Methodology

Specifically, we asked three questions:

Our analysis included 1,439 stocks spanning 142 coastal countries and territories and focused on fisheries within each country’s national waters, a band of ocean that extends 200 nautical miles offshore from each country’s coastline. Together, these countries accounted for about 92 per cent of total global marine catches in 2018, our baseline year for data.² In future editions, we aim to expand coverage to include additional countries and jurisdictions, including the high seas.

Along with stock status, we also highlight the data gap – that is, how much remains unknown about the state of a country’s fish stocks. To do this, we divided stocks into those that had been ‘assessed’ and those that were ‘unassessed’. Assessed stocks had official published stock assessment results or sufficient data to estimate current stock abundance, relative to unfished levels. Conversely, unassessed stocks lacked this information and were of unknown abundance.

All data and analyses were subject to strict internal quality control and assurance processes. Additionally, an independent assessment of the Progress score and Governance analyses was undertaken. Based on the activities, it has been determined that the analyses processes align to the agreed technical methods and documentation, and the analyses processes do not alter or manipulate the relevant dataset(s) beyond the stated intent and agreed technical methods.

To understand the global state of fisheries, we used publicly available information and reconstructed catch estimates generated by the Sea Around Us initiative to develop two metrics:

We combined these two metrics into a single Progress score, which captures each country’s level of progress towards achieving SDG target 14.4. This score ranges from 0 (no evidence of progress) to 100 (a system in which all catch has been assessed and all stocks are at or above sustainable levels).

In line with SDG target 14.4, the Progress score represents the biological sustainability of fish stocks, rather than ecological sustainability, and does not consider the broader impacts of fishing on marine communities or ecosystems. Despite their importance, with few exceptions, there is an absence of information and methods for assessing these broader aspects of sustainability at a global scale. However, we will explore these alternative ecosystem-based approaches in future iterations of the Index.

To calculate stock sustainability, we determined the proportion of assessed fish stocks at the global and country level estimated to be at or above a level of abundance that enables MSY. MSY is the maximum catch that can be continuously removed from a stock, under constant conditions, without affecting long-term productivity. MSY is the most common type of reference point used in fisheries to determine sustainability and is embedded in international policy, such as the United Nation’s Convention on the Law of the Sea.

We estimated the current level of abundance, relative to unfished levels (based on biomass – that is, the total mass of the population in tonnes) for as many stocks as possible within each country’s waters in 2018. This included fish stocks that occur completely within a country’s national waters (national stocks), stocks that are a shared responsibility of neighbouring countries (shared stocks), and stocks that move across multiple exclusive economic zones, are caught by many countries and are managed collaboratively by a regional fisheries body (straddling stocks), that were identified in a country’s reconstructed catch data.

Where available, we extracted relative abundance estimates from recent official³ stock assessments (527 stocks). Where stocks lacked a recent official assessment but had sufficient data publicly available, we used established data limited models – the Bayesian Schaefer Model (BSM) and an updated version of CMSY (known as CMSY++)⁴ – to produce novel estimates of relative abundance (912 stocks). To increase confidence in assessment results, we excluded any CMSY++ results that did not have robust estimates of ‘end biomass’, i.e. published or expert-based biomass estimates since 2014, to inform the model. These models rely on species’ productivity and catch time series data to estimate fisheries reference points, such as MSY and biomass, and were developed to help monitor stocks with little data.⁵ The addition of these new estimates substantially increased the scope and resolution of fisheries data globally and allowed for comparison across countries.

Next, we used the relative abundance estimates to classify the status of each stock. Stocks whose abundance was estimated to be at or above the level that produces MSY were classified as ‘sustainable’, while those whose abundance was below this level were classified as ‘overfished’. This approach recognises that MSY should be viewed as a lower limit, not a target for stock sustainability. Although the actual level of abundance that produces MSY varies across stocks based on their biological characteristics, we applied a single threshold for all stocks in our dataset. This approach enables direct comparison between countries and removes any incentive for countries to set lower, unsupported levels of MSY.

