AN ABSTRACT OF THE THESIS OF
Moises Mug Villanueva for the degree of Master of Science in Fisheries Science
presented January 22. 1993.
Title: Age Determination of Corvina Reina (Cynoscion albus) in the Gulf of Nicoya
Based on Otolith Sgrface Readings and Microincrement Analysis.
Redacted for Privacy
Abstract
approved:
Vincent F. Gallucci (Thesis Professor)
Redacted for Privacy
James D. Hall (Major Professor)
The corvina reina (Cynoscion albus) is an important part of the artisanal fishery
in the Gulf of Nicoya, Costa Rica. Stock assessment on this sciaenid species has been
restricted to the use of length-based methods because of the lack of age data. Direct age
determination methodologies for tropical species often encounter serious difficulties
such as poorly defined hyaline and opaque zones and lack of adequate techniques of
ageing. This thesis presents the results of an age-determination study of Cynoscion
albus based on otolith surface readings and microincrement analysis. Age estimates
were obtained from counts of hyaline zones from surface readings using the light
microscope and from microincrement readings from cross sections of the otolith using
the scanning electron microscope. Validation of age estimates from surface readings
was based on a linear regression of the age estimates from surface readings on age
estimates from integrated daily increment readings. Growth of the otolith was studied
using linear and multivariate regression methods and the results were used to construct
multivariate models for prediction of age. Consistent estimates of age and fish growth
parameters were obtained from surface and microincrement analysis. This study showed
that Cynoscion albus is a slow-growing fish (K = 0.121) and reaches a large size
=
127.5 cm) and therefore is likely to suffer overfishing in the Gulf of Nicoya fisher/.
Age Determination of Corvina Reina (Cynoscion albus) in the Gulf of Nicoya,
Based on Otolith Surface Readings and Microincrement Analysis.
By
Moises Mug-Villanueva
A Thesis
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Completed January 22, 1993
Commencement June 1993
Approved'
Redacted for Privacy
Professor of Fisheries ina Quantitative Science in charge of thesis
Redacted for Privacy
_
Professor
isheries in charge of major
Redacted for Privacy
.
Head of the Department of Fisheries and Wildlife
Redacted for Privacy
Dean of Graduate S
Date thesis is presented
(1/
January 22. 1993
Typed by Moises Mug-Villanueva
Acknowledgments
I am indebted to my major professor Dr. James D. Hall for his generous
academic and intellectual guidance and encouragement throughout my graduate
program and to Dr. Dan Schafer for teaching me statistics and for being part of my
graduate committee. I am also indebted to Dr. Vincent F. Gallucci for his extensive
intellectual guidance and supervision during my thesis research. I am most thankful to
Dr. Hall and Dr. Gallucci for providing me with the rare opportunity of doing my
graduate studies in a joint program between the Department of Fisheries and Wildlife of
Oregon State University and the School of Fisheries of the University of Washington. I
am especially thankful to Dr. Han-Lin Lai for guiding me in the art and science of the
age determination and for his intense critical review of my research, and to John
Hedgepeth and Benyounes Amjoun for helping me with the computer work.
I am most thankful to the School of Fisheries and the Center for Quantitative
Science of the University of Washington for accepting me as a visiting graduate student
and for providing office space and materials for my work, to the
Department of
Geology of the University of Washington for allowing me the use of the Thin Section
Laboratory, to David M. McDougall of the Thin Section Laboratory for sharing with
me his great deal of experience in thin sectioning and polishing, to Dr. John Adams
for
permitting me the use of the Isomet low-speed saw, and specially to Dr. Barbara A.
Reine of the Department of Botany for teaching me the use of the scanning electron
microscope and for assisting me with the sample preparation techniques.
I specially thank the cooperation of the University of Costa Rica
(UCR) and the
Latin American Scholarship Program of American Universities
(LASPAU) that
provided logistic support for this research. I thank my former professor Jorge A.
Campos MSc. and the Research Center for Marine Sciences and Limnology of UCR
(CIMAR-UCR) for providing me with the corvina fishery data and otolith
collection. I
also thank the University of Costa Rica at Limon for providing me the time to complete
my Masters program. Financial support came from the University of Costa Rica through
its Faculty Development Program, from LASPAU and the
United States Information
Agency through a Fulbright Scholarship, and from the USAID
through the Fisheries
Stock Assessment Title XII of the Collaborative Research Support Program.
Finally, I wish to thank my family who provided me the inspiration and support
to conclude my studies. I thank my father Antonio Mug-Ching, my mother Mariana
Villanueva-Gutierrez, and my brother Marco A. Mug-Villanueva who always provided
me with spiritual support and love. I thank my wife Ofelia Salas-Quesada for her
devoted love and companionship and for taking care of our two daughters Elky Paola
and Annette Pamela during my studies. And I thank my daughters for their
understanding, love, and patience.
Table of Contents
Introduction
1
Materials and methods
Age determination using surface readings of the otoliths.
5
Validation of hyaline surface readings using daily increment
readings
13
The growth of Cynoscion albus
15
The growth of the otolith
16
Age determination using surface readings of the otoliths
18
Validation and microstructure of the otolith.
18
The growth of Cynoscion albus
21
The growth of the otolith
33
Results
Discussion.
42
Bibliography.
46
List of Figures
Figure 1. The map of the Gulf of Nicoya, Costa Rica.
4
Figure 2. The sagitta of Cynoscion albus
7
Figure 3. Size distribution of the otolith collection and sampling effort.
10
Figure 4. Hyaline zones of the otolith of C. albus.
19
Figure 5. Microstructure of the otolith of C. albus
22
Figure 6. Validation test of the age estimates from surface readings
based on the age estimates from microincrement analysis.
28
Figure 7. Estimated von Bertalanffy growth curves from surface readings
of hyaline zones with the light microscope (solid line) and daily
increment readings with the scanning electron microscope (dashed line).
30
Figure 8. Otolith length (OL) versus fish length (FL)
33
Figure 9. Otolith width against fish length (A), otolith length (B), and
age (C).
Figure 10. Otolith breadth against fish length (A), otolith length (B), and
age (C).
Figure 11. Increment in thickness of the ventral edge (at point A, see
Figure 2A)..
Figure 12. Estimated von Bertalanffy curve for otolith length (OL).
35
37
38
41
List of Tables
Table 1. Age-Length Key (ALK) for Cynoscion albus based on surface
readings of otoliths.
Table 2. Results of the age determination on 17 otoliths from numerical
integration of daily increments using the SEM and from surface readings
(SR).
Table 3.Validation test based on linear regression of hyaline surface
readings on daily increments readings
Table 4. Analysis of residual sums of squares (ARSS) for the comparison
of the growth curves obtained with the age data from surface readings
(n = 168), daily increment reading (n = 17), and the pooled data (n =
185)
20
27
29
31
Table 5. Comparison of the von Bertalanffy parameter estimates from
surface readings and microincrement readings methods using the 0)-test
(Omega test, Gallucci and Quinn 1979)..
32
Table 6. Summary of the linear regressions
36
Table 7. Extra sums of squares F-test for the significance of terms for
two multivariate models for the prediction of age (Full models) obtained
with stepwise forward regression
Table 8. Von Bertalanffy growth parameters for otolith length
40
41
Age Determination of Corvina Reina (Cynoscion albus) in the Gulf of Nicoya, Costa
Rica, Based on Otolith Surface Readings and Microincrement Analysis.
Introduction
Corvina reina (Cynoscion albus) is
one of the principal targets of the
multispecies artisanal fishery in Costa Rica, but until recently there have been few
scientific studies on the age, growth, and population dynamics of this sciaenid. The
previous effort on its stock assessment used length-based analysis (Stevenson 1981,
Madrigal-Abarca 1985) due, at least in part, to the difficulties associated with the
determination of the age of tropical species. Estimation of the age and growth rates of
tropical fish using otolith and other bony structures has been a persistent problem
because of the difficulties in distinguishing conventional hyaline and opaque zones or
because of the absence of adequate ageing techniques (Brothers, 1979, 1982).
