, I replicated both of these factors in the design.

Chapter 2: Baited Underwater Video – Does Bait Matter?

Methods

Study Site The study was done in Jervis Bay, which is a 102 km2 temperate marine embayment located approximately 180 km south of Sydney, New South Wales, Australia (Fig. 2).

The bay is part of the larger Jervis Bay Marine Park, which extends from north of

Kinghorn Point to south of Sussex Inlet. The Marine Park covers 215km2 and comprises nearly 10% of the Bateman’s Shelf Bioregion (Breen 2005) (Fig. 2).

Jervis Bay Marine Park is biologically diverse and contains a variety of tropical and temperate fish species (Ward & Jacoby 1992). A wide range of habitats occur within the

Marine Park including salt marsh, mangrove, rocky shores, subtidal rocky reefs, subtidal seagrass and sand flats, sandy beaches, and open ocean. The wide range of habitats within the Park provide areas for sanctuary, feeding, and breeding of both resident and migratory marine species (Ward & Jacoby 1992).

This study was done on three shallow subtidal rocky reefs within Jervis Bay: Callala Bay

Reef (35o05’S, 150o43’E), Huskisson Reef (35o20’S,150o40’E), and Plantation Point

(35o04’S, 150o41’E) (Fig. 2). Huskisson Reef is located about 700m offshore and is found in 10 to 12m depth. The reef is subjected to a tidal influx of nutrients from

Currambene Creek, which is a large freshwater catchment with salt marsh and mangrove habitats (Saintilan & Wilton 2001). Similarly, Callala Bay Reef goes down to about 12m.

This reef is also located near a creek mouth and, like Plantation Point, its edges reach the shoreline. Plantation Point is the deepest of the three reefs and drops to 17m at its deepest point. All three reefs have sand and seagrass habitats (Zostera Capricorni)

Chapter 2: Baited Underwater Video – Does Bait Matter? located around the reef edges. Algal diversity on all three reefs is relatively low, with

Ecklonia radiata the most common algae. Previous studies examining fish diversity of these shallow reefs found that Labridae and Monacanthidae were the most speciose families inhabiting with several site-attached species such as damselfishes, red morwong

Cheilodatylus fuscus, and rock cale Crinodus lophodon found in most locations (Barrett et al. 2006). Abundant invertebrate species include the long-spined urchin

Centrostephanus rodgersii, Turbo snails, and red-throated ascidians Herdmania momus.

Chapter 2: Baited Underwater Video – Does Bait Matter?

Sampling Design Sampling took place from June 21 - 23 in 2005 and June 26 – 28 in 2006. Sampling was restricted to daylight hours (8am – 4pm) to avoid confounding influences that might be associated with diurnal-nocturnal daily feeding behaviour. The three subtidal rocky reefs within the bay that were selected for the study, Plantation Point, Huskisson Reef and

Callala Bay Reef (Fig. 2), were chosen because they provided a level of spatial replication, adding generality to the study as well as providing several sampling options in varying weather conditions. In addition, these reefs were selected because they provided more than 1km of continuous subtidal rocky reef, with an easily accessible reef/sand interface. This allowed sufficient spacing to ensure independence between samples.

A two-factor orthogonal design (bait type, location) was used in 2005, and then repeated at the same three reef locations in 2006. Twelve samples were taken at each location, comprising four replicate samples for each of the three bait types: pilchard, abalone, and urchin. Each location was sampled in a day. The positioning of samples along the reef was done haphazardly, and the order of the bait treatments were randomly assigned using a random number table. The position of each sample along the reef was marked using a

Simrad colour depth sounder and GPS plotter. Using these marked positions a minimum of 200m was maintained between each of the samples. This distance of separation was chosen on the basis of previous studies to ensure independence among samples (Ellis &

DeMartini 1995).

Chapter 2: Baited Underwater Video – Does Bait Matter?

The ecotone between the reef and sand was targeted in order to maximise sampling a wide variety of species from both types of habitat. The BRUV was positioned on the sand immediately adjacent to the reef, which minimised the chance of the equipment becoming wedged onto part of the reef. This was accomplished using the depth sounder to locate the edge of the reef when it was not visible from the surface. All samples were collected at a water depth between 3 and 10 m.

A sample consisted of a thirty minute recording of fish attracted to the bait station. The

BRUV was deployed for a minimum thirty five minutes to allow time for it to settle on the bottom before recording. A thirty minute recording period was chosen based on previous studies, which indicated that this deployment interval allowed for consistent estimates of relative density between different areas without incurring additional costs that provide little or no benefit to making comparisons of relative abundance (Willis &

Babcock 2000).

Bait I drew comparisons between three different baits: pilchard (Sardinops neopilchardus,

Phylum Chordata), abalone (Haliotis spp., Phylum Mollusca), and urchin (Heliocidaris erythrogramma, Phylum Echinodermata). The entire body of the pilchard and urchin were used for bait, while only the abalone intestines were used. Abalone gut will hereafter be referred to as “abalone”. Both the pilchard and abalone baits were purchased frozen and kept frozen until the day before their use. Urchins, in contrast, were hand collected at Bellambi Harbour (near Wollongong, NSW), at 1-3 m depth, and then treated in a similar manner to the other baits. The baits were thawed on the day before their use.

Chapter 2: Baited Underwater Video – Does Bait Matter?

For consistency, each treatment consisted of 200 grams of the assigned bait, and this amount was based on quantities used in previous studies (Willis & Babcock 2000). Each type of bait was chopped up into 5 cm cubes, or cut open, in the case of the urchin, to maximize the odour plume. Urchin was placed in a plastic sandwich bag (180 x 170 mm) to help retain its contents. Several perforations were made in the bag by stabbing through the plastic with a sharp dive knife, to allow the oils from the urchin test slowly release into the water column. Bait was replaced after every sample.

BRUV Components The BRUV system is termed a “remote” system because it is lowered, then left on the seafloor while continuously recording video images of the bait and visiting species without the need of an operator. I developed four identical single-video BRUV systems at the University of Wollongong for their use in this research within Jervis Bay Marine

Park. The BRUVs were assembled using a similar design to those developed at the

Australian Institute of Marine Science (Cappo et al. 2002), which were designed to sit on the seafloor while recording from a horizontal position. Each BRUV was composed of a video housing, video camera, stand, bait arm and bridle system with a line attached to the frame (Fig. 3).

Video was recorded using Cannon MV750i digital video cameras. A Canon WA-30.5 wide angle lens (reduces focal length by 0.6x) replaced the standard lens in order to maximise the field of view. Camera settings during recording were set at “auto exposure”, “auto focus” and “long play record mode”. The “long play record mode” provided ninety minutes of recording space onto 60 minute Sony digital video cassettes,

Chapter 2: Baited Underwater Video – Does Bait Matter? allowing two, 30 minute samples to be recorded on one cassette. In contrast, the “normal play” only allowed time for one sample per cassette, without any advantage to identifying fish within the viewing area.

The BRUV stands were made from galvanized steel (Fig. 3). They were designed with a wide-based, rectangular frame to ensure that they would remain upright and stable on high profile reefs when exposed to strong currents, tidal or wave action. Camera housings were bolted within the center of the steel frames to view the bait arm and substrate in a horizontal orientation. The camera housings were made from high-pressure

PVC (polyvinyl chloride) pipe with flat acrylic end-ports. The acrylic port at the forward end of the housing was removable by stainless steel clips to allow camera access while the back port end was permanently fixed (Fig. 3). It was decided to have a clear window at the back of the housing because it allowed me to examine the camera view through the camera view finder and, more importantly, ensure that the camera was recording. Once recording was verified the BRUV could be lowered into the water. Inside the housings cameras were kept stationary using Styrofoam cut-outs glued into place and a backstop positioned to keep the camera as close to the front window as possible.

The bait arm extended 1.5 m from the frame. It was made from PVC conduit pipe and slotted into a steel tube that was welded onto the bottom of the frame. Once inserted into the frame the bait arm was held in place by a removable clip. The ability to remove the pipe from the frame improved the storage and transport of the BRUV. To hold the bait, a plastic mesh bait canister (8cm diameter, 30cm length) was used. The holes in the mesh

Chapter 2: Baited Underwater Video – Does Bait Matter? were approximately 5 mm in diameter, allowing the bait plume to escape into the water column. Bait was added or replaced in the container after every sample through a small mesh door, held shut by Velcro straps.

The BRUVs were lowered and retrieved using 9 mm polyethylene rope. A bridle was tied from each of the top four corners of the BRUVs to ensure the stand remained horizontal while being lowered from the boat. The polyethylene rope was positively buoyant, which ensured it did not sink into the field of view of the video cameras once the stand was resting on the bottom. Floats were attached to the end of the ropes (Fig. 3) and were clearly labeled to minimise the chance of recovering the BRUV out of sequence during sampling.

Chapter 2: Baited Underwater Video – Does Bait Matter?

a) b)

d) c)

Chapter 2: Baited Underwater Video – Does Bait Matter?

