Recruitment and body size in relation to temperature in juvenile ...

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Sep 4, 2008 - Abundance of the 1+ juvenile fish cohort (13–15 month old dependent on survey date) was found to vary inter-annually and was found to be ...

Mar Biol (2008) 155:493–503 DOI 10.1007/s00227-008-1047-3

ORIGINAL PAPER

Recruitment and body size in relation to temperature in juvenile Patagonian toothWsh (Dissostichus eleginoides) at South Georgia Mark Belchier · Martin A. Collins

Received: 11 June 2008 / Accepted: 19 August 2008 / Published online: 4 September 2008 © Springer-Verlag 2008

Abstract Recruitment variability in juvenile Patagonian toothWsh (Dissostichus eleginoides), a commercially important, deepwater nototheniid Wsh, was examined at the subAntarctic island of South Georgia, South Atlantic. Data from 13 demersal trawl surveys conducted over a 20-year period were analysed. Abundance of the 1+ juvenile Wsh cohort (13–15 month old dependent on survey date) was found to vary inter-annually and was found to be inversely correlated with the sea surface temperature (SST) conditions experienced by adults prior to spawning. Environmental temperatures experienced by toothWsh eggs and larvae were not signiWcantly correlated with juvenile density. The mean length of 1+ Wsh attained after 13–15 months was higher in years of high juvenile abundance and was signiWcantly inversely correlated with SST in the summer prior to adult spawning. Trends in toothWsh recruitment variability mirrored those previously observed in a range of krilldependent land-based predators at South Georgia for whom non-seasonal, large-scale climatic events such as El Niño Southern Oscillation (ENSO) are considered the most likely underlying drivers of variability in breeding success. The drivers of recruitment variability in toothWsh are not fully understood but a range of possible mechanisms are considered. A better understanding of recruitment variability holds great interest for Wsheries managers and could be used reWne forecasts of years of good or poor recruitment for the toothWsh Wshery at South Georgia.

Communicated by U. Sommer. M. Belchier (&) · M. A. Collins British Antarctic Survey, Natural Environment Research Council, High Cross, Madingley Road, Cambridge CB3 0ET, UK e-mail: [email protected]

Introduction The Patagonian toothWsh (Dissostichus eleginoides Smitt, 1898) is a large predatory or scavenging demersal perciform Wsh that is endemic to the Southern Hemisphere. Populations are found to the north and south of the Polar Front and are most commonly associated with sub-Antarctic islands and seamounts including South Georgia (South Atlantic) and Kerguelen and Heard Island (Southern Indian Ocean). North of the Polar Front populations are found on the Patagonian Shelf, around the Falkland Islands in the South Atlantic and around other island groups such as the Prince Edward Islands in the Indian Ocean. The Patagonian toothWsh occupies a broad bathymetric range, with the highest density of juvenile Wsh found at depths of around 200 m on the continental shelf (Collins et al. 2007). As Wsh grow they undergo a distinct ontogenic, down-slope migration, with the large adult Wsh most commonly found at depths of 700–2,000 m, although large Wsh are occasionally found over shelf regions (Laptikhovsky et al. 2006). The large size (in excess of 2 m and 100 kg) and high quality Xesh of the Patagonian toothWsh led to the development in the mid 1980s of a valuable circum-polar long-line Wshery, targeting adult Wsh. Since the mid 1990s the Wshery has been managed by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), with mean annual catches at South Georgia of around 3,000–4,000 tonnes, the largest Wshery for toothWsh within the CCAMLR management area (Agnew 2004). Recent studies have shown that annual recruitment of toothWsh juveniles to the adult, exploitable population is highly variable. Data obtained from trawl surveys and commercial Wsheries in the Patagonian shelf region have indicated that pulses of high recruitment to the Wshery occur at a frequency of approximately 4 years (Laptikhovsky and

