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Estimating the ecological impacts of fisheries: What data are needed to estimate bycatches?

Martín A. Hall

Head, Tuna-Dolphin Programme, Inter-American Tropical Tuna Commission, 8604 La Jolla Shores Dr., La Jolla, CA 92037, USA.



The estimate in question will, in some cases, be a composite estimate, with its components being:

In some cases it may be known or assumed that all individuals captured are killed, the proportion becomes one and the estimate is limited to the first term.

2.1 Estimating the numbers of individuals captured

The new formula can be written as:

2.2 Estimating BPUE

2.3 Estimating the level of effort

2.4 Estimating the proportion of individuals captured that die

2.5 Biases

Figure 1. Relative bias (%) in MPT ratio in the estimates of mortality of the eastern spinner dolphin. H-R = Hartley-Ross formula, Clas. = Classical formula, P. = Pascual formula.

2.6 Precision

Figure 2. Changes in variance with sampling coverage using mortality of eastern spinner dolphin per ton for a combined data set. Average of 1,000 simulations. Bootstrap estimates M=100. True ratio = 0.026. H-R = Hartley-Ross formula, Clas. = Classical formula, P. = Pascual formula.

2.7 Representativeness

Many factors can affect the representativeness of the data, and may seriously bias bycatch estimates.

2.7.1 Selection of units of effort to be sampled

2.7.2 Observer effect on crew performance

Can these effects be detected? By comparing the fishing areas, species and size composition of the catch, catch rates, trip duration, etc., of the observed sector of the fleet with the rest, it may be possible to test whether the selection of fishing grounds, and other operational decisions depart from the unobserved fleet pattern (assuming that a combination of data, and samples at landing ports could provide these data). But without information on unobserved vessels, comparisons of crew performance in release procedures, compliance with requirements and regulations, etc. are not possible.

2.7.3 Unobserved mortality

The presence of an observer on a vessel is no guarantee that all the mortality will be observed. The reasons for this include; negligence (e.g., not being present during the fishing operation), temporary disability (e.g., the observer may be sick or injured), poor visibility (e.g., sets in darkness or in rough seas), disappearance of the dead individual prior to observation (e.g., dropping from a hook or falling out of a net, taken by a predator from a net or hook, etc.). A special category of unobserved mortality is that of the individuals that die as a result of the fishing operations, as a result of delayed effects (e.g., animals released with internal injuries, or external injuries that were erroneously believed not to lead to mortality, facilitated predation as a result of alterations in schooling or other behaviour as a result of the fishing operation; stress-or fatigue-induced mortality, etc.).

2.7.4 Underreporting of mortality

Even though it is possible to conceive of some circumstances under which an observer may intentionally overestimate mortality (antagonism with crew, overzealous protection of the species involved, etc.), it is much more likely that the mortality will be under-reported. There are three basic motivations that could lead to this: (i) observers spending prolonged trips at sea may develop bonds of friendship with captains and crews, and that may affect their reports; (ii) captains and crews may intimidate the observer, and the observer may underreport out of fear; and (iii) the observers may be bribed to falsify their reports. Of these three, intimidation should disappear when the vessel arrives in port, and the observer has an opportunity to correct the data and report the incident for the corresponding sanction. The other two are more difficult to identify and correct. The records of the observers could be followed over long periods of time, and those consistently reporting below average values, compared to other observers, could be monitored very closely or eliminated from the programme. In such cases their data would be eliminated from some or all the analyses. Besides these statistical checks, there are very few alternatives to detect these biases. Lie detector tests are not fully accurate, and their legal value is not clearly established. Sting operations or observations on spending patterns by some individuals may identify a few guilty parties, but they do not make it possible to quantify the bias. Placing a sub-sample of "trusted" observers or volunteers mixed with the regular pool could help quantify this difference, by comparing the figures from this and the other group.

2.8 Factors affecting BPUE

All the considerations of the previous sections are focused on the objective of obtaining a good estimate of the incidental mortality of the main bycatch species but none of them contributes to understanding its causes. In addition to producing an estimate of a problem's magnitude, an observer programme should serve as a tool to solve the cause of incidental mortality. To achieve this goal it is necessary to identify possible factors that cause the incidental mortality or increase the average BPUE. These factors can be of several types, depending on the fishery. Some can be environmental factors (visibility, sea state, presence of currents, etc.) and others are related to the gear and its deployment (is the right gear used? Is it deployed in the right way?, etc.). Unfortunately, at the beginning of the studies on estimation and mitigation of bycatches it is not known which factors affect BPUE, so it is recommended that a broad approach be taken, trying to include as many factors as possible. The list of factors is potentially very long, but those affecting the ability of the animals to detect the gear, their behaviour, and the behaviour of the gear should be considered first. Once an adequate database becomes available, statistical techniques, such as generalised linear models (McCullagh and Nelder 1989, Stefánsson 1996) can be used to determine which factors are significant.

