NOAA Technical Report NMFS 36 December 1985

An Egg Production Method

for Estimating Spawning Biomass

of Pelagic Fish: Application

to the Northern Anchovy,

Engraulis mordax

Reuben Lasker (Editor)

U.S. DEPARTMENT OF COMMERCE

National Oceanic and Atmospheric Administration

National Marine Fisheries Service
NOAA TECHNICAL REPORT NMFS

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I Synopsis of biological data on the Blue Crab, Calii'h'ctes sapidus R.1thbun, b)

Mark R. Millikin and Austin B. Williams. March 1984 :19 p.

2. Development of hexagramrnids (Pisces: Scorpaeniformesl in the Northeastern

Pacific Ocean, by Arthur W. Kendall, Jr., and Beverly Vinter. March 1984, 44 p.

3. Configurations and relative efficiencies 01 shrimp trawls employed in southeastern

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and Anthony F. Serra. March 1984, 12 p.

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Alton Y. Roppel April 1984, 26 p.

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February 1978, with comments on the effects of wind, Gulf Stream eddies, and slope

water intrusions, by Daniel E. Smith and Jack W. Jossi. May 1984, 41 p.

6. Ichthyoplankton survey of the estuarine and inshore waters of the Florida Everglades, May '1971 to February 1972, by L. Alan Collins, and John H. Finucane. July

1984, 75 p.

7. The feeding ecology of some zooplankters that are important prey items of larval

fish, by Jefferson T. Turner. July 1984. 28 p.

8. Proceedings of the International Workshop on Age Determination of Oceanic

Pelagic Fishes: Tunas, Billfishes, and Sharks, by Eric D. Prince (convener and editor).

and Lynn M. Pulos (editor). December 1983, 211 p.

9. Sampling statistics in the Atlantic menhaden fishery, by Alexander J. Chester.

August 1984, 16 p.

10. Proceedings of the Seventh U.S.-Japan Meeting on Aquaeulrure, Marine Finfish

CUlture, Tokyo, Japan, October 3-4, 1978, by Carl 1. Sindermann (editor). August IQ84,

31 p.

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Reduker, William L. Current, and Donald W. DuszynSki. August 1994, 18 p.

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Cne, David B. Holts, and Richard W. Butler. September 1984, 16 p.

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1818, by Michael 1. Dadswell, Bruce D. Taubert, Thomas S. Squrers, Donald Marchette, and Jack Buckley. October 1984, 45 p.

15. Chaetognatha of the Caribbean sea and adjacent areas, by Harding B. Michel

October 1984, 33 p.

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from the Pacific Ocean, by Gary A. Wolff. November 1984, 50 p.

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on the Gulf of Mexico, by Maurice L. Renaud. February 1985. 9 p.

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N. Raju. February 1985. 19 p.

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by George H. Darcy. February 1985, 32 p.

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Serranidae), by George H. Darcy. March 1985. 21 p.

n Proceedings of the Eleventh U.S.-hpan Meeting on Aquaculture. Salmon Enhance·

ment, Tokyo, Japan, October 19-20, 1982. by Carl J Smdennann (editor). March 1985.

lU2 p.

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de/phis) in the eastern Pacific, by William F. Perrin, Michael D. Scott. G. Jay Walker.

and Vlfginia L. Casso March 1985, 28 p.

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A. Sakanari, Carol A. Reilly, and Jeannette Whipple. April 1985. 4 p.

30 Synopsis of biological data on the pink shrimp, Panda/us borealis Kr6yer, 1838.

by Sandra E. Shumway, Herbert C. Perkins, Daniel F. Schick, and Alden P Stickney.

May 1985, 57 p.

31. Shark calches from selected fisheries off the U.S. east coast. by Emory D. Anderson, John G. Casey, John 1. Hoey, and W. N. Witzel I: July 1985, 22 p.

32. NUlrient Distributions for Georges Bank and adjacent waters in 1979. by A. F.

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NOAA Technical Report NMFS 36

An Egg Production Method

for Estimating Spawning Biomass

of Pelagic Fish: Application

to the Northern Anchovy,

Engraulis mordax

Reuben Lasker (Editor)

December 1985

U.S. DEPARTMENT OF COMMERCE

Malcolm Baldrige, Secretary

National Oceanic and Atmospheric Administration

John V. Byrne, Administrator

National Marine Fisheries Service

William G. Gordon, Assistant Administrator for Fisheries
The National Marine Fisheries Service (NMFS) does not approve, recommend

or endorse any proprietary product or proprietary material mentioned in this

publication. No reference shall be made to NMFS, or to this publication furnished by NMFS, in any advertising or sales promotion which would indicate

or imply that NMFS approves, recommends or endorses any proprietary

product or proprietary material mentioned herein, or which has as its purpose

an intent to cause directly or indirectly the advertised product to be used or

purchased because of this NMFS publication.

ii
CONTENTS

Lasker, Reuben

Introduction: An Egg Production Method for Anchovy Biomass Assessment 1

Parker, Keith

Biomass Model for the Egg Production Method 5

Picquelle, Susan, and Gary Stauffer

Parameter Estimation for an Egg Production Method

of Anchovy Biomass Assessment 7

Smith, Paul E., and Roger P. Hewitt

Sea Survey Design and Analysis for

an Egg Production Method of Northern Anchovy Biomass Assessment 17

Smith, Paul E., William Flerx, and Roger P. Hewitt

The CalCOFI Vertical Egg Tow (CalVET) Net 27

Stauffer, Gary, and Susan Picquelle

Procedures for Sorting, Staging, and Ageing Eggs 33

Moser, H. Geoffrey, and Elbert H. Ahlstrom

Staging Anchovy Eggs 37

1.0, Nancy C. H.

A Model for Temperature-Dependent Northern Anchovy Egg Development

and an Automated Procedure for the Assignment of Age to Staged Eggs 43

Hewitt, Roger P.

A Protocol for Designing a Sea Survey

for Anchovy Biomass Assessment 51

Picquelle, Susan

Sampling Requirements for the Adult Fish Survey 55

Alheit, Jurgen

Spawning Frequency of Peruvian Anchovies

taken with a Purse Seine 59

Hunter, J. Roe

Preservation of Northern Anchovy in Formaldehyde Solution 63

Hunter, J. Roe, Nancy C. H. 1.0, and Roderick J. H. Leong

Batch Fecundity in Multiple Spawning Fishes 67

Hunter, J. Roe, and Beverly J. Macewicz

Measurement 0i Spawning Frequency in Multiple Spawning Fishes 79

Hewitt, Roger P.

Comparison between Egg Production Method

and Larval Census Method for Fish Biomass Assessment 95

iii

INTRODUCTION:

An Egg Production Method

for Anchovy Biomass

Assessment

REUBEN LASKER

Southwest Fisheries Center,

National Marine Fisheries Service. NOAA.

Po. Box 271.

La Jolla. CA 92038

Fishery scientists engaged in estimating the size of free-swimming

populations have never had a technique available to them whereby

all the parameters could be estimated from a resource survey and

where no parameter values need to be assumed. Recognizing the

need for a technique of this kind, the staff of the Coastal Fisheries

Resources Division of the Southwest Fisheries Center (SWFC) devised an egg production method for anchovy biomass assessment.

PrevIOusly, anchovy biomass was estimated by approximate methods

derived from a long-time series and anchovy larval abundance, which

required about 5 ma ofshiptime each year to integrate the area under

a seasonal spawning curve. One major assumption used in the larval abundance census method is that there is constant proportionality

between larval numbers and spawning biomass. This has now proved

to be erroneous.

The chief advantages of this egg production method are: I) it yields

an instantaneous estimate of egg production and spawning biomass

requiring a single cruise with one or two ships, and 2) each factor

in the biomass estimate is formally derived with estimates of precision. The major disadvantage of the method is that eggs are patchier

and represent a shorter time period than larvae. This requires that

numerous samples be taken to improve precision. Each sample must

be small to reduce variance and to limit the time needed to sort out

the eggs, and the entire spawning area should be encompassed by

the cruise to detect the geographic edge of spawning.

This egg production method is based on an original finding by

Moser (1967) that postovulatory follicles can be seen and used to

determine time of spawning in rockfish. Hunter and Goldberg (1980)

and Hunter and Macewicz (1980), following upon this suggestion,

developed criteria for ageing postovulatory follicles in anchovy and

hence the frequency of spawning of natural populations. This was

confirmed in the SWFC aquarium using Leong's (1971) laboratory

breeding anchovies. Thus incidence of females with postovulatory

follicles or hydrated eggs could be used as a measure of spawning

frequency. Parker's (1980) model, in which all parameters can be

estimated, uses an estimate of egg production divided by the product

of batch fecundity and the proportion of females in the mature stock,

and accounts for the fact that spawning in anchovies is relatively

continuous. Estimates of egg production are derived from direct

plankton net sampling using a net designed by Smith and modified

by Flerx (see Smith et al. 1985). Smith conceived the idea of sampling small numbers of eggs, and guided the procedure at sea each

year since its inception, 1980-84, at the SWFC. Lo (1985) developed

analytical procedures to estimate the natural mortality and the contagious distribution of the eggs. Moser and Ahlstrom (1985)

developed the criteria for staging the eggs.

Besides an estimation of biomass, the application of this technique provides a great deal of information heretofore unobtainable

on the natural history of anchovy populations. For example, we now

can determine the mortality rates of eggs and early larvae and we

have shown that multiple spawners can spawn as many as 20-30 times

in a season. The biological rates we measure appear to be much

more dynamic than we had supposed; egg mortality has differed

greatly from year to year as has fecundity and spawning frequency.

Together these new findings have given us an insight we did not

have before into the potential for recruitment in fish populations.

It is our belief that the egg production method may also be the

technique of choice for determining the spawning biomass of other

multiple spawning pelagic fish, particularly clupeoids, (e.g., sardine, anchovy, and menhaden). Thus this volume is intended to be

a guide to fishery scientists in applying the method to their own

species. We have provided the theoretical basis and described the
operational aspects of the method as we have used it to determine

the spawning biomass of the northern anchovy, Engraulis mordax,

for the last 5 yr in the waters off California and Baja California,

Mexico.

There are several important criteria which must be met before

this egg production method for biomass estimation can be used. The

fish must be a multiple spawner, and its eggs must be pelagic. The

eggs must be caught by a plankton net in the upper layers of the

ocean without significant losses by extrusion. Spawning and

nonspawning adults must be equally available to a trawl or similar

sampler. Application of this technique to other fish may require

modification to fit the biology of the species and circumstances of

sampling and capture.

This manual provides a description of the biomass model and its

mathematical parameters; a physical description of the parameters

themselves, e.g., eggs and spawning adults; and information on the

field methods as we have applied them to determining the spawning biomass of the northern anchovy.

The various steps of the egg production method for determining

northern anchovy biomass, a~ they are done at La Jolla, are charted

in Figure I.

ACKNOWLEDGMENTS _

We are indebted to many people for making this work possible and

they have been recognized by the SWFC for their individual contributions. Special mention must be made of the officers and crew

of the RV David Starr Jordan who have aided us every step of the

way in making this method a successful one.

LITERATURE CITED _

HUNTER, 1. R., and S. R. GOLDBERG.

1980. Spawning incidence and batch fecundity in northern anchovy, Engraulis

mordax. Fish. Bull., U.S. 77:641-652.

HUNTER, 1. R., and B. 1. MACEWICZ.

1980. Sexual maturity, batch fecundity. spawning frequency and temporal pattern in the Northern anchovy, Engraulis mordax. during the 1979 spawning

season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

LEONG, R.

197\. Induced spawning of the northern anchovy, Engraulis mordax Girard. Fish.

Bull., U.S. 69:357-360.

LO. N. C. H.

1985. A model for temperature-<lependent northern anchovy egg development and

an automated procedure for the assignment of age to staged eggs. In R. Lasker

(editor), An egg production method for estimating spawning biomass of pelagic

fish: Application to the northern anchovy, Engraulis mordax, p. 43-50. U.S.

Dep. Commer., NOAA Tech. Rep. NMFS 36.

MOSER, H. G.

1967. Seasonal histological changes in the gonads of Sebastodes paucispinis Ayres.

an ovoviviparous teleost (Family Scorpaenidae). 1. Morpho\. 123:329-354.

MOSER, H. G.• and E. H. AHLSTROM.

1985. Staging anchovy eggs. In R. Lasker (editor), An egg production method

for estimating spawning biomass of pelagic fish: Application to the northern

anchovy, Engraulis mordax, p. 37-4\. U.S. Dep. Commer., NOAA Tech. Rep.

NMFS 36.

PARKER, K.

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

SMITH, P. E., W. FLERX, and R. HEWITT.

1985. The CalCOFI vertical egg tow (CaIVET) net. In R. Lasker (editor), An

egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engraulis mordax, p. 27-32. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

2
TIME FLOW CHART FOR FIELD, LAB AND ANALYSIS PROCEDURES

January February March April May June

Field Collection

Data Management

Lab 1 (Adults)

I Curate Samples I

I Prepare Histological Sections

I Read Slides

L Determine Fecundities

Prepare Cruise Data Key Punch lab Data (Trawl) I Design Data Base Sheets (Trawl)

Prepare Cruise Data Key Punch Field Data (TraWl) Sheets (Egg tows)

I Prepare lab Data Sheets Key Punch and List

Field Data (Egg tows)

Key Punch (Egg tow) Data

I Sort Eggs

Stage Eggs

1 Age Eggs

IPre-Cruise Logistics Obtain Adult Samples I Prepare

I

(Trawl) IPre-Cruise logistics l Cruise

(Egg tows) Obtain Egg Samples Reports

Estimate m~

Determine Reproduction ~~ act cammercial lab far histalag~n Weighing Parameters ~E

time and staffing Update Factors Estimate Egg "a

ey design Instructions 1 Fit Production ~m

se announcements Regression

Cont

Design Ship

Cruise Sur v

Crui

Planning &

Analysis

Lab2 (Eggs)

Figure I.-Time now chart for field, laboratory, and analysis procedures.

3
4
Biomass Model for the

Egg Production Method

The relationship between the spawning biomass of a fish stock and

its production of eggs is easily derived. Simply stated, the production of eggs (P) must be equal to the female biomass that produced

those eggs multiplied by the female batch fecundity:

The female biomass is represented as the product of the total

biomass of the entire stock B, both males and females, and R', the

ponion of the entire stock that is egg-producing females. The batch

fecundity F' is the number of eggs spawned per batch per unit weight

of female.

Note that R' is not the biomass of females divided by the biomass

of males plus females, a simple sex ratio in tenns of biomass. Rather

R' is the total biomass of females that has produced eggs in a specified

period of time divided by the biomass of males and females together.

If females spawn more than once during the period of time in which

production is measured, R' may be greater than the simple sex ratio

in terms of biomass. The converse would be true if, on the average,

females spawn less than once.

It is this fundamental definition of R' that allows Equation (I) to

be easily derived. However, in its present form, Equation (I) is of

practical value only when each mature female spawns once during

the time interval over which production is measured, in which case

R' becomes the simple sex ratio estimated from biomass, say R.

In its present fonn, Equation (1) is not useful for multiple spawners,

when population spawning appears to be continuous over the period

of time over which production is measured. There is no way to relate

production of eggs, P, to female biomass that produced those eggs

without making an adjustment for spawning frequency.

R'. the proportion of female-producing biomass, is composed of

two parts: R, the simple biomass-based sex ratio (the biomass of

females to that of males plus females) andf, the fraction of females

spawning during the time interval,

Parker (1980) documented the above relationship and demonstrated

that spawning frequency if) can be estimated if three conditions

are met: 1) Females can be examined for a characteristic which indicates when spawning will or has taken place, 2) the length of time

such a characteristic remains detectable is estimable, and 3) the

spawning rate (or frequency) remains constant over the sampling

interval in which f is estimated.

Under these conditions the spawning fraction if) is the fraction

of females displaying characteristic I above, divided by the length

of time the characteristic remains detectable. For example, if from

a sample of 10 females, 2 display a characteristic which lasts for

I d and which indicates that spawning will take place in approximately 3 d, then the spawning rate can be expected to be 1/5 in

3 d. Spawning frequency so estimated is additive. For instance, a

daily rate can be summed over any length of time, week, year, etc.

However, if multiple spawnings occur in the time period, parameter

f can exceed unity and is no longer properly a "fraction."

Having developed a condition under which the spawning frequency

can be estimated, Parker (1980) rewrote Equation (I) in terms of

the simple biomass sex ratio (R) and the spawning frequency if),

KEITH PARKERl

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

p. 0. Box 271,

La Jolla, CA 92038

ABSTRACT

The spawning fraction of multiple spawners is estimable when females exhibit morphological characteristics which indicate when spawning will take (or has taken)

place. The length of time in which characteristics remain detectable must in itself

be estimable and constant over the field sampling interval. Spawning biomass is

then estimated as a function of the estimated spawning frequency and other

parameters: egg production, batch fecundity, sex ratio, and average weight of

mature females. Based on the delta method, approximate variance estimates for

spawning biomass are derived and given.

'Presenl address: 8263 Vista Drive, La Mesa, CA 92041.

5

P = (B·R')·F'.

R' = Rf

P = B·RIF'.

(I)

(2)

(3)
Equation (4) is a conventional equation relating spawning biomass

to egg production. The estimate of production (p) can be for any

time interval, as long as the fraction of females spawning if) is computed for the same interval. For a species that spawns but once over

the time interval in which production is measured, say a year, Equation (4) is still valid, but now greatly simplified since f = I.

Stauffer and PicqueUe (1980) modified Equation (4) for the northern anchovy, Engraulis mordax, and based the biomass equation

on a daily estimate of production and fraction spawning,

Spawning biomass can be estimated directly,

B = P/(RIF').

B = P'A(k' W)/(R'F'S)

(4)

(5)

LITERATURE CITED _

PARKER, K.

1980. A direcl method for eSlimaling northern anchovy. Engra"lis mordax, spawning biomass. Fish. Bull., U.S. 78:541-544.

PICQUELLE, S., and G. STAUFFER

1985. Parameter estimation for an egg production method of northern anchovy

biomass assessment. In R. Lasker (editor), An egg production method for

estimaling spawning biomass of pelagic fish: Application to the northern anchovy, Engra"iis mordu.x. p. 7-15. I,;.S. Dep. Commer., NUAA Tech. Rep.

NMFS 36.

SEBER,G. A. F.

197,. The estimation (.f an;rnal ahundance and related parameters. Hafner Press,

N.Y, 50/) p.

STAlIFFER, G. D., and S. J. PICQUELLE.

1980. Estimates or the 1980 spawning biomass of the ,ubpopulalion of northern

anchovy. Natl Mar. Fish Serv.. Southwest Fish Cent., La Jolla, CA, Admin Rer. LJ-80-09, .~ I ;J.

where B

P

spawning biomass in metric tons,

daily egg production, numbers of eggs produced per

0.05 m2 per day,

W = average weight of mature females (g),

R = sex ratio, fraction of population that are mature

females, by weight (g), as before,

F = batch fecundity, number of eggs spawned per mature

females per batch,

S the fraction of mature females spawning per day,

A the total survey area (in 0.05 m2),

k conversion factor of grams to metric tons.

Stauffer and Picquelle (1980) found that more stable estimates

of spawning biomass are achieved if Parker's batch fecundity

estimate by weight is replaced by F, eggs per female per batch,

and W, the average weight of mature females. Stauffer and Pi.:-

queUe (1980) demonstrated estimation with an example. A detailed example is given in Picquelle and Stauffer (1985).

Based on the delta method (Seber 1973), Stauffer and PicquelJe

(1980) show the approximate bias and variance of the biomass

estimator to be a function of sample variances and covariances. Bias

(b) is given by

E[B] = J3+b (6)

where E[B] is the expected value of the biomass and J3 is the estimate

from Equation (5). The bias is approximately

b J3(CV(R)2 + CV(F)2 + CV(S)2 + COVS) (7)

where CV denotes coefficient of variation, and COVS is the sum

of terms involving covariances:

COVS = COV(PW)/PW - COV(PR)/PR - COV(PF)/PF

COV(PS)/PS - COV(WR)/WR - COV(WF)/WF

COV(WS)/WS + COV(RF)/RF + COV(RS)/RS

+ COV(SF)/SF. (8)

Ignoring the bias, approximate variance of the estimate is given by

Var B J32(CV(P)2 + CV(W)2 + CV(Ff + CV(S)2 + 2 COVS)

(9)

6
Table I.-Time series of egg production parameters (1980-84).

INTRODUCTION _

The development of equations for estimating egg production

parameters is based on statistical procedures that are applicable to

survey and sampling designs and that give valid estimates of the

parameters and their variances. The purpose of this paper is to present the statistical equations for estimating daily egg production and

daily specific2 fecundity parameters and the associated variance

estimates that have been used for the nOIthern anchovy. For convenience. a summary of the parameter values estimated for the northern anchovy from 1980 to 1984 is included in Table I.

Parameter Estimation for

an Egg Production Method

of Northern Anchovy

Biomass Assessment

SUSAN PICQUELLE and GARY STAUFFER'

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271,

La Jolla, CA 92038 Parameters 1980 1981 1982 1983 1984

Daily egg production PA 26.34 20.96 13.51

(10 '2 eggs/d)

17.25 12.98

DAILY EGG PRODUCTION _

Sex ratio R 0.478 0.501 0.472 0.549 0.582

(no. females/total)

The estimate of daily production of eggs released into the sea, P,

by spawning adult fish is derived by regressing the counts of eggs

on their age using the exponential mortality model. This model

assumes a constant mortality rate.

(1)

870 635 415 652 309

30.28 33.03 32.53 24.35 42.43

B

Average female W 17.44 13.37 18.83 11.20 12.02

weight (g)

Batch fecundity F 7,751 8,329 10,845 5,297 5,485

(no. eggs/batch

per mature female)

Spawning fraction S 0.142 0.106 0.120 0.094 0.160

(no. spawning

females per

mature female)

Daily specific

fecundity

(no. eggs/g biomass

per d)

Spawning biomass

(103 t)

where Pijk the number of eggs in day k age category from station j in stratum i,

tijk the age in days measured as the elapsed time from

the specified spawning time, to, to the time of sampling of station j in stratum i,

Pi the daily egg production per unit area in stratum i,

Z the daily rate of instantaneous egg mortality, and

E.ijk the additive error term.

A number of regression procedures can be used to estimate P and

Z from the observations of Pijk and tijk depending on the design of

the survey and the availability of statistical computer programs.

First, the need to stratify the plankton survey should be evaluated.

Stratification is usually undertaken to reduce the variance of

parameter estimates. If more than one major spawning area exists,

or if the survey is conducted over a relatively long period such that

spawning rates differ among areas or over time, stratification of the

ABSTRACT

The estimate of daily egg production is derived from the exponential mortality

model fit to the egg density data generated by the plankton survey. The specific

formulation of the model used in any particular application depends on the

availability of computer programs to run the regression analysis. The model also

provides an estimate of egg mortality. Stratification and station weighting schemes

depend on survey station pattern. Poststratification of plankton stations is recommended for eliminating those plankton stations occupied that lie beyond the spawning area.

The adult spawning parameters for the northern anchovy example are estimated

from trawl survey data using the equations for the sample mean and variance

from cluster sampling theory. The choice of the most appropriate estimate in any

particular application depends on the sample design. The need for stratifying the

survey depends on whether the daily population fecundity parameters change in

a consistent fashion over the range and duration of the survey.

The estimation of average weight is straightforward except that the weight of

females with hydrated ovaries must be adjusted downward to correct for the temporary weight gain from the increased nuid in the ovaries. Since batch fecundity

cannot be measured for each female fish, it is estimated for each individual from

a regression model of batch fecundity and ovary-free body weight derived from

a sample of female fish with hydrated ovaries. The station value for batch fecundity is estimated as the sample mean of the estimated fecundities. The variance

of the mean fecundity, however, is adjusted to include the additional variance

resulting from the regression estimation.

For the northern anchovy trawl survey, spawning fraction is the proportion of

the mature females which have day-] postovulatory follicles. Evidence from these

trawl surveys indicate female fISh classed as day-O spawners are oversampled. The

number of mature females per station is adjusted to compensate for this bias.

The sex ratio parameter is the fraction of the mature population that is female,

based on weight rather than numbers. Sex ratio data are best generated from a

second subsample. For these trawl surveys, the sampling bias of day-O spawning

females occurs during the peak hours of the evening spawning period and impacts the estimates of spawning fraction and sex ratio.

'Presenl addresses: Nonhwest and Alaska Fisheries eenler, National Marine Fisheries

Service, NOAA, 7600 Sand Point Way NE, Seattle, WA 98115. 'Daily specific fecundity = number of eggs produced/gram of biomass per day.

7
data after the survey would be appropriate. This occurred in the

anchovy spawning survey conducted in 1983 (Picquelle and Hewitt

1984).

In addition, the total survey area may be considerably larger than

the spawning range. This has been the case for the anchovy resource

off the California coast. The anchovy surveys are intentionally

designed to sample the full range of anchovy spawning, knowing

that in anyone year the spawning will occur over a much smaller

area within the range. As a result, many stations are beyond the

spawning area of anchovies and contribute a large number of stations with zero egg counts, thus inflating the variance of the egg

count data set. To reduce the impact of these zero-count stations,

the total survey area is poststratified into two strata depending on

the presence or absence of eggs in the sample. Stratum 0 contains

the stations beyond the geographic area of spawning so that P is

zero for stratum O. The geographic area containing all the anchovy

eggs and the few embedded stations with zero egg counts make up

stratum 1. In this latter case, the size of the geographic area ofstratum

I, AI' and the number of occupied stations, nl> become random

variables with variances and expected values. The magnitude of this

added variance is negligible if nl is larger than 100 (Jessen 1978).

Poststratification of the stations to eliminate those stations beyond

the spawning area is a recommended procedure for estimating egg

production.

In addition to stratification, it is desirable to increase the density

of plankton stations within the geographic area where adult spawning is expected. Increased sample size in this area will reduce the

variance of P for the positive stratum. To correct for differences

in station density, the egg count observations by station need to be

weighted by a factor proportional to their representative area such

that the sum of the station weights in the positive stratum, i=l, equals

nl , the total number of stations in this stratum, i.e.,

version of the model is

This linear model gives the error structure of £ as additive in the

transformed expression. This implies a multiplicative error structure in the nonlinear model. The form of the error in either case

should be studied by examining the variability about PIjk versus age.

This can best be accomplished by examining the residuals between

the observed Pljk and those predicted by the model. The antilog

estimate of P will be biased. An unbiased estimate can be approximated by

where S2 is the estimated residual variance from the regression

analysis, usually denoted by Sy}.

If computer facilities are not readily available. the estimation of

P and Z can be further simplified. This simplification involves

averaging the egg counts Pljk over time intervals of equal length.

A minimum of three time intervals is necessary to estimate the two

parameters P and Z. For the anchovy example, five intervals of

12 h were tried. The modified mortality model in this case is3

PI;' = P\e-Zt'k(l_ e-Z.l/)/Z~I

- where PH: the average number of eggs of age tk sampled during the time interval (tk> tk+I),

!~=tk-t~ = the time elapsed (or age) between spawning and

the beginning of the time interval, k,

to the midpoint of the daily spawning period, and

lit the length of the time interval (tk+1 - tk ) over

which Pljk are averaged.

The linear form of this model is

"I

LWlj = nl'

j-I

where Ai

A

In sampling theory, several estimates of the population mean are

described; the choice of the most appropriate estimate depends on

the sample design. Trawl surveys typically consist of a three-stage

sampling design: I) the selection of the trawl stations, 2) the catch

of fish at the station, and 3) the selection of the subsample of fish

from the catch. The sample design, and hence the estimate, is determined by how each of the stages is executed.

There are two common methods for selecting station locations:

random sampling and judgment sampling. Under the random sampling regime, the trawl stations are distributed randomly over the

survey area. The exact locations of the stations are determined principally by the requirements of convenient and efficient use of ship

time, and by the desire to have stations distributed evenly over the

where the regression coefficients bo = In(P,(I-e-Z&')/ZIJ.t), and

b l = -Z. Substituting the value of Z from bl into bo will provide

an estimate of PI' These estimates of P and Z should be useable

in most cases, but their associated variance estimates will not be

realistic.

'McCaughran, C. A., IntI. Pacific Halibut Comm., Seattle, WA., pers. commun.

May 1981.

DAILY SPECIFIC FECUNDITY _

Station Weighting Alternatives

I A I Ao Var(P) = (I+-)(-Var(P1) + -A Var(Po)) n A

n

= the area of stratum i for each region,

= AI + Ao,

the total number of observations for the survey,

J.ilr(PI ) = estimated for stratum I from the regression

analysis, and

Var(Po) = 0 by definition.

In the event that a computer program for nonlinear regression is

not available, the egg mortality model must be linearized so that

P and Z can be estimated by linear regression methods. The linear

Since the egg counts in the zero stratum are zero, weighting in that

stratum is unnecessary. The preferred statistical technique for

estimating parameters P and Z from Equation (I) is weighted

nonlinear least squares regression fit to individual egg counts and

ages from stations within the positive stratum. The computer program used for the northern anchovy case was BMDPAR (Dixon and

Brown 1981).

The stratified estimate of P can be calculated as the weighted

average of Po and PI' where Po is zero by definition and PI is

estimated by regression analysis, and the weights are the relative

areas of the two stratum, i.e.,

AI Ao P= A P\+ APo

and the variance, adjusted for postsurvey stratification (Jessen 1978)

is

8
(4) = 1 M;Yi Y = --L..--

M ol1;_1 !Ii

larger. This estimate is self-weighting when the subsampling fraction m;!Mi is constant.

Under judgment sampling, the attempt is made to sample with

probability proportional to size. If this can be accomplished, or if

confidence is high that this situation is closely approximated, then

the unbiased estimates of the population mean and the variance are

the same as Equation (2). This estimate is self-weighting when mi

is constant.

If, instead, the stations are selected with probability proportional

to Ui' a measure of size, and the catch size is proportional to the

popUlation size at the station, then the appropriate estimate is

[

M;Yi- = ]2 L..---Y

and Var (Y) = i-I !liMo

11 (11 - I)

where Mo is the total population size. This estimate is selfweighting if nuim;!Mi is constant. However, this estimate is not very

useful because Mo, the total population size, is rarely known, and

the estimates of station sizes, Ui' can rarely be enumerated.

A modification of Equation (2) is used for the trawl survey for

the northern anchovy. As mentioned earlier, this estimate is unbiased

if sampling with probability proportional to size. The information

used to detect high concentrations of anchovies is the occurrence

of anchovy spawning products in the plankton samples taken concurrently, and the presence of apparent schools on the sonar. Both

of these factors are good indicators of local concentrations of anchovies, and the resulting sample design is assumed to be a good

approximation of sampling with probability proportional to size,

justifying the use of Equation (2).

Equal subsample sizes are attempted, but occasionally a station

will produce a very small catch or a catch with very few mature

females (mostly males or mostly immature fish). Both situations

will result in a small subsample, as most of the parameters to be

estimated are for mature females. This occurrence is interpreted as

meaning that an error in judgment sampling has been made. The

actual size of the station, based on mature females, is much smaller

than was estimated at the time the trawl station was selected. Hence,

the probability ofselecting that station should be adjusted a posteriori

to reflect the actual size of the station. This is accomplished by giving

these stations less weight in the estimate; each station is weighted

by its subsample size, mi' Thus, Equation (2) is modified to produce the following estimate:

(2) • n <Yi-y)2

and Var(Y)=:L (-I) i_111 11

the estimate of the population mean,

the number of stations,

where y

n

survey area. This strategy will produce station locations independent of local fish population densities.

Judgment sampling uses information independent of the trawl

samples to place stations where fish abundances are high. This information may consist of a historical account of the distribution of

fish based on current sea temperature and salinity data, results from

a recent survey, the use of sonar to detect fish schools, or observable evidence of local fish concentrations, such as their spawning

products in plankton samples. The resulting distribution of stations

will be patchy, with the high densities of stations coinciding with

high densities of fish. This strategy approximates the sampling technique of probability proportional to a measure of size.

The second stage of sampling, the catch of fish, is ideally a random sample of fish residing at the station. However, some bias may

occur due to net design, the execution of the trawl, fish behavior,

and other variables. In addition to striving for a random sample,

it is also advantageous if the catch size is proportional to the number

of fish at the station. This is valuable information which may be

incorporated into the estimate, but this situation holds only for certain species and sampling methods.

Fish are subsequently sampled randomly from the catch. The subsample size is usually constant, but may vary with the catch size

to produce a self-weighting estimate for some of the estimates

presented below.

Based on this sampling structure, many specific sample designs

and corresponding estimates of the population mean may be considered. The following estimates all assume that the total population size is very large and the finite population correction is approximately 1. Under these conditions, the within-subsample contribution to variance disappears because this quantity is multiplied

by 11Nn which is approximately O.

If stations are selected randomly, and catch size is unrelated to

fish abundance, then each station should receive equal weight and

equal subsample sizes should be attempted. In this case the appropriate estimate is (Cochran 1fJ77)

Di _ i-I

Y=-nmi = the number of fish subsampled from the ith

catch.

This estimate is a biased estimate of the true population mean and

this bias does not necessarily get small as n gets large. The estimate

is self-weighting if mi is constant.

A better estimate exists for the case of random station selection

if the catch size is proportional to the abundance of fish at the station. This is the ratio-to-size estimate:

If mi is constant, this estimate simplifies to Equation (2). This

estimate is biased because it is the ratio of two random variables,

m;Yi and mi' However, the bias is of the order lIn, so that the bias

gets smaller as n gets larger.

- ~Y;; Yi = L..-

j-I m;

the mean of the ith station, and

I.miji - i-I Y=---

I.m;

i-I

and

n

:Lm/<Y; - y)2

Var (Y) = ""'[";"~-"":~'-'-;-1'2---

L-' 11 (11 - I)

i_Ill

(5)

where Mi is the total number of the target fish species caught in

the ith trawl. This estimate is biased because it is a ratio of two

random variables, but the bias is small and gets smaller as n gets

I.M;Yi _ i-I Y=--- I.M;

;-1

(3)

Trawl Survey Stratification

The egg production model assumes that the parameters in the model

are constant over the range and duration of the survey. Ifthis assumption is violated, the survey should be divided into regions or time

spans within which the parameters are constant. The biomass is then

estimated separately for each section of the survey and then summed

to produce the total biomass estimate.

9
The observed frequency distribution of the average female weight

per trawl is usually symmetrical although there may occur a hint

of bimodality ifthere is a large l-yr-old year ciass. The weights within

each trawl tend to be homogeneous. suggesting that the anchovy

schools are homogeneous with regard to weight.

Batch fecundity can be observed only for those females whose

ovaries contain hydrated eggs. There is a high correlation between

the number of eggs per batch and the ovary-free body weight. This

relationship is used to estimate batch fecundity for the same mature

females used to estimate female weight.

The sample of hydrated females is collected throughout the trawl

survey and the number of eggs per batch (Fi

) and ovary-free weight

(W;/) are recorded for each of these females. This data are used

to fit a model regressing batch fecundity on ovary-free weight

A linear regression has explained the data satisfactorily in previous

surveys, although a curvilinear model should be considered depending on the shape of the data.

Using this regression, batch fecundity is estimated for each mature

female subsampled. The accuracy of the estimated batch fecundity

will be improved if the distribution of weights for the sample of

hydrated females used to fit the regression is similar to the distribution of weights for the total sample of females.

Equation (5) is used to estimate average batch fecundity where

the Yij are in this case the estimates Fij. However, there is an added

source of variance that should be included because the Fij are not

observed directly but are estimates with their own associated

variance. Thus, the estimate of variance is adjusted to include this

additional variance (Draper and Smith 1966):

Yij = the observed value for the jth fish sampled

from the ith trawI.

Female weight is estimated from a fixed subsample size of mature

females. The subsample size has ranged from J5 to 25 mature females

for the surveys taken from 1980 through 1983; however, the targeted

subsample size is not always realized, due to very smail catches,

a high proportion of immature fish, or a high proportion of males.

The Yij in Equation (5) is the whole body weight of the jth mature

females sampled from the ith trawl (W;), This observed weight is

adjusted downward for those females whose ovaries contain hydrated

eggs because their body weight is temporarily inflated due to water

retention. This adjusted weight (w:) is estimated from a linear

regression 8f whole body weight regressed on ovary-free weight

(W;/) which is fit cn])' to those females that do not have hydrated

eggs.

(7)

(6) . . • * Wij = a + {3 Wu

Fij = a + {3 Wi)*+ €i)'

the average value for the ith trawl, and

= the number of trawls,

= the number of fish subsampled from each

trawl,

n

LmiYi - i-I y=--- tn1;

i-I

m;

m;

Yi = LYij/m;

j-I

where n

Table 2.-Estimates of egg production parameters and spawning biomass by

region for 1983. Coefficient of variation indicated by parentheses.

Parameters North Bight South Total

Daily egg production P 1.62 7.28 5.06

(no. eggs/0.05 m2 per d) (0.671) (0.0751) (0.332)

Area of region A 0.420 1.33 1.36

(10 12 0.05 m2)

Average female weight (g) W 12.9 11.2 9.63

(0.121) (0.0705) (0.D385)

Batch fecundity F 6,285 5,295 4,423

(no. eggslbatch (0.140) (0.0882) (0.0570)

per mature female)

Spawning fraction S 0.0346 0.103 0.126

(no. spawning females (0.563) (0.174) (0237)

per mature female)

Sex ratio R 0.523 0.559 0.549

(no. females/total) (0.0949) (0.0736) (0.128)

Spawning biomass (103 t) B 77.5 358 216 652

(0.897) (0.214) (0.419) (0.211)

Parameter Estimation

The parameters of the daily population fecundity are all estimated

from samples of anchovies collected on a midwater trawl survey.

These parameters, female weight (W), batch fecundity (F), spawning fraction (S), and sex ratio (R), and their variances, are estimated

using Equation (5) developed previously:

An example of this situation is the Spring 1983 anchovy spawning biomass survey. Two parameters of the daily specific fecundity

varied significantly with geographic regions, female weight decreased

from north to south, and spawning fraction increased from norLh

to south.

The survey area was divided into three regions: north, bight, and

south (Figs. 1,2). Figure 3 illustrates the frequency distribution for

female weight by region; the average female weight for the southern

region was significantly smaller than the average weights for both

the bight and north regions. The pattern for spawning fraction was

the opposite (Fig. 4) with the estimate for the north region being

significantly smaller than the estimates for the bight and south

regions.

Table 2 presents the parameter estimates and biomass estimates

for each region. Each of the population fecundity estimates, W, S,

F, and R, was estimated separately for each region. It was impossible to estimate Po, egg production, independently for each region

because of the small sample sizes per region. Instead, the slope of

the mortality curve, Z, was assumed to be constant for the entire

survey and hence was estimated using all the data. The intercept

of the mortality curve, Po, was allowed to vary between regions and

was estimated by fitting a separate but parallel mortality curve to

each region while holding the mortality estimate, Z, fixed at the

value previously estimated.

The total biomass estimate is simply the sum of the regional

biomass estimates, and the total variance estimate is also just the

sum of the regional variances. This variance estimate ignores any

covariance terms between regions, which is probably trivially small

because all parameters were estimated using separate and independent data for each region, except for the mortality, Z, whose contribution to covariance is probably slight.

10
300

1230

o

1200

8302 MIDWATER

TRAWL SURVEY

+ POSITIVE STATION

o NEGATIVE STATION

BIGHT

Figure I.-Geographic distribution of trawl stations and

positive trawls within each region.

11

Figure 2.-Subdivision of CaiVET survey into strata (0 =

beyond the range of anchovy spawning; 1 = within the range

of anchovy spawning) and regions <North, Bight, and South).
(8)

(9)

where frij is the estimated batch

S.2 _ * _* _ _] + - + (Wi - W.) Va,(,f3) n.

l

n mj )2 I.- II

;_1 n

Var({J)

nil

-

Fj

n 2[ Cli - '1)2 I.mj 1

Var(F) = ;-1 nwhere F

The average value of mi* will be smaller than the average mi, and

the resulting estimate of spawning fraction based on day-l spawners

will be larger to compensate for the bias in sampling day-O spawners.

The parameter sex ratio is the fraction of the mature population

that is female, based on weight rather than numbers. Equation (5)

is again used, where mi is the weight of the subsample rather than

number, and Yi is the fraction of the subsample weight that is attributable to female fish. Both mature and immature fish are included in the estimate because it is impossible to distinguish between mature and immature males. It is assumed that sex ratio by

weight is the same for both mature and immature fish.

To save effort in preserving and weighing individual fish, Yi and

mi are estimated rather than measured directly. A fixed number of

fish are subsampled from each trawl and the numbers of females

and males are recorded. The average weight for each sex is estimated

the estimate of batch fecundity for the whole

population of mature females,

the average batch fecundity for the ith trawl, m·

= tJu/m;

j-I

fecundity for the jth female in the ith subsample,

the variance about the regression (Equation (7»,

the number of hydrated females used to fit the

regression (Equation (7»,

the average ovary-free weight for the ith trawl,

the average ovary-free weight for the n. hydrated

females, and

the variance of the slope of the regression (Equation (7».

Spawning fraction is estimated using Equation (5) by setting :V,

equal to the proportion of mature females in the ith trawl which

have been classifi~d as having day-l postovulatory follicles (day-l

spawners). Thus, yestimates the fraction of mature females in the

population that are day-l spawners, which is a measure of the fraction of mature females which are spawning on any given day.

Spawning fraction can also be estimated by the fraction of females

classified as day-O spawners. However, this fraction has been consistently higher than the fraction of day-l spawners. Past experience

has shown that using day-O spawners may produce a biased estimate,

at least for northern anchovy sampled by a trawl survey. Evidence

of this conclusion will be presented in a later section.

If day-O spawners are indeed oversampled, then day-l spawners

are undersampJed. The sample of mature females from each catch

may be grouped into three caregories: Day-O spawners (mjo); day-l

spawners (m,l); and day 2+ spawners (m?). For a fixed subsampie size, if one group is over-represented then the other two groups

are under-represented. This is corrected by adjusting mj to reflect

what subsample size would have included the observed number of

day-l spawners if day-O had not been oversampled. The number of

day-O spawners included in mi is replaced by the observed number

of day-l spawners, since day-O and day-l spawners should be equal,

on average, because they both measure the number of females spawning during a 24-h period. Thus, the m; in Equation (5) is replaced

by

24

24

0.3

0.3

20

16 20

16

0.2

0.2

BIGHT REGION

NORTH REGION

SOUTH REGION

12

12

SOUTH REGION

BIGHT REGION

NORTH REGION

8

8

0.1

0.1

4

4

~.o 0.1 0.2 0.3

PROPORTION OF SPAWNING FEMALES PER TRAWL

o '---'--.......== o 4 8 12 16 20 24

AVERAGE FEMALE WEIGHT PER TRAWL (grams)

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

0

0.0

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

0

0.0

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

0

0

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

0

0

10

>- 8 0

z

w 6 ::l

0 4 w

a::

l1. 2

Figure 3.-Frequency distribution for average whole-body weight of

mature females in grams for each region.

Figure 4.-Frequency distributions of spawning fractions for each region.

12
0.0 ......-'"1"''-

1800 2000 2200 0000 0200 0400

1900 2100 2300 0100 0300 0500

HOUR

0.4

i Hydrated Eggs

Day 0 & H. Eggs

0.3 Day 0

z

0

i=

a:

0 0.2 c..

0

a:

c..

0.1

(11)

(10)

wr = m(-Wr

W;M = mi\{'Wi\{

where W/

for each trawl from a smaller fixed subsample of each sex. The total

weight of each sex in the subsample is estimated by multiplying the

observed number of fish of that sex by its average weight.

the total estimated weight of the kth sex in the

ith subsample,

the number offish of the kth sex in the ith subsample,

and

W/ the average weight ofthe kth sex in the ith subsample.

Then mi is estimated by the sum of the estimated total weight of

males plus the estimated total weight of females,

and y; is the estimated total weight of females divided by mi Figure S.-Breakdown of day-o females into ovarian categories by time of

sampling.

y; = Wr; m; . (12)

1978

1979

1980

All years

........ .. .......:. ".

0.0 '-,-,..-r-""""-""'--""""-T""""""T--r---r-,..--,,.-

1800 2000 2200 0000 0200 0400

1900 2100 2300 0100 0300 0500

HOUR

0.0 I.....f-....--r-,..--,r-......,-,....---+-T""""""T--t----.,.-

1800 2000 2200 0000 0200 0400

1900 2100 2300 0100 0300 0500

HOUR

0.4

DAY 0 ------ 1978

0.3 1979

,~ 1980

z 1\ All years 0 .•../\ i= \ I \ a: 0.2 ". I \ 0 \/ .X· c.. ".' \ I 0

a: !\/'i.; :~' ....... c.. ..,..:

I '.

0.1 /

I '" ............ I

,

I

0.4

DAY 1

0.3

z

0

i=

a: 0.2 /(:...:::.7\~-\ 0

c..

0

a: /". c.. \

0.1 'v

Figure 6.-Proportion of day-o spawning females by hour for trawl surveys conducted from 1978 to 1980.

Figure 7.-Proportion of day-l spawning females by hour for trawl surveys conducted from 1978 to 1980.

13

Sampling Bias

Spawning fraction may be estimated by either the number of day-O

spawners or the number of day-I spawners, as each is an estimate

of the number of females spawning on any given day. However, as

mentioned earlier, the proportion of day-O spawners is consistently

larger than the proportion of day-I spawners. A hypothesis on the

mechanism causing this result is that females who are actively spawning are more vulnerable to capture by a midwater trawl. This hypothesis is supported by the observation that the catch of spawning

females (day-Q) increases significantly during the hours ofthe evening

when spawning takes place.

This phenomenon is illustrated by Figure 5. This bar chart was

calculated using data from the trawl surveys conducted from 1978

to 1980. Day-O spawners are composed of three types of females:

Females whose ovaries contain hydrated eggs which will be spawned

later that evening (represented by an open bar); females whose

ovaries contain postovulatory follicles indicating they have spawned

earlier that evening (represented by the bar area with horizontal

lines); and females whose ovaries contain both hydrated eggs and

postovulatory follicles indicating they were caught during spawning (represented by vertical lines in the bars). The predominant hours

of spawning are 2100-2359, when the highest number of females

are caught with both hydrated eggs and postovulatory follicles in

their ovaries. This is also the time period when the proportion of

day-O spawners in the catch is highest.

It should also be noted that the proportion of day-O spawners

decreases after 0300. This can be more easily seen in Figure 6, which

shows the proportion of day-O spawners by hour for each year, and

all years combined. Figure 7 shows that the proportion of day-I

spawners also drops off after 0300. This is explained by an increased

error rate in classifying ovaries as to the date of spawning (day-O,

day-I, or later), and in subsequent years trawl catches were not made

after 0300 to avoid this problem.