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494

Brickle 2005). At South Georgia a single strong cohort was observed to dominate the biomass of juvenile toothWsh caught in successive annual surveys over a period of 4 years (2003–2006) (Collins et al. 2007). However, the environmental or ecological mechanisms driving the observed recruitment variability are poorly understood in this species. Atmospheric or climatic forcing of recruitment variability is a well-documented phenomenon. It is thought to cause population size of a many Wsh species to Xuctuate over a range of diVerent time scales (Glantz 1992; Beamish 1995). The close link between climate and Wsheries is best illustrated by the non-seasonal, and sometimes catastrophic events such as those associated with the El Niño-Southern Oscillation (ENSO) including the collapse of the Peruvian anchoveta (Engraulis ringens) Wshery, but interdecadal or multidecadal eVects of climate are also well documented (Lehodey et al. 2006). As the understanding of the relationship between climate and Wsheries increases there has been an increasing trend towards incorporating environmental stock–recruitment relationships into Wsh stock assessments (Sinclair and Crawford 2005) but doubts have also been expressed concerning the reliability of such an approach (Myers 1998; Megrey et al. 2005). Although the relationship between climate and Wsheries of the Northern Hemisphere and upwelling regions has been extensively documented, very little is known about the interannual drivers of variability in the WnWsh Wsheries of the Southern Ocean. In contrast, considerable evidence exists that the recruitment of Antarctic krill (Euphausia superba) is strongly inXuenced by environmental variability (Trathan et al. 2003). Fluctuations in the biomass of Fig. 1 The location of South Georgia and Shag Rocks in relation to the main fronts and currents in the Scotia Sea. Mean frontal positions are shown based on data derived from Orsi et al. 1995 and Trathan et al. 2003 (SACCF = Southern Antarctic Circumpolar Current Front). Areas of continental shelf (3,000 m. Shag Rocks are located approximately 225 km to the west and their associated shelf is separated from South Georgia by a deep gully that reaches depths in excess of 1,200 m in places. South Georgia lies in the path of the Antarctic Circumpolar Current (ACC), a major ocean current consisting of several circumpolar fronts (Orsi et al.

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1995). The Polar Front (PF) to the north isolates South Georgia oceanographically from South America, whilst the southern ACC front (SACCF) located to the south plays an important role in transporting krill to South Georgia from the Antarctic Peninsula region (Hofmann et al. 1998; Thorpe et al. 2002). The Southern Boundary front marks the southern extent of the ACC. In contrast to surrounding waters, the South Georgia shelf is highly productive with both phytoplankton and zooplankton productivity far higher than is typical for the Southern Ocean (Atkinson et al. 2001; Korb and Whitehouse 2004). Data sources Fish survey data Distribution and relative abundance data for juvenile toothWsh were obtained from 13 demersal trawl surveys carried out on the South Georgia and Shag Rocks shelves (CCAMLR sub-area 48.3) between 1986 and 2006 (Table 1). With the exception of the September 1997 survey, all surveys were carried out in the middle of the austral summer (December–February). Each survey, except 2003, followed a random design, stratiWed spatially by depth zone (50–149 m; 150–249; 250–500 m). The principal aim of these surveys was to provide estimates of the relative abundance of demersal Wsh species of commercial interest. EVort (number of trawls) was approximately commensurate with seaXoor area within each stratum although on the earliest surveys (SG87 & SG 88) fewer hauls were carried out in the deeper strata at Shag Rocks and a larger number were made to the rough ground to the south of the island. Details of survey design are provided in Everson et al. (1999). In 2003, trawls were organised in a series of non-random transects Table 1 Details of South Georgia demersal trawl surveys 1986–2006

