Printer Friendly

Population Dynamics of Rotifers in the Floodplain of River Ravi, Pakistan.

Byline: Altaf Hussain, Abdul Qayyum Khan Sulehria, Muhammad Ejaz and Asma Maqbool

ABSTRACT

The population dynamics of Rotifers of a flood plain ecosystem are supposed to change with mixing of flood water from riverine system, during floods. With respect to biodiversity, floodplain ecosystem remained ignored and no work has been done in Pakistan. With the aim to identify monthly changes in the population of rotifer communities in a flood plain, rotifers were estimated through studying the monthly variations of density and diversity of rotifers, from January to December 2012, in the floodplain of River Ravi near Balloki Headworks, Pakistan. A total of 101 species belonging to 32 genera, 15 families and 3 orders were identified from 15 different sites. Family Brachionidae dominated among all (56%) with the Brachionus, Anuraeopsis and Keratella being the most important genera in family Brachionidae. Rotifer density was highest from April to June 2012.

Rotifer density showed a positive correlation with air and water temperature, pH, turbidity and total hardness and strong positive correlation with electrical conductivity, total dissolved solids (TDS) and total alkalinity. Similarly a negative correlation existed between rotifer density and visibility and chlorides and strong negative correlations with dissolved oxygen. Analysis of variance showed a significant difference in rotifers between different months and sites. Shannon diversity index (H) showed high species diversity in August and lowest diversity in November. Simpson index of dominance showed lowest diversity in November. Species richness was highest in August and lowest in April. Species evenness was highest in April and lowest in November.

It is summarized that density of Rotifers remain highest during summer, when plenty of food is available where as diversity of Rotifers reaches to its maximum when riverine water, carries variety of Rotifers, mixes with the stagnant and isolated flood plain water.

Key words

Floodplains, rotifers, River Ravi, population dynamics.

INTRODUCTION

The water characteristics in aquatic environments are important to understand the different biochemical processes taking place in aquatic environment and population dynamics of zooplanktons. Relationship between physicochemical parameters of water and seasonal abundance of rotifers have been studied by Edward and Ugwumba (2010) and Saron and Meitei (2013). Mahar et al. (2000), Baloch et al. (2008), Sulehria and Malik (2012, 2013) and Lashari et al. (2014) have made valuable contributions in studying the relationship of physicochemical parameters of water with zooplankton concentrations in irrigated lake. Zooplankton are good indicators for the assessment of trophic state of water (Imoobe and Adekinka, 2010). Physico-chemical conditions of water body are supposed to determine the density and diversity of fauna and flora (Ayodele and Adeniyi, 2006; Abdul Razak et al., 2009).

Zooplanktons invariably form an integral component of freshwater communities and contribute significantly to biological productivity. Zooplanktons can also play an important role in food chain, indicating the presence or absence or in determining the population densities of certain fishes (Shinde et al., 2012). Population dynamics of zooplankton in fresh water reservoirs depend on a variety of factors. Bozkurt and Guven (2009) reported that abiotic factors such as dissolved oxygen, temperature and light influence the distribution of species. Shashikanth et al. (2008) focused on biotic factors (predation and competition) that can play a major role in seasonal variation of zooplankton species. Sellami et al. (2011) claimed that local factors i.e., predation and competition had a significant role on for change in community structure and species richness of zooplankton.

Mustapha (2010) studied that concentration of nutrients, grazing pressure and reservoir hydrology were responsible for fluctuations in the density of plankton.

Imoobe (2012) held responsible flood during the rainy season for increased population density of zooplanktons. Nkwuda et al. (2013) hypothesized that floods could increase zooplankton species richness and reduce density. Neiff and Neiff (2003) observed that alterations of flood pulses were responsible for changing the structure and dynamics of the aquatic communities. Ward and Tockner (2001) concluded that flood change the water quality of lakes by mixing cool, nutrient and oxygen rich water. Okogwu and Ugwumba (2012) suggest that flood mixes the autochthonous materials in lake and extends its width and affected zooplankton community in floodplain. Lansac-TA'ha et al. (2004) and Bonecker et al. (2005) argued the influence of the water level on the structure and dynamics of zooplanktons in the floodplains.