If one ignores the points corresponding to 0300 and later, then

The parameters Wr and W;M are estimated with little error because

the weights of fish within a trawl catch are quite homogeneous. Thus

the added variance in estimating sex ratio, due to the fact that y;

and m; are estimated rather than observed, is assumed to be trivial.
0.30 r-------------------....,.

a comparison of Figures 6 and 7 shows that the plot of day-I spawners

is quite flat over time, while day-O spawners exhibit a definite peak

at 2100-2359. The comparison is highlighted in Figure 8. The proportion of day-O females is plotted against the proportion of day-I

females for each hour, and I-standard-error bars are drawn for day-I

proportions. The diagonal line shows the values for which the proportions of day-O and day-I spawners are equal. The obvious outlier

points (i.e., those points furthest from the day O=day 1 line) correspond to the time 2100-2359.

0.25

0.20

>-

«

c

z

0.15

a:

o

Q.

o

:E 0.10

0.05

0100 I 2100t

r 2300

I : t0200-0300 I

t0400-0500

The effect of time on the proportion of day-O and day-I females

in the catch can be quantified using contingency table analysis. Table

3 shows the number of females from the 1978-80 trawl survey

samples, by spawning condition and time of their capture. Parentheses contain the expected number of females under the hypothesis

that there is no interaction between time and spawning condition.

The contribution to the i statistic by the cell is in brackets. The

resulting X2 statistic (X2 = 38.85, df = 16) is highly significant (P

= 0.05), thus rejecting the hypothesis of no interaction between time

and spawning condition. Examination of the individual cell's contribution to the test statistic shows that the largest deviations are

due to the hour 2100-2159. Omitting this hour from the analysis produces Table 4 and a nonsignificant (P =·0.05) test statistic (X2 =

20.51, df = 14). Therefore, if the hour 2100-2159 is omitted, there

is no significant relationship between time and spawning condition.

Based on this analysis, the conclusion is made that day-O spawners

are sampled with bias during the peak hours of spawning.

A similar scenario has been discovered for sex ratio and time.

The proportion of females declines radically during the time period

2300-2359. A contingency table analysis (Table 5) shows that there

is a significant interaction between time and sex ratio (x2 = 126.44,

df = 8); an examination of the individual cells shows a large deviation during time 2300-2359. When this time period is removed (Table

6), there is no significant interaction (X2 = 10.63, df = 7). Apparently, there is a sample bias also occurring for sex ratio during

the hours when spawning activity is greatest.

0.00 "'---..I---......l..-----'----'----...J---~

0.00 0.05 0.10 0.15 0.20 0.25 0.30

PROPORTION DAY 0

Figure S.-Day-! vs. day-O females for each hook w.ith standard error bars for

day-! females.

LITERATURE CITED _

COCHRAN, W. G.

1977. Sampling techniques, 3rd ed. John Wiley and Sons, NY, 428 p.

DIXON, w. 1., and M. B. BROWN.

1981. BMDP statistical software. Univ. Calif. Press, Berkeley, CA., 735 p.

DRAPER, N. R., and H. SMITH.

1960. Applied regression analysis. John Wiley & Sons, NY, 407 p.

JESSEN, R. 1.

1978. Statistical survey techniques. John Wiley & Sons, NY, 520 p.

PICQUELLE, S. 1., and R. P. HEWITT

J984. Estimates of the spawning biomass of the northern anchovy for the 1983-84

California fishing season. Calif. Coop. Oceanic Fish. Invest. Rep. 25:16-27.

Table 3.-Contingency table analysis of spawning condition by time. Each cell contains the observed count,

the expected count in parentheses, and the contribution to the x' statistic in brackets.

Time (h)

Spawning 1800- 1900- 2000- 2100- 2200- 2300- 0000- 0100- 0200-

condition 1859 1959 2059 2159 2259 2359 0059 0159 0259 Total

Day-O 25 42 30 67 49 30 29 19 9 300

(27.5) (45.3) (35.9) (44.5) (41.4) (284) (31.8) (32.0) (13.3)

[0.22J [0.24J [0.96] [11.36] [1.41] [0.09J [024J [5.26] [141]

Day-\ 25 31 30 19 27 12 26 18 7 195

(17.8) (294) (23.3) (28.9) (26.9) (185) (20.6) (20.8) (8.7)

[2.87J [0.08] [1.91] [341] [0.00] [227] [1.39] [0.37] [0.32)

Day-2+ 90 158 123 141 135 103 107 126 52 1,035

(94.7) (156.3) (123.8) (153.6) (142.7) (98. I) (109.6) (110.3) (46.0)

[0.23) [0.02) [0.01] [1.03] [OA2] [025) [0.06] [2.25] [0.78]

Total 140 231 183 227 211 145 162 163 68 1,530

x' = 38.85, df = 16

X2'6(0.95) = 26.3

)4
Table 4.-Contingency table analysis ofspawning condition by time, in which the hour 2106-2159

has been omitted. Each cell contains the observed count, the expected count in parentheses,

and the contribution to the -; statistic in brackets.

Time (h)

Spawning 1800- 1900- 2000- 2200- 2300- 0000- 0100- 0200-

condition 1859 1959 2059 2259 2359 0059 0159 0259 Total

Day-O 25 42 30 49 30 29 19 9 233

(250) (41.3) (32.7) (37.7) (25.9) (29.0) (29.1) (12.2)

[O.OOJ [0.01] [0.23J [3.37] [0.64] [O.OOJ [3.53] [0.82]

Day-I 25 31 30 27 12 26 18 7 176

(18.9) (31.2) (24.7) (28.5) (19.6) (21.9) (22.0) (9.2)

[1.96J [0.00] [1.13] [0.08J [2.94J [0.78] [0.73] [0.52]

Day-2+ 90 158 123 135 103 107 126 52 894

(96.1) (158.5) (125.6) (144.8) (99.5) ( 111.1) (111.8) (46.7)

[0.38] [0.00] [0.05] [0.66] [0.12] [0.15] [1.79] [0.61]

Total 140 231 183 211 145 162 163 68 1,303

X' = 20.51. df = 14

114(0.95) = 23.7

Table 5.-Contingency table analysis of sex ratio by time. Each cell contains the observed count, the expected count in parentheses, and the contribution to the 1 statistic in brackets.

Time (h)

1800- 1900- 2000- 2100- 2200- 2300- 0000- 0100- 0200-

Sex 1859 1959 2059 2159 2259 2359 0059 0159 0259 Total

Female 153 349 189 271 227 189 163 187 71 1,799

(131.2) (331.2) (160.3) (268.3) (198.7) (321.9) (154.4) (175.5) (57.4)

[3.62] [0.96] [5.13] [0.03] [4.03] [54.88J [0.48J [0.75J [3.23]

Male 158 436 191 365 244 574 203 229 65 2,465

(179.8) (453.8) (219.7) (367.7) (272.3) (441.1) (211.6) (240.5) (78.6)

[2.64] [0.70] [3.74] [0.02] [2.94] [40.05] [0.35] [0.55] [2.36]

Total 311 785 380 636 471 763 366 416 136 4.264

1 = 126.44, df = 8

x's(0.95) = 15.5

Table 6.-Contingency table analysis of sex ratio by time, in which the hour 2300-2359 has

been omitted. Each cell contains the observed count, the expected count in parentheses, and

the contribution to the 1 statistic in brackets.

Time (h)

1800- 1900- 2000- 2100- 2200- 0000- 0100- 0200-

Sex 1859 1959 2059 2159 2259 0059 0159 0259 Total

Female 153 349 189 271 227 163 187 71 1,610

(143.0) (361.0) (174.8) (292.5) (216.6) (168.3) (191.3) (62.5)

[0.70] [0.40] [1.16] [1.58] [0.50] [0.17] [0.10] [1.14]

Male 158 436 191 365 244 203 229 65 1,891

(168.0) (424.0) (205.2) (343.5) (254.4) (197.7) (224.7) (73.5)

[0.59] [0.34] [0.99] [1.34] [0.43] [0.14] [0.08] [0.97]

Total 311 785 380 636 471 366 416 136 3,501

I = 10.63, df = 7

x\(0.95) = 14.1

15
16
Sea Survey Design and

Analysis for an Egg

Production Method of

Anchovy Biomass

Assessment

PAUL E. SMITH and ROGER P. HEWITTI

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271.

La Jolla, CA 92038

ABSTRACT

A sea survey of spawning habitat is described for the northern anchovy, Engrautis

mordax. The central population occurs within a permanent gyral circulation off

southern California and in the adjacent nearshore and main branches of the

California Current. The geographic scope ofspawning is maximal in winter and

spring, and its extent appears to be a function of population biomass.

About 8 hours after the onset of spawning it becomes possible to obtain effective samples: adult data can be used for about a day and egg data for a little more

than 2 days to estimate vital rates, such as egg production and mortality. The

spawning process is so patchy and dynamic that it has not yet been possible to

gather useful data on adults or eggs during the spawning interval.

The population egg production rate is determined by a survey using about 1,000

vertical plankton tows of 3.5 m3 between -;,) m depth and the surface. The array

of samples is intended to be representative and inclusive of the entire spawning

area. Observations of the number of eggs per sample represent a contagious

distribution (patchy), and the assumptions necessary for a "normal" or "lognormal" model are not met. The assumption ofindependence ofsample parameters

(mean and variance) is not supported with either model. The probability distribution most closely approximated is the "negative binomial!' The parameters of that

distribution change with the age of the egg.

The Southwest Fisheries Center Egg Production Method was initiated with much

historical, geographic, and biological data obtained in the California Cooperative

Oceanic Fisheries Investigations (CaICOFl). It should be possible to initiate an

egg production method on other species in other regions without this vast timeseries of data. Preliminary laboratory work, field surveys, and analyses are described for research at other temperatures and for the diagnosis of egg production for species which spawn at all times of day rather than nocturnally. The

geographic limits of spawning should initially be described from oblique plankton tows filtering larger volumes of water (500-1,000 m3

). Also, differences in

spawning patch intensity may require observations of more than the 3.5 m3 which

is adequate for the anchovy in this region.

'Present address: Commanding Officer. NOAA Ship Miller Freeman. Pacific Marine

Center. 1801 Fairview Ave. East. Seattle. WA 98102.

17

THE SPAWNING PROCESS _

Spawning Area

The northem anchovy, Engraulis mordax, spawns within the regional

eastern boundary current, the California Current system. Figure 1

is a series of overplots of all samples of anchovy eggs collected from

1951 to 1981. These serve to describe the maximum spatial distribution ofspawning in each bimonthly period. Spawning occurs primarily nearshore of the main branch (Hickey 1979) of the California Current. The main branch of the California Current is 300 km off

Washington and Oregon (lat. 45°N), 430 km off Cape Mendocino

Oat. 39'N), TlO km off Point Conception (lat. 34ON), 240 km off

northern Baja California (lat. 30 0N), and 200 km off Cape San

Lazaro (1at. 25'N).

The boundaries of the main branch ofthe California Current shift

in position and are indistinct at every season. The 1950-78 average

in a section normal to the coast at lat. 32°N reveals the three branches

of the California Current postulated by Hickey (1979) (Lynn et al.

1982). The speeds of the surface currents at the cores of these three

zones are given in Table 1. It may be inferred from Figure I that

the nearshore zone of the California Current system is the most consistent spawning site of the northern anchovy and that virtually no

spawning takes place in the outer zone or in the main branch at the

season of heaviest southward flow.

Table I.-Zones of the California Current.

Outer Main Inner ---_. Month u' d' u d u d

January '+3.5 600 - 6.9 400 3.5 100

April -5.2 500 - 6.9 250 -5.2 50

July -3.5 700 -12.0 250 6.9 100

October -2.6 700 - 6.1 400 5.2 100

'u is the current speed at the core in kilometers/day.

'd is the distance of the core from the coast at CalCOFI

line 90 (see Lynn et al. 1982) in kilometers

'indicates Equatorward flow.

In addition to the large-scale features, there are local environmental

events which appear to influence the pelagic spawning population.

Temperature (Lasker et al. 1981; Fiedler 1983) and surface

chlorophyll concentration estimated from analysis of satellite infrared

images (Pelaez and Guan 1982; Fiedler 1983) appear to be important in fine-scale distributions. In the short period in which satellite

image analysis has been possible, 0.2 mg/m3 appears to be a lower

limit of chlorophyll in which anchovy spawning takes place (Fiedler

1983). There also appears to be some diminution of incidence of

eggs at temperatures below 13.5°C (Fiedler 1983) although temperatures as low as noc are not lethal for anchovy eggs. It also appears

that a certain amount of stability in terms of mixing (Lasker 1975;

Bakun and Parrish 1982; Smith and Lasker 1978) and absence of

offshore and southerly transport (Hewitt and Methot 1982; Power

1983) are favorable to the establishment and maintenance ofspawning

areas.

Population size also appears to control the spawning area

(Ahlstrom 1965; MacCall 1983). There is anchovy spawning further offshore and north when the biomass is large, but the spawning area appears to contract toward the Los Angeles Bight when

the biomass is smaller. A simple description of this (MacCall 1983)

would be that a 100,GOO-ton spawning biomass would extend off-
40·

35·

30·

25·

20·

Dec-Jan 40·

35·

30·

25·

20·

Feb-Mar

Jun-Jul 40·

35·

30·

25·

20·

Apr-May 40·

35·

30·

25·

20·

1150 1100

Oct-Nov

25·

30·

35·

40·

200

Aug-Sep

20·

35·

25·

40·

Figure l.-Long-term spawning range of the northern anchovy as estimated from approximately 30,000 observations

of anchovy eggs taken from a larger area between 1951 and 1983. For maps of all observations between 1951 and 1979

consult CalCOFl Atlases 9 and 28 (Kramer and Ahlstrom 1968; Hewitt 1980).

18
shore only 260 km, but a I-million ton spawning biomass would

extend offshore 360 km. Table 2.-Percent females in trawl catches

of northern anchovy at different times of

day.

Spawning Season Time of

ddy

No. of

samples % females SD (%)

Some anchovy spawning takes place at every time of the year, but

winter and spring are times of the most active spawning.

THE SAMPLING PROCESS _

Catchability and Vulnerability

of Adults

1800-1959

2000-2159

2200-2359

llOOO-0159

0200-0359

0400-0559

0600+

77

88

80

64

24

21

8

526

470

45.3

50.5

50A

57.1

65.6

18.9

27.9

26.0

22.2

17.7

11.1

14.7

Epipelagic schooling fish are difficult to sample quantitatively. Ai

times the sample trawls have been placed based on sonar mapping

the previous day. At other times the samples have been taken where

newly spawned eggs were detected by preliminary examination of

plankton samples. Uniform samples of all tows conducted for the

purpose of estimating egg production represent the 7 to 40-m depth

range. The upper limit is set by the minimum depth at which a midwater trawl can be fished.

One aspect of the variation in catchability can be illustrated by

examination of the variation in the sex ratio. If one considers the

data on 362 observations for which sex ratio was determined between 1977 and 1982, there is an interesting distribution of sex ratios

and standard deviations of sex ratio by time of day (Table 2; Hunter

and Macewicz 1980). For comparison, the overall mean ofsex ratios

is 0.497 with a standard deviation of 0.233 and a standard error of

the mean ratio of 0.012.

The dispersion of values, about 50% female, is wider than one

would expect of a binomial sampling error distribution with 10-30

specimens, thus we believe that the phenomenon reflects actual

biological features of the anchovy schooling and behavior pattern.

In further support ofthis idea, the distribution about 50% is skewed

to the side of underestimation of females and the bias arises from

a peak time 2200-2359 which coincides with the maximum spawning activity as seen from the surveys of stage I and II eggs (see Moser

and Ahlstrom 1985). The strength and prevalence of this spawning

behavior are demonstrated by the fact that a 5 % overall bias in sex

ratio may be caused by only 10-15 % of females and their attendant

males.

We postulate that during the spawning act more males than gravid

females are present, and this leads to temporal and spatial heterogeneity; also, the collection of samples with a trawl from a volume

which is 15 m thick, 15 m wide, and 2,000 m long has considerable

chance of mixing these proportions by transecting spawning and

nonspawning clusters. Thus it is that the modal catch category, 43

of 362 samples, is at 50% female. The binomial sampling theorem

for fish sample sizes of 10-30 fish would indicate that about 6%

of the samples would yield <30% female and also 6% would yield

>70% female. The actual observations are given in Table 3.

For the use made of the adult data at present, the sex ratio bias

(see Hunter et al. 1985) is not thought to be of any great importance: the ratio of I-d postovulatory gonads is used for the inverse

of the daily spawning fraction, and the sex ratio is determined to

be 50% because there is no weight differentiation by sex and the

numeric ratio is likely to be 50% as well. In another section (AIheit

1985) we shall see that the Peruvian adult sampling system with purse

seiner exhibits no bias, and we assume that the explanation lies with

the evasion of the trawl or the depth distribution of the sexes. In

19

Table 3.-Actual and expected catches of females of northern

anchovy at different times of day during spawning.

I Mean No. of samples No. sam les observed

time No. uf expected at <30% >70%

(h) samp;cs <30% and >70% female female

1900 77 5 6 13

2100 88 5 26 19

2300 80 5 22 12

0100 64 4 9 II

0300 24 1 I 3

0500 21 1 0 3

0600+ 8 1 0 3

Table 4.-Percent positive egg captures and mean

number of northern anchovy per tow by lime of

day.

Obser- Positive % Mean

Time vations samples positive no.

1800-1959 142 5 3.5 0.120

2000-2159 135 26 19.3 0.919

2200-2359 147 48 32.7 3.265

0000-0159 152 33 21.7 3.303

0200-0359 151 22 14.6 OA64

0400-0559 132 8 6.1 OA62

0600-0759 137 6 4A 0.153

0800-0959 129 I 0.8 0.008

1000-1159 129 5 3.9 0.039

1200-1359 133 2 1.5 0.023

1400-1559 128 2 1.6 0.016

1600-1759 151 I 0.7 0.007

general, the commercial fishery exhibits a sex ratio of the order of

60% female, and the sea survey has a ratio of 50% female (Mais

1974).

The inference that changes in catchability and vulnerability of the

adults are controlled somewhat by the spawning act is strongly supported by the coincidence of spawning detected in the sea. Statistics

are available from 3,936 observations between 1980 and 1983 of

which 1,666 had 1 or more anchovy eggs. Prior to the first cellular

division (Stage r eggs, see Moser and Ahlstrom 1985) there are small

numbers of observations and these reflect the temporal distribution

of spawning in much the same way as the adult sex ratio variance

(Table 4).
Sampling Requirements

for Egg Survey

The egg survey supplies two values to the spawning biomass estimate:

The size of the spawning area and the daily production of eggs per

unit area. When establishing standards for the survey of egg production, it is necessary to consider the inclusion of the entire spawning area, the representativeness of the samples within the area, and

the sufficiency of the number of observations for the required

precision.

There is an obvious bias associated with egg production outside

the surveyed area. The product of the survey area and the egg production/unit area is unbiased even if the survey is much larger than

the spawning area. That is, as the surveyed area outside the spawning area increases there is a corresponding decrease in the mean

number of eggs produced/unit of survey area. However, a secondary objective of the Southwest Fisheries Center Egg Production

Method is to determine the error distribution of each estimated

parameter. The Central Limit Theorem is not valid in reduction of

standard-error-of-the-mean value with increasing number of observations if those values are spatially coherent. If there was a broad

contiguous and continuous area of observations with no eggs in the

observations, the standard error would be correspondingly biased

as an underestimate.

It is not necessary to know the nature of the underlying distribution of observations to use the Central Limit Theorem to estimate

the error distribution of the mean. However, it may be useful to consider some probability-generating distributions in order to forecast

what an adequate number of observations would be, given the sample variance and the objectives of the survey. As an example of the

differences one might encounter, consider: If the eggs were

distributed such that the observations produced a "Normal" distribution, then with each sample one would obtain an independent

estimate of the population mean and the population variance; if the

eggs were distributed such that the observations produced a

"Poisson" distribution, then the estimated mean of the population

would simultaneously produce an estimate of the variance of the

population (equal to the mean); if the eggs were distributed with

areas of high density and areas with no eggs at all such that the

presence of one egg would predict the presence of other eggs in th~

sample so that a "Negative Binomial" distribution of observations

obtains, one would need many independent observations to obtain

a mean number of eggs/unit area with a normal distribution of standard error of the mean. Thus the expense of effort of estimationper-unit precision is much lower with "Normal" and "Poisson"

distributions than it would be with an underlying "Negative

Binomial" distribution. To diagnose this, one needs to compare the

variance and mean of several estimates. If the variance is independent of the mean, the distribution is "Normal"; if the variance is

a power function of the mean, the distribution is probably "Negative

Binomial," although there are other possibilities. For a first approximation, the "Negative Binomial" appears to be a useful working

model for design ofthe egg production survey to determine the mean

and variance of the egg production parameters.

The establishment ofthe "Negative Binomial" model of underlying

distribution of observations does not support speculation as to the

scale or origin of the patchiness, and thus no single set of samples

can be used to interpret pattern.

For the purpose of determining sampling requirements for an egg

survey, it is necessary only to show that the number of samples is

adequate to describe the mean and standard error of the production

of eggs per unit area. A second level of analysis and sampling is

20

necessary to jointly describe the scale and intensity of the patchiness

and so allow speculation and research as to the processes which

underlie the observed pattern. Knowledge of scale of the "patches"

and intervening "spaces" and their shapes is necessary for further

work.

We discuss the description of pattern below merely to emphasize

what we would need to know to interpret processes such as:

I. The interannual variability in patch scale possibly caused by

differences in fecundity attributable to such parameters as

batch size, interval between spawnings, and age composition

of spawners;

') The geographic variability in the scale and intensity of

predation;

3. The interaction of patch scales and numbers of anchovy eggs

with patch scales and numbers of their principal predators,

including adults within the school, adults and juveniles in

oth~r schools of the same species. and other noncannibalistic

predators on anchovy eggs;

4. The relevance of interaction between the sampler size and

tht: anchovy egg patch scale in order to transfer these sample

designs to other anchovy populations or to other species; and

5. The comparison of vertical samples to older oblique samples,

or the effects of taking samples of different size and shape

on survey efficiency.

One reason that the standard sampling tactic (the vertical egg tow

on a systematic grid) is not fully effective for advanced description

of pattern is that observations are taken at one size scale and separated

by a fixed distance. If we take the characteristics of the negative

binomial-the mean, the coefficient of patchiness, "!C', and the percent of the area, P(O), with no eggs-only the mean is a characteristic of the sampled population; k and P(O) result from interactions

betwet:n the scale of the sampler and the scale of the patches of eggs.

For example, ifthe vertical sampler mouth opening were progressively increased from 0.05 m2 to 10 m2 , we would expect the probability of "zero" observations to decrease. The decrease would depend on what fraction of the interpatch spaces were between 25 cm

(the diameter of the smaller sampler) and 357 cm (the diameter of

the larger sampler). For k the equation for the population is:

where k; is the scale-dependent coefficient of patchiness, lJi is the

population mean of all possible areas for sample size "i", and OJ

is the population variance for that set. If the true scale of anchovy

~gg pattern were approximately the same as the larger sampler, the

sample variance would increase under the influence of larger observations and there would be a concomitant diminution of the variance

from the effect of the larger sampler lying across more patch boundaries and thus integrating patch and space densities. If the true scale

of the anchovy egg patches were smaller than the larger sampler,

the variance would decrease because all observations would integrate

some space densities. If the true scale of the anchovy egg patches

were greatly larger than either sampler, the derived !Cs would tend

to be indistinguishable.

Lastly, if the true scale of the anchovy egg pattern is larger than

the spatial interval between stations, the variance will be less because

adjacent observations will be more similar than observations chosen

at random.

There is evidence that several scales of pattern exist which probably originate from different processes. The smallest scale is imposed by the process of fertilization and is at the scale of a single
female or a small group of females. The next scale dimension is

imposed by the general schooling habit. The largest scale within

the subpopulation is called the "school group" and it may contain

several thousand schools ofjuveniles and adults in varying degrees

of spawning condition. For the purposes of this discussion we can

label these scales, meters, hundreds of meters, and thousands of

meters: the biogeographic boundaries of the entire interbreeding

subpopulation (central subpopulation of the northern anchovy) is

400 kIn cross-shore and 1,000 kIn along the coast.

The larger scales are of practical concern for the egg production

method using the Central Limit Theorem; namely, the effect of multipIe observations forming a normal distribution of the standard error of the mean is diminished by coherence among adjacent observations. Preliminary analyses of replicate egg samples (Smith and

Hewitt 1985) indicate that cross-shore observation transects with

observations separated by only 500-1,000 m would be coherent, while

observations in excess of 5,000 m apart are independent of the major persistent source of patchiness at the "school" scale, 100-1,000

m. School groups have not yet been positively identified by the egg

production surveys, but they are obvious from aerial and wideranging sonar mapping surveys (Fiedler 1978; Smith 1978).

To summarize, sample design decisions for the Southwest Fisheries Center Egg Production Method of biomass assessment have

been based on prior knowledge, e.g., 1) the anchovy's spawning

season, 2) the spawning area, 3) size of the school groups, and 4)

size of the schools.

The volume of one observation is 3.5 m3 or 1/20 m2 between 70

m and the surface. The distance between observations is 4 nmi in

the cross-shore direction and 10 or 20 nmi in the alongshore plane.

For the central subpopulation of the northern anchovy, the recommended sampling area is 200 mi cross-shore and 600 mi alongshore.

Random vs. Centric

Systematic Area Sampling

The sample design for the egg production method does not use random sampling: the lines are fixed in cross-shore positions which

conform to historical surveys of biological and oceanographic

features which can be measured only with straight sections at or

near right-angles to the coast. The danger with fixed transects is

that characteristics, such as proximity to a canyon or upwelling site,

the passage close to an island, or the aversion to stations in shipping lanes, all adversely affect the necessary assumption that all

objects to be sampled have had an equal opportunity to appear in

a sample. Another problem is the regular spacing of systematic

samples: if the alongshore or cross-shore spacing coincides with

any periodic element in the distribution of the organisms being

sampled, then the possibility exists for bias through oversampling

some phases of the spatial periodism. For example, if the number

of organisms varied like a sine wave, it is possible that regularly

placed samples will hit the peaks or troughs in the distribution,

thereby over- or underestimating the population. In a strict sense,

statistical limits cannot be established with sets of systematic

samples: there is some evidence (Milne 1959) that for periodic

differences to be important, they would have to be obvious. Milne

(1959) stated "...with proper caution, one will not go very far wrong,

if wrong at all, in treating the centric-systematic-area sample as if

it were random."

21

INITIATING AN EGG

PRODUCTION PROCEDURE --------

The Southwest Fisheries Center Egg Production Method was created

using new principles of sampling and mortality analysis of anchovy

eggs in the sea and residual gonadal tissues indicating recent ovulation. There existed a wealth of data on the geographic distribution

of adults (Mais 1974) and the geographic and temporal distribution

of anchovy spawn (Kramer and Ahlstrom 1968). It should not be

necessary to repeat the CalCOFI effort at each site and for each

species to develop egg production procedures for other species in

other geographic areas. It is the purpose of this section to describe

minimal initial steps for the egg production method.

Initiation of Field Sampling

Observations of larger larvae (5-10 mm) from high-volume oblique

tows (ca. 1,000 m3) would be superior to the CalVET (3.5 m3

) tows

for establishing the regional boundaries and season optimum for

the egg production method for a given species. For widespread

pelagic species exhibiting multiple spawning, interstation distances

of 40-120 nmi should suffice (74-222 kIn) to delimit spatially the

spawning area. Monthly, bimonthly, or seasonal surveys should be

sufficient.

Laboratory and Field Studies

of Spawning Behavior

While it is conceivable that temperature-dependent rates of egg

development can be derived from the analysis of field samples and

ancillary depth and temperature data, it is recommended that

laboratory-controlled temperature experiments be used to establish

the temperature-dependent rate model. In particular, the extremes

of temperature may be difficult to observe adequately in the field

in any given year.

In the field, even when there is no main time of day for spawning, it is possible to determine the number of eggs spawned per day

by:

N, = Nof~ exp[-Z(t - x)l!(x) dx

where N, is the number of eggs in a particular stage and later stages

at time t; No is the total number entering the series; exp[-Z(t-x)]

is the probability that an egg at time x is still alive at time t; Z is

the constant age-specific death rate; and fix) is the frequency of the

stage at time x (Manly 1974). The actual frequency function can

be inserted in the equation. For example, a normal distribution of

spawning time would yield the equation:

J

,-p./cr

N, = Noexp(-Zt) _~ (27T)-1/2 exp(-1/2x2) d'(

One must, of course, have more than four samples to solve this equation (Manly 1974).

When regional and seasonal criteria for spawning have been

established, there must be an intensive field study to find the sample distribution in time and space which will be sufficiently precise

for the purposes of egg production estimate of spawning biomass.

The conditions which must be noted from the data set are (after

Southwood 1978): I) Distribution of the time of spawning, 2)

variability of survival rates, 3) stage-dependent sampling efficien-
cy, 4) duration of stages, and 5) probability distribution of eggs as

a function of time and age.

Working assumptions for the central population of the northern

anchovy at lat. 33°N in March are:

I) Spawning occurs between 1800 and 0200, essentially normally

distributed with a midpoint of 2200 hours.

2) The survival rate is assumed to be constant between 0200 of

the first day after spawning until hatching begins (normally

60 h).

3) All stages are sampled with equal efficiency, but the period

when spawning is actually occurring or after hatching begins

is excluded from survival stimulation.

4) Duration of egg stages is proportional to a single temperature

(usually the surface temperature).

5) The probability distribution of eggs/unit surface area is completely characterized by the two parameters of the negative

binomial distribution, the arithmetic mean and the dispersion parameter k, a function of the population mean and

variance. These parameters are age-specific, the mean

decreasing with age and k increasing with age.

The last assumption must be considered for the regression method

of estimating the precision of the slope and intercept estimates, as

there are, as yet, no formal solutions for regression equations under

these conditions.

Staging Eggs in Other Species

or in Tropical or Arctic Habitats

The anatomical description of the II stages of eggs is given for anchovy in Moser and Ahlstrom (1985). Also, an experimental definition of the mid-age of each stage and the conversion of stage, timeof-tow, and temperature information are described by Lo (1985). Vole

here describe some approaches to fishes whose spawning behavior

and definition of stages are dissimilar to the anchovy.

The possible number of discrete stages assigned to the continuum

of embryonic development is ultimately detennined by the presence

of recognizable anatomical features. For example, although not used

in this work, the 2-cell, 4-cell, and 8-cell stages of the embryonic

development could be used to follow population features immediately

after fertilization. For convenience the nominal hatching time of 60

h has been divided into 11 stages for a mean duration of about 6

h. If one were dealing with a tropical fish with a hatching time of

20 h, it would seem more reasonable to maintain the number of

arbitrarily defmed stages at 10 or so, rather than to reduce the number

of stages to 3 of about 6-h length. Similarly in the Arctic situation,

where hatching may take several weeks, one may need to pool several

days' spawning to gain sufficient sample sizes to estimate mortality

rate and egg production.

Were the stages equal in duration and spawned at an instant, one

would easily see the progression of these stages with time. Since

the period of spawning is approximately 1/4 d, and the duration of

the stages is from 2 to 9 h, the system used here was originated

for the sardine (Ahlstrom 1943) temperature-specific development

rate and later applied to the anchovy (see below). Since these are

both temperture-zonp- clupeoid fishes, the rationale for these stages

is listed below for the purpose of using this technique for fishes in

other latitudes or taxa.

While it has not been possible to obtain exact information on fertilization time or the exact timing of the transitions between stages,

it is possible to combine quantitative laboratory and field data to

make a best description of the major events in embryogenesis. This

22

description can then be used to design definitive work in the

laboratory or field as needed for future studies on these or other

fish. We base all of the arbitrary descriptions on a starting time of

1800 (6 p.m.) for onset of spawning, with the midpoint of spawning at 2200 (10 p.m.), and finishing at 0200 (2 a.m.). Bolin (1936)

observed that cell cleavage in the anchovy embryo occurred at approximately half-hour intervals, thus we assume that the interval

between fertilization and first cleavage is about 0.5 h. Since the duration of the Stage II eggs from first cleavage until the onset of epiboly

or cellular overgrowth of the yolk is about 7 h and the number of

Stage II eggs collected is about seven times the number of Stage

I eggs, we assume that the Stage I egg persists about I h or 0.5 h

to be fertilized and 0.5 h more until the first cleavage.

Table 5 is from a summary of all field data taken in 1980-83, with

1,666 samples positive for some stage of anchovy egg. For each of

the first five stages, the mean number of eggs per 0.05 m2 is listed

for each of 12 2-h periods, and next to each abundance is the

cumulative percentage from the onset of the stage to the end of 24

h. For the cumulative percentage of each stage the point at which

5 % of the eggs have appeared, 50% and 95 % points on the

cumulative curve are listed at the bottom of the table. The cumulative

effects of temperature have little effect on the early stages. The sets

included here are from all temperatures encountered in the surveys,

mostly between 13° and 16.5°C in these years with an average

temperature of 15.40c.

In the laboratory experiment, it was not convenient to constrain

the gravid anchovies, thus it is not known for certain when the first

spawning begins under controlled conditions. Following spawning

in the laboratory, the eggs were collected in the outflow in a passive

net and were transferred into containers with temperatures controlled

at approximately 13.5°, 15.1°, and 16.3°C. This means that the early

stages concluded their development at a common temperature of

about 15°C and were subsequently placed in controlled temperatures.

Thus, for the tables which follow, the temperature is that at which

most of Stage III and all of the ensuing stages were passed. The

original data were somewhat more finely grouped, but low numbers

of specimens in some categories and brevity made some lengthening of observation intervals desirable. To unify these numbers, the

raw data were converted to numbers per hundred collected at each

time interval, and then the numbers were summed for each stage

and the cumulative sum at each reported interval was divided by

the total to yield the tabled value of cumulative percent. The 0 in

the table means that no specimens of that stage were spotted before

that interval; the 1.000 means that no specimens in that stage were

found after that interval. All Stage I eggs had developed before the

eggs were caught at the outflow and most Stage II and some Stage

III eggs were present before the systematic counting and staging

began. The experiment was tenninated before all larvae had reached

the 3.5-mm length.

The actual times of day of the important events were injection

of hormones in the afternoon of the preceding day and collection

of the eggs in the morning. The first staging ensued at about 1300.

For any small set of anchovy samples, Stage I and Stage XI appear to be too short for any analytical purpose: each appears to

be about an hour long. The other stages probably last between 5

and 13 h, and these durations diminish with increasing temperature

and development. Thus for other species in lower and higher water

temperature, the detection and use of a daily cycle of spawning should

include redefined stages which are markedly shorter than one day

at the beginning of development. The ensuing stages can be longer

as is convenient for data gathering and storage.
Table 5.-Tabulation of field abundance of northern anchovy eggs as a function of time in hours after spawning;

00 refers to the mid-point of spawning.

Stages

II III IV V

Age in eggs! cum. eggs! cum. eggs! cum. eggs! cum. eggs! cum.

hours 0.05m2 % 0.05 m2 % 0.05 m2 % 0.05 m2 % 0.05 m2 %

-04-02 0.120 0.014 0.113 0.002

-02-00 0.919 0.118 1.511 0.026

00-02 3.265 0.490 6.252 0.125

02-04 3.303 0.866 11.612 0.308

04-06 0.464 0.919 10.298 0.471

06-08 0.462 0.972 8.932 0.613 0.197 0.004

08-10 0.153 0.989 11.358 0.792 2.029 0.047

10-12 0.008 0.990 7.426 0.910 4.767 0.149

12-14 0.039 0.995 3.969 0.973 5.178 0.259 0.109 0.003

14-16 0.023 0.997 1.023 0.989 7.474 0.419 0.316 0.013

16-18 0.016 0.999 0.258 0.993 8.945 0.609 1.109 0.048

18-20 0.007 1.000 0.450 1.000 8.762 0.796 2.378 0.121

20-22 2.831 0.856 5.056 0.278 0.873 0.026

22-24 1.926 0.897 5.911 0.462 2.482 0.102

24-26 3.408 0.970 7.388 0.691 2.599 0.108

26-28 1.105 0.994 6.842 0.903 3.421 0.284

28-30 0.298 1.000 1.411 0.947 4.570 0.422

30-32 0.318 0.957 5.576 0.576

32-34 1.241 0.995 5.263 0.751

34-36 0.155 1.000 3.318 0.851

36-38 2.078 0.914

38-40 1.181 0.950

40-42 1.109 0.984

42-44 0.543 1.000

Age at which

5% appeared -1.5 h 0.5 h 10 h 18 h 22.5 h

50 % appeared 0.0 6.0 16 24 30

95 % appeared 4.5 13.5 25.5 31 40

Abnormal Embryos

There appears to be a need for stages which can be recognized even

with a distorted specimen. A large fraction of the anchovy eggs are

decidedly abnormal and stage classification is quite difficult. We

have sought to modify sample washing and fixation to diminish this

problem, but the specimens are distorted when fresh and alive (Sandknop and Stevens2). Also these abnormal embryos do not seem to

be associated with any particular stage or age of egg. Table 9 is a

correlation matrix for the disintegrated eggs and the aged ones. The

highest correlation is between disintegrated and total eggs, and even

this shows no more than 7% of the number of disintegrated eggs

can be predicted from the number of eggs in a sample.

Table 6.-Correlation matrix among categories of northern

anchovy eggs.

Age of

eggs <8 h I d 2 d 3 d 4d DIS+I

I d 0.101

2d 0.029 0.396

3 d -0.022 0.176 0.277

4d -0.024 0.029 0.002 0325

DIS+ 0.045 0.150 0.143 0.111 0.073

Total eggs 0.388 0.786 0.737 0.465 0.130 0.258

lOIS = disintegrated eggs but with chorion intac!.

'E. M. Sandknop, Biological Technician, and E. L. Stevens, Fishery Biologist. Southwest Fisheries Center, National Marine Fisheries Service, NOAA, P.O. Box 271, La

Jolla, CA 92038, pers. commun. Dec. 1981.

23

The time in the field of the proportion of the spawning area covered

by spawn (Fig. 2), the mean number of eggs per observation, the

standard deviation, the standard error of the mean (Fig. 3), and the

dispersion coefficient k of the negative binomial (Fig. 4) are consistent with the anchovy laboratory data and that for the Pacific sardine analyzed by Ahlstrom (1943).

SUGGESTIONS FOR

FUTURERESEARCH _

Three characteristics of the anchovy make the assignment of ages

possible: One is that the anchovy egg is demonstrably spawned

during a limited period in each day; another factor is that stages

have been assigned so that their duration is about one-third of a day

so that ages can be unequivocally assigned if the temperature and

time of tow is known; lastly, the total incubation time is about 3

d (see Table 7).

This leads one to the questions: How would one estimate egg

production if the eggs were produced at all hours of the day? How

would one proceed if the total incubation time were <I d?-more

than 10 d?

Research on these questions could proceed along these lines. For

the case of the long incubation period, it is not necessary to follow

the course of mortality through the entire incubation period. For

example, if the incubation period were 14 d and the ages of eggs

could readily be determined for only 3 d, the mortality and production rate from that period would suffice for an estimate of the

production of spawn; the ensuing stages of eggs would not even have
to be counted or staged.

The rate of production could probably be estimated without knowing the time-of-day of spawning. For example, in Table 8 estimates

of rate of production could be determined solely from empirical

abundance information and incubation time. For the purpose of this

exercise, I have assumed that the 11 stages are incubated in 66 h,

or 6 h/stage. Deviations of abundance from the regression estimate

of abundance are of two kinds: Sampling variability and duration

differences from the even duration assumption. Ifsampling variability is ignored, then stage lengths longer or shorter than the average

stage duration can be estimated.

ACKNOWLEDGMENTS _

We would like to acknowledge the assistance of Carol Kimbrell for

organizing and conducting the temperature laboratory experiments,

H. Geoffrey Moser and his staff for providing data on staged eggs,

Nancy Lo, Susan Picquelle, and Gary Stauffer for determining the

age of eggs from field samples, James R. Thrailkill, Rich Charter,

and William C. Flerx for planning and conducting the field surveys,

designing and constructing the sampling equipment, and Cynthia

Meyer and Celeste Santos for entering and checking the egg survey

data. We are particularly grateful to Richard Methot who read an

early draft of this manuscript.

1.0 50

0.9

5-1-------0 ----

AGE (hours)

'.

24 32 40 48 56 64

AGE (hours)

16

40

r

I

I

,

I

30 I

I

I

,

I

I

I

t

20 ,

,

I

I

I

" il:

I!

~I

I,"

:l o I

-4 0 4 8

5-·\..-1-----M-----!--H-

,

,

,

,

\

!'

,

'I w

...J

Q.

,

I «

III

I a:

I w

Q.

III

Cl

Cl

w

r

I

0.1 I

o LLt...L.....L---L-----L_L.-....L-----l.---l_..J......--l....-

-4 0 4 8 16 24 32 40 48 56 64

0.2

0.4

0.7

0.3

0.5

0.6

0.8 Q.

«

III

w

>

i=

iii

o

Q.

«

LL

o

>

...

:::i

iii

«

al

o

a:

Q.

Figure 2.-Time course of proportional occurrence (number of observations with

eggs of a given age divided by the number of observations with any age anchovy

egg). Dashed lines under "S" indicate observations during the spawning period.

The dashed line under "u" represents observations during the hatching period.

The process assumed to control the solid line under "D" is dispersal.

0.60

0.50 a:

w...

w

«

II:

: 0.40

z

o

iii

II:

W

Q.

III 0.30

C •

•

Figure 3.-Time course of the primary statistical parameters, the arithmetic mean

(below), the standard deviation of the observations (above), and the standard error

of the mean (cross-bars on the arithmetic mean line). Within ages the standard

deviation is believed to be a function of the mean, and this function of the mean

changes with time owing to dispersal (see Figure 4). Standard error of the mean

bars are ±2 (or approximately the 95% limits). For this illustration the number

of observations is 1,666 taken between 1980 and 1983 as part of the egg production method estimate of anchovy spawning biomass. The dashed lines under "s"

and "u" represent spawning and hatching as in Figure 2. The principal process

controlling the slopes of the standard deviation and mean under "M" is mortality. The convergence of the standard deviation and mean lines is caused by dispersal of eggs.

0.20 L--...-<::J.4--8L-1.L6----l24--:!3::-2-~4!:0--4;';18;----;:'56

AGE (hours)

Figure 4.-Negative binomial distribution is represented by two parameters: the

arithmetic mean (see Figure 3) and "k", the "dispersion parameter!' The points

represent maximum-likelihood fits to sample data in seven 8-h intervals which

contain samples unbiased by spawning or hatching. The line represents the linear

least-squares fit to these points.

24
Table 7.-Cumulative incidence of laboratory-spawned and reared nortllern

ancllovy eggs and larvae.

Age Stage of development Larvae -------

(h) IV V VI VII VIII IX X 2.5 mm 3.0 mm

16 0 at 13.5°C

24 0.226 0

32 0.812 0.204 0

40 0.995 0.723 0.128 0 0

48 1.000 0.985 0.759 0.265 0.032 0

56 /.000 0.992 0.907 0.552 0.032 0 0

64 1.000 /.000 1000 0.684 0174 0.100 0

72 0.947 0.802 0.292 0.004

80 1.000 1.000 0.724 0.014

88 0.880 0.271

96 0.975 0.554

104 1.000 0.763

Il2 0.843

120 0.888

128 0.977

136 1.000

16 0.028 0 at 15.l o

C

24 0.591 0.010 0

32 0.963 0.505 0.075

40 1.000 0.965 0.459 0 0

48 1.000 0.974 0.458 0.016 0

56 1.000 0.981 0.874 0.273 0 0

64 1.000 0.976 0.929 0.500 0.145 0

72 1.000 1.000 1.000 0.436 0.078

80 1.000 0.230

88 0.527

96 0.810

104 0.868

Il2 1.000

16 0.025 0 at 16.3°C

24 0.766 0.069 0

32 0.944 0.881 0.231 0

40 1.000 1.000 0.923 0.570 0.037 0

48 1.000 0.974 0.880 0.210 0 0

56 1.000 1.000 0.746 0.387 0.250 0.004

64 1.000 1.000 0.625 0.046

72 0.837 0.367

80 1.000 0.685

88 0.930

96 1.000

Table 8.-Empirically derived stage durations of northern ancllovy eggs.

Stage X 2SE 4X T RE 0 CUM F L d

1 0.77 0.28 3.08 3 13.78 1.34 0- 1.34 0.67

II 5.34 0.80 21.36 9 12.85 9.98 1.34-11.32 6.33 6.42 -0.09

III 3.86 0.76 15.44 15 11.98 7.73 11.32-19.05 15.19 13.55 1.64

IV 2.79 0.48 11.16 21 11.17 6.00 19.05-25.05 22.05 21.12 0.93

V 2.75 0.62 11.00 27 10.41 6.34 25.05-31.39 28.22 30.70 -2.48

VI 3.06 0.44 12.24 33 9.71 7.56 31.39-38.95 35.17 39.24 -4.07

VII 2.28 0.36 9.12 39 9.05 6.04 38.95-44.99 41.97 47.13 -5.16

VIlI 1.65 0.22 6.60 45 8.44 4.69 44.99-49.68 47.34 52.07 -4.73

IX 2.45 0.14 9.80 51 7.87 7.47 49.68-57.15 53.42 56.28 -2.86

X 1.86 0.10 7.44 57 7.34 5.92 57.15-63.07 60.11 62.63 -2.52

XI 0.44 0.074 1.76 63 6.84 1.54 63.07-64.61 63.84 65.65 -1.81

X = mean number of eggs by stage (n = 1,666) per observation

SE = standard error of number of eggs by stage.

4X = daily production by stage if duration is 6 h per stage.

T = midtime of stage if duration is 6 h per stage.

RE = regression estimate of abundance (first approximation).

0 = duration of stage in hours if regression error is ignored.

CUM = cumulated age of stages in Ilours.

F = midtime of eacll stage estimated from field data.

L = midtime of eacll stage estimated from lab experiment.

d = difference in Ilours.

25
LITERATURE CITED _

AHLSTROM, E. H.

1943. Studies on the Pacific pilchard or sardine (Sardinops caerulea). 4. Influence of temperature on the rate of development of pilchard eggs in nature.

U.S. Fish WildI. Servo SSR 23, 26 p.

