SOME STUDIES ON REPRODUCTIVE BIOLOGY OF SOL (CHANNA MARULIUS) IN THE PUNJAB, PAKISTAN
MUHAMMAD ZAFARULLAH BHATTI 03-arid-842
Department of Zoology Faculty of Sciences Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi Pakistan 2010
SOME STUDIES ON REPRODUCTIVE BIOLOGY OF SOL (CHANNA MARULIUS) IN THE PUNJAB, PAKISTAN
By
MUHAMMAD ZAFARULLAH BHATTI (03-arid-842)
A thesis submitted in partial fulfillment of the requirement for the degree of
Doctor of Philosophy
In
Zoology
Department of Zoology Faculty of Sciences Pir Mehr Ali Shah Arid Agriculture University, Rawalpindi Pakistan. 2010
CERTIFICATION
I hereby undertake that this research is an original and no part of this thesis falls under plagiarism. If found otherwise, at any stage, I will be responsible for the consequences.
Student’s Name: Muhammad Zafarullah Bhatti Signature:______
Registration No.: 03-arid-842 Date: ______
Certified that the contents and form of thesis entitled “Some studies on reproductive biology of Sol (Channa marulius) in the Punjab, Pakistan” submitted by Mr. Muhammad Zafarullah Bhatti have been found satisfactory for the requirement of the degree.
Supervisor: ______(Dr. Afsar Mian)
Member: ______(Dr. Mazhar Qayyum)
Member: ______(Dr. Azra Khanum)
Chairman, Department of Zoology: ______
Dean, Faculty of Science: ______
Director, Advance Studies: ______
i
DEDICATED
TO
MY PARENTS
ii CONTENTS
Page
LIST OF TABLES VII
LIST OF FIGURES X
LIST OF PLATES XIII
ACKNOWLEDGEMENTS XIV
ABSTRACT XVI
1 INTRODUCTION 1
1.1. Background 1
1.2. Sol (Channa marulius) 8
1.3. Objective 13
2. REVIEW OF LITERATURE 16
2.1 Growth 16
2.1.1. Age Related Changes
2.1.2. Length Weight Relationship 17
2.1.3. Condition Factor 20
2.2. Karyotype
2.3. Reproductive Cycle 21
2.3.1. Gonadosomatic Index 22
2.3.2. Hepatosomatic Index 23
2.3.3. Histological Changes 24
2.2.3.1 Testes 25
iii 2.2.3.2. Ovaries 26
2.3.4. Steroid Hormone 28
2.3.4.1. Testosterone 29
2.3.4.2. Estrogen 30
2.3.4.3. Progesterone 31
3 MATERIALS AND METHODS 33
3.1. Study Area 33
3.2. Morphometric Analysis 40
3.2.1. Morphometric Measures and Meristic Counts
3.2.2. Length –Weight Relationship
3.3. Karyotype
3.3.1. Slide Preparation and Photography
3.3.2. Chromosome Analysis and Karyotype
3.3.3. Chromosome Classification
3.3. Growth 43
3.4.1. Seed Procurement and Transportation 43
3.4.2. Rearing 44
3.4.3. Sampling and Measurements 45
3.4.4. Analysis 46
3.5. Reproductive Changes 46
3.5.1. Sampling 46
iv 3.5.2. Histological Studies 48
3.5.3. Hormonal Profile 50
3.5.4. Analysis 51
4 RESULTS AND DISCUSSION 53
4.1. Morphometry 53
4.2. Karyotype
4.2.1. Chromosomes: Number and Morphology
4.3. Growth 73
4.3.1. Length 73
4.3.2. Weight 75
4.3.3. Length Weight Relationship 75
4.3.4. Condition Factor 78
4.4. Reproductive Biology 88
4.4.1. Gonadosomatic Index 88
4.4.2. Hepatosomatic index 96
4.4.3. Sex Hormone Profile 102
4.4.3.1. Estrogens 102
4.4.3.2. Progesterone 103
4.4.3.3. Testosterone 104
4.4.4. Histological Changes 111
4.4.5. General Consideration
v SUMMARY
LITERATURE CITED 116
vi LIST OF TABLES
TABLE No. TITLE PAGE
1.1 World fisheries and aquaculture (excluding aquatic plants) 5 production and utilization (million tons) during different years. (The State of World Fisheries Aquaculture, FAO, 2008). 3.1 Monthly temperature range (o C) (maximum - minimum) 41 of north (Islamabad) central (Lahore) and southern Punjab, (Bahawalpur), between May 2005 and April 2007 (Source: Pakistan Meteorological Department)
4.1 Summary of different morphometric variables of adult 69 Channa marulius captured in December 2005 –February 2007 from Taunsa Lake (southern Punjab, Pakistan). lengths in “cm”, and weight in “g”, n = 21 for all variables
4.2 The summary of different meristic variables of adult 70 Channa marulius captured in December 2005 –February 2007 from Taunsa Lake (southern Punjab, Pakistan) n = 21 for all variables
4.3 Regression of different morphometric and meristic 72 characters against standard length in Channa marulius captured from Taunsa Lake (southern Punjab, Pakistan). All measure in “cm”.
4.4 Age related changes in length of Channa marulius 73 maintained in earthen ponds at Chenawan Fish Hatchery
4.5 Age related changes in weight of Channa marulius 77 maintained in earthen ponds at Chenawan Fish Hatchery
4.6 Age – length - weight relationships and condition factor 84 (K) in different age groups for Channa marulius at different ages maintained at Chenawan Fish Hatchery (n= sample size, K = Condition factor)
4.7 ANCOVA: output with age (month) taken as categorical 88 variable, length (log natural) as covariate and weight (log natural) as dependent variable in Channa marulius.
vii 4.8 Values of gonadosomatic index (GSI) of female Channa 91 marulius during the sampling calendar months 4..9 ANCOVA output for the effects of months and length of 99 fish (covariate, ln) on ovary weight (ln) of female Channa marulius
4.10 Pairwise comparison among months based on estimated marginal means (means adjusted for the effect of covariate) on ovary weight of female Channa marulius
4.11 Values of gonadosomatic index (GSI) of male Channa marulius during the sampling calendar months
4.12 ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (ln) of testes of male Channa marulius
4.13 Pairwise comparison among months based on estimated marginal means (adjusted for the effect of covariate) on weight of gonads of male Channa marulius
4.14 Values of hepatosomatic index (HSI) of female Channa marulius during the sampling calendar months
4.15 ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (ln) of liver (ln) of female Channa marulius
4.16 Pairwise Comparison among months based on estimated marginal means (means adjusted for the effect of covariate) of weight of liver of Female Channa marulius
4.17 Values of gonadosomatic index (GSI) of male Channa marulius during the sampling calendar months
4.18 ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (ln) of liver of male Channa marulius
4.19 Pairwise comparison among months based on estimated marginal means (adjusted for the effect of covariate) on weight of liver of male Channa marulius
4.20 Values of estradiol of female Channa marulius during the sampling calendar months
viii 4.21 Monthly differences in Estradiole level of female Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 63.596 , P < .05 followed by Scheffe test for multi comparison.
4.22 Values of progesterone of female Channa marulius during the sampling calendar months
4.23 Monthly difference in Progestrone level of female Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 183.56 , P < .05 followed by Scheffe test for multi comparison.
4.24 Values of testosterone of male Channa marulius during the sampling calendar months
4.25 Monthly differences in Testosterone level of male Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 49.212 , p < .05 followed by Scheffe test for multi comparison.
4.26 Frequency of ovaries under different maturation stages of female Channa marulius during different calendar months
4.27 Frequency of testes under different maturation stages of male Channa marulius during different calendar months
4.28 Matrix showing the Pearson correlation coefficient between different variables of reproductive activity in female Channa marulius (n = 33)
4.29 Matrix showing the Pearson correlation coefficient between different indicators of reproductive activity in male Channa marulius (n = 20)
ix LIST OF FIGURES
FIGURE NO. TITLE PAGE
1.1 World fisheries and aquaculture production and 6
utilization (The State of World Fisheries and
Aquaculture - 2000 (SOFIA)
1.2 Distribution of Channa marulius in South East Asia 11
(Courtenay and Williams 2004; USGS)
3.1 The hydrographical map of Pakistan showing all rivers 40
and their tributaries and the densely populated Punjab
province
3.2 Map of the part of Punjab province of Pakistan showing 45
main head works in the Punjab
3.3 Schematic representations of the body measurements 49
and head measurement of Channa marulius
4.1 PCA graph, Factor Score plots of total length for 78
different samples of the Channa marulius based upon
22 morphological characters. (F1- F21 are the fish
specimen)
4.2 A karyotype of Channa marulius (Hamilton 1922) 81
4.3 Linear graph showing age related changes in length of 85
Channa marulius maintained at Chenawan Fish
x Hatchery
4.4 Linear graph showing age related changes in weight of 89
Channa marulius maintained at Chenawan Fish
Hatchery
4.5 Linear graph showing age Relationship between log 92
values of wet weight against the log values of total
length of Channa marulius maintained at Chenawan
Fish Hatchery
4.6 Linear graph showing age relationship between wet 93
weight against the total length of Channa marulius
maintained at Chenawan Fish Hatchery
4.7 Graphical representation of condition factor for Channa 96
marulius over a period of 15 months maintained at fish
Hatchery Chenawan
4.8 Bar chart of the b values (coefficient of variance) of all 97
groups of Channa marulius maintained at Chenawan
Fish Hatchery
4.9 Pattern of seasonal variations in the gonadosomatic 100
index of female Channa marulius
4.10 Pattern of seasonal variations in the gonadosomatic 102
index of male Channa marulius
4.11 Pattern of seasonal variations in the hepatosomatic 106
xi index (HSI) of female Channa marulius
4.12 Pattern of seasonal variations in the hepatosomatic 108
index (HSI) of male Channa marulius
4.13 Variation in the serum estradiol in female Channa 113
marulius
4.14 Variation in the serum progesterone in female Channa 116
marulius
4.15 Variation in the serum testosterone in male Channa 119
marulius
4.16 The graphic representation of variations between GSI 131
with estradiol in female Channa marulius
4.17 The graphic representation of variations between GSI 132
with progesterone (a) and with HSI (b) in female
Channa marulius
4.18 The graphic representation of variations between HSI 133
with progesterone (a) and with estradiol (b) in female
Channa marulius
4.19 The graphic representation of variations between GSI 134
with testosterone in male Channa marulius
4.20 The graphic representation of variations between GSI 135
with HSI (a) and Testosterone in male Channa
marulius
xii LIST OF PLATES
Plate No. TITLE PAGE 1.1 Picture of Channa marulius captured from Namal Lake
(District Mianwali) Punjab, Pakistan (courtesy: Deputy
Director Fisheries, Punjab Fisheries Department)
3.1 The picture of Head Taunsa, Dera Ghazi Kahn,
(Southern Punjab) a, and head mole dhand (Lake) b.
4.1 Spread of the diploid chromosomes of Channa marulius
captured from Head Taunsa (southern Punjab, Pakistan)
a, after clearing b.
4.2 Photographs of ovary of Channa marulius in different
maturation stages a: immature, b: developing, c: mature,
d: ripe and e: spent
4.3 Photographs of testes of Channa marulius in different
maturation stages a: immature, b: developing, c: mature,
d: ripe and e: spent
xiii ACKNOWLEDGEMENTS
I express my profound gratitude to my supervisor Prof. Dr. Afsar Mian, HEC
Eminent Scholar and Former Dean, Faculty of Sciences, PMAS Arid Agriculture
University, Rawalpindi, for his personal concerns, kind guidance, valuable discussions, suggestions and encouragements throughout the course of study. I am really benefited from his competence, knowledge, experience and profound learning.
I feel pleasure to express my gratitude to Prof. Dr. Mazhar Qayyum, Chairman
Department of Zoology, and Prof. Dr. Azra Khanum, the members of my supervisory committee, for their scholarly guidance, expert suggestions and sympathetic attitude during the present research. Prof Dr. Mazhar Qayyum was also instrumental in providing necessary facilities at the Department. I am also obliged to Prof. Dr. Yasmin
Musaddeq, ex-Chairperson Department of Zoology, for providing guidance and necessary encouragement at the initial stages of this research.
Special thanks to Mr. Saeedur Rehman and his staff at Fish Nursery unit for their helps in executing my research work. Dr. Naseem Akhtar has been a source of inspiration throughout the conduct of this research. Thanks are also due to Dr.
Muhammad Ayub (former DG Fisheries, Punjab) and Mr. Muhammad Ashraf (DG
Fisheries, Punjab) for their constant support. Many thanks to Dr. Muhammad Rafique,
Director, PMNH Islamabad, Dr. Muhammad Naeem, BZU Multan and Mr. Sajid Ali
Naqvi for their help, particularly in analyzing the research data.
xiv Thanks are also extended to my colleagues Ch. Iftikhar Ahmad, Syed Zulfiqar
Ali Abdi and Miss Sana Urooj who worked tirelessly with me in final organization of the research out put.
I acknowledge the Punjab Fisheries Department, for granting me the study leave and facilitated the field studies. I am also thankful to all of my friends and
colleagues for their moral support and encouragement throughout the study.
My sincere acknowledgement are due to my father, my mother (late), my
brother, Iqbal, my wife Razia and my kids (Zeb, Aatiqa, and Zeshan), who remained a
constant source of prayers, well wishes and inspiration for me.
Muhammad Zafarullah Bhatti
xv ABSTRACT
Sol (Channa marulius) is a good target species for introduction into the aquaculture system of Pakistan, being indigenous and having potential to survive under variety of stressful freshwater conditions. The present study has been undertaken to study the growth and reproductive biology of the species under the conditions of
Punjab (Pakistan). The analysis of morphometric and meristic characters suggested a significant correlation between the morphometric characters and a non-significant correlation between meristic characters, suggesting that meristic characters have a higher taxonomic value. Principal Component analysis suggested that fishes of different sizes have different patterns of growth of recorded variables. The fish with an average size of 7.37 cm (2.88g) increased to 53.8 cm (1165.7 g) from the age of 2 months to the age of 16 months. The fish at different ages suggested an isometric growth of weight in relation to length, with an average regression coefficient value of
3.05. Analysis of different reproductive biology variables conducted on fish captured from wild conditions suggested that the condition factor, gonadosomatic index (GSI), levels of progesterone and testosterone started gradually increasing after December, reaching peak values in April and a sudden decline in May. However, estrdiol peaked in March and showed minimum level in June. Hepatosomatic index (HSI) showed an inverse pattern, showing a decline in December with minimum values in May, when it started increasing to maximum values in the later part of the year. The pattern of histological changes in gonads followed the pattern of other variables of reproductive biology indicating that these variables truly represent the reproductive state of the
xvi individual. The studies suggest that the species is a long day species, where the reproductive activities commence after December and spawning takes place between late march and early May, under the environmental conditions of the Punjab
(Pakistan).
xvii 1
Chapter 1
INTRODUCTION
1.1. BACKGROUND
The human population of the globe has increased from some 1.6 billion in
1900 to around 6.1 billions in 2000, suggesting an almost four times increase in the human mouths to be fed over the hundred years from the available food energy resources of the globe. The increasing human population is liable to result in increasing food insecurity at individual, national and global levels, leading to a multitude of socioeconomic and political problems, ultimately resulting in political instabilities and terrorism. Food availability is thought to be the key factor in achieving the food security, yet it may not be able to fight the problem of malnutrition resulting in poor health and loss of man hours.
Recent advances in agricultural sciences and agricultural technologies have averted the problem of starvation, to certain degree, yet have not been able to provide balanced nutrition to satisfy health needs to the majority of the human population, especially that falling below poverty line. Diversifying the food base along with technologies to increase productivity are collectively required for fighting starvation and malnutrition together with cheaper availability of balanced food for the poverty stricken masses. The problem of malnutrition can thus be addressed by improving access to the quantity and quality of food which may require diversification of the present food base. 2
Protein is the basic food ingredient and hence is very important for human health and normal growth. Under the present trends, the major part of the protein requirements of the human populations is met from livestock and poultry resources.
Aquaculture also provides the quality protein (Alikunhi, 1953), yet is not presently exploited to its capacity. Whereas the production of farmed poultry and livestock is reaching its saturation point, aquaculture has expanded only during recent years and still has sufficient potential to grow to help save the human population from malnutrition occurred through protein deficiency.
Fish is the source of best quality white protein. It is the most important single source of high quality protein. It is generally believed that a consistent source of fish is essential for the nutritional health of a large segment of the world’s population. Fish has the potential to ensure a quality food, providing some 16 % of the animal protein consumed by man and available estimates suggest that some one billion people, worldwide, rely on fish as their primary source of animal protein
(FAO, 1997). Fish also has substantial social and economic importance. The estimates in hand indicate that international trade of fish exceeds some US$ 51 billion per annum (FAO, 2000). The aquaculture and fisheries sector provides direct employment to over 36 million people (FAO, 2000), while around 200 million people are directly or indirectly associated with income generation through fish (Garcia and Newton, 1997) around the globe. The global consumption and hence its market has increased from some 40 million tones in 1970 to around 86 million tones in 1998 (FAO, 2000) and the projected consumption has been placed at 110 million tons for the year 2010 (FAO, 1997). 3
The major source of the fish has primarily been the capture fisheries, and currently, on a global scale two thirds of the total food fish supply comes from harvesting natural waters, mainly the marine waters. Inland capture fisheries till date has a relatively little contribution in meeting the global demand of fish protein.
With the increasing demand for fish in the market under increasing human population and health awareness, the stress on natural fisheries resources is increasing. Under such circumstances the capture fisheries have not been able to keep pace with the gradually increasing market demands. Evident signs of over- harvesting of the marine fisheries resources have started appearing in many areas, as is indicated by a decreased catch despite the increasing number and sophistication of the catching gadgets.
The global fish consumption has increased by 31% during 1990-1997 though the marine fish supply increased by only 9% during this period (FAO,
1999). This has serious consequences on the natural fisheries resources, as the pressure of a higher demand forces the harvesters to put in more efforts. This has resulted in fishing much above the renewable potentials of the fish resource and hence the gradual depletion of the stock of natural commercial fisheries. It is believed that around half of the known ocean fisheries resources are completely exploited (FAO, 1999) and around 70% require immediate management measures to save such stocks for the future generations (MacLennan, 1995). Under such a pattern of harvesting the natural fish resources, the capture fisheries have become stagnant, and in many places are showing declining trends (FAO 2008; Table 1.1). 4
To meet the ever increasing demand for the fish, aquaculture in the recent years has expanded rapidly and is now becoming the fastest growing food- producing industry in the world (FAO, 2000; Figure 1.1). In contrast to the stagnation or even the decline of capture fisheries, aquaculture production has exhibited a sharp increase after the World War II (FAO, 2000). However, with the exception of China, the world aquaculture production has exhibited a somewhat lower annual growth rate (5.3%) in 1990’s as compared with that (7.1%) in 1980’s and this trend confirmed during the 2000 - 05 period (FAO, 2008). The major present day concern is to increase per unit area production by applying different innovations / technologies rather than increasing the total area under the aquaculture.
