© 2005 International Council for the Exploration of the Sea
Did over-reliance on commercial catch rate data precipitate the collapse of northern cod?
Department of Fisheries and Oceans, Northwest Atlantic Fisheries Centre PO Box 5667, St John's, Newfoundland, Canada A1C 5X1
*Correspondence to P. A. Shelton: tel: +1 709 7722341; fax: +1 709 7724105. e-mail: sheltonp{at}dfo-mpo.gc.ca.
It has been suggested that a number of "lessons" can be learned from the collapse of the northern cod stock off Newfoundland and Labrador. However, not all purported lessons have been validated with available data. One lesson is thought to be that over-reliance on commercial catch rate data and an incorrect assumption regarding the functional relationship between catch rate and population size were major contributors to overestimating stock size, precipitating the collapse. The current study describes calibration approaches used in assessments, and evaluates alternative functional relationships between commercial catch rates and stock size. In addition, historical population size is re-estimated using only research vessel data and compared with estimates obtained based on both commercial catch rate and research vessel data. Calibration with commercial catch rate contributed to overestimating stock size in some years, but there is no evidence that the assumed functional relationship between commercial catch rate and population size was a significant factor in the collapse.
Keywords: catch rate, cod, collapse, model calibration, population estimation, stock assessment
Received 3 November 2004; accepted 4 April 2005.
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Introduction |
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 Top Introduction Calibration approaches applied...MethodsResultsDiscussionReferences |
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The northern cod (Gadus morhua) stock off Newfoundland and Labrador (NAFO Divisions 2J + 3KL; Figure 1) collapsed precipitously in the late 1980s and early 1990s and has not recovered. It has become the classic case study of the failures of fisheries science and management to ensure sustainability of a commercially exploited fish population, despite availability of a considerable amount of scientific data. It has been suggested that many "lessons" can be learned from this case study (Hilborn and Walters, 1992; Hutchings and Myers, 1994; Hutchings, 1996; Walters and Maguire, 1996), but not all purported lessons have been carefully validated with available data.
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One lesson is thought to be that over-reliance on commercial catch rate data combined with an incorrect assumption regarding the functional relationship between commercial catch rate (CR) and population size was a major contributor to overestimating stock size, and precipitated the collapse (Hilborn and Walters, 1992; Hutchings and Myers, 1994; Hutchings, 1996; Walters and Maguire, 1996; Rose and Kulka, 1999). There is prima facie evidence that this was the case. Commercial catch rates were used extensively in the calibration of northern cod population models by DFO (Canadian Department of Fisheries and Oceans) and NAFO (Northwest Atlantic Fisheries Organization) scientists over the period from extension of jurisdiction to 200 nautical miles in 1977 up to the moratorium on directed fishing in 1992 (Bishop and Shelton, 1997). It is known that assessments overestimated the size of the stock through the 1980s (Sinclair et al., 1991). It is also well known that progressive improvement in fishing techniques through learning and technological advancement (Hilborn and Walters, 1992), interaction between the heterogeneity in fish distribution and searching activities of fishers (Paloheimo and Dickie, 1964), and abundance-dependent expansion and contraction of range (MacCall, 1990) can all cause departures from a strictly proportional relationship of the form y = bx between a CR index y and stock size x. In the case of northern cod, it has been claimed that the relationship between CR and stock size could best be described by a power function, y = bxc, with c in the range 0.4–0.5 (Hutchings and Myers, 1994; Walters and Maguire, 1996). A power model with c < 1 corresponds to CR remaining relatively high when a population declines, the so-called "hyperstability" phenomenon (Hilborn and Walters, 1992). The purported incorrect assumption of a strictly proportional relationship between CR and stock size by assessment scientists, instead of a power model, has been stated to be a prime factor in the overexploitation and collapse of northern cod (Hutchings and Myers, 1994; Hutchings, 1996; Walters and Maguire, 1996).