Acquiring knowledge about the factors affecting BPUE allows one to: (a) improve the estimation of the bycatch levels; and (b) develop mitigation procedures (regulations, technology, education, etc.) to address them. The latter constitutes the basis for most bycatch reduction programmes. It is recommended that input from fishers be given a high priority when establishing the list of factors to consider.


Most of the problems, and solutions, mentioned for the target species apply for the other components of the bycatch. If the sampling design is based on the main bycatch species, however, it is quite possible that the estimates for other species have broader confidence intervals, and may be biased. This could be a serious problem if the bycatch of the "main" species has a uniform or random distribution, and some of the secondary species are very patchy in their distribution.


Knowledge of the spatial and temporal distribution of the bycatches is crucial to the quality of the estimates, and to the mitigation programmes. From the estimation point of view, the stratification of the data into spatial and temporal units that reflect real heterogeneities, will be an effective way to improve the estimates and reduce the costs of the sampling programmes. From the point of view of the mitigation programmes, it provides a quick assessment of the feasibility of spatial and temporal closures as mitigation measures.


To put in perspective the impact of a fishery, it is very important to compare the level of mortality with the population size, and its net recruitment. The "relative mortality" is the ratio of mortality to population size. These data may come from the fishery, but most commonly will require special surveys, tagging experiments, or other procedures. Without them, the mortality data have only limited value because the assessment of their significance is left to the "gut feelings" of those interested. Time series of BPUE data could be used to monitor trends in the populations taken, but only after the same careful procedures that should be used in the interpretation of CPUE data. An additional problem in the use of BPUE data is that many possible actions taken to reduce bycatches would result in lowering the BPUE without reflecting any population changes. A system where the index of abundance is also a performance measure is not likely to be very informative over time because the trends in the population will become confounded with the performance changes that may be the objective of management.


Bycatches should be expressed as a function of the catches in the same fishing operations to facilitate the comparison among areas, gears, etc. Some ratio estimates may require the catches In other cases the catches will put the bycatches into perspective by showing the ecological costs of different operations under a comparable standard (Hall 1996.)


This paper provides a brief description of the data requirements to implement an effective bycatch mitigation programme. The value of simulations performed on real data from pilot samples is emphasised as a tool to provide statistical insights into the problem without the need for complex theoretical analyses. The use of resampling techniques to deal with bias and precision problems is also proposed as a major component of the estimation process. Finally, in order to contribute to the solution of bycatch problems, the exploration of the causes of the bycatch must be an integral part of the sampling scheme.


ALVERSON, D.L., FREEBERG, M.H., MURAWSKI, S.A. & POPE, J.G. 1994. A global assessment of fisheries bycatch and discards. F.A.O. Fish. Tech. Paper No. 339, Rome, 233 pp.

COCHRAN, W.G. 1977. Sampling Techniques. 3rd ed. J. Wiley & Sons, London, 428 pp.

DAYTON, P.K., THRUSH, S.F., AGARDY, M.T. & HOFMAN, R.J. 1995. Environmental effects of marine fishing. Aquatic conservation. Mar. Freshw. Ecosystems, 5: 205-232.

EFRON, B. 1982. The jack-knife, the bootstrap and other resampling plans. CBMS Regional Conference Series in Applied Mathematics 38, S.I.A.M., Philadelphia, 92 pp.

EFRON, B., & TIBSHIRANI, R.J. 1993. An introduction to the bootstrap. Monographs on Statistics and Applied Probability 57, Chapman and Hall, New York, 436 pp.

HALL, M.A. 1996. On bycatches. Rev. Fish Biol. Fisheries, 6: 319-352.

HALL, M.A. 1998. An ecological view of the tuna-dolphin problem: impacts and trade-offs. Rev. Fish Biol. Fisheries, 8: 1-34.

HALL, M.A. & BOYER, S.D. 1986. Incidental mortality of dolphins in the eastern tropical Pacific tuna fishery: description of a new method and estimation of 1984 mortality. Rep. Int. Whal. Commn., 36: 375-381.

