The Effect of Parasite Infection on Clam (Austrovenus Stutchburyi) Growth Rate and Body Condition in an Environment Modified by Commercial Harvesting

The effect of parasite infection on clam (Austrovenus stutchburyi) growth rate and body condition in an environment modified by commercial harvesting

Sorrel O’Connell-Milne

A thesis submitted for the degree of Masters of Science (Marine Science) University of Otago Dunedin, New Zealand

May 2015

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Abstract Commercial fishing often reduces densities and changes the structure of target populations. Within these target populations, the transmission dynamics of parasites are usually strongly dependent on host densities. Because parasites have direct impacts on their host and also indirect effects on interspecific interactions and ecosystem function, harvest-induced reductions in host density can have wide repercussions.

The present research investigates the effect of commercial harvesting on echinostome parasite infection within the Otago clam fishery. Clams (Austrovenus stutchburyi) have been commercially harvested from Blueskin Bay since 1983, and since 2009, experimental harvesting has extended to beds within Otago Harbour. Parasite loads (numbers of echinostome metacercariae per clam) within areas of high fishing pressure were compared to adjacent unharvested areas to assess the effects of harvesting on parasite abundance in clams. At 14 sites within Blueskin Bay and Otago Harbour, a subset of shellfish of varying age and sizes were analysed for parasite load. Unparasitised juvenile clams were also collected and caged in situ over a winter and summer period to monitor spatial and temporal patterns of parasite infection. Finally, the effect of parasite load on the growth rate of clams was monitored both in situ and in a laboratory experiment, in which juvenile clams were infected with varying levels of parasite and mortality, body condition and foot length was quantified.

Overall, commercial harvesting resulted in a 36% increase in average parasite load compared to control areas. Although mortality was unaffected by parasite infection, high parasite loads were found to deleteriously affect the growth, body condition and foot length of clams. Therefore, harvesting has the potential to alter both the local transmission of echinostome parasites and their impact on individual hosts. Increased parasite load not only affects clam physiology, but can also cause behavioural changes resulting in broader impacts on the surrounding ecological community.

Harvesters may be able to reduce their influence on parasite infection levels in clam populations by harvesting less intensively, and allowing more time between harvests for clam biomass to regenerate. iv

Acknowledgements Firstly, I would like to extend a big thank you to Robert Poulin, Candida Savage, and Will Rayment my supervisors for their advice and support throughout the year. Thanks to Candida for her knowledge on the estuarine environment, scientific methods of data collection and statistics. Thanks to Robert for his wealth of knowledge on parasites, guiding me to think critically and always having his door open to questions and ideas. Thanks also to Will, for stepping in for the last few months at the crucial stages of statistical analysis and draft reading. Your help with both R and statistical design was much appreciated. These three surpassed all of my expectations; I could not have hoped for better mentors.

Thank you also to those staff in the marine, surveying, statistics, geography, and zoology departments for the positive chats and encouragement. In particular, thanks to Doug Mackie and Rueben Pooley for helping with experimental setup and algal cultures and listening to my many questions. Thank you Tim Jowett of the Statistics Department, for your help with GLMMs and ensuring my models fitted the data. Also, thank you to Julie Clark and Nicky McHugh for putting up with the stinky shellfish while they dried.

Thank you to the directors and staff at Southern Clams Ltd for the support both financial and in kind - especially Roger Belton, Tane Gray, Graham Granger, and last but not least Dave Redshaw who I can’t thank enough for being there every boat trip, no matter the time of day, weather, or workload.

Thank you to my friends and fellow students who made this year so enjoyable and especially those that got involved: Janice Heung, Fatima Jeorge, Chris Niebuhr, Jesse Watt, Fanny Maure, Mathieu Morin, Anne Besson, Steph DeHamel, Tom McTavish, Georgia Bell and Brenton Twist, thanks for the help with collecting clams, putting out cages and taking sediment samples no matter the mid-winter temperatures. Thank you Bryony Leek, Carolyn Barnes and especially Sitara Morgenster for your many hours of editing. Thank you also to Anya Studer and Tommy Leung, for guiding the collection of my parasite from the primary gastropod hosts. Finally yet importantly, a big thank you to my family and Angus Robertson for being ever-present and listening at each stage of my project, from editing drafts to inspiration and providing the encouragement to continue. v

Table of contents

Abstract ...... iii Acknowledgements: ...... iv Table of contents ...... v List of figures ...... vii List of tables ...... viii Chapter 1: Introduction ...... 1 1.1 General introduction ...... 2 1.2 General biology of Austrovenus stutchburyi ...... 3 1.3 Clam harvesting...... 4 1.4 Clam parasites ...... 5 1.5 The main issue ...... 8 1.6 Study location ...... 8 1.7 Objectives ...... 10 1.8 Overview ...... 10 2 Chapter 2: Spatial and temporal variation in parasitism of clams as a function of commercial harvesting ...... 12 2.1 Introduction ...... 13 2.1.1 Environmental variables influencing the clam Austrovenus stutchburyi ...... 14 2.1.2 Harvesting of the clam Austrovenus stutchburyi ...... 15 2.1.3 Effects of commercial clam harvesting...... 16 2.1.4 Echinostome parasites of the clam Austrovenus stutchburyi ...... 16 2.1.5 Objectives of Chapter Two ...... 17 2.2 Methods ...... 18 2.2.1 Pilot study: site selection and environmental characteristics ...... 18 2.2.2 Experimental caging: spatial and temporal variability ...... 22 2.2.3 Statistical analysis ...... 24 2.2.4 Snapshot sampling: spatial variability of parasites within a harvesting context .. 27 2.2.5 Statistical analysis ...... 28 2.3 Results ...... 30 2.3.1 Pilot study: site selection ...... 30 vi

2.3.2 Experimental caging: spatial and temporal variability ...... 33 2.3.3 Snapshot sampling: spatial variability of parasites within a harvesting context .... 37 2.4 Discussion ...... 41 2.4.1 Parasite accumulation rates (cage experiment) ...... 42 2.4.2 Snapshot sampling: spatial variability of parasites within a harvesting context .. 44 3 Chapter 3: Clam mortality, growth and body condition in response to parasite infection . 49 3.1 Introduction ...... 50 3.1.1 Objectives of Chapter Three ...... 51 3.2 Methods ...... 51 3.2.1 Maintenance of clams ...... 52 3.2.2 Experimental infection of clams with Curtuteria australis ...... 53 3.2.3 Assessing the effect of infection ...... 55 3.2.4 Clam body condition and parasite load indices ...... 55 3.3 Statistical analysis ...... 56 3.4 Results ...... 56 3.5 Discussion ...... 61 4 Chapter 4: Discussion ...... 65 4.1 Thesis findings ...... 66 4.2 Management significance ...... 68 4.3 Further study ...... 69 4.4 Conclusion ...... 71 References ...... 73 Appendix ...... 88

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List of figures

Figure 1.1 The echinostomes C. australis and Acanthoparyphium spp...... 6 Figure 1.2 The three-host life cycle of the echinostomes ...... 7 Figure 1.3 The three study locations within Otago ...... 9 Figure 2.1 Paired harvested and unharvested study sites ...... 19 Figure 2.2 Average elevation at fourteen sites over three locations ...... 31 Figure 2.3 Percentage of organic carbon in sediment at fourteen 32 Figure 2.4 Monthly average air and water temperatures 33 Figure 2.5 Average growth of clams within cages 34 Figure 2.6 Average parasite load for commercially harvested and unharvested areas 38 Figure 2.7 Average density of clams 38 Figure 2.8 Average biomass of clams 39 Figure 2.9 Average shell lengths of clams 40 Figure 3.1 The relationship between the shell growth and parasite load of clams 58

Figure 3.2 The relationship between the soft tissue dry weight without parasites (STDWep) and parasite load of clam 59 Figure 3.3 The relationship between the condition index (calculated excluding parasite mass) and parasite load of clams 59 Figure 3.4 Average foot length of clams 60 Figure 3.5 The relationship between the foot length and parasite load of clams 61 Figure A.1 Map indicating areas harvested by Southern Clams Ltd from 2011 – 2014 89 Figure A.2 Simulation-based model diagnostics plot for experimental caging model 90 Figure A.3 Simulation-based model diagnostics plot for density 91 Figure A.4 Simulation-based model diagnostics plot for biomass 92 Figure A.5 Simulation-based model diagnostics plot for snapshot field sampling 93

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List of tables

Table 2.1 Sampling tree for the caging experiment ...... 26 Table 2.2 Sampling tree for the snapshot sampling ...... 29 Table 2.3 Results of GLM investigating the (fixed) effects season caged, treatment, average parasite infection and site on clam growth...... 35 Table 2.4 ANOVA (Type III tests) of GLM investigating the (fixed) effects season caged, treatment, average parasite infection and site on clam growth...... 35 Table 2.5 Candidate models for metacercarial load in clams...... 36 Table 2.6 Results of the GLMM investigating significance of the (fixed) effects shell length and treatment on clam parasite infection...... 36 Table 2.7 Candidate models for metacercarial load in clams...... 37 Table 2.8 Results of the GLMM investigating significance of the (fixed) effect of sampling period on clam parasite infection...... 37 Table 2.9 Results of the GLMM investigating significance of the (fixed) effect of harvesting on clam density...... 39 Table 2.10 Results of the GLMM investigating significance of the (fixed) effect of harvesting on clam biomass...... 39 Table 2.11 Candidate models for metacercarial load in clams...... 41 Table 2.12 Results of the GLMM investigating significance of the (fixed) effects age, condition and treatment on clam parasite infection...... 41

Chapter 1: Introduction

General introduction 2

1.1 General introduction Fishing is one of the most pervasive anthropogenic activities in the oceans, with the most immediate effect of reducing the density of the target species (Jackson et al. 2001, Wood et al. 2010). The reduction in target species may have subsequent impacts on the individual as well as the surrounding ecosystem. However, as the density of the target species is reduced, the resultant effect on parasite abundance and prevalence is often overlooked. Over the past three decades, parasitic infections in commercially fished species have been declining (Lafferty 2008). Generally, wild fisheries target the larger members of the population. Removal of larger individuals results in a changing population structure and in extreme cases a reduction of individual’s mean size and size at maturity (Stergiou 2002). When the average size of individuals is reduced, parasite abundance may decline too, as large fish tend to carry more parasites than smaller fish (Arneberg 2002). Additionally, as stocks of high trophic level species are removed, the abundance of their prey increases (Scheffer et al. 2005). The increased abundance of species at lower trophic levels has associated risks of disease and parasite outbreak (Lafferty 2004).

Fluctuation in density of a fished stock changes the abundance and transmission efficiency of parasites (Arneberg et al. 1998, Lafferty 2012). Marine parasites have diverse responses to fishing, often determined by the life cycle of the parasite and their relationship with the fished host (Kuris & Lafferty 1992). The impact of fisheries on parasites may be both direct and indirect (Wood et al. 2010, Wood & Lafferty 2014). Reduced densities of target species due to fishing directly affects parasites, such as reducing the abundance of parasites in the target species due to decreased transmission events (Wood et al. 2010). However, reduced densities of hosts may also have a wide range of indirect effects on parasites, such as modifying routes of infection and changing rates of parasitism in non-target species (Wood et al. 2010). Subsequently, the deleterious effects on the surrounding community structure are often difficult to predict (Wood & Lafferty 2014). For example, when predators of sea urchins are fished, urchin abundance increases due to release from predation pressure, which in turn promotes outbreaks of bacterial epidemics (Lafferty 2004). Simultaneously, crab populations increase and feed on gastropods, the primary hosts for the parasites of the urchin, thus resulting in an urchin population with reduced parasite infections (Sonnenholzner et al. 2011).

In the current study, the New Zealand clam Austrovenus stutchburyi will be used as a model organism to investigate variations in parasitism as a function of commercial harvesting. This General introduction 3 clam is targeted by a commercial fishery within New Zealand. The host-parasite system involving A. stutchburyi and its echinostome parasites has been well studied (Allison 1979, Martorelli et al. 2006, Leung & Poulin 2007a, Leung 2008, Leung et al. 2009c, 2010). Within intertidal ecosystems, these echinostomes indirectly enhance biodiversity and productivity (Mouritsen & Poulin 2005, Wood et al. 2007). However, the effect of a harvest on echinostome parasite infection in A. stutchburyi is unknown.

1.2 General biology of Austrovenus stutchburyi The clam A. stutchburyi (Wood 1828), otherwise known as the New Zealand littleneck clam, cockle or tuangi, is a venerid bivalve indigenous to New Zealand waters (Morton 2004). They are typically found buried in the top 10 cm of sediment of estuarine sand flats (Larcombe 1971, Wildish 1984). As suspension-feeders, A. stutchburyi require fine, stable sand to facilitate digging and maintain their perpendicular position in the sediment (Powell 1979).

Austrovenus stutchburyi is a common constituent of soft-sediment estuarine ecosystems throughout New Zealand (Pridmore et al. 1990). This clam often accounts for most of the macrofaunal biomass in intertidal sand banks, with densities ranging from <40 to 4500 individuals per square metre (Stephenson & Chanley 1979, Ministry of Fisheries 2014). As A. stutchburyi is often present in high densities, it has been argued that it plays a role as a keystone species (Power et al. 1996). In any case, its role as an ecosystem engineer is indisputable (sensu Jones et al. 1997). The clam is an autogenic ecosystem engineer, as its shell often provides the only hard substrate for attachment of invertebrates within mud flat environments (Thomas et al. 1998). In addition, A. stutchburyi provides essential ecosystem services as a bioturbator, thus increasing the oxygenation of surface sediment. It also performs the biogeochemical functions of water clarification and biodeposition of nutrients to the sediment as pseudo-faeces (Newell 2004).

Recruitment of A. stutchburyi is highly variable both spatially and temporally (Irwin 2004, Kainamu 2010, Ministry of Fisheries 2014). The factors driving recruitment are not fully understood, however, increased settlement of juveniles has been observed at low shore sites in beds with high densities of adult clams (Blackwell 1984, Dobbinson et al. 1989). Clams have separate sexes, with a four month spawning period from January to April (Larcombe 1971, Stephenson & Chanley 1979). General introduction 4

Once A. stutchburyi settle out from the planktonic stage, juvenile clams can migrate up to 1.5m through the sediment between tidal cycles, to find a suitable habitat (Larcombe 1971). These juveniles are recruited to the spawning biomass when their shell length reaches between 18 to 20 mm (measured from the umbo to the shell edge) (Larcombe 1971).

Typically, A. stutchburyi grow to 30 – 50 mm in shell length (McKinnon 1996). Shell size is not necessarily an indicator of age, as growth rates of shell are not uniform (McKinnon 1996). There may be variation in growth rates between and within sites. The size–age relationship in clams is not straightforward, as growth reflects a combination of environmental factors, including temperature, salinity, food availability, and shore height (Dobbinson et al. 1989, Marsden & Adkins 2010).

1.3 Clam harvesting Within New Zealand, A. stutchburyi are a resource subject to customary, recreational, and commercial harvesting. These clams are culturally important and a taonga (treasure) species for Māori (Colenso 1880). Clams feature in the customary diet of Māori, and large historic shell middens found throughout New Zealand are indicative of the historical importance of this kaimoana (sea food) (Waselkov 1987). Contemporary customary and recreational harvest from wild stocks occurs in many communities. Austrovenus stutchburyi is also a commercially significant species, with products sold on both domestic and international markets. Commercial clam fisheries have been operating in New Zealand since the early 1980s. Presently, commercial harvesting occurs in Otago, Whangarei, Tasman Bay and Golden Bay (Williams et al. 2009).

Commercial harvesting in Otago has occurred since 1983 (Wildish 1984). The Dunedin based company Southern Clams Limited (SCL) is the only commercial harvester and distributor of Otago clams. Out of a total allowable commercial catch of 1,470 tonnes, SCL currently harvest 800 tonnes of shellfish a year, from Blueskin Bay and Otago Harbour. Biomass reports from 1984 to 2010 show that the total biomass of clams within Blueskin Bay has remained constant, despite intensive commercial harvesting (Wildish 1984, Jiang et al. 2011). This may be due to large, albeit sporadic recruitment events (Breen et al. 1999). However, a reduction in juvenile and medium sized clams has been observed in harvested areas (Wing et al. 2002, Stewart 2008a, Kainamu 2010). Commercial harvesting from Otago Harbour is experimental, with a General introduction 5 report on the effects of harvesting in the area set to be released in 2016 to determine the possibility of further harvesting (Stewart 2010). As the sole operator, there is no pressure on SCL from competitive fishing. Since 2003, SCL have used a systematic rotational harvest scheme (Belton 2012). Shellfish are harvested using a body dredge pulled through the top few centimetres of sediment. Although there is currently no legal shell-size limit for harvesting clams within New Zealand, the harvest technology used by SCL is selective and only removes clams with shell lengths greater than 27 mm (Stewart 2008a).

Harvesting affects shellfish stocks directly as it reduces clam density and changes the age structure of the population. In the Otago commercial clam fishery, the method of hand harvesting by SCL reduces the biomass of clam within a harvested area to approximately 30% of standing biomass (Irwin 2004).

The effects of commercial harvesting of clams on the ecosystem have been assessed for many aspects. There has been research into the impact of harvesting on the feeding patterns of birds, although studies within the Otago Harbour were not conclusive (Schmechel 2001, Onley 2010, 2013). The role of clam shells for carbon sequestration within Otago Harbour has been investigated, because harvesting removes many tonnes of calcareous material (Smith et al. 2010). The changes to sediment oxygenation, macroalgal cover and recolonization of non-clam infauna post-harvest have also been examined (Stewart 2010). On the sandflats, tracks left as the harvest crates are pulled through the sediment were found to be visually noticeable for up to two weeks, before gradually blending in again with other surface features (Irwin 2004). Besides the reduction in clam biomass, harvesting is reported to leave no obvious long term changes in community structure; infaunal animals appear to recover from the effects of harvesting within 30 to 40 days (Irwin 2004, Stewart 2013). However, when assessing the effects of commercial harvesting and changes to community structure, parasites had thus far been overlooked.

1.4 Clam parasites Clams may be host to many different parasites ranging from trematodes to copepods (Leung & Poulin 2007a, b, Leung et al. 2009c), which may reside either within or on A. stutchburyi’s shell. However, the current study will focus on echinostomes, a sub-group of trematodes, in particular the species Acanthoparyphium spp. and Curtuteria australis (Figure 1.1). General introduction 6

Acanthoparyphium spp. and C. australis are very closely related phylogenetically and are considered ecologically equivalent (Babirat et al. 2004). Both taxa contain cryptic species complexes with numerous genetically distinct but undescribed species (Leung et al. 2009b).

Figure 1.1 The echinostomes C. australis and Acanthoparyphium spp. (A) within the second intermediate host, the clam Austrovenus stutchburyi; (B) echinostomes encysted within the foot tissue of the clam; (C) singular metacercariae cyst (unidentified taxa) (C) (image courtesy of R. Poulin).

Trematodes usually have multiple-stage life cycles with gastropods as their first intermediate host (Poulin 2006). The echinostomes C. australis and Acanthoparyphium spp. have a three- stage life cycle and need to pass through three specific organisms before reaching maturity (Allison 1979). Adult echinostomes live in the small intestine of the oystercatcher (Haematopus ostralegus), where they release eggs which are expelled along with the host’s faeces. The miracidium (a free-swimming ciliated stage) leaves the egg and penetrates the gastropod primary intermediate host. Curtuteria australis infects the whelk (Cominella glandiformis) while Acanthoparyphium spp. infect the mud snail (Zeacumantus subcarinatus) (Allison 1979, Martorelli et al. 2006). Inside the gastropod, the echinostome forms redia (an asexually reproductive stage) within the gonadal tissue, essentially castrating the host and morphing the gonad into a parasitic ‘cercarial factory’. The echinostome emerges from the gastropod host as cercariae (the free-swimming infective larval stage). The cercariae larval stages of Acanthoparyphium spp. are approximately 280 µm long, while those of C. australis are larger, at 690 µm in size (Allison 1979).The clam (the second intermediate host) ingests the cercariae through its inhalant siphon as it filter feeds. Once within the clam, the cercariae bury into the clam’s foot and encyst as metacercariae (Allison 1979, Martorelli et al. 2006). Clams can accumulate several hundred to over a thousand metacercariae in some areas (Thomas & Poulin 1998). The survival time of metacercariae within their host is not well known, but General introduction 7 longevity of approximately one year has been documented for these species (K. Mouritsen, unpublished data) and for other species of trematode survivorship of between 14 to 18 months has been recorded (Erasmus 1958). Parasite infection in clams reduces the use of the clam’s foot, hindering it from burying into the sediment (Thomas & Poulin 1998, Jensen et al. 1999, Mouritsen 2002a). In this way, the parasite positively influences its transmission to the definitive host, the oystercatcher (Allison 1979). The life cycle of the echinostome is completed through predation of the clam by the oystercatcher, resulting in ingestion of the encysted metacercariae (Figure 1.2) (Allison 1979, Martorelli et al. 2006).