The purpose of the present study is to go beyond the prima facie evidence and to look at how CR data were actually used and what effect this may have had on the estimates of population size. There are three parts to this study: (i) a brief review of approaches taken in assessments to calibrate models of northern cod with CR and research vessel (RV) data; (ii) an exploration of the relationship between CR and stock size; and (iii) retrospective analyses of estimates of population size based only on RV data, compared with the original assessments based on CR and RV data. Conclusions are then drawn regarding the actual role of CR data in assessments of northern cod.
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Calibration approaches applied in assessments |
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TopIntroductionCalibration approaches applied...MethodsResultsDiscussionReferences |
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The approach used in annual stock assessments to derive population estimates for northern cod from CR and RV data varied from year to year, and evolved over time. The influence of these methodological changes cannot be ignored in interpreting the role of CR data in the estimation of population size. Assessment approaches between 1977 and 1993 are described in Bishop and Shelton (1997), based on details provided in annual assessment documents. Major methodological changes relevant to this study are summarized in Table 1. As methodologies improved and more data became available, assessments evolved from an ad hoc exploration of alternative values of terminal fishing mortality (Ft) using virtual population analysis (VPA; Quinn and Deriso, 1999) to the use of a formal statistical framework (ADAPT; Gavaris, 1988).
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Starting in 1980, VPA calibration was based on regression models of standardized CR against various measures of stock size (Table 1). Standardized CR was obtained by applying a general linear model to log-transformed data (a multiplicative model), controlling for factors such as country, gear, month, and division (Gavaris, 1980). From 1980 to 1987, the regression model applied in the calibration was an intercept model, y = a + bx, where y is the standardized CR, x a measure of stock size, a the intercept, and b defines the slope of the relationship between CR and stock size. Baird et al. (1991) reported that criteria for selecting Ft from the intercept model over this period were some combination of (i) highest r2, (ii) pattern of residuals (particularly for the most recent data points in the regression), and (iii) closeness of the intercept to the origin. These three criteria played varying roles in the decision on the appropriate Ft value, and assessment documents routinely reported that Ft was selected based on the value that "agreed best with the data". In practice, r2 and intercept values were often similar across a range of Ft, making the choice somewhat arbitrary. In all years, the final model included an intercept. Ft resulting in the smallest intercept was adopted by default only when highest r2 co-occurred with the smallest intercept (e.g. 1983). Once ADAPT was introduced in 1988, a log zero-intercept model, ln(y) = ln(bx), was routinely applied.
In 1982 a major change was introduced into the assessment. Rather than treating the CR data as a single series from 1962 onwards, concerns over changes in catchability caused by changes in the fishing fleets after extension of jurisdiction in 1977 led to separate standardizations of CR data for the periods 1962–1979 and 1979–1982. The two series were then joined by scaling each relative to the common 1979 value. Also in 1982, preliminary RV data for part of the stock area were evaluated as an index, but the final calibration was based only on CR data. In 1984, RV data began to influence the scientific advice from the assessment for the first time, and Ft was chosen by averaging the values that maximized r2 from separate intercept models fitted to CR and RV data. In 1985, a change in the way CR data for the two time periods were combined was introduced. Rather than scaling by 1979 values, scaling was based on both 1978 and 1979 data. A second calibration was run with data only from 1977 on, because of concerns regarding changes in catchability. Results from the second calibration only were used as the basis for scientific advice in 1985.
In 1986, the use of age-aggregated population numbers rather than biomass was introduced in the calibration with RV data. Again two separate calibrations were run, the first with CR data for 1962–1985, and the second with CR data for 1979–1985. Both calibrations were considered in providing scientific advice. From 1987 on, the CR data prior to 1978 were no longer used in the assessment because of concerns about joining the time-series spanning the periods before and after extension of jurisdiction. In 1988, the ADAPT framework was implemented, and CR and RV indices were included in a single minimization. The RV index was age-disaggregated for the first time, and consequently received effectively seven times more weight in the sums of squares minimization than the age-aggregated CR index. In 1989, separate ADAPT formulations were applied to CR and RV data, and Ft was determined as the average from the two analyses. This had the effect of giving the CR and RV data equal weight in the estimation. Over the period 1990–1992, CR data were age-disaggregated and combined with age-disaggregated survey data in a single ADAPT formulation. CR data were not included in the final model used as a basis for providing scientific advice in 1992, and were dropped completely from the assessment in 1993.
