Development and application of management procedures for fisheries in southern Africa

Transcription

1 ICES Journal of Marine Science, 56: Article No. jmsc , available online at on Development and application of management procedures for fisheries in southern Africa H. F. Geromont, J. A. A. De Oliveira, S. J. Johnston, and C. L. Cunningham Geromont, H. F., De Oliveira, J. A. A., Johnston, S. J., and Cunningham, C. L Development and application of management procedures for fisheries in southern Africa. ICES Journal of Marine Science, 56: Management procedures (MPs) have been used to regulate two major South African fisheries (the demersal hake fishery and the pelagic fishery for sardine and anchovy) since the early 1990s and are currently undergoing revision, while new MPs have recently been adopted for the South African west coast rock lobster fishery and Namibian hake and seal fisheries. The development and revision of these MPs are summarized in this paper, in particular with regard to their robustness to key uncertainties. The most notable common advantage of the use of an MP approach in these five fisheries has been to render the process of providing scientific total allowable catch recommendations more transparent, thus enhancing credibility between fishery scientists and members of industry International Council for the Exploration of the Sea Key words: anchovy, hake, management procedure, operating model, robustness, rock lobster, sardine, seal. Received 26 November 1998; accepted 7 May H. F. Geromont: MARAM, Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch 7701, South Africa. Tel: ; fax: ; helena@maths.uct.ac.za. J. A. A. De Oliveira: Marine and Coastal Management, Private Bag X2, Rogge Bay 8012, South Africa. Tel: ; fax: ; jdolivei@sfri.wcape.gov.za General introduction Management procedures (MPs) have been used in South Africa to regulate the demersal hake fishery (Punt, 1992, 1993) and the pelagic fishery for sardine and anchovy (Butterworth and Bergh, 1993; Butterworth et al., 1993; Cochrane et al., 1998) since the early 1990s and are currently undergoing revision, while new MPs have been adopted recently for the South African west coast rock lobster fishery and Namibian hake and seal fisheries. Some of the benefits of this approach include evaluating the consequences of the main sources of uncertainty by means of simulation tests and subsequently developing MPs robust to these, enabling various interest groups (including industry) to participate in the development and thus the decision-making process, taking a longerterm view of resource utilization by testing the impact of a given MP over a number of years and, finally, reducing the unnecessary workload generated by possibly complex annual assessments. We discuss the current progress in developing new MPs for the South African and Namibian fisheries for Cape hake, the South African pelagic and west coast rock lobster fishery and the Namibian seal fishery, and the problems encountered with previous applications for two of these resources. For South African hake, the previous MP had not allowed for a change in agespecific fishing selectivity away from smaller fish that has taken place over the past few years, so necessitating a revision which makes allowance for these transient effects. Problems encountered with specifying the bias associated with abundance estimates from research surveys of Namibian hake have highlighted the need for developing MPs that are robust to this source of uncertainty. For the pelagic fishery, problems have included encompassing a sufficiently wide range of plausible scenarios for resource status in the face of highly variable resources, and trying to manage essentially conflicting fisheries (anchovy and sardine) within a combined MP framework. The South African west coast rock /99/ $30.00/ International Council for the Exploration of the Sea

2 Development and application of management procedures for fisheries in southern Africa 953 Biomass and catch ( 10 3 t) Total biomass Exploitable biomass Catch GLM c.p.u.e. Survey c.p.u.e. estimates of abundance ( 10 3 t) Figure 1. Estimates of total and exploitable biomass as estimated by an age-structured production model, GLM-standardized c.p.u.e. and research survey estimates of abundance for South African west coast hake. Total annual catches are also indicated. 97 lobster resource has recently come under severe strain, largely as a result of a period of very slow somatic growth that commenced in the late 1980s, and uncertainties about likely future trends in this growth have created a need for a MP to set annual total allowable catches (TACs). An environmental anomaly in 1994 caused concern about the future of the Namibian seal resource which necessitated the development of a MP that would be robust to a wide range of such environmental, and other, uncertainties. In this paper, each of these cases is discussed in turn, and some of the common features and conclusions are summarized. South African hake Introduction Cape hake (Merluccius spp.) form the basis of South Africa s most valuable fishery, with a 1997 landed value approaching US$200 million. The fishery was heavily fished by foreign vessels until a 200-mile fishing zone was declared in Since then, with catches sharply reduced, a gradual recovery has taken place (see Fig. 1, which shows past catches and c.p.u.e. for the west coast component of the resource). The first MP applied to both west and south coast resources to provide TAC recommendations was operational from 1990 to This procedure was based on an f 0.2 harvesting strategy coupled to a dynamic Schaefer production model, and made use of c.p.u.e. data, standardized only by application of crude vessel An f strategy is a constant effort strategy, with the effort level calculated from a surplus production model. For the f 0.2 strategy, this effort level is that for which the slope of the equilibrium yield vs. effort plot is 20% of the slope of this curve at the origin. power factors, and research survey estimates of abundance. Details of the robustness testing and selection