EXECUTIVE SUMMARY

The New Zealand aquaculture industry is presently dominated by the production of Greenshell™ mussels in terms of total yield, water-space utilisation and total revenue. However, there has been recent emphasis by a number of mussel farmers in the Marlborough Sounds to amend permits and consents so that other bivalve species can be farmed. In response to this, the Ministry of Fisheries commissioned the Cawthron Institute to use available information to perform a desktop investigation into the marginal differences between the environmental interactions of a range of bivalve species to underpin stocking density guidelines.

A hazard assessment was used to identify the major environmental interactions between bivalves and the surrounding marine environment and this highlighted several major risk pathways, several of which were through the feeding and excretory behaviour of the bivalve crop. Marginal differences between the transfer of material by the different species were therefore investigated using a range of feeding models and environmental data from the Marlborough Sounds and Glenhaven Aquaculture Centre. The key result from analysis of the marginal differences between a range of bivalve species was that mussels generally appear to exhibit the highest clearance and excretion rates of the bivalves considered. Similarly, biodeposition intensity greater than 400 g/day/1000ind occurred most frequently in mussels (40%) followed by, scallops (33%), cupped oysters (29%), flat oysters (11%), and finally clams/cockles (6%).

Overall, it appears that based on the model utilised here, the substitution of mussels, specifically Perna canaliculus, with any of the other alternate species/groups proposed would not be likely to increase either the clearance of the surrounding water, the biodeposition of suspended matter or the amount of dissolved ammonia through excretion. In fact, on an equivalent numbers basis substitution with any of the alternate groups may reduce these interactions, especially where either flat oysters or clams/cockles are considered. This is a key result of this study and suggests that there is no strong evidence in terms of material processed by the different bivalves considered here to restrict the stocking density of non-mussel bivalves to substantially lower densities by comparison to the stocking densities used for mussels.

The hazard assessment also identified that farming structures can potentially lead to changes in the surrounding environment through the alteration of water flows. Scaling analyses were performed that highlight the relative differences in cross-sectional areas posed by different farming methods. The results from this analysis indicate that the present mussel farming practices occupy a greater cross- sectional area by comparison with the other methods that are presently used. Hence there is little evidence to suggest that the stocking densities of other species using different growing techniques, as described here, should be more overly restricted by comparison with present marine farming practices.

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TABLE OF CONTENTS

EXECUTIVE SUMMARY...... III 1. INTRODUCTION...... 1 1.1. Scope and objective...... 1 2. BACKGROUND INFORMATION...... 1 2.1. Potential species and culture methods...... 1 2.2. Diseases ...... 4 3. HAZARD ASSESSMENT ...... 6 4. METHODOLOGY ...... 9 4.1. Material fluxes ...... 9 4.1.1. Literature search ...... 10 4.1.2. Environmental datasets...... 11 4.1.3. Shellfish size ...... 11 4.1.4. Comparative histograms ...... 12 4.2. Attenuation of water flows ...... 12 5. RESULTS...... 13 5.1. Differences in the material fluxes using Beatrix Bay data...... 13 5.1.1. Environmental data in Beatrix Bay ...... 13 5.1.2. Clearance Rate histograms for Beatrix Bay ...... 14 5.1.3. Ammonia nitrogen excretion rate histograms for Beatrix Bay...... 17 5.2. Differences in material fluxes using Glenhaven Aquaculture Centre pond data...... 18 5.2.1. Environmental data for Glenhaven...... 18 5.2.2. Clearance rate histograms for Glenhaven...... 21 5.2.3. Total rejection rate histograms for Glenhaven...... 24 5.3. Attenuation of current flows...... 26 6. SUMMARY AND RECOMMENDATIONS ...... 28 7. REFERENCES...... 31 8. APPENDICES ...... 33

LIST OF FIGURES

Figure 1. Example of an ‘ear’ hung scallop...... 2 Figure 2. Examples of culture systems used for oysters. L-R: baskets, trays, Rotoshells...... 3 Figure 3. Influence diagram detailing the likely hazards (in a risk assessment sense) associated with the establishment of a suspended bivalve farm...... 6 Figure 4. Beatrix Bay temperature data recorded between 1994 and 2006...... 13 Figure 5. Chla data recorded for Beatrix Bay between 1994 and 2006...... 14 Figure 6. Comparative histograms showing the range and relative frequency of predicted clearance rates by bivalve group for Beatrix Bay...... 15 Figure 7. Comparative histograms showing the range and relative frequency of predicted ammonia nitrogen excretion rates by bivalve group for Beatrix Bay...... 18 Figure 8. Daily temperature data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006...... 19

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Figure 9. Daily chlorophyll a data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006...... 20 Figure 10. Daily total particulate matter data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006...... 21 Figure 11. Comparative histograms showing the range and relative frequency of predicted clearance rates by bivalve group for the Glenhaven Aquaculture Centre ponds...... 22 Figure 12. Comparative clearance rate histograms for P. canaliculus and P. novaezelandiae models from similar NZ studies by Teaioro (1999) and Keeley (2001) applied to the Glenhaven Aquaculture Centre pond data...... 23 Figure 13. Comparative histograms of C. gigas CRs by population and individual assessment methods adapted from Barille et al.(1997) and applied to the Glenhaven Aquaculture Centre pond data...... 24 Figure 14. Comparative histograms showing the range and relative frequency of predicted total rejection rates by bivalve group for the Glenhaven Aquaculture Centre ponds...... 25

LIST OF TABLES

Table 1. Threat posed by parasites and diseases to common bivalves of commercial importance in New Zealand...... 5 Table 2. Animal sizes chosen for the analysis...... 12 Table 3. Calculations for surface area presented to currents and equivalent densities of shellfish per area of seabed for theoretical shellfish culture configurations...... 27

LIST OF APPENDICES

Appendix 1. Feeding and excretion rate models used in this report...... 33

vi Cawthron Report No. 1192 October 2006

1. INTRODUCTION

1.1. Scope and objective

GreenshellTM mussels, Perna canaliculus, are currently the dominant species cultured in the New Zealand aquaculture industry. Although there are a number of operations that farm oysters, salmon and to a lesser extent paua, these operations have a considerably smaller total tonnage yield and value by comparison with the mussel industry. However, our understanding is that due to a number of factors there is an increasing desire for mussel farmers to add other bivalve species to their farming permits and consents. Regulatory authorities, including the Ministry of Fisheries (MFish) and regional councils are therefore faced with managing the culture of these other species often in the absence of robust information on the effects of farming these species.

MFish therefore commissioned Cawthron to provide guidance on appropriate stocking densities for other bivalve species that applicants may wish to culture. Hence the objective of this study is to utilise existing information in an investigation of the potential environmental risks associated with the culture of different bivalve species. In particular, this work focuses on the extraction and generation of particulate matter and the attenuation of water flows around farming structures.

Section 2 of this report contains background information on the major bivalve species either presently being cultured in New Zealand, or which are being considered for culture in New Zealand on a commercial scale. This section also contains information about the potential disease threats to each species. Section 3 contains a general hazard assessment for bivalve farming activities including the identification of the major risk pathways. Section 4 describes the analytical methods used in the study and results are presented in Section 5, followed by a summary in Section 6.

2. BACKGROUND INFORMATION

2.1. Potential species and culture methods

A large variety of bivalve species are cultured worldwide, but only those most relevant to the New Zealand situation are considered here. These species include some animals that are presently on the 2004 MFish gazetted aquaculture species list: ƒ Mussel (GreenshellTM, Perna canaliculus and blue, Mytilus galloprovincialis) ƒ Scallop (Pecten novaezealandiae) ƒ Oyster (Pacific, Crassostrea gigas and flat, Tiostrea chilensis)

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ƒ Cockle (Austrovenus stutchburyi) Some species not presently on the MFish gazetted list will also be considered, as follows: ƒ Geoduck (Panopea zelandica and Panopea smithae) ƒ Ribbed mussel (Aulacomya maoriana) ƒ Toheroa (Paphies ventricosa) ƒ Tuatua (Paphies subtriangulata)

The methods currently used to farm the GreenshellTM mussel, and potentially the blue mussel are well documented and in common use throughout New Zealand (i.e. the longline/dropper system). Any further development to these growing techniques is likely to involve a variation on the present methodologies. Ribbed mussels are presently not considered to be a high unit price product, but are thought to have indirect economic value to Maori for cultural reasons. The most obvious method for farming these animals would be the longline system presently used for Greenshell™ mussels.

