SCRS/2012/118 Collect. Vol. Sci. Pap. ICCAT, 69(1): 335-377 (2013)

INDICES OF STOCK STATUS FROM THE CANADIAN BLUEFIN TUNA FISHERY

A.R. Hanke1, I. Andrushchenko, J.D. Neilson and C. Whelan

SUMMARY

The catch of Atlantic bluefin tuna from the Canadian rod and reel, tended line and harpoon fisheries is standardized for two geographically distinct areas: south west Nova Scotia and the southern Gulf of St. Lawrence. Nominal and standardized series from the two areas suggest an increasing trend in abundance that has been sustained since 2000.

RÉSUMÉ

La capture de thon rouge des pêcheries canadiennes de canne et moulinet, de ligne surveillée et au harpon a été standardisée pour deux zones géographiques différentes: le Sud-Ouest de la Nouvelle-Écosse et le Sud du golfe du Saint-Laurent. Les séries nominales et standardisées des deux zones suggèrent une tendance à la hausse de l'abondance qui se maintient depuis 2000.

RESUMEN

Se estandarizaron las capturas de las pesquerías canadienses de atún rojo de caña y carrete, barrilete y arpón, para dos zonas geográficas diferenciadas: Suroeste de Nueva Escocia y parte meridional del golfo de San Lorenzo. Las series nominales y estandarizadas de las dos zonas sugieren una tendencia creciente en la abundancia que se ha mantenido desde 2000.

KEYWORDS

Tuna fisheries catch rates, composition, hurdle model, bluefin tuna, rod and reel, catch standardization

1. Description of the data source

1.1. Description of the fishery and target species

The Canadian commercial bluefin fishery occurs between July and November, targeting bluefin tuna migrating into Canadian waters. There are two main commercial fisheries. One occurs off the coast of southwestern Nova Scotia (SWNS) and the other is in the southern Gulf of St. Lawrence (sGSL). The spatial distribution of the southwestern Nova Scotia fishery from 2010 to 2011 has been generally consistent with that of previous years (2002 – 2009), with catches localized along the northern edge of Georges Bank, the Hell Hole, Fundy Bay, St. Margaret’s Bay/Halifax and Canso (Figure 1). The Gulf of St. Lawrence fishery also showed consistency in fishing areas, typically being conducted in waters north of Prince Edward Island and west of Cape Breton Island (Figure 1).

Prior to 2004, the majority of trips for the SWNS fishery took place during the month of August, but in recent years the bulk of the fishing has taken place during September (Figure 2). This fishery has been dominated by rod and reel catches since the early 2000s, with smaller contributions by tended line, electric harpoon and trap (St. Margaret’s Bay); tended line was the predominant gear prior to 1996 (Figure 3). The Scotia-Fundy (SF) home fleet accounts for 50% of the catches in SWNS waters and since 2003 this proportion has increased to 75% due to fewer trips made by ex-sector fleets (GNS, GNB, PEI, PQ) (Figure 4).

In the sGSL the two largest fleets are from P.E.I. and Nova Scotia. The relative proportion of data from these fleets is shown in Figure 4. Fishing occurs between late June and November (Figure 5). Since 2000 the fishing tended towards a mostly August season. From 2006 to 2009 the tendency was to split the season into an early and late component and in 2010 there was only a late component. A return to pre-2000 fishing occurred with the

1 Fisheries & Oceans Canada, Biological Station, 531 Brandy Cove Road, St. Andrews, NB E5B 2L9 Canada. Email address of lead author: [email protected]. 335 implementation of individual transferable quotas in 2011. These trends are also evident in Figure 2 which emphasizes the amount of data associated with each year/month combination. In the SWNS fishery the switch to individual quotas began in 2004 and until 2011 the tendency has been towards a September oriented fishery.

Both the sGSL and SWNS fisheries have witnessed a transition from tended line dominated fishing to rod and reel (Figure 3). Tended line is now a very small proportion of fishing.

1.2. Ecosystem Considerations

Anecdotal evidence from Canadian fishermen indicates that while bluefin are abundant in Canadian waters, the bluefin tuna in the Gulf of St Lawrence are showing poorer body condition throughout the fishing season (see Section 1.7, but also see Figure 13 which illustrates a recent improvement in condition). This was not the case for Southwest Nova Scotia, where the fishermen indicated they have not seen a problem with the condition of the fish. For the 2012 fishing season, the fishermen reported higher than usual water temperatures early in the fishing season. Depending on location, there were varied reports concerning the abundance of bait fish (herring, mackerel and squid). For example, there were promising reports of the abundance of baitfish from Chedabucto Bay (off Nova Scotia, see Section 1.7). Abundance and condition of bluefin tuna in Canadian waters will depend on many factors; particularly the availability of their prey.

Atlantic bluefin tuna are seasonal migrants to feeding grounds in Atlantic Canadian waters (Scott and Scott, 1988). Bluefin in the northwest Atlantic feed on smaller fish, depending on the local species available, including; Atlantic herring, Atlantic mackerel, sand lance, bluefish, silver hake and squid (Bigelow and Schroeder, 1953; Chase, 2002; Dragovich, 1970). Commercial catch and trawl survey indices indicate that Atlantic herring and Atlantic mackerel are principal pelagic prey for bluefin tuna in the Gulf of Maine, and cephalopods (squid) are an important secondary source of prey (Chase, 2002). The Canadian fishermen report that bluefin are mainly feeding on herring and mackerel, although recent observations from the fishery suggest that bluefin are opportunistic predators, with varied prey such as lobsters and hagfish apparent in the stomachs of tuna collected off southwest Nova Scotia.

There are two stocks of Atlantic herring in Canadian waters that correspond with areas of bluefin tuna fishing. The 4VWX Herring corresponds with the bluefin fishery in southwestern Nova Scotia, the Bay of Fundy and the Scotian Shelf. The herring in 4T correspond the to the bluefin fishery in the southern Gulf of Lawrence north of Prince Edward Island and to the west of Cape Breton. The 4T herring stock is further divided into spring and fall spawning components. Given the timing of aggregations of both bluefin tuna and herring in the southern Gulf, it is likely that the fall component is the most consequential in the bluefin diet.

The herring spawning component for southwest Nova Scotia and the Bay of Fundy has seen a 32% reduction in spawning stock biomass from an average of 551kt from 2001-2004 to 377kt average from 2005-2010 (Figure 6) (DFO 2011). There is little or no sign of improvement from lower abundance levels observed in 2005-2010. The lack of rebuilding is a cause for concern. Science advice to management is to exercise caution, including catch restrictions on small fish. No observations suggesting reasons for concern or reasons to change the current management regime have been noted for the offshore Scotian Shelf portion of this stock. Although not understood, the declines in the southwest Nova Scotia and Bay of Fundy herring coincides with an observed change in herring condition; 2010 had the lowest fish condition on record since 1974 for the southwest Nova Scotia herring (this was not observed for the Bay of Fundy or of Scotian Shelf fish). There is also a trend of declining mean weight at age for the fish in this stock. The average weight at age values for 2000-2009 are lower than the long term averages from 1965 onwards. It has been reported that herring are staying in deeper, cooler waters where they are not vulnerable to weirs and less vulnerable to purse seines, although presumably still available for bluefin tuna.

Atlantic herring in the southern Gulf of St Lawrence are managed as two separate spawning components; spring spawners and fall spawners. The spring spawning component spawning stock biomass (18,300t) is just below the precautionary approach limit reference point (22,000t) placing it in the critical zone (DFO 2012a). The spring spawning population biomass has been declining since 1994 (Figure 7A) and has remained at low levels. However, as noted above, the spring spawning component is likely less important for bluefin than the fall component. The fall spawning component has significantly more biomass than the spring component. Unlike the spring spawning component, the fall spawning component is slightly above (183,800t) the precautionary approach upper stock reference point (172,000t) and the stock remains at a moderate level of abundance compared to the late 1970’s and early 1980’s (Figure 7B). Similar to the southwest Nova Scotia herring, both

336 the spring and fall spawning components are showing decreased weight at age. The causes of these decreases are unknown.

Landings of Atlantic mackerel in NAFO subareas 3 and 4 (which includes the range of bluefin tuna in the Canadian Atlantic) increased substantially in the 2000’s to reach an historic high of 54,621t in 2005, before landings dramatically declined to 8,544t in 2011. Similar trends in landings were also seen in the United States. The index of spawning biomass (measured by egg surveys) declined between 1993 and 1998, before an increase resulting from a strong 1999 year class. Following the strength of the 1999 year class, the spawning biomass index declined again to reach historic lows since 2005 (Figure 8) (DFO 2012b). The declines in Atlantic mackerel abundance are caused by unsustainable fishing mortalities and a lack of recruitment.

Research on the diet of bluefin tuna in the northwestern Atlantic has shown that squid is an important prey item (Bigelow and Schroeder, 1953; Chase, 2002; Dragovich, 1970). Anecdotal comments from Canadian fishermen indicate that squid is being seen in very high numbers in 2012; however, there is unfortunately no stock assessment or research available for the status of squid in Canadian waters.

