STOCK ANALYSIS OF MURREL

DISSERTATION submitted in partial fulfilment of the requirements

for the award of the degree of

iHas^ter of ^^ilogopljp IN

ZOOLOGY

BY

RANA SAMAD

FISH NUTRIT ION RESEARCH LABORATORY DEPARTMENT OF ZOOLOGY

ALIGARH MUSLIM UNIVERSITY ALIGARH (INDIA)

1994

DS2500

*'^SUlii\>\4^^'^'\'^

2 3 FEB 19^^

^006-a~z^z[K6

M.Sc. Ph.D.. F.N.A.Sc. Professor

CERTIFICATE

This is to certify that the dissertation

entitled "Stock Analysis of Murrel" has been

completed under my supervision by Ms Rana Samad.

This work is original and has been independently

persued by the candidate.

I permit the candidate to submit the dissertation

in partial fulfilment for the award of the

degree of Master of Philosophy in Zoology of

the Aligarh Muslim University, Aligarh.

A.K. Jafri

Fisheries Laboratory, Department of Zoology, Aligarh Muslim Universit\, _^AIlgirh 202001. Indu) Te! lOllicei 91-571-25b4b, tResi 91-571- ^ 0 1 0 6 ' '

ACKNOWLEDGEMENT

I wish to thank my supervisor, Prof. A.K. Jafri/

who most kindly and affectionately provided me an

excellent guidance throughout the tenure of my work.

He has been a great source of personal and professional

inspiration.

I offer my sincere thanks to the Chairmai,

Department of Zoology, for providing necessary

laboratory facilities.

Thanks are also due to Dr. Saleem Mustafa for

his valuable suggestions and constructive criticism.

I would like to thank my teacher Dr. Mukhtar A. Khan

for his kind help. I am grateful to Dr. Jamal A. Khan

and Dr. Afifullah Khan for helping me in data analysis.

Gracious cooperation of my laboratory

colleagues. Dr. Shabana Firdaus, Dr. Abul Hassan,

Mr. Farooq Anwar, Mr. Erfanullah, Ms. Aafrin Alvi and

Ms. Nazura Usmani, is thankfully acknowledged.

My heartfelt thanks are also due to my brother,

Mr. Salim •Javed, for his continuous inspiration and

generosity.

I am extremely thankful to all my seniors and

friends especially Dr. Jamal Ahmad, Mr. Niamat Ali,

Ms. Sadia Arjumand, and Ms. Sughra Arshad for selfless

help and encouragement. I thank Mr. Naseeruddin for

helping me throughout the work.

Mr. Kafeel A. Khan deserves thank for neat and

clean typing.

Financial assistance rendered by University

Grants Commission is also acknowledged.

(RANA SAMAD)

CONTENTS

PART I

General Introduction 1-11

PART II

Chapter - i Intraspecific stock evaluation of the 12-25

common freshwater pond murrel/ Channa

punctatus [Bloch] - A preliminary-

study.

PART III

Bibliography 26-38

GENERAL INTRODUCTION

Among the vertebrates/ fishes are the richest

group comprising over 20/000 living representatives

(Nikolsky, 1976). Together with such a great

diversity of structure and mode of life, determined

by a variety of conditions under which fishes live,

they possess a number of common features. Often,

in a group of fish/ these features are so similar

that they are taken as one species. However, no two

fish are exactly similar, even if they belong to

the same species. Genetic or phenetic homogeneity

over the entire distribution of the species is

rarely observed due to heterogeneity and disconti­

nuity of the environment.

The increasing demand for quality protein

has diverted the attention of fishery scientists

to improve the quality of fish stocks, both for

culture as well as capture purposes. This has alsc

generated much interest in discrimination of fisr

stocks. The Stock Concept International Symposia

held in Ontario, Canada/ in 1961 emphasized the neec

to develop a refined upto-date stock concept based on

ecological and genetic principles, examine the

prospects and strategies for preservation of gene

pools, explore the potential for the use of stock

concept in rehabilitation of freshwater resources,

and finally to develop the use of this concept in

fisheries.

Intraspecific groups of fishes have variously

been described as race, tribe, population, subpopula-

tion, stock and subspecies, to reflect the

magnitude of differences among such subdivisions.

Several definitions of each of these terms have been

proposed by fishery scientists at different times.