Scallops are extensively farmed in many regions of the world; particularly in South-east Asia, and are generally farmed in lantern cages, stacked trays or “ear” hung from ropes. Ear hanging is where a hole is drilled through the shell near the hinge (see Figure 1) and a tie is put through it, which is then woven through the supporting dropper. The scallops can be placed every 12 to 15cm down the dropper. Generally this growing method is not used in high energy areas.

“Ear” hole drilled here

Figure 1. Example of an ‘ear’ hung scallop.

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An alternative method of scallop culture is using stacked trays or lantern cages. These structures can be suspended from a buoy or backbone, or inserted into a frame which is positioned on the seabed. However cages with seabed supports are prone to increased predation pressure. Trays are generally suspended in a manner that leaves a space between each tray. By contrast lantern cages tend to consist of a net tube woven with 6–12 ply polyethylene thread, separated into 7–8 chambers by plastic discs of 30 cm diameter. A space of 15 cm is often left between every two discs. The number of chambers deployed is dependent upon on the depth of the water at the site. Cages are generally about 1.4–1.5 m in height although individual operators and communities often modify these themes to some extent. Cages and trays are generally only used in sheltered or semi-sheltered environments in countries where labour costs are low, as the cages require regular clearing of fouling organisms, which if left on the structures can considerably reduce crop yields.

Pacific oysters (Crassostrea gigas) are cultivated in bags, purses, trays (including Roto-shells) or sticks (generally used in inter-tidal situations). Bags, purses and trays used for oyster cultivation are generally made out of polyethylene and are suspended singly or in stacks (Figure 2).

Figure 2. Examples of culture systems used for oysters. L-R: baskets, trays, Rotoshells.

Species which bury themselves such as cockles (Austrovenus stutchburyi), geoduck (Panopea zelandica and Panopea smithae), toheroa (Paphies ventricosa), tuatua (Paphies subtriangulata) are unlikely to be cultivated in an exposed structure such as open trays. It is suggested that a container holding a form of substrate would be suspended or placed on the seabed and the grow-out stock of the burrowing species introduced to it. It is possible that the containers would be stacked; however due to the additional weight of substrate, the stacks

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would probably contain a limited number of trays (unless an alternative lighter substrate is developed), which are likely to be smaller than the oyster trays shown in Figure 2. This means that the total surface area of the sides of the array would also be reduced. Also due to the presence of a substrate, there would be no water flow through the trays, so the level of water flow attenuation per tray would be greater than for an oyster tray. However, deposition to the seabed would be less than that derived from the oyster trays as the density of animals per m2 is likely to be lower.

2.2. Diseases

Table 1 indicates cases where diseases and/or parasites have been seen or reported in the named bivalves. Empty boxes do not necessarily indicate freedom from the pathogen; rather they may reflect the paucity of studies of pathogens on some of these species. Nevertheless, New Zealand molluscs generally have a low pathogen burden and hence the mollusc aquaculture sector in New Zealand is presently far less constrained by comparison with international aquaculture operations. The main exception is Bonamia, which has had a well publicised impact on the Bluff oyster fishery. Perkinsus and APX have the potential to cause losses and the ostreid herpes virus has caused shellfish mortalities in hatcheries. Digestive epithelial virosis and rickettsiae occur at high prevalences and intensities in a number of shellfish species and are associated with mortalities, but it cannot be said if they are cause or consequence of mortality/morbidity. Other pathogens are of fairly minor importance.

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Table 1. Threat posed by parasites and diseases to common bivalves of commercial importance in New Zealand.

Parasites/diseases in descending order of importance

Digestive epithelial virosis virosis epithelial Digestive Spionids (Mud worms) (Mudworms) Spionids Mastigocoleus, Hyella Hyella Mastigocoleus, Rickettsiae >2 species Ostreid herpes virus Australophialus Mycoplasmosis Lichomolgus Pinnotheres Nematopsis Pseudomyicola Paravortex Wafer worms Perkinsus Epicladia Epicladia Bonamia Digenea Cliona APX

Shell borers Mytilus edulis (blue mussel) Y Y Y Y Y Y Y Y Y Y Perna canaliculus (GreenshellTM mussel) Y Y Y Y Y Y Y Y Y Y Y Y Y

Mollusc hostspecies Crassostrea gigas (Pacific oyster) Y Y Y Y Y Ostrea (Tiostrea) chilensis (Bluff oyster) Y Y Y Y Y Y Y Pecten novaezelandica (scallop) Y Y Y Y Y Y Y Y Y Y Y Panopea zelandica (geoduck) Austrovenus stutchburyi (cockle) Y Y Y Y Y Y Y Y Mactra discors Y Dosinia anus Surf Y Spisula aequilatera clams Y Paphies subtriangulata Y

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3. HAZARD ASSESSMENT

Influence diagrams are recognised as an effective means of showing the possible hazards (in a risk assessment sense) associated with the establishment of suspended bivalve (e.g. mussels, oysters etc) farms (Figure 3). In this figure we have simply isolated the hazards associated with marine farming, although it must be highlighted that in any given region there are a number of hazard sources that may pose a risk to the aquatic environment. Hazards associated with other activities in the marine environment can be significantly greater than risks from marine farming activities.

Benthic Targeted Values Wi l dli fe biodiversity species

Benthic Benthic Benthic communities Pelagic communities Receivers habitat outside communities within footprint footprint

Particulate Crop/fouling SPM Structures/ Stressors deposition/ deposition extraction crop DIN release

Marine Source farms

BivalveBivalve Farming Farming Risk Pathways Pathways

Figure 3. Influence diagram detailing the likely hazards (in a risk assessment sense) associated with the establishment of a suspended bivalve farm.

The influence diagram is structured into a number of layers that represent different segments of the risk pathways. For example the lower levels show the stressors associated with the possible source of stress in this case (the farms). The stressors themselves resulting from the establishment of farms may be divided in a number of different ways, but in this case they have been divided into four categories. The first stressor is the deposition of parts of the crop, and associated epibiota, on the seafloor beneath the farm. This occurs both naturally, for example during storm events, and as a result of human activities, for example during harvesting operations when fouling organisms or other unwanted shellfish either fall off the

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crop rope, or are deliberately returned to the water. The second stressor occurs as a result of the generation of faecal material by the crop; whereby particulate material, in the form of faeces and pseudofaeces is deposited to the seafloor, and dissolved nutrients are released back into the water column. This particulate deposition can lead to the organic enrichment of the benthic environment, and the release of dissolved nutrients can stimulate pelagic primary productivity under some conditions. The third stressor is the extraction of suspended particulate matter (SPM) from the water-column as a result of the grazing behaviour of the culture stock, and some of the associated fouling organisms that colonise the crop and structures. The fourth stressor is the structures and crop which acts as new hard habitat in the water column and hence can attract and retain organisms that would not normally survive in the water-column, such as macro-algae and demersal or reef fishes.

The next level of the hazard assessment diagram contains the receivers of the stressors. These have also been divided into four categories here; although once again may be allocated in a number of ways. The first receiver identified here is the benthic habitat, this relates to the physical structure of the habitat, which can be altered primarily through the deposition of hard material such as shells from the crop. In some cases the shell material can build up beneath farms, and this can change the physical structure of the benthic environment from being a soft sediment substrate to a substrate containing pockets of reef like structures. The presence of the structures can also lead to an alteration of water current flows, which can in turn influence benthic biodiversity.

The second receiver category is the benthic communities within the deposition footprint. These communities are likely to be subjected to some form of organic enrichment from the deposited material. This material can also smother some communities, or alternatively the influx of organic material can lead to changes in biogeochemical processes occurring within the sediments and water-column directly above the seabed. There is a large body of literature describing how soft sediment benthic communities respond to the introduction of organic material; however it must be noted that the community response is generally very site-specific.

Benthic communities outside the deposition footprint can also be influenced by changes that occur within the footprint (receiver number three). For example, the deposition of organic material and crop etc, can theoretically lead to increases in the abundance of predators within the deposition footprint. In theory, these predators can then traverse beyond the footprint and impact on communities outside the deposition footprint. Furthermore, if biogeochemical cycling processes within a large farmed area are dramatically changed and the farmed area covers a large proportion of the local marine environment, then in theory this may influence the ability of the region to deliver essential ecosystem services such as nutrient cycling and pollutant assimilation. Existing native populations of the crop species can also be influenced outside the farm footprint, through the establishment of the crop species in habitats within their dispersal range and this can potentially lead to loss of genetic diversity of wild stocks of the crop species. Fouling organisms may also provide a threat to existing communities of similar species, as the structures can become reservoirs for fast-growing competitive species.