1965. A review of the effects of the environment on the Pacific sardine. In

Intl. Comm. Northwest Atlantic Fisheries Spec. Publ. 6, p. 53-74.

ALHEIT, J.

1985. Spawning frequency of Peruvian anchovies taken with a purse seine. In

R. Lasker (editor), An egg production method for estimating spawning biomass

of pelagic fish: Application to the northern anchovy, Engraulis mordax, p.

59-61. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

BAKUN, A., and R. H. PARRISH.

1982. Turbulence, transport, and pelagic fish in the California and Peru Current Systems. Calif. Coop. Oceanic Fish. Invest. Rep. 23:99-112.

BOLIN, R. L.

1936. Embryonic and early larval stages of the California anchovy, Engraulis

mordax, Girard. Calif. Fish Game 22:314-321.

FIEDLER, P. C.

1978. The precision of simulated transect surveys of northern anchovy, Engraulis

mordax, school groups. Fish. Bull., U.S. 76:679-685.

1983. Satellite remote sensing of the habitat ofspawning anchovy in the Southern

California Bight. Calif. Coop. Oceanic Fish. Invest. Rep. 24:202-209.

HEWITT, R. P.

1980. Distributional atlas offish larvae in the California Current region; northern anchovy, Engraulis mordax (Girard), 1966 through 1979. CalCOFI Atlas

28, 101 p.

HEWITT, R. P., and R. D. METHOT, JR.

1982. Distribution and mortality of northern anchovy larvae In 1978 and 1979.

Calif. Coop. Oceanic Fish. Invest. Rep. 23:226-245.

HICKEY, B. M.

1979. The California Current System - hypotheses and facts. Progress in

Oceanography 8(4): 191-279.

HUNTER, J. R., and B. J. MACEWICZ.

1980. Sexual maturity, batch fecundity, spawning frequency and temporal pattern of spawning for the northern anchovy Engraulis mordax during the 1979

spawning season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

HUNTER, J. R., N. C. H. LO, and R. J. H. LEONG.

1985. Batch fecundity in multiple spawning fishes. In R. Lasker (editor), An

egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engraulis mordax, p. 67-77. U.S. Dcp.

Commer., NOAA Tech. Rep. NMFS 36.

KRAMER, D., and E. H. AHLSTROM.

1968. Distributional atlas of fish larvae in the California Current region: northern anchovy, Engraulis mordax (Girard). 1951 through 1965. CalCOFI Atlas

9, 269 p.

LASKER, R.

1975. Field criteria for survival of anchovy larvae: the relation between inshore

chlorphyll maximum layers and successful first feeding. Fish. Bull., U.S.

73:453-462.

26

LASKER, R., J. PELAEZ, and R. M. LAURS.

1981. The use of satellite infrared imagery for describing ocean processes in relation to spawning of the northern anchovy (Engraulis mordax). Remote Sensing of Environment 11:439-453.

LO, N. C. H.

1985. A model for temperature-dependent northern anchovy egg development and

an automated procedure for the assignment of age to staged eggs. In R. Lasker

(editor), An egg production method for estimating spawning biomass of pelagic

fish: Application to the northern anchovy, Engraulis mordax, p. 43-50. U.S.

Dep. Commer., NOAA Tech. Rep. NMFS 36.

LYNN, R. J., K. A. BLISS, and L. E. EBER.

1982. Vertical and horizontal distributions of seasonal mean temperature, salinity, sigma-t, stability, dynamic height, oxygen and oxygen saturation in the

California Current, 1950-1978. CalCOFI Atlas 30, 513 p.

MacCALL, A. D.

1983. Population models of habitat selection, with application to the northern

anchovy. Ph.D. Thesis, Univ. Calif. San Diego, 170 p.

MAIS, K. F.

1974. Pelagic fish surveys in the California Current. Calif. Dep. Fish Game,

Fish Bull. 162, 72 p.

MANLY, B. F. J.

1974. A note on the Richards, Waloff and Spradbery method for estimating stage

specific mortality rates in insect population. Biom. Zeitschr. 17:77-83.

MILNE, A. A.

1959. The centric systematic area-sample treated as a random sample. Biometrics

15(2):270-297.

MOSER, H. G., and E. H. AHLSTROM.

1985. Staging anchovy eggs. In R. Lasker (editor), An egg production method

for estimating spawning biomass of pelagic fish: Application to the northern

anchovy, Engraulis mordax, p. 37-41. U.S. Dep. Commer., NOAA Tech. Rep.

NMFS 36.

PELAEZ, J., and F. GUAN.

1982. California Current chlorophyll measurements from satellite data. Calif.

Coop. Oceanic Fish. Invest. Rep. 23:212-225.

POWER, J.

1983. Larval anchovy (Engraulis mordax) drift in the California Current. Results

of a simulation model. Natl. Mar. Fish. Serv., NOAA, Southw. Fish. Cent.,

La Jolla, CA, Admin. Rep. U-83-23, 36 p.

SMITH, P. E.

1978. Biological effects of ocean variability: time and space scales of biological

response. Rapp. P.-v. Reun. Cons. Int. Explor. Mer 173:117-127.

SMITH, P.E., and R. P HEWITT.

1985. Anchovy egg dispersal and mortality as inferred from close-interval observations. Calif. Coop. Oceanic Fish. Invest. Rep. 26:97-110.

SMITH, P. E., and R. LASKER.

1978. Position of larval fish in an ecosystem. Rapp. P.-v. Reun. Cons. Int. Explor. Mer 173:77-84.

SOUTHWOOD, T. R. E.

1978. Ecological Methods: With particular reference to the study of insect populations. Chapman and Hall. Lond., 524 p.
The CalCOFI

Vertical Egg Tow

(CaIVET) Net

PAUL E. SMITH, WILLIAM FLERX,

and ROGER P. HEWITTI

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA.

Po. Box 271. La Jolla, CA 92038

ABSTRACT

The vertical egg tow (CaIVET) net was devised by CalCOFI (California Cooperath'e

Oceanic Fisheries Investigations) to estimate egg production in the central subpopulation of northern anchovy an4"Sirnilar fishes. This paper describes the sampling characteristics ofthe net and its interaction with physical and distributional

features of the anchovy egg. Problems discussed include the horizontal patchiness ofthe eggs and intensity of their distribution, volume and depth distribution

of the water filtered, egg retention, and towing characteristics of the net.

The mouth area of the CalVET net is 0.05 m2; the tow is vertical to minimize

the volume of water filtered per unit depth; the mesh size of 0.150 mm is selected

for total retention of the anchovy eggs under all likely conditions. The mesh area

of the net is three times the mouth area in the conical portion and five times the

mouth area in the cylinder. The conical mesh is the minimum size necessary for

highly efficient filtration, while the cylindrical portion reduces the probability

of the net clogging during a single tow. A flowmeter detects sequential clogging

ofthe net during a series of tows. The net is lowered and raised rapidly to diminish

the effects of ship drill and undersea currents which impose uneven trajectories

on the net. The net is probably not capable of sampling active larvae 5 mm or

longer, owing to the small mouth size and the disturbance to the net's path from

the towing wire.

Design and working drawings of the frame and net are included.

'Present address: Commanding Officer, NOAA Ship Miller Freeman, Pacific

Marine Center, 1801 Fairview Ave, East, Seattle, WA 98102,

27

HORIZONTAL PATCHINESS _

We assume that eggs are released in the open sea by the gravid

females of a northern anchovy school in close proximity to one

another where they are fertilized by males. Previous samples of anchovy and sardine eggs indicated that most are found at densities

of 1,000 to 5,000 eggs/m2 when spawned, although only a small

proportion of the samples actually contained eggs at these densities

(Smith 1973; Smith and Richardson 1977:84). There is also evidence

that most eggs are found in the upper 70 m of the water column

(Ahlstrom 1959; Pommeranz and Moser 1983).

To shorten the sorting time for samples, we used a small net. 0.05

m2 in cross section. To reduce the time spent sorting out the anchovy eggs from plankton, we used a vertical tow through the upper 70 m rather than a normal oblique tow, since a vertical tow captures far less extraneous plankton. Sample simulations on existing

data for unstaged and staged anchovy eggs indicated that adequate

sample precision could be obtained with 500 to 1,000 positive egg

samples.

Previous studies by sonar, oblique plankton tow samples, and

observations of spawning in the laboratory indicated three contributors to horizontal patchiness of anchovy eggs in the sea: I)

The act of fertilization; 2) the schooling habit; and 3) the propensity of schools to be contagiously distributed. The expected scale of

horizontal patchiness from the act of fertilization is of the order of

meters to tens of meters. The expected scale of horizontal patchiness

from the schooling habit ranges from hundreds to thousands of

meters. The expected scale of patchiness from the school group scale

is of the order of kilometers to tens of kilometers. A study using

eight replicate tows per station identified the school scale as the primary source of variance. Samples replicated at the same station indicated that only during the first half day after spawning was the

fertilization swann a significant source of variance relative to the

school-size scale. To achieve statistical independence among adjacent

samples, we decided to space the samples at least 3 km apart. The

most usual spacing between samples has been 6 km in the offshoreonshore direction and about 16 or 32 km in the alongshore direction.

DEPTH DISTRIBUTION

OF WATER FILTERED _

The design objective ofthe CalVET tow was to filter a uniform and

measured volume of water for each increment of depth from 70 m

to the surface. The chief barriers to this goal are 1) ship drift and

undersea currents, 2) clogging of the net, and 3) cyclic vertical motions of the towing wire caused by the heave and roll of the ship

(Hewitt 1983).

The primary effect of ship drift and undersea currents is to distort

the distribution of water filtered/unit surface area to a given depth.

The ideal tow as designated here is to sample about 50 L water/m

of depth to a depth of 70 m, or to near-bottom in shallow waters.

First of all, ship drift and undersea currents diminish the depth attained with the fixed length of towing wire. For example, if the wire

has strayed from the vertical by 30°, 70 m of wire will achieve only

61 m depth. Similarly 5° stray will affect the depth attained by less

than 1 m. Secondly, ship drift and undersea currents change the

angle of stray with time. For example, the net when vertical will

filter 50 L water/m of depth, and at 30° the net will filter 58 L

water/m of depth. Our usual experience is that the oversampling

occurs in the upper layers relative to the deeper layers. In the recommended sample series all tows are repeated when the angle of stray

has exceeded 30°.
The most important specification in this category is that the net

must emerge from the water at right angles to the surface. It is known

from horizontal samples at the surface that great concentrations of

eggs may exist there, thus to drag the net along the surface toward

the ship is to risk vast oversampling of the eggs.

The chief error caused by clogging of the meshes of the net is

the relative undersampling ofthe shallow vs. deep water in an ascending vertical tow. It is conceivable that a net which is filtering 50

Lim of depth might clog in the upper layers and filter 40 or fewer

liters per m of depth (Smith et al. 1968). The viscous resistance

of the filtering surface requires that about three times as much mesh

apcrture as mouth aperture is required to filter water efficiently. For

this reason the CalVET net is fitted with a truncated conical portion which contains three times as much mesh aperture area as the

opening of the net. Since the mesh chosen is about 46 % open area,

the 0.15 m2 aperture area of the conical section is achieved with

0.33 m2 of mesh. In addition, to diminish the danger of the net

changing filtration efficiency during the tow due to clogging, the

net is fitted with a mesh cylinder with five times the mesh aperture

area compared with the mouth opening of the net. This should be

ample for a tow this length and with this mesh size (0.333 mm; see

below) in coastal waters off California.

Filtering efficiencies of fJ7 % are possible with simple net apertures. Efficiencies of 100% and more are possible with inverted conical net entrances like the original Hensen net. The complicated

Hensen technique was not chosen because the filtration efficiency

becomes a function of net speed, and the placement of the flowmeter in the flow section to obtain a representative sample of water

filtered is poorly understood. Also, reverse cone structures increase

the lateral drag of the net and worsen the consequences of ship drift

and undersea currents. The design of the CalVET net makes clogging unlikely within a tow; thus the use of a flowmeter is not required to verify the constant filtration of water per unit depth.

However, nylon nets are subject to sequential clogging in a serie~

of tows, and flowmeters are recommended to ascertain and correct

this problem. Deviations of flowmeter revolutions of 10% or more

should be cause for exchange or careful washing of the net. For example, a calibration factor of 0.273 m/revolution of the flowmeter

would predict that 256 revolutions be characteristic of a suitable tow

from 70 m to the surface. Flow readings of 231 revolutions for the

full tow, or 3.3 revolutions/m of wire out in shallow tows, would

indicate that a sequence of clogging between tows may have begun.

Another retention problem with vertical net tows relative to

horizontal and oblique tows is the direct connection of the net to

the ship. The roll and heave of the ship could at times impart

velocities to the net less than or in excess of design expectations.

Several consequences are possible between motion of the net and

the ship's roll and heave. The most serious problem is noted with

simultaneous roll and heave downward when the net containing eggs

approaches the surface (Hewitt 1983). Should the downward velocity

exceed the recovery rate of the net, the net would collapse from

below, there would be reverse filtration of water through the mesh

apertures, and the eggs would be expelled from the mouth of the

net. Probably the next most important danger is that when the net

containing eggs approaches the surface, the simultaneous roll and

heave upward will add the speed of the ship's motion to the already

high speed of the net recovery wire. In this case, the eggs lying on

the mesh might be ruptured or extruded through the mesh apertures.

Quantitatively less important, perhaps, is the likelihood that a net

at depth might be propelled upward fast enough to filter water and

turn the flowmeter, thus oversampling the volume at that depth. The

flowmeter is normally jammed against the mesh on the downward

28

path. To diminish these effects, the net is lowered at 1-1.2 m/s and

recovered at the same speed. In this way we achieve a depth of 70

m in I min and recover at the same speed. The net is stopped for

10 s at the bottom. Tows which vary substantially from this regimen

should be repeated.

RETENTION OF ANCHOVY EGGS _

The main considerations in retention of anchovy eggs by the CalVET

net are the relative size of the egg, the mesh aperture, and the filtration velocity. The minimum dimension of the northern anchovy's

egg is about 0.65-0.85 mm in February, and 0.55-0.80 mm in August

(Smith and Richardson 1fJ77:61). Such an object should be fully retained by mesh sizes <0.4 mm according to the "diagonal rule."

The diagonal rule states that the minimum dimension of the object

to be sampled should be greater than the diagonal ofthe mesh aperture. Absolute retention is affected also by the filtration velocity.

For example, the CalVET net proceeds through the water at a

nominal velocity of 70 m/min. The active filtering surface is about

three times the net mouth area, thus the filtration velocity is 1.2

m/s divided by 3, or 0.4 m/s. This is a high filtration velocity relative

to the normal oblique tows. Thus the net mesh size for the CalVET

was selected to be 0.150 mm. The main reason for the high net velocity is to diminish the time for errors of ship drift and undersea

current to accumulate.

DESIGN AND WORKING DRAWINGS

OF THE CalVET NET _

The CalVET frame and net are much smaller than traditional

ichthyoplankton nets: 0.25 m diameter mouth opening (0.05 m2

mouth area) and the total length of the net is <1.5 m. The net is

lowered to a depth of 70 m and retrieved vertically at 70 m/min;

strict controls govern the field procedures, and a tow is rejected if

the wire strays too far from the vertical or if the retrieval rate is

too fast or too slow. The results from field testing the gear in 1fJ79

indicated a very high degree of fidelity among eight replicates at

a single station; the test was conducted over 70 stations and within

a 2oo-fold range in egg abundance.

Figures 1-5 describe the bongo-type (PAIROVET) version of the

CalVET sampler. The frame was designed to facilitate comparison

of nets constructed of various materials and to provide replicate

observations when using similar nets; it has become one of the standard samplers used by the Southwest Fisheries Center. The frame

is constructed of 6061-T6 aluminum with stainless steel fittings. The

nets are nylon mesh attached to the frame with adjustable stainless

steel strapping. The cod end is removable and attached to the rest

of the net by means of a plastic collar. The net and cod end are

sewn inside a "sleeve" constructed of 2-mm mesh vinyl-coated

polyester tnot shown) to protect them from abrasion.

Nets of several mesh sizes have been used by the Southwest

Fisheries Center. All have been constructed using the dimensions

shown in the figure; total area of net material is 0.95 m2 . With the

exception of the 0.035-mm mesh, all of the net materials have approximately the same porosity, i.e., the portion of the net area which

is open. Smith et al. (1968) suggested that adequate filtering efficiency can be maintained in coastal waters if the ratio of aperture

area to mouth area is at least 3.4 for a net of the proportions described. Thus, these nets may be expected to perform well with the

exception of the very fine (0.035 mm) mesh net which may clog

in turbid coastal waters (Table I).
Table I.-Ratio of aperture area to mouth area for various

net mesh sizes. Nets with mesh <0.333 mm are protected

by a 2-mm mesh nylon sheath. See text.

LITERATURE CITED _

ALHSTROM, E. H.

1959. Vertical distribution of pelagic fish eggs and larvae off California and Baja

California. Fish. Bull., U.S. 60:106-146.

HEWITT, R.

1983. Roll, heave and vertical ichthyoplankton tows. Ocean Sci. Eng. 8:41-51.

POMMERANZ. T., and H. G. MOSER.

1983. Vertical distribution study. RIV Ellen B. Scripps, March 19-Apri14, 1980.

Technical tow data and envirorunental observations and preliminary data lists

and summaries of vertical distribution of northern anchovy (Engraulis mordax)

eggs and larvae. Southw. Fish. Cent., Natl. Mar. Fish. Serv, NOAA, P.o.

Box 271, La Jolla. CA 92038. Admin. Rep. U-83-01. 368 p.

SMITH. P. E.

1973. The mortality and dispersal ofsardine eggs and larvae. Rapp. P.-v. Reun.

Cons. int. Explor. Mer 164:282-292.

SMITH, P. E., R. C. COUNTS, and R. I. CLUTTER.

1968. Changes in filtering efficiency of plankton nets due to clogging under

tow. 1. Cons. Perm. Int. Explor. Mer 32:232-248.

SMITH. P. E.• and S. L. RJCHARDSON.

1<n7. Standard techniques for pelagic fish egg and larva surveys. FAO Fish. Tech.

Pap. 175, 100 p.

3.04

8.55

9.69

9.31

8.74

9.37

Aperture areal

mouth area

Aperture

area

(m2

)

0.15

0.43

0.48

0.47

0.44

0.47

Total

Mesh area

(mm) _---'-(m_2

...:.)__Po_r_o_si--=ty'---_

0.035 095 0.16

0.Q75 0.95 0.45

0.150 0.95 0.51

0.250 0.95 0.49

0.333 0.95 0.46

0.505 0.95 0.49

BACK VIEW (B)

TOP VIEW

NOTE: SEE DETAIL DRAWING

FOR PARTS/DIMENSIONS

OF SHADED AREA

o

• - 1/4". ~·'/l" e.o<. TS

AS51"IL[ .""'OL'

"(401,uSSIOl

I

"

1

r-c---------==-:::_='===-------c::?

1----------ID·:v'.·-------__

A

I~

B

FRONT

CALVET NET FRAME (PAJROVET VERSION)

Drawn by: Ken Raymond

Revisions:

SCALE: 1/2"=1"

Date: 1113/83

C

Figure I.-Back and top view of PAJROVET version of CalVET net frame.

29
k-------------------------IB- '/2" --------------------------~

SIDE VIEW

6061 T6 ALUM.

1-<-----' -1/4'~

18 !G---'0~-CL ~'-I/I6'''''i H

1/4"

T r-------,

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o ~~~ c

PAIROVET BACK 1-o-'-1/B',-+--'-I/"~ 3/B"

PAIROVET FRONT

Figure 2.-Side view of PAIROVET net frame.

A FRONT VIEW B

4_ '/4 3/4

110""0><[40

MACHINE SOlIS

12~ ""lGl.E " SltlltH.ESS S'[[L "

--- --:;.-:;..--

NOTE: SEE DETAIL DRAWING

FOR PARTS/DIMENSIONS

OF SHADED AREA

S"/e·RAO,US -_--L.

Figure 3.-Front view of PAIROVET net frame.

30
DETAIL-SHADED AREA

316 STAINLESS STEEL

PART III

(KNURLED KNOB)

I

2-1/2" DIAMETER

1

9/16"

1/2"-13 TAPPED HOLE

1" ; T 9 1/2" • I 2"

7/S" 1

H

3/S"

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1

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TOP

PART I

9/32"

15/32" 1/4"

I I

f'- I" ----'+-1·3/4'~

COARSE THREAD

A'

I I I I

11/32" 3/S"

9/32"

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T

1

END (A',A",A"')

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H

1/4"

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COARSE THREAD

1/2"

COARSE THREAD

Ioof-e=---- 2 -1/2";...'----;~-il

T

5/S"

...

5/S"

-*-

STAINLESS STEEL m3/16" X 1/2" [j] HEX HEAD- COARSE

SEE HOLE

PATTERN ("SIDE

VIEW" C-D)

T

3/4"

1-

~1-31/64~

1/2"

H

Figure 4.-Detailed view of wire attachment for PAIROVET net frame. "Shaded area" refers to Figure 3.

31
"..Aope Hem

A

27 em oia.

+

A'

B

o10 em Ol.m•••,

B'

A,

"

"

"

"

"

"I

"

" 27cm "II

""

"

"

I

""

"

""

18 oz. vinyl coaled nylon

Nitex HC-3 nylon mesh

...- 8 oz. daeron sailcloth

Nlt8.ll HC-3 nylon mesh

c.,nYI co.,•• nylon

B

110cm

___-'-----'1

B'

A'

~~I-!"------------7ocm-------------.,lr-~-.-.e-m~If....---------- 60cm----------+7.6cm~ 6 .• cm

Figure 5.-CaIVET net dimensions. For nets with mesh sizes <0.333 mOl, a protective sheath of 2-0101 mesh nylon is used. See Table I.

32
Procedures for

Sorting, Staging,

and Ageing Eggs

GARY STAUFFER and SUSAN PICQUELLE'

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

Estimation of the dail}' production of eggs spawned is based on data for the number

of eggs sampled during the plank10n survC)'. This requires that the age ofindividual

eggs be determined. To accomplish this, eggs ofthe surve}'ed species must be sorted

out of the plankton samples, staged according to their state of embryonic development, and aged. The initial step in processing the plankton samples is removing

the fish eggs and larvae and identifying the eggs of the target species. The second

step is assigning each egg to a stage of embryonic development and counting the

number of eggs of each stage for each planktoll sample. Once all the samples have

been staged, ages are assigned separately to each sample of the staged eggs based

on a stage/temperature/age key, station temperature, and time ofstation occupancy.

This procedure is subject to a number of sources of error that should be kept

in mind and evaluated for each application.

'Present addresses: Northwest and Alaska Fisheries Center, National Marine Fisheries

Service, NOAA, 7600 Sand Point Way NE, Seattle, WA 98115.

33

INTRODUCTION _

The daily production of eggs spawned into the sea is estimated by

regressing a mortality model to density data on the number of eggs

at age derived from plankton samples. To generate the egg density

data, the fish eggs (and larvae) of the target species must be sorted

from the plankton samples, staged on the basis of embryonic development, and aged. This process can begin as soon as the plankton

samples have been transferred to the laboratory. At the Southwest

Fisheries Center (SWFC), this procedure for the eggs and larvae

of northern anchovies is carried out by three separate groups.

SORTING _

The method of sorting eggs and larvae from the CalVEP samples

are similar to the procedures outlined by Kramer et al. (1972) and

Smith and Richardson (977). The volume of plankton in CaIVET

samples was not measured. In this survey, plankton volumes were

quite small because of the size of the CalVET net and the short duration of the tow and were not necessary for estimation of spawning

biomass.

The plankton sarnples must be sorted by personnel trained in the

identification of fish eggs and larvae particularly of those species

from the survey area. Sorters are responsible for cross-checking the

inside and outside labels of each sample jar as it is processed. It

is critical that sample identification numbers written on all data forms

fIlled out by the sorters match those on the sample jar labels. Sorters

are responsible for picking out the eggs and larvae for all species

and identirying the target species. At the SWFC. eggs and larvae

of the target species are placed in 2-dr vials, fIlled with diluted Formalin, capped, and labeled with station identification numbers. Additional station data to be recorded on the staged egg data forms are

water temperature and time of collection. These data are necessary

for ageing the staged eggs at a later date.

Depending on the objectives of a particular survey, other species

may also be sorted. Egg counts and possibly larval lengths of the

target species are recorded on staged egg data forms. Sorting time

per sample depends on the volume and quality of plankton and the

quantity of ichthyoplankton in the samples. A sorter at the SWFC

can process about eight CaIVET samples per day. If processing of

the plankton samples is on a strict schedule as it is at the SWFC,

then it is advisable to sort first the samples collected at stations with

the highest expected density of eggs.

STAGING _

The second step in processing eggs of the target species is the assigning of an embryonic developmental stage to each egg. More training, experience, and time are required to accurately stage the embryonic development of fish eggs. The 2-dr vials containing sorted

eggs of the target species and the respective staged egg data forms

are turned over to a second group responsible for staging eggs at

the SWFC.

Working with each sample separately, the technician pipettes or

empties the eggs in a vial into a petri dish and sorts the eggs under

a binocular dissecting scope into groups for each standardized

developmental stage that spans incubation from time of fertilization to hatching, as described in Moser and Ahlstrom (1985). Eggs

'For a description of the CalVET net, see Smith et aI. (1985).
with disintegrated embryos are often difficult to stage and require

special attention (see Moser and Ahlstrom 1985). In some samples,

as much as 50% of the eggs could be disintegrated and difficult to

stage. The number of eggs in each stage group are counted and

recorded on the staged egg data sheet. The number of eggs for which

it is impossible to assess the embryonic condition must be recorded

also. The sum of the number of eggs staged should equal the earlier

sorter's count. If not, then all groups should be recounted and any

discrepancies accounted for and noted. When the staging of a sample is completed, all the eggs must be returned to the vial and the

sample archi,ed in a storage area.

AGEING _

Once all the station samples have been staged, the completed staged

data forms can be turned over to a team which assigns ages to the

staged eggs. Although this group of two or three people need not

be skilled in identification of eggs and larvae or egg stages, they

must understand the daily spawning cycle and the effect of

temperature on development rate. It is recommended that each team

member age the eggs for all stations independently of the others.

This serves as a check of potential ageing errors and biases that

could result from subjective decisions on likely ages of eggs for which

the day of spawning is not obvious.

Assigning ages to eggs based on the stage of embryonic development is a relatively straightforward procedure if spawning occurs

within a brief time interval during the 24-h daily cycle and if the

duration of egg stages is less than a day for the range of temperatures

observed during the survey. If either one of these conditions is not

the case in any particular application, then the procedure described

here will have to be modified in order to estimate daily rate of egg

production in the sea.

Before the ageing step can begin, the team must specify the hour

of peak spawning within the daily cycle to determine time zero for

egg development. This can be determined from the time of day that

newly fertilized eggs appear in the egg collections and from observations on the spawning behavior or condition of the adults. A

stage/temperature/age key as described in Lo (1985, fig. 2) must be

available for the target species of the survey. This key represents

embryonic growth curves for each developmental stage, relating time

to develop with temperature. From these curves, the time or age

from fertilization to time of collection can be estimated given the

stage of development and station surface temperature, which is

assumed to be the temperature at which the egg was incubated. The

age of an egg can be calculated by estimating its age in whole days

and then adding on the portion of a day that has elapsed between

peak spawning hour and the time of day the sample was collected.

For northern anchovies off California, the peak spawning hour is

set at 2200. Thus eggs need be aged only to the nearest day and

then adjusted for the portion of the day between sampling and peak

spawning.

The benefit of having all spawning occur in the same short interval each day is that the ages of the eggs within each sample are

separated by 24-h increments. Because the duration of any particular

stage is much less than 24 h, the distribution of eggs of a single

sample over the different developmental stages should form distinct

groups or modes with unrepresented stages separating each group.

One can then assume that each group is separated by 24 h. This

pattern is extremely helpful in assigning whole-day ages to groups

of eggs within a sample. However, this pattern becomes blurred for

samples taken from colder temperatures where the duration of each

34

stage is longer and the modes or groups of eggs may overlap. This

pattern is also less clear for the advanced stages because the ages

are assigned with less precision. The longer the incubation time,

the more inflated the variance in the age key becomes as the effects

of variability in growth rate and environmental factors accrue.

These two problems are partially avoided by truncating the data

series and eliminating the eggs older than a specific age. The primary

reason for doing this is to avoid the time period when eggs begin

to hatch into larvae and are no longer available for sampling. Truncation of egg density data for eggs older than the age at which the

onset of hatching is expected for the warmer temperatures encountered on the survey insures that mortality is the only process

contributing to the decline in egg abundance. This also eliminates

eggs for which the procedure of assigning ages has the greatest

uncertainty.

For the northern anchovy surveys conducted by the SWFC, time

was saved by taking temperture data at the surface only, at most

stations. The recorded temperature data represent the maximum incubation temperatures that eggs would likely encounter in the upper mixed layer, where anchovy eggs are found. In a few cases, eggs

could have been assigned to either one of two spawning days based

on the age key. In these cases, the older age was assigned based

on the assumption that the egg was probably incubated at a

temperature colder than the surface waters. However, the majority

of eggs closely corresponded to the predicted age suggested by the

embryonic growth curves and by the separation of egg-stage modes.

Plankton samples collected during the spawning hours will undersample the new eggs until spawning is completed for the daily spawning period. To avoid underestimating daily egg production from the

mortality model, egg densities ofthe youngest ages exclude samples

collected during the spawning period. For northern anchovies this

period was between 1800 and 0200. These samples do provide data

on eggs older than approximately one-half day (for further discussion see Picquelle and Stauffer 1985).

After assignment of ages by all team members working independently of one another, the staged egg data forms were sorted

into convenient time and temperature strata. The team as a group

examined the data forms for each stratum for consistency among

samples in the assigned age of each stage. At this time, discrepancies between the ages assigned by different team members and

among stations with similar conditions were discussed and rectified.

This final comparison is very important to minimize any differences

among the team, to reduce errors, and to insure that the determinations from the age key are consistent throughout the ageing exercise.

The ageing step can be automated using a computer. Based on

the stage/temperature/age key, a reference table can be constructed

and included in a computer program. The table should contain the

estimated ages of eggs for each of the II stages at temperatures

ranging from 10° to 22"C, sampled at any time throughout a 24-h

period. Ages are assigned to stages according to the reference table.

The advantages of the automated system are twofold. 1) It saves

time: the current manual system requires about 1 wk of manpower

to age the eggs, enter the data, and build the data fIles for the estimation of daily egg mortality and egg production; the automated system

requires one-half day at most to process the staged eggs and produce a daily egg mortality curve. 2) It standardizes the method:

the automated system eliminates the subjectivity of human judgment and variation resulting from operator error, thus the accuracy

of the egg production and the egg mortality estimate can be improved (see Lo 1985).
ASSUMPTIONS AND SOURCES

OF ERROR _

1) Anchovy eggs are easily distinguished because of the oblate

spheroid shape. As a result, the sorting procedure for anchovy eggs

is quite accurate and relatively efficient. The sorting of spherical

eggs of other species may require more skill and resorting to check

for accuracy if there is a potential confusion with other species.

2) Often a high fraction of the fish eggs have disrupted or

disintegrated embryos. In these cases, the developmental stage must

be determined by additional criteria. For the northern anchovy example, it was assumed that this condition occurred during the

plankton tow and that eggs in this category had a similar mortality

history. The validity ofthis assumption should be examined in each

application of the egg production method.

3) The assumption that 100% of the eggs are retained by the

plankton net should be tested. Also, the catching process and fixation may stimulate the eggs to hatch.

4) The mortality model assumes that all egg stages including

unfertilized eggs have the same rate of mortality. If unfertilized eggs

make up only a small fraction of the total eggs, and if they persist

in the water column for <1 d, then it is probably sufficient to assign

them as l-d-old eggs. This ignores the bias in the estimate of daily

egg production created by the different mortality rates of unfertilized eggs and the inability to age unfertilized eggs. On the other

hand, if unfertilized eggs are not an insignificant fraction of the total,

then the egg production mortality model must be modified to account for them.

5) The ageing of staged eggs is facilitated by a short spawning

interyal within a daily period. Assigning ages to embryonic stages

will become less reliable as the spawning interval makes up a greater

fraction of the daily period. Stage durations of <12 h at the usual

incubation temperature fucilitates the assigning of daily ages to staged

eggs. If embryonic development is slow, which is often the case at

low temperatures, then there is a good possibility that eggs at a single

stage could have resulted from more than a single spawning episode.

If this occurs, then the arbitrary stages described here must be

divided further.

6) The duration of an egg stage is a function of the incubation

temperature. The measured temperature at a plankton station may

not be the actual temperature at which the collected eggs were incubated within the water column. The temperature measurement

must be representative of the temperature at which the majority of

the eggs incubate. This requires a study of the vertical distribution

of eggs compared with the temperature depth profile.

LITERATURE CITED _

KRAMER, D., M. M. KALIN, E. G. STEVENS, J. R. THRAILKILL, and JR.

ZWEIFEL.

1m. Collecting and processing data on fish eggs and larvae in the California

Current region. U.S. Dep. Commer., NOAA Tech. Rep. NMFS Circ. 370, 38 p.

LO, N. C. H.

1985. A model for temperature-dependent northern anchovy egg development and

an automated procedure for the assignment of age to staged eggs. In R. Lasker

(editor), An egg production method for estimating spawning biomass of pelagic

fish: Application to the northern anchovy, Engraulis mordax, p. 43-50. U.S.

Dep. Commer., NOAA Tech. Rep. NMFS 36.

MOSER, H. G., and E. H. AHLSTROM.

1985. Staging anchovy eggs. In R. Lasker (editor), An egg production method

for estimating spawning biomass of pelagic fish: Application to the northern

anchovy, Engraulis mordax, p. 37-41. U.S. Dep. Commer., NOAA Tech. Rep.

NMFS 36.

35

PICQUELLE, S., and G. STAUFFER.

1985. Parameter estimation for an egg production method of northern anchovy

biomass assessment. In R. Lasker (editor), An egg production method for

estllnating spawning biomess of pelagic fish: Application to the northern anchovy, Engraulis mordux, p. 7-15. U.S. Dep. Commer. , NOAA Tech. Rep.

NMFS 36.

SMITH, P. E., and S. L. RICHARDSON.

1977. Standard techniques for pelagic fish egg and larva surveys. FAO Fish. Tech.

Pap. 175, 100 p.

SMITH, P. E.. w. FLERX, and R. HEWITT.

1985. The CalCOFI vertical egg lOw (CalVET) nel. In R. Lasker (editor), An

egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engralllis //lorda-<, p. 'D-32. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.
36
Staging Anchovy Eggs

H. GEOFFREY MOSER and ELBERT H. AHLSTROM

Southwest Fisheries Center,

National Marine Fi!:heries Service. NOM,

Po. Box 271, La Jolla, C4 92038

ABSTRACT

The developmental period of northern anchovy eggs is divided into eleven stages.

These stages are defined by structural criteria chosen from the sequence of morphological changes which occur during embryogenesis. Samples of eggs, preserved

in 3% formaldehyde solution, are examined under a dissecting microscope using

soft transmitted light. In Stage I eggs, cell division has not yet begun and the

cytoplasm appears as a cap at one pole of the elliptical yolk mass. Cell division

occurs during Stage II to produce a blastodisc. At Stage III the size of the individual blastomeres is greatly reduced and the blastodisc has the appearance of

tissue. Stages IV, V, and VI are defined by the fraction of the yolk mass covered

by the blastoderm. The proportion of tail length to head length defines Stages

VII and VIII, and the proportion of tail length to yolk mass length defines Stages

IX, X. and XI. The procedure for staging eggs with disintegrated embryos is

described.

37

INTRODUCTION _

The eleven egg stages used since 1980 in egg production biomass

estimates are modified from stages established by Ahlstrom (1943)

for the Pacific sardine, Sardinops sagax. Northern anchovy eggs

differ markedly from those of the Pacific sardine in size, shape, and

in the absence of an oil globule. The strongly elliptical eggs of

Engraulis mordax measure 1.23-1.55 mm at the major axis and

0.65-0.82 mm at the minor axis (Bolin 1936), whereas developing

sardine eggs range from 1.35 to 2.05 mm with a mean of 1.70 mm

(Ah~trom 1943). The sardine embryo, however, is only slightly

larger than the embryo of the anchovy since the wide perivitelline

space of the sardine accounts for almost half the total egg diameter.

Also, the rates of development of major embryonic features and organ

systems are comparable in the two species.

METHODS _

Eggs are sorted from the plankton samples as described by Stauffer

and Picquelle (1985) and preserved in 3 % buffered Formalin in 2-dr

vials. For staging, each sample is placed in a watch glass with water

and examined under a dissecting microscope, using the microscope

mirror to produce a soft transmitted light. A direct light source does

not allow one to distinguish fine structures of the embryos.

Most samples contain several groups of eggs representing widely

separated stages from several days' spawnings. An initial cursory

examination allows one to sort most of the eggs into these several

subgroups, which can then be assigned to stages. The stages are

based on structural criteria chosen from the sequence of morphological changes which occur during embryogenesis. These are

described below and illustrated in Figures I and 2.

EGG STAGES _

Stage I

Cell division has not yet begun. In intact eggs the cytoplasm of the

single cell appears as a clear hemisphere at one pole, easily differentiated from the yolk mass which is divided into granules. The

cytoplasm may be displaced to other locations around the periphery

of the yolk mass, but there is usually some accumulation at one pole,

which allows the stage to be identified.

Stage II

This begins with the division of the single cell into two cells or

blastomeres. The division is first noticeable when a furrow develops

in the middle of the cytoplasmic cap. Small bubble-like structures

(probably artifacts) are often visible along the furrow and help identify it. The next cleavage plane is at right angles to the first, and

subsequent synchronous divisions in both meridional and latitudinal

planes produce a hemispherical mound of cells, termed the blastodisc. After the 5th or 6th division, the blastodisc has a berry-like

appearance, the so-called "mulberry stage," and with subsequent

divisions the blastomeres become increasingly smaller and more

difficult to distinguish individually. During a certain phase of the

early divisions the blastomeres are about the same size as the yolk

granules. Ifthe blastodisc and yolk mass become disrupted during

collection or preservation, the blastomeres may become distributed

among the yolk granules. They may be distinguished from one

another since they have different refractive indices and the

blastomeres appear darker when viewed with transmitted light.
Figure I.-Stages of northern anchovy eggs. A. Stage I; B. Stage II (2 cells); C. Stage II (16 cells); D. Stage II

("Mulberry''); E. Stage II (late); F. Stage ill (mid); G. Stage ill (late); H. Stage IV (mid); I. Stage V (mid). Original

illustrations of A, B, D, G, by G. Mattson; C, E, F, H, I from Bolin (1936).

38
H

1

2"

t.11: ------ -- St~10'.- ~~·_~_ 1

! St.4 3"

St.10:

--SC91

i St.4 2

--§-t"-~r--St~ -5- 3"

,

c

Figure 2.-Stages of northern anchovy eggs. A. Stage V (late); B. Stage VI; C. Stage VB; D. Stage VBI; E. Stage

IX; F. Stage X; G. Stage XI; H. Diagrammatic egg showing relationship of epiboly and tail length to stage; right side

indicates fraction of the yolk mass covered by the blastoderm in Stages ill, IV, and V; left side shows tail lengthlhead length

proportions which deline Stages VII and VBI and tail length/yolk mass length proportions which define Stages IX, X, and

XI; I. Newly hatched anchovy. Original illustrations of A, C, and F by G. Mattson; B from Bolin (1936); original illustrations

of D and E by H. Orr; original illustration of G by G. Moser; H prepared by B. Sumida; I from Kramer and Ahlstrom (1968).

39
Stage III

Ahlstrom (1943) defined this stage in sardine eggs as beginning with

the appearance of the segmentation cavity. The segmentation cavity

of teleost eggs is the space formed between the blastodisc and the

yolk mass during late cleavage. In most anchovy eggs in our collections the blastodisc is shrunken and somewhat cup-shaped and consequently the segmentation cavity, which is a delicate structure, is

obliterated. We have found it preferable to define the beginning of

Stage ill on the basis ofthe appearance of the blastoderm, i.e., when

it has the appearance of tissue rather than of a collection of individual

cells. This stage marks the beginning of gastrulation. The margin

of the blastodisc becomes slightly thickened and is termed the germ

ring. At one region of the germ ring the thickening extends inward

to form the embryonic shield, which defines the future axis of the

embryo. Gastrulation proceeds by further proliferation and downward

movement of cells in the region of the germ ring by a process known

as epiboly. Simultaneously, proliferation and inward migration (emboly) of cells from the margin of the embryonic shield produce the

organ-forming cell layers of the primordial embryo. At the end of

Stage III the germ ring is one-third down the yolk mass and the

bilateral nature of the primordial embryo is apparent.

Stage IV

At the beginning of this stage the germ ring has enclosed one-third

of the yolk mass and the embryo is beginning to form along the

median region of the embryonic shield. At the end of this stage,

defined by the germ ring enveloping two-thirds of the yolk, the head

region of the embryo is becoming apparent.

Stage V

This stage begins with the germ ring two-thirds down the yolk and

ends with the closure of the blastopore and the complete enclosure

of the yolk by the cellular sheath of the embryo. The stage is characterized by rapid differentiation resulting in the formation of several

somites in the midregion of the embryonic axis, development of the

notochord which can be seen from a dorsal viewpoint, and differentiation of the optic vesicles from the brain.

Stage VI

This stage begins with the closure of the blastopore and ends when

the tail starts to separate from the yolk mass. The embryonic sheath

of cells is extremely thin and, in some samples, it may be difficult

to determine the point of blastopore closure. In these cases the event

can be estimated from the position of the caudal terminus of the

embryonic axis, since it grows toward the pole with the edge of the

cellular sheath. Initially the caudal region lies flat against the polar

region of the yolk, then gradually thickens and becomes more rounded at the tip until it is clearly separate from the yolk. During this

stage the somites are apparent along the entire body axis (except

at the caudal portion), the lens primordium appears in the eye, and

the regions of the brain begin to differentiate.

Stage VII

At the beginning of this stage the tip of the tail free from the yolk

is broadly rounded, then begins to narrow as it elongates. The notochord extends almost to the tip and the finfold is just becoming visible. At the end of this stage the length of the free tail is one-half

40

the length of the head. For this purpose, head length is considered

the distance from the tip of the snout to the back of the cerebellum

(see Fig. 2H). Relative tail length is the criterion for each remaining stage.

Stage VIII

This stage begins when the free tail length is l:,reater than one-half

the head length and ends when tail length equals head length. The

tail becomes pointed during this stage and begins to bend away from

the axis of the body, to the right or left side. The curvature of the

tail generally increases with development, but is subject to individual

variability (Fig. 2). Judgement is required in compensating for curvature in estimating relative tail length; however, accuracy and precision increase rapidly with practice.

Stage IX

This stage begins with the tail extending one-quarter the length of

the yolk sac and ends when it reaches one-half the yolk sac length.

The gut is now apparent along the ventral surface of the tail, and

its terminal section passes through the fin fold which is now considerably wider than in the previous stage. The pectoral fin buds

appear as lateral thickenings as do the otic vesicles.

Stage X

This stage starts when the tail is one-half the length of the yolk sac

and ends when it reaches three-quarters of the yolk sac length.

Stage XI

This is the final stage before hatching and is defined by a tail length

greater than three-quarters of the length of the yolk sac.

Disintegrated (Dis) Eggs

Eggs with embryos in various states of disintegration are found in

many samples, and some samples contain a large proportion of

disintegrated eggs. Despite some preliminary field and laboratory

experiments, we are not able to determine whether disintegration

is caused by net damage, fixation, mortality prior to capture, or some

combination of these. The sampling design requires that all eggs

be assigned a stage regardless of condition. Empty egg shells and

eggs which have no identifiable morphological features are assigned

the "Dis" (disintegrated) category. These are later assigned a stage,

by pro rating, during the aging procedure (see Lo 1985). With detailed examination, eggs containing damaged or shrunken embryos

can be staged. Usually they are part of a mode which is present

in the sample and thus can be staged by comparison with the groups

of intact eggs. In the early-stage disintegrated eggs, the blastomeres

and yolk granules are intermingled but can be distinguished since

the former appear darker in transmitted light. In eggs beyond Stage

III, the embryos are rarely disassociated but may be distorted or

shrunken and oriented abnormally because of the disintegration of

the yolk mass. Despite their condition, these embryos have the morphological features described for intact embryos and can be staged,

although this requires more attention to morphological details; particularly useful are careful observations on the degree of differentiation of myomores, median finfold, and head structures such as

eyes, brain lobes, and otic vesicles.
LITERATURE CITED _

AHLSTROM, E. H.

1943. Studies on the Pacific pilchard or sardine (Sardinops caerulea). 4. Influence of temperature on the rate of development of pilchard eggs in nature.

U.S. Fish. Wild!. Serv., Spec. Sci. Rep. 23, 26 p.

BOLIN, R. L.

1936. Embryonic and early larval stages of the California anchovy Engraulis mordax Girard. Calif. Fish Game 22(4):314-321.

KRAMER, D., and E. H. AHLSTROM.

1968. Distributional atlas of fish larvae in the California Current region: Northern Anchovy, Engraulis mordax Girard, 1951 through 1965. Calif. Coop.

Oceanic Fish. lnves!. Atlas 9, 269 p.

LO, N. C. H.

1985. A model for temperature-dependent northern anchovy egg development and

an automated procedure for the assignment of age to staged eggs. In R. Lasker

(editor), An egg production method for eSlimating spawning biomass of pelagic

fish: Application to the northern anchovy, Engraulis mordax, p. 43-50. U.S.

Dep. Commer. , NOAA Tech. Rep. NMFS 36.

STAUFFER, G., and S. PICQUELLE.

1985. Procedures for sorting, staging, and ageing eggs. In R. Lasker (editor),

An egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engraulis mordax, p. 33-35. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

41
42
A Model for TemperatureDependent Northern

Anchovy Egg Development

and an Automated

Procedure for the

Assignment of Age

to Staged Eggs

NANCY C. H. LO

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

A functional relationship between age and developmental stage of northern anchovy, Engraulis mordax, eggs for various temperatures was determined based

upon data collected in two laboratory experiments. The age of an egg was found

to be a mixed exponential and power function of temperature and stage. An

automated procedure was also developed using a reference table to assign age to

staged eggs for any given time of tow and sea temperature ranging from 10° to

22°C. A comparison between the manual system and the automated procedure

was made based on 1980-83 data, and the difference was found to be minimal.