Apart from testing different advanced technologies for obtaining higher growth potential, the addition of new fish species into the aquaculture system is also being exercised to widen the aquaculture base and to fetch a higher market price (Ali and Akif, 2007). It is believed that aquaculture potential still exists for many fish species. However, the successful introduction of a new species into the aquaculture system, including exotic species, needs careful study of its biology.
The introduction of exotic tilapia (Oreochromis niloticus and O. mosambicus) into the freshwaters of Pakistan has resulted in an uncontrolled growth in the population of this fish, which still has to find a place in the local market. It has also created stressful conditions for the survival and growth of many local species having local market acceptance (Job, 1967). 5
Table 1.1: World fisheries and aquaculture (excluding aquatic plants) production and utilization (million tons) during different years. (The State of World Fisheries Aquaculture, FAO, 2008). 2000 2001 2002 2003 2004 2005 PRODUCTION Inland Capture 8.8 8.9 8.8 9.0 9.2 9.6 Aquaculture 21.2 22.5 23.9 25.4 27.2 28.9 Total inland 30.0 31.4 32.7 34.4 36.4 38.5 Marine Capture 86.8 84.2 84.5 81.5 85.8 84.2 Aquaculture 14.3 15.4 16.5 17.3 18.3 18.9 Total marine 101.1 99.6 101.0 98.8 104.1 103.1 Total Capture 95.6 93.1 93.3 90.5 95.0 93.8 Total Aquaculture 35.5 37.9 40.4 42.7 45.5 47.8 Total world fisheries 131.1 131.0 133.7 133.2 140.5 141.6 UTILIZATION Human consumption 96.9 99.7 100.2 102.7 105.6 107.2 Non- food uses 34.2 31.3 33.5 30.5 34.8 34.4 Population (billions) 6.1 6.1 6.2 6.3 6.4 6.5 Per capita food fish supply (kg) 16.0 16.2 16.1 16.3 16.6 16.6
million tons (
Production
Figure 1.1: Growth in world fisheries and aquaculture production during recent past. (The State of World Fisheries and Aquaculture, FAO, 2000).
6
In Pakistan, pond culture is still below a semi-intensive level. It is traditionally dominated by a few freshwater species, i.e., six indigenous and exotic species, which mainly include the Indian major carps {rohu (Labeo rohita), mori
(Cirrhinus mrigala), thaila (Catla catla) } and the Chinese carps {grass carp
(Ctenopharyngodon idella), silver carp (Hypophthalmichthys molitrix), big head
(Aristichthys nobilis)}, usually in polyculture and /or integrated with animal husbandry.
Being herbivore, these fish species can only harvest one trophic level, which poses limitations on increasing per unit area yield. There are attempts to add some more species into the aquaculture system of Pakistan. The catfish and snakeheads have been considered as good option, as these can be stocked in relatively higher densities with external supply of prepared balanced food. The intensive monoculture of the catfish can be attempted for optimum production and profit. Various fishes are being considered for intensive monoculture and snakeheads are considered to be the strong candidate for the purpose, having great potential.
Snakeheads (genus Channa) belong to family Channidae and are native to
Asia and tropical Africa. These are partially air breathing freshwater fishes and considered as thrust predators. Most of these are piscivorous. These are called as snakeheads because of having certain snake-like characters including elongated and cylindrical bodies, presence of large scales on the head in most of the species and somewhat flattened head with eyes located in a dorso-lateral position on the anterior part of the head. There is lot of variation in size among the snakeheads, some remaining below 17 cm in length while most of the snakehead has great growth potential and can attain a length of 180 cm. 7
Snakeheads have been regarded as good food and aquarium fish, and can fetch higher prices in the market. These have long been regarded as a valuable food fish by the Asian people and have been popular in most of the markets. Channa marulius is considered as important food fish in Andhra Pradesh, India (Talwar and
Jhingran, 1992) and Jamshedabad, India (Rao and Durve, 1989). Channa striata is the most preferred fish of Andhra Pradesh, India (Sriramlu, 1979). Snakeheads are preferred in Cambodia, as these can be marketed fresh and sometimes even live
(Rainboth, 1996). Bardach et al. (1972) recorded that the culturing of these fish species can be considered in kitchen or village ponds, rice fields and even in the irrigation wells and the aquatic habitats which are otherwise not suitable for culturing other fish species. Despite the fact that snakeheads can tolerate a wide range of conditions in tropical habitats i.e., ponds, canals, ditches, drains, rivers, etc. (Smith, 1945) yet their supply has always remained limited and mainly comes from the capture fisheries. The recent decline in the harvest of snakeheads from natural waters, due to over fishing, has attracted fish farmers towards its culture under the farmed conditions.
Some 29 species of snakehead are known from Africa (genus Parachanna, three species) and Asia (genus Channa, 26 species) (Mirza, 1995). Some of these have been introduced in the fish culture system of Kampochia and Vietnam
(Pantulu, 1976). Sol (Channa marulius) is an important representative of this group, which is indigenous to Pakistan (Rafique, 2007), and other parts of South
East Asia. It can possibly attain the length of 183 cm and weight up to 30 kg. Due to its large size and better growth rate, in addition to its survival under low 8
dissolved oxygen through a partial dependence on air respiration, it is considered as a good candidate for introduction into the farming system of Pakistan. However, the availability of fish seed, produced under controlled hatchery conditions has remained the major obstacle in its introduction. Further, the optimum exploitation of this fish species for commercial culturing requires a detailed study on the biology of this species, with special reference to its reproductive biology. The present project is aimed at studying growth performance and reproductive biology of C. marulius under the physico-biotic conditions of the Punjab, Pakistan.
1.2. SOL
Sol (Channa marulius: Plate 1.1), also variously called bullseye snakehead, giant snakehead, great snakehead, cobra snakehead, Indian snakehead, belongs to the family Channidae (superclass Osteichthyes, class Actinopterygii, subclass
Neopterygii, infraclass Teleost, supraorder Acanthopterugii, order Perciformes, suborder Channoidei). The native range of this species extends from Pakistan through India, Sri Lanka, Bangladesh, Nepal, Thailand, Laos, Cambodia, Myanmar and China (Courtenay and Williams, 2004; Figure 1.2). Sol is known by different local names in different parts of its distribution range {Pakistan: Sol, Soal; India:
Haal (Assam), Sal, Gajal (West Bengal), Pumurl, Bhor (Bijar), Kubrah, Sawal,
Dowlah Kobra (Punjab), Saal (Orissa), Poomeenu, Phoolachapa, Phool-mural
(Andra Pradesh), Aviri, Puveral (Tamil Nadu), Chaeruveraal, Curvuva, Bral
(Kerala), Hoovina-murl, Madinji, Aviu (Karnataka); Sri Lanka: Ara, Gangara,
Kalmuha (Sinhalse), Iru Viral (Tamil); Cambodia: Trey Raws; Thailand: Pla Chon
Ngu Hao (Smith, 1945, Talwar and Jhingran, 1992)}. 9
Plate 1.1: Channa marulius captured from, Namal Lake (District Mianwali), Punjab, Pakistan (courtesy: Deputy Director Fisheries, Punjab Fisheries Department).
Figure 1.2: Distribution of Channa marulius in South East Asia (Courtenay and Williams 2004; USGS).
10
Channa marulius was originally described by Hamilton (1822) based upon the specimen captured from the river Ganges and its tributaries. The fishes of this species have been given different names, i.e., Ophiocephalus sowara Cuvier, 1831,
Ophiocephalus grandinosus Cuvier, 1831, Ophiocephalus leucopunctatus Sykes,
1839, Ophiocephalus theophrasti Valenciennes, 1840, all of which are now considered as the synonymes and have been withdrawn in favour of Channa marulius following the priority rule.
The description of C. marulius has appeared in literature (Hamilton, 1822;
Talwar and Jhingran, 1992; Fuller and Benson, 2010), which constitutes the basis for development of the following description of the species. Channa marulius is a large sized fish specie, having and elongated and cylindrical body, dark grey above and yellowish-white below. Dark patches appear along lateral line and the fins are spotted. A distinctive organ spot is located on the caudal peduncle. The dorsal profile of the body rises from the tip of the snout to the front of the dorsal fin, then onward it is almost horizontal. The ventral profile is slightly arched upto the origin of the anal fin, whence onward it is somewhat straight. Thus the body is the deepest in front of the dorsal fin, where its depth is greater than the breadth. The head is large compressed dorso-ventrally and tapering. Scales on the top of the head are of moderate size with a rosette of head scales, appearing between orbits, and there is no patch of scales on gular region. Snout is somewhat pointed and slightly smaller that the inter-orbital width. Large and rounded eyes are placed in dorso-lateral position, closer to the tip of the snout than the posterior end of the operculum. Cleft of the mouth extend upto the posterior edges of the eyes and the 11
barble is absent. Mouth is large and almost oblique, lower jaw somewhat protruding, with 7-18 canine teeth located behind a single row of villiform teeth, widening into 5-6 rows at the jaw symphysis. Teeth are present on prevomer only
(absent on palatines). The pectoral fin length is smaller than the head length (about half of head length, Talwar and Jhengran, loc cit). The ventral fin reaches the anal aperture and the dorsal fin extends beyond the caudal base. The candal fin is rounded.
The description of Talwar and Jhengran (loc cit) has given the meristic counts of the fin rays (dorsal =45-55, anal =28-36, pectoral =16-18, pelvic =.6, caudal = 13-16), lateral line scales (60-70) and pre-dorsal scales (16) of this fish specie. The rows of the scales located between posterior margin of the orbit and pre-opercular region are placed at an angle of 10o, and lateral line scales drop in the form of two rows between 16th and 18th perforated scale.
Different species of the genus Channa, including C. marulius, inhabit large lakes and rivers. Channa marulius is also adapted to ponds and other smaller bodies of standing water (Lee and Ng, 1991, 1994). Smith (1945) believes that the species is found in every kind of tropical freshwater habitat, including, ponds, canals, ditches and drains. Channa marulius is more adapted to live in sluggish or standing water in canals, lakes and swamps, having submerged aquatic vegetation
(Rainboth, 1996). The presence of the species has though been reported from swamps, ponds (Jhingran, 1984) and from flood forests (Roberts, 1993), but the species prefers clean water with sandy or rocky substrate (Talwar and Jhingran, 12
1992). Pethiyagoda (1991) described the deep pools in rivers and occasionally the deep lakes as more suitable habitat for the species. The young fish are facultative air breather, but their adults are obligate air breather.
Sol is a carnivorous fish species (Jhingran, 1984) depending upon the food coming from a variety of animal origin, including, fish, frogs, snakes, insects, earthworms and tadpoles (Rahman, 1989), and even water birds and rodents. Sol may bite a man with its strong canine like-teeth. There are reports of cannibalism in this species (Devaraj, 1973a), which may result in a poor survival rate of the young ones, which may cause some problems in its farming (Devaraj, 1973b; Mirza and
Bhatti, 1993.
Channa marulius is being successfully cultured in Hong Kong, though
Mirza and Bhatti (1993) did not recommend the inclusion this fish species into the fish culture system of Pakistan due to its piscivorous habit. However, sol is considered as a hardy species, and because of its air breathing capability exhibits a high tolerance to low levels of dissolved oxygen and a voracious feeding habit.
Channa marulius breeds naturally in ponds and brood size varied between
375 and 3,000 in different swamps recorded in Karnateka, India. The eggs are pale red-yellow with a diameter of around 2 mm. The eggs hatch in 54 hours at 16 -26o
C and in 30 hours at 28 – 33oC (Parameswaran and Murugesan, 1976). Parents lay the eggs in nests, built with weeds and leaves of aquatic plants (Pethiyagoda,
1991), and guard the spawn until the young reach the size of some 10 cm (Breder and Rosen, 1966). Males show a territorial behavior (Pethiyagoda, 1991). 13
1.3. OBJECTIVES
The growth and reproduction of an organism, including fish, is controlled by environmental factors, like conditions of temperature, light and the availability of food, apart from range of tolerance to different biotic/ abiotic factors, the internal potentials of the species controlled by its the genomic set up, evolved during its evolutionary history (Morgan, 2008). The populations of C. marulius surviving under the conditions of the Punjab (Pakistan) represent ecotype / ecotypes having specific genomes, adapted to a specific set of environmental conditions. The breeding season of C. marulius has been reported as June – August in southern Nepal (Shrestha, 1990), April – June in Pakistan (Mirza and Bhatti,
1993), and rainy season (Khan, 1924). Two distinct breeding seasons i.e., May -
June and November – December, have also been reported for the population surviving in Andhra Pradesh, India (Srivastava, 1980). The present study has been conducted on the hypothesis that C. marulius under the conditions of the Punjab
(Pakistan) has specific spawning season and growth rates.
The reproductive status of different species of fish stock has been variously judged through macroscopic analysis of the gonads (Vitale et al., 2005), yet the supportive histological studies have been frequently used for placing the macroscopic observations on sounder basis (Saborido-Rey and Junquera, 1998;
Kjesbu et al., 2003). The levels of reproductive hormones provide further confirmation to the reproductive status of the fish stock. None of the previous studies have exploited all these variables together. Such studies are almost absent for C. marulius, especially for the ecotype surviving in the waters of the Punjab
(Pakistan). 14
Under the hypothesis specific objectives of the present attempt are to study:
1. age related changes in length and weight
2. season related anatomical changes in gonads (gonadosomatic index,
GSI) and liver (hepatosomatic index, HSI), as indices of reproductive
status
3. histological changes in the gonads, in relation to different seasons, and
4. seasonal changes in serum level of major reproductive hormones. viz,
testosterone, progesterone and estradiol.
The study will help in understanding the functioning of the reproductive system and growth rate in this species under the environmental conditions of the
Punjab (Pakistan). The information, thus collected, will be of practical importance in the farming of the species and development of induced spawning practices, which may help in breeding of the species under the hatchery conditions.
Additional studies on the morphometric and merismatic variables of a sample of adult C. marulius, along with karytyping of selected fish collected from the Punjab
(Pakistan) were also undertaken to know the degree of variation of the present stock of this fish species, compared with those available from other parts of its distribution range. 15
Chapter 2
REVIEW OF LITERATURE
2.1. GROWTH
2.1.1. Age Related Changes
Comparative studies on growth of different species of the genus Channa suggested that two species, i.e., Channa marulius and C. striatus, have better growth potential as compared with the other species of this genus (Devaraj, 1973a,
Wee, 1982). Channa marulius can attain the length of 122 cm (Bardach et al,
1972). Some individuals of the species attained a length of 180 cm and a weight of
30 kg under the condition of Maharashtra State, India (Talwar and Jhingran, 1992) though the specific conditions and age of such a fish was not mentioned.
Some reports have appeared on growth rate of C. marulius maintained in different water bodies. The stock of this species maintained in a tank in the
Karnataka State, India, showed that the individuals of this species with an average length of 3.7 cm attained the average length of 52.8 cm in 8 months. The study showed that the fish had a growth rate of 2.5 – 4.0 mm per day during the first 3 months of age, which decreased to 0.8 – 1.3 mm per day for the rest of the 5 months of the study. The average growth rate for the first 8 months of age was placed at 7 cm per month (Murugesun, 1978). Channa marulius attained a length of
30 cm during the first year of its life under the condition of the Maharashtra State,
India (Talwar and Jhingran, 1992). Ahmad et al. (1990) also reported a decrease in 16
the growth rate of C. marulius stock, surviving in the river Kali (northern India), with an increase in age. However, they have not specified the age of their fish stock. A decrease in growth with increasing age has also been reported for C. marulius specimen obtained from the river Ghaggar, Rajastan (India) but highest growth rate was reported for the second year of age (Johal et al, 1983). No study is in hand on changes in weight of C. marulius with age.
2.1.2. Length-Weight Relationship
Few studies concerning age related changes in morphometric characters have appeared in literature on fish biology. Such studies are difficult and the indirect variables of growth are not reliable (Jones, 2000). The fish biologist have remained attracted towards the length-weight relationship, length being treated as a predictor variable, which may act as an indicator of age, with certain limitations.
Many previously available studies (Wootton, 1990; Pauly, 1993; Petrakis et al,
1993; Ozaydin et al., 2007; etc.). Moutopoulos and Stergiou (2002) suggested that the analysis of the length-weight relationship is important for fish biologists and managers as it allows: (a) conversion of growth in length to growth in weight, (b) estimation of biomass from length observations, (c) estimate of the condition of the fish, and (d) between region comparisons of life histories of certain fish species.
Such studies have also been considered important for the analysis of comparative growth (Froese and Pauly, 1998). The length-weight relationship is population specific, though this relationship changes with developmental stages of life, like, metamorphosis, growth and onset of the maturity (Thomas et al., 2003). 17
The length-weight relationship is based upon the cube law, i.e., weight = a . length3, where “a” is a species specific constant. Various studies suggested that the cube law is not applicable to all the fish species, and there are inter-specific or even inter-population variations, and hence the relation is now expressed as W = a L b, where W = weight of fish (g), L = standard length, (Pauly, 1983) or total length of fish (cm) (Abowei , 2009), a = constant (intercept), and b = length exponent
(slope). Under the cube law the value of 3 for “b” suggests isometric growth of weight in relation to length, while values lower than 3 indicate a negative allometric growth and conversely values higher than 3 indicate a positive allometric growth in the fish (Gayanilo and Pauly, 1997).The value of “b” primarily depends upon the shape and fatness of the individuals, controlled by a number of different factors, including environmental factors, like, temperature, food availability, etc. (Pauly, 1984), which may vary seasonally (Bagenal and
Tesch, 1978; Ozaydin et al., 2007), gonadal maturity, sex, stomach fullness, health, preservation techniques, season and habitat (Cherif et al., 2008).
