The increase in quotas for deep-sea species caught by French vessels (+70% for black scabbardfish and roundnose grenadier) which occured in November 2012 is the result of a political and scientific maneuver that BLOOM has been denouncing for years, and which can be traced back to the 2009 French multi-stakeholder negotiations (« Grenelle de la Mer »).


The deep-sea fishing Commission, which was a spin off of the Grenelle negotiations was supposed to establish whether French deep-sea bottom trawl fisheries were sustainable or else they were to cease. The Commission, which went on for a year despite numerous incidents, resulted in the resignation of NGOs (July 2010) and a public denunciation of the rapporteur and IFREMER scientist Alain Biseau for his blatant bias in favor of the fishing industry (see NGO press release (only in French) about the rapporteur and put forward by NGOs to dismiss the shameful report produced by Alain Biseau to greenwash deep-sea trawl fisheries) and

This consultation served as a test run for the industrial fishing sector which was able to measure BLOOM’s determination to protect the deep ocean and to prohibit the most devastating fishing method for vulnerable ecosystems: deep-sea bottom trawling.


During the Commission, industrial lobbies with the complicity of the rapporteur Alain Biseau deleted all references to any data that challenged their attempt to establish deep-sea fisheries as sustainable, that is, all available peer-reviewed data since all serious publications have proven the destructive nature of deep-sea bottom fishing and the very clear unsustainability of these fishing endeavors. As a result, the industry and its rapporteur produced as biased a report as can be, totally void of any scientific reference!


The industry started plotting its strategic plan in the run up to the reform of the Deep-Sea Access Regime, which was due any time soon after. Although blocking the release of the European Commission’s legislative proposal for over a year, the French industry lobbies were not able to stop Fisheries Commissioner Maria Damanaki to release its legislative proposal in July 2012, just a few days after the main industrial deep-sea fishing fleet of Intermarché (Scapêche) was weakened by BLOOM’s legal success at prohibiting an advertisement that claimed the “sustainability” of deep-sea fish species caught by Intermarché’s fleet.


A few Ifremer researchers, closely tied to Lorient and Boulogne-sur-Mer’s industrial fleets, immediately after the release of the European Commission’s legislative proposal in July 2012, came to the rescue of industrial fishing lobbies by producing a white paper calling deep-sea bottom trawl fishing “sustainable” and making other such outrageous, non-substantiated, non-referenced claims.


Rapidly, this position paper on the Ifremer’s Website was used by industry politicians such as at the time French Fisheries Minister Frédéric Cuvillier. See here


In order to navigate the reform of the deep-sea fishing regulation and avoid at all costs the ban of deep-sea bottom trawling, the industry plan, with the full support of the French government and a few dedicated industry-friendly politicians such as Frédéric Cuvillier, Isabelle Thomas and Alain Cadec, was to first establish that deep-sea fisheries were sustainable. Because this was impossible to obtain through a series of proper international scientific publications, the industry decided to weigh in on political processes which was a low hanging fruit for them given the blind support of the at-the-time French fisheries minister Frédéric Cuvillier.
Their first target was to obtain a quota increase at the November 2012 Council discussion on TACs and quotas. But to justify a quota increase for those deep-sea fish species caught by the French, the industry needed some sort of favourable scientific recommendation.
This is where the plot thickens but becomes fascinating in order to understand how far-reaching and deeply toxic the influence of the industry can be on public processes.


Weighing in on quota decision-making: how does the fishing industry proceed?


Step 1: Place industry-biased scientists in ICES processes.

Easy: the IFREMER is mainly funded by the French Fisheries Ministry and its President is appointed by the French Prime Minister. The French Research Institute for the exploitation of the Sea is essentially driven by a political agenda.

The French researchers, unabashed about their pro-industry positions, are:

  • Pascal Lorance in the ICES working group on deep water species (WGDEEP), who in spite of a long background publishing on the problems of mixed bottom trawl fisheries, radically changed his mind since he became coordinator of the DEEPFISHMAN research project, which brought him to work very closely with the industry;
  • Alain Biseau (again), representing France at the ICES Advice Committee “ACOM” which assesses opinion of the working groups and turns them into formal and quantified ICES notice (see list of members http://www.ices.dk/community/groups/Pages/ACOM-Members.aspx)


Step 2: Ensure that an industry scientist enters the consultation body which advises the European Commission on fisheries matters: STECF. Ticked.

François Théret, a colleague from Alain Biseau at the Lorient Ifremer research station on fishing techniques, used his scientific status to infiltrate the advisory body to the European Commission for fisheries issues (the Scientific, Technical and Economic Committee for Fisheries – STECF), which is in particular responsible for giving a “critical opinion” for the annual setting of total allowable catches and quotas and assess the opinion of ACOM. Right after being confirmed on STECF lists, François Théret joined Intermarché’s fleet (Scapêche). See BLOOM’s press release

The French paper Le Monde also revealed that François Théret had taken a two-year leave of absence from the Ifremer, meaning his “special mission” within Scapêche, in order to help it wade through the scientific plot to ensure minimal impact of the Deep Sea Access Regime, was fully blessed by the IFREMER.