43

INTRODUCTION _

In the first section of this paper, I discuss the modelling of temperature-dependent anchovy egg development based on data from two

laboratory experiments conducted at the Southwest Fisheries Center

(SWFC). This temperature-dependent egg development curve is used

to assign ages to the field-collected eggs after they are staged according to their anatomical development. In the second section, I

discuss an automated procedure for accomplishing the assignment

of ages.

TEMPERATURE AND DEVELOPMENT _

Both laboratory and fieltl-collected anchovy egg data indicate that

the developmental rate of eggs is temperature-dependent. The higher

the temperature, the shorter the time required to reach a given stage.

The relationship between the age of eggs and temperature for a given

stage has been studied in the past (Zweifel and Lasker 1976; Zweifel

pers. comm.l

) and a Gompertz growth curve fitted to the laboratory egg development data of both anchovy and sardine.

To improve our knowledge of the relationship between temperature and development of anchovy eggs and yolksac larvae, in 1981

a laboratory experiment was conducted at three temperatures (13.5°,

15.0°, and 16.5°C) using eggs from a captive brood stock (La 1983).

These egg data were used along with those collected at temperatures ranging from 13.8° to 20.8°C for stages III, VI, VIII, IX, and

XI in an earlier experiment to develop a revised model for expressing the development of anchovy eggs at a given temperature (Table

1). Stages are described by Moser and Ahlstrom (1985), and procedures for sorting and staging eggs by Stauffer and Picquelle (1985).

Table i.-Average age (in hours.minutes) of northern anchovy eggs for

each of 10 developmental stages (Stage I not observed) at various temperatures (0C) from laboratory experiments conducted at the SWFC.

Temperature

CC)

(1.0 1983) Zweifel and Lasker (1976)

Stage 13.9 15.2 16.2 13.8 15.2 16.6 18.0 19.4 20.8

II 6.82 6.42 6.40

III 16.36 13.55 13.14 20 15 10 9 8 6

IV 24.91 21.12 20.18

V 35.88 30.7 25.56

VI 44.63 39.24 33.20 42 35 26 24 21 9

VII 49.64 47.13 38.56

VIII 52.5 52.07 43.64

IX 61.l 56.28 50.48 58 50 39 35 33 28

X 66.09 62.63 54.78

XI 69.79 65.65 56.10 78 65 55 44 39 35

MODEL DEVEWPMENT

AND RESULTS _

To choose an appropriate model for the relationship between age

and temperature for a particular stage, I examined the age-temperature relationship empirically for stages III, VI, VIII, IX, and XI,

because data on these stages were available for a wide temperature

range (data for stages VIII and IX were combined to increase the

sample size).

11. R. Zweifel, Southeast Fisheries Center, National Marine Fisheries Service, NOAA,

75 Virginia Beach Drive, Miami, FL 33149, pcrs. commun. July 1983.
Figure I.-Observed (denoted by various symbols) and predicted ages (smooth

lines) oftime to the jth stage as a function oftemperature (Oe) based on egg development data collected from two laboratory experiments conducted at SWFC. The

predicted values are computed from Equation (4).

0200

E

XI

0200

B c o

Age of eggs on daily basis

0200 0200 0200 0200

S A

22

21

20

19

18

°17 'Z...

! 16 :J

15 ..

<>

E 14 ..

... 13

12

11

10

9

0 12

Figure 2.-Function relationship of average age of eggs for the jth stage based

upon time of lOW and sea surface temperature rC).

24 36 48 60 72 84 96 108 120 132 Age (hours)

2200 1000 2200 1000 2200 100022001000 22001000 2200 1000

Time of tow

XI

Stage

c II

o III

IV

+ V x VI

o VII

• VIII & IX

• IX

• X

• XI

12

11

10

9t--'---,...l---r-'--.----'--,...--...>.,-->r-~~r__..:::.,..~.,..::...........,

o 12 24 36 48 60 72 84 96 108 120 132

Age (hours)

13

22

21

20

19

18

.E 17

i 16

15 ..

<>

E 14 ..

...

For all four stages, the exponential function fitted the data well,

i.e.,

Y· = a·eb,1 1,1 1 (1)

Temperature (0C) In at hi Ct R2

13.9 0.717 -0.206 2.4 0.96

13.5 0.731 -0.153 2.13 0.96

16.2 0.793 -0.206 1.94 0.99

where Yi,1 is the average age of the ith-stage anchovy eggs at temperature tOe. The coefficients (aib) are for the ith stage only. The

initial fitting of the model was accomplished by linear regression

of the natural logarithm of the ages on the temperatures (In Yi' =

In ai + b;f). The coefficient'of determination (R2) ranges from 0.82

to 0.98:

In order to include all the existing data on anchovy egg development in a single model, Equations (I) and (2) were combined into

one equation:

(3)

where the coefficients a, b,c, and d were common for all stages and

all temperatures. Equation (3) was then fitted to all temperaturespecific egg development data (Table 1). The resulting model is:

Stage In aj hj R2

III 5.02 -0.155 0.95

VI 5.50 -0.126 0.82

VIII, IX 5.54 -0.107 0.95

XI 5.88 -0.113 0.98

Y,., = 16.07 e.-(O.I 145,+0 0098i)jI.74 . (4)

All the coefficients are temperature specific; a" b" and c, are for

temperature tOe. Linear regressions of the natural logarithms of

average age on stage (In Yi,1 = In a,+bl'i+clln(i» show an excellent fit with R2 ranging from 0.96 to 0.99 for each of the three

temperatures:

Next, the development data were examined for a given temperature

where ages were available for most of the stages. In this analysis,

only the latest laboratory data were included because the other data

set had only four or five egg stages. The temperatures used were

13.9°, 15.2°, and 16.2°C (mean temperature experienced by all egg

stages). For each of the three temperatures, the development curves

were more complicated than time-to-stage curves described above.

A simple exponential function was not sufficient. Instead, the function was a combination of an exponential and a power function:

Yi,l = a, eb,i (i)c, (2)

The observed and predicted ages of anchovy eggs were plotted in

Figure I.

For each of the 11 stages, the average age of anchovy eggs can

be estimated from Equation (4) for a given temperature. A family

of 11 temperature-age curves was used as the key to determine the

ages of anchovy eggs collected in the field in conjunction with the

time of tow and sea surface temperature, assuming 1800-0200 was

the spawning time with 2200 as the peak (Fig. 2).

To use Figure 2 to assign age to anchovy eggs after they are staged,

the following is done. First, time zero was assumed to be 2200, the

midpoint of the daily spawning period. All the eggs observed between 1800 and 0200 were classified as newly spawned eggs (S).

Eggs that fall in the consecutive 24-h intervals from 0200 to 0200

are classified as day 0, day I. day 2, and day 3 eggs (or A-day, B-day,

C-day, D-day eggs), depending on the time of tow and the sea surface temperature. For example, the eggs collected from a tow taken

at 1800 h at 16°C should have the age assignment as below

(theoretically no stage II should be observed):

44
AN AUTOMATED PROCEDURE _

The above assignment of ages to staged eggs is on a daily basis.

With the information of time oftow, the age of eggs can be expressed

in hours, e. g., A-day eggs are 20 hold (20 h from 22(0) and B-day

eggs are 44 h old in this example.

Stage I

Age S

II III IV V

A A A

VI VII

B B

VIII IX X XI

B B B B,C

where Yi.1 is from Equation (4), k is time of tow, and t is the expected time of observing stage i eggs. t is obtained from the peak

spawning time (st) (=2200 for northern anchovy) and average age

(Yi,,):

t = remainder of (Yi.1 + st)/24.

The basic formula is used for samples taken between T-G and t+G

h. The quantity G is chosen to be 2 X the standard deviation of ages

within stage (sd). If Yi,l.k<2 xsd, G is set to be equal to Yi.l.k, or

The automated procedure for assigning an age to a staged anchovy

egg is a FORTRAN computer program (STAGEAGE) coded for

VAX2 computer. It takes input data of staged eggs along with sea

temperature and time of tow and assigns ages to eggs according to

a reference table (see Table 3). This reference table contains the

estimated ages of eggs for each of the 11 egg stages (see Moser and

Ahlstrom 1985) at temperatures ranging from 10° to 22°C for any

time throughout a day. In the following paragraphs, I describe the

construction of the reference table.

The estimated ages (Yi,t.k) in the reference table are the average

ages (Yi,,) computed from Equation (4) adjusted for the time of tow

(k) assuming that the peak spawning time is 2200. If the eggs are

observed before their expected time, an age younger than Yi,t will

be assigned. Otherwise, an older age will be assigned. The basic

formula of determining the age of eggs (Yi.l.k) is

The average standard deviation over three temperatures (13.9 °,

15.2°, 16.2°C) is between 2 and 5 h.

The average age (Vi) and the expected time of tow (7) for each

stage and temperature combination are given in Table 2. The assignment of ages of eggs as a function of the time of tow (k) and sea

surface temperature (t) is computed as below:

(7)

IX X XI

533

VIII

3

if k<t-G

t-G<k<t+G

t+G<k.

if Yi.l,k>2 x sd

otherwise.

G = { 2xsd

Yi.l,k

II III IV V VI VII

2 4 4 4 4 3

Stage

sd (h)

Yi,t.k = Yi,t + k - t (5)

'VAX is a trademark of Digital Equipment Corporation. Notice Equation (7) is a modified version of Equation (5).

Table 2.-Average age and expected time of tow for each combination of stages (i) and

temperatures (I) ranging from 10° to 22°C.

Temp. Stage

(0e) II III IV V VI VII VIII IX X XI

Average (Yi) (in hours.minutes)

10 4.23 13.16 24.21 36.25 48.40 60.36 71.51 82. II 91.27 99.36 106.36

II 3.54 11.50 21.43 32.28 43.24 54.03 64.05 73.17 81.34 88.50 95.04

12 3.29 10.33 19.22 28.57 38.43 48.12 57.09 65.22 72.44 79.13 84.47

13 3.06 9.24 17.16 25.50 34.31 42.59 50.58 58.17 64.52 70.39 75.36

t4 2.46 8.23 t5.24 23.02 30.47 38.20 45.27 51.59 57.5t 63.00 67.26

15 2.28 7.29 13.44 20.32 27.27 34.11 40.32 46.22 51.36 56.11 60.08

16 2.12 6.40 12.15 18.19 24.29 30.29 36.09 41.21 46.01 50.07 53.38

17 1.58 5.57 10.55 16.20 21.50 27. II 32.14 36.52 41.02 44.41 47.49

18 1.45 5.18 9.44 14.34 19.28 24.15 28.45 32.53 36.36 39.51 42.39

19 1.34 4.44 8.41 13.00 17.22 21.38 25.38 29.19 32.38 35.32 38.02

20 1.24 4.13 7.45 11.35 15.29 19.17 22.52 26.09 29.06 31.42 33.55

21 1.15 3.46 6.55 10.20 13.49 17.12 20.23 23.19 25.57 28.16 30.15

22 1.06 3.21 6.10 9.13 12.19 15.20 18.11 20.48 23.09 25.13 26.59

Expected time of tow (t) (in hours.minutes)

10 2.23 11.16 22.21 10.25 22.40 10.36 21.51 8.11 17.27 1.36 8.36

II 1.54 9.50 19.43 6.28 17.24 4.03 14.05 23.17 7.34 14.50 21.04

12 1.29 8.33 17.22 2.57 12.43 22.12 7.09 15.22 22.44 5.13 10.47

13 1.06 7.24 15.16 23.50 8.31 16.59 0.58 8.17 14.52 20.39 1.36

14 0.46 6.23 13.24 21.02 4.47 12.20 19.27 1.59 7.51 13.00 17.26

15 0.28 5.29 11.44 18.32 1.27 8.11 14.32 20.22 1.36 6.11 10.08

16 0.12 4.40 10.15 16.19 22.29 4.29 IQ.09 15.21 20.01 0.07 3.38

17 23.58 3.57 8.55 14.20 19.50 1.11 6.14 10.52 15.02 18.41 21.49

18 23.45 3.18 7.44 12.34 17.28 22.15 2.45 6.53 10.36 13.51 16.39

19 23.34 2.44 6.41 11.00 15.22 19.38 23.38 3.19 6.38 9.32 12.02

20 23.24 2.13 5.45 9.35 13.29 17.17 20.52 0.09 3.06 5.42 7.55

21 23.15 1.46 4.55 8.20 11.49 15.12 18.23 21.19 23.57 2.16 4.15

22 23.06 1.21 4.10 7.13 10.19 13.20 16.11 18.48 21.09 23.13 0.59

45
Thus, the age for eggs ofstage i observed at temperature t is always

within Yi,t ±G (i.e., between two standard deviations of age within

a stage). Equation (7) eliminates the possibility of assigning either

too young or too old an age to eggs that were sampled at the time

which is more than G hours before or after the expected time of

tow. Occasionally, the eggs are taken 12 h away from the expected

time of spawning. These eggs can be either the youngest or the

oldest eggs for that stage. In this case, the maximum and minimum

ages are then randomly assigned to those eggs because there is no

way of distinguishing eggs between the young and old ages within

stage.

The reference table for stage IV anchovy eggs is given (Table

3). In the table, the first column is the time of tow (01-24 h). The

rows corresponding to 25 h are the maximum ages used for random selection of ages for eggs observed at 12 h away from the expected time. Row I contains temperatures ranging from 10° to

2ZOC. Each entry from row 2 and on is the estimated age for a

combination of time of tow and sea temperature. For a given

temperature, and time of tow. ages are assigned to each stage according to the reference table. The reference table for all stages

is included in FORTRAN program STAGEAGE (Hewitt et al.

1984).

Use of Computer Program STAGEAGE

Input Data File-The input data file of eggs should include tow

identification (lD) information, e.g., cruise number, location (line

and station for CalCOFI survey), stratum, weighting factor (Hewitt

et aI. 1984), tow number, tow time, sea surface temperature, number

of eggs for each stage, and total number of eggs. Variables in tow

ID and total eggs are useful for data checking. The other variables

are essential for estimating the ages of eggs (Table 4).

Output Data Files-Several output data files are available from

STAGEAGE. STAGEAGE can be used not only to assign ages to

staged eggs, but also to stratify the survey area into regions as desired.

Regions are defined as area between line numbers. The user can

choose output data file(s) and the number of regions in the execution instructions (see next section). The major output data ftle names

in logic unit numbers are FOR026. OAT, FOR029. OAT.

FOR036.DAT, FOR037.0AT, FOR038.0AT (Tables Sa-e).

Table 3.-PIlrtial listing of the reference table. Estimated age (in hours.minutes) for stage IV for ~ch combination of time of to'." (t-24 h) and tem~rature

(loo-22"C). Asterisks (0) indicate the estimated age corresponding to expected time of tow (n (see Tables 2a, b). Row 2S IS for random assIgnment

of ages for eggs observed at U h before or after expected time of tow.

Time Temperature (0 C)

of

tow

(k) 10 11 12 13 14 15 16 17 18 19 20 21 22

1 28. 25 27. 28 27. 57 27. :;0 27. 02 27. 32 26 19 24. 20 6. 34 4. 60 3. 35 20 3. 13

2 28 2:; 28. 28 28. 57* 28 :;0 28. 02 28 32 26. 19 8. 20 6. 34 4. 60 4 35 4. 20 4. 13 29. 28 29. 57 29. :;0 29. 02 28. 60 5. 3:; :; 20 5. 13 ~..,

21~. 2~: ~~ 26. 19 8. 20 6. 34 S.

4 30. 2~ 30. 28 30. 57 30. 50 30. 02 28. 32 10. 19 8 20 6. 34 6. 60 6 3S 6. 20 6. 13

5 31. 2~) 31. 28 31. 57 31. 50 31. 02 28. 32 10. 19 B. 20 7. 34 7. 60 7. 3:> 7. 20 7. 13

6 32. 2~ 32. 28* 32. 57 32. 50 31. 02 12. 32 10. 19 8 20 8 34 8. 60 B. 35 B. 20 8. 13 12. 32 10. 19 9. 20 9. 34 9. 60 9. 35 9. 13* ~g* 9. -, 33. 25 33. 28 33. 57 33. 50 31. 02 8 34 25 3" 28 34. 57 33 :;0 31 02 12. 32 10. 19 10 20 10. 34 10. 60 10 35 10. 10. 13

9 33. 25 35. 2B 35. 57 33. :;0 15 02 12. 32 1 1. 19 11. 20 1 1. 34 11. 60 11. 35* 11. 20 11. 13

10 36. 25* 36. 28 36. 57 33. 50 15 02 12. 32 12. 19 12. 20 12. 34 12. 60* 12 33 12. 20 12. 13

11 37. 2:' 37. 2B 36. 57 .17. SO 15 02 13. 32 13. 19 13. 20 J3. 34 13. 60 13. 35 13. 20 13 13

12 38 25 38. 28 36. 57 17. :;0 15. 02 14. 32 14. 19 14. 20 14. 34* 14. 60 14. 35 14. 20 14. 13

13 39. 2~ 39. 28 36. 57 17.50 15. 02 15. 32 15. 19 15. 20 15. 34 15. 60 15. 35 15. 20 15. 13

14 1\0. 25 40. 28 20. 57 17.50 16. 02 16. 32 16. 19 16.20* 16. 34 16. 60 16. 35 16. 20 16. 13

15 41. 25 . 40. 28 20. 57 17. 50 17. 02 17. 32 17. 19 17.20 17. 34 17. 60 17. 35 17. 20 17. 13

16 42. 25 40. 28 20. 57 18. 50 18. 02 /18. 32 18. 19* 18.20 18. 34 18. 60 18. 35 18. 20 17. 13

17 43. 2~' 40. 28 20. 57 19. 50 19. 02 19. 32 19 19 19.20 19. 34 19. 60 19. 35 18. 20 17. 13

18 44. 25 24. 28 20. 57 20. 50 20. 02 20. 32* 20.- 19 20.20 20. 34 20. 60 19 35 18 20 17. 13

19 44. 2~ 24. 28 21. 57 21. 50 21. 02 21. 32 21. 19 21. Z!O 21. 34 20. 60 19. 35 lB. 20 1. 13

20 44. 25 24.28 22. 57 22. 50 22. 02 22. 32 22. 19 22.20 22. 34 20. 60 19. 35 2. 20 1. 13 21 44. 25 24. 28 23 57 23. 50 23. 02* 23. 32 23. 19 23.20 22. 34 20. 60 3. 35 2. 20 1. 13

24.20 ..,., 22 28. 25 24. 28 24.57 24. SO 24. 02 24. 32 24. 19 34 4. 60 3. 35 2. 20 1. 13

23 28. 25 25. 28 25.57 25. 50* 25. 02 25. 32 25. 19 24.20 22. 34 4. 60 3. 35 2. 20 1. 13 6. 34 4. 60 3. 35 2. 20 ., 24 28 2J 26. 28 26 57 26. 50 26. 02 26. 32 26. 19 24.20 13

25 44. 2~ 40.28 36. 57 33. 50 31. 02 28.32 26. 19 24.20 22. 34 20.. 60 19 35 lB. 20 17. 13

46
FOR026.DAT contains tow ID, region, tow time, temperature,

and number of eggs and age grouped by 24-h increments: 0-3, 4-27,

28-51,52-75, and 76-99 as S, A, B, C, and D-day categories for

each tow. The program assigns number 0 to an age if it is impossible to observe eggs that belong to such a day category for a given

time of tow. For example, S-day eggs are never observed at 1200

(Table 5a).

FOR029.DAT contains the same data as FOR026.DAT except

the age is not included and this file was formatted for the CalCOFI

data base for the SWFC (Table 5b).

FOR036.DAT contains tow ID, region, tow time, temperature,

and number of eggs and age for each stage by tow (Table 5c).

FOR037.DAT contains records in which at least one stage was

observed outside the normal range of expected time, i.e., t±G.

This file is useful for double-checking the accuracy of data on eggs

observed at unusual times (Table 5d).

FOR038. DAT contains tow ID and two variables: number of eggs

and age for A, B, and C-day eggs. The day categories with age

>2.5 d are excluded. Therefore, the total number of records is <3 x

the number of tows. This file can be used directly for regression

estimates of egg production and egg mortality rates (Table 5e).

Execution Instructions-The program may be executed interactively

or as a batch job. An example of a set of commands for VAX is

given below with input data file FILENAME:

$ASSIGN FILENAME FOR025

$RUN STAGEAGE

( ... enter I for each of the output files needed:FOR026,028,029,

036,037, and 038. Enter 2, otherwise.)

121211

(enter number of regions)

3

(enter max (CaICOFI) line number for each region, separated by

space.)

826 950 1500

This set of commands takes FILENAME as the input file and asks

for output files FOR026, 029, 037, and 038. Commands in parentheses are prompted by the machine. Other lines are inputs by the

user. The input and output data ftles for 1983 anchovy eggs are listed

in Tables 4 and 5 for illustration.

Table 4.-Partiallisting of input data file for 1983 northern anchovy eggs (N8302.DAT) for the computer program STAGEAGE. (Cruise no. is 8302; 8 was

deleted from printout.)

0-

'" ;S x 1J C

ci 0> '" V co

c ci LL LL E c E C, o .<: '" c 0 c a a .s:~ .<: ci. Egg stages .... _.... ;: V V .~B E .~ (Il co--- :0

'" U "'0> .... '" 0 n; n; co 0

'" .- 0> 00>

V I-- V V Cfl S~ ° I-- I-- II III IV V VI VII VIII IX X XI 0", I--~

302 1 733 500 0 1.000 030205 408 150 0 0 0 0 0 0 0 0 0 0 0 0 0 302 2 733 510 0 1. 000 830205 545 149 0 0 0 0 0 0 0 0 0 0 0 0 0

302 3 733 520 0 1.000 030205 631 149 0 0 0 0 0 0 0 0 0 0 0 0 0

302 4 733 530 0 1.000 030205 837 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 5 733 540 0 1.000 830205 1028 146 0 0 0 0 0 0 0 0 0 0 0 0 0

302 6 733 550 1 1.000 830205 1113 148 0 0 0 0 0 0 0 0 0 1 0 0 1

302 7 733 560 0 1. 000 830205 1159 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 8 733 570 0 1.000 830205 1245 150 0 0 0 0 0 0 0 0 0 0 0 0 0

302 9 733 580 0 1.000 830205 1328 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 10 733 590 0 1.000 830205 1416 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 t 1 733 600 0 1.000 830205 1633 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 12 741 600 0 1. 000 830205 1831 146 0 0 0 0 0 0 0 0 0 0 0 0 0

302 13 741 590 0 1. 000 830205 2035 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 14 741 580 0 1.000 830205 2109 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 15 741 570 0 1.000 830205 2144 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 16 741 560 0 1.000 830205 2231 147 0 0 0 0 0 0 0 0 0 0 0 0 0

302 17 741 550 1 1.000 830205 2328 146 0 0 0 0 1 0 0 0 0 0 0 0 1

302 18 741 540 1 1. 000 830206 20 146 0 0 0 0 0 0 0 1 0 0 0 0 1

302 19 741 530 1 1.000 830206 113 146 0 0 0 0 0 0 0 3 0 0 0 0 3

302 20 741 520 0 1. 000 830206 151 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 21 741 510 0 1.000 830206 228 149 0 0 0 0 0 0 0 0 0 a 0 0 0

302 22 741 500 0 1.000 030206 312 149 0 0 0 0 0 0 0 0 0 0 0 0 a 302 23 741 492 0 1. 000 030206 417 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 24 750 405 1 1.000 830;~06 619 146 0 0 a 0 0 0 0 0 0 0 0 0 0 302 26 750 500 1 1. 000 830206 1539 151 0 0 0 0 0 0 0 0 0 2 0 0 2

302 27 750 510 1 1. 000 830206 1717 151 0 0 0 0 0 0 0 0 0 0 0 0 0

302 29 750 520 1 1.000 830206 2232 151 0 0 0 0 0 0 0 0 0 0 0 0 0

302 30 750 530 1 1.000 030206 2311 148 0 0 0 0 0 0 0 0 0 0 0 0 0

302 31 750 540 1 1.000 030207 8 143 0 0 0 0 0 0 0 0 2 0 0 1 3

302 32 750 550 1 1.000 830207 49 143 0 0 0 0 0 0 0 0 0 2 0 0 2

302 33 750 560 1 1.000 030207 147 144 0 0 0 0 0 0 0 0 0 2 0 0 2

302 34 750 570 1 1. 000 830207 231 145 0 0 0 0 0 0 0 0 0 1 0 0 1

302 35 750 580 0 1. 000 830207 309 144 0 0 0 0 0 0 0 0 0 0 0 0 0

302 36 750 590 0 1. 000 830207 350 146 0 0 0 0 0 0 0 0 0 0 0 0 0

302 37 750 600 0 1.000 830207 441 146 0 0 0 0 0 0 0 0 0 0 0 0 0

302 38 758 600 1 1.000 830207 616 146 0 0 0 0 0 0 0 2 0 0 0 0 2 302 39 758 590 1 1.000 030207 720 146 0 0 0 0 0 0 0 2 0 0 0 0 2

302 40 758 580 1 1.000 830207 807 146 0 0 0 0 0 0 0 0 2 0 0 0 2

302 41 758 570 1 1.000 030207 852 144 0 0 0 0 0 0 0 0 0 0 0 0 0

47
Table 5a.-Partiallisting of output data file (FOR026.DAT) for 1983: Number of northern anchovy eggs and estimated ages (in

hours) grouped by 8(0-3 h), A(4-27 h), 8(28-51), C(52-75 h), D(76-99 h). Disintegrated eggs are obtained by subtraction. E-day

eggs (IOO-U3 h) are not observed for northern anchovy and thus are not included in the output. (Cruise no. is 8302.)

Ol

c: cO

ci t: Ol (.)

c: ci LL LL E c:

.;:; No. eggs and ages (h )/day catagories Ol c: 0 c: E- 0 ;; s;;: 0 Cl '" .~B Cii ;: U U e '0, ;: Ol OJ E s A B C 0 Cii Cii Ol U Ol o E 0 U 0 (fl '" Ol

I- U u ?;.e 0 rr: ..-';; l- N h N h N h N h N h I302 17 7'11 :):)0 1 1. 000 83020~ 1 2328 14 O. 1. 1. 2~. O. 48. O. 71. O. O. 1. 302 18 7'11 540 1 1. 000 830206 1 2420 14 O. 2. O. 20. 1. 50. O. 71. O. O. 1. 302 19 7'11 530 1 I. 000 830206 1 113 14 0 3 O. 20. 3. 51. O. 65. O. O. 3. 302 24 750 '1S5 1 1 000 830206 1 619 14 O. 0 O. 7. O. 37. O. 53. O. O. O. 302 26 750 ~OO 1 1. 000 830206 1 1539 15 O. 0 0 16. O. 41. 2. 62. O. O. 2. 302 27 750 510 1 1. 000 830206 1 1717 15 0 2. O. 19. O. 43. 0 64. O. O. 0 302 29 750 520 1 1. 000 030206 I 2232 15 0 2. O. 2'1. O. 48. O. 66. O. O. O. 302 30 750 530 1 1. 000 830206 I 2311 14 O. I. O. 19. O. 48. O. 71. O. O. O. 302 31 750 540 1 I. 000 830207 I 24 8 14 O. 2 O. 20. 2. 50. 0 71. O. O. 3. 302 32 750 550 1 I. 000 030207 I 2449 14 O. 2. O. 20. O. 49. 2. 69. O. O. 2. 302 33 750 560 I I. 000 030207 I .l 47 14 O. 3 0 20 O. 46. 2 57. O. O. 2 302 34 750 570 I I 000 U30207 1 231 14 O. 0 0 5. O. 34. I. ~7. O. 0 1. 302 38 758 600 1 I. 000 O:~O207 I 616 14 O. O. O. 7. O. 37. 2. 51>. O. O. 2 ~O2 39 758 590 1 1. 000 830207 I 720 14 O. O. 0 7. O. 34. ., 57 . 0 O. 2 302 40 758 580 1 1. 000 830207 I 8 7 14 O. O. O. 8. O. 35. 2. ~a. O. O. 2. 302 41 758 570 I 1. 000 830207 I 852 14 O. 0 O. 8 O. 35. O. 59. O. O. O. 302 42 758 560 1 I. 000 830207 1 934 14 O. O. 0 10. O. 36. O. 59. O. O. 0 302 43 750 550 1 I. 000 830207 1 1039 14 O. O. O. 11 O. 37. 2. 60. O. O. 2 302 44 758 540 1 1. 000 830207 1 1122 14 O. O. 0 11. 0 38. 2. 61. O. O. 2 302 45 758 530 I 1. 000 030207 1 12 0 15 0 0 O. 13. I. 38. I 62. O. O. 2 302 46 758 520 1 I. 000 830207 1 1235 15 0 O. O. 13 O. 38. 3 61. O. O. 3 302 47 758 510 1 1. 000 8:30207 I 1316 15 O. 0 O. 15. O. 40 O. 63. O. O. O. 302 49 758 495 1 I. 000 830207 I 1430 15 O. O. O. 16. O. 40. O. 63. O. O. O. 302 50 767 480 1 1. 000 030207 1 17 9 15 0 0 O. 17. O. 43. O. 6~ O. O. 0 302 51 767 '190 1 I. 000 030207 1 1828 15 O. 2. 0 20. I. 44. O. 64. O. O. I. 302 52 767 500 1 1. 000 830207 I 2046 15 O. 2. 0 23. O. 47 O. 66. 0 O. 0 302 53 767 510 1 I. 000 830207 1 2225 15 O. 2 3. 24 1. 48. O. 66. O. O. 4. 302 5.4 767 520 I I. 000 830208 I 2443 15 0 3. 0 21 O. 49. O. 54 O. O. O. 302 55 767 ~30 1 I. 000 830208 I 131 15 0 3. O. 22 O. 50. O. 5l1. O. O. O. 302 56 767 540 1 I. 000 830208 1 217 15 O. 0 O. 4. 1. 28. O. 53. O. O. 1. 302 57 767 550 1 1. 000 830208 1 3 6 15 O. O. 1. 5. I. 29. O. 53. O. O. 2. 302 58 767 560 1 1. 000 830208 1 528 15 O. O. O. 6. 1. 31 O. 54. O. O. I. 302 59 767 570 1 I 000 830208 .l 622 14 O. 0 O. 7. 1 32. O. 58. O. O. 1. 302 64 775 590 1 1. 000 a3020B I 1414 14 O. O. O. 15. 1. 38. O. 64. O. O. I. 302 65 775 580 1 1. 000 83C208 1 1453 14 O. O. O. 15. O. 41. O. 64. O. 0 O. 302 66 775 570 1 1. 000 030208 1 1529 15 0 0 0 11> O. 41. 1. 62. O. O. I. 302 67 775 560 ! I. 000 030208 1 1615 15 O. O. O. 17. I. 42. 1. 66. O. O. 2. 302 68 775 550 I I. 000 1130208 I 17 3 14 O. O. O. 18. O. 44. 0 67. O. O. O.

Table 5b.-Partial listing of output data file (FOR029.DAT). Number of northern anchovy

eggs grouped by 8(0-3 h), A(4-27 h), 8(28-51 h), C(52-75 h), D(76-99 h), and E(lOO-U3 h).

0

Ol E- x "0 c: e ;: ci Ol Ol U '0

c: ci U. LL E c E No. eggs/ Ol 0 ... .;:; e c c:

.~ C 0 0 ;; s;;:~

.;:; ci

3: u u .~E S 3: E day categories .~ en co '; OJ '" Ol "'Ol 0

'" Cii Ol U

'" 0 Ol °Ol U ?;.e .- Ol

I- U U Cf) 0 l- I- S A B C 0 E DOl I- Ol

-----

8302 19 741 530 1 1.00 830206 113 146 0 0 3 0 0 0 0 3 8302 2'1 750 485 1 1.00 830206 619 146 0 0 0 0 0 0 0 0 8302 26 750 500 1 1. 00 830206 1 539 151 0 0 0 2 0 0 0 2 8302 27 750 510 1 1. 00 830206 1717 151 0 0 0 0 0 0 0 0 8302 29 750 520 1 1. 00 830206 2232 151 0 0 0 0 0 0 0 0 8302 30 750 530 1 1.00 8302062311 148 0 0 0 0 0 0 0 0 8302 31 750 540 1 1. 00 830207 24 8 143 0 0 2 0 0 0 1 3 8302 32 750 550 1 1. 00 830207 2449 143 0 0 0 2 0 0 0 2 8302 33 7:)0 560 1 1.00 830207 147 144 0 0 0 2 0 0 0 2 8302 34 750 570 1 1. 00 830207 231 145 0 0 0 1 0 0 0 1 8302 38 758 600 1 1.00 830207 616 146 0 0 0 2 0 0 0 2 8302 39 758 590 1 1.00 830207 720 146 0 0 0 2 0 0 0 2 8302 40 758 580 I 1.00 830207 8 7 146 0 0 0 2 0 0 0 2 830;1 41 758 570 1 1.00 830207 852 144 0 0 0 0 0 0 0 0 8302 42 758 560 I 1.00 830207 934 144 0 0 0 0 0 0 0 0 8302 43 758 550 1 1.00 830207 1039 149 0 0 0 2 0 0 0 2 8302 4'1 758 540 1 1.00830207 1122 149 0 0 0 2 0 0 0 2 8302 45 758 530 1 1.0083020712 0 151 0 0 1 1 0 0 0 2 8302 46 758 520 1 1.00 830207 1235 151 0 0 0 3 0 0 0 3 8302 '17 758 510 1 1.00 830207 1316 153 0 0 0 0 0 0 0 0 8302 49 758 '19:) 1 1.00 830207 1430 150 0 0 0 0 0 0 0 0 8302 50 767 480 1 1.00830207 17 9 150 0 0 0 0 0 0 0 0 8302 51 767 '190 1 1.008302071828 151 0 0 I 0 0 0 0 1 8302 52 767 500 1 1.00 830207 2046 152 0 0 0 0 0 0 0 0 8302 53 767 510 I 1.00 830207 2225 151 0 3 1 0 0 0 0 4 8302 54 767 520 1 1.008302082443 152 0 0 0 0 0 0 0 0 8302 55 767 530 1 1.00 830208 131 152 0 0 0 0 0 0 0 0 8302 56 767 540 I 1. 00 830208 217 151 0 0 I 0 0 0 0 1 E!302 57 767 550 1 1.00 830208 3 6 151 0 I I 0 0 0 0 2 8302 58 767 560 1 1. 00 830208 528 151 0 0 I 0 0 0 0 1 8302 59 767 570 1 1. 00 830208 6;?i2 143 0 0 1 0 0 0 0 1 8302 64 775 590 1 1.00 830208 1414 145 0 0 1 0 0 0 0 1 8302 65 775 580 1 1.00830208 1453 145 0 0 0 0 0 0 0 0 8302 66 775 570 I 1.00830208 1529 153 0 0 0 1 0 0 0 1 8302 67 775 560 1 1.00830208 1615 151 0 0 1 1 0 0 0 2 8302 68 775 550 1 1.00830208 17 3 148 0 0 0 0 0 0 0 0 8302 69 775 540 1 1.00830208 1824 148 0 0 0 0 0 0 0 0 8302 70 775 530 1 1.008302082044 152 0 0 1 0 0 0 0 1 8302 71 775 520 1 1.008302082121 152 0 0 0 0 0 0 0 0 8302 72 775 510 1 1.00 830208 2315 152 0 0 0 0 0 0 0 0 8302 73 775 500 1 1.00 830209 2410 151 0 2 2 0 0 0 0 4 8302 74 775 495 1 1.00830209 150 149 0 7 1 0 0 0 0 8 8302 75 783 510 1 1.00830209 314 151 0 0 1 0 0 0 0 1

48
Table 5c.-Partial listing of output data file (FOR036.DAn. Number of northern anchovy eggs and estimated ages (in hours) are grouped by developmental stages

I-XI. (Cruise no. is 8302.)

"

c S .:S

ci - '" 0> " U

c ci LL E c LL -;; E c 2l c a a £~ 0 '+0 ci. No. eggs and ages (h )/egg stages

:J ;; U U .~B 'e;, ;; E 0

'" '" CIl 0

'" " 0 CIl U f- U U cil ~~ 0 a: f- f- II III IV V VI VII VIII IX X XI

302 19 741 ~30 1 1. 000 B30206 113 14 O. 3. O. 4. O. 23. O. 27. O. 27. O. 30. O. '1. 3. '1. O. '1. O. 57. O. 73. 302 24 7'0 4B' I 1. 000 83020b 619 14 O. 4. O. B. O. B. O. 31. O. 32. O. 32. O. ~1. O. '6. 0 56. O. 57. O. 61. 302 26 7>0 '00 I 1. 000 83020b 1'39 I' O. O. O. II. 0 17. O. 17. O. 19. O. 41. O. 41. O. 41. 0 41. 2. b2. O. 65 302 27 7>0 "0 I 1. 000 830206 1717 I' O. O. O. 3. O. 19. O. 19. O. 19. O. 42. O. 43. O. 43. 0 43. O. 62 O. bb. 302 29 7'0 520 1 I. 000 830206 2232 15 O. O. O. 3. O. 21 O. 24. O. 24. O. 26. 0 46. O. 4B. O. 48 O. 50. O. 66. 302 30 750 530 I 1. 000 830206 2311 14 O. I. O. 4. O. 23. O. 25. O. 2~. O. 46. O. 49. O. 49 O. 49. O. 69. O. 73. 302 31 750 540 I I. 000 830207 24 B 14 O. 2. O. 4. O. 23. O. 26. O. 26. O. 46. O. 50. O. ~O. 2. 50. O. 69. O. 73. 302 32 750 550 I I. 000 830207 2449 14 O. 2. O. 4. O. 23. O. 26. o. 26. O. 46. O. 50. O. 50. O. 50. 2. 69. O. 73. 302 33 750 560 I I. 000 830207 147 14 O. 3. O. 4. O. 23. O. 27. O. 27. O. 30. O. 51. O. 51. O. 51. 2. ~7. O. 73. 302 34 7~0 570 I 1. 000 830207 231 14 0 4 O. 4. O. 7. O. 28. 0 28. O. 30. O. '1. 0 52 0 52 I. 57. O. 73. 302 3B 75B 600 I 1. 000 830207 616 14 O. 4 O. B. O. B. O. 31 O. 32. O. 32. O. ~1. 2. '6 0 56 0 ~7 0 61 302 39 75B 590 I I. 000 830207 720 14 O. 4. O. 9. O. 9. O. 31. O. 33 O. 33. O. 39. 2. ~7. 0 ~7 0 ~7. O. 61. 302 40 7~B 5BO 1 1. 000 8:.30207 B 7 14 O. 4. 0 10. O. 10. O. 31. O. 34. O. 34. 0 39. O. 57. 2. 59 O. 58. O. 61. 302 41 75B 570 1 1. 000 030207 a'2 14 o. 4. O. 10 O. 10. O. 31. O. 34. O. 34. O. 39. 0 57. 0 58 0 5B O. 61. 302 42 7~B 560 1 I. 000 030207 934 14 O. 4. O. 11. O. 11. O. 1'. O. 3=:'. O. 35. O. 39. O. ~7. 0 59. O. 59. O. 61. 302 43 75B ~~o I I. 000 B30207 1039 14 0 4 0 12. O. 12. 0 I' O. 36. O. 36. O. 39. O. 57. 2 60 0 bO. O. 61. 302 44 758 540 I I. 000 830207 1122 14 0 4. O. 12. O. 13. O. 15. O. 37. O. 37. O. 39. O. 57 2 61 0 61. O. 61. 302 45 75B 530 I I. 000 030207 12 0 15 O. O. 0 II. O. 14. O. 14. O. 35. I. 3B. O. 3B. O. 40. 0 61 I. 62. O. 62. 302 46 7~B ~20 I I. 000 830207 123' 15 O. O. 0 11. 0 14 O. 14. O. 35. O. 3B. O. 3B O. 40. 2 61 I 62 0 62. 302 47 75B 510 I I. 000 030207 1310 15 0 O. O. 11. O. 15. O. 15. 0 19. O. 39. 0 39 O. 40 0 41. O. 62 0 63. 302 49 75B 49~ I I. 000 830207 1'130 15 O. O. O. 11. O. 16. O. 16. O. 19. O. 40. O. 40. 0 40 O. 41 0 62. O. 64. 302 50 767 4BO I I. 000 030207 17 9 15 0 O. 0 11 0 19. O. 19. O. 19 O. 42 O. 43. O. 43. O. 43. O. 6~. O. 66. :t02 51 767 490 I 1. 000 030207 1828 15 O. O. O. 3. O. 20. O. 20. O. 20. O. 42. I. 44. O. 44. 0 44. 0 62. O. 66 302 52 767 '00 1 I 000 830207 2046 I' O. 0 O. 3 0 21. O. 22. 0 22. O. 26. O. 46. O. 46 0 "'. 0 ~iO 0 66 302 53 767 510 I 1. 000 030207 222~ I' O. O. O. 3. O. ..1. 3 24. O. 24. O. 26. O. 46. I. 4B 0 48 0 ~O. 0 66. 302 54 767 520 1 I. 000 830208 2443 I' O. 2 o. 3 O. 5 O. 26. O. 26 O. 26 O. 46. O. 50 0 50 0 ~iO 0 54. 302 55 767 530 I 1. 000 83020B 131 I' O. 3. O. 3. O. 5. O. 27. O. 27. O. ~7. O. 46. O. ~1. 0 51. 0 51 0 ~4.

302 56 767 540 I I. 000 830208 217 I' O. 4. O. 4. O. ,. O. 2B. 1. 28. O. 2B. O. 34. o. 52 0 '2 0 52. 0 ~4.

302 ~7 767 550 1 I. 000 830208 3 6 15 O. 4. I. 5. o. 5. o. 2B. I. 29. O. 29. O. 34. O. 52 0 ~3 0 53 0 54. 302 5B 767 ~60 I I. 000 830208 52B 15 O. 4. 0 7. O. 7. 0 28. 1. 31. O. 31. O. 34. O. 52 0 55 0 5~1 O. 55. 302 59 767 ~70 I 1. 000 830208 622 14 o. 4. 0 B O. B. O. 31. 1. 32. O. 32. O. 51. O. 56 0 56 0 0j'! O. 61. 302 64 77~ 590 1 I. 000 030208 1414 14 O. O. O. 12 O. 16. O. 16. I. 3B. O. 40. 0 '0. O. 45 0 64 0 64. O. 64. 302 65 775 ~BO 1 I. 000 830208 1453 14 O. O. O. 12. O. 16. O. 16. O. 3G. O. 40. O. 40. O. 45 a 64. 0 64 0 64. 302 66 775 570 I ,. 000 030208 1~29 15 0 O. 0 11. 0 17. 0 17. O. 19. 0 41 O. 41. O. 41. 0 41. I 6~ 0 65. 302 67 775 '60 I I. 000 830~08 Ibl~ 15 O. 0 O. 11 0 lB. O. lB. O. 19. O. 42. I. 42. O. 42 0 4 ~.~ 0 b2 I. 66 302 6B 775 ~50 I 1. 000 83020A 17 3 14 O. O. 0 12. O. 19. O. 19. O. 22. O. 43 0 43. O. 45 0 67 0 67 0 67 302 69 775 540 1 I. 000 030208 1824 14 O. 0 O. 12 O. 20. O. 20. O. 22. O. 44. O. 44. O. 45 0 67 O. 6B 0 68. 302 70 775 530 1 I. 000 8:"]0208 2044 15 O. 0 O. 3. O. 21. 0 22. O. 22. 0 42. O. 46. I. 46 0 46 0 50 O. 66. 302 71 775 520 1 I. 000 830208 2121 15 O. O. O. 3. O. 21. O. 23. O. 23. O. 26. O. 46 O. 47 0 47 0 ~IO O. 66 302 72 775 510 1 I. 000 830208 2315 IS 0 I. O. 3 O. 21. O. 25. O. 25. 0 26. 0 46. O. 49 0 49. 0 50 0 54 302 73 775 500 1 1 000 830209 2410 15 0 2. O. 3 0 5. 2. 26. O. 26 O. 26. O. '6 0 ~o 2 50 0 :;0 0 54. 302 74 775 495 I I 000 030209 150 14 O. 3. §. 4. 0 2:3. O. 27. 5. 27. O. ~O 0 51. 0

" 1 51 0 51 O. 73. 302 75 7B3 510 I I. 000 B30209 314 15 0 4. 5. 0 5. O. 2B. O. 29 O. 29 1. 34. 0 ~,2 0 53 0 ~,J 0 54.

Table Sd.-Partial listing of the output data file (FOR037.DAT): estimated age (h) and number of northern anchovy eggs

for those egg stages observed within or beyond the normal ranges of expected tow time (T±G, see text). (Cruise no. is 8302.)

" ;; c .... .... '" B

0 - 0) .:S .~ .~ 0>

C Q) 0) u c ci LL LL E '+0 c .:S " 0> Q) ,,- 0> .... £

"~ c a a £~ 0 ci. '" " Ql "0 0_ "0> "0) ;; u u .~E 'e;, ;; " E ;; '" c.", 2 ... " " 0)

0 ci ~E '" '" .... Q) 0

'" Q) o E " '" 0 ..... c. ..... 0> U f- U U en ~~ 0 a: ~.;; f- w -10 ::>0 w Z W"+:'

302 26 750 500 1 I. 000 930206 1 15 39 t5 62 50 62 10 2. 6. 302 32 7:10 :1:10 I I.' 000 U30207 1 ;/4 49 14 69 :17 69 10 2. 13. 302 33 7:10 :160 1 I. 000 830;!O7 1 1 47 14 :17 :17 69 10 2. 13.

302 34 7:10 :170 1 1. 000 B30207 1 2 31 14 :17 :17 69 10 1. 13.

