Enhancing the Haliotis iris fishery a preliminary bioeconomic evaluation

Transcription

1 Enhancing the Haliotis iris fishery a preliminary bioeconomic evaluation Dr Anthony Hart, Principal Research Scientist, Western Australian Fisheries and Marine Research Laboratories

2 Table of Contents Executive Summary Introduction An Integrated Enhancement Fishery Bioeconomic model Conditioning the Enhancefish bioeconomic model to Haliotis iris populations Reseeding scenarios (PAU 7 - whole fishery) Reseeding scenarios (PAU 7 statistical areas P721, P722, P727, P734) Effects of enhancement on wild stock genotype Sensitivity analysis Reseeding scenario results (PAU 7 whole fishery) Reseeding scenario 1 (30% of natural recruitment and LML = 118mm) Discussion - Reseeding scenario Reseeding scenario 2 (80% of natural recruitment and LML = 118mm) Discussion - Reseeding scenario Reseeding scenario 3 (150% of natural recruitment and and LML = 110 mm) Discussion - Reseeding scenario Reseeding scenario results (areas P721, P722, P727, P734) Discussion - Reseeding scenario in proposed experimental areas Sensitivity analysis General Discussion Practical implementation References Tables Figures P a g e

3 Executive Summary This report presents a preliminary bioeconomic evaluation of an integrated enhancement fishery for Haliotis iris. The approach taken was to firstly ascertain the population biology and fishing strategy of the fishery, to ensure that the proposed reseeding scenarios were commensurate with the carrying capacity of the fishery, as indexed by annual recruitment and stock biomass. Secondly, costs of fishing and management were considered in addition to the costs of culturing and releasing juvenile paua. Finally, the potential genetic effects of reseeding were also examined. Analyses were undertaken on both the whole PAU 7 fishery, and statistical areas within PAU 7 (P721, P722, P727, P734). Three main reseeding scenarios (30%, 80% and 150% of natural recruitment) were investigated under three different survival trajectories (14%, 11%, and 7%) to the legal minimum length of 12.5 cm. Survival trajectories were based on experimentally determined mortality rates of 11 mm (1.1 cm) juvenile paua. In all scenarios, the target was a 53% increase in stock biomass. Under scenario 2 for PAU 7 (80% of natural recruitment), the target equated to a biomass increase from 1500 t to 2300 t, and a yield (catch) increase from 225 t to 393 t. Sensitivity analyses of the interacting factors of target biomass, harvest rates, size-at-fishing, size-at-release, cost-of-reseeding, cost-of fishing, and value of harvest on economic viability were also undertaken. The analyses indicated that a reseeding programme for Haliotis iris has a high chance of being economically viable, if the appropriate size and density-at-release is chosen and the programme has explicit restocking and stock enhancement targets. All scenarios examined were profitable, with the exception of those where size at release was 18+ mm. Neither cost of reseeding nor cost of fishing had a significant effect on economic viability. Instead, commercial viability of reseeding was dependent primarily on harvest price, and secondarily on size-at-release. None of the scenarios investigated resulted in a serious risk to the genetically effective population size, although the biomass of the pure strain wild stock was substantially reduced in large reseeding scenarios. To implement a commercial scale reseeding programme, a range of key issues are identified for detailed investigation. First amongst these is that industry and government must accept that an enhancement fishery will, by necessity, operate in a different manner to a traditional fishery because it is about the total system, rather than the sum of the parts. This will require cultural change and adaptation from all stakeholders and recognition of its increased complexity. 2 P a g e

4 1 Introduction Reseeding, or the release of hatchery reared juveniles into the wild to increase recruitment to the fishery, has been as been a sought after industry development and management strategy in the New Zealand paua fisheries for over 20 years (Cooper, 2010; Roberts, 2005). Reseeding can used to achieve two broad management objectives. These are restocking and stock enhancement. Restocking aims to increase the biomass of depleted populations to levels that provide sustainable yields, in other words, to levels where natural recruitment alone can sustain the fishery. Stock enhancement aims to increase the yield in the fishery by adding extra recruits over and above what the stock naturally produces. Both strategies lead to increased biomass. However they differ in their duration. Restocking is a finite activity, it will cease when sufficient biomass has been attained to produce future generations of recruits. Stock enhancement can be considered an infinite strategy, a way to maintain and stabilise higher yields without compromising spawning biomass. In practice, the reseeding research options being considered by the Paua Industry Council are primarily about stock enhancement, although there will also be restocking that occurs in a few populations subject to extensive fishing, where harvest and quota has reduced over time. A summary of the main outcomes of previous experiments has concluded that, practiced properly, reseeding of paua is likely to be economically viable at a commercial scale (Cooper, 2010; Roberts, 2005). A similar conclusion was reached by Hart et al., (2013) for greenlip abalone in Western Australia. A key difference between these studies, apart from the species in question, is that Hart et al (2013) considered an integrated program, whereby fishing quota and size limits were linked to the level of reseeding being applied to the population. This approach has not been applied to paua fisheries; instead reseeding has been evaluated as a stand-alone activity, independent from the other management rules such as size-limits and quotas. The reality however is that they are linked because, once on the sea floor, reseeded paua become part of the wild population. Knowing there is additional investment on the bottom, regardless of what state the wild adult breeding biomass is considered to be in, provides management and industry with new options to maximise sustainable and economic yield. However, the additional investment is not without risk. The placing of hatchery bred-animals into a wild population brings into question the possibilities of disease introduction from a hatchery, and potential genetic changes to wild stock diversity, as the two types of stock start to breed. The scientific disciplines of restocking and stock enhancement and their application as fishery management tools have progressed significantly in the last two decades. There are now enhancement fisheries that have been certified as sustainably managed by the MSC (Marine Stewardship Council). An example of these relevant to paua fisheries is the Japanese scallop fishery in Northern Japan ( The objective of this report is to provide a preliminary bioeconomic evaluation of an integrated enhancement fishery for Haliotis iris. 1.1 An Integrated Enhancement Fishery In simple terms, an integrated enhancement fishery considers the total system. First, the population biology and fishing strategy of the fishery is ascertained, to ensure that the proposed levels of enhancement are commensurate with the carrying capacity of the fishery. This means utilising 3 P a g e