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The fourth receiver category is the pelagic communities. Suspended bivalve culture interacts with these communities by directly extracting phytoplankton and zooplankton (Jiang & Gibbs 2005), as well as via the release of recycled nutrients that can stimulate phytoplankton growth, and through the attraction of pelagic fishes, some of which congregate around structures. Whilst phytoplankton and zooplankton have little direct economic value, they have significant indirect value in terms of supporting higher trophic levels.

The upper layer of the influence diagram contains the system values. Once again these values can be categorised in a number of ways and here we have chosen to divide them into three broad categories. The first is titled benthic biodiversity; this encompasses biodiversity both within the footprint and outside the immediate effects footprint, although having said this, the majority of effects are generally restricted to within the footprint. As discussed above, changes to the stressors can lead to changes in the benthic receiving environment and in some cases, this can lead to reductions in benthic biodiversity. This is particularly the case where heavy organic loading occurs, which results in communities being smothered, or becoming unable to cope with the influx of organic material. This is common beneath fish cages, but substantially less likely to occur beneath suspended bivalve farms.

The second value category encompasses targeted fisheries stocks which include demersal, shellfish and pelagic species (Gibbs 2004). Suspended bivalve farms not only alter the surrounding benthic and pelagic habitat and communities, but also the catchability of species, since many forms of fishing cannot easily take place within the bounds of the farm. Objectors of marine farms often highlight the negative interactions that can lead to reductions in the carrying capacity of other fish species (through the extraction of eggs etc), however there is increasing evidence that the establishment of marine farms can also lead to increases in the catchability of fishes.

The third value category focuses on wildlife and includes birds and marine mammals. Objectors to the establishment of bivalve farms have often highlighted the possibility of entanglements of marine mammals and there has been at least one reported entanglement incident. There is also the possibility that bird foraging behaviour changes with the establishment of bivalve farms although to date there is not a great body of evidence describing these effects.

The influence diagram in Figure 3 shows that there are a large number of ways that the establishment of bivalve farms can interact with the surrounding environment. To make these more tractable, it is convenient to identify the major ‘risk pathways’ between the hazard source and the endpoint values. A review of the work of a number of investigators both within New Zealand, and internationally, suggests that several dominant risk pathways can be identified, as follows: 1. Loss of benthic biological diversity within deposition footprint resulting from deposition of organic material. This pathway involves both burial of organisms, and mortality associated with changes to geochemical processes.

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2. Loss of pelagic and benthic biological diversity outside the deposition footprint resulting from the consumption or appropriation of suspended particulate organic matter (phytoplankton and zooplankton including eggs and larvae) by the bivalve crop. 3. Loss of benthic biological diversity outside the deposition footprint resulting from either changes to predation, changes to water current flows, or the introduction of invasive species. 4. Mortality of marine mammals resulting from entanglement.

The dominant, immediate impacts of suspended bivalve culture are generally considered to be associated with the first two of these pathways and hence they will receive particular attention in this study. The third effect also largely depends on the level of organic loading occurring within the footprint and will also be considered here. However given that all of the bivalves grown using suspended techniques are exposed to high fouling levels, and there are little quantitative data available on fouling for most of these species, the marginal differences in the risks of various farms hosting invasive species will not be considered in this study. The risk pathways relating to point 4 will be discussed here, as various farming structures can lead to differing effects on current flows, and the associated risk of mammal entanglement.

4. METHODOLOGY

This section describes the methods used to analyse the available information on the impacts of the culture of various bivalve species on material fluxes and water flows.

4.1. Material fluxes

In this section we focus on the marginal differences between the fluxes of material passing through the cultured stock of different bivalve species; as differences in these fluxes underpin the marginal differences in the major two risk pathways (points 1 and 2) identified in Section 3. The key to determining these differences is in predicting the feeding rates of the selected bivalve species in order to make comparative judgements about the interspecific differences in the flux of material associated with feeding that are likely to occur. These rates were determined using a three-step process, as follows: 1. An extensive literature search to identify the empirical models relating feeding, rejection, and excretion rates of the bivalves discussed in this report to both animal size and at least one environmental forcing factor. 2. Application of the models using environmental data from the Marlborough Sounds and the Cawthron Institute’s Glenhaven Aquaculture Centre to predict the marginal changes to fluxes of particulate matter through different cultured species in farms located in the Nelson/Marlborough growing areas.

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3. Pooling of the results into comparable histograms so that the marginal differences in the extraction and generation of particulate matter for different farmed bivalve species can be easily determined. These three steps are discussed in greater detail in the following sections.

4.1.1. Literature search

It is widely recognised that bivalve feeding and excretory rates can be largely explained by individual animal size and several key environmental factors including temperature, salinity, and seston (food) availability. Due to a general lack in salinity:feeding rate relationships we specifically focused our attention on models relating animal size, and at least temperature or food availability, to clearance rate (CR). The most widely used measures of food availability for bivalves are total particulate matter (TPM) and/or chlorophyll a (chla). The quality of this available food can have a major affect on the feeding behaviour of bivalves, especially with respect to ingestion and absorption rates. However, these are complex relationships and obtaining food quality data requires more labour intensive analyses of the available seston than that required for TPM or chla alone. Therefore for the purposes of this investigation we have specifically only concentrated on the more obvious effects of seston quantity on bivalve feeding behaviour. However, the assumption that the quality (relative organic content) of naturally occurring seston generally decreases as TPM increases held for almost all of the studies cited.

The references and variables used to determine feeding and excretion rates for each of the target groups are provided in Appendix 1. Reasonably comprehensive feeding studies were available for the dominant NZ aquaculture species P. canaliculus and C. gigas. TPM based feeding relationships for P. novaezelandiae were available from Keeley (2001) and Teaioro (1999) although the affect of temperature was not included in either study. Teaioro (1999) also provides the only (to our knowledge) available comparative study between local species, specifically P. novaezelandiae, P. canaliculus, and Paphies australis (pipi). There was a major dearth of empirical feeding information for all of the other target species. In light of this, relationships published for species considered taxonomically similar to the target species were used as a best approximation. This included using the European flat oyster Ostrea edulis in place of T. chilensis; the great scallop Pecten maximus, Japanese scallop Chlamys farreri, and the sea scallop Placopecten magellanicus were used in conjunction with P. novaezelandiae due to the limited information on the native species; and the manila clam (Rudi) Tapes phillipinarum, and common (European) cockle Cerastoderma edule were used to represent A. stutchburyi and Bassina.yatei.

Modification of the available models was necessary to produce a standardised unit of output for CR (m3/day/1000 individuals), total rejection rate (TRR, g/day/1000 individuals), and total ammonia nitrogen excretion rate (TANexc, gTAN/day/1000individuals). We also utilised some of the published data sets to develop our own interpolated models. Specifically, CR and TANexc versus temperature relationships for P. canaliculus and a CR versus temperature

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relationship for P. maximus were derived from data reported in James et al.(2001) and Laing (2004) respectively.

4.1.2. Environmental datasets

The second step was to apply the models using data from the Marlborough Sounds growing region so that we can compare the marginal differences to fluxes of particulate material based on the measured environmental conditions, rather than just laboratory conditions. Unpublished (Cawthron) environmental datasets for Beatrix Bay were combined with an extensive time- series of temperature and chla values extrapolated from both published studies (Gibbs & Vant, 1997; Ogilvie et al. 2000; James et al. 2001; Gibbs et al. 2002; Ogilvie et al. 2003) and the Marlborough Sounds Environmental Monitoring Programme (www.niwascience.co.nz/services/sounds). The lack of TPM data within these datasets excluded many of the models from the Beatrix Bay comparison. Of the 21 feeding models cited in Appendix 1 only 11 (denoted by *) were applied to the Beatrix Bay dataset, and none of these were in the ‘cockles/clams’ group. Further, the lack of TPM data also meant that the total rejection rates (TRR) and associated deposition of filtered material could not be estimated and compared for this dataset. All excretion rate references were applied across the Beatrix Bay dataset as these models only required animal size and temperature data.

Due to the limitations of the Beatrix Bay dataset, historical data from Cawthron’s Glenhaven Aquaculture Centre Ltd. (GACL) were also used. The GACL data consisted of daily averaged temperature, TPM and chla measured during 10 weeks of intensive sampling between May and October 2002 (Pilcher 2002). All 21 feeding rate models listed in Appendix 1 were applied to the GACL data and associated TRRs were estimated using this dataset.