Specifically, our method assumes that MSY occurs at 50 per cent of unfished levels of stock abundance,⁶ with a 10 per cent margin of error, which means that a stock is considered ‘overfished’ if its current abundance is less than 40 per cent of its unfished abundance. Note, 219 stocks in our dataset were assessed based on spawning stock biomass (SSB) – the total weight of fish in a stock that are old enough to reproduce. In these instances, stocks with an SSB greater than or equal to 20 per cent of the unfished level of SSB were classified as ‘sustainable’, while those whose abundance was below this level were classified as ‘overfished’. These approaches for classifying stocks align with the method used by the Food and Agriculture Organization of the United Nations (FAO).⁷

Finally, global and country-level stock sustainability metrics were calculated as the proportion of assessed stocks classified as ‘sustainable’ within the global dataset and within each country’s national waters, respectively.

We recognise that calculating MSY requires quantitative data and technical expertise, which is not available for all fisheries, and that in the absence of this data, other indicators of stock status can be used. We aim to incorporate other indicators that are used to assess stock status, such as risk-based approaches and indicator species, in future versions of the Index.

To fully understand the state of a country’s fisheries, it is important to consider not only what is known – that is, the state of assessed stocks – but also what is unknown. Quantifying how much remains truly unknown is a key challenge in fisheries. For example, we do not have a clear understanding of how many stocks exist in a country or region to calculate exactly how many remain ‘unassessed’.

In this version of the Global Fishing Index, we use catch as a proxy for understanding this knowledge gap. This is not a perfect proxy, as the ability to assess a large proportion of the catch depends on the size and diversity of fisheries in a country’s waters. For example, temperate countries’ fisheries are often dominated by a small number of species, while countries in the tropics have highly diverse, multispecies fisheries.

To calculate data availability, we quantified the proportion of the total reconstructed catch within each country’s waters from 1990 to 2018 that was represented by the assessed stocks in our dataset. We focused on this historical period to account for stocks that were previously abundant or caught in high amounts but have since been reduced to very low levels of catch.

First, we estimated the total reconstructed catch from within each country’s waters for this 29-year period. The Sea Around Us catch reconstruction process combines reported ‘official’ catch estimates with other information (such as trade records, seafood consumption rates, national employment data and vessel registries) to provide a more comprehensive and accurate estimate of total marine catch within a country’s national waters. In the absence of formally defined stock boundaries, species catches were split into stock-level catches using marine ecoregions.⁸ Marine ecoregions constitute ecologically distinct areas and were used to represent the geographical ranges of individual stocks within a species.

To estimate what proportion of the total catch has been ‘assessed’, we divided the combined catch (in tonnes) of the assessed stocks in our dataset by the total reconstructed catch within each country’s waters for 1990 to 2018.

We also evaluated the proportion of ‘nationally managed catch’ that had been assessed for each country. This includes catches from national and shared stocks, but excludes catches from straddling stocks, such as tuna or other highly migratory species, that move across multiple exclusive economic zones, are caught by many countries and are managed collaboratively by a regional fisheries management organisation (RFMO).

We collected governance data for each country using publicly available information including published datasets, reports and peer-reviewed journal papers. These data were supplemented with an online questionnaire and interviews with local fisheries experts, including government officials, scientists and academics, fishing industry representatives and non-government organisation (NGO) staff. We collected 274 completed questionnaires across 116 countries and conducted 216 interviews across 76 of the assessed countries. Data were collected between August 2019 and May 2020.

We used this data to score each of the 72 indicators (out of 100). Indicator scores were then averaged to produce attribute and dimension-level scores. We surveyed 43 experts (including government officials, NGO staff, academics and industry members) to understand the relative importance of each of the six dimensions for ensuring sustainable fisheries and calculating dimension-level weights. We then combined the six dimension-level scores to produce an overall weighted average assessment score (out of 100) for each country.

We used multiple decision criteria to convert the assessment scores to a Governance capacity level, ranging from very low (no evidence of a system for governing fisheries) to very high (representing a well-developed system with very high capacity to secure sustainable fisheries). This approach considers the strength of the governance system, based on the overall assessment score, as well as the level of balance across the dimensions, based on dimension-level scores (Table 1). This approach recognises that each of the six dimensions are crucial for ensuring a well-functioning governance system and that a high score in one dimension cannot fully compensate for a low score in another.

Where a country does not meet all required criteria, it was capped at the highest Governance capacity level in the lower balance criteria.

We awarded each country a single overall grade, based on 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.

Grades were determined based on a country’s Progress score and Governance capacity. 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 2).

Countries fall into a grading band for different reasons, and it is important to review country-specific results and recommendations on our website.