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Fig. 30. Median as a function of maximum larval length.
111


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13


Recent issues in this series

31. Evidence of Nearshore Summer Upwelling Off ‘Atlanile City, New Jersey. By Merton Ingham and James =
Eberwine. November 1984. iii + 10 Ps 5 figs. NTIS Access. No. PB85-150290. a ane

32. Secondary Production of Benthic Macrofauna: at ‘Three Stations of Delaware Bay and Coastal Delaware.
By Stavros Howe and Wayne Leathem. November 1984. ix + 62 P. 6 figs., 191 tables. NTIS Access. No. PB8S-
1457S3/AS. . . - ‘

33. MARMAP Surveys of the Continental Shelf from Cape Hatteras, North Caroline, t6 Cape Sable, Nova
Scotia (1977-1983). Atlas No. 1. Summary of Operations. By John D. Sibunka and Myron J Silverman,
November 1984. vii + 306/p., 52 figs., 2 tables. NTIS Access. No, PB85- 150985/AS. .

% 34, Oceanology: Biology of the Ocean. Volume 2. Biological Productivity of the Ocean. ByM E. Vinogtadov,
. editor in chief. First printed by Nauka Press, Moscow, 1977. Translated from the Russian by AlbertL. ‘Peabody. :
January 1985. x + 518 p., 81 figs., 59 tables. NTIS Access. No. PBE5- 204683/AS. " 28

35. Annual NEMP Report on the Health of the Northeast Coastal Waters, 1982, By John B. Peirce, Carl R.
Berman, and Marlene R. Rosen, eds., and Robert N. Reid (benthos), Catherine E. Warsh (water quality), and
Edith Gould (biological effects), topic coords. January 1985. xi + 68 Pa 29 2) Ties. 5 tables. NTIS Access. No.
PB85-219129/AS.

36. Growth and Survival of Larval Fishes in Relation to the Trophodynamics of Georges Bank Cod and  ~ 5
Haddock. By Geoffrey C. Laurence and R. Gregory Lough. Janvary 1985. xvi + 150 p., 67 fies. 1S tables, / = > ¢
lapp. NTIS Access. No. PB85-220093/AS. e . . .

37. Regional Action Plan. By Bruce E. Higgins, Ruth Rehfus, John B. Pearce, Robert. J Pawlowski, Robert
L. Lippson, Timothy Goodger, Susan Mello Roe, and Douglas W. Beach. April 1985. ix + +84 AP ”Afigs» 6tables,
2 ~ 9app. NTIS Access. No. PB85-219962/AS.

38. The Shelf/Stope Front South of Nantucket Shoals and Georges Bank as Delineated by Satellite Infrared _
Imagery and Shipboard Hydrographic and Plankton Observations. By J. B. Colton, Jr., J. L. Anderson, J. E.
O.Reilly, C.A. Evans-Zetlin, and H.G. Marshall. May 1985. vi + 22 p., 14 figs. NTIS Access. No. PBBS-221083.

39. USA Historical Catch Data, 1904-82, for Major Georges Bank Fisheries. By Anne M. T. Lange a and Joan
E. Palmer. May 1985. iii + 21 p., 12 figs., 2 tables. NTIS Access. No. PB85- 233948/AS.

40. Indexing the Economic Health of the U.S. Fishing Industry’s Harvesting Sector. By Virgil J ‘Norton,
Morton M. Miller, and Elizabeth Kenney. May’ 1985. v + 42 p., 44 figs., 25 tables, 1 app. NTIS Access. No.
PB85-217958/AS.

41. Calculation of Standing Stocks and Energetic Requirements of the Cotaceans of the Northeast United -
States Outer Continental Shelf. By Robert D. Kenney, Martin A.M. Hyman, and Howard E. Winn. May 1985.

iv + 99 p., 1 fig., 5 tables, 1 app. NTIS Access. No. PBE5- 239937/AS. . ee

42. Status of the Fishery Resources Off the Northeastern United States for. + 1985, By Conservation &
Utilization Division, Northeast Fisheries Center. August 1985. iii + 137 Po 46 figs. 49 tables. (NTIS Access...”
No. PB86-125473/AS. : 7 .

43. Status of the Fishery Resources Off the Northeastern United States for 1986. By ‘Conservation &
Utilization Division, Northeast Fisheries Center, September 1986, iii + + 130e» 45 figs. 48 tables. NTIS Access.
No. PB87-122115/AS.

(continued on inside backcover)



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Fig. 26. Median as a function of mean of spawning curve using sand ecl parameters.

107


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ICHTHYOPLANKTON SURVEYS: A STRATEGY FOR MONITORING
FISHERIES CHANGE IN A LARGE MARINE ECOSYSTEM

Kenneth Sherman

National Marine Fisheries Service
Northeast Fisheries Center
Narragansett Laboratory
Narragansett, RI 02882-1199

Large marine ecosystems are extensive areas of the globe, encompassing: ap-
proximately 200,000 km?, or more, within the Exclusive Economic Zones of coastal nations
in which biological communities have evolved together in response to unique bathymetry,
hydrography, and circulation (Sherman and Alexander, 1986). The biomass of fish stocks
inhabiting large marine ecosystems (LME’s) in the North Atlantic have been altered sig-
nificantly, particularly since the 1960’s, resulting in negative economic impact to fishing in-
terests on both sides of the Atlantic. The fluctuations in fish biomass within LME’s have
been of sufficient magnitude to result in species "flips" from positions of dominance to
subordinate positions, in less than a decade, within several ecosystems around the rim of
the Atlantic Ocean. A biomass flip occurs when the population of a dominant species
rapidly drops to a very low level and is replaced by another species. In the North Sea
ecosystem, where Atlantic herring (Clupea harengus) was a major component of the
fisheries yield, the catch fluctuated between 600,000-800,000 metric tons (mt) from the
1920’s through the early 1960’s. Atlantic herring catches reached a peak of one million
tons in 1965 followed by a biomass flip to a subordinate position in the North Sea ecosys-
tem between 1965 and 1970. Catches in 1975 were less than 50,000 mt, and the North Sea
herring fishery was closed in 1977. It took 5 years (until 1982) for the stock to rebuild to a
level where a small quota could be allowed. A similar decline occurred in Atlantic mack-
erel (Scomber scombrus). By 1980, the catch of Atlantic herring and Atlantic mackerel con-
tributed only a fraction of their long-term average yield. During the period of pelagic
decline, the biomass of bottom fish flipped upward, including haddock (Melanogrammus
aeglefinus) and Atlantic cod (Gadus morhua), along with the catch of small, fast-growing
industrial fish such as sand eel (Ammodytes spp.), Norway pout (Trisopterus esmarkii), and
sprat (Clupea sprattus) (Fig. 1).

Off the northeast coast of the United States, a similar biomass flip has been ob-
served. Between the mid 1960’s and 1970's, the biomass of the fishable stocks of cod, had-
dock, flounders, Atlantic herring, and mackerel all declined by just over 50%, from a level
of approximately 8 million metric tons (mmt) to less than 4 mmt (Fig. 2). During this
period, the population of sand eel exploded from less than a few hundred thousand tons to
over 1 mmt, constituting a large-scale biomass flip in the Northwest Atlantic. The spawn-
ing stock biomass for Atlantic herring on Georges Bank reached a peak of approximately
1.2 mmt in 1967 and plummeted over the next 10 years to a complete collapse of the com-
mercial fishery in 1977. During the years 1972 to 1981 surveys of ichthyoplankton on
Georges Bank revealed a decline from 2,000x10° Atlantic herring larvae to fewer than
5x10” Atlantic herring larvae on the Bank.

Sand eel, Atlantic herring, and Atlantic mackerel inhabit, at least for part of the
year, the same areas on Georges Bank and the Southern New England continental shelf.
Evidence of Atlantic herring predation on sand ecl and mackerel predation on the early
developmental stages of both Atlantic herring and sand ecl has becn observed within the
Northeast Continental Shelf ecosystem (Maurer, 1976). It is hypothesized that, in the ab-

3


Table 1. Summary statistics for Georges Bank and Southern New England yellowtail
flounder stocks. All values are log..

° - “ Egg Survey n
Region Year TrawlIndex Population Estimate Ink
Georges Bank - - 1979 1.74 17.88 16.14
oe 1980 2.16 : 17.37 15.21
1981 1.94 17.96 . 16.02
1982 1.73 17.54 15.80 |
Average Lo 189 17.69 15.79
Standard Error 10 14: 21
Southern New 1979 2.40 19.13 16.73
England. 1980 2.48 18.63 16.15
. 1981 2.86 18.36 15.50
1982 3.22 * 19.57 16.35
Average 2.74 18.92 16.18
Standard Error 19 .27 26
Average of both regions 15.99
Standard Error 17

116


Colton, J. B., Jr., and J. L. Anderson. 1983. Residual drift and residence time of Georges
Bank surface waters with reference to the distribution, transport, and survival of Jar-
val fishes. _MARMAP Contribution MED/NEFC 82-10. NOAA Tech. Mem.
NMFS-F/NEC-24. 44 pp.

Colton, J. B., Jr. J. R. Green, R. R. Byron, and J. L. Frisella. 1980. Bongo net retention
rates as effected by towing speed and mesh size. Can. J. Fish. Aquat. Sci. 37:606-
623. :

Colton, J. B., W. G. Smith, AW. Kendall, P. Berrien, and M. P. Fahay. 1979. Principal
spawning areas and times of marine fishes, Cape Sable to Cape Hatteras. Fish.
Bull., U.S. 76:911-915.

Davis, C. S. 1987. Components of the zooplankton production cycle in the temperate
ocean. J. Mar. Res. 45:947-983.

Evans, C. A., J. E. O’Reilly, and J. P. Thomas. 1987. A handbook for the measurement of
chlorophyll a and primary production. Biomass Scientific Ser. No. 8. SCAR/SCOR
and NOAA/NMFS. Texas A&M Univ., College Station, TX. 114 pp.

Fahay, M. P. 1983. Guide to the early stages of marine fishes occurring in. the western
North Atlantic Ocean, Cape Hatteras to the Southern Scotian Shelf. J. Northw. Atl.
Fish. Sci. 4:423 pp.

Fahay, M. P. 1987. Larval and juvenile hakes (Phycis-Urophycis sp.) examined during a
study of the white hake, Urophycis tenuis (Mitchell), in the Georges Bank-Gulf of
Maine area. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Sandy Hook Lab.
Ref. No. 87-03. 22 pp.

Fahay, M. P., and P. Berrien. 1981. Preliminary description of larval tilefish Lopholatilus
chamaeleonticeps. Rapp. P.-v. Reun: Cons. int. Explor Mer 178:600-602.

Fahay, M. P., and D. F. Markle. 1984. Gadiformes: Development and relationships, pp.
265-283. In H. G. Moser, W. J. Richards, D. M. Cohen, M. P. Fahay, A. W. Ken-
dall, Jr., and S. L. Richardson (Eds.) Ontogeny and systematics of fishes. Am. Soc.
Ichthyol. Herpetol. Spec. Publ. No. 1:760 pp.

Goulet, J. 1981. Information resource management for MARMAP ccosystems research.
Proceedings of the Federal Information Processing Council of New England Con-
ference. Woods Hole, 23-24 April 1981. - :

Goulet, J. R, Jr. 1985. Data management for analysis of large marine ecosystems. ICES
C.M. 1985/L:1.

Goulet, J. R., Jr., J. K. Sailor, J. K. Berry, and K. Sherman. 1981. Computer-assisted map
analysis and marine ecosystem information. pp. 264-272. Jn Procecdings of Oceans
81 Conference, Sept. 1981. Mar. Technol.

Green, J. 1981. Aspects of Calanus finmarchicus trophadynamics in the arca of high larval
haddock abundance in spring on Georges Bank. ICES C.M. 1981/L:32.

Green, J. R. 1983. Seasonal zooplankton standing stock, and dominant spcecics abundance
in continental shelf waters in and near the area potentially influenced by dumping at

122


2.0 (SD = 0.15). The regression coefficients for two species (summer flounder and yellow-
tail flounder, Limanda ‘ferruginea) were significantly different than 2.0. It is not clear from
this analysis why their coefficients are different and additional study is needed to deter-
mine if the logarithmic transformation of their catch data is appropriate. For the remain-
ing taxa the appropriate transformation to normalize the catch frequencies is to convert to
logarithms (Elliot, 1971).

With the present MARMAP sampling intensity of 25 to 50 stations per subarea,
most taxa have a coefficient of variation between 35 and 55%. At a sample size of 50 sta-
tions the mean coefficient of variation for all 19 taxa is 40.7%, which would decrease to
28.8% if sample size was 100. For 50 stations the coefficient ranged from a low of 33.2 for
Gulfstream flounder, Citharichthys arctifrons, to a high of 54.6 for the lanternfish, Ceratos-
copelus maderensis. A combined plot of the coefficients of variation for all 19 taxa for
sample sizes 25, 50, 75, and 100 stations is shown in Fig. 1. Plots of In mean vs. In variances
for each of the 19 taxa are shown in Fig. 2.

. The correlation matrices for silver hake and haddock are shown in Table 2. Of the
110 correlations calculated for both species, only 11 are significantly different than zero at
P >0.01 and an additional 7 at P >0.05. An examination of Table 2 reveals that of the 18
significant correlations, 11 occur between adjacent length intervals and all are positive.
Only two negative correlations, both for haddock, are significant and are between 4-mm
catches and 11-mm and 12-mm catches. The overall pattern of correlation of catches be-
tween lengths indicates, at least for the simulation model of Hauser et al. (this volume)
that the selection of the coefficient of variation as an input parameter need not integrate a
function to account for autocorrelation of catches by length.

LITERATURE CITED

Bliss, C. I, and R. A. Fisher. 1953. Fitting the binomial distribution to biological data and
a note on the efficient fitting of the negative binomial. Biometrics 9:176-200.

Elliot, J..M. 1971. Some methods for the statistical analysis of samples of benthic inver-
tebrates. Freshwater Biol. Assoc. Spec. Publ. No. 25:148 pp.

Hauser, J. W., M. P. Sissenwine, and W. W. Morse. This volume. A model to evaluate
spawning stock size estimates derived from larval abundance.

Pennington, M. P. 1983. Efficient estimators of abundance, for fish and plankton surveys.
iometrics 39:281-286.

Sibunka, J. D., and M. J. Silverman. 1984. MARMAP surveys of the continental shelf
from Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). At-
las No. 1, Summary of operations. NOAA Tech. Mem. NMFS-F/NEC-33. 306 pp.

Taylor, L. R. 1961. Aggregation, variance, and the mean. Nature, Lond. 189:732-735.

62


For purposes of this report, ichthyoplankton listings of larval abundance for the
1977-1983 time period were compared with combined spring and autumn
trawl survey results from 1977-1984." Spearman’s Rank Correlation, a nonparametric test
for association (see Sokal and Rohlf, 1981), was used to calculate a coefficient of rank cor-
relation for the top 20 taxa from the two data sets in the Middle. Atlantic, Southern New
England, Georges Bank and Gulf of Maine subareas (Fig. 1). A nonsignificant or zero,
rank correlation is interpreted as meaning the data sets are complementary, i.e., they
provide information about different components of the finfish community. On the.other

and, a positive correlation would not necessarily indicate that the data sets are redundant
as the analysis only considers mean abundance. The top 20 taxa account for 76-99% of the
total stratified mean catch by weight and 87-95% of total stratified mean number in the
trawl survey data base for the 8-year-period, and 78-89% of the mean larval abundance for
the 7-year ichthyoplankton data set.

RESULTS

Results of the ranking test show that the two data bases were not correlated, or had
negative correlations, indicating that they were complementary. The principal taxa on the
trawl listing are different, or occur in significantly different order than those taxa repre-
sented as larvae in the ichthyoplankton list. Whereas dogfish (Squalus acanthias) and
skates (Rajidae), taxa of known high biomass, occur on trawl listings for all four subareas,
they do not occur in the ichthyoplankton data set simply because of their reproductive
strategies. Conversely, economically and ecologically important species. such as; bluefish
(Pomatomus saltatrix) and anchovies (Engraulidae) rank high on the ichthyoplankton list-
ings for the Southern New England and Middle Atlantic subareas, respectively, but they do
not appear on the trawl listing for either subarea. Finally, the sand eel (Ammodytes spp.), a
species with an estimated spawning biomass of about 1 million metric tons (mmt) (Morse,
1982), and the dominant taxon on the ichthyoplankton data set for three of the four sub-
areas, occurs near the end of the trawl listing for only the Middle Atlantic subarea. In
point of fact, half, or less, of the 20 principal taxa are common to both listings in each sub-
area (Table 1). Given these differences, the non-parametric ranking test produced the ex-
pected results. It showed no positive correlations between trawl listings of stratified mean
weight tow” and ichthyoplankton listings of mean number of larvae 10 m“* surface area in
any of the four subareas (Fig. 2). Comparison of stratified mean numbers of fish tow”
from the trawl surveys and larval abundance estimates produced like results. Conversely,
correlations from comparison of spring and autumn trawl surveys (stratified mean weight
tow”) for the 8-year time period are significant to highly significant in 3 of the 4 subareas.
Only in the Middle Atlantic subarea are the twice-yearly survey results uncorrelated.
Within-year comparison of stratified mean number towTM from the trawl produced. sig-
nificant positive correlations in the Gulf of Maine and on Georges Bank but not in the
Southern New England and Middle Atlantic subaréas. .

DISCUSSION

Emphasis in fisheries recruitment research has shifted from studies of single species
to a'‘community approach which considers ecosystems and multispecies interactions that af-
fect fish production at different trophic levels (Sherman et al., 1983). The NEFC trawl. and
ichthyoplankton surveys provide the foundation for this new approach in coastal waters off
the northeastern United States. - .

Surveys of fish eggs and larvae have been shown to represent an effective sampling
strategy for estimating interannual variability in multispecies fish communities (Pennington
and Berrien, 1982; Stauffer and Charter, 1982). The NEFC trawl! surveys, through their

20


LOG SUMMED LARVAE/DAY

0.S

T - 1 T T T T
22.5 25.0 27.5 30.0 32.5 35.0 37.5 40.0 42.5
AGE (DAYS)

Fig. 10. Logarithms of age frequencics summed over all cruises.

91


unit of area to be converted into an estimate of spawner biomass for those species with
pelagic eggs. A cohort model was developed to estimate the proportion of finfish biomass
which is immature. This model was used to scale up spawner biomass estimates. An addi-
tional adjustment was made to take account of species with non-pelagic eggs. In the case
of sand eel the spawner biomass is based on back-calculated larva abundance. For others
(e.g., dogfish; skates [Rajidae]; squid [Cephalopoda]; redfish [Sebastes spp.]; and river
herrings [Alosa spp.]) the amount added is based on methods of Clark and Brown (1977).

METHODS

Planktonic fish egg collections used in estimating spawner biomass and total popula:
tion biomass reported in this paper are made during surveys conducted between Nova
Scotia and Cape Hatteras (Fig. 1). The area was covered in full or in part six to eight times
per year for the 1979 to 1984 reporting period. Each full survey included approximately
175 plankton sampling stations. Plankton sampling procedures are outlined in Smith and
Goulet (this volume) and described in detail by Sibunka and Silverman (1984).

All fish eggs are removed from samples.

For each station, the catch is adjusted to
become the number of eggs sampled per 10 m~ of sea surface area using the following
relationship:

xj = 10 C; (dij) , (69)

2 at station i

where x; = number of eggs sampled per 10 m:

C; = catch of eggs at station i,

d; = maximum sampling depth at station i,

v, = volume (m) of water strained by the net at station i, and

i = the ith station of the non-zero catch series 1, wh.

The expected density (per unit area, E(C)) of eggs caught during a survey is a func-
tion of the biomass of spawners (B) which produce pelagic eggs, the average number of
eggs spawned per unit weight of spawners, both sexes combined (F), the mortality rate of

eggs (Z), their development time to hatching (t), and the area (A) and period of time (T)
sampled by the survey:

E(C) = ( FBe2tdty/AT
fo)
= (FB[I-e2")yAZT. (2)

If the sample mean catch per unit area (C) is substituted for E(C), and equation (1)
is solved for spawner biomass:

B= (CAZTB)/(F[1-e'2")) (3)

27


tion of yellowtail flounder larvae was similar to haddock. Georges Bank produced the
most larvae during 1977-1981, but in 1982 the Middle Atlantic Bight subarea had very high
production and in 1983 Southern New England dominated.

Yearly production within a subarea often varies between 1 and 2 orders of mag-
nitude, particularly in those subareas that are not the dominant producers. - This is not
surprising due to the effects of larval drift and the method of calculating production. Lar-
val drift will move larvae into adjacent subareas, i.e., into subareas where they were not
spawned, and, because these larvae are often relatively large, the mortality adjusted abun-

lances are inflated in subareas where spawning is light. For example, calculated haddock
production in Southern New England for 1983 is quite high, though the production of
recently-hatched larvae (3-6 mm) is highest on Georges Bank. Therefore, some caution is
needed when interpreting larval production as presented by subarea.

The total annual production index (see Table 2) summed over all subareas appears
to be a better indicator of spawning biomass than either the individual subarea production
indexes or the unadjusted for mortality catch per 10 m*. The unadjusted abundances do
not take account of the effects of mortality which is an unrealistic approach when larval
abundance is related to spawner biomass.

LITERATURE CITED

Campbell, J. W., and J. E. O’Reilly. In press. Role of satellites in estimating primary
productivity on the Northwest Atlantic Continental Shelf. Continental Shelf Res.

Cushing, D. H. 1975. Marine ecology and fisheries. Cambridge Univ. Press, Cambridge.

78 pp.

Hauser, J. W., M. P. Sissenwine, and W. W. Morse. This volume. A model to evaluate
~ . ‘spawning stock size estimates derived from larval abundance.

Sherman, K. 1986. Measurement strategies for monitoring and forecasting variability in
large marine ecosystems. pp. 203-231. In K. Sherman and L. M. Alexander (Eds.)
‘Variability and management of large marine ecosystems. AAAS Selected: Sym-
posium 99, Westview Press, Boulder, CO. 319 pp.

Sibunka, J. D., and M. J. Silverman. 1984. MARMAP surveys of the continental shelf

from Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). At-
las No. 1. Summary of operations. NOAA Tech. Mem. NMFS-F/NEC-33. 306 pp.

§2


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23


Table 2 (continued).

Species Year GOM GB SNE MAB

Engraulidae 1977 » 6645.4 104424.4
1978 11949.6 _83291.6
1979 182785.1 54411.1
1980 4373.2 31330.9
1981 1024.6 83409.9
1982 4809.4 14399.1
1983 10204.0 3122.4

55



CALCULATED EGGS/DAY

0.0

T 1 T 7 sa 1
700.0 750.0 800.0 950.0 900.0 950.0 1000.0 1050.0 1100.0 1150.¢

DAY

Fig. 11. Back-calculated eggs spawned compared to original spawning curve.

92


of absolute abundance since:significant sources of potential bias exist for both estimators.

Collie and Sissenwine (1983) estimated the catchability coefficient of the survey
trawl for yellowtail. flounder on Georges Bank and in Southern New England using com-
mercial catch statistics. Specifically, they assume: .

Zy= qPp

where q is the catchability coefficient of the survey, that is, q = I/k. Table 2 gives their es-
timates:of q and.estimates based on the egg surveys. It is seen that the estimates of q are
nearly the same for Georges Bank, but are markedly different for Southern New England.
This implies, because the information provided by the trawl surveys is used similarly in
both methods (Pennington, 1986), that the population estimates of the Georges Bank stock
are nearly identical and the Collie-Sissenwine estimates for Southern New England are ap-
proximately one-third of the egg based stock size estimates. This discrepancy may be due
to bias in the egg estimates or inaccuracies in the catch data.

It should be noted that the lack of a significant difference between the estimates of
In k for the two regions implies that the relative difference in the average trawl survey in-
dex is not significantly different from the relative difference in the average population es-
timates given by the egg surveys (Table 1). That is, both fishery-independent surveys gen-
erate similar estimates of the mean relative difference in population between the two
areas.

Likewise, if k (or q) is the same in both areas (and if the assumptions made are
valid) then the combined plot of In P, vs. In Z, (from Table 1) would be linear with slope
equal to one. Fig. 2 shows the plot off the estimates from the two regions. The estimated
slope of 1.1 is not significantly different from one.

Even though the amount of egg data is at present limited, it is evident that the
population estimates based on the plankton surveys can provide an important verification
of the consistency of the trawl survey index. For example, the adjustment factors (last
column in Table 1) display no major trends over time, which gives further support to the
assumption that the (smoothed) trawl survey index is proportional to the actual population.
Thus, if combined, the two types of surveys can provide the basis for generating a timely
fishery-independent estimate of absolute abundance and also provide population estimates
for the entire trawl survey period. This is especially important for a species such as yellow-
tail flounder, for which VPA estimates of abundance are not yet available.

LITERATURE CITED

Azarovitz, T. 1981. A brief historical review of the Woods Hole Laboratory Trawl Survey
Time Series. In: W. G. Doubleday and D. Rivard (Ed.). Bottom trawl surveys.
Can. Spec. Publ. Fish. Aquat. Sci. 58:62-67.

Berrien, P., and J. Sibunka. 1987. Yellowtail flounder, Limanda ferruginea, total annual
“8 production and population biomass estimates for northeast U.S. waters, 1979-
1982. (Unpublished ms.

Berrien, P., W. Morse, and M. Pennington. 1984. Recent estimates of adult spawning

stock biomass off the northeast United States from MARMAP ichthyoplankton sur-
veys. NOAA Tech. Mem. NMFS-F/NEC-30. 111 pp.

114


Lassiter, R. R. 1962. Life histo: aspects of the bluefish, Pomatomus saltatrix (Linnaeus),
from the coast of North Carolina. M.S. Thesis, N. C. State College, Raleigh. 103

Pp. :

Laurence, G. C., and W. i. Howell. 1981. Embryology and influence of temperature and
salinity on early development and survival of yellowtail flounder Limanda feruginea.
Mar. Ecol. Prog. Ser..6:11-18.

Lockwood, S. J., J. H. Nichols, and W. A. Dawson. 1981. The estimation of a mackerel
eine sgombrus L.) spawning stock size by plankton survey. J. Plank. Res.
. 3217-233. .

Mari, A., and I. Ramos. 1979. Fecundity of silver hake on the Scotian Shelf. ICNAF Res.
Doc. 79/VI/66.

Merriner, J. V. 1976. Aspects of the reproductive biology of the weakfish, Cynoscion
regalis (Sciaenidae), in North Carolina. Fish. Bull., U.S. 74:18-26.

Merriner, J. V., and J. L. LaRoche. 1977. Fecundity of the northern puffer, © Sphoeroides
maculatus, from Chesapeake Bay. Ches. Sci. 18(1):81-84.

Morse, W. W. 1980a. Spawning and fecundity of Atlantic mackerel, Scomber scombrus, in
the Middle Atlantic Bight. Fish. Bull., U.S. 78:103-108.

