Recent trends in stock-recruitment of Blackwater herring (Clupea harengus L.) in relation to larval production

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1 ICES Journal of Marine Science, 58: doi:1.16/jmsc , available online at on Recent trends in stock-recruitment of Blackwater herring (Clupea harengus L.) in relation to larval production C. J. Fox Fox, C. J. 21. Recent trends in stock-recruitment of Blackwater herring (Clupea harengus L.) in relation to larval production. ICES Journal of Marine Science, 58: Recruitment at age 2 plotted against spawning stock biomass (SSB) for the Blackwater herring stock shows a dome-shaped pattern. This has been apparent in recent years ( ) when, despite high spawning stock biomass, resulting year classes have been poor. In 1994, 1996 and 1997 plankton surveys were undertaken in the Blackwater Estuary to estimate the production of yolk-sac larvae. The results of production, average cohort growth and mortality were compared with the results from surveys carried out in 1979 when spawning stock biomass (SSB) was close to the minimum historically recorded. In each year of the present study, estimated levels of larval production were higher than in Following hatching, average cohort growth rates appeared to be similar to those in 1979 but mortality rates appeared to be greater. Levels of larval production increased linearly with spawning stock biomass but there was an inverse relationship between estimated survival from hatching to recruitment at age 2 and the level of larval production. The results suggest that, in the years studied, year-class strength was determined by density dependent and/or environmental processes operating after hatching as opposed to processes operating at the egg stage. Keywords: Blackwater Estuary, herring, stock-recruit, larval production. Received 9 December 1999; accepted 9 March 21. C. Fox: CEFAS, Lowestoft Laboratory, Pakefield Road, Lowestoft, Suffolk, NR33 HT, England, United Kingdom. c.j.fox@cefas.co.uk Introduction The Thames estuary herring comprise a small, localized stock which are sometimes called Blackwater herring. They are members of a spring-spawning (between late February and April) coastal race as opposed to the larger offshore stocks in the North Sea, which spawn in the autumn (Wood, 1981). The inshore migration of Blackwater herring starts in early October with fish concentrating within 1 miles of the East Anglian coast in preparation for spawning the following spring (Wood, 1981). The principal recognised spawning site is the Eagle Bank at the mouth of the Blackwater Estuary (Figure 1), although there is historical evidence of limited spawning at Stone (opposite Osea Island) and at Herne Bay on the Kent coast (Wood, 1981; Dempsey and Bamber, 1983). Eggs are laid on these gravel banks between February and April and hatch after two to three weeks. Historical estimates of spawning stock biomass (SSB) and subsequent recruitment at age 2 are shown in Figure 2 (CEFAS, unpublished data). Pair trawling over the spawning grounds during the 196s dramatically reduced the stock with the result that by 1977, SSB had fallen to a historical low. Similar trends were observed in the North Sea stocks leading to the closure of these herring fisheries between 1977 and 198. Since then, the SSB for the Blackwater herring has been above 2 tonnes and reached the highest level recorded in However, these high SSB levels generated relatively weak year classes. During the spring of 1994, 1996 and 1997 weekly sampling was undertaken in the estuary to investigate conditions affecting growth and survival of herring larvae in this region (Fox et al., 1999). The present paper compares larval production, growth and loss rates with historical estimates from 1979 reported in Henderson et al. (1984). Materials and methods The Blackwater Estuary was divided into 21 sampling boxes with a single station assigned to each box /1/ $35./