criteria are given in Punt (1992, 1993). The first major subsequent development was the standardization of the c.p.u.e. data by means of general linear modelling (GLM) techniques, which resulted in an index of abundance that was no longer increasing at about 2% per year, but instead showed very little positive trend. The second was the realization that there had been a shift in fishing selectivity by the trawl fleet during the 1980s away from smaller fish (this was likely the result of the illegal use of net liners diminishing over time as the resource biomass increased, their use became less necessary to boost catches to economic levels). If the existing procedure had been applied using the new GLM-standardized c.p.u.e. data, an f 0.2 harvesting strategy would have led to a severe drop in TAC according to the Schaefer model, largely because this age-aggregated model is unable to take the change in fishing selectivity away from smaller fish into account. It is primarily for this reason that a new MP was required for the west and south coast resources, in which the chosen harvesting strategy guaranteed TACs that would provide acceptable socio-economic stability for industry while at the same time resulting in biological risks that are acceptable in terms of scientific norms. Candidate MPs for west coast hake The TAC for each year is determined by applying a Fox or Schaefer (age-aggregated) or age-structured production model to estimate a catch for that year corresponding to an f 0.n harvesting strategy. The formula which provides the TAC recommendations (Geromont and Glazer, 1998) is: TAC y =ΔTAC y 1 +(1 Δ)TAC y,f0.n (1)

3 954 H. F. Geromont et al. where TAC y is the TAC in year y for y>1998, Δ is a control parameter whose value is pre-chosen, and TAC y,f0.n is the TAC for year y corresponding to a f 0.n harvesting strategy according to the production model specified. The group of MPs described by Equation (1) is distinguished by the control parameter Δ and the choice of harvesting strategy f 0.n, coupled to a choice of production models, each of which was chosen by decisionmakers on the basis of achieving an optimum trade-off between the values desired for various measures of procedure performance. In addition, the TAC for 1999 was not allowed to be less than that in The control parameter Δ determines how much (and hence how smoothly) the TAC is adjusted from one year to the next. For example, if Δ=0 (previous MP), the TAC would be changed immediately to correspond to the chosen f 0.n harvesting strategy according to the appropriate production model, while at the other extreme, a Δ=1 choice would result in a constant catch harvesting strategy. An intermediate value of Δ=0.5 was selected. The production models can be divided into two groups: Fox and Schaefer age-aggregated production models (AAPM) In order to accommodate the recent change in commercial fishing selectivity (Geromont and Butterworth, 1996), the c.p.u.e. data corresponding to the period during which the fishing selectivity changed away from smaller fish are omitted from the model fitting procedure, so resulting in separate indices of relative abundance for the periods of assumed constant fishing selectivity, each with its distinct catchability coefficient. In addition, the model also fits to the summer and winter research trawl survey estimates, treated as relative abundance indices because of likely biases in the absolute abundance estimates provided by the swept-area methodology used. Age-structured production model (ASPM) This model (Geromont and Butterworth, 1998a) takes commercial and survey catch-at-age data into account in addition to the c.p.u.e. and survey abundance estimates that are fitted by the Fox and Schaefer surplus production model estimation procedures discussed above. The change in fishing selectivity is incorporated explicitly in the model by estimating time-dependent selectivities-at-age from the commercial catch-at-age data, so distinguishing between the commercially exploitable and total biomass of the resource, and thus taking account of their changing ratio over time (see Fig. 1). Robustness tests and results The operating models of the resource used for these tests constituted age-structured production models fitted to research survey and commercial abundance and catchat-age data, and admitting fluctuations in recruitment about the assumed stock recruitment relationship (details of these models can be found in the Appendix to Geromont and Butterworth, 1998a). Comparison of performance statistics for the three groups of candidate MPs (Schaefer, Fox, and ASPM) indicated that the Schaefer production model estimator of the previous MP no longer performed well, as it led to large increases in TAC in the short term which in turn resulted in substantial decreases later as the procedure attempted to correct for the resource depletion caused by these high initial catches (Geromont and Butterworth, 1998a). There was considerable similarity between projections for the Fox and ASPM estimators (see for comparison of performance statistics Geromont and Butterworth (1998b)). The advantage of the former estimator is that it is much simpler and so more efficient in terms of computation time, and robustness tests were therefore performed mainly for the Fox-model-based MPs (see for details Geromont and Butterworth (1998c)). Following consideration of initial results, decisionmakers requested that three choices of harvesting strategy be investigated in more detail: f 0.05,f 0.1, and f The question was then whether these options showed adequate robustness in anticipated risk-related performance to uncertainties about models and assumptions. All three choices of harvesting strategy were judged to have shown such robustness to the uncertainties listed in Table 1. The only result of possible concern was that of a combination of A2a (c.p.u.e. data positively biased) and A3 (no future research surveys). Therefore, if independent research surveys to estimate abundance are not continued in future, particular care will need to be taken to guard against failure to