Furthermore, the large size and thickness of the sagitta in sciaenids makes them
particularly difficult to age. Thus, stock assessment of fish in general and sciaenids in
particular often relies on length-based methods (Isaac, 1990).
Since Panne lla (1971) reported the existence of daily otolith increments, a
significant body of research on the microstructure of the otolith has emerged, but most
of it has focused on ageing larval and juvenile fish (Jones 1986), or on environmentally
dependent phenomena (Campana and Neilson 1985, Wright et al. 1990, Mai llet and
Check ley 1990). In contrast, Ralston (1985) and Ralston and Miyamoto (1981, 1983)
have used the density of daily growth increments to estimate age and growth in tropical
lutjanids. Ralston and Williams (1988) developed a cost-effective method of age
determination based on the numerical integration of daily increments in conjunction with
the light microscope and Morales-Nin and Ralston (1990) adapted this method of
microstructure analysis to the Scanning Electron Microscope (SEM). Microincrement
analysis was the primary source of data in all these studies and the results demonstrate
the feasibility of ageing adult tropical lutjanids.
2
Continued development of the application of microincrement analysis to other
tropical species will lead to an increased level of accuracy in the stock assessment of
tropical fisheries. Microincrement analysis is also a potentially useful method of age
validation when an alternative method is the primary source of data, especially since the
common methods of validation that involve recaptures of marked fish or growth in
captivity are typically impractical in tropical fisheries. Lai and Campos (1989) used
otolith surface readings to age two other corvinas in the Gulf of Nicoya and applied a
method of validation that depended upon the ability to identify modal peaks in the size
distribution and to relate these to ages. But size-based methods of stock assessment are
subject to errors that stem from the inherently confounded nature of size data, by the
frequent Ad hoc nature of the methods of analysis, which sometimes lack valid statistical
foundations, and by the excessive sensitivity of certain parameters in the models to small
errors in estimation (Lai and Gallucci 1987). It must also be noted, however, that given
the costs of operation of a SEM facility it may be practical to use microincrement
analysis with a SEM only on tropical species that have some central ecological or
fishery role or that are particularly susceptible to over-exploitation.
Corvina reina fits this description since it is the most sought after and the largest
corvina in Costa Rica, and the one most likely to experience recruitment overfishing.
Therefore, the present study has three objectives:
(a) To provide an efficient age-determination methodology and validation procedure to
estimate age for the tropical sciaenid Cynoscion albus using otolith surface readings and
microincrement analysis.
(b) To provide appropriate direct estimates of age at length and the corresponding von
Bertalanffy growth parameters, Loo, K, and to, for the stock assessment of C. albus in
the corvina fishery in the Gulf of Nicoya, Costa Rica.
(c) To contribute to the general knowledge of age and growth of tropical fish.
This paper presents the results of the first age determination for Cynoscion albus
based on surface readings of its otoliths. It is also the first application to use the
microincrement analysis to age adults of a long-lived species.
The fishery on C. albus occurs in the Gulf of Nicoya on the Pacific coast of
Costa Rica (Figure 1). C. albus is one of five species under study, by the Centro de
Investigacion en Ciencias del Mar y Limnologia (CIMAR) of the University of Costa
Rica and by the Management Assistance for Artisanal Fisheries Program (MAAF) of the
University of Washington, all of which are part of the "corvina complex" that occurs in
the Gulf. The fishery is a drift gillnet fishery using three different sized gillnets
of 3" (7.6
cm), 5" (12.7 cm), and 6" (15.0 cm). This investigation of the age and growth of
3
corvina reina is part of a project focused on the stock assessment of the five species that
are the most abundantly caught and presented to the market. An overview of the
multispecies-multigillnet problem is in preparation (Gallucci et al. 1993 in prep.). Lai et
al. (1993) have completed a preliminary investigation of strategy options for the C.
albus fishery with the multigillnet sizes but treated as a single species fishery.
4
850 W
Atlantic
Ocean
0
100N -
The Gulf of Nicoya
850 W
Figure 1. The map of the Gulf of Nicoya, Costa Rica.
5
Materials and methods
Age determination using surface readings of the otoliths
A sample of 583 pairs of otoliths, sagittae (Figure 2), was collected from C.
albus landings in the Gulf of Nicoya during the period of 1986 to 1989 (Figure 3 A).
The sampling program was concentrated in 1987 and 1988, but did not sample every
month (Figure 3 B, C, D, E). Ninety five percent of the sample (533 otoliths) was
collected during 1987 and 1988, 74% (433 otoliths) in 1987, mostly from July and
August, and 21% (120 otoliths) from 1988, mostly from March and April. The
information recorded for each otolith includes sample number, date of collection, and
fish length. After extraction and cleaning, the otoliths were sent to the laboratory for
preservation. Three different methods were used to preserve the otolith collection:
stored dried in sealed plastic bags, stored in a 50% alcohol solution, and stored in
glycerine.
Sagittae of Cynoscion albus are large and thick, although these otoliths are
considered thin amongst the sciaenids (Chao 1986). Its shape resembles that of an oval
with a concave-up curvature (Figure 2). Characteristically, the thickness of the otolith
increases with the size of the otolith, making it difficult to read for growth marks such
as hyaline or opaque zones. Knowledge of the sagitta's morphology is required to
understand the growth of this sagitta and its relation to the age determination process.
The sagitta of C. albus can be divided into six major parts
1. Distal and proximal faces.
A vertical plane divides the sagitta into the proximal and distal parts or faces
(Figure 2A, B) The distal area faces the external part of the skull and has a series of
bumps and notches that start at the nucleus of the bone and extend to the anterior part.
Readings of hyaline and opaque zones are more easily done over the distal face. The
proximal area faces the inner part of the fish skull, and has the sulcus .
2. Anterior, posterior, and cross sections.
A cross plane through the focus or nucleus divides the sagitta into the anterior
part or rostrum and the posterior part , tail or antirostrum (Figure 2A). A
cross section
6
of the sagitta shows the nucleus or focus, the sulcus, and the dorsal and ventral axes of
growth (Figure 2E, F).
3. Dorsal and ventral areas:
An horizontal plane divides the sagitta in two areas, dorsal and ventral (Figure
2A, C, D). The ventral margin tends to increase in thickness along the frontal edge as
the sagitta grows, specially when the fish attains older ages, while the dorsal margin
presents very little increase in thickness in comparison to the ventral edge (Figure 2E,
F).
The thickness of reina otoliths is a major part of the problem in age readings
because a dense calcium carbonate deposition accompanies increments of thickness, and
does not permit easy transmission of light. Therefore, growth zones are not easy to
distinguish when viewed with transmitted or reflected light. To improve the visibility of
growth marks, one sagitta, usually the right one, from every pair was ground with
silicon carbide wet sandpaper in a series of grades of 220, 320, and 400 grit. The
grinding was done by hand sanding the distal face of the sagitta over a cylinder of
wood, to which strips of wet sandpaper were attached. This grinding process was
chosen as a consequence of the natural concavity of the sagitta. The grinding process
was frequently monitored by examining the otolith under a light microscope. The
ground otoliths were immersed in water, which was the refraction medium and placed in
a petri dish with a black background for contrast. Otoliths were analyzed with a total
magnification that ranged between 8x and 24x.
Otoliths were viewed under a Zeiss binocular stereomicroscope (model SR)
with a camera attachment and two light sources. The stereomicroscope was equipped
with a 50-mm objective lens, an optional objective lens of 100 mm, a magnification
changer set to 0.8, 1.2, 2.0, 3.2, and 5, and two eye pieces of W10 X/ 25 Br. A Nikon
N6006 SLR camera was used to take pictures of the growth marks. A
Schott light
source (KL 1500) with two 2-branch goose-neck light conductors was used for
reflected light analysis. An Epi illuminator with halogen filament was used for optional
transmitted light analysis.
Age determination was based on counts of the number of hyaline zones (dark
zones when viewed with oblique reflected light on a black background) on the distal
face of the otolith, assuming that one hyaline zone was formed per year (Casselman
1983). Two ways of counting hyaline zones were used: counting from the center or
nucleus to the anterior edge, and counting from the nucleus to the posterior edge. The
choice of the direction of counting depended upon how well defined the zones were
after grinding.