Analysis of video footage Video footage from each of the 30 minute deployments was examined in the laboratory using the video cameras and running the video output through a television screen. On review of the footage, the 30 minute sampling period started once the BRUV settled on the bottom. A time counter on the video screen was used to determine the start time and time of all subsequent recordings. All species were counted as well as the time of their first arrival (t1st) and the maximum number viewed at any one time (Max n). Several references were used to confirm species identification (Hutchins & Swainston 1999,

Edgar 2000, Kuiter 2000). Fish were only recorded if they came within an estimated 2m from the bait. This viewing area has been standardised to an area of 9.4 m3 (Coram, M. and Gladstone, W. unpubl. data), although no estimates of absolute density have been attempted. Max n and t1st have been used as indices in several recent studies using

BRUV. The advantage of Max n is that individuals are not counted more than once.

However, it can result in conservative estimates when fish congregate in high densities because fish in the foreground obscure the view of fish in the background. Max n is synonymous with the npeak used by Priede and co-workers (1994; 1998), the MAX used by Willis and Babcock (2000), the MAXNO of Ellis and DeMartini (1995) and the MaxN of Cappo et al. (2004). Previous studies have shown that this index is correlated with fish abundance (Willis et al. 2000) and is also comparable with other well established measures for estimating fish abundance such as long-line catch rates (Ellis & DeMartini

1995). Similarly, Willis and Babcock (2000) found t1st to be an accurate time-based index of relative abundance for blue cod (Parapercis colias).

Chapter 2: Baited Underwater Video – Does Bait Matter?

Statistical Analysis Sampling years (2005, 2006) were analysed separately for two important reasons. First, equipment failure resulted in the loss of a replicate from the 2005 data set. Hence, more replicates were completed in the second year, which would have resulted in an unbalanced design or required eliminating one replicate for each of the baits at all locations (Underwood 1997). Second, including both years in the design would have constituted a three-factor ANOVA with two random factors (Time and Location) and one fixed factor (Bait), and there are no appropriate F-tests for testing the main effects in an experimental design with two or more random factors unless both of those factors are nested (Quinn & Keough 2002). Quasi F-tests can be calculated to examine the main effect, but these tests are only approximate at best (Burdick 1994).

Univariate analysis Four dependent variables were examined: relative abundance (Max n), species richness, species diversity index (H′) (Shannon-Weiner Diversity Index), and first time of first arrival (t1st1). t1st1 was the t1st for the first species that arrived in each sample.

Comparisons between assemblages and families were examined using Total Max n, which was calculated by taking the sum of the Max n for all species in each sample.

H′ was calculated incorporating Max n data into the formula:

S was the number of species recorded per drop.

Chapter 2: Baited Underwater Video – Does Bait Matter?

pi was the relative abundance of each species, calculated as the proportion of individuals of a given species to the total number of individuals in the assemblage: , where

N was the total number of all individuals (Total Max n):

, and ni was the number of individuals in each species (the abundance of each species was found using Max n).

Dependent variables were tested using a two-factor General Linear Model Analysis of

Variance (ANOVA) (GMAV 5 software, Institute of Marine Ecology, University of

Sydney). In addition, family and species-specific abundance were compared. Bait was analysed as an orthogonal fixed factor with 3 levels: pilchard, abalone, and urchin.

Location was analysed as a random factor with 3 levels: Callala, Huskisson, and

Plantation Point. Assumptions of normality were examined by viewing the data.

Assumptions of heterogeneity of variances were examined using Cochran’s C-test and data were transformed if significant heterogeneity was detected. If no appropriate transformation produced homogeneous data than the untransformed data were analysed as ANOVA is robust for heterogeneous data (Underwood 1997). Interactions between bait and location where pooled if p values were greater than 0.25 (as suggested in

Underwood 1997). Differences among bait types or locations were examined by doing post hoc pairwise comparisons using the Student-Newman Keuls (SNK) test after significant ANOVA (GMAV 5 software, Institute of Marine Ecology, University of

Sydney).

Chapter 2: Baited Underwater Video – Does Bait Matter?

Multivariate analysis Non-metric multidimensional scaling (nMDS) ordination, based on a Bray-Curtis dissimilarity matrix of fourth-root transformed data, was used to visually examine variation in the fish assemblage for years 2005 and 2006 (PRIMER software, Plymouth

Marine Laboratories) (Clarke 1993). Fourth-root transformations were used as they are effective for abundance data where several zeros are present and there are few large numbers (Quinn & Keough 2002). Centroids of the assemblage at each location were displayed on the nMDS ordination because of the large number of replicate samples

(PCO software, Anderson 2001, Anderson 2003). Distance-based permutational multivariate analysis of variance (PERMANOVA) based on Bray-Curtis dissimilarity matrix of fourth-root transformed data was used to test the null hypothesis of no difference in assemblage structure among baits and among locations (PERMANOVA software, Anderson 2005). Bait was analysed as an orthogonal, fixed factor with 3 levels: pilchard, abalone, and urchin, and location as an orthogonal random factor with 3 levels:

Callala, Huskisson, and Plantation Point.

Chapter 2: Baited Underwater Video – Does Bait Matter?

Results

A total of 47 species from 30 families were recorded over the two years of sampling: 35 species from 23 families in 2005 and 40 species from 26 families in 2006 (see Appendix

1). Thirty two species from 21 families were recorded using abalone, 36 species from 26 families using pilchard, and 33 species from 22 families using urchin. Overall, Labridae and Monacanthidae were the most speciose families recorded (see Appendix 1).

Fish Species Richness and Abundance In 2006, I detected a significant difference in species richness of fishes attracted by different baits (Table 2, Fig. 4). Further analysis revealed that this difference could be explained by greater species richness attracted to pilchard than urchin (SNK test: p<

0.05). It was at two of the three locations, Callala Bay Reef and Huskisson Reef, that I detected a greater mean number of species using pilchard than urchin bait. The largest difference occurred at Callala, where more than double the mean number species were recorded using pilchard compared to urchin (Fig. 4). There were no differences in species richness between baits detected in 2005; however it is important to note that once again the largest difference in the mean number of species attracted to pilchard and urchin was at Callala Bay Reef (Fig. 4) and there was little difference between the means at Plantation Point Reef.

Chapter 2: Baited Underwater Video – Does Bait Matter?

2005 2006

12 12

10 10

8 8

6 6

4 4

Species Richness 2 2

0 0

100 100

80 80

60 60 Max n

40 40 Total 20 20

0 0

2.00 2.00

1.60 1.60

′ 1.20 1.20 H 0.80 0.80

0.40 0.40

0.00 0.00

800 800 700 700 600 600 (s)

1 500 500

400 400 t1st 300 300 200 200 100 100 0 0 C H PP C H PP Figure 4. Mean (± SE) species richness, relative abundance (Total Max n), Shannon-Weiner Diversity Index (H′), and first time of first arrival (t1st1) of fish in the presence of three baits (pilchard , abalone , and urchin ) at three locations (Callala (C), Huskisson (H), and Plantation Point (PP) in 2005 (n=3) and 2006 (n=4)

Chapter 2: Baited Underwater Video – Does Bait Matter?

Species Richness Total Max n H′ t1st 1 2005 df MS F MS F MS F MS F Bait 2 8.11 1.07 1.67 2.68 0.33 1.23 0.89 0.18 Location 2 16.78 2.21 1.04 1.67 0.31 1.16 5.17 2.90 B x L 4 9.89 1.30 0.70 1.13 0.18 0.66 4.92 2.76 RES 18 7.07 0.61 0.29 1.78 Transformation Nil ln (x+1) ln (x+1) Nil

2006 Bait 2 42.53 5.41 4.45 3.77 0.66 2.64 2.73 0.85 Location 2 23.03 2.93 2.28 1.93 0.91 3.64 18.07 5.61 B x L 4 7.44 0.95 0.50 0.43 0.16 0.62 1.77 0.55 RES 27 7.93 1.28 0.26 3.43 Transformation Nil ln (x+1) ln (x+1) Nil

In 2006, the relative abundance of fish (Total Max n) attracted to the baits was significantly different (Table 2, Fig. 4). Similar to the species richness variable, there was a greater relative abundance recorded when the BRUV was baited with pilchard compared to urchin (SNK test p >0.05). The mean number of individuals recorded at the three locations in 2006, as indicated by mean Total Max n (Fig. 4), ranged between 39 and 52 when using pilchard, and between 23 and 48 using abalone. In the same year, the mean number of individuals recorded at each of the three sites when using urchin ranged between 7 and 19. In fact, over eight times the Total Max n was recorded using pilchard bait verses urchin at Huskisson, and over 6 times the amount was recorded at Callala. In

2005, a similar trend was observed amongst the locations although evidently the differences were not great enough to detect differences amongst the baits in this year

(Table 2, Fig. 4).

Chapter 2: Baited Underwater Video – Does Bait Matter?

Family-specific and species-specific comparisons were examined and there were no clear differences in the relative abundance of fish attracted among baits for the two most speciose families: Labridae and Monacanthidae (Table 3). Additionally, the relative abundance of the five most prolific species was examined and there were no significant differences in relative abundance among baits for any of the other species examined

(Table 3).

The trends indicated by H′ paralleled species richness and relative abundance, although there was no difference between baits detected in either year (Table 2, Fig. 4). In contrast, a significant difference in H′ was detected between locations in 2006. More specifically, results were explained by differences between Plantation Point and Callala using post hoc SNK test (p<0.05). In fact, in 2006, H′ for all three treatments increased at

Plantation Point, the greatest difference recorded was for urchin where its H′ increased from 0.49 and 0.87 at Callala and Huskisson respectively, to 1.35 at Plantation Point.

