Global Fishing Index

FAQs

We have answered some of the most frequently asked questions about the Global Fishing Index below.

Why do we need a Global Fishing Index?

The Global Fishing Index aims the raise the public profile of the issue of overfishing and the need for better management and action, not only to restore fish stocks but also ensure their long-term sustainability.

We aim to reach audiences outside of those who usually engage with fisheries, raising the public profile of fisheries and the need for action.

The Index is designed to measure and track country-level progress toward the globally agreed Sustainable Development Goal target 14.4: to effectively regulate harvesting, end overfishing and restore stocks to biologically sustainable levels.

By repeating the Index at regular intervals, we can help monitor progress, including any adverse impacts and successful activities. This information can also be used to inform priority areas for interventions.

As a global analysis, the Index does not provide fishery-specific interventions. Rather, the Index should be used as a starting point to guide deeper analyses and discussions to develop fit-for-purpose solutions.

What is Minderoo doing to help address the problem of overfishing?

At Minderoo, we are working to end overfishing and ensure that all fisheries operate sustainably and responsibly.

We will work closely and in collaboration with countries that are willing to drive reforms and significant change into how their fisheries are managed. We will form alliances and partnerships with like-minded organisations, so that Minderoo’s resources can be leveraged for maximum benefit.

Aside from the Global Fishing Index, we have multiple other projects underway designed to help eliminate the drivers of overfishing, push for policy change and help build capacity to better monitor and manage fisheries.

These include:

  • working to increase accountability of distant water fishing fleets
  • measuring the extent of seafood fraud and mislabelling in the Australian seafood sector
  • campaigning to establish a stronger, more effective seafood import control system for Australia

Over the coming months, we plan to expand the scope and range of interventions that are used to ensure sustainable fisheries – focusing on the Indo-Pacific Region first.

Target countries in the region are currently being identified and will be our highest priority for active engagement and advocacy over the short, medium and long term.

We will also work with developed economies with strong influence on the fishing practices of other countries. Here, we intend to support the use of market-based approaches and policy, regulatory, industry and consumer influence to end overfishing in target countries by 2030.

We will release more details about our specific advocacy, engagement and intervention plans over the coming months.

What does the ‘Overall grade’ represent?

We awarded each country a single overall grade to communicate high-level results simply and easily.

Grades reflect a country’s current performance and the outlook for restoring fish stocks and ensuring sustainable fisheries. The highest possible grade is A, followed by B, C, D, E and F.

The grades are based on our key indicators – each country’s Progress score and Governance capacity – and are designed to complement, rather than replace these metrics. Countries fall into a grading band for different reasons, and it is important to review country specific results and recommendations alongside the grades.

First, the Progress score was used to identify the grading band. Progress scores between 0-10 represent ‘negligible progress’, Progress scores between 10-40 represent ‘limited progress’, Progress score between 40-70 represent ‘some progress’, Progress score between 70-90 represent ‘significant progress’ and Progress score between 90-100 represent achieving SDG target 14.4 and flourishing, sustainable fisheries.

We then used the Governance capacity level to determine the final overall grade. Where a country had limited Governance capacity (i.e. level 5 or lower), it was downgraded, representing an increased risk of the over exploitation of fish stocks in the future and/or limited prospect of improvement from current levels of progress towards SDG target 14.4 (Table 1).

Table 1: Rubric used to determine a country’s overall grade, based on its Progress score and Governance capacity

01-table-201-table-2
Did you use official stock assessments?

Yes, where available, we used official stock assessments from national or regional fisheries authorities and scientific advisory bodies, such as the United States’ National Oceanic and Atmospheric Administration (NOAA), the Australian Fisheries Management Authority (and state or territory authorities), the International Council for the Exploration of the Sea (ICES), the Canadian Department of Fisheries and Oceans (DFO), the New Zealand Ministry for Primary Industries, and regional fisheries management organisations (RFMOs), among others.

Where recent official estimates of relative abundance (e.g. current biomass relative to unfished biomass, B/B0) were available, these values were used directly in our analysis. This includes data from official assessments published since 2016 by national authorities or since 2014 by RFMOs.

Thirty-six percent of stocks in our dataset (527 stocks) were assessed using relative biomass estimates directly from recent official assessment results.