Survey code

Season

radiating out from South Georgia from shallow to deep water (Collins et al. 2004). All surveys used a commercial sized otter trawl with a headline height of 4–6 m, a wingspread of approximately 18–22 m and a cod-end mesh of 40mm. Juvenile (1+) toothWsh were considered to be fully selected by the trawl. The net was Wshed on the seaXoor during daylight hours for approximately 30 min at a speed of 4 knots. By necessity a number of diVerent survey vessels were used throughout the survey series; however, the use of large trawl vessels of similar power, identical Polyvalent trawl doors and constant trawl-warp to depth ratios coupled with the rough Wshing grounds at South Georgia meant that possible eVects resulting from changes in vessel were considered negligible (Everson et al. 1999). The Wsh catch was sorted by species and weighed using motion compensated marine scales. The total catch of toothWsh was recorded (kg) and, where possible, all individual toothWsh were measured (to 1 cm category below total length, TL), weighed (g) sexed and their otoliths removed. Randomly selected sub-samples of toothWsh were collected and analysed as above when catches were large. Since 2002 age-determination of juveniles caught on surveys has been carried out using conventional thin section methods (Ashford et al. 2002). Length frequency analysis of toothWsh catch data was carried out using RMIX an ‘R’-based version of the ‘MIX’ software (Macdonald and Pitcher 1979) in order to calculate the mean length of each identiWed cohort. Each year’s data were examined separately with the number of cohorts and initial input estimates of component means estimated from length frequency plots. ‘RMIX’ was constrained to have a constant coeYcient of variation (standard deviation proportional to the mean) and was run from diVerent starting parameters to Wnd the optimal solution (minimising Chi-squared).

Survey vessel

Start

End

No. of trawls South Georgia

Shag Rocks

SG87

1986–1987

Professor Siedlecki

29 Nov. 1986

17 Dec. 1986

108

13

SG88

1987–1988

Professor Siedlecki

19 Dec. 1987

12 Jan. 1988

109

4

SG90

1989–1990

Hill Cove

6 Jan. 1990

26 Jan. 1990

59

9

SG91

1990–1991

Falklands Protector

22 Jan. 1991

11 Feb. 1991

73

13

SG92

1991–1992

Falklands Protector

3 Jan. 1992

26 Jan. 1992

74

14

SG94

1993–1994

Cordella

4 Jan. 1994

08 Feb.1994

77

19

SG97

1997–1998

Argos Galicia

2 Sep. 1997

29 Sep.1997

59

12

SG00

1999–2000

Argos Galicia

16 Jan. 2000

30 Jan. 2000

35

17

SG02

2001–2002

Dorada

5 Jan. 2002

1 Feb. 2002

49

20

SG03

2002–2003

Dorada

7 Jan. 2003

31 Jan. 2003

30

15

SG04

2003–2004

Dorada

7 Jan. 2004

5 Feb. 2004

44

21

SG05

2004–2005

Dorada

7 Jan. 2005

25 Jan. 2005

28

15

SG06

2005–2006

Dorada

3 Jan. 2006

1 Feb. 2006

47

19

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496

The density of 1+ juvenile toothWsh (identiWed by size from survey length frequency data) was derived using the swept area method for each survey calculated from haul by haul catch weight, net opening and trawl speed data. Density was expressed as the mean density (ln(N/km2)) for each survey. SST data Mean monthly sea surface temperature data for the South Georgia and Shag Rocks region covering the period November 1984 to July 2006 were obtained from the National Oceanographic and Atmospheric Administration (NOAA, United States Department of Commerce), available at the National Center for Atmospheric Research (NCAR) webpage (http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP/ .EMC/.CMB/.GLOBAL/.Reyn_SmithOIv1/.monthly/). The data were part of the SST O1 V.2 set, produced with operational global SST analyses using optimal interpolation (Reynolds et al. 2002). The data were selected from a single grid cell with a resolution of 1° latitude and 1° longitude with a midpoint centred on 54°S, 41°W. This cell encompasses the area of highest juvenile density observed, is a region of high spawning activity (Agnew et al. 1999) Fig. 2 A schematic representation of the life-cycle of Patagonian toothWsh in the South Georgia and Shag Rocks region

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and is close to the location of the highest recorded densities of larval toothWsh (North 2002). Analyses Multiple regression analysis was used to relate (a) juvenile (1+) toothWsh abundance and (b) size of 1+ Wsh (a proxy for growth rate), to the environmental conditions experienced by toothWsh at diVerent stages of reproduction and development measured by the following predictor variables: (1) summer maximum SST, approx. 6 months prior to spawning (Tspawn); (2) Winter/spring minimum SST, approx. 2 months post-spawning (Tegg) representing environmental temperatures during egg development and incubation, and (3) Summer/Autumn maximum SST, approx 6 months post spawning (Tlarvae) representing temperatures experienced by larvae. Putative developmental periods were assigned based on adult reproductive (Kock and Kellermann 1991; Agnew et al. 1999) and larval/juvenile studies (Evseenko et al. 1995; North 2002) for toothWsh at South Georgia (Fig. 2). Time trends were included as a linear trend with year. Abundance was ln transformed to measure multiplicative changes in density, and to help stabilise the variance, reduce skewness and approximate to a Normal distribution.