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Methods |
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Relationship between catch rate and stock size
Four models of the relationship between CR and stock size were considered in the present study: y = a + bx (intercept model), y = bx (zero-intercept model), y = bxc (power model), and ln(y) = ln(bx) (log zero-intercept model). The intercept, zero-intercept, and power models are all nested within the full model y = a + bxc. The zero-intercept model is in turn nested within both power and intercept models. The intercept model was used to calibrate the VPA from 1980 to 1987, after which the log zero-intercept model was applied within the ADAPT framework. Hutchings and Myers (1994) asserted that a power model was the more appropriate model to apply to northern cod commercial CR data. This assertion was examined for data from the 1980 to 1987 assessments by applying an F test for nested models (
= 0.05). Zero-intercept, intercept, and power models were applied to the actual CR series from each assessment, using assessment-specific measurement units of stock size (i.e. 4+ biomass, exploitable biomass, mid-year exploitable biomass, mid-year offshore exploitable biomass, or beginning of year population numbers at age; Table 1), and assuming additive normal error. Stock size from the last VPA-based assessment of northern cod (Bishop et al., 1993) was used as the x-variable in the evaluation. This assessment used only RV data in the calibration of ADAPT. In the 1988–1991 assessments, a log zero-intercept model, assuming lognormal multiplicative error, was applied using ADAPT. The fit of this model was compared graphically with the fit of a power model for this period. Although not used in the actual assessments, zero-intercept and power models were compared statistically for the 1988–1991 data to evaluate whether a power model provided a better fit.
Retrospective analysis
Retrospective analysis denotes an examination of change in successive estimates of fishery variables such as population size (Sinclair et al., 1991; Mohn, 1999). In this study, annual assessments over the period 1977–1993 were replicated using terminal fishing mortality estimated in the final assessment model in each year, and resulting estimates of 4+ population size were plotted to examine the retrospective pattern. This exercise was then repeated using only RV estimates for 1982 and 1984–1991 to determine terminal fishing mortality (an RV index was not considered in the original 1983 assessment). This required re-estimation of Ft using RV data for those assessments for which separate calibrations were not carried out at the time of the original assessments (1988, 1990, 1991). The relative retrospective patterns from calibrations with and without CR data were then compared.
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Results |
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Relationship between catch rate and stock size
Sums of squares (SS) for the fit between the CR data from each assessment between 1980 and 1987 and the baseline estimate of stock size from the 1993 assessment (most recent estimates of population trajectory) were computed for zero-intercept, intercept, and power models (Table 2). In most cases, the SS for intercept and power models were similar and provided significantly better fits to the data than the simpler zero-intercept model (P13 and P23
0.05). In five of the comparisons, the power model had a slightly smaller SS than the intercept model (1980, 1981, 1983, 1985b, and 1986a), but both models gave similar fits to the data (Figure 2). In nearly all cases, the zero-intercept model predicted lower CR at low stock size than the intercept and power models. This would lead to larger estimates of stock sizes in the VPA when stock size was actually low. The largest difference in SS between the zero-intercept model and the two more complex models occurred in the 1985a and 1986a calibrations (Table 2). In both cases the zero-intercept model fitted the data poorly, under-predicting CR at low stock size, and over-predicting it at large stock size (Figure 2). Model fits for the intercept and power models were similar in both cases.
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Graphical comparison of log zero-intercept, zero-intercept, and power models to data from the 1988 to 1991 assessments showed that fits were similar (Figure 3; only age 6 model fits are plotted as examples for the age-disaggregated 1990 and 1991 assessments – other ages gave similar results). The biggest difference in predicted CR overall between the two models was in 1991 for age 6. Statistical comparison of zero-intercept and power models showed that, in all cases, the reduction in SS achieved by adding the exponent was not significant (Table 3).