302 39 758 590 1 I. 000 B30207 1 7 20 14 :17 4:1 :17 8 2. 2. 302 4:1 7:18 :130 1 1.000 830207 1 12 0 1:1 62 50 62 10 1. 6. 302 46 7:18 :120 1 1.000 830207 1 12 3:1 1:1 61 41 61 <;> 2. 1. 302 46 7:18 :;2C 1 1. 000 B30207 1 12 3:1 1:1 62 :;0 62 10 1. 6. 302 64 77:1 :190 1 1. 000 830208 1 14 14 14 38 22 38 5 1. 4. 302 66 77:1 :;70 1 1. 000 830208 1 1:1 2<;> 1:; 62 :;0 62 10 1. 6. 302 67 775 :;60 1 1.000 830208 1 16 1:; 15 66 :14 66 11 1. 10. 302 74 775 495 t 1. 000 830209 1 1 50 14 4 4 12 2 2. 6. 302 7:; 7B3 ~10 1 1. 000 B30209 1 3 14 I:; 34 34 46 7 1. 14. 302 76 7B3 :;20 1 1.000 830209 1 4 :l 1:1 34 34 'II. 7 1. 14. 302 B6 791 :;90 1 1.000 B30209 1 12 43 1:1 62 :10 62 10 2. 6. 302 92 791 :;30 1 1. 000 B30209 1 16 4:1 1:1 42 26 42 6 3. 8. 302 92 791 :;30 1 1.000 830209 1 16 45 1:1 62 0;0 62 10 3. 6. 302 9B BOO :;40 t 1.000 8302tO 1 4 12 15 4 0 4 1 3. 24. 302 98 BOO :;40 1 1.000 830210 1 4 12 I:; 52 40 :.'52 8 2. 20. 302 100 800 560 I 1.000 830210 1 9 0 15 11 3 It 2 3. :I. 302 100 BOO :;60 1 1. 000 030210 I 9 0 I:; 3:1 19 1:1 5 2. 1. 302 102 800 580 1 1.000 030210 1 11 30 15 11 3 11 2 1. 5. 302 100 80B ::;70 1 1. 000 B302tO 1 19 :;3 t:J 66 54 66 11 I. JO. 302 133 817 580 1 1.000 830214 1 2 33 I:; 4 0 4 I 10. 24. 302 133 817 :;80 I 1.000 830214 1 :2 33 15 28 12 28 4 3. 18. 30? 133 817 580 t 1. 000 830214 1 2 33 1:1 34 34 46 7 1. J4. 30? 133 8t7 580 I 1.000 830214 1 2 33 15 52 40 52 8 I. 20. 302 134 817 590 t 1. 000 830214 1 3 10 15 4 0 4 1 2. 24. 302 139 825 570 1 1.000 B302J4 1 7 20 15 4 0 4 1 1. 24. 302 t46 825 490 1 1. 000 0302t4 1 12 32 t5 61 41 61 9 1. 1. 302 15:; 833 406 1 t.OOO 030214 2 t9 36 15 0 0 4 1 10. 24. 302 1:;5 B33 406 1 1. 000 830214 2 19 36 15 3 3 11 2 4. :J. 302 165 841 450 1 1. 000 8302t5 2 9 20 t6 10 2 10 2 11. 4. 302 165 84t 450 1 1.000 830215 2 9 20 16 56 44 56 10 5. 24. 302 165 841 450 t 1. 000 830215 2 9 20 16 59 47 59 It 3. 3. 302 166 84t 440 1 1.000 33021' 2 to 5 16 59 47 59 11 3. 3. 302 172 850 410 I I. 000 830215 2 16 0 16 42 30 42 7 2. 10. 302 173 850 4~O t 1.000 030215 2 16 35 16 42 30 42 7 4. 10. 302 t70 850 470 1 1.000 830215 2 20 :;4 15 0 0 4 1 1. ~4.

302 17B 850 470 1 1. 000 830215 2 20 54 15 3 3 11 2 1. :J. 302 178 850 470 t 1. 000 830215 2 20 54 1:J 66 54 66 11 2. 10. 302 179 850 480 1 1.000 830215 2 22 20 15 0 0 4 1 2. 24.

49
DISCUSSION _

The automated procedure should be fully tested before being implemented. For the anchovy egg data, 1980-83 data of aged eggs from

both manual and automated procedures were compared based upon

positive tows (tows with at least one egg sampled) (Table 6). Although there were some differences between the results of these two

procedures, the results from the automated procedure are encouraging. The differences are due to different methods of age assignment and to subjective elements in the manual age assignment

method. In the manual system, day category (S, A, B, C, D, and

E) was first assigned to eggs (Stauffer and Picquelle 1985). An actual age was then computed based upon the time of tow (k) and day

category:

where f = 0,1,2, ... for A,B,C, ...-day eggs. In the automated

system, the age was assigned according to Equation (7) before the

day category was assigned. Equation (8) yields a range of ages larger

than that from Equation (7) and thus gives larger values for maximum ages. This difference affects the ages of older eggs, particularly

in the case where eggs older than 2.5 d are excluded in computation of egg mortality. For example, at temperature 15°C, the maximum age for stage XI is 66 h using Equation (7), and the maximum age is 72 h using Equation (8) for eggs that were sampled

at 0100. Thus, more eggs would be assigned to older age groups

when Equation (8) was used rather than Equation (7). The subjectivities of human judgment or human errors of the manual system

are evident in several steps in the manual methods. These include

1) misassignment of age from the key structure due to inexperience

or the fatigue of the worker; 2) determination of age for eggs which

were observed at a time significantly different from the expected

time (Table 2); and 3) assignment of age to eggs observed around

0200 which is the break point of A, B, C, D, and E-day categories

(Fig. 2).

To adopt the program for other species would require 1) a model

for the temperature-dependent egg development, e.g., Equation (4);

2) the distribution of age within each egg stage to obtain G in Equation (6); and 3) the peak spawning time (Sf) for Equation (5), so

that a reference table can be constructed which is the base of the

automated procedure.

lllble Se.-Partiallisting of data file (FOR038.DAT): Number of eggs

and age (in days) excluding eggs >2.5 d old. (Cruise no. is 8302.)

.,

e

0 --0

e 0 U. U. '" ., > 5l e 0 0 .0 '" :J ;: U U e E '" .,"0

0 iii iii '" :J Ol Ole U I- U U 0 Z~ <t:.:o

302 6 0733 0550 830205 0 0000 O. 4583

302 6 0733 0550 830205 O. 0000 I. 5694 302 6 0733 0550 830205 I. 0000 2. 5417

302 17 0741 0550 830205 I. 0000 I. 0417 302 17 0741 0550 830205 O. 0000 2. 0104

302 17 0741 0550 830205 O. 0000 2. 9583 302 18 0741 0540 830206 O. 0000 O. 8229

302 18 0741 0540 830206 1. 0000 2. 0833

302 18 0741 0540 830206 O. 0000 2. 9583 302 19 0741 0530 830206 O. 0000 O. 8438

302 19 0741 0530 830206 3. 0000 2. 1250

302 19 0741 0530 830206 O. 0000 2. 7083

302 24 0750 0485 830206 O. 0000 O. 2778

302 24 0750 0435 830206 O. 0000 1. 5208

302 24 0750 0485 830206 O. 0000 2. 3958

302 26 0750 0500 830206 O. 0000 O. 6667 302 26 0750 0500 830206 O. 0000 1. 7083

302 26 0750 0500 830206 2. 0000 2. 5833

302 27 0750 0510 830206 O. 0000 O. 7917

302 27 0750 0510 830206 O. 0000 I. 7813

302 27 0750 0510 830206 O. 0000 2. 6667 302 29 0750 0520 830206 O. 0000 O. 9896

302 29 0750 0520 830206 O. 0000 2. 0000

302 29 0750 0520 830206 O. 0000 2. 7500

302 30 0750 0530 830206 O. 0000 0 8021

302 30 0750 0530 830206 O. 0000 2. 0104

302 30 0750 0530 830206 O. 0000 2. 9583

302 31 0750 0540 830207 O. 0000 O. 8229

302 31 0750 0540 830207 2. 0000 2. 0833

302 31 0750 0540 830207 O. 0000 2. 9583

302 32 0750 0550 830207 O. 0000 O. 8229

302 32 0750 0550 830207 O. 0000 2. 0417

302 32 0750 0550 830207 2. 0000 2. 8750

302 33 0750 0560 830207 O. 0000 O. 8438

302 33 0750 0560 830207 O. 0000 1. 9063

302 33 0750 0560 830207 2. 0000 2. 3750

302 34 0750 0570 830207 O. 0000 O. 2083

302 34 0750 0570 830207 O. 0000 I. 4271

302 34 0750 0570 830207 I. 0000 2. 3750

302 38 0758 0600 830207 0 0000 O. 2778

302 38 0758 0600 830207 O. 0000 1. 5208

302 38 0758 0600 830207 2. 0000 2. 3333

:;102 39 0758 0590 830207 O. 0000 O. 3056

302 39 0758 0590 830207 O. 0000 1. 4167

302 39 0758 0590 830207 2. 0000 2. 3750

302 40 0758 0580 830207 O. 0000 O. 3333 302 40 0758 0580 830207 O. 0000 1. 4375

age = k+2+24Xf (8)

Table 6.-Number of northern anchovy eggs per tow grouped by days S(0-3

h), A (4-27 h), B (28-51 h), C (52-75 h), and D (76-99 h) from the manual

system (m) and the proposed automated system (a) for each year in 1980-83.

No. eggs/day categories Disintegrated No.

S' A B C 0 eggs Total' tows] ._--

1980 m 2.72 13.65 8.86 4.91 0.16 0.82 31.14 312

a 2.61 13.74 9.78 4.08 0.03 30.24

1981 m 2.76 12.32 10.33 6.91 0.47 0.85 33.72 564

1.81 13.86 12.00 4.98 0.13 32.78

1982 m 2.49 9.00 7.00 4.44 0.31 0.89 24.23 308

a 1.13 10.50 7.77 3.78 0.16 23.34

1983 m 1.95 9.16 8.42 2.88 0.002 0.67 23.07 482

a 2.01 9.31 8.51 2.61 22.44

'S eggs from manual system (m) include some disintegrated eggs.

2Difference between "m" and "a" is the disintegrated eggs which were included

in I'm," but not in "a."

'Positive tows only.

50

LITERATURE CITED _

HEWITT. R., A. BINDMAN, and N. LO.

1984. Procedures for calculating the egg production estimate of spawning biomass. Natl. Mar. Fish. Serv., NOAA, Southw. Fish. Cent., La Jolla. CA,

Admin. Rep. U-84-19, 46 p.

LO, N. C. H.

1983. Re-examination ofthree parameters associated with anchovy egg and larval

abundance: Temperature dependent incubation time, yolk-sac growth rate and

egg and larval retention in mesh nets. Natl. Mar. Fish. Serv., NOAA, Southw.

Fish. Cent., La Jolla, CA, NOAA-TM-NMFS-SWFC-31.. 33 p.

MOSER, H. G., and E. H. AHLSTROM.

1985. Staging anchovy eggs. In R. Lasker (editor), An egg production method

for estimating spawning biomass of pelagic fish: Application to the northern

anchovy, Engraulis mordax, p. 37-41. U.S. Dep. Commer., NOAA Tech.

Rep. NMFS 36.

STAUFFER, G., and S. PICQUELLE.

1985. Procedures for sorting, staging, and ageing eggs. In R. Lasker (editor),

An egg production method for estimating spawning biomass of pelagic fish:

Application to the nonhern anchovy, Engraulis mordax, p. 33-35. U.S. Dep.

Commer.• NOAA Tech. Rep. NMFS 36.

ZWEIFEL. J. R., and R. LASKER.

1976. Prehatch and posthatch growth of fishes-A general model. Fish. Bull.,

U.S. 74:609-621.
A Protocol for Designing

a Sea Survey for Anchovy

Biomass Assessment

ROGER P. HEWITTI

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

The objective of obtaining a representative sample of the adult northern anchovy

population, for the purposes of determining reproductive status, is discussed.

Several considerations affecting this objective are listed, including deterioration

of tissue, vulnerability to sampling gear, geographic variability in reproductive

behavior, logistic limitations, and secondary indicators of the presence of fish.

The timing and duration of a survey, the laboratory equipment required, and

potential problems are discussed. Specific specifications for a desired survey vessel

are also outlined including sea day capability, gear operations, vessel speed, personnel, storage, work space, and cruise plan.

'Present address: Commanding Officer, NOAA Ship Miller Freeman, Pacific

Marine Center, 1801 Fairview Ave. E., Seattle, WA 98102.

51

SEA SURVEY DESIGN

AND METHODS _

Collection Gear Requirements

The primary requirement for trawl collection gear is that it provides a representative sample of the adult anchovy population.

Because it is the average fish that is of interest, rather than the average

location, sampling density should parallel the density of fish. Thus,

relatively fewer samples need be taken in sparsely populated waters

near the edge of the range; however, these areas must be covered

sufficiently well to confirm the extent of the range. Adult sampling

should coincide as much as possible with the time and area of egg

samples. Several considerations make this requirement difficult to

achieve. These considerations include:

I) Fish must be preserved in a fresh condition so that histological

criteria may be used to determine their reproductive status. The

Southwest Fisheries Center currently requires that tissue be fixed

within an hour of being caught, and this appears to be adequate.

(Adult surveys conducted with a purse seiner off Peru extended this

period to 2 h without adverse consequences; 1. Alheit2

.) Because

it is not possible to determine when a fish was captured, trawls must

be of short duration so as to set and retrieve the net, subsample the

catch, expose the gonads, and preserve the fish within the specified

time period. The same must be required of alternative sampling gears

such as purse seine or lampara nets.

2) Some portions of the adult population may be more vulnerable

to capture than others; catches may vary with sampling gears, with

time of day, and with reproductive status. In 1981, actively spawning female Engraulis mordax were oversampled with a trawl relative

to females which had spawned the day before; purse seine catches,

paired with the trawls, yielded equal proportions of active and postactive spawners. The sex ratio, determined from the trawl sample,

was biased (towards males) only during the hours of spawning

whereas the purse seine selectively caught females regardless of the

time of day. The 1982 trawl survey caught equal proportions of active and postactive spawners although the sex ratio changed during

the hours of spawning favoring the males (Picquelle and Hewitt,

1983). In contrast, a 1981 purse seine sample of Peruvian anchovy,

Engraulis ringens, obtained off Peru oversampled actively spawning females as well as showed a' diurnal pattern in the sex ratio of

caught fish (Alheit et al., 1984). Furthermore, a comparison of the

distribution of actively spawning females with a binomial distribution suggested that the fish were not independently distributed in

the collections; fish which had spawned the day before appeared

to be independently distributed. It was concluded from these observations that males and actively spawning females segregate out from

other females duri.ng the peak hours of spawning at a depth (or an

area) where they are more vulnerable to the trawl (Alheit et aI.,

1984). This behavior appears to begin early in the day before the

ovaries hydrate and ends a few hours after spawning.

Bias due to gear selectivity, temporal or geographic distribution,

or fish behavior should be watched for. Because it is not always evident, every set of adult collections should be checked for possible

bias. Sampling gears and procedures should be modified so as to

minimize potential bias. The ideal sampler is one that is' invisible

to the fish, to preclude avoidance, and one that samples through

the entire vertical range of their distribution. If the source of bias

cannot be eliminated, it may be corrected by use of appropriate

availability factors and/or statistical stratification. If size of fish

2J. A1heit, Pappelweg 32, 5400 KobleD2, West Germany, pers. commun. August 1983.
follows an oceanographic or geographic pattern, the samples must

cover the range. For fishes which spawn very locally in time or space,

representative sampling may be difficult, while for widely distributed

spawners representative sampling may not be difficult to achieve.

3) Spawning may occur in areas where it is difficult to sample the

adults. These include the nearshore and othershallow water zones

where there is not sufficient depth to fish a trawl or set a purse seine

net. Engraulis mordax spawns in the nearshore zone with the same

intensity as observed throughout its habitat (Hewitt and Brewer,

1983); however, the reproductive output of adults in this zone must

be inferred because of the difficulty in sampling there. It may be

necessary to choose a sampling gear, which can be deployed in

shallow or obstructed areas (such as a lampara net), for those populations that deposit a large portion of their spawn in shallow waters.

4) Time and personnel requirements must also be considered when

selecting a sampling gear. As mentioned above, a gear should be

eliminated if it cannot be set, retrieved, and the catch preserved

in less than a specified time period. The vessels available and their

speed of travel between stations may be determined by the choice

of sampling gear. In general, a purse seine requires more people

to deploy than does a trawl; however, there may be considerable

variation between boats. One to two people are required to ~ubsample

and preserve the catch in addition to the personnel necessary to fish

the gear.

Secondary information may be useful for improving sampling efficiency, but care must be taken not to cause unrepresentative sampling. For example, presence of eggs in the plankton tows indicates

presence of fish, but absence of eggs does not imply absence of fish.

Adult samples from areas of low spawning rates may be very important in obtaining a good biomass estimate. Secondary information may improve trawl success rates. Such information may include

signs of fish encountered during recent survey operations, signs of

predators, and results of other observers such as the fishery, airplane

pilots, or other concurrent research cruises. Iffish behavior is known,

oceanographic information on water temperature, clarity, etc., may

provide useful clues to presence and absence of fish.

It is highly recommended that adult collections be examined for

evidence of avoidance and selectivity. In this regard, it is a good

practice to sample the catch for age composition. This information

may be used as additional criteria to compare gears, geographic

areas, and time of day.

SURVEY TIMING AND DURATION _

The timing of the survey should be based on biological information. The survey should be conducted during peak spawning activity

of the adults. The number ofsamples required to estimate the spawning fraction increases exponentially as that fraction decreases (P.

E. Smith3) so that the additional cost of sampling outside the spawning season rapidly becomes unacceptable. It is absolutely necessary

that adult sampling be conducted simultaneously with egg sampling,

either on the same vessel or on different vessels working in the same

vicinity.

The duration of the survey depends on logistical considerations.

These include area ofthe survey, desired sampling intensity, distance

between stations and speed of the vessel, and fraction of the day

available to conduct adult sampling. If more than one vessel is

available, sampling may be conducted 24 hours/day, which would

'P. E. Smith, Southw. Fish. Cent., Natl. Mar. Fish. Serv., NOAA, La Jolla, CA

92038, pers. commun. Sept. 1983.

52

allow more stations to be occupied in the same amount of time.

However, the fish may be less catchable during daylight hours, either

because they are deeper or because they can better avoid the net.

As with the choice of gear. a compromise must be made between

quantity and quality of the data (i.e., precision and accuracy).

EQUIPMENT AND SUPPLIES _

Adult sampling equipment can be divided into two general categories: Sampling gear and laboratory supplies. Sampling gear is

usually specific to the vessel employed for the survey and is discussed

below under "Vessel Requirements." Laboratory equipment refers

to everything necessary to subsample the catch and preserve the

specimens: buckets for subsampling, preserving solution, labels,

data sheets, and specimen jars. Also useful are a small scoop,

specimen jar rack, dissecting scissors, small spatula, forceps, and

a hand digital logger with at least three registers (e.g., blood cell

counter). The survey should be planned in enough detail to take

the proper amount ofsupplies. Because space on a vessel is usually

at a premium and because running short of supplies is also costly,

it is r:::commended that ~xtra supplies be kept onboard.

SOURCES OF ERRORS, BIASES,

AND POTENTIAL PROBLEMS _

The most serious source of bias is the selectivity of adult fish sampling gear. As discussed above, suspected biases should be investigated and. if necessary, changes should be made to the gear and/or

sampling procedures. A representative sample is achieved when each

adult fish has an equal probability of being caught by the sampler;

if ripe females are more vulnerable to capture than the rest of the

adult population or if fish were more able to avoid the net during

':;,'main times of the day, then a representative sample is not achieved,

amI this fact must be considered. In the survey for Engraulis mordax, where these problems were encountered, ripe females were

eliminated from the calculation of the spawning fraction and adult

sampling was conducted during only a portion of the day.

Error may be introduced when there is geographic heterogeneity

in spawning and homogeneous sampling. Close examination of the

results and postsurvey stratification, if indicated, is the most direct

method of reducing this error. Error may also be introduced when

subsampling the catch aboard ship (e.g., an inadvertent preference

for large fish); this may be reduced by devising a systematic procedure for selecting fish. Finally, it is important to clean the net

between sets; fish can get caught in the webbing and become part

of the apparent catch of a subsequent set. Off California, pelagic

red crabs sometimes contaminate the catch and abrade the fish; these

fish cannot be distinguished from the residual of a previous trawl

unless the net is thoroughly flushed between sets.

VESSEL REQUIREMENTS _

Because the survey vessel is the most important piece of equipment

to be specified, it is prudent to consider the requirements in some

detail. The following subsections outline the minimum considerations. Additional specifications and detail in planning will aid in

the conduct of the survey. It is impossible to prepare too much.
Sea Days Capability

The vessel must be able to take on sufficient provisions and fuel

to conduct a major portion of the survey without returning to port.

A minimum two-week capability should be required to maintain

survey continuity and to obtain samples in a reasonably short period

of time. Bear in mind that a port call involves travel time to port,

time in port, and travel time back to the next station; delays in sampling can easily become longer than originally anticipated.

Gear Operations

The vessel should be equipped with the specified adult sampling

gear rather than bringing new gear aboard. The gear should be clean

and in good operating order. The vessel's crew should be proficient

in deploying and retrieving the gear as well as repairing minor

damage to the net without returning to port. If members of the scientific party will be required to help operate the gear, the number of

people and their duties should be clearly specified.

The winch requirements (as outlined above for egg sampling)

should be clearly specified and stressed as critical to the conduct

of the survey. Other requirements include provisions for measuring

the wire angle and washing down the net.

It is most important that any collection operations (egg or adult)

which involve the cooperation of the crew and the scientific party

be discussed thorougWy and even practiced before the survey begins.

Vessel Speed

Knowledge of the vessel's speed is a key element in the planning

of a survey because a major portion of time is spent underway between stations. Speed will vary according to sea conditions and the

loading of the vessel; however, a realistic estimate of the expected

average speed is very useful. The survey may be planned first and

a minimum vessel speed specified as a criterion for vessel selection.

Personnel

The primary requirement for the vessel personnel is that they be

adequate in number and sufficiently skilled to accomplish the

specified operations. Competence in navigation should be a major

requirement; this not only involves human skill but the proper equipment as well. It should be specified that each station must be accurately located and that it is not sufficient to know only the vessel

position relative to port or land. As noted above, vessel personnel

should know how to operate and repair the adult sampling gear.

Supplies and Specimen Storage

The vessel must have adequate space dedicated to dry storage of

sampling supplies and specimens. These requirements must be

calculated from the survey plan and can be considerable, particularly

for the adult fish specimens. In addition to dry storage, storage space

on deck may be specified for sampling gear and freezer storage may

be necessary for some specimens.

53

Laboratory and Work Space

The vessel must have a covered space, well lit and well ventilated,

that can be dedicated for use in processing specimens; running water

and a drain are essential. Sufficient work space must exist on deck

to store and deploy the egg samplc:r and the adult sampler, to remove

their catches, and to subsample in the case of adult catches.

CRUISE PLAN

AND WORK SCHEDULES _

A cruise plan, distributed to all personnel involved (vessel crews

and scientific parties) greatly increases the chance for a successful

survey. Such a plan should include a brief statement of the cruise

objectives, schedule of port calls, map of the stations and the order

in which they are to be occupied, activities to be accomplished at

each station, list of the personnel participating and those in charge,

and a list of the equipment necessary to accomplish the objectives.

Work schedules should also be made and distributed prior to the

cruise. These schedules alert participants as to when they will be

working and what they will be doing so that they may be prepared.

Careful thought should be given to how many people will be required on each vessel and whether the vessel can accommodate them.

As an example, conducting operations 24 hours a day will require

two or three work shifts for egg sampling, plus additional people

for adult sampling. Each shift should have a designated leader, and

one person, either from the crew or from the scientific party, should

be in charge of adult sampling operations.

The value of a good plan cannot be emphasized enough. The plan

should convey to all participants a clear, concise statement of what

is to be accomplished on the cruise and how it is to be done. It should

give the impression that a considerable amount of thought and

preparation has already been done, and what remains is to carry

out the plan. A survey cruise rapidly becomes tedious as the same

operations are performed over and over; the plan helps people mark

time and keep track of progress.

LITERATURE CITED _

ALHEIT, 1., V. H. ALARCON, and B. 1. MACEWICZ.

1984. Spawning frequency and sex ratio in the Peruvian anchovy, EngrauliJ

ringens. Calif. Coop. Oceanic Fish. Invest. Rep. 25:43-52.

HEWITT, R. P., and G. D. BREWER.

1983. Nearshore production of young anchovy. Calif. Coop. Oceanic Fish. Invest. Rep. 24:235-244.

PICQUELLE, S. 1., and R. P. HEWITT.

1983. The northern anchovy spawning biomass for the 1982-83 California fishing

season. Calif. Coop. Oceanic Fish. Invest. Rep. 24:16-28.
54
INTRODUCTION _

SAMPLE SIZE RELATIONSHIPS _

In two-stage sampling, the estimates of the population mean and

variance are (Cochran 1963),

intertrawl component of variance,

= ..{J.. Xi -..{!l. Xij

X = L- where Xi = L~ (1)

i-I n j_1 m

f. (Xi - XY

s r = .:..i-~'--,---

n - I where

The number of independent observations directly impacts the estimated variance of a parameter; the higher the number of observations, the smaller the variance. A trawl survey is usually a two-stage

sample design; hence the number of observations is determined by

the number of trawls taken (n) and the number of fish subsampled

from each trawl (m). However, for a fixed total sample size (nm),

varying combinations of nand m will produce varying values of

the estimated variance because the fish within a trawl are typically

more similar than fish between trawls, that is, fish within trawls

are positively correlated and hence are not independent observations. For example, the intratrawl correlation coefficient for female'

weight data collected during the 1980 survey was 0.60. Thus it is

advantageous to find the optimal combination of nand m that will

produce the minimum variance.

Sampling Requirements for

the Adult Fish Survey

SUSAN PICQUELLEI

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

The question of how many fish should be collected to estimate population fecundity parameters is addressed. The goal is to determine the optimal combination

of the number of stations to occupy (11) and the number of fish to subsample per

station (m) that will provide the minimum variance of parameter estimates. The

collection of mature fish for this purpose is considered to be a two-stage sample

design in which the total number of fish processed is equal to 11 times m. In most

cases, the subsample of fish taken from a trawl station can be treated as a cluster

sample, and a simple relationship between variance of the parameters and the

sample sizes, 11 and m, may be established. Spawning fraction, the parameter with

the largest relative variance, is chosen to evaluate alternative combinations of 11

and m. In terms of the total number of fish processed, it is generally more efficient in a statistical sense to occupy more trawl stations and to subsample fewer

fish per station than vice-a-versa. If the major cost of collecting data is associated

with ship operations, then it is cheaper to occupy fewer trawl stations and subsample more fish per station. The equations and Figure 1, based on northern anchovy data from California, provide criteria for determining the combination of

11 and m which achieves desired levels of variance.

ff(Xij - xy

Sf = .:..i--'-"!.li.c.-.".I__-,-,-_

n (m - I) = intratrawl component of variance,

I, nlN, where N is the total number of stations, and

h mlM, where M is the total number of elements at each

station.

(Note: for simplicity's sake, two-stage sampling with stations of equal

size is used here for illustration purposes.) Equation (2) relates

variance to the values of nand m, and this equation can be used

to find the optimal values of nand m which will produce the

minimum variance.

But first, some simplifications can be made. In the majority of

fisheries surveys, the sampling fraction}; is negligibly small so that

the value II = 0 may be substituted into equation (2). This reduces

to

(3)

'Present address: Northwest and Alaska Fisheries Center, National Marine Fisheries

Service, NOAA, 7600 Sand Point Way NE, Seattle, WA 98115.

and the intratrawl component of variance disappears. Because of

this simplification, the trawl sample may be treated like a cluster

sample. In cluster sampling, the trawl average, Xl' is measured

without error, i.e., every fish is measured. In two-stage sampling,

the trawl average is estimated with error, but in this case that error

is negligible and does not impact the total variance estimate.

By considering the subsample of fish taken from a trawl as a cluster

sample, a simpler relationship between variance and values of nand

m may be established. The intracluster correlation (p) may be expressed as a function of the ratio of the cluster-sample variance to

the random-sample variance:

55
Solving equation (4) for m after substituting equation (7) for 2 .

o random gives

(10)

The major cost of data collection is associated with ship operations,

not with processing the fish in the laboratory. For a fixed number

of fish sampled, it is much cheaper to take fewer trawls and larger

subsamples, although this reduces the precision of the estimates.

Thus, what is more efficient statistically (many trawls and small

subsamples) is the exact opposite of what is more efficient financially (few trawls and large subsamples). If the costs of taking a

trawl (CI) and of processing a fish (C2) are known, these costs may

be incorporated in the relationship between nand m and a new function may be derived which minimizes total cost (C),

COST CONSIDERATIONS _

of the estimate. They suggest general sampling strategies rather than

specific criteria.

It is generally more efficient (in terms of number of fish processed)

to take more trawls and fewer fish per trawl than vice-a-versa. For

example, consider a spawning fraction of 0.10 and a desired coefficient of variation of 0.125. If 80 trawls are taken, then 10 fish should

be subsampled, for a total of 800 fish. On the contrary, if only 50

trawls are taken, then 26 fish need to be subsampled, for a total

of 1,250 fish. This is true because the fish within each trawl tend

to be positively correlated and hence are not independent observations, while the fish between trawls are uncorrelated, thus contributing more information per fish.

(8)

(7)

(6)

(5)

(4)

nm

x (l - X)

n (n - 1)

tL(x;j-x)2

;-Ij-I

i. (x; - X)2

i-I

criCfUSI~f

crtrandom

cr1random = crtbinom~1

cr.fcfuslrf

--- 1+ P (m - 1) (J"2 -

random

nm (nm - 1)

The fish sampled during the trawl survey are uscd to estimate

several parameters, i.e., sex ratio, spawning fraction, fecundity, and

female weight. The optimal combination of m and n will not be the

same for all parameters. Hence, the parameter with the largest

relative variance is chosen to pick the values of m and n. This

parameter is spawning fraction for the northern anchovy example.

Spawning fraction is distributed approximately as a binomial

distribution. We can simplify equation (4) by substituting the variance

of a binomial distribution for the random-sample variance

where

and

Values for ~, P and oJ, I are needed to specif., the relation- xc uster J.)

ship between m and n. It is more convenient to work with the coefficient of variation (cv) rather than variance directly because one

can then specify the desired precision in terms of percent of the

parameter rather than in absolute terms. This changes equation (8) to

m (l-x)(1-p)

nxclI 2 - (I - x)p (9)

We wish to minimize C under the constraint of Equation (9).

C = nC t + nc 2 [ (I - x)(1 - p) ]. (11) nxcv 2 -(I-x)p

C · ... db' ac 0 IS mmlmlze y settmg - = .

an

where cv =

This results in the following values for nand m:

Consider the example presented earlier where x = 0.10 and

the desired coefficient of variation is 0.125 (again using P = 0.0448

from the 1982 survey data). Suppose the cost of taking one trawl

(CI) is $1,000 and the cost of processing one fish (C2) is $25. These

conditions result in the values minimizing cost of n = 45 and

m = 29.

Frequently the number of trawls taken is determined by factors

not related to desired precision and not directly controllable, such

as the number of days at sea, weather condition, and the success

rate of catching the target species. Before a survey begins, only the

number of days at sea is known; however, predictions about the other

two factors mentioned are available, so that an approximate number

of trawls can be deduced. Then the graphs may be used to find the

necessary value of m to attain the desired coefficient of variation.

Another consideration ofselecting nand m is the expected number

of spawning females subsampled in a trawl. If the spawning fracX

Considering a range of values for the coefficient of variation is

useful to see how nand m change as the precision of the estimate

of ~_ changes. It is also worthwhile to consider a range of values

for x, because estimates of this are not available until after the sur-

'!..ey, but it is possible to specify a range of values within which

x is likely to fall. A value for P may be selected using an estimate from previous surveys.

NUMERICAL EXAMPLE _

As an example, the attached series of graphs (Fig. 1) was constructed

using the estimate of P calculated from ~e 1982 survey data using

Equation (4) (P = 0.0448). Values of x range from 0.06 to 0.12

in !!Jcrements of 0.02, with one graph corresponding to each value

of x. On each graph are five lines corresponding to five values of

the desired coefficient of variation (0.100 to 0. 200). The vertical axis

is m, the subsample size; and the horizontal axis is n, the number

of trawls.

These graphs do not serve to pinpoint the precise combination

of m and n that is optimal. Instead, they illustrate how nand m

together determine the precision of the estimate, given the value

n =

CI(I - x)p + (1- x)y'CIC2P(1 - p)

C\x ClI 2 (12)

(13)

56
tion is 0.10, and only 10 females are subsampled from each trawl,

then the expected number of spawning females sampled from each

trawl is only I, based on a binomial distribution where n = 10 and

p = 0.10. This will lead to a high proportion (35 % on average) of

trawl subsamples with no spawning females, thus inflating the

variance. By raising m to 15 females, the average percent of trawl

subsamples with no spawning females drops to 21 %; for 20 females

the percent is 12 %.

LITERATURE CITED _

COCHRAN. W. G.

1963. Sampling techniques. John Wiley and Sons, N.Y., 413 p.

30

25

""' :::E

LU 20

N

Ci5

LU 15 -'

a..

:::E

;;j 10

II)

::::>

en

5

SPAWNING FRACTION = 0.06

. \" \

\ \

\ 0\50 0.1\ . \ \.

\.... 0.1~5 \ ..

..... \ "- ... \

0.29.0 ', "'- "'-

..................." ........................

............

.....

30

25

20

15

10

5

SPAWNING FRACTION =0.08

. \ \

\ \ '. 0.125

\ \ . \ 0.150

\ \ \ \0.~75 ".

\. \ \ . \

0.29.0 \ "-

'.... \ "'- . '.

"

,"-

' :.:.:.:-:.......: ...............

20 40 60 80 100

0 .......--'------'---.......- ..........----'

o

30

25

LU 20 N

Ci5

15

a..

:::E

«

en 10

II)

::::>

en

5

SPAWNING FRACTION = 0.10

\ \ \ \ \ \

: \ \ 0.100

\ \ \ \

I; \ 0.125

\ \ \ \

\

\ 0.150 \ . \ \' \ \0.1..75 \ \ . ". \ .... ". , ....

0.200........', "'-

\ ..... '...... ' ..........

'<:::::::::~;;~;::;

30

25

20

15

10

5

SPAWNING FRACTION = 0.12

\ \ \ \ \ \~\ \ 0.100

: \" \ \ \ 0.125

, \ \ \.

\ 0.150 "\ ~; \

\6~17~\ \ \ ...... \ \, 0.200 ....., ....

\ , "'"....." ..... '-...... ,','......... ".

"-.. .... ...... -"""" '<~.~~.:::~;;.;: ..:.~

20 40 60 80 100

NUMBER OF TRAWLS (N)

0'-----'---"'-----..........--'---....

00 20 40 60 80 100 o

NUMBER OF TRAWLS (N)

Figure I.-Relationship between subsample size and number oftrawls for a range of values for spawning

fraction and coefficient of variation.

57
58
Spawning Frequency of

Peruvian Anchovies Taken

with a Purse Seine

JURGEN ALHEIT

Cooperative Peruvian-German Investigations Project

(PROCOPA-GlZ) , Instituto del Mar del Peru,

Apartado 22, Callao, Peru

ABSTRACT

The incidence of postovulatory follicles was used to determine spawning frequency

of the Peruvian anchovy, Engraulis ringens. Because the fish were collected with

a purse seiner, samples could be obtained day and night. This allowed two independent estimates of spawning frequency, one for females taken one day after

spawning and another for females taken two days after spawning. The correlation between these two estimates was tested with a paired I-test, and the reliability of using incidence of postovulatory follicles to determine spawning frequency

was thus proven. The vulnerability of female anchovy to the purse seine changed

according to their reproductive state. Females in the prespawning hydrated stage

are oversampled by the purse seine and therefore cannot be used to determine

spawning frequency.

59

INTRODUCTION _

For the Southwest Fisheries Center (SWFC) egg production method,

accurate estimates of percent spawning frequency by females is an

essential statistic. With a representative sample, one should be able

to derive three independent estimates of spawning frequency (i.e.,

fraction of mature females spawning per day): 1) percentage of

females with hydrated oocytes; 2) percentage of females with day-l

postovulatory follicles (age: 9-32 h); and 3) percentage of females

with day-2 postovulatory follicles (age: 33-56 h).

Using Hunter and Goldberg's (1980) technique of recording the

incidence of postovulatory follicles, spawning frequency was determined for the Peruvian anchovy, Engraulis ringens (Alheit et al.

1984; Santander et al. 1984). However, an important difference in

sampling techniques between California and Peru was the type of

gear used to obtain females. In the California surveys, a small stern

trawler was used which permitted only night catches of adult anchovies (Hunter and Goldberg 1980; Hunter and Macewicz 1980;

Stauffer and Picquelle 1981). In Peru, however, anchovies were collected with a purse seiner and could therefore be sampled both night

and day (Alheit et al. 1984).

Females with postovulatory follicles and females in the hydrated,

prespawning stage were obtained for the entire 24-h cycle. There

is possible bias in such a 24-hour sampling scheme in determination of spawning frequency introduced by the time of capture and

affecting the incidence of females with postovulatory follicles (see

Stauffer and Picquelle 1985). Thus, the use of a purse seine for Peruvian anchovy gave new insights into this bias problem. As hydrated

females were sampled during the day with purse seine, daytime incidence ofspawning frequency could be compared with night samples. The importance of night and additional day samples of anchovies for the validation of Hunter and Goldberg's (1980) method

is described in this section, and the influence of different sampling

gear (trawl versus purse seine) and of the reproductive behavior of

mature anchovies on the obtained data of spawning frequency and

sex ratio is also discussed.

RESULTS _

If the spawning frequencies for day-l and day-2 females are shown

to come from populations with the same mean, their combination

would double the sample size available for the determination of

spawning frequency and reduce the variance of the estimate.

In order to see if the frequencies could be combined, a test of

the differences between paired samples, a paired t-test (Snedecor

and Cochran 1967), was carried out. The paired samples were the

frequency of day-l and day-2 females in each of 49 collections of

20 females each. A paired test was used due to the likely correlation between samples taken from the same collection. The null

hypothesis was that the mean difference between samples was zero.

The results of the test gave a t value of 1.196 which was not significant when compared to the critical value of a t distribution with

a = 0.05 and n - I = 48 df. Therefore, the null hypothesis could

not be rejected at the 5% level of significance and the two samples

can be combined.

Spawning frequency of the day-l females was 0.1726 with a variance of 2.3248xlO-4 , a standard deviation of 0.0152, and a coefficient of variation of 0.0883 (Table 1). Spawning frequency of the

day-2 females was 0.1481 with a variance of 1.7224XIO-4 , a

standard deviation of 0.013l, and a coefficient of variation of 0.0886

(Table I). After joining the data from day-l and day-2 females, the
Table I.-Mean percentage of hydrated, day-I, day-2, and day-II

day-2 females with variance (V), standard deviation (SD), and coefficient of variation (eV).

Reproductive stage

of females Mean \i SD CV

Hydrated 0.2306 1.2198x 10- 3 0.0349 0.1515

Day-I 0.1726 2.3248 x 10-4 0.0152 0.0883

Day-2 0.1481 1.7224 x Ill- 4 0.0131 0.0886

Day-1 + Day-2

(combined) 0.1604 1.0175> 10-1 00\01 0.0629

combined spawning frequency was 0.1604 with a variance of 1.0175

xlO-4, a standard deviation of 0.0101, and a coefficient of variation of 0.0629 (Table I). The combination of day-l and day-2 females

reduced the coefficient of variation by nearly a third. This would

be important for estimates of spawning biomass when using the

SWFC egg production method, because the coefficient of variation

of the total biomass estimate would also be reduced (Santander et

al. 1984).

The spawning frequency value of 16.04 % (Table 1) means that in

August/September 1981 a mature Peruvian anchovy female spawned

a new batch of eggs every 6.23 days, on average. The high daily

incidence of 23.06% of hydrated females (Table 1) clearly shows

the oversampling of females in the hydrated stage. Comparison of

the coefficient of variation of the hydrated females with that of the

day-l and day-2 females demonstrated much higher variability in

the occurrence of hydrated females in the samples.

DISCUSSION _

The midwater trawl is reportedly a biased sampler with respect to

sex ratio and hydrated females (Hunter and Goldberg 1980; Stauffer and Picquelle 1981). A higher than expected number of trawl

samples had either a high or a low number of females. Furthermore,

hydrated females were twice as numerous as day-l females. Picquelle

and Hewitt (1983) suggest that males and hydrated females segregate

from other females at the hours of peak spawning at a depth where

they are more vulnerable to the trawl.

The purse seine also seems to collect samples which are biased

with respect to sex ratio and hydrated females (Alheit et al. 1984).

As for the trawl, this is complicated by the fact that both biases are

interrelated. In the present study, oversampling of hydrated females

occurred in the early morning hours when the onset of hydration

could be determined only by recording the migration of the oocyte

nucleus to the pole. At this time, the oocytes have not increased

perceptibly in size and the ovary is a small fraction of the total female

body weight. Three different explanations are possible for the oversampling of hydrated females in purse seines:

1) Hydration decreases the ability of female anchovies to avoid

nets;

2) Females segregate vertically (by depth) and those with hydrated

oocytes are more accessible to the purse seine than other females;

3) Females segregate horizontally (by area) and those with hydrated oocytes occur in different areas than those without hydrated

oocytes.

In any case, the suggestion by Hunter and Macewicz (1980) to use

incidence of hydrated females for determination of spawning frequency seems unfeasible with purse seine collections, even if day

samples of anchovies can be obtained.

60

The sex ratio in the 49 Peruvian collections ranges from 12.62 %

to 90.50% females with an average of 56.43 %. Night purse seine

collections contain a high percentage of hydrated females (with

respect to the female fraction) and also a high percentage of males.

Hydrated females are oversampled day and night, but co-occurrenco::

of high percentages of hydrated females and males is recorded only

at night. It might be hypothesized that the high male ratio in these

night collections is the result of hydrated females about to spawn,

which are attractive to and surrounded by a high number of males

(Hunter and Goldberg 1980). Ifthe hypothesis is correct that hydrated

females are caught more often than expected because of their increased vulnerability to the net, then only the hydrated females should

be oversampled and not the males as well. Thus it seems more likely

that hydrated females segregate, either by depth or by area, from

"normal schools" taking a high percentage of males with them,

thereby forming "spawning schools" which are dominated by males.

An average sex ratio in the Peruvian survey (Alheit et al. 1984)

was biased by night coll~ctions with a high percentage of hydrated

females. When these collections were omitted. the average sex ratio

rose to 57.9%. Assuming a sex ratio of 50% females, the purse seine

clearly oversamples females (Alheit et al. 1984) whereas the trawl

seems to undersample them slightly (Stauffer and Picquelle 1981;

Picquelle and Hewitt 1983). Klingbeil (1978) reports similar findings

when he compared the sex ratios obtained from commercial purse

seiners (females:males = 1.60:1) and from research trawlers

(females:males = 1.09: I). He suggests that the male-dominated

schools may not form the large dense aggregations necessary for

effective purse seining, as do the other schools. This might explain

the difference in sex ratios estimated for the northern and Peruvian

anchovy. The large purse seiner used in Peru may have shot the seine

when the echosounder indicated a relatively large, dense femaledominated school. However, the California trawler took samples over

a larger area and thus included more male-dominated schools which

had segregated for the daily spawning period and which had formed

rather loose, less dense, aggregations. Therefore, if the hypothesis

is correct that spawning schools segregate by area (horizontally) from

normal schools, it would seem that the trawl is a more suitable tool

for determining the sex ratio of anchovies.

Interpretation of the different sampling results for hydrated females

is rather difficult. They were oversampled by the Peruvian purse

seiner in 1981 and by the California trawler in 1980 and 1981 (Stauffer

and Picquelle 1981; Picquelle and Hewitt 1983). However, in 1982

the California trawler did not oversample the hydrated females (Picquelle and Hewitt 1983) which, according to the authors, might have

been due to fishing the net at a shallower depth. This oversampling

problem of hydrated females might be solved by a comparative study

between a purse seiner and a larger, midwater trawl which allows

fishing in depths not reached by a purse seine.

LITERATURE CITED _

ALHEIT, 1., V. H. ALARCON, and B. MACEWICZ.

1984. Spawning frequency and sex ratio in the Peruvian anchovy, Engraulis

ringens. Calif. Coop. Oceanic Fish. Invest. Rep. 25:43-52.

HUNTER, 1. R., and S. R. GOLDBERG.

1980. Spawning incidence and batch fecundity in northern anchovy, Engraulis

mordax. Fish. Bull., U.S. 77:641-652.

HUNTER, 1. R., and B. MACEWICZ.

1980. Sexual maturity, batch fecundity, spawning frequency, and temporal pattern of spawning for the nortbern anchovy, Engraulis mordax, during the 1979

spawning season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.
KLINGBEIL, R.A.

1978. Sex ratios of the northern anchovy, Engrau/is mordax, off Southern California. Calif. Fish Game 64:200-209.

PICQUELLE, S. 1., and R. P. HEWITT.

1983. The northern anchovy spawning biomass for the 1982-83 California fishing

season. Calif. Coop. Oceanic Fish. Invest. Rep. 23:16-28.

SANTANDER, H., 1. ALHEIT, and P. E. SMITH.

1984. Estimado de la biomasa desovante de la anchoveta peruana, Engrau/is

ringens, con el "Metodo de Produccion de Huevos" en 1981. Bol, Inst. Mar

Peru, Callao (In press).

SNEDECOR, G. W., and W. G. COCHRAN.

1967. Statistical methods. Iowa State Unlv. Press, Ames, 593 p.

STAUFFER, G. D., and S. 1. PICQUELLE.

1981. Estimate of the spawning biomass of the northern anchovy central subpopulation for the 1980-81 fishing season. Calif. Coop. Oceanic Fish. Invest.

Rep. 22:8-13.

1985. Procedures for sorting, staging and ageing eggs. /n R. Lasker (editor),

An egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engrau/is mordax, p. 33-35. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

61
62
Preservation of

Northern Anchovy in

Formaldehyde Solution

J. ROE HUNTER

Southwest Fisheries Center,

National Marine Fisheries, Service, NOAA,

P. O. Box 271, w Jolla, CA 92038

ABSTRACT

Preservation and curation techniques used for northern anchovy, Engraulis mor·

dax, taken in routine hiomass surveys are described, and the effects of formaldehyde solution on length and weight are documented. Preservation in 10%

butTered formaldehyde solution caused a 4% increase in anchovy wet weight after

24 h, but only negligible changes occurred over the next 340 d. Preservation also

caused a 2% shrinkage in standard length after 24 h which increased to 3% after

340 d.

63

INTRODUCTION

The fish reproductive parameters used in the egg production biomass

estimate (spawning fraction, female weight, batch fecundity, and

sex ratio) are based on analysis of formalin-preserved specimens

taken in trawl or purse seine collections. Careful attention to preservation and curation techniques is essential for an accurate measurement of these variables.

PRESERVATION _

Histological analysis requires special care in preservation. Post·

ovulatory follicles are relatively subtle histological structures, and

poor preservation makes it impossible to stage them. Fish should

be preserved while alive. Neither frozen specimens nor fish dead

for some time can be used. A limited amount of biological material

is preserved per collection container. We preserve only five aduit

anchovies per quart jar, roughly 80-150 g of tissue in 800 ml of

formalin (see following). In all specimens, the body cavity is slit

open along the SIde using a long incision to insure adequate preservation of the ovary. Care must be taken not to cut the ovary; this

is difficult in females with hydrated eggs. If eggs are lost, they

should be added to the jar.