7
HZ
B
HZ
Figure 2. The sagitta of Cynoscion albus. (A). The distal face of the otolith can be
divided into the anterior, posterior, dorsal, and ventral parts. The age of the fish can be
estimated by the number of hyaline zones (HZ). The growth in breadth of the otolith can
be measured at the points AB and CH. (B). Proximal face of the otolith contains the
sulcus.
8
Ventral edge
Dorsal edge
Figure 2 (Continued). (C). The lateral view of the ventral part of the sagitta shows the
growth in width or thickness (W , W015, and W0.05 see page 16 for definitions), the
ventral edge, and the sulcus. The growth in thickness can also be measured at the point
"A" of the ventral edge. (D). The lateral view of the sagitta shows the dorsal edge and
the notches. Notches can also be seen in the lateral view of the ventral part.
9
9
VE
E
VE
F
DE
DE
Figure 2 (Continued). (E) cross section of an otolith (OL = 17.94 mm) from a 46-cm
fish. (F) cross section of an otolith an otolith (OL = 34.20 mm) from a 102-cm fish.
These two sections show the dorsal (DA) and ventral (VA) axes of growth, nucleus
(N), sulcus (S), and the thickness of the ventral edge (VE). Note the increment in
thickness of the ventral edge in the larger otolith.
10
Total sample size collected from 1986-1989 (N=583)
2520
115
A
E
2
10
5.
11
1:14
22- 3333g44'235323 ?-
s
Length (cm)
0
1988 (N= 120)
3Ng
g Q `41 2
IA
53
51 3 3' n
112
O$333F
Length (cm)
1987 ( N=433)
20 18 16
14 12 -
C
E 10-
2 86420
7-?-'332324`4212323AP33833213 0
Length (cm)
Figure 3. Size distribution of the otolith collection. A. Size distribution of the otoliths
collected from 1986 to 1989. B. Size distribution of the otoliths collected in 1988. C.
Size distribution of the otoliths collected in 1987.
11
1988 (N=120)
6o50
14030-
D
2010 0
MIR
2
1
3
4
5
6
7
8
9
10
12
11
Month
1987 (NS32)
E
1
2
3
4
5
6
7
8
9
10
11
12
Month
Figure 3 (Continued). D. Sample size by month in 1988. E. Sample size by month in
1987.
12
The first growth mark was counted at about 0.9 to 1.2 mm from the nucleus of
the otolith. This criterion was selected by observing the distance between the nucleus
and the first visible mark in the smaller otoliths. Subsequent counts of hyaline zones
followed under the assumption that the distance between two growth marks should
narrow as the counting approaches the margin. When the otoliths showed a growth
increment in thickness of the ventral edge, further counts of hyaline zones were taken in
that dimension. The results of the age determination of the surface readings were used
to construct an age-length key and to estimate the von Bertalanfy growth parameters.
Grinding reina otoliths is a time consuming process. At the beginning, 57
otoliths of different sizes were used as a training sample. As expected, the time spent in
grinding increased with the thickness of the otolith. For example, for small otoliths it
took between 15 to 25 minutes but for larger otoliths time ranged between 30 minutes
up to 2 hours. Therefore, a subsample of 151 otolith pairs was selected from the 529
pairs available over the range of fish lengths between 31 cm to 100 cm. A second
subsample of 17 otolith pairs was selected from the 54 available pairs over the range of
for fish sizes from 101 cm to 115 cm. Fish lengths in both subsamples were divided into
5-cm length intervals from 31 cm to 115 cm resulting in 17 strata, and random samples
was taken from each interval. The first group of 151 pairs were selected according to
ni = Ni (n I N 1_00)= Ni (151 / 529) = Ni (0.285)
where ni is the number of otoliths pairs sampled by stratum i = 1,2...14; Ni is the total
number of otolith pairs in strata i, n = 151 is the sample size, and N<100 = 529 is the
number of otoliths from fish equal to or less than 100 cm. The second group of
otoliths was selected according to
ni = Ni(n 1 N,100) =
(17 / 54) = Ni (0.315)
where ni is the number of otolith pairs sampled by stratum i = 15, 16, 17; Ni is the
total number of otolith pairs in strata i, n = 17 is the sample size, and N>100 = 54 is the
number of otoliths from fish larger than 100 cm. The fraction of the otoliths in the
second subsample was slightly higher to account for the increased information in
otoliths from older animals with longer and thicker otoliths.
13
Validation of hyaline surface readings using daily increment readings.
It was not possible to reconstruct modal classes from length frequency data (Lai
and Campos 1989, Morales-Nin and Ralston 1990) nor to use marginal increment
formation for validation (Kimura et al. 1979) because sampling effort varied among
years and because otoliths were not collected every month (Figure 3). Other
validation alternatives, such as the use of oxytewacycline (OTC) tinction combined with
capture-recapture or growing the fish in captivity (Casselman 1987), were not feasible
due to circumstances in the fishery.
An alternative validation procedure is to estimate age using daily increment
readings. Gauldie and Radtke (1990) concluded that microincrementation in fish otoliths
is an obligatory process tied to daily and seasonal physiological cycles of the fish.
Therefore, an estimate of age is possible if it is assumed that daily obligatory
microincrements occur in C. albus and that these can be defined and counted under the
SEM. Resulting estimates of age are then used to validate the age determination based
on surface readings of the hyaline zones interpreted as annual marks.
Thus, a sample of otoliths for microincrement analysis was randomly
subsampled from the otoliths that were subjected to surface analysis with the light
microscope. One otolith from each 5 cm length interval from 30 cm to 115 cm was
chosen for daily increment readings, resulting in a sample size of 17 otoliths. Otoliths
were selected for microincrement analysis under the SEM without knowledge of the
age assigned by the surface readings method. For consistency the right side sagitta was
usually prepared for surface readings so the left side sagitta was chosen for
microincrement analysis.
The age determination of this otolith sample generally followed the technique
of numerical integration of daily increments described by Ralston and Williams (1988).
Some modifications were made in the sample preparation and in the sample reading
techniques for SEM analysis provided by Morales-Nin and Ralston (1990).
Otoliths were embedded in casting polyester resin and cut with an Isomet lowspeed saw across the focus to produce cross sections. Sections were glued to aluminum
stubs with silver paste (Ted Pella, Inc.) and let dry overnight. The focus was exposed
by polishing by hand with 0.3 micron aluminum oxide over a glass plate and finishing
with soft goat leather. After polishing, the preparations were rinsed in alcohol and water
to wash off residual debris. Otoliths were then etched for five minutes in
1%
14
hydrocloric acid. After the etching was completed, the samples were rinsed again in
water and alcohol. To eliminate humidity, and avoid problems of charging (Morales-Nin
and Ralston, 1990), the otolith preparations were dried in an oven at 60 °C overnight.
Finally, the preparations were coated with gold-paladium for four minutes in a
Hummer-V Sputter Coater. This coating time provides the otolith with a 300 A° thick
gold-paladium surface approximately. Longer coating time can put an excessive layer
of gold-paladium over the sample with the danger that the topographic contours
produced by the etching can be lost. Shorter coating times avoid this problem but
provide weak signals, hence poor images (B. Reine, Department of Botany, University
of Washington, personal communication).
The preparations were viewed in a JEOL-840A scanning electron microscope
using an acceleration voltage of 15 kv, a magnification that ranged between 20x and
3300x, and a working distance of 10 mm to 12 mm. Counts of increments were made
along the ventral axis of growth at 2000x and 3300x. A replica of the ventral axis was
stratified in one-millimeter intervals on a piece of paper using the one-millimeter scale
provided by the TV monitor at 20x. This stratified replica was then used to identify and
position the strata on the TV screen. The number of strata per otolith depended upon
the length of the ventral axis.