We understand that fisheries authorities use other methods to monitor and assess stock health, including mixed species and qualitative approaches. Where possible, this information was used to inform novel assessments for the Index. We are also exploring how to better incorporate this information in future editions of the report.

How did you estimate stock abundance, where official stock assessment results weren’t available?

Detailed biomass-based stock assessments are not available for many fish stocks globally. Because their status is ‘unknown’, they are often left out of calculations or reporting on fisheries sustainability.

To increase data coverage, particularly in developing economies, we used the reconstructed catch data, along with stock information, to derive novel estimates of biomass using established data limited methods. This was done in partnership with the Sea Around Us initiative.

First, we built out a global database of qualitative and quantitative information about the condition of individual fish stocks over time. We conducted a series of literature searches to collate a wide variety of supplementary data into a ‘priors’ database, including information from official stock assessments, scientific publications, independent biomass or relative biomass/abundance data, fisheries independent survey data, catch per unit effort data and expert opinion. This database included both publicly available data and material, as well as materials that were shared with us during the research process. In particular, we focused on collecting information about recent biomass, which could be used as an ‘end biomass prior’ in the models.

We then used established data-limited methods, CMSY++1 (an updated version of CMSY) and the Bayesian Schaefer Model (BSM)2, to derive biomass trends over time. Note, assessments conducted using CMSY++ without an informed end biomass prior were excluded from our results.

We were able to obtain sufficient information to generate biomass estimates using CMSY++ or BSM for 912 stocks. BSM assessments were used for 516 stocks (36 per cent of our dataset), while CMSY++ was used for 396 stocks (28 per cent of our dataset).

Additional details about this process are available in the Technical Methods available on the downloads page.

Are your CMSY estimates reliable?

We used a recently refined version of CMSY, known as CMSY++, to generate relative biomass estimates for 396 stocks (28 per cent of the stocks in our dataset).3, 4

CMSY uses catch data, productivity and prior knowledge about relative depletion at various points in time to estimate biomass trends over time. This approach has been independently evaluated and reviewed alongside other ‘catch-only’ methods, with reviewers identifying potential biases that need to be taken in account by users.5, 6, 7 In particular, recent reviews highlighted the need to incorporate good prior knowledge about the stock, rather than relying on default model heuristics.8, 9 These conclusions were also supported in an independent review of the CMSY method, which was commissioned by Minderoo as part of the Global Fishing Index scoping process.10

Since it has been published, the CMSY model has also been applied in over 55 scientific publications.

When applying CMSY++ for the Global Fishing Index, we undertook rigorous checks to data quality. For example, we only included stocks with a continuous catch time series of 20 years or more and with a total catch of at least 100t over the full time series, with no more than 20 per cent of their catch documented as discards. Additionally, decisions on the application of this model to various stocks was informed by expert guidance, including by Dr Rainer Froese (the creator of CMSY).

We collated a global ‘prior’s database’ to inform the assessments, with information about the reduction of biomass by fishing from carrying capacity at the start, middle and/or end of the time series. These priors include: qualitative information from local experts, conventional stock assessments and independent biomass or relative biomass/abundance data, fisheries independent survey data and catch per unit effort data. This includes data from the RAM assessment database,11, 12 as well as the primary, scientific literature and official assessments by national or regional management organisations.

Initial model results were reviewed by country and/or regional experts, where possible. Experts were also asked to provide additional information about recent biomass levels, with this data incorporated into the model to improve the reliability of the results. A total of 164 experts were contacted, with 48 providing information to improve the data for 63 countries.

Based on recognised model limitations, we excluded assessments conducted using CMSY++ without an informed ‘end biomass’ prior from our results. This resulted in the removal of approximately 1000 stock assessments from the Index’s results. You can read more about our use of CMSY and quality assurance processes in the Technical Methods available on the downloads page.

How did you determine if a stock was sustainable?

One of the measures we use to assess progress toward SDG target 14.4 is stock sustainability – that is, the proportion of fish stocks within biologically sustainable levels. This is combined with data availability to calculate a country’s Progress score in the Index. Note, while we report these supporting metrics as important contextual information, they should not be used on their own to assess a country’s performance.