Chapter 2: Baited Underwater Video – Does Bait Matter?

2005 2006 Categories Source df MS F p df MS F p Labridae Bait 2 4.70 1.90 0.264 2 8.78 1.400.346 Location 2 12.93 5.92 0.011 2 17.53 4.50 0.021 Ba x Lo 4 2.48 1.14 0.371 4 6.28 1.61 0.200 RES 18 2.19 27 3.90 Monacanthidae Bait 2 0.03 1.84 0.993 2 0.36 1.530.321 Location 2 0.17 1.49 0.253 2 1.36 2.94 0.070 Ba x Lo 4 0.02 0.16 0.955 4 0.24 0.51 0.729 RES 18 0.12 0.96 0.476 27 0.46 Heterodontus portusjacksoni Bait 2 1.37 1.95 0.257 2 7.44 5.64 0.069 Location 2 0.48 0.59 0.564 2 4.86 4.41 0.022 Ba x Lo 4 0.70 0.86 0.504 4 1.32 1.20 0.335 RES 18 0.81 27 1.10 Pagrus auratus Bait 2 0.62 0.29 0.761 2 0.63 1.73 0.287 Location 2 0.09 0.17 0.842 2 0.44 1.04 0.369 Ba x Lo 4 2.11 4.07 0.016 4 0.37 0.86 0.501 RES 18 0.52 27 0.43 Pictilabrus laticlavius Bait 2 0.48 1.53 0.321 2 0.86 0.55 0.616 Location 2 0.15 0.19 0.828 2 1.03 1.50 0.241 Ba x Lo 4 0.31 0.40 0.803 4 1.57 2.29 0.086 RES 18 0.78 27 0.69 Ophthalmolepis lineolata Bait 2 1.78 0.94 0.462 2 2.69 2.040.245 Location 2 6.78 13.07 0.001 2 7.86 7.26 0.003 Ba x Lo 4 1.89 3.64 0.024 4 1.32 1.22 0.326 RES 18 0.52 27 1.08 Atypichthys strigatus Bait 2 91.00 1.29 0.371 2 334.11 0.87 0.486 Location 2 87.11 1.89 0.180 2 455.44 0.78 0.470 Ba x Lo 4 70.78 1.54 0.234 4 384.03 0.66 0.628 RES 18 46.04 27 585.89

Chapter 2: Baited Underwater Video – Does Bait Matter?

There were no significant differences detected for time of the first fish arrival between the three different baits in either year (Table 2), although there were differences between locations in 2006. The time of fish arrival to all three baits was shortest at Plantation

Point in 2006 (Fig. 4), the largest differences occurring between Plantation Point and

Huskisson (SNK test p< 0.01). At Plantation Point in 2006, average t1st1 was 4 and 7 times faster using pilchard and abalone respectively, and 21 times faster for urchin, compared to their fastest response at either of the two locations.

Fish Assemblage There was no difference between the compositions of the fish assemblages that responded to the three different baits (Table 4). However, a multivariate ordination revealed more similarities between the assemblages attracted to the pilchard and abalone baits, compared to the assemblage attracted to the urchin bait (Fig. 5). Moreover, the fish assemblage that responded to the urchin bait varied among locations and years. I detected a significant difference between the three locations in 2005 and 2006 (Table 4).

An nMDS plot revealed a clear separation between Plantation Point and the other two locations (Fig. 5), with little variation among baits or years. In 2005, Plantation Point was significantly different to Callala, and in 2006, Plantation Point was significantly different to Callala and Huskisson (Table 4).

Chapter 2: Baited Underwater Video – Does Bait Matter?

Table 4. PERMANOVA differences in fish assemblage among baits and among locations for 2005 (n=3) and 2006 (n=4). Significant differences at α = 0.05 are indicated by bold type.

2005 2006 df MS F P df MS F p Bait 2 3441.30 0.994 0.44 2 2295.97 0.89 0.583 Location 2 4715.21 2.137 0.011 2 5902.69 2.184 0.006 B x L 4 3461.67 1.569 0.35 4 2579.86 0.955 0.539 RES 18 2206.33 27 2702.93

Post Hoc Comparison T P T p Callala x 0.866 0.655 1.063 0.346 Huskisson Callala x 1.814 0.002 1.656 0.009 Pl. Point Pl. Point x 1.3128 0.105 1.7512 0.002 Huskisson

Chapter 2: Baited Underwater Video – Does Bait Matter?

Discussion

This study provides the first baited remote underwater video (BRUV) comparison of baits and demonstrated that different types of bait used in this sampling technique can result in differences in the abundance and species richness of temperate reef fish at certain locations. Three separate baits were examined: pilchard, abalone, and urchin, in two separate years of sampling. In the second year of sampling the number of replicates was increased and it was discovered that using pilchard bait in BRUV attracted a greater number of species, and a higher abundance of fish than urchin bait. In contrast, post hoc comparisons revealed no differences between pilchard and abalone baits. From a methodological standpoint, pilchard and abalone are a better choice of bait based on consistencies in the fish assemblage detected at different locations between years. The fish assemblage detected using urchin bait showed considerable variation at most locations between 2005 and 2006.

Mean species richness recorded while using pilchard and abalone baits was comparable to other BRUV studies on shallow temperate reefs within Australian waters (Watson et al. 2005). At Callala and Huskisson, the average number of species recorded in 2005 and

2006 using pilchard and abalone ranged between five and ten, while the average number of species recorded with urchin bait at these same locations was between two and four.

Similarly, overall abundance, estimated by Total Max n, was significantly less using urchin in 2006, compared to the other two baits. In 2006 I recorded an average of approximately 35 and 45 individuals while using abalone and pilchard bait respectively, which are comparable to numbers reported from a BRUV study in northern Australia

Chapter 2: Baited Underwater Video – Does Bait Matter? where Cappo et al. (2004) reported an average of 29 individuals per BRUV drop. On the other hand, an average of less than 17 individuals was recorded in 2006 while sampling with the urchin bait.

Previous studies have shown that urchin is not found in the gut contents of many fish species (Russell 1983) and although this bait attracted a lesser abundance of fish and species richness than pilchard at most locations in one of the years of sampling, I do not argue that temperate fish have a taste preference for pilchard. Instead, this study aimed to examine baits as a method of attracting fish. Considerable manipulation was done to the baits, particularly urchin bait which was caught, frozen, then placed in a plastic bag in an attempt to release the odour into the water column at a slow pace, therefore retaining the attractant properties for as long as possible. However, there is strong evidence supporting the use of pilchard bait for BRUV studies.

There was a clear difference between Plantation Point and the other locations in 2006 with similar trends in 2005. H′ was greater at Plantation Point for all three treatments in the second year of sampling. More dramatic was the large decrease in the time of first arrival of fish for all three treatments. These differences could be a result of greater fish density at Plantation Point compared to the other locations. Unfortunately, using BRUV to estimate absolute fish density is problematic because the sampling area is difficult to estimate due to variation in dispersal of bait plume depending on current speed (Priede &

Merrett 1996, Willis & Babcock 2000, Cappo et al. 2002). However, other studies have

Chapter 2: Baited Underwater Video – Does Bait Matter? found a correlation between time of first fish arrival and absolute fish density (Priede et al. 1990, Armstrong et al. 1992).

The treatment most affected by location when examining time of first arrival in 2006 was urchin, with a huge decrease in the mean time of first arrival at Plantation Point. A potential explanation for the increased effectiveness of the urchin bait at Plantation Point is that the attractive properties of the urchin bait disperse quickly in the water column despite efforts to retain these qualities, resulting in less chance of attracting species from outside the immediate sampling area. Therefore, if Plantation Point is indeed an area with a high density of fish, then a long-lasting attractant becomes less important for sampling species richness and abundance. Species such as the Port Jackson Shark

Heterodontus portusjacksoni, which are unlikely to be found on the reef during the day

(McLaughlin & O'Gower 1971), will be recorded in fewer numbers if the bait plume is rapidly dispersed, regardless of the location. Indeed, the average number of H. portusjacksoni recorded at Plantation Point over the two years of sampling was only 0.5 while baited with urchin, compared to 2.8 and 4.95 for abalone and pilchard baits respectively (see Appendix 1). In addition, research has shown that snapper (P. auratus) preys heavily on echinoids (Russell 1983) and although I did not detect any differences among baits when examining this species, the greatest snapper Max n recorded at

Plantation Point was using urchin bait.

A greater density of fish at Plantation Point combined with the diffusive properties of urchin would also explain why there appeared to be a greater temporal variation in the

Chapter 2: Baited Underwater Video – Does Bait Matter? composition of the fish assemblages detected using urchin at Callala and Huskisson compared to Plantation Point, as illustrated in Figure 5. In contrast, temporal variation in the fish assemblage at all three locations was more consistent when examining pilchard and abalone. Indeed, if urchin bait does in fact sample a smaller area, particularly along reefs where species types are not densely populated, then there would be less chance of finding consistency in the assemblage between years.