Two to six sample counts were taken from each stratum depending upon the
readability of the microincrements along the stratum. Each stratum was scanned for
prospective sample sites. The electron beam was positioned on the desired sample site
by moving the selected portion of the stratum to the center of the TV screen, using the
x-y stage controls at the lowest magnification and then gradually turning to the
magnification appropriate for counting. Each time the magnification was changed the
selected sample site was repositioned to the center of the screen. To move the electron
beam to another sample site the magnification was turned to the lowest value and the
same process started again.
At every sample site in each stratum, the number of increments per 10 gm was
recorded. In order to facilitate counting of the microincrements the sample was rotated
inside the SEM chamber so the 10 gm scale appeared on the screen parallel to the
direction of growth of the microincrements. The resulting counts of increments per 10
pm were extrapolated to 100 p.m for each stratum. The average number of increments
per 100 gm were then extrapolated to 1 mm. The resulting total number of increments
per stratum was integrated for every millimeter of radius. Totals of increments per
millimeter of radius were added up and divided by 365 to obtain the estimation of age in
years. When additional growth in width at the margin (thickness) was observed further
15
counts of microincrements were taken in that portion of the otolith, and the average
number of increments was added to the total counts for the estimation of age. A linear
regression was used to compare the ages determined by the surface reading and daily
increment methods. Let X be the age from daily increment readings and Y be the age
from the surface method. Two-sided t-test was used to test the null hypothesis Ho : Y =
X or Ho : b = 0, m =1 against the alternative hypothesis Ho : Y = m X + b or Ho : b 0,
m 1. Failure to reject Ho implies that no statistical difference exists between the age
reading from the two methods.
The growth of Cynoscion albus
The growth of C. albus was assumed to follow the von Bertalanfy growth
model
=
where
(1 eic("°))
LI is the length at time t, and the parameters of the model are : Lam, the
asymptotic length; K, the growth constant; and to is the hypothetical age at which a fish
would have length zero, a constant.
The age at length data were used to fit two von Bertalanffy growth curves. The
first curve was fitted with the data from surface readings. The second curve was fitted
with the data from daily increment readings. Parameter estimates were obtained using
the SYSTAT nonlinear estimation procedure. A statistical comparison of the two
growth curves was carried out using analysis of residuals sums of squares (ARSS)
(Chen et al., 1992), and by the Omega-test (Gallucci and Quinn, 1979). The co-test
takes into account the negative correlation of K and Lc., where an increase in one
requires a decrease in the other. To mitigate the effect of this negative correlation in a
comparison test, the test is done on a reparameterized version of the model.
16
The growth of the otolith
Casselman (1987) proposed that the function of a structure can explain its
differential growth and its ability to record age and that the growth of the otoliths as
organs of equilibrium may be less associated with increase in fish length and more to the
passage of time. Thus, the growth of the sagitta of C. albus may in fact provide
valuable information for the prediction of age.
The growth of the corvina reina sagitta was studied by taking measurements of
its length, width and breadth (Figure 2). Linear regression was used to relate the otolith
length to fish length. Linear regression was also used to relate otolith width and
breadth with respect to fish length, otolith length, and age. Multivariate models for the
prediction of age were constructed with the data on measurements of fish length, otolith
length, otolith width, otolith breadth, and the age estimates from surface readings. Extra
sum of square F-tests were used to test the significance of terms in the multivariate
prediction models. In addition, to illustrate the role of the otolith length in the
estimation of age von Berta lanffy curves for the growth of the otolith in length and
breadth were constructed. The measurements of the otolith were taken in millimeters
(± 0.01 mm) with a caliper as follows :
(a) otolith length (OL) was measured from the tip of the frontal edge to the tip of the
posterior edge (Figure 2B).
(b) otolith width was measured at four different points (Figure 2C) :
b. 1. Wmax or maximum width. Usually measured near the focus or nucleus of the
sagitta.
b.2. W015 or width taken at 15% of the otolith length measured from the frontal
edge to the nucleus.
b.3. W0.05 or width taken at 5% of the otolith length measured from the frontal
edge to the nucleus.
b.4. WA width or thickness taken at the ventral edge or margin of the otolith at
point "A".
(c) otolith breadth was measured as the distance between the dorsal and ventral
margins at the points A-B and C-H (Figure 2A). The dorsal margin presents two
lips, B and H, that were selected as reference for the measurements of breadth
17
and connected with a line perpendicular to the horizontal plane of the otolith to
the points A and C of the ventral margin. Thus, two measurements of breadth, AB
and CH, were obtained for each otolith. Point "A" of the ventral margin was also
used to take measurements of width or thickness of the ventral edge of the otolith
as previously described.
18
Results
Age determination using surface readings of the otoliths
Hyaline zones appeared as dark bands in the otolith of C. albus (Figure 4). The
distance between two adjacent hyaline zones decreased toward the margin of the
otolith. Figure 4 shows six hyaline zones on a 47-mm otolith corresponding to a 65.5 cm fish (Figure 4A), and nine hyaline zones on a 56-mm otolith from a 83-cm fish
(Figure 413). Hyaline zones lay down late in life were closer in older fish than in younger
ones and therefore harder to distinguish. Also, the distance between adjacent hyaline
zones in the frontal area was smaller than in the posterior area. This is because the
anterior area is smaller than the posterior area. This fact made the readings of growth
marks particularly difficult to make in older otoliths when the anterior portion was used
to count the increments
Seventeen age classes, ranging from 2-years-old to 18-years-old fish, were
determined by the surface readings of hyaline zones (Table 1). Generally speaking, the
resulting age-length key presents a mixture of ages and lengths that suggests
three
main patterns. First, the number of ages within a 5-cm length class increases as the fish
grows larger. Second, with four exceptions, each age contained two to three length
classes. And third, the length distribution contained in two consecutive age classes
overlaps with one to two length categories, except for ages 9-10, and 12-13.
Validation and microstructure of the otolith
SEM analysis of cross sections of C. albus otoliths shows visible
microincrements for young fish as well as for adult fish (Figure 5). The average
number of increments per 100 p.m increases as the counts
move from the focus to the
margin of the otolith (Table 2). This is an indication that the width of the
microincrements decreases as the fish grows older. The average number of increments
19
A
B
Figure 4. Hyaline zones of the otolith of C. albus. After grinding, the hyaline zones
were easier to see under the light microscope. With transmited light and black
background, the hyaline zones appear as dark bands. A. 47.0 mm otolith from a 65.5 cm
fish showing six hyaline zones (six years). B. 56 mm otolith from a 83 cm fish showing
nine hyaline zones (nine years). For this otolith late hyaline zones are hard to
distinguish.
Table 1. Age-Length Key (ALK) for Cynoscion albus based on surface readings of otoliths.
Length intervals are in centimeters.
Interval
31-35
36-40
41-45
46-50
51-55
56-60
61-65
66-70
71-75
76-80
81-85
86-90
91-95
96-100
101-105
106-110
111-115
Totals
Fraction
2
3
1
1
3
1
4
4
Years
5
6
7
8
9
10
11
12
13
14
15
16
17
18
3
6
4
7
3
9
4
8
5
10
9
1
5
5
19
10
10
14
5
5
5
4
.02
total
2
4
20
10
7
2
2
5
15
17
15
3
5
3
1
1
3
4
2
1
14
4
2
1
6
13
12
20
.04
.08
.07
.12
34
.20
15
.09
19
.11
10
.06
8
.05
6
.04
7
.04
11
1
3
1
1
1
2
1
6
.04
10
5
5
1
1
1
.03
.01
.01
.01
168
1.0
fraction
.01
.02
.04
.05
.05
.03
.06
.08
.12
.09
.10
.09
.08
.07
.06
.03
.01
1.0
21
per 100 gm increases from 19.98 increments within the first millimeter to 97.5
increments at the eighth millimeter of radius. Problems of charging and irregularity in
the microincrements within the first 2 mm around the nucleus caused serious difficulties
in achieving clear readings of microincrements in that portion of the otolith, but for
most of them 2 microincrements per 10 pm were observed. Despite this difficulty
this
technique produced age estimates that were very close to the age estimates provided by
the surface readings.