The term stock has vaguely been used in many ways

to delimit groups of fish from systematic to applied

management units. Darwin applied this term to races

that descended from a single wild stock, while in

the 20th century the word referred to a related

group of organismis. The term was thus used to define

what presently is called a species, which m,ay be

a race, a population or a subpopulation. The species

m.ay be phenot ypi cally differentiated or else genoty-

pically different but do not show variation as a

result of phenotypic plasticity. Svedang (1990)/

while studying the population of Arctic charr,

observed that genetic basis of life history

variation in a sympatric population of this fish

show no genetical background to the variation in

life history traits between sympatric dwarf and

normal fish/ but differences in size and age at

maturity could be explained in terms of phenotypic

plasticity.

For any applied study on fish, it is

important to know the nature of their stock. It is

known that response of fish to feeds, habitat

mitigation, and protein assimilation is strongly

influenced by nature of its stock (Skereslet 1973;

Johnson 1983; Sparholt 1985; and Longholz 1990).

Ihssen et al. (1981) studied ecological,

morphological and electrophoretic variations among

five allopatric stocks of lake whitefish (Coregonus

clupeaformis) and observed that these differed in.

terms of growth rate, movement patterns, fecundity,

eoa and larval size.

Identification of stocks of fish has lone

been the province of morphologi st s. Morphom.et ric,

ireristic, calcareous, biochemical and cytogenetic

characters were miostly used to identify fish stocks.

(Svardson 1952; McCart and Pepper 1971; Sharp _et_ al .

1978; Gold 1979; Todd and Smith 1980; Ihssen _et _aJ_.

1981; casselman _et. _al. 1981; Todd et_ ed. 1981; Howell

and Black 1981;and Tsvetnenko 1991). Although

morphometric characters are influenced by environ­

mental differences/ they can be as valuable in

indicating stock discreteness as other more

genetically related features. Casselman et al.

(1981) studied eleven morphometric and seven

meristic characters of the stocks of lake whitefish

(Coregonus clupeaformi s) and using multivariate

analysis of these characters/ observed that meristic

variables contributed minimally while morphometric

variables contributed maximally. Todd et al. (1981)

studied morphological differences between parents

and offspring of ciscoes and noted that hatcherv

fish differed from the parents more than the parens

species differed from one another. These

morphological differences were probably due to the

effects of different temperatures and other stresses

on developing embryo. Coregonines and salmonids,

in generals have long been known to develop varied

phenotypes in response to environment (Koelz, 1929;

Hile, 1937; Martin, 1949; Svardson, 1952; Frost,

1965; and Loch, 1974). Corti _et al^. (1988) performed

multivariate analysis of morphometric characters

to investigate the distinctness and interrelationships

of six stocks of the common carp. Creech (1992)

studied morphometric variation between populations

of male and female Atherina boyeri and A. presbyter,

using Multiple Group Principal Component Analysis.

His results indicated a large amount of

morphological variation between females of the two

species while males were differentiated as a result

of differences in body shape. Li sifa (1990) studied

the population of silver carp, bighead and grass

carp and found obvious intraspecific divergence in

morphometric characters among the population of

these fishes.

Ihssen _e_t al. (1981) reviewed the various-

methodologies used for stock identification.

Calcified structures like scales and otoliths have

been used for many years to identify and

discriminate specimens from specific areas,

subpopulation, races or stocks of both marine and

freshwater fishes. The scale method of stcck

identification and assessment. was used to manace

i!T,portant fisheries units (Henry, 1961). Scale

sizes, measured within and between the zones, were

often utilized to determine both the origin and

identification of fish stocks (Rowland 1969; and

Martin, 1978). The characteristic configurations

of the circuli in and about annuli were used to

separate local stocks of northern pike, Esox lucius

(Casselman, 1967). Although otoliths have been used

for routine studies of age and growth, some charac­

teristics of otolith appeared stock specific.

Messieh (1972) identified the stocks of Atlantic

herring (Clupea harengus) on the basis of

qualitative shape analysis of their otoliths.

Otolith shape analysis, using planar shape quanti­

fication, was also used to discriminate whitefish

(Coregonus clupeaformis) stocks from Lake Hurcn

(Casselman et al., 1981). Other bony structures

examined to differentiate subspecific groups of fish

included cranium osteology. Gasowka (1970) used

cranial osteology to examine several form,s ct

whitefish (Coregonus lavaretus) and concluded triet

dentary shape could be a good diagnostic feature.