GOODMAN, L.A. 1960. On the exact variance of products. American Statistical Association Journal, 55: 708-713.

MCCULLAGH, P. & NELDER, J.A. FRS. 1989. Generalized Linear Models, Second edition. Chapman & Hall, London, 511 pp.

RAO, J.N.K. 1969. Ratio and regression estimators. In N.L. JOHNSON & H. SMITH Jr., eds., New developments in survey sampling. Wiley Interscience, London. 732 pp.

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STEFÁNSSON, G. 1996. Analysis of groundfish survey abundance data: combining the GLM and delta approaches. ICES J. Mar. Sci., 53: 577-588.

Monitoring tuna fisheries in the western Pacific

Antony D. Lewis

Oceanic Fisheries Coordinator, Secretariat of the Pacific Community, Ocean Fisheries Programme, P.O.Box D5, Noumea Cedex 98848, New Caledonia.

Abstract: Existing arrangements for monitoring the large western pacific tuna fishery, primarily for scientific purposes, are described. The annual catch of 1.2-1.4 million tonnes of the four main tuna species is taken by around 7000 vessels. Primary coverage of the catch and effort by domestic and distant water fleets is achieved through logsheet coverage at national level, and is currently 80% of the catch in the Secretariat of the Pacific Community area. Port sampling and observer programmes have been established relatively recently, and provide limited coverage. The various data are compiled by the SPC/Oceanic Fisheries Programme (OFP) and maintained in an accessible Regional Tuna Fishery Database. Current levels of monitoring are not adequate for some purposes, with other types of data increasingly being required from the fishery and its operational environment. It is hoped that an arrangement being developed for the conservation and management of regional highly migratory fish stocks will provide a framework for increased monitoring efforts.


Fisheries that capture tuna in the western Pacific Ocean range over a vast area, eastwards from the coasts of Asia out into the Central Pacific, and from northern Japan, at nearly 50° N, to similar latitudes in the Southern Hemisphere. The major volume of the catch is however, taken in tropical waters, and most detailed statistics until recently, have been compiled for the so-called South Pacific Commission (now Secretariat of the Pacific Community (SPC)) statistical area (Fig. 1), which covers 30 million km2 of ocean including the EEZs of 24 coastal states and large areas of high seas. Recognising the need to collect information throughout the range of tuna stocks exploited by the fishery, there has been an increasing tendency to collect statistics over a wider area, from 50° N to 50° S and 120° E to 150° W (Fig. 1). The area, conveniently called the Western and Central Pacific Ocean (WCPO), was recently adopted for the collection of statistical data by the 11th Standing Committee on Tuna and Billfish (Anon. 1998). The breadth of this area at the Equator represents one quarter of the earth's circumference.

Figure 1. The Western and Central Pacific Ocean, showing the WCPO boundaries (heavy and dotted line) and the SPC statistical area (thin line). EEZ areas are clear and high seas shaded.

Figure 2. Annual tuna catch, 1970 - 1997, by gear type, in the Western and Central Pacific Ocean. Catches of skipjack, yellowfin, bigeye and albacore tuna, the four main target species, are included.

Table 1. Number of active vessels in the Secretariat of the Pacific Community (SPC) statistical area since 1990 (1997 figures may be incomplete).

Year Longline Pole-and-Line Purse seine Total
1990 496 245 189 930
1991 599 227 209 1,035
1992 649 198 209 1,056
1993 1,150 159 202 1,511
1994 1,240 164 199 1,603
1995 1,221 173 186 1,580
1996 1,162 165 183 1,510
1997 1,010 155 183 1,348

Table 2. Tuna catch by species in the Western and Central Pacific Ocean (WCPO), since 1990.

Year Skipjack Yellowfin Bigeye Albacore Total
1990 784,765 313,350 73065 33,414 1,204,594
1991 977,193 354,105 60,982 31,120 1,423,400
1992 894,252 352,441 69,804 33,634 1,350,131
1993 720,263 362,653 72,579 30,998 1,186,493
1994 874,625 366,670 76,806 36,432 1,354,533
1995 891,221 313,178 61,294 39,209 1,304,902
1996 898,732 245,306 61,726 39,638 1,245,402
1997 792,121 377,371 71,077 40,864 1,281,433

Table 3. Catch of tuna species by gear in the Western and Central Pacific Ocean (WCPO), in 1997. Catches in tonnes; albacore catches are for the Pacific south of the Equator.