The southern Gulf of St Lawrence has seen a major shift from a large groundfish and forage fish dominated system, to one dominated by small bodied forage fish. Although the groundfish fishery has been under moratorium since the mid 1990’s, increased natural mortality is preventing the groundfish from rebuilding, thus maintaining the southern Gulf as a forage fish dominated system (Dufour et al., 2010). Between 1985 and 2008, the surface waters of the Gulf of St Lawrence have seen an average increase in sea surface temperature of 2ºC (Galbraith et al., 2009). However, this is a short time series for warming trends and older records need to be reviewed to determine is this is a longer term warming trend. The cold intermediate layer (200-300m) was exceptionally warm from the late 1960’s until the early 1980’s, followed by very cold temperatures from 1986 to 1998 (DFO, 2012c). Temperatures at these depths have since returned to the long term average values. The impacts of these changes on bluefin tuna in this area are unknown at present, although the effects of such changes on bluefin tuna distribution and abundance are currently being investigated by DFO.

The Scotian Shelf has also seen structural shifts in the ecosystem as a result of changing environmental conditions and human activities (Worcester and Parker, 2010). This ecosystem has seen a major increase in the abundance of seals, benthic macroinvertebrates, phytoplankton and small pelagic fish, accompanied by decreases in groundfish and zooplankton. More recently, phytoplankton and zooplankton abundance levels are returning to their long term averages. The surface water temperature in the Gulf of Maine and along the Scotian Shelf shows high levels of variability with no discernible trend. A gradual cooling of deeper water was seen on the eastern Scotian Shelf during the same time period as the exceptionally cold intermediate layer in the Gulf of St Lawrence (mid 1980’s to 1990’s), but this was not observed on the western Scotian Shelf. As with the ecosystem changes in the southern Gulf of St Lawrence, it is unclear what the impact of these changes are on bluefin tuna.

The southern Gulf of St Lawrence, Scotian Shelf and southwestern Nova Scotia are all areas with high human impact. There are several other threats or human activities (such as oil and gas exploration, the impacts of aquatic invasive species, ocean acidification and a wide suite of contaminants) ongoing in these areas for which the impacts on different species, including bluefin, and the ecosystems as a whole are unknown.

1.3. Available statistics and changes in reporting requirements

In the Canadian bluefin fishery, detailed trip information comes from fishermen’s logs and is supplemented by anecdotal reports from the fishery. The submission of log records through the Canadian Atlantic statistical system has been mandatory since 1994 and provides real-time monitoring of catch and effort in the bluefin fishery. Since 1996, the system was extended to include coverage of trips with zero catch. At the end of every trip, the log information is checked by an independent, certified Dockside Monitor and submitted to the Monitoring Company for input into the central computer system. Ideally, this results in 100% coverage of log records and individual fish sizes, though slight variation exists from year to year (<3%). Despite this variation, available log records are assumed to be representative of the entire fishery.

There have been no changes to reporting requirements following the institution of mandatory log submission in 1996. The Canadian Atlantic statistical system provides information on trip catch (number and weight of tuna), size of fish (length and weight of GSL fish; weight of SWNS fish), effort (hours fished), date, gear characteristics, home port (fleet), catch location (latitude and longitude) and weight of other species caught in SWNS (albacore, bigeye, yellowfin).

337 1.4. Variables used in the development of the index, including variables related to targeting.

Southwest Nova Scotia index data series includes catches dating back to 1988 and has been limited to months August, September and October; occasional catches during May, June and November are excluded from the analysis as they are not present consistently throughout the years. The dataset includes gears rod and reel, tended line and electric harpoon, within two areas (Area 5 – inside Fundy Bay, Area 7 – outside Fundy Bay). The fleets involved in the SWNS fishery include the Scotia-Fundy home fleet and ex-sector fleets like PEI, Gulf Nova Scotia, Gulf New Brunswick and Province of Quebec. The data is aggregated to a trip level.

The southern Gulf of St. Lawrence fishery is prosecuted by fleets from Quebec, P.E.I, Newfoundland, Nova Scotia and New Brunswick homeports. The P.E.I. and Nova Scotia fleets are the largest of the five and have fished regularly since 1981 (Figure 5). The possibility of fleets fishing in distinct geographical areas required that the catch not be aggregated over homeport. As a consequence, there was little support in the data for the Quebec, Newfoundland and New Brunswick fleets in all years so they had to be dropped from the analysis.

The two main gears used in the southern Gulf of St. Lawrence were rod and reel and tended line with the former replacing the latter over the time course of the series (Figure 3). The data for the temporal explanatory variable month was truncated to include only fishing from August to October because fishing outside this time window was rare. Lastly, an explanatory variable was introduced to capture the trend in fishing season length by fleet, gear and month.

1.5. Size, age range and condition of the fish that the index applies to.

For southwest Nova Scotia, annual trends in individual fish weight are dictated by the market and are not considered to be representative of the population structure. In general, however, the range of the weights caught in the SWNS fishery has expanded in the late 2000s, with the mode showing an upward trend (Figure 9). The data used in index calculations have a mean weight of 168kgs, with 25th and 75th percentiles of 132kg and 192kg respectively.

Figure 10 illustrates the annual weight frequency distributions, with the most recent year highlighted. Considerable interannual variation is apparent, with a modal progression evident from 2002 to 2006 and again between 2007 and 2010. The 2011 distribution is similar to 2003. Fishermen targeting different sized fish according to market demands and temporal shifts in fishing effort confound the interpretation, however. Figure 11 shows the monthly distribution of weight anomalies, where the mean of the annual mean weights was used as the base2. In general, the recent condition of the fish seems somewhat above the long term means.

The most reliable size metric for the Gulf fishery, and the one for which we consistently have data, is weight. There is however occasional problems with it that relate to situations where the dockside monitors were not able to obtain a round weight. These dressed weights would then be scaled to round using a standard factor of 1.25 regardless of how the fish was dressed. Additional data collection irregularities are also possible prior to the introduction of the dockside monitoring program in 1998. Figure 12 shows the trend in the weight frequency from 2000 to 2011. The modal weights of bluefin for years 2000, 2001, 2009, 2010 and 2011 are all above 300 kg and are a minimum of 40 to 50 kg heavier than fish in 2002 to 2008. The trend in the bluefin tuna weight anomalies time series (Figure 13) represents the observed round weight minus the standard weight. The standard weight was calculated using the Parrack and Phares (1979) length-weight relationship for bluefin in the western Atlantic captured at any time. This relationship was developed using 3200 fish spanning the length range of 20 to 372 cm whereas the Gulf fish were between 50 and 400 cm long with the majority between 250 and 300 cm. The anomalies reflect the change in the condition of the fish within each year and across all years within each month. The monthly series show that fish have been heavier relative to the standard in the last three years in all months.

1.6. Changes in the fishery that might affect catch rates.

There have been no changes to the fishery structure following the institution of mandatory log submission in 1996 and the move from a competitive fishery to an Individual Transferrable Quota (ITQ) system in 2004. Additional variation in market demand for a given size class has had some effect on the SWNS fishery catch size distribution, as noted in previous industry consultations.

2 Unlike the sGSL, it was not possible to match the observed weights to an observed length. 338 The P.E.I. fleet has been fluctuating between 225 to 250 vessels since 1999 while the Nova Scotia fleet had between 50 to 100 vessels over the same time span. The fishing gear and method has not experienced any innovations that would alter the catch rates. The fishermen are sensitive to the market and will try to find the fish that will provide the largest return, particularly for the Nova Scotia fleet. This may lower catch rates as fishermen spend more time selecting an appropriate fish. The duration and timing of the sGSL fishing season has been in a state of flux since 2000. Over much of this period, fleets had a fixed quota but individuals within a fleet competed for their catch. The small quotas would not allow for extended seasons so a burst of fishing activity would occur at 2 or 3 pre-arranged times during the year. Each of these windows of opportunity was short by design, to allow managers to ensure that the TAC would not be exceeded. Under this system, the shortest season on record occurred in September/October of 2010 lasting a total of 6 days, 3 for P.E.I boats and 3 for Nova Scotia boats. In the year that followed, fishermen were given a quota and the season expanded to 86 days. With these new management practices, we could expect lower catch rates.

1.7. Industry reports from fishing industry consultations.

Gulf of St. Lawrence

A consultation with the GSL fishing industry was held in Charlottetown, Prince Edward Island on Aug. 7, 2012. This meeting was well attended, with 29 fishermen, processors and government officials participating. DFO Science presented recent information extracted from fishermen’s logbooks, and the most recent catch rate information. In general, the audience agreed with the main conclusions: the fishery distribution was typical of previous years, the size composition of the catch was broader, the body condition of the fish was poorer than historic values, and that recent catch rates were the highest observed since 1980, the start of the time series. Many participants noted the very short opening in 2010 (two days for the PEI fleet) during which the quota was caught. Fishermen queried how catch rates could be used as an index of abundance when management and fishing decisions vary from year to year.

Fishermen noted that small (90-135kg round weight) fish were particularly abundant in 2011 and 2012. They referred to seeing “acres” of jumping tuna corresponding to this size class – which probably consists of the 2003 year-class.

Fishermen expressed concern over the condition of fish and noted that regardless of month, the condition of fish seemed lower than expectations. One fisherman with a long experience noted that tuna “are acting stupid” and are comparatively easy to catch.

Southwest Nova Scotia

An industry consultation was held August 14, in Wedgeport, Nova Scotia. As much of the fleet was at sea on that particular day, the meeting was less well attended than the one described above.