5 reliable estimates of wild stock spawning biomass, recruitment, growth, maturity, mortality and size of fishing where available. Secondly, the costs of fishing and management are considered in addition to the costs of culturing and releasing juvenile paua. Finally, the potential genetic effects of reseeding need to be examined as these cannot be assumed to be negligible in a commercial scale enhancement program. All of these can be considered in a bioeconomic model that integrates population dynamics with the economics of aquaculture and fishing. 2 Bioeconomic model In this study, bioeconomic evaluations were undertaken using the Enhancefish model developed by Lorenzen (2005) and Lorenzen and Medley (2006), with software and manuals sourced from enhancefish.html. Enhancefish uses a dynamic pool fisheries model to quantitatively assess impacts of stock enhancement on biological and economic parameters (Lorenzen and Medley, 2006). Outcomes can be evaluated against a range of fisheries management options, such as varying levels of fishing effort and size-at-harvest. The model extends traditional dynamic pool models to accommodate stock enhancement by incorporating numerous parameters including; density dependent effects in the pre-recruit stage, population regulation in the recruited phase via size-dependent mortality and density-dependent growth, and biological differences and interactions between hatchery and wild fish (Lorenzen, 2005). Full mathematical details on the model can be sourced from Lorenzen (2005), and see Hart et al., (2013) for an application to abalone fisheries in Australia. The choice of discount rate in NPV (Net Present Value) analysis can have a large impact on the outcomes of an economic assessment. When discounting flows of economic benefits from natural or environment resources, it has been argued that smaller discount rates will more accurately reflect the needs of both current and future generations (Sumaila and Walters, 2005). This contrasts with the high discount rates that are generally applied to a risky investment strategy (e.g. 10%), which reseeding of abalone is likely to qualify as, given the lack of success in commercial scale enhancement programmes. A 6% discount rate was chosen for NPV analysis in this assessment, as a compromise between the two opposing approaches. 2.1 Conditioning the Enhancefish bioeconomic model to Haliotis iris populations The Enhancefish model is a deterministic equilibrium model, meaning that it considers only the longrun average situation, and does not model year to year variability. Its outputs are the long-run expected figures after a number of years of implementation. It is useful for exploring potential future scenarios, but needs to be calibrated against existing stock assessment models to ensure enhancement options being considered are valid in the context of the fishery and biology. To ensure the Enhancefish model can accurately describe a paua population currently being fished, biological and harvest parameters were sourced from the PAU 7 stock assessment models of Breen and Kim (2005) and MacKenzie and Smith (2009a). The final Enhancefish parameters chosen to describe the biology, economics, and stock enhancement scenarios examined for the PAU 7 fishery are summarised in Table 1. In some cases the two models specified aspects of the biology differently, for example, growth in the PAU 7 model is controlled by two parameters (Ga average growth at length 75mm, and Gb 4 P a g e