In line with SDG target 14.4, we classify a fish stock whose abundance, measured using biomass, is at or greater than the level that can produce the maximum sustainable yield (MSY) as ‘sustainable’. In contrast, when abundance is below this level, we classify the stock as ‘overfished’.

We apply a single threshold for this classification, which considers a stock to be at MSY (that is, sustainable levels of abundance) when its current biomass is at 40 per cent of the unfished biomass. This approach is based on the UN Food and Agriculture Organisation’s (FAO) assessment methods13 and is based on fisheries theory, which predicts that MSY occurs at 50 per cent of unfished biomass. We apply a 10 per cent confidence band, to allow for uncertainties in the data and models. Thus, a fish stock whose abundance (biomass) is at or greater than 40 per cent of unfished levels is classified as ‘sustainable’. In contrast, when abundance is below 40 per cent of unfished levels, the stock is classified as ‘overfished’.

We recognise that the biomass that produces MSY will vary across stocks, depending on individual species characteristics, and that fisheries authorities may use different thresholds, where there is evidence to do so. However, for the purpose of the Index, we chose to apply a single threshold to all stocks to mitigate any perverse incentives for authorities to set lower, unsubstantiated levels as a means of improving their performance.

Additionally, we understand that single estimates do not account for interannual variation in stock abundance and that biomass trends over time are also important for understanding stock conditions. We also acknowledge the value of including an assessment of fishing mortality, however, this information was not available for many of the stocks in our dataset, particularly those whose results are obtained from official assessment reports.

Similarly, our approach did not consider the broader impacts of fishing on marine communities or ecological sustainability. Despite their importance, there is a general absence of information and methods for assessing these broader aspects of sustainability at a global level.

We hope to incorporate these components in future iterations of the Index.

Please see the Technical Methods, available on the downloads page, for additional information on the stock classification process.

What does the Progress score measure?

To measure each country’s progress towards SDG target 14.4, the GFI used publicly available information and reconstructed catch estimates to develop two metrics:

  1. Stock sustainability: the proportion of assessed stocks that are estimated to be at or above a level of abundance that enables MSY.
  2. Data availability: the proportion of a country’s total catch that comes from ‘assessed’ stocks, namely stocks that have sufficient data to determine their relative abundance (based on biomass) and are included in our dataset.

We combined these two metrics to produce a single Progress score, which represents a country’s current level of progress towards SDG target 14.4. The score ranges from 0, i.e. negligible progress, to 100, in which all fish stocks are assessed and estimated to be at or above sustainable levels of abundance.

Combining these two metrics helps qualify the sustainability of a country’s fisheries as whole, rather than only assessing fisheries with sufficient data. For example, while some countries may have a high proportion of assessed stocks at sustainable levels of abundance, these stocks may only represent a small proportion of the total catch in national waters. Thus, using stock sustainability alone may be misleading and misrepresent a country’s progress to SDG target 14.4.

We report these two metrics, as well as other key statistics such as the number of stocks assessed, alongside the Progress score to help identify a country’s priority areas for action; however, supporting metrics should not be used on their own to assess a country’s performance.

All treatment and analysis decisions to construct the Progress score were made using blinded country names to ensure no prior biases influenced decision-making.

What catch data did you use?

We primarily use the Sea Around Us reconstructed catch data for our analyses.

While global fisheries statistics have been collected dating back to 1950, country-level data are often incomplete or inconsistently reported, resulting in different levels of quality and completeness across countries. The reconstruction process works to address many of these issues, producing a higher-resolution and more-complete catch time series for each country. You can read a full description of the Sea Around Us catch reconstruction methods here.

Within the Index, we use the reconstructed catch in each country’s national waters to estimate the total catch for each country. This includes catches by domestic and foreign-flagged fishing vessels taken within a country’s territorial seas and exclusive economic zone (EEZ). This data is used in two ways:

  1. To calculate the ‘data availability’ metric for each country, which measures how much of the total catch in each country’s waters from 1990-2018 is represented by the assessed stocks in the Index. We use catch data dating back to 1990 to capture species that were historically caught in high volumes, but whose catches have dwindled in recent years.
  2. As input data into data-limited models (CMSY++ and BSM) when calculating novel estimates of relative abundance. For these analyses, we use the full catch time series dating back to 1950 or when the fishery started (if more recent than 1950).