Figure 1.2 The three-host life cycle of the echinostomes Curtuteria australis and Acanthoparyphium spp.. The different life stages of the echinostomes are indicated in italics, and hosts are shown in the boxes. Arrows indicate the direction of parasite transmission.

Parasite infection within clams not only affects the target host but also has a wide range of effects on the surrounding environment (Poulin & Mouritsen 2006). Clams forced to live at the surface of the sediment due to high parasite numbers within their foot have cascading effects throughout the local environment. The shells of surfaced clams increase benthic surface heterogeneity, which in turn increases diversity and density of other species (Mouritsen & General introduction 8

Poulin 2005). The shells of surfaced clams also create drag as water flows over them, reducing bioturbation and mixing of water. This changes near-seabed hydrodynamics, altering sedimentation patterns and increasing the settlement of fine particles (Poulin & Mouritsen 2006).

Parasite load within individual clams is known to be highly variable even at small spatial scales. Variations in parasite load for this clam have been recorded within the same bed due to tidal height (Mouritsen et al. 2003). At high-shore sites, clams have a higher load of parasites per individual, while at low-shore sites, there is a higher overall density of parasites per square meter, even though there is a lighter load of parasites per individual (Poulin et al. 2000, Mouritsen et al. 2003). This variation in parasite load provides reason to suspect that a change in density due to harvesting may also have an effect on parasite infection within clams.

1.5 The main issue Although harvesting has been shown to have impacts on numbers of parasite infections in other fisheries (Wood et al. 2010, Wood & Lafferty 2014), little is known about the impact of the clam fishery on parasite loads. Although trematode parasites in clams were first reported in New Zealand in 1905 (Chilton 1905), no study has determined the effect of harvesting on the distribution and density of these parasites. In addition, the cost of these parasites for the clam fishery and their effect on the commercial quality of the shellfish remain unknown. For ecological and commercial reasons, it is necessary to understand this host-parasite relationship in the context of harvesting.

1.6 Study location The current study takes place within three discrete locations in Otago on the South East coast of the South Island; inner Otago Harbour, outer Otago Harbour and Blueskin Bay (Figure 1.3). The Otago Harbour and Blueskin Bay locations were selected for the current study as intensive commercial harvest of A. stutchburyi has taken place in these areas over the past three years. In addition, the harbour and inlet support the customary and recreational harvest of clams.

Blueskin Bay (45o73’S, 170o59’E) was selected as a study location as the population of the clam A. stutchburyi that resides within this inlet has been under commercial harvest pressure for approximately 30 years (Wildish 1984, Jiang et al. 2011). A large sand spit closes the General introduction 9 mouth of the bay to create a well-defined inlet of 5.84 km2 (Wing et al. 2002), with fresh water input from the Waitati River and Careys Creek. Blueskin Bay lies within the East Otago Taiāpure, therefore the recreational take of shellfish in the area is reduced to 50 clams per person per day rather than the standard 150 clams. A taiāpure (local fishery) is a customary management area which encourages community involvement and is underpinned by people’s responsibility to care for the environment with the goals of maintaining and enhancing local fisheries (Hepburn et al. 2010).

The Otago Harbour (45o50’S, 170o35’E) is a long (23 km), narrow (mean width = 2 km), and shallow (mean depth = 4.5 m) tidal inlet with a shipping channel dredged to 12 m along the northern bank (Single et al. 2010), covering 46 km2. Two study locations were chosen within Otago Harbour; the first in the inner harbour and the second in the outer harbour. These locations are roughly separated by Quarantine Island and Goat Island, as well as by rocky peninsulas protruding from the mainland towards the islands.

Figure 1.3 The three study locations in Otago: the inner Otago Harbour, the outer Otago Harbour and Blueskin Bay General introduction 10

1.7 Objectives My overall aim was to investigate the impact of a reduction in clam density due to commercial harvesting on echinostome parasite infection within the clam A. stutchburyi. My intention was to infer the effects of the parasite infections on the surrounding ecosystem by observing the effect of the parasites on the clam. In order to do so, two objectives were laid out.

Objective one was to investigate the spatial and temporal variability of parasites accumulation within the clam A. stutchburyi between unharvested areas and density-modified areas due to sustained intensive commercial harvesting. Field sampling would provide a ‘snapshot’ which detailed the spatial fluctuations of parasite infection, while a caging experiment over 8 months would provide information on temporal parasite infections. Parasite infection levels in clams from commercially harvested and unharvested areas were compared while accounting for potentially confounding factors, such as clam age and body condition. My hypothesis was that there would be more parasite infections over summer and that clams in harvested areas would have higher numbers of echinostome parasite infections due to a reduced density of hosts.

Objective two was to investigate the effect of echinostome parasites on the growth rate, foot length, mortality, and body condition of juvenile clams. The effect of parasitic infections could be observed by subjecting juvenile clams to treatments involving increasing numbers of parasites. My hypothesis was that with increasing numbers of parasite infections there would be a deleterious effect on the growth rate, foot length and body condition of the clam.

1.8 Overview The current study is presented as four chapters, consisting of a general introduction (the present chapter), two chapters dedicated to separate studies and a general discussion.

The first data chapter (Chapter Two) will examine variations in spatial and temporal parasite infection in commercially harvested and unharvested areas. A caging experiment was utilised to assess the current temporal and spatial variability in parasite infections within the local system. Complementary field sampling of the study sites allowed a snapshot of the system to observe the pattern of parasite infection in harvested and unharvested environments. This also allowed the relationship between parasite load and the age and body condition of clams to be quantified in both the harvested and unharvested environments. General introduction 11

The second data chapter (Chapter Three) focusses on the potential impact of parasites on the mortality, growth, foot length and body condition of juvenile clams. This was assessed by experimentally infecting juvenile shellfish with increasing loads of parasites.

Chapter Four integrates the results of the previous two chapters and provides a general discussion of the findings.

2 Chapter 2: Spatial and temporal variation in parasitism of clams as a function of commercial harvesting

Spatial and temporal variability of parasite infection in clams 13

2.1 Introduction Commercial harvesting is known to reduce the population density of target species (Ludwig et al. 1993, Botsford et al. 1997), while at the same time reducing the density of potential hosts for parasites (Wood et al. 2010) and allowing unfished competitors or prey populations to follow a compensatory increase (Myers et al. 2007). Population density can affect parasite transmission and thus the intensity of infection experienced by individual hosts (Arneberg et al. 1998). When parasites are directly transmitted within a species, the reduced density of hosts may lower the transmission frequency of those parasites (Wood et al. 2010). However, social interactions between hosts can allow for transmission to occur, and in some cases the parasite levels may persist (Wood & Lafferty 2014). Directly transmitted parasites are therefore more resilient to fishing pressure on their host (Johnson et al. 2011, Wood & Lafferty 2014). On the other hand, parasites with complex life cycles may be more sensitive to the effects of harvesting, as the reduction in density of a host may cause a ‘life cycle bottleneck’ reducing transmission efficiency among hosts (Wood et al. 2010). When the parasites’ definitive host is fished, the parasite load within the system may be reduced due to the parasites being unable to complete their full life cycle (Wood & Lafferty 2014). For parasites with complex life cycles, the indirect effects of fishing are often multifaceted, such as on the surrounding ecosystem and secondary hosts (Lafferty 2008). Changes in parasite infection within a host population may cause ecosystem shifts (Mouritsen & Poulin 2002, Kuris et al. 2008), affect the host directly, or indirectly change its behaviour, thereby altering transmission rates of the parasite to its next host (Lafferty 2004, 2008, Sonnenholzner et al. 2011).

The commercially harvested clam A. stutchburyi was used to test the impact of harvesting on parasite load in clams. Since the trematode parasites (family Echinostomatidae) within A. stutchburyi have complex life cycles involving three hosts, the number of parasite infections may be more likely to fluctuate. When clam density is reduced by harvesting, the average parasite load in clams is likely to change, especially if the abundance of the definitive host, the oystercatcher Haematopus ostralegus, is unaffected (Wood & Lafferty 2014). In the current study, spatial and temporal patterns of echinostome infection in clams were investigated in situ in both harvested and unharvested areas.

Spatial and temporal variability of parasite infection in clams 14

2.1.1 Environmental variables influencing the clam Austrovenus stutchburyi Since Wood described the clam A. stutchburyi in 1828, it has been a popular study organism in New Zealand. Researchers have investigated many aspects of its ecology, such as aging, growth variations in relation to density, its role in the carbonate budget and as a second intermediate host of echinostome parasites (Allison 1979, Dobbinson et al. 1989, McKinnon 1996, Smith et al. 2010). The clam A. stutchburyi often dominates the macrofaunal community in New Zealand estuaries; where shellfish beds may have >700 individuals per square metre as counted in inlets of Dunedin (McKinnon 1996), while in some estuaries as many as 3000 - 4500 individuals per square metre have been reported (Stephenson & Chanley 1979, Ministry of Fisheries 2014). However, the clams may also live at low densities, such as in Doubtful Sound, where <40 individuals per square metre are observed following changes in salinity (Macrellis 2001).

The availability of food is the principal constraint of productivity, driving the density, size and growth of A. stutchburyi (Larcombe 1971, Cameron 1997). Clams generally feed during the hour before and up to three to four hours after high-tide, depending on their elevation on the shore that affects their submersion time (Williams & Pilditch 1997). The time submerged is proportional to the clam’s filtration capacity and dictates the amount of filter feeding that can occur (Beentjes & Williams 1986); clams at low-shore sites can have almost double the time available to filter feed than those at high-shore locations (Larcombe 1971, Mouritsen et al. 2003). Due to the increased availability of food, larger individuals and higher densities of clams are found at low-shore sites compared to the higher shore sites. However, beyond a threshold density clams are subjected to intraspecific competition for food resources (Stephenson 1981, Blackwell 1984, Dobbinson et al. 1989), which results in the impediment of their growth (McKinnon 1996, Mouritsen et al. 2003).

In addition to the reduced time available for filter feeding, food availability is also affected by the position of A. stutchburyi within the shellfish bed, which affects their ability to access inflowing seston-rich seawater. With each tidal cycle, water laden with phytoplankton flows into inlets and harbours. As clams filter-feed, the water flowing over the clam bed is depleted of seston (Pawson 2004). This results in large, fast growing individuals forming high density shellfish beds adjacent to the channels and nearest the mouth of inlets. Further from the channels and mouth, A. stutchburyi have slower growth rates, reach a smaller maximum size and occur at progressively lower densities, as the water they filter has a lower concentration Spatial and temporal variability of parasite infection in clams 15 of seston, having been depleted by passing over clam beds (Larcombe 1971, Voice 1975, Stephenson 1981).

2.1.2 Harvesting of the clam Austrovenus stutchburyi Since the arrival of Māori in New Zealand, there has been a subsistence harvest of A. stutchburyi by (Waselkov 1987). Clams have continued to feature as kaimoana (sea food) in New Zealand with a combined recreational and customary harvest in Otago estimated at 20 tonnes per year (Ministry of Fisheries 2014). In the Otago region, an A. stutchburyi clam fishery, has been in operation by Southern Clams Ltd (SCL) since 1983 (Wildish 1984). Clams were initially commercially harvested from Papanui Inlet and Blueskin Bay. Since 2007, however, no harvest has been undertaken in Papanui Inlet (Jiang et al. 2011). Commercial harvesting currently occurs within Blueskin Bay and Otago Harbour.

In Blueskin Bay, the total A. stutchburyi biomass has remained relatively constant since the initial biomass survey in 1984 (Wildish 1984, Irwin 2004, Stewart 2008a, Kainamu 2010, Jiang et al. 2011). The most recent total biomass estimate (clams with shell length >2 mm) for Blueskin Bay was 13,892 tonnes (S.D. ± 587), of which 8008 tonnes (S.D. ± 288) was in commercial beds (Jiang et al. 2011). The relativly constant biomass of the harvested area, despite intensive harvesting, may be due to recruitment events. The most recent recruited biomass estimate for the entire Blueskin Bay was 11441 t, of which 6880 t was in commercial beds. Contrary to other reports, a biomass survey in 2002 considered the clam biomass in Blueskin Bay to have been declining by 50 tonnes a year ever since the initial biomass survey of 1984 (Wing et al. 2002). But since 2002, further stock assessments have estimated the biomass to be increasing and the 2002 prediction was reassessed (Jiang et al. 2011). The problem is that a measure of total biomass provides no information about the relative contribution of constituent size classes. When size classes of clams were considered, studies observed a decrease of juvenile (2 – 19 mm) and medium (20 – 35 mm) sized clams over time in Blueskin Bay (Wing et al. 2002, Stewart 2008a, Kainamu 2010).

It has been predicted that the largest and most productive beds of A. stutchburyi within the Otago region are found in Otago Harbour (Breen et al. 1999), with a total estimated shellfish biomass of 70,000 tonnes (Stewart 2010). Harvest of shellfish within Otago Harbour had been banned since the 1960s due to water quality issues, but these issues have since been Spatial and temporal variability of parasite infection in clams 16 resolved by adequate treatment of sewage and improved overflow systems (Stewart 2008b). A resource and habitat survey for Otago Harbour was finished in 2008 (Stewart 2008b). This led to the presentation of a special permit to SCL in 2009, allowing commercial harvest in certain areas of Otago Harbour to experimentally investigate the impact of harvesting on surrounding communities and habitat (Stewart 2009, 2010, 2013).

2.1.3 Effects of commercial clam harvesting The size-specific reduction of density caused by harvesting has some obvious impacts, such as changes in biomass, age structure and length frequency distributions of remaining clams (Irwin 2004). The effect of a harvest on the clam density of an area is determined by the intensity of the harvest. Areas completely stripped of clams may take many years to recover, with only 15% of original biomass restored after an 18 month period (Stephenson 1981). Within the Otago fishery, a hand dredge is used to manually harvest strips 60 cm wide by 2-3 m long, leaving behind shellfish below 27 mm. It is an intensive harvest leading to a reduction in biomass and density by 70% and 55% of the original stock respectively (Irwin 2004). The harvest team members work systematically side by side, but due to the need for ‘elbow room’ there is a gap between team members, leaving small areas unharvested (pers. comm. T. Grey). As migration is especially frequent on the edge of disturbances, the spatial distribution of the remaining shellfish becomes homogeneous again soon after the harvesting is over (Stephenson 1981, McDonald 1999). Although the reduction in the density of clams due to commercial harvesting has been assessed in previous theses (Irwin 1999, 2004, Kainamu 2010), the effect of this change in density on the number of parasite infections has not been addressed.

2.1.4 Echinostome parasites of the clam Austrovenus stutchburyi The echinostomes Acanthoparyphium spp. and Curtuteria australis parasitise the clam A. stutchburyi, an important fisheries target and ecosystem engineer (Martin & Adams 1961, Allison 1979). While in the clam, the echinostomes positively influence their transmission from the clam to their definitive host, the South Island pied oystercatcher (Allison 1979). Once a certain infection threshold has been crossed and the clam is subjected to a heavy parasite infestation, the encysted metacercariae (the juvenile parasite stage) reduce the clam’s ability to use its foot to bury into the sediment (Thomas & Poulin 1998, Jensen et al. 1999, Mouritsen 2002a). Individuals stranded at the surface have a seven-fold increase of Spatial and temporal variability of parasite infection in clams 17 succumbing to predation by birds (Thomas & Poulin 1998). However, it also puts the parasite at risk of not reaching the terminal host, because fish such as the spotty (Notolabrus celidotus) may crop the tip from the foot of the surfaced clam (Mouritsen & Poulin 2003c).

Assuming cercariae (the parasite’s infective stage) actively search for their host and are evenly spread within the intertidal zone due to tidal water movement, clams at low-shore sites (which are generally at a higher densities) may indirectly ‘compete’ for parasites, and clear the water of a finite number of cercariae (Mouritsen et al. 2003). On the other hand, parasites may not become depleted from the water column at high-shore sites, where clams are at lower densities (Dobbinson et al. 1989, Mouritsen et al. 2003). The idea of parasites becoming ‘diluted’ in areas with high clam density by spreading out the number of cercariae in the environment among more potential hosts has also been proposed by Leung & Poulin (2007).

Echinostome infection levels within the clam A. stutchburyi fluctuate on many scales, from nation-wide patterns of infection (Studer et al. 2013) to local variability within individual sand banks (Mouritsen et al. 2003). Otago Harbour in Dunedin is identified as having the highest abundance of metacercariae per clam within New Zealand (Studer et al. 2013). Within Otago Harbour, several sites are known for their high or low echinostome load, and large variations are found even among bays in close proximity (Thomas & Poulin 1998, Mouritsen 2002a, Babirat et al. 2004, Mouritsen & Poulin 2005, Leung 2008). However, little is known of the distribution of these echinostome cercariae within the water column. In addition, although laboratory studies observe an increased emergence of cercariae at 25oC (Allison 1979, Koprivnikar & Poulin 2009), no in situ experiments have ever been conducted on temporal emergence of cercariae. The occurrence of the echinostomes Acanthoparyphium spp. and C. australis throughout the year and the seasonality of emergence of these cercariae are unknown.

2.1.5 Objectives of Chapter Two Although the echinostome parasites Acanthoparyphium spp. and C. australis have been studied extensively, the distribution of these ecologically equivalent echinostomes has not been investigated in the context of an anthropogenically altered ecosystem. The current study brings together two areas of research, the effects of commercial harvesting on the density of Spatial and temporal variability of parasite infection in clams 18 target species and the effects of echinostome parasites on the bivalve host. The aim of the current chapter is to examine spatial and temporal variability of parasite accumulation within the clam A. stutchburyi in commercially harvested as well as unharvested areas, within three locations in Otago; inner Otago Harbour, outer Otago Harbour and Blueskin Bay. To achieve this, two complementary observational studies were conducted. Rates of parasite accumulation in each study site were assessed using unparasitised juveniles placed in cages in situ for eight months, allowing for measurement of spatial and temporal variation in parasite accumulation among sites. Placing cages in both harvested and unharvested areas, allowed for a test of the relationship - if any - between harvest pressure and parasite accumulation. The effect of parasite load on juvenile clam shell growth in situ was also observed. Complementary to the caging study, field sampling provided a ‘snapshot’ which detailed the spatial fluctuations of parasite loads. Samples of clams from sites within both the commercially harvested and unharvested areas throughout the three study locations were compared with each other to assess differences in parasite infection in the context of a harvest, alongside other factors such as clam shell size, age, and body condition.

As the studies described in the current chapter occurred in situ, it was necessary to account for variations in the surrounding environmental factors. The current chapter lists the selection criteria for study sites alongside a description of their environmental characteristics.

2.2 Methods

2.2.1 Pilot study: site selection and environmental characteristics Potential study sites were selected to ensure similar environmental conditions between paired harvested and unharvested areas. This allowed comparison between study sites and reduced the potential influence of confounding factors when assessing the effect of commercial harvesting. Candidate harvest sites were required to have had at least two commercial harvests within the last three years, and an available ‘control’ site in an adjacent unharvested area. Sites with two harvests were identified using harvest data recorded by SCL. Harvesting pressure in the harvest sites selected was deemed intensive (pers. comm. T. Grey), leading to the expectation of a reduction of 70% and 55% of original values, respectively of the biomass and density in those areas (Irwin 2004). Candidate control sites were located as closely as possible to the harvested sites, to ensure comparable environmental conditions, providing a Spatial and temporal variability of parasite infection in clams 19 minimum distance of 15 m as a buffer zone from a harvested area. The term ‘unharvested’ is used in regards to an area that has not been subjected to commercial harvesting. Recreational or customary harvesting may have taken place, however any take was assumed to negligible as the study sites were only accessible by boat.

To reduce the confounding effects of environmental gradients, potential study sites were also required to be at a similar elevation above sea level. It was therefore necessary to locate all suitable sites within 0.5 m of mean low water spring (MLWS) on the intertidal sand flats, as this ensured comparable emersion times. Similar periods of emersion were required because predation pressure, clam parasite load and growth rates vary with the clams’ position on the bed (Mouritsen et al. 2003). Additionally, larger individuals and higher densities of clams at these low positions on the bed have been hypothesised to cause intraspecific competition for parasites (Mouritsen et al. 2003). Consequently, at this tidal elevation the effect of a reduced density of clams, due to commercial harvesting, on parasite infection may be more pronounced.