2 Recent trends in stock-recruitment of Blackwater herring Colchester R. Colne 51.8 Mersea Is. Clacton Maldon Osea Island R. Blackwater Eagle Bank Wallet Latitude (N) 51.7 Bradwell Marshes Buxey Sand East Swin Middle Deep 51.6 Southend-on-Sea Foulness Is. Maplin Sands 51.5 Canvey Is. Thames Estuary Longitude (E) Figure 1. Map of the Thames estuary showing location of the Blackwater Estuary. 1.2 (Figure 3). Sampling began at the top of the river around low water and plankton tows were taken against the incoming tide. The whole sampling plan took about eight hours so seaward stations were sampled around high tide over the Eagle Bank. Because of weather conditions in 1994 and 1996, it was not possible to sample the outer, exposed stations every week (Table 1). In 1997, the vessel size was increased enabling the full sampling area to be covered every week. At each station, a Lowestoft Gulf VII sampler (Nash et al., 1998) equipped with a 27-μm mesh net was deployed at 3 knots for 5 1 minutes from a commercial fishing vessel. The sampler was towed from the starboard derrick to avoid the wake of the ship. The sampling profile was a vertical saw-tooth pattern to within 1 m of the seabed. Water flow through the net was logged using an internal flow-meter (Valeport, Dartmouth, Devon, UK) in the nose-cone, an additional external flow-meter was also mounted on the sampler frame. Environmental data were recorded using an FSI (Falmouth Scientific Instruments, Falmouth, USA) internally logging micro-ctd. Upon recovery of the

3 752 C. J. Fox Recruits (age 2) Spawning stock biomass (tonnes) Figure 2. Recruitment (at age 2) against spawning stock biomass derived from the 1999 Blackwater herring Virtual Population Analysis (CEFAS, Lowestoft, unpublished data). Recruitment at age 2 and has been plotted against the SSB in the year of spawning, points are labelled with year of spawning; years indicated with a filled symbol are those for which field data are considered in this paper; solid line shows a Ricker stock-recruit curve fitted by non-linear least-squares Mersea Is. Clacton-on- Sea Latitude (N) Maldon T S U R Q P O N M L Bradwell K J I H G F D E A C B Longitude (E) Figure 3. Map of the Blackwater estuary showing locations of sampling stations and bathymetry. Medium grey=foreshore; light grey <1 m charted depth; white >1 m charted depth sampler, the net was washed down and the catch immediately fixed in 4% (v/v) formaldehyde in distilled water buffered with 2.5% (v/v) sodium acetate trihydrate (Tucker and Chester, 1984). In the laboratory, herring larvae were sorted from the samples, counted and the standard lengths of up to 1 randomly selected larvae per station measured using an interactive image analysis package (ColorMorph, Perceptive Instruments, Halstead, England linked to an Olympus SZH1 stereo-microscope). Calibration was checked daily against a slide graticule (Graticules Ltd, Tonbridge, England). Standard lengths of herring larvae were corrected for net and fixative induced shrinkage using the equation given in Fox (1996). Length data were then binned into.5-mm length categories and pooled across the study area to generate length frequency distributions for each sampling date. Distinct cohorts were initially identified by eye following which the length frequency data were decomposed using Mix 2.3 (Icthus Data Systems, Ontario, Canada). Because

