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Fisheries management must address multiple, often conflicting objectives in a highly uncertain context. While the bio-economic performance of trawl fisheries faces high levels of biological and economic uncertainty, the impact of trawling on broader biodiversity is also a major concern for their management. The purpose of this study is to propose a model-based framework to formally assess the trade-offs associated with balancing biological, economic and non-target species conservation objectives in a mixed fishery. This framework is applied to the Australian Northern Prawn Fishery (NPF). We apply a stochastic co-viability framework of analysis to a multi-species bio-economic model of the NPF considering multiple management objectives. In particular, we consider the implications of including a formal non-target species conservation constraint. Results show that, due to the variability in the interactions between the fishery and the ecosystem, current management strategies present biological and economic risks. The trade-offs associated with respecting at each point in time biological, economic and non-target species conservation constraints with high probability and maximizing the net present value of the fishery are quantified.

Population models form the basis for the assessments of species in the tiger prawn component of Australia's northern prawn fishery. Penaeus semisulcatus and P. esculentus are assessed using a size-structured population model. These assessments form the basis for a control rule which predicts future total allowable catches (TACs) for P. semisulcatus and P. esculentus so that the discounted profit from the fishery is maximized. However, there are concerns with this approach: (i) the TAC predictions have consistently overpredicted actual catches and (ii) the assessment for one of the species exhibits a retrospective pattern. A series of analyses was conducted to explore the causes of these observations. Results indicate that catch, effort, and recruitment prediction can be improved substantially by changing the assumed selectivity pattern for one of the surveys, changing how the length frequency data are assembled from the raw data collected, changing the constraints on the minimum amount of effort by target fleet, modifying how the distribution of effort by week is forecasted, and dropping the length frequency data from the most recent recruitment survey. More generally, the analyses illustrate how retrospective analysis can be used to improve how assessments and projections are undertaken when the quantities of interest are known retrospectively.

This paper details Australian research that developed tools to assist fisheries managers and government agencies in engaging with the social dimension of industry and community welfare in fisheries management. These tools are in the form of objectives and indicators. These highlight the social dimensions and the effects of management plans and policy implementation on fishing industries and associated communities, while also taking into account the primacy of ecological imperatives. The deployment of these objectives and indicators initially provides a benchmark and, over the life of a management plan, can subsequently be used to identify trends in effects on a variety of social and economic elements that may be objectives in the management of a fishery. It is acknowledged that the degree to which factors can be monitored will be dependent upon resources of management agencies, however these frameworks provide a method for effectively monitoring and measuring change in the social dimension of fisheries management.Essentially, the work discussed in this paper provides fisheries management with the means to both track and begin to understand the effects of government policy and management plans on the social dimension of the fishing industry and its associated communities. Such tools allow the consideration of these elements, within an evidence base, into policy arrangements, and consequently provide an invaluable contribution to the ability to address resilience and sustainability of fishing industries and associated communities.

This paper details Australian research that developed tools to assist fisheries managers and government agencies in engaging with the social dimension of industry and community welfare in fisheries management. These tools are in the form of objectives and

This article analyzes interviews with natural resource managers in South East Queensland (SEQ), Australia. The objectives of the research are (i) to apply and test deductive/inductive text analysis methods for constructing a conceptual model of water quality decision-making in SEQ, (ii) to understand the role of information in the decision-making process, and (iii) to understand how to improve adaptive management in SEQ. Our methodology provided the means to quickly and objectively explore interview data and also reduce potential subjective bias normally associated with deductive text analysis methods. At a more practical level, our methodology indicates potential intervention points if one is to influence the decision-making process in the region. Results indicate that relevant information is often ignored in SEQ, with significant consequences for adaptive management. Contextual factors (political, social, and environmental) together with effective communication or lobbying strategies often prevent evidence-based decisions. We propose that in addition to generating information to support decisions, adaptive management also requires an appraisal of the true character of the decision-making process, which includes how stakeholders interact, what information is relevant and salient to management, and how the available information should be communicated to stakeholders and decision-making bodies. 2014 Royal Swedish Academy of Sciences.

