21 results found
Sharma R, Winker H, Levontin P, et al., 2021, Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN's SDGs, SUSTAINABILITY, Vol: 13
Sharma R, Levontin P, Kitakado T, et al., 2020, Operating model design in tuna Regional Fishery Management Organizations: Current practice, issues and implications, FISH AND FISHERIES, Vol: 21, Pages: 940-961, ISSN: 1467-2960
Levontin P, Walton JL, Kleineberg J, 2020, Visualising uncertainty a short introduction, London, Publisher: Sad Press, ISBN: 9781912802050
How should we understand and visualise the uncertainty inherent in decision-making? A Publication of the Analysis Under Uncertainty for Decision Makers Network
Rindorf A, Mumford J, Baranowski P, et al., 2017, Moving beyond the MSY concept to reflect multidimensional fisheries management objectives, Marine Policy, Vol: 85, Pages: 33-41, ISSN: 0308-597X
Maximising the long term average catch of single stock fisheries as prescribed by the globally-legislated MSY objective is unlikely to ensure ecosystem, economic, social and governance sustainability unless an effort is made to explicitly include these considerations. We investigated how objectives to be maximised can be combined with sustainability constraints aiming specifically at one or more of these four sustainability pillars. The study was conducted as a three-year interactive process involving 290 participating science, industry, NGO and management representatives from six different European regions. Economic considerations and inclusive governance were generally preferred as the key objectives to be maximised in complex fisheries, recognising that ecosystem, social and governance constraints are also key aspects of sustainability in all regions. Relative preferences differed between regions and cases but were similar across a series of workshops, different levels of information provided and the form of elicitation methods used as long as major shifts in context or stakeholder composition did not occur. Maximising inclusiveness in governance, particularly the inclusiveness of affected stakeholders, was highly preferred by participants across the project. This suggests that advice incorporating flexibility in the interpretation of objectives to leave room for meaningful inclusiveness in decision-making processes is likely to be a prerequisite for stakeholder buy-in to management decisions.
Levontin P, Baranowski P, Leach AW, et al., 2017, On the role of visualisation in fisheries management, Marine Policy, Vol: 78, Pages: 114-121, ISSN: 1872-9460
Environmental change has focused the attention of scientists, policy makers and the wider public on the uncertainty inherent in interactions between people and the environment. Governance in fisheries is required to involve stakeholder participation and tobe more inclusive in its remit, which is no longer limited to ensuring a maximum sustainable yield from a single stock but considers species and habitat interactions, as well as social and economic issues. The increase in scope, complexity and awareness of uncertainty in fisheries management has brought methodological and institutional changes throughout the world. Progress towards comprehensive, explicit and participatory risk management in fisheries depends on effective communication. Graphic design and data visualisation have been underused in fisheries for communicating science to a wider range of stakeholders. In this paper, some of the general aspects of designing visualisations of modeling results are discussed and illustrated withexamples from the EU funded MYFISH project. These infographicswere tested in stakeholder workshops, and improved through feedbackfrom that 2process. It is desirable to convey not just modelling results but a sense of how reliable various models are. A survey was developed to judge reliability of different components of fisheries modelling: the quality of data, the quality of knowledge, model validation efforts, and robustness to key uncertainties. The results of these surveys were visualized for ten different models, and presented alongside the main case study.
Whitlock RE, Kopra J, Pakarinen T, et al., 2016, Mark-recapture estimation of mortality and migration rates for sea trout (Salmo trutta) in the northern Baltic sea, ICES JOURNAL OF MARINE SCIENCE, Vol: 74, Pages: 286-300, ISSN: 1054-3139
Kempf A, Mumford J, Levontin P, et al., 2016, The MSY concept in a multi-objective fisheries environment - Lessons from the North Sea, Marine Policy, Vol: 69, Pages: 146-158, ISSN: 1872-9460
One of the most important goals in current fisheries management is to maintain or restore stocks above levels that can produce the maximum sustainable yield (MSY). However, it may not be feasible to achieve MSY simultaneously for multiple species because of trade-offs that result from interactions between species, mixed fisheries and the multiple objectives of stakeholders. The premise in this study is that MSY is a concept that needs adaptation, not wholesale replacement. The approach chosen to identify trade-offs and stakeholder preferences involved a process of consulting and discussing options with stakeholders as well as scenario modelling with bio-economic and multi-species models. It is difficult to intuitively anticipate the consequences of complex trade-offs and it is also complicated to address them from a political point of view. However, scenario modelling showed that the current approach of treating each stock separately and ignoring trade-offs may result in unacceptable ecosystem, economic or social effects in North Sea fisheries. Setting FMSY as a management target without any flexibility for compromises may lead to disappointment for some of the stakeholders. To treat FMSY no longer as a point estimate but rather as a “Pretty Good Yield” within sustainable ranges was seen as a promising way forward to avoid unacceptable outcomes when trying to fish all stocks simultaneously at FMSY. This study gives insights on how inclusive governance can help to reach consensus in difficult political processes, and how science can be used to make informed decisions inside a multi-dimensional trade-off space.