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Plots of standardised residuals from the Wtted regression were consistent with the assumptions of (a) constant variance (correlation between absolute residuals and Wtted values r = ¡0.28, p = 0.35), and (b) Normality (Anderson– Darling statistic AD = 0.29, p = 0.55). Mean length of the 1+ cohort derived for each survey from the ‘RMIX’ analyses were used as the response variable for assessing the relationship between SST and Wsh length. One-way ANOVA was used to compare depth of capture of diVerent year classes and length at age of 1+ toothWsh in diVerent survey years. Statistical analyses were performed using Minitab® v.14 software (Minitab Inc, PA, USA).

Results SST at South Georgia Mean monthly SST data for the South Georgia/Shag Rocks regions are shown in Fig. 3. Peak summer temperatures occurred in February and March and ranged from 2.78 to 4.97°C between years whilst the range of winter minima was less (¡0.28 to 1.24°C). Mean annual SST ranged from 1.23 to 2.53°C. Juvenile toothWsh distribution and size structure ToothWsh were caught in 48% of the 983 research trawls carried out over the South Georgia and Shag Rocks shelf region during 13 surveys between 1986 and 2006. Fish size ranged from 11 to 127 cm TL but large Wsh (>75 cm) were rare, accounting for only 1% of the total toothWsh catch. All Wsh smaller than 75 cm were juvenile (immature) with a sex ratio of approximately 1:1 (0.47/0.53, M/F). The density of toothWsh over the Shag Rocks shelf was considerably higher than at South Georgia. Juvenile toothWsh were taken

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in 82% of hauls at Shag Rocks and only 40% of those at South Georgia. The total number of trawls made at Shag Rocks accounted for only 19% of the total but accounted for 73% of the total toothWsh catch by weight. The length frequency distributions of toothWsh catches for each survey were polymodal (Fig. 4). Annual cohort progression was observed in successive surveys (e.g. 1990– 1992 and 2003–2006) with a single large cohort dominating the length frequency distributions in most years. Despite inter-annual variability in the length distribution of Wsh within each age class (Fig. 4), separating size–classes both visually and using the R-mix programme was straightforward. Previous studies (North 2002) have clearly demonstrated that the modes observed within the survey data represent separate year classes. The 1+ cohort, conWrmed by otolith ageing (comprising Wsh ranging in length from 14 to 24 cm), was the youngest/smallest caught by the survey bottom trawl and was not observed on all surveys (e.g. 2002, 2004 and 2005). The density and distribution of diVerent age-classes varied both spatially and temporally. All 1+ toothWsh were caught in water depths less than 200 m and were at their highest density in shallow water areas over the Shag Rocks shelf. Low densities of 1+ Wsh were also taken in smaller numbers at shallow water sites at South Georgia but were absent from the shelf areas to the north of the island (Fig. 5). In surveys carried out after 1994 1+ Wsh were rarely caught over the South Georgia shelf but were periodically caught at Shag Rocks at high densities. Subsequent analyses excluded the limited 1+ cohort data obtained for the South Georgia shelf. An ontogenetic migration into deeper water was observed in older/larger Wsh (Fig. 5). The mean depth of capture of 1+ Wsh (140 m) was signiWcantly shallower than for older cohorts (209–240 m for 2+–4+ Wsh, ANOVA F3,722 = 29.9, p < 0.001).

