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.

Economic value of recreational fishing in Moreton Bay and the potential impact of the marine park rezoning

In 2009, the area of the Moreton Bay Marine Park was increased from 0.5 per cent of the Bay area to 16 per cent. During the planning process, opposition by commercial and recreational fishers alike was raised, arguing that loss of fishing grounds would lead to substantial loss in economic benefits. The commercial sector was compensated through a buyback of fishing effort, but the recreational sector received no compensation. In this paper, we develop a travel cost model to estimate the potential economic impact on the recreational sector from the marine park rezoning. The results suggest that, counter to initial claims, non-market recreational fishing benefits may have increased by between $1.3m and $2.5m a year, with a current total annual value of around $20m. Keywords: Travel cost model; Economic valuation; Moreton Bay Marine Park; Recreational fishing

Analysing commercial catch and effort data from a penaeid trawl fishery: A comparison of linear models, mixed models, and generalised estimating equations approaches

Statistical methods are often used to analyse commercial catch and effort data to provide standardised fishing effort and/or a relative index of fish abundance for input into stock assessment models. Achieving reliable results has proved difficult in Australia's Northern Prawn Fishery (NPF), due to a combination of such factors as the biological characteristics of the animals, some aspects of the fleet dynamics, and the changes in fishing technology. For this set of data, we compared four modelling approaches (linear models, mixed models, generalised estimating equations, and generalised linear models) with respect to the outcomes of the standardised fishing effort or the relative index of abundance. We also varied the number and form of vessel covariates in the models. Within a subset of data from this fishery, modelling correlation structures did not alter the conclusions from simpler statistical models. The random-effects models also yielded similar results. This is because the estimators are all consistent even if the correlation structure is mis-specified, and the data set is very large. However, the standard errors from different models differed, suggesting that different methods have different statistical efficiency. We suggest that there is value in modelling the variance function and the correlation structure, to make valid and efficient statistical inferences and gain insight into the data. We found that fishing power was separable from the indices of prawn abundance only when we offset the impact of vessel characteristics at assumed values from external sources. This may be due to the large degree of confounding within the data, and the extreme temporal changes in certain aspects of individual vessels, the fleet and the fleet dynamics.

A maximum-likelihood method for estimating natural mortality and catchability coefficient from catch-and-effort data

A simple stochastic model of a fish population subject to natural and fishing mortalities is described. The fishing effort is assumed to vary over different periods but to be constant within each period. A maximum-likelihood approach is developed for estimating natural mortality (M) and the catchability coefficient (q) simultaneously from catch-and-effort data. If there is not enough contrast in the data to provide reliable estimates of both M and q, as is often the case in practice, the method can be used to obtain the best possible values of q for a range of possible values of M. These techniques are illustrated with tiger prawn (Penaeus semisulcatus) data from the Northern Prawn Fishery of Australia.

Linking spatial stock dynamics and economics: Evaluation of indicators and fishery management for the travelling eastern king prawn (Melicertus plebejus)

Reduced economic circumstances havemoved management goals towards higher profit, rather than maximum sustainable yields in several Australian fisheries. The eastern king prawn is one such fishery, for which we have developed new methodology for stock dynamics, calculation of model-based and data-based reference points and management strategy evaluation. The fishery is notable for the northward movement of prawns in eastern Australian waters, from the State jurisdiction of New South Wales to that of Queensland, as they grow to spawning size, so that vessels fishing in the northern deeper waters harvest more large prawns. Bioeconomic fishing data were standardized for calibrating a length-structured spatial operating model. Model simulations identified that reduced boat numbers and fishing effort could improve profitability while retaining viable fishing in each jurisdiction. Simulations also identified catch rate levels that were effective for monitoring in simple within-year effort-control rules. However, favourable performance of catch rate indicators was achieved only when a meaningful upper limit was placed on total allowed fishing effort. Themethods and findings will allow improved measures for monitoring fisheries and inform decision makers on the uncertainty and assumptions affecting economic indicators.

A retrospective evaluation of sustainable yields for Australia's Northern Prawn Fishery

The fundamental aim in fisheries management is to determine an optimal fishing effort for sustainably harvesting from a replenishable resource. The current management objective of Australia's Northern Prawn Fishery is to maximize the long-term net economic return following Australian government policy, resulting in an average recent catch of tiger prawn species of about 1,250 tons only. However, the maximum sustainable catch stated from different studies is around 3,000-4,700 tons. We also evaluated the net profit assuming that there was no buyback scheme in 2005 and the fishing fleet was kept at 89 vessels since 2005 and concluded that 40% more catch on average (2006-2009) and an additional total profit of A$ 17 million ( excluding crew cost) could have been gained in addition to the many millions of dollars of savings in the buyback scheme. These findings have great implications for future management in Australia and elsewhere because there is a grave concern of overfishing worldwide.