To insure adequate preservation of the ovaries, we use a 10%

buffered formaldehyde solution (formalin). Quantities of chemicals

required for an 18-L container of buffered 10% formaldehyde

preservative are as follows:

16.2 L distilled water

117 g sodium phosphate dibasic (granular, NazHzP04)

72 g sodium phosphate monobasic (granular, NaH2P04 ' H20)

1.8 L formaldehyde solution (37 %).

Dissolve the sodium phosphate diabasic and stir in the distilled

water; then mix in the sodium phosphate monobasic until dissolved,

and finally add the formaldehyde solution.

Although Bouin's solution (Galigher and Kozloff 1971) might improve the quality of histological sections of ovarian tissue, its use

is impractical for production work. Bouin's is more difficult to use

on shipboard because represervation is required and because Bouin's

preservation makes fecundity estimation difficult. Specimens pre·

served as described above are kept in the original preservative until

curated, which may occur after as much as 2-3 mo of storage.

CURATION _

A total of 15-25 females with active ovaries are removed from each

collection in random order, blotted, weighed (nearest 0.1 g), and

length measured (nearest 1 mm). We curate five more females per

collection than needed for the spawning frequency estimate (see Picquelle 1985) in order to allow for females that will be rejected after

histological analysis because of immaturity. (It is easier to curate

a few additional females than to return to the original collection to

process additional fish.) After a female has been weighed, the ovary

is removed, blotted dry, and weighed to the nearest mg. Females

may be discarded at this point, but the ovary is represerved in fresh

buffered formaldehyde solution and stored individually in a vial.

Ovaries that appear to be hydrated are noted, as are the presence

and quantity of loose eggs in the jar. Each female is assigned a unique

identification number (collection number plus fish number).
In female anchovy of 12 g or less, we consider ovaries immature

when the ratio of ovary weight/female weight (less ovary) is 0.01.

For females of 12 g or less, the probability of maturity is less than

5 % when the gonad body weight ratio ~0.Ql (Hunter and Macewicz

1980). These ovaries are stored in vials. but not processed histologically, regardless of the size of the ovary. Histological criteria are

used to distinguish between immature and inactive ovaries in females

heavier than 12 g (Hunter and Macewicz 1985).

Males are processed along with the females if a separate sample

is not taken for sex ratio estimation (Picquelle 1985). If males and

females are preserved together, fish must be taken randomly from

the jars to maintain a random order by sex. Males are weighed until

the combined total of male plus female weight in a single sample

equals 500 g (the combined weight needed for sex ratio calcula

tions). and thereafter no additional males are processed in that

sample.

EFFECTS OF PRESERVATION _

The reproductive parameters used for biomass estimation are expressed in terms of live wet weight, but as the specimens are preserved in formaldehyde solution, a correction coefficient must be

used.

The wet weight and length of 75 northern anchovy (ranging in

weight from 2.6 to n.o g; mean weight 14.03 g) were determined

when alive, 24 h after formaldehyde preservation, and at intervals

over 340 d. Fifty-five fish were treated using the standard method

described above (preserved alive with body cavity slit), 10 fish were

first pithed, body cavity slit, and preserved while still alive, and

10 were pithed, slit, and allowed to die over a 20-min period before

preservation.

In nearly all fish, the wet weight increased as a result of preservation. In only one of the 75 fish preserved was the wet weight after

85 d less than the initial live wet weight, and in only four fish was

the weight the same. The increase in wet weight was minor. The

mean increase in wet weight of the 55 fish preserved using the

standard method was about 4 %. In these fish, the total gain in wet

weight occurred within 24 h after preservation and thereafter it remained about the same (Fig. 1). Pithed anchovy did not struggle

in the preservative, and the initial weight gain after preservation was

only 1%; but they gained weight steadily, attaining a 3% gain in

20 d and thereafter weight remained about the same. No difference

existed between the two groups of pithed fish, indicating that death

itself had no effect on subsequent weight in formalin. Struggling

of live fish in formaldehyde solution appears to increase the initial

rate of fluid uptake, but after 20 or more days the difference between fish preserved alive and those pithed or dead was 1% or less.

This could cause a slight error in estimated live weight if some fish

were preserved dead and others alive and the collection was curated

immediately. For biomass estimation, we use the mean for all data

on fish preserved alive (+4.3%). Most fish in our surveys are

preserved alive and weighed 30-40 d later.

The length of all fish declined as a result of formalin preservation. Shrinkage after 24 h in preservative was 2% and increased

to 3 % after 340 d in preservative (Table 1). Shrinkage rates did not

vary among the three treatment groups.

Similar effects of formalin preservation (shrinkage in length and

gain in wet weight) were documented for salmon by Parker (1963),

but plaice lost 9% of their wet weight when preserved in 4% formalin and sea water (Lockwood and Daly 1975), and Rosenthal and

Westernhagen (1976) report no significant change in three species

64

Table I.-Effect of formalin preservation on

standard length and wet weight of Northern anchovy preserved alive.

Percent change

Elapsed time from live measurement

in formalin Length Weight

(Days) (mean, 2xSE*) (mean, 2xSE*)

1 -2.26 0.21 4.20 0.54

5 -2.44 0.24 4.20 0.59

10 -2.55 0.24 4.26 0.60

21 -2.81 0.24 5.40 0.74

42 -2.46 0.23 4.35 0.68

84 -2.27 0.21 3.70 0.74

341 -2.93 0.23 3.74 0.72

*Two times the standard error of the mean, where

n for each sample = 55, except at elapsed time 21

days where n = 38.

of siganids after formalin fixation. These and other studies (see

reviews by Parker 1963, and Lockwood and Daly 1975) indicate that

considerable variation exists with formalin preservation. Factors that

account for this variation include species differences, fish size (life

stage), state of the fish when preserved, duration of the fish in formalin, and ratio of formalin and dilutant. Among dilutants, fresh

water is clearly preferable to sea water (Lockwood and Daly 1975).

Clearly, the effects of formalin preservation are quite specific and

calibration is required for any changes in technique, species, or life

stage.

LITERATURE CITED _

GALIGHER, A. E., and E. N. KOZLOFF.

1971. Essentials of practical microtechnique. 2d ed. Lea & Febiger, Philadelphia,

531 p.

HUNTER, 1. R., and B. MACEWICZ.

1980. Sexual maturity, batch fecundity. spawning frequency, and temporal pattern of spawning for the northern anchovy, Engraulis mordax, during the 1979

spawning season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

1985. Measurement of spawning frequency in multiple spawning fishes. In R.

Lasker (editor), An egg production method for estimating spawning biomass

of pelagic fish: Application to the northern anchovy, Engraulis mordax, p.

79-94. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

LOCKWOOD, S. 1., and C. de B. DALY.

1975. Further observations of the effects of preservation in 4% neutral formalin

on the length and weight of O-group flatfish. 1. Cons. Int. Explor. Mer

36:170-175.

PARKER, R.

1963. Effects of formalin on length and weight of fishes. 1. Fish. Res. Board

Can. 20: 1441-1455.

PICQUELLE, S.

1985. Sampling requirements for the adult fish survey. In R. Lasker (editor),

An egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engraulis mordax, p. 55-57. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

ROSENTHAL, H., and H. WESTERNHAGEN.

1976. Effect of formalin fixation on length, weight and condition factors of three

siganid species. Arch. Fischereiwiss. 27(1):37-43.
6 PRESERVED ALIVE (N" 55)

5 X= 4.3 : .. n__ n_n _dUU u u ----- ~u n ---------------r2

1

I

--~x =2.50 -

I

PITHED AND PRESERVED ALIVE N = 10)

PITHED AND PRESERVED DEAD (N =10)

0 Ll.__L-_...L_....l.__L-I_..l..._---L.__J..-_..l..._-..l.__.L-_-.L.._-..l.__.L-_-.L.._-..l.__.L-_....L.....J

U

Gi

c. 5

!;-~---,- z 0

;;:

e" 5

:~ u~J-:.:::.:.===-- -- ==--- -- ~===-:-==-===-I r1 ~" 1 ~,~ 2.70

0L.J.._-L._.....J.._---l__L-_..L...._...l.-_-l...._-L.._--l._---l__L-_.l--_..I.-_..l-_....J..._-L._.....J..~

1 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340

ELAPSED TIME IN FORMALIN (days)

PRESERVED ALIVE (N =55)

-3 -I - -- - - - --- -- -- - -7-- - - - -

-2 I X= 2.53

-HI I I I 0

- (N =10) r:: PITHED AND PRESERVED ALIVE I Ql

u

---1----.-.-.........

Gi -3 rHN - - - - -

X=~2.40} - ------

:I:

:; -2

Z

w

.... -1

w I e" 0 <

:oc:

z PITHED AND PRESERVED DEAD (N =10) ii2

:I: 1.hU_ II) -3

...._----j-- -

X=-2.207 - - -- -2

-1

0

1 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340

ELAPSED TIME IN FORMALIN (days)

Figure I.-Effect of 10% formaldehyde preservation on northern anchovy wet weight (upper) and standard length (lower); points are wet weight

(upper) or mean loss in standard length (lower) expressed as a percentage of the original live wet weight or live length; bars are ±2xstandard

error of the mean.

65
66
Batch Fecundity in

Multiple Spawning Fishes

1. ROE HUNTER, NANCY C. H. La,

and RODERICK 1. H. LEONG

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

P.O. Box 271, La Jolla, CA 92038

ABSTRACT

Methods for estimating batch fecundity are described, including identification

and sampling the eggs that constitute one spawning batch within the ovary. Using

northern anchovy, Engaulis mordax, as an example, methods are developed for

evaluating the accuracy and precision of batch fecundity estimates. Included in

this analysis are the number and location of ovarian tissue samples, optimal

numbers of females, and selection of the appropriate function to express the relation between batch fecundity and female weight. We found for anchovy that the

optimum number of ovarian tissue samples was 2-3 per ovary and that to keep

the coefficient of variation for the mean fecundity of population under 10% required a sample of 50 or more females. Analysis of covariance indicated that the

batch fecundity of northern anchovy varied significantly among years (1951-84)

indicating that the relation hetween female weight and fecundity must be newly

established each year.

67

INTRODUCTION _

A key issue in the estimation of fecundity of oviparous fishes is

whether or not the annual fecundity can be estimated from the standing stock of advanced oocytes in the ovary prior to the onset of

the reproductive season. In some boreal species, frequently called

total or isochronal spawners, all the eggs to be released in a season

develop synchronously prior to spawning (hence the term isochronal)

and spawning typically takes place over a short period (Holden and

Raitt 1974). In such species, the standing stock of oocytes within

a certain range of maturity classes is considered to represent the

annual fecundity of the spawner. The groups of oocytes to be spawned in the season are usually identifiable because a distinct hiatus

in oocyte maturity classes exists between the small, immature,

unyolked oocytes that occur the year around and the synchronously maturing annual batch (Hickling and Rutenberg 1936; Yamamoto

1956). Although some of these fishes may spawn repeatedly during the season, for example, whiting and haddock, the standing stock

of yolked eggs is considered representative of the annual fecundity

(Hislop 1975; Hislop et al. 1978; Hislop, pers. commun. 1

). An exception to this occurs when unfavorable conditions result in resorption of some of the advanced eggs in the ovary at the end of the

season. The extent of this potential bias (overestimation of annual

fecundity) is unknown.

In many temperate and tropical fishes (frequently called multiple, partial, serial, or heterochronal spawners), annual fecundity

is seasonally indeterminate and batch fecundity is the only useful

measurement. In such fishes the standing stock of yolked eggs,

regardless of maturity state, give no indication of annual fecundity

because these fishes continuously mature new spawning batches

throughout a typically protracted spawning season. In the active

ovaries of fishes with indeterminate annual fecundity, the oocytes

usually occur in nearly all maturity stages; they range in size continuously from small unyolked oocytes <0.1 mm diam. to yolked

oocytes 0.4-0.7 mm diam., and no large hiatus exists between maturity classes of oocytes except for one between hydrated oocytes and

advanced yolked oocytes which is of a temporary nature. Such fishes

usually spawn many times during a season. The northern anchovy

spawns at 7-10 d intervals for 2 or 3 mo and averages 20 spawnings

per yr (Hunter and Leong 1981), and the scianid, Seriphus poUtus,

has a similar reproductive output (DeMartini and Fountain 1981).

Thus, for these fishes, identification of a predetermined annual

spawning batch is a hopeless exercise, and the only useful fecundity measurement is the number of eggs produced in a single spawning batch (batch fecundity); annual fecundity is a function of both

the batch fecundity and the number of spawnings per year. Spawnings are so numerous in these fishes that small unyolked oocytes

<0.1 mm diam. would have to mature in a season to account for

the number of spawnings (Hunter and Leong 1981).

The standing stock of oocytes is occasionally used to estimate annual fecundity in such common fishes as Scomber, Trachurus, and

Merluccius, which by the standard criteria have indeterminate

fecundity. That annual fecundity is predetermined in such fishes is

an assumption with little or no supporting evidence. The criteria

and approaches for distinguishing between determinate and indeterminate fecundity are discussed in greater detail (Hunter and

Macewicz 1985).

The objective of this paper is to describe the methodologies for

estimating batch fecundity in fishes with indeterminate seasonal

fecundity. We do not consider the well documented methodology

'John R. G. Hislop, DAFS Marine Lab., P.o. Box 101, Victoria Road,

Aberdeen AB9 8DB, Scotland, pers. commun. Oct. 25, 1983.
PILCHARD

HERRING

to 1.2

0.9 1,0 1.1 1.2

ANCHOVY

---- MATURE

- SPAWNED

1'"-.... , , A

, ,

" '"",';

t ,

I \

\

,U0,5 1.0 1.2

'0

O·b.o 0.1 0.2 0.3 0.4 0.5 0.6 0.7

EGG SIZE (mml

for fecundity estimation of fishes with seasonally detenninate fecundity (see, for example, Holden and Raitt 1974). In anchovy and other

fishes with indeterminate annual fecundity, the oocytes in active

ovaries are typically distributed in 1-2 modes (Fig. 1), each mode

representing a single spawning batch. Maturation of oocytes and

vitellogenesis are a continuous cycle: when one spawning batch is

spawned, another spawning batch is ready for the last stages of

maturation and spawning (Fig. 2). Vitellogenesis proceeds rapidly

after a spawning, with the ovary doubling in dry weight during the

interval between spawnings (Hunter and Leong 1981). The fmal stage

of maturation, hydration, is characterized by a rapid secretion of

fluid of low specific gravity into the advanced eggs by the granulosa

cells of the follicle (Fulton 1898). This fluid causes more or less

complete fusion or solution of the yolk granules producing the

translucent appearance of hydrated eggs. The volume of the egg or

wet weight increases three- or four-fold (Fulton 1898), but the increase in dry weight is negligible (LeClus 1979a). In northern anchovy, hydration begins about 12 h before spawning when the eggs

are between 0.6 and 0.8 rom (major egg axis) and causes a four-fold

increase in wet weight of the ovary as the egg increases to 1.3 rom

(major axis) (Hunter and Macewicz 1980; Hunter and Leong 1981)

(Fig. 2). Ovulation and spawning soon follow completion of hydration in most c1upeoids (anchovy, pilchard, sardines, and others) but

in herring, a total spawner, ovulated eggs may be retained in the

ovary for an extended period.

Figure I.-Frequency distribution of oocyte diameter in the ovaries of herring,

pilchard (Hickling and Rutenberg 1936), and northern anchovy (Hunter and Leong

1981). Herring spawns a single batch each year; other species are multiple-batch

spawners. In the anchovy, the solid line shows a recently spawned female, the

broken line a female about to spawn (just before hydration ofthe oocytes). (From

Blaxter and Hunter 1982.)

SPAWN SPAWN

2.0 t t 1.3 .....

Q -E

- (l)E

t- 1.5 ,,- ::r:: ,,::r:: 52 wu

W LLt- o:i

t- 1.0

W o w"

MATURATION & 1. !::!Z

VITELLOGENESIS MATURATiON & VITELLOGENESIS

0-

>- 0.8 Z~ a:: 0.5 etet et

> 0.4 ~g, 0

0 0 !

0 i i i i i I i i i i i

4 5 6 0 1 2 3 4 5 6 0

ELAPSED TIME FROM SPAWNING (days)

Figure 2.-Maturation cycle of a U.5 g northern anchovy female during peak spawning months where the average interval between spawnings is

7 d. The change in mean wet weight of the ovary is indicated on the left axis and the mean diameter of the oocytes in the most advanced spawning

batch on the right axis. Data from Hunter and Goldberg (1980) and Hunter and Macewicz (1980).

68
LABORA~RYPROCEDURES-------------

Identifying and Counting

Oocytes in a Batch

A number of criteria have been used to identify the oocytes to be

included in a spawning batch. These include 1) counts of all yolked

oocytes; 2) estimation of the number of oocytes in the most advanced

spawning batch by measuring the size distribution of oocytes in the

ovary and identifying the most advanced (largest) modal group of

oocytes; and 3) estimation of the number of oocytes in a spawning

batch by counting the number of hydrated oocytes.

The first method can be rejected because the standing stock of

yolked oocytes gives indication neither oftotal fecundity nor of batch

size in fishes with indeterminate fecundity and is appropriate only

for fishes with determinate seasonal fecundity. The second method

(oocyte size frequency) usually gives results similar to those based

on counts of hydrated oocytes iffemales with highly advanced oocytes

are used (Hunter and Goldberg 1980; Laroche and Richardson 1980).

We believe the third method, counting the hydrated oocytes, is

preferable because it requires less time and avoids the problem of

partitioning oocytes between the most advanced mode and the adjacent group of smaller oocytes. Before describing methods 2 and

3, it is important to consider methods of sampling the ovary.

Methods of Sampling an Ovary

It is impractical to count and measure all advanced oocytes, or to

count all hydrated oocytes in an ovary, owing to the great fecundity

of most marine fishes. Thus, regardless of the method used for identifying the spawning batch, ovarian subsamples are required, and

these are related to either the ovarian weight (gravimetric method)

or the total volume of an aqueous suspension of all oocytes in the

ovary (volumetric method). The gravimetric method is based on

counting oocytes in weighed samples of ovarian tissue and relating

the tissue samples to the total ovary weight. In the volumetric

method, the ovary is preserved in Gilson's fluid which frees the

oocytes from the ovarian tissue by breaking down the connective

tissue (see Baganel 1967 for the recipe for Gilson's fluid). The released oocytes are cleaned, put in a volumetric cylinder fIlled to

a known volume with water, shaken to provide thorough mixing,

subsamples of known volume are withdrawn using a Stempel pipette,

and the oocytes staged and counted (Holden and Raitt 1974).

Automatic oocyte counters may also be employed.

The volumetric method may be used for batch fecundity estimation if the eggs constituting the batch are identified using the egg

size-frequency method; however, the volumetric technique is inappropriate if the hydrated oocyte method is used because Gilson's

fluid destroys hydrated eggs. Substantial shrinkage of oocytes occurs when ovaries are preserved in Gilson's fluid; an average

shrinkage of24 % (compared to formalin-preserved ovaries) occurs

when skipjack and yellowfin tuna ovaries are preserved in Gilson's

fluid, but no differential shrinkage occurs among oocyte size classes

(Joseph 1963). Thus, to make oocyte size classes comparable to live,

or formalin-preserved, or histological sections, the extent of

shrinkage must be measured and the data corrected. Treatment with

Gilson's fluid also destroys the ovary, making histological analysis

impossible.

We use the gravimetric method of MacGregor (1957), which is

somewhat similar to the gravimetric method "B" of LeClus (1977)

who evaluated two gravimetric and one volumetric techniques. AI69

though LeClus obtained very low coefficients of variation for all

techniques in her 1977 methods paper, the relative fecundity

estimated for the South African anchovy in a subsequent paper

(LeClus 1979b) was as variable as those employing less complicated

procedures (MacGregor 1957, 1968; Hunter and Goldberg 1980).

Her use of vacuum dry weight of the ovary, instead of formalin wet

weight, seems an unnecessary refmement. Natural variability in batch

fecundity appears to be much greater than the variation caused by

differences in the technique of sampling the ovary.

The step-by-step procedure for the hydrated oocyte method is

outlined below. It will be elementary to many biologists, but it is

intended as a guide for inexperienced staff. Except for some details

outlined in a subsequent section, the same procedure can be used

to estimate batch fecundity using the oocyte size-frequency method.

The Hydrated Oocyte Method

1. The basic method is as follows: Numbers of hydrated oocytes

in weighed tissue samples of formalin-preserved ovary are counted

and the counts are then projected to estimate numbers of hydrated

oocytes in the entire ovary which is assumed to be equivalent to

batch fecundity.

2. Prior to batch fecundity estimation, females are accurately

weighed, and the ovary removed, weighed, and stored in an individual vial of buffered 10% formalin. Ovaries which appear

hydrated are noted along with an estimate of the numbers of free

eggs in a collection jar (Hunter 1985). Only hydrated ovaries which

have not lost oocytes are used for fecundity estimation; ovaries that

have lost oocytes in the jar are rejected after histological examination because they contain postovulatory follicles.

3. Needed supplies and equipment include a balance sensitive to

0.1 mg (which should be checked with standard weights), a dissection microscope with a lOx objective, hand counter, forceps, scalpel,

bottle of glycerin (33 % glycerol solution by volume) with eyedropper, glass slides (25 x75 mm), cover slips (22X50 mm), paper towels

for blotting, and weighing paper.

4. Remove ovary from the formalin fixative and blot dry with paper

towel. Break the ovarian membrane and remove three tissue samples

of the ovary. The ovary is soft and the sample can be removed easily

with the tip of the forceps or scalpel. Remove samples from positions about one-third of the distance from each end of the ovary

to insure that no two samples come from the same portion of the

ovary (only one ovary, left or right, need be used). Try to obtain

a tissue weight of 30-50 mg, as this will contain an adequate number

of hydrated oocytes (100-200). Place sample on a preweighed piece

of weighing paper and record weight to nearest 0.1 mg. Pieces of

ovary can be added or removed to vary sample weight.

5. Place the sample on a slide and cover with 3-4 drops of glycerin.

After 10-15 min, loosen the oocytes by gently tapping the piece of

ovary with the blunt tip ofthe forceps. After the oocytes are loosened,

add 3 or 4 more drops of glycerin, spread the sample over the slide,

and cover with a cover slip so that it floats on the fluid. (We found

that this concentration of glycerin had no effect on the diameters

of oocytes taken from formalin-preserved ovaries, even after 24 h.)

6. Place the slide under the microscope, and with a hand counter

tally the number of hydrated oocytes in the sample. Hydrated oocytes

can be distinguished easily from other oocytes by their large size
(usually ~0.8 mm in the major axis in northern anchovy), wrinkled

appearance when formalin preserved (yolked but nonhydrated oocytes

usually retain their smooth surface contour), and by their translucence (nonhydrated eggs are relatively opaque, Fig. 3). Some

damage to the hydrated oocytes may occur during slide preparation.

In some cases, the chorion may be ruptured and the yolk extruded.

Do not count empty chorions, and count only those fragments judged

to be major portions of the oocytes.

7. Batch fecundity (Y) for each female is calculated from the product of the number of hydrated oocytes (eggs) per unit weight in the

tissue sample and the ovary weight (left and right sides combined)

(2).

8. The egg production method requires that batch fecundity be expressed as a function of female weight and not length, i.e., EY =

few) where female weight (w) is the formalin wet weight of the female

without the ovary (formalin wet weight can be converted to live

weight using coefficients given in Hunter 1985). We use ovary-free

wet weight of females since females with hydrated ovaries temporarily

have a higher weight than the average female because of the increased

weight of the hydrated ovary. The ratio of female body weight without ovary to female weight with ovary (excluding females with

hydrated or immature ovaries) can be used to convert ovary-free wet

weight to total body weight. This ratio in northern anchovy was 0.95

for female anchovy taken 1978-79 (Hunter and Macewicz 1980).

Oocyte Size-Frequency Method

If the number of females with hydrated oocytes is insufficient for

a batch fecundity estimate, the more time-consuming oocyte sizefrequency distribution method can be employed (MacGregor 1957).

This method takes 1-3 h per fish (3 tissue samples per fish) as compared with 1-1.5 h for the hydrated oocyte method. In this method,

a size-frequency distribution of oocytes is constructed and the most

advanced modal group of oocyte size classes (the mode composed

of the largest oocytes) is determined by inspection. The total number

of oocytes within the oocyte size classes that constitute the advanced

modal group is considered to be the spawning batch. This method

usually gives results similar to those based on counts of hydrated

oocytes if females with highly advanced oocytes are used (Hunter

and Goldberg 1980; Laroche and Richardson 1980). The mean size

of the group of oocytes that constitutes the most advanced spawning batch should be ~0.5 mm, as estimates of batch fecundity are

somewhat inflated if a less mature ovary is used (Hunter and

Goldberg 1980).

In northern anchovy, a tissue sample weight of ~10 mg will insure that about 100 oocytes are included in the most advanced modal

group of oocytes. All oocytes ~0.3 mm in a tissue sample are counted

using a set of hand counters and measured to the nearest 0.05 mm.

We use an optical comparator at 50x magnification and measure

the oocytes with a rule on the viewing screen of the comparator.

A starting oocyte size ~0.3 mm is recommended to insure that a

Figure 3.-Hydrated oocytes in a tissue sample taken from a northern anchovy ovary preserved in formaldehyde solution. A. Hydrated oocytes;

B. Unyolked and yolked oocytes (before hydration); C. Empty chorion of a hydrated oocyte (the chorion, or a major fragment of it, would he

included in the count of hydrated oocytes for the batch fecundity estimate). These hydrated oocytes were 1.2 mm long in the major axis.

70
sufficient number of 0.05-mm oocyte size classes exist below the

most advanced modal group. Inclusion of these small oocyte size

classes insures an accurate separation of the tail of the advanced

mode of oocytes from the smaller oocytes adjacent to it. To separate

the tail of the advanced modal group from the adjacent group of

smaller oocytes, we use probability paper analysis (Harding 1949;

Cassie 1954). In other respects, the oocyte size-frequency method

is the same as the hydrated oocyte method, and the previous section can be used as a guide.

ACCURACY AND PRECISION _

In this section we develop methods to evaluate the accuracy and precision of estimating batch fecundity using the hydrated egg methodology, and apply these procedures to northern anchovy fecundity data.

Accurate estimation of batch fecundity depends upon selection of

an unbiased location for the samples of ovarian tissue and the selection of an appropriate regression model to express the relation between female weight and batch fecundity. The precision of the

estimate depends upon the number of ovarian tissue samples taken

per female and the total number of females. The weight of the individual tissue sample also affects precision, but we have not considered this element. We have instead kept the tissue samples within

a weight range that yields about 100-200 hydrated oocytes per sample.

In the first subsection we use analysis of variance to detect the

possible effects of location of tissue samples within the ovary. In

this analysis we use a sample of 12 northern anchovy ovaries in which

6 tissue samples were taken per ovary at specified locations. In the

next subsection we determine how the number of tissue samples

affect the precision of the fecundity estimate; consider various

fecundity-weight models; and determine the optimum numbers of

fish and tissue samples for a given cost. For this analysis we add

an additional 12 fish to the sample used in the first section, all of

which had 6 tissue samples per fish. In the third subsection we use

seven data sets on anchovy batch fecundity taken 1951-60 and 1978-84

(n ranges, 19-127) to validate selection of the fecundity-female weight

model and to assess the precision of regression estimates of batch

fecundity. In the final subsections we consider how the number of

fish in the sample affects precision of the fecundity estimate and

how the batch fecundity varies among years.

Table I.-Effect of location of ovarian tissne samples from northern anchovy

on the number of hydrated eggs per nnit sample weight (g). Effects evaluated

by taking tissue samples (n = sample size) from three positions (two ends,

I and ill, and middle, ll) from both the right and left ovary. Analysis of

variance indicates insignificance of either side or position within a side (SS

= sum of squares; MS = mean square).

Positions Mean no. of eggs/g of ovary tissue

of sample Right ovary Left ovary Both ovaries

in ovary x n x n x n

I 5,237 740 12 5.143 1,158 12 5,190 950 24

1\ 4,919 790 12 5,243 831 12 5,081 810 24

III 5,296 1,005 12 5,540 2,019 12 5,418 1,564 24

All 5,151 845 36 5,309 1,396 36

Two-way analysis of variance of eggs/g of ovary tissue.

55 due to df 55 M5 F

Right vs. left ovary I 0.0053 0.0053 0.14

Position within ovary 2 0.0268 0.0134 0.34

Interaction 2 0.0269 0.0134 0.34

Error 66 2.5854 0.0392

Total 71 2.6444

be taken from any location or from either the right or left sides.

It should be noted, however, that all of our samples were offemales

taken at a time of day (1900-0100 h) when hydration was nearly complete. If females are taken earlier in the day, position effects may

be likely because hydration does not proceed at a uniform rate

throughout the ovary; rather it begins at the periphery and spreads

to the central section of the ovary, producing larger hydrated oocytes

(more mature) at the periphery than in the center. Thus the number

of hydrated oocytes per gram of ovary may be higher in the central

section and lower on the periphery at early stages of hydration. Variation in extent of hydration does not appear to be a major source

of error, but it should be evaluated prior to making a fecundity

estimate in a new species or when samples are taken at a new time

of day.

Optimum Number of Tissue Samples

and Numbers of Fish

for Fecundity Estimation

A. The general fecundity model-The true batch fecundity (y)

where all eggs are counted, and the fish weight relationship (w) is

defined as:

where the error term (A) has a mean = 0, and variance = ai. Y

and Yw are interchangeable in later sections. Since all the hydrated

eggs in a batch (Y) are not counted,f(w) are fitted to the estimated

batch fecundities (Y) calculated from m ovarian tissue samples per

fish.

In this section we develop equations to estimate the optimum number

of fish and tissue samples to be used for fecundity estimation using

data on the northern anchovy. The precision of the sample variance

(or mean square error) around the regression of batch fecundity on

female weight (a~) (a measure of the goodness of fit of the

fecundity-weight model) was used to determine the optimum number

of tissue and fish samples. This procedure required a definition of

a general fecundity model and development of functions to express

the error terms.

Location of Tissue Samples

Within the Ovary

To determine if location of the tissue samples affects estimates of

batch fecundity in anchovy, we took 6 ovarian tissue samples from

each of the 12 ovaries; three samples were taken from the left ovary

and three from the right. In each set of three, one sample was taken

in the center and the other two were about one-third of the distance

from each end of the ovary. The number of eggs per unit weight

of the ovary (x) was calculated for each tissue sample. We tested

effects of right or left ovarian side, and position of tissue samples

within a side, using the two-way analysis of variance. The natural

logarithm of x was used in the analysis because there is a positive

correlation between the same sample mean and its standard deviation. The assumption of homogeneity within sample variance is

violated when the means differ.

No difference existed either in the location of the tissue sample

within right or left sides of the anchovy ovary or between right and

left sides (Table I). Thus in northern anchovy, tissue samples can

71

Y", = j(w) + A (I)
Let's denote for the ith fish, i= I, ... ,n:

W j = gonad-free fish weight = fish weight minus gonad weight

= total number of hydrated eggs in the ovary

Yij = hydrated egg count in the )th tissue sample )=1, ... ,m

zij = weight of )th tissue sample

Zj = formalin wet weight of gonad

m = number of tissue samples from an ovary

Mi = maximum number of tissue samples in an ovary

Y,j = estimated total number hydrated eggs in the ovary from the

)th tissue sample = (yj/Zij)Zi

Yj = estimated total number of hydrated eggs in the ovary

m

= L Y,/m

)=1

Y = sample mean number of hydrated eggs = L Y,/n I

Yj = estimate of batch fecundity from the regre5sion model.

Suppose Yij is an unbiased estimate of Yj , then

The variance of the sample variance (s~) is used in the next section for computing the optimum number of ovarian tissue samples

for fecundity estimation.

B. Optimum number of tissue samples-Since the goodness of

fit of any model is measured by s~, we chose to minimize the

variance of s~ with respect to the number of tissue samples (m) for

a fixed total cost function (Scheffe 1959).

(7)

where c is the total funds available,

c, IS the cost of processing a fish, and

L': is the cost of processing a tissue sample.

Under the assumption of normality of the error terms, one obtains

the variance of s~ as:

Yij = Y; + Y;j - Y; = f (w) + Ai + ejj (2)

(8)

a} .. s/

0= - andO = - . (J'~ s)

mr(s}) = 2(J'~

The optimum sample sizes for selected parameter values are listed

in Table 2. The optimum tissue sample size (m) depends on the values

of each of the five parameters, i.e., q, () = a;/a~. c, C,. and c2.

where

(3)

= f(Wi) + ~j

where eij = Yij - is the within-ovary error term and is assumed

normally distributed with mean = 0 and variance = a;. Using

Equation (2) and the fact that

m

Yj = L Yij/m, we have

)=1

Y; = f(wj) + Ai + ei·

Thus the variance around the regression line based upon data set

(Y;, Wj) is composed of two variance components: One is ai and

the other is a;, the within-ovary variance. The unbiased estimates

of ai, and a~ are

The parameter q is the number of regression coefficients in the model

and n is the number of fish sampled. Most if not all fecundity regressions use only two coefficients (Bagenal 1967) and consequently

we use q = 2 in this article, and subsequent computations should

be redone if q>2. For simplicity, we assume that Mj = Mj = M

for ) * i, and a~ a~ = ar , J

2 2 Mj - m a'; ~i = Ai + ej. and a~ = eTA + -M - . 'im Table 2.-0ptimum number of ovarian tissue samples required for batch

fecundity estimation of northern anchovy with two regression coefficients

(q=2) and maximum tissue samples >30 within an ovary (M>30) for

various degrees of data variability (e=o; lo~) and cost constraints (clc,

and c,lc,).

Ratio of Total funds

within-ovary available for Relative index of

variance to estimated cost processing costs

variance per tissue (costs of fishlcost of

about the line sample sample (c,lc,)'

(0=0; lo~) (clc,) 0' 4

50 2 2 2

o = 0,5 200 2 3 3

10.000 2 3 3

50 2 3 3

0=1 200 2 4 4

10,000 2 4 5

50 3 4 4

0=2 200 3 5 6

10,000 3 6 7

50 3 5 4

11 = 3 200 4 7 8

10,000 4 7 9

50 4 6 4

11 = 4 200 5 8 10

10,000 5 9 II

50 5 6 4

11 = 5 200 6 9 11

10,000 7 II 13

*0 = case where cost of capturing fish is negligible relative to cost of fecundity estimate,

72

(6)

(4)

(5)

n-q

t IY; - f(w)P

i-I

22 M - meT;

eTA = eT~ - ~-;;;-

2 2 2_ M - m !!..... SA = S~ M m

and

and

Thus

where
The finite population correction factor (I-mlM) can be ignored for

M 30. This means that it is unlikely that the finite population

correction will ever be used because it is very unlikely that a tissue

sample as large as 1/30 of the ovary weight would ever be used in

a fecundity estimation. Hence, an infinitely large M (M 30) can

be used for all calculations.

To evaluate the adequacy of Equation (3), we compute a ratio of

01 and o~, Le., K = 0110~; K 1. A large K implies the variation

in Equation (3) is too high and a larger sample size is desirable.

When K is close to I, the precision of Equation (3) is nearly as good

as that of Equation (I) which uses the true fecundity where all eggs

in a batch are counted. K is computed from the following equation:

(9)

and

K=-= - s/ [I---II-0+ I· s} m M

Table 3 gives K values for number of tissue samples ranging from

I to 6 for e = 0.5-0.6. K can be computed easily for other values

of eand number of possible tissue samples within an ovary. The

precision of Kdepends on the variance of s1 and s~ and the cost

function for processing the fish and making the fecundity estimate

[Equation (7)]. Costs dictate the number of fish used and the number

of tissue samples taken per fish.

To evaluate K for different cost functions (hence sample sizes),

it is necessary to select a proper function to express the relationship between fecundity and female weight, few). We used four

models and the data set of 24 fish (Table 3). The four models were:

fl(w) = awb + e

hew) = aebw + e

f3(w) = a + b In(w) + e

f4(w) = a + bw + e·

The linear model had the greatest precision because it had the lowest

s1 and s~ (Table 3). The linear model also seems a preferable

method of expressing the fecundity-weight relationship in northern

anchovy when much larger data sets are considered (see next

section).

The parameter e= s;ls~ (a measure of the relative variability

within tissue samples) ranged from 0.5 to 0.6, depending on the

regression model selected for the 24-fish sample. In our case, the

cost (Cl) of catching and curating a single fish is negligible relative

to the cost (c2) of counting the hydrated eggs in a tissue sample

because many fish must be taken for the spawning frequency estimation. Thus for northern anchovy, C/C2 f\J O. Using Table 2, the optimum number of tissue samples (m) is 2. For m=2, and e=;0.5,

K=1.3 [Equation (9)]. This means that the variance around Equation (3) is about 1.3 times that of the model based on counts of all

hydrated eggs in the ovary [Equation (I)]. To reduce the Kvalue,

more tissue samples are needed which increases the total cost (c).

For northern anchovy, there is no reason to increase the number

of tissue samples beyond three, because the reduction in Kbecomes

negligible at larger sample sizes (Table 3).

Validation of the regression model

In the previous section we concluded that the linear model for expressing the relation of female batch fecundity to female weight was

preferable, but we used a small data set (n = 24) in which 3-6 tissue

samples were taken per fish. In this section w~ test and evaluate

this conclusion by fitting a linear model Ciiw=y + b(w-w» and

two nonlinear models CY = aebwand Y= awb) to all existing data

sets on the fecundity of northern anchovy (1950-84) (Tables 4 and

5). In these sets the number of tissue samples per fish varied from

I to 3. Mean square error (MSE) = L(Y-Yf/(n-2) was computed

for all three models for each data set. Although no apparent difference existed among MSE values for the three models, and no

pattern existed in the residuals (Fig. 4), the simple linear model

is preferable because: I) it explains as much variation as the curTable 3.-Effect of ovarian tissue samples taken per ovary (m) on the ratio K for various models that

express the relation between female weight, w (without ovary) and batch fecundity, V.'

Maximum no.

of tissue ts; IK for 1-6 tissue samples/ova Regression i( samples *s~

model few) (x \03) (M) (X \03) 52

A 2 4 6

(I)mJ' 6.302 5.729 0.60 1.60 1.30 1.20 1.15 1.12 1.10

a = 325.07 80 5.772 0.60 1.59 1.29 1.19 1.14 1.11 1.09

b = 1.2423 30 5.844 0.59 1.57 1.28 1.18 1.13 1.10 1.08

(2) aeb. 7,112 6,539 0.53 1.53 1.27 1.18 1.13 1.11 1.09

a = 3,281.28 80 6,582 0.52 1.5\ 1.25 1.17 1.12 1.10 1.08

b = 0.0612 30 6,654 0.50 1.50 1.24 1.16 1.11 1.09 1.07

(3) a+b In(w) 6,274 5.702 0.60 1.60 1.30 1.20 1.15 1.12 1.10

a =-31,831.73 80 5,744 0.60 1.59 1.29 1.19 1.14 1.11 1.09

b = 15,371.04 30 5.816 0.59 1.57 1.28 1.18 1.13 1.\0 1.08

(4) a+bw 6,220 5,648 0.61 1.61 1.31 1.20 1.15 1.12 1.\0

a = 3,190.38 80 5,690 0.60 1.59 1.29 1.19 1.14 1.11 1.09

b = 838.11 30 5,762 0.60 1.58 1.28 1.18 1.13 1.10 1.08

'From equation (6).

tWithin-ovary variance (5;) = 3,436x103 from Equation (5); ratios computed using 7 digits.

IK is a measure of the variance around regression line relative to the "free" variance around the curve

(Equation (I). When K = I, the variance from subsampling ovarian tissue is 0 since all eggs are counted.

73
Table 4.-Sample statistics for batch fecundity estimation of the central subpopulation of northern

anchovy for various years. (See Addendum for 1985 data.)

Statistic 1951-60" 1978 1979 1980 1981 1982 1983 1984

n t 19 23 44 33 127 109 83 87

Linear regression 532 279 693 563 752 617 588 532

coefficient (b)

Linear regression 1,122 2,023 -4,410 -1,891 -1,979 -180 -1,002 -554

intercept (a)

Sy·x; 2,752 3,103 2,935 1,276 2,522 2,583 1,282 1,281

Sample me~n batch 10,270 7,546 8,506 7,745 9,083 10,031 5,828 5,862

fecundity (y)t

Sample mean ovary- 17.18 19.76 18.64 17.10 14.70 16.54 11.63 12.06

free fish weight (w)t

Sample standard 6.57 6.62 5.32 4.77 5.81 4.41 4.75 5.54

deviation of fish

weight (sw)

I(w-w)2 777 964 1,208 728 4,253 2,100 1,850 2,639

Mean fish weight 17.50 16.20' 18.60 12.90' 12.02

f,:?m survey 13.40 11.20

(w) 9.63

Standard error of 0.96 0.471 0.37 1.56' 0.46

fish weight (s;;) 0.52 0.79

0.37

Adjusted mean batch 8,900 4,597 6,241 6,423 9,237 9,055 7,870 7,640

fecundity for ovary-free

fish weight = 14.95 g§

Standard error of 536 494 358 408 207 225 264 256

batch fecundity for

14.95 g fish §

"From MacGregor (1968).

'Sample mean batch fecundity 0') and mean fish weight (w) are computed from data set with n fish.

;Standard deviation about the line.

§Computed from analysis of covariance.

'Computed from individual cruises (1981 values for two cruises and 1983 for three cruises).

vilinear model; 2) its regression coefficients have a simpl~ biological

meaning (b = batch fecundity/gram female weight, Y = mean

batch fecundity); and 3) for the egg production estimate, the fecundities of the largest and smallest fish are not as critical as for the

fish in the middle range, which is well explained by the simple linear

model.

Analysis of these eight data sets also indicated that the standard

deviation of the batch fecundity is a linear function of the female

weight (R2 ranges from 0.2 to 0.6). The minimum variance and unbiased estimates of the regression coefficients can be obtained

through a weighted least squares regression with the inverse of thl::

variance as the weight (Draper and Smith 1981). In most cases the

standard errors of regression coefficients from the weighted least

squares were smaller than those from the regular least squares.

Precision of Batch Fecundity Estimation

and the Numbers of Females

In the previous sections, we have considered the optimum number

of ovarian tissue samples of northern anchovy relative to costs and

have examined various regression models for biases in expressing

the fecundity-fish weight relationship. This analysis indicated that

if two or three tissue samples per fish are taken, further precision

can be obtained only through increasing the numbers of fish in the

sample, and we also showed that for anchovy the simple linear model

is the preferred regression model. The objective of this section is

74

Table 5.-Mean square error (MSE)* of linear (unweighted and weighted)

and nonlinear (exponential and power function) models for relationship

between batch fecundity and fish weight of northern anchovy, based on

data sets by years.

Regression models

Linear Nonlinear

Power Sample

Unweighted Weighted Exponential function size

Year (xlO-6) (xlO-6) (n)

1951-60 7.6 9.0 7.3 7.5 19

1978 9.6 8.3 10.2 8.1 23

1979 6.5 7.4 7.8 8.3 44

1980 1.6 1.5 1.5 1.5 33

1981 6.4 5.6 7.1 6.4 127

1982 6.8 4.9 6.7 6.6 109

1983 1.7 1.9 1.9 1.6 83

1984 2.2 1.3 3.5 2.3 87

"MSE = I(Y-i)l/(n-2) where Yis the estimated batch fecundity from subsamples. MSE, rather than Tf-, is used to measure the fitness of the model

because Tf- is inappropriate for nonlinear equation;.

to determine the effect of the number of females on the precision

of the regression estimates of batch fecundity (Y) using the linear

model. All the historical data for batch fecundity in the northern

anchovy (1951-84) were used in this analysis.

The average batch fecundity for the spawning population can be

estimated (Yw)from a regression model where wis an average of

ovary-free female fish weight for the survey. Batch fecundity is based
0 0

0 • • '2 ,. 20 2. 2. 32 0 • • 12 ,. 20 2' 2. 32

20 20

1$78 1982

,. ,. ° 00./'

.2 12 ),....• . . / /. .0 0 ' :','

· ..

'. .

0 0 ,. 20 2. 2. 32 0 • • 12 ,. 20 2. 2. 32 0 • • 12

,.

12

• 2

(10) u 2.[1. + _(:....-w_·_-_w....:...)2....,..}

n I,(w-w)2

on ovary-free weight whereas the weight of each female in the survey

includes the ovary weight. Thus the mean weight of females (w)

in the survey must be adjusted to ovary-free weight to estimate the

batch fecundity for the average female in the population. This is

done by multiplying female weight by 0.95, i.e., w= 0.95' w

(Hunter and Macewicz 1980) (Table 4). The average female weight

in the fecundity samples (w) may be different from wbecause the

fish used iIi the fecundity estimate are a small subsample of the

thousands of mature fish taken in a survey. Hence, wis preferable

for biomass estimation. Generally speaking, wand ware similar

although occasionally the difference has been as great as 2 g.

The precision of the regression estimate of batch fecundity is

measured by its coefficient of variation, cv(Yw). The variance of Y,.,.

for a particular fish weight # is equal to

where a2 is the variance around the regression line (estimated by

s~) and # is measured without error. To evaluate the effect of

numbers of fish on the precision of the regression estimate, we

calculated the cv of Ywand Yw-2 for each of the data sets. Four

elements affecting the variance of Yw* are a2 , n, #, and the sums

of squares (L(w-w)2). Although the variances of fish weight (s~)

are quite similar among years, the sum of squares (L(W-w)2 =

(n-l)s~) are different (Table 4). A small value of a},.,. results from

either a large n and/or a wide range of fish weights. Increasing sample

size n and/or increasing L(W-W)2_ reduces a},.,. .

The coefficient of variance of Y;v was expressed as a function of

the number of fish in the fecundity sample. For this analysis we

used two versions of the power function (cv(Ywln) = (xonP): One

in which wis assumed to be the same as wand the other in which

wis equal to w-2 [Equations (11) and (12)]. In the latter equation,

the cv of Yw- 2 sets the upper bound for the cv of Y;v .

..,

1881

./ 1083 .:./

/

.. <.:' .......

• #.... :::

- "

·l·i.:... '.0 " , '/.:-;/..- ,. "0 • . _.' .

12

oo!-'--!-.-"--;;.~'::-2 L'-!;;.-'-;;';2O:"-::2';-"-;2~. "-:.-='2

..