4 Recent trends in stock-recruitment of Blackwater herring 753 Table 1. Summary of survey coverage. Year Sampling date Number of herring larvae sampled Sites not sampled Survey vessel March 78 A H FV Gill, CK March 68 A, B, C, D, F, H FV Gill, CK March 1 6 A H FV Gill, CK123 6 April A FV Gill, CK April 77 A, B, C FV Gill, CK April 644 FV Gill, CK123 26April 848 A,B,C,D FV Gill, CK123 4May 33 A,B,C,D FV Gill, CK123 1 May 114 A, B, C FV Gill, CK March 2 B, C FV Gill, CK March 28 B, C FV Gill, CK123 3 April 48 B, C FV Gill, CK123 9 April 435 FV Gill, CK April 18 FV Gill, CK123 April 892 FV Gill, CK123 3 April 653 FV Gill, CK May 7 FV Gill, CK March 71 FV Oceanus, CK94 March 636 FV Oceanus, CK94 1 April 499 FV Oceanus, CK94 7 April 1 4 FV Oceanus, CK94 14 April 92 FV Oceanus, CK94 21 April 622 FV Oceanus, CK94 29 April 535 FV Oceanus, CK94 5 May 288 FV Oceanus, CK94 data were often skewed, gamma and Weibull, as well as Gaussian distributions, were fitted as appropriate. Cohort growth rates were estimated from regressions of modal length increase against time. The concentration of larvae (number m 3 ) by cohort at each station was estimated from the numbers of larvae caught and the water volume filtered. The volume filtered during each tow was derived from the flow-meter records using flume-tank calibrations described in Brander et al. (1993) and Nash et al. (1998). To generate estimates of the total number of larvae in the estuary on a particular date, the volume of water in each sampling box (Figure 3) was required. This was estimated by digitising the bathymetry of the estuary from Admiralty charts (numbers 1183, 3741 and 1975) to yield a three dimensional model. For each sampling time and location, tidal height was derived using TideCalc v1.1 (NP158, Ministry of Defence Hydrographic Office, Taunton, UK) and the estimated volume of water in the sampling box at the time of sampling estimated using the volume integration function in Surfer v6 (Golden Software Inc., Colorado, USA). Considered over the whole estuary, data on herring larval concentrations were usually highly skewed. Data transformation failed to improve normality suggesting that variance estimates based on guassian distributions would not be appropriate. As an alternative, the quartile larval concentrations (weighted by the volume of the sampling box) were generated for each sampling date. These values were then raised by the total water volume in the estuary to yield a point estimate and range for the total numbers of larvae in each cohort. Instantaneous loss rates of larvae from the study area were determined as the slope of the linear regression of the logarithmic decline of larval numbers in each cohort against time. The estimated date of hatch of each cohort was derived by solving the linear regressions of modal length increase for 8. mm (the modal length for newly hatched, laboratory reared Blackwater herring larvae, C. F., unpublished data). The total number of yolk-sac larvae hatched in each cohort was then estimated by solving, for the estimated hatch date, the linear regressions of the logarithmic decline in larval numbers against time. Since cohorts could often only be tracked for two or three weeks, it was not possible to generate confidence intervals around the estimate of numbers of larvae hatched. Data on SSB and subsequent recruitment at age 2 were taken from the most recent available Virtual Population Analysis for the stock (Darby and Flatman, 1994; CEFAS 1999, unpublished data).