Maximum likelihood estimation of mortality and growth with individual variability from multiple length-frequency data

We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L-infinity. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

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.

Kissing fish: Rex Hunt, popular culture, sustainability and fishing practices

Natural resource managers and scientists focus on the behaviour of individual recreational fishers to understand environmental problems associated with this leisure activity. They do this in an effort to identify ways to change attitudes in order to facilitate environmentally friendly choices. This applied use of ABC psychology (attitude, behaviour, choice) has not delivered the expected results. This article offers a different approach by investigating an emergent practice in diverse fishing communities, rather than looking to the responsibility of the individual recreational fisher. Using practice theory, I trace the change from take-all to catch-and-release fishing in Australia by analysing the texts of celebrity fisher Rex Hunt, who is an advocate for releasing fish. I combine this with oral history testimony from a sample of recreational fishers from the broader Australian community to show how change happened. The practice of catch-and-release fishing emerged through the combination of sociotechnical and historically specific elements present in popular culture, including the media. Paying attention to the way different elements catalyse provides a rich account of the changing modes of sustainability in recreational fishing communities.

Effects of fish density distribution and effort distribution on catchability

The effects of fish density distribution and effort distribution on the overall catchability coefficient are examined. Emphasis is also on how aggregation and effort distribution interact to affect overall catch rate [catch per unit effort (cpue)]. In particular, it is proposed to evaluate three indices, the catchability index, the knowledge parameter, and the aggregation index, to describe the effectiveness of targeting and the effects on overall catchability in the stock area. Analytical expressions are provided so that these indices can easily be calculated. The average of the cpue calculated from small units where fishing is random is a better index for measuring the stock abundance. The overall cpue, the ratio of lumped catch and effort, together with the average cpue, can be used to assess the effectiveness of targeting. The proposed methods are applied to the commercial catch and effort data from the Australian northern prawn fishery. The indices are obtained assuming a power law for the effort distribution as an approximation of targeting during the fishing operation. Targeting increased catchability in some areas by 10%, which may have important implications on management advice.

AITPM Email Newsletter Volume 0904, April 2009: Presidents Message

President’s Report Hello fellow AITPM members, A few weeks ago we saw another example of all levels of Government pulling together in real time to try to deal with a major transport incident, this time it was container loads of ammonium nitrate falling off the Pacific Adventurer during Cyclone Hamish and the associated major oil spill due to piercing of its hull off Moreton Bay in southern Queensland. The oil spill was extensive, affecting beaches and estuaries from Moreton Island north to the Sunshine Coast; a coastal stretch of at least 60km. We saw the Queensland Government, Brisbane, Moreton Bay and Sunshine Coast Regional Council crews deployed quickly once the gravity of the situation was realised to clean up toxic oil on beaches and prevent extensive upstream contamination. Environmental agencies public and private were quick to respond to help affected wildlife. The Navy’s HMAS Yarra and another minesweeper were deployed to search for the containers in the coastal area in an effort to have them salvaged before all ammonium nitrate could leach into and harm marine habitat, which would have a substantial impact not only on that environment but also the fishing industry. all of this during the final fortnight before a State election.) While this could be branded as a maritime problem, the road transport and logistics system was crucial to the cleanup. The private vehicular ferries were enlisted to transport plant and equipment from Brisbane to Moreton Island. The plant themselves, such as graders, were drawn from road building and maintenance inventory. Hundreds of Councils’ staff were released from other activities to undertake the cleanup. While it will take some time for us to know the long term impacts of this incident, it seems difficult to fault “grassroots” government crews and their private counterparts, such as Island tourism staff, in the initial cleanup effort. From a traffic planning and management perspective, we should also remember that this sort of incident has happened on road and rail corridors in the past, albeit on lesser scales. It underlines that we do need to continue to protect communities, commercial interests, and the environment through rigorous heavy vehicle management, planning and management of dangerous goods routesincluding rail corridors through urban areas), and carefully considered incident and disaster recovery plans and protocols. I’d like to close in reminding everyone again that AITPM’s flagship event, the 2009 AITPM National Conference, Traffic Beyond Tomorrow, is being held in Adelaide from 5 to 7 August. SA Branch President Paul Morris informs me that we have had over 50 paper submissions to date, from which a very balanced and informative programme of sessions has been prepared. www.aitpm.com has all of the details about how to register, sponsor a booth, session, etc. Best regards all, Jon Bunker