The value of “b” calculated on 36 species captured from Aegean Sea
(Greece) ranged between 2.27 and 3.70, though in one of the species (Citharus linguatula) it was as low as 1.29. No significant seasonal variation in value of “b” was reported for the species for which seasonal data was available (Moutopoulos and Stergiou, 2002). The comparison of these result with those available previously
(Petrakis and Stergiou, 1995) suggested a difference, which was attributed to difference in sample size, sampling area / season and length range (Mountopoulos and Stergiou, 2002). In another study on 11 marine fish species from the Gulf of 18
Tunisia (Mediterranean Sea) the values of b ranged between 2.67 and 3.36 (Cherif et al., 2008). Some low values of b have been suggested for elephant fish
(Mormyrus rume; male =1.69, female = 2.13, combined = 1.99), in the river Ose
(southwestern Nigeria), showing a strong negative allometric growth, though the species was still able to survive in the freshwater environment. (Odedeyi et al,
2007). Le Cren (1951) argues that maintenance of the cube law and hence maintenance the value of “b” close to 3 is rather rare and values below 2 have also appeared for a number of fish species (Thomas et al., 2003). Little information on length weight relationship is available on Channa spp., and especially on C. marulius.
2.1.3. Condition Factor
The condition factor (K) or coefficient of condition (CF), also sometimes referred as length-weight factor, has been frequently used by fish biologists as an index of well being, pulpiness, fatness or relative robustness of a fish (Bagenal,
1978). The index is represented by a relationship between the weight of the fish and its length, and calculated using the formula: K = 100 * W / Lb; where K = condition factor, W = weight of the fish (g), L = total length of fish (cm) and b = value of constant obtained from weight length relationship (Pauly, 1984).
The value of the condition factor decreases with a decrease in the weight of fish in relation to its length (Bakare, 1970; Fagade, 1979).The factor has been used as an index of feeding intensity, growth (Fagade, 1979), and available environmental conditions (Bagenal and Tesch 1978). The value of the condition 19
factor also changes with the reproductive status of the fish, and the highest values appeared during the spawning and reproductive activity, due to accumulation of fat
(Vazzoler, 1996) and development of gonads (Le Cren, 1951; Angelescu et al.,
1958). A higher value of the condition factor during certain seasons may indicate the state of sexual maturity and degree of nourishment (Gomiero and Braga, 2005).
Variation in the condition factor also appeared between two sexes in certain species. The value of K was reported as 0.787 and 0.859 in male and female elephant fish (Mormrus rume) in the river Ose, southern Nigeria, respectively
(Olabode et al., 2007). The condition factor was reported to be higher in late stages of maturation as compared with the earlier stages of maturation of gonads in female kutum (Rutilus frissi kutum) (Kousha et al., 2009) indicating an increase in the size of gonads under maturation. The value of the condition factor exhibited a gradual increase with the increasing maturity of the gonads and the maximum value corresponded with the maximum development of the ovaries in kutum but the condition factor persisted at higher levels even after recession of the ovaries (Sabet et al., 2009).
2.2. KARYOTYPE
Fish karyotypes are now a day being analyzed in the field of taxonomy and aquaculture. Fish karyotyping have been a subject of extensive studies because of its potential in sex control, better performance and rapid production of inbred lines
(Thorgard and Allen, 1987; Lin and Peter, 1991). The study of fish chromosomes is also being used as one of the models for detecting environmental mutagens and 20
genotoxic pollutants (Kligerman et al., 1975; Manna, 1989) and may help in developing some insight into the inter-population variations.
Since the late 1960s’ there has been an increasing interest in the study of fish chromosomes. A volume of literature is available on the chromosomes of the fishes belonging to family Cyprinidae (Rab, 1981), especially on the commercially important fishes (Al-Sabti, 1985; Zhang and Reddy, 1990; Fister, 1989; Boro,
2001). In the Indian region, Khuda-Bukhsh (1996), Khuda-Bukhsh and Tiwary
(1994) and Khuda-Bukhsh and Chakrabarti (1996, 1999) worked on the chromosomes of Indian major carps, coldwater fishes, silver carp, cat fishes and various other cyprinid and siluroid fishes. Rafique (1992) and Rafique et al. (2000) conducted karyological studies of the subfamily Rasborinae of family Cyprinidae from Pakistan.
Little literature is available on the chromosomes of the fishes belonging to the C. marulius. All the available studies,, however, have recorded 44 as the diploid number of chromosomes of C. marulius (NBFGR, 1998; Supiwong et al.,2009). Reports, however, differ in the number of metacentric, submetacentric and telocentric chromosomes of C. marulius. NBFGR (1998) recorded 40 metacentric and 4 telocentric chromosomes in Indian population of the species, while Donsakul (1991) and Supiwong et al. (2009) have recorded 4 metacentric, 4 submetacentric and 36 telocentric chromosomes in the karytype of C. marulius population maintained in Thailand.
21
2.3. REPRODUCTIVE CYCLE
The range of tolerance of a species to different environmental factors is the narrowest during the reproductive period and hence the reproductive activity of a fish species, like any other organism, requires a specific set of ecological and biological controlling factors. Thus, the species adjusts its reproductive activity to the part of the year when the optimal survival of the young is ensured (Odum,
1974). Under such conditions the species is expected to show a specific set of changes in the somatic and reproductive organs to support the spawning at the set season. Various studies have exploited different variables to judge the reproductive status of the species, so that the spawning period can be defined, which may help in the management of fish in nature and / or under farmed conditions.
2.3.1. Gonadosomatic Index
The size and the activity of the gonads changes with season and the age.
Gonadosomatic index (GSI) is an index indicating the relative development of the gonads (gonad weight) standardized against the total weight. The index has been frequently used to judge the relative development of the gonads (Vlaming et al.,
1982), with the assumption that the gonads are well developed in sexually active individuals and regress during the period of sexual inactivity. The GSI is generally calculated using the formula: GSI = (gonad weight/ body weight) X 100 (Roffda,
1983). For more accuracy and to minimize the effect of changes in the mass of gonads at various development stages, some workers, in the recent years, have tried to refine this formula as: GSI = 100 X gonad weight / (body weight–gonad weight), and have used the equation in their studies (Tracey et al., 2007; Muchlisin et al.,
2010). The eviscerated weight can also be used to further reduce the effect of the weight of visceral contents. 22
Different studies have suggested seasonal variation in the value of GSI, ascribed to the corresponding changes in the reproductive activities (gonadal development) of the species. The GSI values in female kutum (Rutilus frisil kutum) started rising in March reaching the peak values (29.5) in April and exhibited a sharp decline in May (Sabet et al., 2009; Saeed et al., 2010; Kousha et al., 2009).
The values of GSI in male golden rabbitfish (Siganus guttatus) remained below 1.0 during December–April and showed significant increase in May (4.5) and June
(11.1) and a decline in July (8.3) and August (1.4), suggesting spawning in this fish during May–July (Rehman et al., 2000). The spawning season corresponded with higher values of GSI (male 2.1, female 7.8) as compared with spent or immature stage (male 0.3, female 0.8) in Rhabdosargus haffara captured from the Red Sea
(Abuzinadah, 2001).
The study on the GSI variation in Channa gachua from Godavari
(Aurangabad, India) revealed that the female fish maintained a low GSI (6.0-12.0) for the major part of the year. The GSI started rising in June (25.2) achieving to peak value in July (55.7) and followed by a rapid decline in August (34.5)
(Gaikwad et al., 2009) suggesting peak reproductive activity of the species in July.
Similar high peak GSI values have also been reported in male (8.0) and female
(98.8) in the May sample of Capoeta capoeta umbla and these values remained low during June–April period (Erdouan et al., 2002). The values of GSI presented in these studies are very high compared with similar values appearing in literature regarding other specie.
23
In the two sexes of the black rockfish (Sebastes schlegeli), GSI values exhibited peaks during different times of the year (male = October-November; females = April –May), which has been explained by the fact that the mating in the species occurs when the male matures and sperm are stored in the female to fertilize eggs as they are produced (Mori, et al., 2003). This appears to be the species adaptation, and is not probably characteristic of most teleost.
2.3.2. Hepatosomatic Index
Extra energy is required by the fish to start the process of maturation of the gonads and reproductive activity. This energy, obtained through feeding activities, is stored in the body tissues before the onset of reproduction (Love, 1970). The onset of maturation initiates with the accumulation of sufficient energy in the body tissues, mainly in liver (Godo and Haug, 1999) which is spent during reproductive activities.
A linear relation has been reported between the lipids accumulated and the number of the eggs produced in fish stock of cod (Gadus morhua) in Barents Sea
(Marshall et al., 1999). The process of vitellogensis in teleosts also involves hepatic production of the yolk precursor (vitellogenin), which is incorporated into the yolk proteins (lipovitellin and phosphovitin) in the ovaries (Campbell and Idler,
1976; Campbell, 1978; Ng and Idler, 1979; Idler and Campbell, 1980). The production of vitellogenin results in the increase in the liver weight, while the body prepares for reproductive activities. Hepatosomatic index (HSI) has been developed to indicate the relative weight of the liver in comparison with the total weight {HSI = (liver weight / total body weight) X 100} and is sometimes used in 24
the analysis of the fish reproductive cycle and the spawning quality (Vitale et al.,
2006).
None of the studies has reported HSI values for any of the species of the genus Channa. The studies on seasonal variation in the viviparous teleost (black rockfish, Sebastes schlegeli) suggested that the HSI values gradually increase before the onset of the breeding season in both the sexes and its values exhibited a sharp decline with the onset of the breeding activities. In viviparous teleosts, the value of the index remained low during the gestation period (Mori et al., 2003).
2.3.3. Histological Changes
Histological studies on gonads provide more reliable and direct indications of the reproductive status of the organism and hence are more dependable for the analysis of the reproductive cycle (West, 1990). Several studies are available that analyze seasonal variation in the level of reproductive activities in different species
(Murua and Motos, 1998; Saborido-Rey and Junquera, 1998; Kjesbu et al., 2003, etc.), but none is in hand on C. marulius or any other Channa species.
2.3.3.1. Testes
The fish reproductive physiologists, in general have placed more emphasis on the study of histological changes in the female reproductive physiology and relatively fewer studies are available on the male reproductive physiology (Bowers and Holliday, 1961; Koya et al., 2002). The testis in fishes generally appear as a pair of elongated structures, composed of a series of branched seminiferous 25
tubules, which are embedded in the stroma in the fish. The testis mainly comprises of thin-walled tubules or lobules, which contain germ cells (spermatogonia). The spermatogonia divide in clusters and are enclosed in a cyst. The primary spermatogonia (representing the stem cell) are present throughout the year and divide mitotically to produce the secondary spematogonia, which finally produce the primary spermatocyst. The spermatocysts divide by meiosis to form the spermatids, which are finally transformed into spermatozoa (Fishelson et al.,
2006).
Generally four different stages i.e. immature, prespawning, spawning and post spawning (spent), of the testicular development are identified based upon the histological variations, which represent different stages of the reproductive activity of the individual fish (Muchlisin et al., 2010; Koya et al., 2002; Mori et al., 2003;
Rehman et al., 2000). Using such histological classification of the testes, the cyclic change in the reproductive activity has been reported in golden rabbitfish (Siganus guttatus; Rehman et al., 2000), Rasbora tawarensis (Muchlisen et al., 2010) and black rockfish (Sebastes schlegeli; Mori et al., 2003).
2.3.3.2. Ovary
The ovaries (one or commonly two) lie in the upper part of the body cavity of the female fish, almost parallel to the kidney. The shape and the size of the ovary vary with the stages of the sexual maturity (Goswami and Sundararaj, 1971;
Vitale et al., 2005). Ovaries are generally bi-lobbed structures in most fishes with a 26
short oviduct. Each lobe contains ovigerous lamellae, their number and dimensions verifying with growth and reproductive stage of the fish.
Maturation of the egg is a long process that involves complex physiological and biochemical changes (discussed in detail by Fishelson et al., 2006). Maturation is accomplished in the fish oocyte, involving meiotic division, resulting in four cells and oocyte giving rise to two polar bodies. During this process, the enlarged nucleus of the primary oocytes moves towards more peripheral position, when its membrane breaks down and the first meiotic division is completed with extrusion of the polar body. The second meiotic division starts immediately, but is arrested at metaphase (Goswami and Sundararaj, 1971; Masui and Clarke, 1979). During this process, a distinct animal pole separates from vegetal pole, in some species. The yolk also undergoes some type of maturation and becomes less opaque. The oil droplets, when present, coalesce to form one or more larger droplets. Soon after, the mature (secondary) oocyte ovulates out of the follicular envelope, and acquires a jelly coat (Goswami and Sundararaj, 1971). The ovulated eggs are then spawned in water and are almost immediately fertilized.
The ovaries have been generally classified into seven stages of the reproductive activity, (virgin, developing, early maturing, maturing, spawning or ripe, spent and resting) which have been variously used in understanding the seasonal variation in reproductive activity of different fish species (Vitale et al.,
2005; McDermott and Lowe, 1996; Abuzinadah, 2001; Saeed et al. 2010).
27
2.3.4. Steroid Hormone
The development and the activities of the gonads are controlled through the steroid hormones produced in the gonads. The levels of these hormones in the blood stream are indicative of the reproductive status of the gonads and thence the organism. Hormones, levels are though direct indicators of reproductive activity, yet are costly, and need more sophisticated handling, and hence are not frequently exploited for studies on seasonal variations in reproductive activity. The analysis of circulating hormones levels have been used in the analysis of the cyclic variation in the reproductive activities of fish, especially when employed along with histological and GSI variations (Fostier et al., 1983; Zohar et al., 1982; Pankhurst and Carragher, 1992; Carragher and Pankhurst, 1993; Amiri et al., 1999).
2.3.4.1. Testosterone
The androgens have a strong role in different aspects of the reproductive activities of the male fish, which includes the development of the testes. Two steroid hormones, i.e., 11-Ketotestotesterone (11-KT) and testosterone (T), are the main androgenic hormones in fish (Idler and Campbell, 1980; Carolsfeld et al.,
1996; Matsuyama et al., 1991). The androgenic activity of 11-KT has been reported to be 10 to 17 times higher than that of T, and hence 11- KT has been considered to be the real androgenic hormone in fish (Arai, 1967). The conversion of androstenedione to 11-KT, via T and 3-hydroxytestesterone, has been proposed to be the major biosynthetic pathway in fish testes. The conversion of 11-KT from tritiated testosterone by the testes has been reported to be optimum at 6 – 21 o C in rainbow trout (Onchoryncus mykiss) and at 11 – 36 o C in goldfish (Carracious 28
oratus), which suggest that this is a species specific control, depending upon the adaptation range of the species (Kime, 1979).
11-KT has been detected in the blood plasma of males of many teleost species and has been regarded as the major androgen responsible for inducing spermatogenesis (Kime, 1979; Miura et al., 1991; Billard et al., 1982). However, testosterone has been regarded as the major androgen in the Japanese sardine
(Sardinops melanostictus), as only T was detected from the blood of maturing males of this species, and appreciable levels of 11-KT could not be detected
(Matsuyama et al., 1991). In Pacific herring (Clupea pallasii) both 11-KT and T were present in almost equal levels in the plasma of the sexually maturing males
(Carolsfeld et al., 1996). Elevated levels of 11-KT have been recorded in stages when the testis were developed and spermatogenesis was in process, which indicated that this hormone is responsible for controlling spermatogenesis in black rockfish, Sabastes schliqili (Mori et al., 2003).
In male Rhabdosargus haffara the concentration of T showed a gradual increased from immature, through developing and maturing stages of the male gonads and maximum concentration was exhibited at mature stage, while the plasma concentration of testosterone decreased during spawning and spent stage of testicular development (Fostier et al., 1982; Abuzinadah, 2001).
2.3.4.2. Estrogens
The hormonal control of the annual reproductive cycle of females has been established (Abuzinadah, 2001), and the control of oogenesis and egg release is 29
known in many marine fishes (Fostier et al., 1983; Kobayashi et al., 1989;
Pankhurst and Conroy, 1988; Pankhurst and Carragher, 1992; Rosenblum et al.,
1987; Richard et al, 1993; Sabet et al., 2009; Carragher and Pankhurst, 1993).
Variation in the hormone level during the annual cycle or during pre- ovulary period has been reported in many studies by different workers for different fish species (Zohar et al., 1982). The studies conducted on Rhabdosargus haffafa suggested that the plasma level of estradiol was the highest at the time of maturation of ovaries (7.65 ng/ml), but decreased slightly during spawning stage and was low in the spent stage. The blood levels of estrogens were low during pre- vitellogenic stage, and serum level of estradiol-17β started increasing with the appearance of yolk globules in oocytes, indicating a role of estrogens in hepatic synthesis of yolk precursor (Kagawa et al., 1984; Mori et al., 2003). Higher levels of serum estrogens have also been associated with the process of vitellogenesis in different fish species (Campbell and Idler, 1976; Vlaming et al., 1982; Takemura et al., 1991; Takano et al., 1991; Nagahama et al., 1991). The decline in the 17β - estradiol is believed to indicate completion of the vitellogenesis (Kobayashi et al.,
1988), which under the sex-steroid feed-back mechanism allowed a hypothalamus mediated GtH surge (Fostier et al., 1983). No decline in the estrogen levels was recorded prior to oocyte maturation in tilapia, Oreochromis mossambicus (Mac
Gregor et al., 1981). Increase in the level of estradiol was recorded throughout the period of oocyte growth and spawning was recorded, which was associated with the spawning season of this fish species (Cornish et al, 1993; Cornish, 1998). 30
2.3.4.3. Progesterone
The production of progesterone (17-α, 20-β dihydroxy progesterone) by the fish ovary was reported by different workers, including Suzuki et al. (1991). The cyclic fluctuation of the progesterone was suggested in a carp, Cyprinus carpio
(Billard et al. 1982). Progesterone is known to stimulate the last stages of oocyte maturation (Nagahama, 1987; Kime et al., 1992) and has been regarded as an oocyte maturation inducing steroid. The hormone is believed to initiate translation of cyclic mRNA in the oocytes (Nagahama, 1997). The progesterone stimulated ovulation in yellow perch, Persa flavescent, (Goetz, 1983). In many teleosts, the progesterones have a dominant role in oocyte maturation (Goetz, 1983; Nagahama ,
1987; Lee et al., 2002), and increased levels of plasma progesterone have been indicated at oocyte maturation and ovulation (Kobayashi et al., 1985) when peak levels of this steroid hormone appeared (Kobayashi et al., 1987; Kime et al., 1992).