The ages assigned by the numerical integration of daily increments were not
significantly different from the ages assigned by the surface readings for the same fish
(t-test p-value > 0.10) ( Figure 6, Table 3). If the assumption that the observed
microincrements correspond to daily periods of growth is true, the SEM data validate
the age determination based on surface readings of hyaline zones.
The growth of Cynoscion albus
The
length-age relationship as estimated from surface readings and daily
increment readings appears to be well described by the von Bertalanffy growth model
(Figure 7). Fish growth in length reaches an asymptote as age increases. The
von
Bertalanffy growth curves obtained by the surface readings and daily increment readings
are visually similar. To statistically test the similarity a modified analysis
of residual
sums of squares (ARSS) (Chen et al. 1992) was carried out and the null hypothesis that
the curves are similar was rejected at a = 0.05 (Table 4)
One reason for rejection of the null hypothesis in this analysis was that the
sample size for the daily increment reading was about 10% of that for
surface readings.
This illustrates a limitation of using an F-test on the growth curves for comparison when
the samples sizes differ greatly. An alternative is to test whether
the parameter estimates
themselves K and Loo are statistically different where one set of data and estimates
comes from each ageing method. The omega-test (Gallucci and Quinn, 1979)
showed
that the *surface readings) value is contained within the 95%
confidence interval of the
*(daily readings) value but the reverse is not true. Thus, there is a statistical basis for
not rejecting Ho : co(surface readings) = (w -daily readings) (Table 5). The conclusion
is reasonable since the Loo values differ by only 5 cm over 127 cm and the K values
differ by 0.05 over 0.12. The big difference in sample sizes
causes the ambiguity in the
test results.
22
A
B
Figure 5. Microstructure of the otolith of C. albus. A. Nucleus. Note the early
microincrement deposition and the later irregularity of the microincrements. B. View of
microincrements within 3 mm from the nucleus. Note the difference of width regularity
from microincrements near the nucleus above.
23
C
D
Figure 5 (Continued). C. View of microincrements within 4 mm D. Microincrements
within 5 mm from the nucleus.
24
E
F
Figure 5 (Continued). E. Microincrements within 6 mm from the nucleus, and F. View
of microincrements within 7 mm from the nucleus.
25
G
_;,,,,,6P0P,1
-----..c.' ,..--
....r44. ,-..,
1.......-
'''.
r-*ite---.....
. -,-
, _ . ,......_,
_
_ .-.-
rt..
-7
.4.0% ' .:.
----- -1..,-..,"" -.--.= 1.--
;%;
....- .-
"-;,,,,.,.. .' . .k.'...............". ....._
-
,
- -.'''!..r.ac
-..--.7...._
Z."...""
' ."-
-z
...- ._-s-......-- -_;10-.
-
_.....,
.--
...,..
_"""=.:--- ,.._-;,," ,'..
1:
'-,'"'"
.------_--
,....---
---."-4
.
....- ..
-.4110
-..---. -1"--""--
-
."...----I
,-..-:.---
.--
-
.....-..
. . r - -- - . . ,- ;L. ii
,_ .......
...
--'
S'
---7
...ii ilk 7
'''.''''
SaiSiS:.-...."....' '"'"-"''.- - .4..._ I 4-
Figure 5 (Continued). Etching was different in the sulcus side (SS), antisulcus side
(ASS), and withing the first two millimeters from the nucleus. G. Charge on the otolith
Some otoliths
presented a heavy check around the nucleus area running in the antisulcus side (Small
arrow). H. Within 2 mm around the nucleus the microincrements appear very irregular.
Left: a 360x magnification. Right: a factor 4 magnification of the square in the left.
preparation appears as a cloud on the SEM image (large arrow).
26
I
J
Figure 5 (Continued). I. Closer view of the difference in etching results at the sulcus
(SS) and antisulcus side (ASS). The ventral axis of growth appears to be a limit for the
difference in etching results. J. Preparation without problems of charging. White
patches were caused by reprocessing the sample (repolishing and reetching), but did not
affect the visibility of microincrements.
27
Table 2. Results of the age determination on 17 otoliths from numerical integration of
daily increments using the SEM and from surface readings (SR). FL is the fish length in
cm, Radius is the radius of the ventral axis in mm. Numbers in the first row are strata of
one millimeter each from the focus to the margin of the otolith. Numbers in the strata
columns are average numbers of microincrements per 100 pm, and in the parenthesis is
the number of observations per strata. Additional counts of increments were taken at
the dimension of thickness ("+") when appropriate. Numbers in Average and SD rows
are the pooled average number of increments per 100 p.m per strata, and the
corresponding standard deviation.
Strata
FL
Radius
34.6
3.4
36.8
41.6
49.5
54
57.5
67.8
70.5
73.2
79.9
86.5
90.5
92.5
100
102
111
111.8
Total
Average
SD
1
20
(2)
3.5
20
(2)
3.5
20
(2)
4
20
(2)
4
20
(2)
5.1
20
(2)
5.1
20
(2)
4.8
20
(2)
5
19.66
(2)
5.5
20
(2)
5.5
20
(2)
6
20
(2)
6.5
20
(2)
7+ 0.75 20
(2)
6.3 + 1
20
(2)
7 + 0.3 20
(2)
6 + 1.8 20
(2)
339.7
19.98
0.29
2
3
4
20
54
(5)
45
(4)
56
(5)
53.3
(6)
37.5
(4)
60
(6)
52
(5)
56
(5)
46.6
(3)
48
(5)
42.5
(4)
58
(5)
34
(5)
46
(5)
52
(4)
52
(5)
66
(5)
858.9
50.52
2.88
60
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
17.6
(3)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
20
(2)
337.6
19.86
0.75
(3)
56.6
(3)
67.5
(4)
64
(5)
55
(4)
76
(5)
62
(5)
66
(5)
53.3
(4)
62
(5)
54
(5)
68
(5)
48
(5)
62
(5)
60
(5)
60
(4)
70
(5)
1048
61.67
2.63
5
75
(4)
72
(5)
66.6
(3)
60
(4)
70
(5)
70
(4)
74
(5)
70
(5)
71.6
(6)
70
(4)
70
(5)
76
(5)
845.2
70.43
2.05
6
7
8
75
(2)
70
(2)
73.3
(3)
76.6
(3)
74
(5)
87.5
(4)
76
(5)
78
(4)
78
(5)
80
(5)
768.4
76.84
2.17
95
(4)
93
(3)
90
(4)
90
(4)
104
(5)
442
94.4
2.40
97.5
(4)
97.5
(4)
292
97.5
0.0
Age
SEM
3.2
Age
SR
3.1
2
3.6
3
4.3
5
3.6
4
7.1
5
6.4
6
5.9
6
5.4
6
7.0
7
6.7
8
8.6
9
8.9
10
12.7
13
11.3
12
11.3
11
14.0
15
3
28
T
14
12
10
8
6
I-1
I
0
2
4
6
8
10
12
14
X
Figure 6. Validation test of the age estimates from surface readings based on the age
estimates from microincrement analysis. Y corresponds to the age estimates from
surface readings, X correspond to the age estimates from daily increment readings, the
solid line corresponds to the null hypothesis Y = X.
29
Table 3. Validation test based on linear regression of hyaline surface readings on daily
increment readings. Y corresponds to the ages obtained with surface readings, X
corresponds to the ages obtained with numerical integration of daily increments, b is
the intercept, m is the slope, and ci is the error term.
Parameter
Estimate
b
-0.477
0.478
m
1.081
0.060
SE
Y=X+ei
Ha: Y=mX+b+ei
Ho :
Alternatively
Ho : b =0 and m =1
Ha:b *0 and m*1
Decision rule: If
t* 5
If t*
t(0.95, 15) = 2.131 conclude Ho
> t(0.95, 15) = 2.131 conclude Ha
t*-test for b : -0.477695 / 0.478396 = -0.998536
t*-test for m : 1.08096 1/0.060163 = 1.348967
Therefore: Ho : b = 0 and m = 1 or Ho : Y = X
is concluded.