Fishermen commented that the modestly increasing nominal catch rate series shown by DFO understates their success on the water. The southwest Nova Scotia fleet has operated on the basis of Individual Transferrable Quotas since 2003, and the decision on fishing is contingent on market, availability of other tuna species, and the success of the PEI fishery. Fishermen stressed that bluefin tuna is just one of the species they target (this contrasts with the PEI fishery, which is based exclusively on bluefin tuna).

Fishermen also noted that the abundance of bluefin tuna is causing problems for other fisheries, such as groundfish bottom longline, herring purse seine and gillnet fisheries. Similar to the southern Gulf of St. Lawrence, fishermen noted seeing large schools of jumping tuna, in the size group expected for the 2003 year- class. In contrast with the southern Gulf of St. Lawrence, fishermen reported no problem with fish condition.

More information on industry reports from around the Canadian Atlantic zone can be found in Appendix One.

2. Methods

2.1. Data Exclusions and Rationale

The SWNS dataset is limited to catches made using tended line, rod and reel, and harpoon; fish landed in the St. Margaret’s Bay trapnet fishery are excluded as both the initial catch location of the fish and the associated effort 339 of the trapnet fishery (e.g. hours ranched, effort required to catch and bring the fish into the trap) are not known. Catches landed in Nova Scotia by the Newfoundland fleet have been actively excluded from the index dataset, as these vessels do not behave in the manner consistent with the other fleets. Geographically, index data has been limited to catches inside the Canadian 4X, 5Y and 5Z NAFO areas (Figure 14), as these historically contained the majority of the fishing activity. The season is limited to August, September and October, excluding occasional May, June and November catches.

All valid Gulf trips must fall within ‘Area 2’, which conforms to a box bounded by 68°W longitude to 63°W longitude and 40°N latitude to 45°N latitude. If a trip could not be identified as coming from within this box either by NAFO unit area or geographical coordinates, it was excluded. Additionally only data from the P.E.I. and Nova Scotia fleets fishing from August to October using tended line and rod and reel were retained.

Although significant effort has been put into improving the quality of the historic data, additional issues have surfaced and need to be investigated in future assessments (see Research Recommendations). The Gulf data are very detailed but tend to lack details about the fishing such as geographical coordinates and bait for trips where nothing was caught. This has limited the standardization to very basic factors.

2.2. Management Regulations

There have been two major management shifts in the Canadian bluefin tuna fishery: the introduction of mandatory log submissions in the mid-1990s and the switch to an Individual Transferable Quota (ITQ) fishery in the mid-2000s. Starting in 1996, mandatory log submissions provided detailed information on all trips targeting bluefin tuna in Canadian waters, including trips with no catch; prior to 1996, the trip information was submitted on a voluntary basis. The second management change occurred in 2004, when the fishery moved away from a competitive structure and towards a management approach which assigned specific shares of the annual quota to individual fleet sectors (ITQ).

With possible absence of effort for unsuccessful trips prior to 1996, indices calculated during that period are expected to over-estimate the abundance. Aside from the change in reporting structure, there is no reason to believe that fishing behaviour and effort associated with the catch differed drastically between 1988 to 1995 and 1996 to 2003.

The introduction of a new management approach in 2004 may have caused legitimate changes to the fishing activity in this region. In the SWNS fishery, the mean trip length doubled in the years immediately following the change, while the proportion of unsuccessful trips landed by the Scotia Fundy fleet decreased dramatically (Figure 15). Neither of these changes is currently reflected in the nominal CPUE (Figure 16) or in the current analysis, though concerns were brought up at the industry consultation (Section 1.6). No method to address changes in management was used in the 2011 SWNS CPUE update, but it is strongly advised to incorporate a management variable into the future assessment (see Research Recommendations).

For a description of management practices from 2007 to 2009 in the Gulf, see Hanke and Neilson (2010). In 2010, the season was short for both the PEI and NS fleets (3 days) and occurred in late September, early October. In the following year, both fleets adopted an individual quota system which resulted in a self governed season that started in July and ended in October. The implementation of an individual quota in the Gulf will reduce the catch rates as fishermen attempt to maximize their economic yield. They will be more selective when fishing resulting in more effort hours. Due to the large variation in the number of days fished per month across the whole time series but more notably in the recent past, a factor reflecting the number of days fished per month (season length) and homeport was incorporated in the model as an explanatory variable (Figure 17).

2.3. Dataset used in the Analysis

A summary of the data for each of the explanatory variables is given in Table 1 for SWNS and Table 2 for the sGSL. Catch rates and the probability of catch are given in Table 3a and Table 5. Table 3b provides estimates using the 2010 model.

The spatial distribution of the southwestern Nova Scotia fishery in recent years (2010-2011) has been generally consistent with that of previous years (2002 – 2009), with catches localized in the Hell Hole and Grand Manan Island (Fundy Bay) (Figure 14). Fishing along the northern edge of Georges Bank occurred in 2010, but was absent in 2011.

340 The fishery in the Southern Gulf of St. Lawrence spans the north shore of P.E.I. and St. Georges Bay located between P.E.I. and Nova Scotia. Increasingly the trend has been for the fish to occur throughout this domain whereas in the past the fishing was focused towards the eastern end of P.E.I.

2.3.1. The effort catch variable

In both the sGSL and SWNS fisheries, hours fished have been used as the measure of effort (Paul et al. 2010). Alternative measures include trip length in days, number of vessels, number of trips and length of season. Each of the alternatives is generally linearly related to hours fished and their usefulness depends on the level of aggregation of the data.

The catch variable for both fisheries was the count of bluefin tuna caught. In the sGSL this count and the hours was aggregated by day, fleet (P.E.I and N.S.), month (August, September, and October) and gear type (rod and reel and tended line). The count and hours fished for the SWNS data was aggregated by trip.

2.4. Model Standardization

Hurdle models (i.e. delta models) were fit to both the SWNS and sGSL bluefin tuna count data. The models had two components: a binomial model to model the probability that a zero value is observed and a truncated Poisson model for the counts. The pscl package (Zeileis et al. 2008) allowed maximum likelihood estimates for the truncated count component and the hurdle zero component to be maximized separately. Prior to model simplification, the Poisson counts were tested for overdispersion against a complementary truncated negative binomial model for the counts using a likelihood ratio test. The model selection in both cases involved starting with as full a model as the data would allow and then dropping the least significant interactions and main effects until none could be rejected using a likelihood ratio test (Zeileis and Hothorn 2002). Factors and interaction terms were retained if the p-value for the Chi-square statistic was between 0.5 and 0. No year effects were included in the models due to the unbalanced nature of the data across the year*factor categories and its missingness for some year*factor combinations.

The year effect was extracted from the model by averaging the predictions for all combinations of levels of the categorical variables while holding the continuous variable hours fished at the median value of 48 h for the sGSL and mean value of 24h for SWNS. Standard errors for the year effects were estimated using a bootstrap procedure in which the original records were sampled with replacement to create 500 datasets of similar size. These datasets were used to recalculate the year effects using the same component models (Vignaux, 1994).

For the SWNS and sGSL data the likelihood ratio test comparing the Poisson count model to the negative binomial alternative produced a Chi-square of 182.73 and 671.24 (p-values= 0), respectively, supporting an hypothesis of overdispersion. Thus a truncated negative binomial distribution was specified for the counts and a binomial distribution for the zeros for both datasets.

The fully prescribed component models (zero and count) for SWNS were identical:

ƒ(Count,Zero) ~ year + month + home_mgt_area + gear_code + log(hours) + log(hours)2 + month:(gear_code + home_mgt_area) + log(hours):(month + home_mgt_area + gear_code)

The SWNS data were fit with logistic links for the count and zero models and no further reductions of terms was possible.

The fully prescribed component models (zero and count) for sGSL were identical:

2 ƒ(Count,Zero) ~ year + (month + home_mgt_areat + gear_code + season_duration + log10(hours+.5) )

The sGSL data were also fit with logistic links for the count and zero models. The component models were simplified to:

2 2 ƒ(Count) ~ year + log10(hours+.5) + month + (home_mgt_area + gear_code + log10(hours+.5) ) - homeport: log10(hours+.5)

2 2 ƒ(Zero) ~ year + home_mgt_area + month + log10(hours+.5) + (gear2 + + log10(hours+.5) )

341 A summary of the model selection process is given in Table 6. Summary of the final models are given in Table 7 for SWNS and Table 8 for sGSL.

3. Model Diagnostics

Residuals do not show any patterns and the variances are fairly homogeneous across all explanatory variables and the fitted values (Figure 18, Figure 19). The residuals for the SWNS model are somewhat heavy tailed but the departure from normality is not severe (Figure 20). The normal plot for the residuals from the sGSL model also has heavier tails than expected under normality but the distribution is symmetric around zero (Figure 20). The heavier tails will inflate the standard errors and lead to more conservative tests for the fixed effects.