To avoid unintentional subjectivity, locations of suitable sites were identified on a map and assigned a number. A random number generator was used to randomly selected fourteen treatment sites (each including a paired harvested and control area) from the suite of candidate locations in commercially harvested and unharvested areas, four sites in both the inner and outer Otago Harbour and six sites in Blueskin Bay (Figure 2.1). The harvest pressure for the selected sites may be viewed in the appendices (Figure A.1). Spatial and temporal variability of parasite infection in clams 20

14 in Blueskin 14 Blueskin in Bay

Harbour and 9

8 the in Otago outer

4 the in inner Otago 5 Harbour,

Figure 2.1 harvestedPaired and unharvestedstudy sites 1 Spatial and temporal variability of parasite infection in clams 21

On selection of the sites, their elevation on the sand bank was recorded using a Trimble GPS. A theoretical submergence rate was calculated from tidal predictions in the N.Z. Tidal Almanac. Sites had no more than a three-hour air exposure period during each low tide, to ensure clams had a similar period under water to feed and acquire parasites through the inhalant current. Sediment samples were taken to assess substrate homogeneity among sites. For this purpose, three sediment samples were taken from within 5 m of each site using a 50 ml syringe corer to a depth of 5 cm (Fredensborg et al. 2005). All plastic ware was acid washed prior to sampling. Corers were rinsed between sampling in de-ionised water.

To characterise the sediment characteristics of each site, grain size and organic carbon were analysed for each sample. Percentage of organic carbon was determined using a loss on ignition method (Mook & Hoskin 1982). Samples were pre-treated with hydrochloric acid (HCl) to remove shell fragments (Ryba & Burgess 2002). Sediment was dried for 12 hours at 105oC and ashed for four hours at 550oC, weighing after each process to the nearest 0.001g. The percentage of organic carbon in each sample was derived from its organic carbon content using the Van Bemmelen factor of 1.724, which assumes matter contains approximately 58% carbon (Van Bemmelen 1890).

Sediment grain size was measured with a laser diffraction particle size analyser (Malvern Mastersizer 2000). Samples were washed twice with milli-Q water to remove salt. Between each wash, the samples were centrifuged at 1000 rpm for 10 minutes to ensure all sediment was retained when the water was poured out of the test tube. Samples were prepared for analysis using 10% hydrogen peroxide to remove organic matter and Calgon, to disperse the sediment particles (Singer et al. 1988). Grain size was used as an indicator of current flow, as finer particles settle in areas with slower water movement. Previous studies in Blueskin Bay found no significant variation of sediment size across the estuary, with almost 99% of sediment made up of 125 – 250 µm grains (Irwin 2004). Previous studies in Otago Harbour observed sediment to be generally made up of fine sand, with a significant proportion within a 63 – 250 µm range of grain sizes (Stewart 2013). Harbour sediments have low concentrations of heavy metals, despite the coastline being highly modified from port and city developments and land reclamation projects (Purdie & Smith 1994).

Harbour and Blueskin Bay water temperatures as well as air temperatures were recorded from May to December 2014. A salinity buoy was deployed by SCL in a central channel of the Spatial and temporal variability of parasite infection in clams 22

Blueskin Bay estuary; it used an electrical conductivity sensor (model EC350) to recorded water temperatures every 15 minutes. Otago Harbour air and water temperatures were recorded from the Portobello Marine Laboratory at five-minute intervals with Davis Instruments stainless steel temperature probes (model 7818).

Variations in site elevation, organic matter and grain size data, between harvest and control sites as well as between the three study locations (the inner Otago Harbour, outer Otago Harbour and Blueskin Bay), were analysed using one-way analysis of variance (ANOVA). Tukey’s post-hoc test was used for pair-wise comparisons of mean values between the study locations to determine where differences lay (Zar 1999). Significance was set at the 5% confidence level (α = 0.05). All statistical analyses were carried out using the software package R 3.1.2 (R Development Core Team 2014).

2.2.2 Experimental caging: spatial and temporal variability In preparation for the caging experiment, 3,450 juvenile clams with an average length of 12.8 mm (S.D. = 2 mm) were collected by hand from a sand bank on the south side of Quarantine Island in Otago Harbour and transported in a cooler to Portobello Marine Laboratory. As the number of pre-existing echinostome metacercariae affect the establishment success of new metacercariae (Leung et al. 2010), juvenile clams were used here as they have high growth rates and harbour low numbers of metacercariae (McKinnon 1996). The time out of water during transport was not appreciably longer than what would have been experienced naturally with the low tide, and within four hours of collection, clams were back in seawater. Clams were maintained in the laboratory in running sand-filtered seawater, at the same temperature as that of Otago Harbour water, with 1cm of sand to allow burying.

Of the juvenile clams collected, a subsample of 70 were dissected and their parasite load assessed in order to establish the baseline parasite load of the cohort. The foot of each clam was removed, by cutting along the narrow bridge between the gonad and foot base, as described in Leung & Poulin (2011), then mounted on a glass slide and flattened beneath a cover slip (Leung et al. 2010). The foot was flattened until transparent in order to make visible the encysted metacercariae within the foot to make it possible to count them under a dissection microscope. When counting encysted metacercariae, no distinction was made between the two different echinostome taxa, C. australis and Acanthoparyphium spp.. This Spatial and temporal variability of parasite infection in clams 23 was because molecular markers are required to be able to distinguish between the two taxa, and it was not deemed to be necessary as they play similar roles within the clam (Babirat et al. 2004). Hereafter, the term ‘echinostomes’ is used to refer to both of these parasite species collectively.

The juvenile clams were individually selected at random to create 84 groups of 30 shellfish. The length of each clam shell was measured, from umbo to shell edge, using digital callipers to the nearest 0.1 mm. To determine the cage within which each group would be set out, they were allocated a cage identification code, as described further below.

The remaining 840 clams were maintained in running sand-filtered seawater, at the same temperature as that of Otago Harbour water, with 1cm of sand to allow burying. Clams were fed 2 L of mixed algae feed daily, made up of equal quantities of the phytoplankton Isochrysis galbana, Tetraselmis chui, Skeletonema costatum and Pavlova lutheri. They were held in the laboratory for the following four months until they were needed, in August. Prior to set out in the cages, the clams were marked with red acrylic nail polish paint for identification.

Three circular cages (18 cm diameter, 15 cm height) made of plastic-mesh (7 mm mesh diameter) were placed a metre apart parallel to the water line, on the 22nd and 23rd of April 2014, at each of the 14 study sites (Figure 2.1). Cages were buried 10 cm into the sediment using a trowel. Displaced sediment was sieved and added back into the cages. The cages received an identification code made up of their site number, the treatment (H for unharvested or C for control), and the cage replicate number (1, 2 or 3). For instance, cage 1H2 was at site 1 in a harvest (treatment) area and is the second replicate cage. Next, each group of 30 juvenile clams were placed in their respective cage, with the posterior end of each clam pushed into the sediment to facilitate burrowing. After two weeks, the cages were checked to ensure that they were free from macrofaunal cover and stably situated on the bank.

Four months later, on the 19th of August, 10 clams were recovered from each cage. At this time, eight of the 84 cages were missing: 1H2, 2H1, 2H2, 2H3, 3H2, 6H2, 7C2 and 10H3. The cause of their disappearance is unknown. As clams were removed, ten additional juvenile clams were added to each cage to maintain a density of approximately 30 clams per cage. As Spatial and temporal variability of parasite infection in clams 24 these clams were from the same original cohort, and had been held in the laboratory in water free of parasite cercariae over the prior four-month period, it was assumed they had the same baseline infection intensity.

Another four months later, on the 18th of December, all clams were recovered from the remaining cages. At this time, eight additional cages were missing: 7H2, 7H3, 9C1, 9C2, 9C3, 9H3, 10C3, and 10H1. Clam mortality within each remaining cage was quantified. All clams collected were frozen at -18oC. The length of each clam shell was measured, from umbo to shell edge, using digital callipers to the nearest 0.1 mm. Clam growth at cage level was assessed using the following equation:

푮 = 푳풇 − 푳풊 where average growth rate of caged clams (G) is a function of the difference between the average length of clams per cage at the beginning of the caging period (Li) and the average length of clams per cage at the end of the caging period (Lf). The clam foot was dissected and parasites counted as described above. The accumulation rate of metacercariae for this period was ascertained using the following equation:

풂 − 풃 푴 = 풕 where the accumulation rate of metacercariae (M) corresponds to the average number of new metacercariae per clam (a), minus the number of baseline parasites (b), divided by the number of days during which the clams were caged (t).

2.2.3 Statistical analysis All statistical analyses were carried out using the software package R 3.1.2 (R Development Core Team 2014). A general linear model (GLM), with a Gaussian error structure and ‘identity’ link function, was used to determine how the shell growth of clams was affected by the fixed effects site, sampling period, treatment and parasite load. As mortality was low and the time of death over the caged period could not be established, mortality was not Spatial and temporal variability of parasite infection in clams 25 incorporated into the analyses. All data were inspected for violation of normality and equal variance. A type three ANOVA was run on significant variables.

A generalised linear mixed effects model (GLMM) using package lme4 (Bates et al. 2014) was used to assess the relationship between the response variable, parasite load, and the fixed factor predictor variables treatment, clam shell length, and sampling period. Treatment, shell length, and sampling period were chosen as environmentally important factors. However, as the sampling period was found to correlate with clam’s shell length, two sets of models were assessed. The first set included the predictor variables clam shell length and treatment. The second set included sampling period and treatment as predictor variables. Treatment indicates the harvesting pressure the clams have experienced by being in either a harvested or unharvested area. Shell length was also chosen as a factor, as it provides a measure of the clam’s body size. Finally, the sampling period was used in the model to indicate the season and length of time the clam had been in the field, as some clams had been out over a winter or summer season for four months or out over both seasons for an eight month period. As the shell length of clams was a continuous variable, it was scaled using a z-score (standardized score). Converting to a z-score resulted in the creation of a standardized score in order for the mean of the continuous data to be 0 and the standard deviation 1. Z-scores were created using the ‘scale()’ function, which effectively subtracts the mean of all data points from each individual data point, then divides each value by the standard deviation of all points.

In the model, the study location, site and cage were treated as nested random effects, due to the strong nested structure of this experimental design. Multiple replicate cages were nested within replicate sites, which were randomly positioned on sand banks within three locations: Blueskin Bay, the inner Otago Harbour, and outer Otago Harbour (Table 2.1).

Spatial and temporal variability of parasite infection in clams 26

Table 2.1 sampling tree for the caging experiment, example for one site. The same sampling scheme was repeated for each of the 14 sites across three locations: the inner Otago Harbour, outer Otago Harbour and Blueskin Bay. The sampling periods indicate when the clams were put into and removed from the cages (T1: ten clams were caged over a four month period in winter, T2: 20 clams were caged for 8 month over winter and summer, and T3: ten clams were caged over a four month period in summer. Location Site Treatment Cage Sampling period April August December Inner Harbour 1 Control Cage 1 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out Cage 2 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out Cage 3 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out Harvest Cage 1 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out Cage 2 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out Cage 3 T1 Clams in Clams out T2 Clams in Clams out T3 Clams in Clams out

Due to the overdispersed nature of this count data, the model was considered with both Poisson as well as with negative binomial error structures. Simulation-based model diagnostics were used to compare the predicted outcomes based on the model to the raw data to determine whether the models’ error structure fitted the distribution of the data (Pan & Lin 2005). These diagnostics indicated that negative binomial with a ‘logit’ link function was the best error structure to model the data (Figure A.2).

Spatial and temporal variability of parasite infection in clams 27

The models were constructed for comparison using a manual backwards stepwise selection process. Akaike’s Information Criterion with a correction for finite sample sizes (AICc) was used to identify the best model of those tested. The model with the lowest AICc value had the best compromise between fit and complexity. A model difference of two AICc points was necessary to define the best model (Anderson & Burnham 2002).

For the best fitting model, the estimate value given for z-score scaled fixed factors were unscaled, by dividing the estimate value by the standard deviation of the fixed factor. The exponential of the estimated change was taken to find the multiplicative value of each factor (McCullagh & Nelder 1989). Following this, a one-unit increase of the fixed factor resulted in an increase in response variable (i.e. parasite load) equal to that of the multiplicative value.

2.2.4 Snapshot sampling: spatial variability of parasites within a harvesting context At each study site in the first week of November, four 0.25 m2 quadrats were randomly sampled along a 10 m transect, parallel to the water line at MLWS. Each quadrat was excavated to a depth of 0.1 m using a trowel. Sediment was washed through a 2 mm mesh sieve to retain shellfish. The retained clams were placed in a sealed plastic bag, labelled with the quadrat reference number and transported in a cooler to the laboratory. Clams were held for 24 hours in running seawater to allow them to clear any sediment from their digestive tract. They were then washed clean of exogenous material, dried with a paper towel to remove excess water and weighed to the nearest 0.1 g using a digital balance. Clam density was quantified by counting clams within each sample. Subsamples of clams from each quadrat were taken by lining up clams from largest to smallest in rows of 10 – 20, depending on sample size, and by randomly selecting a clam from each row until a subsample of 20 clams was reached. If a sample had fewer than 20 clams, the sample was used in its entirety.

For each subsample, clam length, from umbo to shell edge, was measured using digital callipers to the nearest 0.1 mm. However, shell length and the age of clams are not necessarily correlated (McKinnon 1996). Therefore, clams were aged by counting the number of growth interruption lines, seen as dark rings on the shell, predicted to occur during periods of reduced growth through winter (Coutts 1974, McKinnon 1996). Ages were recorded as categories of year groups, from age one to age seven. Clams eight years old and over were combined into one age group, as ageing clams older than this using visual methods is difficult Spatial and temporal variability of parasite infection in clams 28 due to shell erosion. It is unclear whether the number of interruption lines identified are specifically equal to the number of years (McKinnon 1996). However, the number of lines have been found to correlate strongly with age, and hence are useful in the present comparative context (Mouritsen 2002a). Parasite load was assessed as described in the pilot study above. The soft tissue of the clam was removed from the shell and, along with the foot, oven-dried at 60oC for 24 hours and weighed to the nearest 0.001 g to determine the soft- tissue dry-weight (STDW).

Clam body condition was calculated using a residual index (Jakob et al. 1996). Clam body mass (STDW) was regressed on clam shell length after the data were transformed to reciprocals to meet the assumptions of regression. The residual distances of individual points from this regression line then served as an indicator of whether the individuals’ body condition was above or below that predicted for its length (Cone 1989). The body condition of clams was not compared between treatments, as there may have been confounding effects from the availability of food and any effect of parasite load on the clam.

2.2.5 Statistical analysis All statistical analyses were carried out using the software package R 3.1.2 (R Development Core Team 2014). A GLMM using the lme4 (Bates et al. 2014) package with a Gaussian family and ‘identity’ link function was used to assess differences in clam density and biomass for the fixed factor treatment. Site was treated as a random effect. Simulation-based model diagnostics were used to compare the predicted outcomes based on the model to the raw data for density (Figure A.3) and biomass (Figure A.4) of clams. This was done to observe whether the models’ error structure fitted the distribution of the data (Pan & Lin 2005).

A GLMM using the lme4 (Bates et al. 2014) package was also used to assess the relationship between parasite load and the fixed factors treatment, body condition, shell length, STDW and age. As clam STDW, shell length and age were strongly correlated (r2 ≥ 0.64), they could not be included together in the model. As shell length is determined by the growth rate of the clam, which may be slowed by various factors, causing shells to grow wider rather than longer with the resultant shell becoming more spherical (McKinnon 1996), this variable was deemed to be a less reliable measure (McKinnon 1996). Clam STDW may also be subject to variability, as it fluctuates with food availability and the presence of reproductive tissue Spatial and temporal variability of parasite infection in clams 29

(Coughlan & Ansell 1964, Walne 1972). Therefore, age was included in the model as an environmentally important measure of the clam’s time within the environment. Treatment and clam’s body condition were also chosen as environmentally important factors. The treatment indicated the harvesting pressure the clams experienced in a harvested area or lack thereof in an unharvested area, whereas body condition gave an indication of the clam’s health. As the body condition of clams was a continuous variable, it was rescaled to create a z-score. Z-scores were created using the ‘scale()’ function, which effectively subtracted the mean of all data points from each individual data point, then divided each value by the standard deviation of all points.

The study location, site and sample quadrat were treated as nested random effects in the model, due to the strong nested structure of this experimental design. Multiple sample quadrats were nested within replicate sites, which were randomly positioned on sand banks within three locations: the inner Otago Harbour, outer Otago Harbour and Blueskin Bay (Table 2.2).

Table 2.2 Sampling tree for the snapshot sampling, example for one site. The same sampling scheme was repeated for each of the 14 sites across three locations: the inner Otago Harbour, outer Otago Harbour and Blueskin Bay. Location Site Treatment Quadrat Inner Harbour 1 Control 1 2 3 4 Harvest 1 2 3 4

Due to the zero-inflation of the overdispersed count data, the model was considered with both negative binomial and Poisson error structures. Simulation-based model diagnostics were used to compare the predicted outcomes based on the model to the raw data, for the purpose of observing whether the models’ error structure fitted the distribution of the data (Pan & Lin Spatial and temporal variability of parasite infection in clams 30

2005). Negative binomial with a ‘logit’ link function was determined to be the best error structure to model the data (Figure A.5). The models were constructed for comparison using a manual backwards stepwise selection process. Akaike’s Information Criterion with a correction for finite sample sizes (AICc) was used to identify the model of best fit as described previously. For the best fitting model, the estimate value given for z-score scaled fixed factors were unscaled, by dividing the estimate value by the standard deviation of the fixed factor. The exponential of the estimate was taken to find the multiplicative value of each factor. Following this, a one-unit increase of the fixed factor resulted in an increase in the response variable (parasite load) equal to that of the multiplicative value.

2.3 Results

2.3.1 Pilot study: site selection All sites were within 0.5 m of MLWS (-0.99 m from mean sea level) in an area with a 2.1 m tidal range. There was no statistically significant difference in shore elevation between harvest and control treatment areas (One-way ANOVA F 1, 82 = 1.61; p = 0.21). However, there was a statistically significant difference between the elevation of sites at Blueskin Bay and those in the outer Otago Harbour (Figure 2.2; One-way ANOVA F 2, 81 = 11.5; p < 0.01). Spatial and temporal variability of parasite infection in clams 31

0.5 Inner Harbour

0.4 Outer Harbour

0.3 Blueskin Bay

0.2

0.1

-0.1 Elevation from MLWS (m) (m) MLWS Elevationfrom -0.2

-0.3 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site Number

Figure 2.2 Average elevation at fourteen sites: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent ±1 standard error. N = 6 measurements per site.

Different sites did not have homogeneous organic content. Although there were no significant differences between harvested and unharvested areas (One-way ANOVA F 1, 82 = 0.98; p = 0.33), organic content of the sediment varied between locations with significantly higher carbon levels in Blueskin Bay compared to those in the inner Otago Harbour (Figure 2.3;

One-way ANOVA F 2, 81 = 6.938; p < 0.001). Within the Blueskin Bay Inlet, the highest organic carbon values occurred close to the river inputs, and lowest values near the estuary mouth. Conversely, in Otago Harbour organic matter increased towards the harbour mouth.

Spatial and temporal variability of parasite infection in clams 32

3.50 Inner Harbour 3.00 Outer Harbour

Blueskin Bay 2.50

2.00

1.50 % Organic Carbon Organic % 1.00

0.50

0.00 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site

Figure 2.3 Percentage of organic carbon in sediment at fourteen sites: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent ±1 standard error. N = 6 samples per site.

Sediment grain size was homogeneous, with no significant variation between sample sites. Across sites, sediment was predominantly made up of 100% sand (62.5 – 1000 µm). A slight departure from this trend was observed in Blueskin Bay; at two sites near the edge of the estuary, the sediment consisted of 4% clay (2 – 60 µm) while one of these sites also had 0.13% silt (0.1 – 1.9 µm).

The average water temperature was greater in summer (~14.5°C) than in winter (~8.5oC). However, Blueskin Bay stayed an average 2oC warmer than Otago Harbour from the start of the survey period through to July. In August and September, this difference dropped to only 0.6oC and 0.1oC respectively. Otago Harbour then became 1oC warmer than Blueskin Bay for the remainder of the survey period (Figure 2.4).

Spatial and temporal variability of parasite infection in clams 33

o 10

6 Harbour Water

Temperature ( Temperature Blueskin Bay Water 4 Air 2

July

May

June

August

October

December November November September Figure 2.4 Monthly average air and water temperatures observed in Otago Harbour and Blueskin Bay from May to December 2014. Error bars represent ±1 standard error.