Step 3: Ensure that deep-sea fisheries, for which there is insufficient data to be able to judge fish stock trends, to know fish stock statuses, to even be certain about the genetic structure of the stock that is targeted, let alone to know anything about the 100+ bycatch species which are thrown overboard dead, are considered “well-documented”.

That sounds like a harder trick to pull on fisheries managers and political decision-makers. How did that happen? Discretely, while no one was looking… Here’s what happened.


To obtain a quota increase, the strategy was to put forward that if deep-sea fisheries data were robust, they were somehow biased since they were only based upon vessels catch data, therefore misrepresenting actual stock data (a fisher looks for fish, whereas a researcher applies a specific methodology to count fish).

As a reminder, deep-sea species are classified with other species as “data poor stocks” because the data needed to calculate MSY do not exist[1]. Scientists met at an ICES workshop (WKLIFE) on data-poor stocks to allocate all European fish stocks in various categories, ranking from 1 to 7.

Category 1 corresponds to the stocks for which data is abundant and accurate, and Category 7 corresponds to a total absence of data, typically species caught incidentally and in small volume.


The usual French industry-friendly scientists managed to get deep-sea stocks caught by French fleets allocated in Category 3. A complete fraud. Category 3 corresponds to stocks with available independent scientific assessments for fishing, which is not the case of deep-sea species! Category 4 includes “stocks for which a time series of catch can be used to approximate MSY.” The danger lies with categories 3 and 4. In these two categories, survey indices, such as catch per unit effort (CPUE), are treated as equivalent whether they come from fisheries-independent data or from fisheries-dependent data. The scientific justification for this is weak. Fisheries independent survey data is obtained from sampling stations located using a random or stratified random design. It should go without saying that fisheries stations are located using various biases, but generally are repeats of locations that produced reasonable numbers of fish on previous occasions. Consequently, there is no way to make an unbiased estimate of any of the parameters called for under Category 3 or 4.


This problem is discussed in Walters and Martel’s (2004) book “Fisheries Ecology and Management.” They note: “Two main problems have caused dangerously mis-leading overestimates of abundance, recruitment, and net production during population declines and the onset of overfishing: (1) the use of commercial catch per unit effort (CPUE) or other relative-abundance indices that are, in fact, not proportional to abundance (Harley et al. 2001) and (2) changes over time in the size/age selectivities that confuse the interpretation of population composition data” (p. 94).

The first of these is especially problematical. Harley et al. (2001) showed for several ICES fish stocks, the commercial CPUE remained high while the survey data showed that populations were declining (so-called “hyperstability”). That this can happen is due at least in part to the fact that experienced fishing boat captains can find areas where fish are concentrated, and some species may show severe contractions of their range just before the final collapse (for example, North American cod; see Myers and Cadigan 1995).


The importance of these distinctions has to do with the fact that category 3 species can be exempt from applying the uncertainty cap or the precautionary reduction if it is felt that the abundances of the species are increasing or are at least stable. However, if the commercial CPUE data are likely to be underestimating the degree to which the fish population may be maintaining itself, then such an exemption would be ill-advised.


Category 3 species should therefore be those for which there is survey data to substantiate population abundance claims based on commercial CPUE. However, if all that is available for estimating abundance is fishery-dependent data, those species should be assigned to category 4 and the application of the uncertainty cap and precautionary buffers be mandatory.


For example in the case of theBlack scabbardfish (Aphanopus carbo) in Subareas VI, VII, and Divisions Vb and XIIb, the claim has been made that abundances are stable at least, and perhaps increasing (WGDEEP 2012). However, the only fishery-independent data for this species comes from surveys taken off Scotland but at depths much greater than where the commercial fishery operates, and those CPUE values have very wide variances indicating extreme patchiness in the abundance values. With regard to fisheries dependent CPUE data, most come from French vessels who land most of the Black scabbardfish in these northern areas. However, they have contracted their fishing effort into a smaller number of ICES rectangles (compare WGDEEP 2012 with WGDEEP 2009) thus perhaps unwittingly producing hyperstable estimates.


Thestrategy of French researchers was to manage to withdraw French-caught deep-sea stocks from the pool of species for which quota increases are capped. It opened the technical, procedural door to an outrageous, scientifically unjustifiable quota increase: +70% in the French-caught deep-sea species quotas for 2013-2014!


The reality of deep-sea stocks: miles away from any sustainability

ICES has never declared any deep-sea fish species to be at MSY, or that MSY is known for any deep-sea fish species. In fact, the data do not exist to support any calculation of MSY[2],[3]. In the last few years, ICES has convened a special working group, WKLIFE, to deal with deep-sea and other species which are all classified as “data poor stocks” because the data needed to calculate MSY do not exist for most of the species on which ICES give advice[4].


In order to deal with these data poor species, including all exploited deep-sea species, special methods using catch data have been invented[5]. These methods hope to result in predicting levels of exploitation, and thus, total allowable catch (TAC) for these species.