Species Purse seine Pole-and-line Troll Longline Other Total
Skipjack 600,003 200,633   1,479 48,739 850,854
Yellowfin 230,498 11,726   72,177 80,022 394,423
Bigeye 28,491 3,434   55,669 8,451 96,045
Albacore     6,583 30,330 25 36,938


  1. Monitoring catches; to address a variety of industrial and scientific needs;
  2. Monitoring vessel activity; usually to meet compliance requirements, but also as an integral part of monitoring catches and interpreting catch rates, and
  3. Electronic monitoring; a relatively recent development for both compliance and enforcement needs.

2.1 Why monitor?

The Agreement for the Implementation of the Provisions of the United Nations Convention on the Law of the Sea of 10 December 1982, relating to the Conservation and Management of Straddling Fish Stocks and Highly Migratory Fish Stocks, otherwise known as the UN Implementing Agreement (UNIA), reaffirms generally accepted requirements to monitor catches and vessel activity, in support of conservation and management objectives. These include requirements to, inter alia,

  1. "Ensure" that measures (to ensure the long term sustainability of straddling fish stocks (SFS) and highly migratory fish stocks (HMFS) are based on the best scientific advice available;
  2. Assess the impacts of fishing, other human activities and environmental factors on target stocks and species belonging to the same ecosystem or associated with, or dependent on, the target stocks;
  3. Apply the precautionary approach in accordance with Article 6 of UNIA;
  4. Take measures to prevent or eliminate overfishing and excess fishing capacity and to ensure that levels of fishing effort do not exceed those commensurate with the sustainable use of fishery resources;
  5. Take into account the interests of artisanal and subsistence fishers;
  6. Collect and share, in a timely manner, complete and accurate data concerning fishing activities on, inter alia, vessel position, catch of target and non-target species and fishing effort, as set out in Annex 1 of UNIA as well as information from national and international research programmes, and
  7. Implement and enforce conservation and management measures through effective "monitoring, control and surveillance".

2.2 Who monitors?

2.3 What is monitored?

The basic fishery data collected as part of monitoring activity are listed in the UNIA Annex 1 and include the following:

  1. Time series of catch and effort data, by fishery (gear) and fleet;
  2. Total catch in number, weight or both, by species (target and non-target) and fishery;
  3. Discard statistics, including estimates where necessary;
  4. Effort statistics and fishing location;
  5. Catch composition by length, weight and sex;
  6. Other biological data, such as information on age, growth, recruitment, and stock distribution, and
  7. Other relevant research data (including studies on environmental, oceanographic and ecological factors affecting stock abundance).

2.3.1 Catch effort data

2.3.2 Total catch

2.3.3 Catch composition data

2.3.4 Observers

2.3.5 Other data

2.3.6 VMS/surveillance

2.4 Is the current level of monitoring of the western Pacific tuna fishery sufficient?

  1. Improved statistical coverage of the fisheries of eastern Indonesia and the Philippines;
  2. Consolidated size composition data for most species throughout the range of their geographical distribution, and
  3. Improved understanding of biological processes affecting abundance, catchability etc.


ANON. 1998. Report of the Eleventh Meeting of the Standing Committee on Tuna and Billfish, 28 May - 6 June 1998, Honolulu, Hawaii. August 1998, 108 p.

BAILEY, K., WILLIAMS, P.G. & ITANO, D.G. 1996. By-catch and discards in western Pacific tuna fisheries: a review of SPC data holdings and literature. SPC Oceanic Fisheries Programme Technical Report No. 34. Secretariat of the Pacific Community, Ocean Fisheries Programme, P.O.Box D5, Noumea Cedex 98848, New Caledonia.

HALL, M.A. & WILLIAMS, P.G. (in press). Bycatches in Pacific tuna fisheries. National Coalition for Marine Conservation: Symposium on Managing Highly Migratory Fish of the Pacific Ocean, November 4-6, 1996, Monterey, California.

HAMPTON, J., BIGELOW, K. & LABELLE, M. 1999. A summary of current information on the biology, fisheries and stock assessment on bigeye tuna (Thunnus obesus) in the Pacific Ocean, with recommendations for data requirements and future research. SPC Technical Report No.36. Secretariat of the Pacific Community, Ocean Fisheries Programme, P.O.Box D5, Noumea Cedex 98848, New Caledonia.

