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  • 1
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    Status and rebuilding of European fisheries (2018)
    Elsevier
    In:  Marine Policy, 93 . pp. 159-170.
    Details
    Publication Date: 2021-03-19
    Description: Since January 2014, the reformed Common Fisheries Policy (CFP) of the European Union is legally binding for all Member States. It prescribes the end of overfishing and the rebuilding of all stocks above levels that can produce maximum sustainable yields (MSY). This study examines the current status, exploitation pattern, required time for rebuilding, future catch, and future profitability for 397 European stocks. Fishing pressure and biomass were estimated from 2000 to the last year with available data in 10 European ecoregions and 2 wide ranging regions. In the last year with available data, 69% of the 397 stocks were subject to ongoing overfishing and 51% of the stocks were outside of safe biological limits. Only 12% of the stocks fulfilled the prescriptions of the CFP. Fishing pressure has decreased since 2000 in some ecoregions but not in others. Barents Sea and Norwegian Sea have the highest percentage (〉60%) of sustainably exploited stocks that are capable of producing MSY. In contrast, in the Mediterranean Sea, fewer than 20% of the stocks are exploited sustainably. Overfishing is still widespread in European waters and current management, which aims at maximum sustainable exploitation, is unable to rebuild the depleted stocks and results in poor profitability. This study examines four future exploitation scenarios that are compatible with the CFP. It finds that exploitation levels of 50–80% of the maximum will rebuild stocks and lead to higher catches than currently obtained, with substantially higher profits for the fishers.
    Type: Article , PeerReviewed
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    DOI: 10.1016/j.marpol.2018.04.018
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 2
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    A new approach for estimating stock status from length frequency data (2018)
    Oxford Univ. Press
    In:  ICES Journal of Marine Science, 75 (6). pp. 2004-2015.
    Details
    Publication Date: 2021-02-08
    Description: This study presents a new method (LBB) for the analysis of length frequency data from commercial catches. LBB works for species that grow throughout their lives, such as most commercially-important fish and invertebrates, and requires no input in addition to length frequency data. It estimates asymptotic length, length at first capture, relative natural mortality, and relative fishing mortality. Standard fisheries equations can then be used to approximate current exploited biomass relative to unexploited biomass. In addition, these parameters allow the estimation of length at first capture that would maximize catch and biomass for a given fishing effort, and estimation of a proxy for the relative biomass capable of producing maximum sustainable yields. Relative biomass estimates of LBB were not significantly different from the “true” values in simulated data and were similar to independent estimates from full stock assessments. LBB also presents a new indicator for assessing whether an observed size structure is indicative of a healthy stock. LBB results will obviously be misleading if the length frequency data do not represent the size composition of the exploited size range of the stock or if length frequencies resulting from the interplay of growth and mortality are masked by strong recruitment pulses.
    Type: Article , PeerReviewed
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    DOI: 10.1093/icesjms/fsy078
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 3
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    Learning from the peer review of ‘Estimating stock status from relative abundance and resilience’ (2020)
    Institute for the Oceans and Fisheries, University of British Columbia
    In:  In: Marine and Freshwater Miscellanea II. , ed. by Pauly, D. and Ruiz-Leotaud, V. Fisheries Centre Research Reports, 28 (2). Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada, pp. 111-124.
    Details
    Publication Date: 2020-03-19
    Description: This contribution presents the detailed responses to the peer-review of Froese et al. (2019) “Estimating stock status from relative abundance and resilience” (ICES J. Mar. Sci. 2019) which outlined a method called “AMSY” for inferring biomass trends for stocks for which only catch-per-unit-effort and limited ancillary (‘priors’) data are available. The responses emphasize that the required priors are legitimate and straightforward to obtain, thus, making AMSY a method of choice in data-sparse situations. This is also a good example of the role of peer-review in validating and improving science.