31
Chapter 3
MATERIAL AND METHODS
3.1. STUDY ARE A
The province of the Punjab 30.55 – 31.33 °NL, 71.51-74.21 °E; area =
205344 km2) is the northeastern province of Pakistan. The major part of the province generally represents an alluvial slope flood plan, attitude of around 180m above sea line in the south gradually ascending to around 500 m above sea line in the northern parts (Figure 3.1).
The climate of the province is hot and dry, summer temperatures may touch
48° C in the southern parts and the winter temperatures may drop to below freezing levels for some nights, especially in the northern parts.(Table 3.1)
The summer monsoon (July – August) remains the major source of rainfall in the province while winter monsoon are scanty. The area witnesses annual fluctuations of rainfall, with 3-4 years of good rains followed by some equal number of years with low rainfall. Flash floods occur during August – September.
Rapid glacier melts with sudden increase in temperature during recent years sometimes also create flooded conditions in the rivers (Roberts, 1977; Rafique
2007). There are five rivers (Indus, Jhulum, Chanab, Ravi and Sutluj) flowing through the province, in north – south direction. A number of tributaries and hill torrents join these rivers at different places. A network of canals has been developed with dams and barrages constructed at suitable places. 32
P U N J AB
Figure 3.1: The hydrographical map of Pakistan showing all rivers and their tributaries and the densely populated Punjab province
33
Table 3.1: Monthly temperature range (o C) (maximum-minimum) of north (Islamabad) central (Lahore) and southern Punjab, (Bahawalpur), between May 2005 and April 2007 (Source: Pakistan Meteorological Department)
Month Bahawalpur Lahore Islamabad
May 2005 41 - 23 40-- 20 35-17 June 46 - 27 45 - 20 45-20 July 45 - 23 37 - 20 28 - 31 August 39 - 25 37 - 20 36 - 20 September 35 - 23 37 - 20 36 - 18 October 34 - 17 35 - 10 35 - 08 November 29 - 10 28 - 02 27 - 03 December 23 - 03 28 - 00 22 - 00 January 2006 20 - 02 25 - 02 22 - 02 February 22 - 07 30 - 07 26 - 05 March 27 - 15 33 - 08 31 - 07 April 30 - 19 37 - 11 40 - 11 May 40 - 22 43 - 20 42 - 18 June 45 - 28 42 - 20 40 - 18 July 41 - 27 40 - 21 38 - 21 August 37 - 27 37 - 20 36 - 21 September 36 - 24 35 - 17 35 - 16 October 33 - 17 35 - 15 33 - 13 November 28 - 11 28 - 05 23 - 05 December 22 - 04 22 - 01 20 - 03 January 2007 21 - 05 25 - 00 25 - 00 February 22 - 13 26 - 05 22 - 06 March 27 - 14 37 - 05 31 - 07 April 31 - 19 41 - 20 38 - 11 34
Sol (C. marulius) is an indigenous fish species distributed (Figure 3.2) from
Chashma downstream in the river Indus (Mirza, 1999; Rafique, 2007). The species is present in natural waters only however, there is a generally increasing trend of stocking this species in fish ponds to control unwanted / trash fish because of its carnivorous habit. This exercise is especially common in the southern Punjab, where the progressive farmers exploit the species to control the recently introduced exotic tilapia (Oreochromis. mossambicus) in their ponds. However, availability of the seed of this fish species and low survival rates (attributable to cannibalism) remain the main constraint in its introduction into the regular farming system. The species spawns naturally and frequently in the ponds appearing along the river
Indus when it passes through the southern districts of Dera Ghazi Khan (Head
Taunsa) and Muzaffar garh. (Plate 3.1) Fish farmers of the area collect seed of this species, with the help of local fishermen, which is stocked in the nursery ponds, and later introduced into selected ponds having culturable fish. Sol is also netted from the impoundments present around Tounsa Lake by local fishermen and sold in the market and the present stock of this fish is limited.
3.2. MORPHOMETERIC ANALYSIS
A sample of 21 specimens of freshly caught adult (both sexes) identified C. marulius (sol) were randomly collected out of the catch of the fishermen engaged in their regular netting exercise at different locations of the Taunsa Barrage lake
(30o 30’45 38” NL, 70o 51; 27 41”E; Dera Ghazi Khan, southern Punjab, Pakistan).
The samples of both sexes were collected in three successive nettings carried out during from December 2006–February 2007. 35
Plate 3.1. Views of the Taunsa Barrage (upper) and Head Mole Dhand (lower) 36
The fish specimens were immediately transferred to the field laboratory established close to the sampling site. Different measurements recorded as early as possible, using top loading digital balance (Sertorius, with minimum count of 0.1 g) for wet weight, and meter rod (minimum count 1 mm), divider, thread, and
Perspex tray method for length. The specifications of different morphometric variables were standardized as following. (Figure 3.2)
i. Total wet weight
ii. Total length (TL): From tip of the snout to the tip of the caudal fin.
iii. Standard length (SL): From tip of snout to the structural base of the
caudal fin
iv. Head length (HL): From the tip of the snout to the end of the
opercular bone with both the jaws closed
v. Pectoral fin length (Pel.FL): Distance from extreme base of the rays
to farthest tip.
vi. Pectoral fin distance from mouth tip
vii. Pelvic fin length (PEL): Distance from extreme base of rays to the
farthest
viii. Pelvic fin distance from mouth tip
ix. Dorsal fin length (DFL): From the structural beginning to the end of
the dorsal fin 37
x. Dorsal fin height (DFH): From the extreme base of the largest fin
ray to its farthest end
xi. Dorsal fin distance from mouth tip
xii. Ventral / anal fin length (VFL): From the structural beginning of the
ventral fin to the end of the ventral fin
xiii. Ventral fin height (VFH): From the extreme base of the largest fin
ray to its farthest end
xiv. Caudal fin length (CFL): From the structural base of the caudal fin
to the tip of the caudal fin
xv. Mouth width
xvi. Eye diameter (ED): Distance across the visible portion of the eye
ball
xvii. Fin ray count: Number of rays in the fins; pectoral fin rays (Pel.
FR), pelvic fin rays(PFR), dorsal fin rays (DFR), ventral fin rays
(VFR) and caudal fin rays (CFR) xviii. Lateral line scale (LLS): Scales along the lateral line from end of the
head to the beginning of the caudal fin
xix. Above lateral line scales (ALLS): Scale count from lateral line to
beginning point of dorsal fin
xx. Below lateral line scale (BLLS): Scales from lateral line to the
beginning point of ventral fin
38
Figure 3.2: Schematic representations of the body measurements and head measurement of Channa marulius : TL (total length),SL (standard length), HL (head length), ED (eye diameter), DFL (dorsal Fin length),D FH (dorsal fin height), CPL (caudal peduncle length), VFL (ventral fin length),VFH (ventral fin height), LL (lateral line), PelFL (pelvic fin length), PFL (pectoral fin length), PelFDM (pelvic fin distance from mouth tip), PecFDM (pectoral fin distance from mouth tip)
39
Record of direct counts on meristic characters was directly recorded.
Different statistical constants (mean, standard error of mean, coefficient of variation, range, 95% confidence limits of mean etc.) were calculated for each individual variable using conventional statistical procedures (Sokal and Rohlf,
1995) using computer software MiniTab-15. The linear regressions of each variable with standard length was also calculated, and value of regression constant (b) calculated.
3.3. KARYOTYPE
3.3.1. Preparation
Selected specimens of C. marulius (n = 7 15-20 cm long), collected from the river Indus in and around the Head Taunsa, (Punjab, Pakistan) and maintained in aquarium (30'X18'12' size), were used for karyological studies following
Oellermann and Skelton (1990) with slight modifications. Each fish caught from the aquarium by a small hand net, and weighed using top loading balance (sartorius minimum count 0.01 g), were given 0.01 ml/g body weight of 0.1 % colchicine
(100 mg /100 ml distilled water) solution through intramuscular route using 27 gauge syringe. The injected fishes were maintained for 4-10 hours in a separate aquarium under normal conditions, when gill arches were removed and teased apart. Gill tissues thus removed were placed in 0.4% potassium chloride (KCl) hypotonic solution for 40 minutes. This treatment helps cells to swell up resulting in a better spreading of the chromosomes (Manna, 1989). The hypotonic solution was decanted and tissues rinsed in a freshly prepared fixative (3 parts ethanol/ 40
methanol: 1 part glacial acetic acid). After thorough rinsing, the tissues were left in the fixative for a complete fixation.
For slide preparation, staining and preservation the method devised by
Rafique (1992) was adopted. Slides were cleaned by boiling in a detergent for 20 minutes, rinsed thoroughly in tap water, dipped into two changes of 90% ethanol and then swirled in distilled water. The slides were dried in the oven at 50 0C.
Clean and dry slides were placed on a slide warmer adjusted at 60 °C. The fixed tissue was dropped on a clean and dry glass slide, allowing it to dry and stained covered with cover slip. The prepared slides were observed under light microscope
(OLYMPUS BH-2) at high power (100 X) using oil immersion. Edges of the cover slips of the slides having good spreads were sealed with the nail polish and maintained for further studies and photography.
The cells having good metaphase spreads were photographed using a 35 mm camera fitted with automatic film advance on OLYMPUS BH-2 light microscope attached with an automatic exposure system with built-in microcomputer. The negatives were developed in pepitol developer for 2-3 minutes at 3000 X. The photographs were then put into the fixative (250 g sodium thiosulphate + 50 g potassium meta-bisulphite + 5 ml acetic acid + 1 liter of water) for 30 minutes. The photographs were thoroughly washed in tap water to remove any traces of developer or fixative and dried on a photograph drier.
41
3.3.2. Analysis
The diploid chromosome number was determined by examining photographs of several well-spread metaphases. The modal number was taken as the diploid chromosome number of the species.
Metaphase chromosomes of a species were arranged in decreasing order of size, keeping in view the placement of centromere to develop a karyotype. During preparation of karyotypes, homologous chromosomes were paired on the basis of the similarity in their morphology and size. The homologous pairs were arranged in descending order of their sizes and assigned number in consecutive order, the largest regarded as pair 1. Each chromosome of the karyotype was also represented by a specific number in consecutive order.
3.3.3. Chromosome Classification
Individual chromosomes and the homologous pairs were classified as metacentric, submetacentric and telocentric using the location of the centromere and the arm ratio between the lengths of two arms of the chromosomes (arm ratio:1
= metacentric, < 1-0.5 = submetacentric, < 0.5-> 0 = subtelocentric, and 0 = telocentric) as proposed by Levan et al (1964).
3.4. GROWTH
3.4.1. Seed Procurement
Around 500 randomly selected identified fingerlings of C. marulius, were procured out of the stock being maintained by Khalid Arain Fish Farm (a private fish farm located at Moza Wasandaywali, District Muzaffargarh, southern Punjab) 42
at the end of May 2005. Every attempt was made to save the fingerlings from the netting injuries or stress, and only vigorous, uninjured and healthy looking fingerings were accepted. The fingerlings were claimed to be collected from the
Head Mol-Dhand (one of the pond of the main barrage lake of Head Taunsa,
District Dera Ghazi Khan, south Punjab) through different attempts undertaken during April 2005, and were being maintained under the normal farm conditions along with similar stocks of other fish. The stock at the time of procurement was believed to be around 2 months of age.
The sol fingerlings, thus procured, were first transported to Fish Nursery
Unit, Muzaffargarh (maintained by the Provincial Fisheries Department, located at some 35 km from the farm) in an open hauler filled with water taken from the farm and covered with net under minimum transportation stress. The seed was conditioned in the hatchery concrete tanks of the nursery unit for 10 hours. The seed was then further transported to Chenawan Fish Hatchery (District Gujranwala, located in central Punjab some 12 hours drive from the Muzaffagarh Nursery
Unit), in polythene bags (90 cm X 60 cm), in a mini truck. Each bag carried around 30 fingerlings (weighing around 100 g) and filled up to 1/3rd with water, leaving some 2/3rd space which was filled with oxygen gas.
Two earthen fish ponds (20 m X 15 m, 1.3 m deep) had already been earmarked by the hatchery administration (Punjab Fisheries Department) and adequately prepared to receive the sol fish seed. The fingerlings were carefully transferred to the fish ponds, after due acclimatization to the hatchery conditions.
Due care was taken to save the fingerlings from injury and transfer shock. The 43
activities of the fingerlings at the Chhenawan hatchery ponds were closely monitored (over the next 48 hours after stocking of the fingerling) and dead fingerlings were removed as and when noticed.
3.4.2. Rearing
The fingerling fish were reared using conventional rearing methods in the ponds. To increase the productivity, the ponds were enriched with chemical fertilizers {(urea = 20 kg / ha; Di-ammonium phosphate, (DAP) = 15 kg/ ha)} and cow dung (12,000 kg/ ha) before the first stocking. Supplementary feed having
30% and 25% protein level for the first 6 months and containing 25% protein for rest of the study period prepared by using the formula of Khan, (2004) {fish meal,
15% and 11%; rice bran, 21% and 27%; maize gluten, 21% and 27%; soybean meal, 15% and 11%; ground nut meal, 15% and 11%; vitamin premix = 1.5%, vegetable oil = 7%} was provided twice a day (at 9 AM and 2 PM. The ration of supplementary feed was adjusted on a monthly based sampling of the fish stock and maintained around 3 -5 % of the fish biomass in the pond.
Regular monitoring of the water quality of the experimental ponds was maintained throughout the study period. Water temperature (using digital thermometer, Inolab WTW, Germany) was recorded at around 10.00 AM daily, while pH (using portable field digital pH meter, Inolab WTW, Germany) was recorded on a monthly basis (first week of each month) directly in the fish rearing ponds. The samples of water were collected on monthly basis and used in determining the levels of ammonia (spectrophotometric method) and biological oxygen demand (BOD; using the volumetric method). For determining BOD 44
potassium dichromate, (K2Cr2O7, Merck) was used as strong oxidizing agent, and volumes of K2Cr2O7 used were measured. The information thus collected was used to maintain desirable culture conditions at the rearing pond and necessary remedial measures were adopted whenever any abnormality was detected in the water quality. The fingerlings/ fish found dead in the pond were removed from the pond, as and when detected.
3.4.3. Sampling and Measurements
The fish were maintained in ponds for 14 months and sampled at almost same date during the last week of each calendar month, starting from May 2005.
The fingerlings were allowed to settle under the pond conditions of the Chhenawan
Fish Hatchery before the first sampling. Drag nets (mesh size of 2.5 cm) were used to catch the fingerlings/ fish from the pond. The first two samplings efforts were directed to capture the maximum number of the fingerlings through repeated dragging of the net. However, as repeated netting is prone to inflict injuries on the fish stock, each pond was seined twice only during the rest of the monthly samplings, but the size of the sample was kept at above 30 fish.
The sampled specimen were maintained close to the pond environment, as much as possible, to avoid a transfer shock. The sampled fish was taken out of the water and immediately weighed using digital top loading balance (Shimadzu 120
HA, Germany; minimum count 0.1 g), and total length recorded using graph paper method and Perspex measuring tray (minimum count = 1 mm). Due care was taken to cause minimum stress to the individual fish and to completely avoid injury. 45
General physical health of the individual fish was observed and the fish was released back into the stocking pond, after due acclimatization. The unhealthy looking fish were not included in the sampling and were removed from the stock also.
3.4.4. Analysis
The data on the length and the weight of each sampled fish for each monthly sample was pooled to calculate different statistics, i.e., mean, standard error of mean (SEM), range, coefficient of variation, and 95% confidence limits of mean (95% CL), separately for the two variables (Sokal and Rohlf, 1995), using computer software (Microsoft Excel). The age of the first sample was taken as two months, assuming that the fingerlings netted in April hatched in March (first sample in May). Linear regressions of the natural transformed values of length and weight with age were calculated to work out the regression equation and coefficient for length and weight with age separately.
Difference between the means (weight or length) of two consecutive months was regarded as weight or length gained during the month. Specific growth rate (SGR) for weight was calculated by the formula: In W(t) – In W(o)*t-1 (where
W(t) = final weight, W(o) = initial weight, t = 30 as standard duration of month).
Specific growth rate (SGR) for length was calculated by the formula; In L(t) – In
L(o) / 30 where L(t) = final length after specific duration, L(0) = initial length of specific period and t = 30 taken as standard duration of the month.
46
Length weight relationship was also calculated for each month following
Pauly (1983), as: W a Lb = ln W = ln a + ln L . b {(where ln = natural log, W = wet weight (g), L = total length (cm) a = species specific constant (intercept) and b = length exponent (slope)}. Condition factor (K) was calculated by formula (Pauly,
1984): K = W / Lb, where K = condition factor, = W = wet weight (g), L = total length (cm) b = species specific length exponent (slope) taken from the length weight-relationship.
Analysis of covariance (ANCOVA) was carried out using computer software (SPSS) for determining the significance (p = 0.05) of the effect of different variables taking age (months) as categorical variable, log natural weight as dependant variable and length (log natural) as covariate.
3.5. REPRODUCTIVE CHANGES
3.5.1. Sampling
Healthy looking adult C. marulius (length 745cm, weight 7725g) were collected using drag nets from different ponds associated with the Taunsa Barrage
Lake (Dera Ghazi Khan, South Punjab, Pakistan) during different calendar months
(December 2006, February, March, April, May, June, September 2007) of the year, with special emphasis on the spring /summer (Febuary –June) months, which have been regarded as the reproductive period of the species. A sample size of seven (7) from both sexes was initially sought for each calendar month to give 99% confidence to the sampling. However the number of fish actually available for studies remained below level due to small size of catch of fish of this species. Each 47
of the sampled fish was anesthetized using MS 222 (Sigma) and taken to the field laboratory for further study and sample collection.
i. Wet weight (using top loading balance, Shimadzu 120 HA, Germany,
minimal count 0.1 g) and length using measuring scale (minimal count 1
mm) were recorded immediately after the collection of the sample at the
sampling site.
ii. A volume of 2.5 ml blood sample was collected soon after the capture of
the fish using cardiac puncture technique (efforts to collect the blood from
the ventral vein did not succeed, especially in smaller fish),using
heparinzed sterilized 5 ml disposable syringe, and transferred to EDTA
treated clean and sterilized blood sampling tubes. The blood samples were
taken to the field laboratory where it was centrifuged (Labofuge –I HL–
120 Germany) at 3,000 rpm for 10 minutes. The serum part of the blood
was separated and collected in jets (2 ml), which were taken to the
laboratory under ice cooled conditions and stored at -140C for the
hormonal analysis.
iii. Each fish sampled was then dissected through a mid ventral cut. Gonads
and liver were carefully separated from the rest of the visceral mass and
weighed with the portable digital mini-balance (Shimadzu 120 HA,
Germany; minimum count 0.1 g). Samples of appropriate size of gonads
were then preserved in Bouin’s fixative (Saturated picric acid 3,000 ml;
formaldehyde 1,000 ml; glacial acetic acid 200 ml) placed in separate 48
vials and taken to Islamabad (Pakistan) and kept for further processing for
histological studies.