2.3.2 Experimental caging: spatial and temporal variability Juvenile clams that were collected for the laboratory experiment harboured very few parasites, with a baseline of 0.26 metacercariae per clam and 19% prevalence (percentage of infected individuals). Clam mortality over the 8-month cage period was low, with an average of 3.8 (S.D. = 4.6) deaths per cage.

Juvenile clam parasite load was very similar at the end of the four month period over winter and summer. During winter, the average parasite load had increased to 0.7 metacercariae per clam and 46% prevalence. During summer, the average parasite load had increased to 0.62 metacercariae per clam and 43.3% prevalence. For clams caged for the eight months spanning the winter and summer periods, the average parasite load increased to 1.04 metacercariae per clam and 54% prevalence.

The GLM indicated that clam shell growth had a seasonal increase, with differences between harvested and unharvested areas and among individual sites (Figure 2.5; Table 2.3). The Spatial and temporal variability of parasite infection in clams 34 average shell growth observed for clams caged for four months over winter (2.8 mm) was significantly lower than that of clams caged for four months over summer (4.2 mm) (Table

2.4; One-way ANOVA F 2, 78 = 128.5; p < 0.001). The average shell growth of clams caged for the full eight month period (7 mm) was no different to the growth of clams caged over the four month winter and summer periods combined. The shell growth of clams was significantly higher in harvested areas, with 45% greater growth on average than the growth in unharvested control areas (One-way ANOVA F 1, 78 = 7.6; p = 0.006). Shell growth also varied among sites (One-way ANOVA F 1, 78 = 8.4; p < 0.001). The parasite load of caged clams did not appear to affect shell growth in situ (p = 0.9).

Summer 6 Winter

3 Growth (mm) Growth 2

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Sites

Figure 2.5 Average shell growth of clams within cages over summer and winter at fourteen sites: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars ±1 standard error. N = 6 measurements per site. Spatial and temporal variability of parasite infection in clams 35

Table 2.3 Results of GLM investigating the (fixed) effects season caged, treatment, average parasite infection and site on clam growth. The multiplicative value for season caged is referenced to a winter period, that for treatment is referenced against a control treatment and each site is referenced to site 1. Fixed effects Estimate Multiplicative value Std. Error t-value Pr (>|t|) (Intercept) 2.414152 11.18029 0.30503 7.914 9.2 e-13 Season caged 1.545135 4.688605 0.136312 11.335 < 2e-16 Treatment 0.372768 1.451747 0.135132 2.759 0.00663 Average parasite load -0.00479 0.995224 0.210862 -0.023 0.98192 Site 2 -0.94417 0.389001 0.374162 -2.523 0.01281 Site 3 -0.30013 0.740726 0.355844 -0.843 0.40053 Site 4 -1.44847 0.234929 0.352782 -4.106 7 e -05 Site 5 0.296112 1.344621 0.34855 0.85 0.39712 Site 6 0.056152 1.057758 0.363887 0.154 0.87760 Site 7 0.232257 1.261444 0.373526 0.622 0.53515 Site 8 0.902538 2.465854 0.350087 2.578 0.01104 Site 9 1.382721 3.985732 0.390418 3.542 0.00055 Site 10 0.981659 2.66888 0.389195 2.522 0.01285 Site 11 0.651543 1.918499 0.355763 1.831 0.06931 Site 12 -0.06357 0.938413 0.354375 -0.179 0.85792 Site 13 0.311937 1.366069 0.348786 0.894 0.37277 Site 14 -0.38779 0.678553 0.348518 -1.113 0.26787

Table 2.4 ANOVA (Type III tests) of GLM investigating the (fixed) effects season caged, treatment, average parasite infection and site on clam growth. Sum Sq. Df F value Pr (>F) (Intercept) 41.347 1 62.6389 9.21E-13 Season caged 84.814 1 128.4894 < 2.2e-16 Treatment 5.023 1 7.6096 0.006637 Average parasite load 0 1 0.0005 0.981921 Site 72.361 13 8.4325 3.28E-12

Spatial and temporal variability of parasite infection in clams 36

Of the GLMMs compared, the best model emerged with clam shell length and treatment as predictors of parasite load (i.e. model with lowest AICc value; Table 2.5). The length of the clam shell was found to significantly affect parasite uptake (Table 2.6). An increase in shell length of one mm resulted in 14% more parasites (p < 0.001). Treatment also had significant input into the model’s fit, with on average 11% more parasites in unharvested areas than in harvested areas (p = 0.042).

The sampling period had a significant effect on parasite infection (Table 2.7). Over the full eight month sampling period there were 53% more parasite infections than over the four month winter sampling period (Table 2.8; p < 0.001). However, there was no significant variation of infection between the winter and summer four month sampling periods (p = 0.14).

Table 2.5 Candidate models for metacercarial load in clams. Akaike's information criterion with a correction for finite sample sizes (AICc) and Δ 1c values of the models investigated with parasite load as the response variable (generalised linear mixed effect model with Poisson error structures). Bracketed information indicates the predictor variables included in the model. The model with the lowest AICc is shown in bold. Candidate models AICc Δ AICc Model 1 (Length & Treatment) 6152.2 0 Model 2 (Length) 6154.2 2 Model 3 (Treatment) 6362.2 210

Table 2.6 Results of the GLMM investigating significance of the (fixed) effects shell length and treatment on clam parasite infection. The multiplicative value for treatment is referenced against a control treatment. Estimate Multiplicative value Std. Error z value Pr (>|z|) Intercept -0.24029 0.7864 0.09477 -2.535 0.0112 Shell length 0.37997 1.132807 0.02561 14.834 <2e-16 Treatment -0.11189 0.894143 0.05503 -2.033 0.042

Spatial and temporal variability of parasite infection in clams 37

Table 2.7 Candidate models for metacercarial load in clams. Akaike's information criterion with a correction for finite sample sizes (AICc) and Δ AICc values of the models investigated with parasite load as the response variable (generalised linear mixed effect model with Poisson error structures). Bracketed information indicates the predictor variables included in the model. The model with the lowest AICc is shown in bold. Candidate models AICc Δ AICc Model 1 (Season) 6287.1 0 Model 2 (Season & Treatment) 6289.1 2 Model 3 (Treatment) 6362.2 75.1

Table 2.8 Results of the GLMM investigating significance of the (fixed) effect of sampling period on clam parasite infection. The multiplicative value for a full 8 months and summer period are referenced to a winter period. Estimate Multiplicative value Std. Error z value Pr (>|z|) Intercept -0.432 0.65 0.116 -3.66 2.6 e -4 Full 8 months 0.422 1.53 0.053 7.98 1.5 e -15 Summer -0.098 0.91 0.067 -1.46 0.14

2.3.3 Snapshot sampling: spatial variability of parasites within a harvesting context Infected clams were found at all study locations (Figure 2.6). Prevalence (the percentage of infected individuals) ranged from 84.5% in the inner Otago Harbour to 97% in the outer Otago Harbour and Blueskin Bay. Average parasite load within the inner Otago Harbour was the lowest, with an average infection of 13.6 (S.E. = 0.8) metacercariae per clam, whereas average parasite load within the outer Otago Harbour and Blueskin Bay was respectively 197.2 (S.E. = 7.9) and 140.9 (S.E = 5.4) metacercariae per clam. Clams from one site (site 5) in the outer Otago Harbour had markedly higher infection loads (Figure 2.6), indicating that variation in parasite infections can occur on a small spatial scale.

Clam density (Figure 2.7) in harvested areas was, on average, 37% lower than in unharvested control areas (Table 2.9). Similarly, the biomass of clams (Figure 2.8) in harvested areas was, on average, 52% lower than in unharvested control areas (Table 2.10).

Spatial and temporal variability of parasite infection in clams 38

700

600 Harvest

Control 500

400

300

Parasite load per clam per loadParasite 200

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Sites

Figure 2.6 Average parasite infection for commercially harvested and unharvested (control) areas at each site: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent the standard error. N = 80 clams per treatment.

200 Control 180 Harvest

160

) 2 140 120 100 80 60

Density (clams/0.25 (clams/0.25 m Density 40 20 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site Figure 2.7 Average density of clams within a 0.25 m2 quadrat at sites 1 - 14 in commercially harvested and unharvested (control) areas: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent ±1 standard error. N = 4 quadrats per treatment.

Spatial and temporal variability of parasite infection in clams 39

3000 Control Harvest 2500

2000

1500 Biomass Biomass (g) 1000

500

0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site Figure 2.8 Average biomass (wet weight) of clams within a 0.25 m2 quadrat at sites 1 - 14 in commercially harvested and unharvested (control) areas: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent ±1 standard error. N = 4 quadrats per treatment.

Table 2.9 Results of the GLMM investigating significance of the (fixed) effect of harvesting on clam density. The multiplicative value for treatment is referenced against a control treatment. Fixed effects Estimate Multiplicative value Std. Error t-value Pr (>|z|) (Intercept) 4.53 92.75856 0.1303 34.76 < 2e-16 Treatment -0.4525 0.636036 0.059 -7.67 1.72E-14

Table 2.10 Results of the GLMM investigating significance of the (fixed) effect of a harvest on clam biomass. The multiplicative value for treatment is referenced against a control treatment. Fixed effects Estimate Multiplicative value Std. Error z-value Pr (>|z|) (Intercept) 7.286117 1459.891 0.086321 84.41 <2e-16 Treatment -0.71399 0.489687 0.005949 -120.02 <2e-16

Spatial and temporal variability of parasite infection in clams 40

Overall, there was no significant difference between the average shell length of clams at commercially harvested and unharvested (control) areas (Paired t-test, p = 0.097). Despite this, shellfish were observed on average to be larger at control areas than harvested areas for 10 of the 14 sites (Figure 2.9).

50 45 40 35

30 25 20 Length(mm) 15 Harvest 10 Control 5 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Site

Figure 2.9 Average shell lengths of clams at each site in commercially harvested and unharvested (control) areas: site 1 - 4 in the inner Otago Harbour, 5 - 8 in the outer Otago Harbour and 9 - 14 in Blueskin Bay. Error bars represent ±1 standard error. N = 80 clams per treatment.

Of the GLMMs compared, only the model with the lowest AICc was considered. The model with treatment, age and condition as predictors of parasite load per clam emerged as the best model (i.e. model with lowest AICc value; Table 2.11). All fixed effects had a significant influence on parasite infection (Table 2.12). In particular, there was a significant effect of harvesting on parasite load (p < 0.001). Overall, harvested areas had 36% more parasites per clam on average than unharvested control areas. Age also had a significant effect with parasite loads increasing by 61% for each sequential age category (p < 0.001). Clams body condition also had a significant effect on parasite infection (p < 0.001), with a one unit increase in body condition resulting in 2% more parasites.

Spatial and temporal variability of parasite infection in clams 41

Table 2.11 Candidate models for metacercarial load in clams. Akaike's information criterion with a correction for finite sample sizes (AICc) and Δ AICc values of the models investigated with parasite load as the response variable (generalised linear mixed effect model with negative binomial error structures). Bracketed information indicates the predictor variables included in the model. The model with the lowest AICc is shown in bold. Candidate models AICc Δ AICc Model 1 (Treatment, Age, Condition) 21903.8 0 Model 2 (Age, Condition) 21921.8 18 Model 3 (Age) 21981.4 77.6 Model 4 (Treatment, Age) 21963.1 59.3 Model 5 (Treatment, Condition) 23754.8 1851 Model 6 (Condition) 23755.2 1851.4 Model 7 (Treatment) 24546.8 2643

Table 2.12 Results of the GLMM investigating significance of the (fixed) effects age, condition and treatment on clam parasite infection. The multiplicative value for treatment is referenced against a control treatment. Fixed effects Estimate Multiplicative value Std. Error t-value Pr (>|z|) (Intercept) 0.735625 2.086786 0.649261 1.13 0.257 Age 0.477324 1.611756 0.008413 56.74 < 2e-16 Condition 0.01641 1.016546 0.027316 5.57 2.59E-08 Treatment 0.305278 1.357002 0.064805 4.71 2.47E-06

2.4 Discussion Harvesting of A. stutchburyi does not only have an impact on the target population but also on the surrounding environment. When clam biomass is reduced, many aspects are affected, such as a reduced food resource for predatory whelks (Cominella glandiformis) and oystercatchers (Haematopus ostralegus), and a reduced habitat for anemones (Anthopleura aureoradiata) that reside on clam shells (Mouritsen & Poulin 2003a). The aims of the current study were (1) to measure the impact of harvesting on clam echinostome load and (2) the effect of parasites on clams. This was achieved with field sampling at three study locations, by measuring infection levels of remaining clams in harvested areas, in comparison to clams in areas of no harvest. In parallel, unparasitised juvenile clams were caged to assess the Spatial and temporal variability of parasite infection in clams 42 recruitment of cercariae from the water column. Parasite uptake was assessed seasonally and the effect of parasites on condition and growth of clams in situ was measured.

2.4.1 Parasite accumulation rates (cage experiment) When using caged juvenile clams to assess parasite accumulation rates, a significantly different infection rate was observed between harvested and unharvested areas. Metacercariae infections in caged clams were 11% lower in harvested than unharvested areas, which indicates there may have been fewer cercariae to be ingested from the water column. However, due to the very low accumulation rate of parasites in the cage experiment, the results cannot be meaningfully interpreted. Prior studies within Otago Harbour have observed much higher rates of in situ parasite accumulation than were observed during the present study. At Lower Portobello Bay, clams were found to have an average accumulation rate of 0.5 metacercariae per day (Mouritsen 2002a), while in Company Bay, where clams live in higher densities, a lower accumulation rate of 0.2 metacercariae per day was recorded (Leung & Poulin 2007b). By contrast, the present study recorded parasite accumulation rates of between 0.09 and 0.11 metacercariae per month.

The rate of parasite infection was low over both the winter and summer sample periods. The juvenile clams used to assess the summer period took up fewer parasites than their winter counterparts. Fewer infections in summer may have been due to a reduction of clam’s body condition during the four months that they were held within the laboratory. This is suggested as the growth of clams in situ far exceeded that of the clams held in the laboratory for the same period. At initial set up in April, the average shell length of clams was 12.5 ± 2.2 mm. During the four months that clams were kept in situ the average shell length increased to 15.2 ± 1.8 mm. In comparison, the average shell length of clams held in the laboratory over the same period only increased to 13 ± 1.3 mm. Therefore, as shell growth is not observed in food limited individuals (de Montaudouin 1996), the feed within the laboratory may have been insufficient to meet the energy requirements of the clams and limited their growth or the tank environment may have lowered growth rates. The body condition of clams may also be reduced when individuals receive insufficient nutrients. A reduction in clam body condition will detrimentally affect clam filtration rate and uptake of parasites. In future studies, it may be more effective to use larger unparasitised individuals with a shell length greater than 25 mm as, during sampling in situ, infection intensity was observed to increase at this length. Spatial and temporal variability of parasite infection in clams 43

However, the temporal variability of parasite infections from the current caging study may represent the natural variation of parasites incorrectly, due to the low accumulation rates over the study period. Infection rates were expected to differ season by season, as variation in parasite infection has been suggested in previous studies (Mouritsen 2002b, Koprivnikar & Poulin 2009, Studer & Poulin 2012, de Montaudouin et al. 2012). Although no in situ experiments have been conducted, cercariae emergence increases in the laboratory at 25oC (Allison 1979, Koprivnikar & Poulin 2009). Reduced parasite acquisition was expected in winter due to lower temperatures which result in a marked reduction in bivalve filtration rate (Walne 1972). Conversely, warmer waters in summer result in an increased filtration rate of clams (Walne 1972). Likewise, warmer waters are predicted to increase cercariae production, and greater numbers of cercariae are expected to emerge from their gastropod host (Mouritsen 2002b, Koprivnikar & Poulin 2009). Therefore, based on this information and other parasites patterns of emergence, it has been assumed that transmission events primarily occur in summer months (Mouritsen et al. 2003, Studer & Poulin 2012). Although temperature loggers recording summer and winter temperatures did not record the spikes in temperature necessary for cercariae emergence, this may have been due to the loggers situated in the channel. Previous studies have recorded individual tidal pools formed within depressions in the sandflat during low tide at temperatures far greater than the channel, reaching temperatures of up to 30 degrees during Dunedin summer months (Studer & Poulin 2012).

The low parasite accumulation rate of caged clams in the current study may have resulted in significant differences remaining undetected (i.e. a type II error). This could limit predictions of parasite accumulation rates beyond the cage environment. It is possible that the presence of the cage structures caused unnatural artefacts (Hall et al. 1990) by changing the flow of water carrying cercariae or obstructing the movement of first intermediate hosts. The small body size and respective filtration rate of juvenile clams may have contributed to the low accumulation rate of parasites (Walne 1972). However, similarly sized juvenile clams collected in situ have been observed with parasite loads greater than 50 (pers. obs. S. O’Connell-Milne).

The growth rates of caged clams varied temporally; clams grew faster in summer than in winter. Juvenile clams grow faster than adult shellfish, with an observed rate of more than 1 Spatial and temporal variability of parasite infection in clams 44 mm a month far exceeding that reported for adult clams (Marsden 2004). A six month summer study in the Avon-Heathcote Estuary found average in situ growth rates of adult clams to range from 0.17 and 0.35 mm per month (Marsden 2004). Juvenile shellfish were selected for the caging experiment due to their high growth rate, in the hope of observing not only variations in the infection rate of parasites among sites, but also the effect of parasites on clam growth rates in situ.

The growth rates of caged clams in situ had significant variation between sites. However, relating variations in clam growth rate to parasite load is extremely difficult in situ as growth rates may be extremely variable between sites (Larcombe 1971, Blackwell 1984, Martin 1984, Dobbinson et al. 1989). Additionally, the variation in growth rates between sites could not be related to the parasite load due to the low level of infection achieved in the caging experiment. Periods of low shell growth may be due to environmental conditions, such as submersion time or clam density (Jensen 1992, McKinnon 1996). Although the elevation of sites differed significantly among locations, the environmental significance of this variation was minimised by positioning sites near MLWS. This ensured the clams were subjected to long periods of immersion. Immersion time determined the available period for clams to filter feed and acquire echinostomes. In addition, variations in growth rates between sites may have been due to unmeasured environmental factors, such as the sites’ distance from the main channel or the water flow rate (Cameron 1997). These factors may affect food availability and the clearance rate of the clam (Grizzle et al. 1992).

2.4.2 Snapshot sampling: spatial variability of parasites within a harvesting context The observational study of echinostome variation in the context of a commercial harvest was conducted in an environment modified by long-term harvesting. This caused the results to have some limitations, as the harvest regime was not experimentally controlled and there was a lack of baseline pre-harvest data (i.e. a Before-After Control-Impact design). Consequently, this study may not allow for the mechanism behind the increased parasite load in harvested areas to be fully understood. Regardless, this study provides insights into the effects of harvesting on parasite infection within clams under present conditions.

Echinostome parasite loads within the clam A. stutchburyi were observed to be 36% higher in harvested areas than in unharvested areas once clam age and body condition had been Spatial and temporal variability of parasite infection in clams 45 accounted for. In unharvested areas, individuals tended to occur at higher densities, which creates an encounter-dilution effect, lowering the chance of infection for densely-packed individuals (Mooring & Hart 1992). When the density of clams is reduced by a commercial harvest, this encounter-dilution effect is reduced and clams no longer ‘compete’ for parasites. Therefore, the parasite load of remaining clams is increased. As the parasites’ primary hosts, i.e. whelks (Cominella glandiformis) and mud snails (Zeacumantus subcarinatus), are not removed by a harvest (Stewart 2010), it is assumed the environment retains a constant production of cercariae from these hosts.

If individual parasite load is increased in a harvested area, this may have detrimental effects on the surrounding ecosystem. Greater infections result in shellfish stranded at the sediment surface and unable to bury (Thomas & Poulin 1998, Jensen et al. 1999, Mouritsen 2002a). More intense parasitism in harvested areas may therefore increase the susceptibility of clams to predation by reducing the clam’s burrowing ability (Thomas & Poulin 1998). This increased predation within harvested areas may further slowdown the recovery of an already reduced biomass. However, increased parasite load may also have beneficial effects. Once highly parasitised clams are stranded at the surface, they increase heterogeneity of surface structures (Mouritsen & Poulin 2002). Surfaced clam shells provide substrate for attachment or shelter for epifauna and cause density and diversity of benthic organisms to increase (Thomas & Poulin 1998, Mouritsen & Poulin 2005). In addition to limiting vertical movement, echinostomes also reduce horizontal movement via crawling of surfaced clams (Mouritsen 2002a). Because bioturbation of the top layer of sediment by clams depresses the density of co-occurring infauna (Flach 1996, Whitlatch et al. 1997), the reduced movement of clams results in increased abundance of infauna (Mouritsen & Poulin 2002). As these organisms increase in number, so too will their predators (Reise 1985). The result is greater local biodiversity, which may increase the resilience of the ecosystem (Mouritsen & Poulin 2002).

