Bioeconomic modelling and risk assessment of tiger prawn (Penaeus esculentus) stock enhancement in Exmouth Gulf, Australia

A bioeconomic model was developed to evaluate the potential performance of brown tiger prawn stock enhancement in Exmouth Gulf, Australia. This paper presents the framework for the bioeconomic model and risk assessment for all components of a stock enhancement operation, i.e. hatchery, grow-out, releasing, population dynamics, fishery, and monitoring, for a commercial scale enhancement of about 100 metric tonnes, a 25% increase in average annual catch in Exmouth Gulf. The model incorporates uncertainty in estimates of parameters by using a distribution for the parameter over a certain range, based on experiments, published data, or similar studies. Monte Carlo simulation was then used to quantify the effects of these uncertainties on the model-output and on the economic potential of a particular production target. The model incorporates density-dependent effects in the nursery grounds of brown tiger prawns. The results predict that a release of 21 million 1 g prawns would produce an estimated enhanced prawn catch of about 100 t. This scale of enhancement has a 66.5% chance of making a profit. The largest contributor to the overall uncertainty of the enhanced prawn catch was the post-release mortality, followed by the density-dependent mortality caused by released prawns. These two mortality rates are most difficult to estimate in practice and are much under-researched in stock enhancement.

Stock-recruitment relationships of the tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in the Australian Northern Prawn Fishery

This paper investigates the stock-recruitment and equilibrium yield dynamics for the two species of tiger prawns (Penaeus esculentus and Penaeus semisulcatus) in Australia's most productive prawn fishery: the Northern Prawn Fishery. Commercial trawl logbooks for 1970-93 and research surveys are used to develop population models for these prawns. A population model that incorporates continuous recruitment is developed. Annual spawning stock and recruitment indices are then estimated from the population model. Spawning stock indices represent the abundance of female prawns that are likely to spawn; recruitment indices represent the abundance of all prawns less than a certain size. The relationships between spawning stock and subsequent recruitment (SRR), between recruitment and subsequent spawning stock (RSR), and between recruitment and commercial catch were estimated through maximum-likelihood models that incorporated autoregressive terms. Yield as a function of fishing effort was estimated by constraining to equilibrium the SRR and RSR. The resulting production model was then used to determine maximum sustainable yield (MSY) and its corresponding fishing effort (f(MSY)). Long-term yield estimates for the two tiger prawn species range between 3700 and 5300 t. The fishing effort at present is close to the level that should produce MSY for both species of tiger prawns. However, current landings, recruitment and spawning stock are below the equilibrium values predicted by the models. This may be because of uncertainty in the spawning stock-recruitment relationships, a change in carrying capacity, biased estimates of fishing effort, unreliable catch statistics, or simplistic assumptions about stock structure. Although our predictions of tiger prawn yields are uncertain, management will soon have to consider new measures to counteract the effects of future increases in fishing effort.

Spawning stock dynamics of two penaeid prawns, Metapenaeus bennettae and Penaeus esculentus, in Moreton Bay, Queensland, Australia

Spawning stock dynamics of 2 commercially important penaeid prawns, Metapenaeus bennettae and Penaeus esculentus, from 9 stations in Moreton Bay (27°15'S, 153°15'E), southeast Queensland, Australia, were examined. An egg production index (EPI), based on the relative abundance, proportion that were mature or ripe, and size of adult females, was used as a measure of egg production in the 2 populations. Egg production by M. bennettae was 20 to 30 higher than that by P. esculentus, extended over 7 to 8 mo each year and peaked from February to March (late summer to early autumn). Monthly patterns in egg production by M. bennettae varied between years. In contrast, P. esculentus produced most of its eggs in a single, clearly defined peak in October (spring), although production continued to March (early autumn) each year. The seasonal onset and subsequent decline in maturation in P. esculentus were rapid. Egg production by M. bennettae was several times higher at the 5 northern stations than at the 4 southern stations and negatively correlated with salinity during the main spawning period. Egg production by P. esculentus was less varied among stations and positively correlated with depth. P. esculentus appeared more likely than M. bennettae to experience recruitment overfishing because (1) the peak spawning period for P. esculentus was dependent on relatively few adult females spawning over a short period, and (2) the selectivity of trawl nets used in the bay was much higher for P. esculentus spawners than for those of M. bennettae. Compared with more northern populations, P. esculentus in Moreton Bay matured at a larger size, had lower incidences of insemination and mature or ripe females, and had a shorter spawning period. These results suggest the likelihood of recruitment overfishing in P. esculentus increases with increasing latitude.