30
120
100
80
Length (cm) 60
40
20
0
0
2
4
6
8
10
12
14
16
18
Age (years)
Figure 7. Estimated von Bertalanffy growth curves from surface readings of hyaline
zones with the light microscope (solid line) and from daily increment readings with the
scanning electron microscope (dashed line). Both curves were estimated using nonlinear regression. The open circles in the figure correspond to the age estimates
obtained from surface readings of 168 otoliths. The age estimates from daily increment
readings are not shown.
31
Table 4. Analysis of residual sums of squares (ARRS) for the comparison of the growth
curves obtained with the age data from surface readings (n = 168), daily microincrement
readings (n = 17), the pooled data (n = 185).
Method Loo
K
Surface
127.5
0.121
Daily
122.1
Pooled
127.3
0.172
0.124
to
-0.136
0.919
-0.047
R2
0.997
0.993
0.997
df
RSS
2759.893
769.808
3864.243
165
14
182
Ho = There is no difference between the estimated growth curves from the surface
and daily rings methods.
Ha = There is a significant difference between the estimated growth curves from the
surface and daily rings methods.
F* = [ ( RSSp- RSSs) / ( DFp-DFs)] / [ RSSs / DFs]
= [ ( RSSp-RSSs) / 3 (K-1)] / [ RSSs / N - 3K]
where RSS is the residual sums of squares of the pooled data, RSSs is the summed
residual sums of squares from surface and daily methods (RSS(s urface) + RSS( ily)),
DFp and DFs are the degrees of freedom of the pooled and summed estimations, K is
the number of groups in the comparison (K = 2), and N is the total sample size (N =
168 + 17 = 185) (Chen et al. 1992).
F* = [ (3864.243-3529.70) / 3)] / [ 3529.70 / 179] = 5.65
If F* 5 F(.95; 3,170)
If F* > F(.95; 3,179)
= 3.20, conclude H0.
= 3.20, conclude Ha.
(Neter et al 1989).
Therefore: Ha is concluded.
32
Table 5. Comparison of the von Bertalanffy parameter estimates from surface readings
and microincrement readings methods using the w test (Omega test, Gallucci and Quinn
1979). Parameter estimates are presented with the corresponding asymptotic standard
errors (ASE) and variance (VAR).
Correlation matrix
Surface Leo
K
Leo
1.000
K
-0.961
1.000
tO
-0.738
0.880
Daily
K
Leo
Estimates
Surface
Estimate ASE VAR
Leo
127.503
3.364 11.3168
K
0.121
1.000
tO
-0.136
0.008 0.00006
0.183 0.033489
tO
Daily
Estimate
122.091
ASE VAR
0.172
0.919
0.054 0.002916
tQ
Leo
1.000
Lee
K
-0.949 1.000
-0.754 0.899
K
to
1.000
to
12.83
0.64
164.6089
0.4096
= KLee
Var(w) = L002 Var(K) +K2 V ar(1,00)+ 2KLoo corr(k,1,00) jVar(k)Var(1,00)
Omega
Estimate
co-surface
15.3
0o-daily
21.00
Var
0.4081
0.7223
SE = Standard error
UL = confidence interval upper limit
LL = confidence interval lower limit
SE
0.6388
4.552
95% Uj.,
16.68
95% LL
29.92
12.08
14.18
33
The growth of the otolith
The plot of otolith length against fish length suggests a linear relation (Figure
8), OL = 0.269 (FL) + 6.04 (p-value < 0.005). A plot of the residuals shows no
trend.
40T
ma
35
30
25
ih
latt
E
E20
a
*A
011,
,P-
15
10
5 -0
0
20
40
60
80
100
120
Fl (cm)
Figure 8. Otolith length (OL) versus fish length (FL).
Otolith width as measured by Wes, W0.15, and Wo.05, with respect to fish
length (Figure 9A) and with respect to otolith length (Figure 9B) appears linear.
Graphs of the residuals showed an increase in the variance of the residuals with an
increase in fish length and otolith length. A natural logarithmic transformation (see
Table 6) of the otolith width corrects the trend in residuals (Neter et al 1989). The
slopes of the regression of W
on fish length and otolith length were different than the
corresponding slopes of the regressions for W0.15 and W0.05 on fish length and otolith
length (t-tests p-values < 0.05). This suggests that the rate of growth of the otolith is
greater near the focus than closer to the frontal edge of the otolith. The slopes of the
regression of Wa15 and W0.05 on otolith length were the same. The linear regression
explains 90% to 92% of the variation of Wes, 82% to 83% percent of the variation
of W0.15 and
74% to 75% percent of the variation of Wm. In summary, the
34
relationship between otolith length and fish length appears linear but the relationships
between otolith width and fish length and between otolith width and otolith length are
probably non-linear despite the linear looking curves in Figures 9 A, B.
Otolith breadth is more clearly linearly related to fish length and otolith length
than were the width dimensions (Figure 10A, B, Table 6). The linear regression
explains about 94 to 95 percent of the variation in breadth measured at the points AB,
and about 93 to 94 percent of the variation in breadth measured at the points CH (See
Figure 2C, D). The slopes of the regressions of breadth (AB and CH) on fish length and
otolith length are statistically the same ( see Table 6). The difference between the
regression lines was on the intercept only. The residuals of these regressions show no
trend, therefore transformation of the data was not necessary.
The slopes of the log-transformed regressions of otolith width as measured by
Wes, W0.15, and W0.05 on age were the same (see Table 6, Figure 9C). A natural
logarithmic transformation of the width was required to correct increasing variance with
increasing age. The linear regression of width on age explained about 82 percent of the
variation for W and for Wa15, and about 78 percent of the variation of W0.05. There
was no statistical difference between the slopes of the regressions of breadth (AB, CH)
on age (t-test p-value > 0.05) (See Table 6 and figure 10C). This suggests that these
two measurements of otolith breadth are growing at the same rate with respect to age.
The regression of breadth on age explained 87 percent of the variation on AB and 85
percent of the variation on CH.
The ventral width measured at the point A (see Figure 2A, E, F) remains rather
constant but starts to increase rapidly and non-linearly when a fish achieves larger sizes
(Figure 11A), i.e.: fish lengths in the vicinity of 100 cm (Figure 11A), otolith length in
the vicinity of 30 mm (Figure 11B), and fish of about 10 years (Figure 11C). The non-
linear growth that begins around point A for these large fish offers alternative
opportunities for determining ages. Kimura et al. (1979), Boehlert (1985), and Fowler
(1990) all used the thickness of the otolith to take additional counts of hyaline zones on
large fish otoliths. This illustrates that it is possible to read ages using additional
surfaces beyond the cross section for estimating age.
35
...
76-
stays
5-
Wmox
432-
O W0.15
A
W0.05
10
0
40
20
60
80
100
120
Ash length (cm)
9876g 54-
°lams 0
auszi:b. AP.
Ore
32-
R2
0
_
o W0.15
0
Et-.)
0
.1.
lie
Wmox
o 1:1-40
B
W0.05
deile 3004.01)Orfr
'`
cb
1o
0
5
10
2)
15
25
30
35
40
Otollifi length (mm)
987-
'
5-
III
42-
1
1
61
.
111
I I
I
1
I
i
0
Wmox
O
Dgg
ne.iggiP;"
S
1
o
o
e
BB
V
1
:
0
VV0.15
li
C
c
:
%cos
I
s
0
0
2
4
6
8
10
12
14
16
18
Age (Ma)
Figure 9. Otolith width against fish length (A), otolith length (B) and age (C). Note the
slight curvature of the plots. N= 168
Table 6. Summary of the linear regressions. Logarithmic transformation helped
to correct some of the problems with non
random error distributions. In case of the dimension A, the logaritmic transformation slightly
improved the fit.