4.1.3. Shellfish size

Given that bivalve farms typically contain animals of different sizes, three size classes were chosen for each species based on shell length (SL; Table 2). This included the most likely size of the initial ‘spat’ introduced to the farm site, the optimum target grow-out size, and a middle size group. Shell length related dry and live weights (DW and LW respectively) were determined for each species using published and unpublished relationships as listed in Table 2.

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Table 2. Animal sizes chosen for the analysis.

Individual sizes considered Middle Optimum Group/species Measure Initial spat References grow-out grow-out Clams/cockles SL (mm) 10 25 40 DW (g) 0.14 0.21 0.43 Hammen (1968) LW (g) 0.23 3.23 12.52 Pfieffer et al.(1999)

Flat oysters SL (mm) 20 40 70 DW (g) 0.01 0.19 1.26 Haure et al.(1998) LW (g) 0.86 8.71 56.28 Rodhouse & O’Kelly (1981)

Cupped oysters SL (mm) 20 40 90 DW (g) 0.02 0.14 1.09 Ren et al.(2000) LW (g) 1.10 7.97 81.02 Bacher & Baud (1992)

Scallops SW (mm) 20 40 90 DW (g) 0.22 0.47 3.15 Keeley (2001) LW (g) Keeley (2001) 2.68 16.09 148.17 Laing (2004)

Mussels SL (mm) 20 40 90 DW (g) 0.04 0.26 2.38 Hatton (2002) LW (g) 0.9 6.01 55.23 Cawthron unpublished

4.1.4. Comparative histograms

The referenced models were applied to the environmental datasets to generate separate feeding (CR & TRR) and excretion (TANexc) rate outputs for bivalves of each size in the growing areas. These were then pooled by species/group and plotted as a series of histograms to allow an interspecies comparison of both the expected range and likelihood of occurrence in feeding, excretion and biodeposition rates.

4.2. Attenuation of water flows

It is a given that the establishment of aquaculture structures will lead to at least some changes to water current flows within the immediate area of the farm. At present there is a lack of consensus over the magnitude of these effects around many aquaculture structures. Of even more significance, is the fact that science’s ability to predict the effect of reduced current flows on many ecological processes is presently weak. Although detailed numerical and experimental scientific investigations can be commissioned to look at these effects, the scope of this report was restricted to a desktop comparison of the scales of magnitude differences between the present methodology for farming mussels in New Zealand, and likely methodologies for selected other species. Hence in the following section we present the gross differences between farming structures using a desk-top scaling analysis.

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5. RESULTS

5.1. Differences in the material fluxes using Beatrix Bay data

5.1.1. Environmental data in Beatrix Bay

Consider first the environmental conditions in the Marlborough Sounds. Temperature ranged between 9ºC and 20ºC with a distinctive dip in the occurrence of temperatures between 14- 15ºC (Figure 4). It may be argued that this may be an artifact of compounding gaps in the dataset for similar times of the year. However, complete annual datasets for temperature plotted individually for 1994/95 (Gibbs & Vant 1997), 1997/98 (Ogilvie et al. 2000) and 1999 (Gibbs et al. 2002) display a similar pattern to Figure 4. Visual analysis of a time-series plot of annual temperature data shows that water temperatures of 14-15ºC occur during late autumn and late spring. During this time water temperatures are undergoing the most rapid change, so temperatures in the 14-15ºC range occur at a lower frequency than other temperatures in the annual dataset.

100

80

60

18% 16% No of obs 40 13% 13%

10% 9%

20 6% 6% 5% 3% 1% 0% 0% 0 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Temperature (ºC)

Figure 4. Beatrix Bay temperature data recorded between 1994 and 2006.

Beatrix Bay displayed consistently low levels of chla (Figure 5). Over half (52%) of the time chla concentrations were below 1.1 µg/l; a level which is generally considered to constitute poor food availability for bivalve growth. Chla levels of up to 8 µg/l were recorded in the dataset but these ‘bloom’ events were infrequent, and short-lived. The temporal sensitivity of the data used (weekly to monthly) must be considered and it is accepted that smaller time-scale events of increased food availability can occur in these environments which may not be

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represented by this dataset. However, for the purposes of this comparative study we have characterised food availability at Beatrix Bay as generally low with occasional blooms.

90 30% 80

70

22% 22% 60

50

40

No of obs of No 13%

30

20 6%

4% 10 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0 0.1 0.6 1.1 1.6 2.1 2.6 3.1 3.6 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 Chla (µg/l)

Figure 5. Chla data recorded for Beatrix Bay between 1994 and 2006.

5.1.2. Clearance Rate histograms for Beatrix Bay

Figure 6 illustrates the CR outputs by bivalve group for the Beatrix Bay dataset. Three associated models were applied to each of the cupped oysters, flat oysters, and mussels groups whilst the scallops group histogram is the result of only two models (as denoted in Appendix 1). Comparative histograms of CR could not be generated for the clams/cockles group.

14 Cawthron Report No. 1192 October 2006

0.8 A. Cupped oysters 0.6 C.gigas 0.44 (SL-90mm) n=831 0.4 0.37

0.2 0.08 0.10 0 0.8 0.67 B. Flat oysters 0.6 O.edulis ence r

r (SL-70mm) n=831 0.4 0.25 occu f 0.2 0.03 0.05 0 0.8 equency o r

f C. Scallops 0.6 C.farreri, P.maximus (SW-90mm) n=554 0.4

Relative 0.24 0.2 0.19 0.10 0.10 0.07 0.06 0.06 0.06 0.01 0.02 0.03 0.00 0.01 0.04 0 0.8 D. Mussels 0.6 P.canaliculus, M.galloprovincialis 0.45 (SL-90mm) n=831 0.4 0.24 0.2 0.12 0.11 0.04 0.04 0 0.00

0 40 80 120 160 200 240 280 320 360 400 440 480 520 560 600 CR (m3/day/1000ind)

Figure 6. Comparative histograms showing the range and relative frequency of predicted clearance rates by bivalve group for Beatrix Bay.

Cupped oyster models predicted a maximum of 145 m3/day/1000ind with 44% of CR’s to occur within the range 80-120 m3/day/1000ind. Flat oyster CR’s were predicted across a similar range to cupped oysters, although with a slightly lower maximum of 135 m3/day/1000ind. The majority (67%) of CR’s for this group also occurred over a lower range (0-40 m3/day/1000ind). This majority can largely be attributed to the application of the Haure et al. (1998) model which predicted CR’s based on temperature alone, but was developed over a range of food concentrations comparable in both quantity and quality to the other models used for this group (Appendix 1). The main difference was the larger size of animals (5-120 g

Cawthron Report No. 1192 15 October 2006

LW) tested by Haure et al. compared to the smaller ‘spat’ sizes (0.001-14.4 g LW) tested by both Rodhouse & O’Kelly (1981) and Spencer (1988). The application of the latter models to the optimal harvest size (~56 g LW) used here could potentially overestimate CR at this larger size.

The scallops group had the highest CR’s with a maximum of 595 m3/day/1000ind predicted. There were two distinct sets of CR values for the scallops group, a low range of 0-200 m3/day/1000ind and a high range of 240-600 m3/day/1000ind. These separately represent the two models (Hawkins et al. 2001 and Laing 2004 respectively, Appendix 1) we were able to apply to the Beatrix Bay data. The Hawkins et al. model predicted CR for the Japanese scallop C. farreri, a slightly smaller scallop than P. novaezelandiae, which is generally found in gravelly or reef-type substrates. We consider the range of CR values generated by the Hawkins et al. model more realistic than the Laing (2004) outputs which, although modelled on a more related species (P. maximus), only investigated juvenile animals between 10 and 25 mm SL. The problem with this lies in the fact that small bivalves feed and respire at much higher mass-relative rates compared to larger animals. Applying the Laing (2004) model to the optimal harvest scallops (90 mm SL) produced outputs that are most likely too high for P. novaezelandiae at this size. This is further evidenced by the results from the GACL dataset, which enabled us to include P. novaezelandiae specific models (Figure 11).

The mussels group had a wider range of predicted CR’s compared to the oyster groups with a maximum of 280 m3/day/1000ind. Similar to the scallops group there was a model related bimodal grouping of CR’s with peaks in occurrence at 80-120 m3/day/1000ind (Denis et al. 1999; James et al. 2001) and 240-280 m3/day/1000ind (Hawkins et al. 1999).