LAWSON, T.A. 1998. Tuna Fishery Yearbook 1997. Secretariat of the Pacific Community, Noumea, New Caledonia. 133p.

LEHODEY, P., BERTIGNAC, M, HAMPTON, J., LEWIS, A. & PICAUT, J. 1997. El Niño Southern Oscillation and tuna in the western Pacific. Nature 389: 715-718.

OCEANIC FISHERIES PROGRAMME 1997. Estimates of bycatch and discards in central and western Pacific tuna fisheries; preliminary results. SPC/OFP Internal Report No. 33, 30p.

OCEANIC FISHERIES PROGRAMME 1998a. Coverage of western and central Pacific tuna fisheries by data held by the SPC Oceanic Fisheries Programme. 11th Meeting of the Standing Committee on Tuna and Billfish, 30 May - 6 June, Honolulu, Hawaii. Working Paper 4, 21p.

OCEANIC FISHERIES PROGRAMME 1998b. Estimates of annual catches of target species in tuna fisheries of the western and central Pacific Ocean. Ibid, Working Paper 5, 67p.

Sampling and estimation of discards in multi-species fisheries

Tatsuro Matsuoka

Kagoshima University, Faculty of Fisheries, Shimoarata 4-50-20, Kagoshima 890-0056, Japan.



where d represents discarded and c represents retained catch in a fishing sector, determined through sampling. A discard amount, D in a sector is described as;

where C is the total catch landed in the sector.

2.1 Estimation of discards from summed landings

where dij is the observed discard of species-j within a range of sector-i.

2.2 Estimation of discards from the landing of target species

where ct is the retained catch of target species-t during sampling, d(t) is the summed discards during the sampling period when species-t is targeted, r (t) is the discard ratio, Ct is the total landing of species-t over all sectors and D(t) is the estimated, summed discards when species-t is targeted. This relationship holds when one sector is analysed with landing statistics which are independent and not affected by other sectors. When applied, however, to many fisheries and multi-species fisheries in particular, this method was found to over-estimate the total discards (Matsuoka 1996). It is therefore necessary to review the global discard estimate of 27 million tonnes produced by this method given the inaccuracies of this model.

2.3 Estimation of discards by fishing gear type

2.4 Discard per unit effort (DPUE)


3.1 Species composition of the Danish seine fishery in southern Japan

3.2 Operational practices for uncommon species

Table 1. Common species occurring in discards and landings by number and weight, recorded on 14 sampling occasions over 3 years, from the cuttlefish sub-sector of a Danish seine fishery in southern Japan.

  Landings Discards
Number of species 29 79
Common species (N) 17 17
Common species (%N) 58.6 21.5
Summed weight (kg) 402.8 621.5
Common species (wt) 316.3 150.5
Common species (%wt) 78.5 24.2

3.3 Correlation of discards and landings

3.4 Distribution of discard data

3.5 DPUE and the index of variation

Table 2. Indices of variation of the discard ratio and the discard per unit effort (DPUE) derived from data recorded on 37 sampling occasions over 3 years from a Danish seine fishery in southern Japan.

Sum./Sum. = The discard ratio of summed discards to summed landings.
Sum./Tgt. = The discard ratio of summed discards to target landings.

3.6 Estimation of discards

Table 3. Estimates of the annual discard in the cuttlefish sub-sector of the Danish seine fishery in southern Japan, derived from data recorded on 37 sampling occasions over 3 years.

Methods Summed landings (t) Cuttlefish landing (ton) Discard ratio Discard estimation (t)
    by sub-sector All sectors    
DPUE         32.1
Sum./Sum. 26.0 13.4   1.59 41.4
Sum./Tgt.     25.9 4.86 125.9

Sum./Sum. = The discard ratio of summed discards to summed retained catch.
Sum./Tgt. = The discard ratio of summed discards to target species retained.


4.1 The nature of discard practices in multi-species fisheries

4.2 DPUE and the summed discard ratio

although the estimation of discards will be less reliable than those made with actual effort data.

4.3 Application of the discard ratio based on the target catch

4.4 The estimation of individual species discards

4.5 Recommendations for discard estimation

4.6 Future requirements of discard estimation


ALVERSON, D.L., FREEBERG, M.H, MURAWSKI, S.A. & POPE, J.G. 1994. A global assessment of fisheries bycatch and discards. FAO Fisheries Technical Paper 339, FAO, Rome, 233pp.