Wmax
Fish length
Otolith
length
Age
R2
LN(W) = 3.869 x10-3 (FL) + 0.49
89.1
LN(W) = 0.0143(OL) + 0.41 91.3
LN(W) = 0.0213 (Age) +0.61
81.6
LN(14715)= 3.529x10-3 (FL) + 0.32
82.0
LN(14/15) = 0.0129(OL) + 0.25
82.9
LN(W5) = 0.0203(Age) + 0.42
81.9
AB
Fish length
Otolith
length
Age
R2
W15
R2
R2
W5
LN(W5)= 3.527x 10-3(FL) + 0.17
74.3
LN(W5) = 0.0129(OL) + 0.10
75.5
LN(W5) = 0.0207(Age) + 0.27
77.7
CH
R2
AB = 0.105(FL) +1.76
93.8
CH = 0.104(FL) + 2.96
92.6
AB = 0.385 (OL)
0.44
94.7
CH = 0.383(OL) + 0.73
94.3
AB = 0.582(Age) + 5.11
87.0
CH = 0.575(Age) + 6.29
85.3
37
16
14
12
t 10
g
AB
18
O
6
ii
A
CH
4
2
0
0
20
40
80
do
103
120
Ash length (cm)
0
8-
AB
a 64-
O CH
i
B
20
5
O
10
20
15
25
30
35
40
OW lith length Om*
16-
0
14 -
a
:
2-
tl
fro
10 -
8-
I
a4-
i1
2
i
0
C
8
B
.
AB
1
O CH
C
gi
20
i
O
2
4
6
8
10
12
14
16
18
Age (years)
Figure 10. Otolith breadth against fish length (A), otolith length (B), and age (C). N=
168.
38
4,5
4
13.5
2.5
12
A
1.5
0,5
isus Air
ay.
sr **vete
0
43
0
60
80
100
120
Rsh length (cm)
4.5
4
13.5
3
2.5
1
2b 1.5
t
"8
10.5
B
.:
l
, el %diter ,41404014.
0
0
5
10
15
20
25
30
35
40
Otoltlh length (nen)
4.5 -
4-
13.5
3
2.5
C
2
1.5
1
->6
0.5
1
1
1
1
1
0
0
2
4
6
1
1
8
10
12
14
16
18
Age (yews)
Figure 11. Increment in thickness of the ventral edge ( at point A, see figure 2A).
Allometric growth is evident at the ventral edge. The ventral edge
growth increases
rapidly at about 100 cm of fish length (A), 30 mm of otolith
length (B), and 10 years
old for age (C). N= 168.
39
Another approach to the estimation of ages
uses the presence of these
additional surfaces on the uncut otolith. Measurements are taken on the axes of growth
of the otolith leading to an estimate of age with the use of a multivariate model
(Boehlert 1985). Stepwise forward regressions of age versus all the measurements
taken from the otolith indicated that the width at the ventral edge and at W5, fish
length, and otolith length are predictors of age (Table 7). When fish length and otolith
length are together in the set of all variables for the regression, the model selects fish
length and width at the ventral edge (A), and the multivariate model becomes Age = 130
+ 131FL +132A (full model R-squared = 0.94), where FL is fish length and A is the width
at the ventral edge. Extra sum of square analysis (Neter et al. 1989) of the reduced
model against the full model showed that A is important in the model (F-test, p-value <
0.01). The mean error for the predicted ages from this model is -1.06 years with a range
of -3.68 to 0.75 years. When otolith length is substituted for fish length in the set of
variables, the model becomes Age = 130 +
OL + 131 A + 132 W5 (Full model Rsquared = 0.92), where OL is otolith length, A is the ventral width, and W5 is the width
closest to the frontal margin of the otolith. Extra sums of square test of the reduced
models Age =130 + 131 OL + pt A, Age = 130 + p, OL + I32W5, and Age = 130 + OL
against the full model showed that the terms A and W5 are important predictors of age
(F-tests, p-values < 0.05). The mean error for the predicted ages from this model is
0.0045 years with a range of -3.04 to 2.388 years. In summary, the two multivariate
models presented above are good predictors of age and the thickness at the ventral
edge is in both models. The first requires fish length and the thickness at the ventral
edge (measurement of width at point "A"), while the second requires otolith length, the
thickness at the ventral edge, and W5. This second model illustrates the importance of
otolith length as a predictor of age.
The growth of the otolith was also modeled with the von Bertalanffy growth
equation. Figure 12 shows that otolith length appears to reach an asymptote. This
further illustrates the role of the otolith as a source of age information as was
demonstrated by one of the multivariate models for the prediction of age that includes
otolith length as the first predictor variable. The von Bertalanffy parameters estimates
for the growth of the otolith appear in Table 8.
40
Table 7. Extra sums of squares F-test for the significance of terms for two multivariate
models for prediction of age (Full models) obtained with stepwise forward regression.
The age data was obtained from surface readings of hyaline zones. FL is fish length, OL
is otolith length, "A" is the width at the ventral edge, and W5 is the width closest to the
frontal margin of the otolith.
A.
Full model
: Age = 130 + 131FL + 02 A
Reduced model : Age =
Model
Full
Reduced
v-excluded
none
A
+
FL
SSE
df
F-test
p-value
107.603
165
1322.03
<0.0001
197.545
166
137.91
< 0.01
Final model : Age = -3.569 + 0.123 (FL) + 1.908 (A) (R-squared = 0.94)
B.
Full model :
:
Age = 130 +1310L + 02 A +133 W5
Reduced model 1 : Age = 130 + 131 OL
2: Age = 130 +
133W
3 : Age = 130 +131 OL +
Model
v-excluded
SSE
Full
None
142.837
Reduced 1 A, W5
229.957
Reduced 2 A
178.690
df
F-test
p-value
164
646.441
< 0.0001
166
50.01
< 0.0001
165
Reduced 3 W5
< 0.0001
165
41.165
4.016
146.335
< 0.025
Final model : Age = -6.147 + 0.457 (OL) + 1.561 (A) + 0.609 (W5)
(R-squared = 0.92)
41
40
35
30
25
01. (mm) 20
15
10
5
0
2
4
6
8
10
12
14
16
18
20
Age (years)
Figure 12. Estimated von Bertalanffy curve for otolith length (OL). Open circles
correspond to the observed otolith sizes.
Table 8. Von Berta lanffy growth parameters for otolith length. Asymptotic standard
errors (A.S.E.) and 95% confidence intervals for the estimates are provided.
Parameter Estimate
01..p.
k
tO
A.S.E.
Upper
Lower
R-squared
39.891 mm
0.549
40.967
0.998
0.126
-1.276
0.005
0.146
38.816
0.116
-1.567
0.137
-0.989
42
Discussion
Surface readings and the analysis of the microstructure of the otolith of
Cynoscion albus provided consistent direct estimates of age. The confidence intervals
around the growth parameters Loo and K from surface readings are based on 168
samples distributed over the 115 cm plus size and are suitably narrow (Leo from 120.86
cm to 134.14 cm, K from 0.10 to 0.13). The intervals around Lee and K from daily
increments are based on only 17 samples and are much less narrow (Leo from 94.57 cm
to 149.61 cm, K from 0.06 to 0.29), but consistent with those from surface readings.
The point estimates of the Lee's differ by 5 cm and those of K differ by 0.05 year 1.
Despite of the consistency in the parameter estimates from both growth curves, the Ftest rejected the hypothesis of their being statistically the same, apparently due to the
differences in sample sizes. On the other hand, the omega test, which statistically
compares the parameter estimates, did not reject the hypothesis of similarity. Therefore,
the validation method has actually provided a large enough sample so that a second
curve could be constructed and compared to the primary age determination, with good
results.
My estimates of the von Bertalanffy growth parameters based on the age
estimates of C. albus from otolith readings differ markedly from previous estimates
made from length frequency analysis. Stevenson (1981) used a transformation of the
von Bertalanffy growth equation and 1976/1977 data to estimate the annual growth of
C. albus from the Gulf of Nicoya based on modal length progression. He assumed that
Leo was 120 cm, the maximum observed length, and reported that K ranged from 0.40
to 0.55. Madrigal-Abarca (1985) used ELEFAN I to analyze data collected from the
Gulf of Nicoya in 1979 and 1980. He presented estimates of Leo = 135.0 cm and 125.0
cm, and K = 0.43 and 0.40, respectively for the 2 years. He estimated a life span of 7
to 7.5 years. My K-values from otolith surface readings and microincrement analysis
are only 30% and 42%, respectively, of the smallest K reported by Madrigal-Abarca.