Experimental animal size was comparable for all models but the environmental conditions tested were different. The James et al. model used an interpolated temperature relationship at low food levels (chla <1.1 µg/l), whilst the Hawkins et al. and Denis et al. models related food availability (chla) to CR at 16.4ºC and 20-26ºC respectively. Feeding behaviour studies on P. canaliculus (Waite 1989; Hawkins et al. 1999) have shown maximal CR’s to generally occur at chla levels between 1-2 µg/l, with a sharp decline in CR below this minimal feeding threshold. This may explain the generally lower CR outputs from the James et al. model, but not from the Denis et al. example, especially given the high temperatures used during the latter study.

A critical difference in the experimental methodology used to generate the models may provide a plausible explanation of the bimodal CR grouping. Both the James et al. and Denis et al. models were generated through measurements of total CR for a group or ‘population’ of >10 similar sized mussels before being averaged by the number of individuals in this population. Hawkins et al. determined individual CR’s for 10 separate mussels, ignoring any that weren’t actively feeding. The latter approach provides a much more detailed analysis of individual feeding behaviour but highlights a classic shortfall in applying these types of studies in an applied predictive manner. By ignoring inactivity they may not truly represent averaged

16 Cawthron Report No. 1192 October 2006

feeding activity at the population scale and can over-estimate CR for large numbers of animals (see Figure 13 and associated paragraph). For this reason the high CR peak for the mussels group (240-280 m3/day/1000ind) may be unrealistically high at the population scale.

Figure 6 suggests that, under Beatrix Bay conditions, CR will generally be highest in scallops, followed by mussels, cupped oysters and finally flat oysters. Further consideration of the underlying models suggests that predominant CR’s will be in the ranges 120-200 m3/day/1000ind for scallops, 40-160 m3/day/1000ind for both mussels and cupped oysters, and 0-40 m3/day/1000ind for flat oysters.

5.1.3. Ammonia nitrogen excretion rate histograms for Beatrix Bay

There were a very limited number of studies relating bivalve TANexc to factors other than animal size, and none attempting to empirically determine the effects of diet. Using the Beatrix Bay dataset it was possible to generate comparative histogram plots for P. canaliculus (by applying interpolated relationships across data presented in James et al. 2001), C. gigas (by combining relationships presented in Bougrier et al. 1995 and Boucher et al. 1988), and T. phillipinarum (directly from models presented in Zhu et al. 1999 and Higano et al. 2005). These are illustrated in Figure 7.

0.8 A. Clams 0.6 T.phillipinarum (SL-40mm) n=554 0.4 0.31 0.31 0.18 0.2 0.12 0.06 0.01

ence 0 r r 0.8 B. Cupped oysters

occu 0.57 f 0.6 C.gigas 0.43 (SL-90mm) n=277 0.4

0.2 equency o equency r f 0 0.8 C. Mussels Relative Relative 0.6 P.canaliculus (SL-90mm) n=277 0.4 0.21 0.24 0.23 0.2 0.14 0.08 0.09 0.01 0

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4 TANexc (gTAN/day/1000ind)

Cawthron Report No. 1192 17 October 2006

Figure 7. Comparative histograms showing the range and relative frequency of predicted ammonia nitrogen excretion rates by bivalve group for Beatrix Bay. Predicted TANexc was similar between the clam and cupped oyster groups with a majority in occurrence within the range 0.4-0.8 gTAN/day/1000ind. Mussel TANexc was predicted as 2-3 times that of either oysters or clams at the optimal harvest size. We would expect animals with higher meat DW’s (mussels compared to oysters and clams, Table 2) to have higher TANexc rates, especially during times of nutritive stress when protein catabolism becomes an important energy pathway for maintaining basic metabolism. The very low food availability (<1.1 µg chla/l) in the James et al.(2001) study could well have influenced the higher TANexc outputs in the mussels group; however the model is somewhat appropriate given the generally low chla levels in the Beatrix Bay environmental dataset.

TANexc provides a major ‘feedback’ mechanism between filter-feeding bivalves and the phytoplankton that they graze upon. TANexc provides phytoplankton with an immediate and readily available source of dissolved nitrogen, an often growth-limiting element in marine systems. The growth of phytoplankton in the Marlborough Sounds is generally nitrogen limited during summer months (Gibbs & Vant 1997), but a recent study (Ogilvie et al. 2003) has suggested that ‘feedback’ nitrogen from mussel excretion is able to support and slightly increase chla levels during these times as the phytoplankton can grow slightly faster than the mussels are able to clear them from the water column. It stands to reason that as more nitrogen is recycled through the TANexc pathway, less (nitrogen) is available for sediment enrichment through biodepostion. However, this interaction will depend on a myriad of food quality and feeding process variables and the comparative effects of differing TANexc rates between different bivalve groups cannot be speculated on the basis of the information provided in this study.

5.2. Differences in material fluxes using Glenhaven Aquaculture Centre pond data

5.2.1. Environmental data for Glenhaven

Temperatures for the GACL pond study were between 9-16ºC, similar to those recorded in Beatrix Bay (Figure 8). By contrast to Beatrix Bay however, temperatures were most often between 14-15ºC. However, it must be noted that the GACL dataset is not representative of a full year and the annual temperature range for the site is 5-27ºC.

18 Cawthron Report No. 1192 October 2006

22

24% 20

18 20% 19% 16

14 15% 12 13% 10 No of obs 8

7% 6

4

2 1% 0 9 10111213141516 Temperature (ºC)

Figure 8. Daily temperature data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006.

Food availability in the GACL ponds also displayed a similar pattern to the Beatrix Bay dataset, although levels, measured as chla, were generally higher (Figure 9). Nearly half (48%) of the time chla is >1.7 µg/l in the ponds compared to only ~26% in Beatrix Bay (Figure 5). Bloom events are also much more intense, with chla levels of up to 35 µg/l recorded in the ponds.

Cawthron Report No. 1192 19 October 2006

70

60

50

52%

40

30 No of obs No

26% 20

10 7% 6% 2% 0% 0% 0% 1% 0% 1% 0% 1% 0% 0% 1% 0% 0% 0% 1% 0 0.0 3.5 6.9 10.4 13.9 17.4 20.8 24.3 27.8 31.2 34.7 Chla (µg/l)

Figure 9. Daily chlorophyll a data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006.

TPM was between 2-40 mg/l and followed a similar pattern in occurrence to chla (Figure 10). This largely reflects the phytoplankton dominated nature of the suspended material in the ponds, although the highest TPM values result from significant resuspension events due to wind and rain, similar to in natural shallow coastal systems.

20 Cawthron Report No. 1192 October 2006

40

42% 35

30

25 29%

20 No of obs 15

10 11%

6% 5 4% 4% 2% 1% 1% 1% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0 2 6 10 14 18 22 26 30 34 38 TPM (mg/l)

Figure 10. Daily total particulate matter data recorded for seawater ponds at the Glenhaven Aquaculture Centre between May and October 2006.

5.2.2. Clearance rate histograms for Glenhaven

Figure 11 illustrates the outputs in CR by group for the GACL dataset. Due to the availability of TPM data it was possible to include the clams/cockles group in these analyses.

Predicted CR’s for the clams/cockles group were generally low and occurred over a narrow range with a maximum of only 61 m3/day/1000ind. Relatively low and constant CR’s is a typical feeding behaviour within this group (Teiaoro 1999; Bacon et al. 1998). Although there was no readily available feeding model for the target A.stutchburyi cockle, individual (40 mm SL) feeding rates of 15 m3/day/1000ind at 15ºC were reported by Pawson (2004) for this species. It was also reported by Pawson that individual cockles were only active for 40% of the time, suggesting that actual population CR’s could be even lower still.

The cupped oyster, flat oyster and mussel groups all displayed similar results to the Beatrix Bay dataset (Figure 6). Flat oyster CR’s were predicted to occur up to 105 m3/day/1000ind but with the majority of occurrence in the range 0-40 m3/day/1000ind. The majority of cupped oyster and mussel CR’s were again predicted to occur between 40-120 m3/day/1000ind. However the maximum CR predicted for the cupped oysters increased to 175 m3/day/1000ind, and there was an increase in the occurrence of CR’s >160 m3/day/1000ind from 0% to 19%.