The Australian Northern Prawn fishery (NPF) is one of the few that has adopted a dynamic version of a ‘maximum economic yield’ (MEY) target, and, on this basis, the fishery is undergoing a process of substantial stock rebuilding. This paper details the bioeconomic model that is used to provide scientific management advice for the NPF, in terms of the amount of allowable total (and tradable) gear length in the fishery, both in terms of the MEY target and the path to MEY. It combines the stock assessment process for two species of tiger prawns (brown and grooved tiger prawns) with a specification for discounted economic profits, where the harvest function in the profit equation is stock dependent. Results for the NPF show a substantial ‘stock effect’, indicating the importance of conserving fish stocks for profitability. MEY thus occurs at a stock size that is larger than that at which maximum sustainable yield is achieved, leading to a ‘win-win’ situation for both the industry (added profitability) and the environment (larger fish stocks and lower impacts on the rest of the ecosystem). Sensitivity results emphasize this effect by showing that the MEY target is much more sensitive to changes in the price of prawns and the cost of fuel, and far less so to the rate of discount.

The performance of management strategies for a prawn fishery in northern Australia is evaluated using the management strategy evaluation (MSE) approach. The operating model on which the analyses are based includes population dynamics models for four prawn species and five stocks of each species, an effort allocation model and a benthic impacts model. Management is implemented through controls on the fishing effort that targets the two main target species (Penaeus semisulcatus and Penaeus esculentus) and the technical interactions between the two species are also taken into account. The total effort set by management is distributed to regions and grid cells in each region through effort allocation models. The performance measures used in this study cover conservation of the target species, economic returns and the impact of fishing on benthic communities. Two classes of management strategy are evaluated. One class seeks to move stocks towards the target spawning stock size which is a pre-specified fraction of the spawning stock size at which Maximum Sustainable Yield (MSY) is achieved using a threshold control rule, while the other class selects time-trajectories of future effort to maximize discounted profit. Management strategies that control effort levels to maximize the total profit over the long-term outperform those which aim to move the spawning stock size toward SMSY in terms of most performance measures. For example, even when the target stock size for the MSY-based management strategy is selected to be the same as that which maximizes profits, selecting effort to maximize profits leads to lower variability in catches and profits. This study illustrates how broader ecosystem considerations can be included in MSE analyses without the need for the development and implementation of full ecosystem models and hence provides a "middle road" between single-species MSEs and full ecosystem MSEs. Crown

The development of innovative methods of stock assessment is a priority for State and Commonwealth fisheries agencies. It is driven by the need to facilitate sustainable exploitation of naturally occurring fisheries resources for the current and future economic, social and environmental well being of Australia. This project was initiated in this context and took advantage of considerable recent achievements in genomics that are shaping our comprehension of the DNA of humans and animals. The basic idea behind this project was that genetic estimates of effective population size, which can be made from empirical measurements of genetic drift, were equivalent to estimates of the successful number of spawners that is an important parameter in process of fisheries stock assessment. The broad objectives of this study were to 1. Critically evaluate a variety of mathematical methods of calculating effective spawner numbers (Ne) by a. conducting comprehensive computer simulations, and by b. analysis of empirical data collected from the Moreton Bay population of tiger prawns (P. esculentus). 2. Lay the groundwork for the application of the technology in the northern prawn fishery (NPF). 3. Produce software for the calculation of Ne, and to make it widely available. The project pulled together a range of mathematical models for estimating current effective population size from diverse sources. Some of them had been recently implemented with the latest statistical methods (eg. Bayesian framework Berthier, Beaumont et al. 2002), while others had lower profiles (eg. Pudovkin, Zaykin et al. 1996; Rousset and Raymond 1995). Computer code and later software with a user-friendly interface (NeEstimator) was produced to implement the methods. This was used as a basis for simulation experiments to evaluate the performance of the methods with an individual-based model of a prawn population. Following the guidelines suggested by computer simulations, the tiger prawn population in Moreton B