This results indicates a much slower growing fish and thus a much older fish for the
same length, in other words, Cynoscion albus is a fish more vulnerable to overexploitation than previously estimated. In particular, the oldest fish in this project was
estimated to be 18 years old at 108.0 cm.
Length-based methods are a popular way to describe the growth of tropical
fish because of the difficulties of ageing these species, but they do not perform well for
43
long-lived or slow-growing species, or for species with multiple or prolonged spawning
(Casselman, 1987). Isaac (1990) compared growth parameters for 27 sciaenid species
using El .EFAN I and II, Shepherd's Length Composition Analysis (SLCA), and the
Powell-Wetherall method (P-W). She concluded that FT .EFAN tends to overestimate
Lee with a higher bias than the estimates of SLCA and P-W, and thus produces smaller
estimates of K. Kimura (1980) suggested that maximum likelihood estimation provides
one of the best estimates of the von Bertalanffy parameters and that, in practice, these
estimates correspond to those obtained by non-linear estimation. Non-linear estimation
was used for C. albus to estimate the growth parameters from both the otolith surface
readings and the microincrement analysis. The similarity of these Lee estimates to those
in Stevenson(1981), and Madrigal-Abarca (1985) suggests that ELF.FAN I was not
overly biased in the estimation of Lee, but that the estimates of K are likely to be
biased, when compared directly to estimates from age data. This does not contradict
the conclusion of Isaac (1990), who was comparing estimates from different lengthbased methods.
High values of K have been reported for the genus Cynoscion but usually in
smaller species (Stevenson 1981, Maceina et al. 1987, Lai and Campos 1989). Age
determination studies on larger sciaenids can provide lower values of K. For example,
Beckman et al. (1990) reported a range of K of 0.04 to 0.05 for Pogonias cromis,
which reaches a maximum size of 110 cm, and compared it with the value of K of 0.21
the previously reported value based on tagged fish less than 80 cm.
Lai and Campos (1989) used surface readings of whole otoliths to age
Cynoscion stolzmanni (corvina coliamarilla) and Cynoscion squamipinnis (corvina
aguada). These two species are also caught in the Gulf of Nicoya along with C. albus
and other sciaenids. Corvina coliamarilla is second in size to C. albus, reaching sizes
close to 100 cm, while corvina aguada is a medium size sciaenid, reaching sizes around
55 cm. Lai and Campos presented higher K values for these two species of Cynoscion
than the one that I obtained for C. albus from otolith readings, and reported shorter life
spans. They reported for C stolzmanni an Lee of 96.7 (SD = 7.3), K = 0.318 (SD =
0.146), to = -0.946 (SD = 0.935), and a life span of about 9 years. For C. squamipinnis
they reported and Lee = 55.7 (SD = 0.9), a K = 0.370 (SD = 0.026), to = -0.797 (SD =
0.106), and a life span of about 7 years. Lai and Campos (1989) used length frequency
modal analysis to validate the age estimates and found no statistical difference between
otolith and length frequency methods. This illustrates that length frequency analysis can
work for species with shorter life spans. In contrast, I found that C. albus reaches at
least 18 years of age and presents an increasing number of age classes with increasing
44
size class, this is a typical case where length-based methods are not adequate to study
the growth of fish (Casselman 1987). In the present study, I used age estimates from
daily increment readings to validate the age estimates from hyaline surface readings and
found no statistical difference between the results.
The results of the SEM analysis provided evidence to suggest that the hyaline
zones laid down in the sagittae of Cynoscion albus correspond to annual periods of
time, but the validity of these age estimates is strongly dependent on the assumption
that the microincrements observed on the sagitta of corvina reina correspond to daily
periods of crystalline deposition. Recent physiological studies on the growth of the
otolith suggests that microincrement formation is an obligatory process in otoliths and
that it is tied to endogenous diel physiological and seasonal cycles (Gauldie and Nelson,
1988, Gauldie and Radtke, 1990). This result provides a foundation for the assumption
of a daily deposition in the otolith of C. albus and supports the use of the otolith for age
determination purposes.
The occurrence of daily increment deposition has been reported in a variety of
studies (e.g. Campana and Neilson, 1985) and provides additional support to the
assumption that daily microincrementation is a generalized process in fish, as was
suggested by Panne lla (1971, 1974) for both temperate and tropical fish. Although
much of the research in this area has been devoted to the study of the environmental
causes of daily increments such as temperature, photoperiod, feeding frequency and
salinity, many studies provide validation for daily increment formation ( e.g. Taubert
and Coble 1977, Mai llet and Check ley 1990, Mollony and Choat 1990, Wright et al
1990, Umezawa and Tsukamoto 1991, /hang and Runhan 1992). Many of these
studies demonstrate daily microincrements for larvae and juvenile fish but the work of
Ralston (1976, 1985), Ralston and Miyamoto(1981, 1983), Ralston and Williams
(1988), Mora les-Nin and Ralston (1990) have demonstrated the occurrence of daily
rings in adult fish as well. Also, the occurrence of annual growth mark formation
appears to be common in sciaenids in both temperate and tropical waters. For
example, annual growth marks have been validated for Sciaenops ocellatus (Beckman
et al 1989, Murphy and Taylor 1991, Prentice and Dean 1991), Cynoscion nebulosus
(Maceina et al 1987), Cynoscion nothus (DeVries and Chittenden 1982), Cynoscion
stolzmanni and Cynoscion phoxocephallus (Lai and Campos 1989), Pogonias cromis
(Beckman et al 1990), and Micropogonias undulatus (Barger 1985). Evidence of daily
deposition on the scales of juveniles of Cynoscion regalis have also been recently
reported (Szedlmayer et al. 1991).
45
Conversely, evidence from the macro and microstructure of otoliths has been
reported against the use of otoliths for age determination. Gauldie (1988) argued that
the microincrement formation process and the resulting shape of the otolith are more
related to the hearing function of the sagitta than to time. Gauldie (1990) critiqued the
traditional check-mark reading methods of age determination and proposed that the
linear relation between otolith length and fish length and the allometric relationship
between fish length and weight, constitute evidence against a time keeping property of
the otoliths. He argues that check rings are deposited in the otolith in response to
weight-related changes of the body, like skeletal reconstruction. Gauldie and Nelson
(1990) proposes that the contact of the ventral edge over the otic cleft creates a
restriction on the growth of the otolith and that for ageing purposes counts of
microincrements taken in this area will be misleading.
It is not clear precisely why it is suggested that a linear relationship between
otolith length and fish length precludes the use of the otolith for age determination.
Rather, such a relationship present opportunities for easy prediction of one or the other.
The results on Cynoscion albus also suggest linear relationship between otolith length
and fish length, as well as linear relations of otolith breadth with fish length, and otolith
breadth with otolith length. The relationship of otolith width with fish length and otolith
width with otolith length probably is not linear. The relationships between otolith
length, otolith width, and otolith breadth are also suggestive of shortcuts that involve
neither surface or microincrement preparations and readings. Combined
with the growth
curve of otolith length versus age being asymptotic it is likely that multivariate models
may be used for the prediction of age. In fact such models for C. albus
account for
more than 90% of the observed variation. These multivariate models can be valuable
alternatives for age determination when trained readers or laboratory equipment for age
determination are not available. It is possible that age-otolith keys may be more precise
and cost-effective than age-fish length keys and may offer special
opportunities for
tropical fishery management.
In summary, this study provides the first direct age determination for Cynoscion
albus. It demonstrates the use of otoliths for age determination of large tropical
sciaenids using both hyaline surface readings and daily increment analysis. It presents
age estimates leading to consistent estimates of von Bertalanffy growth parameters. It
also provides two multivariate linear regression models to estimate age from coarse
measurements taken from the otolith as an alternative to the time consuming
microscope-based measurements.
46
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