Clams with a higher body condition had greater numbers of echinostome parasites. This relationship was similar to the findings of Mouritsen et al. (2003). A positive correlation between parasite load and body condition suggests that the encysted parasites (which are in a semi-dormant state) impose no measurable physiological cost on the clam host. However, correlation does not equal causation. The positive relationship observed between parasite load and body condition appeared to be due to individuals with a greater body condition having a Spatial and temporal variability of parasite infection in clams 46 greater filtration rate (Coughlan & Ansell 1964). As filtration is the mechanism of parasite infection (Allison 1979), this may allow uptake of more cercariae from the water column (Riisgard 2001, Mouritsen et al. 2003).

Residuals from the regression between the dry weight of clam soft tissue and clam shell length were used as a body condition index. However, the use of dry flesh weight to assess bivalve condition has been criticised. This is due to the gonadal mass of clams, which can account for a large portion of the body weight and fluctuates seasonally (Coughlan & Ansell 1964, Walne 1972). During the spring months, due to increases in gonadal mass and nutrient storage, flesh weight may increase by 30 - 50% (Larcombe 1971). Later in the spring, due to the extended reproductive period of clams, individuals are likely to be at different stages of spawning, greatly affecting body condition (Larcombe 1971, Stephenson 1981). Although parasite load is unaffected by clam sex (Mouritsen 2002a), in future studies it may be beneficial to identify the reproductive status of the clams (i.e. ‘immature’, ‘ripe with eggs’ or ‘spawned’). To reduce the effect of gonadal variation affecting body weight, shellfish in the current study were collected early in the spring prior to the spawning period, all within the same week.

Older clams also had greater numbers of echinostome infections. The pattern of older and larger clams harbouring more metacercariae has commonly been seen in field-collected samples (Allison 1979, Poulin et al. 2000, Leung & Poulin 2007a, Leung et al. 2009c). The greater number of metacercariae in larger clams may be correlated with their greater filtration rate, as well as with parasite accumulation over time (Coughlan & Ansell 1964). As the age of the clam was correlated to shell size, this also supports previous findings of a positive relationship between the shell length and parasite load of clams observed locally (Thomas & Poulin 1998) and in the northern hemisphere (de Montaudouin et al. 1998).

The snapshot field sampling indicated that the abundance of echinostomes might fluctuate on small spatial scales. The parasite load of clams varied among study locations, with higher levels of infection found in the outer Otago Harbour and Blueskin Bay than in the inner Otago Harbour. Additionally, within these locations individual areas may have substantially higher parasite infection as seen at site five. The number of echinostomes within the water column may have varied depending on the distribution of the parasites’ first intermediate hosts, the whelk (C. glandiformis) and mud snail (Z. subcarinatus). Spatial variations in the Spatial and temporal variability of parasite infection in clams 47 metacercarial load per clam has been linked to the prevalence of whelks at a site (Studer et al. 2013). Local infaunal surveys found far greater numbers of whelks and mud snails at central banks in the outer Otago Harbour than inner Otago Harbour (Stewart 2010). However, in previous studies in the Otago region, the abundance of whelks, as well as prevalence of the echinostome C. australis within whelks, were observed to be evenly spread throughout the intertidal zone on a local scale (Mouritsen et al. 2003). Due to the small distance between treatments, the distribution of released cercariae was assumed to be approximately homogeneous between harvest and control areas in the present study (Mouritsen et al. 2003). However, small unrecognized gradients such as in hydrodynamic conditions could in principle also affect the rate at which the clams accumulate parasites (Mouritsen 2002a). The abundance of gastropods as first intermediate host and definitive avian hosts (oystercatchers) should be quantified in future studies to discern reasons for small-scale differences in parasite infection rates (Studer et al. 2013).

Many other factors may affect echinostome accumulation within clams. Although A. stutchburyi are the secondary intermediate host of echinostomes, organisms such as other parasites (Gymnophallidae), the mudflat anemone (Anthopleura aureoradiata) and wedge shell (Macomona liliana) may have an effect on the parasite load in clams. Gymnophallid parasites also encyst in this clam and have been found to have a positive association with echinostome species (Poulin et al. 2000, Leung & Poulin 2007b). The mudflat anemone predate on parasites as they enter the water column surrounding the clams’ intake siphon, therefore reducing the availability of parasite for A. stutchburyi (Mouritsen & Poulin 2003a). The wedge shell may act as a ‘parasite sink’, accumulating potentially infective cercariae and reducing the number of parasites in the system (Leung & Poulin 2008). In future studies, the distribution of all organisms with potential effects on parasite loads within clams should be quantified; however, this was beyond the scale of the current study.

Oystercatcher abundance may also affect parasite availability; oystercatchers have a strong seasonal pattern of abundance, with high numbers present on clam beds in winter months (Onley 2013). Infected oystercatchers pass out echinostome eggs continuously, although not all of these survive (Allison 1979). In the current study, bird presence was not accounted for, and there is no systematic data on seasonal bird presence in this area. Bird populations between Otago Harbour and Blueskin Bay can vary markedly both spatially and temporally (pers. comm. D. Onley). In Tasman and Golden Bay, harvesting has been observed to Spatial and temporal variability of parasite infection in clams 48 negatively affect oystercatcher populations due to reduced clam density (Schmechel 2001). In Otago Harbour, oystercatcher aggregations in harvested areas have been observed in the days following a harvest (Onley 2013). As oystercatchers avoid feeding on larger, more heavily- parasitised clams, an increased parasite load in smaller clams in harvested areas may result in greater echinostome infection in oystercatchers and may detrimentally affect oystercatcher populations (Norris 1999). Additionally, as more heavily parasitised clams become easier prey for oystercatchers, increased parasite load may result in greater consumption of clams from within harvested areas (Norris 1999). In future studies, it may be essential to link both spatial and temporal variation in clam infection levels to the occurrence or abundance of the final oystercatcher host.

In summary, harvesting leads to an increase in per capita infection levels, relative to those observed in clams from adjacent unharvested areas, when accounting for differences in clam body condition, age and variation among sites. Given that parasite infections appear to increase with clam body condition, there may be consequences for the remaining clam populations in harvested areas. These changes in parasite infection may affect the clams directly or indirectly, for instance changing their behaviour. Additionally, increased numbers of parasite infections may cause ecosystem changes such as altered abundance of associated infauna, increased rate of avian predation, and variations to hydrodynamic processes and therefore sediment makeup. Commercial harvesters would do well to consider how these effects may impact the wild stock, to ensure sustainability into the future. For example, wild stock may be impacted by increased predation by oystercatchers, resulting in slower regeneration of clams. Commercial harvesters could control for this, by leaving longer periods between subsequent harvests to allow the biomass of clams to replenish. 49 Spatial and temporal variability of parasite infection in clams

3 Chapter 3: Clam mortality, growth rate and body condition in response to parasite infection

The impact of parasite infection on clam Austrovenus stutchburyi 50

3.1 Introduction Parasites have varying impacts on their hosts. Most organisms are infected by parasites, and infected individuals are often host to multiple species. Generally, parasites have a deleterious effect on the well-being of their host, sometimes resulting in mortality of the host (Fredensborg et al. 2004). More commonly, parasites negatively affect the growth, reproductive fitness, nutrition, energetic budget and behaviour of their host (Poulin 1994, Poulin & Thomas 1999, Lafferty et al. 2008, Stumbo et al. 2012). In addition, changes in the environment, such as climate change or invasion of a new species, may increase parasite abundance (Harvell et al. 2002). Subsequently, a previously harmless parasitic organism may negatively affect the host at increased infection levels (Harvell et al. 1999).

The impact of a parasite on its host may be determined by the role the host plays in the parasite’s life cycle. For trematodes in particular, hosts may serve as either definitive hosts, harbouring the adult stage of the parasite, or intermediate hosts, harbouring the asexually multiplying or encysting stages of the parasite (Kearn 1998). In the first intermediate host, a trematode parasite often destroys the host gonads and reroutes host energy towards its own asexual reproduction. In contrast, trematodes generally utilise their second intermediate host to facilitate transmission to the final host through predation; they typically encyst in a dormant state within muscle or other tissues in the second intermediate host, causing relatively little damage to key host organs (Combes 1991, Poulin 1994, Lafferty 1999).

For the echinostomes Acanthoparyphium spp. and Curtuteria australis, the clam Austrovenus stutchburyi plays the role of second intermediate host (Allison 1979, Martorelli et al. 2006). These echinostomes encyst in the foot of the clam as metacercariae, where they remain inactive in a state of hypobiosis (Chappell 1993). In addition to hosting parasites, this clam has economic value as a commercially targeted species and is of cultural importance to Māori. It also provides essential ecosystem services, for example, by filtering suspended particles from the water column and improving water quality (Dame 1993, Newell 2004).

Commercial harvesting reduces clam biomass within harvest beds and may also change the size structure of remaining clams (Wing et al. 2002, Stewart 2008a, Kainamu 2010). Anthropogenic change to the environment by commercial harvesting of clams, as described in Chapter Two of the current study, causes an increase in the average parasite load of remaining clams. In an environment with constant production and release of cercariae from The impact of parasite infection on clam Austrovenus stutchburyi 51 gastropod primary intermediate hosts, reduced biomass of the clam second intermediate host may result in an increased parasite load per individual among the remaining clams. However, it is unknown how the subsequent level of parasite infection may affect A. stutchburyi.

3.1.1 Objectives of Chapter Three The aim of this chapter was to assess the effect of echinostome parasites on the mortality, shell growth rate, foot length and body condition of the clam A. stutchburyi. Assessment of the foot length of clams was included in this study because the foot is not only instrumental in burrowing, but also the only site in the clam’s body where the parasites accumulate. In Chapter Two, I showed that A. stutchburyi with a greater number of echinostome parasites have a higher body condition. However, slight variations in immersion time, food availability and the density of surrounding clams may also have caused their body condition to fluctuate in situ. To directly observe the effect of echinostome parasite infection on A. stutchburyi without the confounding environmental effects, a laboratory-based experiment was carried out to complement the in situ findings. For this purpose, juvenile clams were experimentally infected with the echinostome C. australis under controlled laboratory conditions, to quantify the influence of varying levels of parasite infestation.

3.2 Methods Two hundred juvenile clams with an average length of 13.2 mm (S.D. = 0.6 mm) were collected by hand from a sand bank on the south side of Quarantine Island in Otago Harbour on the 17th of November 2014 and transported to the laboratory in a cooler. As the number of pre-existing echinostome metacercariae affect the establishment success of new metacercariae (Leung et al. 2010), juvenile clams were used here as they have high growth rates and harbour low numbers of metacercariae (McKinnon 1996). The time out of water during transport was not appreciably longer than what the juvenile clams would have naturally experienced during low tide, and within four hours of collection the clams were back in seawater in the laboratory.

Of the juvenile clams collected, a subsample of 70 were dissected and their parasite load assessed in order to establish the baseline infection level of the cohort. The foot of each clam was removed, by cutting along the narrow bridge between the gonad and foot base, as described in Leung & Poulin (2011), mounted on a glass slide and flattened beneath a cover The impact of parasite infection on clam Austrovenus stutchburyi 52 slip (Leung et al. 2010). The foot was flattened until transparent such that encysted metacercariae within the foot were visible and could be counted under a dissection microscope. No distinction was made between C. australis and Acanthoparyphium spp. when counting encysted metacercariae, as they play similar roles within the clam and because molecular markers are necessary to distinguish between these two taxa (Babirat et al. 2004).

3.2.1 Maintenance of clams Phytoplankton bag cultures were created of the microalgae Isochrysis galbana, Tetraselmis chui, Skeletonema costatum and Pavlova lutheri. In each case, 20 L culture bags were filled with seawater, which was filtered using a progressive 10 µm, 5 µm, 1 µm and 0.35 µm filtering system and sterilised with ultraviolet light. To each culture bag, 100 ml of highly concentrated algae stock culture and Guillards F/2 medium were added (Keller et al. 1988).

Guillards F/2 medium consisted of NaNO3, NaHPO4, FeCl3 (7H20), Na EDTA, NaSiO3 and

MnCl2 (4H2O) as well as trace solutions of ZnSO4 (7H2O), CoCl2 (6H2O), Na2MoO4 (2H2O) and vitamins B12 and H (biotin). Algae cultures were grown in a continuous light environment for ten days, then harvested for feeding in the log phase of growth (Kainamu 2010).

These four phytoplankton species are common within Otago waters and were chosen for their nutritional content and size. This ensured adequate nourishment and uptake by the juvenile clams while laboratory experiments were underway. Tetraselmis chui is a unicellular flagellate about 9 µm x 15 µm (Guillard & Ryther 1962). It is commonly used in filtration studies due to its high nutritional value, in particular proteins and lipids (Whyte 1987, Wikfors et al. 1996, Heggie 2008, Kainamu 2010). Isochrysis galbana and D. tertiolecta have also been used as feed in laboratory experiments, as they are efficiently retained by bivalve gills (Winter 1978, Pawson 2004). Isochrysis galbana is also used for commercial aquaculture of manila clams (Tapes philippinarum) (Coutteau et al. 1994). The diatom Skeletonema costatum was incorporated into the feed to ensure clams received a source of calcium carbonate for shell development (Laing et al. 1987).

Twelve replicate 15 litre tanks were set up to hold clams between each subsequent infection period, as well as for an additional two months after experimental infections. Sieved sand was added to each container to a depth of 20 mm. Air stones maintained adequate aeration and The impact of parasite infection on clam Austrovenus stutchburyi 53 gentle water movement in each tank. Micro-valves connected to 4 mm hosing sustained an even inflow of water to each tank. Each replicate group was kept in a separate tank to avoid pseudo-replication. Clams remained submerged throughout the experiment and were rotated clockwise to a new tank each week, to ensure there was no ‘tank effect’.

During the experimental period, a Masterflex L/S multichannel peristaltic pump (model 07534-08) on a timer distributed 500 ml of the mixed algae feed, made up of equal quantities of I. galbana, T. chui, S. costatum and P. lutheri, to each tank at regular 12.4 hour intervals (Williams & Pilditch 1997). Pulses of food in the laboratory artificially simulated the tidal flux of phytoplankton in situ to replicate the tidal rhythmicity and maintain the clams’ endogenous circatidal rhythm (Beentjes & Williams 1986, Williams & Pilditch 1997). The natural rhythmicity of clams results in shell gaping and siphon activity at each expected high tide (Beentjes & Williams 1986), simulating this ensured that clams all fed at the same time and had equal chances of acquiring parasites through the inhalant siphon at each infection event. Once the tidal rhythmicity was experimentally embedded, it was essential to ensure these pulses of food were regular as, if not, it could be lost again within two tidal cycles. The lack of a tidal cycle has been hypothesised to cause limited growth of clams within the laboratory (Beentjes & Williams 1986, McKinnon 1996).

3.2.2 Experimental infection of clams with Curtuteria australis For experimental infections, 1500 whelks, Cominella glandiformis, were collected by hand from Lower Portobello Bay in Otago Harbour and transported in a cooler to the laboratory. To identify infected whelks, C. australis cercariae emergence was stimulated by incubating the whelks individually in circular containers (4 cm diameter) in the laboratory at 25oC under constant light for 30 minutes, following the methods of Fredensborg et al. (2005). The individual containers were examined under a dissection microscope for cercariae. The whelks producing C. australis were maintained in the laboratory for future use. Curtuteria australis was used for experimental infections rather than Acanthoparyphium spp. because of their greater cercarial output per whelk and the ease in which cercariae can be induced to emerge from the whelks on demand (Leung et al. 2010). To ensure the mass of the encysting parasites could be calculated, clams were infected with a single parasite species. This was necessary to calculate the body condition of clams independent of parasite load.

The impact of parasite infection on clam Austrovenus stutchburyi 54

For each experimental infection, whelks were haphazardly selected from those maintained in the laboratory and cercariae emergence was induced as above (Fredensborg et al. 2005). After initial emergence, cercariae display energetic swimming, are positively phototactic and negatively geotactic, which is thought to increase dispersion (Leung 2008). Three hours after the ‘dispersal phase’, the larvae become positively geotactic to aid uptake through the clam’s filter feeding siphons (Leung et al. 2010). At this time, cercariae were collected with a 200 ml pipette and added to the experimental beakers at the required cercarial density.

Clams were selected at random to create 12 groups of 10 individuals. The length of the clam shell was measured from umbo to shell edge, to the nearest 0.1 mm using digital callipers. Clams, once dried thoroughly with a paper towel, were tagged with nail varnish allowing identification. Each group was randomly allocated to one of four treatments, using a random number generator. The four treatments consisted of a control (not exposed to cercariae), a low treatment (10 cercariae/clam), a medium treatment (50 cercariae/clam), and a heavy treatment (100 cercariae/clam). As approximately 60% of available cercariae were successful in infecting the clams in previous studies (de Montaudouin et al. 1998), the number of parasites to infect each treatment group with (Ii), was calculated using the following equation:

푰풇 푰 = ÷ ퟎ. ퟔ 풊 ퟒ

where the final infection level for each treatment (If) was divided into four weekly infection events and divided by the predicted infection success rate (60%). Clams were subjected to this dose of cercariae (Ii) once a week for four consecutive weeks, which allowed parasite numbers to build up in the gradual manner that was representative of in situ infections (Leung et al. 2009c). Therefore, to achieve low, medium and high infection levels clams were exposed to 5, 21, and 42 cercariae respectively for each infection event.

For infection, clams were held individually in cylindrical containers (30 mm diameter) with the posterior end of each clam pushed into the sediment to facilitate burrowing. Sieved sand was added to each container to a depth of 20 mm and covered with 20 mm of sand-filtered seawater. After 60 minutes for the clams to acclimatise, C. australis cercariae were pipetted into the water. Clams remained immersed for 12 hours at 20oC to allow sufficient time for filtration of the water and uptake of the cercariae (Wegeberg & Jensen 2003). The impact of parasite infection on clam Austrovenus stutchburyi 55

3.2.3 Assessing the effect of infection On the 3rd of March, approximately three months (106 days) after the start of the experimental infections, the shell length of each clam was measured from umbo to shell edge, to the nearest 0.1 mm, with digital callipers. The daily, length-specific growth rate of clams was calculated using the following equation:

(푳풇 − 푳풊) 푮 = 풕 where the average daily length-specific growth rate (G) was given by the difference between the average length of clams at start of the experiment (Li) and the average length of clams after three months (Lf), divided by the duration of the experiment in days (t) (Kautsky 1982).

The foot of the clam was dissected as described above, and the foot was placed on a flat surface, straightened without stretching, then measured to the nearest 0.1 mm with digital callipers (Thomas & Poulin 1998). The foot was then mounted on a glass slide as described above, to count encysted echinostomes. Clam soft tissue was removed from the shell and, along with the foot, oven-dried at 60oC for 24 hours. The tissue was weighed to the nearest 0.001 g to determine the clam soft-tissue dry-weight (STDW).

3.2.4 Clam body condition and parasite load indices As C. australis metacercariae occupy a round cyst with an average diameter of 0.023 cm and little variation in body size, the volume of an individual parasite was calculated based on the formula for a sphere. The mean body volume of an encysted parasite was calculated as 0.0007 cm3, which converts to a mass of 0.0007 g assuming that parasite density equals that of water (Santoro et al. 2013). The total mass of parasites per clam was the product of the weight of an individual cyst, multiplied by the number of cysts per clam. The soft tissue dry weight of the clam excluding parasites (STDWep) was calculated by removing the predicted total mass of parasites from the wet weight of the clam. A conversion factor of 8.7% was used to calculate the wet weight of an individual clam from STDW (Ricciardi & Bourget 1998). The wet weight of the clam without parasites was then converted back to STDW to give STDWep.

The impact of parasite infection on clam Austrovenus stutchburyi 56

The residual index was used to calculate the body condition of each clam (Jakob et al. 1996). Clam body mass (STDW) was regressed on clam shell length, after the data was natural log- transformed to meet the assumptions of regression. The residual distances of individual points from this regression line then served as an indicator of whether the individual’s body condition was above or below the condition predicted for its length (Cone 1989). In addition, the body condition excluding parasite mass (STDWep) of each clam was also regressed on the clam’s shell length. This was done because the greater the parasite load within a host, especially in the case of small juvenile shellfish, the more likely it is that body condition is overestimated, unless the mass of parasites is taken into account (Lagrue & Poulin 2015). Body condition and STDW could only be calculated for 95 of the 116 clams due to logistical reasons.