5 754 C. J. Fox Results A summary of the survey coverage is given in Table 1 whilst a full description and maps of larval herring concentrations can be found in Fox et al. (1999). In general, the water volumes sampled were between m 3 on each tow. In 1994, large numbers of yolk-sac larvae were recorded on 14 and 29 March and 19 April. In 1996, yolk-sac larvae were recorded on 28 March, 3 April, April and 11 May and, in 1997, yolk-sac larvae were found in large numbers on 18 March, 7 and 21 April. Large numbers of yolk-sac larvae were not present in the surveys of the week preceding these dates so they probably represented cohorts which had recently hatched. It was assumed that cohorts had hatched over 1 2 d as reported by Dempsey and Bamber (1983) and that they could subsequently be tracked by decomposition of the length frequency data (Figures 4 6). Observed changes in cohort modal length and cohort numbers with time are shown in Figures 7 9. Increases in modal length varied between.9 mm d 1 and.26 mm d 1 (Table 3) whilst instantaneous loss rates were estimated at between.8 d 1 and.27 d 1 (Table 4). Estimates of hatch dates and the numbers of yolk-sac larval production are presented in Table 5. Because of poor weather, locations outside of site I could not be sampled on 29 March 1994 but large numbers of herring larvae were caught at this location (Fox et al., 1999). Further larvae may have been present offshore and since the second cohort of 1994 was first detected on this date, the abundance of this cohort may have been underestimated. The results of the VPA undertaken in 1999 for this stock (Table 6) indicate that the SSB was considerably higher in the 199s than in 1979 and that the age structure was less skewed towards younger fish. Estimated levels of larval production for 1994, 1996 and 1997 were all greater than in 1979 (Figure 1). However, these increased levels of larval production did not lead to correspondingly strong year classes as measured by the number of recruits at age 2 (Table 6 and Figure 11). Discussion Analysis of herring stocks worldwide shows that most exhibit a compensatory pattern in their stockrecruitment relationships (Cushing, 1973; Ulltang, 198; Rosenberg and Doyle, 1986; Winters and Wheeler, 1987; Cushing, 1992; Zheng, 1996). This is generally taken to indicate the existence of density-dependent controls on recruitment such that strong recruitment is suppressed when the spawning stock biomass is high. In addition, data for individual years are usually widely scattered about the mean relationship. This may be interpreted as the influence of density-independent processes although some of the variance may be generated by age-lengthfecundity and spawning duration effects not taken into account when using spawning stock biomass as a proxy for egg production (Lambert, 1987; Heath and Richardson, 1989; Lambert, 199; Zheng, 1996). The Blackwater stock is typical of these patterns having a Ricker-type relationship implying a level of densitydependent control leading to over-compensation (Figure 2). It has often been suggested that density-dependence in herring operates at the egg stage since the substrates they require for spawning may be limited in area (Wood, 1981; Zheng, 1996; Iles and Beverton, 2). When the spawning stock biomass is high, eggs may be deposited in thick layers leading to anoxia and reduced hatching success. This has been demonstrated for Pacific herring (Clupea harengus pallasii) but does not appear to be a common occurrence in Atlantic herring (Taylor, 1971; Alderdice and Hourston, 1985; Stratoudakis et al., 1998). Where the extent of the spawning substrate is not limited, it has been shown that it is the extent of the spawning patches which increases with spawning stock size, rather than the thickness of the egg layers (Johannessen, 1986). Herring spawn has been shown to attract predators and a density-dependent effect could operate (Tibbo et al., 1963; Hempel and Hempel, 1971; Johannessen, 198; Rankine and Morrison, 1989). Similarly, incoming spawners may cannibalise eggs deposited earlier in the season and this might have more impact when the spawning stock biomass is high (Haegele and Schweigert, 1985; Stocker et al., 1985; Winters and Wheeler, 1987). If strong density dependence does operate at the egg stage, it should be apparent in the relationship between larval production and spawning stock size (Rosenberg and Doyle, 1986). Based upon larval surveys in the Clyde, Saville et al. (1974) did find reduced larval production at the highest levels of spawning stock biomass. However, they suggested this might be peculiar to the Clyde where the extent of suitable spawning habitat is limited. In the Blackwater, estimated production of larvae in the years studied appeared to be linearly related to spawning stock size. There are clearly problems associated with the use of mortality corrections to estimate numbers of larvae hatched but the above conclusion holds even if one considers larval production based upon the numbers of yolk-sac larvae actually sampled (Table 6). Although the number of years of data available are limited, evidence of strong density-dependent mechanisms operating at the egg stage was not apparent. Year-class strength is the result of both densitydependent and density-independent processes and it is difficult to disentangle the two (Heath and Richardson, 1989). Several studies have shown that densityindependent processes operating at the egg stage contribute significantly to inter-annual variability in this

6 Recent trends in stock-recruitment of Blackwater herring March March March Number of larvae measured April April April April May Estimated live length (mm) Figure 4. Herring larval length frequency plots for stock. Heath and Richardson (1989) reported that out of seven Atlantic herring populations studied, the Blackwater stock exhibited the greatest densityindependent survival variance between spawning biomass and recruitment to the spawning stock. This was attributed to the shallow, estuarine spawning location increasing the vulnerability of the eggs to storm damage. Such an event occurred in 1967 and led to almost complete recruitment failure in that year (Wood, 1981). However, such catastrophic failures at the egg stage are exceptional and probably play a limited role in the overall stock dynamics (Houde, 1989). The resulting recruitments from the years studied here were not clear outliers from the Ricker fit (Figure 2) so, although such

7 756 C. J. Fox 1 28 March April April 1996 Number of larvae measured April April April Cohort 4 11 May Estimated live length (mm) Figure 5. Herring larval length frequency plots for a pattern could have arisen due to environmental conditions, it seems more likely that density-dependent mechanisms operating afer hatching were predominant in these years. Considering larval growth and mortality, increased avoidance of the sampling gear by larger larvae could bias results (Brander and Thompson, 1989). However, similar gears were used in both Henderson et al. (1984) and the present study so the results should be comparable. Henderson et al. (1984) reported that the growth of yolk-sac larvae averaged.17 mm d 1 increasing to.43 mm d 1 for the post yolk-sac stage. Estimates of growth rates from the present study appeared similar given that the cohorts could only be tracked for a week or two after yolk-sac absorption. However, similar cohort growth rates do not necessarily indicate that the population was growing equally well in both years since the estimates may be biased by selective mortality of slow growing larvae. Henderson et al. (1984) also reported the loss rate, averaged over the two cohorts tracked, as.68 d 1. The instantaneous loss rates of early stage herring larvae during the present surveys appeared much higher. Loss rates calculated in this way include advection of larvae out of the study region. In 1979 sampling extended further offshore than the present study but few larvae