Morse, W. W. 1980b. Maturity, spawning and fecundity of Atlantic croaker, —_ Micro-
Re ones wndulatus, occurring north of Cape Hatteras, North Carolina. Fish. Bull.,

Morse, W. W. 1981. Reproduction of the summer flounder, Paralichthys dentatus. J. Fish.
Biol. 19:189-203.

Mountain, D. G. 1985. A review of MARMAP hydrographic sampling. MARMAP Con-
tribution No. FED/NEFC 85-24. Unpubl. ms.

Parker, K. 1980. A direct method for.estimating northern anchovy, Engraulis mordax,
spawning biomass. Fish. Bull., U.S. 78:541-544.

Parrish, J. D. 1975. Marine trophic interactions by dynamic simulation of fish species.
Fish. Bull., U.S, 73:695-716.

Parrish, B. B., and A. Saville. 1962. The estimation of fishing mortality rate for bank
spawners, from larval abundance data. ICES C.M. 1960, Doc. No. 40 (mimeo).

Pearson, J.C. 1929. Natural history and conservation of redfish and other commercial
sciaenids on the Texas coast. Bull. U. S. Bur. Fish. 44:129-214.

Pennington, M. P. 1983. Efficient estimators of abundance, for fish and plankton surveys.
iometrics 39:281-286. .

Picquelle, S. J., and R. P. Hewitt. 1983. The northern anchovy spawning biomass for the
1982-83 California fishing season. CalCOFI Rep. 24:16-28.

33


where TIME is the development time in days
TEMP is the water temperature ‘in degrees centigrade.

The larval growth rate is used in the formula:
L2=L1*EXP(Q)
where Q is the growth rate
L2 is the length of the larvae on a given day
L1 is the length of the larvae on the preceding day.
The growth rate (Fig. 4) is determined from the formula:

Q-QMAX*(KI*EXP[R1M{T-T1}])/(1.0+K1*[EXP{R1*(T-T1)}-1.0])

where R1_ - = (1.0/[T2-T1})*LN([K2*{1.0-K1}]/[K1*{1.0-K2}})
QM. = the maximum growth rate
T = the environmental temperature
Tl = the lower threshold temperature
Ki = the growth rate multiplier near the lower threshold
T2 = the upper threshold temperature :
K2 = the growth rate multiplier near the upper threshold

(Thornton and Lessem, 1978). The input constants are species specific.

In the second module, the date of the first cruise is selected randomly for each of -
the one hundred simulations. The target date of subsequent cruises is evenly spaced from
this date using the target cruise interval specified as an input parameter.

The simulated population of eggs and larvae is sampled according to the cruise
schedule. Each cruise samples organisms from age 0 up to the maximum age vulnerable to
sampling (AMAX). The spawning date of these cohorts ranges from the date of the cruise
to AMAX days prior to the cruise (Fig. 5).

Cruises which do not sample eggs or larvae (they are either before the spawning
period or more than AMAX days after the spawning period) are eliminated from further
consideration.

Fig. 6 shows larval length vs. age for various cruises. The various curves reflect the
various temperature regimes during egg development and larval growth. Fig. 7 shows lar-
val abundance vs. length for various cruises. The shapes of the various curves reflect the
relation of the cruise date to the spawning curve. Early in the spawning period small larvae
are well represented while toward the end of the spawning period larger larvae receive bet-
ter representation. .

The estimation of the number of eggs spawned requires that each length category
represented in the simulated sample of larvae be assigned an age. The ages are assigned
using the same temperature-dependent egg development time and larval growth rate func-
tions and the temperature regime described above. If these functions apply exactly, con-
verting from age to length and then back to age does not introduce an error. But the
model allows for anomalies from these functions (as described below). These anomalies
are not taken account of in the estimation module of the model (because they are not
_ observable). Therefore, they contribute to uncertainty in the estimates. Fig. 8 gives an

15


ABSOLUTE ABUNDANCE ESTIMATES.USING TRAWL AND
ICHTHYOPLANKTON SURVEY DATA

1. Summary statistics for Georges Bank and Southern New England

yellowtail flounder stocks... ee 6 ee ee

2. Estimates of the catchability coefficients (q) of the trawl survey
for yellowtail flounder based on egg surveys (ES) and Collie and

Sissenwine method (CS). 2... ee ee

LIST.OF FIGURES

ICHTHYOPLANKTON SURVEYS: A STRATEGY FOR MONITORING
FISHERIES CHANGE IN A LARGE MARINE ECOSYSTEM

1. Estimated changes i in the biomass of fishes in the North Sea,

1960-1976, with simulated yield and biomass projections to 1980. ... ,

2. Decline in the Fishable biomass of Georges Bank, Gulf of Maine, and
: Southern.New England between 1968 and 1975.

MARMAP ICHTHYOPLANKTON SURVEYS: AN OVERVIEW OF
METHODS AND DATA BASE MANAGEMENT.

1. Standard station plan and four subareas for NEFC ichthyoplankton
surveys.

2. Concéptual data base design for MEDBIM.............

3. Actual data base design for MEDBIM.

A COMPARISON OF INFORMATION CONTENT FROM TRAWL AND
ICHTHYOPLANKTON SURVEYS

1. Standard station plan-and-four subareas for NEFC ichthyoplankton

SUIVEYS., Se

2. Comparison of principal taxa from NEFC trawl (1977-1984) and
:,. ichthyoplankton (1977-1983) surveys in four subareas off the

‘ northeastern United States, using pearman ’s Rank Correlation. . , ,

USE OF EGG DATA TO ESTIMATE TOTAL FINFISH BIOMASS FOR THE

NORTHEAST CONTINENTAL SHELF ECOSYSTEM

1. Total survey area and subarea boundaries... . 2... 2... ee

Page

Page


a EXECUTIVE SUMMARY

4
4

\ /

~ The Northeast Fisheries Center has conducted ‘standardized ichthyoplankton sur-
veys of the Northeast Continental Shelf ecosystem for about a decade. Fhi§ report
describes an evaluation of the surveys to determine their usefulness, the uniqueness of the
information they provide, and the relationship between the quality of results and the survey
effort.

Broadscale, long-term, fishery-independent surveys are needed to monitor large
marine ecosystems. The abundance, distribution, and specics composition of the finfish
community are very dynamic. Changes in the finfish community may be caused by fluctua-
tions in the natural environment and pollution, or they may be biologically regulated (e.g.,
predation, including fishing). Ichthyoplankton surveys are a useful means of monitoring
these changes Since environmental variables and indices of production at lower trophic
levels are monitored simultaneously, these surveys help to distinguish between the poten-

tial causes of population change.

Ichthyoplankton surveys sample virtually all of the finfish (exceptions are sharks and
skates) that Spawn on the continental shelf. Lists of the dominant species collected during
ichthyoplankton surveys are compared to analogous lists from trawl surveys. These lists
are uncorrelated, which implies that the two sources of information are complementary.
Several species of economic (e.g., Atlantic herring, Clupea harengus, and Atlantic mack-
erel, Scomber scombrus) and ecological (e.g., sand eel, Ammodytes spp., and Gulf Stream
flounder, Citharichthys arctifrons) importance are better represented in ichthyoplankton
surveys than trawl surveys.

In order to use ichthyoplankton abundance to estimate spawning biomass, several
biological parameters must be estimated. These include Jarval growth rate and an annual
mortality rate per unit time. But, an index which is proportional to spawning biomass can
be calculated using an estimate of mortality rate per unit length pooled over several years.
The index can be calculated for most of the species collected during ichthyoplankton sur-
veys. The index is given for haddock (Melanogrammus aeglefinus), Atlantic herring, Atlan-
tic cod (Gadus morhua), silver hake (Merluccius bilinearis), hakes of the genus Urophycis,
and anchovies (Engraulidae), The pooled mortality rates per unit length are given for 15
additional species.

Ichthyoplankton data are used to estimate total finfish biomass. Total finfish
biomass estimates are ecologically important in order to quantify total energy flow which
relates to the role predation and competition play in regulating recruitment and multi-
species production potential. A time series of total finfish biomass estimates will allow
testing of the hypothesis that fishing affects species composition, but that total biomass is
relatively robust to exploitation. Methods of estimating total biomass from trawl surveys
are reasonably good for the principal demersal species, but they are suspect for pelagics
and lightly exploited species.

Ichthyoplankton estimates of total finfish spawning biomass are based on a model
that assumes that: (a) the number of eggs spawned is proportional to biomass of mature
fish; (b) egg development time is a function of temperature; (c) egg mortality rate is 10%

er day (the results are robust to this assumption); and (d) samples of egg abundance can
be treated as random in time and space. A simple cohort model is devcloped in order to
estimate the ratio of spawning biomass to immature biomass. Biomass estimates for
species that do not have pelagic eggs or larvae (e.g., sharks, skates) are based on trawl sur-
veys.

iii

Preceding page blank |


The age at which the mature biomass has diminished to 5% of its peak is:

t, = ([log.{0.05}}/g,) + t, (8)

The ratio of immature to mature biomass (X) is derived by dividing equation (5) by
equation (6). The sensitivity of X, g, and t, to g, and t, is given in Table 3.

For the northeast region, maturity is typically at age two or three and most of the
biomass has perished by age 10 or less. Therefore, it is reasonable to expect that the imma-
ture biomass is at least 45% of the mature biomass. To estimate total biomass, the mature
biomass estimated from ichthyoplankton data should be multiplied by 1.45.

RESULTS

Subarea values of daily egg. production are plotted (Figs. 3-6) along with accumu-
lated values over the total survey area (Fig. 7). These graphs of egg production show that
finfish spawning is at a minimum level during November through March, increases during
April to June or July with a seasonal peak during June, July or August then declines in
August to October.

Annual egg production estimates for 1979 to 1984 are listed by subarea and for the
total survey area (Table 4). These values are annually integrated totals, or areas beneath
the curves noted above. The Gulf of Maine consistently produced the fewest eggs over the
six years examined. Although Georges Bank exhibited some of the highest egg densities,
Southern New England and Middle Atlantic waters produced more eggs because of the
larger size of these subareas.

Annual spawner biomass estimates, derived primarily from egg data and ranging
from 3.6 to 5.9 mmt, are provided along with total finfish population biomass estimates of
5.3 to 8.6 mmt (Table 4 and Fig. 8). These estimates are compared directly to similar stock
estimates given by Conservation and Utilization Division, NEFC (1985).

DISCUSSION

Previous estimates of total finfish biomass off the northeastern United States were
based on a combination of trawl survey and commercial fisheres data (Clark and Brown,
1977; Conservation and Utilization Div., NEFC, 1985). While the methodology may be
reasonable for the principal demersal species which are vulnerable to a bottom trawl it is
less appropriate for pelagic and other unexploited species. Advantages of an
ichthyoplankton-based estimate are that it is useful for all species with pelagic eggs or
larvae, it is fishery independent and does not depend on the use of landing statistics. Fur-
thermore it includes species not vulnerable to the otter trawl.

Resulting estimates provided here appear to be relatively stable between years, and
the magnitude of the fishery resource appears to be greater than that reported by Clark
and Brown (1977) and Conservation and Utilization Division, NEFC, (1985).

Fecundity values found in the literature and used in this paper represent results of
several research efforts. With such a variety of studies and methodologies it follows that
there may be inconsistencies between, and systematic problems among, the various studies,
which in turn may have biased our population estimates. For cxample, if there is a

30


MARMAP sampling intensity and as input into computer simulations of spawning stock
assessment, applying the backcalculation method to larval catch data (Hauser et al., this
volume).

The population coefficient of variation, as an estimate of variability and uncertainty
of each of the catch data, may be applied in the computer simulation to all length intervals
without change, or may be randomly assigned for indiyidual lengths, or sets of length inter-
vals. The question is, are the abundances (No./10 m“) of individual lengths (mm) corre-
lated between stations within a cruise such that the coefficient of variation should not be
randomly selected for each length? If autocorrelation does occur between lengths, the
election of the coefficient of variation in the simulation should account for the degree of
association indicated by the correlations. An analysis of this association is presented.

METHODS

A total of 50 MARMAP-. ichthyoplankton surveys made from 1977 to 1984 were
used in this analysis (Sibunka and Silverman, 1984). Each survey was divided into four
subareas, each subarea cgntains a maximum.of 60 stations. Within each subarea, the mean
catch of larvae per 10 m“.and its variance were calculated for each of 19 taxa. Pennington
(1983) applied the Delta distribution to fish egg and larval catches from MARMAP surveys
to derive an efficient estimate of the variance for the mean when zero and nonzero tows
are included in the calculation. His methods were used to calculate the means and
variances of the larval catches. If.the subarea contained less than 20 stations or the target
taxon was present in less than 5 stations, the subarea was not included in the analysis. The
means and variances were converted to logarithms (In) and a least squares-regression was
calculated to estimate a common slope (b) and intercept (a) for each taxon (Elliot, 1971).

The sampling coefficient of variation was calculated as:
(Vanay + 100

where n equals the number of stations sampled. Coefficients of variation were calculated
for n equals 25, 50, 75, and 100. :

Regressions were calculated by subarea for six taxa to determine if between-subarea
differences could be detected in the underlying frequency distributions. No significant dif-
ference (P <0.05) was found between subarea regressions within taxa; therefore, subareas
were combined to calculate the common regression for each taxon.

Correlation matrices were calculated for silver hake, Merluccius bilinearis, and had-
dock, Melanogrammus aeglefinus, to measure the association in the abundance of catchgs at
length within each station. Input to the calculation was the abundance (No./J0 m*). at
length (3-14 mm) at each station where the target species was captured. A matrix of Pear-
son product-moment correlations was calculated for all combinations of lengths for each
species. :

RESULTS AND DISCUSSION
The results of the regression analysis and the coefficients of variation for various

sampling intensities are listed in Table 1. The slopes (b) range from 1.6 for summer
flounder, Paralichthys dentatus, to 2.3 for Benthosema glaciale and the average for all taxa is

61


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NOAA Technical Memorandum NMFS-F/NEC-57

An Analysis and Evaluation oe

of Ichthyoplankton Survey Data pan |
from the Northeast Continental

Shelf Ecosystem

U.S. DEPARTMENT OF COMMERCE :
National Oceanic and Atmospheric Administration _.
National Marine Fisheries Service ~

Northeast Fisheries Center
Woods Hole, Massachusetts -

Aug ust 1988

, REPRODUCED BY
; U.S. DEPARTMENT OF COMMERCE

| NATIONAL TECHNICAL INFORMATION SERVICE
SPRINGFIELD, VA. 22161



CALCULATED/INPUT EGGS SPAWNED

LEGEND
O = SAMPLING COEFFICIENT OF VARIATION = 0%
O = SAMPLING COEFFICIENT OF VARIATION = 50%

4

na

L

100.0 150.0 200.0 250.0 300.0 350.0 400.0
L

PERCENT STANDARD DEVIATION

0.0 50.0

30.035.0 40.0 45.0 $0.0 $5.0 60.0 65.0 70.0 75.0 80.0 3.0 90.0 95.0
DAYS BETWEEN CRUISES

Fig. 15. Haddock percent standard deviation as a function of days betwcen cruises.

96


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119




CALCULATED/INPUT EGGS SPAWNED

LEGEND
O- SAMPLING COEFFICIENT OF VARIATION = 0%
= O = SAMPLING COEFFICIENT OF VARIATION - 50%

MEDIAN
ut

T 7 T T T T T T r 1 T 1
30.035.0 40.0 45.0 50.0 5.0 60.0 65.0 70.0 75.0 80.0 85.0 90.0: 95.0
DAYS BETWEEN CRUISES

Fig. 16. Haddock median as a‘function of days between cruises.

97


MS - Master Station (2 and 1 repeated)
<->>(msns)
NS - Net Sampling (4 and 3 repeated)

ZB - Zooplankton Biomass (4 sub-schema and subset)
<-(zpns)
<->>(mszp)
| ZP- Zooplankton (5)
<-(zsns)
<->>(mSzs)
ZS - Zooplankton Stage (6 subset and restructured)

LL - Larval Length (8 and 7.repeated)
EG - Egg (9)
DT - Depth Temperature (10 subset and sub-schema)
BS - Bottle Sampling (10 sub-schema):,
SS - Sub-Station (11)
PL - Plankton (12)
Key: A
<->>(aabb)
B USE MEDSFT:AABB builds a join of one

Ato many B for all records in both
data sets.

A

<-(bbaa) -
B USE MEDSFT:BBAA builds a join of one

A to many B for the current B

selection set.

Fig. 3. Actual data base design for MEDBIM. The bold face indicates data sets that are
currently implemented. The conceptual design has been modified for case of user access.

18


LO is the hatching length oe : Bee :
MO is the mortality rate for larvae at hatching length wi
MD is the rate at which the mortality decreases with length.

While 100 simulations are normally run and summarized, ‘this number can be al-
tered. When run for one simulation, diagnostic data and graphs can be produced: 3

Four statistics are, recorded’ concerning the 100 calculated mortality rates of the:100
simulations. These are the mean, the standard deviation, the minimum, and the maximum.
A larger number of statistics are recorded concerning the 100 ratios-of.calculated to. simu-
lated egg production. First the median, the mean, the standard deviation, the minimum,
the maximum, the lower 90% confidence bound, and the upper 90% confidence bound are
recorded. These are determined from an ordered table of results. Then:the natural
logarithms of the ratios are taken and the mean and standard deviation of the logarithms
are recorded. The antilog of the mean of the logarithms is calculated. The standard devia-
tion factor is calculated as the antilog of the standard. deviation of the logarithms. :A-value
of 1.0 is then: subtracted from the standard deviation factor and the result multiplied by 100
to estimate the percent standard deviation. The logarithmic’statistics are also used to-cal-
culate antilogarithmic values for the mean, standard deviation, lower 90% confidence
bound, and upper 90% confidence bound which are also recorded. Confidence bounds are
equal to the antilog of the mean of the logarithm multiplied or divided by the antilog of the
standard deviation of the logarithm raised to the power of the Z statistic for the confidence
level desired. : ~ . .

The large number of statistics is recorded for possible future use depending on the
probability distribution of the results of the simulations. If the ratios of estimated to simu-
lated eggs are not very variable, then their distribution might approximate normal. But for
the simulations of interest we expect the ratios to be quite variable. Their possible range.is
from zero to infinity. Therefore, they are likely to have a skewed distribution such as log-
‘normal. In this case the antilog of the mean of the logarithms is:a‘useful statistic. It is the
geometric mean and it is an estimate of the median (the value displayed inthe figures. that
-are given in the results), The median is a more suitable-statistic than the mean for skewed
distributions since it is less sensitive to-extreme values. The percent standard deviation is a
useful measure of precision (also displayed in the figures).. About two thirds of the ratios
are within the range of the estimated median times or divided by (1 + [percent. standard
deviation/100}). i

RESULTS AND DISCUSSION

Some examples of results. from exercising the model are shown in Figs. 13 through
30. Each point represents the percent standard ‘deviation or estimate of the median of 100
simulations. - :

Silver hake input parameters were used except where otherwise noted; haddock
parameters and sand cel parameters were used in some of the simulations. The only dif-
ference between species in these runs of the model was in their temperature-dependent
growth parameters and in their spawning curves.. The temperature-dependent growth
curves are shown in Fig. 4. Haddock has maximum spawning at 90 Julian days (spring) and
silver hake at 195 Julian days (summer). The standard deviations of the spawning curves
were 21 days for haddock and 36 days for silver hake.

_ Standard parameters were used except where otherwise noted. The present sam-
pling strategy consists, on the average, of six cruises per year, or 61 days between cruises.
tandard parameters were 61 days between cruises, a mortality rate of 0.1 per day, a

77


A MODEL TO EVALUATE SPAWNING STOCK SIZE
ESTIMATES DERIVED FROM LARVAL ABUNDANCE

_ John W. Hauser’, Michael P. Sissenwine', and Wallace W. Morse?

National Marine Fisheries Service
Northeast Fisheries Center

‘Woods Hole Laborato’
Woods Hole, MA 0254.

Sandy Hook Laboratory
Highlands, NJ 07732

AB STRACT

Larval fish abundance’ data. have been used ‘to back calculate estimates of ¢;
spawned and the spawning stock which produced them. This paper describes a simulation
-model designed to determine the accuracy and precision of estimates under various condi-
tions. The model simulates a population ofa specific species subject to the effect of en-
vironmental temperature, sampling, and the estimation procedure. Egg estimates were
compared to simulated egg production. The model can be used to examine the effects of
cruise frequency, number of samples per cruise, measurement and analysis techniques,
species growth characteristics, species spawning characteristics, and mortality rates.

-Preliminary results indicated that the standard deviation of the spawning curve is
the most important biological parameter with respect to precision. Estimates of eg 8B
production. are more precise for silver hake (Merluccius bilinearis) than haddoc!
(Melanogrammus aeglefinus); the former’s spawning curve has a larger standard deviation.
Both cruise frequency and within-cruise. sample size strongly influence precision and ac-
curacy. ‘The current sampling intensity appears minimally adequate.

INTRODUCTION

There are several approaches to estimating the abundance of fish populations
(Sissenwine et al., 1983). One approach uses data that characterizes the spatial and tem-
poral distribution "of larvae and their size composition (Berrien et al., 1984). The size com-
position data is used to estimate larval mortality rate and to adjust the density of larvae to
correspond to their density at hatching. These adjusted densities are integrated over time
and space to estimate production’ of larvae which’ presumably is proportional to ‘the
biomass of spawners.

The approach is based on numerous assumptions. It combines estimates derived at
different stages of the analysis. This makes it difficult to evaluate the accuracy and preci-
sion of spawning stock size estimates analytically, but a numerical approach is feasible.

This paper describes a Monte Carlo simulation model which is used to evaluate es-
timates. of spawning biomass.. The model relates precision and accuracy to sampling inten-
sity.” tt can be used to evaluate alternative estimation methods.

: ‘The paper describes preliminary results (model runs) for three important species off
the northeastern USA; haddock, silver hake, and sand eel (Ammodytes sp.) The model can
be used to draw more generic conclusions by varying the parameters.

72




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Ys 9ULTRUT JO SOF 0! 1 N uoHeqnsul [BIOL 2 “O14

(92) SYNIVYAdW3L NONVENONI =X

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IND189 S{UjOd sePUNOY, 1}94H0)0, O
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6
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10.0 15.0 20.0 25.0 30.0 35.0
1 m L L 1 1

EGG DEVELOPMENT TIME (DAYS)

5.0
L

0.0

T T 1
7.5

TT T
0.0 2.5 5.0 10.0 12.5 iS.0 17.5

TEMPERATURE (DEGREES C)

Fig. 3. Egg development time as a function of temperature.

84


Table 1. The results of the application of Taylor’s power law to the MARMAP larval fish
data. The slopes (b) and intercepts (a) were calculated by the equation Y = aX” where X
equals the mean catch per 10 m@ and Y equals its variance. 1“ = the coefficient of deter-
mination and Sy = the standard error of the slope. The coefficient of variation isgiven for
sample size (n). * = slope is significantly different than 2.00 (P >0.01).

Coefficient of Variation

Taxon b’ a 2 & n=25n=50_-n=75_ n=100
Herring 2.124 7.774 .994 0.110 55.8 39.4 32.2 27.9
Engraulidae 2.013 9.266 .971 0.076 60.9 43.0 35.1 30.4
C. maderensis 1.935 14.927 .940 0.041 713 546 446 38.6
-B. glaciale . 2.264 7.053 .956 0.118 53.1 37.6 30.7 26.6
Urophycis spp. ‘1.993 7.166 .985 0.034 53.5 37.9 30.9 26.8
Atlantic cod 2.025 6.621 .975 0.044 515 36.4 29.7 = 25.7
Haddock 2.062 7.023 .980 0.058 53.0 37.5 30.6 26.5
Pollock 1.950 7.889 .915 0.136 56.2 39.7 32.4 28.1
Offshore hake 1.988 9.792 ..972 0.101 62.6 443 36.1 © 313
Bluefish 2.113 6.421 .982 0.074 50.7 35.8 29.3 25.3
Atlantic croaker 2.065 9.157 .999 0.037 60.4 42.8 34:9 30.3
Atlantic mackerel 2.088 8.864 .985 0.073 59.5 42.1 344 298
Butterfish 1.895 7.373 .946 0.076 54.3 38.4 314 275
Redfishes 1.744 10.029 .947 0.103 63.3 44.8 366 31.7
Gulf Stream flounder 2.058 5.517 .972 0.061 47.0 33.2 27.1 23.5
Smallmouth flounder 1.913 8.425 .981 0.061 58.1 41.0 33.5 29.0
Summer flounder* 1.640 10.494 946 0.093 64.8 45.8 37.4- 32.4
American plaice 2.218 7.049 .956 0.213 53.1 37.5 30.7 26.6
Yellowtail flounder* 1.853 8.773. .973 0.050 59.2 41.9 342 29.6

63


ae

ATLANTIC
.

36

Fig. 1. Standard station plan and four subareas for NEFC ichthyoplankton surveys.
24


Table 1 (continued).

No. eggs per
Taxon gm of female Source
Solea solea 471 Houghton, Last and Bromley, 1985
Limanda ferruginea 2435.6 Howell and Kessler, 1977
Paralichthys dentatus 730 Morse, 1981 ;
Pseudopleuronectes americanus 1687 Bigelow and Schroeder, 1953
1850 X= 1586 Topp, 1968 .
1220 Saila, 1961
Glyptocephalus cynoglossus 310.5 Bowering, 1978
Hippoglossus hippoglossus 43 Bigelow and Schroeder, 1953
Centropnistis striata 223.4 Cupka-et al., 1973 :

Mean fecundity for 23 species = 720 per gm of female

36


CALCULATED/ INPUT EGGS SPANNED

LEGEND :
O = SAMPLING. COEFFICIENT OF. .VARIATION = 0%
S © = SAMPLING COEFFICIENT OF VARIATION = SOZ%

MEDIAN

1.5

0.5 1.0

0.0 $0.0 100.0 150.0 200.0 250.0 300.0 350.0
MEAN OF SPAWNING CURVE

Fig. 24, Mcdian as a function of mean of spawning curve using silver hake parameters:

105


WEN GULFLOF &
70° MAINE, ..?
§ at
is
a

!

© MISDLE $}
+ ATLANTIC fi

Fig. 1. Total survey area and subarea boundaries.
41


Pennington, M. 1983. Efficient estimators of abundance for fish and prankton surveys.
MARMAP Contribution MED/NEFC 81-9). Biometrics 39:281-2

Pennington, M. and P. Berrien. 1981. Measuring the effects of the variability of egg den-
sities over space and time on egg abundance estimates. ICES C.M. 1981/G:70.

Powers, K. D. 1980. How seabirds adapt to ocean processes. : Oceanus 26(1):11-18.

Powers, K. D. 1980. Pelagic distributions of marine birds-off the northeastern U.S.
‘NOAA Tech. Mem. NMFS-F/NEC-27. 285 pp.