Gorski et al. (2013) observed that connectivity of floodplain habitats govern population dynamics of zooplanktons. Ward and Stanford (1995) observed that connectivity among the different floodplain environments affected the aquatic community structure, through allowing the exchange of fauna that increases productivity. They argued the interchange of micro-fauna between different environments responsible for increasing the productivity of the interconnected floodplains. Aoyagui and Bonecker (2004) argued that the connectivity favoured species richness than abundance. Loverde-Oliveira et al. (2009) and Fantin-Cruz et al. (2010, 2011) submitted that fluctuations in water level and temporary connectivity of the river channel with adjacent floodplain resulted in changing the spatial and temporal patterns of present communities.

Planktons are supposed to be a reliable tool to assess the pollution status of aquatic bodies. Any slight change in environmental conditions can lead to the change in plankton communities. Zooplanktons have long been used as pollution indicators (Webber et al., 2005), played an important role and served as bioindicators for understanding water pollution status (Contreras et al., 2009; Davies and Otene, 2009).

Pakistan floodplain ecosystems are poorly studied with respect to abundance and distribution of rotifers. These ecosystems, being situated in the tropics constitute a favourable habitat for species-rich communities. Only routine limnological surveys of rivers, lakes and in some fish ponds had been conducted and not from floodplains. The aims of this study were: i) to analyze the physicochemical parameters of water of a floodplain lake of river Ravi located in District Kasur, Pakistan; ii) to determine abundance and distribution of Rotifers community; iii) to investigate any correlation between physical and chemical parameters of water and rotifers abundance.

MATERIALS AND METHODS

Study area

The floodplain under study is situated on the River Ravi near Balloki Headworks in District Kasur, Pakistan. It is about 65 Km (42 miles) away from Lahore in south-west direction at Latitude: 31 11' 25" North and Longitude: 73 52' 40" East (Fig.1). The floodplain covers an area of about 8.6 square Km. The climate is tropical with a marked monsoonal season. Average atmospheric temperature ranges from a minimum of 5C in winter to a maximum of 50C in summer (Hussain et al., 2013). Average monthly mean rainfall ranges from 6.7mm to 199.6 mm (mean 52.01mm) with minimum in November and maximum in July, 2012 and humidity 70.40%. Water level varies in different months of the year, being lowest in winter (October to April) and highest in summer (July to August) every year.

Water sampling for physicochemical parameters

Monthly variations of physicochemical characteristics of water were studied from January to December, 2012. Samples were taken from surface, from 15 different sites between 9.0 A.M. to 5.0 P.M., usually, in 2nd but sometimes in the 3rd week of every month (Fig. 2). Three samples were collected from each sampling site (taking 45 samples in total). Atmospheric and water temperature (C), pH, dissolved oxygen (mg/l), electrical conductivity (uS/cm), total dissolved solids (mg/l), turbidity (NTU) and transparency (cm) were measured on the spot with their respective meters. Secchi disc was used to measure transparency. For the determination of total alkalinity (mg/l), total hardness (mg/l), and chlorides (mg/l), water samples were taken in one litre sampling bottles and transported in ice container to the Laboratories at Govt. College University, Lahore, for further processing (APHA, 2005; Hach, 2003).

Plankton sampling

Plankton samples were taken on monthly basis using standard plankton net of mesh size 37u (Wisconsin net). Three samples were collected from each sampling site (taking 45 samples in total). Sampling for zooplankton was carried out by horizontal towing of the net on a boat for about two meters, holding the net firmly in hand while sitting on boat. Sampled volume was calculated after Perry (2003). Samples were kept in 50 m1 plastic bottle and preserved in 4-5% formaldehyde solution (Koste, 1978).

Counting and identification of rotifers

Rotifers were counted in Sedgwick-Rafter counting chamber (AHPA, 1995) at 60-100x using an inverted Olympus microscope. Rotifers were identified on the basis of different morphological characters, size, shape and behavior of rotifers (Ward and Whipple, 1959; Koste, 1978, Pennak, 1978). Live organisms were also observed under the microscope, after staining with vital stain (1% neutral red), in order to study some of the internal features of the organisms. Photographs of specimens were taken with the help of microscope LEICA HC 50/50 microscope with 5 megapixel camera fitted on it, for identification of Rotifers.