3.5.2. Histological Studies
The field fixed tissues of the gonads were taken out of the Bouin’s fluid and processed for histological studies following Gretchen (1984). The fixed tissue samples were given repeated washes with 70% commercial grade ethyl alcohol till the Bouin’s fluid was completely removed. The tissues were than passed through ascending grades of alcohol, and given repeated washes with the absolute alcohol to ensure complete removal of water from the tissue. The dehydrated tissue was kept in cedar wood oil (Merck) for 10 hours and cleared with xylene (Merck). The tissues were then embedded in the paraffin wax (Merck) (melting point 50-57oC).
Sections of the embedded tissues were cut (6 µm thick) using microtome (Rotatory, manual China). The sections were placed on a clean glass slide, wax removed by mild heating and placing in xylene, The tissue was further processed through grades of alcohol for differential double staining (eosine and haematoxyline) and preparation of permanent slides using Canada Balsam.
The permanent slides were then studied for different histological features under the light microscope (Swift M 7000 D). Photomicrographs of the slides were prepared for further detailed examination using light microscope (100 X, oil emersion, Swift M 7000 D). Each slide was catagorized into one of the class of the reproductive activity: 49
Testes (following Rehman et al., 2000):
I. Immature: Seminal lobes totally occupied by clusters of
spermatogoania.
II. Pre-spawning: Spematocytes constituting > 50% of the germ cells, fewer
spermatogonia.
III. Spawning: Having higher proportion of spermatids and spermatozoa
dominating with decreased percentage of the spematocytes.
IV. Post-spawning: No spermatozoa; with sporadic appearance of spermatogonia
and spermatocytes.
Ovaries (following Saeed et al., 2010):
I. Virgin or immature: Oogonial nest small with dense basophilic cytoplasm
with central nucleus and few large nucleoli around the
edge.
II. Developing or early maturing stage: Nucleus increased in size and multiple
nucleoli appearing and weakly stained area
(circumnuclear ring, CNR) appearing.
III. Early maturing: Large visible eggs, CNR moving towards outer part of the
cell and large number of oocytes
IV. Late maturing stage: Large number of oocytes with some ripe ova. 50
V. Spawning or final maturation stage: Ripe ova dominating (chorion thicker
and nucleus migrating towards the animal pole)
dominant.
VI. Spent stage: Large number of empty follicles (post-ovulatory follicles;
oocytes in early developing stage.
VII. Resting: All oocytes in early development stages. Some post ovulatory
structure indicating previous spawning.
The frequencies of individual of each monthly sample falling in different
classes of reproductive activity were directly analyzed to develop a pattern of
seasonal variation for reproductive activity
3.5.3. Hormonal Profile
The serum samples separated from the blood collected from different adult
fish during different seasons and stored at -14oC were used for the determination of
the levels of three major gonadal hormones (males = testosterone; female =
estradiol and progesterone). The concentrations of these hormones were
determined by using Immunotech Radio-immunoassay kits, (supplied by
IMMUNOTECH SAS 130 av Marseille Cedex 9, France). All these kits made use
of (iodine isotope) (I 125) labelled hormones, which are basically intended for use
with human samples. The concentration of hormone were then calculated using 6
readings of radioactivity using Beckman Gamma 8500 Microprocessor Counter.
51
3.5.4. Analysis
The changes in the reproductive activity were analyzed separately with different variables. Gonadosomatic index (GSI = 100 X (wt of gonad / body weight of fish) and hepatosomate index (HSI = 100 X (weight of liver / body weight of fish) were calculated for individual fish The individual values for different specimen collected during different sampling calendar months were pooled and different statistics constants for range, mean, 95% confidence limits of mean and standard error of mean, were calculated for different variables for each calendar month. The differences between different samples were judged by application of
ANOVA. The Pearson correlation coefficient (r2) were calculated for analysis of association between different variable of reproductive activity.
Analysis of covariance (ANCOVA) was carried out (using computer software SPSS) to determine the effect of months (independent variable), on the weight of gonads / liver (dependant variable), using length as covariate. Based on adjusted means of gonads / liver weight, pairwise comparisons between months were calculated by applying multiple comparison Bonferroni test.
The hormone levels of samples collected during different months were pooled for calculation of mean and standard error of mean for each month.
Monthly differences in level of hormonal variables (estradiol, progesterone and testosterone) were analyzed by Analysis of variance (ANOVA) followed by multiple comparison Scheffe test for assessment of significant differences between samples of different calendar months (Sokal and Rolf, 1995 and SPSS computer software). 52
Chapter 4
RESULTS AND DISCUSSION
4.1. STOCK COMPOSITION
The present identification of the specimen of C. marulius is based upon the morphological characters (Mirza, 1999). No study is available on analysis of mansural characters and supportive karyological analysis to confirm the taxonomic status of this population and the possible variation of this population from the other populations of this species distributed along its distribution range. The study of the biology of the species requires a better identification of the stock / population / ecotype under the analysis for increasing its predictive value when exploited for other stocks. For this purpose, the analysis of morphometric and meristic variable alongwith karyotyping can be useful.
The present study focused upon the analysis of the mansural variable on relatively smaller sample of individual of the species (21), which could be collected, followed by the karyological studies on selected individuals (7). This is a preliminary study aimed at confirming the taxonomic identification of this population of C. marulius and demands further studies for better understanding possible interstock variations.
53
4.1.1. Morphometry
The summary of the statistics calculated for 16 morphometric variables of
21 adult C. marulius sampled from the shallow water bodies of Taunsa Barrage
Lake (southern Punjab, Pakistan) between December 2005 and February 2006 are presented in Table 4.1.
The values of coefficient of variation were very high for wet weight higher
(> 40%), high for standard length, total length, pectoral fin length, dorsal fin length, ventral fin length, ventral fin height, and caudal fin length, dorsal fin length, mouth width and head length, pectoral fin distance, pectoral fin length, and eye diameter (10–40%). Variability was very low for dorsal fin from the mouth tip
(7%).
The analysis on 8 different meristic variables of the samples of C. marulius under present study (Table 4.2), suggested a relatively low variability for all the variables as indicated by low coefficients of variation. The coefficient of variation calculated for all the variables ranged between 2–10%, except for “Below lateraline scales” where it was10.65 %.
The linear regression equations of different morphometric and meristic variable against standard length (regarded as predictor of growth related changes) are presented in Table 4.3. There was a significant positive linear regression of all the morphometric variables with the length. Such a regression was however not significant for different meristic variables. 54
Table 4.1: Summary of different morphometric variables of adult Channa marulius captured in December 2005 –February 2007 from Taunsa Lake (southern Punjab, Pakistan). lengths in “cm”, and weight in “g”, n = 21 for all variables.
95% CL CV Variables Mean±SEM Range of mean (%)
Total wet weight 1687.00±57.02 101.30-8000 1567-1800 121.94
Total length 54.90±3.84 25.00-92.50 42.92-62.92 32.06
Standard length 47.23± 3.39 21.50-80.00 40.15-54.31 32.88
Head length 10.85±0.58 6.00-16.00 9.64-12.06 24.33
Pectoral fin length 7.01±0.53 4.20-12.20 5.91-8.11 34.95
Pectoral fin distance 13.84±0.40 11.50-16.80 13.00-14.67 13.29 from mouth tip
Dorsal fin length 32.83±2.66 19.60-61.50 27.28-38.38 37.10
Dorsal fin height 3.22±0.20 2.20-5.00 2.88-3.63 28.26
Dorsal fin distance 13.20±0.21 7.56-17.00 12.78-13.62 6.59 from mouth tip
Pelvic fin length 4.90±0.21 3.00-6.00 4.48-5.32 19.59
Pelvic fin distance 12.38±0.38 10.00-19.00 11.5-13.17 14.14 from mouth tip
Ventral fin length 20.77±1.52 13.00-37.00 17.10-23.94 33.51
Ventral fin height 2.50±0.18 1.30-4.50 2.12-2.87 32.40
Caudal fin length 7.20±0.58 3.50-12.50 5.99-8.41 37.08
Mouth width 5.50±0.29 3.70-8.70 4.90-6.10 24.55
Eye diameter 1.24±0.05 0.80-1.70 1.14-1.34 18.48
SEM: Standard error of mean CV: Coefficient of variation CL: Confidence limit
55
`Table 4.2: The summary of different meristic variables of adult Channa marulius captured in December 2005 –February 2007 from Taunsa Lake (southern Punjab, Pakistan) n = 21 for all variables
Variables Mean±SEM Range CV
Dorsal fin rays 53.0±2.57 51–55 2.22
Ventral fin rays 33.6±2.53 32–35 2.59
Pelvic fin rays 7.43±0.15 7–9 9.25
Pectoral fin Rays 5.3±0.13 4–6 6.70
Caudal fin rays 13.7±0.18 13–15 6.02
Lateral line scale 66.0±0.68 60–72 4.72
Above lateral line scales 8.5±0.11 8–9 5.93
Below lateral line scales 12.5±0.29 10–16 10.63
SEM: Standard error of mean CV: Coefficient of variation
56
Table 4.3: Regression of different morphometric and meristic characters against standard length in Channa marulius captured from Taunsa Lake (southern Punjab, Pakistan). All measure in “cm”.
Variables Mean ±SEM R2 Regression Equation
Head Length 10.85 ± 0.58 0.86 HL = 0.7101X – 0.3465
Pectoral fin length 7.01 ± 0.53 0.82 Pec F. L.= 0.88156X – 1.4811
Pectoral fin distance 13.84 ±±0.40 0.47 PecFDM = 0.2586X + 1.5246 from mouth Dorsal fin length 32.83 ±2.66 0.63 DFL = 0.5786X + 0.0858
Dorsal fin height 3.22 ± 0.20 0.82 DFH = 0.7523X – 1.729
Dorsal fin distance from 13.20 ± 0.21 0.99 DFDM = 0.681X – 0.0506 mouth tip Pelvic fin length 4.90 ± 0.21 0.83 PelvFL = 0.6387X – 1.0455 Pelvic fin distance from 12.38 ±0.38 0.82 PelFDM = 0.174X+ 1.9573 mouth tip Ventral fin length 20.77 ± 1.52 0.84 VFL = 0.8869X – 0.3124
Ventral fin height 2.50 ± 0.18 0.91 VFH = 0.8937X – 2.5178
Caudal fin length 7.20 ±0.58 0.98 0.9668X – 1.7662 Eye diameter 1.24 ±0.05 0.64 ED = 0.4855X – 1.650 Mouth width 5.50 ±0.29 0.58 MW = 0.5395X – 0.3742
Pelvic fin rays 7.43 ±1.65 0.1319 PecFR = 0.0961X – 1.626
Pectoral fin rays 5.30± 0.13 0.0218 PFR = 0.0497X + 1.4793
Dorsal fin rays 53.0 ±2.57 0.0093 DFR = 0.0075X + 3.9485
Ventral fin rays 34 0± 2.53 0.1001 VFR = 0.0247X + 3.4206
Caudal fin rays 14.0 ± 6.07 0.1466 CFR = 0.071X + 2.3467
Lateral line scale 66.0±4.71 0.2077 LLS = 0.0662X + 3.9369
Above lateral line scale 9 0± 5.67 0.0563 ALLS = 0.0437X + 1.975
Below lateral line scale 13.00 ± 10.23 0.0102 BLLS = 0.0321X + 2.4002 SEM: Standard error of mean 57
The values of the morphometric and meristic variables are species specific, depending upon its genome, and vary with age and sex. These variables therefore have a taxonomic value and are exploited for identification of the species and in identifying inter-specific differences. However, changes in the values of these variables also relate to the environmental conditions, like, food, temperature, rearing conditions, seasons, etc. (Boverton and Holt 1959; Jakupsstovu and Haug
1988; Bromley 1989). The morphometric variables exhibit wider variations as compared with the meristic variables, the later (meristic variables) having a higher taxonomic value, while the former are more under the control of age and other environment related factors.
A number of studies are available on morphometric and meristic characteristics of different fish species. However, none of references concerns the morphometric characters of C. marulius, except that the length of the pectoral fin is about half of the head length (Talwar and Jhingran, 1992). The pectoral fin in the present sample is about 64% of the head length. Talwar and Jhingran (loc cit.) have given the meristic characterization of this species. They concentrated on the number of rays in the dorsal fin (45–55), pectoral fin (16–18), pelvic fin (6), caudal fin (13-16) ventral fin (6) and also the number of lateral line scales (60-70). The number of the dorsal fin rays (51-55, mean 53, SEM 2.6), caudal fin rays (13-15, mean, 14, SEM, 6.1) and lateral line scales (60–72, mean 66, SEM 4.7) of the present sample are within the ranges described by Talwar and Jhingran (1992).
However, the numbers of the pectoral fin rays of the present sample (4–6, mean 5,
SEM 1.2) remain considerably lower than those of the previous sample. The 58
sample of Sol under the present also have much larger number of the ventral fin rays (32-35, mean 34, SEM 2.5) as compared with Talwar and Jhingran (loc cit) sample where it was constant (6) with no described variation. The present sample of the fish is different from that of Talwar and Jhingran (loc cit) only with regard to the length of pectoral fin, both in its length (relatively longer compared to head length) and in the number of rays (fewer) and pelvic fin rays (remarkably more).
This suggested that the present sample of the fish represents C. marulius though has a longer pectoral fin and higher number of pelvic fin rays, which can be ascribed to the subpopulation or ecotype variations.
The present study can act as a base line reference point for the species, to be used in future studies and detailed description of the species. However, the present data needs to be taken with care, as it concerns a sample collected during winter from one locality. Further the size of the present sample (n = 21) of the fish is comparatively small as may be required for sampling the population for such studies. However, keeping the size of the fish and the capture (2-3) per day from the sampling site, the present size of the sample may be considered as adequate.
The present sampling could not collect the sol longer than 92.5 cm, weighing 8,000 g (8 kg), though the fish measuring 120 – 122 cm (Murugesun, 1978) and 180 cm
(weighing 30 kg, Talwar and Jhingran, 1992) have been reported previously. It appears that the records of Talwar and Jhingran (loc cit) are some odd records and do not represent the normal values and probably concerns some old fish maintained in some farm. The values of maximum length and weight, available from the present study, probably do not indicate the maximum attainable length and weight 59
under the physic-biotic conditions of this part of the range of distribution of sol and
/or its genetic potential, as the fish stock of the sampling area experiences regular commercial netting during winter.
The general information available on the spawning and breeding seasons of this species in the area (April, present study) may suggest that the fish in the
December catch were around 7 months of age, and hence the present sample may include fish samples of the previous breeding season, which still had to achieve maturity. Present sample thus includes the fish which are still immature and hence does not totally represent the sample of the adults.
Higher values of coefficient of variation and significant values of regression coefficients for the morphometric variables as compared with the meristic variables suggest that the meristic variables have a higher taxonomic value, as compared with the morphometric variables, which appear to be more under the control of age and other environmental related changes and hence have a lower taxonomic value.
4.1.2. Karyotype
Plate 4.1 shows the mitotic chromosomal spread of C. marulius and the karyotype of this species is presented in Figure 4.2, showing the chromosomes in a descending order of sizes. The count of the chromosomes in different metaphase chromosome spread suggested a 2n number of 44, which could be organized into
22 homologous pairs (n = 22) for the fish species / population under the present study. Three previously studies on C. marulius (Donsakal, 1991; NBFGR, 1998; 60
(a) (b)
Plate No. 4.1: Spread of the mitotic metaphase chromosomes of Channa marulius captured from Head Taunsa (southern Punjab, Pakistan) a, without clearing, b. after clearing
61
Figure 4.1: A karyotype of Channa marulius captured from Head Taunsa (southern Punjab, Pakistan). (bold numbers above denote the number assigned to homologous pair and small numbers below denote the number assigned to individual chromosome)
62
Supiwong et al; 2009) have also suggested the 2n number of 44 for the species. This suggests that the fish sample under the present study belongs to C. marulius. This confirms our previous observations on general morphology along with morphometric and meristic analysis, suggesting that the sample exhibit a good degree of similarity in the majority of variable to justify assigning this population to the C. marulius.
The karyotypic analysis suggests that all 44 chromosomes are metacentric and no submetacentric, telocentric or subtelocentric chromosome was observed.
The fundamental arm number (FN) of the present population of C. marulius has been calculated as 88 (2 X # of metacentric chromosome). The present results are not in conformity with any of the previous studies. The studies on the stock of C. marulius maintained in Thailand indicated a predominance of telocentric chromosomes (36) with some submetcentric (4) and metacentric (4) (Donsakul,
1991; Donsakul and Wichian, 1991; Supiwong et al, 2009). The karyological analysis of the population of the species from India revealed the presence of 40 metecentric and 4 telocentric chromosomes (NBFGR, 1998). The population of C. maruilus of the southern Punjab, Pakistan, (present study), is closer to the Indian population, having no telocentric chromosomes and having all metacentric chromosomes. Intrapopulation differences have also been recorded under the present studies on mansoral character, which appeared confirmed through the karyological studies A number of studies are available on different fish species where the diploid chromosome number though remains same, but the relative number of different types of the chromosome is different for their different 63
populations (Rishi, 1976; Tripathi and Sharma, 1987; Rafique, 1992). These discrepancies can be ascribed to excessive chromosomal contractions as a consequence of high dose, or over exposure to cholchicine, improper fixation of the tissue, difference in method of chromosomes preparation and classification
(Zhang and Reddy, 1990). However, such variation can also be caused among different populations of the species due to chromosomal changes followed by isolations during the evolutionary history of the populations.
Channidae is one of the advanced families of freshwater teleost fishes. The species belonging to this family originated in the south Himalayan region of the
Indian subcontinent at least 50 million years ago, during the early Eocene epoch
(Bohme, 2004). This characteristic is also indicated in the karyotyping of this species having all metacentric chromosome and no telocentric chromosome. The telocentric chromosomes are considered the most primitive chromosomes
(Morescalchi, 1975; Campos Cuevas, 1997). The presence of a majority of the telocentric chromosomes in Thailand population of C. marulius (Donsakal, 1991;
Donsakal and Whichia, 1991; Supiwong et al; 2009) is hard to explain under this logic.