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Retrospective analysis
The abundance of the 4+ population estimated in the original assessments shows that substantial downward revisions were common (Figure 4a). A number of these revisions coincided with methodological changes in the assessment described in Table 1, but revisions also reflect variations in indices used to calibrate the VPA and retrospective errors from unknown sources (e.g. catch under-reporting). Both CR and RV series used in calibration went through a number of changes between 1985 and 1989, beyond merely the addition of a survey data point for each subsequent assessment (Bishop and Shelton, 1997). There were downward revisions of VPA and ADAPT estimates also when calibration was performed with RV data only, but the magnitude was less (Figure 4b). Ratios of the original assessment estimates of the 4+ population to estimates based only on RV data in the calibration (Figure 4c) showed that differences were greatest in 1985, 1986, and 1989.
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The simplest explanation for large ratios in 1985 and 1986 is the difference in CR and RV trends over this period (Figure 5). Whereas the age-aggregated RV index had begun to decline after 1981, the CR index continued to increase until 1985. However, comparison is complicated by the fact that the RV index in the 1985–1987 assessments was based on fish aged 6+, whereas the CR index was derived from offshore commercial catches, in which there were considerable quantities of fish aged 4 and 5. The 1993 assessment baseline estimates indicate that the 4+ population only stopped increasing in 1985, consistent with the CR series. Although the general trends between the CR index and the 1993 assessment estimates of population size were reasonably consistent when age composition is taken into account, the magnitude of the post-1977 increase in the CR index was considerably greater than the population increase indicated by the 1993 assessment. A large 1986 RV index value resulted in a considerable upward revision in the size of the stock in the 1987 assessment (Figure 4a). When combined with the decline in CR in 1986, this resulted in a smaller ratio between estimates from the two calibrations for 1987 (Figure 4c), although in retrospect, both estimates were much too high.
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A sequence of major downward revisions in estimates of the size of the stock occurred in the 1988–1993 assessments (Figure 4a). The ADAPT framework was used for the first time in 1988. Data available in this assessment showed that the RV index had dropped considerably from the high 1986 value for nearly all ages used in the calibration, and the CR index had continued to decline for a second year (Figure 5). Because the indices had both declined and the ADAPT assessment gave effectively more weight to the age-disaggregated RV data, estimates of the 4+ population for 1987 using only RV data and those obtained from the original 1988 assessment based on both CR and RV data were quite similar. In the 1989 assessment, the age-aggregated CR series and the age-disaggregated RV index were applied in separate ADAPT runs, and the estimates of Ft were averaged, effectively giving both indices equal weight. In this assessment, 1986 and 1987 CR index values were revised upwards, and with the addition of the 1988 value, this gave an increasing trend in the CR series, in contrast with the RV index, which remained low for a second year (Figure 5). The diverging indices and the approach of averaging the estimates between the separate calibrations with the RV and CR data resulted in the CR data having considerable influence in the 1989 assessment relative to the previous assessment, giving the strongest evidence of CR data being misleading over the period of the cod collapse. Although there were further major revisions in the estimates of population size over the period 1990–1993, CR data had negligible impact in the 1990 and 1991 assessments, and were not used to calibrate ADAPT in 1992 and 1993.
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Discussion |
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TopIntroductionCalibration approaches applied...MethodsResultsDiscussionReferences |
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The widespread failure of fisheries management to maintain sustainable harvests of marine fish resources is epitomized by the case of the northern cod stock off Newfoundland. Reasons for this failure are still analysed and debated, reflecting a desire on the part of the fisheries science community to learn from mistakes. While the stock was still collapsing, it was recognized by scientists doing the assessments that population size had been overestimated, and a major downward revision was presented in the 1988 assessment (Baird et al., 1991). Three explanations were provided for the overestimation: too much weight given to misleading CR data, influence of the 1986 RV index outlier, and the use of subjective calibration methods prior to 1988. Of these three shortcomings, misleading CR data has received the most attention.