4. Model Results

The index of abundance for the SWNS fishery, shown in its nominal and standardized forms (Figure 21, top), has been increasing since a low in 2000. In the 4 years from 2000 to 2003, both the standardized and nominal trend shows a rate of change in catch that is roughly 4 times that observed or estimated from 2004 to 2011. The change point corresponds to the year when the fishery introduced individual quotas. Accounting for the effect of this change in management practice was not possible. The methods from the 2010 assessment (Paul et al. 2010) were applied to the SWNS data and the outcome (orange line) is shown relative to the estimate from the current model (green line). The 2010 model tracks the nominal series more closely while the 2012 model shows a departure from the nominal series prior to 1992 and after 2002. By not modeling the relationship between the catch and effort and introducing the effort as an offset, the 2012 model yields an index similar to the 2010 model.

The sGSL indices (Figure 21, bottom) have shown an increasing trend since 1996. The observed and estimated abundance in 2010 is a clear outlier in the series and the associated confidence interval is about 5 times larger than the next largest interval. The uncertainty associated with the estimate can be attributed to a small number of observations for this year and that they occurred over a one week period. From about 2004 to 2010 the fishing seasons became quite fragmented (i.e. multiple short duration openings) and focused (i.e. occurred in parts of some months) (Table 2) and this is reflected by more variability in the series with the most aberrant being 2010. In 2011 the industry introduced self-regulatory (ITQ-like) measures that caused the fishing to once again span the entire “fishing season” as it did in 2000.

5. Research Recommendations

Given the changes in the management of the SWNS fishery and the impact on the abundance index, consideration should be given in the future to splitting the series or attempting to estimate the management effect. It will also be important to revisit the catch data from 1988 to 1996 to determine the amount of zero-catch trips that should be present in the data. Figure 15 shows that during the period when the reporting of zero catch was not mandatory, most trips were successful. The uncharacteristically high number of zero catch trips in 1993 deserves an in depth examination.

The last decade has shown a less pronounced relationship between the catch of bluefin tuna in SWNS and the effort hours (Figure 22). A possible explanation is that a portion of the trips target other tunas and the hours associated with this effort is inappropriately attributed to the bluefin catch. Figure 15 shows the portion of all bluefin trips that also caught other tunas (bigeye, yellowfin, albacore) ranges from 10-40%. The fraction of each trip that is devoted to each species is not exactly known. In some cases, the vessel spends several days only targeting other tunas, leaving bluefin for last. As there is no specific target variable recorded in the logbooks, the entire length of the fishing trip is currently used in the bluefin CPUE calculation. This concern was raised by the industry during the August 2012 consultation and consequently should be addressed by developing a method to separate the bluefin from other tuna effort.

The current methodology for both the sGSL and SWNS limits the data to months 8-10. This has been the practice in previous assessments perhaps because few fish were caught at other times. In recent years however, substantial fishing has occurred in July and November. Thus, a reanalysis using a larger time window seems warranted.

342 The sGSL series was also affected by management changes. The small overall fleet quota and lack of individual quotas in recent years forced the fishery into short duration punctuated harvests. It should be determined if there is a way to account for this effect. Also in more recent years, the fishery has given better detail on catch location. The spatial patterns in the catch should be incorporated in the catch analysis.

References

Achim Zeileis, Christian Kleiber, Simon Jackman 2008,. Regression Models for Count Data in R. Journal of Statistical Software 27(8). URL http://www.jstatsoft.org/v27/i08/.

Achim Zeileis, Torsten Hothorn (2002). Diagnostic Checking in Regression Relationships. R News 2(3), 7-10. URL http://CRAN.R-project.org/doc/Rnews/

Bigelow, H. B. and Schroeder, W.C. 1953, Fishes of the Gulf of Maine. U.S. Fish and Wildlife Service Fishery Bulletin Vol. 53.

Chase, B. 2002, Difference in diet of Atlantic bluefin tuna (Thunnus thynnus) at five seasonal feeding grounds on the New England continental shelf. Fishery Bulletin 100:168-180.

DFO, 2011, 2011 Assessment of 4VWX herring. DFO Can. Sci. Advis. Sec. Science Advisory Report 2011/046.

DFO, 2012a, Assessment of Atlantic herring in the southern Gulf of St Lawrence (NAFO div. 4T). DFO Can. Sci. Advis. Sec. Science Advisory Report 2012/014.

DFO, 2012b, Assessment of the Atlantic mackerel stock for the northwest Atlantic (subareas 3 and 4) in 2011. DFO Can. Sci. Advis. Sec. Science Advisory Report 2012/031.

DFO, 2012c, Canada’s State of the Oceans Report, 2012: A report by the Fisheries and Oceans Canada Centre of Expertise on the State of the Ocean. DFO/2012-1818.

Dragovich, A. 1970, The food of bluefin tuna (Thunnus thynnus) in the western north Atlantic ocean. Transactions of the American Fisheries Society. 99(4):726-731.

Dufour, R., Benoît, H., Castonguay, M., Chassé, J., Devine, L., Galbraith, P., Harvey, M., Larouche, P., Lessard, S., Petrie, B., Savard, L., Savenkoff, C., St-Amand, L. and Starr, M. 2010, Ecosystem status and trends report: estuary and Gulf of St. Lawrence ecozone. DFO Can. Sci. Advis. Sec. Res. Doc. 2010/030.

Galbraith, P.S., Pettipas, R.G., Chassé, J., Gilbert, D., Larouche, P., Pettigrew, B., Gosselin, A., Devine, L. and Lafleur, C. 2009, Physical Oceanographic Conditions in the Gulf of St. Lawrence in 2008. DFO Can. Sci. Advis. Sec. Res. Doc. 2009/014

Hanke, A.R. and Neilson, J. D. 2010, Catch Rate Standardization for the Canadian Southern Gulf Of St. Lawrence Bluefin Tuna Fishery, 1981 to 2009. Collect. Vol. Sci. Pap. ICCAT, 66(2): 762-774 (2011).

Paul, S. D., Hanke, A.R., Vanderlaan, A.S.M., Busawon, D. and Neilson, J. D. 2010, Indices of Stock Status from the 2009 Canadian Bluefin Tuna Fishery. Collect. Vol. Sci. Pap. ICCAT, 66(3): 1170-1203 (2011)

Scott, W.B. and Scott, M. G. 1988, Atlantic fishes of Canada. Can Bull. Fish. Aquat. Sci. vol 219.

Vignaux, M. 1994, Catch per unit effort (CPUE) analysis of west coast South Island and Cook Strait spawning hoki fisheries, 1987-93. NZ Fisheries Association Research Document No. 94/11.

Worcester, T., and Parker, M. 2010, Ecosystem Status and Trends Report for the Gulf of Maine and Scotian Shelf. DFO Can. Sci. Advis. Sec. Res. Doc. 2010/070.

343 Table 1. Reduced dataset description for the Southwest Nova Scotia bluefin tuna fishery. Home Management Area Gear Month Area Tended Year SF GNB GNS PEI PQ Harp R&R Line Aug Sep Oct 5 7 1988 38 0 0 2 0 0 0 40 10 30 0 40 0 1989 111 18 33 31 20 0 0 213 136 64 13 213 0 1990 94 20 17 21 14 0 0 166 63 82 21 166 0 1991 118 10 25 51 14 0 0 218 132 51 35 218 0 1992 130 9 30 48 14 11 0 220 73 134 24 220 11 1993 324 71 116 47 93 162 0 489 203 346 102 489 162 1994 88 41 48 51 54 44 0 238 146 135 1 238 44 1995 159 44 40 50 37 65 0 265 191 122 17 265 65 1996 178 62 44 47 42 105 39 229 265 79 29 268 105 1997 157 71 34 55 48 94 106 165 256 85 24 271 94 1998 232 42 20 34 22 112 109 129 222 110 18 238 112 1999 151 22 25 45 23 62 132 72 201 57 8 204 62 2000 136 36 18 42 48 31 173 76 154 63 63 249 31 2001 213 38 10 59 39 31 230 98 143 144 72 328 31 2002 162 115 116 42 48 27 417 39 200 280 3 456 27 2003 86 28 14 25 34 13 151 23 123 64 0 174 13 2004 105 1 1 29 12 22 68 58 80 54 14 126 22 2005 88 28 0 37 2 6 135 14 67 78 10 149 6 2006 93 6 6 10 25 7 119 14 37 92 11 133 7 2007 68 7 13 0 5 13 71 9 34 39 20 80 13 2008 89 7 12 0 0 11 87 10 25 60 23 97 11 2009 77 10 3 0 0 5 69 16 18 59 13 85 5 2010 85 14 12 0 0 5 92 14 29 68 14 106 5 2011 93 27 8 0 0 11 104 13 29 67 32 117 11