detect increases in fishing efficiency which would bias c.p.u.e. upwards as an index of abundance. (Details of robustness tests and performance statistics for the Fox model estimator can be found in Geromont and Butterworth (1998c).) Having shown adequate robustness for the three harvesting strategies, the next step was to choose a particular strategy on which to base TAC recommendations. Of the three, only f 0.15 showed a greater than 50% chance of reaching the estimated MSY level by 2009, whereas f 0.05 resulted in a relatively large probability of a net spawning biomass decline over the 10-year projection period. On the other hand, the f 0.15 strategy would almost certainly have led to a short-term decrease in TAC from the current level of t (Geromont and Butterworth, 1998c). Advisers to decision-makers opted for an intermediate strategy of f In terms of the revised MP of Equation (1), with Δ=0.5 and based on an f harvesting strategy

4 Development and application of management procedures for fisheries in southern Africa 955 Table 1. Summary of robustness tests of the South African west coast hake management procedure (for further details see Geromont and Butterworth (1998c)). Robustness test Notable performance difference from base case A Changes altering future data generated by operating model: Catches Risk A1 Extent of variability of future recruitment altered. No Yes A2 Future c.p.u.e. change in efficiency not detected ((a) positive or (b) negative). Yes (if A2+A3 combined) Yes (if A2+A3 combined) A3 No future research surveys. A4* Future commercial catches have different selectivity (to allow for inclusion of long-lining) note that in the past long-lining contribution to total catch has been small and therefore not distinguished in operating model. A5 Increase or drop in carrying capacity (and recruitment) due to ecosystem change. Yes No B Changes affecting assessment based on past data: B1 Commercial c.p.u.e. data split into separate series of abundance for small (age 0 3) and medium+large (age 4+) fish. B2 Natural mortalities-at-age fixed at lower values than surprisingly high values in production model (Geromont and Butterworth, 1998a). B3 ASPM allows for recruitment variation about deterministic stock-recruitment relationship for the past 8 years. No No Yes No No No B4* ADAPT/VPA model used to estimate model parameters. B5 Discards taken into account. Marginal No B6* Pre-1978 ICSEAF commercial catches-at-age included in analyses. B7 Data for c.p.u.e. analysis ignore by-catch correlation. No No *Robustness tests A4, B4, and B6 were not evaluated. International Commission for the Southeast Atlantic Fisheries.

5 956 H. F. Geromont et al. Biomass ( 10 3 t) Relative abundance (q = 0.2) Absolute abundance (q = 1) Research survey summer Research survey winter Catch Figure 2. Age-structured production model estimates of age 2+ biomass for the Namibian hake resource for two scenarios: treating the research survey data as an index of relative and of absolute abundance. The research survey summer and winter survey data and reported catches are also shown. 94 coupled to a Fox production model, the resultant TAC recommendation for 1999 for the west coast hake resource was t, the same as the TAC of the previous year. The future A revised MP for the south coast hake resource needs to be developed (previously also managed in terms of a f 0.2 harvesting strategy coupled to a Schaefer production model). A particular concern here is that, in contrast to the west coast, long-lining, which has a very different selectivity pattern from trawling, constitutes a substantial component of recent catches, and may increase in future. As regards the MP for west coast hake, the basic ASPM assessment may not necessarily best reflect the actual present resource status and dynamics, so that it is important to check that candidate MPs are reasonably robust to various alternative plausible population models. In particular, an ADAPT/VPA approach, which estimates annual recruitment without the need for a stock-recruitment relationship, needs to be investigated as an alternative resource assessment model. Furthermore, the hake resource has been considered as a single stock in the revised MP evaluation so far, whereas it actually consists of two different species: shallow-water Cape hake (M. capensis) and deep-water Cape hake (M. paradoxus). Punt (1992) tested robustness of the previous MP to this, and found it to be adequate, but he assumed continuation of current selectivity patterns. However, increasing long-lining activities show different species- and sex-specific selectivities in their catches, and this development could have important implications for management which need to be investigated. Namibian hake Introduction The fishery for hake off Namibia commenced in the 1960s. In the early 1970s, ICSEAF (International Commission for the Southeast Atlantic Fisheries) was formed to regulate the multi-national fishery that had developed. Reported catches decreased and c.p.u.e. increased through the 1980s, although under-reporting of catches over this period has been alleged. In 1990, following Namibian independence, catches were sharply reduced and the fishery became primarily a local enterprise (see Fig. 2). Assessment of the hake resource was facilitated by combined hydroacoustics/swept-area trawl surveys carried out by a Norwegian research ship (the RV Fridtjof Nansen ) under an aid programme. However, management of the Namibian hake resource is at present confounded by the wide range of results of scientific assessments of its status. At the one extreme, if estimates of abundance from the research surveys are taken to provide reliable values for the resource biomass in absolute terms, the resource is evaluated as being heavily depleted (1997 age 2+ biomass (B 2+ ) about 0.1 of carrying capacity (K 2+ )), with large reductions in the TAC necessary if further depletion is to be avoided. At the other extreme, if the same results are considered as indices of relative abundance only, the resource is estimated to be above its MSY level, with B about 0.8 of K 2+, and large increases in TAC are possible without endangering the future of the fishery (see Fig. 2). The debate about the reliability or otherwise of estimates of absolute abundance from the research surveys has not been resolved. In the meantime, therefore, an interim approach for recommending annual TACs is