Diversity indices

Shannon and Simpson diversity indices were calculated, (Shannon and Weaver, 1949, Simpson, 1949), Species richness (SR) was calculated after Margalef (1951) and Species evenness or equitability (E) was calculated after Pielou (1966), to study the abundance and distribution of species in the floodplain of river Ravi near Balloki Headwork's in Pakistan.

Statistical analysis

Different statistical techniques such as Analysis of variance (ANOVA) and Correlation matrix (Pearson's correlation), were used to investigate the significance level of Rotifer density and to find the relationship between rotifers and physicochemical parameters. Samples were collected from 15 different sites in each month. Three samples were taken from each sampling site so that ANOVA be applied. MINITAB 2013 and SPSS 16 (statistical package) programs were used to analyze the data.

RESULTS AND DISCUSSION

Seasonal variations of different physicochemical parameters observed during the whole period of study are shown in (Fig. 2). According to this atmospheric temperature was found maximum in April (40.32C) and minimum in January (16.62C). Water temperature was recorded maximum in July (33.8C) and minimum in December (14.15C). Present investigation revealed that air and water temperature followed almost similar pattern. It was mainly due to the seasonal and climatic variations in the region. Similar trend was studied by Caldwril (2003) and Kolo and Oladimeji (2004).

pH was found maximum in July (8.5) and minimum in December (6.8). The increase in pH in warm months might be due to the increase of carbonates, nitrates and phosphates ultimately resulting in eutrophication in summer. Similar findings had also been reported by Kamble et al. (2009). Sudden decrease in pH in August might be due to diluting effect of incoming colder water into the stagnant comparatively warmer water of flood plain. In the result of lowering of water temperature, production of CaCO3 is decreased, resulting into lowering of pH. Where as in September, influx of flood water into stagnant floodplain water is reduced, which results in increase in pH in these months again. Araoye (2009) and Mustapha (2009) had also reported similar findings.

Dissolved oxygen was maximum in January (9.46 mg/L) and minimum in June (5.0 mg/L). Increase in oxygen concentration in July might be due to the stirring effect of rain influx of rain and flood water. Low concentration of oxygen in summer (from March to June) was due to the decreased solubility of oxygen during warmer months, Oxygen concentration increased in August due to stirring effect of incoming colder flood water. Similarly, higher concentration of oxygen during winter was due to increased solubility of oxygen during colder months, along with the stirring effect of rain and flood water in July and August. Similar observations, regarding increase or decrease of oxygen, in the result of rain or flood water and decrease or increase of water temperature during winter or summer, were recorded by Morrison et al. (2001) and Hussain et al. (2013).

Electrical conductivity and total dissolved solids were the highest in June (330 uS/cm) and the lowest in January (232.76 uS/cm). Increase in their values in summer was due to the evaporation factor resulting in decrease in total quantity of water (minimum water level in June i.e., 11 feet) and increased water level in August and September (maximum water level i.e., 15 feet) was due to the dilution factor. These observations were in agreement with the findings of Mustapha (2009), Singh et al. (2010), Samal (2011) and Mirza et al. (2013).

Total dissolved solids were maximum in June (211.2 mg/L) and minimum in January (148.97 mg/L). Turbidity ranges from monthly mean values of 4.62 NTU to 63.7 NTU, being highest in July and the lowest in February. Visibility was the highest in December (150 cm) and the lowest in July (30.48 cm). Inverse relationship was observed between turbidity and visibility. Temporal behavior of turbidity and visibility was not noted. Mirza et al. (2013) and Khan and Chaudhury (1994) also recorded similar observations. Total hardness was recorded maximum in June (160 mg/L) and minimum in August (120 mg/L). Total alkalinity was found maximum in June (119 mg/L) and minimum in August (100 mg/L). Total hardness and total alkalinity also followed the same pattern and expresses no casual relationship. Concordant observations were also showed by Ratushnyak et al. (2006) and Park and Shin (2007). The values of chloride contents were the highest in January (34.93 mg/L) and the lowest in August (20 mg/L).