344

Table 2. Number of observations by factor for the Gulf of St. Lawrence bluefin tuna fishery. Observations are the trip level data aggregated by day within the year, homeport, gear and month factors. Homeport Gear Month Days Fished Category (days) Year P.E.I. Nova Scotia RR TL Aug Sep Oct (0,7] (7,14] (14,21] (21,28] (28,31] 1981 87 0 0 87 31 30 26 0 0 0 26 61 1982 57 0 0 57 31 25 1 1 0 0 25 31 1983 126 0 45 81 26 48 52 0 0 26 0 100 1984 90 57 36 111 28 53 66 0 0 7 34 106 1985 88 36 0 124 32 46 46 2 0 34 28 60 1986 113 20 30 103 48 41 44 6 14 0 30 83 1987 71 2 0 73 27 30 16 2 14 0 27 30 1988 73 19 2 90 27 37 28 10 9 19 24 30 1989 86 18 8 96 35 32 37 6 12 0 25 61 1990 118 13 35 96 50 50 31 1 12 0 68 50 1991 92 33 25 100 37 31 57 4 0 29 28 64 1992 109 43 51 101 26 78 48 0 17 52 0 83 1993 160 79 114 125 49 90 100 5 0 0 118 116 1994 134 105 105 134 89 107 43 0 0 45 78 116 1995 167 162 162 167 106 116 107 0 0 0 50 279 1996 171 163 166 168 111 119 104 0 0 0 100 234 1997 179 148 179 148 90 119 118 0 0 0 28 299 1998 157 121 160 118 92 118 68 0 0 0 100 178 1999 126 100 135 91 88 107 31 9 22 0 27 168 2000 148 144 170 122 104 101 87 0 0 0 130 162 2001 134 110 142 102 106 81 57 0 0 57 126 61 2002 107 75 123 59 107 70 5 5 0 0 70 107 2003 74 51 77 48 102 23 0 10 13 0 0 102 2004 40 48 68 20 57 31 0 6 0 59 23 0 2005 64 55 80 39 81 37 1 1 12 25 81 0 2006 81 54 97 38 76 47 12 12 0 39 0 84 2007 25 23 33 15 16 9 23 9 16 23 0 0 2008 52 44 67 29 27 22 47 8 34 54 0 0 2009 23 22 33 12 14 9 22 22 23 0 0 0 2010 5 3 6 2 0 3 5 8 0 0 0 0 2011 90 63 138 15 44 57 52 0 13 25 84 31

345

Table 3a. Dataset description, nominal and standardized CPUE series from the current model for the Southwest Nova Scotia bluefin tuna fishery (rod and reel, tended line and harpoon), based on catch and effort data from commercial logbooks for August through October (1988‐2011). Number of Number of Trips with Trips with no Number Hours Nominal Standardized Std. Std. Year BFT catch catch of Fish Fished CPUE CPUE low upp 1988 40 0 230 845 27.22 4.29 3.8 4.81 1989 209 4 1,114 3,152 35.34 4.41 4.03 4.81 1990 163 3 861 2,666 32.3 4.36 3.94 4.83 1991 182 36 714 3,452 20.69 2.62 2.29 2.97 1992 228 3 853 4,754 17.94 3.18 2.9 3.49 1993 391 260 1,039 11,244 9.24 1.7 1.52 1.88 1994 281 1 867 4,992 17.37 2.81 2.62 3.06 1995 330 0 1,088 7,534 14.44 2.84 2.6 3.15 1996 256 117 675 10,315 6.54 1.36 1.2 1.53 1997 203 162 445 9,606 4.63 0.92 0.77 1.09 1998 244 106 845 8,931 9.46 1.91 1.68 2.12 1999 207 59 894 5,653 15.81 2.79 2.48 3.17 2000 159 121 347 7,208 4.81 0.94 0.79 1.07 2001 266 93 1,027 9,162 11.21 2.31 2.03 2.61 2002 247 236 1,105 9,057 12.2 2.31 2.01 2.66 2003 179 8 1,120 5,945 18.73 4.86 4.44 5.32 2004 128 20 550 6,209 8.86 2.25 1.83 2.72 2005 124 31 590 5,796 10.18 2.56 2.1 3.04 2006 138 2 720 5,919 12.16 3.98 3.52 4.46 2007 91 2 347 3,632 9.55 3.19 2.8 3.68 2008 108 0 561 3,917 14.32 4.34 3.77 4.97 2009 84 6 365 2,468 14.79 3.4 2.89 3.91 2010 99 12 359 2,830 12.69 2.9 2.48 3.38 2011 105 23 383 2,769 13.83 3.02 2.58 3.52

346 Table 4b. Dataset description, nominal and standardized CPUE series from the 2010 model for the Southwest Nova Scotia bluefin tuna fishery (rod and reel, tended line and harpoon), based on catch and effort data from commercial logbooks for August through October (1988‐2011). Number of Number of Trips with Trips with no Number Hours Nominal Standardized Std. Std. Year BFT catch catch of Fish Fished CPUE CPUE low upp. 1988 40 0 230 845 27.22 1.62 0.76 3.45 1989 209 4 1,114 3,152 35.34 2.71 1.27 5.75 1990 163 3 861 2,666 32.3 1.92 0.90 4.08 1991 182 36 714 3,452 20.69 1.64 0.88 3.07 1992 228 3 853 4,754 17.94 1.14 0.63 2.06 1993 391 260 1,039 11,244 9.24 0.81 0.44 1.48 1994 281 1 867 4,992 17.37 0.98 0.54 1.78 1995 330 0 1,088 7,534 14.44 0.78 0.45 1.34 1996 256 117 675 10,315 6.54 0.48 0.28 0.82 1997 203 162 445 9,606 4.63 0.51 0.30 0.88 1998 244 106 845 8,931 9.46 0.65 0.37 1.13 1999 207 59 894 5,653 15.81 1.09 0.62 1.92 2000 159 121 347 7,208 4.81 0.38 0.22 0.65 2001 266 93 1,027 9,162 11.21 0.74 0.42 1.30 2002 247 236 1,105 9,057 12.2 0.92 0.52 1.62 2003 179 8 1,120 5,945 18.73 0.84 0.48 1.47 2004 128 20 550 6,209 8.86 0.51 0.28 0.90 2005 124 31 590 5,796 10.18 0.83 0.46 1.47 2006 138 2 720 5,919 12.16 0.67 0.38 1.19 2007 91 2 347 3,632 9.55 0.60 0.34 1.06 2008 108 0 561 3,917 14.32 0.87 0.48 1.58 2009 84 6 365 2,468 14.79 1.11 0.62 1.99 2010 99 12 359 2,830 12.69 1.05 0.59 1.88 2011 105 23 383 2,769 13.83 1.18 0.50 2.78

347

Table 5. Dataset description, nominal and standardized CPUE series for the Southern Gulf of St. Lawrence bluefin tuna fishery (tended line and rod and reel), based on catch and effort data from commercial logbooks for August through October (1981‐2011). Days with Catch Totals Catch 95% CI Year Fail Succeed p Fish Hours Nominal Standard L U 1981 38 49 0.56 363 12,778 2.84 1.30 0.90 1.79 1982 20 37 0.65 343 23,405 1.47 0.70 0.42 1.12 1983 34 92 0.73 566 29,167 1.94 1.37 0.89 1.73 1984 90 57 0.39 177 12,684 1.40 0.81 0.61 1.07 1985 85 39 0.31 102 21,256 0.48 0.25 0.16 0.36 1986 108 25 0.19 35 8,929 0.39 0.24 0.15 0.36 1987 65 8 0.11 9 1,930 0.47 0.28 0.12 0.46 1988 75 17 0.18 26 3,447 0.75 0.48 0.27 0.80 1989 83 21 0.20 25 3,234 0.77 0.50 0.27 0.88 1990 115 16 0.12 24 7,634 0.31 0.19 0.11 0.30 1991 98 27 0.22 35 3,177 1.10 0.67 0.42 1.07 1992 100 52 0.34 110 5,648 1.95 1.09 0.80 1.56 1993 161 78 0.33 181 10,252 1.77 0.80 0.61 1.05 1994 181 58 0.24 120 23,399 0.51 0.22 0.15 0.30 1995 181 148 0.45 369 28,451 1.30 0.65 0.51 0.81 1996 231 103 0.31 229 70,762 0.32 0.13 0.08 0.19 1997 218 109 0.33 221 55,975 0.39 0.15 0.10 0.21 1998 179 99 0.36 247 36,276 0.68 0.26 0.19 0.36 1999 131 95 0.42 387 35,367 1.09 0.40 0.30 0.53 2000 174 118 0.40 553 62,214 0.89 0.32 0.22 0.42 2001 141 103 0.42 377 51,550 0.73 0.25 0.17 0.34 2002 96 86 0.47 549 53,201 1.03 0.36 0.25 0.49 2003 50 75 0.60 460 42,754 1.07 0.54 0.40 0.71 2004 42 46 0.52 613 32,021 1.91 0.71 0.46 1.04 2005 44 75 0.63 700 45,090 1.55 1.12 0.89 1.41 2006 63 72 0.53 859 55,297 1.55 0.61 0.43 0.83 2007 23 25 0.52 452 16,172 2.77 0.79 0.44 1.39 2008 57 39 0.41 515 22,372 2.30 0.75 0.51 1.01 2009 20 25 0.56 630 15,169 4.13 2.43 1.31 3.80 2010 1 7 0.88 533 3,567 14.94 7.63 1.13 14.98 2011 43 110 0.72 503 5,204 9.67 2.51 2.06 3.09

348 Table 6. Results of the sGSL model selection. The starting log likelihood was ‐5416.3 and the final was ‐ 5474.6. At step 7 the two‐way interactions with season_duration though significant were dropped because of the improvement in the standard errors.