4.2. GROWTH
4.2.1. Length:
The available data on the change in the body length with the increasing age has been presented in Table 4.4 (Figure.4.2). The table and figure suggest that the average length of 7.34 ± 0.03 cm at the age of 2 months gradually increased to 64
Table 4.4: Age related changes in length of Channa marulius maintained in earthen ponds at Chenawan Fish Hatchery
Age n Length 95% CL CV LG DGR Mean ± SEM Mont (cm) % cm/mont h h 2 156 7.34 ± 0.03 5.04 0.14 3 171 8.76 ± 0.24 3.65 0.1 1.39 0.36 4 73 9.83 ± 0.03 2.54 0.06 1.01 0.58 5 76 11.71 ± 0.05 3.59 0.17 1.85 0.37 6 65 12.9 ± 0.06 3.94 0.23 1.37 0.46 7 60 14.91 ± 0.06 3.22 0.21 1.92 0.47 8 35 17.17 ± 0.14 4.00 0.66 2.26 0.64 9 34 20.79 ± 0.12 3.46 0.52 3.62 0.33 10 54 22.97 ± 0.12 3.87 0.80 2.18 0.50 11 52 26.66 ± 0.13 3.56 0.91 3.69 0.47 12 57 30.56 ± 0.17 4.22 1.67 4.00 0.44 13 52 35.02 ± 0.17 3.57 1.56 4.36 0.52 14 43 40.87 ± 0.28 4.45 3.34 5.88 0.47 15 53 47.14 ± 0.26 3.97 3.57 6.24 0.44 16 43 53.8 ± 0.25 3.10 2.79 6.66 0.58 LG = Length gain = Final length - Initial Length = (Lt – Lo) DGR = Daily Growth Rate = (In Lt – ln Lo)*100t -1 (t = 30) SEM = Standard error of mean CV = Coefficient of variation
Figure 4.2: Relationship between length (cm) and age (months) of Channa marulius maintained at Chenawan Fish Hatchery
65
attain the length of 53.80 ± 0.25 cm at the age of 16 months, suggesting an average increase of 3.01 cm per month. The values of the coefficient of variation for the different age groups remained low, fluctuating between 0.14% and 3.57%, indicating some degree of intra-class homogeneity. The increase in length was rather slow in the earlier ages, which generally become rapid with increasing age so that the length gained during a month generally from 1.39 cm/ month during the
3rd month to 6.66 cm/ month during the 16th month of age. However, the daily specific growth rate remained relatively constant (fluctuating between 0.331 cm and 0.64 cm between different age groups). Previous studies on growth related changes in the length of C. marulius suggested that the stock reared in a tank achieved an average length of 52.8 cm from the initial average length of 3.7 cm in
8 months , suggesting an increase of 6 cm per month (Murugesun, 1978).
The fish stock under the present study could attain an average length of
17.17 ± o.14 cm by the 8th month of age. No data is available on the length of fry at the time of its emergence from the egg, yet the present information suggests a much lower growth of C. marulius stock maintained under the present condition as compared with that maintained by Murugesan (loc cit). It is difficult to conclude whether such a low growth rate is the characteristics of the population of this species inhabiting southern Punjab (Pakistan) or it was an attribute of the environmental condition of the culture ponds including the supplementary ration provided to support the fish growth. Quality and quantity of food is known to effect the growth of the fish (Beverton and Holt, 1959; Bromley, 1989, Takupsstovu and
Hang, 1988). Further studies would be required on environmental determinants and 66
the stocking densities for achieving growth of the species under pond condition.
Because the stock was washed away, beyond the 16th month of age, the age related increase in the length could not be monitored directly under the controlled conditions. However, there are indications to suggest that the fish continues growing even after 16 months of age as fish measuring 92.5 cm was netted from natural waters.
Previous studies on the age related increase in the body length has suggested a higher increase in the length during the first 3 months (2.5–4.0 mm per day) followed by lower increase in the length during the rest of the 5 months of the study period (0.8–1.3 mm per day) (Murugensan, 1978; Johal, et al. 1983; Ahmad et al., 1990). Limited conclusive information is available on the stock of C. marulius under the present study. However, the increase in the length has ranged between 0.40 and 0.75 mm per day, which remain slightly lower than that recorded in previous studies. No previous study is available on the pattern of age related growth i.e. length of C. marulius or other species of the genus Channa for the ages beyond 8th months.
4.2.2. Weight
The average weight of the fingerlings at the age of 2 months of 2.86 g increased to the average weight of 1,165.79 g at the age of 16 months (Table 4.5,
Figure 4.4). The increase in the weight was low between 2nd and 7th month of age.
The weight recorded a rapid increase in weight during the subsequent months (8-
16) of age. A pattern of sigmoid growth has been previously 67
Table 4.5: Age related changes in weight of Channa marulius maintained in earthen ponds at Chenawan Fish Hatchery Age n Weight 95% CV WG DGR Mean ± SEM CL
Month (g) % (g/ month) % 2 156 2.86 ± 0.038 0.164 17.30 3 171 4.64 ± 0.047 0.137 9.50 1.78 1.60 4 73 6.48 ± 0.109 0.144 11.97 1.62 0.99 5 76 11.85 ± 0.128 0.115 14.10 5.10 1.98 6 65 14.85 ± 0.097 0.052 12.20 3.26 0.84 7 60 25.68 ± 0.319 0.0962 25.0 8.83 1.57 8 35 37.07 ± 1.013 16.16 15.25 13.74 1.54 9 34 66.7 ± 1.249 10.92 10.77 29.18 1.93 10 54 83.86 ± 1.594 13.96 13.31 20.97 0.91 11 52 131.56 ± 1.872 10.25 10.71 43.21 1.34 12 57 193.6 ± 3.027 11.78 11.7 62.86 1.31 13 52 324.9 ± 11.332 25.15 12.24 144.90 1.86 14 43 538 ± 6.537 7.97 13.90 170.39 1.36 15 53 750.08 ± 18.146 17.61 12.50 225.17 1.22 16 43 1165.79 + 17.75 9.99 9.80 432.55 1.54
WG = Weight Gain = Final Weight - Initial Weight = (Wt – Wo) DGR = Daily Growth Rate = (In Wt – ln Wo)*100t -1 (t = 30) SEM = Standard error of mean CV = Coefficient of variation
Figure 4.3: Age related changes in weight of Channa marulius maintained at Chenawan Fish Hatchery 68
recorded in Channa spp., suggesting that the greatest increase in the weight occurred during the second year of age (Johal et al., 1983), and the growth rate declined with increase in age (Ahmad et al., 1990). Direct data on the growth of the present stock of C. marulius is not available at ages beyond 16th month (stock being lost due to flood), but it appears that the fish continue attaining weight and fish weighing up to 8.0 kg has been netted from the natural waters (present study).
The intra-group coefficient of variation relatively remained low (9.5–25.0), indicating some degree of homogeneity of the sample. However, the values of coefficient of variation for different weight groups remained higher than those suggested for the intra-group variability in the length. This gives support to the assumption that the length is a more direct determinant of the age as compared with the weight. The increase in weight with age showed a gradual increase from an average of 1.78 g during the 3rd month, to an average of 432.25 g during the 16th month. However, the daily specific growth rate of weight remained relatively constant, fluctuating between 0.84 and 1.98. The daily growth rates exhibited during different months did not follow any pattern, and were erratic, which indicated that such variation are not age related and can be regarded as chance sampling error or the variations in the available environmental conditions, including food, during different parts of the year.
4.2.3. Length-Weight Relationship
The length-weight relationship of the individuals sampled at different ages was calculated and the results of this analysis are in Table 4.6 and in Figures 4.4. 69
Table 4.6: Age – length - weight relationships and condition factor (K) in different age groups for Channa marulius at different ages maintained at Chenawan Fish Hatchery (n= sample size, K = Condition factor)
Age n Mean Mean Relationship Parameters (Month) cm) (g) a b R2 (K) 2 156 7.37 2.88 0.014 2.66 0.73 0.72 3 171 8.76 4.66 5.16 3.13 0.77 0.69 4 73 9.83 6.48 1.41 3.15 0.83 0.67 5 76 11.71 11.85 0.01 3.18 0.90 0.72 6 65 12.90 14.85 5.89 2.38 0.98 0.67 7 60 14.91 25.68 0.12 3.09 0.93 0.71 8 35 17.17 37.07 1.55 2.92 0.91 0.73 9 34 20.79 66.70 0.03 3.03 0.92 0.74 10 54 22.97 83.86 0.10 3.30 0.95 0.72 11 52 26.66 131.56 0.06 2.81 0.91 0.69 12 57 30.56 193.60 0.04 2.67 0.97 0.67 13 52 35.02 324.94 2.55 3.32 0.98 0.78 14 43 40.89 538.00 18.54 2.90 0.95 0.74 15 53 47.14 750.08 8.51 2.99 0.96 0.70 16 43 53.80 1165.79 0.04 3.07 0.96 0.75 combined 1024 6.22 3.02 0.999 0.71
Figure 4.4: Linear graph showing relationship between log values of wet weight (g) against the log values of total length (cm) of Channa marulius maintained at Chenawan Fish Hatchery
70
The values of the length exponent “b” mostly remained between 2.59 and
3.26, except for the 6th month of age, when it was 2.37. The value of “b” calculated for the pooled sample of all the age groups was 3.05 r2 = 0.999) indicating isometric growth of the weight in comparison with the length. Variation in the length weight relationship with the age of the fish has also been indicated previously (Thomas et al., 2003). In the absence of a report on the value of b in C. marulius or/ and other species of genus Channa, it appears that the species is maintaining an almost isometric increase in weight at different lengths at all ages.
The different values of b, appearing for different age groups exhibited erratic fluctuations. This suggests that the b-values are probably fluctuating under chance sampling error or being controlled by unanalyzed environmental determinants.
Analysis of covariance (ANCOVA) output (Table 4.7) with age (month) taken as categorical variable, weight (natural log transformed) as dependents variable and length (natural log transformed) as covariate suggested that length
(F=5518.6), df=1,1023, p=0.00) very significantly predicted the value of weight.
This is understandable as length and weight of the overall sample has a strong linear regression relationship (In weight = ln 2.178 + 3:022. In total length; R2 =
0.999; Figure 4.5). ANCOVA also indicate that the age is also a strong predictor of weight (F = 46.5, df = 14, 1023, p=0.000). However, variability contributed by age
(1.571) was much lower than that contributed by length (13.330), indicating that length is strong predictor of weight as compared with age.
71
Under the cube law, the value of 3 for “b” indicates an isometric growth of fish. Deviations from 3.0 indicate some degree of negative (< 3) or positive (<3) allometric growth of the weight in comparison with the length (Pauly, 1983;
Gayanilo and Pauly, 1997). However, the value of “b” is controlled by a number of factors, intrinsic and extrinsic, and hence the isometric value is seldom recorded
(Fagbenro et al., 1991; Thomas et al., 2003; Cherif et al., 2008) and the values of
“b” ranging between 1.9 and 3.4 have been frequently reported for samples unasserted for age, for fish of different fish species (Mountopoulos and Stergiou,
2002; Petrakis and Stergiou, 1995; Thomas et al., 2003; Cherif et al., 2008; Gurkan et al, 2010).
The analysis of the length weight relationship has a value to the fish biologists, as the other morphometric parameters of growth are considered as generally unreliable (Jones, 2000). Such an analysis allows conversion of growth in length to growth of weight, estimation of biomass from observations on length, estimation of the condition of fish and comparison between species and regions
(Wootton, 1990; Pauly, 1993; Petrakis and Stergiou, 1993; Goncalves et al., 1996;
Binoholan and Pauly, 1998; Morato et al., 2001; Stergiou and Mountpoulos, 2001;
Mountpoulos and Stergiou, 2002; Ozaydin et al., 2007) and the comparative growth (Binoholan et al., 1998).
Length and weight data are useful standard results of fish sampling programs (Morato et al., 2001). In fish, size is generally more biologically relevant than age, mainly because several ecological and physiological factors are more 72
Table 4. 7: ANCOVA: output with age (month) taken as categorical variable, length (log natural) as covariate and weight (log natural) as dependent variable in Channa marulius.
Mean Source Sum of Squares df F p square
Corrected Model 3910.822a 15 260.721 107935.953 .000
Intercept 3.836 1 3.836 1587.884 .000
Length (log natural) 13.330 1 13.330 5518.574 .000
Age 1.571 14 0.112 46.462 .000
Error 2.435 1008 0.002
Total 15153.019 1024
Corrected Total 3913.257 1023
R2 = 0.999 (Adjusted R2 = 0.999)
73
size-dependent than age-dependent. Consequently, variability in size has important implications for diverse aspects of fisheries science and population dynamics, It is usually easier to measure length than weight, and weight be predicted later on using the length-weight relationship.
4.2.4. Condition Factor
The values of the condition factor (K) calculated for different age groups (Table
4.6) suggest that the value of K has persistently remained below 1 for all the age groups. Values of K have fluctuated between 0.67 and 0.78 for different ages without following some specific age related pattern. The value of K for the total sample was 0.71.
The condition factor, being the indicator of well being, pulpiness and relative robustness of the fish (Bagenal, 1978), is based upon the assumption that the heavier fish of a given length are in better conditions (Bagenal and Tesch,
1978) and is an index of the feeding intensity (Fagade, 1979), and the value of K of
“1.0” indicates a perfect growth of weight with regard to the length. Not much has been recorded on the growth related changes in the value of the condition factor.
The values of K falling below 1 for the present sample indicate that the weight of the fish falls below that demanded by the length under the ideal conditions. This does not necessarily suggest that the stock under the present study was undernourished due to the availability of food. No information is available on the condition factor variation at different ages under the conditions of natural waters, and this might reflect some species specific character. 74
This study is the only study on C. marulius or any other species of genus
Channa where the growth has been analyzed through different parameters, i.e., length, weight, and age relationships and condition factor. The study was though handicapped due to washing away of the stock and could not be continued beyond
16th month of age, yet, there are indications to suggest that the fish of this species continues growing even beyond two years of age. Further studies are though, required on different stocks and for older ages, yet it gives a preliminary insight into the growth pattern followed by the species. The study suggests that sol keeps on growing at fairly constant daily growth rate, where weight maintains an almost isometric growth with age, the latter being the better determinant of age. The values of condition factor consistently falling below 11.0 indicates that weight falls below that the demanded by length at least during first 16 months of its age.
4.3. REPRODUCTIVE BIOLOGY
Variation in the reproductive activity of this stock of the C. marulius living under the condition of natural waters of Taunsa Barrage (Dera Ghazi Khan, South
Punjab, Pakistan) was studied through following different routes, i.e., gonadosomatic index (GSI), hepatosomatic index (HSI), sex hormone levels and histological changes in gonads. ANCOVA has been exploited to separate the impact of the covariate (total length) on gonad or liver weight. The present study has limitations with regard to two basic aspects and hence needs to be taken with care for developing generalization on this species. The present study concentrates on one specific locality, i.e., Tanusa Barrage, having its own environmental conditions like temperature, water quality, availability of food and day light. Not 75
much variation is expected in day length and temperatures along the distribution range of the species, especially in the Punjab (Pakistan), but variations in water quality and availability of food between different water bodies are expected.
Further the present study is based upon a relatively smaller sample size (3-6 females, 2-4 males) than that desired for such studies. The study was initially designed to collect a minimum sample of 7 specimen separately males and female for each sampling month four samplings in a year to give a confidence of 99%, yet even this number could not be maintained with the belief that over sampling could lead to total depletion of natural stock. With the present sample size with increase in number of samplings this study can give us a general idea on the possible pattern of variation in reproductive activity followed by the species in this area and hence may require further confirmation.
4.3.1. Gonadosomatic Index
Female: Seasonal variations in the values of the gonadosomatic index
(GSI) of the female marulius are presented in Table 4.8 (graphic presentation in
Figure 4.5). The mean value of GSI was the lowest in December, which showed a rise in February, attaining a peak level in April, which was followed by a rapid decline, ultimately touching the lowest values in September and remained at the minimum levels during August–December period.
Subjected the data to ANOVA suggested a highly significant (F=182.95, df
6, 26; p<0.01) difference in the values of GSI between different calendar months indicating a significant seasonal variation The application of ANCOVA with 76
Table 4.8: Values of gonadosomatic index (GSI) of female Channa marulius during the sampling calendar months
95% Confidence Interval Mean ± SEM Min. Max. Month n for Mean
Lower Upper bound bound Dec 4 .222 ± .0168 .19 .27 .1690 .2756 Feb 4 .940 ± .0303 .86 1.00 .8436 1.0364 Mar 6 1.879 ± .0297 1.75 1.98 1.8022 1.9548 Apr 5 3.168 ± .1839 2.66 3.75 2.6568 3.6782 May 6 .8578 ± .0375 .74 .99 .7613 .9542 Jun 3 .4307 ± .0455 .38 .52 .2349 .6266 Sep 5 .2436 ± .0280 .20 .35 .1658 .3215
) Mean ±2 SEM ( GSI
Figure 4.5: Pattern of seasonal variations in the gonadosomatic index of female Channa maruliu. Error bars indicate SEM 77
months (seasons) taken as categorical variable, weight of ovary (log natural) as dependent variable and length (log natural) as covariate (output result Table 4.9) suggest that length significantly predicts the weight of the ovary (F=141.04, df 1,
25, p<0.01) indicating that ovary weight is strongly influenced by length. The amount of variation accounted in weight of ovary by the model (6.958 units) is mainly contributed by months length (4.885 units), which reduced unaccounted error variation (0.262 units). The model also indicated months (season) have significant influence on ovary weight (F=77.59, df = 6, 25, p<0.01). when the effect of covariate (fish length) is controlled.
Pair wise comparison amongst the months for the mean weight of the gonads (adjusted for the effect of covariate length) suggested a significant difference between December-February, February-March, March-April, April-May and May-June (p<0.05) and 0 non-significant differences between June-September and September-December (p>0.05, table 4.10). The analysis of seasonal variation in GSI, supported by ANCOVA of the ovary weight adjusted to the effect of length indicates that the size of ovary starts increasing some times between December and
February and largest size appearing in April.
Male: The corresponding analysis of the seasonal variations in GSI in males (Table
4.11; Figure 4.6) presented a pattern reasonably similar to that followed in females.
