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Catch statistics are perhaps the most commonly collected data and are widely available for many fisheries. However, it is currently difficult to provide scientific advice for management purposes using only catch data. This article presents a catch-only method for stock assessment of data-poor fisheries. It uses time series of catches and two priors, one for the intrinsic population growth rate derived from life history parameters, and another for stock depletion based on catch trends. The method applies an optimization algorithm to search the potential parameter space. All computations are model or equation based rather than using predefined rules. The utility of this method is demonstrated by applying it to 13 stocks in Australia that are assessed using Stock Synthesis--an assessment package that can make use of a variety of data sources. The estimated parameters, including carrying capacity, intrinsic population growth rate, maximum sustainable yield, and depletion from the catch-only method are broadly comparable with those from the full assessments. The circumstances in which the method may perform poorly, such as longer-term changes in productivity and episodic recruitment, are highlighted. [ABSTRACT FROM AUTHOR]

Ecosystem-based management (EBM) is now widely accepted as the best means of managing the complex interactions in marine systems. However, progress towards implementing and operationalizing it has been slow. We take a pragmatic approach to EBM. Our simple definition is balancing human activities and environmental stewardship in a multiple-use context. In this paper, we present case studies on the development and implementation of EBM in Australia. The case studies (Australia's Ocean Policy, the Great Barrier Reef, New South Wales (NSW) marine estate, Gladstone Harbour, and South Australia and Spencer Gulf) span different spatial scales, from national to regional to local. They also cover different levels of governance or legislated mandate. We identify the key learnings, necessary components and future needs to support better implementation. These include requirements for clearly identified needs and objectives, stakeholder ownership, well defined governance frameworks, and scientific tools to deal with conflicts and trade-offs. Without all these components, multi-sector management will be difficult and there will be a tendency to maintain a focus on single sectors. While the need to manage individual sectors remains important and is often challenging, this alone will not necessarily ensure sustainable management of marine systems confronted by increasing cumulative impacts. [ABSTRACT FROM AUTHOR]

What do you get when a lawyer, a modeller, an economist, a social scientist and an ecologist talk about the ocean? Besides an interesting conversation, it is likely there will be some consideration of how to solve many of the problems facing marine ecosystems around the world. That is precisely what the MSEAS 2016 symposium on understanding marine socio-ecological systems aimed to do. From 30 May to 3 June in Brest, France, the symposium gathered over 230 participants from around the world and from multiple disciplines to discuss the challenge of explicitly considering the human component in producing synoptic assessments of marine social-ecological systems. The symposium fostered dynamic debates on the inter-disciplinary collaborations needed to support management of ongoing and anticipated growth in multiple ocean uses, with particular consideration of the triple bottom line of ecological, economic and social sustainability. Building on the illustrations produced by a professional cartoonist during the meeting, this graphic novel summarizes the key challenges ahead in understanding marine socio-ecological systems and draws a path for future research endeavours in this domain. [ABSTRACT FROM AUTHOR]

The World Ocean presents many opportunities, with the blue economy projected to at least double in the next two decades. However, capitalizing on these opportunities presents significant challenges and a multi-sectoral, integrated approach to managing marine socio-ecological systems will be required to achieve the full benefits projected for the blue economy. Integrated ecosystem assessments have been identified as the best means of delivering the information upon which marine resource management decisions can be made. By their nature, these assessments are inter-disciplinary, but to date have mostly focused on the natural sciences. Inclusion of human dimensions into integrated ecosystem assessments has been lagging, but is fundamental. Here we report on a Symposium, and the articles emmanating from it that are included in this Theme Set, that address how to more effectively include human dimensions into integrated ecosystem assessments. We provide an introduction to each of the main symposium topics (governance, scenarios, indicators, participatory processes, and case studies), highlight the works that emerged from the symposium, and identify key areas in which more work is required. There is still a long way to go before we see end-to-end integrated ecosystem assessments inclusive of all the major current and potential ocean use sectors that also encompass multiple aspects of human dimensions. Nonetheless, it is also clear that progress is being made and we are developing tools and approaches, including the human dimension, that can inform management and position us to take advantage of the multi-sectoral opportunities of sustainable blue growth. [ABSTRACT FROM AUTHOR]

Harvest strategies (HSs) have been applied to many data-rich fisheries, and are now increasingly being applied in data-limited situations. These have been evaluated using simulation frameworks, including management strategy evaluation (MSE), but few studies have considered the full spectrum from data-rich to data-limited strategies, in the context of the risk-cost-catch trade-off. This involves evaluating whether the cost of implementing a HS, the risk to the resource and catch taken from the resource have been appropriately balanced, given the value of the resource. HSs implemented for Australian Commonwealth fisheries were placed in eight tiers, ranging from data-rich to data-limited, and their performance evaluated using an MSE based on a full end-to-end ecosystem model. Generally, the risk to the resource increased as fewer data were available, due to biases in the assessments and slow response times to unexpected declines in resource status. The most datarich tiers maximize discounted catches and profits over a 45-year projection period. However, the opportunity costs response is variable, and shows that the benefit of short-term high catches have to be compensated by resource recovery in the long term. On average, more data leads to improved management in terms of risk of being overfished and not reaching a target, but this requires lower initial catches to recover the resources and lower short-term discounted profits. [ABSTRACT FROM AUTHOR]