Cawthron Report No. 1192 21 October 2006

0.8 0.68 A. Clams/cockles 0.6 R.phillipinarum (SL-40mm) n=252 0.4 0.32

0.2

0 0.8 B. Cupped oysters 0.6 C.gigas 0.41 (SL-90mm) n=420 0.4 0.26 0.2 0.19 0.11 0.02 0 0.8 0.68 C. Flat oysters

occurrence 0.6 f O.edulis (SL-70mm) n=252 0.4

0.2 0.16 0.16 requency o requency f 0 0.8

Relative Relative D. Scallops 0.6 0.54 P.novaezelandiae, C.farreri, P.maximus, P.magellanicus (SW-90mm) n=420 0.4

0.2 0.10 0.07 0.05 0.06 0.04 0.01 0.04 0.02 0.02 0.03 0.01 0 0.8 E. Mussels 0.6 P.canaliculus, M.galloprovincialis (SL-90mm) n=336 0.4 0.30 0.27 0.2 0.16 0.07 0.07 0.09 0.03 0

0 40 80 120 160 200 240 280 320 360 400 440 480 520 CR (m3/day/1000ind)

Figure 11. Comparative histograms showing the range and relative frequency of predicted clearance rates by bivalve group for the Glenhaven Aquaculture Centre ponds.

Scallops again displayed the greatest range of CR with a maximum of 500 m3/day/1000ind. However, a majority (54%) of CR’s were predicted to occur within the range 0-40 m3/day/1000ind, which was largely due to the inclusion of the P. novaezelandiae specific models (Appendix 1). This strongly suggests that population CR’s >200 m3/day/1000ind as determined using the Laing (2004) model, are probably unrealistically high for this species at the optimal harvest size (90 mm SL).

22 Cawthron Report No. 1192 October 2006

Further, scallops may not necessarily have explicitly higher feeding rates than mussels, as suggested in Figures 6 and 11. Comparing CR outputs for P. canaliculus (Teaioro 1999) and P. novaezelandiae (Teaioro 1999; Keeley 2001) using the GACL dataset showed a significant difference (paired t-tests, P<0.001) in feeding rate between these two species (Figure 12). P. canaliculus (90 mm SL) had both a wider range and generally higher CR compared to P. novaezelandiae (90 mm SW). Conditions were very similar in both studies with models relating CR to TPM at average temperatures of ~16ºC. Due to the larger body mass of P. novaezelandiae at the optimal harvest size (Table 2) scallop feeding rates could well be similar or even exceed those of mussels during times of elevated temperatures as the basal metabolic energy (i.e. food) requirement would conceivably be higher. However, this is speculative as there is (to our knowledge) no available comparative studies between these two species over a range of different temperatures.

100

80

60 P.canaliculus - Teaioro (1999) P.novaezelandiae - Teaioro (1999) P.novaezelandiae - Keeley (2001)

No of obs 40

20

0 10 15 20 25 30 35 40 45 50 CR (m³/day/1000ind)

Figure 12. Comparative clearance rate histograms for P. canaliculus and P. novaezelandiae models from similar NZ studies by Teaioro (1999) and Keeley (2001) applied to the Glenhaven Aquaculture Centre pond data.

Figure 13 illustrates a clear example of differences in population generated CR’s versus individual generated CR’s. The histograms plot data generated from the GACL dataset using two separate models of C. gigas CR adapted from Barille et al. (1997). The study concurrently measured the total feeding rate from a raceway containing 100 oysters and the individual feeding rates of six individual oysters in a feeding chamber. Similar food conditions and relative water flows were maintained for both systems. Extrapolating the individual based results to a thousand 90 mm SL oysters estimates CR to be 4-8 times higher than the population based model or, put another way, it predicts an activity level within the population of only 12-24%. This suggests that CR’s determined from models based on an individual

Cawthron Report No. 1192 23 October 2006

animal approach (as with most of the models used for this study) may grossly overestimate feeding rates at the population scale.

100

80

Population CR Individual CR 60

No of obs 40

20

0 20.0 50.6 81.2 111.8 142.4 173.0 CR (m³/day/1000ind)

Figure 13. Comparative histograms of C. gigas CRs by population and individual assessment methods adapted from Barille et al.(1997) and applied to the Glenhaven Aquaculture Centre pond data.

The GACL pond data produced a similar, but expanded result on the Beatrix Bay dataset. Figure 11 suggests that, under the GACL pond conditions, CR will generally be highest in scallops, followed by mussels, cupped oysters, flat oysters and finally clams/cockles. However, further consideration of the models used illustrates that this ranking may not be clear-cut. Further to the uncertainty produced by applying models developed on exotic species rather than the target native comparisons, CR values at the upper end of the ranges predicted (i.e. >200 m3/day/1000ind) may in fact be unrealistically high at the population scale. Taking this evidence into account, it seems most realistic that population CR’s for all of the groups will be within the range 0-200 m3/day/1000ind with predominant feeding rates between 40-120 m3/day/1000ind for cupped oysters and mussels, and 0-40 m3/day/1000ind for clams/cockles, flat oysters and scallops.

5.2.3. Total rejection rate histograms for Glenhaven

Figure 14 shows the predicted TRR’s for each bivalve group under the GACL pond scenario. The TRR provides a proxy of the potential biodeposition rates for each group. Actual biodeposition will of course be site-specific and influenced by many factors including water currents, depth of the site and the quality of the seston.

24 Cawthron Report No. 1192 October 2006

1 0.94 0.8 A. Clams/cockles R.phillipinarum, P.australis 0.6 (SL-40mm) n=336 0.4 0.2 0.05 0.01 0 1 B. Cupped oysters 0.8 0.71 C.gigas 0.6 (SL-90mm) n=504 0.4 0.2 0.20 0.05 0.02 0.01 0.00 0.00 0.01 0.00 0.00

ence 0 r r 1 0.89 C. Flat oysters 0.8 occu

f O.edulis 0.6 (SL-70mm) n=252 0.4

equency o 0.2 r

f 0.08 0.02 0.00 0.00 0.00 0 1 D. Scallops Relative Relative 0.8 0.67 P.novazelandiae, C.farreri, P.magellanicus 0.6 (SW-90mm) n=336 0.4 0.26 0.2 0.05 0.01 0.01 0 1 0.8 E. Mussels P.canaliculus, M.galloprovincialis 0.60 0.6 (SL-90mm) n=336 0.4 0.25 0.2 0.09 0.03 0.01 0.01 0.01 0.01 0.00 0

0 400 800 1200 1600 2000 2400 2800 3200 3600 4000 4400 4800 5200 TRR (g/day/1000ind)

Figure 14. Comparative histograms showing the range and relative frequency of predicted total rejection rates by bivalve group for the Glenhaven Aquaculture Centre ponds.

TRR was estimated using a very simplistic mass balance model which considered the total mass filtered by the organism minus the amount assimilated through digestion. This is represented by CR x TPM - OAR (organic absorption rate). OAR was estimated using a static, literature-based absorption efficiency (AE) for each group multiplied by the amount of particulate organic matter (POM) filtered. This is represented as AE x CR x POM. In respect of simplicity this model makes two major assumptions. The first is that all filtered POM is ingested. Therefore the outputs will slightly underestimate the actual total rejection rate, especially at higher TPM’s, as some of the available POM is rejected as pseudofaeces and

Cawthron Report No. 1192 25 October 2006

therefore not ingested and assimilated. However this error is relatively small compared to the total amount of material generally being filtered, and would not impact the overall shape or range of values in Figure 14. The second major assumption is that AE is constant. It is known that AE in bivalves is variable in relation to the quality of the available food and temperature. Unfortunately these relationships are complex and in the case of temperature, not well documented for bivalves.

The average (±sd) organic content (OC) of the pond seston (0.19 ± 0.08; Pilcher 2002) was assumed to be representative of the general food quality in the ponds. From the literature (Appendix 1) we applied an AE of 0.75 for mussels and both oyster groups and a slightly lower AE of 0.65 for clams/cockles and scallops due to a comparatively lower ability to organically enrich their ingested ration. The Laing (2004) model was not included in the TRR predictions for the scallop group on the basis of the factors previously discussed for Figures 6 and 11.

It is immediately apparent in Figure 14 that TRR for all of the groups is largely influenced by the available TPM (Figure 10) rather than CR (Figure 13). Regardless of group the majority of TRR’s are less than 400 g/day/1000ind, reflecting the generally low levels of TPM in the GACL pond data. The largest range of TRR was displayed by the mussels group with both the highest maximum at 5160 g/day/1000ind and the highest relative occurrence (40%) of TRR’s over 400 g/day/100ind.

On the premise of increased TRR representing increased biodeposition intensity, Figure 14 suggests that biodeposition will generally be most intense for mussels followed by scallops, cupped oysters, flat oysters and finally clams/cockles. However, it is advised that these results be treated cautiously as site-specific factors, especially hydrodynamic interactions with the rejected material, may overcome the small differences between the first three groups. It is also possible that the inclusion of more complex interactions between absorption and temperature and/or food quality could affect the overall result.