Overall, the fish assemblage detected in this study was a good representation of the taxonomic composition of the fish assemblage reported from UVC in Jervis Bay and comparable locations in eastern Australia, with Labridae and Monacanthidae the most speciose families observed (Barrett et al. 2006, Gladstone 2006). Fish baits selected for the study were aimed at attracting carnivorous predators, however fish from all trophic guilds were sampled. The schooling planktivores Atypichthys strigatus and Trachurus novaezelanidae were recorded in high abundance and the herbivore Kyphosus sydneyanus was also sampled (see Appendix 1). This confirms results from other BRUV studies that have also shown that this technique is useful for surveying a thorough representation of the reef fish community because fish are not only attracted to the bait, but also to the activity of fish surrounding the bait (Cappo et al. 2004).

Indeed, the advent of BRUV has provided reef fish ecologists with an effective survey method compared to other fish survey techniques such as long-line and trawl (Ellis &

DeMartini 1995, Cappo et al. 2004). This technique is extremely useful in marine protected areas (Willis & Babcock 2000) and is less prone than other survey methods to

Chapter 2: Baited Underwater Video – Does Bait Matter? zero counts that lead to results with low statistical power (Cappo et al. 2002). However, the potential benefits of this technique can be increased by developing and employing consistency in the methods used among researchers, which will reduce biases and enable us to make broader comparisons within the literature.

There have been very few studies which attempt to standardize the methodology for using

BRUV on reefs more shallow than100m. Surprisingly, this is the first study that has compared the effectiveness of different baits and fortunately my findings lead me to suggest that researchers using BRUV to study temperate reefs have made a good decision in selecting oily, soft fleshed baitfish, namely pilchard, to attract the greatest abundance of fish. These findings are a step forward in an effort to standardize the method of

BRUV and reduce the biases.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

Introduction

Marine parks are being established worldwide in an effort to protect and conserve coastal

resources and diversity (Jennings 2001), and the protection of reef fish is often a key

objective of marine park management. Reef fish play an ecologically important role in

the function of temperate reefs and have a direct effect on the function of other organisms

constituting the reef community (Kingsford 1998, Witman & Dayton 2001). However,

there is considerable pressure on reef fish populations because many of the species found

on temperate reefs are commercially important and are heavily targeted for food, sport,

and bait (Kingsford et al. 1991). Therefore, there is an ongoing effort by marine park authorities to monitor local reef fish assemblages in an attempt to understand the processes that influence the abundance and diversity of these communities and to successfully manage, conserve, and restore their populations (Abesamis 2006, Blyth-

Skryme et al. 2006).

Marine ecologists have long been aware that differences in the physical nature of habitat influences the spatial variation of abundance and diversity of temperate reef fish assemblages (e.g. Choat & Ayling 1987, Gillanders & Kingsford 1998). Physical habitat qualities can influence the population biology because differences in these qualities affect a number of abiotic variables including light, nutrients, and oxygen. Indeed, the depth at which a habitat occurs is an important factor in influencing patterns of species richness

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video and abundance (Dufour et al. 1995, Denny 2005). For example, Curley et al. (2002) found that urchin barrens were devoid of certain species of fish in depths less than 13 m.

The proximity of a reef relative to the mainland can also influence the composition of the fish assemblage (e.g. Shepherd et al. 2005). Coastal reefs are generally productive areas in part because of high quantities of nutrients are that are present resulting from a number of factors including upwelling events (vertical mixing) and nutrient-rich runoff from the land (Clarke 1940, Ryther & Yentsch 1958). Arguably, productivity is ultimately determined by food web structure (Borer et al. 2005) although abiotic factors such as nutrients are the building blocks for potential production (Ryther & Yentsch 1958).

Patch reefs are also known to be productive areas. Many organisms that establish on these reefs are able to collect and store nutrients from the typically nutrient deficient offshore waters, and increase the productivity of the area as explained by the “island mass effect” (Doty & Oguri 1956). These examples of nutrient availability only touch on the number of differences between coastal and patch reef habitats; however, both are productive habitats with unique reef fish communities that are often distinguishable from one another even when located within relatively close proximity (Shepherd et al. 2005).

It is imperative for marine park management to understand how these habitat factors govern the spatial variation of temperate marine reef fish assemblages (Day et al. 2002).

This begins with baseline surveys, which can be used by park authorities to make ecologically relevant decisions on the design of reserves, and continues with robust monitoring programs, which evaluate their success (see Garcia-Charton et al. 2000). In

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

New South Wales, the zoning plan for marine parks gets reviewed every five years, making ongoing research essential for maximizing the conservational benefits of the marine parks.

Several researchers have employed baited remote underwater video (BRUV) to examine spatial comparisons of temperate reef assemblages within marine parks (Willis &

Babcock 2000, Westera et al. 2003, Willis et al. 2003, Denny & Babcock 2004). The

BRUV technique is a good method for surveying fish assemblages within sensitive marine areas such as marine reserves because it is non-extractive and non-destructive compared to traditional capture techniques such as trawl and long-line. Additionally,

BRUV has several advantages over the commonly used survey method of underwater visual census (UVC) because it can be used at depths unsuitable for SCUBA divers that are limited by decompression limits.

The first aim of this study was to use BRUV to provide the Jervis Bay Marine Park management with baseline data on the abundance and diversity of reef fish in several reef locations including: shallow and deep coastal reefs, and deep patch reefs. Additionally, I sought to determine if differences in depth and proximity to land influences the composition of the reef fish community. As deep patch reefs are not currently represented in Jervis Bay Marine Park’s sanctuary zoning plan I feel this research is important to examine these areas for differences in fish diversity that could potentially justify including this habitat into the Park’s future sanctuary zoning plan.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video Methods Sampling took place from 28 September – 14 December, 2005, and March 3 – 17, 2006.

The 2005 sampling period extended over a much longer period than 2006 because of

several factors including boat and crew availability and unfavourable weather and ocean

conditions. The sampling periods will be referred to as the calendar years from which

they occurred, 2005 and 2006 respectively, although it should be noted that these two sampling periods took place within a twelve month span. Sampling was restricted to daylight hours (8am – 4pm) to avoid confounding influences that might be associated with diurnal-nocturnal feeding behaviour.

Six reefs, two of each of three different habitat types, were selected for the study: coastal shallow reefs Honeymoon Bay (35o03’S, 150o46’E) and Lobster Rock (35o00’S,

150o50’E); coastal deep reefs Long-nose Point (35o05S, 150o46’E) and Little Beecroft

Peninsula (35o01’S, 150o51’E); and patch deep reefs Sir John Young Banks (34o58’S,

150o53’E) and Middle Ground (35o06’S, 150o46’E) (Fig. 6). Eight replicate BRUV

drops were done in each location. For the case of this study, deep reefs are defined as reefs deeper than 15m and shallow reefs are 10m or less. Patch reefs are defined as reefs separated from the mainland and not connected to any other hard substrata. Both patch reefs are a minimum 2km from the nearest mainland (Fig. 4). All deep samples in the study were taken in depths between 17 and 33m and shallow locations were sampled at depths between 3 and 10m. Habitat types were sampled haphazardly.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

0246810Kilometers

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Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

Four identical BRUV were used for this experiment. The design of the BRUV and methods for deployment are described in the Methods section of Chapter 2. BRUV were baited with 200 g of pilchard (Sardinops neopilchardus) based on quantities used in previous studies (Willis & Babcock 2000). The pilchards were chopped up into 5 cm cubes, to maximize the odour plume, before being placed in the bait container.

Analysis of video footage Quantitative data were collected from video tapes as discussed in the Methods section of

Chapter 2.

Statistical Analysis Sampling years (2005, 2006) were analysed separately as discussed in the Methods

section of Chapter 2.

Univariate analysis Four dependent variables were examined: relative abundance (Total Max n), species

richness, species diversity index (H′) (Shannon-Weiner Diversity Index), and first time of

first arrival (t1st1). These are the same dependent variables as examined in Chapter 2.

More detail on these variables can be found in the Methods section of Chapter 2.

Dependent variables were tested using a two-factor General Linear Model Analysis of

Variance (ANOVA) (GMAV 5 software, Institute of Marine Ecology, University of

Sydney). Habitat was analysed as an orthogonal fixed factor with 3 levels: coastal

shallow, coastal deep, and patch deep, and location was analysed as a random factor

nested within habitat, with 2 levels. Assumptions of normality were examined by

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video viewing the data. Assumptions of heterogeneity of variances were examined using

Cochran’s C-test and data was transformed if significant heterogeneity was detected. If no appropriate transformation produced homogeneous data than the untransformed data were analysed as ANOVA is robust for heterogeneous data (Underwood 1997).

Interactions between habitat and location where pooled if p values were greater than 0.25

(as suggested in Underwood 1997). Significant differences revealed by ANOVA were examined by doing post hoc pairwise comparisons using the Student-Newman Keuls

(GMAV 5 software, Institute of Marine Ecology, University of Sydney).