Estimating the efficiency of a small beam trawl for sampling tiger prawns Penaeus esculentus and P. semisulcatus in seagrass by removal experiments

The efficiency with which a small beam trawl (1 x 0.5 m mouth) sampled postlarvae and juveniles of tiger prawns Penaeus esculentus and P, semisulcatus at night was estimated in 3 tropical seagrass communities (dominated by Thalassia hemprichii, Syringodium isoetifolium and Enhalus acoroides, respectively) in the shallow waters of the Gulf of Carpentaria in northern Australia. An area of seagrass (40 x 3 m) was enclosed by a net and the beam trawl was repeatedly hand-hauled over the substrate. Net efficiency (q) was calculated using 4 methods: the unweighted Leslie, weighted Leslie, DeLury and Maximum-likelihood (ML) methods. The Maximum-likelihood is the preferred method for estimating efficiency because it makes the fewest assumptions and is not affected by zero catches. The major difference in net efficiencies was between postlarvae (mean ML q +/- 95% confidence limits = 0.66 +/- 0.16) and juveniles of both species (mean q for juveniles in water less than or equal to 1.0 m deep = 0.47 +/- 0.05), i.e. the beam trawl was more efficient at capturing postlarvae than juveniles. There was little difference in net efficiency for P, esculentus between seagrass types (T, hemprichii versus S. isoetifolium), even though the biomass and morphologies of seagrass in these communities differed greatly (biomasses were 54 and 204 g m(-2), respectively). The efficiency of the net appeared to be the same for juveniles of the 2 species in shallow water, but was lower for juvenile P, semisulcatus at high tide when the water was deeper (1.6 to 1.9 m) (0.35 +/- 0.08). The lower efficiency near the time of high tide is possibly because the prawns are more active at high than low tide, and can also escape above the net. Factors affecting net efficiency and alternative methods of estimating net efficiency are discussed.

The genetic effective and adult census size of an Australian population of tiger prawns (Penaeus esculentus)

This study compares estimates of the census size of the spawning population with genetic estimates of effective current and long-term population size for an abundant and commercially important marine invertebrate, the brown tiger prawn (Penaeus esculentus). Our aim was to focus on the relationship between genetic effective and census size that may provide a source of information for viability analyses of naturally occurring populations. Samples were taken in 2001, 2002 and 2003 from a population on the east coast of Australia and temporal allelic variation was measured at eight polymorphic microsatellite loci. Moments-based and maximum-likelihood estimates of current genetic effective population size ranged from 797 to 1304. The mean long-term genetic effective population size was 9968. Although small for a large population, the effective population size estimates were above the threshold where genetic diversity is lost at neutral alleles through drift or inbreeding. Simulation studies correctly predicted that under these experimental conditions the genetic estimates would have non-infinite upper confidence limits and revealed they might be overestimates of the true size. We also show that estimates of mortality and variance in family size may be derived from data on average fecundity, current genetic effective and census spawning population size, assuming effective population size is equivalent to the number of breeders. This work confirms that it is feasible to obtain accurate estimates of current genetic effective population size for abundant Type III species using existing genetic marker technology.

Population genetic structure of the brown tiger prawn, Penaeus esculentus, in tropical northern Australia

Eight polymorphic microsatellite loci were analysed in six population samples from four locations of the Australian endemic brown tiger prawn, Penaeus esculentus. Tests of Hardy-Weinberg equilibrium were generally in accord with expectations, with only one locus, in two samples, showing significant deviations. Three samples were taken in different years from the Exmouth Gulf. These showed no significant heterogeneity, and it was concluded that they were from a single panmictic population. A sample from Shark Bay, also on the west coast of Australia, showed barely detectable differentiation from Exmouth Gulf (F (ST) = 0 to 0.0014). A northeast sample from the Gulf of Carpentaria showed low (F (ST) = 0.008) but significant differentiation from Moreton Bay, on the east coast. However, Exmouth Gulf/Shark Bay samples were well differentiated from the Gulf of Carpentaria/Moreton Bay (F (ST) = 0.047-0.063). The data do not fit a simple isolation by distance model. It is postulated that the east-west differentiation largely reflects the isolation of east and west coast populations that occurred at the last glacial maximum when there was a land bridge between north-eastern Australia and New Guinea.

