The dismal record of fisheries management worldwide is often blamed on managers' and scientists' bigoted pursuit of the flawed Maximum Sustainable Yield (MSY) objective. This paper aims at clarifying that MSY has never been a key element in the EU Common Fisheries Policy (CFP), and has not been for several decades the basis of scientific advice provided in support of that policy. The recent emergence of MSY in debates about the CFP might be a rhetoric response to international pressure rather than a willing change in policy. The major danger of assigning the notorious failure of the CFP to a wrong culprit, MSY, is to distract research efforts away from investigating the real causes that likely lay in the institutional set-up. Many objections against the reference points associated with MSY, as targets or limits, are well-founded but controversies among experts, when left unbridled, just provide the opportune climate for politicians to delay actions in the direction of reduced fishing impacts on fish stocks and marine ecosystems.

We, members of the Association Francaise d'Halieumetrie, share the conviction that European fisheries have a future. It is time to get off the wrong track. Radical change is required to embark on the path of sustainable development and truly implement the ecosystem approach to fisheries. Today, high fishing pressure is deployed to catch a rare resource, which in return is responsible for the rarity. We must reverse the situation: an abundant resource that affords high catches applying moderate fishing pressure. All management tools and especially all actors must be mobilized. The transition is not simple, and European solidarity must accompany the changes. It is well worth the effort. By reducing fishing pressure, it will be possible in the medium term to restore fish stocks, to make ecosystems return to good ecological status, to stabilize and even increase catches and to considerably improve economic efficiency. This is obviously in the interest of fishers but it is also in the interest of future generations and all users of this common heritage that is the sea. (C) 2011 Elsevier B.V. All rights reserved.

Mesnil, B., and Rochet, M-J. 2010. A continuous hockey stick stock-recruit model for estimating MSY reference points. - ICES Journal of Marine Science, 67: 1780-1784.

This paper reviews a selection of nine indicators for assessing the biological state of a fish population monitored only by using trawl surveys in which catchability is assumed constant from time to time and place to place. The intention is to inform or remind of the range of possibilities and of associated practical and statistical issues. The indicators, grouped according to relationships with abundance, length, age, weight, and reproduction, are documented in a standard format covering estimation, interpretability, sensitivity, considerations for reference points where possible, and an example of their application. Lastly, selected indicators together with year-class curves fitted to abundance indices-at-age are applied to the North Sea cod to demonstrate the feasibility of an assessment based on only one trawl survey. Results support findings of the International Council for the Exploration of the Sea (ICES) working group on the assessment of demersal stocks in the North Sea and Skagerrak.

Large uncertainties in catch data (officially-reported landings and discards) are undermining the ability of scientific organisations to provide valid management advice based on the conventional approach of analytical stock assessments. There is thus an urgent need to consider alternative tools that do not depend on long series of precise age-structured catch data. This paper presents four fishery-independent assessment models developed under the EU project FISBOAT (Fishery Independent Survey Based Operational Assessment Tools). It also reports on rudimentary tests based on simulated data, using the same data sets and protocol as an evaluation study conducted by the US National Research Council in 1997. The survey-based assessment models at hand are able to reliably capture the major signal in biomass and recruitment, although they smooth out transient changes. However, they cannot provide absolute abundance estimates, only relative values on an arbitrary scale. The survey-based approaches could provide more rapid updates of the state of stocks than catch-based methods.

Statistical Process Control (SPC) methods are extensively used in manufacturing contexts to monitor production processes. This article illustrates their potential utility for monitoring the state of marine ecosystems, using survey indicators. We exemplify the use of one SPC tool, the cumulative sum (CUSUM) control chart, to detect persistent changes in the state of a system as new observations are collected, using simulated and real data. Practical guidelines are given on how the chart parameters can be tuned to achieve an acceptable compromise between the ability to detect anomalies quickly and keeping the risk of false alarms low. The common performance measures associated with control charts depend on some key assumptions being met, and the potential impact of their violation is indicated.

Ideas and considerations are put forward for managing fisheries and marine populations using primarily trawl surveys to supply biological and spatial indicators of the state of stocks, and to permit catch per unit effort (CPUE)-based assessments. Trawl surveys seldom allow absolute estimates of fish population sizes but, if appropriately located, timed, and designed, can provide a broad range of information about catchable fish species and the ecosystem that supports them. This information may be more conducive to sustainable management of fisheries than the traditional focus on the abundances of selected stocks. The paper first briefly proposes how survey-based methods might supplement existing fishery-dependent stock assessments, as would be necessary during a transition phase to a more ecosystem-orientated system of management. Full survey-based management is then considered in relation to management objectives, the selection of indicators, survey design, reference periods, levels and directions, statistical aspects, CPUE-based assessments, and management responses to good and bad signals from the ecosystem. We argue that existing fishery-dependent stock assessments cannot be claimed to produce absolute estimates of stock abundance and fishing mortality because natural mortality (M) is seldom known accurately and, therefore, that they should not be presumed superior to the relative information from surveys, and an agreeable form of adaptive management.