Hilborn and Walters (1992) expressed an opinion that cod biologists had been misled by increasing CR values attributable to increased harvesting efficiency rather than increased stock abundance following extension of jurisdiction in 1977. Hutchings and Myers (1994) endorsed this view, suggesting that increased ability to locate large assemblages of fish coupled with apparent increased concentration of northern cod in the 1980s had led to a non-linearity between CR and exploitable biomass, which could best be captured by a power curve. They concluded that the assumption of a strictly proportional relationship between CR and stock size in assessments was a prime factor in the overexploitation and collapse of the northern cod stock. Based on the 1993 assessment baseline estimates, the 4+ population did in fact increase from extension of jurisdiction in 1977 until 1985. However, the decline that began after 1986 was not detected until the 1988 assessment. CR data contributed somewhat to overestimation in the 1987 and 1988 assessments, but the impact was much larger in the 1989 assessment. In that assessment, the CR index suggested that the stock was beginning to increase again, whereas the RV index did not. The influence of the 1989 assessment on management decisions is considered further below. The impact of CR data on the 1990 and 1991 assessments was negligible, and from the 1992 assessments on, CR data were not used to calibrate the ADAPT.
Although the impact of CR data was substantial in only a few years during the decline and collapse of northern cod, the question remains whether or not the use of a more appropriate functional form of the CR-population size relationship, such as a power model, would have reduced overestimation. Hutchings and Myers (1994) examined the appropriateness of the power model for data from two time periods: 1962–1981 and 1982–1991. Data for the first time period correspond with the index of stock size used for calibrating the VPA in the 1982 assessment. However, the analysis by Hutchings and Myers (1994) differs from that actually applied in the 1982 assessment in a number of important respects. They used CR values from a preliminary analysis carried out by the NAFO Scientific Council in June 1982, rather than data from the final assessment, which took place in September 1982. Concerns were expressed at the June 1982 meeting that high CR values in 1980 and 1981 may have resulted from increased availability and not from increased abundance, and concerns were also expressed that catchability may have changed through increased efficiency after 1973 (Bishop and Shelton, 1997). For those reasons, data for the periods 1962–1979 and 1979–1982 were standardized separately (Bishop and Shelton, 1997). The two standardized series were then joined by scaling with the common 1979 value. This had the effect of decreasing the 1979–1981 CR values compared with the data analysed by Hutchings and Myers (1994). Further, in the calibration of the VPA in the assessment, data points for 1974–1976 were eliminated as outliers, whereas those data were included in the analysis by Hutchings and Myers (1994). In their analysis Hutchings and Myers compared a zero-intercept and a power model fit, and concluded that a power model provided a significantly better fit. In the actual assessment, an intercept model was fitted. In the present analysis, both the intercept and power models provided significantly better fits to the data than the zero-intercept model ( = 0.05), but the SS for intercept and power model fits were nearly identical and there were negligible differences between predicted values from the two models. The present study therefore concludes that the assessment would have been no different had a power model been used in the calibration rather than an intercept model. This conclusion also holds for other assessments over the period 1980–1987, corresponding to the period when ad hoc VPA calibration methods were used.
Catch rate data from the second time period analysed by Hutchings and Myers (1994), 1982–1991, do not correspond to any CR data series used in an actual stock assessment. The closest match is from the 1991 assessment, the last in which CR data were used in the calibration of the VPA. In that assessment, age-disaggregated CR data for ages 5–12 for the period 1983–1990 were applied in an ADAPT formulation. Hutchings and Myers (1994) used an age-aggregated index of CR and compared zero-intercept and power models. The actual model used in the assessment was a log zero-intercept model [ln(y) = ln(bx)]. In the present analysis, the zero-intercept and power models were compared on an age-by-age basis for the 1991 assessment data, and for none of the ages were the reduction in SS achieved by the power model significant. Graphical comparison of the log zero-intercept model and power model for CR data from the 1988 to 1991 assessments suggested little difference in predicted CR. It is therefore concluded that the assessment outcome would not have been different had a power model been used over the period 1988–1991.
