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|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|26280||2013||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Marine Policy, Volume 40, July 2013, Pages 41–52
Fishery managers are faced with the challenge of maintaining sustainable fisheries at the lowest possible cost while conforming to international and national obligations. Given that fisheries range from low to high value, there is a real need to understand how to trade ecological and economic risks, and the various costs associated with their management, against the benefits from catch. Key to this is an understanding of (a) the costs corresponding to a given level of acceptable risk, or conversely, (b) the change in risk given a change in cost investment. This paper first defines biological, economic and ecosystem risk at a whole-of-fishery level, and then develops a simple model to quantify the trade-offs between risk, cost and catch. Using as case studies Australia's federally managed fisheries that range from data-rich to data-poor, risk was quantified for target species in terms of both their limit and target reference points (defined as “biological risk” and “economic risk”, respectively), and for ecosystems in terms of overall ecological impact (defined as “ecosystem risk”). A statistical linear model was used to quantify the risk–cost–catch frontier for each of the three forms of risk. The most parsimonious models were statistically significant for each. However, the management and research costs were mostly positively correlated with risk, indicating that these tended to be reactive to risk, as opposed to risk decreasing in response to increased costs. The only model where this was not the case was for the ecosystem risk, which is probably because these risks have only recently been assessed and the management response to these risks across all the fisheries has so far been limited. For target species risks, it was not possible to develop a model for proactive use. However, the method itself has merit and, if the costs were defined to a greater level of resolution, and/or a time-dynamic modelling approach considered, these issues could potentially be addressed.
The management of renewable resources such as fisheries can be costly, with much of the cost arising from the need to understand and mitigate the risk of damage to the long-term sustainability of the resources and their related ecosystems. Given that fisheries range in value from relatively low to very high, there is a need to understand how to trade ecological and economic risk and costs associated with management against the benefits, represented by the catch. This relationship is known as the risk–cost–catch frontier . Catch can be defined in terms of both its mean and variability . As fishing pressure increases, the overall mean catch may increase, at least in the short term, but so too may its inter-annual variability. Management costs here are defined broadly in terms of the costs of (1) the information needed to assess and manage the fishery, (2) the management decision process, (3) research and (4) compliance. Finally, risk is used in the context of change and undesirable consequences to the target species and the broader ecosystem as well as to the economics of the fishery. The current study considers risk as having three components: biological risk, pertaining to the target species of the fishery, economic risk in terms of the target species, and ecosystem risk, pertaining to all species and habitats with which the fishery interacts. These are defined in detail in Section 3. Although the directions of the three-way trade-offs between risk, cost and catch are well understood conceptually (Fig. 1), this frontier is only theoretically defined. Fishery managers need to assess this trade-off both within and across fisheries. That is, for a given level of risk, what are the associated costs (management costs) and benefits (catches)? Conversely, if costs or catches are adjusted, what will be the effect on risk?Many fisheries are data-poor , ,  and  and little is known about their stock status or broader ecological impacts. An important component of the risk–cost–catch frontier is uncertainty  and . As the level of uncertainty increases, the precautionary approach  tends to move managers to reduce risk, usually by reducing catch, and/or increasing management costs to better assess and manage risk. The two-way risk–catch or risk–cost trade-offs have often been examined for individual fisheries using Management Strategy Evaluation (MSE), either for target species , , , , ,  and  or for ecosystems  and . These studies, have, in general, supported the need for greater precaution when uncertainty increases, and have shown the value of, for example, fishery independent surveys or multiple sources of data. Despite these MSE approaches, they have almost always been applied at a fishery level rather than across all the ranges of fisheries being managed by a fisheries authority. Ecological risk, embracing all the species with which a fishery interacts, has become increasingly important. The mandate of fishery management extends beyond target species to comply with, in Australia, principles of ecologically sustainable development, addressed by the Environment Protection and Biodiversity Conservation (EPBC) Act  and, more globally, adoption of ecosystem based fishery management  via, for example, the FAO Technical Guidelines for Responsible Fisheries . Mitigating against ecological risk further stretches the cost of management in terms of information needs, but also management actions and compliance costs. Such additional costs will be particularly challenging for small scale, data-poor and/or low value fisheries – meaning that it is difficult to determine risk, let alone have resources available to improve the understanding and management of these fisheries. This paper addresses the question of whether it is possible to define a general risk–cost–catch frontier that can be applied to any given fishery within a management agency's portfolio. Other than conceptually in policy  this has not been defined quantitatively, especially not across a management agency's total portfolio of fisheries. Thus managers are unable to explicitly resolve questions such as, (a) for a specified acceptable level of risk, what would be the corresponding management, research and compliance costs; (b) conversely, given a change in management cost or catch, what would be the change in risk, and is this risk acceptable; and (c) what are the minimum data requirements for, in particular, a new fishery? Australian Commonwealth managed fisheries are used to explore these questions, given the availability of data from fishery status reports (e.g. ) and ecological risk assessments , as well as AFMA data on management costs. Data from these fisheries, ranging from data-rich (e.g. the Northern Prawn Fishery) to data-poor (e.g. the Coral Sea hand collectable fishery), were used first to define biological, economic and ecosystem risk at a whole of fishery level. A quantitative trade-off frontier of risk, cost and catch across the Australian portfolio was then developed.
نتیجه گیری انگلیسی
The above limitations notwithstanding, this work represents a considered attempt to quantitatively define risk and investigate the risk–cost–catch frontier, which has not been attempted elsewhere. The contribution of the work is in the novelty of the approach and its potential value with improved data and a larger sample size (number of fisheries). Most importantly, the current implementation is instructive in terms of what it is telling us about how investment has occurred in the past. This study therefore represents a broad approach and an effective first step to defining risk and quantifying the risk–cost–catch trade-offs. While the relationships between risk, catch and risk uncertainty were intuitive, and the overall model fits were statistically significant, the practical application of the approach is limited by the positive-linear relationship between risk and cost. Regardless of its current lack of practical predictive power, the approach has been informative in highlighting the nature of historical fisheries investment and emphasising the active, and, at times, reactive nature of fisheries management to date. While addressing the issues of data quality and resolution will potentially result in an improved fit to the model and thus broaden its practical application, ultimately, time-dynamic models of the relationships between risk, catch and the costs of management should be developed.