8 Recent trends in stock-recruitment of Blackwater herring March March April 1997 Number of larvae measured April April April April Estimated live length (mm) Figure 6. Herring larval length frequency plots for were caught in this region. Henderson et al. (1984) therefore considered that their loss rates were essentially equal to mortality rates. Subsequent hydrographic modelling indicated that, following hatching, up to 3% of larvae could be dispersed out of the more restricted sampling area used in the present study (Fox and Aldridge, 2). After correcting for these losses, mortality rates from the present study were still higher than reported from 1979 (Table 4). High mortality rates immediately following hatching will not necessarily lead to poor subsequent recruitment. A small reduction in the mortality rates during later stages would still have the potential to generate a strong year class (Cushing, 1974; Houde, 1987, 1989; Bailey, 2). However, it can be concluded that the main controls of year-class strength for Blackwater herring in the years studied were density dependent (or possibly environmental processes) operating between hatching and recruitment at age 2, as opposed to processes operating at the egg stage. The possible mechanisms for generating densitydependent mortality post-hatching will now be considered. Cannabalism of larvae has frequently been cited as a compensatory mechanism for cod stocks (Jarre-Teichmann et al., 2). Whether cannabalism occurs in herring is unclear although fish larvae have been found in the stomachs of North Sea herring

9 758 C. J. Fox Estimated live length (mm) /3 (a) 8/3 15/3 Cohort growth in /3 29/3 5/4 12/4 19/4 26/4 3/5 1/5 Estimated live length (mm) /3 (a) 22/3 Cohort growth in /3 5/4 12/4 19/4 26/4 3/5 1/5 Date Date Loge of estimated number of larvae in estuary (b) 1/3 8/3 15/3 Cohort mortality /3 29/3 5/4 Date 12/4 19/4 26/4 3/5 1/5 Figure 7. Cohort growth (a) and mortality (b) for Vertical bars in (a) indicate the inter-quartile range. Loge of estimated number of larvae in estuary /3 (b) 22/3 29/3 Cohort mortality /4 12/4 Date 19/4 26/4 3/5 1/5 Figure 9. Cohort growth (a) and mortality (b) for Vertical bars in (a) indicate the inter-quartile range. Estimated live length (mm) Loge of estimated number of larvae in estuary / /3 (a) (b) 27/3 27/3 3/4 3/4 Cohort growth in /4 Cohort mortality /4 17/4 Date 17/4 Date 24/4 24/4 1/5 1/5 8/5 8/5 15/5 15/5 Figure 8. Cohort growth (a) and mortality (b) for Vertical bars in (a) indicate the inter-quartile range. (Garrod and Harding, 1981). Compensation could also arise if predators were attracted to concentrations of larvae. Although herring spawn has been shown to attract cod (Gadus morhua) and haddock (Melanogrammus aeglefinus), the behaviour of these predators in relation to larval density does not appear to have been investigated (Johannessen, 198). Density-dependent predation by invertebrates, such as ctenophores, on fish larvae seems less credible given their modes of feeding and the fact that fish larvae only constitute a small fraction of the zooplankton community (Bailey and Houde, 1989). Mechanisms invoking shortage of prey imply that the density and consumption rates of larvae can be sufficiently great that prey abundance is reduced to the point where the larvae suffer reduced growth or even starvation. Several studies have examined this but have failed to demonstrate significant impacts on prey abundance, even when the whole ichthyoplantkon community was considered (Cushing, 1983; Alderdice and Hourston, 1985; McGurk et al., 1993; Pepin and Penney, 2). Other field studies have reported the occurrence of larvae in poor nutritional condition but this has usually been linked to the bottom-up control of prey production rather than larval feeding pressure (Hewitt et al., 1985; Frank and McRuer, 1989; Chícharo et al., 1997). Evidence to support density-dependent growth and mortality at the larval stage is therefore limited although several authors have argued strongly