Electrophoretic data on stock discrimination

has led to a new era in understanding the genetic

structure of a broad range of organism, s, including

many species of fishes. Electrophoretic data are

useful for genetically characterizing individual

stocks based on allelic and genotypic frequencies.

Several workers have used electrophoretic method

in studying biochemical variations among allopatric

and sympatric whitefish population (Lindsey et al.,

1970; Frazin and Clayton 1977: and Imhnoff _et al.;

1980).

Intraspecific chromosomal variation is

considered useful for fish stock identification.

Intraspecifie chromosomal number variation have been

studied by Gold _et. aj.. ( 1977) , Barsiene (1976), Black

ana Howell (1978)/ Le Grande and Cavender (1980). Gold

(1979) observed that, besides species specificity

of chromosome karyotypes, intraindividual and intra-

specific variations of chromosome, m morphology

and number, could also be seen. Intraspecific

chromosomal variation can thus be a useful tool for

fish stock recognition. Ohno et al. (1965) have

demonstrated that rainbow trout can have intra­

individual variation in chromosome number distinct

from intraspecific variation. Similar study was made

on green sunfish, Lepomi s cyanellus (Becak, et al.,

196t ) .

Morphological diversity in ecology, genetics

and behaviour is well known in fishes (Koelz, 1929;

Friendenfelt, 1933; Nikolsky and Reshtnikov, 1970;

Behnke, 1972; Clark, 1973; Ferguson, 1974; White,

1974; Ferguson et_ a_l., 1978; Rufli, 1978; Svardson,

1979; Todd and Smith, 1980; and Todd et_ al., 1981).

These differences may be a reflection of

environmental differences while genetic differences

may not always be reflected morphologically.

According to Sokal and Rinkels (1963) geographic

variation is not likely to be due to adaptation of

few characters to a single environmental variable

but is a multidimensional process, involving

adaptational characters to a variety of

interdependent environmental factors. The geographic

location, therefore, appears to be the source of

selective pressure that results in local genotypic

and phenotypic adaptations. Environmental conditions

at each locality may also affect the development

of phenotypes. In fish population, genetic sources

of phenotypic variation are generally deemea less

important than environmental sources. Several

workers compared morphological distinctness o:

ciscoes from different localities with observeo

g e n e t i c d i f f e r e n c e s and s u g g e s t e d t h a t t h e c i s c o e e

of l a k e s u p e r i o r d i s p l a y e d more p h e n o t y p i c r e s p o n s e s

t o l o c a l e n v i r o n m e n t s t h a n i n n a t e g e n e t i c

d i f f e r e n c e s / i n d i c a t i n g t h a t bo th e n v i r o n m e n t a l and

g e n e t i c f a c t o r s a r e r e s p o n s i b l e f o r d i f f e r e n c e s

among t h e s t o c k s / w i t h p h e n o t y p i c d i f f e r e n c e s being

more r a p i d w h i l e a c c u m u l a t i o n of g e n e t i c d i f f e r e n c e s ^

a s l o w e r p r o c e s s ( H i l e / 1937; S v a r d s o n , 1950; C l a r k e ,

1973; Loch , 1974; and Todd _et_ _al.., 1 9 8 1 ) . Geograph ic

v a r i a t i o n in s p e c i e s c h a r a c t e r i s t i c s i s a f u n c t i o n

of g e n e t i c v a r i a b i l i t y of i n d i v i d u a l s compr i s ing

l o c a l p o p u l a t i o n and of e n v i r o n m e n t a l d i f f e r e n c e ?

t h e y e x p e r i e n c e in t i m e and s p a c e .

S e v e r a l a p p r o a c h e s were made i n t h e p a s t t c

a n a l y s e m o r p h o l o g i c a l c h a r a c t e r s fo r s t c c k

d i s c r i m i n a t i o n . A number of w o r k e r s have used

r a t i o s f o r t h e s e p a r a t i o n of s t o c k s ( B a y l e s s / 1972;

W i l l i a m s , 1976 ; Kerby, 1980; S h a k l e e and Tarraru,

1981; J o h n s o n _eit a j . . , 1983; Harrell, 1984; and H a r r e l i

and Dean, 1 9 8 8 ) . In f i s h m o r p h o m e t r i e s , s i z e i s a

component wh ich can p e r t u r b an a s s e s s m e n t of g e n e r a l

r a t i a l d i f f e r e n t i a t i o n ( T h o r p e , 1 9 8 3 ) . Severa l

netncds h a v e been a p p l i e d t o overcome t h e p r c b l e r .