6 average growth at length 120 mm (MacKenzie and Smith, 2009a), whereas the Enhancefish model specifies growth as a function of two different parameters (average maximum length [L ; cm] and a growth coefficient (K). Care was taken to ensure that the different models gave similar biological descriptions. Enhancefish uses a size-dependent mortality model to describe survivorship of annual recruits as they grow into the population and are subject to harvest. This model is critical to understanding the success of reseeding as the largest changes in mortality are experienced at the smaller sizes. It is however, a different model from that used in the PAU 7 stock assessment model, where natural mortality (M) is assumed to be constant for all size classes between 7 and 16 cm (McKenzie and Smith, 2009a). A recent review across multiple species of abalone has confirmed that mortality is significantly related to body mass (Rosetto et al., 2012) and therefore a size-dependent mortality model is an appropriate description for survivorship in Haliotis iris. Kim et. al. (2002) investigated a size-dependent mortality model for paua assessment and found that it performed similarly to the assumption of a constant M, but they only considered the larger sizes (7+ cm). A comparison of growth (a), mortality (b), current biomass (c), recruitment (d) harvest rate (e), and average catch (f) estimated by the PAU7 and Enhancefish models is provided in Figure 2. The Enhancefish model adequately estimated the main biological and fishing parameters for PAU 7 and therefore provides a useful description of the fishery (Figure 2). The Enhancefish estimate of current spawning biomass used as a base line around which to design a reseeding programme is 1500 tonnes (Figure 2c). 2.2 Reseeding scenarios (PAU 7 - whole fishery) The appropriate levels of reseeding will be cognisant of the carrying capacity of the stock, both in terms of the total biomass that can be sustained, and the annual level of recruitment. For this analysis, the total spawning biomass target being aimed for is 2300 tonnes. This is a 53% increase on the current biomass of around 1500 tonnes, and represents a value about 60% of the original virgin biomass estimate of around tonnes (Figure 26 of McKenzie and Smith, 2009a). A total biomass of 2300 tonnes is expected to result in substantial increases in daily catch rate, without encroaching on the upper limit of biomass where density dependent reductions in growth and recruitment may occur. It is therefore an appropriate spawning biomass target to aim for. In the PAU 7 fishery the long-term average recruitment (of 7 cm animals) has been estimated at 2.4 million (Figure 2d). This can be considered as the average annual recruitment capacity that the fishery can handle. Variability in annual recruitment of 7 cm animals was estimated to be in the range of 1.5 to 3.9 million (McKenzie and Smith, 2009a; Figure 12). Using this knowledge of mean recruitment and its variability, the consequences of reseeding under 3 different scenarios to achieve the 2300 tonne biomass target, was explored. Scenario (1) 30% of average natural recruitment Scenario (2) 80% of average natural recruitment Scenario (3) 150% of average natural recruitment 5 P a g e

7 These result in estimates of 0.72, 1.92, and 3.6 million x 70 mm paua annually. Importantly, all these are within the range of natural variation recruitment in the fishery (1.5 to 3.9 million). To convert estimates of recruitment at 7 cm into the equivalent recruitment at the smaller sizes of reseeded animals (1.1 cm), three estimates of survival of a 1.1 cm animal growing to 12.5 cm (legal minimum length) were applied (14%, 11%, and 7%). These were within ranges described in the literature (Cooper, 2010; Roberts, 2005, McKenzie and Smith, 2009a). Within the Enhancefish model these cumulative survival estimates equate to values of 1.6, 1.85 and 2.15 respectively, for the mortality parameter (M 1 ). Translating these figures into release densities for reseeding resulted in the following: Scenario 1 (30% of Natural recruitment): Release Densities (1.1 cm animals) are 2.4, 2.88, and 3.6 million for a 14%, 11%, and 7% survival to 125 mm respectively Scenario 2 (80% of Natural recruitment): Release Densities (1.1 cm animals) are 6.4, 7.7, and 9.6 million for a 14%, 11%, and 7% survival respectively Scenario 3 (150% of Natural recruitment): Release Densities (1.1 cm animals) are 12, 14.4, and 18 million for a 14%, 11%, and 7% survival respectively Reseeding programmes are typified by two main activities (1) hatchery culture of juveniles, and (b) deployment into the wild. Costs of culture and release were calculated in the following manner. The base cost for hatchery culture of a 1 cm (10 mm) paua was $0.45. Each extra cm above 1 cm was charged at a rate of $0.3 per cm. Deployment costs need to account for cost of release devices, packing, transport, and deployment. An assessment of deployment costs in an Australian abalone fishery was $0.07 cm -1 (Hart et. al., 2013), and a Seafic model from the mid-2000 s estimated $0.04 $0.05 cm -1 (Roberts, 2005). A figure of $0.07 per cm was assumed for this analysis. A graphical summary of reseeding costs is provided in Figure Reseeding scenarios (PAU 7 statistical areas P721, P722, P727, P734) The recent draft research proposal on commercial scale paua reseeding in PAU 7 identified these statistical areas as the most suitable experimental areas to initiate a long-term commercial reseeding programme. For the purposes of estimating annual recruitment and reseeding targets, it was assumed that the current biomass in these areas was at a similar reduced state to overall fishery biomass, and that the same proportional increase (1.53 = 2300/1500) in spawning biomass was being sought. The average long-term catch for each of these areas was used to condition the Enhancefish bioeconomic model, from which the target spawning biomass and annual recruitment for each of these areas were determined (Table 2). The model was then used to model a reseeding scenario based on 60% of annual natural recruitment for each area. The total target biomass and annual reseeding programme were 520 t and million seeds respectively (Table 2). The outcomes in terms of changes in biomass, harvest, and profitability were examined. 2.4 Effects of enhancement on wild stock genotype A significant issue with reseeding and enhancement programs is the effect of interbreeding between wild and hatchery stock on the original genetic diversity. Differences induced by selection in the 6 P a g e