Multivariate analysis Multivariate analysis was done as discussed in the Methods section of Chapter 2. Habitat type was analysed as an orthogonal, fixed factor with 3 levels: coastal deep, coastal shallow, and patch deep, and location was analysed as a nested random factor, within habitat, with 2 levels.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video Results Eighty one species from 43 families were recorded over the two sampling periods (see

Appendix 2). In 2005, there were 44 species sampled from each of the deep habitats and

43 from the shallow habitat, and in 2006 there were 47, 43, and 35 species recorded in

coastal deep, patch deep, and coastal shallow habitats respectively. Several species were

recorded in more than one sample and unique to a habitat. Two species, blue-throated

wrasse (Notolabrus tetricus) and black-banded sea perch (Hypoplectrodes nigroruber)

were only recorded on the coastal deep reefs; common stingray (Trygonoptera testacea),

happy moments (Siganus nebulosus), and black stingray (Dasyatis thetidis) were only recorded on the coastal shallow reefs; and blackspot pigfish (Bodianus unimaculatus), eastern king wrasse (Coris sandageri), velvet leatherjacket (Meuschenia scaber), butterfly perch (Caesioperca lepidoptera), and mosaic leatherjacket (Eubalichthys mosaicus) were only recorded on the deep patch reefs. Overall, Labridae and

Monacanthidae were the most speciose families recorded over the two sampling periods with 11 and 10 species, respectively. Four species from 3 families were recorded at every location in both 2005 and 2006: maori wrasse (Opthalmolepis lineolata)

(Labridae), green moray eel (Gymnothorax prasinus) (Muraenidae), mado (Atypichthys strigatus) (Scorpididae), and silver sweep (Scorpis lineolata) (Scorpididae). In fact, O. lineolata and A. strigatus were recorded in over ninety percent of samples. Two monocanthids, Meushenia flavolineata and Meushenia freycineti, were sampled at all of the deep water locations in both sampling periods, but were poorly represented at the shallow locations. The blue-spotted goatfish (Upeneichthys vlamingii: Mullidae) was more abundant in shallow locations.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video Species Richness and Abundance A difference in the number of species was recorded between habitats in 2006. More

specifically, a greater number of species were found in both of the deep water habitats

compared to the shallow habitat (SNK test p<0.05) and there was no difference in species

richness when comparing the two deep habitats (SNK test p>0.05). There was no

difference in species richness among locations in 2006, however in 2005 species richness

differed by almost a factor of two between the shallow coastal reefs locations (Fig. 7).

Patterns of species diversity, as indicated from the Shannon-Weiner Diversity Index, were similar to those of species richness (Table 5). In 2006, there was a clear separation between the shallow and deep locations with nearly a two-fold greater H′ recorded at the deeper locations (Fig. 7). In addition, a greater difference between the locations was once again evident in 2005 compared to the results from 2006.

There were differences in the time of first arrival among locations in 2005 (Table 5, Fig.

7). The largest differences detected were among the coastal shallow reefs, where a twenty five-fold difference in the mean time of first arrival was recorded (SNK test p<0.05). Surprisingly, there were much greater variations around the means at most locations in 2005 compared to sampling in 2006. Contrary to species richness and H′, there was no significant difference in the time of first arrival between habitats in either year.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video 2005 2006

16 16

12 12

8 8

Species Richness 4 4

0 0

80 80

60 60 Max n 40 40 Total 20 20

0 0

2.5 2.5

2 2

′ 1.5 1.5 H 1 1

0.5 0.5

0 0

100 100

80 80

(s) 60 60 1

t1st 40 40

20 20

0 0 LB LN HB LR MG SJY LB LN HB LR MG SJY

CD CS PD CD CS PD Figure 7. Mean (± SE) species richness, relative abundance (Total Max n), species diversity index (H′) (Shannon-Weiner Diversity Index), and first time of first arrival (t1st1) of fish within three habitat types: coastal deep (CD: ), coastal shallow (CS: ), and patch deep (PD: ). Two locations were sampled in each habitat. Locations included: Little Beecroft Peninsula (LB), Long-nose Point (LN), Honeymoon Bay (HB), Lobster Rock (LR), Middle Ground (MG), and Sir John Young Banks (SJY). In 2005 and 2006 (n=8).

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

Table 5. Two factor ANOVA for the variables: Species Richness, Shannon-Weiner Diversity Index (H′), relative abundance (Total Max n), and time of first species to arrive in seconds (t1st1 ). Transformations to data are reported (Trans.). Significant differences are in bold type at α = 0.05.

Species Richness Total Max n H′ t1st 2005 (n=8) df MS F MS F MS F MS F Habitat 2 1.17 1.99 2124.77 1.451.42 2.21 3.59 0.20 Loc(Ha) 3 0.59 3.89 1463.88 2.49 0.64 3.07 17.58 10.12 RES 42 0.15 587.32 0.21 1.74 Trans. ln (x+1) Nil Nil ln (x+1) 2006 (n=8) Habitat 2 202.75 12.29 1.04 3.33 3.56 66.93 3.43 1.47 Loc(Ha) 3 16.50 1.71 0.31 1.510.05 0.30 2.34 1.39 RES 42 9.67 0.21 0.18 1.68 Nil ln (x+1) Nil ln (x+1)

There were no differences in the relative abundance (Total Max n) of fish among habitats

or locations in either year (Table 5), however more than a two-fold difference was

recorded between the shallow locations in 2005 (Fig. 7). In fact, the relative abundance

of fish at one of the shallow locations in 2006 (Lobster Rock) was the highest recorded

(Fig. 7).

Assemblage Structure The fish assemblage detected on coastal shallow reefs was different from those recorded

on the deep coastal and deep patch reefs in 2006 (SNK test p<0.05) (Fig. 8). In contrast,

I did not detect any difference between the habitats in 2005 (Table 6). Similarities

between the fish assemblage recorded at the coastal deep reef and deep patch reef in both

sampling periods is evident from the nMDS plat visual depiction. Among locations,

there was little difference between the deep habitats in 2005 and 2006 (Fig. 8). In

contrast, fish assemblages in shallow coastal locations were more divergent in space and

time (Fig. 8).

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

In 2006 eleven species were identified as important contributors differentiating the fish assemblages between habitats (Table 7). Six of the eleven species were more abundant in both of the deep water habitats compared to the coastal shallow habitat including: white ear (Parma microlepis), silver sweep (Scorpis lineolata), snapper (Pagrus auratus), green moray eel (Notolabrus gymnogenis), blue groper (Achoerodus viridis), and half-banded sea perch (Hypoplectrodes maccullochi). To examine patterns from 2005 and 2006,

SIMPER comparisons between habitat types were also examined for 2005 and the results were similar (Table 7). Seven of the eight species identified by SIMPER in 2005 were also identified in 2006. The noticeable difference between the two sampling periods was a change in the distribution of the G. prasinus, which was more abundant at the two deep habitats in 2006, but was more abundant in the shallow habitat in 2005 (Appendix 2).

There was little difference between the assemblages detected at the two deep water habitats in either year. Two monocanthids were identified by SIMPER, yellow striped leatherjacket (Meushenia freycinetti) and six-spined leatherjacket (Meushenia freycineti), and each were found to be more abundant in deep patch reefs than the deep coastal and shallow coastal reefs. In fact, of the eleven species identified by SIMPER, eight contributed to variation between the two deep habitats, and seven of these were more abundant in the deep patch reefs (Table 7). In contrast, the fish assemblages at the two shallow locations were different in both years, more noticeably in 2005 (Fig. 8). I examined a SIMPER comparison of locations in 2005, and only two species, Atypichthys strigatus and Ophthalmolepis lineolata, contributed to the differences detected between the shallow coastal locations.

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

Table 6. PERMANOVA differences in fish assemblage between habitat and location for 2005 and 2006.

PERMANOVA 2005 df MS F P Habitat 2 7459.68 1.290 0.262 Location 3 5780.75 3.197 0.001 RES 42 1808.31 2006 Habitat 2 11385.25 2.661 0.017 Location 3 4278.16 3.392 0.001 RES 42 1261.28

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

CD vs CS CD vs PD CS vs PD

Species δ i %δ i δ i/SD δ i %δ i δ i/SD δ i %δ i δ i/SD

2005

Scorpis lineolata 4.86 6.57 1.34 (cd) 2.88 4.93 0.94 6.48 9.21 1.36 (pd) Trachurus 4.84 6.55 1.05 (cd) 4.10 7.02 1.15 (cd) 4.28 6.08 1.02 (pd) novaezelandiae Atypichthys strigatus 4.26 5.76 1.08 (cs) 3.48 5.95 1.05 (pd) 4.36 6.20 1.15 (pd) Gymnothorax prasinus 3.07 4.15 1.12 (cd) 2.25 3.84 0.99 2.93 4.16 1.08 (pd) Achoerodus viridis 2.58 3.49 1.14 (cd) 2.06 3.52 1.08 (cd) 1.14 1.62 0.61 Hypoplectrodes 2.33 3.15 1.00 (cd) 2.01 3.44 0.97 2.05 2.92 0.83 maccullochi Nemadactylus douglasii 1.74 2.36 0.88 2.20 3.77 1.01 (pd) 3.21 4.56 1.24 (pd) Parma microlepis 2.12 2.86 0.95 2.07 3.55 0.96 2.83 4.03 1.08 (pd) 2006 Parma microlepis 3.35 5.00 1.76 (cd) 0.91 1.73 0.60 3.00 4.27 1.81 (pd) Scorpis lineolata 3.27 4.89 1.32 (cd) 2.67 5.06 1.39 (pd) 2.74 3.90 1.04 (pd) Atypichthys strigatus 3.22 4.81 1.32 (cs) 2.29 4.33 1.29 (pd) 2.96 4.21 0.96 Pagrus auratus 3.15 4.70 1.29 (cd) 1.92 3.64 1.09 (cd) 2.55 3.62 1.21 (pd) Notolabrus gymnogenis 2.52 3.77 1.19 (cd) 1.48 2.80 0.89 2.15 3.05 1.11 (pd) Achoerodus viridis 2.51 3.74 1.24 (cd) 1.53 2.90 0.91 1.90 3.20 1.13 (pd) Gymnothorax prasinus 2.40 3.58 1.07 (cs) 1.75 3.31 1.03 (pd) 2.17 3.08 1.07 (cs) Hypoplectrodes 2.37 3.54 1.10 (cd) 1.84 3.48 1.05 (pd) 2.70 3.84 1.38 (pd) maccullochi Meuschenia flavolineata 2.31 3.45 0.95 1.87 3.54 1.09 (pd) 3.08 4.38 1.62 (pd) Meuschenia freycineti 1.62 2.41 0.75 1.95 3.68 1.18 (pd) 3.07 4.36 1.90 (pd) Nemadactylus douglasii 1.22 1.82 0.66 1.82 3.45 1.06 (pd) 2.14 3.05 1.09 (pd)