According to the media the French fishing industry has been in permanent state of crisis for the last 40 years. This paper recounts the events surrounding three major episodes of crises (late 1970s, mid-1990s, and early 2000s), and the measures taken by governments to resolve them. Invariably, these involved the distribution of sizeable amounts of public aids, in different forms, to the fishing sector. The efficacy of the subsidy programmes is discussed with reference to the goals stated by their proponents, regarding trade balance, competitiveness, profitability, employment and safety. Overall, the massive aids granted to the sector (comparable with the gross value of landings, annually) have not achieved the stated objectives and, paradoxically, have been a key factor in the eruption of subsequent crises, notably because they were granted without conditions of genuine changes in the industry's practices. The supreme paradox is that the succession of turbulent demonstrations over the years was the result of aid programmes devised with the overriding objective of preserving social peace.

Trenkel, V. M., Rochet, M-J., and Mesnil, B. 2007. From model-based prescriptive advice to indicator-based interactive advice. - ICES Journal of Marine Science, 64: 768-774.Traditional advice for fisheries management, especially in the ICES world, focuses on short-term stock projections relative to reference points. Primarily, two numbers, spawning-stock biomass and fishing mortality rate, are considered in the advice, although a range of biological processes are included in the stock assessment models. We propose an alternative form of final advice that would not rely on stock predictions and only two numbers, but on a suite of indicators that are combined to provide stock assessment and management advice. For a single stock, the approach consists of monitoring a set of indicators of population state and fishing pressure. Stock reference status at some time in the past is assessed, based on these indicators and/or other available information. Changes in indicator values after this reference time are then estimated, interpreted, and finally combined into a diagnostic that highlights possible causes of the changes observed. After considering management objectives, appropriate management actions can then be proposed. The proposed approach is illustrated for anglerfish stocks in the Celtic Sea and the Bay of Biscay.

A year-class curve is a plot of log cpue (catch per unit effort) over age for a single year class of a species (in contrast to the better known catch curve, fitted to multiple year classes at one time). When linear, the intercept and slope estimate the log cpue at age 0 and the average rate of total mortality, Z, respectively. Here, we suggest methodological refinements within a linear least squares framework. Candidate models may include a selectivity term, fleet-specific parameters, and polynomials in year to allow for gradual variations of Z. An iterative weighting method allows for differing precisions among the different fleets, and a forward (one-step ahead) validation procedure tests predicted cpue against observed values. Choice of the best approximating model(s) is made by ranking the biological credibility of each candidate model, then by comparing graphic plots, precision of prediction, and the Akaike Information Criterion. Two example analyses are (i) a comparison of estimated and true results for five stock simulations carried out by the US National Research Council, and (ii) modelling three beam trawl surveys for plaice (Pleuronectes platessa) in the North Sea. Results were consistent with known, age-related, offshore migrations by plaice. Year-class curves are commended as a widely applicable, statistically based, visual, and robust method.

Catch-survey analysis (CSA) is an assessment method designed to estimate absolute stock abundance from total catch and relative indices, by filtering the latter through a simple two-stage population dynamics model. it qualifies as a tool for data-limited contexts since it does not require data on the full age composition, which are the main impediment to using conventional age-based approaches, either because age data are too costly to obtain routinely, or because some species cannot be reliably aged. This paper focuses on three issues that are not clearly settled in the sparse literature dealing with CSA: i. The sensitivity of stock size estimates to the ratio of recruits to fully recruited survey catchabilities, which needs to be set by the user based on external information; this study shows that sensitivity is not dependent on the magnitude of this parameter. ii. The biases due to changes in catchability, which are to be expected when commercial CPUE data are used as indices; as with other methods, CSA estimates are biased high when increasing trends in the ratio between indices and abundance are not accounted for. iii. The effects of occasional missing indices, which are an element of data limitations; in this example, these effects are found to be small and ephemeral. Investigation of these questions was carried out using artificial data generated with a different, length- and age-structured model, providing true population states for comparisons with CSA estimates.