6 Development and application of management procedures for fisheries in southern Africa 957 Table 2. Stochastic 5-year projection results for the two extreme values of research survey bias factor, q, for Namibian hake. Distribution medians are shown. Units, where pertinent, are thousand tonnes. Catch B 2+ /K Average q=1: C * 97= C * 97= C * 97= q=0.2: C * 97= C * 97= C * 97= required. This on the one hand must not waste the resource, if the more optimistic appraisals of its status are correct, but on the other must provide recommendations for timely reductions in catch levels to avoid further substantial depletion of stock, should future data indicate that it is the current more pessimistic appraisals that reflect reality. A relatively simple approach was chosen because a defensible basis for deciding upon a TAC for 1998 was urgently required. Candidate IMPs considered The purpose of the candidate Interim Management Procedures (IMPs), developed by Butterworth and Geromont (1997), was to provide a simple means of setting TACs in the short term that performed well in terms of catch and risk of resource depletion across the wide range argued for resource status, from heavily depleted to under-exploited. The IMP adjusts the TAC up or down from one year to the next depending on whether recent trends in the research survey abundance index and the GLM-standardized c.p.u.e. data are positive or negative. The formula which provides the TAC recommendations is: TAC y =TAC y 1 [1+λs y ] (2) where TAC y is the TAC in year y for y>1997, TAC 1997 =C * 97 is the IMP starting value (or seed ), λ and C * 97 are control parameters whose values are pre-chosen, and s y is a measure of the average trend in the survey and c.p.u.e. abundance indices from year y 4 toy. The different candidate IMPs described by Equation (2) are distinguished by two control parameters, each of which was chosen on the basis of achieving an optimum trade-off between the values expected for various measures of procedure performance. The first of these parameters (λ) reflects how strongly the TAC is adjusted in response to a trend in resource size. The second control parameter reflects the starting level for the above formula. To calculate the TAC for 1998, this formula requires C * 97 to be input, instead of the 1997 TAC, which has a value chosen by decision-makers. Robustness tests and results An ASPM assessment, fitted to research survey and commercial abundance and catch-at-age data available for both pre- and post-1990 Namibian independence, was used for testing the candidate IMPs (details can be found in the Appendix to Butterworth and Geromont, 1997). As indicated above, the key uncertainty among those tested related to assumptions made about the research surveys, characterized by the value of q, the constant of proportionality between the true biomass and the research survey results. To reflect this uncertainty, the performance of candidate IMPs was tested over a range of ASPM assessment results corresponding to fixing q at values of 1 (taking the survey results as estimates of biomass in absolute terms), 0.8, 0.6, 0.4, and 0.2 (when treating these results as a relative index). Ideally, the performance statistics should be robust across this range, i.e. show acceptable results whichever value of q best reflects the true situation. Upon inspection of initial results it was decided to fix the first of the control parameters, λ, equal to 3, so ensuring fast reaction to trends in the indices of abundance. The second control parameter was chosen by a joint meeting of government scientists and industry representatives after consideration of the results in Table 2, which contains performance statistics for the two extreme values of q (0.2 and 1) for different values of C * 97 ranging from to t. On the one hand, a large C * 97 is desirable as this would maximize the future catch. For example, if q=0.2, a value for C * 97 of t would result in an average TAC over the period from 1998 to 2002 of t. However, if q=1, this choice of C * 97 would lead to a reduction in median age 2+ biomass from a fraction of K 2+ to an even

7 958 H. F. Geromont et al. November survey biomass ( 10 3 t) Sardine Anchovy Sardine by-catch Sardine by-catch with anchovy (%) Figure 3. Estimates of sardine and anchovy adult biomass from the November hydroacoustic surveys, and sardine by-catch as a percentage of the anchovy catch in commercial landings that constitute more than 50% anchovy lower value of On the other hand, a value for C * 97 of t would keep the median 2+ biomass at its current proportion of K 2+ for q=1. A compromise in terms of catch and subsequent risk was necessary and a central value of C * 97= t was eventually adopted. Once the latest c.p.u.e. and research survey estimates of abundance became available, the TAC for 1998 could be determined by applying Equation (2) with the choice of control parameters discussed above. The resultant TAC recommendation for 1998 was t, a 25% increase over the 1997 TAC. The future The main disadvantage of this IMP arises from the necessity that it performs well for extreme scenarios. If the extent of uncertainty about the research survey proportionality constant, q, can be reduced, a new MP can be developed that need no longer cater for extremes, so performing better in terms of maximizing the actual sustainable catch without undue risk to the resource. There are a number of ways of dealing with the uncertainty about q. The most important step would be to eliminate those values that are deemed unrealistically high or low. In addition, weights could be assigned (relative probabilities) to the plausible values, and results for each could then be integrated to obtain resultant distributions. Once progress is made regarding q, work can commence