3.3 Statistical analysis Although similar infection levels were the goal for each treatment, varying parasite uptake rates resulted in widely variable final parasite loads within and among treatments. Therefore, regression analysis was considered the most appropriate method to represent the continuum of parasitic infections when assessing the shell growth rate, foot length and body condition of clams in relation to parasite load (instead of group comparisons using ANOVAs). Regression analyses were therefore used to assess the effect of increasing degrees of parasite infection on growth rate, body condition and foot length of juvenile clams. Multiple linear regression was used to establish any separate effects of parasite load and initial shell length on shell growth rate. Significance was set at the 5% confidence level (α = 0.05). All statistical analyses were carried out using the software package RStudio 0.98.1103 (R Development Core Team 2014).

3.4 Results Juvenile clams collected for the laboratory experiment initially harboured very few parasites; baseline infection intensity was 0.1 metacercariae per clam, with 8.6% prevalence (percentage of infected individuals). Of the clams exposed to experimental infections, 100% were successfully infected.

The impact of parasite infection on clam Austrovenus stutchburyi 57

The survival rate of clams during the three month experimental period was high, with only 3.33% mortality. Parasites did not appear to influence mortality rate of clams in this experiment.

After experimental infection, clams within low, medium and high treatments had an average infection intensity of 13.9 (S.E. = 0.8), 67 (S.E. = 4.4), and 167.2 (S.E. = 14.2) metacercariae per clam respectively. The control group maintained an average of 0.03 metacercariae per clam.

After three months, the rate of shell growth of clams was negatively affected by increasing 2 parasite load (Figure 3.1; multiple linear regression analysis, r = 0.067; F 2, 113 = 4.08; p = 0.026). However, there was no correlation between initial shell length and shell growth rate 2 (multiple linear regression analysis, r = 0.067; F 2, 113 = 4.08; p = 0.161). Additionally, there was no significant correlation between parasite load and the final shell length of clams 2 (regression analysis, r = 0.017; F 1, 114 = 1.66; p = 0.166).

During the 106-day experiment, clams from the control group showed an increase in mean shell length from 13.1 mm (S.D. = 0.7) to 15.8 mm (S.D. = 1.24), corresponding to a specific growth rate of 0.026 mm d-1. Clams with a low infection showed an increase in mean shell length from 13.3 mm (S.D. = 0.6) to 15.5 mm (S.D. = 0.7), corresponding to a specific growth rate of 0.021 mm d-1. Clams with a medium infection showed an increase in mean shell length from 13.1 mm (S.D. = 0.5) to 14.1 mm (S.D. = 0.6), corresponding to a specific growth rate of 0.009 mm d-1. Finally, individuals in the high infection group showed an average increase in shell length from 13.3 mm (S.D. = 0.7) to 15.3 mm (S.D. = 1), corresponding to a specific growth rate of 0.019 mm d-1.

The impact of parasite infection on clam Austrovenus stutchburyi 58

5 4.5 Control Low 4 Medium High 3.5

3 2.5 2

Growth (mm) Growth 1.5 1 0.5 0 0 50 100 150 200 250 300 350 400 Parasite load per clam Figure 3.1 The relationship between the shell growth and parasite load of clams Austrovenus stutchburyi from low, medium, and high experimental parasite infection treatments. The line represents a linear regression. r2 = 0.067.

Once the parasite mass was removed from the mass of the clam, there was a negative correlation between parasite infection intensity and clam soft tissue dry weight (Figure 3.2; 2 regression analysis, r = 0.209; F 1, 93 = 24.6; p < 0.001).

There was no correlation between the level of parasite infection and the body condition of 2 clams (regression analysis, r = 0.013; F 1, 93 = 1.21; p = 0.27). However, after correcting for parasite mass (mean = 10.5%, ranging from 0.3 to an unusually high 62.8% of host mass), the adjusted body condition index decreased significantly with increasing parasite infection 2 (Figure 3.3; regression analysis, r = 0.219; F 1, 93 = 26.08; p = 0.001).

The impact of parasite infection on clam Austrovenus stutchburyi 59

0.06

0.05 Control Low Medium

0.04 High

(g)

0.03 STDW 0.02

0.01

0 0 50 100 150 200 250 Parasite load per clam

Figure 3.2 The relationship between the soft tissue dry weight without parasites (STDWep) and parasite load of clams Austrovenus stutchburyi from control, low, medium, and high experimental parasite infection treatments. The line represents a linear regression. r2 = 0.209.

0.02

Control Low

0.01 Medium

High e p e

0 Condition indexCondition -0.01

-0.02 0 50 100 150 200 250 Parasite load per clam

Figure 3.3 The relationship between the condition index calculated excluding parasite mass (ep) and parasite load of clams Austrovenus stutchburyi from the control, low, medium, and high experimental parasite infection treatments. The line represents a linear regression. r2 = 0.219. The impact of parasite infection on clam Austrovenus stutchburyi 60

Clam foot length also varied among the treatment groups. As the foot lengths of the clams in the control group were shorter than clams in the infection group, a regression of foot length against parasite load for all individuals did not show a clear trend (Figure 3.4). However, when the control group was excluded, there was a negative correlation between foot length 2 and parasite load (Figure 3.5, regression analysis r = 0.096; F 1, 84 = 8.9; p = 0.004).

14 B

10 D AC AA 8

4 Foot (mm) length Foot

0 1 2 3 4 Treatment

Figure 3.4 Average foot length of clams Austrovenus stutchburyi from control (1), low (2), medium (3), and high (4) experimental parasite infection treatments. Letters indicate averages with significantly different values. Error bars represent ±1 standard error. N = 30 clams per treatment. The impact of parasite infection on clam Austrovenus stutchburyi 61

18 Low 16 Medium High

Foot (mm) length Foot 6

0 0 50 100 150 200 250 300 350 400 Parasite load per clam Figure 3.5 The relationship between the foot length and parasite load of clams Austrovenus stutchburyi from low, medium, and high experimental parasite infection treatments. The line represents a linear regression. r2 = 0.096.

3.5 Discussion Under normal environmental conditions, echinostomes are generally considered relatively harmless to their bivalve host due to their low energetic demands as non-growing metacercariae (Vernberg & Vernberg 1971, Wegeberg & Jensen 2003). However, despite their relative latency within the foot of a clam, encysted metacercariae reduce the ability of A. stutchburyi to use its foot for burrowing or crawling (Thomas et al. 1998, Thomas & Poulin 1998). In addition, the process of cercarial penetration causes tissue damage and stress to the clam (Jensen et al. 1999), resulting in immunosuppressant effects (Paul-Pont et al. 2010). This immunosuppression may make the clam more susceptible to further parasitic infection as well as vulnerable to hypoxic conditions (Wegeberg & Jensen 1999). As infection levels increase, echinostomes can negatively affect the physiology and behaviour of the host (Thomas & Poulin 1998, Mouritsen 2002a, Tompkins et al. 2004, Leung & Poulin 2011), and consequently mediate the influence hosts have on the surrounding ecosystem (Mouritsen & Poulin 2002). At high infection levels, the energetic demand of echinostome cysts may become more obvious. This was demonstrated in the present study and supports similar findings in prior studies on the European clam, Cerastoderma edule, which is affected by a phylogenetically related foot-encysting parasite (Wegeberg & Jensen 2003). The impact of parasite infection on clam Austrovenus stutchburyi 62

During the current study, clam mortality did not appear to be affected by echinostome presence. Similarly, when experimentally infected with a phylogenetically similar echinostome parasite, the mortality of C. edule was minimal also (Wegeberg & Jensen 2003). Clams in the present study acquired more parasites than predicted. This may have been due to the predictions of infection success being based only on a single dose of cercariae, whereas multiple infection events were utilised in the current study. As pre-existing metacercariae in a clam have a significant positive effect on the establishment success of new metacercariae (Leung et al. 2010), this may have increased the infection success of each subsequent infection event. When large clams (30 mm shell length) were subjected to cercariae in two separate doses, the number of successful parasites per clam increased almost 4% in the second infection event (Leung et al. 2010).

Echinostome cysts appear to impose an energetic demand on their host as shown by the reduction in shell growth rate as parasite load increased. The shell growth rate of the control group was almost double that of the heavily infected clams. The rate of shell growth within the laboratory was comparable to that of similar-sized individuals caged in situ, therefore it appears that clam diet in the laboratory provided sufficient nutrients for growth. McKinnon (1996) saw little shell growth in laboratory studies when feeding clams 10 ml twice a week of the single-celled alga Dunaliella primolecta. This could either have been the result of the clams’ inability to utilise the food source, or an insufficient quantity of food or from the lack of a tidal cycle (McKinnon 1996). Therefore, to ensure that natural rates of growth occurred in the current study, juvenile clams were fed an excess of mixed algal culture (Tallis et al. 2004) and a tidal feeding cycle was maintained with daily pulses of food (Williams & Pilditch 1997). A mixed diet of phytoplankton has been observed to synergistically boost the rate of shellfish growth and their body condition (Stromgren & Cary 1984).

Experimental infections in the laboratory resulted in reduced soft tissue dry weight and body condition of A. stutchburyi as parasite infections increased. The body condition of the European clam, C. edule, was 12% lower when infected with trematodes compared to uninfected clams following a period of limited food availability (Wegeberg & Jensen 2003). If the body condition of a clam is reduced, the clam’s filtration rate can be negatively affected (Riisgard 2001, Mouritsen et al. 2003), reducing its ability to assimilate food and provide the ecosystem service of filtering estuarine waters. In the current study, however, the rate of shell The impact of parasite infection on clam Austrovenus stutchburyi 63 growth in the control group suggested that clams were adequately nourished, which indicated that negative impacts associated with parasites were not artefacts of insufficient food.

There was a negative relationship between foot length and parasite infection. However, at the lowest levels of infection an increase in foot length of clams was observed. This converse result may have been due to the limited number of encysting cercariae penetrating the foot tissue and causing injuries, thus stimulating tissue regeneration. It is known that clams have fast regenerative rates for their foot tissue as they are at risk of foot cropping by small fish, for example spotties (Notolabrus celidotus) (Mouritsen & Poulin 2003c). There are many marine organisms which can regenerate after suffering tissue damage (Lindsay 2010), for example echinoderms, which regenerate their arms (Bourgoin & Guillou 1994), and crabs, which regenerate their limbs (Edwards 1972). However, although the foot length of clams may be increased at low infection levels, as infections increase foot function may be deleteriously affected nonetheless (Mouritsen 2002a, Mouritsen & Poulin 2003c).

Severe infections undoubtedly have a deleterious effect on foot functionality of clams (Mouritsen 2002a). At high levels of infection, the parasites may simply overwhelm the clam’s ability to regenerate damaged foot tissue. As cercariae penetrate the epidermis of the foot to encyst, the ensuing holes enable fluid to exude from the clam tissue (Lauckner 1983), requiring the clam to expend energy for wound healing. In addition, the clam host produces a tissue layer to surround the metacercariae (Jensen et al. 1999). The movement of haemolymph and contraction of longitudinal muscles within the clam’s foot appears to be limited by the presence of metacercariae cysts (Mouritsen 2002a). A negative correlation between foot length and increasing parasite load in clams has also been found in previous studies (Thomas & Poulin 1998, Mouritsen 2002a).

Reduced foot functionality from increased infections can have a wider impact on the ecosystem (Mouritsen & Poulin 2002). Therefore, the higher parasite loads in commercially harvested areas may reduce the mobility of clams within the sediment and prevent burying into the sediment. Once clams are limited to the sediment surface, chances of avian predation have a seven-fold increase (Thomas & Poulin 1998). Additionally, as parasite infection reduces the ability of the foot to contract, its tip is more likely to be cropped by fish (Mouritsen 2002a, Mouritsen & Poulin 2003c). The removal of the tip of the clam’s foot, where parasites accumulate at 4-fold higher densities than at the base of the foot, may result The impact of parasite infection on clam Austrovenus stutchburyi 64 in underestimation of the clam’s parasite load (Mouritsen 2002a). In future studies, the proportion of foot cropped should be examined and the ‘missing’ cercariae accounted for, to provide a full account of the parasites within an area (Mouritsen & Poulin 2003b).

In summary, infection by the echinostome parasite C. australis appears to affect the clam A. stutchburyi deleteriously. Shell growth rate and body condition are reduced as parasite infections increase. Although foot length is greater at low levels of parasite infection, increasing intensity of infection reduces the length of the foot, which potentially compromises foot functionality. Therefore, as meat quantity is of importance to harvesters, it may be assumed that parasitism, by reducing the body condition of clams, may affect their commercial quality. A commercial harvest appears to cause the change in environmental conditions that facilitate the increase of parasite infection within the remaining clam population. Accordingly, in harvested areas these parasites are likely to have a greater detrimental effect on their hosts. The increased parasite load in commercially harvested areas may result in changes to the growth rate, body condition and behaviour of clams, as well as broader impacts on the ecological community.

4 Chapter 4: Discussion

Discussion 66

4.1 Thesis findings The objective of the current study was to assess the impact of commercial harvesting on echinostome parasite infection within the clam Austrovenus stutchburyi. For most parasites, key aspects such as their host-parasite relationship, their effects on the surrounding environment, and their reactions to anthropogenic changes remain relatively unknown (Leung et al. 2009a). In the case of the echinostomes Acanthoparyphium spp. and Curtuteria australis investigated in the current study, their relationship with their second intermediate host, the clam (Allison 1979, Lauckner 1987, Martorelli et al. 2006), and many of their effects on the surrounding environment have been well explored (Mouritsen & Poulin 2003c, Tompkins et al. 2004, Leung & Poulin 2007a). However, despite some investigations into the response of these echinostomes to climate change (Poulin 2006, Studer et al. 2013), their reaction to many other anthropogenic changes remains unknown. Throughout Otago Harbour and Blueskin Bay, the average infection level of clams from environments untouched by commercial harvesting were compared with those in density-modified environments subject to sustained intensive commercial harvesting. Additionally, the effect of echinostome infections on the growth rate, foot length, mortality, and body condition of clams was investigated.

The snapshot sampling study revealed that commercial harvesting of clams appears to increase per capita infection levels by echinostomes. On average, infections in clams were 36% higher in harvested areas relative to adjacent unharvested areas when accounting for clam body condition, age, and variability between sites. In harvested areas, the increased parasite load is possibly due to the reduction of clam biomass resulting in a greater parasite density per clam.

Echinostome infections were found to be greater in clams with higher body condition in situ. Past studies have also observed this trend (Mouritsen et al. 2003). However, the methods used to calculate body condition in the present study might have masked the effect of the parasite on the clam. As the body condition of clams in situ was calculated using soft tissue dry weight, which included the mass of the infecting parasites, this may have caused heavily infected individuals to appear in better condition than they actually were. The mass of parasites per clam was not calculated for the in situ samples because of the potential for error due to the unknown proportion of each echinostome species and their different metacercarial diameters (Allison 1979). In addition, the effect of an increased parasite load on the body Discussion 67 condition of the clam may have been affected by environmental variability such as the density of surrounding clams, site elevation or food availability. Therefore, a laboratory infection experiment was necessary to investigate more specifically the consequence of increased parasite load for clams, independent of these potentially confounding factors.

A controlled laboratory experiment was used to test whether an increased parasite load causes changes to the clam A. stutchburyi. The laboratory experiment allowed food availability to be standardised and for parasite mass to be accounted for, by infecting with a single parasite species in a controlled environment. Infecting A. stutchburyi with echinostomes in a laboratory setting revealed that metacercariae deleteriously affected the clam. At increased levels of parasite infection, the body condition, rate of shell growth and foot length of A. stutchburyi all reduced significantly.

Based on the laboratory results, increased parasite loads in harvested areas may negatively affect growth rate, foot length and body condition of clams. Therefore, individuals within an area subjected to harvesting may grow slower, have a reduced ability to bury and a weaker filtration rate. Parasites may also affect the body condition of clams in situ, especially in conjunction with challenging conditions such as periods of low food availability over winter. The additional stress from starvation may cause heavily parasitised individuals to lose body condition faster and have a slower recovery rate (Wegeberg & Jensen 2003). When a clam is physically altered by parasites, it is subjected to additional deleterious behavioural changes. Clams with reduced use of their foot become stranded at the surface of the sediment (Lauckner 1984). This increases rates of predation by oystercatchers (Thomas et al. 1998), thermal stress (Thomas & Poulin 1998) and chances of foot cropping by fish (Mouritsen & Poulin 2003c). Therefore, heavily infected clams may not be as resilient as clams with lower parasite loads.

In coastal and intertidal systems, trematodes are often the most influential parasites present (Sousa 1991, Mouritsen & Poulin 2002, Kuris et al. 2008). A single parasite species can have community-wide impact, by modifying the behaviour of a key species and subsequently altering habitat availability, density and diversity of species, as well as community resilience (Thomas & Poulin 1998, Mouritsen & Poulin 2005, Wood et al. 2007). An increased parasite load in harvested areas may affect the structure of the surrounding community and biodiversity in the intertidal ecosystem (Lauckner 1987, Sousa 1991, Poulin & Thomas 1999, Discussion 68

Mouritsen & Poulin 2002). By reducing the clams’ ability to bury into the sediment (Thomas et al. 1998), echinostome metacercariae indirectly increase the heterogeneity of the sediment surface, which boosts the diversity of invertebrate species in the area (Mouritsen & Poulin 2002). Not only are the sediment characteristics altered for infauna, but surfaced shells provide sites for epifaunal attachment and shelter (Thomas & Poulin 1998, Mouritsen & Poulin 2002, 2005). Overall, parasite-mediated increases in local biodiversity may enhance the resilience of the ecosystem (Mouritsen & Poulin 2002).

These findings, based on the clam-parasite system on an Otago mud flat, are relevant to other systems around New Zealand as well as further abroad. As these echinostome parasites occur throughout New Zealand (Studer et al. 2013), the present results may be indicative of patterns of parasite infection for commercially harvested areas in Whangarei, Tasman Bay and Golden Bay. These findings may also be relevant to the European cockle Cerastoderma edule, as it also has echinostome parasites and is commercially harvested (Wegeberg et al. 1999, Gam et al. 2009).

4.2 Management significance The action of removing large numbers of shellfish can initiate a cascade of events, ultimately changing parasite loads within the system and potentially creating changes at an ecosystem level. The present findings stress the importance of informing recreational, customary and commercial harvesters of the significance of human activities on ecosystem dynamics. Increased awareness helps to facilitate better management programs, especially in regards to the use of traditional customary management methods, such as taiāpure (local fishery), mātaitai (customary fishing ground) and rāhui (temporary closures). These methods allow local control of fishery areas focused on sustainability and preservation of culturally important resources, in an attempt to minimise human influence on coastal ecosystems (Hepburn et al. 2010).

Once empowered with the awareness of the multi-dimensional effects of harvesting, commercial harvesters may be able to customise their harvest strategy. Not only does a commercial harvest reduce the biomass and density of clam stocks, it has far wider effects on the target species, as well as on the surrounding environment. The detrimental effects of heavy parasite infections on clams may increase immediate predation pressure and Discussion 69 susceptibility to future environmental changes. This knowledge could be used by commercial harvesters to take measures reducing the additional impact from elevated parasite infection on clam populations. For instance, members of the harvesting crew could leave a gap between them when harvesting, to reduce the intensity of the harvesting. Taking the same number of clams from a wider area may mitigate the effect of reduced density on parasite infections, and thus on clam quality and future yield of clam beds.

As harvesting increases parasite infection within clams, the population may be slower growing and at risk of higher predation rates, resulting in slower regeneration of stocks within the area harvested. The current harvesting of clams from Otago Harbour has resulted in the reduction of harvesting from Blueskin Bay (Jiang et al. 2011). Therefore, assuming the total take is not increased, the effect of opening Otago Harbour to harvesting should be a lower intensity of harvest over a wider area to allow stock to regenerate and minimise parasite infection. This may reduce the overall impact of the harvesting of clams across the Otago region.

4.3 Further study The current research revealed new information about parasite infection within areas affected by commercial harvesting of clams, as well as the effect of these parasites on clam growth rate, foot length, mortality, and body condition. However, it also identified areas where further research is required.