Monthly fluviometric level, measured during the period of studies and rainfall (mm), reported by Pakistan Metrological Department (PMD), are presented in Figure 3. Fluviometric level was recorded highest in August and September (15.0 feet) and minimum in June (11.0 feet). Similarly monthly rainfall was recorded highest in July (199.6 mm) and minimum in November (6.6 mm).

In the present study a total of 101 species of rotifers belonging to 32 genera and 15 families were identified (from January 2012 to December 2012) (Table I). Seasonal variations of rotifer density (Fig. 4) showed higher values from April to June, being maximum in June (1300 Ind./L). Rotifer density was the lowest in December and January (570 and 572). Similar results have been reported by Anderson et al. (2004), Mageed and Heikal (2006), Scholl and Kiss (2008), Sulehria et al. (2009a, 2009b, 2013), Sharma (2011), Nkwuda et al. (2013), Sulehria and Malik (2013) and Manckam et al. (2014).

Rotifer diversity also showed seasonal variation. Higher values occurred in August (40.0 species) and lower values from December to April (34.0 species) (Fig.5). Species diversity was higher from May to August anzd decreased from September to April. Higher diversity of rotifers from May to August might be attributed to the production of new species in summer and inflow of large amount of river water into the flood plain water during monsoon, which brought different types of riverine species. into the floodplain. An interesting observation was made between density and diversity of rotifers with respect to fluviometric level i.e., higher diversity of rotifers was recorded during maximum floviometric level and vice versa. It could be due to the fine niche partitioning among zooplankton species in combination with the micro-and macro-habitat heterogeniceity as hypothesized by Segers (2008).

Highest richness and diversity values at maximum fluviometric level were also observed by Hoberg et al. (2002); Lansac-TA'ha et al. (2004): Aoyogui and Bonecker, (2004b) and Borges and Pedrozo (2009). Thomaz et al. (2007) had also justified the increasing rotifer diversity during increased river water level due to increased connectivity of the floodplain with river which increased the exchange of propaguules, nutrients and organisms among the habitats alongwith the decreased competition among species.

Pearson's Correlation matrix (Table II) was used to find correlation between rotifer density and different physicochemical parameters. According to this rotifer density was showed positive correlated with air temeperature (0.5539C), water temperature (0.5759C), pH (0.4277), electrical conductivity (0.9137 uS/cm), total dissolved solids (0.9137 mg/L), turbidity (0.1889 NTU), total hardness (0.5599 mg/L) and totall alkalinity (0.6648 mg/L) where as rotifers negatively correlated with dissolved oxygen (0.6893 mg/L), visibility (0.3301 cm) and chlorides (0.0921 mg/L).

According to ANOVA (Tables III, IV) there was a statistically (highly) significant difference (P=0.00) in number of rotifers among different groups i.e., months. Similarly there was a non-significant difference (P=0.00) in number of rotifers between different sites, (F=10.170 and different months (F=7.884).

Shannon diversity index (H) of the floodplain (mean calculated using all samples) ranged from 2.21 to 3.14 being lowest in November and highest in August respectively. Simpson index of dominance was lowest in April (0.06) and highest in November (0.17). Highest species diversity recorded in floodplain in August (40 species) is due to the mixing of river water with the floodplain water. River water brings with it the different species present in river, increasing the diversity of Rotifers in flood plain habitats. Similar observations have been recorded by Lansac-TA'ha et al. (2004), Aoyogui and Bonecker, (2004b) and Borges and Pedrozo, (2009). The mean value of species richeness of all samples was highest in August (7.50) and lowest in April (6.00). High value of richness in August showed the highest food chain during August because in August connectivity of flood plain with river increases the exchange of water, minerals, sediments and other organisms between the two habitats.

Similarly diluting effect in floodplain habitat reduces competition among different species, which ultimately improves the species diversity in that specific habitat. Species evenness was the highest in April (0.9) and the lowest in November (0.6) showing the even distribution of species in April (Fig.6).