on the re-development of the procedure. First, re-evaluation of the actual IMP is required: for example, different control parameter (λ, C * 97) combinations could be investigated. However, a longer-term approach is also necessary. That would involve a more thorough analysis in which a comprehensive range of estimators, such as the Schaefer, Fox, and age-structured production models examined for the South African west coast hake fishery, are subjected to a wider range of robustness tests to plausible variations in the assumptions of the underlying population models. South African pelagics Introduction Major development of the South African pelagic fishery started in the 1950s, and annual landings of pelagic species have averaged some t over the past 10 years. Sardine (Sardinops sagax), anchovy (Engraulis capensis), and round herring (Etrumeus whiteheadi) form the bulk of the catch (more than 90% since the mid- 1970s), but only sardine and anchovy are currently subject to annual TACs. AMPwasfirst used to set TACs for anchovy in 1991, but it was extended in 1994 to incorporate both anchovy and sardine. A sardine-only MP was used in 1997 following the very low abundance of anchovy observed during 1996, but that was subsequently abandoned in 1998 following the recovery of anchovy (Fig. 3). These procedures have been described in detail elsewhere (Butterworth and Bergh, 1993; Butterworth et al., 1993; De Oliveira et al., 1998a, b). The MP currently being developed (referred to below as the 1998 procedure) is again multi-species in nature, and is used here to illustrate the trade-offs (anchovy versus sardine) that are fundamental in the pelagic fishery. MPs considered The multi-species MPs used to date have been based on the following biological and fishery-related features: the pelagic fishing season lasts from January to December two hydroacoustic surveys are conducted each year, the November survey providing estimates of the

8 Development and application of management procedures for fisheries in southern Africa 959 adults and the May/June recruit survey estimates of the juvenile components of both species although adult anchovy are targeted in the first 3 months of the year, the anchovy fishery is essentially a recruit fishery, the bulk of landings comprising juveniles targeted from April onwards the sardine fishery targets adult sardine, with fishing effort applied evenly throughout the year mixed shoaling of juvenile anchovy and sardine means that anchovy fishing is inevitably accompanied by a by-catch of juvenile sardine fishing for round herring is usually accompanied by a by-catch of adult sardine. The decision rules for these procedures are designed to allow a two-staged process for setting TACs. The following rules are used: TAC s =βb s adult (3) TAB s =δ+γtac a (5) where superscripts indicate species (s=sardine, a=anchovy), TAC/B is the total allowable catch/bycatch, B adult is the estimate of adult biomass from the November survey, N juvenile is the estimate of recruitment numbers from the recruit survey, back-calculated to the start of the year, and Bz and Nz are averages of the corresponding quantities. Furthermore, f is a function of B adult and N juvenile relative to their respective past averages, β is a fixed proportion, α is a scaling factor linked to the anchovy-sardine trade-off, δ is a fixed tonnage of adult sardine linked to round herring, and γ is a proportion linked to the anchovy TAC indicating juvenile sardine bycatch. For the first stage of setting TACs (usually in January), all three rules are used, but f in Equation (4) assumes that N a juvenile=nx a juvenile (because there is as yet no estimate of forthcoming recruitment) and adjusts the resultant TAC downwards to offer protection against possible poor recruitment. The initial γ is assumed to be a fixed proportion of the initial TAC a. In the second stage (usually in June/July), only TAC a and TAB s are adjusted on the basis of results from the May/June recruit survey. The actual N a juvenile estimate is used in Equation (4) (f no longer adjusts downwards), and the revised γ is now a variable proportion of the revised TAC a, whose magnitude depends on the survey estimate of sardine recruitment. Both the 1994 and 1998 procedures are described by the decision rules above (Equations 3 5), but with differing values for α, β, δ, and the initial γ, and a different way of calculating the revised γ (see below). In addition to the decision rules, these procedures also allow for industry constraints, such as minimum TAC levels and the maximum percentage drop in TAC from year to year that the industry is able to tolerate (Butterworth et al., 1993; De Oliveira et al., 1998a). Furthermore, exceptional circumstances meta-rules replace these decision rules when adult-biomass estimates from the November survey drop below predefined critical levels (De Oliveira, 1995). However, for simplicity, these constraints and meta-rules are not presented here. Considerable uncertainty exists about some of the assumptions of the base-case operating model used to test these procedures, and robustness tests were used to determine to which MP performance was most sensitive. In the case of sardine, the most important uncertainties relate to natural mortality values assumed, the extent of bias assumed in abundance estimates from the November hydroacoustic survey, and the functional form assumed for the stock recruitment relationship. Similar uncertainties were less important for anchovy because the MP eventually selected by advisers to decisionmakers underutilizes anchovy (see below). On the other hand, relative weights accorded to different sources of data in estimating the values of the parameters of the operating model, and the possibility of a regime shift from a system dominated by anchovy to one dominated by sardine, proved of much less consequence to MP performance. Shift in emphasis There has been an important shift in emphasis from the 1994 to the 1998 multi-species procedures related to how the sardine TABs have been calculated. In 1994, the approach was to optimize anchovy