Kell L, Levontin P, Cambell R, et al., 2016, The Quantification and Presentation of Risk, Management Science in Fisheries An Introduction to Simulation-based Methods, Editors: Edwards, Dankel, Publisher: Routledge, ISBN: 9781317615170
Acknowledgements We thank our colleagues Jake Rice (Department of Fisheries and Oceans, Ottawa, Canada), Anthony D.M. ... that helped us unify the literature on management science and management strategy evaluation in fisheries.
Maria Rincon M, Mumford JD, Levontin P, et al., 2016, The economic value of environmental data: a notional insurance scheme for the European anchovy, ICES Journal of Marine Science, Vol: 73, Pages: 1033-1041, ISSN: 1054-3139
Anchovy population dynamics in the Gulf of Cádiz are governed by environmental processes. Sea surface temperature, intense easterly winds, and discharges from the Guadalquivir River have been identified as key factors determining early life stage mortality in this anchovy stock. We have constructed an environment-based recruitment model that simulates the abundance of juveniles under alternative parameters representing plausible biological hypotheses. We are able to evaluate how modelling environment-based recruitment can affect stock assessment and how responding to environmental information can beneﬁt ﬁshery management to allow greater average catch levels through the application of harvest control rules (HCRs) based on environmental conditions. While the environment-based rules generally increase allowable catch levels the variance in catch levels also increases, detracting from the improved value based only on average yield. In addition to changes in revenue, the probability of stock collapse is also reduced by using environmental factors in HCRs. To assess the value of these management systems we simulate a notional insurance scheme, which applies a value to both average yields and uncertainty. The value of the information-driven rules can be determined by comparing the relevant premiums payable for equal levels of insurance cover on revenue within each speciﬁc management regime. We demonstrate the net value of incorporating environmental factors in the management of anchovies in the Gulf of Cádiz despite the increased variability in revenue. This could be an effective method to describe outcomes for both commercial ﬁsheries and ecosystem management policies, and as a guide to management of other species whose dynamics are predictable based on in-season observations.
Oinonen S, Gronbaek L, Laukkanen M, et al., 2016, International Fisheries Management and Recreational Benefits: The Case of Baltic Salmon, MARINE RESOURCE ECONOMICS, Vol: 31, Pages: 433-451, ISSN: 0738-1360
Carruthers TR, Kell LT, Butterworth DDS, et al., 2016, Performance review of simple management procedures, ICES Journal of Marine Science, Vol: 73, Pages: 464-482, ISSN: 1054-3139
Using a management strategy evaluation approach, we compare a range of new and established management procedures (MPs) for setting catch-limits in fisheries. Performance is evaluated with respect to fish life history type, level of stock depletion, data quality, and autocorrelation in recruitment strength. We quantify the robustness of each MP with respect to the various observation processes. Methods using observations of absolute biomass or stock depletion offer the best overall performance and this is consistent across life history types, data qualities, and stock depletion levels. Simple MPs can outperform conventional data-limited methods and data-rich assessments that use time-series of catch and effort data. MP performance is most sensitive to biases in catch data. Our results indicate that often tuning MPs for specific stocks is important, though this may not be viable in data-poor assessment scenarios because of insufficient data and analysis resources.