Fisheries management operates in an environment characterized by multiple risks. These risks are often complementary and can be traded off against each other. An important goal for managers is to develop strategies to minimize the overall risk exposure at minimal cost. We show a simple model that quantifies a range of risks faced by fisheries management agencies in terms of long-term expected budgetary expenditure. The model includes not only the cost a management agency would be expected to incur from overfishing a stock, or from being seen to overfish it, but also the social cost incurred from not achieving its objectives, such as the opportunity cost of foregoing catches and economic returns. These costs can be controlled by adjusting the biomass level targeted by management, or increasing expenditures for data collection to improve the precision of biomass estimates. The overall risk, expressed as the long-term total expected cost to a management agency, depends strongly on the fisheries management objectives, and the emphasis on conservation or economic motives. In general, management under a conservation-oriented objective would reduce risk either by increasing target biomass levels or by expenditure on monitoring and assessment, while a catch-focused objective would seek to lower management costs by reducing expenditure on data collection and assessment. Increased natural stock variability affects the risk of overfishing, and long-term expected costs as the ability to make a meaningful estimate of biomass declines. Management of catch-focused fisheries would reduce the biomass target as stock variability increases, because the benefit of catches are seen to outweigh the cost, or risk of being overfished. The model provides the basis for more extensive risk analyses, and serves as a simple lesson that the consequences of reducing the short-term costs associated with managing a fishery can come with a concomitant increase in overall risk. [ABSTRACT FROM AUTHOR]

The objectives for many commercial fisheries include maximizing either yield or profit. Clearly specified management targets are a key element of effective fisheries management. Biomass targets are often specified for major commercial fisheries that are managed using quantitative stock assessments where biomass is calculated and tracked over time. BMSY, the biomass corresponding to Maximum Sustainable Yield, is often used as a target when maximizing yield is important, while BMEY is the biomass target to maximize profit. There are difficulties in estimating both quantities accurately, and this paper explores default proxies for each target biomass, expressed as biomass levels relative to carrying capacity, which are more easily estimated. Integration across a range of uncertainties about stock dynamics and the costs of fishing suggests that a proxy for BMSY in the range of 35–40% of carrying capacity minimizes the potential loss in yield compared with that which would arise if BMSY was known exactly, while a proxy for BMEY of 50–60% of carrying capacity minimizes the corresponding potential loss in profit. These estimates can be refined given stock-specific information regarding productivity (particularly the parameter which defines the resilience of recruitment to changes in spawning stock size) and costs and prices. It is more difficult to find a biomass level that achieves a high expected profit than a biomass level that achieves a high expected catch, because the former is sensitive to uncertainties related to costs and prices, as well as parameters which determine productivity. [ABSTRACT FROM PUBLISHER]

Smith, A. D. M., Smith D. C., Haddon, M., Knuckey, I., Sainsbury, K. J., and Sloan, S. 2014. Implementing harvest strategies in Australia: 5 years on. – ICES Journal of Marine Science, 71: 195–203.Australian Commonwealth fisheries are managed using a formal harvest strategy policy (HSP) introduced by the federal government in 2007. At the State level, a number of commercial fisheries are also managed under formal harvest strategies, but no overarching policy currently exists to guide their consistent implementation across jurisdictions. There have been 5 years of experience with implementation of the Commonwealth policy across the highly diverse array of commercial fisheries found in Australia. The HSP has an explicit target of maximum economic yield, and an explicit limit set at half the biomass that would support maximum sustainable yield. The policy also specifies an acceptable level of risk associated with falling below the limit reference point. We discuss the experience gained from implementing the HSP in Australia, including a number of challenges faced, and attempt to summarize the benefits and costs of implementing harvest strategies. Our view is that, overall, the benefits clearly outweigh the costs. [ABSTRACT FROM PUBLISHER]

Punt, A. E., Smith, D. C., and Smith, A. D. M. 2011. Among-stock comparisons for improving stock assessments of data-poor stocks: the “Robin Hood” approach. – ICES Journal of Marine Science, 68: 972–981.An approach is outlined for conducting stock assessments in which parameters are estimated for multiple stocks at the same time. Information from data-rich stock assessments, e.g. trends in fishing mortality, and values for parameters of selectivity functions are provided to data-poor assessments in the form of penalties on the estimated parameters, which leads to stock assessments for the most data-poor stocks being informed by those for the most data-rich stocks. The method is applied for example purposes to data for nine stocks in Australia's southern and eastern scalefish and shark fishery. The results of the application confirm that results for data-rich stocks are little impacted by being assessed in conjunction with data-poor stocks and that the results for data-poor stocks can be qualitatively different when information for data-rich stocks is taken into account. [ABSTRACT FROM PUBLISHER]