10

The use of ratio to adjust for size variation has

also been questioned for many statistical reasons

(Atchley et_ aj^., 1976; Humpries e_t aj^., 1981; and

Thorpe, 1983). Regressions have been used bat their

validity appear questionable when within the group

slopes are not equal (Humpries et al., 1981).

For the computation of morphological data/

another technique recently employed is the

multivariate analysis. This has been preferred over

univariate and bivariate analyses. Gould and Johns-on

(1972) have also emphasized the use of multivariate

approach for morphological variation. Multivariate

analysis was employed by several workers to make

the discrimination using principal com.ponent

analysis (PCA). PCA computes a set of uncorrelated

composite variable called principal components frcrr

a variance covariance or correlation matrix. PCA on

variance covariance matrix is reported to cause

environmental factors of high variability to be

highly loaded with these factors tending to doir.inate

the analysis (Causton, 1988). In the present study

multivariate analysis was employed, and PCA was

based on correlation matrix instead of varianc-e

ccvariance rr.atrix, as it preserves allometric

11

relationship among the characters and when all

characters are measured on equal basis in both ways/

PCA/ carried out on correlation matrix/ manifests,

the true loadings.

INTRASPECIFIC STOCK EVALUATION OF TBE COMMON

FRESHWATER POND MURRKL/ CHANNA PUNCTATUS [BLOCH] -

A PRELIMINARY STUDY

INTRODUCTION

Stock evaluation of fish and the application

of these data to conserving and managing the species

is well recognized. Fish stocks are generally discri­

minated using morphometric/ meristic, biochemical

and cytogenetic characters. In the past, large data

set have been generated on the identification of

fish stocks based on morphometric and meristic

characteristics (Sharp et al./ 1978; Casselman

et al. / 1981; Ihssen et_ al. / 1981; Winans, 1985;

Harrell and Dean, 1988; Muoneke et_ al., 1991; and

Creech, 1992). Li Sifa (1990) observed intraspecific

divergence in morphometric characters among

populations of silver carp, bighead and grass carp,

and stated that such differences are directly

proportional to the geographic distance between each

population. Morphometric variability among the

species and stocks of ciscoes of the Great Lake was

studied by Todd et_ a_l. (1981), who noted that

variability among stocks of the same species were

often greater than between different species.

13

In the recent past/ more interest has been

generated in the use of molecular characters for

stock identification, mainly because of their direct

and simple genetic basis. Morphological studies,

using newer concepts and techniques of analysis,

however, continue to be carried out for

identification of stocks of fish. Lowentin (1984)

has stated that morphological differences are clear

and statistically significant while differences in

gene frequency are less powerful in discriminating

population and species. It is presumed that a better

understanding of variability in morphological

characters could result when these variations are

viewed in the light of their relationship with other

molecular character set.

The present work reports the results of

intraspecific stock evaluation in the common

freshwater pond murrel, Channa punctatus, using a

pool of morphometric and meristic characteristics,

and employing, multivariate method, Principal

Component Analysis (PCA), as a diagnostic tool.

14

MATERIALS AND METHODS

Samples of Channa punctatus were collected from

two ecologically distinct regions of the country/ narrely

Aligarh (Lat 27.30 N' 79.40 E) in the north and

Vishakhapatnam (Lat 17.42 N' 83.30 E) in the south. Over

two fifty specimens were examined. These were preserved

in 10% formal saline solution for detailed observations

on their morphometric and meristic characteristics. Fish

showing excessive curvature were discarded. Body weight

of individual fish was taken on a sensitive top can

electric balance (Varbal, India). Measurements tor

morphometric and meristic parameters were made with

manual caliper. Morphometric and meristic parameters

chosen for the study were :

Total Length (TL) Distance between the anterior most

part of the snout and the tip of the caudal fin.