In future studies, it may be of interest to observe how A. stutchburyi are affected by echinostome infections, concurrently with additional stressors such as climate change or limited food availability. In the current study, echinostome parasites had no significant effect on the mortality of clams. However, clams infected with foot encysting echinostomes may suffer a higher mortality rate than their uninfected counterparts when subjected to conditions which induce further stress, such as low oxygen (Wegeberg & Jensen 1999). The parasite load of clams may also be affected by climate change, as the acidity of oceanic and coastal waters is presently increasing steadily (Orr et al. 2005, Feely et al. 2009). Echinostome diversity may be greatly reduced in an acidified system as the molluscan intermediate hosts may become scarce if calcification is detrimentally affected (Marcogliese 2001). The cercariae of various parasite species have been found to react differently when subjected to Discussion 70 increased water pH (MacLeod & Poulin 2015). The effect of increased pH also occurs in conjunction with variations in temperature and salinity, all of which may impact the success of parasite transmission and overall infection rates (Koprivnikar et al. 2010). By considering possible synergies between multiple stressors, a more realistic interpretation of host-parasite relationships in a changing world may be established.

The condition index of clams could not be compared between harvested and unharvested areas due to potential for confounding effects of parasite infection. A reduced density of clams in harvested areas may have resulted in increased food availability for the remaining clams, if food had been previously limiting, subsequently allowing increased body condition of clams (Peterson 1982, Blackwell 1984, Peterson & Beal 1989). The availability of food may be a limiting factor in Otago as clam’s growth was recorded to increase in some areas after a harvest event reduced their density (Irwin 2004). Moreover, it has been suggested that clams in areas of low elevation on the shore, such as in the present study, may be subjected to severe intra-specific exploitative competition (Mouritsen et al. 2003). In the current study, variations in the growth rates of shells for caged clams among sites indicated that the availability of food may have been uneven across localities. Either the density of clams or the proximity of individuals to water with a high seston load may have affected the ability of clams to access food. If body condition was increased by higher food availability, due to higher condition-based filtration capacity, the remaining clams may have an increased chance of encountering free-swimming cercariae (Riisgard 2001). However, as the body condition of clams is reduced by heavy parasite infection, as discussed in Chapter Three, this may confound variation in body condition in regards to food availability. In addition, clams body condition may be more resilient to the effects of parasites when availability of food is increased (Wegeberg & Jensen 2003). In future, the effect of parasite load on the body condition, growth, and foot length of clams subjected to varying degrees of food availability could be investigated.

In the current study, there was no differentiation between the species Acanthoparyphium spp. and C. australis when counting echinostome metacercariae of clams sampled from the field. This was justified as these two species have been deemed ecologically similar and accurately distinguishing them requires molecular markers (Babirat et al. 2004). However, very few species share the exact same niche and different species of parasite, even phylogenetically closely related ones, have been shown to have significantly different effects on the same host Discussion 71

(MacLeod & Poulin 2015). Clams may be subjected to mixed species infections or in some areas infections may be dominated by one species, as observed at the Otakou sand flats (pers. obs. T. Leung). In the current study, an experimental infection with C. australis cercariae revealed negative effects on the growth and body condition of clams. A similar experiment using Acanthoparyphium spp. cercariae would be useful to investigate the impact of the other echinostome parasite commonly infecting A. stutchburyi. This would provide a more global picture of the impact of parasitism on clams.

Combining experimental studies in the laboratory with field surveys of wild populations allows the validation of laboratory results with real-world observations. Additionally, complementary studies may allow identification of possible mechanisms driving in situ observations. Further in situ observations over multiple seasons and years would allow for a greater understanding of host-parasite interactions, in the context of a commercial harvest. Running the caging experiment for an additional four-month period from December 2014 to April 2015 and over multiple years may provide greater insights into the fluctuation of parasite levels over time in Otago. In future studies, the addition of sample sites and cages at the upper and lower intertidal zones may allow for a greater understanding of small-scale spatial variation within the system. Additional sampling of multiple populations in various locations and with differing harvest methods, harvest management and harvesting intensity, would allow for a more comprehensive assessment of the effects of commercial harvesting.

Lastly, as parasites have been proven to affect aspects of the physiology and behaviour of clams (Mouritsen & Poulin 2003c, Tompkins et al. 2004, Leung & Poulin 2007a), the energy budget of the parasite and its interaction with the energy budget of the clam should be considered. In addition, parasite infection should be incorporated into future assessments of community structure and models of ecosystem health (Costanza & Mageau 1999, Mouritsen & Poulin 2002, Hudson et al. 2006, Wood et al. 2007).

4.4 Conclusion The experimental and observational studies carried out in the current study emphasise the importance of considering the role of parasitism on host survival, behaviour and other ecosystem dynamics. On average, individual A. stutchburyi harboured 36% more echinostome parasites in areas affected by a commercial harvest than corresponding Discussion 72 unharvested areas. Although in situ the body condition of clams was observed to increase with parasite load, this could not be attributed to parasite infection due to uncontrolled variation in environmental characteristics. Infection of clams with the echinostome C. australis in controlled laboratory settings found the growth and body condition of clams to be negatively affected. Light infections of the echinostome C. australis also appeared to stimulate foot growth of clams. However, as infection levels increased, negative effects on foot size became apparent. If the level of parasite infections is higher within harvested areas, and parasites have the ability to affect the health of clams and the surrounding ecosystem, harvesters may be deleteriously affecting their resource by constantly removing biomass. By ensuring sufficient time between harvests to allow stocks to repopulate, clam populations may be healthier and retain their resilience.

References

References 74

Allison, F.R. (1979) Life cycle of Curtuteria australis n.sp. (Digenea: Echinostomatidae: Himasthlinae), intestinal parasite of the South Island pied oystercatcher. New Zealand Journal of Zoology 6:13–20 Anderson, D.R., Burnham, K.P. (2002) Avoiding pitfalls when using information-theoretic methods. The Journal of Wildlife Management 66:912–918 Arneberg, P. (2002) Host population density and body mass as determinants of species richness in parasite communities: comparative analyses of directly transmitted nematodes of mammals. Ecography 25:88–94 Arneberg, P., Skorping, A., Grenfell, B., Read, A.F. (1998) Host densities as determinants of abundance in parasite communities. Proceedings: Biological Sciences 265:1283–1289 Babirat, C., Mouritsen, K.N., Poulin, R. (2004) Equal partnership: two trematode species, not one, manipulate the burrowing behaviour of the New Zealand cockle, Austrovenus stutchburyi. Journal of Helminthology 78:195–199 Bates, D., Maechler, M., Bolker, B., Walker, S. (2014) Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software arXiv:1406.5823 Beentjes, M.P., Williams, B.G. (1986) Endogenous circatidal rhythmicity in the New Zealand cockle Chione stutchburyi (Bivalvia, Veneridae). Marine Behaviour and Physiology 12:171–180 Belton, R. (2012) Clam harvesting impact experiment in Otago Harbour. Progress report, p 3. Bemmelen, J.M. Van (1890) Über die Bestimmung des Wassers, des Humus, des Schwefels, der in den colloïdalen Silikaten gebundenen Kieselsäure, des Mangans u.s.w. im Ackerboden. Die Landwirthschaftlichen Versuchs-Stationen 37:279–290 Blackwell, R.G. (1984) Aspects of the population dynamics of Chione stutchburyi in Ohewa Harbour, Bay of Plenty, New Zealand. Ph.D. thesis, University of Auckland Botsford, L.W., Castilla, J.C., Peterson, C.H. (1997) The management of fisheries and marine ecosystems. Science 277:509 – 515 Bourgoin, A., Guillou, M. (1994) Arm regeneration in two populations of Acrocnida brachiata (Montagu) (Echinodermata: Ophiuroidea) in Douarnenez Bay, (Brittany: France): an ecological significance. Journal of Experimental Marine Biology and Ecology 184:123–139 Breen, P.A., Carbines, G.C., Kendrick, T.H. (1999) Stock assessment of cockles in Papanui and Waitati Inlets, Otago Harbour and Purakanui, Otago. Report to the Ministry of Fisheries, p 40. References 75

Cameron, T. (1997) Aspects of growth and condition in Austrovenus stutchburyi (Finlay 1927) (Bivalvia: Veneridae) at Waitati Inlet: influence of shore height and distance from mouth. M.Sc. thesis, University of Otago Chappell, L.H. (1993) Physiology and nutrition. In: Cox F.E.G. (ed.) Modern parasitology - a textbook of parasitology. Blackwell Science, Oxford, p 102 – 192 Chilton, C. (1905) On the occurrence of a species of cercaria in the cockle Chione stutchburyi. Transactions of the New Zealand Institute 37:322 – 325 Colenso, W. (1880) On the vegetable food of the ancient New Zealanders before Cook’s visit, New Edition. Kiwi Publishers, Christchurch Combes, C. (1991) Ethological aspects of parasite transmission. The American Naturalist 138:866–880 Cone, S. (1989) The need to reconsider the use of condition indices in fishery science. Transactions of the American Fisheries Society 118:510 – 514 Costanza, R., Mageau, M. (1999) What is a healthy ecosystem? Aquatic Ecology 33:105–115 Coughlan, J., Ansell, A.D. (1964) A direct method for determining the pumping rate of siphonate bivalves. ICES Journal of Marine Science 29:205–213 Coutteau, P., Cure, K., Sorgeloos, P. (1994) Effect of algal ration on feeding and growth of juvenile manila clam Tapes philippinarum (Adam and Reeve). Journal of Shellfish Research 13:47–55 Coutts, P.J.F. (1974) Growth characteristics of the bivalve Chione stutchburyi. Journal of Marine and Freshwater Research 8:333–339 Dame, R.F. (1993) The role of bivalve filter feeder material fluxes in estuarine ecosystems. In: Dame R.F. (ed.) Bivalve filter feeders in estuarine and coastal processes, Vol. 3. Springer-Verlag, Berlin Heidelberg, p 245 – 269 de Montaudouin, X. (1996) Factors involved in growth plasticity of cockles Cerastoderma edule (L.), identified by field survey and transplant experiments. Journal of Sea Research 36:251–265 de Montaudouin, X., Binias, C., Lassalle, G. (2012) Assessing parasite community structure in cockles Cerastoderma edule at various spatio-temporal scales. Estuarine, Coastal and Shelf Science 110:54–60 de Montaudouin, X., Wegeberg, A.M., Jensen, K.T., Sauriau, P.G. (1998) Infection characteristics of Himasthla elongata cercariae in cockles as a function of water current. Diseases of Aquatic Organisms 34:63–70 References 76

Dobbinson, S.J., Barker, M.F., Jillett, J.B. (1989) Experimental shore level transplantation of the New Zealand cockle Chione stutchburyi. Journal of Shellfish Research 8:197 – 212 Edwards, J.S. (1972) Limb loss and regeneration in two crabs: the king crab Paralithodes camtschatica and the tanner crab Chionoecetes bairdi. Acta Zoologica 53:105 – 112 Erasmus, D.A. (1958) Studies on the morphology, biology and development of a strigeid cercaria (cercaria X Baylis 1930). Parasitology 48:312–335 Feely, R.A., Doney, S.C., Cooley, S.R. (2009) Ocean acidification, present conditions and future changes in a high-CO2 world. Oceanography 22:36–47 Flach, E.C. (1996) The influence of the cockle, Cerastoderma edule, on the macrozoobenthic community of tidal flats in the Wadden Sea. Marine Ecology 17:87–98 Fredensborg, B.L., Mouritsen, K.N., Poulin, R. (2004) Intensity-dependent mortality of Paracalliope novizealandiae (Amphipoda: Crustacea) infected by a trematode: experimental infections and field observations. Journal of Experimental Marine Biology and Ecology 311:253–265 Fredensborg, B.L., Mouritsen, K.N., Poulin, R. (2005) Impact of trematodes on host survival and population density in the intertidal gastropod Zeacumantus subcarinatus. Marine Ecology Progress Series 290:109–117 Gam, M., de Montaudouin, X., Bazairi, H. (2009) Do trematode parasites affect cockle (Cerastoderma edule) secondary production and elimination? Journal of the Marine Biological Association of the United Kingdom 89:1395 Grizzle, R.E., Langan, R., Howell, W.H. (1992) Growth responses of suspension-feeding bivalve molluscs to changes in water flow: differences between siphonate and nonsiphonate taxa. Journal of Experimental Marine Biology and Ecology 162:213–228 Guillard, R.R., Ryther, J.H. (1962) Studies of marine planktonic diatoms. I. Cyclotella nana Hustedt, and Detonula confervacea (Cleve) Gran. Canadian Journal of Microbiology 8:229 – 239 Hall, S.J., Raffaelli, D., Turrell, W.R. (1990) Predator-caging experiments in marine systems: a reexamination of their value. The American Naturalist 136:657–672 Harvell, C.D., Kim, K., Burkholder, J.M., Colwell, R.R., Epstein, P.R., Grimes, D.J., Hofmann, E., Lipp, E.K., Osterhaus, A.D.M.E., Overstreet, R.M., Porter, J.W., Smith, G.W., Vasta, G.R. (1999) Emerging marine diseases - climate links and anthropogenic factors. Science 285:1505–1510 References 77

Harvell, C.D., Mitchell, C.E., Ward, J.R., Altizer, S., Dobson, A.P., Ostfeld, R.S., Samuel, M.D. (2002) Climate warming and disease risks for terrestrial and marine biota. Science 296:2158–2162 Heggie, K. (2008) Nutrient loading and bivalves: temporal and spatial variability in stable isotope composition and growth rates among estuaries with different nitrogen loads. M.Sc. thesis, University of Otago Hepburn, C.D., Vanderburg, P.H., Jackson, A., Flack, B. (2010) Ki uta ki tai: from the mountains to the sea. Holistic approaches to customary fisheries management. In: Te Rito J., Healy S.M. (eds.) 4th International traditional knowledge conference 2010. Knowledge exchange programme of Nga Pae o to Maramatanga, Auckland, p 142–148 Hudson, P.J., Dobson, A.P., Lafferty, K.D. (2006) Is a healthy ecosystem one that is rich in parasites? Trends in Ecology and Evolution 21:381–5 Irwin, C. (1999) The effects of harvesting on the reproductive and population biology of the New Zealand littleneck clam (Austrovenus stutchburyi) in Waitati Inlet. M.Sc. thesis, University of Otago Irwin, C. (2004) The impacts of harvesting and the sustainability of a New Zealand littleneck clam (Austrovenus stutchburyi) fishery in Papanui and Waitati Inlets, New Zealand. Ph.D. thesis, University of Otago Jackson, J.B., Kirby, M.X., Berger, W.H., Bjorndal, K., Botsford, L.W., Bourque, B.J., Bradbury, R.H., Cooke, R., Erlandson, J., Estes, J.A., Hughes, T.P., Kidwell, S., Lange, C.B., Lenihan, H.S., Pandolfi, J.M., Peterson, C.H., Steneck, R.S., Tegner, M.J., Warner, R.R. (2001) Historical overfishing and the recent collapse of coastal ecosystems. Science 293:629 – 637 Jakob, E.M., Marshall, S.D., Uetz, G.W. (1996) Estimating fitness: a comparison of body condition indices. Oikos 77:61–67 Jensen, K.T. (1992) Dynamics and growth of the cockle, Cerastoderma edule, on an intertidal mud-flat in the Danish Wadden Sea: effects of submersion time and density. Netherlands Journal of Sea Research 28:335–345 Jensen, K.T., Castro, N.F., Bachelet, G. (1999) Infectivity of Himasthla spp. (Trematoda) in cockle (Cerastoderma edule) spat. Journal of the Marine Biological Association 79:265 – 271 Jiang, W., Goodwin, E., Stewart, B. (2011) Stock assessment of clams (Austrovenus stutchburyi) in Waitati and Papanui Inlets, Otago, 2010 - 2011. References 78

Johnson, M.B., Lafferty, K.D., Oosterhout, C. van, Cable, J. (2011) Parasite transmission in social interacting hosts: monogenean epidemics in guppies. PLoS ONE 6:1–6 Jones, C.G., Lawton, J.H., Shachak, M. (1997) Positive and negative effects of organisms as physical ecosystem engineers. Ecology 78:1946–1957 Kainamu, A.A. (2010) The fishery trend and feeding capacity of the New Zealand Littleneck Clam, Austrovenus stutchburyi, in a southern New Zealand inlet. M.Sc. thesis, University of Otago Kautsky, N. (1982) Growth and size structure in a Baltic Mytilus edulis population. Marine Biology 68:117 – 133 Kearn, G.C. (1998) Parasitism and the platyhelminths, 1st ed. Chapman & Hall, London Keller, M.D., Bellows, W.K., Guillard, R.L. (1988) Microwave treatment for sterilization of phytoplankton culture media. Journal of Experimental Marine Biology and Ecology 117:279–283 Koprivnikar, J., Lim, D., Fu, C., Brack, S.H.M. (2010) Effects of temperature, salinity, and pH on the survival and activity of marine cercariae. Parasitology Research 106:1167– 1177 Koprivnikar, J., Poulin, R. (2009) Interspecific and intraspecific variation in cercariae release. The Journal of Parasitology 95:14–19 Kuris, A.M., Hechinger, R.F., Shaw, J.C., Whitney, K.L., Aguirre-Macedo, L., Boch, C., Dobson, A.P., Dunham, E.J., Fredensborg, B.L., Huspeni, T.C., Lorda, J., Mababa, L., Mancini, F.T., Mora, A.B., Pickering, M., Talhouk, N.L., Torchin, M.E., Lafferty, K.D. (2008) Ecosystem energetic implications of parasite and free-living biomass in three estuaries. Nature 454:515–518 Kuris, A.M., Lafferty, K.D. (1992) Modelling crustacean fisheries: effects of parasites on management strategies. Canadian Journal of Fisheries and Aquatic Sciences 49:327– 336 Lafferty, K.D. (1999) The evolution of trophic transmission. Parasitology Today 15:111–115 Lafferty, K.D. (2004) Fishing for lobsters indirectly increases epidemics in sea urchins. Ecological Applications 14:1566–1573 Lafferty, K.D. (2008) Ecosystem consequences of fish parasites. Journal of Fish Biology 73:2083–2093 Lafferty, K.D. (2012) Biodiversity loss decreases parasite diversity: theory and patterns. Philosophical Transactions of the Royal Society B: Biological Sciences 367:2814–2827 References 79

Lafferty, K.D., Allesina, S., Arim, M., Briggs, C.J., Leo, G. De, Dobson, A.P., Dunne, J.A., Johnson, P.T.J., Kuris, A.M., Marcogliese, D.J., Martinez, N.D., Memmott, J., Marquet, P.A., McLaughlin, J.P., Mordecai, E. a., Pascual, M., Poulin, R., Thieltges, D.W. (2008) Parasites in food webs: the ultimate missing links. Ecology Letters 11:533–546 Lagrue, C., Poulin, R. (2015) Measuring fish body condition with or without parasites: does it matter? Journal of Fish Biology DOI:10.1111/jfb.12749 Laing, I., Utting, S.D., Kilada, R.W.S. (1987) Interactive effect of diet and temperature on the growth of juvenile clams. Journal of Experimental Marine Biology and Ecology 113:23– 38 Larcombe, M.F. (1971) The ecology, population dynamics and energetics of some soft shore molluscs. University of Auckland Lauckner, G. (1983) Diseases of Mollusca: Bivalvia. In: Kinne O. (ed.) Diseases of marine animals, Volume 2. Biologische Anstalt Helgoland, Hamburg, p 477 – 961 Lauckner, G. (1984) Impact of trematode parasitism on the fauna of a North Sea tidal flat. Helgolander Meeresunter-suchungen 37:185–199 Lauckner, G. (1987) Ecological effects of larval trematode infestation on littoral marine invertebrate populations. International Journal for Parasitology 17:391–398 Leung, T.L.F. (2008) Interspecific and intraspecific interactions of trematodes parasitising the New Zealand cockle Austrovenus stutchburyi. Ph.D. thesis, University of Otago Leung, T.L.F., Donald, K.M., Keeney, D.B., Koehler, A. V, Peoples, R.C., Poulin, R. (2009a) Trematode parasites of Otago Harbour (New Zealand) soft-sediment intertidal ecosystems: life cycles, ecological roles and DNA barcodes. New Zealand Journal of Marine and Freshwater Research 43:857 – 865 Leung, T.L.F., Keeney, D.B., Poulin, R. (2009b) Cryptic species complexes in manipulative echinostomatid trematodes: when two become six. Parasitology 136:241–52 Leung, T.L.F., Keeney, D.B., Poulin, R. (2010) Genetics, intensity-dependence, and host manipulation in the trematode Curtuteria australis: following the strategies of others? Oikos 119:393–400 Leung, T.L.F., Poulin, R. (2007a) Interactions between parasites of the cockle Austrovenus stutchburyi: hitch-hikers, resident-cleaners, and habitat-facilitators. Parasitology 134:247– 255 Leung, T.L.F., Poulin, R. (2007b) Recruitment rate of gymnophallid metacercariae in the New Zealand cockle Austrovenus stutchburyi: an experimental test of the hitch-hiking hypothesis. Parasitology Research 101:281– 287 References 80