Fig. 3 Mean monthly SST (°C) signal for the grid cell with a resolution of 1° latitude and 1° longitude (midpoint centred on 54°S, 41°W (bottom panel). Juvenile (1+) toothWsh density plotted for each survey year (top panel). Arrows link high juvenile abundance with low summer SST approx. 6 months prior to spawning (* indicates years when no survey data were available)

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Mar Biol (2008) 155:493–503 10

n = 463

1987

n = 299

1988

n = 753

1990

n = 677

1991

n = 1120

1992

n = 1090

1994

n = 244

1997

n = 506

2000

n = 2397

2002

5 0 10 5 0 20 15 10 5 0 20 15 10 5 0 15 10 5

Length frequency (%)

0 20 15 10 5 0 10 5 0 10 5 0 15 10 5 0 20 15 10 5 0

2003

n = 325

20 15 10 5 0

2004

n = 398

15

2005

n = 332

10 5 0 15

2006

n = 683

10 5 0

0

10

20

30

40

50

60

70

80

Total length (cm) Fig. 4 Percentage length frequency distribution of Patagonian toothWsh caught during surveys between 1986 and 2006. Dashed lines delineate 1+ year class

Interannual variability in juvenile Wsh density Considerable interannual variability in the cohort strength (density) of 1+ toothWsh was observed over the Shag Rocks

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shelf. Mean density of 1+ Wsh (lnN/km2) ranged from 0 to 8.9 between surveys. Strong 1+ cohorts (e.g. 1990 and 2003) were persistent and were easily tracked in subsequent year’s data (Fig. 4). The 1+ cohort was frequently

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The results of multiple linear regression analysis demonstrated a signiWcant correlation between juvenile (1+) toothWsh abundance at Shag Rocks, SST 6 months prior to spawning (Tspawn) and survey year (r2 = 88%; F4,8 = 14.63; p = 0.001). However, the remaining predictors used (Tegg and Tlarvae) did not contribute signiWcantly to the regression model (Table 2). Subsequent stepwise regression analysis on the four predictors used in the multiple regression model showed that Tspawn accounted for 66% of the observed variation whilst the addition of ‘survey year’ into the model accounted for a further 22% of the observed variation. Further linear regression analysis indicted a signiWcant inverse correlation between Tspawn and ln density of juvenile (1+) toothWsh (r2 = 66%, p = 0.001; Fig. 6). Interannual variability in juvenile Wsh length The mean length of the cohort of 1+ Wsh (13–15 month old dependent on survey date) calculated using Rmix ranged from 15.95 to 21.69 cm and varied signiWcantly between surveys (ANOVA F6,1452 = 239; p < 0.001). Multiple linear regression analysis showed a marked eVect of Tspawn on Table 2 Results of a multiple regression analysis to assess the relationship between density of juvenile (1+) toothWsh and environmental temperature experienced at diVerent life history stages and survey year (R2 = 88.0%) Predictor

Coef

SECoef

t

p

Year

¡0.20

0.061

¡3.35

0.010

Tspawn

¡4.96

0.81

¡6.10

0.000

Tlarvae

¡0.16

0.75

¡0.21

0.84

Tegg

¡0.22

1.04

¡0.21

0.84

10 '90

8

Fig. 5 Distribution and size of catches of three age classes of Patagonian toothWsh juveniles a 1+ (14–24 cm), b 2+ (25–38 cm) and c 3+ (39–48 cm). Only hauls containing toothWsh are presented. 200 and 1,000 m isobaths are shown

Density (lnN/km2)

'94 '88

'03

6

'00

'91

4 '87 '97

2

absent in the intervening years indicating highly variable recruitment. When survey derived- abundance data for 1+ Wsh were plotted alongside a 20-year series of mean monthly SST for Shag Rocks a consistent pattern emerged of cold summer temperatures preceding strong cohorts by a period of 2 years (Fig. 3).

'92 '06 '04

'02 '05

0 2.8

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

SST(oC)

Fig. 6 Mean juvenile (1+) toothWsh density (§SE) at Shag Rocks versus summer maximum SST (Tspawn) at Shag Rocks prior to adult spawning. Labels indicate survey year. Continuous line = regression line (y = 23 ¡ 5.27x: r2 = 66%; F1,11 = 20.98, p < 0.001). Dashed lines = 95% conWdence intervals for the line

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total length (TL), but no eVect of either Year, Tlarvae or Tegg was detected (Table 3). The relationship between TL and Tspawn was well described by a segmented linear regression (R2 = 91.7%,) with a decrease for x < 3.65°C and constant level for x > 3.65°C (Fig. 7). Compared with a linear decrease (R2 = 69.6%), the increased Wt was statistically signiWcant (F1,5 = 13.41, p = 0.015).