Standard Length (SL) Distance in a straightline between

the anterior most part of the snout or the upper lip

which makes the anterior most extremity of the body and

the base of the caudal fin/ where the median finrays

meet the hypura plate.

15

Predorsal Length (PDL) Distance before the dorsal

fin up to the tip of anterior rest part of the

snout.

Head Length (HL) Distance in a straightline between

the anterior most part of the snout or the upper nc,

whichever extends the farthest forward and the

posterior most edge of operculum bone.

Caudal Fin Length (CFL) Length of the caudal fin

from base to tip.

Depth through Dorsal Fin (DDF) Distance between the

dorsal and ventral surface at the deepest point.

Orbit Diameter (OD) Diameter o •: eye orbit.

Scale Counts : Formula expressing the number of

scales along the lateral line and the transverse

row. The lateral line scale count (LLS) denote the

maximum number of scales in the lateral line.

Scales above the Lateral Line (SAL) Scales falling

along the line starting from the origin of the

dorsal fin and extending downward and backward to

16

rreet the lateral line.

Scales below the Lateral Line (SBL) Scales falling

along the line that starts from the origin of the

anal fin and running upward and forward to reach

the lateral line. Any scale encroaching both above

and below the line was counted among the scales from

below the lateral line.

Scale before the Dorsal Fin (SBD) Scales present

in a row before the dorsal fin.

Gill raker count (NGR) Number of gill rakers present

on the first gill arch.

Fin ray count : Number of fin rays on each fin, viz.

dorsal (DFR), ventral (VFR), pelvic (P FR), pectoral

(P FR) and caudal (CFR).

The data on morphological characteristics

were computed for multivariate analysis.

Statistically/ the two sets of parameters were

transformed differently. The data collected were

subjected to Principal Component Analysis (PCA),

an ordination technique, expressing the percentage

of variation for each component. In this analysis,

17

the first component (PCl) expressed the highest

variation in the data set. The next largest

variation was explained by the second component

(PC2). Each component thus accounted for the

decreasing amount of total variation. The first few

significant components containing a high proportion

of total information were termed as principal

component. The variance of each component/ referred

to as eigenvalue or characteristic root/ is a

measure of variability explained by a particular

component. The sum of eigenvalues by particular

component, and the set of eigenvalues together

constitute the main result of PCA.

RESULTS AND DISCUSSION

Morphometric and meristic data on C.

punctatus/ collected from southern and northern

regions of the country, subjected to PCA, indicated

that intragroup differences (variance) were more

pronounced in samples from northern region. Two

important eigenvector for morphometric and meristic

characteristics of samples from the above regions

have been given in Table 1-2 and Fig. 1-2. similarly

component loading of the morphometric and meristic

parameters of the two regions have been plotted

in Fig. 3. It was observed that morphometric

parameters in samples from the northern region were

more scattered in all the graphic components,

indicating greater variations within the group.

In contrast, morphometric parameters in samples

from the southern region were more aggregated,

showing less intragroup variations. Similar pattern

was noted for the meristic characters. Regional

samples mostly differed in the range of size as

apparent from the eigenvalues in Table 3-

Creech (1992), while studying the morpho­

metric variations between the populations of

19

Athernia boyeri and A. presbyter/ using Multiple

Group Principal Component Analysis/ recorded a high

percentage of total variance as explained by PCI,

89% for females and 90% for males/ reflecting

towards existence of large difference in the range

of size. Sharp et al. (1978) performed Multivariate

Analysis on nine morphometric and eleven meristic

characters of the capelin/ Mallotus villosus/ and

observed that four of the nine morphometric

characters provided strong statistical separation

between areas. Their findings suggest that meristic

characters offer little potential for stock

identification. In the present study on C_.

punctatus/ however, significant differences

occurred in meristic characters indicating that

these can also be used in stock discrimination of

the fish.

Gardner et al. (1988) performed PCA on

eleven morphometric characters of Arctic charr,

Salvelinus alpinus/ and noted that PCl/ a general

size vector with the same sign and magnitude/

accounted for 79.6% of the total variance/ while

PC2 accounted for 63.7% of the remaining variance.