5.3. Attenuation of current flows

The hazard assessment described in Section 2 identified that the establishment of marine farming structures can influence benthic biodiversity outside the immediate farm deposition effects footprint through changing water flows. A desktop scaling-analysis is presented here that aims to highlight the gross effects of different farming structures (Table 3).

26 Cawthron Report No. 1192 October 2006

Table 3. Calculations for surface area presented to currents and equivalent densities of shellfish per area of seabed for theoretical shellfish culture configurations.

Standard mussel Basket Tray Rotoshell configuration configuration configuration configuration Figure 2(left) Figure 2(centre) Figure 2(right) GEAR DESCRIPTION Backbone attachment Both sides Alternate sides Both sides Both sides (straddles (straddles (straddles backbone) backbone) backbone) Spacing along backbone ~1m 3 m centers 1.0m centers 0.5m between (varies with site depth) (1.5m overall) Arrangement Vertical droppers Vertical hanging Vertical hanging Surface only chains chains Vertical spacing na 0.3m 0.3m na Primary use Mussels Shellfish grow out Shellfish grow out Spat/juvenile (multiple species) (multiple species) holding Rope/cage/tray dimensions (m) Width 0.2 0.25 0.9 1.2 Length - 0.8 0.9 1.2 Height - 0.1 0.08 0.2

SITE INFORMATION Site depth (m) 4 4 4 4 Vertical use (m)/No. trays per stack ~3 5 5 1

SURFACE AREA CALCULATIONS Surface area per tray/cage Side profile (%) na 0.025 0.072 0.24 End profile (m2) na 0.08 0.072 0.24 Surface area per line/chain Side profile (%) 0.6 0.125 0.36 0.24 End profile (m2) 0.6 0.4 0.36 0.24 Spacing between centers (ropes/chains) 0.7 1 1.5 1.7 Comparative surface area: Side profile (%) 85.7% 3.1% 6.0% 3.5% End profile (m2) 0.6 0.4 0.4 0.08

DENSITY CALCULATIONS Density per m of line/tray 160 80 160 1200* Shellfish per dropper/chain 480 400 800 1200 Shellfish per 100m backbone 192000 40000 53333 70588 Shellfish per 1m backbone 1920 400 533 706 Spacing between backbones (m) 15 15 15 15 Density per Ha sea floor 1280000 266667 355556 470588 Density per m2 128 26.7 35.6 47.1 *Varies considerably depending on size (and age) of the juvenile shellfish, but relative biomass remains similar.

The mussel configuration and the physical dimensions of the cages and stocking densities are based on those provided by United Fisheries and are similar to what is presently in use on some farms. The calculations for the mussel densities are based on the 12:1 culture rope:backbone ratio. These dimensions have then been used to calculate the approximate surface areas that would be presented by the side and end profiles (Table 3). The same table also extends to providing comparative estimates of shellfish densities presented by each of the configurations per 100 m backbone and per unit area of seabed.

Table 3 shows that the tray culture configuration represents a substantially smaller barrier to water movement than conventional mussel farming configurations. From the side-on profile,

Cawthron Report No. 1192 27 October 2006

mussel droppers occupy approximately 86% of the cross section compared with 6.0%, 3.1% and 3.5% for the trays, baskets and rotoshells, respectively. These methods also present a smaller surface area from the end-on profile, with 0.4 m2 area for both trays and baskets and <0.1 m2 for the rotoshells, compared with 0.6 m2 for conventional mussel lines.

This represents a somewhat simplistic way of expressing the relative barriers to flow of the four configurations. It is acknowledged that it does not deal with how the trays might influence flow in a 3-dimension sense. Factors like the surface drag of the top and bottom of the cages and the spacing at which flow between trays and around lines becomes greatly reduced, are not properly considered. This could only really be achieved though the use of a very complex fine-scale numerical hydrodynamic model, which to our knowledge is yet to be successfully developed for this application. It is also a potentially time consuming and expensive path to pursue with questionable likelihood of a robust outcome. So in the absence of that tool, we believe this should provide a crude, but useful means of comparing the methods and highlighting any large scale differences. Small differences should be treated with caution.

6. SUMMARY AND RECOMMENDATIONS

A general hazard assessment was used to highlight the major environmental interactions between bivalves and the surrounding marine environment. This assessment identified a number of key effects pathways through which bivalve farms can interact with the surrounding environment; these include: ƒ Loss of benthic biological diversity within deposition footprints resulting from deposition of organic material. This pathway involves both burial of organisms, and mortality associated with changes to geochemical processes. ƒ Loss of pelagic and benthic biological diversity outside the deposition footprint resulting from the consumption or appropriation of organic suspended particulate matter (phytoplankton, and zooplankton including eggs and larvae) by the bivalve crop. ƒ Loss of benthic biological diversity outside the deposition footprint resulting from either changes to predation, changes to water current flows, or the introduction of invasive species. ƒ Mortality of marine mammals resulting from entanglement.

A key driver for differences in environmental effects between culture species is differences in the fluxes of material (primarily suspended particulate matter) extracted and released back into the water-column during the feeding of the cultured animals. This was therefore investigated in some detail using existing feeding models applied to environmental data from Beatrix Bay and Glenhaven Aquaculture Centre.

28 Cawthron Report No. 1192 October 2006

Rather than trying to choose a single ‘most appropriate’ feeding model for each species, it was hypothesised that by pooling the outputs from several models into a common histogram, the resulting overlap/s may integrate across the experimental methods used to derive each of the models. This was partially successful but strong model specific grouping of CR’s remained evident. The main influences were differences in the size of the experimental animals used, and individual versus population style investigations. However, by considering these influences it was possible to draw some relatively generic conclusions about the comparative feeding, excretion and rejection rates of the five major groups of bivalves considered; ƒ CR – While the range of predicted CRs was quite broad, rates were generally predicted to be between 0-200 m3/day/1000ind for all groups. They were highest in mussels and cupped oysters (40-120 m3/day/1000ind) followed by scallops and flat oysters (0-40 m3/day/1000ind). Clams/cockles had a much narrower range, with all CRs predicted to occur between 0-40 m3/day/1000ind. ƒ TANexc - Limited results, but highest in mussels (1.0-2.4 gTAN/day/1000ind) whilst lower but similar between clams/cockles (0-1.0 gTAN/day/1000ind) and cupped oysters (0.4-0.8 gTAN/day/1000ind). ƒ TRR - Biodeposition intensity greater than 400 g/day/1000ind occurred most frequently in mussels (40%) followed by, scallops (33%), cupped oysters (29%), flat oysters (11%), and finally clams/cockles (6%).

Overall, it appears that based on these models the substitution of mussels, specifically P. canaliculus, with any of the other alternate species/groups proposed would not be likely to increase either the clearance of the surrounding water, the biodeposition of suspended matter or the amount of dissolved ammonia through excretion. In fact, on an equivalent numbers basis substitution with any of the alternate groups may reduce these interactions, especially where either flat oysters or clams/cockles are considered. This is a key result of this study and suggests that there is no strong evidence in terms of material processed by the different bivalves considered here to restrict the stocking density of non-mussel bivalves to substantially lower densities by comparison to the stocking densities of mussels.

Of interest is that this study has provided tangible evidence towards generally held notions on comparative bivalve feeding rates. However, it must be clearly stated that this evidence is based on science referenced from a wide range of studies designed with different investigative objectives under a variety of environmental conditions, and with relatively little input from New Zealand specific examples. Therefore it is not recommended that this study be used for predicting very detailed precise effects of stocking density differences between species or groups. Precision of that nature will require a genuine comparative study between all of the actual species under consideration across a range of standardised environmental conditions.

Alteration of water currents around marine farming structures has been identified as a potential environmental risk pathway and different types of farming structures can lead to different water flow redirection effects. It was beyond the scope of this work to investigate this in a comprehensive manner. Rather, scaling-analyses were performed that highlight the relative

Cawthron Report No. 1192 29 October 2006

differences in cross-sectional areas posed by different farming methods. The results from this analysis indicate that the present mussel farming practices occupy a greater cross-sectional area by comparison with the other methods that are presently used. Hence there is little evidence to suggest that the stocking densities of other species, using different growing techniques as described here should be more overly restricted by comparison with present marine farming practices.