There are two key benefits to using reconstructed catch data in our analyses: first, it provides a better understanding of the total fisheries catch in each country by accounting for sectors that are often excluded from official reports, such as small-scale and recreational fisheries, and second, it provides standardised source of catch data for our analyses.

How did you evaluate fisheries governance?

Governance capacity is assessed against a conceptual framework designed to capture each country’s ability to limit overfishing in its national waters. It characterises the components of the governance system currently in place in each country and does not assess the effectiveness of fisheries management. Achieving sustainable fisheries will depend on a country’s ability to implement policy, plans and activities that are committed to ‘on paper’.

Additionally, the framework does not capture ‘best-practice’ governance. Rather, it is limited to assessing the components of governance which have been linked specifically to the overexploitation of stocks. The framework was informed by extensive literature review based on published evidence to date.

The framework is organised into six dimensions, representing the different key components of fisheries governance demonstrated to be important for limiting overfishing. Dimensions are underpinned by 18 attributes representing the sub-components of governance and measured using 72 indicators. Indicators do not represent each specific action expected to limit overfishing, instead they are used in concert to estimate the strength of each conceptual component of governance.

Identifying appropriate indicators to consistently assess all countries fairly was challenging due to the very different systems of governance in place across the world. In particular, we found a paucity of indicators and data on non-conventional management approaches and small-scale fisheries, where diversity is highest. Future editions of the Index will endeavour to develop indicators that are better suited to measure alternative forms of governance.

When compiling governance indicator data into a single composite score, all treatment and analysis decisions were made using blinded country names to ensure no prior biases influenced decision-making.

How did you collect fisheries governance data?

Most of the information required to inform these indicators is unpublished previously – it is known by fisheries managers in individual countries but is not available at a global scale. Therefore, we engaged a team of 45 researchers globally to collect primary data, complemented by several existing global data sets. We used two approaches to collect data to inform indicators: an open-access online questionnaire shared across fisheries networks and interviews with local, fishery experts, including representatives from the national management agencies whose experience was considered most relevant.

The assessment instrument was designed to characterise the governance system in place, rather than survey the attitudes of respondents. As a result, the framework is most appropriate for measuring if certain components of governance are in place, not how effectively they have been implemented. This led to a positive bias in our results in countries that may have adopted fisheries policies, yet lack the capacity to implement management activities effectively in all fisheries.

We followed the methods published by the European Commission’s Competence Centre on Composite Indicators and Scoreboard to aggregate indicator data into a single composite indicator. Additional details about this process are in our Technical Methods available on the downloads page.

Our governance assessments are intended to provide a high-level summary of governance capacity, identify commonalities across countries, regions and the world and to highlight opportunities for improvement and future research.

What is a fish stock?

A fish stock is a population fish in a defined area from which catches are taken in a fishery. A fish stock may be one or multiple species of fish.

Where able, we used formally defined stock boundaries, for example from published official stock assessment reports, to identify individual fish stocks for a given species.

Where this information was not available, we used the Marine Ecoregions of the World (ME)14 to define individual stocks of a given species. Marine ecoregions were derived to spatially group ecological patterns of marine species and communities, with each ecoregion representing an ecologically distinct area. As such, ME boundaries can be used as a proxy for the geographical range of an individual stock (assuming the species is not migratory). This grouping also ensures that stock assessments are applied at appropriate ecosystem scales.

Does the Index include straddling stocks, like tuna?

Yes, the Index includes data on all marine fish stocks caught within a country’s national waters, including national, shared and straddling stocks.

At a global level, the Index includes 1,332 national or shared stocks (92 per cent of the stocks included) and 107 straddling stocks, which are managed by one of the five tuna RFMOs: the Commission for the Conservation of Southern Bluefin Tuna (CCSBT), the Inter-American Tropical Tuna Commission (IATTC), the International Commission for the Conservation of Atlantic Tuna (ICCAT), the Indian Ocean Tuna Commission (IOTC) and the Western and Central Pacific Fisheries Commission (WCPFC).

In some cases, these RFMO-managed stocks dominate a country’s total catch. While these stocks occur within a country’s national waters, they are managed at a regional level and may not accurately reflect country-level performance in terms of national fisheries sustainability. However, we recognise the importance of these stocks at a national level and the role individual countries play in ensuring sustainable management at a regional level.