The low values of GSI recorded for December started showing an increase in
February. The trend of increasing values of GSI continued so that peak values appeared in April. GSI exhibited a rapid decline in subsequent calendar months 78
Table 4.9: ANCOVA output for the effects of months and length of fish (covariate, ln) on ovary weight (ln) of female Channa marulius
Sum of Source df Variance F p Squares Corrected Model 6.958a 7 .994 94.742 .000
Intercept .894 1 .894 85.206 .000
Length (log transformed) 1.480 1 1.480 141.044 .000
Month 4.885 6 .814 77.591 .000
Error .262 25 .010
Total 51.311 33
Corrected Total 7.221 32
a. R Squared = .964 (Adjusted R Squared = .954)
Table 4.10: Pairwise comparison among months based on estimated marginal means (means adjusted for the effect of covariate) on ovary weight of female Channa marulius
Month(I) Month(J) Adjusted Mean Difference (I-J) p. Dec Feb .592 - 1.241 = -.649 .000* Feb Mar 1.241 - 1.482 = -.241 .032* Mar Apr 1.482 - 1.749 = -.267 .008* Apr May 1.749 - 1.154 = .595 .000* May Jun 1.154 - .904 = .250 .042* Jun Sep .904 - .708 = 196 .436 Sep Dec .708 - .592 = 116 1.000 Covariates appearing in the model are evaluated at the following values: Length (log transformed) = 1.8042 Adjustment for multiple comparisons: Bonferroni. *The mean difference is significant at the .05 level.
79
Table 4.11: Values of gonadosomatic index (GSI) of male Channa marulius during the sampling calendar months
95% Confidence Interval Month n Mean ± SEM Min. Max. for Mean Lower Upper bound bound Dec 3 .2226 ± .0423 .14 .28 .0408 .4040
Feb 2 .4950 ± .0350 .46 .53 .0503 .9397
Mar 4 1.005 ± .0795 .82 1.20 .7523 1.258
Apr 2 2.667 ± .0659 2.60 2.73 1.830 3.505
May 2 .5901 ± .0510 .54 .64 -.0576 1.238
Jun 4 .2759 ± .0152 .23 .30 .2276 .3243
Sep 3 .2209 ± .0134 .20 .24 .1633 .2786
±2 ±2 (Mean
GSI
Figure 4.6: Pattern of seasonal variations in the gonadosomatic index of male Channa marulius. Error bars indicate SEM
80
touching the lowest values in September which were maintained till December.
ANOVA analysis suggested than there is a significant difference (F=209.47, df = 6,
13, p<0.01) between GSI values of different season (months). ANCOVA output generated by months (season) taken are categorical variable, length (log natural) as covariate and weight of testis (log natural) as dependent variable (Table 4.12) suggested that length of fish worked as a predictive of the testes weight (F=30.15, df=1, 12, p<0.001). Therefore the length has an influence over testes weight.
Categorical variable (month / season) also has a very significant predictive influence (F=54.61, df=6, 12, p< 0.001) over testis and shared the major part of the variation (2.44 point compared with total 3.21 points). This indicate that season
(month) have a stronger predictive control over testes weight as compared with the influence of length, contributing only 0.225 points on total variance.
The pairwise comparison of the testis weight (adjusted to the influence of length) suggested a significant difference between December–February, March-
April, April-May and May-June samples (p < 0.05, Table 4.13). The adjusted mean were, however, not significantly different between February-March, June-
September and September-December samples (p > 0.05).
The present analysis, using GSI and ANCOVA, suggest that the testes weight follows seasonal variation, which for the most part run parallel to that followed by ovaries. The size of the testes starts increasing some ware between
December and February and maximum size achieved in April, when testis start receeding and the minimum size is maintained from June till December. 81
Table 4.12: ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (ln) of testes of male Channa marulius
Sum of Source Squares df Variance F p Corrected Model 3.209a 7 .458 61.515 .000 Intercept .153 1 .153 20.557 .001 Length (log transformed) .225 1 .225 30.149 .000 Month 2.442 6 .407 54.613 .000
Error .089 12 .007 Total 12.379 20 Corrected Total 3.298 19 a. R Squared = .973 (Adjusted R Squared = .957)
Table 4.13: Pairwise comparison among months based on estimated marginal means (adjusted for the effect of covariate) on weight of gonads of male Channa marulius
Month(I) Month(J) Adjusted Mean Difference (I-J) p.
Dec Feb .351 - .716 = -.365 .012*
Feb Mar .716 - .991 = -.275 .066
Mar Apr .991 - 1.436 = -.445 .001*
Apr May 1.436 - .719 = .717 .000*
May Jun .719 - .423 = .296 .040*
Jun Sep .423 - .341 = .082 1.000
Sep Dec .341 - .351 = -.009 1.000
Covariates appearing in the model are evaluated at the following values: Length (log transformed) = 1.7055. Adjustment for multiple comparisons: Bonferroni. *The mean difference is significant at the .05 level.
82
The changing values of GSI indicate the changes in size of the gonads standardized to the total body weight, and work as a good indicator of the reproductive status of the testis of the individual (Vlaming et al., 1982; Al Akel et al., 2010). Higher values of GSI are frequently regarded as indicative of spawning season (Abuzinadah, 2001). However, value of GSI is affected by the weight through temporary changes in the visceral mass caused by feeding. Different workers have tried to address this problem and have been subtracting gonad weight from the body weight (Tracey et al., 2007; Muchlison et al., 2010) or using eviscerated body weight. The use of statistical technique of ANCOVA can help in separating the predictive value of weight/length. and the seasons (calendar months) for the size of the gonads and hence can separate the effect of season on the gonad weight. The present study has adopted both the routes of analysis of the changes in gonad weight (ANCOVA is a refined technique compared with GSI), yet both the routes lead to similar results.
Seasonal variations in the values of GSI were reported by different authors for different fish species and areas, yet no direct report is available for C. marulius.
The studies available for an allied species, i.e., C. gachua, conducted in Godavari
(Aurangabad, India) suggested that the female of the species maintained low values of GSI (6 – 12) for the major part of the year, and the values of GSI started rising in June (25) achieving peak level (56) in July and then rapidly declined in August
(34) (Gaikwad et al., 2009). These values of GSI are much higher than the values recorded under present studies for which no explanation can be given. Relaying on the values of GSI suggested by Gaikwad et al. (loc cit) it can be suggested that size 83
of the ovary is probably smaller in C. marulius compared to C. gachua, former probably having smaller size of spawn. The pattern of changes in the gonad weight and hence gonad activity is also different in C. marulius, gonad enlargement starts in January attaining the largest size in April, while in C. gachua the size starts increasing in June attaining the maximum size in July. The information on spawning season of C. marulius in other part of its range of distribution is not available, and some degree of variation in spawning seasons of the species can be expected under different environmental conditions.
4.3.2. Hepatosomatic Index
Female: The seasonal changes in the hepatosomatic index (HSI) in females (Table
4.14; Figure 4.7) suggest that HSI value was maintained at higher values in
September and December, which started showing a decline in February touching the lowest values in May. The HSI values showed a gradual increase in the subsequent months (June) and reaching the highest values in September and
December.
ANCOVA output (Table 4.15), taking the months as categorical variable,
(log natural transformed) weights of liver as dependent variable and length (log natural) as covariate for the female data suggested that length (F=197.6, df = 1, 25, p<0.01) and months (F= 13.3, df = 6, 25, p<0.01) were both strong predictor of the liver weight. The maximum contribution in the model variance was coming from length (1.46 out of total 2.49 points). Pairwise analysis (Table 4.16) of the significance of difference between different calendar months of the liver weight 84
Table 4.14: Values of hepatosomatic index (HSI) of female Channa marulius during the sampling calendar months
95% Confidence Interval Month N Mean ± SEM Min. Max. for Mean Lower Upper Bound Bound Dec 4 .7288 ± .0129 .70 .76 .6877 .7698 Feb 4 .6426 ± .0261 .59 .71 .5596 .7256 Mar 6 .4496 ± .0116 .41 .49 .4198 .4794 Apr 5 .5207 ± .0411 .41 .61 .4065 .6349 May 6 .4081 ± .0126 .37 .46 .3758 .4403 Jun 3 .4531 ± .0271 .40 .49 .3363 .5699 Sep 5 .7762 ± .0170 .72 .81 .7290 .8234
) Mean ±2 SEM SEM Mean ±2 ( HSI
Figure 4.7: Pattern of seasonal variations in the hepatosomatic index (HSI) of female Channa marulius. Error bars indicate SEM 85
Table 4.15: ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (In) of liver (In) of female Channa marulius
Sum of Source df Variance F p Squares
Corrected Model 2.493a 7 .356 48.037 .000 Intercept .937 1 .937 126.360 .000 Length (log transformed) 1.464 1 1.464 197.557 .000 Month .591 6 .098 13.278 .000
Error .185 25 .007 Total 34.890 33 Corrected Total 2.678 32 a. R Squared = .931 (Adjusted R Squared = .911)
Table 4.16: Pairwise Comparison among months based on estimated marginal means (means adjusted for the effect of covariate) of weight of liver of Female Channa marulius
Month(I) Month(J) Adjusted Mean Difference (I-J) p.
Dec Feb 1.110 - 1.075 = .035 1.000
Feb Mar 1.075 - .859 = .216 .017*
Mar Apr .859 - .962 = -.103 1.000
Apr May .962 - .834 = .128 .541
May Jun .834 - .930 = -.096 1.000
Jun Sep .930 - 1.220 = -.290 .004*
Sep Dec 1.220 - 1.110 = .110 1.000
Covariates appearing in the model are evaluated at the following values: Length (log transformed) = 1.8042 Adjustment for multiple comparisons: Bonferroni. *The mean difference is significant at the .05 level. 86
(adjusted to the effect of length) suggested a significant difference between,
February-March and June-September (p<0.05) and a non significant difference between other months (p>0.00).
Male: A similar pattern of seasonal changes in HSI was exhibited in males
(Table 4.17, Figure 4.8), which was much less pronounced than that in the females.
The higher values of HSI persisting in December and February exhibited gradual decline, starting from March touching the lowest values in May. HSI values started showing a rise in subsequent months (June), the maximum value in September.
Subjecting the data on liver weight (log natural, dependent variable), month
(seasons, categorical variable) and length (log natural, covariate) to ANCOVA
(Table-4.18) suggested that body length is a strong predictor of liver weight
(F=71.55, df = 1, 12, p<0.01) in males. Months (season) also have a significant control over liver size (F=14.374, df = 6, 12, p<0.01). Seasons contributed the larger part of the variance (0.271 out of 0.397 points). Pairwise comparison of the liver weight adjusted to the effects of total length, (Table-4.19) suggested a significant difference in adjusted liver weight only between April-May and between June-September (p<0.05).
The HSI is an index developed to represent the relative weight of the liver standardized against the total body weight and has been used to analyze seasonal changes in reproductive activities of the fish (Lambert and Dutil, 2000; Vitale et al., 2006). The index is analyzed with the assumption that fish, like other 87
Table 4.17: Values of hepatosomatic index (HSI) of male Channa marulius during the sampling calendar months
95% Confidence Interval Month N Mean ± SEM Min. Max for Mean Lower Upper Bound Bound Dec 3 .6763 ± .0263 .63 .72 .5634 .7893 Feb 2 .7337 ± .0264 .71 .76 .3979 1.070 Mar 4 .5581 ± .0153 .52 .59 .5093 .6069 Apr 2 .4787 ± .0208 .46 .50 .2139 .7434 May 2 .3259 ± .0160 .31 .34 .1232 .5286 Jun 4 .3728 ± .0077 .35 .39 .3481 .3974 Sep 3 .7086 ± .0402 .63 .77 .5357 .8814
) Mean ±2 SEM Mean ±2 ( HSI
Figure 4.8: Pattern of seasonal variations in the hepatosomatic index (HSI) of male Channa marulius. Error bars indicate SEM
88
Table 4.18: ANCOVA output for the effects of months and length (ln) of fish (covariate) on weight (ln) of liver of male Channa marulius
Sum of Source df Variance F p Squares
Corrected Model .397a 7 .057 18.044 .000
Intercept .152 1 .152 48.553 .000
Length (log transformed) .225 1 .225 71.547 .000
`Month .271 6 .045 14.374 .000
Error .038 12 .003
Total 10.738 20
Corrected Total .434 19 a. R Squared = .913 (Adjusted R Squared = .863)
Table 4.19: Pairwise comparison among months based on estimated marginal means (adjusted for the effect of covariate) on weight of liver of male Channa marulius
Month(I) Month(J) Adjusted Mean Difference (I-J) p.
Dec Feb .851 - .888 = -.037 1.000
Feb Mar .888 - .739 = .148 .210 Mar Apr .739 - .690 = .050 1.000
Apr May .690 - .463 = .227 .043*
May Jun .463 - .556 = -.093 1.000
Jun Sep .556 - .848 = -.292 .011*
Sep Dec .848 - .851 = -.003 1.000 Covariates appearing in the model are evaluated at the following values: Length (log transformed) = 1.7055. Adjustment for multiple comparisons: Bonferroni. *The mean difference is significant at the .05 level.. 89
organisms, expends energy during the process of reproduction. For the successful reproduction the fish is required to acquire and store the energy in the tissue while preparing for the oncoming reproductive activity (Love, 1970; Godo and Haug,
1999) and in some species the major part of such energy is stored in the liver
(Marshall et al., 1999). A linear relationship has been suggested between lipids accumulated and number of eggs produced (Marshall et al., 1999). The energy stored in the liver, during the reproductive inactive period by the fish / teleosts in the form of vitellogenin, is incorporated into yolk proteins, lepovitellen and phosphoriten in ovary (Campbell and Idler, 1976; Campbell, 1978; Ng and Idler,
1979; Idler and Campbell, 1980). This results in an increased liver weight during non-reproductive period and decrease in liver weight during reproductively active season. The decline in liver weight is expected to continue till the spawning is complete and the liver gradually starts accumulating the vitellogenin to prepare for the next spawning.
HSI is rather crude indicator of liver weight, which may be influenced by size of the fish. ANCOVA can help partially to overcome this problem and can separate the effect of season and the size of the fish. The value of the liver weight
(log natural) can be adjusted by eliminating the effect of size. Such refinement can help in better analysis of changes in live weight
Changes in liver weight have been equally indicated through HSI and
ANCOVA in both the sexes. The analysis of present results using both HSI and
ANCOVA suggest decline in liver weight of both the sexes starting sometimes between December and February. ANCOVA suggested significant increase / 90
decrease in adjusted liver weight in females between February and March
(decrease) and June-September (increase). Significant changes in males were produced in adjusted liver weight between April-May (decrease) and between
June-September (increase).
The comparative values of HSI are not available for C. marulius or any other fish of genus Channa to fully judge the values generated under the present study. The changes in HSI correspond with the changes in GSI in both sexes, but
HSI levels remain lower for some period even when the gonad weight starts receding. Such a difference is understandable, the gonads receding immediately after spawning, while liver weight increases to prepare the individuals for next spawning
4.3.3. Sex Hormone
The sex steroid hormone determination under the present study has been carried out using mammalian radio-immunoassay kit, antibodies standardized to human-steroid hormone. There is considerable similarity between fish and mammal steroid hormones, yet the efficiency of this assay for determining the levels of fish steroids needs to be tested. The concentration of the fish hormone appearing through the use of this kit may not be absolute concentration, yet should give relative values. The present study is aimed at analyzing relative variation in the steroid hormones during different parts (season) of the year, therefore, such an assay has fair degree of reliability under the experimental design of the present study. 91
4.3.3.1. Estrogens
The cyclic variation in the levels of circulating serum estradiol (Table 4.20,
Figure 4.9) indicated that the hormone level was low in June and September samples. The serum estradiol levels started increasing in December, then showed a gradual increase, rose through February to achieve peak values in March. The estradiol levels declined in the May touching low levels in June and the subsequent month. ANOVA suggests a significant difference in the estradoil level between different monthly samples. (F=63.596, df = 6, 26, p<0.05). Multiple caparisons, using Scheffe test Table 4.21), has indicated significant (p<0.05) difference in the mean estradoil levels between September-December and February-March
(increase) and between March-April and April-May (decrease).
Estradiol is known as a gonadal hormone, secreted by the ovaries and has a control over oogenesis and vitellogenesis (Abuzinadah, 2001; Fostier et al., 1983;
Goetz, 1983; Pankhurst and Carragher, 1992; Carragher and Pankhurst, 1993) and its surge in plasma levels appears during the pre-ovulary period (Zohar et al., 1982;
Scott and Canario, 1992). Estradiol is involved in hepatic synthesis of yolk precursor (Kagawa et al., 1984). Higher levels of plasma estradiol have been associated with vitellogenesis (Campbell and Idler, 1976; Smith and Hailey, 1988;
Takemura et al., 2003; Takano et al., 1991; Nagahama et al., 1991). The decline in the estradiol level is considered as an indication of completion of vitellogenesis
(Kobayashi et al., 1988). 92
Table 4.20: Values of estradiol of female Channa marulius during the sampling calendar months
95% Confidence Mean ± SEM MIN MAX Interval for Mean Month N (ng/ml) (ng/ml) (ng/ml) Lower Upper Bound Bound Dec 4 1082.0 ± 40.67. 984.00 1173.67 952.58 1211.43 Feb 4 1461.92 ± 16.49 1413.33 1484.33 1409.44 1514.39 Mar 6 2035.72 ± 149.38 1521.33 2453.67 1651.72 2419.72 Apr 5 1295.60 ± 24.28 1231.67 1377.00 1228.20 1363.01 May 6 557.45 ± 62.11 412.00 839.67 398.30 717.59 Jun 3 260.55 ± 61.41 196.33 383.33 -3.6732 524.78 Sep 5 374.20 ± 13.24 327.00 404.00 337.45 410.95
) ml g/ n ( Mean ±2 SEM Estradiol
93
Figure 4.9: Variations in the serum estradiol in female Channa marulius during different calendar months. Error bars indicate SEM 94
Table 4.21: Monthly differences in estradiole level of female Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 63.596 , P < .05 followed by Scheffe test for multiple comparison.