20

Analysis of the morphcnnet ri c data in

satrples of C. punctatus from northern region

accounted for 52% variance on PCI/ a general size

vector, while PC2/ standard length, accounted for

28% of the remaining variance. In fish samples of

southern region, 89% of the total variance was

observed on PCI, indicating that size was more

variable in sample from this region (Table 3). Similarly,

meristic parameters in northern samples of this

fish accounted for 62% of the total variance on

PCI, lateral line scale count. The second highest

variation was observed in PC2, scales above the

lateral line, accounting for 9% of the total

variance. Variations in other component were not

significant. 42% of the total variance was observed

on PCI followed by 19% in PC2 in southern sample.

These observations indicate that lateral line scale

counts were more variable in fish from northern

than southern environment, while scale count above

the lateral line was more variable in the latter

(19%) than in the former (9%) group of fish samples

(Table 4).

For the interpretation of the results,

component loadings of PCA has also been considered.

21

Among morphometric characters (Table 5)/ high

loading on total (0.938) and standard length

(0.932) shows that these parameters contribute to

the maximum variation on PCI. The second highest

variation was observed for orbit diameter (0.925)

on PC2. It is thus inferred that total and standard

length and orbit diameter are important discrimina­

ting characters for C. punctatus. Other variables

like caudal fin length/ depth through dorsal

fin and body weight were found insignificant.

Component loading on morphometric characters,

pertaining to samples from southern region/

revealed less significant variations, except for

the characters like caudal fin length (0.769),

total length (0.536) and orbit diameter (0.839)

that registered high loading on PCI and PC2.

Component loading of meristic characters

in fish samples from northern and southern regions

were also compared (Table 6). In the former, few

characters showed maximum variation. These included

lateral line scale count (0.926)/ scale count above

the lateral line (0.944) and pelvic fin ray count

(0.934) on PCI/ and scale count before the dorsal

fin (0.988) on PC2. In the latter, the components

2?.

that contributed towards variations included

lateral line scale (0.918)/ dorsal fin ray count

(0.935) and ventral fin ray count (0.937) on PCI.

Traditionally; data for morphometric

characters are generally analysed without making

corrections for allometric variations within

populations. Although the use of ratios is an

established technique in fish morphometries/ its

reliability has been questioned because of the

effect of correlation between numerator and

denominator (Atchley and Anaerson 1978; and Reist/

1985). It is known that correlated characters can

also be identified by calculating within the group

correlation matrix of two different populations

from log transformed data of morphometric character

and square root transformation of meristic

characters (Sokal and Rohlf/ 1981). In the present

set of data analysis on £. punctatus/ PCA was

carried out on a correlation matrix instead of

variance covariance matrix. Causton (1988) has

reported that in such studies/ when all characters

are measured on equal basis in both ways/ PCA

carried out on correlation matrix manifests the

true loading.

23

Maoid'eidigh et al. (1988)/ while studyi.na

the populations of twait shad/ Allosa fallax,

carried out PCA on eighteen of its morphomet ric

characters and noted that in correlation matrix,

all the variables were highly correlated and their

component loadings were also high for each of the

variable. These authors further observed that

component loadings were of the same sign and

magnitude, concluding that definite size variation

occurred between two populations but variations

in shape were not discernible. The present study

on C. punctatus/ however/ produced positive and

negative component loadings/ indicating that both

shape and size variations are distinct in this

species. However/ to establish whether such

variations in £. punctatus are the result of

geographic location or an example of genotypic

differentiation requires more detailed

investigations.

SUMMARY

Intraspecific stock discrimination has been

made in the common freshwater pond murrel,

C. punctatus, using a pool of morphometric and

meristic characteristics. Principal Component

Analysis [PCA]/ was employed as diagnostic tool.

Fish samples were collected from northern and

southern regions of the country. PCA revealed that

a high percentage of total variance was associated

with the first component, reflecting a large

difference in the size range. Intragroup variations

were more significant in samples collected from

northern region as compared to those from the

southern region. Out of the eight distinct

morphometric characters chosen for the study and

tested through PCA, only few contributed

significantly. Total and standard length and orbit

diameter showed maximum variation in the northern

fish samples. In the southern fish samples, on the

other hand, maximum variation was observed in total

length, caudal fin length and orbit diameter. Among

the meristic parameters, significant variations

were noticed in scale count on and above the

lateral line, before the dorsal fin, and in pelvic

25

fin ray count of fish samples from northern region.

Meristic parameters showing significant variations

in the southern fish samples included lateral line

scale count/ and dorsal and ventral fin ray count.