Walters and Maguire (1996) endorsed the view that an erroneous assumption that CR data accurately reflected changes in abundance led to gross overestimation of the size of the northern cod stock and was partly to blame for the collapse. They concluded that assessors were "badly wrong" in assuming a "strictly proportional relationship (y = bx)" to abundance, citing the findings of Hutchings and Myers (1994) that a power relationship with an exponent in the range 0.4–0.5 was applicable. Walters and Maguire (1996) were unaware that an intercept model was used in the assessments and that a power model would have given almost identical estimates to the intercept model. MacCall (1999) also overlooked the details of the approach actually taken in the assessments in forming an opinion that the northern cod collapse provided a "notorious recent example" of the problem of non-linear catch per unit effort relationship, citing the findings of Hutchings (1996) related to hyperstability in the CR index, which were based on Hutchings and Myers (1994).
The role of CR data in the collapse of northern cod has therefore been widely misinterpreted. Although the intercept model used in the assessments over the period of ad hoc tuning does not have a mechanistic justification, it nevertheless provided a reasonable approximation to the functional relationship between CR and stock size within the range of the data, and did not lead to overestimation of population size through model mis-specification, as suggested by Hutchings and Myers (1994). This does not mean that a power model of the relationship between CR and stock size is not more appropriate in most cases. There is evidence from this stock and others that a power relationship with an exponent <1 is commonly applicable to modelling CR data. For most of the northern cod annual assessment data sets between 1980 and 1987 examined in this study, the exponent was significantly less than 1.0. These analyses were carried out under the assumption that the independent variable (1993 assessment estimates of stock size) was known precisely, and that the error in CR was normally distributed, to be consistent with the approach taken in the stock assessments and by Hutchings and Myers (1994). Recently Harley et al. (2001) carried out a meta-analysis of 297 CR data sets and, based on observation error and random effects models, found strong evidence of hyperstability (exponent < 1). In contrast with the 1980–1987 calibrations, there was little statistical evidence in the present study of hyperstability in the northern cod CR data used in the ADAPT calibrations over the period 1988–1991. This result is somewhat unexpected given that the fishing fleet was able to target remaining offshore aggregations of northern cod until just before the moratorium (Rose and Kulka, 1999; Shelton and Lilly, 2000). It may reflect management measures to spread fishing effort, noise in the data, and the short CR time-series used in the 1990 and 1991 assessments.
Although there is no evidence to support the contention of Hutchings and Myers (1994) that the assumption of an inappropriate functional relationship between CR and stock size was a prime factor in the overexploitation and collapse of the northern cod stock, it is nevertheless true that recovery of the stock following extension of jurisdiction was overestimated, detection of decline lagged actual decline, and the extent of the decline was underestimated. Use of CR data contributed to these errors. Overestimation in the 1989 assessment stands out, because much smaller estimates of stock size would have been obtained had CR data not been used in the calibration. One can speculate as to whether or not a lower estimate of stock size in 1989 would have had an impact on the management decisions taken then. Fishing mortality levels, although above the F0.1 target and increasing through the early to mid-1980s, were not out of control, and simulations suggest that, had the F0.1 control rule been followed, the stock would not have collapsed, despite the retrospective problem (Shelton, 1998). However, the F0.1 control rule was discarded by fishery managers in 1989 in favour of Fstatus quo, which resulted in a fully recruited F > 1.0. Subsequent stepwise reductions in TAC were ineffective in preventing F rising to >3.0 in 1992, when the moratorium was declared. While a more pessimistic assessment in 1989 might have had some effect, there was a strong reluctance at the time to reduce the TAC to the extent indicated by the scientific assessments. The apparent disappearance of the 1986 and 1987 year classes (Shelton and Lilly, 2000) led to major retrospective errors in the assessment over this period, which were independent of CR data, but by that time, management decisions were not based on scientific assessments and fishing mortality was out of control.