10 Recent trends in stock-recruitment of Blackwater herring 759 Table 2. Distributions fitted to length frequency data. Year Date Cohort Fit Mode Mean s.d. Shape Scale Number of larvae March 1 Weibull March 1 Gaussian March 2 Weibull April 2 Weibull April 2 Gamma April 2 Gaussian April 3 Gaussian April 3 Gaussian May 3 Weibull March 1 Weibull April 1 Guassian April 2 Gaussian April 2 Weibull April 2 Weibull April 3 Gamma April 3 Gaussian May 3 Gaussian May 4 Gaussian March 1 Weibull March 1 Weibull April 1 Gaussian April 2 Gaussian April 2 Weibull April 2 Gaussian April 2 Gamma April 3 Gamma April 3 Gamma that such effects should operate at this time (Iles, 198; Shepherd and Cushing, 198; Horwood et al., 2). An alternative suggestion is that density-dependent mechanisms operate in the period when fish concentrate (Iles and Beverton, 2). Such an effect has been invoked for flatfish where the settling juveniles are typically constrained to shallow nursery grounds. For clupeoids, shoaling begins around metamorphosis and Table 3. Regressions of cohort modal length against day of year. Year Cohort a b Average growth rate s.d. (mm day 1 ) Where cohort modal length (mm)=a+b day of year. could possibly generate density-dependent local food depletion. Any reduction in growth rate would increase the time juveniles are exposured to predators during this vulnerable phase (Gallego and Heath, 1994). Table 4. Regressions of log e total numbers of larvae in estuary with time. Year Cohort a b Average daily loss rate s.d. Average mortality rate NA Where numbers of larvae in estuary=e (a+b day of year). Average loss rate for 1996 excludes cohort 3. Average mortality rate=average loss rate corrected for estimated daily loss of.3 due to advection from the sampling area (Fox and Aldridge, 2).

11 76 C. J. Fox Table 5. Estimated yolk-sac larval production. Year Cohort Estimated numbers of larvae when first detected Estimated hatch date Estimated yolk-sac larval production at hatch March March April Total March April April NA Total March April April Total The results presented here suggest that the overall shape of the stock-recruit curve for Blackwater herring is determined by density-dependent mechanisms acting at some stage after hatching. Evidence for strong Estimated larval production ( 1 9 ) Spawning stock biomass (tonnes) Figure 1. Larval production against spawning stock biomass. density-dependent controls at the egg stage was not found. This conclusion is however based upon data from a limited number of years and validation will require further egg and larval surveys. Since year-class strength results from the combined effect of density-dependent and independent factors, studies which address both issues simultaneously across a number of years will be needed to improve our understanding of the controlling Table 6. Comparison of potential and field-derived larval production estimates. Stock structure data are from the 1999, Virtual Population Analysis (CEFAS, Unpublished data). Year Numbers in stock at the start of the year by age from VPA ( 1 3 ) Total Spawning stock biomass at time of spawning by age (tonnes) Total Field derived larval production 1 (no larval mortality correction) Field derived larval production 1 9 (with larval mortality correction) Resulting recruits at start of year at age 2 ( 1 3 ) Recruits age 2/Larval production

12 Recent trends in stock-recruitment of Blackwater herring 761 Survival between hatching and recruits at age 2 (%) mechanisms (Shepherd and Cushing, 198; Bailey and Houde, 1989). Acknowledgements The present study was funded by MAFF under program MF42, Physical and Biological Controls on Fish Stocks. The author wishes to thank the skippers of FV Gill and Oceanus namely, Reuben Frost, Graham Baker, Tim Cook and the late John Frost for all their help and enthusiasm in undertaking the often arduous sampling program. Also thanks to the plankton sorting team at CEFAS Lowestoft for their hard work in sorting the samples, to Mr Phil Large (CEFAS) for discussions on the Blackwater herring assessments, to Dr M Basson, Mr J. Nichols, Dr J. Horwood and two anonymous referees for their constructive comments on this manuscript. References Estimated larval production ( 1 9 ) Figure 11. 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