Discussion Our analyses indicate that recruitment strength is inversely correlated with sea surface temperature (SST) in Dissostichus eleginoides at South Georgia. Surface water temperatures recorded prior to adult spawning were inversely correlated with juvenile abundance more than 1 year later. The linear relationship observed between ln density and SST prior to spawning suggests an exponential increase in juvenile abundance with decreasing temperature over the observed temperature range. In contrast, SST experienced during the egg and larval stages was poorly correlated with Table 3 Results of a multiple linear regression analysis to assess relationship between length of juvenile (1+) toothWsh, and year and environmental temperature experienced at diVerent life history stages (R2 = 93%) Predictor

CoeYcient (SE)

Year

t

0.017 (0.092)

0.19

¡3.81 (0.78)

Tspawn Tlarvae Tegg

p value 0.86 0.016

¡4.89

0.84 (0.93)

0.90

0.43

¡1.76 (0.76)

¡2.33

0.10

23 '03

22 21

TL (cm)

'90

20 '94

19 '00

18 17

'87

'88 '91

'97

16 15 2.8

3.0

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

SST (oC)

Fig. 7 Relationship between total length and spawning temperature with Wtted segmented linear regression (R2 = 91.7%): y = a + b(x ¡ c) when x · c and y = a where x ¸ c. CoeYcients for the Wtted model are as follows: a = 16.21 (SE = 0.37), b = ¡7.52 (SE = 2.44), c = 3.65 (SE = 0.17). Dashed lines = 95% conWdence interval for model. Standard Error bars are shown and labels indicate survey year

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juvenile abundance, providing an insight into potential mechanisms of recruitment variability in a deep-water demersal Antarctic Wsh species. Inter-annual variability in the strength of toothWsh cohorts has previously been observed around the Falkland Islands (Laptikhovsky and Brickle 2005) where strong cohorts were present approximately every 4 years. However, no attempt was made to link the observed recruitment patterns to environmental variability. The recent availability of reliable age data (Horn 2002), coupled with information on spawning and reproduction, has made it possible to assess the SST conditions experienced by speciWc toothWsh cohorts at diVerent stages of their early life history. Research into the environmental forcing of recruitment in Antarctic Wsh is limited and has been restricted to a handful of studies of commercially important species such as mackerel iceWsh (Champsocephalus gunnari) (Hill et al. 2005). This contrasts with the situation for temperate and tropical species of the northern hemisphere (Lehodey et al. 2006). Here the inXuence of climatic variability on Wsh stock recruitment has been established since the early years of the last century. Data exist for a diverse range of pelagic and demersal species (Glantz 1992; Beamish 1995) and a smaller number of deepwater species such as sableWsh, Anoplopoma Wmbria (Schirripa and Colbert 2006). Research eVort on Antarctic Wsh stocks has been limited largely by inaccessibility and cost. In contrast to Wsh, there is evidence that Xuctuations in the abundance of Antarctic krill (Euphausia superba) and their dependent vertebrate predators, e.g. seals and penguins, are climatically driven. The recruitment of adult krill at South Georgia [by advection from further south around the Antarctic Peninsula (Hofmann et al. 1998)] is enhanced during cold periods while there is little or no inXux during warmer periods (Murphy et al. 2007). In periods of reduced krill abundance the reproductive performance of a wide range of land-based predators, for whom krill constitutes a major component of diet, is greatly reduced (Forcada et al. 2005; Trathan et al. 2007). Such Xuctuations are now thought to result from variability in large scale physical process such as ENSO (Murphy et al. 2007). The current study indicates that toothWsh recruitment broadly follows the same trend. Reproductive success (measured as abundance of 1-year-old Wsh) is reduced or absent when adult spawning follows a warmer summer and is enhanced following colder summers. Adult Patagonian toothWsh are found at peak abundance at depths of 800–1,200 m where they are known to forage on a range of prey including squid, Wsh and crustaceans whilst also scavenging opportunistically on food falls (Arkhipkin et al. 2003). They are opportunistic predators for whom krill is not thought to constitute a major fraction of the adult diet. Juveniles, although predominantly piscivorous,