8 hatchery are passed on to the following generation, then subject to natural selection that will act in the direction of the wild phenotype, and reduce differences over successive generations. The rate at which this phenotypic change occurs is given by the heritability (h 2 ) of the traits in which the wild and hatchery phenotypes differ (Lorenzen, 2005). An advantage of the Enhancefish model is that it explicitly considers this effect in two ways. First by allowing different mortality rates to be specified for wild and stocked wild animals, and secondly by calculating the effective mixing rate between wild-stock and hatchery-stock. This mixing rate is controlled by the heritability parameter (Table 1). Heritability is the change in a quantitative trait due to selection within one generation, relative to the selection differential between the current and the optimal trait value. Heritability of morphological traits is generally around 0.2, that of fitness traits tends to be lower at between 0.01 and 0.1 (Mousseau & Roff, 1987). The main outcome of a responsible reseeding programme is to preserve the potential for adaptive evolution by maintaining sufficient genetic variability in the wild stock, from which it selects its breeders. A good example of this is the chum salmon enhanced fishery in Japan, which releases 1 billion hatchery reared salmon annually, bred from 1.3 million spawners (Miyakoshi et al., 2011). In management plans for threatened and endangered species, a minimum effective breeding population size of 500 has been recommended (Tringali and Bert, 1998, Ryman and Laikre, 1991). However, this is considered a minimum, whereas an optimum is around 5000 animals, particularly if that animal is already exploited. Using an assumption that only 33% of available breeders contribute significantly to the next-generation offspring, the minimum viable wildstock population target (for genetic conservation purposes) is 15,000. This translates into a biomass of approximately 5000 kg, or 5 tonnes, which is considered a threshold value. The different reseeding scenarios were examined for % reduction in wild stock spawning biomass to see if it fell below the threshold value of 5 tonnes. 2.5 Sensitivity analysis Because of the interacting factors of target biomass, harvest rates, size-at-fishing, and differing survival rates for different size at release, it is necessary to clearly specify the objectives for the reseeding programme in order to examine the relative effects of different factors on the profitability. The reseeding programme chosen for sensitivity analysis was scenario 2 (80% of natural recruitment; 2300 tonne biomass target), with the 11% survival trajectory (from 1.1 to cm) and a legal minimum length of 11.8 cm. Sensitivity analyses exploring the effect of varying size-at-release, costs of production and enhancement, value of harvest, and cost-of-fishing on the profitability of enhancement were investigated (see Table 1 for values tested for each variable). 3 Reseeding scenario results (PAU 7 whole fishery) Results from all reseeding scenarios were compared with a No enhancement scenario (Figure 3). The no enhancement scenario was defined by a spawning biomass of 1500 t, a harvest rate of 35%, an average annual harvest of 225 tonnes, a profitability of 6 million, a GVP of 9.7 million, and an NPV (Net Present Value) of 93.9 million (Figure 3). 7 P a g e

9 It must be noted that the commercial fishery in PAU 7 fishery in 2008 only harvested 187 tonnes (McKenzie and Smith, 2009b). An annual harvest of 225 t is the assumed total catch (Table 1 of McKenzie and Smith, 2009a), which includes an estimate of non-commercial catch (18% of total). For the purpose of ensuring the biological model was correct it was necessary to use the higher catch as the No enhancement scenario. 3.1 Reseeding scenario 1 (30% of natural recruitment and LML = 118mm) Spawning biomass and harvest rate: spawning biomass was increased from 1500 to 2240 tonnes (Figure 3a). In the high survival scenario, this was achieved by reducing the harvest rate from 35% to 22% (Figure 3b). In the low survival scenario (7%), harvest rate needed to be reduced to 14% (Figure 3b). Yield: At 14% survival, harvest increased by 40% from 225 tonnes to 316 tonnes (Figure 3c). At 11% survival, average harvest increased by 3% from 229 tonnes to 236 tonnes. At 7% survival, average harvest declined by 8% to 210 tonnes (Figure 3c). Profitability: At 14% survival, profitability increased by 58% from $6 million to $9.5 million (Figure 3d). At 11% survival, profitability increased by 23% from $6 million to $7.4 million. At 7% survival, profitability increased by 3% from $6 million to $6.3 million (Figure 3d). GVP: At 14% survival, GVP increased by 23% from $9.7 million to $12 million (Figure 3e). At 11% survival, GVP decreased by 3% to $9.4 million. At 7% survival, GVP decreased by 18% to $8 million (Figure 3e). NPV: At 14% survival, Net Present Value (NPV) increased by 46% from $93.9 million to $137 million (Figure 3f). At 11% survival, NPV increased by 6% to $100 million. At 7% survival, NPV decreased by 4% to $90 million (Figure 3f). Wild stock genotype: At 14% survival, the wildstock genotype decreased from 1500 to 705 t (Figure 3g). At 11% survival, the wildstock genotype decreased to 1100 tonnes. At 7% survival, the wildstock genotype remained at 1500 t (Figure 3g) Discussion - Reseeding scenario 1 Reseeding at an annual rate of 30% of natural recruitment was a successful restocking scenario and restored the spawning biomass to 2300 tonnes. However this only occurred in conjunction with a substantial reduction in harvest rates, to as low as 14% when survival of reseeded animals was 7% (Figure 3b). Only at the highest survival rate (14%) was there any substantial improvement in the yield and economic indicators. Profitability was still slightly higher than the no enhancement scenario even at 7% survival. There were only minor effects on the existing population genotype, none of the scenarios came close to the 5 tonne threshold. Thus there would be merit in pursuing this strategy purely for restocking purposes, although the overall economic gain to the fishery is likely to be minimal. It would however, create a substantial juvenile aquaculture and reseeding industry, with around 2 3 million releases per year. A noteworthy point is the increased profitability in the low survival scenario (Figure 3d), even though other economic indicators (GVP and NPV) were slightly reduced compared to the no enhancement. This is because of two things: (a) higher catch rates caused by the increased biomass, and (b) fishing 8 P a g e