One method, referred to as “Catch-MSY”, uses catch or landings per unit effort information obtained from fishing captain logbooks or tallybooks[6]. A second method, the “gislasim() function”, uses length data and the von Bertalanffy growth model[7]. Both methods came under criticism during WKLIFEII[8]. For the Catch-MSY method, the problem came from treating catch data as equivalent to fisheries independent survey data[9]. Unfortunately, that can be a serious mistake, since it is possible for catch data to remain stable or even increase while the stock abundance is actually decreasing.[10]


In the end, WKLIFE II concluded that the best that could be done would be to test more simulations, recognizing that there were severe limitations in the data available, including the landings data[11]. At no point did WKLIFEII decide that any of the measures developed were equivalent to MSY. As a result, in the WGDDEEP reports, for example, for blue ling in ICES subdivisions Vb, VI, and VII, the recommendations always state “A reduction in catches should be considered in order to be consistent with the MSY[12] (italics added). A review of the methods used shows that no MSY was calculated, but one or another method attempting to approximate MSY was used. In the case of blue ling as noted above several models were tried using reference points developed by WKLIFE[13]


These same approximations are used for black scabbardfish and roundnose grenadiers. In the latter case a modelling exercise using a Bayesian Surplus Production model[14] was conducted in order to estimate both Bmsy and Hmsy. These models were run using catch data from fishing vessels and so are likely to be inherently biased. Nevertheless, the use of this method also indicates that the data do not exist to calculate MSY for roundnose grenadiers.



Harley, S.J., R.A. Myers, A. Dunn. 2001. Is catch-per-unit-effort proportional to abundance? Canadian Journal of Fisheries and Aquatic Sciences 58: 1760-1772.


Myers, R.A. and N.G. Cadigan. 1995. Was an increase in natural mortality responsible for the collapse of the northern cod? Canadian Journal of Fisheries and Aquatic Sciences 52: 1274-1285.


Walters, C.J. and S. J.D. Martell. 2004. Fisheries Ecology and Management. Princeton University Press.



[1] Report of the Workshop on the Development of Assessments based on LIFE history traits and Exploitation Characteristics (WKLIFE). ICES CM 2012/ACOM:36.

[2] See Haddon (2011). Modelling and Quantitative Methods in Fisheries. CRC Press. In order to calculate the MSY one needs the population growth rate, r, and K, the maximum population size for growth to be positive (p. 287). These paramenters are not known for any deep-sea fish species.

[3] From Martell and Froese (2012). A simple method for estimating MSY from catch and resilience. Fish and Fisheries . “At   a   minimum,   these   models   require time series data   of abundance and removals to estimate   two   model   parameters:   the   carrying capacity k and the maximum   rate of population increase r for a given stock in a given ecosystem. While   estimates   of removals   (defined   here   as catch   plus dead discards) are available for most stocks,   abundance   estimates   are   difficult   and costly to obtain   and   are mostly missing. However, given only a time series of removals, a surprisingly   narrow   range   of r-k combinations   is able to maintain the population such that it neither collapses nor exceeds the assumed carrying capacity. This set of viable r-k combinations   can be used to approximate MSY.”

[4] Report of the Workshop on the Development of Assessments based on LIFE history traits and Exploitation Characteristics (WKLIFE). ICES CM 2012/ACOM:36.

[5] Ibid, WKLIFE 2012, p. 9ff.

[6] Ibid, WKLIFE 2012, p. 14-15.

[7] Ibid, WKLIFE 2012, p. 15 ff.

[8] WKLIFEII, 2012, Report of The Workshop to Finalize the ICES Data-limited Stock (DLS) Methodologies Documentation in an Operational Form for the 2013 Advice Season and to make Recommendations on Target Categories for Data-limited Stocks (WKLIFE II). ICES CM 2012/ ACOM: 79.

[9] WKLIFEII, p. 37.

[10] See for ICES species: Harley, S. J., Myers, R. A., and Dunn, A. 2001. Is catch-per-unit-effort proportional to abundance? Canadian Journal of Fisheries and Aquatic Sciences, 58: 1760–1772 and for a history of the collapse of Canadian cod: Walters, C. J. and Martell, S. J. D. 2004. Fisheries Ecology and Management. Princeton University Press. In the case of Canadian cod, fisheries managers were predicting on the basis of catch numbers future increases in cod abundance even as the stock was in its final stages of collapse.

[11] WKLIFEII, p. 18.

[12] WGDEEP, 2012. Report of the Working Group on the Biology and Assessment of Deep-sea Fisheries Resources (WGDEEP). ICES CM 2012/ACOM:17. This same language is used for almost all deep-sea species.

[13] WGDEEP, 2012, p. 198.

[14] WGDEEP 2012, p. 385. This method suggested that the harvest rate was below Hmsy and that standing stock biomass was below Bmsy but curiously no TAC was recommended. Also, no reference is given for this method so it may be that it was developed for WGDEEP.



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