Component Step Dropped term model df LogLik Chisq Pr(>Chisq)

1 month:log10(hours+0.5) both ‐4 2.5 5.1 0.28 2 month:gear_code both ‐4 2.4 4.8 0.31 3 Gear_code:home_mgt_area zero ‐1 0.5 1 0.31 4 home_mgt_area:log(hours+0.5) count ‐1 0.4 0.8 0.38 5 month:home_mgt_area count ‐2 1.9 3.7 0.16 6 season_duration:home_mgt_area count ‐4 3.2 6.4 0.17 7 all remaining 2‐way with season both ‐37 66.3 132.8 0 8 season_duration count ‐4 2.9 5.7 0.22 9 home_mgt_area:log(hours+0.5) zero ‐1 0.3 0.6 0.46 10 home_mgt_area:month zero ‐2 2.3 4.7 0.1 11 season_duration zero ‐4 1.2 2.3 0.67 Added term

12 log10(hours+0.5)2 both 2 ‐23.1 46.24 0

349 Table 7. A summary of the final SWNS model. Pearson residuals: Min 1Q Median 3Q Max ‐1.9931 ‐0.6827 ‐0.2215 0.5527 9.4966

Count model coefficients (truncated negbin with log link):

Estimate Std. Error z value Pr(>|z|) (Intercept) ‐0.513033 0.252482 ‐2.032 0.042158 * year1989 0.063004 0.09424 0.669 0.503784 year1990 0.041616 0.095565 0.435 0.663224 year1991 ‐0.318747 0.098139 ‐3.248 0.001163 ** year1992 ‐0.330941 0.095715 ‐3.458 0.000545 *** year1993 ‐0.700633 0.095167 ‐7.362 1.81e‐13 *** year1994 ‐0.503738 0.096629 ‐5.213 1.86e‐07 *** year1995 ‐0.491047 0.094053 ‐5.221 1.78e‐07 *** year1996 ‐0.849758 0.100967 ‐8.416 < 2e‐16 *** year1997 ‐1.07794 0.108842 ‐9.904 < 2e‐16 *** year1998 ‐0.479598 0.097055 ‐4.942 7.75e‐07 *** year1999 ‐0.153419 0.097107 ‐1.58 0.114132 year2000 ‐1.085678 0.115152 ‐9.428 < 2e‐16 *** year2001 ‐0.322938 0.095872 ‐3.368 0.000756 *** year2002 ‐0.096975 0.097028 ‐0.999 0.317572 year2003 0.191149 0.097903 1.952 0.050887 . year2004 ‐0.281933 0.103057 ‐2.736 0.006225 ** year2005 ‐0.155774 0.104548 ‐1.49 0.136229 year2006 ‐0.058158 0.102778 ‐0.566 0.571492 year2007 ‐0.3165 0.113508 ‐2.788 0.005298 ** year2008 0.009645 0.105836 0.091 0.927391 year2009 ‐0.185205 0.1107 ‐1.673 0.094321 . year2010 ‐0.325713 0.111788 ‐2.914 0.003572 ** year2011 ‐0.213815 0.111639 ‐1.915 0.055463 . month2Oct ‐0.63143 0.318679 ‐1.981 0.047546 * month2Sept 0.076971 0.129531 0.594 0.552358 home_mgt_areaGNS ‐0.085334 0.222905 ‐0.383 0.701848 home_mgt_areaPEI 0.39382 0.200136 1.968 0.049096 * home_mgt_areaPQ 0.404857 0.211776 1.912 0.055912 . home_mgt_areaSF 0.687936 0.168523 4.082 4.46e‐05 *** gear_codeRR ‐0.042861 0.17893 ‐0.24 0.810689 gear_codeTL 0.736249 0.160257 4.594 4.34e‐06 *** loghours 0.857289 0.100424 8.537 < 2e‐16 *** I(loghours^2) ‐0.07623 0.013887 ‐5.489 4.04e‐08 *** month2Oct:gear_codeRR ‐0.468208 0.203203 ‐2.304 0.021215 * month2Sept:gear_codeRR ‐0.003645 0.081627 ‐0.045 0.964387 month2Oct:gear_codeTL ‐0.442688 0.19509 ‐2.269 0.023260 * month2Sept:gear_codeTL ‐0.117669 0.077168 ‐1.525 0.127296 month2Oct:home_mgt_areaGNS 0.622191 0.312776 1.989 0.046673 * month2Sept:home_mgt_areaGNS 0.077686 0.108885 0.713 0.475556 month2Oct:home_mgt_areaPEI ‐0.41895 0.624942 ‐0.67 0.502614 month2Sept:home_mgt_areaPEI ‐0.284118 0.10572 ‐2.687 0.007200 ** month2Oct:home_mgt_areaPQ 0.240902 0.363626 0.663 0.50765 month2Sept:home_mgt_areaPQ 0.013276 0.098449 0.135 0.892727 month2Oct:home_mgt_areaSF 0.826182 0.247653 3.336 0.000850 *** month2Sept:home_mgt_areaSF 0.055051 0.079415 0.693 0.48818 month2Oct:loghours 0.040345 0.054815 0.736 0.461725 month2Sept:loghours ‐0.030087 0.029919 ‐1.006 0.314602

350 home_mgt_areaGNS:loghours ‐0.043449 0.071275 ‐0.61 0.542129 home_mgt_areaPEI:loghours ‐0.13631 0.062009 ‐2.198 0.027933 * home_mgt_areaPQ:loghours ‐0.133307 0.064858 ‐2.055 0.039843 * home_mgt_areaSF:loghours ‐0.180687 0.052251 ‐3.458 0.000544 *** gear_codeRR:loghours 0.057845 0.053208 1.087 0.276974 gear_codeTL:loghours ‐0.129019 0.049218 ‐2.621 0.008757 ** Log(theta) 2.343411 0.098002 23.912 < 2e‐16 ***

Zero hurdle model coefficients (binomial with logit link):

Estimate Std. Error z value Pr(>|z|) (Intercept) 17.22203 1636.53636 0.011 0.991604 year1989 14.23062 1636.53629 ‐0.009 0.993062 year1990 14.07096 1636.53631 ‐0.009 0.99314 year1991 16.55721 1636.53622 ‐0.01 0.991928 year1992 13.46384 1636.53631 ‐0.008 0.993436 year1993 17.23031 1636.53621 ‐0.011 0.9916 year1994 12.24863 1636.53652 ‐0.007 0.994028 year1995 0.41498 1725.01131 2.41E‐04 0.999808 year1996 17.60917 1636.53622 ‐0.011 0.991415 year1997 18.27534 1636.53622 ‐0.011 0.99109 year1998 17.39518 1636.53622 ‐0.011 0.991519 year1999 16.96161 1636.53622 ‐0.01 0.991731 year2000 18.22463 1636.53622 ‐0.011 0.991115 year2001 17.14468 1636.53622 ‐0.01 0.991641 year2002 17.77731 1636.53622 ‐0.011 0.991333 year2003 15.03755 1636.53626 ‐0.009 0.992669 year2004 17.37934 1636.53624 ‐0.011 0.991527 year2005 17.31237 1636.53623 ‐0.011 0.99156 year2006 14.24027 1636.53638 ‐0.009 0.993057 year2007 14.37591 1636.53638 ‐0.009 0.992991 year2008 0.08794 1881.10326 4.67E‐05 0.999963 year2009 15.28886 1636.53627 ‐0.009 0.992546 year2010 15.77054 1636.53625 ‐0.01 0.992311 year2011 16.24405 1636.53623 ‐0.01 0.99208 month2Oct 0.85107 0.69282 1.228 0.21929 month2Sept ‐0.2298 0.43976 ‐0.523 0.601284 home_mgt_areaGNS ‐1.2245 0.6357 ‐1.926 0.054075 . home_mgt_areaPEI 2.28664 0.77962 2.933 0.003357 ** home_mgt_areaPQ 0.45891 0.74743 0.614 0.539225 home_mgt_areaSF ‐0.18074 0.53984 ‐0.335 0.737776 gear_codeRR 1.74266 0.56232 3.099 0.001941 ** gear_codeTL 3.32516 0.54494 6.102 1.05e‐09 *** loghours ‐1.38595 0.35146 ‐3.943 8.03e‐05 *** I(loghours^2) 0.55593 0.06047 9.193 < 2e‐16 *** month2Oct:gear_codeRR ‐0.40531 0.5088 ‐0.797 0.425681 month2Sept:gear_codeRR ‐0.17197 0.27492 ‐0.626 0.531621 month2Oct:gear_codeTL ‐1.26752 0.49698 ‐2.55 0.010758 * month2Sept:gear_codeTL ‐0.03061 0.25812 ‐0.119 0.905606 month2Oct:home_mgt_areaGNS 0.02945 0.5554 0.053 0.957716 month2Sept:home_mgt_areaGNS ‐0.23287 0.32468 ‐0.717 0.473229 month2Oct:home_mgt_areaPEI 0.12059 0.92794 0.13 0.896605 month2Sept:home_mgt_areaPEI ‐1.37108 0.36185 ‐3.789 0.000151 *** month2Oct:home_mgt_areaPQ ‐0.05635 0.60293 ‐0.093 0.925532 month2Sept:home_mgt_areaPQ 0.03792 0.35929 0.106 0.915941 month2Oct:home_mgt_areaSF 0.29446 0.45218 0.651 0.514911 month2Sept:home_mgt_areaSF 0.68965 0.26947 2.559 0.010489 * 351 month2Oct:loghours ‐0.51141 0.18909 ‐2.705 0.006838 ** month2Sept:loghours ‐0.21327 0.13608 ‐1.567 0.117063 home_mgt_areaGNS:loghours 0.30832 0.22938 1.344 0.1789 home_mgt_areaPEI:loghours ‐0.48093 0.25376 ‐1.895 0.058059 . home_mgt_areaPQ:loghours ‐0.08741 0.24222 ‐0.361 0.718198 home_mgt_areaSF:loghours 0.11984 0.18645 0.643 0.520403 gear_codeRR:loghours ‐0.41617 0.19791 ‐2.103 0.035480 * gear_codeTL:loghours ‐0.92352 0.19593 ‐4.714 2.43e‐06 *** Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Theta: count = 10.4167 Number of iterations in BFGS optimization: 69 Log‐likelihood: ‐1.087e+04 on 109 Df