    Type: Book chapter , NonPeerReviewed
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    OceanRep: Book chapter
  • 4
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    Estimating stock status from relative abundance and resilience (2020)
    Oxford Univ. Press
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    Publication Date: 2023-02-08
    Description: The Law of the Sea as well as regional and national laws and agreements require exploited populations or stocks to be managed so that they can produce maximum sustainable yields. However, exploitation level and stock status are unknown for most stocks because the data required for full stock assessments are missing. This study presents a new method (AMSY) that estimates relative population size when no catch data are available using time-series of catch-per-unit-effort or other relative abundance indices as the main input. AMSY predictions for relative stock size were not significantly different from the “true” values when compared with simulated data. Also, they were not significantly different from relative stock size estimated by data-rich models in 88% of the comparisons within 140 real stocks. Application of AMSY to 38 data-poor stocks showed the suitability of the method and led to the first assessments for 23 species. Given the lack of catch data as input, AMSY estimates of exploitation come with wide margins of uncertainty which may not be suitable for management. However, AMSY seems to be well suited for estimating productivity as well as relative stock size and may, therefore, aid in the management of data-poor stocks.
    Type: Article , PeerReviewed
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Measuring the scientific impact of FishBase after three decades (2023)
    French Ichthyological Society
    Details
    Publication Date: 2024-02-07
    Description: FishBase (www.fishbase.org) is a global, open access information system about fishes that contains published scientific data on topics such as physiology and behaviour, life-history characteristics, and species distributions. Since its creation in the late 1980s, FishBase has evolved into a highly dynamic and versatile tool for scientists and the public. The goal of this study is to quantify the impact of FishBase using citation analysis. We used three sources to count the number of times FishBase has been cited and the ways in which it has been used: Scopus for citations in peer-reviewed journals, Google Scholar for citations by a variety of items on the Internet, and Google Books for citations in books. Our findings reveal that FishBase has received more than 10,000 citations in total from 1994 to 2020 (up to 1,229 annual citations in 2020) across hundreds of peer-reviewed journals in Scopus, while Google Scholar attributed nearly 15,000 total citations to FishBase, with an average of 1,200+ citations per year from 2017 to 2021. Regions that use FishBase the most are in Europe, United States of America, Brazil, and Australia. Some of the top authors citing FishBase come from fields in agricultural (i.e., aquaculture), biological and environmental sciences, and work on fisheries biology and management, as well as parasitology, among others. Most citations of FishBase use it as a source of data for information on diet composition, fish sizes and length-weight relationships, taxonomy, or fish habitat. With a cumulative number of citations in the peer-reviewed literature exceeding 10,000 in Scopus and 15,000 in Google Scholar, FishBase is in the top 1% of all cited items published in this and the previous century.
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 6
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    Ecotrophic perspective in fisheries management: a review of Ecopath with Ecosim models in European marine ecosystems (2023)
    Frontiers
    Details
    Publication Date: 2024-02-07
    Description: The aim of this work is to present the food web models developed using the Ecopath with Ecosim (EwE) software tool to describe structure and functioning of various European marine ecosystems (eastern, central and western Mediterranean Sea; Black Sea; Bay of Biscay, Celtic Sea and Iberian coast; Baltic Sea; North Sea; English Channel, Irish Sea and west Scottish Sea; and Norwegian and Barents Seas). A total of 195 Ecopath models based on 168 scientific publications, which report original, updated and modified versions, were reviewed. Seventy models included Ecosim temporal simulations while 28 implemented Ecospace spatiotemporal dynamics. Most of the models and publications referred to the western Mediterranean Sea followed by the English Channel, Irish Sea and west Scottish Sea sub-regions. In the Mediterranean Sea, the western region had the largest number of models and publications, followed by the central and eastern regions; similar trends were observed in previous literature reviews. Most models addressed ecosystem functioning and fisheries-related hypotheses while several investigated the impact of climate change, the presence of alien species, aquaculture, chemical pollution, infrastructure, and energy production. Model complexity (i.e., number of functional groups) increased over time. Main forcing factors considered to run spatial and temporal simulations were trophic interactions, fishery, and primary production. Average scores of ecosystem indicators derived from the Ecopath summary statistics were compared. Uncertainty was also investigated based on the use of the Ecosampler plug-in and the Monte Carlo routine; only one third of the reviewed publications incorporated uncertainty analysis. Only a limited number of the models included the use of the ECOIND plug-in which provides the user with quantitative output of ecological indicators. We assert that the EwE modelling approach is a successful tool which provides a quantitative framework to analyse the structure and dynamics of ecosystems, and to evaluate the potential impacts of different management scenarios.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 7
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    New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method (2023)
    Pensoft
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    Publication Date: 2024-03-01
    Description: Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the “Catch-MSY” method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge.