TACs independently of sardine by tuning function f (with α=1) to achieve an acceptable level of Risk (defined in the caption to Table 3) for anchovy. Sardine TABs were set as conservatively as possible (but not so conservatively as to render them impossible to implement) and, within these TAB constraints, sardine-directed TACs were optimized by tuning β to achieve an acceptable level of Risk for sardine. The revised γ (and hence revised TAB) in this procedure was not related to any estimate of the relative abundance of (mixed) sardine and anchovy juveniles; the short time-series and unreliability of the sardine recruit survey estimates at the time precluded this possibility. Instead, the revised γ was set equal to the initial γ, unless sardine recruitment was above average, in which case the revised γ was increased linearly as a function of the sardine recruitment (De Oliveira et al., 1998a). The emphasis in the 1998 procedure has shifted towards a more realistic reflection of what the sardine to anchovy juvenile mix is likely to be when setting sardine by-catch levels. This became necessary following the

9 960 H. F. Geromont et al. Table 3. Summary performance statistics for the 1998 management procedure options for South African pelagics. Results are for various values of β, the proportion of the sardine biomass estimate at which the directed sardine TAC is set, and correspond to the initial sardine by-catch allocation set at a proportion γ=0.12 of the initial anchovy TAC. For each of these, α is adjusted to reflect a risk of 10% for sardine. A value for δ of t (allowance for the round herring fishery) is included in the average catch performance statistic for sardine by-catch. Catches are in thousand tonnes. Summary performance statistics are defined as follows: average catch is the average annual catch for the specified categories (anchovy-directed catch, sardine-directed catch, and sardine by-catch) over a 20-year projection period; interannual catch variability is the average annual change in TAC as a percentage of the directed catch; depletion is the average adult biomass at the end of the projection period as a proportion of K, its average value in the absence of exploitation; and risk is the probability that the adult biomass falls below 20% of K at least once during the projection period. Average catch Interannual catch variability (%) Depletion α β Sardine Anchovy Direct By-catch Anchovy Sardine direct Anchovy Sardine direct Risk anchovy high levels of sardine by-catch in anchovy catches from 1994 onwards relative to the years prior to 1993 (Fig. 3), and the relative failure of the 1994 procedure to set workable by-catch levels. The 1998 procedure therefore uses estimates of the sardine to anchovy juvenile mixture from both the recruit survey and commercial catches in order to calculate the revised γ (in this case, the revised γ is essentially a weighted average of the sardine to anchovy ratio from the survey and recent catches). This approach has been made possible because of the increased confidence in the sardine recruit survey estimates and the longer time-series now available for these estimates. The by-catch component of the 1998 procedure therefore provides a more realistic by-catch allocation than did the 1994 procedure, and it uses the by-catch decision rule as a non-negotiable starting point. If higher levels of sardine-directed TACs (i.e. higher β) are desired, then sardine TABs have to be kept low, and in order to do so the anchovy TACs have to be adjusted down (i.e. α decreased) so that the combined procedure (anchovy and sardine together) is tuned to an acceptable level of Risk for sardine (currently 10%). Alternatively, higher anchovy TACs (i.e. larger α) lead to higher sardine TABs, which consequently require sardine-directed TACs to be adjusted down (i.e. β decreased) to keep sardine Risk at the 10% level. Results and future developments The sardine anchovy trade-off is one of the most important features of the 1998 procedure, and it is illustrated by comparing the summary performance statistics given in Table 3 for various values of α and β. Here, once a value for β is set, α is adjusted to reflect the same Risk for sardine in each case, namely 10%. Lower values for β favour an anchovy-directed fishery, although Risk for anchovy is too high for β=0. Alternatively, higher values for β favour a sardine-directed fishery, but lead to underutilization of anchovy (Depletion levels close to 1). Therefore, in the 1998 procedure, the sardine anchovy trade-off is such that, if reasonable levels of sardine-directed catch are to be attained, the anchovy resource will inevitably be underutilized. This feature has grave implications for the anchovy fishery, and approaches are currently being investigated to improve anchovy utilization without sacrificing either sardine-directed catches or the necessity of using a sardine by-catch formulation that reflects the actual observed sardine to anchovy juvenile mix. On the basis of the results given in Table 3, advisers to decision-makers selected an MP option with β= South African west coast rock lobster Introduction The fishery for Jasus lalandii commenced in the late 1800s. Annual catches increased gradually until, by the 1950s, the resource was yielding between and t annually. Smaller catches followed as the resource was fished down, and during the 1980s the fishery yielded 3800 t per year on average. Owing to substantial reductions in the somatic growth rate of the lobsters from 1989, however, the fishery was placed under severe strain, with ever-decreasing TACs