Powers, K. D. 1982. A comparison of two methods of counting birds at sea. J. Ficld Or-
nith. 53:209-222.

Powers, K. D., and E. H. Backus. 1987. Energy transfer to seabirds. pp. 372-374. In R. H.
Backus (Ed.) Georges Bank. MIT Press, Cambridge: 632 pp.

Powers, K. D., and R..G. B. Brown. 1987. Seabirds. pp. 359- 371. In R.H. Backus (Ed.).
Georges Bank. MIT Press, Cambridge. 632 pp.

Powers, K. D., and J.. Cherry. 1983. Loon migrations’ off the coast of the northeastern
United States. Wilson Bull. 95:125-132.

Powers, K. D., and P. M. Payne. 1982. Ecological coherence of Georges Bank to popula-
tions of marine mammals. NOAA, Nat. Mar. Fish: Serv., Northeast Fish. Ctr.
Woods Hole Lab., Woods Hole, MA. Unpl. Rep.

Powers, K. D., and P. M. Payne. 1983. Distribution of marine mammals, birds and turtles
near the Deepwater Dumpsite 106 (DWD-106) and the Philadelphia Dumpsite
(PDS). pp. II-1-92. In J. B. Pearce, D. C. Miller, and C. Berman (Eds.) Northeast
monitorine program 106-mile site characterization update. NOAA Tech. Mem.
NMFS-F/NEC-26. 483 pp.

Powers, K. D., and W. T. Rumage. 1978.. Effect of the Argo Merchant oil spill on bird
populations off the New England coast, 15 Dec. 1976-Jan. 1977. pp. 142-148. In In
the Wake of the Argo. Merchant, Proceedings of a Symposium held 11-13 January

_ 1978. Center for Ocean Management Studies, Univ. Rhode Island, Kingston.

Powers, K. D., and.J. A. Van Os. 1979. A concentration of greater shearwaters in the
western North Atlantic. Am. Birds 33:253.

Powers, K. D., P. M. Payne, and S. J. Fitch. 1982. Distribution of cetaceans, seabirds and
turtles, Cape Hatteras to Nova Scotia, June 1980-December 1981. U.S. Dep. Com-
mer, NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Contract No. NA-81-FA-C-
00023. Woods Hole, MA. 165 pp.

Powers, K. D., P. M. Payne, and D. S. Miller. 1980. A marine mammal observer training
“program. U.S. Dep. Commer., NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr.
Contract No. NA-80-FA-D-0004, Woods Hole, MA. 73 pp.

Prezioso, J., and C. A. Griswold. 1981. Zooplankton community structure in the area of
the Ocean 250 gasoline spill. Lie 20-21. In Barge Ocean 250 gasoline spill. NOAA
Tech. Rep. NMFS SSRF 751. 30 pj

126


Table 2. Fish-egg species-composition of MARMAP I samples, 1979 and 1980.

Percent of total

Percent
Taxon standardized catch occurrence
GULF OF MAINE |
Scomber scombrus 29.61 8.02
Enchelyopus cimbrius 18.71 34.60
Urophycis sp. . 13.14 21.31
Melanogrammus aeglefinus 7.04 9.92
Hippoglossoides platessoides 5.93 14.35
Gadus morhua 4.06 17.72
Pollachius virens 3.76 _ 6.33
Merluccius bilinéaris © 3.64 14.77
Peprilus triacanthus 3.52 4.43
Tautogolabrus adspersus 3.12 5.91
Limanda ferruginea 2.98 9.70
Brosme brosme 2.57 21.73
Glyptocephalus cynoglossus gone 8.23
65
10 other taxa 0.35 0.21 to 2.95
100.00
GEORGES BANK
Gadus morhua 38.79 31.29
Urophycis sp. 29.89 26.07
Melanogrammus aeglefinus 9.37 23.93
Merlucctus bilinearis 7.95 25.15
Limanda ferruginea 4.54 28.22
Hippoglossina oblonga 2.01 12.58
Merluccius albidus 1.65 13.50
Citharichthys/Etropus 1.61 11.66
Scophthalmus aquosus 1.03 13.80
Scomber scombrus 0.93 9.1
97.77
26 other taxa 2.23 0.31 to 12.88
100.00

37


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66


example of the simulated abundance for each cohort (daily spawning group) within each
cruise. . : ae :

An estimate of mortality rate is obtained by summing the larval abundances over all
cruises for each: age interval (Fig. 9). The log of the summed abundance is taken and
plotted against the age (Fig. 10). The slope of the regression line gives the mortality rate.
This mortality rate is used to back calculate from larval abundances to abundances of eggs
spawned (Fig. 11).. In those cases where there are calculated egg spawning estimates for
the same time period from-two:cruises, the estimate based on the youngest larvae is used.
The area under the calculated spawning curve is compared to the area under the actual
spawning curve (Fig: 12). :

As described above, the only source of uncertainty in the estimate of the number of
-eggs spawned is due to the random date of the first cruise. In addition, random variability
may be applied to the.temperature, the spawning curve, the cruise dates, the egg and larval
mortality rates, the egg development rate, the larval growth rate, and the sampled larval
abundances. The mortality rates may be made temperature dependent, and the larval mor-
tality rate may be made:length dependent. The resolution at which the larvae are
measured. can ‘be altered as can other parameters specifying how the subsequent calcula-
tions are done. ‘ : : - - : :

The temperature may be subjected to a normally distributed variability with a stan-
dard deviation specified by the input. The same random variation applies for a certain
number of days and then a new random variation is generated; the number of days is
specified in the input. : .

The cruise dates may also be subjected to a normally distributed variability with a
standard deviation specified by the input.” A new variation applies to each cruise date.

.°,- » The initial spawning curve, the egg and larval mortality rates, the egg development
rate, and the larval growth rate may be subjected to random variability having a log normal
distribution.. For the log normal distributions, the variability is applied: in a. multiplicative
fashion rather than the additive fashion used with normally distributed random variability.
Thus the log normal random variability can never reduce the parameter to negative values.
The coefficient of variation is specified in the input: The same random variation applies
for a certain number of days and then a new random variation is generated; the number of
days is specified in the input. ‘

The sampied larval abundance data may be subjected to random variability to rep-
resent the variability caused by using a finite number of stations (samples) for each cruise.
This variability-is log normally distributed with a coefficient of variation specified by the
input. The same random variation may be applied to all length intervals of a cruise and
changed only for a new cruise; or the random variation may be changed for each cruise and
for sets of length intervals as specified in the input.

While constant egg and larval mortality rates are normally used, the mortality rates
may be linear functions of temperature. The jarval mortality rate may also be a function of
larval length according to the formula:

Se M=MO*EXP(-MD*{L-LO})
- “where L is the larval length :
M is the mortality rate for larvae.of length L

76


significant amount of unaccounted for resorption of eggs within the ovary which was
wrongly attributed to be part of the annual fecundity, then the reported fecundity value is
too high resulting in a reciprocal downward bias of the same magnitude in our spawner
biomass. estimate. Similarly, if an incorrect size threshold was applied in distinguishing
between yolked oocytes which would be spawned in the current year from smaller oocytes
to be spawned in future years, then the reported fecundity value will be biased and in turn
cause a reciprocal bias of the same magnitude in our estimate of spawners.

While we agree that our use of an assumed, extrinsically based, 10%-d"' ¢;
mortality rate, rather than an intrinsically based one, has undoubtedly caused some bias in
our results, we also feel that this bias is probably not profound. For example, halving the
mortality. rate used, to 5%d"', results in a reduction of 13.0% in the estimates provided
and increasing the mortality rate by half (to 15%-d"! per day) and doubling it (to 20%-d"')
result in increases of 10.8% and 19.5% respectively in the estimates of total eggs spawned.

Given additional species empirical egg mortality rates, we will be justified in future
attempts such as this to adjust the rates on perhaps a seasonal or geographic basis. For the
present, the 10%-d"' rate is sufficiently accurate to demonstrate the utility of the method
and illustrate population trends and levels noted above. Additional experimental
measurement of stage duration at varying incubation temperatures for a variety of species
would allow the determination of egg mortality rates for these same species. Therefore,
while acknowledging that there may be biases in our estimates of spawner and total
population biomass, it is important to note that the problems are not intractable. With
improved and increased observations of fecundity, incubation rates and mortality rates the
above-outlined method of estimating biomass can be improved. .

LITERATURE CITED

Ahlstrom, E. H. 1968. An evaluation of the fishery resources available to the California
fishermen. pp. 65-80. In D. Gilbert (ed.). The future of the fishing industry of the
United States. Univ. Wash. Publ. Fish., New Ser. 4.

Berrien, P. 1981. Yellowtail flounder, Limanda Geruainen. estimates of egg abundance
and population size during spring 1977 in Gulf of Maine, Georges Bank, southern
New England and Middle Atlantic Bight waters. ICES C.M. 1981/G:65.

Berrien, P. 1983. Silver hake, Merluccius bilinearis, og census and adult population
(umes for 1979 in waters off eastern United States. ICES C.M. 1983/G:46. 17 pp.
(mimeo).

Berrien, P. LN. A. Naplin, and M. R: Pennington. 1981. Atlantic mackerel, Scomber
scombrus, egg production and spawning population estimates for 1977 in the Gulf of
Maine, Georges Bank and Middle Atlantic Bight. Rapp. P.-v. Reun. Cons. int.
Explor. Mer 178:279-288.

Bigelow, H. B., and W. C. Schroeder. 1953. Fishes of the Gulf of Maine. Fish. Bull. Fish
and Wildl. Serv. 53(74):577 pp.

Bowering, W. R. 1978. Fecundity of witch flounder (Glyptocephalus cynoglossus) from St.

Pierre Bank and the Grand Bank of Newfoundland. J. Fish. Res. Board Can.
35(9):1199-1206.

31


Table 2. Estimates of the catchability coefficients (q) of the trawl survey for yellowtail
flounder based on egg surveys (ES) and Collie and Sissenwine method (C-S). .

95%

. Confidence
Method Region q (x10) . -< Interval (x10°6)
ES SNE 094 0.041 + 2.130...
cs SNE 313 0.189 - 0.437
ES GB 139 0.072° -- 0.267"
cs GB 107 0.061 = 0.153
ES GB & SNE: 114 ; 0.076 - 0.170%»

117


CALCULATED/INPUT EGGS SPAWNED

LEGEND
O = CRUISE INTERVAL = 30 DAYS
o- CRUISE INTERVAL - 61 DAYS
4 = CRUISE INTERVAL = 91 DAYS

11

1.0

0.0 10.0 20.0 30.0 40.0 50.0 80.0 70.0
SAMPLING COEFFICIENT OF VARIATION

Fig. 20. Haddock median as.a function of sampling coefficient of variation.

101


CALCULATED/ INPUT EGGS SPAWNED

LEGEND
O = SAMPLING COEFFICIENT OF VARIATION - 0%
O = SAMPLING COEFFICIENT OF VARIATION = SOZ

200.0 300.0 400.0 500.0 600.0 700.0
ch

“PERCENT STANDARD DEVIATION

100.0

0.0

1 T T 1 T T 7 T — ee
8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0
MAXIMUM LARVAL LENGTH

Fig. 29. Percent standard deviation as a function of maximum larval length.

110


Collie, J. S., and M. P. Sissenwine. 1983: Estimating population size from relative abun-
dance data measured with error. Can. J. Fish. Aquat. Sci. 40:1871-1879.

Pennington, M. 1985. Estimating the relative abundance of fish from a series of trawl sur-
veys. Biometrics 41:197-202.

Pennington, M. 1986. Some statistical techniques for estimating abundance indices from
trawl surveys. Fish. Bull., U.S. 84:519-525.

Sibunka, J., and. M. Silverman. 1984. MARMAP surveys of the continental shelf from
Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). Atlas No.
1, Summary of operations. NOAA. Tech. Mem. NMFS-F/NEC-33. 306 pp.

Smith, W. G., and J. Goulet. This volume. MARMAP ichthyoplankton surveys: An over-
view of methods and data base management.

115


IMO:
oe SE,

NATIONA,
0c,
ey

iS
0%

Y

Fe
a
E
ES

re

NOAA Technical Memorandum NMFS-F/NEC-57

This TM series is used for documentation and timely communication of
preliminary results. interim reports, or special purpose information, and
has not received complete formal review, editorial control, or detailed

editing.

An Analysis and Evaluation
of Ichthyoplankton Survey Data
from the Northeast Continental

Shelf Ecosystem

Wallace G. Smith, Editor
Sandy Hook Lab., National Marine Fisheries Serv:, Highlands, NJ. 07732

U.S. DEPARTMENT OF COMMERCE
C. William Verity, Secretary

National Oceanic and Atmospheric Administration
William E. Evans, Administrator

National Marine Fisheries Service
James W. Brennan, Assistant Administrator for Fisheries
Northeast Fisheries Center
Woods Hole, Massachusetts

August 1988


(continued from inside front cover)...
44. NOAA's Northeast Monitoring Program (NEMP); A Report on Progress of the First Five Years (1979-84) and
a Plan for the Future. By Robert N. Reid, Merton C. Ingham, and John B, Pearce, eds., and Catherine E. Warsh
(water quality), Robert N. Reid (sediments & bottom organisms), Adriana Y: Cantillo (tracé contaminants in
tissues), and Edith Gould (biological effects), topic coords. May 1987. xi +138 13 figs., 1 table,9 app. NTI
Access. No. PB87-210100. Che Sa BE ga 8 : oo

45. Food and Distribution of Juveniles of Seventeen Northwest Atlantic Fish Species, 1973-1976. By Ray E. .
Bowman, Thomas R. Azarovitz, Esther S. Howard, and Brian P. Hayden. May 1987. xi + 57 p., 10 figs.; 19 tables. “*
NTIS Access. No. PB87-215851/AS. ee : mo cad

46. Influence of Freshwater Inflows on Estuarine Productivity. ByJ ames G, Turek, Timothy E. Good;
E. Bigford, and John S. Nichols. May 1987. iii + 26 p. NTIS Access. No. PB87-213666/AS. .

. 47. MARMAP Surveys of the Continental Shelf from Cape Hatteras, North Carolina, to Cape Sable, Nova ‘Scotia
(1977-1984). Atlas No.2. Annual Distribution Patterns of Fish Larvae. By Wallace W. Morse, Michael P. Fahay,
and Wallace G. Smith. May 1987. viii + 215 p., 27 figs., 2 tables. NTIS Access. No. PB87-232831/AS.

48, Indexed Bibliography of the Bay Scallop (Argopecten irradians). By Barbara D. Sabo (Gibson) and Edwin
W. Rhodes. May 1987. iii + 85 p. NTIS Access. No. PB87-231411/AS. os _ Sol ys

49. Northeast Fisheries Center Framework for Inshore Research. By Research Planning & Coordination Staff,
Northeast Fisheries Center. July 1987.. vi + 44 p., 2 figs. 2 tables. NTIS Access. No. PB87-232286/AS. :

50. Status of the Fishery Resources Off the Northeastern United States for 1987. By Conservation & Utilization
Division, Northeast Fisheries Center. October 1987. iii + 132 p., 48 figs., 50 tables. NTIS Access. No. PB88-148549.

51. An Annotated List of the Fishes of Massachusetts Bay. By Bruce B. Collette and Karsten E. Hartel. February :
1988, x + 70 p., 1 fig. 1 table. NTIS Access. No. PB88-179247/AS. re Paes Sas

52. An Evaluation of the Bottom Traw! Survey Program of the Northeast Fisheries Center. By Survey Working :
Group, Northeast Fisheries Center., March 1988. ix + 83 p., 33 figs., 13 tables. NTIS Access.No. PB88-201983/
AS. : wer bee as os

53, Contaminants in Hudson-Raritan Estuary Water and Influence of Cold Storage upon Its Chemical Compo-.”'
sition. By Anthony Calabrese, Lawrence J. Buckley, and J. Christopher Powell. May 1988. vii + 37 p., 10 figs., 11
tables. NTIS Access. No. PB88-225628/AS. . ° cre Pee Ly .

54. Epizootic Ulcerative Syndromes in Coastal/Estuarine Fish. By Carl J, Sindermann. June 1988..y +37 p,8 :
figs. 1 table. : ‘ oe ee a

55. A Plan for Study: Response of the Habitat and Biota of the Inner New York Bight to Abatement of Sewage
Sludge Dumping. By Environmental Processes Division, Northeast Fisheries Center. iii.+ 34 p., 5.figs., 3 tables,
4 app. a aoe ; * -

56. Characterization of the Middle Atlantic Water Management Unit of the Northeast Regional Action Plan. By
Anthony L. Pacheco, Editor. July 1988. v + 322 p., 136 figs., 21 tables." : “wt

/33



CALCULATED/INPUT EGGS SPAWNED

LEGEND
OG = SAMPLING COEFFICIENT OF VARIATION = 0%

z O = SAMPLING COEFFICIENT OF VARIATION = SO%
a O71%
e
= vA
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Se ; was
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ial
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& 87
a © 20%
ue ;
wb
a 10% _—
3 a Ss cee .

30.035.0 40.0 45.0 50.0 55,0 80.0 65.0 70.0 7.0 90.0. 95.0 90.0 95.0
DAYS BETNEEN CRUISES

Fig. 13. Silver hake percent standard deviation as a function of days between cruises.

94


Table 2. Index of annual production of 3-mm larvae per 10 m? for six principal taxa by sub-
area and total annual production for all subareas combined (total x 10"). Subareas are
GOM = Gulf of Maine, GB = Georges Bank, SNE = Southern New England, and MAB =
Middle Atlantic Bight.

Species ‘Year GOM: GB SNE MAB Total
Atlanticcod 1977 527.9 12511.6 1521.5 151.4 6.831
‘ 1978 - 1110.0 3785.8 377.4 156.4 2.762
1979 1919.2 36646.1 653.2 602.1 18.090
1980 - 4133.1 — 19850.7 3408.6 98.6 13.708
1981 9311.3 21382.9 . 2998.2 1097.2 18.424
1982 3338.0 465.9 611.6 107.4 3.022
1983. 229.1 94966.3 2830.6 3.2 43.250
1984 91.3 6657.6 2459.6 280.2 4.604
Silverhake 1977 3697.2 155808.3 2566.7 1918.5 73.216
1978 18413.9 49941.0 1541.4 542.1 36.188
1979  10666.8 37568.4 2925.4 2363.8 27.149
1980 4457.3 16331.0 2216.0 2739.7 13.244
1981 6696.0 13765.1 2941.5 4265.8 15.059
1982 17587.2 335796.2 1299.2 4788.6 162.530
1983 1374.8 57191.5 9537.2 411.5 31.862
Haddock 1977 3645.8 9956.8 1861.4 8.063
1978 = 924.4 3773.0 26.0 2.322
1979 754.3 29309.0 3768.2 15.570
1980 1381.9 26790.8 3450.8 14.732
1981 1136.6 10014.2 421.7 5.431
1982 2445.9 191.8 84.0 1.885
1983 0.0 10031.9 70259.0 46.438
1984 15.4 4955.2 3960.2 4.542
Urophycis spp. 1977 5227.5 49519.8 119790.1 11524.6 103.814
1978 99.2 911.2 210173 3680.0 15.213
1979 829.8 10478.3 13540.1 1104.8 13.916
1980 | 2852.6 15561.9 55640.7 4266.2 44.643
1981 5937.3 5938.2 46587.5 10780.4 41.063
1982 1034.6 5560.5 16480.2 17054.8 23.049
1983 30288.8 14668.2 75182.5 970.8 73.656
Yellowtail, 1977 27993.2 9686.7 2368.1 19.391
flounder 1978 28980.0 8493.6 2655.7 19.276
1979 26748.5 13655.8 2999.7 21.596
1980 49519.4 42802.6 4006.8 49.562
1981 35064.0 31226.1 5563.8 37.246
1982 2898.2 19722.8 42904.2 38.273
1983 16719.4 724721 16223.5 60.207

54


Table 4. Annual egg production, spawner biomass, and total population biomass estimates,

1979-1984.
1979 1980 =: 1981 1982 1983 1984
Egg Production (x 10’)
: (coef. var. in parentheses)
Gulf of Maine 99.366 © 225.099- 105.662 201.757 96.816 103.950

(0.199) (0.259) (0.353) . (0.441)

Georges Bank 456.344. 414.628 295.964 129.029
(0.395) (0.294) —. (0.237) ~— (0.279)

So. New England 518.157 389.724 362.855 375.320
(0.199) (0.205) (0.157) (0.186)

Mid Atlantic 499.057 209.079 444,936 . 202.179
(0.180) (0.158) (0.212) (0.173)
Total Area 1,572.924 — 1,238.530 —1,209.417 * 908.285

(0.145) * (0.130) ” (0.112) 0.136)

(0.249) (0.332)

357.203 375.482
(0.357) (0.281)

455.620 409.929
(0.194) (0.170)

273.629 - 269.684
(0.300) (0.147)

1,183.269 1,159.045
(0.150) ° (0.118)

Plankton-based Spawner Biomass, includes sand ecl (MT)

Gulf of Maine . 293,468 626,701 349,256 521,365
Georges Bank 1,388,675 1,309,028 952,004 434,358
So. New England 1,457,993 1,527,518 1,393,509 1,186,325
Mid Atlantic 1,472,887 803,822 1,407,446 _ 683,765
Total Area 4,613,023 4,267,069 4,102,215 2,825,813
Total Population Biomass (MT)
Gulf of Maine 548,931 . 1,172,245 653,283 975,214
Georges Bank — 2,597,517 2,448,537 1,780,724 812,467
So. New England 2,727,176 2,857,222 2,606,559 2,219,020
Mid Atlantic 2,755,035 1,503,549 2,632,627 1,278,982
Total Area 8,628,659 7,981,553 7,673,193 5,285,683

310,970 328,034
1,116,648 1,171,024
1,468,361 1,385,498

914,524 906,489
3,810,502 3,791,045

581,669 613,588
2,088,690 2,190,401
2,746,568 2,591,574
1,710,617 1,695,588
7,127,544 7,091,150

40


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700.0: 750.0 800.0. 50:0 960-0. 950.6 - 1000:0 * 1080,0°- 1100.0 1180.0
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Fig. 8. Calculated larval frequencies by age category as a function of day spawned for
various cruises during the spawning season. ,

89 .


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14


MARMAP ICHTHYOPLANKTON SURVEYS: AN OVERVIEW OF METHODS
AND DATA BASE MANAGEMENT

Wallace G. Smith' and Julien Goulet?

National Marine Fisheries Service.
Northeast Fisheries Center °

‘Sandy Hook Laboratory
Highlands, NJ. 07732

Narragansett Laboratory
Narragansett, RI 02882-1199

ABSTRACT

Sampling methods and the data processing system designed to archive and retrieve
information are outlined for a decadal time series of ichthyoplankton surveys conducted in
coastal waters’ off the northeastern United States. These surveys, part of a broad-based
fishery ecology study at the. Northeast Fisheries Center, produced 25,000 plankton samples
for ichthyoplankton/zooplankton analysis from 1977 through 1987.

INTRODUCTION

The Northeast Fisheries Center (NEFC) recently completed the 11th consecutive
year of plankton survey in coastal waters off the northeastern United States as part of a
comprehensive fisheries ecosystem study designed to monitor changes in community struc-
ture within marine ecosystems (Sherman, this volume) and- investigate recruitment
mechanisms (Sherman, 1986). Surveys are conducted at monthly-to-bimonthly intervals
and cover the entire continental shelf from Cape Hatteras, North Carolina, to Cape Sable,
Nova Scotia--an area of some 260,000 km’. They provide-a description of the interannual
variability in temporal and spatial patterns of mesoscale distribution, abundance, produc-
tion, and mortality of fish eggs and larvae along with measurements and/or collections of
neuston, zooplankton, phytoplankton, chlorophyll a, temperature, and salinity. Seabird
and mammal census data are collected by personnel from Manomet Bird Observatory,
Manomet, Massachusetts. In addition to their contribution to NEFC’s recruitment initia-
tive, ichthyoplankton data are used to derive fishery-independent estimates of adult spawn-
ing biomass (Berrien et al., 1984; Berrien and Sissenwine, this volume). During the 11-year
period from 1977 through 1987 these surveys provided 25,000 bongo samples for
ichthyoplankton/zooplankton analysis (Table 1). :

SURVEY METHODS

Fish eggs and larvae are collected on two types of cruises: those dedicated to
broadscale plankton surveys; and those with a primary mission of assessing the distribution
and abundance of fish and mollusc populations using trawls, or dredges, respectively. Sta-
tion plans on plankton surveys remain largely unchanged between cruises. Sampling sites
are spaced at 8 to 18-km intervals along seven transects. Others are uniformly distributed
over the shelf at 25 to 35-km intervals. The survey area is sectioned into four subareas for °
analytical purposes (Fig. 1). Ichthyoplankton stations on trawl and dredge surveys are
selected from stratified random station plans and change with each survey (Grosslcin,
1969). Sampling intensity on these cooperative cruises in Jater winter/early spring, summer,
and early autumn is similar to that on plankton surveys.

10


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Fig. 12. Area under curve of back-calculated eggs spawned compared to original spawning
curve. . :

93


Sokal, R. R., and F. J. Rohlf. 1981. The Principles and Practice of Statistics in Biological
Research. 2nd Edition. W. H. Freeman and Co., N.Y. 859 pp.

Stauffer, G. D., and R. L. Charter. 1982. The northern anchovy spawning biomass for the
181-82 California fishing season. Calif. Coop. Oceanic Fish. Invest. Rep. 23: 15-
19.

MARMAP Contribution FED/NEC 87-01

22


CALCULATED/INPUT EGGS SPAWNED

LEGEND
O = SAMPLING COEFFICIENT OF VARIATION = 0%
a O = SAMPLING COEFFICIENT OF VARIATION = SOZ
8]
8]
Zz
Ey
8°]
=
8
8 |
3S
8
° T T T T T T
15.0 20.0 25.0 30.0 35.0 40.0 45.0 sc

STANDARD DEVIATION OF SPAWNING CURVE

Fig. 22. Median as a function of standard deviation of the spawning curve.

103


Morse, W., M. P. Fahay, and W. Smith. 1987. Surveys of the continental shelf from Cape
Hatteras, North Carolina, to Cape Sable, Nova Scotia, 1977-84. Atlas No. 2.
- Annual distribution patterns of fish larvae.. NOAA Tech.'Mem. NMFS-F/NEC-47.

215 pp. . 2

Morse, W. W., and J. W. Hauser. 1985. A study of factors affecting the precision of spawn-
ing stock estimates using MARMAP fish egg and larval surveys. NOAA, Nat. Mar.
Fish. Serv., Northeast Fish. Ctr. Sandy Hook Lab. Ref. No. 85-07. (MARMAP Con-
tribution No. FED/NEFC 85-12.)