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Evaluating the costs and benefits of alternative monitoring programmes for fisheries management

André E. Punt

CSIRO Marine Research, GPO Box 1538, Hobart, TAS 7001, Australia.


Abstract: An approach to the quantitative evaluation of the costs and benefits of different levels of observer coverage is outlined. This approach attempts to value observer programmes in terms of their ability to better satisfy management objectives rather the precision with which quantities that may be of interest to management (e.g. discard rates) are estimated. The approach is illustrated using the observer programme which estimates the discards of blue grenadier by the trawl fishery off eastern and southern Australia and the observer programme that which estimates by-catch of Hooker's sea lions in the fishery for arrow squid off southern New Zealand. The benefits of increased precision for the latter are shown to be small while the impact of different levels of observer coverage on management advice for blue grenadier is found to be substantial for some types of management approaches.


In Australia, observers on fishing vessels are responsible inter alia for validating catches, monitoring catch quotas, advising fishing masters of the correct radio reporting procedures, and observing whether operations and activities comply with Australian government procedures (Nicol 1992). The first of these tasks includes species identification of the catch, measuring a random subsample of the catch, and collection of biological data for ageing, feeding, reproduction, growth, stock-structure and migration studies. Furthermore, it is possible to record recaptures of tagged southern bluefin tuna from vessels carrying observers separately from those captured by vessels not carrying observers, and consequently estimate the probability of tag-reporting for vessels without observers (T. Polacheck, CSIRO Marine Research, pers. commn). Data collected by observers can also form the basis for addressing by-catch reduction issues (e.g. Kennelly 1995). The data collected in Australia are typical of those collected in other observer programs (e.g. Fitzgerald et al. 1993, Lee et al. 1996).

1.1 Eastern stock of gemfish

1.2 Quantitative basis for evaluating the benefits of an observer programme

  1. The development of a model (the "operating model") that reflects inter alia the underlying biological system being managed, how data are collected through logbooks, and survey and observer programmes, and how management decisions impact the resource;
  2. The identification of a set of performance measures to quantify the management objectives (probability of dropping below some threshold biomass, average annual yield, etc.);
  3. The selection of a set of alternative candidate management procedures, and
  4. The use of a simulation approach to evaluate how well different combinations of management procedure, including its associated data collection scheme, perform in terms of the management objectives.


Figure 1. Posterior distributions for the time-trajectories of recruitment, expressed as a fraction of that expected from the deterministic stock-recruitment relationship (1980-97) for blue grenadier off eastern Australia. The solid lines are distribution medians and the dotted lines posterior 90% credibility intervals, while the dashed lines correspond to expected recruitment. Results are shown for assessments that include and exclude the data from the ISMP.

Figure 2. Time-trajectories (1995-2017) of the probability that the spawner biomass of blue grenadier remains above 40% of the virgin level, and the expected spawner biomass, for an annual landed catch of 10,000t. Results are shown for assessments that include and exclude the data from the ISMP.

Figure 3. Medians and 90% intervals of relative error of four management-related quantities plotted against different levels of variance of the discard information. The four quantities are: (a) the 1994 year-class strength, (b) the 1995 year-class strength, (c) the 1996 year-class strength, and (d) the 1997 spawner biomass.

Figure 4. Medians and 90% intervals for the relative error for the estimates of the 1995 year-class strength against different levels of variance for the discard information. Results are shown for analyses that consider different levels of precision of: (a) both the size of discarded catch and its age-structure, (b) only the size of the discard catch, and (c) only the age-structure of the discarded catch.


Figure 5. Medians and 90% intervals for the proportional loss in squid catch as a function of the CV of the by-catch of sea lions in the arrow squid fishery.




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1 A management procedure can be defined as a set of rules which utilise pre-specified data to provide recommendations for management actions (Butterworth et al. 1997, Cochrane et al. 1998).

2 As will be discussed later, accuracy and precision of the estimates of recruitment has been taken as the "management objective" in the absence of agreed and clearly defined management objectives for blue grenadier.

3 `Shrinkage' in the context of blue grenadier involves including in the assessment a prior for year-class strength based on an (estimated) deterministic stock-recruitment relationship. If the assessment data provide little information on a particular year-class, it is "shrunk" to the value predicted from the stock-recruitment relationship.

4 The current level of sampling intensity for blue grenadier was selected before the recent strong year-classes entered the fishery and large-scale dumping started to occur.

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