Table I.-List of Rotifer species collected from floodplains of River Ravi near Balloki Headwork's, Pakistan, from January, 2012 to December, 2012.

1. Philodinidae

###1. Philodina###1. Philodina roseola Ehrenberg

###2. Philodina megalotrocha Ehrenberg

###2. Rotaria###3. Rotaria tridens (Montet)

###4. Rotaria neptunia (Ehrenberg)

###5. Rotaria rotatoria (Pallas)

###6. Rotaria haptica (Gosse)

2. Branchionidae

###1. Anuraeopsis###7. Anuraeopsis fissa (Gosse)

###8. Anuraeopsis navicula Rousselet

###9. Anuraeopsis coelata (De Beauchamp)

###2. Brachionus###10. Brachionus bidentatus Anderson

###11. Brachionus leydigi Cohn

###12. Brachionus quadridentatus Hermann

###13. Brachionus falcatus Zacharias

###14. Brachionus plicatilis (Muller)

###15. Brachionus variabilis (Hampel)

###16. Brachionus calciflorus Palls

###17. Brachionus diversicornis (Daday)

###18. Brachionus forficula Wierzejski

###19. Brachionus angularis Gosse

###20. Brachionus dichotomus Shephard

###21. Brachionus caudatus Barrois and Daday

###3. Euchlanis###22. Euchlanis dilatata Ehrenberg

###4. Keratella###23. Keratella tropica (Apstein)

###24. Keratella valga (Ehrenberg)

###25. Keratella lenzi Hauer

###26. Keratella cochlearis (Gosse)

###27. Keratella tecta (Lauterborn)

###5. Mytilina###28. Mytilina mucronata (Muller)

###6. Notholca###29. Notholca acuminata (Ehrenberg)

###7. Platyias###30. Platyias patulus (Muller)

###8. Proalides###31. Proalides tentaculatus de Beauchamp

###9. Colurella###32. Colurella uncinata (Muller)

###33. Colurella adriatica Ehrenberg

###10. Lepadella###34. Lepadella patella (Muller)

###35. Lepadella triba Myers

###36. Lepadella latusinus (Hilgendorf)

###37. Lepadella vitrea (Shephard)

###38. Lepadella acuminata Ehrenberg)

###11. Squatinella###39. Squatinella rostrum (Schmarda)

3. Lecanidae

###1. Lecane###40. Lecane pertica Harring and Myres

###41. Lecane luna (Muller)

###42. Lecane crepida (Harring)

###43. Lecane ungulata (Gosse)

###2. Monostyla###44. Monostyla obtusa Murray

###45. Monostyla tethis Harring and Myers

###46. Monostyla elachis Harring and Myers

###47. Monostyla subulata Harring and Myers

###48. Monostyla cornuta (Muller)

###49. Monostyla bulla Gosse

###50. Monostyla lunaris (Ehrenberg)

###52. Monostyla closterocerca Schmarda

###53. Monostyla hamata Stokes

4. Proalidae

###1. Proales###54. Proales sordida Gosse

5. Notommatidae

###1. Cephalodella###55. Cephalodella gibba (Ehrenberg)

###56. Cephalodella steria (Gosse)

###57. Cephalodella auriculata (Muller)

###2. Eosphora###58. Eosphora najas Ehrenberg

###3. Monommata###59. Monommata grandis / Tessin (Matchc

###shap?)

6. Lindiidae

###1. Lindia###60. Lindia deridderi koste

7. Trichocercidae

###1. Trichocerca###61. Trichocerca vernalis Hauer

###62. Trichocerca collaris (Rousselet)

###63. Trichocerca rousseletti (Voigt)

###64. Trichocerca ruttneri (Dnner)

###65. Trichocerca branchyura (Gosse)

###66. Trichocerca cavia (Gosse)

###67. Trichocerca porcellus (Gosse)

###68. Trichocerca cylindrica (Imhof)

###69. Trichocerca bicristata (Gosse)

###70. Trichocerca similis (Wierzejski)

###71. Trichocerca elongata (Gosse)

###72. Trichocerca stylata (Gosse)