Moser, H. G., W. J. Richards, D. M. Cohen, M. P. Fahay, A..W. Kendall, Jr., and S. L.
Richardson (Editors). 1984. Ontogeny and systematics of fishes. Am. Soc. Ich-
thyol. Herpetol. Spec. Publ. No. 1:i-ix + 760 pp. ot

Mountain, D. G., and E. B. Cohen. 1982. The effect of water residence time on the
plankton population levels. of Georges Bank. EOS, Trans. Am. Geophys. Union,
1982.. 63(3) (Abstract only). , .

Mountain, D., and E. Cohen. 1982. Biological implications of the Georges Bank physical
oceanography: EOS, Trans. Am. Geophys. Union, 1982. 63(18) (Abstract only).

Mountain, D. G., and E. B. Cohen. 1983. The effect of water residence time on the
piankton population Jevels on Georges Bank. ICES C.M. 1983/L:25.

Mountain; D. G., and. P. F. Jessen. 1983. Variations in the decp water of the Gulf of
Maine, 1979-1980. EOS, Trans. Am. Geophys. Union 1983.’ (Abstract only).

Naplin, N. A., and C. L. Obenchain. 1981. A description of eggs and early larvae of the
snake eel, Pisodonophis cruentifer (Ophichthidae), with comments on egg stages col-
lected in the plankton. Rapp. P.-v. Cons. Int. Explor. Mer 178:580-582.

Nickerson, S., and D. Mountain. 1983. Surface and bottom temperature and bottom
salinity distributions on the continental shelf, Cape Hatteras to Cape Sable from
MARMAP cruises, 1977-1982. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr.
Woods Hole Lab. Ref. Doc. 83-11. ‘ :

OReilly, J., and D. A. Busch. 1979. Summary of measurements of primary productivity
made during MARMAP surveys (Belogorsk 78-01, 78-03, 78-04). NOAA, Nat. Mar.
Fish. Serv., Northeast Fish. Ctr. Sandy Hook Lab. Ref. No. 79-09.

O’Reilly, J. E., and D. A. Busch. 1982. Preliminary-estimates of the annual phytoplankton
primary production for the Northwest Atlantic shelf (Middle..Atlantic Bight,
Georges Bank, Gulf of Maine). ICES C.M. 1981/L:16.

O'Reilly, J. E., and D. A. Busch. 1984. Phytoplankton primary production for the
Northwestern Atlantic shelf. Rapp. P.-v- Reun. Cons. Int. Explor. Mer 183:255-268.

OReilly, J. E., D. A. Busch, R. A. Bruno, and J. Nickels. 1981. Summary of measurements
of primary productivity made during MARMAP surveys (Albatross 79-06,.79-11, Ev-
rika 80-01, 80-02, and Delaware 80-03/Evrika 80-04). NOAA, Nat. Mar. Fish. Serv.,
Northeast Fish. Ctr. Sandy Hook Lab. Ref. No. 81-14, 51 pp.

124


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iS :
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Fig. 19. Haddock percent standard deviation.as.a function of sampling coefficient of *
variation.

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16


EXOGENOUS VARIABLES
AND PARAMETERS

PROGRAM FLOW RANDOM VARIABLES
Mean Daily Temperatures Daily Temperature Anomaly
[
Mean and SD of Spawning —> EGGS SPAWNED +~ Daily Spawning Anomaly
‘Development Parameters —> EGGS DEVELOP + Development Rate Anomaly
‘Mortality Parameters > EGGS DIE + Moniality Rate Anomaly
‘Growth Parameters > LARVAE GROW ~~ Growth Rate Anomaly
‘Mortality Parameters > LARVAE DIE + Mortality Rate Anomaly
Control Variables:
Cruise Interval > + Cruise Date Anomaly
Precision (Sample Size) —> LARVAE SAMPLED -+ Sampling Error
Resolution of Length
Measurements >
Mean Daily Temperatures —> ESTIMATE MORTALITY AND
Growth Parameters > USE IT TO CALCULATE
Development parameters —> NUMBER OF EGGS SPAWNED
CALCULATE STATISTICS ON
RATIOS OF CALCULATED EGGS.
TO ACTUAL EGGS SPAWNED

Fig. 1. Computer simulation program flow diagram showing exogenous and randomly as-
signed variables.

82


Total incubation time until hatching‘regressed‘on temperature for

30 species of marine fisheggs. . 2. ee So

Spawning intensity versus date in the Gulf of Maine for all fish egg

species taken during bongo plankton tows, 1979-1984... . 2.0.

Spawning intensity versus date on Georges Bank for all fish egg

species taken during bongo plankton tows, 1979-1984. bee et

Spawning intensity versus date in Southern New England waters for

| fish egg species taken during bongo plankton tows, 1979-1984. . . ,

Spawning intensity versus date in Middle Atlantic waters for all

fish egg species taken during bongo plankton tows, 1979-1984. . ....

Spawning intensity versus date in the total survey area for all fish

egg species taken during bongo plankton tows, 1979-1984. . 0.) , Se '

Spawner biomass (0) and total fish population biomass (X) estimates, ,
based primarily on planktonic fish egg data, superimposed on Fig. 3
of Cons. and Util. Div., NEFC (1985) illustrating alternative’ stock

biomass estimates for 1979- 1984. ee ee
LENGTH-DEPENDENT MORTALITY AND AN INDEX OF SPAWNING -”

BIOMASS FROM LARVAL ABUNDANCE

1.

Combined length frequency of all haddock larvae caught from 1977
to spring 1984 on MARMAP surveys.

Combined length frequ ency of all Atlantic herring larvae caught
from 1977 to spring 1984 on MARMAP surveys.

Standard and mortality-adjusted abundances of Atlantic cod larvae
caught on Georges Bank in 1980.

Standard and mortality- adjusted abundances of silver hake larvae
caught on Georges Bank in 1978.

VARIABILITY INMARMAP SURVEY. MEAN CATCH PER TOW

1.

A plot of the coefficient of variation and number of samples
within a subarea for nineteen taxa from MARMAP larval fish
surveys, 1977-spring 1984. . .

Linear regressions of log, variance and log, mean n catch per 10 m?
for MARMAP larval fish’ surveys, 1977- -spring 1984.

xi

“59

65

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CONTENTS

Page
LISTOF TABLES,» 2... ee ee ix
LISTOFFIGURES ,. 1... ee x
INTRODUCTION--Michael P. Sissenwine, , , . .. 0. ee ee ee 1
ICHTHYOPLANKTON SURVEYS: A STRATEGY FOR MONITORING
FISHERIES CHANGE IN A LARGE MARINE ECOSYSTEM--Kenneth
Sherman | Sk, ee 3
Literature Cited | ee ee 6
MARMAP ICHTHYOPLANKTON SURVEYS: AN OVERVIEW OF
METHODS AND DATA BASE MANAGEMENT--Wallace G. Smith
and Julien Goulet... ee 10
Abstract, 2. ee 10
Introduction, » 2. ee ee rrr (0)
Survey Methods 2... ee 10
Data Storage and Management. . 2... 2 1 ee ee ee eee ee 11
Literature Cited 2 2 ee ee 12
A COMPARISON OF INFORMATION CONTENT FROM TRAWL AND
ICHTHYOPLANKTON SURVEYS--Wallace G.Smith. . 2... 2.2.24. 19
Abstract, 2 ee 19
Introduction, » 2. ee 19
Method, 2... ee 19
Results 20
Discussion, 2. 20
Literature Cited 2 2 ee ee 21
USE OF EGG DATA TO ESTIMATE TOTAL FINFISH BIOMASS FOR
THE NORTHEAST CONTINENTAL SHELF ECOSYSTEM--Peter Berrien
and Michael P. Sissenwine, 2 2... ee ee 26
Abstract, 2 ee 26
Introduction, 2... ee 26
Methods, 2 6. ww 27
Estimating the Ratio of Immature to
Mature Biomass of a Fish Population, .. 6 6. ee ee 29
Results. 2. 30
Discussion, . oe es 30
Literature Cited 2. ee ee 31

vii

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[ Preceding page blank



CALCULATED/INPUT EGGS SPAWNED

LEGEND
OG = CRUISE INTERVAL - 30 DAYS
O-= CRUISE INTERVAL = 61 DAYS
4 = CRUISE INTERVAL = 91 DAYS

Lat

1.0

MEDIAN
0.8

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0
SAMPLING COEFFICIENT OF VARIATION

Fig. 18. Silver hake median as a function of sampling coefficient of variation.

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0.90 0.95 1.00 1.05 -10

MEDIAN

0.85

0.80
—

0.70 0.75

30.035.0 40.0 45.0 50.0 $5.0 60.0 65.0 70.0 75.0 80.0 @5.0 90.0 95.0
DAYS BETWEEN CRUISES

Fig. 14. Silver hake median.as a function of days between cruises.

95


results. Since only a small number of organisms are captured at 20 mm, and there may be
some avoidance, it is worthwhile to consider reducing the maximum larval length used in
these estimates.

CONCLUSIONS’

Monte Carlo-simulation is a useful tool to evaluate the accuracy and precision of
spawning stock size from larval abundance data. The results reported in this paper are
preliminary. They were intended to demonstrate how the simulation model can be used to
examine alternative levels of sampling intensity. The method can be used to determine the
sensitivity of estimates to various biological parameters. It can be used to examine alterna-
tive estimation methods. oe a

While the results are only preliminary, they do indicate that the current sampling
regime (target cruise intervals of 61 days, sample size of 50 producing a coefficient of varia-
tionof about 50%) is reasonable. Spawning stock size estimates are not precise, but they
are useful for monitoring major changes in the ecosystem that are known to occur and per-
sist for relatively long periods of time (i.e., decadal). The precision of the result can be im-
proved by combining estimates over several years, although this approach eliminates the
possibility of monitoring interannual variability. . .

Analysis using this model.is continuing. The model is being applied to additional
species. Results for herring, sand eel, and Atlantic cod (Gadus morhua) have been ob-
tained. The sensitivity of the results to additional parameters is being investigated. The ef-
fects.of.random variability are being determined for various parameters singly and in com-
bination. Application of the model to egg data is being considered, and program modifica-
tions have been made to facilitate an investigation of egg and larval results.

LITERATURE CITED

Berrien, P. 1983. Silver hake, Merluccius bilinearis, egg census, and adult opulation es-
timate for 1979. in waters off eastern United States. ICES C.M. 1983/G:46. .

Berrien, P., W. Morse, and M. Pennington. 1984. Recent estimates of adult spawning
stock biomass off the northeastern United States from MARMAP ichthyoplankton
surveys. NOAA Tech. Mem. NMFS-F/NEC-30. 111 pp.

Boreman, J. 1983. Simulation of striped bass egg and larva development based on tem-
perature. Trans. Am. Fish. Soc. 112:286-292.

Hewitt, R. P., and R. D. Methot, Jr. 1982. Distribution and mortality of northern anchovy
larvae in 1978 and 1979, CalCOFI Rep. 23:226-245.

Morse, W. W. 1984. An assessment of the Georges Bank haddock stock based on larvae
collected on MARMAP plankton surveys, 1977-1982. pe. 67-87. In P. Berrien, W.
Morse, and M. Pennington (Eds.) Recent estimates of adult spawning biomass off
northeastern United States from MARMAP ichthyoplankton surveys. NOAA Tech.
Mem. NMFS-F/NEC30.

Morse, W. W., and J. W. Hauser. 1985. A study of factors affecting the precision of spawn-

ing stock estimates using MARMAP fish egg and larval surveys. NEFC, Sandy
Hook Laboratory, Rep. SHL 85-07:67 pp.

80


TOTAL FINFISH AND SQUID GULF OF MAINE - CAPE HATTERAS

19000
x
80004 A x
. ony i
= vo n h xx
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ra 40004 ! \ t ‘ \
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2 y ve’ a! voy
. t voou@ ul
eed i , v7 :
, 20004 ’
Fig. “8. . Spawner biomass 0) and _ total. fish population. biomass (X) .estimates,. based

primarily’ on planktonic fish egg data, su
NEFC (1985) illustrating alternative stock

bi

erimposed. on Fig. 3 of Cons. and Util. Div,
iomass estimates for 1979-1984.

48


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LITERATURE CITED

Anderson, E. D. 1985. Status of the Northwest Atlantic mackerel stock--1984. Nat. Mar.
Fish, Serv., Northeast Fish. Ctr., Woods Hole Lab. Ref. Doc. No. 85-03. 46 pp.

Berrien, P. L.,'N. A. Naplin, and M. R. Pennington. 1981. Atlantic mackerel, Scomber
scombrus, egg production and spawning population estimates for 1977 in the Gulf of
Maine, Georges Bank, and Middle Atlantic Bight.. Rapp. P.-v. Reun. Cons. int. Ex-
plor. Mer 178:279-288.

Berrien, P., and M. Sissenwine. This volume. Total finfish biomass in shelf waters off the
northeastern United States, 1979-1984, based on fish egg abundances in plankton.

Cicerone, R. J. 1987. Changes in stratospheric ozone. Science 237:35-42,

Clark, S. H.,-and B. E. Brown. 1977. Changes of biomass of finfishes and squids from the
Gulf of Maine to Cape Hatteras, 1963-74, as determined from research vessel sur-
vey data. Fish. Bull., U.S. 75:1-21.

Colebrook, J. M. 1972. Changes in the distribution and abundance of zooplankton in the
North Sea 1948-1969. Symp. Zool. Soc. London 29:203-212.

Colebrook, J. M. 1977. Annual fluctuations in biomass of taxonomic groups of
zooplankton in the California Current, 1955-59. Fish. Bull., U.S. 75:357-368.

Colebrook, J. M. 1978. Continuous plankton records: zooplankton and environment,
North-East Atlantic and North Sea, 1948-1975. Oceanologica Acta 1(1):9-23.

International Council for the Exploration of the Sea (ICES). 1987. Report of the Workin
Group on Larval Fish Ecology to the Biological Oceanography.Committee of ICES.
C.M. 1987/L:28.

Jakobsson, J. 1980. The North Icelandic herring fishery and environmental conditions
1960-1968. Rapp. P.-v. Reun. Cons. int. Explor. Mer 177:460-465.

Laurence, G. C., and R. G. Lough. 1984. Growth and survival of larval fishes in relation to
the trophodynamics of Georges Bank cod and haddock. NOAA Tech. Mem.
NMFS-F/NEC-31. 150 pp.

MacCall, A. D. 1986. Changes in the biomass of the California Current ecosystem. pp.
33-54. Ia K. Sherman and L. M. Alexander (Eds.) Variability and management of
large marine ecosystems. AAAS Selected Symposium 99, Westview Press, Boulder,
CO. 319 pp.

McCarthy, J. J., Brewer, P. G., and G. Feldman. 1986. Global ocean flux. Oceanus
29(4):16-26.

Maurer, R. 1976. 1976. A preliminary analysis of interspecific trophic relationships be-
tween the sea herring and the Atlantic mackerel. ICNAF Res. Doc. No. 121, Ser.
3967, 22 pp.


Table 1. Fecundity values for 23 fish species used in calculating spawner biomass estimates
from MARMAP I egg samples.

No. eggs per
Taxon gm of female Source
Melanogrammus aeglefinus 640 Hodder, 1963
X= 7215
803 Bigelow and Schroeder, 1953
Gadus morhua 398.1 Buzeta and Waiwood, 1982
Pollachius virens 670 Bigelow and Schroeder, 1953
Merluccius bilinearis 815.2 Mari and Ramos, 1979
Ammodytes sp. 973. Westin et al., 1979
Scomber scombrus 1400 Morse, 1980a
" X = 1237
1074 Bigelow and Schroeder, 1953
Scomberomorus maculatus 661 Earll, 1883
X= 606
551
Scomberomorus cavalla . 248.5 Ivo, 1974
Lopholatilus chamaeleonticeps 750 Freeman and Turner, 1977
Morone saxatilis 196 Jackson and Tiller, 1952
X= 184
192
Morone americana : 500 Sheri and Power, 1968
Micropogonias undulatus , 1000 Morse, 1980b
Pogonias cromis 300 Pearson, 1929
Cynoscion regalis : 1330.7 Merriner, 1976
X = 1200.3
1070.0
Pomatomus saltatrix 404 Lassiter, 1962
Sphoeroides maculatus oo 751 Merriner and LaRoche, 1977

35


Table 3. Response of g,, t, and x to g, and t,.

t,=2yr t=3yr
8 8 t, x 8&2 & x
0.10 -0.12 26.6 0.22 -0.13 25.0 0.35
0.25 -0.16 20.2 0.25 -0.21 163 0.45
0.50 -0.27 13.0 0.34 -0.45 8.7 0.70
0.75 -0.45 8.7 0.46 -0.95 52° 1.13
1.00 -0.74 6.1 0.64 -2.00 35 1.91

39


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Sherman, K., R. Lasker, W. Richards, and A. W. Kendall, Jr. 1983. Ichthyoplankton and
fish recruitment studies in large marine ecosystems. (MARMAP Contribution
MED/NEFC 82-75.) Mar. Fish. Rev. 45(10-12):1-25,

Sherman, K., R. Maurer, R. Byron, and J. Green. 1979. Relationship betwecn larval fish
communities and zooplankton prey species in an offshore spawning ground. Rapp.
P.-v. Reun. Cons. Int. Explor. Mer 178:289-294.

Sherman, K., W. G. Smith, J. R. Green, E. Cohen, M. S. Berman, K. Marti, and J. R.
Goulet. 1987. Zooplankton production and the fisheries of the northeastern shelf.
pp. 268-282, Chapter 25. Jn R. H. Backus (Ed.) Georges Bank. MIT Press,
Cambridge. 593 pp. (MARMAP Contribution No. MED/NEFC 83-47).

Sherman, K., W. Smith, W. Morse, M. Berman, J. Green, and L. Ejsymont, 1984. Spawn-
ing strategies of fishes in relation to circulation, phytoplankton ‘production, and
pulses in zooplankton off the northeastern United States. Mar. Ecol. Prog. Ser.
18:1-19.

Sherman, K., L. Sullivan, and R. Byron. 1978. Pulses in the abundance of fosplankton
prey of fish on the continental shelf off New England. ICES C.M. 1978/L:25.

Sibunka, J. D., and M. J. Silverman. 1984. MARMAP surveys of the continental shelf
from Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). At-
las No. 1, Summary of operations. NOAA TM NMFS-F/NEC-33. 306 pp.

Silverman, M. J. 1982. The distribution and abundance of silver hake, Merluccius
bilinearis, larvae off northeastern United States, 1977-1980. ICES C.M. 1982/G:58.

Silverman, M. J. 1983. Distribution, abundance, and production estimates of yellowtail
flounder, Limanda ferruginea, larvae off northeastern United States, 1977-1981.
ICEA C.M. 1983/G:47.

Silverman, M. J. 1985. Distribution, abundance, and production estimates of yellowtail
flounder, Limanda ferruginea, larvae off the northeastern United States, 1982-1984.
ICES C.M. 1985/L:18.

Sissenwine, M. P. 1986. Perturbation of a predator-controlled continental shelf ecosystem.
pp. 55-83. In K. Sherman and L. M. Alexander (Eds.) Variability and management
of large marine ecosystems. AAAS Selected Symposium 99, Westview Press,
Boulder, CO. 319 pp.

Smith, W. G. 1980. What studies of young fish-tell about fish populations. Underwater
Naturalist 12(4):9-16.

Smith, W. G. 1981. Fish egg/larval surveys in the Northwest Atlantic. Highlight--NEFC
Newsletter, May-June 1981. 8 pp. :

Smith, W. 1982. Sand lance population explosion continues off northeastern United
States. Am. Inst. Fish. Res. Biol. Briefs 11(2):2. :

Smith, W. G. 1982. Sand lance abundant; Atlantic herring larvae disappear. Coast.
Oceanogr. Climatol. News 4(2):21.

130


DWD 106. Jn J. B. Pearce, D. C. Miller, and C. Berman (Eds.) 106-Mile site
characterization update. NOAA Tech. Mem. NMFS-F/NEC-26. 483 pp. NTIS Ac-
cess No. PB84-118363.

Jewell, C. 1984. Temperature structure and surface salinity in the Gulf of Maine durin
1983. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Woods Hole Lab. Ref.
Doe. No. 84-24, ~

Jossi, J. W., and R. R. Marak. 1983. MARMAP plankton survey manual. NOAA. Tech.
Mem. NMFS-F/NEC-21. 258 pp.

Kane, J. 1982. Effect of season and location on the relationship between zooplankton dis-
placement volume and dry weight in the Northwest Atlantic. MARMAP Contribu-
tion No. MED/NEFC 81-8. Fish. Bull., U.S. 80:631-642.

Kane, J. 1984. The feeding habits of co-occurring cod and haddock larvae from Georges
Bank. MARMAP Contribution No. MED/NEFC 82-38. Mar. Ecol. Prog. Ser.
16:9-20.

Kendall, A. W., Jr., and D. Gordon. 1981. Growth rate of Atlantic mackerel (Scomber
scombrus) larvae in the Middle Atlantic Bight: Rapp. P.-v. Reun. Cons. int. Explor.
Mer 178:337-341.

Kirschner, R. A. 1978. Temperature structure and surface salinity in the Gulf of Maine
during 1978. ICES Annales Biologiques 35:30-41.

Kirschner, R. A. 1979. Fall temperature structure in the northern Gulf of Maine: A four-
year comparison. Coastal Oceanogr. Climatol. News 1(2):16-17.

Kirschner, R. A. 1980. Hydrographic work on MARMAP cruises. NOAA, Nat. Mar. Fish.
Serv., Northeast Fish. Ctr. Woods Hole Lab. Ref. No. 80-25.

Lough, R. G. 1982. Absence of cod and haddock larvae on Georges Bank spring, 1982.
~ Red Flag Report. 9 pp.

McKenney, T. 1981. A checklist of some fishes taken with neuston and bongo nets in the
vicinity of Deep Water Dumpsite 106. NOAA, Nat. Mar. Fish. Serv., Northeast
Fish. Ctr. Sandy Hook Lab. Ref. No. 81-26. 35 pp.

McKenney, T. W. 1983. Distribution and abundance of Merluccius albidus larvae in shelf
waters off the northeastern United States, 1977-1981. ICES C.M. 1983/G:48.

McKenney, T. W., A. Johnson, and A. Wells. 1984. Distribution and abundance of
Citharichthys_arctifrons larvae in shelf waters off the northeastern United States,
1977-82. ICES C.M. 1984/G:31.

Miller, D. S., P. M. Payne, and K. D. Powers. 1980. Marine observer manual. Appendix B.
A marine mammal observer training program. U.S. Dep. Commer. NMFS/NEFC
Contract No. NA-80-FA-D-0004. Woods Hole, MA. 147 pp.

Morse, W. 1982. Spawning stock biomass estimates of sand lance, Ammodytes sp., off
northeastern United States, determined from MARMAP plankton surveys, 1974-
1980. ICES C.M. 1982/G:59.

123


INTRODUCTION
Michael P. Sissenwine

National Marine Fisheries Service
Northeast Fisheries Center
Woods Hole Laboratory
Woods Hole, MA 02543

The Northeast Fisheries Center (NEFC) conducts plankton surveys of the northcast
continental shelf, between Cape Hatteras and Nova Scotia, approximately 6-8 times per
year. A standard survey design and method have been used since 1977. These are
described in detail by Sibunka and Silverman (1984) and outlined in this volume by Smith
and Goulet. During the autumn of 1985, the Fisheries Ecology Division initiated a
rigorous quantitative analysis of the ichthyoplankton data collected during these surveys.
The goals of the analysis were: (a) to examine the usefulness of ichthyoplankton survey
data as a fishing independent measure of resource abundance, (b) determine to what ex-
tent the data provides unique information, and (c) determine the relationship between the
quality of survey results (i.e., accuracy and precision of spawning biomass estimates) and
level of survey effort (i.e., sample size within surveys and survey frequency). The results of
these analyses are reported herein.

In order to meet the objective of the study, a multifaceted approach was applied.
The facets are described in individual papers in this document. The first paper in the set
establishes the need for a fishery-independent means of surveying large marine ecosystems.
It outlines the strategy. in place in NEFC for monitoring the finfishes as well as the biologi-
cal and physical variables that almost certainly influence abundance, distribution, and
species composition of the finfish community off the northeastern United States.

The next paper reviews NEFC’s ichthyoplankton sampling methods and how survey
data are processed. This short paper is followed by a comparison of catches from ich-
thyoplankton and trawl surveys, two alternative fisheries-independent methods used by the
NEFC to measure long-term shifts within the finfish community and short-term changes
and abundance levels of economically/ecologically important species. Since no single
method monitors all species with uniform accuracy and precision, it is important to know if
the two survey methods provide complementary or redundant information.

Ichthyoplankton survey data are used to estimate spawning biomass which requires
an estimate of mortality rate. For many species larval mortality rate per unit time cannot
be estimated annually. The next paper introduces an index of abundance that is ap-
propriate for these species. It uses a pooled (over several years) estimate of mortality per
unit length which can be derived for most species.

One of the most important reasons for monitoring the biomass of the entire finfish
community is to determine how variable it is relative to individual specics. There are
ecological reasons to hypothesize that total biomass is more stable. The hypothcsis has
important fisheries management implications. The fifth paper introduces a new method
for estimating total finfish biomass based primarily on egg abundance.

Of course, one of the major controllable (i.e., set by the survey design) variables
that determines the precision of ichthyoplankton survey data is sample size. The sixth

1


OReilly, J. E., C. A. Evans; and'D. A. Busch. 1981. Distribution of phytoplankton biomass
¢chiorphyll a) and rimary productivity in shelf water between Cape Hatteras and
Nova Scotia. pp. 66:67. Jn Third informal workshop:on the oceanography of the
Gulf of Maine and adjacent seas, Univ. New Hampshire, Durham, N. H. 2-5 March
1981. (Abstract only).

OReilly, J. E., C. Evans-Zetlin; and D. A. Busch. 1987. Primary production.. pp. 220-233.
Jn R. H. Backus (Ed.) Georges Bank. MIT Press, Cambridge.

OReilly, J. E., C. Evans, V. Zdanowicz, A. Draxler, R. Waldhauer, and A. Matte. 1980.
Baseline studies on-the distribution of phytoplankton biomass, organic production,
seawater nutrients, and trace metals in coastal water between Cape Hatteras and
Nova Scotia. First Annual Report, Northeast Monitoring Program.

Pastuszak, M., D. Mountain, D. Busch, and W. Smith. 1984. On the influx of Slope Water
and plankton through the Great South Channel and its implications for the recir-
culation of water around Georges Bank. EOS, Trans. Am. Geophys. Union 1984
(Abstract only).

Patanjo, D., S. R. Nickerson, and F. Steimle. 1982. Report on temperature and dissolved
oxygen measurements made on MARMAP surveys between October 1977-
December 1978. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Woods Hole
Lab. Ref. Doc. 82-03. :

Payne, P. M., and J. P. Ross.. [1988.] Loggerhead turtle. In T. French (Ed.) Endangered,
threatened, and special concern vertebrate species in Massachusetts. A publ. of the
Massachusetts Nongame and Endangered Species Program, Div. Fish. Wildl., Bos-
ton, MA ‘(in préss). ° : .