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References |
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Baird J.W., Bishop C.A., Murphy E.F. (1991) Sudden change in the perception of stock size and reference catch levels for cod in northeastern Newfoundland shelves. Northwest Atlantic Fisheries Organization Scientific Council Studies 16:111–119.
Bishop C. A., Murphy E. F., Davis M. B., Baird J. W., Rose G. A. (1993) An assessment of the cod stock in NAFO Divisions 2J + 3K, NAFO SCR Document, 93/86.
Bishop C.A. and Shelton P.A. (1997) A narrative of NAFO Divs. 2J3KL cod assessments from extension of jurisdiction to moratorium. Canadian Technical Report of Fisheries and Aquatic Sciences 2199: 66 pp.
Gavaris S. (1980) Use of a multiplicative model to estimate catch rate and effort from commercial data. Canadian Journal of Fisheries and Aquatic Sciences 37:2272–2275.
Gavaris S. (1988) An adaptive framework for the estimation of population size. Canadian Atlantic Fisheries Scientific Advisory Committee Research Document, 88/29.
Harley S.J., Myers R.A., Dunn A. (2001) Is catch-per-unit-effort proportional to abundance? Canadian Journal of Fisheries and Aquatic Sciences 587:1760–1772.
Hilborn R. and Walters C. (1992) Quantitative Fisheries Stock Assessment and Management: Choice, Dynamics and Uncertainty(Chapman & Hall, New York) 604 pp.
Hutchings J.A. (1996) Spatial and temporal variation in the density of northern cod and a review of hypotheses for the stock's collapse. Canadian Journal of Fisheries and Aquatic Sciences 53:943–962.
Hutchings J.A. and Myers R.A. (1994) What can be learned from the collapse of a renewable resource? Atlantic cod, Gadus morhua, of Newfoundland and Labrador. Canadian Journal of Fisheries and Aquatic Sciences 51:2126–2146.
MacCall A.D. (1990) Dynamic Geography of Marine Fish Populations(University of Washington Press, Seattle) 153 pp.
MacCall A. D. (1999) Use of decision tables to develop a precautionary approach to problems in behaviour, life history and recruitment variability. Proceedings of the 5th NMFS NSAW NOAA Technical Memorandum, NMFS-F/SPO-40: 43–64.
Mohn R. (1999) The retrospective problem in sequential population analysis: an investigation using cod fishery and simulated data. ICES Journal of Marine Science 56:473–488.
Paloheimo J.E. and Dickie L.M. (1964) Abundance and fishing success. Rapports et Procès-verbaux des Réunions du Conseil Permanent International pour l'Exploration du la Mer 155:152–163.
Quinn T.J. and Deriso R.B. (1999) Quantitative Fish DynamicsOxford University Press 542 pp.
Rose G.A. and Kulka D.W. (1999) Hyperaggregation of fish and fisheries: how catch-per-unit-effort increased as the northern cod (Gadus morhua) declined. Canadian Journal of Fisheries and Aquatic Sciences 56:118–127.
Shelton P.A. (1998) A comparison between a fixed and a variable fishing mortality control rule used to manage the cod stock off southern Labrador and the east coast of Newfoundland. Fisheries Research 37:275–286.[CrossRef][Web of Science]
Shelton P.A. and Lilly G.R. (2000) Interpreting the collapse of the northern cod stock from survey and catch data. Canadian Journal of Fisheries and Aquatic Sciences 57:2230–2239.
Sinclair A., Gascon D., O'Boyle R., Rivard D., Gavaris S. (1991) Consistency of some Northwest Altantic groundfish stock assessments. NAFO Scientific Council Studies 16:59–77.
Walters C. and Maguire J-J. (1996) Lessons for stock assessment from the northern cod collapse. Reviews in Fish Biology and Fisheries 6:125–137.[Web of Science]
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