Environmental and fishing effects on the dynamics of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

This analysis of the variations of brown tiger prawn (Penaeus esculentus) catch in Moreton Bay multispecies trawl fishery estimated catchability using a delay difference model. It integrated several factors responsible for variations in catchability: targeting of fishing effort, increasing fishing power and changing availability. An analysis of covariance was used to define fishing events targeted at brown tiger prawns. A general linear model estimated inter-annual variations of fishing power. Temperature-induced changes in prawn behaviour played an important role on the dynamics of this fishery. Maximum likelihood estimates of targeted catchability (4.09 ± 0.42 × 10−4 boat-day−1) were twice as large as non-targeted catchability (1.86 ± 0.25 × 10−4 boat-day−1). The causes of recent declines in fishing effort in this fishery were discussed.

Maximum likelihood estimation of natural mortality and quantification of temperature effects on catchability of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia) using logbook data

It is common to model the dynamics of fisheries using natural and fishing mortality rates estimated independently using two separate analyses. Fishing mortality is routinely estimated from widely available logbook data, whereas natural mortality estimations have often required more specific, less frequently available, data. However, in the case of the fishery for brown tiger prawn (Penaeus esculentus) in Moreton Bay, both fishing and natural mortality rates have been estimated from logbook data. The present work extended the fishing mortality model to incorporate an eco-physiological response of tiger prawn to temperature, and allowed recruitment timing to vary from year to year. These ecological characteristics of the dynamics of this fishery were ignored in the separate model that estimated natural mortality. Therefore, we propose to estimate both natural and fishing mortality rates within a single model using a consistent set of hypotheses. This approach was applied to Moreton Bay brown tiger prawn data collected between 1990 and 2010. Natural mortality was estimated by maximum likelihood to be equal to 0.032 ± 0.002 week−1, approximately 30% lower than the fixed value used in previous models of this fishery (0.045 week−1).

Rising temperatures increased recruitment of brown tiger prawn (Penaeus esculentus) in Moreton Bay (Australia)

Abiotic factors are fundamental drivers of the dynamics of wild marine fish populations. Identifying and quantifying their influence on species targeted by the fishing industry is difficult and very important for managing fisheries in a changing climate. Using multiple regression, we investigated the influence of both temperature and rainfall on the variability of recruitment of a tropical species, the brown tiger prawn (Penaeus esculentus), in Moreton Bay which is located near the southern limit of its distribution on the east coast of Australia. A step-wise selection between environmental variables identified that variations in recruitment from 1990 to 2014 were best explained by a combination of temperature and spawning stock biomass. Temperature explains 35% of recruitment variability and spawning stock biomass 33%. This analysis suggests that increasing temperatures have increased recruitment of brown tiger prawn in Moreton Bay.

The impact of global positioning systems and plotters on fishing power in the northern prawn fishery, Australia

The impact of global positioning systems (GPS) and plotter systems on the relative fishing power of the northern prawn fishery fleet on tiger prawns (Penaeus esculentus Haswell, 1879, and P. semisulcatus de Haan, 1850) was investigated from commercial catch data. A generalized linear model was used to account for differences in fishing power between boats and changes in prawn abundance. It was found that boats that used a GPS alone had 4% greater fishing power than boats without a CPS. The addition of a plotter raised the power by 7% over boats without the equipment. For each year between the first to third that a fisher has been working with plotters, there is an additional 2 or 3% increase. It appears that when all boats have a GPS and plotter for at least 3 years, the fishing power of the fleet will increase by 12%. Management controls have reduced the efficiency of each boat and lowered the number of days available to fish, but this may not have been sufficient to counteract the increases. Further limits will be needed to maintain the desired levels of mortality.

The value of patches of intertidal seagrass to prawns depends on their proximity to mangroves

Penaeid prawns were sampled with a small seine net to test whether catches of postlarvae and juveniles in seagrass were affected by the distance of the seagrass (mainly Zostera capricorni) from mangroves and the density of the seagrass in a subtropical marine embayment. Sampling was replicated on the western and eastern sides of Moreton Bay, Queensland, Australia. Information on catches was combined with broad-scale spatial information on the distribution of habitats to estimate the contribution of four different categories of habitat (proximal dense seagrass, distal dense seagrass, proximal sparse seagrass, distal sparse seagrass) to the overall population of small prawns in these regions of Moreton Bay. The abundance of Penaeus plebejus and Metapenaeus bennettae was significantly and consistently greater in dense seagrass proximal to mangroves than in other types of habitat. Additionally, sparse seagrass close to mangroves supported more of these species than dense seagrass farther away, indicating that the role of spatial arrangement of habitats was more important than the effects of structural complexity alone. In contrast, the abundance of P. esculentus tended to be greatest in sparse seagrass distal from mangroves compared with the other habitats. The scaling up of the results from different seagrass types suggests that proximal seagrass beds on both sides of Moreton Bay provide by far the greatest contribution of juvenile M. bennettae and P. plebejus to the overall populations in the Bay.