(I)Month (J) Month Mean Difference I-J p. Result
Dec Feb -379.92 .224 Nonsignificant
Feb Mar -573.81 .005 Significant
Mar Apr 740.12 .000 Significant
Apr May 737.66 .000 Significant
May June 297.39 .506 Nonsignificant
Jun Sep -113.65 .992 Nonsignificant
Sep Dec -707.80 .001 Significant
95
4.3.3.2. Progesterone
The analysis of the plasma levels of progesterone in the female Channa marulius (Table 4.22; Figure 4.10) revealed that progesterone was present in lower concentration in the fish sampled in February. Progesterone levels exhibited an increase in March and peak level was achieved in April. The peak progesterone levels started showing a decline in May gradually dropping down to the minimum levels in September. The Progesterone level kept fluctuating at such low levels during September-February period. ANOVA suggested a significant difference to the progesterone levels between the samples collected during different calendar months (F=183.56, df = 6, 26, p<0.05). Subsequent analysis, using Scheffe test, suggested significant increase between February-March and March-April samples and a significant decrease between April –May and May-June samples (Table-4.23, p<0.05). Mean progression levels were not significantly different in samples collected June and February (p>0.05).
Progesterone is produced in the fish ovary (Petrino et al., 1990) and its seasonal fluctuations are observed in serum levels (Suzuki et al., 1991; Billard et al., 1972). This steroid hormone is believed to have a role in the oocyte maturation
(Nagahama, 1987; Kime et al., 1991). Thus an increased level of progesterone has been regarded as an indication of oocyte maturation and release in many fish species (Kobayashi et al., 1985, 1987; Kime et al., 1992). Looking at the observation of a peak level of circulating progesterone during April suggested that the oocyte maturation in C. marulius mainly occurs in April, and the species spawns once a year. 96
Table 4.22: Values of progesterone of female Channa marulius during the sampling calendar months
95% Confidence Interval Mean ± SEM MIN MAX For Mean Month N (ng/ml) (ng/ml) (ng/ml) Lower Upper Bound Bound Dec 4 .10150 ± .00504 .091 .112 .08546 .11754
Feb 4 .1868 ± .00347 .179 .194 .1757 .1978
Mar 6 1.0513 ± .13164 .765 1.510 .71293 1.3897
Apr 5 2.9776 ± .08317 2.730 3.178 2.7467 3.2085
May 6 2.2543 ± .16159 1.756 2.730 1.8390 2.6697
Jun 3 .27633 ± .02703 .233 .326 .16002 .39265
Sep 5 .16760 ± .01807 .115 .217 .11743 .2178
) ml g/ n ( esterone esterone g Mean ±2 SEM Pro
Figure 4.10: Variations in the serum progesterone in female Channa marulius during different calendar months. Error bars indicate SEM 97
Table 4.23: Monthly difference in progesterone level of female Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 183.56 , p < .05 followed by Scheffe test for multi comparison.
(I)Month (J) Month Mean Difference I-J p. Result
Dec Feb -.08525 1.000 Non-significant
Feb Mar -.86458 .001 Significant
Mar Apr -1.92627 .000 Significant
Apr May .72327 .004 Significant
May June 1.97806 .000 Significant
Jun Sep .108733 .999 Non-significant
Sep Dec .066100 1.00 Non-significant
98
4.3.3.3. Testosterone
The analysis of the results on the seasonal variations of plasma levels of testosterone in male C. marulius (Table 4.24, Figure 4.11) suggest that testosterone levels were maintained at low levels during December. The testosterone level indicated a slight increase in February ad this trend continued touching the peal levels in April sample. The circulating level of this hormone showed a decline in the May sample, attaining low levels in September. ANOVA suggested a significant (F=49.21, df = 6, 13, p<0.01) difference between testosterone concentration of different calendar months. Multiple comparison, using Scheffe test, (Table-4.25) suggested a significant (p<0.05) increase between March-April and significant decrease between April-May (p<0.01) and May-June (p<0.05).
Testosterone is the main androgenic hormones present in fish (Arai, 1967;
Tamaok, 1980). Peak levels of serum testosterone are associated with sperm maturation, followed by a slight decline at the spawning stage and very low levels at the spent stage (Fostier et al., 1982). Channa marulius appears to follow this pattern with a single peak appearing at the maturation stage occurring in April.
This suggests that the spermatogenesis and sperm maturation stage in this species is completed in April, which is followed by the spawning in late April or early
May.
4.3.4. Histological Changes
Given the generally prevailing idea that the histological analysis of the gonads provides a more reliable and direct indicator of the reproductive status of an organism (West, 1990; Murua and Motos, 1998; Saborido-Rey and Junquera, 1998; 99
Table 4.24: Values of testosterone of male Channa marulius during the sampling calendar months
95% Confidence Interval Mean ± SEM MIN MAX Month N For Mean (pg/m) (pg/m) (pg/m) Lower Upper Bound Bound Dec 3 .1100 ± .0058 .10 .12 .0852 .1348
Feb 2 .2800 ± .0100 .27 .29 .1529 .4071
Mar 4 .6100 ± .0444 .52 .72 .4689 .7511
Apr 2 2.150 ± .3700 1.78 2.52 -2.551 6.851
May 2 .8700 ± .0400 .83 .91 .3618 1.3782
Jun 4 .2750 ± .0156 .23 .30 .2255 .3245
Sep 3 .1233 ± .0088 .11 .14 .0854 .1613
Mean ±2 SEM Testosterone SEM Testosterone ±2 Mean
Figure 4.11: Variations in the serum testoterone in male Channa marulius during different calendar months. Error bars indicate SEM 100
Table 4.25: Monthly differences in testosterone level of male Channa marulius is analyzed by Analysis of Variance (ANOVA) i.e. significant at F (6, 26) = 49.212 , p < .05 followed by Scheffe test for multiple comparison.
(I)Month (J) Month Mean Difference I-J Sig. Result
Dec Feb -.1700 .952 Non-significant
Feb Mar -.3300 .447 Non-significant
Mar Apr -1.5400 .000 Significant
Apr May 1.280 .000 Significant
May June .5950 .032 Significant
Jun Sep .1517 .936 Non-significant
Sep Dec .0133 1.00 Non-significant
101
Kjesbu et al., 2003, Tomkiewiez et al., 2003). The present studies were designed to more accurately identify the spawning season of C. marulius. The reproductive status of each histological preparation was determined following other such studies
(McDermott and Lowe, 1996; Abuzinadah, 2001; Vitale et al., 2005; Saeed et al.,
2010; Rehman et al., 2000; Koya et al., 2002; Mori et al., 2003; Muchlisin et al.,
2010).
Ovaries: The histological analysis of a limited number of ovaries from mature females (Table-4.26 and Plate 4.2 for representation of histomicrophotographs of ovaries at different maturation stages) suggested that during the December sampling, half of the ovaries were classified as immature and the other half as spent mature. All the ovaries in the February sampling were classified as developing. In the March sample, 33% of the ovaries were in developing stage, while the rest of 66% were categorized as mature. Some 80% of the ovaries sampled during the April were ripe while 20% were in the mature stage.
The May sample only 33% of the ovaries were ripe, and the rest were categorized as spent. All the ovaries sampled in June and September were in the spent stage.
The analysis of these result suggest that the sign of development of ovaries start in
December (50% ovaries in early maturing stage and all ovaries entered early maturing stage in February The ovaries pass different maturation stages during
March. The presence of a majority of ripe ovaries, along with some mature ones, indicated the major spawning occurring during April. A decline in the frequency of ripe ovaries indicated that some low level of the spawning still continued till May.
The presence of spent ovaries after May suggest the period of complete reproductive inactivity in later part of the year. 102
Table 4.26: Frequency of ovaries under different maturation stages of female Channa marulius during different calendar months
Maturity Stages of Female
Immature Spent Developing Ripe Spent Mature Total
Count 2 2 0 0 0 0 4 Dec % 50.% 50.% .0% .0% .0% .0%
Count 0 0 4 0 0 0 4 Feb % .0% .0% 100.% .0% .0% .0%
Count 0 0 2 0 0 4 6 Mar % .0% .0% 33.3% .0% .0% 66.6%
Count 0 0 0 4 0 1 5 Apr
Month % .0% .0% .0% 80.% .0% 20.%
Count 0 0 0 2 4 0 6 May % .0% .0% .0% 33.3% 66.6% .0%
Count 0 0 0 0 3 0 3 Jun % .0% .0% .0% .0% 100.% .0%
Count 0 0 0 0 5 0 5 Sep % .0% .0% .0% .0% 100.0% .0%
103
a b
c d
e
Plate 4.2: Photographs of ovary of Channa marulius in different maturation stages a: immature, b: developing, c: mature, d: ripe and e: spent 104
Testes: An identical pattern of cyclic changes in the histology of testis was recorded in the males of this fish species, sampled during different calendar months
(Table-4.27, representation of histomicrographs of testes at different stages of maturation in plate-3).
In the December sample, all the males were classified as immature. The testis sampled during February reflected a pre-spawning stage of development. The
March sample of testes were classified as pre-spawning in 75% of cases, and as spawning in others. All the testis in the April sample were in spawning stage, while in the May sample 50% of the males were in spawning stage and 50% in the post spawning period. In June and September samples, all testes were in the post- spawning or resting stage. This suggests that the reproductive changes in the male gonads start appearing in February and the major spawning occurs in April, with some early and late spawning in March and May respectively. No reproductive activity occurs in the other parts of the year.
No study is in hand describing the histology of C. marulius and / or on the seasonal histological classification of the gonads into different stages of the reproductive activity. The present report is though handicapped because of a smaller size of samples collected during different months from a single locality yet gives a preliminary insight to the seasonal variations in reproductive activities of this species. The collective consideration of histological variations occurring in ovaries and testes indicate that there is good synchronization in the reproductive activities of the two sexes. 105
Table 4.27: Frequency of testes under different maturation stages of male Channa marulius during different calendar months Maturity Stages of Male
Immature Pre- Spawning Post- Resting Total Spawning Spawning
Count 3 0 0 0 0 3 Dec % 100.0% .0% .0% .0% .0%
Count 0 2 0 0 0 2 Feb % .0% 100.0% .0% .0% .0%
Count 0 3 1 0 0 4 Mar % .0% 75.0% 25.0% .0% .0%
Count 0 0 2 0 0 2 Apr
Month % .0% .0% 100.0% .0% .0%
Count 0 0 1 1 0 2 May % .0% .0% 50.0% 50.0% .0%
Count 0 0 0 4 0 4 Jun % .0% .0% .0% 100.0% .0%
Count 0 0 0 0 3 3 Sep % .0% .0% .0% .0% 100.0%
106
a b
c d
Plate 4.3: Photographs of testes of Channa marulius at different maturation stages; a: early spermatogenesis, b: mid spermatogenesis c: late spermatogenesis, d: functional maturation and e: spent
107
4.3.5. General Discussion
The analysis of the reproductive cycle in a fish species has practical importance in fish management and farming. Knowing the spawning season is important and its season varies with the species and even ecotype of a species. The reproductive stages of a fish are associated with changes in the gonads (size, hormones and histology) and other non-reproductive part (liver), which can be exploited for the analysis of the reproductive stage of an organism.
Fish biologist have used the condition factor, gonadosomatic index (GSI, gonad development), hepatosomatic index (HSI, hepatic accumulation of energy rich compounds), circulating levels of steroids (estrogen, progesterone, testosterone, required to support oogenesis and spermatogenesis), and histological variations in the gonads as different indicators of the level of reproductive activity experienced by an individual. Histological studies are direct and more reliable indicator of the reproductive changes, but such studies are difficult and time consuming and are usually taken as the last option. The hormones are though indicators of the reproductive ststus of the gonads, yet reliable to judge the reproductive status of the organism. Such studies are expansive and hence are rarely used for analysis of cyclic changes in the reproductive activity, Doubts have always been expressed over the value of other indicators (i.e., GSI and HSI), yet the researchers have been exploiting these to know the reproductive season of different fish species. The condition factor is very indirect variable, based upon the relative increase in weight (reflecting increase in gonad weight) compared with length. 108
Different workers, in recent years used different combination of these traits for different fish species to provide more reliability to their findings. For example gonad steroids and GSI in kutum (Rustilus frissi kutum), Saba et al., 2009; condition factor, GSI, HSI and histological analysis in kattegat cod (Gadus morhua), Vitale et al., 2006; GSI, hormone and histology in chub (Levciscus cephalus), Guerriero et al., 2005; GSI, hormones and histology in honeycomb grouper (Epinephelus merra), Lee et al., 2002, and Bhanderi et al., 2003; hormone in flounder (Platichthus flesus), Scott et al., 2006; hormone and histology in golden rabbitfish (Siganus guttatus), Rehman et al., 2000; GSI and histology in
Pleurogrammus monopterygus, McDermott and Lowe, 1997; GSI in Resbore tawarenses, Muchlian et al., 2010, histology, GSI and hormone in pacific herring
(Clupea pallasii), Koya et al., 2002, etc. None of the studies has attempted the simultaneous analysis of all these variables to judge the general relationship between these variables and to provide a wider basis and increased reliability for the description of the reproductive cycle.
The correlation between different reproductive activity variables are shown for the females (Table 4.28; Figure 4.12, 4.13, 4.14, 4.15 and 4.16), and males
(Table 4.29; Figures, 4.17, 4.18 and 4.19) C. marulius suggesting a significant
(P<0.05) or highly significant (p<0.01) positive correlation for GSI and hormone levels in both males and females. HSI has a significant negative correlation
(p<0.05) with GSI, and progesterone levels in females. The correlation of HSI is not significant with estradiol level (R2= - 0.178, p= 0.32) in females, and with GSI
(R2 = - 0.186, p = 0.43) and testosterone level (R2 = - 0.368, p = 0.110) males. The graphic representation suggests that GSI curves run parallel with progesterone 109
Table 4.28: Matrix showing the Pearson correlation coefficient between different variables of reproductive activity in female Channa marulius (n = 33)
GSI Estradiol Progesterone HSI
GSI Pearson Correlation .569** .815** -.422*
B-Estradiol Pearson Correlation .569** .851** -.178
Progesterone Pearson Correlation .815** .851** -.380*
HSI Pearson Correlation -.422* -.178 -.380*
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
Figure 4.12: Seasonal variations in GSI and estradiol in female Channa marulius
110
Figure 4.13: Seasonal variations in GSI with progesterone in female Channa marulius
Figure 4.14: Seasonal variations in HSI with progesterone in female Channa marulius 111
Figure 4.15: Seasonal variations in HSI with estradiol in female Channa marulius
Figure 4.16: Seasonal variations in GSIwith HSI l in female Channa marulius 112
Table 4.29 Matrix showing the Pearson correlation coefficient between different indicators of reproductive activity in male Channa marulius (n = 20)
GSI Testosterone HSI
GSI Pearson Correlation .926** -.186
Testosterone Pearson Correlation .926** -.368
HSI Pearson Correlation -.186 -.368
**. Correlation is significant at the 0.01 level (2-tailed).
Figure 4.17: Seasonal variations in GSI with testosterone in male Channa marulius 113
Figure 4.18: Seasonal variations in GSI with HSI in male Channa marulius
Figure 4.19: Seasonal variations in HSI with testosterone in male Channa marulius 114
and estradiol (Figure 4.12) in females, though the hormone peaks are is attained earlier than that of GSI. Contrarily HSI follows an inverse pattern of variation with
GSI, progesterone and estradiol (Figure 4.16) though HSI decline continues even when other factors start declining. In males GSI fluctuation follows the testosterone curve, while HSI follows an inverse pattern of fluctuation with GSI and testosterone level.
The analysis of all the reproductive indicators suggests that C. marulius in the area under present study starts reproductive activity after December. Spawning may occurs between late March and early May, with peak spawning activity in
April. Different reports on the breeding season of this fish species suggested that
Sol breeds in June-August in the Southern Nepal (Shrestha, 1990), rainy season
(Khan, 1924), and April-June in Pakistan (Mirza and Bhatti, 1993). Srivastava
(1980) suggested that in Andhra Pradesh (India) the species has two separate reproductive periods, i.e. May and November-December. The present report partly goes in line with the suggestion of of Mirza and Bhatti (loc cit) and Srivastava
(1980) though we did not find an indication of breeding after early May. It appears that the onset of the breeding season is rather late in eastern parts of the India
Subcontinent. The presence of a second breeding peak in November-December in
Andhre Pradesh (India) as suggested by Srivastava (loc cit) is hard to explain
The sol (C. marulius) may be a long day species, where the reproductive activities are initiated with the increasing day length sometime in the January.
Further control of the breeding is under the environment factors, including 115
temperature, humidity and food. Spawning under the conditions of the Punjab
(Pakistan) occurs earlier (late March to early May) and is delayed in western parts. 116
SUMMARY
Fisheries and Aquaculture has become one of the fast growing sectors in last few decades providing source of best quality protein. With the decline in capture fisheries, major emphasis is now diverted to aquaculture. Efforts are underway to obtain maximum yield per unit area by exploiting of new culture techniques and by adding more species in to the culture system. Sol (Channa marulius) is one of the target species in this respect. It is indigenous to Pakistan and can survive under a variety of stress conditions including high BOD. The species can attain a size of 122 cm and is believed to have good growth rate. The major problem with its introduction in to the aquaculture is availability of seed under hatchery conditions for which basic studies on reproductive biology are required. No specific study is available on this aspect of the species especially with regard to Pakistan and only a few studies / indirect references are available from other part of the globe.
The present study examined of growth and reproductive biology of the fish as exhibited under the conditions of the Punjab Pakistan. Morphometric and meristic studies on wild caught adult C. marulius suggest that all variability of 23 characters was higher as compared with the meristic characters. There was significant correlation between the sizes of morphometric characters, while such correlation was not significant for the meristic characters suggesting that the meristic characters have higher taxonomic values. The karyotype studies revealed that fish has 44 2N chromosomes being metacentric. 117
The studies conducted on 500 fish seed at fish hatchery Chenawan on age related growth suggests that fish of 7.34 cm (2.86 g) at 2 month age increased to
53.80 cm (1165.79) at 16 month of age. The fish exhibited erratic specific growth rate between 0.84 to 1.93% for weight and 0.33 to 0.64% for length. The length weight relationship was almost isometric as the length exponent “b” values ranged between 2.38 and 3.32. The changes may be due to local rearing / environmental conditions. The condition factor remained below one ranging from 0.6 to 0.7.
Fifty three adult (30 female and 23 male) fishes collected from nature were used for study of the reproductive biology. Blood samples were collected through heart puncture and gonads and liver were examined and weighed. Gonadosomatic
Indices (GSI) and Hepatosomatic (HSI) indices were calculated. The values of GSI of female reached its peak during the month of April indicating the peak of breeding activity while the HSI was lowest in May. These results were confirmed by peaks of estradiol and progesterone (in female) and testosterone (in male) and also by histological studies of gonads.
The studies suggested that sol my be a long day species where the breeding activity initiates after December and breeding occurs between late March and early
May in Punjab 118
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