352 Table 8. A summary of the final sGSL model. Pearson residuals: Min 1Q Med 3Q Max ‐1.52852 ‐0.49357 ‐0.27038 0.03761 11.16537

Count model coefficients (truncated negbin with log link):

Estimate Std. Error z value Pr(>|z|) (Intercept) ‐2.77712 0.45503 ‐6.103 1.04e‐09 *** yr1982 ‐0.60615 0.15687 ‐3.864 0.000112 *** yr1983 ‐0.61597 0.14002 ‐4.399 1.09e‐05 *** yr1984 ‐0.84774 0.15804 ‐5.364 8.14e‐08 *** yr1985 ‐1.76591 0.18534 ‐9.528 < 2e‐16 *** yr1986 ‐2.00191 0.35089 ‐5.705 1.16e‐08 *** yr1987 ‐1.98613 1.02663 ‐1.935 0.053037 . yr1988 ‐0.97167 0.38067 ‐2.552 0.010696 * yr1989 ‐1.33334 0.53533 ‐2.491 0.012749 * yr1990 ‐1.80273 0.39171 ‐4.602 4.18e‐06 *** yr1991 ‐1.00124 0.39702 ‐2.522 0.011672 * yr1992 ‐0.22614 0.2013 ‐1.123 0.261274 yr1993 ‐0.62829 0.16496 ‐3.809 0.000140 *** yr1994 ‐1.88256 0.18514 ‐10.168 < 2e‐16 *** yr1995 ‐0.85626 0.14041 ‐6.098 1.07e‐09 *** yr1996 ‐2.29772 0.15555 ‐14.771 < 2e‐16 *** yr1997 ‐2.38365 0.17136 ‐13.91 < 2e‐16 *** yr1998 ‐1.79501 0.16232 ‐11.058 < 2e‐16 *** yr1999 ‐1.36213 0.15719 ‐8.666 < 2e‐16 *** yr2000 ‐1.57801 0.15578 ‐10.13 < 2e‐16 *** yr2001 ‐1.7274 0.1607 ‐10.75 < 2e‐16 *** yr2002 ‐1.34993 0.15916 ‐8.482 < 2e‐16 *** yr2003 ‐1.29689 0.16534 ‐7.844 4.37e‐15 *** yr2004 ‐0.53632 0.17508 ‐3.063 0.002190 ** yr2005 ‐0.86271 0.16754 ‐5.149 2.61e‐07 *** yr2006 ‐0.87887 0.16408 ‐5.356 8.49e‐08 *** yr2007 ‐0.3373 0.19822 ‐1.702 0.088811 . yr2008 ‐0.52675 0.17978 ‐2.93 0.003390 ** yr2009 0.20372 0.19167 1.063 0.287864 yr2010 1.50681 0.27444 5.491 4.01e‐08 *** yr2011 0.38632 0.15948 2.422 0.015422 * I(hrsfish2.lg^2) ‐0.10044 0.08196 ‐1.226 0.220385 month39 0.27695 0.05179 5.347 8.92e‐08 *** month310 0.31259 0.06698 4.667 3.05e‐06 *** homeport5 ‐0.43084 0.06556 ‐6.571 4.99e‐11 *** gear236 ‐1.77255 0.41562 ‐4.265 2.00e‐05 *** hrsfish2.lg 2.43808 0.38182 6.385 1.71e‐10 *** homeport5:gear236 0.6481 0.26472 2.448 0.014356 * gear236:hrsfish2.lg 0.48102 0.17801 2.702 0.006888 ** Log(theta) 1.25065 0.08517 14.683 < 2e‐16 ***

Zero hurdle model coefficients (binomial with logit link):

Estimate Std. Error z value Pr(>|z|) (Intercept) ‐3.43116 0.450035 ‐7.624 2.46e‐14 *** yr1982 ‐0.52136 0.54135 ‐0.963 0.33551 yr1983 2.079555 0.40552 5.128 2.93e‐07 *** yr1984 0.196367 0.358114 0.548 0.583461 353 yr1985 ‐1.63244 0.387608 ‐4.212 2.54e‐05 *** yr1986 ‐1.287 0.372619 ‐3.454 0.000552 *** yr1987 ‐0.93577 0.473861 ‐1.975 0.048294 * yr1988 ‐0.61601 0.396598 ‐1.553 0.12037 yr1989 ‐0.30217 0.378464 ‐0.798 0.424636 yr1990 ‐1.75398 0.397472 ‐4.413 1.02e‐05 *** yr1991 ‐0.00509 0.359331 ‐0.014 0.988693 yr1992 0.387029 0.338865 1.142 0.253398 yr1993 0.202131 0.322272 0.627 0.530525 yr1994 ‐1.39139 0.335655 ‐4.145 3.39e‐05 *** yr1995 ‐0.11829 0.30713 ‐0.385 0.700125 yr1996 ‐2.45987 0.323803 ‐7.597 3.04e‐14 *** yr1997 ‐1.96437 0.321985 ‐6.101 1.06e‐09 *** yr1998 ‐1.32254 0.324909 ‐4.071 4.69e‐05 *** yr1999 ‐0.65336 0.337033 ‐1.939 0.052555 . yr2000 ‐1.04291 0.337438 ‐3.091 0.001997 ** yr2001 ‐1.07882 0.349869 ‐3.084 0.002046 ** yr2002 ‐0.85171 0.391098 ‐2.178 0.029426 * yr2003 0.082512 0.396792 0.208 0.83527 yr2004 ‐0.13344 0.449059 ‐0.297 0.766347 yr2005 1.088336 0.386165 2.818 0.004828 ** yr2006 ‐0.26345 0.408964 ‐0.644 0.519458 yr2007 0.30661 0.506848 0.605 0.545222 yr2008 ‐0.07672 0.428214 ‐0.179 0.857806 yr2009 0.657043 0.511608 1.284 0.199048 yr2010 2.600299 1.196451 2.173 0.029755 * yr2011 2.284722 0.354867 6.438 1.21e‐10 *** homeport5 ‐0.37368 0.100118 ‐3.732 0.000190 *** month39 0.502356 0.097753 5.139 2.76e‐07 *** month310 0.282178 0.113307 2.49 0.012761 * I(hrsfish2.lg^2) 0.786775 0.110174 7.141 9.25e‐13 *** gear236 0.375262 0.295642 1.269 0.20433 hrsfish2.lg 0.52568 0.387146 1.358 0.174517 gear236:hrsfish2.lg ‐0.53056 0.162569 ‐3.264 0.001100 **

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Theta: count = 3.4926

Number of iterations in BFGS optimization: 50

Log-likelihood: -5475 on 78 Df

354

Figure 1. Major fishery areas and fishery distribution of the Southwest Nova Scotia (left) and the Gulf St. Lawrence (right) bluefin fisheries. Middle row shows catch distributions prior to 2010 and the bottom row shows most current two years (2010‐2011) for each fishery.

355

Figure 2. Relative frequency of records by year and months within year used in the analysis of the Southwest Nova Scotia (top) and Gulf St. Lawrence (bottom) bluefin tuna catch data. The width of the bars is indicative of the relative number of observation per year while their length denotes the contribution by month.

356

Figure 3. Relative frequency of records by year and gears (tended line, rod and reel, harpoon) within year used in the analysis of the Southwest Nova Scotia (top) and Gulf St. Lawrence (bottom) bluefin tuna catch data. The width of the bars is indicative of the relative number of observation per year while their length denotes the contribution by gear.

357

Figure 4. Relative frequency of records by year and home management areas (fleets) within year used in the analysis of the Southwest Nova Scotia (top) and Gulf St. Lawrence (bottom) bluefin tuna catch data. The width of the bars is indicative of the relative number of observation per year while their length denotes the contribution by homeport.

358 Scotia Fundy P.E.I. Quebec

2010

2005

2000

Month 1995 6 1990 7 8 1985 9 10 11 Newfoundland Nova Scotia New Brunswick Year 2010 Trips 50 2005 100 150 2000 200 250 1995

1990

1985

200 250 300 200 250 300 200 250 300 Day

Figure 5. Frequency of trips by bluefin tuna fleets from Atlantic homeports fishing in the southern Gulf of St. Lawrence (1981‐2011).

359 800

700 Avg 2001-2004

600

500

400

300 Avg 2001-2010 200 Avg 2005-2010 Spawning Biomass('000t) 100

0 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 Year

Figure 6. SSB index from acoustic surveys for the overall southwestern Nova Scotia/Bay of Fundy spawning component of herring (from DFO 2011).