To ensure that the Progress score reflects country-level performance, we ‘capped’ the score for any country where less than 10 per cent of their total catch assessed came from nationally managed stocks. This includes catches from national or shared stocks but excludes catches from straddling stocks that are managed by RFMOs.

The cap is set at the global median Progress score (23 out of 100) and has the effect of holding ‘capped’ countries in the middle scoring range until more than 10 per cent of their national catch has been assessed and the cap is removed. Twenty-six countries had their scores adjusted due to the cap.

How did you ensure the data are reliable?

Every effort was made to ensure we used the best data available to inform the Index. Both the stock sustainability and governance data sets were subject to strict quality assurance checks internally to ensure consistent methods were applied and errors detected. In instances where data were not considered accurate, they were removed from our dataset.

Our treatment of data and analyses processes were overseen by an independent panel of fisheries experts. Their collective feedback was sought to inform all decisions made to inform the use, treatment and analyses of all data. In cases where advice differed, we relied on the consensus and the stated aims of the project to guide our decisions. Expert panel members support the general direction of the Index and its methods, but do not necessarily agree with every individual methodological decision.

All treatment and analysis decisions were made using blinded country names to ensure no prior biases influenced decision-making.

Additionally, Ernst and Young has undertaken independent assessment of the Global Fishing Index Progress score and Governance capacity analyses and based on the activities undertaken it has been determined that:

  • analyses processes align to the agreed technical methods and documentation
  • the analyses processes do not alter or manipulate the relevant dataset(s) beyond the stated intent and agreed technical methods
  • comments within the scripts reflect the content and methods contained within the scripts
How many countries were included in the Index?

The 2021 edition of the Global Fishing Index includes 142 countries. The Index aims to involve all maritime countries, however, only countries which had local input to governance data collection were included.

What is the baseline data year?

The 2021 Global Fishing Index reports fisheries stock data from 2018 – the most recent year global fisheries statistics were available at the time of compilation.

The data to inform governance assessments was collected in late 2019 and early 2020.

How often will the Global Fishing Index’s results be updated?

The Index will be updated in full every three years over the coming United Nations Decade of Ocean Science from 2021-2030, with the next edition due for publication in 2024.

In the interim, we are committed to developing our methods to ensure continuous improvement.

Where minor issues and errors are identified, we will provide these on the website and update the report accordingly. The digital copy (PDF) of the report available on the Global Fishing Index website will always include any revisions.

In May 2022, we updated the results presented on the Global Fishing Index website and the materials available for download. Please see our Updates section for further details.

I think I spotted an error, how can I get in touch?

We have exercised care and diligence in the preparation of this report and have relied on information from public sources and contributors we believe to be reliable. Despite our best efforts, we understand that some information we have published may include inaccuracies.

Please help us improve the Index by reaching out to us via email to globalfishingindex@minderoo.org, with any concerns you have regarding the accuracy of our information.

How can I submit a case study to share an innovative solution?

We are seeking contributions from around the world of examples of innovations in fisheries governance. Important lessons can be learned from ‘bright spots’ – instances where strong action and innovative solutions are improving fisheries outcomes. The case studies are intended to be a living library of examples of successful approaches to inspire new solutions to address fisheries challenges.

If you have a case study to share, click the button below to get in touch with our team via email to globalfishingindex@minderoo.org.

Get in touch

Have more questions? Think something doesn’t look right? Want to share a case study, or get involved?

We have taken great care in the preparation of this report and have used information from public sources and contributors we believe to be reliable. But, despite our best efforts, we understand that sometimes people make mistakes. Please help us improve the Index by reaching out with any concerns you have about the the Index’s methods or results.

We will update the full report and findings every three years, however, any minor changes or corrections will be flagged on the website, with the PDF of the report always containing the most up-to-date content.