10 Development and application of management procedures for fisheries in southern Africa 961 being set. By 1995 the TAC was only 1500 t. This has since been increased gradually to 1920 t for the 1997 season as somatic growth rates have shown slight improvement. Assessments have shown that the female spawning biomass may be as low as some 20% of its pristine level, raising the possibility of a consequent reduction in recruitment. MP development There is much scientific uncertainty and very diverse political viewpoints about the rock lobster resource. A number of different users have conflicting interests. To confound these problems, there is also a high degree of environmental variability; for example, in causing the major change in somatic growth rate at the end of the 1980s. A management approach that can function effectively under such diverse and different circumstances is clearly a much-desired objective. For these reasons there has been a strong wish to develop a MP for the resource which can be put into place for a period of at least three years, and hence essentially automate the process of TAC recommendations. During the initial stages of the process, advisers to decision-makers were asked to consider a number of issues and to provide some feedback to facilitate the development of a final set of candidate MPs. They chose to endorse a resource rebuilding strategy suggest possible target biomass levels which were between 20 and 50% above the 1996 level to be reached over a 10-year period suggest the 1997 TAC level be set at either a 10 or 20% increase over the 1996 level of 1700 t. In all, 12 candidate MPs were subsequently defined to cover combinations of these management objectives. They used a number of different types of data collected from the resource as inputs into an algorithm to set a TAC each year. The basic rationale is that, if the inputs show an increasing trend in biomass then the TAC is increased, whereas if the inputs reveal a downward trend, the TAC is reduced (for details see Johnston, 1998). The MP thus has an implicit feedback structure and hence is able to self-correct, at least to a certain extent. The three types of data used, each with 3-year averaging, are: commercial c.p.u.e. data FIMS c.p.u.e. data somatic growth data The MPs developed had a 15% maximum TAC reduction constraint built into the algorithm. Those advising the decision-makers felt, however, that there should be situations for which this 15% constraint could be Fisheries-Independent Monitoring Survey. overridden. For this reason exceptional circumstances are identified for which the MP-generated TAC is modified, i.e. allowing more than a 15% TAC reduction if required, in order to offset the consequences of a very bad event. This is seen as an additional safeguard to prevent further depletion of the resource. Robustness tests and results A size-structured model was developed to simulate the resource and its associated fishery. This model provided a framework in terms of which to assess the performance of the various candidate MPs (Johnston, 1998). Summary performance statistics included the average annual catch over the 10-year period, the average interannual catch change, and the biomass above 75 mm carapace length at the end of the projection period divided by that at the start. Simulations were run stochastically and a wide range of robustness tests were conducted (Table 4). The MPs were adequately robust in risk-related terms to most of the uncertainties considered. In other words, the TAC would be adjusted appropriately by the MP so as not to seriously compromise the attainment of the required biomass recovery target. A particularly notable result was that performance is good for uncertainties relating to the future somatic growth rate of the lobsters. Given the recent period of very slow somatic growth which resulted in large reductions in TAC, a MP which can handle the possibility of such future growth reduction in a robust fashion and without high levels of interannual TAC change is a valuable achievement. However, whereas the MPs perform well for most of the robustness trials, they do not perform that well in situations where there is uncertainty regarding future recruitment levels and productivity of the resource. After examination of various results, the advisers selected the least conservative of the 12 candidate MPs the one that aimed for a 20% biomass recovery over the 10-year period in conjunction with a 1997 TAC increase of 20% over the 1996 TAC level. They recommended that that MP be implemented for a period of three years. Future developments The size-structured operating model used in the tests can be improved. Since its development, new data have become available and this model will need to be updated to incorporate these. Certain of the assumptions made are also being re-evaluated. Research into some mechanism for estimating puerulus settlement would aid management, because weak year classes could be predicted in advance and possible recruitment failure

11 962 H. F. Geromont et al. Table 4. Summary of the robustness tests of the South African west coast rock lobster management procedure (for further details, see Johnston (1998)). Robustness test Notable performance difference from base case A Changes altering the future data generated by operating model: Catches Risk A1 Future somatic growth (range from highest to lowest historic levels). Yes No A2 Future stock size (current recruitment and 1996 numbers-at-age half/double current estimates). Yes Yes A3 Environmental catastrophe (50% drop in recruitment for 3 years, or 50% of all lobsters die). Yes Yes A4 Poaching (100% increase or decrease over next 5 years). No No A5 Bias in input indices (post-1994 c.p.u.e. remains constant irrespective of stock trend; 2.5% No No increase/decrease in trap efficiency. A6 Fishing selectivity (hoopnets employed in all post-1996 commercial catches). No No A7 Walkouts (e.g t of female lobsters beached and died due to low oxygen waters in 1997). No No B Changes affecting the assessment based on past data: B1 Natural annual survivorship (0.85 or 0.95 compared to base case value of 0.90). Marginal Marginal B2 Discard mortality (0% to 15% compared to base case estimate of 10%). No No B3 Somatic growth (adult females 0.25 mm more/less than assumed). No No detected in time to make appropriate compensating adjustments to the TAC. Namibian seals Introduction Cape fur seals (Arctocephalus pusillus pusillus) off Namibia comprise some two-thirds of the total population of the species. Breeding colonies stretch from Cape Cross in Namibia to