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video Discussion

With the use of baited remote underwater video (BRUV), this study demonstrated a

difference in H′ and species richness of temperate reef fish recorded at shallow (3 to 10

m) and deep reefs (17 to 33 m) in March of 2006. Additionally, a difference between the

composition of the fish assemblage between shallow and deep water reefs was detected in

2006. Several individual species contributed to the differences including: the schooling planktivore Scorpis lineolata, the scavenger Gymnothorax prasinus, two labrids including the protected species Achoerodus viridis, the commercially important Pagrus auratus, the territorial Parma microlepis, and the half-banded sea perch Hypoplectrodes maccullochi. With the exception of A. strigatus and G. prasinus, all species identified were more abundant at deep reef locations.

The mean species richness at the shallow locations in both 2005 and 2006 ranged between five and ten species, which is in agreement with the species richness recorded from BRUV surveys at three separate shallow reefs within Jervis Bay (see Chapter 2), and slightly greater than findings from a similar BRUV study on shallow temperate reefs within Australia which used a shorter sampling period of ten minutes (Watson et al.

2005). Mean species richness in the two deep habitats ranged between 9 and 16 over the course of the two sampling periods. There have been no other BRUV studies examining species richness on temperate reefs at similar depths to the deep water reefs examined here, but similar numbers have been reported with UVC on temperate reefs in 15 to 20 m

(Dufour et al. 1995).

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video

The relative abundance of fish (Total Max n) recorded in 2005 and 2006 was similar among habitats, however it was surprising to find that the smallest and largest values recorded in the two years of sampling were both at shallow coastal locations. These differences could be attributed to the use of Max n to examine multiple species comparisons. Indeed, Max n has been shown to be a useful measure of relative abundance when comparing a single species among locations (Willis & Babcock 2000), but this measure of relative abundance needs to be considered cautiously when examining multiple species because the schooling behaviour of individual species can largely influence these results. For example, 524 individuals of the schooling species

Atypichthys strigatus were recorded at coastal shallow water locations in 2006, compared to only 369 and 178 in deep patch and deep coastal locations respectively (see Appendix

2). Indeed, A. strigatus was determined by SIMPER to be a large contributor to the differences between the coastal shallow and coastal deep habitats. Similarly, I compared the time for the first species to arrive to the bait (t1st1), and did not detect any difference

between habitats. In Chapter 2, I also found that this variable indicated different patterns

of relative abundance than several other variables examined. Although proven effective

in indicating the relative abundance of some species, t1st1 may not be an accurate

measure of relative abundance for multiple species because it relies heavily upon the

chance location and the behavioural responses of the species in the immediate area of the

BRUV when deployed (Willis & Babcock 2000).

Differences in the composition and abundance of fish assemblages found between depths

are well documented in the literature (Bell 1983, Letourneur et al. 2003) in depth

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video gradients of less than 5 m (Dufour et al. 1995). The half-banded sea perch

(Hypoplectrodes maccullochi) was more abundant at the deep locations, which is in agreement with findings of Curley et al. (2002) who also reported that H. maccullochi increased in abundance with depth. Depth related differences are often attributed to species size and sex. Ontogenetic migration of reef fish is well documented as many undergo regular size related feeding migrations because of competition or prey availability (Helfman 1982, Warburton & Blaber 1992). For many fish species the trend is for larger fish to migrate to deeper water (Macpherson & Duarte 1991). Since the sex of a fish is often related to size (Allsop & West 2003), the size-depth trend may be indicative of sex distributions of reef fish along depth gradients. In several studies, species-specific distribution has been reported where the females inhabited shallower waters than their male counterparts (McCormick 1989, Denny 2005) In rarer cases, females have shown preference for deeper habitats such as the case with Bodianus unimaculatus (Denny 2005). Depth related differences in the composition of the fish assemblage emphasize the need for the Marine Park to incorporate habitats over the entire depth distribution which they occur. Otherwise, if a certain depth range is precluded from sanctuary protection, fishing pressure could potentially have negative affects on the gender structure of a population.

There was spatial variability in the fish assemblage among shallow coastal locations but not among locations at either of the deep water habitats. In 2005, the difference between the shallow locations was greatest and it appeared that the relative abundance, H′, and richness of fish were greater at Lobster Rock than Honeymoon Bay. SIMPER identified

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video two species as contributing to these differences, the schooling species Atypichthys strigatus and the labrid Ophthalmolepis lineolata, both of which were more abundant at

Lobster Rock. There are few obvious differences in these two habitats except for the embayment location of Honeymoon bay, which could potentially be a factor in the differences between the two locations. Lobster Rock is more exposed to ocean currents and potentially receives higher levels of nutrients in that of drift plankton. Indeed, A. strigatus is an opportunistic feeder, and primarily feeds upon plankton (Glasby &

Kingsford 1994).

I did not find differences in H′ or the relative abundance of fish when comparing the deep coastal and deep patch reefs. However, the deep patch reef is indeed an important habitat and deserves strong consideration from Marine Park managers for sanctuary protection because several species, including the protected blue groper Achoerodus viridis, were abundant in these locations. More importantly, over the course of the two sampling periods there were several species that were only recorded at the deep patch reef locations including: eastern blackspot pigfish Bodianus unimaculatus, eastern king wrasse Coris sandageri, velvet leatherjacket Meuschenia scaber, butterfly perch Caesioperca lepidoptera, and mosaic leatherjacket Eubalichthys mosaicus. Unfortunately, abundance of these individual species was too low to show meaningful patterns between coastal and patch reefs although other studies have shown that differences in the fish assemblage at coastal and patch reefs do exist (Shepherd et al. 2005). Therefore, if the goal of Marine

Park management is to protect a comprehensive and adequate representation of the fish

Chapter 3: A Comparison of Fish Assemblage on Coastal and Patch Reefs Using Baited Remote Underwater Video community and fish habitats then deep patch reef habitat should indeed be included with other habitats in the sanctuary zoning plan.

Overall these data indicate that depth and proximity to shore are important factors for

Marine Park authorities to take into consideration when considering which reef habitats should be included in the sanctuary zoning plan. The depth related differences in the reef fish community are well documented and the data clearly indicates that a difference in abundance and diversity of fish occurs in similar habitats at different depths. These differences are not as clear cut when comparing patch and coastal reefs. Nevertheless, the uniqueness of individual species found in these different habitats begs for attention.

Chapter 4: Discussion

I sought to fill a gap in the literature by testing different baits used to attract fish to baited remote underwater video (BRUV) stations. BRUV has been used in several studies to make spatial comparisons in fish abundance (Stobart et al. 2007, Harvey et al. in press), and are increasingly being used by researchers to survey reef fish assemblages in protected areas that require non-destructive, non-intrusive monitoring techniques

(Babcock et al. 1999, Willis & Babcock 2000, Westera et al. 2003, Willis et al. 2003).

Moreover, BRUV has provided a suitable alternative to the commonly used underwater visual census (UVC) survey technique because it can be used in areas that are beyond the depths of SCUBA no-decompression limits. The effectiveness of BRUV to sample fish populations primarily relies on fish attraction to bait, and it is well known that diet within a typical reef assemblage can vary substantially (Russell 1983). Surprisingly, not a single study appears to have examined the effectiveness of bait, so I tested the hypothesis that bait did not influence the species component or relative abundance of reef fish detected.

I then built on these methodological data to provide baseline information to the Jervis

Bay Marine Park. Specifically, I drew comparisons between the fish assemblages on deep patch, deep coastal, and shallow coastal reefs. The Marine Park management has a responsibility to conserve and protect a comprehensive and adequate representation of local habitats and their associated floral and faunal assemblages (ANZECC_TFMPA

1999). Indeed, the design and effectiveness of a marine protected area relies on sound monitoring programs (Allison et al. 1998). In particular, a main focus for marine parks is often the protection of reef fish because these species are often heavily targeted and

Chapter 4: Discussion therefore susceptible to anthropogenic disturbance. There have not been any fish surveys done on the deep reefs in the Marine Park and this habitat is currently not incorporated into the Marine Parks “no-take” sanctuary zoning plan, which comprises the highest level of protection and precludes fishing from these areas. Therefore, evidence was needed to determine if these habitats are ecologically unique, and should be included in the Marine

Park’s sanctuary zoning plan.