20

,.

1079

12

12

20

,.

)(

'"

"

"

W

C

W

I-

..

II:

C

>

:z: 20

..J

..

Io '6

I-

"o

°0 I ~! 8 12 16'~ 24'28';2'

20

2. 1975-77 cv[ Yw- 2 In) = 0.644n-O.

735

(11)

(13)

cv[ Yw In) = 0.438 n- (12) O.

561

For a sample size of 20 fish, the cv of Y;v falls between om and

0.08, and for a sample size of 60 it ranges between 0.03 and 0.04

[depending upon whether Equation (11) or (12) was used] (Fig. 5).

Assuming that the coefficient of variation for the fecundity estimation should be less than 0.10, one should select a sample size that

yields a cv of Y;v = 0.05 because Equations (11) and (12) assume

the fish weight (w) is measured without error; thus, for northern

anchovy, a sample size of 50-60 females is adequate. In the biomass

estimation, the cv for the fecundity estimation is a function of

variances of both Y;v and w. The variance formula for the fecundity estimate including variance of wis given below.

•

ou,...."-'---':-'---L-LL."-'---':-',.-J-LL.:,:-"

a 6 12 16 20 24 28 32 36

1980 2. I. 20

12 ./

fOO' I. .. ;I 12

..

GONAD FREE WET WEIGHT (g)

Figure 4.-Relation between batch fecundity of northern anchovy and their weight

in formaldehyde solution (less ovary) for various years and subpopulations. AIl

panels except lower right are for central subpopulation; lower right is for northern subpopulation, 1975-77, from Laroche and Richardson (1980). Fecundity

estimates for the central population for 1951-60 are from MacGregor (1968) and

are estimated using the oocyte frequency distribution method. Equations for lines

are given in Table 4 for central subpopulation. For northern subpopulation Y =

-5287 + 1098 w, If = 0.55 (our calculation from Laroche and Richardson 1980).

75
84 85

I

82 83

I I

79 80 81

YEAR

78

4

6

2

>

le

z

::)

o

W

II.

J:

o

I-

<

m

c

w

l-

(/)

::)

..,

C

< OL--_l------JL....-........J_--J._--J._--.l.._---'-_....J

1951-60

...- .......

6-cv(yw) --

.-CV(Yw-2gm)- - --

0.10 •

6

0.08 \

\

\

\

\ • \

\

0.06 ,

,,

'> ~,

u ",

"- , 0.04 •

6

0.02

20 40 60 80 100 120

NUMBER OF FISH SAMPLED

Figure 5.-Coefficient of variation (ev) of the regression estimates of batch fecundity for the average female anchovy weight as a function of the number of fish used

to estimate fecundity in various years (see Table 4). Solid line is the ev for the

average weight of females in the fecundity sample, and dashed line is the upper

bound of the ev for the average female weight in the population.

Figure 6.-Adjustcd batch fecundity estimates for average female weight equal 10

14.95 g, and the 95% confidence interval (represented by vertical bars) by years

(see Table 4).

Variation of Batch Fecundity Among Years

The relation between batch fecundity and fish weight has been

estimated annually for the egg production biomass estimation of

northern anchovy because we believed that the relationship could

change from year to year. Otherwise one equation would suffice

for all years. To test this assumption, we performed an analysis of

covariance to compare batch fecundity per female weight (regression coefficients, b) among years. The results show that not all slopes

are the same, and have ranged from 'D9 eggs/g in 1978 to 752 eggs/g

in 1981 (Table 4). Moreover, the average batch fecundity for a female

of 14.95 g (the mean weight of all females in the fecundity samples

when all samples are combined) also differs significantly among

years (Fig. 6). The average number of eggs produced per spawning

by a standard female of 14.95 g has varied by a factor of 2 over

the last 7 yr (1978-84). This does not take into account the variation

in average weight of females in the spawning population which also

shows significant interannual variation. No doubt exists that batch

fecundity of the northern anchovy population varies interannually

and that it is necessary to estimate batch fecundity for each biomass

estimation. On the other hand, if an average fecundity for all years

(1951-84) is necessary, the following equation can be applied:

Yw = -1104 + 614 w.

SUMMARY _

') In northern anchovy, location of the tissue sample within the

ovary has no effect on counts of hydrated eggs. Location of tissue

samples may be important in fishes with larger ovaries or possibly

in anchovy in the earliest stages of hydration. Thus, position effects

must be evaluated for each species and sampling time.

3. The optimum number of tissue samples was 2 or 3 per ovary

in northern anchovy, but a higher number may be necessary if position effects exist.

4. To maintain the coefficient of variation for the average fecundity of the population at less than 10% requires a sample of 50 or

more females.

5. In northern anchovy, a simple linear regression model was

preferable to nonlinear models for expressing the fecundity-female

weight relation but this must be evaluated for each population.

6. For the egg production estimates, the average batch fecundity

of the population can be calculated from the average weight of the

females in the population (based on a weighted sample mean) using

batch fecundity-female weight regression model.

7. The batch fecundity of northern anchovy has varied significantly

among years 0951-84) indicating the batch fecundity-fish weight relation must be estimated for each egg production estimate.

1. Laboratory methods are described for estimating the batch

fecundity of fishes with indeterminate annual fecundity using counts

of the number of hydrated eggs within weighed tissue samples of

the ovary.

76
LITERATURE CITED _

BAGENAL, T. G.

1967. A short review of fish fecundity. In S. D. Gerking (editor), The biological

basis of freshwater fish production, p. 89-1tt. John Wiley, N.Y.

BLAXTER, J. H. S., and J. R. HUNTER.

1982. The biology of the clupeoid fishes. Adv. Mar. BioI. 20:1-223.

CASSIE, R. M.

1954. Some uses of probability paper in the analysis of size frequency distribution. Aust. J. Mar. Freshwater Res. 5:513-522.

DeMARTINI, E. E., and R. K. FOUNTAIN.

1981. Ovarian cycling frequency and batch fecundity in the queen fish, Seriphus

polilus: Attributes representative of serial spawning fishes. Fish. Bull., US.

79:547-560.

DRAPER, N. R., and H. SMITH.

1981. Applied regression analysis, 2d ed. John Wiley, N.Y., 709 p.

FULTON, T. W.

1898. On the growth and maturation of the ovarian eggs of the teleostean fishes.

Annu. Rep. Fish. Board Scotl. 16:88-124.

HARDING, J. P.

1949. The use of probability paper for the graphical analysis of polymodal frequency distributions. J. Mar. BioI. Assoc. U.K. 28:141-153.

HICKLING, C. F., and E. RUTENBERG.

1936. The ovary as an indicator of the spawning period in fishes. J. Mar. BioI.

Assoc. UK. 21:311-317.

HISLOP, J. R. G.

1975. The breeding and growth of whiting, Merlangius merlangus in captivity.

J. Cons. int. Explor. Mer 36: 119-127.

HISLOP, J. R. G., A. P. ROBB, and J. A. GAULD.

1978. Observations on effects of feeding level on growth and reproduction in haddock, Melanogrammus aeglefinus (L.) in captivity. J. Fish. BioI. 13:85-98.

HOLDEN, M. J., and D. F. S. RAITT.

1974. Manual of fisheries science. Part 2-Methods of resource investigation and

their application. FAO Fish. Tech. Pap. lIS (Rev. I), 214 p.

HUNTER, J. R.

1985. Preservation of northern anchovy in formaldehyde solution. In R. Lasker

(editor), An egg production method for estimating spawning biomass of pelagic

fish: Application to the northern anchovy, Engraulis mordax, p. 63-65. U.S.

Dep. Commer., NOAA Tech. Rep. NMFS 36.

HUNTER, J. R., and S. R. GOLDBERG.

1980. Spawning incidence and batch fecundity in northern anchovy, Engraulis

mordax. Fish. Bull., US. 77:641-652.

77

HUNTER, J. R., and R. LEONG.

1981. The spawning energetics of female northern anchovy, Engraulis mordax.

Fish. Bull., US. 79:215-230.

HUNTER, J. R., and B. J. MACEWICZ.

1980. Sexual maturity, batch fecundity, spawning frequency, and temporal pattern of spawning for the northern anchovy, Engraulis mordax, during the 1979

spawning season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

1985. Measurement of spawning frequency in multiple spawning fishes. In R.

Lasker (editor), An egg production method for eStimating spawning biomass

of pelagic fish: Application to the northern anchovy, Engraulis mordax, p.

79-94. US. Dep. Commer. , NOAA Tech. Rep. NMFS 36.

JOSEPH, J.

1963. Fecundity of yellowfin tuna (Thunnus albacores) and skipjack (Ka/suwonus

pelamis) from the eastern Pacific Ocean. Inter-Am. Trop. Tuna Comm., Bull.

7:255-292.

LAROCHE, J. L., and S. L. RICHARDSON.

1980. Reproduction of northern anchovy, Engraulis monlax, off Oregon and Washington. Fish. Bull., U.S. 78:603-618.

LeCLUS, F.

1977. A comparison of tour methods used in fecundity determination of the

pilchard, Sardinops ocella/a. Fish. Bull., S. Afr. 9:1l-15.

1979a. Dry mass yolked oocytes of the South West African pilchard Sardinops

ocellata in relation to maturity stages and spawning cycles, 1972-1974. Investl.

Rep. Sea Fish. Brch. S. Afr. 119, 29 p.

1979b. Fecundity and maturity of anchovy Engraulis capensis off South West

Africa. Fish. Bull., S. Afr. 1l:26-38.

MacGREGOR, J. S.

1957. Fecundity of the Pacific sardine (Sardinops caerulea). Fish. Bull., US.

57:427-449.

1968. Fecundity of the northern anchovy, Engraulis mordax Girard. Calif. Fish

Game 54:281-288.

SCHEFFE, H.

1959. The analysis uf variance. John Wiley, N.Y., 477 p.

YAMAMOTO, K.

1956. Studies on the formation of fish eggs. I. Annual cycle in the development

of ovarian eggs in the flounder, Liopsel/a obscura. J. Fac. Sci. Hokkaido Univ.,

Ser. VI, ZooI. 12.

ADDENDUM _

Since this volume went to press an additional estimate of the biomass

of the central subpopulation of northern anchovy was made in 1985.

Batch fecundity parameters (listed in Table 4) for !..985 were as

follows: n, 85; b, 682; a, -2,03~; Syx' 1,936; Y, 8,490; W,

15.43; s.., 4.26; (w-wf, 1,524; w, 14.50; s;;;, 0.32; adjusted

mean batch fecundity for 14.95 g fish, 8,156; and standard error

of batch fecundity for 14.95 g fish, 211.
78
Measurement of Spawning

Frequency in Multiple

Spawning Fishes

1. ROE HUNTER and BEVERLY 1. MACEWICZ

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

Methods for estimating the frequency ofspawning in natural fIsh populations using

histological criteria are described using the northern anchovy, Engraulis mordax,

as an example. Illustrations and descriptions are provided of oocytes in mature

ovaries, postovulatory follicles, and atretic follicles. Postovulatory follicles are used

to estimate frequency of spawning, and atretic follicles (which may be confused

with postovulatory follicles) are useful in estimating size at fIrst maturity. Postovulatory follicles of four common commercial fIshes, Sardinops sagax, Mer/uedus gayi, Scomber japonieus, and Euthynnus linealus, are also described and illustrated. Methods for estimating spawning frequency other than ovarian histology

are also discussed, as is testing of the assumption of determinate annual fecundity in multiple spawning fIshes.

79

INTRODUCTION _

The egg production method of biomass estimation requires an

estimate of spawning frequency. This requirement exists because

the method was developed for fishes, such as the northern anchovy,

which have indeternlinate annual fecundity. In such, the standing

stock of advanced oocytes gives no indication of annual fecundity

because new spawning batches are recruited from small, unyolked

oocytes during the spawning season. Thus, the rate of egg production can be calculated only from estimates of spawning frequency

and batch fecundity made during a survey period. On the other hand,

in some multiple spawning boreal fishes, including haddock,

Melanogrammus aeglefinus, and whiting, Merlangius merlangus

(Hislop 1975; Hislop et al. 1978; Hislopl), and other fishes

(Yamamoto 1956), the stock of oocytes destined to be spawned in

a season is identifiable at the beginning of the season. In such fishes,

annual fecundity may be considered to be determinate even though

the fishes may spawn repeatedly during the season and the standing

stock of advanced oocytes at the beginning of the season is considered to be equivalent to the annual fecundity. Hence, estimates

of spawning frequency are unnecessary in fishes with determinate

annual fecundity as long as the biomass survey includes the entire

spawning period and nearly all of the stock of advanced oocytes are

actually spawned. In some cases, not all the standing stock of oocytes

are spawned and, consequently, potential annual fecundity is not

realized during the spawning season. Documentation of the existence

of determinate annual fecundity, and of its total utilization during

the spawning season, is essential if the standing stock of oocytes

is used to estimate spawning biomass. This is rarely done satisfactorily, and in a number of cases we believe the presumption of a

seasonally determined fecundity is probably false which may lead

to serious errors in biomass estimation. Estimation of the frequency

of spawning and batch fecundity is one way to test the assumption

of determinate annual fecundity.

The objective of this paper is to describe the methods for

estimating frequency of spawning in natural fish populations. We

begin with a brief discussion of histological methods, followed by

a general description of the oocytes in an active ovary of northern

anchovy, Engraulis mordax. We then describe the estimation of

spawning frequency using aged postovulatory follicles (employed

in the current method for biomass estimation of northern anchovy)

and briefly discuss other methods. In the second section of the paper

we discuss ovarian atresia, because histologists must be able to

distinguish postovulatory follicles from atretic follicles, and knowledge of atresia is also necessary to separate postspawning females

from immature ones. In the final sections we discuss tests of the

assumption of determinate fecundity and future applications of

histological classification of ovaries.

Most of the descriptions and all of the data in this paper are for

the northern anchovy. Nevertheless we have tried to bring out important differences that may exist among species and to mention

methodologies other than the ones we use for northern anchovy.

HISTOLOGICAL METHODS _

All the techniques discussed in this paper involve, at least to some

extent, histological examination of fish ovaries. In this section we

briefly discuss the histological techniques used and comment on the

IJohn R. G. Hislop, DAFS Marine Lab., P.O. Box 101, Victoria Road, Aberdeen

AB9 8DB, Scotland, pers. commun. 25 Oct. 1983.
procedures and time required to use histological classification for

fish population work.

Histological preparation of tissues

Almost all northern anchovy ovaries histologically examined for postovulatory follicles were fixed in 10% neutral buffered Formalin

(NBF), embedded in Paraplast, and 6-Jilll serial sectioned slides were

made and stained by Harris' hematoxylin followed by Eosin counter

stain. This procedure gave good results, and specific steps can be

found in Luna (1968), Preece (1965), or most any histotechnique

handbook. It is also possible to use resin embedding, sectioning on

a rotary microtome, and Lee's Methylene blue-basic fuchsin staining (JB-4 Embedding Kit, Data Sheet No. 123, Polysciences, Inc.,

1982). This technique may be preferable for small ovaries or small

pieces of ovaries, although it is more difficult to get many serial

sections and may not be practical for larger ovaries.

In addition to the instructions given in standard histotechnique

texts, we found the following procedures and precautions to be useful in preparation of Hematoxylin and Eosin (H&E) sections of northern anchovy ovaries.

Fixation-Bouin's fixative gave better results than 10% NBF, but

it required transferring ovaries into 70% ethanol within 1-2 d or the

ovaries become hard and brittle. Transferring is possible in the

laboratory but at sea it is often impractical. It is important to fix

ovaries quickly and thoroughly, otherwise lysis or poor differentiation may occur. We insured proper exposure to fixative by slitting

the abdomen of fish before fixing. In larger fish it is best to remove

the whole ovary from the fish and preserve it separately. It is even

better to cut a I-cm section from the midsection and preserve it in

ample fixative. Initial freezing of whole fish or ovaries is not recommended; fixation after freezing results in poor-quality H&E sections in which postovulatory follicles cannot be consistently

identified, thus producing substantial errors in the estimation of

spawning frequency. In addition, the process of thawing may cause

lysis of hydrated oocytes.

Inflltration-Hardening of ovaries may occur if time spent in xylene

or toluene is not kept at a minimum or if temperature of paraffin

is not kept below 60°C.

Sectioning-It is necessary to have 10-20 good serial sections per

slide for histological analyses. Cold (4°C) blocks and knives usually improve sectioning. If shattering occurs, it is possible to soak

blocks (prefaced-off) in ice water for a short time (1-15 min) to improve sectioning with little or no shattering.

Mounting-Wiping slides with a very fme coat of Mayer's Albumen

Affixative and drying mounted slides are often necessary to keep

sections attached to slides. By mounting as many sections as possible on a slide, it may be possible later to microscopically trace questionable structures.

Staining-The standard procedure for Harris' Hematoxylin and

Eosin staining is quick and easy, and results in good staining of postovulatory follicles. Initially a trial run is necessary to find out the

optimal amount of time spent in each stain. Other stains, i.e.,

Mason's Trichrome, periodic acid-Schiff reagent, or Heidenhain's

iron hematoxylin, can also be used except they often require more

time or more elaborate techniques. These stains may be preferable

80

for study of structures other than postovulatory follicles, for example. nuclear changes in oogenesis.

Rates of Processing and Classification

The production of slides depends largely upon the capacity of the

automatic tissue infiltrator and the number of histotechnicians. In

small research laboratories (infIltrator capacity = 30 samples per

batch) production of 100-150 H&E slides (one ovary per slide) per

week for one person is close to the maximum rate of production.

Thus, for production work it is preferable to use commercial

histological laboratories where H&E slides can be produced more

quickly at a cost of (in 1983) about $4.00/slide.

The time required to classify each slide of ovarian tissue (about

10 sections per slide) depends upon the amount of detail recorded.

If only spawning frequency is estimated (ageing postovulatory

follicles and identification of hydrated oocytes), one person can

classify about 1,000 slides in 25 d (8 hId). Two to three times as

much time is required if all other significant histological characteristics of the ovary are recorded, including the presence and abundance of alpha through delta stages of atretic yolked and unyolked

oocytes and the relative abundance of oocyte classes. We have

employed this detailed system over the years to provide a complete

record of the condition of the ovary. However, our analysis indicates

that the system can be simplified by identifying only hydrated oocytes,

two age classes of postovulatory follicles, and by classifying ovaries

into three atretic states (defmed in a subsequent section). This reduces

classification time per ovary to nearly the equivalent of that required

to estimate only spawning frequency, yet the ability to identify major

changes in atretic condition, and to separate postspawning females

from immature females, is still maintained.

HISTOWGICAL CHARACTERISTICS

OF OOCYTES _

The northern anchovy is a multiple spawning fish (Hunter and

Goldberg 1980) with asynchronous oocyte development, i.e., oocytes

in many stages of development occur simultaneously in reproductively active ovaries (Wallace and Selman 1981). During the spawning season, oocyte development is a continuous process involving

all stages of oocytes, with a new spawning batch maturing every

week to 10 days in peak spawning months (Hunter and Leong 1981).

The average female anchovy spawns at least 20 times per yr, yet

within the ovary only 1-3 potential spawning batches of yolked

oocytes exist and fewer than 10 potential batches exist when all

oocytes >0.1 mm are included (Hunter and Leong 1981). Oocytes

~0.1 mm constitute the reservoir of oocytes that are present in ovaries

year-round in inactive as well as active ovaries. Little or no atresia

occurs among oocytes in this size range. Thus, in anchovy spawning, batches must be recruited from the reservoir of oocytes ~O.l

mm to account for the observed frequency of spawning. This means

the fecundity of northern anchovy is clearly seasonally indeterminate.

Oocyte development and maturation in teleosts, reviewed recently by Wallace and Selman (1981), has been frequently subdivided

into many stages (Yamamoto 1956; Lambert 1970b), but a simpler

histological classification system seems appropriate for the purpose

of this manual. We have combined the stages of past authors into

four oocyte classes (unyolked, partially yolked, yolked, and

hydrated), and we describe below for the northern anchovy the

histological characteristics of each class.
Unyolked Oocytes

This class includes all oocytes without yolk that are between about

0.04 and 0.35 mm (Fig. la, b). Oocytes <0.04 mm are excluded

because they consist mostly of "oogonial nests," have no true follicle layer, and appear not to undergo degeneration (Fig. lb). The

smaller oocytes within this class (0.04-0.15 mm) are spherical, have

a large nucleus, and have cytoplasms that are narrow, homogeneous,

and very densely stained with hematoxylin (Fig. Ib). A very thin,

single layer of elongated, spindle-like cells (the beginning of the

granulosa layer) surrounds these small oocytes. The large oocytes

in this class are oval; their cytoplasm stains faintly with hematoxylin and has a cloudy, mottled appearance (Fig. ld). The oval nucleus

of these oocytes contains several nucleoli and is surrounded by a

granular perinuclear zone. In these larger oocytes a thin, definite,

hyaline membrane which has a faint eosinophilic stain (percursor

of the zona radiata) appears between the oocyte and the growing

follicle. The follicle consists of a narrow, single, inner layer of

cuboidal granulosa cells and a single outer layer of flat elongated

thecal cells with some blood capillaries. The larger oocytes also

may have some small vesicles in the periphery of the cytoplasm.

These vesicles are at times difficult to distinguish and they seem

to disappear in yolked oocytes. No oil vacuoles exist, as northern

anchovy eggs do not contain oil droplets.

Partially Yolked Oocytes

Oocytes in this class are in the early stages of yolk deposition

(vitellogenesis) and range in size from 0.3 to 0.5 mm (major axis)

(Fig. ld, g). The class includes oocytes in the initial stage of yolk

deposition up to and including those in which yolk granules or

spherules extend 3/4 of the distance from the periphery to the

perinuclear zone. Yolk deposition starts at the periphery of the oocyte

cytoplasm as small eosinophilic staining granules and then subsequently spreads internally until it nearly reaches the finely granular

perinuclear zone. Usually by this time the granules have become

small spherules. The oval-shaped nucleus of oocytes in this class

contains several nucleoli. At the time yolk appears in the oocyte,

delicate striations appear on the hyaline membrane between the

oocyte and follicle layer and it is henceforth referred to as the zona

radiata. As maturation proceeds, the follicle layer becomes wider

due to an increase in the width and proliferation of the granulosa

cells. The thecal cells do not increase in size but remain elongated,

flat cells with occasional blood capillaries, and form a thin outer

covering to the follicle. The thecal cells do not change until hydration, when they become even flatter arid have a stringy appearance.

Yolked Oocytes

Oocytes in this class range from 0.45 to 0.80 mm (major axis) and

all contain yolk spherules or globules throughout the region between

the periphery of the oocyte and the perinuclear zone (Fig. le, d).

As vitellogenesis continues, the yolk varies from spherules in the

smaller oocytes to large globules in the larger ones. Just prior to

spawning «24 h) the globules fuse to form yolk plates (Fig. lh).

Such oocytes are excluded from this class, since this characteristic

is diagnostic of the last (hydrated) class of oocytes. The nucleus of

oocytes in the yolked class is oval with numerous nucleoli and is

centrally located until just before hydration, when it migrates to the

animal pole. The granulosa cells have a wide rectangular shape in

81

cross section and a large oval nucleus; their walls are clearly evident in sagittal section where they form polyhedrons. The zona

radiata is a wide, striated, eosinophilic band until hydration, when

it stretches thin and the striations seem to disappear.

Hydrated Oocytes

These oocytes range in size from 0.75 to 1.2 mm (major axis) (Fig.

Ig, h). Hydration (rapid uptake of fluid by the follicle; Fulton 1898)

begins at about the time the nucleus has completed its migration

to the animal pole (Fig. Ie, f) and yolk globules have begun to fuse,

forming yolk plates. The nucleus of a hydrated oocyte is not visible

because after the nucleus has arrived at the animal pole the nuclear

membrane disintegrates, dispersing its contents into the cytoplasm.

During hydration, all yolk globules fuse into plates and the oocyte

expands greatly, stretching the granulosa and thecal cell layers. At

this time the granulosa cells in cross section appear as long, thin

rectangles, the thecal cells are extremely flat and have a string-like

appearance, and the zona radiata is very thin and lacks striations.

Hydrated oocytes are the most ephemeral of all oocyte classes since

this stage lasts for less than a day, whereas the other stages are always

present in reproductively active anchovy ovaries. Migratory nuclei

may be seen as early as 24 h before ovulation, but hydrated oocytes

in which all globules are fused to form yolk plates do not occur

earlier than 12 h before spawning. We have observed no atresia in

hydrated oocytes; apparently, in northern anchovy, nearly all hydrated

oocytes are ovulated.

The hydrated oocyte stage in northern anchovy begins when the

nuclear membrane disintegrates and ends at ovulation. As this was

an arbitrary decision, the duration of this stage could be increased

by including the period of nuclear migration. This broader definition of the hydrated stage might be useful when sampling occurs

before complete hydration or if hydration occurs very rapidly, as

might be the case in tropical fishes.

ESTIMATION OF

SPAWNING FREQUENCY _

Postovulatory Follicle Method

In northern anchovy, each hydrated oocyte is surrounded by a thinly stretched follicle of an inner, epithelial layer of granulosa cells

and a single, outer connective tissue layer of thecal cells with some

blood capillaries. At ovulation, the fully hydrated oocytes are released

from their encompassing follicles. The follicle does not fragment

and pass out of the ovary with the hydrated oocyte but retains its

integrity. The follicle collapses away from the opening formed for

the release of the hydrated oocyte into the lumen and remains in

the ovary as an evacuated follicle, or postovulatory follicle. Spawning occurs simultaneously with ovulation or in <60 min after ovulation. Initially, the postovulatory follicle is a distinct structure, but

it rapidly deteriorates and is resorbed. In northern anchovy, by 48

h after ovulation postovulatory follicles can no longer be accurately discriminated from the intermediate stages of atretic oocytes.

To use postovulatory follicles for estimation ofspawning frequency,

it is necessary to divide the deterioration and resorptive processes

of the follicle into a series of distinct histological stages, each with

an assigned age (time from spawning). This requires a series of ovary

samples taken at regular intervals from the time of spawning and

can be accomplished by spawning fish in the laboratory (Leong 1971)
a

Figure I.-Development of northern anchovy ovary at various magnifications. Stain = H&E; bar = 0.1 mm.

a) Immature ovary consisting of unyolked oocytes and no atresia.

c) Normal, mature ovary with many fully yolked oocytes 00.

e) Prespawning ovary showing oocytes in the migratory nucleus stage

(M).

g) Imminent «12 h) spawning ovary with hydrated oocytes (H) still

within their follicle layers. (U = unyolked; P = partially yolked.)

82

b) Enlargement of (a) showing small, spherical, unyolked oocytes (U)

with a large central nucleus and "oogonium nests" (0).

d) All stages of oocytes: unyolked (U), partially yolked (P), and yolked

(Y), are present in normal mature ovaries. (g = granulosa epithelial

cell layer; z = zona radiata; n = nucleus; y = yolk globules.)

f) Enlargement of a migratory nucleus oocyte (M). (n = nucleus;

y = yolk globules.)

h) Enlargement of a hydrated oocyte. Note that the yolk globules have

fused into yolk plates (yp), and there is no prominent nucleus due

to disintegration of the nuclear membrane.
or by sampling spawning schools over a 24-h period in the sea

(Goldberg et al. 1984; Alheit et al. 1984). The latter approach requires estimating the average time of spawning for the population

and has somewhat greater uncertainties than the preferable laboratory approach. At moderate temperatures (f\J16°C) we recommend

taking samples of at least 10 females with postovulatory follicles

at 4-h intervals for 3-4 d. At higher spawning temperatures, e.g.,

28-30°C, sampling at 1-2 h intervals might be required. Once the

classification criteria and stages are defined, it is necessary to conduct a blind classification of ovaries that include females with all

stages of postovulatory follicles as well as those without these structures. The classification system we employ for northern anchovy

is described below, and the results of the original blind classification are given in Hunter and Goldberg (1980), although our level

of accuracy has considerably improved since that initial test.

Age "0 Day" postovulatory follicles in anchovy-Included in age

O-day postovulatory follicles are those new, remnant, evacuated

follicles that are from 0 to 23 h old. In our surveys, however, we

include in this age those postovulatory follicles about 0 to 5 hold

since we trawl for northern anchovy only during the nightly spawning period (1800-0300 h). In laboratory-spawned females sacrificed

0-4 h after spawning, the new postovulatory follicles show no signs

of degeneration but they may undergo some structural changes. At

ovulation, while the follicle is collapsing, the follicle cell layers,

appearing cord-like, form loose folds or loops. The granulosa cells,

which had been extensively stretched during hydration, appear

elongated and narrow with a large prominent nucleus in the center

(Fig. 2a); the thinly stretched thecal layer thickens and becomes

more noticeable. After spawning, the fully collapsed postovulatory

follicle is a much more tightly folded or looped structure. It is

relatively large, irregular in shape, with an irregular lumen which

frequently contains eosinophilic granules of uncertain origin. The

granulosa cells of this new postovulatory follicle (age-O day) are

characteristically columnar or cuboidal and in some cases have

hypertrophied slightly; these cells are arranged orderly along the

edge of the lumen with their cell walls usually evident and possessing prominent nuclei. The nucleus of the granulosa cells may be

located at either the apex or base of the cell. In field-caught fish,

the follicles with apical nuclei appear to occur in fish taken near

the time of spawning and those having basal nuclei somewhat later

(Fig. 2b, c). After spawning, the thecal cell layer is more clearly

defined, adheres closely to the granulosa layer, and contains blood

capillaries.

We use the above characteristics of the follicle plus no signs of

follicle degeneration as the diagnostic characteristics of postovulatory

follicles of age O-day. Our surveys occur only at about the time of

spawning, about 1800 to 0300 h, an insufficient period for significant follicle degeneration to occur. Ifsampling times were extended

6-8 h or longer after the peak hour of spawning, early degenerative

follicle characteristics would have to be included as a characteristic

of age O-day postovulatory follicles. Degeneration appears to start

6-8 h after spawning in northern anchovy. The first sign of degeneration is the presence of a few pycnotic nuclei in the granulosa cells,

followed shortly by the migration of a few lymphocytes into the

postovulatory follicle; finally a few vacuoles appear in the granulosa

layer. In northern anchovy, all of these events occur before the postovulatory follicle is 12 hold.

Age "1 Day" postovulatory follicles in anchovy-Degeneration

is pronounced in postovulatory follicles examined about 24 h after

spawning. The characters we use to classify postovulatory follicles

83

as age I-day are those that appear between 19 and 28 h after spawning, since our surveys occur only near the time of spawning. We

describe follicles of age 19-28 h and subsequently discuss identification of older follicles.

By 19-28 h after spawning, the regressing postovulatory follicle

is greatly shrunken and has fewer folds, hence a less irregular form

than a new postovulatory follicle. The lumen, which is much reduced, may contain some granular material, although not as much

as occurs in the lumen ofO-day postovulatory follicles. The granulosa

cells of the follicle no longer have the orderly alignment characteristics of age O-day postovulatory follicles, although some pattern

in arrangement of cells can still be seen. Some of the nuclei of the

granulosa cells are pycnotic, vacuoles are common, and only few

of the cell walls are intact. The underlying layer of thecal cells is

present, although less distinct, than in an age O-day postovulatory

follicle (Fig. 3).

Postovulatory follicles older than 28 h in anchovy-Classification

beyond 28 h becomes difficult as the follicle continues to degenerate,

and by 48 h it may easily be confused with the beta stage of atretic

follicles (see section on atresia). A postovulatory follicle 48 hold

is one-half to one-fourth the size of 24-h-old follicles, the lumen

is much reduced or absent, and no eosinophilic granules are present. Cell walls are absent in the remaining granulosa layer tissue,

and a few vacuoles or pycnotic nuclei may be seen. The theca is

present but is often indistinct as it becomes incorporated into the

ovarian connective tissue stroma. The number of postovulatory

follicles in the ovary appears to be reduced by 48 h after spawning.

Fewer follicles may be present because they were resorbed or, alternatively, fewer may be seen per section because of the growth of

the larger oocytes. We believe that by 3-4 d after spawning all postovulatory follicles have been resorbed, although they might produce

a structure that is indistinguishable from delta-stage atretic follicles.

However, delta-stage atretic follicles are far less numerous in the

ovary than new postovulatory follicles.

Postovulatory follicles in other fishes-The structure of ovaries

among teleosts is relatively similar to anchovy especially in species

that spawn unadorned pelagic eggs. As far as we can ascertain, the

postovulatory follicles of such fishes differ only in minor details

from the descriptions we have provided for the northern anchovy.

The postovulatory follicles of the Peruvian anchovy, Engraulis

ringens, is identical in all respects to that of the northern anchovy,

regardless of follicle age, and hence will not be discussed further.

We illustrate and briefly describe postovulatory follicles of four other

species to indicate the variation in these structures among common

commercial fishes that spawn unadorned pelagic eggs of about I

mm diam. These fishes include Pacific sardine, Sardinops sagax,

Chilean hake, Merluccius gayi, chub mackerel, Scomberjaponicus,

and black skipjack, Euthynnus lineatus.

The new postovulatory follicle (near the time of spawning) of these

four species has the following characteristics in common with northern anchovy: a very convoluted shape with many folds or loops;

a lumen containing some granular or particulate material; a definite

granulosa epithelial cell layer lining the lumen; linearly arranged

granulosa cells of cuboidal or columnar shape which contain a prominent nucleus; a definite thecal connective tissue layer with blood

capillaries; and, most importantly, no degeneration of the follicle.

Various minor differences from anchovy in the appearance of a new

postovulatory follicle are mentioned below. The new postovulatory

follicles of chub mackerel seem to differ from anchovy only in the

presence of fewer granules in the lumen just after spawning (Fig.

4a, b). In the Chilean hake, the granulosa layer at the time of spawn-
Figure 2.-Postovulatory follicles 01 age o-day; elapsed time from spawning about 0-6 h. In a, b, and c, bar = 0.1 mm; in d, bar = 0.05 mm; g = granulosa

epithelial cell layer; t = thecal connective cell layer; and L = lumen of follicle.

a) At ovulation the postovulatory follicle (arrow) collapses away from the

hydrated oocyte (H).

c) Follicle with the nuclei (n) at the base of the granulosa cells (g). Elapsed

time from spawning is 1-6 h.

84

b) Newly collapsed follicle with nuclei (n) at the apex of the granulosa cells

(g). Elapsed time from ovulation <1 h.

d) Enlargement of follicle age O-day (from Hunter and Goldberg 1980).
Figure 3.-Postovulatory follicles of age I-day; elapsed time from spawning about 24 h. Degeneration of the follicle is pronounced by 24 h. In a, b, and c, bar

0.1 mm; in d, bar = 0.05 mm; g = granulosa epithelial cell layer; t = thecal connective cell layer; L = lumen of follicle.

a, b) Follicles from sea-caught anchovies; the next batch of yolked oocytes (Y) is evident.

c, d) Follicle from anchovy spawned in the laboratory (from Hunter and Goldberg 1980).

85
Figure 4.-New postovulatory follicles of four species of marine fishes. Bars = 0.1 nun; fJ = beta atresia; g = granulosa epithelial cell layer;

t = thecal connective cell layer.

a) Chub mackerel, Scomber japonicus, at ovulation, and

c) Chilean hake, Merluccius gayi. Histological material from S. R.

Goldberg, Whittier College, Whittier, CA.

e) Pacific sardine, Sardinops sagax, from Peru after spawning at sea.

Histological material from S. R. Goldberg, Whittier College, Whittier, CA.

86

b) 1 h after spawning (laboratory-induced with hormones). In both

sections (a) and (h), a single beta-stage atretic follicle (fJ) is present;

in (a), the atretic follicle contains 12-13 vacuolated areas which may

be remnants of the oil droplet.

d) Black skipjack, Euthynnus lineatus, at the time of spawning

(hydrated oocytes were in lumen of the ovary). Histological material

from K. Schaefer, IATfC, La Jolla, CA.

o At ovulation (laboratory-induced with hormones).
ing appears to be coiled up inside a less irregular thecal layer covering, and the lumen is less distinct than anchovy and contains many

fewer granules (Fig. 4c). The follicles of black skipjack differ from

anchovy only by the pres~nce of a thicker thecal layer that adheres

to the granulosa cells (Fig. 4d). The only differences between sardine (Goldberg et al. (984) and anchovy in the appearance of new

postovulatory follicles are the slightly longer columnar granulosa

<.:ells, the occurren<.:e of more particles in the lumen, and a few

vacuoles in the granulosa cells of the sardine (Fig. 4e). During ovulation the sardine foI1icle may have quite a different appearance from

the anchcvy as the granulosa layer contains numerous vacuoles and

the cells are more strongly hypertrophic (Fig. 4f). These differences

in the appearance of new postovulatory follicles seem trivial relative

to their overall similarities, indicating that the new postovulatory

follicles of most fishes should be easy to identify using the genera!

characteristics we have described.

We now consider the characteristics of degenerating postovulatory

follicles in these four species and how they compare to the descriptions for the northern anchovy. The four species have the following

characteristics in common with anchovy: an irregular shape that

is smaller and much less convoluted than a new postovulatory follicle; the presence of a lumen, although the size may be greatly

reduced; degeneration of granulosa cells (pycnotic nuclei, few cell

walls, vacuoles usually present, and lack of alignment of nuclei);

and an identifiable thecal layer. The degenerating postovulatory follicle (about 24 h old) of chub mackerel differs from the anchovy

because a few red blood cells may occur among the granulosa cells

and in the lumen and because very few vacuoles occur in the

granulosa layer (Fig. 5a). Bara (1960) noticed red blood cells in the

lumen of a degenerating postovulatory follicle of the Atlantic

mackerel, Scomber scombrus, indicating this may be a common

characteristic of Scomber. In the degenerating postovulatory follicles

of the Chilean hake, some of the pycnotic granulosa cells appeared

to have been sloughed into the lumen, a characteristic not seen in

anchovy ovaries, and the granulosa cells contained very few vacuoles

relative to the anchovy (Fig. 5b). In addition, the thecal layer in

the hake now appears to be in closer contact with the remaining

granulosa layer than it is in a new postovulatory follicle. The

degenerating follicles in black skipjack differ from anchovy by the

presence of a much thicker thecal layer surrounding the granulosa

layer (Fig. 5c). The degenerating follicle of the sardine (age about

24 h) differs from the anchovy and from a new sardine postovulatory

follicle by having a considerably thicker thecal layer and by the

separation of the granulosa layer from the thecal layer. In addition,

the degenerating granulosa cells of the sardine may be enlarged

slightly and may be sloughed into the lumen (Fig. 5d). These differences among degenerating postovulatory follicles indicate minor

differences in oocyte structure and perhaps differences in the pattern of resorption among species. However, our descriptions for

northern anchovy can be used as a general guide for identification

of postovulatory follicles in these and presumably other species. After

identification of postovu]atory follicles, it is best to age them by

laboratory experiments or round-the-clock sea samples (see previous

section).

A cautionary note on ageing postovulatory follicles-The persistence of postovulatory follicles in the ovary of the northern anchovy and the Peruvian anchovy is the same, and it appears that

Pacific sardine may have a similar duration. These species spawn

at moderate temperatures, 13-19°C. In tropical species that spawn

at high temperatures, spawning frequency, resorption of postovulatory

follicles, and ovarian maturation all may be accelerated. For exam87

pIe, the dragonet, Callionymus enneactis, spawns daily at 28-30°C,

and postovulatory follicles are not seen 15 h after spawning and were

only clearly distinguishable up to 3 h after spawning (Takita et ai.

1983). Clearly in such a rapidly maturing ovary, postovulatory

follicles would be highly transitory in nature. Thus, the duration

of postovulatory stages must be newly estimated for each species,

and an assumption that the duration of these stages in a new species

is similar to northern anchovy is highly speculative.

Anatomical Maturity Scales

and the Gonosomatic Index

Systems tor grading ovaries accordi:lg to macroscopic characteristics

have long been used in fishery research; they include the Hjort scale

(Bowers and Holliday 1961) and numerous others (see, for example, Holden and Raitt 1974; Macer 1974; Foucher and Beamish 1977;

and Robb 1982). Typically, these systems include an immature stage,

several stages for maturing ovaries, one for active ovaries, 1-2 stages

for hydrated ovaries ("ripe" or "running ripe"), and various stages

for "spent" ovaries. At present only the hydrated oocyte stage or

stages have sufficiently distinct macroscopic characteristics (large

ovary size, large hyaline oocytes) to be of value for estimating spawning frequency.

The terminology used in maturity scales to identify "spent" ovaries

is confusing, as "spent" may refer to ovaries with new postovulatory

follicles or to atretic postspawning ovaries. Macer (1974) used the

terms "spent" and "partially spent" to make this distinction. At

present the anatomical stages that seem to be equivalent to postovulatory ovaries are too ambiguous to be used to estimate spawning frequency. It might be possible using a laboratory calibration

to identify some macroscopic characteristics that could be used to

identify postovulatory ovaries for a short time after spawning. On

the other hand, hydrated ovaries and postovulatory ovaries «24 h

old) have similar sampling biases. Thus, the need to develop such

anatomical criteria is not great unless postovulatory ovaries could

be. detected macroscopically 24 h after spawning, which seems

unlikely.

The gonosomatic index (GSI)-the ratio of ovary weight divided

by fish weight or the equivalent (Davies 1956)-can be used to detect

hydrated ovaries since the wet weight of hydrated ovaries is two to

four or more times that of other maturity stages. However, the GSI

has the inherent problem that dividing by an expression of body

size usually does not compensate completely ("normalize") for the

effects offish size (Davies 1956; Vlaming et al. 1982). For the same

reproductive state, small fish usually have a lower GSI than do larger

fish, and this effect increases with maturation of the ovary (Vlaming et al. 1982; Hunter and Goldberg 1980). In other words, ovary

weight increases fister with fish length than does somatic weight.

The assumption underlying the GSI is that ovary weightlfish weight

relation has the same slope for different maturity stages; this is clearly not the case. Thus for accurate detection of hydrated ovaries,

regression analysis or other techniques are probably preferable to

the simple ratio. Gonad weight has the same ambiguities as do the

maturity scales when used to detect other maturity stages. Postovulatory ovaries differ little in weight from the earlier stages of

postspawning (atretic) ovaries.

In summary, the traditional methodologies for assessment of

reproductive condition other than histology (anatomical maturity

scales, and GSI) can be used to identify females with hydrated

ovaries. The incidence of such females with hydrated ovaries might

be used to provide at least a crude index ofspawning frequency (see
Figure 5.-Degenerating postovulatory follicles in four marine fishes. Bars = 0.1 mm; g

b = red blood cells.

granulosa epithelial cell layer; t thecal connective cell layer;

a) Chub mackerel 24 h after spawning Oaboratory-induced with hormones).

c) Black skipjack. Histological material from K. Schaefer, IATIC, La Jolla,

CA.

88

b) Chilean hake. (Histological material from S. R. Goldberg, Whittier College, Whittier, CA.

d) Pacific sardine from Peru about 24 h after spawning. Histological material

from S. R. Goldberg, Whittier College, Whittier, CA.
below). These methods are useful, however, for estimating the duration of the spawning season, and they could possibly be used to provide a size or age-specific index of the relative duration of the season.

At present these methodologies alone cannot be used to accurately

identify in multiple spawners either postovulatory females or post--

spawning females, but it is possible th:lt the GSI or maturity scale

.::ould be calibrated using histological detection uf spawning frequency. Such a calibration would be worthwhile where a long

hi~torica! record of GSI or maturity-scale determinations existed,

because little i~ known of the interannual variation in spawning frequency in marine fish stocks. The technique of estimating spawning frequency using anatomical detection of females with hydrated

ovaries is discussed in the next section.

Hydrated Oocyte Method

The incidence of females with hydrated oocytes can provide a quantitative estimate of the frequency of spawning in natural populations.

Using this technique, DeMartini and Fountain (1981) found that the

percentage of female queenfish, Seriphus politus (Family Sciaenidae), spawning per day averaged 13.6% over a 4-5 mo spawning

season indicating that the mean interval between spawnings was

7.4 d. The chief advantage of the hydrated oocyte method is that

spawning frequency estimates can be made using gross anatomical

examinations of ovaries, and extensive histological processing and

analysis are not required. Two preliminary steps required for estimation of spawning frequency using this method are outlined below.

1. Verification of gross anatomical criteria-The anatomical

crite-ria used to identify hydrated ovaries must be verified using

standard histological criteria, although advanced hydrated ovaries

are relatively easy to identify from anatomical criteria or their weight

(see Hunter et aI. 1985; DeMartini and Fountain 1981). In addition,

it is important to examine histologically the hydrated ovaries from

females captured over the entire hydration period to determine the

range of stages of hydration that are anatomically detectable.

2. Estimation of the optimal time for sampling-To estimate

spawning frequency using the incidence of females with hydrated

ovaries, females must be sampled prior to the onset of spawning,

but at a time sufficiently close to the onset of spawning, so that all

females destined to spawn are detectable using gross anatomical

characteristics of the ovary. In addition, the duration of the period

of hydration must be established and it must be documented that

nearly all hydrated oocytes are spawned in less than 24 h. These

determinations require that a series of samples of females be taken

at regular intervals at sea over 24-48 h (see DeMartini and Fountain 1981). The optimal time for sampling females with hydrated

ovaries can be determined from this series and biases caused by the

onset ofspawning or by the failure to detect hydration can be avoided.

The chief advantage of the hydrated ovary method over the use

of the postovulatory follicles is that histological examination is not

necessary after the preliminary work outlined above. On the other

hand, our data on northern anchovy indicate three actual or possible disadvantages. First, sampling for the incidence of females with

hydrated ovaries can be done only during a very limited portion of

each day. In anchovy this period is probably 6 h or less, whereas

females with day-old postovulatory follicles can be sampled at any

time of day. The second possible disadvantage is that females with

hydrated ovaries may be more vulnerable to trawls and perhaps other

89

fishing gear than females in other reproductive states. This may bias

an estimate based on hydrated ovaries. We find that spawning frequency estimates based on the number of female northern anchovy

with hydrated ovaries and new postovulatory follicles can as much

as double those estimates based on the incidence of day-old postovulatory follicles. However, this bias may be the result of the trawl

oversampling the depth strata where hydrated females are abundant

rather than a lack of avoidance by hydrated females. The third disadvantage of the hydrated ovary method is that incidence of females

with hydrated ovaries is contagiously distributed among fish samples

whereas females with day-old postovulatory follicles are not (Hunter

and Goldberg 1980; DeMartini and Fountain 1981). This increases

the variances of the estimate and demands a larger sample size. The

contagion is probably caused by the separation of fish prior to spawning into groups composed mostly of males and hydrated females

and other groups with fewer males and non-hydrated females.