This paper describes a simulation study that evaluated the performance of the scientific advisory process used by ICES to recommend total allowable catches (TACs) for roundfish stocks. A "management strategy evaluation" approach is used, involving development of an operating model to represent the underlying reality, and an observation model to generate pseudo data that are then used within a management procedure. The management procedure comprises an assessment that uses data to estimate parameters of interest and a decision rule to derive TAC recommendations for the following year. There are two important results: including realistic sources and levels of uncertainty can result in far from optimal management outcomes based on the current procedures; and current ICES biomass and fishing mortality reference points are not always consistent, and several are clearly inappropriate. This is because the types of projection used by ICES do not incorporate important lags between assessing stock status and implementing management measures, and they also ignore important sources of uncertainty about the actual dynamics, as well as our ability to collect data and implement management regulations (i.e. model, measurement, and implementation error, respectively). The simulation approach also showed that better management is not necessarily going to be achieved by improving the assessment, because even with a perfect assessment (where the simulated working group knew stock status perfectly), stocks may crash at fishing levels that standard stochastic projections would suggest were safe. It is proposed that, in future, operating models that represent the best available understanding of the actual system dynamics be used to evaluate models and rules considered for application. These operating models should capture the plausible range of characteristics of the underlying dynamics, but not necessarily model their full complexity. In general, they will be more complex than those used by assessment working groups, so developing management procedures that are robust to a broad range of uncertainty. However, the models and rules used as part of the management procedure should be simpler than those used at present. Crown Copyright (c) 2005 Published by Elsevier Ltd on behalf of International Council for the Exploration of the Sea. All rights reserved.

Current scientific management objectives for ICES roundfish stocks are to ensure conservation of the biological resource and do not explicitly consider economic or social objectives. For example, there are currently no objectives to maximize the sustainable yield or to reduce variability in total allowable catches (TACs). This is despite the fact that the current system can result in wide annual fluctuations in TAC, limiting the ability of the fishing industry to plan for the future. Therefore, this study evaluated management strategies that stabilized catches by setting bounds on the interannual variability in TACs. An integrated modelling framework was used, which simulated both the real and observed systems and the interactions between system components. This allowed the evaluation of candidate management strategies with respect to the intrinsic properties of the systems, as well as our ability to observe, monitor, assess, and control them. Strategies were evaluated in terms of risk (measured as the probability of spawning-stock biomass falling below a biomass threshold for the stock) and cumulative yield. In general, bounds on interannual TAC change of 10% and 20% affected the ability to achieve management targets, although the outcome of applying TAC bounds could not have been pre-judged because results were highly dependent on the specific biology of the stock, current status, and the interaction with assessment and management. For example, for North Sea haddock, management became less responsive to fluctuations resulting from large recruitment events. Simulated target fishing mortality levels were rarely achieved, regardless of the TAC bound applied, and actual fishing mortality rates oscillated around the target. In the longer term, more restrictive bounds resulted in oscillations of greater amplitude and wavelength in yield and SSB. Bounds had less effect when a stock was close to the biomass corresponding to the target F. Risk for stocks that are declining or currently at low abundance may be greater, because if bounds restrict the extent to which TACs can be reduced each year, they could lead to collapse of the stock and the loss of all future revenue. However, for a recovered stock or one at high abundance, the loss of yield as a result of bounds would be smaller than that caused by the total collapse of the fishery. At low stock size or if the stock was declining, catches should be changed more rapidly than when the stock was increasing or at a high level, especially high stock sizes acting as an insurance against uncertainty. Therefore, rebuilding strategies, and strategies aimed at maintaining the stock above prescribed limits, should be considered separately. (c) 2005 International Council for the Exploration of the Sea. Published by Elsevier Ltd. All rights reserved.

The Catch-Survey Analysis (CSA) method of assessment aims at estimating stock abundance from relative indices by filtering measurement error in the latter through a simple two-stage population dynamics model. The method is not widely used and the associated literature is still limited. The objective of this work is to improve current understanding of the properties of the method, using data generated from a known fully age-structured population. A sensitivity analysis confirms that CSA is capable of providing reliable information about general stock trends. However, absolute estimates are sensitive to the parameter relating survey catchabilities of the two stages, which needs to be estimated externally with methods that warrant further validation. Biased results are also obtained when changes in the catchability of the fleet providing indices are not corrected for during data preparation. Conventional diagnostics fail to detect violations of the constant-q assumption and improved diagnostics are thus needed. CSA is proved to be a very valuable method to support management advice in data-limited contexts in which age data are lacking or uncertain. Subject to some refinements, it can even challenge VPA-based assessments, notably when the latter use uncertain age data.