10 at a lower minimum size of 118 mm, to optimise meat yield and decrease time to harvest. On average, a 118 mm paua is harvested 1 year earlier (age 6.5) compared to a 125 mm animal (age 7.5). 3.2 Reseeding scenario 2 (80% of natural recruitment and LML = 118mm) Spawning biomass and harvest rate: spawning biomass was increased from 1500 to 2240 tonnes (Figure 3a). In the high survival scenario, this was achieved by increasing the harvest rate from 35% to 45% (Figure 3b). In the low survival scenario (7%), harvest rate needed to be reduced to 24% to achieve the target biomass (Figure 3b). Yield: At 14% survival, harvest increased by 110% from 225 tonnes to 483 tonnes (Figure 3c). At 11% survival, average harvest increased by 71% from 229 tonnes to 393 tonnes. At 7% survival, average harvest increased by 35% to 310 tonnes (Figure 3c). Profitability: At 14% survival, profitability increased by 127% from $6 million to $13.6 million (Figure 3d). At 11% survival, profitability increased by 90% from $6 million to $11.4 million. At 7% survival, profitability increased by 50% from $6 million to $9.05 million (Figure 3d). GVP: At 14% survival, GVP increased by 90% from $9.7 million to $18.4 million (Figure 3e). At 11% survival, GVP increased by 54% to $14.9 million. At 7% survival, GVP increased by 22% to $11.8 million (Figure 3e). NPV: At 14% survival, Net Present Value (NPV) increased by 136% from $93.9 million to $222 million (Figure 3f). At 11% survival, NPV increased by 87% to $176 million. At 7% survival, NPV increased by 40% to $132 million (Figure 3f). Wild stock genotype: At 14% survival, the wildstock genotype decreased from 1500 to 400 t (Figure 3g). At 11% survival, the wildstock genotype decreased to 513 tonnes. At 7% survival, the wildstock genotype decreased to 705 t (Figure 3g) Discussion - Reseeding scenario 2 Reseeding at an annual rate of 80% of natural recruitment was a successful restocking and stock enhancement scenario. It restored the spawning biomass to 2300 tonnes and substantially increased the profitability, GVP, and NPV. Even at the lowest survival (7%), a significantly enhanced GVP (by 22%), and profitability (by 50%) occurred. There was a greater reduction in the existing wild stock genotype with the higher hatchery stock survival, however none of these scenario s resulted in wild stock biomass falling anywhere near the 5 tonne threshold. Thus there would be merit in pursuing this strategy for both restocking and stock enhancement purposes as there would be substantial economic gain to the fishery and it would create a large juvenile aquaculture and reseeding industry, with around 6 9 million releases per year. To reiterate the point above, the increased profitability is driven not only by the extra animals in the water, but also by the higher catch rates and harvest rates caused by the increased biomass, and fishing at a lower minimum size of 118 mm, to optimise meat yield and decrease time to harvest. 9 P a g e