Endnotes

  1. Froese, R., Demirel, N., Coro, G. and Winker, H. (2021). User Guide for CMSY++, GEOMAR, Kiel, p. 17. https://oceanrep.geomar.de/52147/ [15 September 2021]
  2. Froese, R., Demirel, N., Coro, G., Kleisner, K.M. and Winker, H. (2017). Estimating Fisheries Reference Points from Catch and Resilience, Fish and Fisheries 18, (3), pp. 506-526, https://doi.org/10.1111/faf.12190 [03 June 2021]
  3. Froese, R., Demirel, N., Coro, G., Kleisner, K.M. and Winker, H. (2017). Estimating Fisheries Reference Points from Catch and Resilience, Fish and Fisheries 18, (3), pp. 506-526, https://doi.org/10.1111/faf.12190 [03 June 2021]
  4. Froese, R., Winker, H., Coro, G., Palomares, M.L.D., Tsikliras, A.C., Dimarchopoulou, D., Touloumis, K., Demirel, N., Vianna, G.M.S., Scarcella, G., Schijns, R., Liang, C. and Pauly, D. (in review). Catch Time Series As the Basis For Fish Stock Assessments: The CMSY++ Method, Fish and Fisheries,  [3 March 2021]
  5. Rosenberg, A.A., Fogarty, M.J., Cooper, A.B., Dickey-Collas, M., Fulton, E.A., Gutierrez, N.L., Hyde, K.J.W., Kleisner, K.M., Kristiansen, T., Longo, C., Minte-Vera, C.V., Minto, C., Mosqueira, I., Osio, G.C., Ovando, D., Selig, E.R., Thorson, J.T. and Ye, Y. (2014). Developing new approaches to global stock status assessment and fishery production potential of the seas, Food and Agriculture Organization of the United Nations, Rome. [2 July 2021]
  6. Pons, M., Cope, J.M. and Kell, L.T. (2020). Comparing performance of catch-based and length-based stock assessment methods in data-limited fisheries, Canadian Journal of Fisheries and Aquatic Sciences, pp. cjfas-2019-0276, https://doi.org/10.1139/cjfas-2019-0276 [19 February 2020]
  7. Free, C.M., Jensen, O.P., Anderson, S.C., Gutierrez, N.L., Kleisner, K.M., Longo, C., Minto, C., Osio, G.C. and Walsh, J.C. (2020). Blood from a stone: Performance of catch-only methods in estimating stock biomass status, Fisheries Research 223, p. 105452, 10.1016/j.fishres.2019.105452 [2019/12/16/06:32:44]
  8. Bouch, P., Minto, C. and Reid, D.G. (2021). Comparative performance of data-poor CMSY and data-moderate SPiCT stock assessment methods when applied to data-rich, real-world stocks, ICES Journal of Marine Science 78, (1), pp. 264-276, 10.1093/icesjms/fsaa220 [11/24/2021]
  9. Sharma, R., Winker, H., Levontin, P., Kell, L., Ovando, D., Palomares, M.L.D., Pinto, C. and Ye, Y. (2021). Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs, Sustainability 13, (11), https://doi.org/10.3390/su13116101 [7 July 2021]
  10. Chin, V., Marchant, R. and Cripps, S. (2020). A technical review of data-limited biomass assessment methods in fisheries. Report for Minderoo Foundation., ARC Centre for Data Analytics for Resources and Environment, Sydney, Australia, p. 31.
  11. Ricard, D., Minto, C., Jensen, O.P. and Baum, J.K. (2012). Examining the knowledge base and status of commercially exploited marine species with the RAM Legacy Stock Assessment Database, Fish and Fisheries 13, (4), pp. 380-398, https://doi.org/10.1111/j.1467-2979.2011.00435.x [2021/11/24]
  12. RAM Legacy Stock Assessment Database (2020). RAM Legacy Stock Assessment Database v4.491. https://doi.org/10.5281/zenodo.3676088 [30 March 2020]
  13. Food and Agriculture Organization of the United Nations (2011). Review of the state of world marine fishery resources, FAO Fisheries and Aquaculture Technical Paper, Rome, p. 329. http://www.fao.org/3/i2389e/i2389e.pdf [2 January 2021]
  14. Spalding, M.D., Fox, H.E., Allen, G.R., Davidson, N., Ferdaña, Z.A., Finlayson, M., Halpern, B.S., Jorge, M.A., Lombana, A., Lourie, S.A., Martin, K.D., McManus, E., Molnar, J., Recchia, C.A. and Robertson, J. (2007). Marine Ecoregions of the World: A Bioregionalization of Coastal and Shelf Areas, BioScience 57, (7), pp. 573-583, https://doi.org/10.1641/B570707 [18 June 2021]