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do take small quantities of krill in their diet (Collins et al. 2007). It is unlikely that adult condition and spawning success are directly related to krill abundance as has been observed in mackerel iceWsh (C. gunnari). In this predominantly krill feeding species, body condition is often poor during periods of low krill abundance (Everson et al. 1997) which in turn can reduce or prevent reproductive development (Everson et al. 2000). Inter-annual variability in reproductive condition has been recorded in toothWsh. A two-season study of commercial Wsh catches showed that in one season 25–43% of adult Wsh delayed or failed to spawn whilst 100% of individuals reached spawning condition in the following year. It was suggested that this reduction in reproductive output could reduce larval production and recruitment (Everson and Murray 1999). Information on bentho-pelagic coupling in the Scotia Sea is limited (Murphy et al. 2007); however, in other regions of the Southern Ocean, high benthic productivity has been linked to high pelagic productivity (SchnackSchiel and Isla 2005). Although the precise nature of these interactions are poorly understood it has been suggested that Xuxes in faecal pellets from krill may contribute signiWcantly to the cycling of carbon from surface waters. Periods of increased krill abundance at South Georgia could be linked to an increase in prey quality and abundance in the benthic environment and a possible increase in the reproductive output of toothWsh. The similarities in the temporal patterns of reproductive success observed in krill dependent predators and toothWsh, a predator/scavenger occupying a higher trophic level could be inXuenced by such ‘bottom-up’ control. In the current study there was no apparent correlation between cohort strength and SST recorded during early life history stages in toothWsh. However, drawing parallels with a range of other Wsh species (Pepin and Myers 1991; Bradford and Stephenson 1992) it is likely that variable larval mortality, whether temperature dependent or not, will play a key role in determining year class strength in toothWsh. ToothWsh eggs are pelagic and have duration of approximately three months and the pelagic larval stage is thought to have a similar duration (Evseenko et al. 1995; North 2002). This makes toothWsh vulnerable to predation and/or starvation for a protracted period. Current knowledge of toothWsh egg and larval distribution and abundance is limited and it is therefore diYcult to assess whether temperature controls survivorship in these early life history stages. The reproductive strategy seen most frequently in nototheniids is to have an extended pelagic egg and larval stage (Kock and Kellermann 1991; White 1998). This is regarded as a paradox in that life history strategies favour dispersal whilst ecological and genetic studies indicate limited dispersal in these species (White 1998). Whilst many nototheniid Wshes have overcome this apparent problem by

501

spawning within the fjords and bays of the sub-Antarctic islands (Kock 1992) and having demersal eggs (C. gunnari), toothWsh are known to spawn many kilometres from shore on the shelf break. A number of recent population genetic studies have shown that there is only limited gene Xow between toothWsh populations in the Southern Ocean (Shaw et al. 2004; Rogers et al. 2006) and yet great potential for dispersal exists through the early life history stages. No genetic diVerences exist between toothWsh at South Georgia and those at Shag Rocks and tagging studies also indicate that there is movement of adults between the two shelf regions (Marlow et al. 2003). Transport processes between spawning grounds and nursery areas can act as a critical determinant of recruitment success (Shelton and Hutchings 1982). For toothWsh, that have a pelagic phase of around 6 months, egg and larval retention processes potentially inXuence levels of recruitment. Limited larval sampling has shown larval and early juvenile toothWsh to be present over much of the South Georgia and Shag Rocks shelf areas (Evseenko et al. 1995; North 2002). However, our study indicates that they recruit in the greatest numbers to the nursery ground of Shag Rocks. Despite their geographical proximity, there are a number of physical and biological diVerences between the two locations that may favour Shag Rocks over South Georgia. The reduced numbers of piscivorous Wsh species, such as the Scotia Sea iceWsh Chaenocephalus aceratus at Shag Rocks (Reid et al. 2007), may reduce predation on young toothWsh in this area. Conversely, the abundance of the small notothen Patagonotothen guntheri (a dominant prey item for juvenile toothWsh at Shag Rocks (Collins et al. 2007)) suggests that conditions are more favourable for toothWsh survival than those found at South Georgia where P. guntheri is absent (Collins et al. 2008). Whilst there is a considerable amount of information available on the coarse scale oceanographic processes that operate around South Georgia (e.g. Thorpe et al. 2002; Meredith et al. 2005), little is currently known about the Wne scale movement of currents between the Shag Rocks and South Georgia shelves and how this may vary between seasons and years. The inXuence of Wne-scale oceanographic variability on recruitment is therefore diYcult to determine. Data obtained from a recent summer zooplankton survey indicates that there is considerable retention of zooplankton over the South Georgia shelf and suggests that retention time for particles in this area could exceed 3 months during the summer period (Ward et al. 2007). Whilst these observations oVer a plausible explanation of the retention of toothWsh larvae at Shag Rocks and South Georgia there is currently no information available for the potentially critical winter and spring periods or on the interannual variability in the Wne-scale current Xows around South Georgia.