Despite its actual and possible disadvantages, the simplicity of

the hydrated ovary method i~ appealing. It seems a useful initial approach, especially since past estimates ofspawning frequency were

based on various speculative arguments (number of modal groups

of oocytes in the ovary, or standing stock of yolked oocytes) and

were in error by a factor of ten or more. The hydrated ovary method

certainly provides a useful first approximation of spawing frequency at a relatively low cost.

ATRESIA _

In northern anchovy, as well as in most other seasonal spawning

fishes, a low incidence of oocyte atresia (degeneration of oocytes)

occurs throughout the spawning season but becomes marked as the

spawning season closes and the remaining advanced oocytes in the

ovary are resorbed. The incidence of atresia is not used directly

in the estimation of spawning biomass using the egg production

method, but it is important for several other reasons: I) A general

knowledge of atresia is required to age postovulatory follicles because

some stages of follicular atresia are very similar in appearance to

late-stage postovulatory follicles; 2) it is a key histological marker

for the cessation of spawning, and as a consequence can be used

to determine whether or not a cruise period is optimal for biomass

estimation (estimates near the end of the season have less precision); 3) it is necessary for accurate estimates ofsize at first maturity;

and 4) it is essential for separating immature females from those

in postspawning condition, a distinction required by the egg production method.

Atretic Stages

Oocyte degeneration or oocyte atresia has been divided into four

or more sequential stages. We use the nomenclature and general

characteristics defined by Bretschneider and Duyvene deWit (1947)

and Lambert (1970a), but details of the descriptions of individual

stages are based on our examination of northern anchovy ovaries

(Hunter and Macewicz 1985).

During the initial stage of the atretic process, alpha (a), the entire oocyte is resorbed, including the yolk if present, by the hypertrophying granulosa cells of the follicle. In the second stage, beta

(fJ), the major degeneration and resorption of the follicle (granulosa

and thecal cells) occurs. In the third, gamma (y), and fourth, delta

(d), atretic stages, regression of the theca and granulosa cells continues, greatly reducing the size of the follicle, and a yellow-brown
pigment appears in H & E sections. The histological characteristics

used to identify these stages in northern anchovy are outlined below.

Alpha stage atresia-In the alpha stage of atresia the oocyte is

resorbed, leaving only the follicular layers. The early phase of alpha

stage atresia is characterized by disintegration of the nucleus, evident by an irregular shape and granular, dark, basophilic staining,

and the disintegration of some of the yolk globules, indicated by

less refractive globules, fused globules, or globules expanded and

ofless regular shape (Fig. 6a, b, c). The zona radiata slowly dissolves

as indicated by the loss ofstriations and uneven diameter (Fig. 6b).

In the subsequent phase of alpha atresia, granulosa cells enlarge

and upon rupture of the zona radiata invade the degenerating oocyte

(Fig. 6d). Yolk adjacent to the invading granulosa cells liquifies (loses

all structural integrity and appears as a homogeneous eosinophilic

area), and becomes phagocytized by the granulosa cells as indicated

by the presence of yolk in the vacuoles of these cells. The basophilic

staining cytoplasm is also resorbed by the granulosa cells. In the

alpha stage of atresia, blood capillaries and vessels are numerous

in the thecal connective layer which does not proliferate or invade

the oocyte but remains as a thin layer covering the granulosa cells.

The alpha stage ends when resorption of the oocyte is complete (all

cytoplasm and yolk are gone). The resulting structure (beta stage)

is usually much smaller than the original oocyte. The subsequent

atretic stages (beta-delta) are steps in the resorption of the remaining follicle and the structure at this point is called an atretic follicle, the term atretic oocyte being reserved for only the alpha stage

of atresia.

In unyolked oocytes, the alpha stage process is similar but without yolk (Fig. 6e, f). The nucleus disintegrates, the thin pre-zona

radiata (if present) dissolves, and the granulosa cells enlarge and

with only a slight proliferation phagocytize the unyolked oocyte.

When resorption is complete, all that remains is the atretic follicle.

Beta stage atresia-Initially the beta-stage atretic follicle is a compact structure composed of numerous disorganized granulosa cells

surrounded by a thin thecal and blood vessel layer. The nucleus of

some of the granulosa cells is pycnotic and many of the cells contain intraceBular vacuole(s) that may be empty or contain amorphous

particles. Occasionally one or more large intercellular cavities may

exist among the granulosa ceBs (Fig. 7b, d). Preovulatory beta-stage

atretic foBicles containing such cavities may easily be confused with

postovulatory follicles (older than 48 h), and as a consequence we

do not age postovulatory follicles older than 48 h (Hunter and

Goldberg 1980). In addition, small (older) beta-stage atretic follicles

from yolked oocytes (Fig. 7c, d) are indistinguishable from betastage atretic follicles from unyolked oocytes. Thus, we do not identify the original oocyte type undergoing atresia in beta or subsequent atretic stages; such distinctions are made only for alpha-stage

atretic oocytes.

Three different patterns of atresia may occur at the conclusion

of the beta stage: 1) The follicle may follow the classic pattern

outlined by Bretschneider and Duyvene deWit (1947) and pass

through subsequent gamma and delta stages (both characterized by

increased pigmentation, see below); 2) the foBicle may be completely

resorbed during the beta stage, leaving no histological characteristics that can be identified; and 3) the follicle may pass directly from

a beta stage structure to a delta structure without passing through

the intervening gamma stage. In northern anchovy, either the duration of the gamma stage is very short or few follicles pass through

the gamma stage into the delta stage, because in regressing ovaries

the incidence of gamma stages is very low compared to those of

either beta or delta stages.

90

Gamma stage atresia-The gamma-stage atretic follicle is usually

much smaller than the typical beta stage follicle (Fig. 7e). The

granulosa cells contain flocculent material of light-yellow hue, and

have nuclei of very irregular shape. The granulosa cells are surrounded by many fewer thecal cells and blood vessels than occur

in the beta-stage atretic follicles. Occasionally we see an atretic foBic1e of quite different appearance in anchovy ovaries which we classify

as a gamma-stage atretic follicle; they are included in the gamma

stage because they also. contain flocculent material of light-yellow

hue. In this case, the flocculent yellow material is extraceBular rather

than intercellular and the material is encapsulated by a layer of

granulosa and thecal cells. It is possible that the extracellular flocculent material is produced by the disintegration of granulosa cells.

Delta stage atresia-The diagnostic characteristic of this stage is

the presence of a dark yeBow-brown, finely granular pigment in the

granulosa cells (Fig. 7f). The delta-stage atretic foBicles are normally

very small structures typically composed of 2-20 granulosa cells

in the connective tissue stroma. Thecal cells and blood vessels no

longer directly encompass the granulosa ceBs because they have been

absorbed into the ovarian connective tissue stroma.

Atretic States

For population work it may be impractical to grade every ovary for

the abundance of each of the four atretic stages. To simplify the

assessment of atretic condition of the ovary, we have defined four

atretic states which are based on some of the atretic stages described

in the previous section. The duration of these states was estimated

for anchovy in L'-le laboratory and then assessed using starvation to

trigger resorption of the ovary (Hunter and Macewicz 1985). In addition, the spawning potential of sea-caught females that were classed

in these states was estimated by calculating the incidence of females

with postovulatory follicles and hydrated eggs within each atretic

state (N > 5000); their results are summarized below.

Atretic state O-Females classed as atretic state 0 have yolked

oocytes present and no alpha atresia of yolked oocytes. Beta stage

atresia may be present but is not considered, as it cannot be separated

with certainty from late-stage postovulatory follicles (>48 hold).

Female anchovy in this state have a high potential ofspawning, with

spawning occurring at a frequency of every week to 10 d.

Atretic state I-Females with yolked oocytes in which <50% of

the yolked oocytes are in the alpha stage of atresia. Frequency of

spawning of females classed in this state is less than half of that

in females of atretic state O. Thus, atretic state 1 is an index of a

decline in spawning rate (Table 1). Females appeared to persist in

this state under natural conditions for extended and probably variable

periods, but the state persisted in the laboratory under induced starvation for only 5-7 d. Atretic state 1 is the most common atretic

condition during peak spawning periods, and it can be used to detect

differences in spawning between length classes; it appears to be a

more sensitive index of differences in reproductive rate among length

classes than is the incidence of postovulatory follicles (Hunter and

Macewicz 1985).

Atretic state 2-Females with yolked oocytes in which ~50% of

the yolked oocytes are in the alpha stage of atresia. Females in atretic

state 2 persisted for about 9 d in the laboratory, and it seems to have

a similarly short duration in natural populations. It is the best

measure of the absolute rates of ovary resorption in the population
Figure 6.-Alpha (a) stage atresia in yolked (Y) and unyolked (U) oocytes. Bar = 0.1 mm.

a, b) Yolked oocyte undergoing alpha atresia (Ya). Notice dark

irregular nucleus (n), uneven dissolving zona radiata (z), hypertrophic

granulosa cells (g); and alpha atresia of a large unyolked oocyte (Va).

c, d) Only remnants of yolk material (y) remain among the invasive

phagocytizing granulosa cells in this late phase of alpha atresia (la).

Note also the thecal layer (I) and Ihe closely associaled red blood cells

(b). Y = yolked oocyte; Ya = alpha yolked atretic oocyte.

e, f) Unyolked oocytes in Ihe alpha stage of atresia (Va). Note enlargement of granulosa (g) and disintegration of nucleus (n). Ya = alpha

yolked atretic oocyte; (J = beta alrelic follicle.

91
Figure 7.-Stages of atresia following complete yolk absorption. Bar = 0.1 mm.

a, b) Typical beta «(3) stage atresia. Note the disorganized granulosa

cells with some pycnotic nuclei (p) or intracellular vacuoles (v). t =

thecal connective cell layer; c = intercellular cavities.

c, d) Disintegration of granulosa continues in these older beta (/3)

atretic follicles. Note the large intercellular cavity (c) and the prominent, contracted thecal cell layer (t). Also present is an unyolked oocyte

in early alpha (Va) stage and several delta (0) stage atresia cells.

e) Two types of gamma (y) atresia seen in northern anchovy ovaries.

Note flocculent material (I) and the thecal connective cell layer (t).

I) Delta (0) stage atresia characterized by dark-yellow, fine, granular

pigment and an irregular nucleus (n).

92
Table I.-Histological classificationsI of northern anchovy ovaries and the

reproductive implications. PO = postovulatory.

---------

and could be used to forecast the end of reproduction near the end

of the spawning season. A high incidence of females in this state

indicates that cessation of spawning in the population is imminent.

Atretic state 3-Females without yolked oocytes in which beta stage

atresia is present. This state identifies females in late postspawning

condition. The state persisted for about 30 d in the laboratory, and

it may last much longer under natural conditions while the numerous

small oocytes are resorbed. (The laboratory data indicate that the

duration of this state could be increased if definitions were redefined

to include gamma + delta stages of atresia which have a longer life

in the ovary than does the beta stage.) This state is used to separate

females in postspawning condition from immature females (females

with no previous reproductive history). Consequently, identification of females in this state is essential for accurate estimates of age

or size at first maturity and for an accurate definition of spawning

biomass using the egg production method.

TESTING THE ASSUMPTION

OF SEASONALLY DETERMINATE

FECUNDITY _

A critical assumption underlying some biomass estimates from ichthyoplankton d~ta and many estimates of annual fecundity in fishes

is that the annual fecundity in a species is determined at the beginning of the spawning season. Validation of this assumption of determinate fecundity requires proof that I) all oocytes destined to be

spawned in a season are identifiable at the beginning of the season

and no new spawning batches are recruited from the reservoir of

small unyolked oocytes that exist in the ovary the year round, and

2) the identified standing stock of yolked oocytes that constitute the

maximum potential annual fecundity are in fact spawned and only

a negligible quantity of these oocytes are resorbed at the end of the

season.

The traditional evidence for determinate fecundity is the presence

of a major gap in oocyte maturity stages or size classes between

the oocytes matured for the season and the reservoir of immature

oocytes present year-round in the ovary (Yamamoto 1956). The presence of such a gap in oocyte classes in females taken at the beginning of the season seems to be adequate proof that the standing stock

of oocytes is a measure of maximum annual fecundity, as long as

the gap is not between a batch of hydrated oocytes and other yolked

oocytes. The absence of such a discontinuity in oocyte classes is

evidence for indeterminate fecundity. In some cases, however, determinate annual fecundity is believed to exist despite the fact that oocyte

size classes are continuously distributed in the ovary. In such cases,

spawning frequency and batch fecundity for the species must be

estimated over the season and their product (fecundity x frequency)

compared to the standing stock of mature oocytes at the beginning

of the season. This was done for whiting and haddock in the

laboratory by Hislop (1975) and Hislop et al. (1978).

For northern anchovy, Hunter and Leong (1981) compared field

estimates of spawning frequency with standing stocks of oocytes.

They showed that oocytes as small as 0.1 mm must be included in

the annual fecundity to account for 10 spawnings per yr and estimated

that anchovy spawn an average of 20 or more times per yr. Their

analysis clearly documents the existence of indeterminate fecundity in anchovy. However, anchovy have a continuous oocyte distribution, and so indeterminate fecundity is expected in this species.

In species for which determinate fecundity is inferred because

of a discontinous oocyte distribution, it is also necessary to document that the maximum annual fecundity estimated from the standing stock of oocytes is in fact realized in the sea (see above). To

validate this assumption requires an analysis of rates of atresia of

yolked and partially yolked oocytes. The key atretic state in such

an analysis would be one similar to our atretic state 2 where many

oocytes are in the alpha stage of atresia. It should be borne in mind

that this state may have a short duration.

In anchovy the mean duration of this state is only 9 d and the

maximum only 20 d (Hunter amd Macewicz 1985). Consequently,

sampling to determine the extent of resorption of oocytes must be

done over a relatively short period near the end of the season;

otherwise, significant oocyte resorption may not be detected.

Substantial oocyte resorption has been observed in the Pacific hake,

Merluccius productus, which seems to have a discontinuous oocyte

distribution (Foucher and Beamish 1m?). They conclude that the

standing stock of yolked oocytes is very likely in excess of the number

of oocytes that will be spawned, except in exceptional years.

In conclusion, an assumption of determinate fecundity requires

extensive work to prove, and in some cases may be only wishful

Reproductive implications

High probability of

spawning within 1-10

d'

Spawning occurred 1 d

ago"

Probability of spawning

is half that of atretic

state 0'.

Spawning occurred <24

h ago'.

Probability of spawning

= 0; may have had an

active ovary 1-20 d ago

(average 8 d)'.

Key histological

characteristics

Hydrated oocytes present Spawning will occur in

>12 h'

Yolked oocytes present; no

alpha-stage atretic yolked

oocytes.

Alpha stage atresia of

yolked oocytes; ;;'50% of

yol ked oocytes are

affected.

No yolked oocytes present;

beta stage atresia

present.

Alpha stage atresia of

yolked oocytes; ;;'50% of

yolked oocytes are

affected.

No yolked oocytes present;

no beta atretic follicles.

3

State

Age O-day PO Postovulatory follicles

<24 hold.

Age I-day PO Postovulatory follicles

24-48 hold.

Immature

n

a

v

e

v

Ovary

Spawning States

A Hydrated

Atretic States

A 0

ProbabIlity of spawning

= 0; may have had an

active ovary ;;'16-30 d

ago'.

Probability of spawning

= 0; no evidence of

past reproduction within last 30 or more d.

May develop an active

ovary within ;;'31 d'.

'Ovaries are classed into both spawning and atretic states, but the reproductive

implications are for a single-state classification and not for a combination of atretic

and spawning states.

'Hunter and Macewicz 1980.

'Hunter and Goldberg 1980.

'In peak spawning months the average female spawns at 1-10 d intervals (Hunter

and Leong 1981); hence females with active ovaries are likely to spawn within 1-10

d depending on maturity of the ovary.

'Based on the fraction of females in spawning states within atretic state I (Hunter

and Macewicz 1985).

6Hunter and Maccwicz 1985.

'Hunter and Leong 1981.

93
thinking. The most conservative assumption is that seasonal fecundity is indeterminate for multiple spawning fishes and that estimates

of batch fecundity and spawning frequency are required. The

documented cases of determinate fecundity appear to be restricted

to boreal or cold temperate climates where spawning seasons are

short. Thus in most of the world's oceans indeterminate fecundity

and multiple spawning are the rule for epipelagic spawners, and

estimates of spawning frequency are essential both for biomass

estimation using ichthyoplankton data and for estimates of annual

fecundity.

FUTURE APPLICATIONS

OF HISTOLOGICAL CLASSIFICATION

OF OVARIES _

An important future application of the histological classifications

we have described is the study of reproductive processes in multiple spawning fish populations. This work requires not only

histological classification but sufficient laboratory calibration and

analysis of sea data to be able to specify the reproductive implications and duration of each class. Sufficient data exist on northern

anchovy to make a relatively accurate interpretation of the reproductive significance of each spawning and atretic state (Table I).

Reproductive state and its approximate duration can now be related

to the physiological state of the female (age, size, fat content,

biochemical composition, instantaneous growth rate from otoliths

or RNA/DNA ratios, and environmental conditions). In this way

it may now be possible to identify the factors controlling the 2-3

fold variation in batch fecundity (Hunter et al. 1985), the potentially large variation in spawning frequency and duration of the

spawning season, and, most importantly, the functions regulating

partitioning of energy between reproduction and growth.

LITERATURE CITED _

ALHEIT, 1., V. H. ALARCON, and B. 1. MACEWICZ.

1984. Spawning frequency and sex ratio in the Peruvian anchovy, Engraulis

ringens. Calif. Coop. Oceanic Fish. Invest. Rep. 25:43-52.

BARA, G.

1960. Histological and cytological changes in the ovaries of the mackerel Scomber

scomber L. during the annual cycle. Rev. Fac. Sci. Univ. Istanbul Ser B. Sci.

Nat. 25:49-91.

BOWERS, A. B., and F. G. T. HOLLIDAY.

1961. Histological changes in the gonad associated with the reproductive cycle

of the herring (Clupea harengus, L.). Mar. Res. Dep. Agric. Fish. Scotl. 5:1-16.

BRETSCHNEIDER, L. H., and J. 1. DUYVENE deWIT.

1947. Sexual endocrinology of non-mammalian vertebrates. Monographs on the

progress of research in Holland during the war, Vol. II. Elsevier, NY., 147 p.

DAVIES, D. H.

1956. The South African pilchard (Sardinops ocellara) sexual maturity and

reprdduction 1950-54. S. Afr. Div. Sea Fish. Invest. Rep. 22, 55 p.

DeMARTINI, E. E., and R. K. FOUNTAIN.

1981. Ovarian cycling frequency and batch fecundity in the queenfish, Seriphus

politus: Attributes representative of serial spawning fishes. Fish. Bull., U.S.

79:547-560.

FOUCHER, R. P., and R. 1. BEAMISH.

1977. A review of oocyte development in fishes with special reference to Pacific

hake (Mer/uccius productus). Can. Fish. Mar. Servo Tech. Rep. 755, 16 p.

FULTON, T. W.

1898. On the growth and maturation of the ovarian eggs of teleostean fishes.

Annu. Rep. Fish. Board Scot!. 16:88-124.

GOLDBERG, S. R., V. H. ALARCON, and J. ALHElT.

1984. Postovulatory follicle histology of the Pacific sardine, Sardinops sagax,

from Peru. Fish. Bull., U.S. 82:443-445.

94

HISLOP, J. R. G.

1975. The breeding and growth of whiting, Merlangius mer/angus, in captivity.

J. Cons. int. Explor. Mer 36:119-127.

HISLOP, 1. R. G., A. P. ROBB, and 1. A. GAULD.

1978. Observations on effects of feeding level on growth and reproduction m haddock, Melallogra'lllllus aeglefillus (L.) in captivity. J. Fish. BioI. 13:85-98.

HOLDEN, M. J., and D. F. S. RAITT (editors).

1974. Manual of fisheries science. Part 2 - Methods of resource investigation and

rheir application. FAO Fish. Tech. Pap. 115 (Rev.]), 241 p.

HUNTER, 1. R., and S. R. GOLDBERG.

1980. Spawmng incidence and batch iecundity in northern anchovy, Engraulis

mordax. Fish. Bull., U.S. 77:641-652.

HUNTER, 1. R.• and R. LEONG.

1981. The spawning energet;cs of female northern anchovy, Engraulis mordax.

Fish. Bull., U.S. 79:215-230.

HUNTER, 1. R., N. C. H. LO, and R. 1. H. LEONG.

1985. Batch fecundity m multiple spawning fishes. In R. Lasker (editor), An

egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engraulis mordax, p. 67-77. U.S. Dep. Commer., NOAA Tech. Rep. NMFS 36.

HUNTER, 1. R., and B. J. MACEWICZ.

1980. Sexual maturity, batch fecundity, spawning frequency and temporal pattern in the northern anchovy, Engraulis mordax, during the 1979 spawning

season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

1985. Rates of atresia m the ovary of captive and wild northern anchovy, Engraulis

mordax. Fish. Bull., U.S. 83:119-136.

LAMBERT, 1. G. D.

1970a. The ovary of the guppy, Poecilia reticulata. The atretic follicle, a corpus

atreticum or corpus luteum praeovulationis. Z. Zellforsch. 107:54-67.

LAMBERT, 1. G. D.

1970b. The ovary of the guppy, Poecilia reticulara. The granulosa cells as sites

of steroid biosynthesis. Gen. Compo Endocrinol. 15:464-476.

LEONG, R.

1971. Induced spawning of the northern anchovy, Engraulis mordax Girard. Fish.

Bull., U.S. 69:357-360.

LUNA, L. G.

1968. Manual of histological staining methods of the Armed Forces, Institute of

Pathology, 3d ed. McGraw-Hill, N.Y.

MACER, C. T.

1974. The reproductive biology of the horse mackerel, Trachurus trachurus (L.)

in the North Sea and English Channel. 1. Fish. BioI. 6:415-438.

PREECE, A.

1965. A manual for histological technicians, 2d ed. Little, Brown & Co., Boston.

ROBB, A. P.

1982. Histological observations on the reproductive biology of the haddock,

Meiallogramlllus aeglefillus (L.). J. Fish. BioI. 20:397-408.

TAKITA, T., T. IWAMOTO, S. KAI, and I. SOGABE.

1983. Maturation and spawning of the dragonet, Callionymus enneaclis, in an

aquarium. Jpn. 1. Ichthyol. 30:221-226.

VLAMING, V. de, G. GROSSMAN, and F. CHAPMAN.

1982. On the use of the gonosomatic index. Compo Biochem. Physiol. 73A:31-39.

WALLACE, R. A., and K. SELMAN.

1981. Cellular and dynamic aspects of the oocyte growth m teleosts. Amer. Zool.

21:325-343.

YAMAMOTO, K.

1956. Studies on the formation of fish eggs. I. Annual cycle in the development

of ovarian eggs in the flounder, [jopsetta obscura. 1. Fac. Sci. Hokkaido Univ.

Ser. VI, Zool. 12:362-376.
Comparison between Egg

Production Method and

Larval Census Method

for Fish Biomass

Assessment

ROGER P. HEWITTI

Southwest Fisheries Center,

National Marine Fisheries Service, NOAA,

Po. Box 271, La Jolla, CA 92038

ABSTRACT

Ichlhyoplanklon abundance and production are related to the aggregate weight

of spawning adults. The problem is first formulated in terms of annual production and fecundity. The abundance of northern anchovy larvae, used to index annual production, is related 10 the daily production of eggs. Advantages of the egg

production method of assessing stock biomass are discussed.

'Present address: Commanding Officer, NOAA Ship Miller Freeman, Pacific Marine

Center, 1801 Fairview Ave. E., Seattle, WA 98102.

95

INTRODUCTION _

This final article discusses the general problem of relating ichthyoplankton data to the aggregate weight of spawning adults and reviews

various solutions. The first section deals with the problem as traditionally formulated; that is, the annual production of eggs and iarvae is related to adult biomass by annual fecundity. The second section reformulates the problem in instantaneous terms; that is, daily

production and daily fecundity. The third section relates the two

ichthyoplankton methods used to estimate the northern anchovy

populations: The larval census method and the egg production

method. The fourth section discusses the advantages of the egg pro·

duction method.

ANNUAL PRODUCTION

OF EGGS AND LARVAE _

Although ichthyoplankton surveys have been conducted for many

purposes-to detect unexploited fish stocks, to study development,

biogeography and systematics of fishes, and to forecast future population growth-Hensen and Apstein (1897) initially proposed that the

surveys be used to index the spawning population of adults. The

idea was appealing because of the ease ofsampling eggs and larvae

relative to sampling adults. Ichthyoplankters are found in a restricted

vertical range of the sea, they have no or very limited ability to avoid

capture, and simple sampling gear can be employed which allows

for increase in the density of observations.

The basic model relating the weight of the spawning population

to production of eggs is (Saville 1964)

B---P

FxR

where B is the weight of the spawning population, P is the annual

production of eggs, F is the annual female fecundity on a weight

basis (annual specific fecundity), and R is the female fraction of

the population. Application of the method requires the ability to

identify reproductive products of the target species and knowledge

of their development rates, the geographic and seasonal extent of

spawning, and the determination of batch size and number of batches

spawned by a female each year.

The production of eggs can be estimated from egg abundance

adjusted for their development time and the mortality suffered during

this period (Sette 1943). Annual abundance is estimated by integrating individual observations over both the survey area and the

spawning season. Several spatial integration procedures have been

employed: Contouring the observations and measuring the

topographic volume (Buchanan-Wollaston 1926; Van Cleve and

Seymore 1953; Simpson 1959); summing of strata averages raised

by strata areas (Sette 1943; Smith 1972; Berrien et al. 1981); and

summing individual observations raised by the area that each observation represents (Sette and Ahlstrom 1948). The three methods

yielded similar results when applied to surveys of Pacific sardine

spawning by Sette and Ahlstrom (1948). Temporal integration has

been accomplished by summing successive surveys weighted by the

portion of the year that they represent (Sette and Ahlstrom 1948;

Berrien et al. 1981) by measuring the area under the curve that

describes the survey abundance by time of year (Simpson 1959; Bannister et al. 1974), integrating a normal curve scaled to describe the

seasonal variation in spawning activity (Saville 1956), and summing

quarterly estimates of average abundance (Smith 1972). English
(1964) advocated procedures which averaged over space and time

because ofthe large (and unpredictable) variance between observations; he argued that estimates from integrating procedures did not

have reliable estimates of variability and were not amenable to comparisons between years. Adjustments for development time and mortality can be made either before integration (e:g., Berrien et aI. 1981),

after integration (Sette 1943), or in a stepwise mixture of integration and adjustment (e.g., Bannister et al. 1974). Unless there is

a strong correlation between abundance and rate of development

or mortality within the survey area, the order of calculation should

make little difference in the final estimate of annual egg production. If these factors are independent, then the various procedures

discussed above are algebraically equivalent.

The most recent statistical advance in the description of ichthyoplankton surveys is the use of a weighted negative binomial distribution to describe the sample distribution (Zweifel and Smith 1981).

Individual observations can be weighted for sampling bias and error (e.g., extrusion, avoidance, variations in the sample volume,

and development rate), and the mean of the fitted distribution is

an unbiased estimate of the production rate with a well-described

error structure. Production is estimated by raising this mean over

the space-and-time stratum encompassed by the observations. By

fitting a weighted negative binomial to successive stage-specific sample distributions, an age-specific production curve may be derived

(Hewitt 1982). Application of this procedure to the 30-yr time series

of northern anchovy larvae surveys revealed a change in the microdistribution pattern (patch dispersal) of larvae as they grew and a

change in the mortality rate with the level of egg production (Hewitt

1982).

Annual specific fecundity is estimated from knowledge of the

number of eggs released per unit weight per spawning and the

number of spawnings per year. Both factors can be affected by environmental conditions such as the amount, quality, and availability of food. For boreal species, for which spawning seasons tend

to be distinct, short, and predictable, estimating annual specific

fecundity may be less of a problem than for temperate and tropical

populations, with protracted or even continuous spawning seasons.

The problem of estimating annual specific fecundity may be sidestepped by assuming that production or abundance of eggs and larvae is proportional to the weight of the adult population; the proportionality constant is estimated by regressing the abundance of

larvae on an independent estimate of population size (Smith 1972;

Saville and Schnack 1981). Thus

B=kxC (Smith 1972)

(1973), and Ulltang (1977). The proceedings of both symposia on

the Early Life History of Fish (Blaxter 1974; Lasker and Sherman

1981) include several reports of estimates of stock size from ichthyoplankton surveys and provid<: a good introduction to a much larger

body of literature.

DAILY PRODUCTION

OF EGGS AND LARVAE _

Development of the ability to determine the near-term reproductive

status of a female allowed (he stock-estimation problem to be reformulated in terms of parameters that were easier to measure.

Hunter and Goldberg (1980) and Hunter and Macewicz (1980)

developed criteria to describe the anchovy spawning cycle apparent

in gonad tissue with a resolution of one day; i.e., it is possible to

classifj fish that were spawning on the day of capture, those that

spawned the day previous to capture, those that spawned 2 days

previous to capture, etc. Thus a direct measure of daily specific

fecundity is possible as the product of the fraction of females spawning per day times the weight-specific batch fecundity. It is not

necessary to integrate egg production over the spawning season

because both fecundity and production can be expressed on a daily

basis. The model relating the weight of the population to the daily

production of eggs is (Parker 1980)

B

where B is the weight of the spawning population, Po is the daily

production of eggs, Fs is the specific daily fecundity, and R is the

female portion of the population. These parameters can be estimated from a representative sample obtained over the spawning habitat.

For a fish that spawns continuously over a protracted spawning

season (e.g., anchovy), the observations need not be made synoptically; rather, data collected over a 30-day cruise can be pooled

without introducing large errors. This method has been used since

1980 to estimate the spawning stock of northern anchovy (Picquelle

and Hewitt 1983a, b).

The production of eggs was estimated from the age-specific production curve (Fig. 1). The production rate of eggs at time zero

(spawning) was raised over the survey area to estimate daily production by the population. The variance of this estimate was reduced

using postsurvey stratification of the survey area.

Specific daily fecundity was estimated as the product of three

parameters:

where F is the average batch fecundity, S is the average fraction of

aduit females spawning per day, and W is the average weight of an

adult female. These parameters were estimated from a sample of

adult fish obtained concurrently with a sample of their eggs. The

adult sample consists of "'100 trawl stations, and the egg sample

"'1,000 plankton stations. Results of the four surveys conducted

through 1983 are summarized in Table I.

where C is the annual census of larvae and k is the proportionality

constant. This procedure has come to be known as the Larval Census Method (Smith and Richardson 1977). Application of the method

assumes that annual specific fecundity does not vary between years

nor does the larval mortality rate (hence the use of larval abundance

rather than production). To the extent that specific fecundity and

larval mortality rate are independent of population size, violation

of the assumptions introduces error but not bias in the estimate of

the constant of proportionality.

The theory and conduct of ichthyoplankton surveys are discussed

thoroughly in Smith and Richardson (1977); their bibliography (Smith

and Richardson 1979) contains over 1,000 citations and is complete

through 1973, including proceedings of the first Symposium on the

Early Life History of Fish held at Oban, Scotland in 1973 (Blaxter

1974). The estimation of adult spawning stock size from egg and

larval surveys is also discussed by Saville (1964, 1977), Hempel

96

Fs

F x S

W
EGG PRODUCTION

PRODUCTION CURVE

z

o

Io

:l

o

o

Q:

a..

o

AGE (days)

Figure I.-Age-specific production curve of fish eggs. The curve is estimated from

abundance-at-age data and the intercept is defined as the production rate (per

unit area) of eggs at time zero (spawning).

RELATIONSHIP BETWEEN

EGG PRODUCTION

AND LARVAL CENSUS _

The standing stock of larvae results from the production of eggs

modified by mortality. Eggs are spawned continually by the adult

population; some of them hatch, some of the larvae survive to metamorphosis, and many more perish as eggs or larvae. The average

abundance of eggs and larvae is the sum of this process over all

ages; i.e., the area under the production curve (Fig. 2). Thus, egg

production is proportional to the zero intercept of the production

curve, and the larval census is proportional to the area below the

production curve. Both are raised above the survey area for population estimates and have a constant relationship to the extent that mortality is constant. The annual northern anchovy larval census was

the latter value summed over four quarters (Smith 1972).

The expected abundance of northern anchovy larvae is the integral

of the larval production curve from the time of hatch to 30 days

(the oldest age at which anchovy larvae are effectively caught). The

larval production curve is an extension of the egg production curve,

and this is the basis for an analytical connection between the two

methods. The larval production curve may be parameterized as (Lo

1985; Hewitt and Brewer 1983)

for t < th

where P, is the production of t-day old larvae, th is the age at hatch,

and f3 is the larval mortality coefficient which describes how rapidly

survival improves with age. The egg production curve may be

parameterized as (Picquelle and Hewitt 1983a)

Table I.-Egg production estimates of northern anchovy spawning biomass (1980-83). C.V. = coefficient of variation

(standard deviation/mean).

1980',4 1981 (Feb)'" 1981 (Apr)'" 19822,4 19833,5

Est. CV. Est. ev. Est. CV, Est. ev. Est. CV,

Daily egg production Po 26.34 0.111 20,96 0,101 12.59 0.087 13.51 0.237 17.25

(XIO'2 eggs/d)

Fraction of mature females S 0.142 0.125 0.106 0.122 0.125 0.092 0.120 0.038 0.094

spawningld

Sex ratio of weight R 0.478 0.120 0.501 0.063 0.495 0.051 0.472 0.081 0.549

(females/total)

Batch fecundity F 7,751 0.075 8,329 0.052 8,846 0.045 10,845 0,047 5,297

(no. eggs/batch)

Average female weight W 17.44 0.055 13.37 0.039 16.20 0.029 18.83 0.019 1l.20

(XI0-6 t)

Daily population fecundity q=SRF/W 30.28 33,03 33.84 32.53 24.35

(X 10-6 eggs/day-ton)

Spawning biomass B=Pdq 870 0.225 635 0,183 372 0.147 415 0.257 652 0.211

'Documented in Stauffer, G.D., and S. J. Picquelle (Unpubl. manuscr.) Egg production estimates of spawning biomass of

the northern anchovy, Engraulis mordax, for 1980 and 1981. SWFC, La Jolla, CA.

'Documented in Picquelle and Hewitt (1983a).

'Documented in Picquelle and Hewitt (l983b),

'These surveys were conducted with a 333-l'm mesh net estimated to retain 91 % of the eggs. Original estimates were elevated

by a factor of 1/0.91.

'Biomass estimate was actually calculated as the sum of three regional biomass estimates, Parameter estimates reported here

are averaged over the entire survey area for comparison purposes, See Picquelle and Hewitt (1983b) for regional parameter

estimates.

97
..E 60 I

>.

..

..

co

co

CD

(;

: 40 >

!

UJ

I-

-<

a:

z

o

t= 20 o

=>

c

o

a:

a..

th 10 20

AGE SINCE FERTILIZATION (days)

Figure 2.-Age-specific production curve of anchovy eggs and larvae. The average

abundance of larvae is the shaded area under the larval production curve.

where Z is the instantaneous mortality coefficient, assumed to be

constant over the incubation period. The production of eggs at the

end of the incubation period may be substituted for the production

of larvae at th .

The annual census of larvae averaged 2.12 times the standing stock

during the spawning season (Stauffer and Picquelle 1980). The annual larval census also underestimated the true abundance of larvae because of losses due to extrusion and avoidance (Smith 1972:

Lenarz 1972, 1973; Lo 1983). Thus, the annual census of larvae may

be related to the daily production of eggs:

where r is the fraction of the larval population represented in an

ichthyoplankton sample; r is a variable which is dependent on the

size distribution of the larvae caught and the time of their capture.

These relationships are developed in more detail by Stauffer (1983).

Picquelle and Hewitt (1983a, b), and Lo (1985).

As was noted above, spawning biomass may be estimated using

the larval census method by multiplying C times the constant of proportionality; this assumes no variability in reproductive output or

early mortality. Spawning biomass may be estimated using the egg

production method by dividing Po by the daily specific fecundity;

this procedure specifically accounts for variability in reproductive

output and early mortality.

Results from the time series of egg production are listed below,

together with projected larval census estimates. During the first two

years larval surveys were conducted concurrently, and the measured

larval census agreed well with the projected larval census.

YEAR Po C C

(x 10 12 eggs/d) (X 109 larvae) (x 109 larvae)

1980 26.34 17.22 18.10

1981 (Feb.) 20.96 35.12 28.58

(Apr.) 12.59 30.85

1982 13.51 20.97

1983 17.25 15.80

98

The egg production surveys were conducted with the CalVET

sampler described in Smith et a1. (1985). The CalVET sampler has

a 25-cm diameter mouth and is retrieved vertically to the surface

from 70 m depth; it was designed to sample a small volume of water

in a short period of time relative to the standard CalCOFI bongo

sampler used to conduct larval surveys. The bongo sampler is a

paired net with 60-cm diameter mouths and is retrieved obliquely

to the surface from 210 m depth. Although the sampling gears are

quite different, they yield consistent and compatible estimates of

ichthyoplankton production.

These relationships may also be used to estimate historical egg

production from the production curve of larvae and the abundance

of eggs (La 1985). MacCaIl and Methot (1983) assembled the various

measures of anchovy spawning biomass (egg production, backprojected egg production, acoustic surveys, and aerial spotter logs);

they used acoustic and aerial data to fill in missing ichthyoplankton

survey years and scaled the measures to the recent (1980-82) egg

production estimates of biomass. The resulting 30-yr time series

is the basis for a population model used to manage the harvest of

anchovy (Pacific Fishery Management Council 1983).

ADVANTAGES OF THE EGG

PRODUCTION METHOD _

The egg production method is based on a model which uses instantaneous rates (daily egg production and daily specific fecundity).

As such, a great economy is realized relative to annual estimates,

because the necessary field data can be obtained on a single cruise.

In the case of anchovy, at least four surveys were required to define

the annual spawning activity (Smith 1972). Thus a major advantage

to the egg production method is the relatively low cost of collecting

field data.

The egg production method is also more precise than other ichthyoplankton methods. Early mortality and adult reproductive output

are both measured rather than assumed or extrapolated from other

observations. The extrapolated estimates may be accurate but they

have a finite error associated with the estimation process that is

eliminated when these parameters are measured directly. In the case

of anchovy, the egg production method is also probably more accurate than the larval census method (Picquelle and Hewitt 1983a).

This is because of inaccuracies in estimating the proportionality constant between the annual census of larvae and the weight of the adult

stocks.

The egg production estimate of spawning biomass can be broken

down into several factors each of which can be estimated, with an

associated variance, from a sample of the population. These

variances, together with the covariance between the parameters, may

be used to estimate the variance ofthe estimate ofspawning biomass.

This is not so easily done with estimates based on annual rates

because certain factors must be estimated without an idea of their

variance (e.g., the number of batches spawned per year). It is also

possible to measure the real variance of the egg production estimate

ofspawning biomass by conducting multiple surveys during the same

year as was done in 1981.
LITERATURE CITED _

BANNISTER, R. C. A., D. HARDJ G, and S. J. LOCKWOOD.

1974. Larval monality and subsequent year class strength in the plaice

(Pleuronectes platessa L.). In J. H. S. Blaxter (editor), The early life history

of fish, p. 21-37. Springer-Verlag, N.Y.

BERRIEN, P. L., . A. NAPLIN, and M. R. PENNI GTON.

1981. Atlantic mackerel, S<:omber 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.

BLAXTER, J. H. S. (editor).

1974. The early life history of Fish. Springer-Verlag, N.Y., 765 p.

BUCHANAN-WOLLASTON, H. J.

1926. Plaice-egg production in 1920-21, treated as a statistical problem, with comparison between the data from 1911, 1914 and 1921. Fish. Invest. Ser. 2 Mar.

Fish., G.B. Minist. Agric. Fish. Food 9 (2).

ENGLISH, T. S.

1964. A theoretical model for estimating the abundance of planktonic fish eggs.

Rapp. P.-v. Reun. Cons. int. Explor. Mer 155:174-182.

HEMPEL, G. (editor).

1973. Fish egg and larval surveys. FAO Fi h. Tech. Pap. 122, 82 p.

HENSEN, Y, and C. APSTEIN.

1897. Die Nordsee-Expedition 1895 des Deutschen see fischerei-vereins. Uber

die eimenge de winter laichenden fische. Helgol. Wiss. Meeresunters. 2(2),

101 p.

HEWITT, R. P.

1982. Spatial pattern and survival of anchovy larvae: Implications of adult

reproductive strategy. Ph.D. thesis, Univ. Calif. San Diego, 187 p

HEWITT, R. P., and G. D. BREWER.

10 83. Nearshore production ofyOl:ng anchovy. Calif. Coop. Oceanic Fish. li;·

vest. Rep. 24:235--244.

HUNTER, J. R., and S. R. GOLDBERG.

1980. Spawning incidence and batch fecundity in northern anchovy, Engraulis

mordax. Fish. Bull., U.S. 77:641·652.

HUNTER, 1. R , and B. MACEWICZ.

1980. Sexual maturity, batch fecundity, spawning frequency and temporal patt~rn of spawning for the northern anchovy, Engraulis mardtL(, during the IlTJ9

spawning season. Calif. Coop. Oceanic Fish. Invest. Rep. 21:139-149.

LASKER, R., and K. SHERMAN (editors).

1981. The earl) life history of fish: Recent studies. Rapp. P.-v. Reun. Cons.

int. Explor. Mer 178, 6(JJ p.

LENARZ, W. H.

1972. Mesh retention of larvae of Sardillops caeralea and Engmulis marcltu l'y

plankton nets. Fish. Bull., U.S. 70:839-848.

1973. Dependence of catch rates on size of fish larvae. Rapp. P.-v. Reun. Cons.

int. Explor. Mer 173:270-275.

LO, N. C. H.

1983. Re-examination of three parameters associated with anchovy egg and larval abundance: Temperature dependent incubation time, yolk-sac growth rate

and egg and larval retention in mesh nets. Southwest Fish. Cent., Natl. Mar.

Fish. Serv., NOAA, Tech. Memo. TM-NMFS-SWFC-3I, 33 p.

1985. Egg production of the central stock of northern anchovy, Engraulis mardtLr, 1951-82. Fish. Bull., U.S. 83:137-150.

MacCALL, A. D., and R. D. METHOT.

1983. The historical spawning biomass estimates and population model in the

1983 anchovy fishery management plan. Natl. Mar. Fish. Serv., NOAA,

Southw. Fish. Cent. Admin. Rep. U-83-17, 53 p.

PACIFIC FISHERY MANAGEMENT COUNCIL.

1983. Northern anchovy fishery management plan. Pac. Fish. Mgmt. Counc.,

Portland, OR 97201.

PARKER, K.

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

PICQUELLE, S. J., and R. P. HEWITT.

1983a. The northern anchovy spawning biomass for the 1982-83 California fishing

season. Calif. Coop. Ocean Fish. Invest. Rep. 24:16-28.

1983b. Estimates of the spawning biomass of the northern anchovy for the 1983-84

California fishing season. Natl. Mar. Fish. Serv., NOAA, Southw. Fish. Cent.,

La Jolla, CA, Admin. Rep. U-83-15, 40 p.

SAVILLE, A.

1956. Eggs and larvae of haddock (Gadus aeglejinus L.) at Faroe. Mar. Res.

Dep. Agric. Fish. Scotl. 4.

1964. Estimation of the abundance of a fish stock from egg and larval

surveys. Rapp. P.-v. Reun Cons. int. Explor. Mer 155:164-173.

99

SAVILLE, A. (ed.tor).

1977. Survey muhods of appraising fishery resources. FAO Fish. Tech. Pap.

171,76 p.

SAVILLE, A., and D. SCHNACK.

1981. Some thoughts on the current status ofstudies of fish egg and larr..1distribution and abundance. Rapp. P.-v. Reun. Cons. In!. Explor. Mer 178:153-157

SETTE, 0. E.

1943. Biology of the Atlantic mackerel (Scomber scambras) of North America.

Part I: Early life history, including the growth, drift and monality of the egg

and larval populations. U.S. Fish. Wildl. Serv., Fish. Bull. 50:149-237.

SETTE, O. E., and E. H. AHLSTROM.

1948. Estimations of abundance of the eggs of the Pacific pilchard (Sardinops

caerulea) offsouthern California during 1940 and 1941. J. Mar. Res. 7:511-542.

SIMPSON, A. C.

1959. The spawning of the plaice (Pleuronectes platessa) in the North Sea. Fish.

Invest. Ser. 2 Mar. Fish., G.B. Minist. Agric. Fish. Food 22(7), 111 p.

SMITH, P. E.

1972. The increase in spawning biomass of northern anchovy, Engraulis mardtLr.

Fish. Bull., U.S. 70:849-874.

SMITH, P. E., and S. L. RICHARDSON.

1977. Standard techniques for pelagic fish egg and larval surveys. FAO Fish.

Tech. Pap. 175, 100 p.

1979. Selected bibliography on pelagic fish egg and larval surveys. FAO Fish.

Circ. 706, 97 p.

SMITH, P. E., W. FLERX, and R. HEWITT.

1985. The CalCOFI vertical egg tow (CaIVET) ne!. In R. Lasker (ed.tor), An

egg production method for estimating spawning biomass of pelagic fish: Application to the northern anchovy, Engmulis /'lOrdax, p. 27-32. U.S. Dep. Commer.. NOAA Tech. Rep. NMFS 36.

STAGFFER, G D

1983. Calibration of northern anchovy spawnIng biomass estimates derived by

egg production and !arval census methods. Calif. Coop. OceanIC FIsh. Inves!.

Rep. 24: 11-15.

STAUFFER, G. D., and S. J. PICQUELLE.

1980. Estimates of the 1980 spawning biomass of the central subpopulation of

northern anchovy. 'btl. Mar. Fish. Serv., NOAA, Southw. Fish. Cent. Admin. Rep. LJ-80-09, 41 p.

ULLTANG,o.

1977. Methods of measuring stock abundance other than by the use of commercial catch and effort data. FAO Fish. Tech. Pap. 176, 23 p.

VAN CLEVE, R., and A. H. SEYMORE.

1953. The production af halibut eggs on the Cape St. James spawning bank off

the coast of British Columbia 1935-46. Rep. Int. Pac. Halibut Comm. 19, 44 p.

ZWEIFEL, 1. R.. and P. E SMITH.

1981. Estimates of abundance and monality of larval anchovies (1951-75): Application of a new method. Rapp. P.-v. Reun Cons. in!. Explor. Mer 178·

248-259.