11 3.3 Reseeding scenario 3 (150% of natural recruitment and and LML = 110 mm) Spawning biomass and harvest rate: spawning biomass was increased from 1500 to 2280 tonnes (Figure 3a). In the high survival scenario, this was achieved by increasing the harvest rate from 35% to 55% (Figure 3b). In the low survival scenario (7%), harvest rate needed to be maintained at 35% to achieve the target biomass (Figure 3b). Yield: At 14% survival, harvest increased by 191% from 225 tonnes to 667 tonnes (Figure 3c). At 11% survival, average harvest increased by 148% from 229 tonnes to 568 tonnes. At 7% survival, average harvest increased by 104% to 467 tonnes (Figure 3c). Profitability: At 14% survival, profitability increased by 213% from $6 million to $18.8 million (Figure 3d). At 11% survival, profitability increased by 175% from $6 million to $16.5 million. At 7% survival, profitability increased by 131% from $6 million to $13.9 million (Figure 3d). GVP: At 14% survival, GVP increased by 160% from $9.7 million to $25.3 million (Figure 3e). At 11% survival, GVP increased by 122% to $21.6 million. At 7% survival, GVP increased by 82% to $17.7 million (Figure 3e). NPV: At 14% survival, Net Present Value (NPV) increased by 241% from $93.9 million to $321 million (Figure 3f). At 11% survival, NPV increased by 189% to $272 million. At 7% survival, NPV increased by 46% to $137 million (Figure 3f). Wild stock genotype: At 14% survival, the wildstock genotype decreased from 1500 to 240 t (Figure 3g). At 11% survival, the wildstock genotype decreased to 285 tonnes. At 7% survival, the wildstock genotype decreased to 362 t (Figure 3g) Discussion - Reseeding scenario 3 Reseeding at an annual rate of 150% of natural recruitment was a successful restocking and stock enhancement scenario. It restored the spawning biomass to 2300 tonnes and substantially increased the profitability, GVP, and NPV. There was a greater reduction in the existing wild stock genotype than in scenario 1 or 2, however none of the scenario s resulted in wild stock biomass falling anywhere near the 5 tonne threshold. Pursuing this strategy for both restocking and stock enhancement purposes would result in substantial economic gain to the fishery and create an enormous juvenile aquaculture and reseeding industry, with around million releases per year. To reiterate the point above, the increased profitability is driven not only by the extra animals in the water, but also by the higher catch rates and harvest rates caused by the increased biomass, and fishing at a lower minimum size of 110 mm, to optimise meat yield and decrease time to harvest. It is likely however, that conducting a reseeding programme of this magnitude would push the capacity limits of the fishery, and there may be reductions in wild growth and recruitment. For example, the low survival scenario (7%) resulted in less yield and GVP to the fishery than the 14% survival trajectory for Scenario P a g e

12 4 Reseeding scenario results (areas P721, P722, P727, P734) Spawning biomass and harvest rate: spawning biomass was increased from 340 to 520 tonnes (Figure 4a). This was achieved by reducing the harvest rate from 35% to 23% (Figure 4b). Yield: Average harvest increased by 36% from 55 tonnes to 75 tonnes (Figure 4c). Profitability: Profitability increased by 45% from $1.1 million to $1.6 million (Figure 4d). GVP: GVP increased by 33% from $2.1 to $2.8 million (Figure 4e). NPV: NPV increased by 19% from $18.6 to $22.1 million (Figure 4f) Discussion - Reseeding scenario in proposed experimental areas Reseeding at an annual rate of 60% of natural recruitment (1.06 million) into the sub-areas was a successful restocking and stock enhancement scenario under the assumed 11% survival trajectory. It increased the spawning biomass, profitability, GVP, and NPV. With a well-designed reseeding programme, careful mapping of the habitat and releases area, and appropriate training of personnel, the proposed experimental reseeding proposal has a reasonable chance of being cost-effective. At the very least it will generate a substantial hatchery culture industry. 5 Sensitivity analysis For the whole of PAU 7, the reseeding programme chosen for sensitivity analysis was scenario 2 (80% of natural recruitment; 2300 tonne biomass target), with the 11% survival trajectory (from 1.1 to cm ), and a legal minimum length of 11.8 cm. Size-at-release had a large effect on economic viability. Overall, the reseeding programme was profitable for size-at-release between 0.9 and 1.7 cm (Figure 5a), however highest profitability was between 0.9 and 1.1 cm size-at-release, and it declined sharply between 1.2 and 1.7 cm size-atrelease (Figure 5a). Both the costs of reseeding (Figure 5b) and of fishing (Figure 5d) had a minimal effect on profitability of the reseeding programme over the range examined. Value of harvest had the highest effect on the overall profitability of the reseeding programme, and varied between $2 million at $28/kg to $11 million at $48/kg (Figure 4c). 6 General Discussion These analyses indicate that a reseeding programme for Haliotis iris has a high chance of being economically viable, if the appropriate size and density-at-release is chosen and the programme has explicit restocking and stock enhancement targets. All scenarios examined were economically viable, with the exception of those where size at release was 18+ mm. Neither cost of reseeding nor cost of fishing had a significant effect on economic viability. Instead, viability was dependent primarily on harvest price, and secondarily on size-at-release. 11 P a g e