Leung, T.L.F., Poulin, R. (2008) Size-dependent pattern of metacercariae accumulation in Macomona liliana: the threshold for infection in a dead-end host. Parasitology Research 104:177–180 Leung, T.L.F., Poulin, R. (2011) Intra-host competition between co-infecting digeneans within a bivalve second intermediate host: dominance by priority-effect or taking advantage of others? International Journal for Parasitology 41:449–54 Leung, T.L.F., Poulin, R., Keeney, D.B. (2009c) Accumulation of diverse parasite genotypes within the bivalve second intermediate host of the digenean Gymnophallus sp. International Journal for Parasitology 39:327–31 Lindsay, S.M. (2010) Frequency of injury and the ecology of regeneration in marine benthic invertebrates. Integrative and Comparative Biology 50:479–493 Ludwig, D., Hilborn, R., Walters, C. (1993) Uncertainty, resource exploitation, and conservation: lessons from history. Science 260:17–36 MacLeod, C.D., Poulin, R. (2015) The combined effects of ocean acidification and parasitic infection alter the calcifying ability of a marine gastropod. Manuscript in preparation Macrellis, H.M. (2001) The littleneck clams that couldn’t: the New Zealand Littleneck Clam (Austrovenus stutchburyi) population in Doubtful Sound and the role of the Manapouri Power Plant in influencing clam distribution. M.Sc. thesis, University of Otago Marcogliese, D.J. (2001) Implications of climate change for parasitism of animals in the aquatic environment. Canadian Journal of Zoology 79:1331 – 1352 Marsden, I.D. (2004) Effects of reduced salinity and seston availability on growth of the New Zealand littleneck clam Austrovenus stutchburyi. Marine Ecology Progress Series 266:157–171 Marsden, I.D., Adkins, S.C. (2010) Current status of cockle bed restoration in New Zealand. Aquaculture International 18:83–97 Martin, N.D. (1984) Chione stutchburyi population responses to exploitation. M.Sc. thesis, University of Auckland Martin, W.E., Adams, J.E. (1961) Life cycle of Acanthoparyphium spinulosum Johnston, 1917 (Echinostomatidae: Trematoda). The Journal of Parasitology 47:777–782 Martorelli, S.R., Poulin, R., Mouritsen, K.N. (2006) A new cercaria and metacercaria of Acanthoparyphium (Echinostomatidae) found in an intertidal snail Zeacumantus subcarinatus (Batillaridae) from New Zealand. Parasitology International 55:163–167 McCullagh, P., Nelder, J.A. (1989) Generalized linear models, 2nd edition. Chapman & Hall, London References 81

McDonald, S. (1999) A disturbance in the community: lateral migration of Austrovenus stutchburyi. Post-graduate diploma project, Otago University McKinnon, J. (1996) Studies of the age, growth and shell increment patterns in the New Zealand cockle (Austrovenus stutchburyi). M.Sc. thesis, University of Otago Ministry of Fisheries (2014) Cockles (COC). Ministry of Fisheries, Wellington, p 9 Mook, D.H., Hoskin, C.M. (1982) Organic determinations by ignition: caution advised. Estuarine, Coastal and Shelf Science 15:697–699 Mooring, M.S., Hart, B.L. (1992) Animal grouping for protection from parasites: selfish herd and encounter-dilution effects. Behaviour 123:173–193 Morton, J. (2004) Seashore ecology of New Zealand and the Pacific. Bateman, Auckland Mouritsen, K.N. (2002a) The parasite-induced surfacing behaviour in the cockle Austrovenus stutchburyi: a test of an alternative hypothesis and identification of potential mechanisms. Parasitology 124:521–528 Mouritsen, K.N. (2002b) The Hydrobia ulvae-Maritrema subdolum association: influence of temperature, salinity, light, water-pressure and secondary host exudates on cercarial emergence and longevity. Journal of Helminthology 76:341–347 Mouritsen, K.N., McKechnie, S., Meenken, E., Toynbee, J.L., Poulin, R. (2003) Spatial heterogeneity in parasite loads in the New Zealand cockle: the importance of host condition and density. Journal of the Marine Biological Association of the UK 83:307– 310 Mouritsen, K.N., Poulin, R. (2002) Parasitism, community structure and biodiversity in intertidal ecosystems. Parasitology 124:101–117 Mouritsen, K.N., Poulin, R. (2003a) The mud flat anemone-cockle association: mutualism in the intertidal zone? Oceologia 135:131–137 Mouritsen, K.N., Poulin, R. (2003b) Parasite-induced trophic facilitation exploited by a non- host predator: a manipulator’s nightmare. International Journal for Parasitology 33:1043–1050 Mouritsen, K.N., Poulin, R. (2003c) The risk of being at the top: foot-cropping in the New Zealand cockle Austrovenus stutchburyi. Journal of the Marine Biological Association of the UK 83:497–498 Mouritsen, K.N., Poulin, R. (2005) Parasites boosts biodiversity and changes animal community structure by trait-mediated indirect effects. Oikos 108:340–350 References 82

Myers, R.A., Baum, J.K., Shepherd, T.D., Powers, S.P., Peterson, C.H. (2007) Cascading effects of the loss of apex predatory sharks from a costal ocean. Science 315:1846 – 1849 Newell, R. (2004) Ecosystem influences of natural and cultivated populations of suspension- feeding bivalve molluscs: a review. Journal of Shellfish Research 23:51 – 61 Norris, K. (1999) A trade-off between energy intake and exposure to parasites in oystercatchers feeding on a bivalve mollusc. Proceedings: Biological Sciences 266:1703–1709 Onley, D. (2010) Report on monitoring of birds in relation to clam harvesting in Otago Harbour, December 2008 – March 2010. Report to Southern Clams Ltd, p 40 Onley, D. (2013) Report on monitoring of birds in relation to clam harvesting in Otago Harbour, December 2008 – August 2012. Report to Southern Clams Ltd, p 49 Orr, J.C., Fabry, V.J., Aumont, O., Bopp, L., Doney, S.C., Feely, R. a, Gnanadesikan, A., Gruber, N., Ishida, A., Joos, F., Key, R.M., Lindsay, K., Maier-Reimer, E., Matear, R., Monfray, P., Mouchet, A., Najjar, R.G., Plattner, G.-K., Rodgers, K.B., Sabine, C.L., Sarmiento, J.L., Schlitzer, R., Slater, R.D., Totterdell, I.J., Weirig, M.-F., Yamanaka, Y., Yool, A. (2005) Anthropogenic ocean acidification over the twenty-first century and its impact on calcifying organisms. Nature 437:681–686 Pan, Z., Lin, D.Y. (2005) Goodness-of-Fit methods for Generalized Linear Mixed Models. Biometrics 61:1000–1009 Paul-Pont, I., de Montaudouin, X., Gonzalez, P., Soudant, P., Baudrimont, M. (2010) How life history contributes to stress response in the Manila clam Ruditapes philippinarum. Environmental Science and Pollution Research International 17:987– 998 Pawson, M. (2004) The cockle Austrovenus stutchburyi and chlorophyll depletion in a southern New Zealand inlet. M.Sc. thesis, University of Otago Peterson, C.H. (1982) The importance of predation and intra- and interspecific competition in the population biology of two infaunal suspension-feeding bivalves, Protothaca staminea and Chione undatella. Ecological Monographs 52:437–475 Peterson, C.H., Beal, B.F. (1989) Bivalve growth and higher order interactions: importance of density, site, and time. Ecology 70:1390–1404 Poulin, R. (1994) Meta-analysis of parasite-induced behavioural changes. Animal Behaviour 48:137 – 146 References 83

Poulin, R. (2006) Global warming and temperature-mediated increases in cercarial emergence in trematode parasites. Parasitology 132:143 – 151 Poulin, R., Mouritsen, K.N. (2006) Climate change, parasitism and the structure of intertidal ecosystems. Journal of Helminthology 80:183–191 Poulin, R., Steeper, M.J., Miller, A.A. (2000) Non-random patterns of host use by the different parasite species exploiting a cockle population. Parasitology 121:289–295 Poulin, R., Thomas, F. (1999) Phenotypic variability induced by parasites: extent and evolutionary implications. Parasitology Today 15:28 – 32 Powell, A.W. (1979) New Zealand mollusca: marine, land, and freshwater shells. Collins, Auckland Power, M.E., Tilman, D., Estes, J.A., Menge, B.A., Bond, W.J., Mills, S., Daily, G., Castilla, J.C., Lubchenco, J., Paine, R.T. (1996) Challenges in the quest for keystones. BioScience 46:609–620 Pridmore, R.D., Thrush, S.F., Hewitt, J.E., Roper, D.S. (1990) Macrobenthic community composition of six intertidal sandflats in Manukau Harbour, New Zealand. New Zealand Journal of Marine and Freshwater Research 24:81–96 Purdie, J.M., Smith, A.M. (1994) Heavy metals and hydrocarbons in Otago Harbour sediments. Consultants Report to the Otago Regional Council, p 51 R Development Core Team (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Austria Reise, K. (1985) Tidal flat ecology: an experimental approach to species interactions. Springer-Verlag, Berlin Ricciardi, A., Bourget, E. (1998) Weight-to-weight conversion factors for marine benthic macroinvertebrates. Marine Ecology Progress Series 163:245–251 Riisgard, H.U. (2001) On measurement of filtration rates in bivalves — the stony road to reliable data: review and interpretation. Marine Ecology Progress Series 211:275–291 Ryba, S.A., Burgess, R.M. (2002) Effects of sample preparation on the measurement of organic carbon, hydrogen, nitrogen, sulfur, and oxygen concentrations in marine sediments. Chemosphere 48:139–147 Santoro, M., Mattiucci, S., Work, T., Cimmaruta, R., Nardi, V., Cipriani, P., Bellisario, B., Nascetti, G. (2013) Parasitic infection by larval helminths in Antarctic fishes: pathological changes and impact on the host body condition index. Diseases of Aquatic Organisms 105:139–148 References 84

Scheffer, M., Carpenter, S., Young, B. (2005) Cascading effects of overfishing marine systems. Trends in Ecology and Evolution 20:579–581 Schmechel, F. (2001) Potential impacts of mechanical cockle harvesting on shorebirds in Golden and Tasman Bays, New Zealand. Report to the Department of Conservation, Wellington, p 52 Singer, J.K., Anderson, J.B., Ledbetter, M.T., McCave, I.N., Jones, K.P.N., Wright, R. (1988) An assessment of analytical techniques for the size analysis of fine-grained sediments. Journal of Sedimentary Petrology 58:534–543 Single, M., Bell, R., McComb, P. (2010) Physical coastal environment of Otago Harbour and offshore: assessment of effects of proposed dredging by Port Otago Ltd. Report to Port Otago Ltd, Dunedin, p 75 Smith, A.M., Wood, A.C.L., Liddy, M.F.A., Shears, A.E., Fraser, C.I. (2010) Human impacts in an urban port: the carbonate budget, Otago Harbour, New Zealand. Estuarine, Coastal and Shelf Science 90:73–79 Sonnenholzner, J., Lafferty, K.D., Ladah, L.B. (2011) Food webs and fishing affect parasitism of the sea urchin Eucidaris galapagensis in the Galapagos. Ecology 92:2276– 2284 Sousa, W.P. (1991) Can models of soft-sediment community structure be complete without parasites? American Zoologist 31:821–830 Stephenson, R. (1981) Aspects of the energetics of the cockle Chione (Austrovenus) stutchburyi in the Avon-Heathcote Estuary, Christchurch, New Zealand. Ph.D. thesis, University of Canterbury Stephenson, R.L., Chanley, P.E. (1979) Larval development of the cockle Chione stutchburyi (Bivalvia: Veneridae) reared in the laboratory. New Zealand Journal of Zoology 6:553– 559 Stergiou, K.I. (2002) Overfishing, tropicalization of fish stocks, uncertainty and ecosystem management: resharpening Ockham’s razor. Fisheries Research 55:1–9 Stewart, B. (2008a) Stock assessment of clams (Austrovenus stutchburyi) in Waitati Inlet, Otago, 2007. Report for Ministry of Fisheries, p 24. Stewart, B. (2008b) Clam (Austrovenus stutchburyi) resource and habitat survey in Otago Harbour (COC3), Otago, 2008. Dunedin. Report for Southern Clams Ltd, p 55. Stewart, B. (2009) Investigations into the feasibility of commercial harvest of clams (Austrovenus stutchburyi) in Otago Harbour (COC3), Otago. Report for Ministry of Fisheries, p 25. References 85

Stewart, B. (2010) Investigations into the effects of commercial harvest of clams (Austrovenus stutchburyi) on infauna and substrate in Otago Harbour (COC3), Otago: report on phase I harvesting. Report for Ministry of Fisheries, p 63. Stewart, B. (2013) Investigations into the effects of commercial harvest of clams (Austrovenus stutchburyi) in Otago Harbour, (COC3), Otago: report on phase II harvesting, 2012. Report for Ministry of Fisheries, p 66 Stromgren, T., Cary, C. (1984) Growth in length of Mytilus edulis L. fed on different algal diets. Journal of Experimental Marine Biology and Ecology 76:23–34 Studer, A., Poulin, R. (2012) Seasonal dynamics in an intertidal mudflat: the case of a complex trematode life cycle. Marine Ecology Progress Series 455:79–93 Studer, A., Widmann, M., Poulin, R., Krkosek, M. (2013) Large scale patterns of trematode parasitism in a bivalve host: no evidence for a latitudinal gradient in infection levels. Marine Ecology Progress Series 491:125–135 Stumbo, A.D., James, C.T., Goater, C.P., Wisenden, B.D. (2012) Shoaling as an antiparasite defence in minnows (Pimephales promelas) exposed to trematode cercariae. Journal of Animal Ecology 81:1319–1326 Tallis, H.M., Wing, S.R., Frew, R.D. (2004) Historical evidence for habitat conservation and local population decline in a New Zealand fiord. Ecological Applications 14:546–554 Thomas, F., Poulin, R. (1998) Manipulation of a mollusc by a trophically transmitted parasite: convergent evolution or phylogenetic inheritance? Parasitology 116:431–436 Thomas, F., Renaud, F., de Meeus, T., Poulin, R. (1998) Manipulation of host behaviour by parasites: ecosystem engineering in the intertidal zone? Proceedings: Biological Sciences 265:1091–1096 Tompkins, D.M., Mouritsen, K.N., Poulin, R. (2004) Parasite-induced surfacing in the cockle Austrovenus stutchburyi: adaptation or not? Journal of Evolutionary Biology 17:247– 256 Vernberg, W.B., Vernberg, F.J. (1971) Respiratory metabolism of a trematode metacercaria and its host. In: Cheng T.C. (ed.) Aspects of the Biology of Symbiosis. University Park Press, Baltimore, p 91–102. Voice, A.J. (1975) The invertebrate ecology and the Chione stutchburyi population on the intertidal sand flats at Aramoana, Otago Harbour, New Zealand. B.Sc. (Hons) project, University of Otago References 86

Walne, P.R. (1972) The influence of current speed, body size and water temperature on the filtration rate of five species of bivalve. Journal of the Marine Biological Association of the UK 52:345–374 Waselkov, G.A. (1987) Shellfish gathering and shell midden archaeology. Advances in Archaeological Method and Theory 10:93–210 Wegeberg, A.M., Jensen, K.T. (1999) Reduced survivorship of Himasthla (Trematoda, Digenea)-infected cockles (Cerastoderma edule) exposed to oxygen depletion. Journal of Sea Research 42:325–331 Wegeberg, A.M., Jensen, K.T. (2003) In situ growth of juvenile cockles, Cerastoderma edule, experimentally infected with larval trematodes (Himasthla interrupta). Journal of Sea Research 50:37–43 Wegeberg, A.M., de Montaudouin, X., Jensen, K.T. (1999) Effect of intermediate host size (Cerastoderma edule) on infectivity of cercariae of three Himasthla species (Echinostomatidae, Trematoda). Journal of Experimental Marine Biology and Ecology 238:259–269 Whitlatch, R.B., Hines, A.H., Thrush, S.F., Hewitt, J.E., Cummings, V. (1997) Benthic faunal responses to variations in patch density and patch size of a suspension-feeding bivalve. Journal of Experimental Marine Biology and Ecology 216:171–189 Whyte, J. (1987) Biochemical composition and energy content of six species of phytoplankton used in mariculture of bivalves. Aquaculture 60:231–241 Wikfors, G.H., Patterson, G.W., Ghosh, P., Lewin, R.A., Smith, B.C., Alix, J.H. (1996) Growth of post-set oysters, Crassostrea virginica, on high-lipid strains of algal flagellates Tetraselmis spp. Aquaculture 143:411–419 Wildish, K. (1984) An initial study of the New Zealand cockle (Austrovenus stutchburyi) resource in Papanui and Waitati inlets. Report to the Ministry of Agriculture and Fisheries, p 8. Williams, B.G., Pilditch, C.A. (1997) The entrainment of persistent tidal rhythmicity in a filter-feeding bivalve using cycles of food availability. Journal of Biological Rhythms 12:173–181 Williams, J.R., Smith, M.D., Mackay, G. (2009) Biomass survey and stock assessment of cockles (Austrovenus stutchburyi) on Snake Bank, Whangarei Harbour, 2009. Report to the Ministry of Fisheries, Wellington, p 22. Wing, S., Irwin, C., Granger, G. (2002) Biomass survey and yield estimates for the New Zealand littleneck clam (Austrovenus stutchburyi) in Papanui and Waitati inlets, Otago References 87

during 2002. Report to the Ministry of Fisheries and Southern Clams Ltd, Dunedin, p 34. Winter, E. (1978) A review of the knowledge of suspension-feeding in Lamellibranchiate bivalves, with special reference to artificial aquaculture systems. Aquaculture 13:1 – 33 Wood, C.L., Byers, J.E., Cottingham, K.L., Altman, I., Donahue, M.J., Blakeslee, A.M.H. (2007) Parasites alter community structure. Proceedings of the National Academy of Sciences of the United States of America 104:9335–9339 Wood, C.L., Lafferty, K.D. (2014) How have fisheries affected parasite communities? Parasitology 142:134 – 144 Wood, C.L., Lafferty, K.D., Micheli, F. (2010) Fishing out marine parasites? Impacts of fishing on rates of parasitism in the ocean. Ecology Letters 13:761–775 Zar, J.H. (1999) Biostatistical analysis, 4th edition. Prentice-Hall, New Jersey

Appendix

Appendix 89

Figure A.1 Map indicating areas harvested by Southern Clams Ltd (SCL) from 2011 – 2014 in

(A) the inner Otago Harbour, (B) the outer Otago Harbour and (C) Blueskin Bay, with the treatment for each study site indicated in the legend. Coloured lines indicate the boundaries within which each individual harvest event has occurred. When an area is reharvested, a new colour is used for the harvest boundary lines therefore areas bordered by lines of different colours have been subjected to successive harvests over the three year period. Data is from SCL. Appendix 90

Figure A.2 Simulation-based model diagnostics plot for experimental caging model with negative binomial error structure and the fixed factors treatment, age and body condition. Observed and simulated frequencies of parasite load averaged for age were plotted in four plots based on the treatment and clam’s body condition. Treatment is indicated by the (C) control on the left and (H) harvest on the right. Body condition was divided into halves with the top plots containing clams with lower body condition (1) and lower plots representing clams with higher body condition (2). The similar distribution of observed and simulated values shows the model is a good representation of this data set. Appendix 91

Figure A.3 Simulation-based model diagnostics plot for density with a Gaussian error structure and fixed factor treatment. Observed and simulated frequencies of densities of clams with groupings based on harvested (H) and unharvested (C) areas. The similar distribution of observed and simulated values shows the model is a good representation of this data set.

Appendix 92

Figure A.4 Simulation-based model diagnostics plot for biomass with a Gaussian error structure and fixed factor treatment. Observed and simulated frequencies of biomass of clams with groupings based on harvested (H) and unharvested (C) areas. The similar distribution of observed and simulated values shows the model is a good representation of this data set.

Appendix 93

Figure A.5 Simulation-based model diagnostics plot for snapshot field sampling model with negative binomial error structure and the fixed factors treatment, age and body condition. Observed and simulated frequencies of parasite load averaged for age and treatment were plotted in four plots based on the clam’s condition index. Plot 1 represents the quantile of clams with the lowest condition index, plot 2 and 3 the second and third quantiles, while plot 4 shows the quantile of clams with the highest condition index. The similar distribution of observed and simulated values shows the model is a good representation of this data set.