360

A. Southern Gulf of St Lawrence spring spawning herring

450 Age 4 140 400 4+ biomass 120 350 t)

100 3 illions) 300

250 80

200 60 150 40 100 Age 4+ biomass (10 Age 4 abundance (m 20 50

1978 1982 1986 1990 1994 1998 2002 2006 2010

B. Southern Gulf of St Lawrence fall spawning herring

Age 4 800 4+ biomass 350

700 300

600 t) 3

illions) 250 500 200 400 150 300 100 200 Age 4+ biomass (10 Age 4 abundance (m 100 50

1978 1982 1986 1990 1994 1998 2002 2006 2010

Figure 7. (A) Spring spawner component age 4 numbers (millions of fish) and age 4+ biomass (103 t). The value for age 4 in 2012 is an estimate based on an average recruitment rate of the previous five years. (B) Fall spawner component age 4 numbers (millions of fish) and age 4+ biomass (103 t). (from DFO 2012a)

361 450000

400000 Total

350000 Spawning

300000

250000

200000

BIOMASS (t) BIOMASS 150000

100000

50000

0 1960 1970 1980 1990 2000 2010 2020 YEAR

Figure 8. Total and spawning Atlantic mackerel biomasses (t) in NAFO subareas 3 and 4 for the 1968‐ 2011 period. (from DFO 2012b).

362

Figure 9. Round weight (kg) of recent catches made in the Southwest Nova Scotia (top) and the Gulf St. Lawrence (bottom) bluefin fisheries. Red line indicates series mean.

363 Year 0.015 2002

2003

2004

0.010 2005 2006

2007 Frequency

2008 0.005 2009

2010

2011

0.000

100 200 300 400 500 600 Weight (kg)

Figure 10. Weight frequency distributions for the Southwest Nova Scotia tuna fishery. The terminal year is in black.

364 07 08 400 300

200

100 0

-100

-200

09 10 400

300

200 Weight anomaly (kg) anomaly Weight

100

0

-100

-200 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Year

Figure 11. Time series of weight anomalies for bluefin tuna caught in the Southwestern Nova Scotia tuna fishery. The anomaly is the weight observed minus the mean weight for the series. Month 11 has been combined with Month 10 due to the paucity of data.

365 0.006

Year 0.005 2000 2001 2002 0.004 2003 2004 2005 2006 0.003 Frequency 2007 2008 2009 0.002 2010 2011

0.001

0.000

100 200 300 400 500 600 Weight (kg)

Figure 12. Weight frequency distributions for Gulf of St. Lawrence bluefin tuna. The terminal year is in black.

366 7 8 400

200

0

-200

-400

9 10 400

Weight anomaly (kg) anomaly Weight 200

0

-200

-400 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Year

Figure 13. Time series of weight anomalies for bluefin tuna caught in the Gulf of St. Lawrence. The anomaly is the weight observed minus the standard weight of the fish given its length. The standard weight was calculated using the Parrack and Phares (1979) relationship for bluefin tuna captured in the western Atlantic at any time. This relationship was developed using 3200 fish spanning the length range of 20 to 372 cm. The Gulf fish are between 50 and 400 cm long but most are between 250 and 300 cm.

367

Figure 14. Top plot is a map of coastal water surrounding southern Nova Scotia with a red line defining the geographical limits of SWNS index data series. Bottom plots are historic (2002‐2009, left) and recent (2010‐2011, right) distributions of the reduced dataset for the SWNS fishery.

368

Figure 15. Top plot shows the counts of successful (N>0, red) and unsuccessful (N=0, blue) trips in the Southwest Nova Scotia fishery for 1988‐2011. Bottom plot shows the annual proportion of Southwest Nova Scotia trips with only bluefin catches.

369

Figure 16. Nominal CPUE for Southwestern Nova Scotia (top) and Gulf of St. Lawrence (bottom) bluefin fishery, in number of fish per 100 hours.

370 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

(0,7] (7,14] (14,21]

(21,28] Season length

(28,35]

year

Figure 17. Relative frequency of records by year and season length. The width of the bars is indicative of the relative number of observation per year while their length denotes the contribution by season length. Season length is essentially the number of days fished by month and fleet within each year.

371 Standardized residuals Gear versus fitted values -202468 -202468

(0.118,0.913] (2.5,3.3] (4.89,5.69] (7.28,8.07] HRRTL

Month Home_mgt_area -202468 -202468

Aug Oct Sept GNB GNS PEI PQ SF

Log(hours) Year -202468 -202468

(-0.699,-0.12] (1.04,1.62] (2.78,3.36] (4.51,5.09] 1988 1992 1996 2000 2004 2008

Figure 18. Plots of standardized residuals from the SWNS model to test for homogeneity of variance.

372 Standardized residuals Gear versus fitted values -2 2 4 6 8 -2 2 4 6 8

(-0.303,30.4] (91.7,122] (184,214] (276,306] RR TL

Month Home_mgt_area -2 2 4 6 8 -2 2 4 6 8

8910 PEI NS

Log10hours 0.5 Year -2 2 4 6 8 -2 2 4 6 8

(-0.305,0.0561] (1.14,1.5] (2.22,2.58] 1981 1986 1991 1996 2001 2006 2011

Figure 19. Plots of standardized residuals from the sGSL model to test for homogeneity of variance.

373 Normal Q-Q Plot Sample Quantiles Sample -5 0 5 10

-4 -2 0 2 4

Theoretical Quantiles Frequency 0 1000 2000

-5 0 5 10 15 20

raw residuals

Figure 20. Raw residuals from the SWNS (upper) and sGSL (lower) models.

374 2.5

2.0

1.5 catch/mean(catch)

1.0

0.5

1990 1995 2000 2005 2010 year

14

12

10

8

6 catch/mean(catch)

4

2

198519901995200020052010 yr Figure 21. Standardized (green line) and nominal indices (blue points) for the SWNS (top) and sGSL (bottom) bluefin tuna fisheries. Line ranges represent the upper 97.5% and lower 2.5% index values from 500 bootstrap runs. The orange line represents the index generated using the methodologies of Paul et al. 2010.

375

Figure 22. Relationship between effort and catch in the SWNS fishery (top). Bottom figure shows relationship between total hours fished per trip and total weight of other tunas (excludes Bluefin). Color indicative of the number of bluefin tuna caught.

376

Appendix One. Summary of Industry Observations on the Fishery in the Canadian Atlantic Zone, 2011‐ 2012 Year Area Comments 2011 Newfoundland Many “nuisance tuna” on the Grand Banks interfering with fishing operations; currently it is not economic to fish for them. Fishermen reported being able to sail from the Baie de Chaleurs to Halifax and see 2011 Southern Gulf - bluefin the entire time. Quebec The 2011 season was marked by a large number of fish around Canso and the 2011 Canso fishermen had no problem catching their quota due to a higher hook up rate. (Chedabucto The average size of bluefin tuna caught in 2011 was higher than in previous Bay) years (increased from 325lbs to 400 lbs). The fish ranged from approximately 200 lbs to 1000 lbs. It was also noted that the fishery extended later in the season in 2011, with boats fishing into December. The fishery was economically driven. For instance: fishermen were getting a good

price for small fish (200+ lbs) in 2011 so they would leave their hooks in the water even when they encountered a school of smaller fish. Under normal circumstances, the fishermen would remove their hooks from the water until they encountered bigger fish. Furthermore, fishermen noted that fishery in Canso used to start in July, but due to the current high catch rate, the fishery does not start until October and targets fish as they leave the Gulf (higher quality fish). 2012 Canso Tuna were spotted for the first time during the lobster season (early June). It might (Chedabucto have to do with a high abundance of bait fish (mackerel, herring & squid) present Bay) this year and the fact that the water temperature is higher than usual. It is thought that tuna will be even more prevalent this year and might have better condition due to the high abundance of high quality food.

Note: Canso will carry out their 1st trap net fishery in approx. 12 years targeting mackerel and squid. This is due to the large abundance of baitfish and the good price for baitfish which they hope will outbalance the gear damage caused by grey seals. The condition of baitfish seems to be higher (increase in size of mackerel). Pollock returning to Tusket and John’s Island 2012 SWNS Reports of abundant small (50 to 150 lb) bluefin 2012 Georges Bank Bluefin showed up two weeks early this year. 2012 Northern US Bluefin foraging off the Îles de la Madeleine. Bluefin off North Lake but do not 2012 Southern Gulf -- seem to be foraging. The tuna are eating herring and mackerel. BFT off Fisherman's Bank are big, off North Lake the schools are mixed and off the North Cape the fish Iles de la are 1000 lb. Generally the large and small fish do not mix when feeding because the Madeleine smaller fish out compete the larger ones during feeding. The fish arrived early this year in early June. The next earliest run was 15 years ago when they arrived in the 3rd week of May. There are reports of fish coming back to the Bay de Chaleur and sightings in the Strait of Belle Isle where tuna chased mackerel into a cove. Charter (catch and release) is ongoing now with very positive reports. Lots of fish 2012 Southern Gulf -- off Tignish and Rustico. PEI Mentioned during early August industry meetings – concern over condition and 2012 Southern Gulf -- fatness of tuna. In recent years, fish do not appear to be in as good condition as PEI expected in a given month. Herring are not concentrated around PEI. Small tuna showing up. Lots of squid available. 2012 Offshore observer

377