Main Findings

I examined three different baits - pilchard, abalone, and urchin - and recorded differences between the relative abundance of fish recorded when using BRUV in 2006. At most locations, pilchard and abalone were equally effective and attracted a similar number of species and relative abundance of fish. In contrast, fewer species and lower relative abundance of fish was detected using the urchin bait at most locations. The greatest differences detected between the baits were between pilchard and urchin bait, therefore suggesting pilchard bait was indeed the most effective bait for attracting a higher abundance and diversity of fish.

H′ was different among locations in the second year of sampling, particularly because greater values were recorded at Plantation Point. Additionally, differences in the time of first arrival varied between locations in 2006, with a considerable increase in times at

Plantation Point especially with the urchin bait. I speculated that two factors were influencing these results. First, the urchin bait had a watery consistency and its attractant properties were potentially not retained in the water column for as long as the other two

Chapter 4: Discussion baits, thereby reducing its ability as an attractant. Second, Plantation Point appears to have the highest density of fish, which meant that fish were attracted relatively rapidly even for a bait that diffused quickly. Therefore, the urchin bait was equally effective as the other two baits at this particular location. Nevertheless, as the behaviour and structure of the fish community can vary in space, it is important to use bait that provides researchers with consistent results. This point emphasises the advantage of using pilchard bait over urchin bait. Moreover, pilchard bait along with other bait fish have predominantly been used in BRUV studies which makes it the most convenient choice of bait for drawing comparisons within the literature.

I next examined differences in the fish assemblage between coastal shallow, coastal deep, and deep patch reefs. Once again, I conducted the experiment in two separate sampling periods as the response of fish may vary with time. Surprisingly, I did not detect any differences between the two deep habitats in either year, although several species were found exclusively in the deep patch habitat. Unfortunately, these species were rarely recorded which meant that meaningful patterns were not detected. Nevertheless, this finding emphasises the need for protection of the deep patch reef habitat because marine reserves function to protect biodiversity. I detected differences between the composition and abundance of fish at shallow and deep water habitats. Indeed, depth related differences for temperate reef fish are well documented (Dufour et al. 1995, Denny 2005) and my findings emphasise the need for Marine Park management to maintain protection of reef habitats within as broad of a range of depth that it occurs within the Park.

Chapter 4: Discussion

Implications of my findings

My findings clearly underscore the utility of pilchard bait in detecting differences in fish abundance in shallow coastal reefs. However, these findings need to be interpreted cautiously because as indicated the composition and abundance of fish detected on shallow coastal reefs using BRUV are different to those found on deep reefs. Therefore, the applicability of my bait findings beyond shallow coastal reefs remains unclear.

Unfortunately, there have not been any other studies comparing different baits with

BRUV, therefore making generalisations difficult. However, if the difference between the baits was in fact caused by an inability of the attractant plume of the urchin to remain in the water column, then undoubtedly this problem would continue to affect the number of fish sampled in most locations because it inevitably samples a smaller volume compared to the other baits.

Examining spatial patterns in nature is a key ecological issue for Marine Park management to better understand the processes governing them, which equips the managers with the tools to make informative decisions on the design and effectiveness of marine protected areas (Allison et al. 1998, Garcia-Charton et al. 2000). Undoubtedly, the goal for Marine Park management to conserve and protect marine biodiversity extends beyond the reach of the Jervis Bay Marine Park, as a network of marine parks has been established state-wide. The results from this study have been used to compare the abundance and distribution of reef fish on a scale of tens of kilometres around Jervis

Bay, as well as for drawing comparisons at the scale of hundreds of kilometres in a study that examined results from several BRUV studies within NSW Marine Parks (see

Chapter 4: Discussion

Appendix 3). However, the findings from the cross-study comparison need to be interpreted cautiously as inaccuracy in the estimates are potentially increased by the biases caused by differences in sampling methods (see Andrew & Mapstone 1987). To minimise these biases and maximise the ability to examine large scale spatial comparisons, researchers have started to apply identical sampling methods to draw comparisons on a global scale (Wahl et al. 2004). Similarly, to address large scale patterns of abundance and distribution of marine-life there is a need to standardise the sampling methodology by addressing the differences in the BRUV sampling techniques used by researchers and employing a single effective survey method.

Future Research

By testing the effectiveness of different baits, I have addressed one of the potential biases associated with BRUV. However, there are several issues that remain unclear and require investigating in an effort to standardise a technique that is gaining popularity amongst reef fish ecologists and becoming more prevalent in the literature. For example, does the amount of bait have any effect on the fish assemblage attracted to the BRUV?

Based on previous studies, there does not appear to be any conclusive answer, as the amounts used by researchers have varied between 200gm (Willis & Babcock 2000) and

1kg (Cappo et al. 2004). These are relatively small amounts, considering that some professional fishers using fish traps use several kilograms of pilchard bait at a time, and replace the bait every time the trap is lifted (J. Lindfield, pers. comm.).

Chapter 4: Discussion

Bait manipulation is another topic surrounding bait effectiveness. Some researchers have reported changing bait after every drop (Ellis & DeMartini 1995), yet it remains to be tested if the attractant properties of bait are lost after being submersed for 30 minutes.

One professional fisher that I spoke to reported that he “cooked” his pilchard bait in the sun to bring up the oils that eventually made up the bait plume. These different manners of treating bait could potentially increase the attractant qualities of the bait.

Fish accessibility to the bait is another potential bias that remains to be explored. Having viewed footage from other BRUV studies, it appears that when fish have some access to the bait in the bait canister their feeding activity becomes more aggressive and as a result some fish appear less reluctant to approach the bait canister. The activity around the bait can have either a positive or negative effect, by encouraging inquisitive fish to the area

(Cappo et al. 2004), or alternatively increasing competition for the bait and dissuading other fish from approaching (Armstrong et al. 1992).

Indeed, Marine Park management can improve their effectiveness to examine spatial comparisons at several scales by addressing many of the biases associated with the

BRUV sampling technique. Additionally, there is the potential to get more information from the BRUV sampling program, if there is funding to upgrade the current single video design to a stereo-video sampling design. As many studies have shown, increases in the size of fish are often a good indication of the success of marine protected areas (Dufour et al. 1995, Roberts 1995, Russ & Alcala 1996b, Edgar & Barrett 1999, Evans & Russ

2004), and size measurements can be very difficult when sampling with single cameral

Chapter 4: Discussion

BRUV. Indeed, single camera BRUV has been used to make size comparisons (Willis &

Anderson 2003, Cappo et al. 2004) although accurate measurements could only be made when the fish were swimming in precisely the same plane as a calibration scale, perpendicular to the camera, and immediately next to, or between, the scale grids. UVC is a potential alternative method to single camera BRUV, although UVC is restricted to shallow waters and, moreover, divers’ estimates can lack precision. Edgar et al. (2004) found estimates of fish length by UVC deviated in either direction as much as 30mm.

These inconsistencies can greatly reduce the statistical power of the sampling to detect differences in fish length (Harvey et al. 2001, Harvey et al. 2002). In answer to this,

Shortis and Harvey (1998) developed a stereo-video system which has been successfully put into practice and provides researchers with accurate fish size measures (Harvey et al.

2002). In fact, Harvey and associates (Harvey et al. 2001) have shown that length estimates obtained using stereo video were substantially more accurate than those obtained from UVC and single video.

Regardless of whether the current BRUV monitoring program within Jervis Bay continues to use a single video technique, or employs stereo-video, I strongly advocate the continuation of the BRUV monitoring program in and around the Marine Park, to examine the effectiveness of the Park at protecting fish biodiversity. Specifically, I recommend a program that continues to examine habitats that are within reach of the Park boundaries and are not incorporated in the Marine Park sanctuary zoning plan because as the results from this study have indicated, these habitats can potentially harbour fish species that are not found in currently protected habitats. In particular, BRUV should be

Chapter 4: Discussion used to survey fish in the deep water habitats, as these areas are typically under- represented in ecological surveys.

The BRUV technique is rapidly improving, and will benefit Jervis Bay Park in monitoring its effectiveness to protect and restore fish biodiversity in the area. This study has shown that the BRUV sampling technique can detect differences in the composition and relative abundance of fish among habitat types. These data can assist Marine Park management in making sound decisions on future zoning plans.

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Appendix

Appendix 1. Mean number of individuals surveyed at three locations in Jervis Bay Marine Park: Callala, Huskisson, and Plantation Point, in two years of sampling: 2005 (n=3), and 2006 (n=4). Individuals were recorded using baited remote underwater video, which was baited with either: abalone, pilchard, or urchin.