Romakkaniemi A, Apostolidis C, Bal G, et al., 2015, Best practices for the provision of prior information for Bayesian stock assessment, Copenhagen, Denmark, Publisher: ICES, . ICES Cooperative Research Report No 328
This manual represents a review of the potential sources and methods to be applied when providing prior information to Bayesian stock assessments and marine risk analysis. The manual is compiled as a product of the EC Framework 7 ECOKNOWS project (www.ecoknows.eu).The manual begins by introducing the basic concepts of Bayesian inference and the role of prior information in the inference. Bayesian analysis is a mathematical formalization of a sequential learning process in a probabilistic rationale. Prior information (also called ”prior knowledge”, ”prior belief”, or simply a ”prior”) refers to any existing relevant knowledge available before the analysis of the newest observations (data) and the information included in them. Prior information is input to a Bayesian statistical analysis in the form of a probability distribution (a prior distribution) that summarizes beliefs about the parameter concerned in terms of relative support for different values.Apart from specifying probable parameter values, prior information also defines how the data are related to the phenomenon being studied, i.e. the model structure. Prior information should reflect the different degrees of knowledge about different parameters and the interrelationships among them. Different sources of prior information are described as well as the particularities important for their successful utilization. The sources of prior information are classified into four main categories: (i) primary data, (ii) literature, (iii) online databases, and (iv) experts. This categorization is somewhat synthetic, but is useful for structuring the process of deriving a prior and for acknowledging different aspects of it.A hierarchy is proposed in which sources of prior information are ranked according to their proximity to the primary observations, so that use of raw data is preferred where possible. This hierarchy is reflected in the types of methods that might be suitable –
Leach AW, Levontin P, Holt J, et al., 2014, Identification and prioritization of uncertainties for management of Eastern Atlantic bluefin tuna (Thunnus thynnus), Marine Policy, Vol: 48, Pages: 84-92, ISSN: 0308-597X
In recent decades there has been steady progress towards a risk-based management approach for fisheries. An important first step in a risk analysis framework is scoping to identify, describe and catalog the sources of uncertainty that might have an impact on a fishery. This paper introduces a methodology based on a range of tools to formalize the process of elicitation of uncertainties, from both experts and stakeholders, for the International Commission for the Conservation of Atlantic Tunas (ICCAT). ICCAT is a regional fisheries management organization responsible for the conservation of tunas and other highly migratory fish in the Atlantic Ocean and its adjacent seas. The aim of the elicitation was to identify and prioritize uncertainties for inclusion in Operating Models for Management Strategy Evaluation (MSE). The tool presented in this paper supports the qualitative prioritization of uncertainties, while also visualizing the degree of consensus among stakeholders on particular issues. Perceptions of uncertainty in fisheries often vary widely among scientists, industry and other interest groups, so tools that can facilitate inclusion and representation of different opinions are useful where decision-making depends on broad agreement and more generally, where effective management depends on commitment from stakeholders.
Hillary RM, Levontin P, Kuikka S, et al., 2012, Multi-level stock-recruit analysis: Beyond steepness and into model uncertainty, ECOLOGICAL MODELLING, Vol: 242, Pages: 69-80, ISSN: 0304-3800
Edwards CTT, Hillary RM, Levontin P, et al., 2012, Fisheries Assessment and Management: A Synthesis of Common Approaches with Special Reference to Deepwater and Data-Poor Stocks, REVIEWS IN FISHERIES SCIENCE, Vol: 20, Pages: 136-153, ISSN: 1064-1262
Levontin P, Kulmala S, Haapasaari P, et al., 2011, Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon, Publisher: OXFORD UNIV PRESS
Pulkkinen H, Maentyniemi S, Kuikka S, et al., 2011, More knowledge with the same amount of data: advantage of accounting for parameter correlations in hierarchical meta-analyses, MARINE ECOLOGY PROGRESS SERIES, Vol: 443, Pages: 29-37, ISSN: 0171-8630
Kulmala S, Levontin P, Lindroos M, et al., 2010, Atlantic Salmon Fishery in the Baltic Sea – A Case of Trivial Cooperation
This paper analyses the management of the Atlantic salmon stocks in the Baltic Sea through a coalition game in the partition function form. The signs of economic and biological over-exploitation of these salmon stocks over the last two decades indicate that cooperation among the harvesting countries, under the European Union's Common Fisheries Policy, has been superficial. Combining a two-stage game of four asymmetric players with a comprehensive bioeconomic model, we conclude that cooperation under the Relative Stability Principle is not a stable outcome. In contrast, the equilibrium of the game is non-cooperation. The paper also addresses the possibility of enhancing cooperation through more flexible fishing strategies. The results indicate that partial cooperation is stable under a specific sharing scheme. It is also shown that substantial economic benefits could have been realised by reallocating the fishing effort.
Mumford JD, Leach AW, Levontin P, et al., 2009, Insurance mechanisms to mediate economic risks in marine fisheries., ICES Journal of Marine Science, Vol: 66, Pages: 950-959
Mumford JD, Leach AW, Levontin P, et al., 2008, The potential for insurance to mediate economic risks in marine fisheries, Corvalis, Oregon, USA, Fourteenth Biennial Conference of the International Institute of Fisheries Economics & Trade (IIFET), Publisher: The International Institute of Fisheries Economics & Trade
Levontin P, 1999, Ramification Groups:Hasse-Arf Theorom and Frey Curves, Publisher: University of Washington
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