Payne, P. M., J. R. Nicholas, L: O’Brien, and K. D. Powers. 1986. Distribution of the
humpback whale (Magaptera novaeangliae) on Georges Bank and in the Gulf of
Maine in relation to-densities of the sand eel (Ammodytes americanus). Fish. Bull.,
USS, 84:271-277.

Payne, P. M., K. D. Powers, and J. E. Bird. 1983. Opportunistic feeding on whale fat by
Wilson’s storm-petrels Oceanites oceanicus in the western North Atlantic. Wilson
Bull. 95:478-479. : . .

Payne, P. M., and L. A. Selzer (Editors). 1980. Characterization of whale use of.the Mas-
sachusetts Bay and Cape Arundel, Maine, areas. Report to Sanford Ecological _
»» Services, Natick, MA.. Army Corps of Engineers, New England Div., Contract No.
DACW33-85-D-0002-0003. ; i

Payne, P. M., R. Sears, and F. W. Wenzel. [1988.] Bluc whale. Jn T. French (Ed.) Endan- .
gered, threatened, and special concern vertebrate species in Massachusetts. A publ.
of the Massachusetts Nongame and Endangered Species Program, Div. Fish. Wildl.,
Boston, MA (in press). .

Payne, P. M., L. A. Selzer, and A. R. Knowlton. 1984. Distribution and density of
cetaceans, marine turtles, and seabirds in the shelf waters of the northeastern
United States, June 1981-December 1983, based on shipboard observations.
NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Contract NA-81-FA-C-00023.

246 pp.
125


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43


Total finfish biomass estimates from ichthyoplankton surveys are compared with
bottom trawl survey estimates. The former are consistently higher (up to a factor of two)
and are generally more stable over the short time series (1979-1984) available for com-
parison. The recent ichthyoplankton estimates are comparable to estimates from bottom
trawl surveys that applied about two decades ago. One interpretation of these results is
that total finfish biomass is relatively stable although species composition is highly variable.

The most important control variables that determine the quality of ichthyoplankton
survey data are: (1) the sample size within surveys, and (2) the frequency of surveys. In
order to examine the importance of sample size, plots of the log of variance versus log of
the mean were prepared for 20 species. The plots are well described by a linear relation-
ship with slope of approximately two for all species. This means that the coefficient of
variation (cv) is independent of the mean. For a sample size of 50 per subarea, which is
typical of the current sample size, the cv ranged from 33.2% to 54.6% with a mean of
40.7% for the 20 species. If sample size were doubled, the average cv would decrease to
28.8%; if it were halved, the cv would increase to 57.6%.

A Monte Carlo simulation model is used to examine the combined effect of sample
size within surveys and survey frequency on the accuracy and precision of spawning
biomass estimates. The importance of biological parameters (c.g., growth rate, duration of
spawning season) and various assumptions (e.g., constant mortality rate, normally dis-
tributed spawning probability function) are also examined.

The model simulates spawning, egg and larval growth, and mortality, sampling of
larvae, and the calculations that are made to estimate spawning biomass. Several com-
ponents of the model incorporate realistic random effects (e.g., timing of surveys, sampling
error, random variations in mortality, and growth rates) which led to uncertainty in simu-
lated estimates of spawning biomass. By repeating the simulations numerous times and
comparing the simulated spawning biomass to the simulated estimates of spawning
biomass, accuracy and precision are assessed.

The model was applied to three representative species: haddock which is a spring
spawner, silver hake which is a summer spawner, and sand eel which spawns in winter and
has an extended larval period.

The results indicate that spawning biomass estimates are about equally sensitive to
sample size within surveys and frequency of surveys. Both are minimally adequate. Spawn-
ing biomass estimates are generally unbiased, but their cv’s are over 100%. This means
that only changes in spawning biomass of greater than a factor of two can be detected from
a single year’s data; ie., there is about a one-third probability that a factos-of-two dif-
ference is due to estimation error. The implication is that spawning biomass estimates are
most useful for monitoring trends in abundance which persist over several years.

The simulation shows the relative importance of certain biological parameters and
assumptions of the method. For example, the duration of the spawning scason is a more
important parameter than the duration of the larval period. The simulation model is a
powerful tool. It will continue to be used to improve estimates derived from ich-
thyoplankton data.

Planktonic egg surveys and bottom trawl surveys both provide unique and valuable
measures of abundance and composition of fishery resources. Egg surveys can provide es-
timates of absolute abundance of adults; trawl surveys produce relative measures of abun-
dance. The final paper in the set uses egg data for yellowtail flounder to illustrate a tech-


VARIABILITY IN MARMAP SURVEY. MEAN CATCH: PER TOW
Wallace W. Morse ,

National Marine Fisheries Service: .
Northeast Fisheries Center’
Sandy Hook Laboratory
Highlands, NJ. 07732

ABSTRACT

Nineteen taxa from the MARMAP larval fish data set were analyzed to determine
the efficacy of using a logarithmic transformation to normalize the catch frequencies and
to derive estimates of variability in mean catch per 10 m*. The application of Taylor’s
power law indicated the logarithmic transformation is appropriate for larval catches. The
mean coefficient of variation for all taxa for a sample size of 50 stations is 40.7 and the
range of coefficients is 33.2 to 54.6. Correlation analysis indicated that between-length
abundances were not strongly correlated except for adjacent-length intervals.

INTRODUCTION

A key population parameter estimated from the MARMAP ichthyoplankton sur-
veys on the Northeast Continental Shelf is the mean catch of larvae per 10 m“ and its as-
sociated variance. The mean is used to estimate the total number of larvae within a par-
ticular area by simple areal expansion. The distribution of larvae within the survey area
has a highly aggregated distribution. The presence of larvae at a given station increases the
probability of larvae occurring nearby, which results in large variances relative to the mean.
A Suitable model for the frequency distribution of larval catches is the negative binomial
(Bliss and Fisher, 1953). The negative binomial distribution has two parameters, the mean
u and the exponent k. The reciprocal of k is a measure of the: excess variance, or clump-
ing, of individuals in the population (Elliot, 1971). A more general method to measure the
dispersion of individuals in a population is by using Taylor’s power law (Taylor, 1961)
which says that the variance (¢“) of a population is proportional to a fractional power of
the mean (y) where: :

o2= ay and therefore logo” = loga+b*log yu .

The parameter b is a measure of dispersion within a population such that if b = 1, then the
dispersion is random and as b increases above 1 to infinity, then the population is progres-
sively aggregated. Samples from aggregated populations must be transformed to normalize
the sample frequency distributions before the. application of parametric statistics. The es-
timated parameter b is used to evaluate the appropriate transformation by replacing each
sample count (X) by XP, where p = 1- b/2: Thus for b = 2, then p = 0 and-a logarithmic
transformation is applied to the original data (Elliott, 1971).

In this paper, Taylor’s power law is applied to the MARMAP larval catch data to
evaluate the use of logarithms as the appropriate transformation to normalize the fre-
quency distributions and ‘to estimate the population coefficient. of variation, and to es-
timate the sample coefficient of variation for various sample sizes. The estimated coeffi-
cients of variation provide a baseline for evaluating the effects of altering the current

60


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58




study shows Iength-dependent mortalities’ trend in the contrary direction. If only growth
and mortality are considered then age-dependent mortality must increase dramatically
during summer to compensate for the increased growth rate.

The question to be answered is "What causes the increase in mortality with increas-
ing water temperature?" The most often cited sources of larval mortality within this study
area include the abiotic factors: advection, warm core rings, storm events, anomalous tem-
peratures; and the biotic factors: starvation, predation, cannibalism. The abiotic factors
which show clear seasonal trends include warm core rings, storm events, and, by inference,
advection. These factors exert their greatest influence during the winter and spring so they
can be eliminated as the causative factors. Anomalous temperatures are unlikely to have a
seasonal trend and can also be dismissed, leaving biotic factors as the most promising.

Of the three biotic factors, cannibalism is the least understood source of mortality,
though it must have a strong density-dependent component. The combined effects of serial
spawning, which is characteristic of many species and assures a wide length (age) range of
co-occurring larvae on the spawning grounds, and the clear seasonal trend in the density of
larvae, with the lowest in early spring and peak in summer, make cannibalism a possible
source of increased larval mortality.

Starvation has been hypothesized as a major source of larval mortality for the past
80 years. Emphasis has been placed upon the effects of prey density on the survival of
first-feeding larvae and has been variously called the "critical period hypothesis" or
"match-mismatch hypothesis." The survival, or lack of it, of first-feeding larvae does not
play a role in this discussion because the length yequencies of the survey catches contain
very few yolk-sac or first-feeding larvae (Table 1). These small larvae are, in general, ex-
truded through the meshes of the 0.505-mm mesh nets. The events which shape the mor-
tality curves in this study occur after the "critical period." Two indicators of prey
availability, primary production (Campbell and O'Reilly, in press) and zooplankton density
(Sherman, 1986), peak during the summer months and are at.a minimum in winter over
much of the shelf. Though starvation can not be ruled out as the source of increased mor-
tality, the coincidence of seasonal cycles of larval density and the indicators of prey
availability do not support the starvation hypothesis.

The last biotic factor is predation. The consumption rates of predators on larval
fish is, at least partially, a function of water temperature as it relates to increasing metabo-
lism with increasing temperature. The combined effects of high larval densities and high
metabolic requirements of predators during summer as compared to winter make preda-
tion a likely mechanism to explain the increase in average mortality from winter through
summer. High larval density decreases the required search time needed by predators to
encounter their prey, which in turn should increase mortality rates. The seasonal changes
in mortality rates and their possible relationship to predation will be investigated in more
detail in the near future.

Biomass Index

Table 2 lists the indexes of annual production of 3-mm larvae for six taxa by year
and subarea. Considerable variability is evident between years and, as expected, between
subareas. Georges Bank production is highest for cod and silver hake for all years. Had-
dock production is highest on Georges Bank in all years except 1982 and 1983, when
Southern New England and the Gulf of Maine dominated, respectively. Southern New
England produces the highest numbers of Urophycis spp. larvae in all years. The produc-

51


TONS

MILL.

ALL SPECIES

10
* BIOMASS
4 * *
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1960 1970 1980
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* NORWAY *
x kk
24 POUT y wee
he IF te gee e YIELD
ry
©
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1960 1970

8

1980

Estimated changes in the biomass of fishes in the North Sea, 1960-1976, with simu-
lated yicld and biomass projections to 1980. The 1.0 million metric ton decline in Atlantic
mackerel and Atlantic herring stocks from 1968-1976 from excessive fishing mortality is
thought to be compensated for in the North Sea Ecosystem by replacement with small,

growing, opportunistic species (i.e., sprat, sand eel, Norway pout). (Adopted from Ur-
sin, 1977.) . .


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Fig. 2. Comparison of principal taxa from NEFC trawl (1977-1984) and ichthyoplankton
(1977-1983) surveys in four subareas off the northeastern United States, using Spcarman’s
Rank Corrclation. Results show no significant (P<0.05) positive correlations for the two
data sects. Sample size (n), correlation coefficient (r), and probability valucs (p) are noted
for gach subarca. Taxa appearing in only one of the two data sets were assigned the rank
of 24,

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45


Collecting methods for all facets of the MARMAP surveys from 1977 through 1983
are described in detail by Sibunka and Silverman (1984). This report outlines only the ich-
thyoplankton sampling operation which involves double oblique tows with a 61-cm bongo.
The net is lowered to within a few meters of the bottom, or to a maximum depth of 200 m
at 50 m-min"', and retrieved at 20 m-min’TM’. Ship speed varies between 1 and 2 kt to main-
tain a 45° wire angle during the tow. One side of the bongo is fitted with a 0.505-mm mesh
net for ichthyoplankton studies, the other with a 0.333-mm mesh net for zooplankton
monitoring. A flow meter is suspended at the mouth on each side of the bongo to record
the amount of water filtered. To eliminate flow meter windmilling when setting the gear,
disposable beverage cups are placed over the fins on the meter before setting the bongo.
The cups are washed into the nets upon impact with surface water and retrieved after the
tow when the net’s contents are removed. A mechanical time-depth recorder is attached to
the towing wire just above the bongo to record tow profile and maximum sampling depth.

Initial processing of the plankton samples is completed at the Sea Fisheries In-
stitute, Szczecin, Poland. Larvae are sorted, identified, measured, and counted at the in-
stitute, then returned to NEFC’s Sandy Hook Laboratory, along with appropriate logs and
fish eggs. Quality control procedures are completed at Sandy Hook, and data are subse-
quently entered into the computer (VAX). Fish eggs of some S50 taxa, used largely for as-
sessment purposes, are identified and staged at Sandy Hook with results then archived in
the VAX. .

DATA STORAGE AND MANAGEMENT

The MARMAP Ecosystem Data Base and Information Management (MEDBIM)
System consists of a Data Base, a Quality Control Processing System, a Data Dictionary-
Documentation System and a Query and Report System.

The Query and Report system is provided by the $1032, the DBMS used to imple-
ment MEDBIM. A library of record formats and procedures will contain commonly used
procedures and output formats.

The Data Dictionary-Documentation system completely defines MEDBIM, includ-
ing record formats, data set structures, software logic, file references, data locator, legal
codes, taxonomic numbers, etc. It is also implemented in $1032.

The Quality Control Processing system consists of software modules, associated
data structures, and processing instructions. The software modules are grouped into path-
ways each providing for the processing needed to move data, along one path, from input
records to the master data base. There is at least one path for each of the master data sets.
Sometimes there are several, as input record formats are changed or data are received
from a new source. Over 50 pathways have been defined, of which approximately 15 are
active. Another 20 software paths defining system utilities (e.g., data management) or user
access procedures have been built. The Quality Control Processing software has been
implemented in both $1032 and in DBASE Il.

The MEDBIM data base was originally designed as shown in Fig. 2, with each data
set containing only elements which truly belonged to the primary key shown. At each level,
the key presumes the keys at higher level. us the primary key for Larvae includes the
primary keys for Net, Experiment, Station and Cruise. Not all data types pertaining to
FED are included in this design. It is, however, open-ended and new data sets can be
added as long as the proper linking keys are included.

11


Smith, W., A. Wells, and D. G. McMillan. 1979. The distribution and abundance of ich-
thyoplankton in the Middle Atlantic Bight as determined from coastal surveys and
site-specific studies 1965-1976. NOAA-BLM Interagency Agreement AA550-IA7-
35. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Sandy Hook Lab. Ref. SHL
79-02. 263 pp.

Stoddard, A., J. E. O’Reilly, T. E. Whitledge, T. C. Malone, and J. F. Hebard. 1986. The
application and development of a compatible historical data base for the analysis of
water quality management issues in the New York Bight. Oceans ’86 Symposium,
Conference Record, Monitoring Strategies Symposium, Vol. 3 of 5, Sept. 23-25,
1986, Washington, D.C.

Sullivan, L. 1980. Distribution, abundance and mortality estimates of larval butterfish,
Peprilus triacanthus, from MARMAP surveys, 1977 and 1978. ICES C.M. 1980/G:18.

Sullivan, L. F., J. R. Goulet, Jr. 1980. Protocol for data flow through the MIS (MARMAP
Information System): Ichthyoplankton zooplankton, and related sampling data.
NOAA, Nat: Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 80-
53.

132

_ %-US. GOVERNMENT PRINTING OFFICE: 1988-5 01-716 /80074


minimum larval length of 3 mm, a maximum larval length of 20 mm, and a length interval
of 0.1 mm. A 50% sampling coefficient of variation was calculated from actual silver hake
data based on a sample size of about 50. The sampling coefficient of variation is propor-
tional to the square root of sample size. The standard value of the sampling coefficient of
variation was taken as 50%. A new random variation was applied to each 1 mm length in-
terval within each cruise. This was done because preliminary analysis of actual data indi-
cated minimal covariance between 1 mm length intervals. For these preliminary simula-
tions the only sources of uncertainty that were modelled were the random start date of the
first cruise and the sampling variability.

Use of the standard parameters resulted in a 118% standard deviation for silver
hake and a 159% standard deviation for haddock. This means that two-thirds of the ratios
for silver hake were between 0.46 and 2.18; for haddock the range was about 0.39 to 2.59.
The medians of the results were in most cases close to one and present less of a problem
than the percent standard deviations which can be large.

Figs. 13 and 15 show how the percent standard deviation may be reduced by increas-
ing the number of cruises. Very few cruises produced grossly unsatisfactory results while a
very high number of cruises produced little advantage over a moderately high number.
The different results for the two species was due in large measure to the smaller standard
deviation of the haddock spawning curve. Fig. 21 shows how silver hake would respond if
the standard deviation of its spawning curve was changed. If it was changed to 21 days, the
result would be a 145% standard deviation.

Figs. 17 and 19 show how the sampling coefficient of variation effects results.
Decreasing the sampling variation decreases the variability of the results. The current sam-
pling coefficient of variation of 50% was attained by using 50 samples per cruise (n=50).

he number of samples per cruise necessary to attain various sampling coefficients of
variation is also indicated on Figs. 17 and 19. The diminishing returns of increasing the
. number of samples per cruise is thus made evident.’

Figs. 17 and 19 may be used to estimate the effects of various sampling strategies.
Suppose that it were possible to change the cruise interval from 61 days to 30 days. Would
this be a cost effective way of improving the estimate of silver hake spawning? Fig. 17
shows that this would have the same effect as retaining a cruise interval of 61 days and
decreasing the sampling coefficient of variation to about 37. That sampling coefficient of
variation corresponds to about 90 samples per cruise. Decreasing the cruise interval from
61 to 30 days would about double the cost. Since the number of samples per cruise could
be increased from 50 to 90 for less than double the cost, this would be more cost effective
than doubling the number of cruises. The same rationale can be applied to haddock in Fig.
19. In this case, however, about 300 samples per cruise would be necded to produce the
same improvement as reducing the cruise interval to 30 days.

These figures may also be used to evaluate a reduction in sampling intensity. If the
cruise interval is changed from 61 to 91 days for silver hake, it would have the same effect
as changing the number of samples per cruise from 50 to 28. However, if the cruise inter-
val were changed to 91 days, the results for haddock would deteriorate beyond the point of
being useful; a deterioration for which an increased number of samples per cruise could
not compensate.

A notable feature of Fig. 17 is that the curves for 91 and 61 days are parallel while
those for 30 and 61 days merge for low values of sampling coefficient of variation. The
parallel form also appears in Fig. 19 for haddock. This means that the beneficial cffects of
reduced cruise interval is independent of sampling coefficient in some cases. However, as

78


Buzeta, M.-L, and K. G. Waiwood. 1982. Fecundity of Atlantic cod (Gadus morhua) in the
southwestern Gulf of St. Lawrence. Canadian Tech. Rept. Fish. Aquat. Sci. 1110:6

PP. eo

Clark, S. H., and B. E. Brown. 1977. Changes in biomass of finfishes and squids from the
Gulf of Maine to Cape Hatteras, 1963-74, as determined from research vessel sur-
vey data. Fish. Bull., U.S. 75:1-21. ‘ :

Conservation and Utilization Division, NEFC. 1985. Status of the fishery resources off the
northeastern United States for 1985. NOAA Tech. Mem. NMFS-F/NEC-42. 137

PP.

_ Cupka, D. M., R. K. Dias, and J. Tucker. 1973. Biology of the black sea bass, Céntropristis
striata (Pisces: Serranidae) from South Carolina waters. S.C. Wildl. Mar. Resour.
Dep. (unpubl. ms.). 93 pp. : . : foe vies

Earll, R. E. 1883. The Spanish mackerel, Cybium maculatum (Mitch.) Ag.; its natural his-
‘ tory and artificial propagation,. with an account of the origin and development of
the fishery. Rep. U. S. Commer. Fish. 1880, pp. 395-426. ~~ ”

Freeman, B., and’S. Turner. 1977. Biological and fishériés data on tilefish, Lopholatilus
chamaeleonticeps Goode and Bean. SHL, NEFC; Tech. Ser. Rep. No. 5, 41 pp.

Hardwick, J. E. 1973. Biomass estimates of spawning herring, Clupea'pallasi, herring ‘eggs
and associated vegetation in Tomales Bay. Calif. Fish Game 59(1):33-61.

Hennemuth, R. C._ 1979. Man’as predator. ‘pp. 507-532. Jn Patil, G. P. and M.
Rosenzweig (Eds.), Contemporary Quantitative Ecology and Related Ecometrics.

Hodder, V. M. 1963. Fecundity of Grand Bank haddock. J. Fish, Res. Board Can.
20:1465-1487. : ; a BO , a

Houde, E. D. 1977. Abundance and potential yield of the round herring, Etrumeus teres,
and aspects ofits early life history in the eastern Gulf of Mexico. Fish. Bull., U.S.
75:61-89. : :

‘Houghton, R. G., J. M: Last, and P. J. Bromley. 1985. Fecundity and egg size of sole
(Solea solea (L.)) spawning in captivity. J. Cons. int. Explor. Mer 42:162-165.

Howell, W. H., and'D. H. Kessler. 1977. Fecundity of the Southern New England stock of
yellowtail flounder, Limanda ferruginea. Fish. Bull., U.S. 75:877-880. os

Iversen, S. A. 1977. Spawning,: ee production and stock size of mackerel (Stomber
scombrus L.) in the North Sea 1968-1975. ICES C. M. 1977/H:17. 18 pp. (mimeo).

Iversen, S. A., and A. Eltink. 1983. Spawning, egg-production and stock size’ of North Sea
mackerel in 1982, ICES C.M. 1983/H:46. 12 pp. (mimeo).

Ivo, C.T.C. 1974. Epoca de desova e idade na primeira maturacao sexual da cavala, Scom-
beromorus cavalla, no Estado do Ceara. Arq. Cien. Mar. 12(1):27-29.

Jackson, H. W., and R. E. Tiller. 1952. Preliminary observations on spawning potential in
the striped bass (Roccus saxatilus) (Walbaum). Md. Dep. Res. Educ., Publ. 93:16 pp.

32


DATA COLLECTION AND METHOD OF ANALYSIS -

Six to seven ichthyoplankton surveys have been conducted each year (1977-present).
Stations are 25.to 35 km apart, and approximately 180 stations were sampled with 35 to 50
in each of four subareas of the Northeast Continental Shelf ecosystem, Mid-Atlantic,
Southern New England, Georges Bank, and Gulf of Maine. A standard 61-cm bongo net
array fitted with 0.505- and 0.333-mm mesh nets (Posgay and Marak, 1980) was used. All
larvae from the 0.505-mm net were enumerated and identified to the lowest taxon possible.
The larvae were measured to the nearest 0.1 mm. ‘Survey methods are outlined in this
volume by Smith and Goulet and described in detail by Sibunka and Silverman (1984).

The larval data were then used to develop spawning stock estimates. The length
and abundance of larvae were corrected for. net extrusion, net avoidance, and shrinkage
(Smith and Richardson, 1977). Length frequencies were converted to age frequencies
using a temperature dependent growth function and the temperature at time of capture.
Larval mortality was calculated by summing age frequencies over all surveys of the year
and determining the slope of the exponential regression line of age vs. frequency. This lar-
val mortality was used to back-calculate frequencies to-hatching. Estimates of egg mor-
tality and egg incubation time were used to, back calculate to the number of eggs spawned
at each station. The total number of eggs spawned in the survey area was then determined.
Spawning stock biomass was calculated from the eggs .spawned:using appropriate length,
weight, fecundity, and sex ratio information. See Morse (1984), Zweifel and Smith (1981),
and Hewitt and Methot (1982) for a more detailed explanation.

This. method contains assumptions and approximations which influence the biomass
estimation. These lead to numerous questions. Are there sufficient cruises per year to
develop an adequate spawning curve? Is the calculated larval mortality .rate based on these
cruises sufficiently accurate? Is. the within-survey variability excessive for accurate deter-
mination of spawning stock biomass? How important are precise length measurements?
How important-are. precise estimates of larval growth rates? How important is’ precise
temperature information? Which species are appropriate for this method? What spawn-.
ing and growth characteristics must such species have? What degree of random variability
can be tolerated in the environment, the species characteristics, and the cruise schedule?
The computer model is designed to answer questions such as these. ta,

MODEL DESCRIPTION

A simplified flow chart of the computerized simulation model is given.in Fig: 1. The
model simulates fish eggs and larvae in their environment, sampling of fish larvae, and es-
timation of the number of eggs spawned. The ratio of the estimated to simulated number
of cogs spawned is a measure of effectiveness of spawning stock size estimates derived
from farval abundance data.

The model has three modules. The first module simulates.the spawning of eggs, egg
development and mortality, and larval growth and mortality. Inputs to the model include a
species-specific spawning curve (eggs Spawned per day vs. day of the year) and an annual
temperature regime (temperature vs. day). Mortality rates for eggs and: larvae are input.
Egg development time and larval growth rate.are modclled as functions of daily tempera-
ture. The larval growth rate function has species-specific parameters, the egg development
time function does not... The model simulates anomalies (random variations) in tempera-
ture and biological rates. : .

73


The estimated instantaneous mortality rate per mm length was used to scale up the
number at length to the number of 3 mm larvae produced by taxon, year, and subarea.
These subareas are the Gulf of Maine, Georges Bank, Southern New England, and Middle
Atlantic Bight. The mean abundance per 10 m? of 3 mm larvae, adjusted for mortality, was
calculated for each subarea and survey. Figs. 3 and 4 show results of larval abundance
scaled up to 3 mm for Atlantic cod and silver hake compared to the unscaled abundances.
The scaled up abundance was then divided by the number of sampling days used to com-
plete the survey within a subarea. This is an index of the daily production of 3 mm larvae
per 10 m? for cach survey and subarea. The average of these values gives an index of the
production rate per day of 3 mm larvae during the entire spawning season.

An index of annual production of 3 mm larvae was determined by multiplying the
daily production rate times the number of days within the spawning season for cach sub-
area‘and taxon. The beginning of. the spawning season was estimated as the midpoint day
between the start of the first survey of the year which contained larvae for the target
species and the end of the previous survey. The end of the spawning season was estimated
as the midpoint day between the end of the last survey of the year with the target species
and the beginning of the subsequent survey. The number of days between the midpoint
days defined the spawning season. The daily index of larval production was multiplicd by
the total number of days within the spawning season to yield the index of annual larval
production per 10 m®.. The annual production estimate was then multiplicd by the surface
area within each subarea and summed to give the total annual production within the survey
area.

RESULTS AND DISCUSSION
Mortality Rates

The estimates of average instantaneous mortality rate per mm length for 15 taxa are
iven in Table 1. These rates do not account for interannual variability in mortality, but do
indicate the considerable range and trends of values between species. The lowest rate
(0.17) was. found for sand eel (Ammodytes spp.), which is a slow-growing, winter-spawnin,
taxon. The fast-growing, summer-spawning triglids have the highest rate (0.97). Little dif-
ference in mortality is seen for winter-spawning fish (range 0.17-0.20). The four spring-
spawners have.a low mortality of 0.23, higher than the highest winter spawner, and a high
of 0.66.- The summer spawners have one of the lowest mortalities listed at 0.20, but also
have the two highest recorded at 0.75 and 0.97. Although both spring- and summer-
spawner mortalities are quite variable, the average mortalities within each season show a
clear trend of increasing from a low of 0.19 in winter to 0.40 in spring and 0.48 in summer.