###73. Trichocerca pusilla (Jennings)

8. Gastropidae

###1. Ascomorpha###74. Ascomorpha ecaudis Perty

###75. Ascomorpha saltans Bartsch

9. Asplanchnidae

###1. Asplanchna###76. Asplanchna priodonta Gosse

###77. Asplanchna herricki (De Guerne)

###78. Asplanchna girodi De Guerne

###79. Asplanchna brightwelli (Gosse)

10. Synchaetidae

###1. Polyarthra###80. Polyarthra dolichoptera Idelson

###81. Polyarthra vulgaris Carlin

###82. Polyarthra minor Voigt

###83. Polyarthra remata (Shorikov)

###2. Synchaeta###84. Synchaeta tremula (Muller)

###85. Synchaeta lakowitziana Lucks

###86. Synchaeta tavina Hood

###87. Synchaeta oblonga Ehrenberg

###88. Synchaeta litoralis Rousselet

###89. Synchaeta stylata Wierzejski

###90. Synchaeta longipes gosse

###Synchaeta jollyi Shiel and Koste

11. Microcodonidae

###1. Microcodon###91. Microcodon sp.

12. Testudinellidae

###1. Filinia###92. Filinia opoliensis (Zacharias)

###93. Filinia pejleri Hutchinson

###94. Filinia terminalis Plate

###95. Filinia passa (Muller)

###96. Filinia longiseta (Ehrenberg)

###2. Testudinella###97. Testudinella patina (Hermann 1783)

13. Hexarthridae

###1. Hexarthra###98. Hexarthra sp.

14. Flosculariidae

###1. Beauchampia###99. Beauchampia sp.

15. Colothecidae

###1. Atrochus###100. Atrochus tentaculatus Wierzejski

###2. Collotheca###101. Colotheca coronetta Cubitt

Table II.- Pearson's correlation matrix of rotifer density and different physiochemical parameters in floodplain of river Ravi, Pakistan, from January, 2012 to December, 2012.

Variables###Rotifer###Air###Water###Dissolved###Electrical###TDS###Turbidity###Visibility###Total###Total###Chlorides

###density###Temp.###Temp.###pH###oxygen###Cod.###(mg/L)###(NTU)###(cm)###hardness###alkalinity###(mg/l)

###(Ind./L)###(C).###(C).###(mg/L)###(uS/cm)###(mg/L)###(mg/l)

Rotifer density (Ind./L)###1###0.55###0.58###0.43###-0.69###0.91###0.91###0.19###-0.33###0.56###0.66###-0.09

Air temperature (C).###0.55###1###0.95###0.71###-0.89###0.52###0.51###0.47###-0.54###0.49###0.39###-0.24

Water temp. (C).###0.57###0.95###1###0.79###-0.92###0.55###0.55###0.6###-0.69###0.33###0.29###-0.46

pH###0.43###0.71###0.79###1###-0.62###0.44###0.44###0.59###-0.7###0.26###0.23###-0.3

Dissolved oxygen (mg/L)###-0.69###-0.89###-0.92###-0.63###1###-0.71###-0.71###-0.44###0.56###-0.48###-0.41###0.32

Electrical Cod. (uS/cm)###0.91###0.52###0.55###0.44###-0.71###1###1###0.08###-0.2###0.6###0.72###-0.06

TDS (mg/L)###0.91###0.52###0.55###0.44###-0.71###1###1###0.08###-0.2###0.6###0.72###-0.06

Turbidity (NTU)###0.19###0.48###0.6###0.59###-0.44###0.08###0.078###1###-0.76###0.13###-0.08###-0.33

Visibility (cm)###-0.33###-0.54###-0.69###-0.7###0.56###-0.2###-0.2###-0.76###1###0.01###0.19###0.55

Total hardness (mg/L)###0.56###0.49###0.33###0.26###-0.48###0.6###0.6###0.13###0.01###1###0.81###0.59

Total alkalinity (mg/l)###0.66###0.39###0.29###0.23###-0.41###0.72###0.72###-0.08###0.19###0.81###1###0.36

Chlorides (mg/l)###-0.09###-0.24###-0.46###-0.3###0.32###-0.056###-0.06###-0.33###0.55###0.59###0.36###1

Table III.-Analysis of Variance of rotifers between different months in floodplain of river Ravi, Pakistan, from January 2012 to December 2012.