13 It needs to be stressed however that this analysis is a preliminary evaluation, and a detailed evaluation using local specific knowledge and properly costed parameters would be required if the decision is made to proceed with a commercial scale programme. 6.1 Practical implementation To implement a commercial scale reseeding programme, a detailed evaluation should consider the following issues. - Industry should accept that an enhancement fishery will, by necessity, operate in a different manner to the current fishery because it is about the total system, rather than the sum of the parts. Paua divers in an enhancement fishery are not just harvester s; they may also undertaking breeding, reseeding, stock surveys, and associated R&D, so as to optimise reefspecific production and enhancement targets. - A reseeding business model needs have a sustainable growth trajectory managed under clear business rules of maximising profitability, GVP, employment. It needs to build the programme incrementally, first by targeting a specific area such as the statistical areas identified in this report, and then increasing from there, with the end goal being a whole of management area approach. - A viable business model would be for current quota owners to invest (or sell) a proportion of their capital (ITQs) into an Enhancement company that has exclusive (or near to) access to both the harvest (e.g. 55 tonnes) and initial areas proposed for the reseeding programme (e.g. P721, P722, P727, P734 in PAU 7). Such a model will provide the necessary capital and cash flow so the company can obtain business loans, invest in R&D, and proceed with building the reseeding programme on a self-sufficient basis, supported by industry development grants. - The use of the current GPS dive tracking systems to ascertain accurate habitat areas, catch and biomass levels, and guide staff to the exact reef location for release will be critical to the success of the programme. - For example, an enhancement fishery may plan rotational fishing and reseeding every 2 years in order to maximise cost-benefit, particularly as a significant cost is packing and transport of the release device to the actual habitat. Deploying and harvesting 2 years worth of seed may be more cost-effective rather than annually. - The first outcome of a cost-effective reseeding program will be substantial development of the hatchery culture sector. The second outcome will be an increase in yield and value of the wild fishery. Therefore, commercial arrangements between the wild fishery and hatchery sector should be developed to enhance the chances of a successful reseeding programme. Such arrangements must ensure that appropriate breeding and biosecurity protocols are implemented to maintain wild stock genetics and minimise disease-risk. - Biomass surveys to ascertain density and size-structure information must be integrated into the programme. These will facilitate the development of bioeconomic models. - Accurate bioeconomic models that can be tailored to area specific growth and biomass production should be cornerstone of the enhancement business. They will enable different harvesting and reseeding programmes to be simultaneously tested for their costeffectiveness, as it is likely that area or reef-specific size-limits and catch targets will be the required. 12 P a g e

14 7 References Breen P.A., Kim, S.W. (2005). The 2005 stock assessment of paua (Haliotis iris) in PAU 7. New Zealand Fisheries Assessment Report 2005/ p. Cooper J (2010). Summary and review of reseeding trials in New Zealand. A report to the Paua Industry Council Ltd. Hart AM, Strain LWS, Hesp A (2013). Stock enhancement of greenlip abalone Part III: Bioeconomic evaluation. Reviews in Fisheries Science. 21(3-4): Kim, S.W., Breen, P.A. & Andrew, N.L. (2002). Evaluation of the paua stock assessment model with an individual-based operating model. Final Research Report Ministry of Fisheries Research Project PAU200l/01. Objective 2 Lorenzen K (2005). Population dynamics and potential of fisheries stock enhancement: Practical theory for assessment and policy analysis. Phil. Trans. Royal Soc. B 360: Lorenzen K., Medley P.A.H. (2006). Enhancefish Manual (Beta Release). London: Imperial College McKenzie A., Smith, A.N.H. (2009a). The 2008 stock assessment of paua (Haliotis iris) in PAU 7. New Zealand Fisheries Assessment Report 2009/ p. McKenzie A., Smith, A.N.H. (2009b). Data inputs for the PAU 7 stock assessment in New Zealand Fisheries Assessment Report 2009/ p. Mousseau, T.A. & Roff, D.A. (1987) Natural selection and the heritability of fitness components. Heredity 59: Miyakoshi Y, Nagata M, Kitada S, Kaeriyama M (2011). Current hatchery programs and future stock management of chum salmon in Hokkaido, Northern Japan. Abstract submitted to the 4 th International Symposium on Stock Enhancement and Sea Ranching, Shanghai, China. Roberts R (2005). Paua reseeding trials in Marlborough: economic model and summary of results to date. Cawthron Report No Prepared for PAUMAC 7. Rosetteo M, De Leo G. A., Bevacqua, D., Micheli F (2012). Allometric scaling of mortality rates with body mass in abalones. Oecologia. 168: Ryman N, Laikre L (1991). Effects of supportive breeding on genetically effective population size. Conservation Biology 5(3) Sumaila, U. R., and C. Walters (2005). Intergenerational discounting: A new intuitive approach. Ecol. Econ. 52: Tringali MD, Bert TM (1998). Risk to genetic effective population size should be an important consideration in fish stock enhancement programs. Bulletin of Marine Science. 62(2): P a g e