The calculation of length-dependent mortality, whether daily, seasonal, or annual is,
of course, interrelated to the growth rate of the individual larvae used in the calculation. A
constant rate of growth and mortality must be demonstrated for all individuals in the
samples for length-dependent mortality estimations to reflect actual changes in larval
population mortalities. The assumption of constancy of growth and mortality rates is, of
course, difficult to demonstrate from bimonthly survey catch data. However, assuming
seasonal trends in growth rates, i.e., growth rates increase with increasing temperature, the
classical Q,, function, leads to some interesting conclusions. By applying thc Q,, function
to larval growth qualitatively, then larval growth will increase from winter water tempera- =
ture conditions to a peak during the summer. If this is the case, then a larva of a given
length is older if captured during winter than if captured in summer, all else being equal. If
age-dependent mortality remains constant regardless of season (water temperature) then
estimates of length-dependent mortality would be higher in winter than in summer. This

50


The second module simulates the sampling of larvae. The control variables that
characterize the sampling regime and determine its effectiveness are the target interval be-
tween cruises, precision of larval abundance estimates within cruises (which is a function of
sample size), and the resolution of length measurements. The model allows for an
anomaly in the cruise date (relative to the target date) and sampling error in larval density
at the time of each cruise.

The third module uses the simulated data from module two to estimate the number
of eggs spawned. The same annual temperature regime, egg development parameters, and
growth rate parameters that were used in module one are used here. Larval mortality rate
1s estimated from the simulated length composition data. This estimate of mortality rate is
used to back calculate the number of eggs spawned.

In general, the simulation is: run one hundred times for each set of parameters. The
hundred simulations differ due to the random variables. Not all of the random variables
need be exercised during each set of one hundred simulations. In this way, the sensitivity
of the results to these random factors can be evaluated. A more detailed description of the
model follows. Deterministic and random components of the model are described
separately.

Water temperature is modelled as a sine/cosine function of the day of the year. The
parameters of the function are specific to the location where larval samples are collected.
All the simulations described in this paper apply to Georges Bank (off the northeastern
USA). The appropriate model is:

TEMP=9.46-4.86*SIN(0.0172*DAY)-1.43*COS(0.0172*DAY)

where TEMP equals the temperature in degrees Centigrade, DAY equals the day of the
year (Fig. 2). The parameters are for Georges Bank for the period 1977-1986 at a depth of
0 to 50 m (Mountain, 1986).

A normal spawning function truncated to 0-at ~ 3 standard deviations is used. The
mean, standard deviation, and the area under the curve are specificd as input parameters.
In the first module of the model, the abundance of each simulated daily cohort (individuals
spawned on a specific day) is maintained up to a maximum age (AMAX) specified as an
input parameter. The maximum age corresponds to the maximum age vulnerable to sam-

pling.

The spawned eggs are subjected to egg development, egg mortality, larval growth,
and larval mortality. The simulation uses a 1-day timestep.

The mortality rates are used in the formula:
N2=N1*EXP(-M)
where M is the mortality rate '
N2 is the number of organisms on a given day
N1 is the number of organisms on the preceding day.

Egg development time from spawning to hatching (Fig. 3) is calculated from the for-
mula:

TIME=0.0495462*EXP(6.63757*EXP[-0.0266*TEMP])

74


CALCULATED/INPUT EGGS SPAWNED

LEGEND
O = SAMPLING COEFFICIE

aaa

MEDIAN
0.8250.850 0.875 0.900 0.925 0.950 0.975 1.000 1.025

T T T T T — ——1
0.000 0.025 0.080 0.075 0,100 0.125 0.150 0.175 ~ 0.200
MORTALITY RATE 7

Fig. 28. Median as a function of mortality rate.

109


ABSOLUTE ABUNDANCE ESTIMATES USING TRAWL AND
ICHTHYOPLANKTON SURVEY DATA

Michael Pennington

National Marine Fisheries Service
Northeast Fisheries Center
_ , Woods Hole Laborato:
ot a . Woods Hole, MA 0254.

ABSTRACT

Planktonic egg surveys and bottom trawl surveys both provide unique and valuable
measures of the abundance and composition of fishery resources, but the type of informa-
tion. derived from each survey is quite different. The egg surveys can provide estimates of
the absolute abundance of fish, whereas the trawl surveys produce relative measures of
abundance (i.e., catch per standard haul). An estimate of the mean ratio of the absolute-
to-relative abundance provides a basis for converting trawl survey indices from relative to
absolute. measures of abundance. . The, technique is illustrated with data on the yellowtail
flounder, Limanda ferruginea, in Southern New England and Georges Bank waters.

INTRODUCTION

For many. species, egg surveys are the only fishery independent means to estimate
the absolute abundance of adults. Even for major exploited species, spawning stock es-
timates derived from egg surveys. may be needed to check the accuracy of.other stock size
estimates. However, several egg surveys throughout the spawning season are needed along
with considerable sample processing to obtain estimates of acceptable precision for a single
species/stock. The plankton samples must first be sorted back in the laboratory, and then
further laboratory analysis must be done on eggs (staging) for the species of interest before
deriving ‘abundance estimates. In addition, it is:necessary to know (or determine)
temperature-dependent egg development rates and age/length fecundity relationships for
the stock. At best there is a lag of six months to a year before the estimates are available.

_ Incontrast, a.single trawl survey can generate abundance data on a large number of
species (including immature stages).within a matter of a few days or weeks, but the result-
ing indices are estimates of relative abundance, not of.absolute abundance. The trawl in-
dex is assumed to be proportional to the actual population of fish, and if this is the case,
the time series of trawl surveys can be used to monitor trends in abundance. However, the
constants of proportionality are generally not. known and may be different for each specics
or. even for different stocks of the same species. Thus, it is often difficult to compare the
abundance of. different species or stocks. .

The egg surveys can be used to calibrate the trawl index, that is, to estimate the
proportionality constant relating the trawl survey index and the actual abundance. of fish.
Given several pears with both egg and trawl survey data, we can use these proportionality
constants to. check the, critical assumption that they are consistent over time. If this as-
sumption holds, then.one can use:the mean coefficient for calculating the changes in ab-
solute:abundance for the.entire time series of the trawl surveys. The objective of this paper
is to illustrate-the technique. ‘ ., .

112


A COMPARISON OF INFORMATION CONTENT FROM TRAWL AND
ICHTHYOPLANKTON SURVEYS

Wallace G. Smith

National Marine Fisheries Service
Northeast Fisheries Center
Sandy Hook Laboratory
Highlands, NJ_ 07732

ABSTRACT

Spearman’s Rank Correlation Test was used to determine whether finfish com-
munity information collected on trawl and ichthyoplankton surveys of shelf waters from
Cape Hatteras, N.C., to Cape Sable, NS., is complementary or redundant. Results show
that the two data sets are complementary. There was no positive correlation between trawl
listings of stratified mean weight tow’' or stratified mean number tow’' and an ich-
thyoplankton jisting of mean number of larvae 10 m* surface area. Combining results of
trawl and ichthyoplankton surveys provides a more comprehensive approach for monitor-
ing finfish community structure than utilizing information from. only one of the sampling
strategies.

INTRODUCTION

Decadal time series of biological.and oceanographic observations are needed to
monitor changes and formulate and test hypotheses that will provide an understanding of
the interactive processes that regulate fish production in the sea. To that end, coastal trawl
surveys of groundfish populations were initiated by the Northeast Fisheries Center (NEFC)
in 1948 with objectives to: (1) monitor fluctuations in structure and size of fish popula-
tions; (2) assess fish production potential; (3) determine environmental factors controlling
fish distribution and abundance, and (4) provide ecological data to understand inter-
relationships between fish and their environment (Grosslein, 1969). Trawl surveys were
standardized in 1963. A few years later (1953) surveys of fish eggs and larvae of varying
scope, intensity and purpose were initiated and continued thereafter into the 1970’s. Some
targeted a single species and were areally limited, others were more extensive in both
coverage and objectives (Marak and Colton, 1961; Boyar et al., 1973; Lough ct al., 1985).
Beginning in 1977, NEFC scientists initiated a standardized survey of fish eggs and larvae
off northeastern United States that is part of the Center’s ongoing Marine Resources
Monitoring, Assessment, and Prediction (MARMAP) Program (Sherman et al., 1983).
The objective of this paper is to compare the principal taxa collected on NEFC’s two major
survey efforts from the late 1970’s through the early 1980’s and determine whether they are
complementary or redundant.

METHODS

Trawl survey methods are reviewed by Azarovitz (1981); ichthyoplankton survey
methods by Smith and Goulet (this volume). For a detailed description of ichthyoplankton
survey procedures, see Sibunka and Silverman (1984). Trawl surveys are conducted twice
annually, in late winter/early spring and in autumn; ichthyoplankton surveys are carried out

19


LIST OF TABLES
MARMAP ICHTHYOPLANKTON SURVEYS: AN OVERVIEW OF
METHODS AND DATA BASE MANAGEMENT
1. Summary of MARMAP I survey activities, 1977-1987. . 2. 2... 2 2 ee

A COMPARISON OF INFORMATION CONTENT FROM TRAWL AND
ICHTHYOPLANKTON SURVEYS

1. Comparison of 20 principal taxa from combined spring and fall
NEFC trawl surveys (weighted mean weight/tow (kg) 1977-1984) and ich-
thyoplankton surveys (mean number of Jarvae/10 m* surface area

1977-1983). 6 6 we ee ee

USE OF EGG DATA TO ESTIMATE TOTAL FINFISH BIOMASS FOR
THE NORTHEAST CONTINENTAL SHELF ECOSYSTEM.

1. Fecundity values for 23 fish species used in calculating spawner
biomass estimates from MARMAP I egg samples... . . 2... --

2. Fish-egg species-composition of MARMAP J samples, 1979 and 1980. . . .
3. Response of g,,t,andxtog,andt,.. 2... . 2... e Lee

4. Annual cag production, spawner biomass, and total population biomass
estimates, 1979-1984... 2. 1 1 ee ee ee

LENGTH-DEPENDENT MORTALITY AND AN INDEX OF SPAWNING
BIOMASS FROM LARVAL ABUNDANCE

1. Estimates of the instantaneous mortality rates per millimeter length
for fish larvae collected on MARMAP ichthyoplankton surveys, 1977-

Page

1984... ee 53

2. Index of annual production of 3-mm larvae per 10 m? for six principal
taxa by subarea and total annual production for all subareas combined
(totalx 103). 2 ee

VARIABILITY IN MARMAP SURVEY MEAN CATCH PER TOW

1. The results of the application of Taylor’s power law to the MARMAP
larval fish data, . 1. ee ee

2. Pearson product-moment correlations of abundance of larvae for
lengths between 3 and 14 mm for silver hake and haddock... 2. 2 1 ee


Sand, R. L., J. R. Goulet, L. J. Bass, and S. H. Koelb. 1985. The design and management
of a large ecosystem database using a scientific data base management system.
Paper for presentation at the 4th Working Symposium on Oceanographic data sys-
tems, Scripps, La Jolla, CA. Sponsored by IEEE. (NOAA, Nat. Mar. Fish. Scrv.,
Northeast Fish. Ctr, Narragansett Lab. Ref. No. 85-21; also MARMAP Contribu-
tion No. FED/NEFC 85-22).

Schneider, D. C., G. L. Hunt, and K. D. Powers. 1980. Energy flux to pelagic birds: A
comparison of Bristol Bay (Bering Sea) and Georges Bank (Northwest Atlantic).
pp. 259-277. In J. P. Crosall (Ed.) Seabirds: Feeding ecology and role in marine
ecosystems. Cambridge Univ. Press, Cambridge (UK). 408 pp.

Selzer, L. A., and P. M. Payne. [1988.] Ecological differences in the distribution of the
white-sided dolphin (Lagenorhynchus acutus) and common dolphin (Delphinus del-
phis) in the shelf waters of the northwest Atlantic. Mar. Mamm. Sci. (in press).

Sherman, K. 1978. Ecological implications of biomass changes in the Northwest Atlantic.
ICES C.M. 1978/L:24. . ao

Sherman, K. 1979. Oil, fisheries, and the Georges Bank ecosystem. NOAA, Nat. Mar.
Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 79-38.

Sherman, K. 1979. MARMAP fishery ecosystems study news. NOAA, Nat. Mar. Fish.
Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 79-12. :

Sherman, K. 1979. Report.of the ICES Working Group on Larval Fish Distribution.
ICES C.M. 1979/L:10. : :

Sherman, K. 1979.. Fisheries ecosystem studies off the northeast coast of the United
States: Summary of the initial results. ICNAF Res. Doc. 79/VI/114. :

Sherman, K. 1979. Emerging ecosystem theory in relation to plankton studies in the
Northwest Atlantic. -ICNAF Res. Doc. 79/VI/117. . :

Sherman, K. 1980. MARMAP, a fisheries ecosystem study in the NW Atlantic: Fluctua-
tions in the ichthyoplankton-2ooplankton components and their potential for impact
on the system. pp. 9-37. In F. P. Diemer, F. J. Vernberg, and D. Z. Mirkes (Eds.)
Advanced concepts in ocean measurements for marine biology. Belle W. Baruch
Institute for Marine Biology and Coastal Research. Univ. South Carolina Press,
Columbia.

Sherman, K. 1980. MARMAP fisheries ecosystem studies off the northeast. coast of the
USS. Paper presented to the Workshop on Remote Sensing, hcld at Estes Park, CO,
19-25 August 1979. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett
Lab. Ref. No. 79-62. ,

Sherman, K. 1980. Biomass: Organization of a large-scale ecosystem study. Working
paper for International. Scientific Workshop on Management of Southern Ocean
Organisms. Co-sponsors: The Oceanic Society of the U.S., The Center for Law and
Social Policy, and International Union for Conservation of Natural Resources, Car-
negie Conference Center, Washington, DC. 31 March-2 April 1980. NOAA, Nat.
Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 80-23.

127


Saila, S. B. 1961. The contribution of estuaries to the offshore winter flounder fishery in
Rhode Island. Proc. Gulf Caribbean Fish. Inst., 14th Ann. Session pp. 95-109.

Saville, A. 1964. Estimation of the abundance of a fish stock from egg and larval surveys.
Rapp. P.-v. Reun. Cons. int. Explor. Mer. 155:164-170.

Sette, O. E. 1943. Biology of the Atlantic mackerel (Scomber scombrus) of North
America. Part I: Early life history, including growth, drift and mortality of the egg
and larval populations. U. S. Fish Wildl. Serv., Fish. Bull. 50(38):149-237.

Sheri, A. N., and G. Power. 1968. Reproduction of white perch, Roccus americanus, in the
Bay of Quinte, Lake Ontario. J. Fish. Res. Board Can. 25:2225-2231.

Sherman, K., C. Jones, L. Sullivan, W. Smith, and P. Berrien. 1981. Congruent shifts in
sand eel abundance in western and eastern North Atlantic ecosystems. Nature
291(5815):486-489.

Sibunka, J. D.,and M. J. Silverman. 1984. MARMAP surveys of the continental shelf from
Cape Hatteras, North Carolina to Cape Sable, Nova Scotia (1977-1983). Atlas No.
1. Summary of operations. NOAA Tech: Mem. NMFS-F/NEC-33. 306 pp.

Smith, P. E. 1972. The increase in spawning biomass of northern anchovy, Engraulis
mordax. Fish. Bull., U.S. 70:849-874.

Smith, W. G., and J. Goulet. This volume. MARMAP ichthyoplankton surveys: An over-
view of methods and data base management.

Stauffer, G. D. 1980. Estimate of the spawning biomass of the northern anchovy centeral
subpopulation for the 1979-80 fishing season. CalCOFI Rep. 21:17-22.

Topp, R. W. 1968. An Estimate of fecundity of the winter flounder, Pseudopleuronectes
americanus. J. Fish. Res. Board Can. 25:1299-1302.

Walsh, M., P. Hopxins, and P, Rankine. 1983. Results of the North Sea mackerel egg sur-
veys in 1982. ICES C.M. 1883/H:49. 24 pp. (mimeo).

Westin, D. T., K. J. Abernathy, L. E. Meller, and B. A. Rogers. 1979. Some aspects of

biology of the American sand lance, Ammodytes americanus. Trans. Am. Fish. Soc.
108(3):328-331.

34


LENGTH-DEPENDENT MORTALITY AND AN INDEX OF SPAWNING

BIOMASS FROM LARVAL ABUNDANCE--Wallace W. Morse... 2... 49
Abstract, 2. ee 49
Introduction 49
Methods... 49
Results and Discussion , 2... 50
Literature Cited ©. ee 52

VARIABILITY INMARMAP SURVEY MEAN CATCH PER

TOW--Wallace W. Morse, 2... 60
Abstract, | ee 60
Introduction, - 60
Method 2 ow 61
Results and Discussion... . ee ee 61
Literature Cited |. ee 62

A MODEL TO EVALUATE SPAWNING STOCK SIZE ESTIMATES

DERIVED FROM LARVAL ABUNDANCE--John W. Hauser, .

Michael P. Sissenwine, and Wallace W. Morse... . 2... ee ee 72
Abstract, | 72
Introduction, . og ee 72
Data Collection and Method of Analysis, . 2... te ee 73
Model Description... Le ee 73
Results.and Discussion | |)... ee 77
Conclusions, | fe 80
Literature Cited 2.) 80

ABSOLUTE ABUNDANCE ESTIMATES USING TRAWL AND

ICHTHYOPLANKTON SURVEY DATA--Michael Pennington, 2... . 112

Vili


Equation (3) was applied to C for each survey and subarea. C and its standard er-
ror were calculated by Pennington’s (1983) method based on the delta distribution. Term
A was set equal to the surface area of each subarea. The mortality rate was assumed to be
10%'d"! (Z = 0.10536). This is a reasonable, somewhat conservative, estimate of daily e
mortality based on observed rates of 5.0% for Atlantic mackerel in 1932 (Sette, 1943),
11.6% for Atlantic mackerel in 1977 (Berrien et al., 1981), 16.2% for yeHowtail flounder
(Limanda ferruginea) in 1977 (Berrien, 1981), 47.0% for silver hake (Merluccius bilinearis)
in 1979 (Berrien, 1983), a mean of 11.8% for Atlantic cod (Gadus morhua) and haddock in
1979-1982 (Berrien, unpubl. data) and a mean of 26.6% for yellowtail flounder in 1979-
1982 (Berrien, unpubl. ms.). Julian date midpoints of sampling corresponding to each cal-
culated mean egg density were derived using first and last positive-tow occurrences in each
subarea. The time span (T) representing each survey was defined as extending from
halfway between preceding and following survey midpoints, truncated at year’s end. The
value for fecundity (F), the number of eggs produced annually per unit weight of spawners,
was determined from existing information on 23 species (Table 1). Fecundity values for
species co-occuring on Tables 1 and 2 were weighted by their respective percent abun-

lances. For species‘whose fecundity is unknown the overall mean for 23 species (720 eggs
per gm female) was used, weighted by the combined percent abundance of these species.
Assuming a 1:1 sex ratio the weighted mean fecundity values per gm female were con-
verted to the following fecundity values per metric ton (mt), both sexes included: Gulf of
Maine 453,200,000, Georges Bank 342,450,000, Southern New England 504,550,000 and
Middle Atlantic 374,450,000. In order to allow adjustment of catches for mortality a time
period of egg incubation (t) was estimated. Incubation time was calculated from prevailing
temperature and the function shown in Fig. 2, The data points and resulting fitted curve in
this figure are based on existing information for 30 species of marine fish eggs. Prevailing
water temperature at the time of each survey within each subarea was calculated from
regressions of mean water-column temperature on Julian date from hydrographic survey
data (Mountain, 1985; D. G. Mountain, pers. commun.).

The number of eggs spawned per day (K,), which is an index of spawning intensity,
is derived from equation (3) by multiplying by F and dividing by T:

K, = CAZ/l-e* (4) °

Since the demersal eggs of sand eel are rarely seen in our plankton samples, and be-
cause this fish is known to constitute a significant portion of the finfish biomass within our
survey area (Sherman et al., 1981), we added estimates of spawner biomass of sand eel
based on larva data to that of other species based on egg data. Sand cel spawner biomass
for the total survey area has been calculated at between 701,440 and 1,228,830 mt over the
years 1979 to 1984 (W. W. Morse, pers. commun.).

In addition to the egg species comprising the bulk of our samples (Table 2) and
sand eel noted above, certain other species do not produce pelagic eggs (e.g. herring,
winter flounder, dogfish, and skates) and are not represented by our egg collections. These
species currently account for about 29% of the finfish and squid biomass cstimates based
on otter trawl data using the method of Clark and Brown (1977) (S. H. Clark, pers.
commun.). The biomass estimates derived from eggs were raised by 29% to account for
these species.

28


CALCULATED/ INPUT EGGS SPAWNED

LEGEND .
O = SAMPLING COEFFICIENT OF VARIATION ‘= 0%
O= SAMPLING COEFFICIENT OF VARIATION = SOZ

80.0 100.0 120.0 140.0
L L 1 —

60.0

PERCENT STANDARD DEVIATION
40.0

ag —e = —- = & =,
T
0

si)
a

500.075 1000125 | OIS 0178 0.200
MORTALITY RATE

T
0.000 0.025 io}

Fig. 27. Percent standard deviation as a function of mortality rate.
108


National Academy of Sciences [NAS]. 1979. Carbon dioxide and climate: A scientific
assessment. Climate Research Board, Nat. Acad. Sci., Washington, D.C. 496 pp.

Sherman, K., and L. M. Alexander (Editors). 1986. Variability and management of large
marine ecosystems. AAAS Selected Symposium 99, Westview Press, Boulder, CO.
319 pp.

Sherman, K., and L. M. Alexander (Editors). In press. Biomass and geography of Large
Marine Ecosystems. AAAS Selected Series. Westview Press, Boulder Colorado.

Sherman, K., J. R. Green, J. R. Goulet, and L. Ejsymont. 1983. Coherence in zooplankton
of a large Northwest Atlantic ecosystem. Fish. Bull., U.S. 81:855-862.

Sherman, K., C. Jones, L. Sullivan, W. Smith, P. Berrien, and L. Ejsymont. 1981. Con-
gruent shifts in sand eel abundance in western and eastern North Atlantic ecosys-
tems. Nature 291(5815):486-489.

Sherman, K., W. Smith, W. Morse, M. Berman, J. Green, and L. Ejsymont. 1984. Spawn-
ing strategies of fishes in relation to circulation, phytoplankton production, and
pulses in zooplankton off the northeastern United States. Mar. Ecol. Progr. Ser.
18:1-19. .

Sissenwine, M. P., and J. G. Sheperd. 1987. An alternative perspective on recruitment
overfishing and biological reference points. Can. J. Fish. Aquat. Sci. 44:913-918.

Smith, P. E., and S. L. Richardson. 1977. Standard techniques for pelagic fish egg and
larvae surveys. FAO Fish. Tech. Paper 175, Rome.

Ursin, E. 1977. Multispecies fish stock assessment for the North Sea. ICES C.M.
1977/F:42. 19 pp. ,


paper examines the relationship for the. twenty most abundant spccics of larvac.
The other important control variable is the frequency of surveys. The following paper
describes a simulation model that was designed to evaluate the sensitivity of back-
calculations of spawning biomass from larval abundance to: (a) sample size within surveys,
b) survey frequency, (c) several biological characteristics of the fish populations, and
d) certain assumptions of the method. The simulation model is a powerful tool that will
continue to be used to refine survey design and estimation procedures.

For many species of marine fishes, surveys of spawning products provide the only
fishery independent means to estimate the absolute abundance of adults. The final paper
illustrates a procedure for converting trawl survey indices from relative to absolute
measures of abundance by using egg survey data to estimate a proportionality constant
relating the trawl survey index and the actual abundance of fish.


nique for estimating a proportionality constant that can be used to convert trawl survey in-
dices from relative to absolute measures of abundance. If we can demonstrate from
several years of trawl and egg surveys that the proportionality constants are consistent over
time, the mean coefficient can be used for calculating changes in absolute abundance for
NEFC’s entire trawl survey time series.

Michael P. Sissenwine

Chief, Fisheries Ecology: Division
Northeast Fisheries Center
Woods Hole, MA 02543


APPENDIX: LIST OF REPORTS BASED ‘ON MARMAP SURVEYS

Able, K. W., M. P. Fahay, and D. F. Markle. 1987, Development of larval snailfishcs
(Pisces: Cyclopteridae: Liparidae) from the western North Atlantic. Can. J. Zool.
64:2294-2316. .

Able, K. W., D. F. Markle, and M. P. Fahay. 1984. Cyclopteridae: development. «pp.
428-438. In H. G. Moser, W. J. Richards, D. M. Cohen, M. P. Fahay, A. W. Kendall,
Jr., and S. L. Richardson (Eds.) Ontogeny and systematics of fishes. Am. Soe. Ich-
thyol. Herpetol., Spec. Publ. 1:760 pp.

Azarovitz, T. R, CJ. Byrne, M. J. Silverman, B. L. Freeman, W..G. Smith, S. C. Turner, B.
A. Halgren, and’P. J. Festa. 1980. Effects on finfish and lobsters. Chap. 13, pp.
295-314. In R. L. Swanson and C. J. Sindermann (Eds.) Oxy; nogen depletion and as-
sociated benthic mortalities in New York Bight, 1976. NOAA Prof. Paper 11.

Berman, M. S., H. P. Jeffries, R. M. Lambert, and K. Sherman. 1981. Environmental
gradients on a coastal megalopolis II: Size frequency distributions in zooplankton.
CES C.M. 1981/L:28.

Berrien, P. 1981. Comments 0 on efficiency of NEFC surveys. ICES Larval Fish Ecology
Working Group Report, Lowestoft, Suffolk, UK, 1-3 July 1981. NOAA, Nat. Mar.
» Fish. Serv., Northeast Fish. Ctr., Sandy Hook Lab. Ref. 82-2.

Berrien, P. L. 1981. Yellowtail flounder, Limanda ferry gine, estimates of egg abundance
and population size during spring 1977 in Gulf of Maine, Georges Bank, Southern
New England, and Middle Atlantic Bight waters. ICES C.M. 1981/G:65.

Berrien, P. 1983. Silver hake, Merluccius bilinearis egg census and adult Eopailation es es-
timate for 1979 in waters off eastern United States. ICES C.M. 1983/

Berrien, P. 1984, Silver hake, Merluccius bilinearis, egg census and adult population es-
timates for 1979 and 1980 in waters off eastern United States. ICES CM.
1984/G:29. (MARMAP Contribution No. MED/NEFC 84-14).