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Our results indicate that the size attained by juvenile toothWsh at 13–15 months is inXuenced by the same mechanisms that appear to regulate abundance. Colder temperatures experienced by adults prior to spawning were strongly inversely correlated with an increase in mean Wsh length at one year old. The precise mechanisms driving enhanced growth are again thought to be complex but it appears from our limited data that the direct physiological aVects of temperature on growth are negligible or indiscernible over the relatively small range of temperatures experienced. Enhanced growth is likely to be attributable to favourable feeding conditions that in turn would lead to increased survival. It is unsurprising that growth and survivorship appear to be linked with higher growth rate associated with the largest cohorts of toothWsh at South Georgia/Shag Rocks. In addition to temperature, our results indicate a weak, but signiWcant, eVect of survey year on juvenile toothWsh density. Densities of juvenile toothWsh in recent years have been lower (or completely absent) compared to those observed during earlier surveys. It is plausible that vessel eVects could give rise to these observations as recent data were obtained from surveys conducted from a single vessel, Dorada. However, there is little evidence that catch rates for other sympatric species varied between survey years. Analysis of the length frequency data of recent surveys indicate that there has been consistently poor toothWsh recruitment at South Georgia with 1+ Wsh largely absent in all consecutive surveys from 2004. The strongly signiWcant relationship between SST and juvenile toothWsh density is unlikely to be an artefact of sampling. A better understanding of the mechanisms driving recruitment variability holds interest for Wsheries managers and suggests that the relationship presented here could be used to forecast years of good or poor recruitment for toothWsh. Strong cohorts can be tracked in survey data for many successive years and it is assumed that these will recruit to the Wshery when they move oV shelf into deeper water at about 7–9 years of age. Such information could be used to integrate SST into a stock-recruit model for toothWsh. However, it should be noted that similar relationships between recruitment and temperature have been shown for a large number of Wsh species. Of these very few have been applied practically in Wsheries forecasting whilst many have not withstood subsequent analytical scrutiny (Myers 1998; Megrey et al. 2005). Francis (2006) has highlighted the need for robust cross-validation of environment–recruit relationships that includes the careful screening of predictors (such as SST). The ability to detect environmentrecruit relationships and to measure their strength is likely to depend on the length of the recruitment series available. Whilst the current study uses data from surveys spanning over 20 years it is still based on a relatively small number of observations. Consequently, the addition of further data

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and validation needs to be undertaken before the results are used in a predictive capacity for management purposes. Acknowledgments The authors wish to thank the oYcers and crew of all research vessels involved in South Georgia surveys since 1986. We are indebted to the scientists who have assisted with the at-sea biological sampling over the years. We are grateful to P. Rothery (CEH) for providing statistical advice and to two anonymous referees for improving the manuscript. The study was funded by the Government of South Georgia and South Sandwich Islands (GSGSSI) and contributes to the BAS DISCOVERY 2010 programme.

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