Size and time of day affect the response of postlarvae and early juvenile grooved tiger prawns Penaeus semisulcatus De Haan (Decapoda:Penaeidae) to natural and artificial seagrass in the laboratory

Juvenile tiger prawns (Penaeus semisulcatus De Haan and P. esculentus Haswell) show a strong association with vegetated habitats and are rarely caught on non-vegetated areas. This pattern of distribution may be caused by postlarvae selecting vegetation when they settle, or to differences in post-settlement mortality in different habitats. In this study, we examined whether the postlarvae and early juvenile stages of P. semisulcatus would distinguish between seagrass (Zostera capricorni Aschers) without epiphytes, artificial seagrass and bare substratum in the laboratory. The responses of prawns reared from the egg to different stages of postlarval and juvenile development were tested to determine whether, and when, each size class showed a response to a particular habitat. Five size classes of postlarvae (average carapace lengths [CL] of 1.2, 1.4, 1.6, 1.7 and 2.0 mm) were offered a choice between Z. capricorni and bare sand. Small size classes of postlarvae either did not respond to Z. capricorni (1.2 and 1.6 mm CL), or were more abundant on bare substratum than Z. capricorni. In contrast, the largest size classes of postlarvae (1.7 and 2.0 mm CL) were more abundant on Z. capricorni during the day but not at night. The behaviour of postlarvae changed markedly at a size of 1.7 mm CL (22 days from the first nauplius): smaller postlarvae frequently swam in the water column; 1.7 and 2.0 mm CL postlarvae spent much more. time resting on the substrate and perched on seagrass leaves. This size at which postlarvae first respond to seagrass during the day, and show mainly benthic behaviour, is similar to the size at which they are found on shallow seagrass beds in northern Australia. Large postlarvae (2.7 mm CL) and juveniles (4.1 mm CL) both were more abundant on artificial seagrass than bare sand during the day but not at night, indicating that they respond to structured habitats. When large postlarvae (2.4 mm CL) and juveniles (3.5 mm CL) were offered a choice between Z. capricorni without epiphytes and artificial seagrass, they were more abundant on the Z. capricorni, which suggests that chemical cues from seagrass may explain some of the responses of P. semisulcatus to seagrass. (C) 1997 Elsevier Science B.V.

A broad-scale analysis of links between coastal fisheries production and mangrove extent : a case-study for northeastern Australia

The paradigm that mangroves are critical for sustaining production in coastal fisheries is widely accepted, but empirical evidence has been tenuous. This study showed that links between mangrove extent and coastal fisheries production could be detected for some species at a broad regional scale (1000s of kilometres) on the east coast of Queensland, Australia. The relationships between catch-per-unit-effort for different commercially caught species in four fisheries (trawl, line, net and pot fisheries) and mangrove characteristics, estimated from Landsat images were examined using multiple regression analyses. The species were categorised into three groups based on information on their life history characteristics, namely mangrove-related species (banana prawns Penaeus merguiensis, mud crabs Scylla serrata and barramundi Lates calcarifer), estuarine species (tiger prawns Penaeus esculentus and Penaeus semisulcatus, blue swimmer crabs Portunus pelagicus and blue threadfin Eleutheronema tetradactylum) and offshore species (coral trout Plectropomus spp.). For the mangrove-related species, mangrove characteristics such as area and perimeter accounted for most of the variation in the model; for the non-mangrove estuarine species, latitude was the dominant parameter but some mangrove characteristics (e.g. mangrove perimeter) also made significant contributions to the models. In contrast, for the offshore species, latitude was the dominant variable, with no contribution from mangrove characteristics. This study also identified that finer scale spatial data for the fisheries, to enable catch information to be attributed to a particular catchment, would help to improve our understanding of relationships between mangroves and fisheries production.

Deriving optimal fishing effort for managing Australia's Moreton Bay multispecies trawl fishery with aggregated effort data

Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs-the effort ranged from 9500-11 500 to 6000-7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.