Algoa Bay in South Africa. Until 1974, no quota system for seal harvests was enforced, and it was the market and closed seasons that regulated exploitation. In the 10 years before the international market for fur-seal skins collapsed in 1983, the population yielded an average annual harvest of about pups. Aerial censuses of the annual pup production started in December 1971 and a population model was developed to estimate the population size off Namibia which, for 1993, was roughly (excluding pups). However, a severe environmental anomaly in 1994, which caused the death of a large number of both adult seals and pups, caused some concern among industry and scientists about the future of the resource. MP development An age- and sex-structured population model based on that developed by Butterworth et al. (1995) and extended in Appendix 10 of Anon. (1997) was used to estimate the current size and sex/age structure of the population. A MP was then constructed and tested using this as the operating model for the underlying dynamics. Aerial censuses, conducted between 18 and 24 December at least every 3 4 years since 1971, monitor the number of seal pups born. It is assumed for testing purposes that these surveys will continue every three years, following the last survey which was conducted in December In late 1994 and early 1995 many pups and adult seals died from starvation, which arose from food shortages associated with an intrusion of warm, low-oxygen water into the northern Benguela. A large number of aborted foetuses was also discovered in The aerial survey counts from December 1994, 1995, and 1997 were used to estimate the extent of additional adult female and pup mortality and abortions that occurred during this period, which were found to be 40, 34, and 46% respectively. Figure 4 shows the fit of this model to the census data. The industry advised preferred minimum and maximum annual harvest levels (TACs) for both pups and bulls. These values were and for the pups and 3000 and 7000 for the bulls. The algorithm was designed to enforce these specific constraints. For year y, the most recent pup census in December of year y-2 (or earlier) is used as an input, because the counting of the aerial census photographs takes time and the TACs need to be set early in the year. Future pup census data were assumed to reflect the same level of error as was estimated when the population model was fitted to the historic data (a 13% CV). Since 1987, observations have been made to enable the rates of pup survival from birth to mid-december (when the aerial surveys are conducted), from mid-december to mid- January and post-weaning (which occurs at approximately 8 months of age), to be estimated. In the projections, future survival rates are drawn at random from the associated distributions of observed values. The first two estimates of survival rate are also used as inputs. Essentially, the harvest levels set rise from the

12 Development and application of management procedures for fisheries in southern Africa 963 Numbers of seal pups (thousands) Model-predicted number of pups Projected numbers of pups under base case Projected numbers of pups under worst case scenario (A1) Pup harvest and projected harvest Census values Figure 4. Base case fit to the census data (where the trajectory passes exactly through the last three censuses) and future projections for the base case and robustness test A1, with pup harvest and projected harvest levels. minimum to the maximum specified over a range of values of the product of the most recent census estimate and these observations of survival rate. An equation similar in form to Equation (1) is used to reduce the extent of interannual TAC fluctuations. Full details are given in Butterworth et al. (1998). Robustness tests and results Two key performance statistics were focused upon: the adult female numbers in 2013 relative to those in 1997 (F(13/97)) and the adult female to territorial bull (F:M(13)) ratio in Roughly speaking, these statistics are separately determined by the sizes of the pup and bull harvests, respectively. When the model was projected forward for 15 years, with fixed annual catches of pups and 7000 bulls, favourable results for these statistics were obtained (i.e. results involving no risk of unintended or undue depletion). A wide range of deterministic robustness tests reflecting differences in model inputs and assumptions to those of the base case (see Table 5) were run for these fixed harvest levels. As all these predictions were favourable, the model was then projected forward with a fixed double pup harvest, i.e pups and 7000 bulls. Stochastic projection results were obtained for the robustness tests yielding the most pessimistic risk-related results in terms of adult female depletion. These tests differed from deterministic ones in that they allowed for variation in future rates of pup survival and random error in future aerial censuses of pups. These most pessimistic tests were A1, B6, B7, and B11 (see Table 5 for details). Under the original fixed pup and 7000 bull harvest levels, these robustness tests gave a median F(13/97) ratio ranging from 1.17 to For the fixed pup and 7000 bull harvest levels, the median F(13/97) ratio dropped below one for a number of the tests (representing a net decrease in the number of adult females), whereas the F:M(13) ratio increased to fairly high values. It reached a median of for the B6 (female annual survival=0.92) robustness test. When the management procedure described above was projected forwards with maximum constraints of and 7000 on the pup and bull harvests, respectively, the statistics showed an improvement. The F:M(13) statistic improved further when the maximum bull harvest was reduced from 7000 to A MP with a 5000 bull harvest maximum and a maximum pup harvest of for the years , increasing to in 2001 and in 2002, was finally selected. The MP will decrease these harvest levels linearly from these maxima to lower values as the product of the most recent aerial pup census results and the birth to mid-january survival rate drops from