The significance of data has been briefly

discussed.

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Table 5. COMFCNh:>,r

CiiAXXA pL:XCTArL;S FROM TWO RiGICX;

character Region

North South

PC 1 PC 2 PC 1 PC 2

TL

SL

PDL

0 0

CFL

DDF

HL

BW

Important contributor to this component,

0 . 9 3 8 *

0 . 9 3 2 *

0 . 1 7 8

0 . 2 8 3

0 . 2 0 0

0 . 4 8 2

0 . 4 4 9

0 . 4 6 9

- 0 . 0 6 5

- 0 . 0 7 3 5

- 0 . 0 5 3

0 . 9 2 5 *

- 0 . 9 5 4

0 . 0 1 2

- 0 . 7 2 6

- 0 . 6 3 7

0 . 536*

0 . 3 5 4

0 . 4 9 3

0 . 262

0 . 7 6 9 *

0 . 4 1 5

0 . 4 5 2

0 . 5 1 7

0 . 4 1 5

0 . 2 9 6

0 . 4 4 2

0 . 8 9 3 *

0 . 3 3 5

0 . 3 4 5

0 . 4 7 8

0 . 3 9 7

T a b l e 6 . CO.MFOXENT LCADIXG OF TEN .MERISTIC rARA.YETERS

CHANNA PUNCTATUS FROM TWO REGIONS

C h a r a c t e r

LLS

SAL

SBL

SBD

NCR

DFR

P FR

VFR

P^FR

NCR

R e g i o n

North South

PC 1 PC 2 PC 1 PC 2

0 . 9 2 6 *

0 . 9 4 4 *

• 0 . 8 1 5

0 . 1 1 5

0 . 203

0 . 2 1 1

0 . 9 3 4 *

0 . 5 0 1

0 . 4 6 5

0 . 1 9 7

- 0 . 6 8 3

- 0 . 6 6 1

0 . 6 4 2

0 . 9 8 8 *

- 0 . 0 0 0 2

- 0 . 0 4 5

- 0 . 0 7 7

0 . 0 2 4

- 0 . 0 1 8

- 0 . 1 0 1

0 . 9 1 8 *

0 . 5 2 1

0 . 2 8 1

0 . 7 5 3

0 . 4 2 0

0 - 9 3 5 *

0 . 0 3 6 4

0 . 9 3 7 *

0 . 1 0 2

0 . 0 7 1

- 0 . 0 6 6

- 0 . 1 6 6

- 0 . 8 9 9

- 0 . 0 7 1

- 0 . 5 8 3

- 0 . 1 7 5

0 . 2 7 6

0 . 0 6 7

0 . 0 7 3

- 0 . 0 8 9

* I m p o r t a n t c o n t r i b u t o r t o t h i s component

Fig. 1. Two important e igenvectors of morphometric

characters in C. punctatus from northern

(0) and southern (•) r eg ions .

0 7 -j o

OD

05

03

OD

DDF O O T L

0 5 L

0 1 OPDL

,- - — [ [ , —

- 0 5 - 0 3 -01 - n 1 -

i 1

0 1 03 !^L't)5 • T L

• DDF • OBV.

<^^'- OHL

0-7

- 0 3 • SL

- 0 5 i

- 0 7

- 0 9 -!

o CF L

Fig. 2. Two important eigenvectors of meristic

characters in C. punctatus from northern

(0) and southern (•) regions.

0 9

o SBO

0 7

0 5

0-3

0 1

-0 9 -0 7

(NGR

NVR

P z ^ R * SBD? • D F R S A L » # 1 1 5

L L S

=1 FR 0 °SAL

-0 5 ^ i'cT" -0.1 \ ^ T ^ ^

N 6 R

0-5 07 0-9

•0-3 -I ISEL

o DFR

- 0 - 5 1

• 07 j

09

Fig. 3. Component loading of morphometric and

meristic characters of C. punctatus from

northern and southern regions. Meristic Z\ ,

northern; A , southern; morphometric 0/

northern; • southern.

i S B L

SBD OOD

• 0 0

Hi

0 3 -

B M »

. D D F

• S L

- 0 7 - 0 3 £, - 0 1

4CFR 0 5

seo s L ^ n P,F(i ICfR

- 0 3 -

-cs-

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