    Type: Article , PeerReviewed
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 8
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    Scientific knowledge gaps on the biology of non-fish marine species across European Seas (2023)
    Frontiers
    Details
    Publication Date: 2024-03-08
    Description: Available information and potential data gaps for non-fish marine organisms (cnidarians, crustaceans, echinoderms, molluscs, sponges, mammals, reptiles, and seabirds) covered by the global database SeaLifeBase were reviewed for eight marine ecosystems (Adriatic Sea, Aegean Sea, Baltic Sea, Bay of Biscay/Celtic Sea/Iberian Coast, Black Sea, North Sea, western Mediterranean Sea, Levantine Sea) across European Seas. The review of the SeaLifeBase dataset, which is based on published literature, analyzed information coverage for eight biological characteristics (diet, fecundity, maturity, length-weight relationships, spawning, growth, lifespan, and natural mortality). These characteristics are required for the development of ecosystem and ecological models to evaluate the status of marine resources and related fisheries. Our analyses revealed that information regarding these biological characteristics in the literature was far from complete across all studied areas. The level of available information was nonetheless reasonably good for sea turtles and moderate for marine mammals in some areas (Baltic Sea, Bay of Biscay/Celtic Sea/Iberian Coast, Black Sea, North Sea and western Mediterranean Sea). Further, seven of the areas have well-studied species in terms of information coverage for biological characteristics of some commercial species whereas threatened species are generally not well studied. Across areas, the most well-studied species are the cephalopod common cuttlefish (Sepia officinalis) and the crustacean Norway lobster (Nephrops norvegicus). Overall, the information gap is narrowest for length-weight relationships followed by growth and maturity, and widest for fecundity and natural mortality. Based on these insights, we provide recommendations to prioritize species with insufficient or missing biological data that are common across the studied marine ecosystems and to address data deficiencies.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 9
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    Fish Stocks (2024)
    Elsevier
    Details
    Publication Date: 2024-04-15
    Description: Fishes occur in a wider range of habitats than any other vertebrate or invertebrate group, from the upper reaches of streams in high mountain ranges to the mouths of temperate and tropical rivers, and from the intertidal zone to the ocean's abyss. Fish grow in size, spawn and die, either from natural causes (predation, diseases, ageing) or from being caught in fishing nets if the population is exploited. These dynamical processes are expressed with mathematical equations and are used in population models to estimate fisheries reference points (stock assessment), which in turn provide the basis for fisheries management. Fish populations subjected to fisheries exploitation are called fish “stocks”. Fishing has been increasingly affecting fish stocks and ecosystems both directly and indirectly, and along with the human-induced climate change they pose major threats to fish biodiversity worldwide. Using the available data stored in local or global databases to assess the status of all stocks, even the data-poor fish stocks, and following an ecosystem approach to fisheries management that incorporates effort reduction through marine protected areas, may contribute to the sustainable exploitation of fisheries resources.
    Type: Book chapter , NonPeerReviewed
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    OceanRep: Book chapter
  • 10
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    On the pile-up effect and priors for Linf and M/K: Response to a Comment by Hordyk et al. on “A new approach for estimating stock status from length frequency data” (2019)
    Oxford Univ. Press
    Details
    Publication Date: 2023-01-12
    Description: There is a recognized need for new methods with modest data requirements to provide preliminary estimates of stock status for data-limited stocks (e.g. Rudd and Thorson, 2018). Froese et al. (2018) provide such a method, which derives estimates of relative stock size from length frequency (LF) data of exploited stocks. They show that their length-based Bayesian biomass estimation method (LBB) can reproduce the “true” parameters used in simulated data and can approximate the relative stock size as estimated independently by more data-demanding methods in 34 real stocks. However, in a comment on LBB, Hordyk et al. (2019) claim (i) that the master equation of LBB is incomplete because it does not correct for the pile-up effect caused by aggregating length measurements into length classes or “bins”, (ii) that LBB is highly sensitive to equilibrium assumptions and wrongly uses maximum observed length (Lmax) for guidance in setting a prior for the estimation of asymptotic length (Linf), and (iii) that the default prior used by LBB for the ratio between natural mortality and somatic growth rate (M/K) of 1.5 (SD = 0.15) is inadequate for many exploited species. These comments are addressed below
    Type: Article , PeerReviewed
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    OceanRep: Article in a Scientific Journal - peer-reviewed
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