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7. REFERENCES

Bacon GS, MacDonald BA, Ward JE 1998. Physiological responses of infaunal (Mya arenia) and epifaunal (Placopecten magellanicus) bivalves to variations in the concentration and quality of suspended particles I. Feeding activity and selection. Journal of Experimental Marine Biology and Ecology 219: 105-125. Barillé L, Prou J, Héral M, Razet D 1997. Effects of high natural seston concentrations on the feeding, selection, and absorption of the oyster Crassostrea gigas (Thunberg). Journal of Experimental Marine Biology and Ecology 212: 149-172. Boucher G, Boucher-Rodoni R 1988. In situ measurement of respiratory metabolism and nitrogen fluxes at the interface of oyster beds. Marine Ecology Progress Series 44: 229-238. Bougrier S, Geairon JM, Deslous-Paoli JM, Bacher C, Jonquières G 1995. Allometric relationships and effects of temperature on clearance and oxygen consumption rates of Crassostrea gigas (Thunberg). Aquaculture 134: 143-154. Denis L, Alliot E, Grzebyk D 1999. Clearance rate responses of Mediterranean mussels, Mytilus galloprovincialis, to variations in the flow, water temperature, food quality and quantity. Aquatic Living Resources 12: 279-288. Deslous-Paoli JM, Lannou AM, Geairon P, Bougrier S, Raillard O, Héral M 1992. Effects of the feeding behaviour of Crassostrea gigas (Bivalve Molluscs) on biosedimentation of natural particulate matter. Hydrobiologia 231: 85-91. Gibbs M 2004. Interactions between bivalve shellfish farms and fishery resources. Aquaculture 240(1-4):267-296 Gibbs M, Ross A, Downes M 2002. Nutrient cycling and fluxes in Beatrix Bay, Pelorus Sound, New Zealand. New Zealand Journal of Marine and Freshwater Research 36: 675-697. Gibbs MM, Vant WN 1997. Seasonal changes in factors controlling phytoplankton growth in Beatrix Bay, New Zealand. New Zealand Journal of Marine and Freshwater Research 31: 237-248. Haure J, Penisson C, Bougrier S, Baud JP 1998. Influence of temperature on the clearance and oxygen consumption rates of the flat oyster Ostrea edulis: determination of allometric coefficients. Aquaculture 169: 211-224. Hawkins AJS, James MR, Hickman RW, Weatherhead M 1999. Modelling of suspension- feeding and growth in the green-lipped mussel Perna canaliculus exposed to natural and experimental variations of seston available in the Marlborough Sounds, New Zealand. Marine Ecology Progress Series 191: 217-232. Hawkins AJS, Fang JG, Pascoe PL, Zhang JH, Zhang XL, Zhu MY 2001. Modelling short- term responsive adjustments in particle clearance rate among bivalve suspension- feeders: separate unimodal effects of seston volume and composition in the scallop Chlamys farreri. Journal of Experimental Marine Biology and Ecology 262: 61-73. Higano J, Hirano K, Kitahara S, Fuji A 2005. Filtration and ammonia excretion of Manila clam, Ruditapes philippinarum, and their ecological impacts in Ariake Sound, Japan. Journal of Shellfish Research 24: 657-658.

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Iglesias JIP, Urrutia MB, Navarro E, Alvarez Jorna P, Larretxea X, Bougrier S, Heral M 1996. Variability of feeding processes in the cockle Cerastoderma edule (L.) in response to changes in seston concentration and composition. Journal of Experimental Marine Biology and Ecology 197: 121-143. James MR, Wetherhead M, Ross AH 2001. Size-specific clearance, excretion, and respiration rates, and phytoplankton selectivity for the mussel Perna canaliculus at low levels of natural food. New Zealand Journal of Marine and Freshwater Research 35: 73-86. Jiang W, Gibbs MT 2005. Predicting the carrying capacity of bivalve shellfish culture using a steady, linear food web model. Aquaculture 244: 171-185. Keeley NB 2001. Seston supply & scallop (Pecten novaezelandiae) production in the Firth of Thames, New Zealand. MPhil Thesis. Biological Sciences, University of Waikato, New Zealand. Laing I 2004. Filtration of king scallops (Pecten maximus). Aquaculture 240: 369-384. Navarro E, Iglesias JIP, Ortega MM 1992. Natural sediment as a food source for the cockle Cerastoderma edule (L.): effect of variable particle concentration on feeding, digestion, and the scope for growth. Journal of Experimental Marine Biology and Ecology 156: 69-87. Ogilvie SC, Ross AH, James MR, Schiel DR 2003. In situ enclosure experiments on the influence of cultured mussels (Perna canaliculus) on phytoplankton at times of high and low ambient nitrogen. Journal of Experimental Marine Biology and Ecology 295: 23-39. Ogilvie SC, Ross AH, Schiel DR 2000. Phytoplankton biomass associated with mussel farms in Beatrix Bay, New Zealand. Aquaculture 181(1): 71-80. Pawson M 2004. The cockle Austrovenus stutchburyi and chlorophyll depletion in a southern New Zealand inlet. MSc Thesis. Marine Sciences Department, Otago University. Pilcher O 2002. The Dynamics of a Bivalve Nursery System: an investigation of the coupling dynamics between outdoor phytoplankton ponds and a pumped upweller nursery system used for ongrowing bivalve spat. University of Waikato Ren JS. Ross AH. Schiel DR 2000. Functional descriptions of feeding and energetics of the Pacific oyster Crassostrea gigas in New Zealand. Marine Ecology Progress Series 208: 119-130. Rodhouse PG, O'Kelly M 1981. Flow requirements of the oysters Ostrea edulis L. and Crassostrea gigas Thunb. in an upwelling column system of culture. Aquaculture 22: 1-10. Spencer BE 1988. Growth and filtration of juvenile oysters in experimental outdoor pumped upwelling systems. Aquaculture 75: 139-158. Teaioro I 1999. The effects of turbidity on suspension feeding bivalves. Biological Sciences. 109 p. University of Waikato. Waite RP 1989. The Nutritional biology of Perna canaliculus with special reference to intensive mariculture systems. University of Auckland. Zhu S, Saucier B, Durfey J, Chen S, Dewey B 1999. Waste excretion characteristics of Manila clams (Tapes philipinarum) under different temperature conditions. Aquacultural Engineering 20: 231-244.

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8. APPENDICES

Appendix 1. Feeding and excretion rate models used in this report.

Table 1. Models of clearance rate and total rejection rate used in the study.

Clearance rate (CR) and Total rejection rate (TRR) models used Individual measure of Environmental variables size Meat Shell Live Group dry Temp Chla TPM Species length weight Reference weight (ºC) (µg/l) (mg/l) (SL) (LW) (DW) Clams/cockles Navarro et al.(1992) C. edule √ √ Iglesias et al.(1996) C. edule √ √ Bacon et al.(1998) M. arenaria √ √ Flat oyster *Rodhouse & O’Kelly O. edulis √ √ (1981) *Spencer (1988) O. edulis √ √ √ *Haure et al.(1998) O. edulis √ √ Cupped oysters *Rodhouse & O’Kelly C. gigas √ √ (1981) *Spencer (1988) C. gigas √ √ √ Deslous Paoli et al.(1992) C. gigas √ √ *Bougrier et al.(1995) C. gigas √ √ Barille et al.(1997) C. gigas √ √ Ren et al.(2000) C. gigas √ √ √ Scallops Bacon et al.(1998) P. magellanicus √ √ Teaioro (1999) P. novaezelandiae √ √ *Hawkins et al.(2001) C. farreri √ √ √ Keeley (2001) P. novaezelandiae √ √ *Laing (2004) P. maximus √ √ Mussels *Hawkins et al.(1999) P. canaliculus √ √ √ *Denis et al.(1999) M. galloprovincialis √ √ Teaioro (2001) P. canaliculus √ √ *James et al.(2001) P. canaliculus √ √ *CR models applied to Beatrix Bay dataset

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Table 2. Models of total ammonia nitrogen excretion rate used in the study.

Total ammonia nitrogen excretion rate (TANexc) models used

Individual measure of size Environmental variables Meat Shell Live Group dry Temp Chla TPM species length weight Reference weight (ºC) (µg/l) (mg/l) (SL) (LW) (DW) Clams/cockles Zhu et al.(1999) T. phillipinarum √ √ Higano et al.(2005) R. .phillipinarum √ √ Cupped oysters Boucher et al.(1988) & C. gigas √ √ Bougrier et al.(1995) Mussels James et al.(2001) P. canaliculus √ √

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