Berrien, P., W. Morse, and M. Pennington. 1984. Recent estimates of adult spawning
stock biomass off northeastern United States from MARMAP Tchthyoplankton Sur-
veys. NOAA Tech. Mem. NMFS-F/NEC-30. 111 pp.

Berrien, P. L., N. A. Naplin, and M. R.. Pennington. 1981. Atlantic mackerel, Scomber
scombrus, egg production and spawning population estimates for 1977 in the Gulf of
Maine, Georges Bank, and Middle Atlantic Bight. Rapp. P.-v. Reun. Cons. int. Ex-
plor. Mer 178:279-288.

Busch, D., and J. Green (Compilers). 1981. Reference document: U.S.-U.S.S.R. coopera-
tive fisheries research in the Northwest Atlantic, 1981 meeting, 16-19 November,
Moscow. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr., Narragansett Lab.
Ref. No. 81-79.

Busch, D. A., and D. Mountain. 1982. Phytoplankton biomass and physical conditions on
Georges Bank in an area of larval cod and haddock concentrations. EOS, Trans.
Am. Geophys. Union 63(3). Abstract only.

120


CALCULATED/INPUT EGGS SPAWNED

LEGEND
O-= CRUISE INTERVAL = 30 DAYS
O= CRUISE INTERVAL = 61 DAYS
4 = CRUISE INTERVAL = 91 DAYS

n=25

4 ° i=) r=) 2
=) s=) r=) i)
+ NI 7 W
W u u ce
4 c <| c

“LV

n

\

ZO

mn

PERCENT STANDARD DEVIATION
0.0 25.0 50.0 75.0 100.0 125.0 150.0 175.0 200.0 225.0

N

34
°
2
3
roy

0.0 10.0 20.0 30.0 40.0 $0.0 50.0 70.
SAMPLING COEFFICIENT OF VARIATION

Fig. 17. Silver hake percent standard deviation as a function of sampling coefficient of
variation.

98


“sKoans CVWUVW UO pQ6t Suds 02 1/6] WO IYysNed seATE] SuIIOY ONUEPY [Je JO Aouonboy yISua] pourquiog -z “By

(wat) HLONST

Fooot

0002

oo0e

o00r

0005

0009

wetwesauz>

57


time, and a thorough quality control review of all data, 1977 through the present, was in-
itiated. As each data set was implemented, compromises were made to accommodate
limitations imposed by the PDP, or to reduce the complexity of the user interface. Fig. 3
shows the actual design and the links between the currently implemented data sets (bold).
The actual design (Fig. 3) differs from the conceptual design (Fig. 2) in that some data sets
have been composited to reduce linking complexity at the expense of data redundancy, and
some data sets have been split apart for storage efficiency.

LITERATURE CITED

Berrien, P., and ‘M. Sissenwine. This volume. Use of egg data to estimate total finfish
biomass for the Northeast Continental Shelf ecosystem.

Berrien, P., W. Morse, and M. Pennington. 1984. Recent estimates of adult spawning
stock biomass off northeastern United States from MARMAP Ichthyoplankton Sur-
veys. NOAA Tech. Mem. NMFS/F-NEC-30. 111 pp.

Sherman, K. 1986. Measurement strategies for monitoring and forecasting variability in
large marine ecosystems. pp. 203-321. In K. Sherman and-L. M. Alexander (Eds.)
Variability and management of large marine ecosystems. AAAS Selected Sym-
posium 99, Westview Press, Boulder, CO. 319 pp.

Sherman, K. This volume. Ichthyoplankton surveys: A strategy for monitoring change in a
large marine ecosystem. : . : .

Sibunka, J. D., and M. J. Silverman. 1984. MARMAP survey of the continental shelf from

Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). Atlas No.
1, Summary of Operations. NOAA Tech. Mem. NMFS-F/NEC-33. 306 pp:

12


Smith, W..G. 1982. Surveys reveal Atlantic herring larvae missing from Georges Bank.
Coast. Oceanogr. Climatol. News 5(1):7.

Smith, W. 1983. Temporal and spatial shifts in spawning times of selected fish and inver-
tebrate species in the Georges Bank region. (MARMAP Contribution MED/NEFC
83-28). NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Sandy Hook Lab. Rep.
No. SHL 83-08. 22 pp.

Smith, W. G. 1985. There are no shortcuts to understanding information required for
managing interdependent fish populations. Comm. Fish. News June 1985. p. 22.

Smith, W. 1987. BIOMAC: A proposal for a joint U.S.-Polish-Canadian spawning
biomass assessment of Atlantic mackerel (Scomber scombrus) off northeastern
United States and Canada, April through August 1987. NOAA, Nat. Mar.. Fish.
Serv., Northeast Fish. Ctr. Sandy Hook Lab. Ref. No. SHL 87-01. 10 pp.

Smith, W., P. Berrien, D. G. McMillan, and A. Wells. 1981. The distribution, abundance
and production of Atlantic cod and haddock larvae off northeastern United States
in 1978-79 and 1979-80. ICES C.M: 1981/G:52.

Smith, W., and E. Johnson. 1986. Contrasts in distribution patterns of larval Atlantic her-
ring in the Georges Bank area, early 1970's vs. early 1980’s. NAFO SCR 86/93:17

PP.

Smith, W., and W. Morse. 1984. Monthly distribution patterns of larval haddock,
Melanogrammus aeglefinus, off northeastern United States 1977-82, with observa-
tions on transport in the Georges Bank region. ICES C.M. 1984/G:30.

Smith, W. G., and W..W. Morse. 1985. Retention of larval haddock; Melanogrammus
aeglefinus, in the Scorges Bank region, a gyre-influenced spawning area. Mar. Ecol.
Prog. Ser. 24(1-2):1-13.

Smith, W. G., and W. Morse. 1985. Seasonal distribution, abundance, and diversity pat-
terns of fish eggs and larvae in the Middle Atlantic Bight. ICES C.M. 1985/L:27.

15 pp.

Smith, W. G., D. G. McMillan, C. Obenchain, P. Rosenberg, A. Wells, M. Silverman, E.
Baranowski, and N. Adamus. 1980. Spawning cycles of marine fishes off the north-
eastern United States based on broad scale surveys of eggs and larvae, 1977-79.
ICES C.M. 1980/L:66. 22 pp.

Smith, W., D. McMillan, and W.-Wells. 1981. Changes in northeastern ichthyoplankton
populations may be weather related. Coast. Oceanogr. Climatol. News 3(3):32-33.

Smith, W., D. G. McMillan, and A. Wells. 1981. The distribution and abundance of Atlan-
tic herring larvae in the Gulf of Maine region as determined from MARMAP sur-
veys, 1980-81. NAFO SCR Doc. 81/1X/115.

Smith, W., M. Pennington, P. Berrien, J. Sibunka, M. Koniecza, M. Baranowski, and E.
Meller. 1979. Annual changes in the distribution and abundance of Atlantic cod
and haddock larvae off the northeastern United States between 1973-74 and 1977-
78. ICES C.M. 1979/G:47. :

131


Page

A MODEL TO EVALUATE SPAWNING STOCK SIZE ESTIMATES
DERIVED FROM LARVAL ABUNDANCE

1. Computer simulation program flow diagram showing exogenous
and randomly assigned variables... 2 6 6 2 ee ee ee eee ee

Environmental temperature for the year... 2 1. ee ee ee ee
Egg development time as a function of temperature... . 2.2... eee

Growth rates of various species as a function of temperature... .....

a nS)

Abundance of organisms subject to sampling for various cruises

during the spawning period as a function of the day the organisms

were spawned... 2 6 6 we ee ee ee
.6. Larval length as a function of age... 6... 1 ee ee
7. Larval length frequencies for various cruises... 2. 2... ee ee

8. Calculated larval frequencies by age category as a function of day

spawned for various cruises during the spawning season... .... 1...
9. Age frequencies summed over all cruises. . 2... ee ee ee
10. Logarithms of age frequencies summed over all cruises, . 2... 1...

11. Back-calculated eggs spawned compared to original spawning

12, Area under curve of back-calculated eggs spawned compared to

original spawning curve., © 2... es
13. Silver hake percent standard deviation as a function of days

between cruises. | 2. ee ee ee
14. Silver hake median as a function of days between cruises... .......
15. Haddock percent standard deviation as a function of days between

cruises. SL ee ee
16. Haddock median as a function of days between cruises... . 2.2...

17. Silver hake percent standard deviation as a function of sampling
coefficient of variation... 6 6. ee es

18. Silver hake median as a function of sampling coefficient of
variation. 0 ee

xii


Sherman, K. [1988.] Large marine ecosystems as global units for recruitment experiments.
In B. Rothschild (Ed.) Toward a theory on biological-physical interactions in the
world ocean. D. Reidel Publishing Co., Dordrecht, Holland. (in press).

Sherman, K., and L. Alexander (Editors). 1986. The variability and management of large
- marine ecosystems. AAAS Selected Symposium 99, Westvicw Press, Boulder, Ct
319 pp.

Sherman, K., and B. E. Brown. 1982. Fisheries management and marine ecology, a case
history from the northeastern United States. MARMAP Contribution MED/NEFC
82-73. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref.
No. 82-74.

Sherman, K., and J. R. Goulet, Jr. 1986. Management of time-serics data for large marine
ecosystems. (MARMAP Contribution No. FED/NEFC 86-01) NOAA, Nat. Mar.
- Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 86-05. .

Sherman, K., and C. Jones. 1980. The zooplankton component of a Northwest Atlantic
ecosystem. ICES C.M. 1980/L:67.

Sherman, K., D. Bearse, and L. Sullivan. 1979. Variations in the zooplankton biomass of
Georges Bank: Spring-1976 and 1977. ICES Annales Biologiques 34:87-89.

Sherman, K., L. Bivins, P. Jeffries, A. Poularikas, C. Katsinis, M. Berman, and R. Maurer.
1982. Technical constraints to understanding very large marine ecosystems (VLE’s).
Presentation to J.O.A. Meeting, August 1982 at Halifax, N.S. Abstract. NOAA,
Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 82-22.
(MARMAP Contribution MED/NEFC 82-34. )

Sherman, K,, J. W. Deming, J. F, Grassle, R. V. Lynch, E. Shulenberger, and C. Taillie.
1980.” Marine populations: - Processes and interactions. pp. 539-544. ‘In F. P.
Diemer, F. J. Vernberg, and D. Z. Mirkes (Eds.) Advanced concepts in ocean
measurements for marine biology. Belle W. Baruch Inst. for Mar. Biol. and Coastal
Research, Univ. of South Carolina Press, Columbia.

Sherman, K., J. R. Green, and M. Berman. 1984. Zooplankton of the northeast shelf
ecosystem with a focus on waters of Southern New England and the Mid-Atlantic
Bight. RAP Report. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragan-
sett Lab. Ref. No. 84-14. (MARMAP Contribution No. MED/NEFC 84-15).

Sherman, K., M. Grosslein, D. Mountain, D. Busch, J. O’Reilly, and R. Theroux. 1988.
The continental shelf-ecosystem off the northeast coast o1 the United States. Chap-
ter 9, pp. 279-337. In H. Postma and J. J. Zijlstra (Eds.) Ecosystems of the world
Vol. 27, Continental Shelves. 406 pp. Elsevier Scientific Publishing Co., Amster-
dam, The Netherlands.

Sherman, K., C. Jones, and J..;Kane. 1979. Zooplankton of continental shclf nursery and
feeding grounds. ICES C.M. 1979/L:27.

Sherman, K., C. Jones, L. Sullivan, W. Smith, P. Berrien, and L. Ejsymont. 1981. Con-

gruent shifts in sand eel abundance in western and’eastern North Atlantic ecosys-
tems. Nature 291(5815):486-489.

129


1 Cruise (survey, time period)
<->>
2 Station (location, time, weather, selection keys)
<->>
3 Experiment (time, ship speed)
<->
4 Net (haul factors, tow depth, biomass)
<->>
5 Zooplankton (abundance)
<->> e
6 Stage (count, abundance)
<->>
7 Larvae (abundance)
<>
8 Length (count, abundance)
<->> :
9 Egg (count, abundance)
<>
10 Sample Depth (hydro, nutrients, chlorophyll, etc.)
<->>
11 Sub-Station (location, time)
<->>
12 Plankton (zoo and phyto abundance)
<->
13 Zoo-Stage (abundance)
Key: A

<->> For each B there is onc A.
B For cach A there are 0,1 or many B.

Fig. 2. Conceptual data base design for MEDBIM. Each data set (Cruise, Station, ete.)
contains only variables that-are specific to that data type.

7


40.0 60.0 80.0, 100.0 120.0
L rn L

20.0
n

ORGANISMS/DAY AFTER MORTALITY

0.0

700.0 750.0

Fig. 5. Abundance of o}
Spawning period as a fu

800.0 850.0 900.0

rganisms subject to sam;

pling for various cruises during the

nction of the day the Organisms were spawned.

86


Sherman, K. 1981. NOAA’s MARMAP program in the northeast. MARMAP Circular
MED/NEFC 81-1. .

Sherman, K. 1981. Draft report of the Workin Group on Larval Fish Ecology to the
Biological Oceanograp y Committee of ICES, Lowestoft, England, 3-6 July 1981.
NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. 81-69.

Sherman, K. 1981. Fisheries ecosystem studies and underway samplers. pp. 227-250. In
Water sampling while under way. Proceedings of a Symposium and Workshops 11-
12 Feb. 1980, Washington, DC.

Sherman, K. 1981. Zooplankton of Georges Bank and adjacent waters.in relation to
fishery ecosystem studies. pp. 40-43. Zn Third informal workshop on the oceanog-
raphy of the Gulf of Maine and adjacent seas. Univ. New Hampshire, Durham:

Sherman, K. (Editor). 1982. MARMAP fisheries ecosystem news. NOAA, Nat. Mar. Fish.
Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 82-06.

Sherman, K. 1982. Report of the Working Group on Larval Fish Ecology to. the Biologi-
cal Oceanography Committee of ICES, 1982. ICES C.M. 1982/L:3.

“Sherman, K. 1982. Perturbations in the structure of fisheries ecosystems in the North At-
lantic. Presentation at Cherry Hill, N. J., 13-15 April 1982. Abstract. NOAA, Nat.
. Mar. Fish, Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. No. 82-32.

Sherman, K. 1982. Report of the Eighth Annual Meeting of the Advisory Committee of
the Plankton Sorting and Identification Center, Narragansett, RI, 30 March-1 April
1982. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Narragansett Lab. Ref.
No. 82-18.

Sherman, K. 1984. Report of the Working Group on Larval. Fish Ecology to the. Biologi-
cal Oceanography Committee of ICES, Hirtshals, Denmark, 25-27 June.1984. ICES
C.M. 1984/L:37, :

Sherman, K. 1985. Background reports on the ecology of sand lance within the northeast
shelf ecosystem. Briefing for Mid-Atlantic Fisheries Management Council,
Philadelphia, PA, March 1985. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr.
Fisheries Ecology Div., Narragansett Lab. Ref. No. 85-06.

Sherman, K. 1986. Introduction to parts one and two: Large marine ecosystems as trac-
table entities for measurement and management. pp. -7. In K. Sherman and L. M.
Alexander (Eds.) Variability and management of large marine ecosystems. AAAS
Selected Symposium 99, Westview Press, Boulder, CO. .319 pp.

Sherman, K. 1986. Measurement strategies for monitoring and forecasting variability in
large marine ecosystems. pp. 203-236. Jn K. Sherman and L. M. Alexander (Eds.)
Variability and management of large marine ecosystems. AAAS Selected Sym-
posium 99, Westview Press, Boulder, CO. 319 pp.

Sherman, K. In press, Biomass flips in large marine ecosystems. Jn K. Sherman and L.

M. Alexander (Eds.) Biomass and geography of large marine ecosystems. AAAS
Selected Symposium Series, Westview Press, Boulder, CO.

128


the cruise interval was further reduced from 61 to 30 days for silver hake, the bencficial ef-
fect was reduced most markedly if the sampling coefficient of variation was low. A low
sampling coefficient of variation permits precise back calculations which make a moderate
cruise interval satisfactory. If the sampling coefficient of variation is higher, additional
cruises can help by reducing the time over which back calculations need to be made.

The description of the model indicated many input parameters that could be varied.
Some of them have been varied to give additional perspective on the characteristics of the
model and to indicate how the model might be used in the future. Figs. 21 through 30 vary
certain parameters, while retaining the parameters that were used for silver hake, unless
otherwise noted.

rie. 21 demonstrates the importance of the standard deviation of the spawning
curve. There is a nonlinear relationship which is similar to the curves in Fig. 15 which ex-
amines the effect of cruise interval. The relationship between the cruise interval and the
width of the spawning curve is important, though not necessarily simple. Insufficient
cruises for the width of the spawning curve give rapidly deteriorating results, while a very
large number of cruises during the spawning period offers little advantage. It may be
worthwhile to introduce the ratio of the number of days between cruises to the standard
deviation of the spawning curve as a new combined parameter to be examined in the fu-
ture.

In Fig. 23 the effect of the date of peak spawning (i-e., mean of the spawning curve)
is examined. The results deteriorate if peak spawning is during the coldest time of the
year. The large percent standard deviations shown in Fig. 23 are accompanied by high
median values shown in Fig. 24. The graphs of the medians have not been discussed very
much as the medians are generally near 1.0, or they are overshadowed by the effects of the
percent standard deviation. In the case of Fie. 24, however, they are noteworthy. The
mean calculated mortality rates and the standard deviations of the mortality rates were

also high in these cold temperature cases.

These poor results for winter were due to the fact that a silver hake larvae would
grow very slowly (Fig. 4) at cold temperatures. Silver hake do not, in fact, spawn in winter.
The example is also unrealistic, since mortality rates might well be reduced in winter. Fig.
25 uses growth parameters for sand eel, a winter spawner (Fig. 4). Much better winter
results were obtained. The results (not shown) were also better (for silver hakc) when tem-
perature was held constant at its winter time low level instead of varying it realistically.

Slow growth may be expected in winter. This is an advantage in that larvae will be
in the water column for a long time, thus filling the gaps between cruises. Slow growth is,
however, a disadvantage in that mortality operates over a longer time so that the cffects of
errors in mortality estimation are exagerated. Furthermore, the larval life extends through
a wide range of temperatures, introducing additional complexity into the calculations.
Thus, winter is, from a larval point of view, a time of varying temperature as well as low
temperature. Further work wili be necessary to determine how well the procedures work
in winter.

Fig. 27 shows the effects of varying the mortality rate. There is little effect. The
procedure should work well with a good range of mortality rates. However, the effect of
randomly varying mortality rates as well as many other random variations still has to be in-
vestigated.

The effect of reducing the maximum larval length from 20 mm is shown in Fig. 29.
Reducing the maximum larval length produces a slow and then a rapid deterioration of

79


19.

20.
21.

22.
23.

24.

25.

26.

27.
28.
29.
30.

Haddock percent standard deviation as a function of sampling
coefficient of variation, ©. 6 ee ee

Haddock median as a function of sampling coefficient of variation... . . .

Percent standard deviation as a function of standard deviation of
the spawning curve... 6 6 ee ee ee ee

Median as a function of standard deviation of the spawning curve... . . .

Percent standard deviation as a function of mean of spawning
curve using silver hake parameters... . 6 ee ee ee ee ee

Median as a function of mean of spawning curve using silver
hake parameters... 6 6 ee ee ee ee ee

Percent standard deviation as a function of mean of spawning
curve using sand eel parameters. . - - 6 6 ee ee ee ee ee

Median as a function of mean of spawning curve using sand eel
parameters. © 6 6 ee ee ee ee ee ee

Percent standard deviation as a function of mortality rate. 6. 6. 6 es
Median as a function of mortality rate... - 6 6 2 ee ee ee ee ee
Percent standard deviation as a function of maximum larval length.

Median as a function of maximum larval length... . . 2.6... e+e

ABSOLUTE ABUNDANCE ESTIMATES USING TRAWL AND
ICHTHYOPLANKTON SURVEY DATA

1.

Biannual (spring and fall) estimates of the abundance of one-
year-and-older yellowtail flounder on Georges Bank and in
Southern New England... 1... ee

Linear relationship between the egg survey abundance estimate
and the trawl survey index of relative abundance. . 2... 1... ee

xiii


GROWTH RATES OF VARIOUS SPECIES

37 LEGEND
a = HADDOCK
© = SILVER HAKE
4 = HERRING
é | += SAND LAUNCE
3
w 8
eo 2)
Cc
oe
-
Ea
2 34
gs
a]
8
3

0.0 2.0 4.0 8.0 8.0 10.0 12.0 14.0 16.0
TEMPERATURE (0EG. CENTIGRADE)

Fig. 4. Growth rates of various species as a function of temperature.
5 85


SUMMED LARVAE/DAY

0.0

15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
AGE (DAYS)

Fig. 9. Age frequencies summed over all cruises.
90


CALCULATED/INPUT EGGS SPAWNED

LEGEND
O= SAMPLING COEFFICIENT OF VARIATION = 0
O = SAMPLING COEFFICIENT OF VARIATION = SO%

PERCENT STANDARD DEVIATION
20.0 30-0 40.0 50.0 60.0 70-0 80.0

10.0
rn

ee

0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0
MEAN OF SPAWNING CURVE

0.0

Fig. 25. Percent standard deviation as a function of mean of spawning curve using sand cel
parameters. :

106


Table 1. Estimates of the instantaneous mortality rates per millimeter length for fish
larvae collected on MARMAP ichthyoplankton surveys, 1977-1984. Spawning season is in-

dicated as (W) = winter, (SP) = spring, and (SU) = summer. -

Taxon Season Lengths.(mm) “Mortality
Atlantic herring (Ww) 8-42 0.2033
Engraulidae (SU) 417 0.5951
Atlantic cod (SP) 5-33... -0.2280
Haddock (SP) 431 0.3064.
Silver hake (SU) 4-41 ; “0. 2529
Pollock ' (W) 4-33 0.2064
Urophycis spp. (SU) 3-46 10.2038
Ammodytes spp. (W) 5-50 0.1706. °
Atlantic mackerel (SP) 3-17 -0.6555
Butterfish (SU 3350 02117
Redfishes (SU) 6-14 -0.7471:
Triglidae (SU). - 3-12 -0:9733
Gulfstream flounder (SU) 4-45 -0.4199
Smallmouth flounder (SU) - 427 -0.4023 -
Yellowtail flounder (SP) 5-25 -0.4260

53


“WU ¢ 0} Poze]
-noyeo yorg pue 5,W QT Jad yores prepueys yI0q Joy UMOYS O18 SedUEPUNGe OU]. *oains yord Jo skep ul UONeINP sy) SMOYS sIEq
out Jo Ippim auf, “8/61 Ul Yue Sod109H UO IYsNED oeArE] DALY JOAIIS JO soouepunge paisnipe-Ajyjeqow pue prepueig “p “Sty

Ava NYIIAP
ogc _ 0Ze ouz ove 002
L — L A A, 1
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Looz
or
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009
a
m
2
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wwe OL GalvINoWwoIOVA LS
saHoivo auvanvis (__] | 0001
L oozt

59


sence of any prolonged environmental change, . the decline in both Atlantic herring
and Atlantic mackerel stocks during the mid 1970’s released predation pressure on sand
eel and allowed the population to explode (Sherman et al., 1981). Fishing mortality has
been reduced on Atlantic herring and Atlantic mackerel stocks since the mid 1970’s. No
fishery exists for sand eel. It appears that the reduction of fishing mortality on Atlantic
mackerel and Atlantic herring has allowed the stocks to begin a recovery trend. Atlantic
mackerel has increased to approximately. 1.2 mmt based on recent estimates (Anderson,
1985). Significant numbers of herring from the 1983 year class have appeared in trawl sur-
veys and commercial catches on Georges Bank in 1987 (M. Fogarty, personnel communica-
tion) suggesting the possibility that some level of spawning stock recovery may be imminent
on the Bank.

In these examples of biomass flips, commercially valuable species (e.g., Atlantic her-
ring, Atlantic mackerel) appear to have been replaced for a period of scveral years by
species of lesser economic value (e.g., sand eel). At present, it appears that following the
reduction of fishing effort by foreign vessels in the mid 1970's, the fishing power of the U.S.
flect operating within the Northeast Continental Shelf ecosystem has grown to the level
sufficient to depress spawning potential below the level necessary for populations to
replenish themselves through recruitment (Sissenwine and Sheperd, 1987). Conversely,
through prudent management and conservation it is possible to allow for the recovery of
heavily exploited populations to levels that will support a sustainable yield. To provide a
scientific basis for measuring changes in species abundance levels and the design of ra-
tional conservation strategies, the Northeast Fisheries Center conducts systematic surveys
of fish stocks and their environments over the entire 260,000 km? of the Northeast Con-
tinental Shelf ecosystem from the Gulf of Maine to Cape Hatteras. Since 1963 bottom
trawl surveys have been conducted in spring and autumn, and since 1977 surveys of fish
eggs and larvae (ichthyoplankton) have been made at approximately bimonthly intervals.
The ichthyoplankton provides an independent measure of spawning biomass of important
pelagic and demersal fish populations. The survey effort is part of the NMFS Marine
Resource Monitoring, Assessment, and Prediction (MARMAP) program.

The MARMAP ichthyoplankton surveys of the NEFC are designed to measure
long-term (decadal) trends in species abundance, including recovery of depleted stocks,
and estimate short-term changes in the abundance levels of the spawning biomass of im-
portant species for which other reliable abundance indices are unavailable, are ques-
tionable, or are incomplete (e.g., silver hake, Merluccius bilinearis; sand ecl; Atlantic her-
ring; Atlantic mackerel; and yellowtail flounder, Limanda ferruginea, in some areas). Es-
timates of the status of biomass of these fish stocks are especially. important if NMFS is to
provide the best scientific information available, setting appropriate limits on fishing within
the Northeast Shelf Ecosystem.

Ichthyoplankton surveys provide information on the entire finfish biomass, except
for a few species which do not have pelagic eggs or larvae. Preliminary analysis suggests
that the total finfish biomass may be significantly higher than presently estimated from
commercial catch and bottom trawl survey data. One of the papers in this volume (Berrien
and Sissenwine) estimates a biomass of about 7.3 mmt which could probably sustain-a yield
double the present level, but only if the catch consists of a greater number of species than
are presently utilized. Ichthyoplankton survey results suggest that species that are rela-
tively abundant such as sand eel, searobins, Prionotus spp.; bay anchovy, Anchoa mitchilli;
flatfishes, including smallmouth flounders, Etropus microstomus; and Gulf Stream flounder,
Citharichthys arctifrons, represent the potential for supporting expanding fisheries for com-
mutated or: minced seafood products. The surveys also provide information on changes in
spawning times and places. They are an important means for: (1) measuring present

4


. 8
ae
” at’e
= i
=?
a @,°9
*] Bas
z e 3°
Zu gos
= fe
x7 4 °°
3 R98 *. 10
a8 gties* ®
ae an
3 Bose" ; eGo
zo Bos gare
: ° eat)
=o] Bee XXX
= aaa gett!
73] preee 00? Nanhai
Breer tee cei nanse?
4 at ALALLALLESSSensneonsseensee
aa
2
3
+ T T T T T T r t ——,
9.0 5.0 10.0 15,0 20.0 25.0 30.0 38.0 40.0 .45.6 50.0 55.0 60.0
AGE (DAYS)

Fig. 6. Larval length as a function of age.