15 8 Tables Table 1. Model parameters, baseline values, and ranges used in sensitivity analysis for the Paua 7 bioeconomic enhancement model Parameter Baseline value Range Description Growth, morphometry, and reproduction L 15.9 cm Asymptotic length at biomass 0 K 0.21 Von bertalanfy growth rate g Density dependent growth / competition coefficient cm kg -1 α Length-meat weight coefficient β Length-meat weight exponent L m 9.1 Length at 50% maturity (cm) p -4 Steepness of maturity function rp 1 Relative reproductive performance of stocked fish Life History and evolution parameters L Length at settlement (cm) A Age at settlement (years) L r 7 Length at recruitment (cm) A r 3 Age at recruitment (years) h heritability of life-history traits Natural mortality and Stock Recruitment (Beverton& Holt) M1 w 1.7 Mortality of wild phenotype at L = 1 cm, equivalent to M = 0.15 at 12 cm (McKenzie& Smith, 2009a) M1 s Mortality of stocked phenotype at L = 1 cm a Maximum recruits per unit SSb (@ L r = 7 cm) b 2,663,321 Maximum recruitment (@ L r = 7 cm) r m 5 steepness parameter (maximum annual reproductive rate) Fishing parameters and economics C c 225,000 Current average catch (kg) F Fishing mortality (0.43 equates to 35% exploitation rate) L c , 11 Gear selection length (minimum harvest size; cm) q -4 Steepness of gear selectivity curve γ Cost of fishing ($ kg -1 ; whole weight) π Ex-vessel price of fish ($ kg -1 ; whole weight) ϕ 3.5 Management cost ($ kg -1 ; whole weight) δ 6% Discount rate. For NPV analysis Stock enhancement parameters and costs D S , 9.6 Density of stocking (millions) of 1.1 cm animals under three survival rates (14%, 11%, 7%) for reseeding scenario 2 L S Length-at-stocking (cm; shell length) γ $$$ 0.60 Hatchery production + enhancement costs ($ cm -1 ) Enhancement costs assumed at $0.07 cm -1 $$$ Enhancement costs include cost of release devices, packing, transport, and deployment. 14 P a g e

16 Table 2. Average catch (t), estimated biomass and recruitment from the Enhancefish model, and proposed reseeding scenarios in the PAU 7 experimental statistical areas. Statistical Area P721 P722 P727 P734 TOTAL Population and fishery statistics Average catch (numbers) 50,000 60,000 70,000 18,000 Average catch (t)(0.275 kg per paua) Current spawning biomass (t) Annual recruitment (1.1 cm) 450, , , ,000 Recruitment (1.1 cm) per t of spawners 5,300 5,200 5,200 5,200 Reseeding scenarios Target % increase in biomass 53% 53% 53% 53% Target biomass (t) Reseeding target at 11 mm (60% of annual recruitment) 270, , ,000 96,000 1,060, P a g e

17 9 Figures Figure 1. Assumed economic costs of paua production and reseeding as a function of size-atrelease. 16 P a g e

18 (a) (b) (c) (d) (e) (f) Figure 2. Comparison of (a) growth rates [75 and 120 mm Haliotis iris], (b) mortality (shown as cumulative survival), (c) mean biomass [t], (d) mean annual recruitment [70 mm animals], (e) exploitation rate (% of available harvested), and (f) average catch [t] in the PAU 7 fishery as estimated by the PAU 7 model (McKenzie and Smith, 2009a; Breen and Kim, 2005), and the Enhancefish model. Error bars on PAU 7 model are the 5% and 95% percentiles from the model outputs. 17 P a g e

19 (a) (b) (c) (d) (e) (f) (g) Figure 3. Comparison of current PAU 7 stock and economic indicators (No enhancement) with three enhancement scenarios under varying survival (14%, 11%, 7%) of paua reseeded at 11 mm. Indicators are (a) spawning biomass, (b) harvest rate, (c) yield, (d) profitability, (e) GVP, (f) NPV Net Present Value, and (g) wildstock genotype biomass 18 P a g e

20 (a) (b) (c) (d) (e) (f) Figure 4. Comparison of current stock and economic indicators in statistical areas P721, P722, P727, and P734 of PAU 7, with those resulting from an enhancement scenario of 1.06 million reseeds (11 mm) at 11% survival. Indicators are (a) spawning biomass, (b) harvest rate, (c) yield, (d) profitability, (e) GVP, and (f) NPV Net Present Value 19 P a g e

21 (a) (b) (c) (d) Figure 5. PAU 7 reseeding: Sensitivity analysis to the effect of changes in: (a) size-at-release, (b) cost of enhancement ($ cm -1 ), (c) value of harvest ($ kg -1 ), and (d) cost of fishing on the profitability of stock enhancement in the PAU 7 fishery. All sensitivity analysis is in relation to the 11% survival trajectory (M 1 = 1.85) of scenario 2, aiming for a target biomass of 2300 tonnes. 20 P a g e