Family Scientific Names Abalone Pilchard Urchin Callala Huskisson Pl.Point Callala Huskisson Pl.Point Callala Huskisson Pl.Point ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 Aplodactylidae Aplodactylus lophodon 0.3 0.3 Carangidae Pseudocaranx dentex 0.25 5 9.0 Trachurus novaezelandiae 6.5 1.5 7.0 2.5 0.25 25 1.0 11.25 1.75 Chaetodontidae Chelmonops truncatus 0.7 0.3 Cheilodactylidae Cheilodactylus fuscus 0.25 0.25 0.25 0.25 Cheilodactylus vestitus 0.3 Nemadactylus douglasii 0.25 0.3 Dasyatidae Dasyatis brevicaudata 0.25 Dinolestidae Dinolestes lewini 3.3 7.5 1.7 0.5 0.75 0.7 Enoplosidae Enoplosus armatus 0.5 0.25 0.25 Gobidae Bathygobius krefftii 0.25 Heterodontidae Heterodontus 0.3 1.25 0.7 1.3 1.5 0.7 1.75 1.0 1.25 1.7 3.25 0.7 1 0.3 0.25 0.5 portusjacksoni Kyphosidae Kyphosus sydneyanus 1.0 Labridae Achoerodus viridis 0.3 0.25 0.25 0.25 0.25 0.7 0.25 Eupetrichthys angustipes 0.3 0.25 0.25 0.3 0.25 0.25 0.25 Notolabrus gymnogenis 0.3 0.25 0.3 0.5 0.5 0.3 0.25 0.7 0.75 0.5 0.7 0.5 Ophthalmolepis lineolata 1.3 1 0.7 0.75 3.3 2.25 1.3 2 0.3 0.25 2.3 2.5 1.3 0.5 1.3 1.5 Pictilabrus laticlavius 1.0 0.25 0.7 0.25 0.7 0.75 1.0 2 0.3 0.5 0.7 0.25 0.5 0.3 0.25 0.7 0.75 Suezichthys gracilis 0.3 0.25 Latridae Latris lineata 2.7 0.75 Monacanthidae Meuschenia flavolineata 0.25 0.25 Meuschenia freycineti 0.25 0.25 0.25 0.25 Meuschenia venusta 0.25 Nelusetta ayraudi 0.7 0.5 0.3 0.75 0.3 0.25 0.3 0.5 0.3 0.25 Monodactylidae Schuettea scalaripinnis 0.25 Mullidae Parupeneus spilurus 1.7 0.25 4.0

Appendix

Upeneichthys vlamingii 1.3 1.75 0.7 3 0.3 0.5 3.3 0.25 0.3 0.5 0.7 0.5 0.7 0.5 Myliobatidae Myliobatis australis 0.25 0.25 Odacidae Odax cyanomelas 0.25 0.25 0.3 Ostraciidae Anoplocapros inermis 0.25 0.25 Parascylliidae Parascyllium ferrugineum 0.25 0.25 0.7 0.25 Pinguipedidae Parapercis ramsayi 0.3 0.5 0.3 0.25 0.3 0.25 0.3 0.25 Platycephalidae Platycephalus 0.25 0.3 0.3 0.3 0.7 caeruleopunctatus Pomacentridae Parma microlepis 0.75 0.7 0.25 0.7 0.25 Rhinobatidae Aptychotrema rostrata 0.3 Trygonorrhina fasciata 0.3 0.25 1.7 1 1.3 0.5 0.7 0.25 0.3 0.25 Scorpididae Atypichthys strigatus 22.5 15.3 16.75 7.7 11.25 2.3 35.5 1.7 20.5 8.0 7.5 12 1.25 4.0 18.75 Scorpis lineolata 1.0 1.25 0.3 0.25 0.5 0.3 2.75 0.5 1.7 9 1.75 0.3 1.5 Serranidae Hypoplectrodes maccullochi 0.3 0.5 0.3 0.5 0.25 0.25 0.25 0.3 0.25 Hypoplectrodes nigroruber 0.25 Sparidae Acanthopagrus australis 0.25 1.0 Pagrus auratus 5.3 3.25 0.7 2.5 1.0 0.5 0.3 1 5.0 0.25 1.7 1 0.25 4.7 0.75 Squatinidae Squatina australis 0.3 Tetraodontidae Tetractenos hamiltoni 0.3 Torquigener 0.3 0.5 0.5 pleurogramma Tetrarogidae Centropogon australis 0.25 Urolophidae Trygonoptera testacea 0.25 0.3 0.5 0.25 0.7

Appendix

Appendix 2. Number of individuals recorded (n=8) in 2005 and 2006 on six temperate rocky reefs: Little Beecroft Peninsula (LBC), Long Nose Point (LN), Honeymoon Bay (HB), Lobster Rock (LR), Middle Ground (MG), and Sir John Young Banks (SJY), using baited remote underwater video. Two reefs were sampled in three habitats: coastal deep (CD), coastal shallow (CS), and patch deep (PD).

Family Scientific Names CD CS PD LBC LN HB LR MG SJY ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 ‘05 ‘06 Acanthuridae Prionurus microlepidotus 1 Aplodactylidae Aplodactylus lophodon 3 6 2 1 1 Aulopidae Hime purpurissatus 4 2 4 2 2 3 Berycidae Centroberyx affinis 2 Brachaeluridae Brachaelurus waddi 1 Carangidae Pseudocaranx dentex 12 1 3 1 31 55 5 1 1 Seriola lalandi 15 2 3 2 Trachurus novaezelandiae 5 195 7 9 91 32 34 112 6 1 Chaetodontidae Chelmonops truncatus 2 4 2 5 Cheilodactylidae Cheilodactylus fuscus 2 2 3 5 3 Nemadactylus douglasii 6 1 3 6 1 4 5 7 7 Dasatidae Dasyatis thetidis 2 Dasyatidae Dasyatis brevicaudata 1 2 1 2 4 Dinolestidae Dinolestes lewini 22 2 2 3 3 19 2 22 28 1 Enoplosidae Enoplosus armatus 1 3 2 4 2 2 2 3 Girellidae Girella zebra 1 Heterodontidae Heterodontus portusjacksoni 2 8 8 5 Kyphosidae Girella tricuspidata 6 1 10 Labridae Achoerodus viridis 6 5 5 5 1 3 4 1 6 Bodianus unimaculatus 2 4 Coris picta 1 1 2 1 Coris sandageri 1 1 Eupetrichthys angustipes 1 2 2 Notolabrus fucicola 1 1 1 Notolabrus gymnogenis 4 5 6 6 1 3 2 1 5 1 5 Notolabrus tetricus 1 1 Ophthalmolepis lineolata 20 32 17 36 12 17 20 22 8 20 25 23 Pictilabrus laticlavius 1 1 5 3 1 Suezichthys gracilis 1 Latrididae Latridopsis forsteri 1 Latris lineata 6 Monacanthidae Acanthaluteres vittiger 1 1 Eubalichthys bucephalus 2 1 4 2 3 4 3 Eubalichthys mosaicus 2 Meuschenia flavolineata 5 6 5 5 1 4 11 2 8 Meuschenia freycineti 2 4 3 2 2 6 5 10 Meuschenia scaber 2 2 Meuschenia trachylepsis 1 Meuschenia venusta 1 Nelusetta ayraudi 1 1 4 5 Scobinichthys granulatus 1 Moridae Lotella rhacina 1 2 3 1 3 1 3 Mullidae Parupeneus spilurus 2 3 2 1 1 4

Appendix

Upeneichthys lineatus 2 4 3 2 Upeneichthys vlamingii 6 6 1 3 2 2 1 Muraenidae Gymnothorax prasinus 10 6 10 2 3 3 6 12 11 8 5 4 Myliobatidae Myliobatis australis 3 1 Odacidae Odax cyanomelas 1 3 1 1 1 Orectolobidae Orectolobus maculatus 1 1 1 3 Ostraciidae Anoplocapros inermis 1 Pempherididae Pempheris affinis 2 Pempheris multiradiata 2 Pentacerotidae Pentaceropsis recurvirostris 1 Plesiopidae Paraplesiops bleekeri 1 Trachinops taeniatus 19 3 1 53 Pomacentridae Chromis hypsilepis 59 5 10 6 15 15 10 13 Mecaenichthys immaculatus 1 1 1 1 Parma microlepis 6 8 4 8 2 2 6 7 4 9 Parma unifasciata 1 10 Pomatomidae Pomatomus saltatrix 1 Rhinobatidae Aptychotrema rostrata 1 Trygonorrhina fasciata 2 1 4 1 5 1 Scorpaenidae Scorpaena cardinalis 3 1 4 3 1 2 1 2 4 Scorpididae Atypichthys strigatus 22 57 77 121 20 207 160 317 110 169 176 200 Scorpis aequipinnis 1 Scorpis lineolata 26 15 44 25 61 3 3 3 26 41 195 33 Serranidae Acanthistius ocellatus 2 3 2 2 1 4 Caesioperca lepidoptera 4 7 Hypoplectrodes annulatus 2 4 2 2 2 2 6 Hypoplectrodes maccullochi 6 7 5 6 6 7 1 10 Hypoplectrodes nigroruber 2 2 Siganidae Siganus nebulosus 3 Sparidae Acanthopagrus australis 1 1 1 10 5 Pagrus auratus 8 5 18 4 3 5 5 13 4 Squatinidae Squatina australis 1 Tetraodontidae Canthigaster callisterna 1 2 1 3 Torquigener pleurogramma 1 Tetrarogidae Centropogon australis 2 1 Trachichthyidae Trachichthys australis 2 10 Triglidae Lepidotrigla papilio 1 Urolophidae Trygonoptera testacea 2 3