87


FISHABLE BIOMASS OF GEORGES BANK, GULF OF MAINE AND
SOUTHERN NEW ENGLAND

BIOMASS IN MILLION METRIC TONS
a
T

YEAR

Fig. 2. Decline in the fishable biomass of Georges Bank, Gulf of Maine, and Southern -
New England between 1968 and 1975. (Adapted from Clark and Brown, 1977.)

9


Table 2 (continued).

Percent of total Percent
Taxon standardized catch occurrence
SOUTHERN NEW ENGLAND
Scomber scombrus 32.19 17.89
Urophycis sp. 21.61 41.24
Tautogolabrus adspersus 8.44 9.42
Limanda ferruginea 7.20 24.48
Peprilus triacanthus 6.68 12.99
Merluccius bilinearis 6.27 35.78
Hippoglossina oblonga 4.40 31.26
Citharichthys/Etropus 2.99 26.55
Scophthalmus aquosus 1.63 21.28
Merluccius albidus. 1.44 12.43
Gadus morhua 1.38 : 17.89
Anchoa mitchilli 101 2.45
95.24

37 other taxa 4.76 0.19 to 15.07

100.00
MIDDLE ATLANTIC
Anchoa mitchilli 49,22... : 14.34
Prionotus sp. 9.12 ae 27.00
Citharichthys/Etropus 7.21 aa 41.53
Urophycis sp. 6.42 ona 37.99
Peprilus triacanthus 5.20 16.01
Cynoscion regalis 3.54 8.75
Scomber scombrus 2.69 8.57
Hippoglossina oblonga 2.64 33.71
Pomatomus saltatrix 2.43 8.38
Scophthalmus aquosus 2.24 26.26
Anchoa hepsetus 1.89 5.96
Merluccius bilinearis 1.34 14.90
Unknown #180 (Micropogonias undulatus?) ote 4.84
57 other taxa 4.82 0.19 to 16.76

100.00

38


TEMPERATURE (DEGREES C)

T y 7 T T 7 —- 1
0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0 400.0
DAY :

Fig, 2. Environmental temperature for the year.

83


historic nature and quantitative sampling methods, represent an important strategy for
monitoring trends in abundance and mortality, and for estimating fish stock inventories
(Clark, 1979). This evaluation demonstrates the complementary nature of the trawl and
ichthyoplankton data sets. Trawl surveys are better suited for assessing sharks, skates and
rays, mone of which produce young stages vulnerable to plankton nets, while ich-
thyoplankton surveys provide more meaningful information on pelagic species and small
fishes of little or no economic significance. Together, the two surveys provide a com-
rehensive strategy for monitoring and assessing changes in the community structure of
ishery resources off the northeastern United States.

LITERATURE CITED

Azarovitz, T. R. 1981. A brief historical review of the Woods Hole Laboratory trawl sur-
vey time series. pp. 62-67. Jn W. G. Doubleday and D. Rivard (Eds.). Bottom trawl
surveys. Can. Spec. Publ. Fish. Aquat. Sci. 58:273 pp.

Boyar, H. C., R. R. Marak, F. E. Perkins, and R. A. Clifford. 1973. Seasonal distribution
and growth of larval herring (Clupea harengus L.) in the Georges Bank-Gulf of
Maine area from 1962 to 1970. J. du Cons. 35:36-51.

Clark, S. H. 1979. Application of bottom-trawl survey data to fish stock assessment.
Fisheries 4(3):9-15.

Grosslein, M. D. 1969. Groundfish survey program of BCF Woods Hole. Comm. Fish.
Rev. 31(8-9):22-35.

-Lough, R. G., G. R. Bolz, M. Pennington, and M. D. Grosslein. 1985. Larval abundance
and mortality of Atlantic herring (Clupea harengus L.) spawned in the Georges
Bank and Nantucket Shoals areas, 1971-78 seasons, in relation to spawning stock
size. J. Northw. Atl. Fish. Soc. 6:21-35. .

Marak, R. R., and J. B. Colton, Jr. 1961. Distribution of fish eggs and larvae, temperature,
and salinity in the Georges Bank--Gulf of Maine area, 1953. NOAA Tech. Rep.
NMFS Spec. Sci. Rep.-Fish. 398:1-61.

Morse, W. 1982. Spawning stock biomass estimates of sand lance, Ammodytes sp., off
Coe sae. sanited tates, determined from MARMAP surveys, 1974-80. ICES

Pennington, M., and P. Berrien. 1982. Measuring the effect of the variability of egg den-
sities over space and time on egg abundance estimates. pp. 127-141. In Report of
the Working Group on Larval Fish Ecology. Lowestoft, England 3-6 July 1981.
ICES C. M. 1982/L:3.

Sherman, K., R. Lasker, W. Richards, and A. Kendall. 1983. Ichthyoplankton and fish
recruitment studies in large marine ecosystems. Mar. Fish. Rev. 45(10-12):1-25.

Sibunka, J., and M. Silverman. 1984. MARMAP surveys of the continental shelf from
Cape Hatteras, North Carolina to Cape Sable, Nova Scotia (1977-1983). Atlas No.
1. Summary of Operations. NOAA Tech. Mem. NMFS-F/NEC-33. 306 pp.

Smith, W. G., and J. Goulet. This volume. MARMAP ichthyoplankton surveys: An over-
view of methods and data base management.

21


Busch, D., and J. O’Reilly._ 1979. Summary of "4C simulated in situ measurements MAR-
MAP cruises 1978. For joint meeting in-Moscow, U.S.S-R. NOAA, Nat. Mar. Fish.
Serv., Northeast Fish. Ctr. Narragansett Lab. Ref. 79-08.

Cain, T. E. 1981. Temperature structure and surface salinity in the Gulf of Maine in 1979.
ICES Annales Biologiques 36:36-43.

Campbell, J. W., and\J. E. O'Reilly. In press. Role of satellites in estimating primary
productivity on the Northwest Atlantic continental shelf. Continental-Shelf Res.

Cohen, E. B. 1980. A preliminary summary of available data on nutrients, . prima
productivity, and chlorophyll @ for the ICNAF larval herring research area, 1975-
1978. (Also NAFO, SCR Doe. 80/1X/140).

Cohen,.E. B.. 1985. Recent research at the Northeast Fisheries Center on some factors af-
fecting the recruitment of Georges Bank cod and haddock. NOAA, Nat. Mar. Fish.
Serv., Northeast Fish. Ctr. Woods Hole Lab. Ref. Doc. No. NG. (MARMAP Con-
tribution No. FED/NEFC 85-09).

Cohen, E. B., and M. Grosslein. Ecosystem modelling in the Marine Ecosystems Division.
‘A status report. NOAA, Nat. Mar. Fish. Serv., Northeast Fish. Ctr. Woods Hole
Lab. Ref. Doc. .No. 84-08: (MARMAP Contribution No. MED/NEFC 84-08.)' -

Cohen, E. B., and M. D. Grosslein: 1987. Production on Georges Bank compared with
other shelf ecosystems. pp. 383-391. Jn R. H. Backus (Ed.) Georges Bank, MIT
Press, Cambridge. . : eo

Cohen, E. B., M. D. Grosslein, M. P. Sissenwine, F..Steirile,.and:W. R. Wri ht. 1982. An
energy budget for Georges Bank. Can. Fish. Aquat. Sci. Spec. Publ. 59:95-107.

Cohen, E. B., G. Laurence, and W. Smith. 1984. The-role of starvation and predation i in
regulating y year class Strength in several fish stocks on Georges Bank. _ICES Cc. M.
- 1984/G:3

Cohen, E. B., D. G. Mountain, and S. H. Clark.- 1982.. Comparison of energy flow in three
Northwestern Atlantic ecosystems. ICES C.M. 1982/L: 47.

Cohen, E., D. Mountain, and W. ‘Smith. 1982. Physical processes and year-class strength of
‘commercial fish stocks on Georges Bank. EOS. . Trans. Am. Geophys. Union
63(45):956 Abstract #L031C-38.

Cohen, E. B., D.“G. Mountain, and WwW. G. Smith. 1984. Com arison of cod and haddock
spawning in 1982 and 1983 on Georges Bank.. NAFO SCR Doc. 84/VI/7S.

Cohen, E., W. R. Wright, and R. J. Schlitz. 1981. Primary productivity on Gcorges Bank
«with an explanation of why it is so high. p. 50. Jn Third informal workshop on the
oceanography of the Gulf of Maine and adjacent seas, Univ. New Hampshire,
. Durham, 2-5 Mar. 1981. (Abstract only).

Colton, J. B., Jr., J. L. Anderson, J. L. O’Reilly, C. A. Evans-Zetlin, and H. G. Marshall.
1985. The shelf/slope front south of Nantucket Shoals and Georges Bank ‘as ©
delineated by satellite infrared imagery and. shipboard hydrographic and plankton
observations. NOAA Tech. Mem. NMFS-F/NEC-38. 22 pp.

121


trends and forecasting future trends in species abundance, indcpendent-of the
catchability biases of the bottom trawl survey for pelagic species, and (2) providing infor-
mation on yield statistics with fisheries-independent estimates.of abundance. This ad-
vantage has been recognized’ widely and has led to the use of ichthyoplankton surveys as
means of estimating mackerel abundance on the northeast shelf (Berrien et al., 1981), At-
lantic herring and Atlantic mackerel abundance in the North Sea, thé entire multispecies .
fish community of the Norwegian Sea and of selected species, in other large marine ecosys-
tems, including estimates of sardine.and anchovy in the California Current ecosystem, the
Oyashio and Kuroshio Current ecosystems, the Benguela Current ecosystem, the Hum-
bomen ecosystem, and the Iberian Coastal ecosystem (Sherman and Alexander, in
press).

Data resulting from the surveys are used-to measure’ variability of the ich-
thyoplankton prey field, primary productivity, secondary productivity, and hydrography of
the Northeast Shelf ecosystem. These measurements are useful for providing cause and ef-
fect information on the anthropogenically, or naturally-induced, biomass flips that have oc-
curred within the ecosystem in the past,and are likely to occur in the future. The surveys,
in addition to providing information on the status of fishery resources, are also used to
monitor the state of natural productivity: of the Northeast Shelf ecosystem: - This informa-
tion is relevant 'to studies of global ocean flux conducted by NSF, NASA, and NOAA
(McCarthy et al:, 1986) in relation to possible impacts on the fisheries of global heating
that may result from ozone depletion (Cicerone, 1987) and the greenhouse effect (NAS,
1979).

Based on our analyses of the NEFC Plankton time-series data, we have concluded
that the-natural environmental variability of the Northeast Shelf ecosystem is less than in
the California Current upwelling ecosystem where interannual levels of primary produc-
tivity and zooplankton levels (Colebrook, 1977; Smith and Richardson, 1977) can vary two
to three-fold, and where the temperature signal has shown a:marked change over the past
two decades (MacCall, 1986). “Large-scale environmental signals, particularly those as-
sociated with temperature changes, can also be significant causes of changes in species
dominance for continental shelf areas at the northern boundaries of distributions of both
pelagic and demersal species, including the Arcto-Norwegian cod’ of the Barents and Nor-
wegian Seas (ICES, 1987) and the North Icelandic herring (Jakobsson, 1980). No evidence
of changes in long-term trends in zooplankton-biomass of the northeast shclf ecosystem or
species composition has, as yet, been detected (Sherman et al.; 1983) although changes
have been detected in the zooplankton field of the Northeast Atlantic based on-analyses of
oe meseries of continuous plankton recorder sampling of the region (Colebrook, 1972,
1978). _ : :

The NEFC ichthyoplankton surveys measure bioenvironmental changes that could
have a primary influence on recruitment success. - Of particular concern are the fish species
that have evolved a gyre-rélated spawning strategy at their southern limit of distribution,
including cod and haddock on Georges Bank (Sherman et al., 1984). From the studies of
Laurence and Lough (1984), we have concluded that "on the average" prey densitics do
not limit survival of cod and haddock larvae on Georges Bank. It'is important, howéver, to
maintain a monitoring program of prey availability and abundance since oceanographic
phenomena and anomalies may effect the. concentration of prey or effect fish eggs and
larvae directly. Therefore, we have designed the NEFC mesoscale MARMAP surveys to
monitor large-scale events dealing With: 1). primary production--by monitoring the
phytoplankton field with underway fluorometry, 2) secondary production--by monitoring
the zooplankton field as sampled simultaneously with ichthyoplankton, and. 3) the .
hydrographic field--by.monitoring water column stability, water mass variability.

5


LENGTH-DEPENDENT MORTALITY AND AN INDEX OF SPAWNING BIOMASS
FROM LARVAL ABUNDANCE

Wallace W. Morse

National Marine Fisheries Service ,
Northeast Fisheries Center
Sandy Hook Laboratory
Highlands, NJ 07732: --

ABSTRACT

The average length dependent mortality rates for 15 taxa of marine larval fishes col-
lected from 1977-1984 off the northeast United States show a seasonal trend from lowest in
winter to.a peak in summer... The mechanism to explain this trend appears to be predation
upon the larvae which includes cannibalism.. An index of annual production of 3 mm
larvae was calculated for Atlantic cod (Gadus morhua), silver hake (Merluccius bilinearis),
haddock (Melanogrammus aeglefinus), Urophycis spp., and yellowtail flounder (Limanda
ferruginea). The index adjusts larval abundance for length dependent mortality and is more
appropriate for relating spawner biomass to larval abundance than the unadjusted catches.

INTRODUCTION

In temperate and subarctic oceans the production of fish larvae is not temporally or
areally constant throughout the year for any given species, or for all taxa, combined.
Various factors, both biotic and abiotic, contribute to producing .an annual cycle in the
spawning (Cushing, 1975). The abundance and length composition of fish larvae at any
given time throughout the far is a function of the production rate (hatching rate), mor-
tality rate, and larval growth rates: The interaction of these rates obscures the relationship
between larval standing stock abundance and parental biomass, but. backcalculation
methods, described and evaluated elsewhere in this document (Hauser et al.); can be used
to estimate the relationship. The backcalculation method requires a considerable body of
information (e.g., estimates of mortality and fecundity) that is not available for many
species.

This paper presents estimates of average (over years) larval mortality rates per unit
length for 15 of the more abundant taxa in the larval finfish community of the Northwest
Atlantic shelf ecosystem. Average mortality rates are used to derive an index of parental
spawning biomass for six taxa. The index is applicable in those situations where backcalcu-
lated estimates of biomass are not feasible.

METHODS

The fish larvae collected on 50 MARMAP surveys conducted during 1977-1984 be-
twecn Cape Hatteras, North Carolina, and Nova Scotia were used in this analysis (Sibunka
and Silverman, 1984). To derive estimates of larval mortality for 15 taxa, the length fre-
quency of each taxon for all surveys combined was compiled and the exponential decline in

numbers at length (mm) was calculated ‘by the method of-least squares. The length inter-'

vals ‘used were selected to eliminate unusually. large specimens which would: unduly in-
fluence the results. Examples of the length frequencies are shown in’Figs. 1 and 2 for had-
dock and Atlantic herring (Clupea harengus).

49


yueg sosi0sH uo Jopunog [eimojjod Jopjo-pue-eof-ou0 JO douRpuNge sy} JO sayeUITso (jjey pue Suns yjenuurig “] “SL

y OO!

7 00%

- 118

+ OOF

\ + oor

(SNOITIW) S3ONVaNNaY

+005

009



CALCULATED/INPUT EGGS SPAWNED

: LEGEND
O =~ SAMPLING COEFFICIENT OF VARIATION = 0%
O = SAMPLING COEFFICIENT OF VARIATION = 50%

300.0. 350.0 ©

200.0 250.0
rm n in

150.0
L

PERCENT STANDARD DEVIATION
‘100.0

50.0
1

15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0
STANDARD DEVIATION OF SPAWNING CURVE

0.0

Fig. 21. Percent standard deviation as a function of standard deviation of the spawning
curve.

102


CALCULATED/INPUT EGGS SPAWNED

LEGEND
_G= SAMPLING COEFFICIENT OF VARIATION = 0%
O = SAMPLING COEFFICIENT OF VARIATION = SOZ

150.0 200.0 250.0 300.0 380.0
ni 1

100.0

PERCENT STANDARD DEVIATION

$0.0
1

0.0

=—4

0.0 “50.0 | 100.0 180.0 200.0 280.0 300.9 380.0
MEAN OF SPAWNING CURVE : ,

Fig. 23. Percent standard deviation as a function of mean of ft spawning curve using silver
hake. parameters.

104


Vi


Mountain, D. 1986. Internal memorandum of 2 June :1986. Woods Hole Laboratory,
Northeast Fisheries Center, Woods Hole, MA. :

Posgay, J. A.. and R. R. Marak. 1980. The MARMAP bongo zooplankton samplers. A.
Northw. Atl. Fish. Sci. 1:91-99.

Sibunka, J. D:, and M. J. Silverman: 1984... MARMAP surveys of the continental shelf
from Cape Hatteras, North Carolina, to Cape Sable, Nova Scotia (1977-1983). At-
las No. 1. Summary of operations. NOAA Tech. Mem. NMFS-F/NEC-33:306 pp.

Silverman, M. J. 1983. Distribution, abundance, and production estimates of yellowtail
flounder, Limanda ferruginea, larvae off northeastern United States, 1977-1981.
ICES C.M. 1983/G:47.

Sissenwine, M. P., T. Azarovitz, and J. B. Suomala. 1983. Determination’ of fish abun-
dance: pp. 51-101. In’ A. G. MacDonald and L. G. Prievy (Eds.) ‘Experimental biol-
ogy at sea; Academic Press, New York. .

Smith, W. G., and J. Goulet. This volume. MARMAP ichthyoplankton: surveys: An over-
view of methods and data base management.

Smith, P. E., and S. Richardson. 1977. Standard techniques for pelagic fish eggs and larval
surveys, FAO Fish. Tech. Pap. 175:100 pp.

Smith, W. G., P. Berrien, D. G. McMillan, and A. Wells. 1981. The distribution; abun-
dance, and roduction of Atlantic cod and haddock larvae off northeastern United
States in 197879, and 1979-80. ICES €.M. 1981/G:52.-

Thornton, K. W., and, A. S. Lessem. 1978. A temperature algorithm for modifying biologi-
cal rates. Trans. Am. Fish. Soc. 107(2): 284-287.

Zweifel, J. R., and P. E. Smith. 1981. Estimates of abundance. and mortality of larval

anchovies (1951-75): gepPltcation of a new method. Rapp. P. “Vv. - Reun. Cons. int.
Explor. Mer 178:248-259.

81


USE OF EGG DATA TO ESTIMATE TOTAL FINFISH BIOMASS
FOR THE NORTHEAST CONTINENTAL SHELF ECOSYSTEM

Peter Berrien’ and Michael.P. Sissenwine?

National Marine Fisheries Service
Northeast Fisheries Center

"Sandy Hook Laboratory
Highlands, NJ._ 07732

?Woods Hole Laborato
Woods Hole, MA 0254:

ABSTRACT

The spawner biomass and total population biomass for the entire finfish community
off northeastern United States were estimated for years 1979 to 1984 based primarily on
egg surveys. Surveys were conducted 6 to 8 times per year between Nova Scotia and Cape
Hatteras. Sampled egg densities were adjusted to account for mortality. The biomass of
spawners was estimated assuming that the number of eggs spawned is proportional to the
biomass of spawners. Further adjustments were made to take account of specics that do
not have pelagic eggs (e.g. sand eel, Ammodytes spp., and dogfish, Squalus acanthias and
Mustelus canis) and the immature component of the population. Spawner biomass es-
timates for the six years ranged from 3.6 to 5.9 million metric tons (mmt) and total popula-
tion biomass estimates from 5.3 to 8.6 mmt. These estimates are similar in magnitude to
estimates derived from trawl surveys two decades earlier, but significantly higher than
recent estimates using the same method.

INTRODUCTION

Ichthyoplankton surveys are a useful means for monitoring changes in structure and
dominance within fish communities of marine ecosystems. Such surveys have been used
widely in estimating spawner and population biomass of individual species including: At-
lantic mackerel, Scomber scombrus, (Sette, 1943; Iversen, 1977; Berrien et al., 1981; Lock-
wood et al., 1981; Walsh et al., 1983; Iversen and Eltink, 1983); Atlantic herring, Clupea
harengus, (Parrish and Saville, 1962, Hardwick, 1973); haddock, Melanogrammus aeglefinus,
(Saville, 1964); round herring, Etrumeus teres, (Houde, 1977); and northern anchovy,
Engraulis mordax, (Ahlstrom, 1968; Smith, 1972; Parker, 1980; Stauffer, 1980; Picquelle and
Hewett, 1983). To date biomass estimates derived from ichthyoplankton data have only
been applied on a species by species basis. However, the sampling strategy used to monitor
ichthyoplankton of the northeastern United States continental shelf is suitable for estima-
tion of spawner biomass and total population biomass for the entire finfish community, as
described in this paper. Trends in total finfish biomass estimates are useful indicators-of
potential fishery yicld. In addition an annual time series of total finfish biomass estimates
is relevant to the hypothesis that fishing affects species composition but that production
and finfish density are relatively constant (¢.g., Hennemuth, 1979). .

The methods we used for deriving total finfish biomass estimates are based on a
model that: (1) assumes the number of eggs spawned is proportional to the biomass of ma-
ture fish; (2) assumes egg development time is a function of temperature, independent of
species; (3) applies an egg mortality rate of 10%-d"'; and (4) treats ichthyoplankton survey
data as a random sample in time and space. The model allows the mean catch of eggs per

26


METHODS

Trawl survey procedures are described by Azarovitz (1981). The trawl survey in-
dices were constructed using a technique described in Pennington (1985). Briefly, the
method filters the original catch per tow series to remove the effects of yearly random fluc-
tuations in catchability. Ichthyoplankton survey procedures are reviewed elsewhere in this
volume by Smith and Goulet and described in detail by Sibunka and Silverman (1984).
Procedures for the use of egg data to estimate yellowlal stock size are described by Ber-
tien et al. (1984) and Berrien (1987). -Data on the abundance of yellowtail flounder were
derived from trawl and ichthyoplankton surveys conducted during the 4-year period be-
tween 1979 and 1982. :

It is assumed that the functional relationship between the actual population of fish
in year t, P,, and the expected value of the trawl survey index, Z;, is of the form

Prak2y On

where k is assumed to be constant over time (see Pennington, 1986): The estimates of P,
based on the egg surveys, and of Z, from the-trawl surveys are'assumed to be lognormally
distributed with equal coefficients Of variation (see Collie and Sissenwine, 1983; Berrien et
al., 1984; Pennington, 1985). Thus ‘ - riot

In Py = In Z ay

is normally distributed with mean equal to In k. The average value of expression (2) over
the years for which data are available is an estimate of In k and from the assumptions, it
follows that the anti-log of the average is a consistent estimator of k. ' ~ oe

RESULTS |

Table 1 gives the’absolute abundance estimates for 1979-1982 based On egg surveys
for yellowtail flounder on Georges Bank and in Southern New Engiand, along with the cor-.
responding indices of relative abundance from the trawl surveys. In the last column‘are the
estimates of In k for each year and region along with the areal estimates. The two areal és-*
timates are not statistically different. Hence the average of the two (15.99) is used to es-
timate In k in both regions. Fig. 1.shows the estimates of the actual abundance of‘age one
and older yellowtail flounder on Georges Bank and in Southern New England from 1968 to”
1985 obtained by applying a proportionality constant equal’ to exp [15.99]: to ‘each’
(smoothed) trawl survey series. : * .

The: standard ‘error of: the adjustment’ factor: (last row, Table -1)’ reflects ‘the~
variability of the egg-based estimates and the trawl survey index. As the number of egg’
surveys increases, the standard error of k will decrease to 0, but the final variance of the
abundance estimates can be no smaller than the variance of the trawl survey index. .

DISCUSSION

- The variability of'k appears to be small ‘relative to the variability commonly ob-
served in stock size over time. Therefore; only a limited number of egg surveys may be”
necessary to estimate k.. Ideally, however, egg surveys should be done periodically-to
determine the consistency of the proportionality constants over timc, and especially over a’
range of population sizes. In addition, comparisons should be made between VPA and
egg-based estimates whenever possible to check for consistency between the two measurcs

113


Bo
a
Lo
oj}*
= Sie
Q x
a o
isu x,
Go} °
ret xo
& lt ye
Zz o 25
8 o! 4 x >
§s4 v xs
ian + Vx oy
xo
ta v
S| a My ee
Zo + Fy ey
Sst + Bag, on
j Bagh + RYogg ee
v
a "Ste, XK IV EE Bg,
8 Seer OMARRALAL ETT
S|, pes beh SNeEsee th
aes 5 bi bobets ig
3 | SeseuasiaawecdduwuenbiessscsonnsconesTeRSapaMReNuMSUNNGSe
30 35 40 £5 50 55 50 65 7.0 75 8&0 85

NETH (MM)

Fig. 7. Larval length frequencies for various cruises.

88


ESTIMATING THE RATIO OF IMMATURE TO MATURE
BIOMASS OF A FISH POPULATION

. The concentration of eggs collected by a random sample can be used to estimate the
biomass of mature fish in a population. In order to estimate total population biomass it is
necessary to know or estimate the ratio of immature to. mature biomass, i.e., X = B /Bz
where B, is the immature biomass and Bg is the mature biomass. A statistically derived es-
timate is, impractical for a variety of reasons. For example, random sampling is not pos-
sible since not all species or maturity stages have equal probability of being sampled. :

X can be estimated by making a few simple, but plausible, assumptions about
populations. We assume that the biomass of a cohort of fish increases monotonically from
eggs until the age of maturity (ty) at an instantaneous rate of gy, and that it decreases
monotonically at an instantaneous rate of g5 until the biomass 1s diminished to 0. In
theory, this will take an infinitely long period of time for an exponential model. The age at
which the mature biomass has been reduced to 5% of its peak is tp. B, is the biomass at
time 0; i.e., biomass of eggs spawned. Then, the biomass of immature fish is: , .

-. t gyt
By= | ‘Bye at ; -
fe) _ :
: git ;
=(Bogy)(e -1) ; a - — 6)
The biomass of mature fish is:

t (t-t})
B, & 122 1

. git Solety] _—
2Be Vege? 1)

By a oO
=-Boe’ is oO

Of course B, is related to the mature biomass. It is reasonable to assume it is about
10% (Parrish, 1975). This assumption allows us to functionally relate gy to gy and ty:

t
gz 0.100! - 7)

29