No.of rotifers###ANOVA

###Sum of Squares###Df###Mean Square###F###Sig.

Between Groups (Months)###693142.515###11###63012.956###7.884###.000

Within Groups###1342779.062###168###7992.733

Total###2035921.577###179

Table IV.-Analysis of Variance of rotifers between different Sites in floodplain of river Ravi, Pakistan, from January, 2012 to December, 2012.

No.of rotifers###ANOVA

###Sum of Squares###Df###Mean Square###F###Sig.

Between Groups (Months)###943046.406###14###67360.458###10.170###.000

Within Groups###1092875.170###165###6623.486

Total###2035921.577###179

CONCLUSIONS

The greatest species density and diversity of rotifers was observed during warm months of the year i.e., from May to August. It may be attributed to food availability, rapid reproduction rates and suitability of the physicochemical parameters of water such as water temperature, pH, turbidity, total hardness, electrical conductivity, total dissolved solids (TDS) and total alkalinity which were positively correlated with rotifer's abundance. High rotifer diversity during high fluviometric level, suggests the connectivity of the two habitats during flood seasons that favors the exchange of materials and organisms between two habitats which ultimately improves the food chain. A significant difference in rotifer density and diversity was found among different months and sites. Shannon diversity index (H) showed presence of high species diversity in the floodplain in August. Simpson index of dominance also supported this fact. Species richness was highest in August and lowest in April.

Species evenness was highest in April and lowest in November. A more comprehensive study of floodplain is recommended as floodplains are rich in zooplanktons and are potential source of fish.

ACKNOWLEDEMENTS

I am grateful to the Department of Sustainable Development Study Centre, GC University, Lahore and Department of Fisheries, Punjab, Lahore, for providing the the necessary instruments, used during the present research.

Conflict of interest statement

Authors have declared no conflict of interest.

REFERENCES

Abdul-Razak, A., Asiedu, A.B., Entsua-Mensah, R.E.M. and Degraft-Johnson, K.A.A., 2009. Assessment of water quality of the Oti River in Ghana. West. Afr. J. Appl. Ecol., 15: 45-60.

APHA (American Public Health Association), 2005. Standards methods for the examination of water and wastewater. 21st Ed. Washington, D.C., USA.

Ayodele, H.A. and Adeniyi, I. F., 2006. The zooplankton fauna of six impoundments on the river Osum, Southern Nigeria. The Zoologist, 1: 49-67.

Anderson, S., Aoyagui, M. and Bonecker, C.C., 2004. Rotifers in different environments of the Upper Parana River floodplain (Brazil): richness, abundance and the relationship with connectivity. Hydrobiologia, 522: 281-290.

Araoye, P.A., 2009. The seasonal variation of pH and dissolved oxygen (DO2) concentration in Asa lake Ilorin, Nigeria. Int. J. Phys. Sci., 4: 271-274.

Baloch, W.A., Soomr o, A.N. and Buledi, G.H., 2008. Zooplankton, especially Rotifer and Cladoceran communities of the spring and rainwater streams (Nai) in Kirthar range, Sindh, Pakistan. Sindh Univ. Res. J. (Sci. Ser.), 40: 17-22.

Borges, M.G. and Pedrozo, C.S., 2009. Zooplankton (Cladocera, Copepoda and Rotifera) richness, diversity and abundance variations in the Jacui Delta, RS, Brazil, in response to the fluviometric level. Acta Limnol. Bras., 21: 101-110.

Bonecker, C.C., Costa, C.L.D., Velho, L.F.M. and LansactA'ha, F. A., 2005. Diversity and abundance of the planktonic rotifers in different environments of the Upper Parana River floodplain (Parana State - Mato Grosso do Sul State, Brazil). Hydrobiologia, 546: 405-414.

Bozkurt, A. and Guven, S.E., 2009. Zooplankton composition and distribution in vegetated and unvegetated area of three reservoirs in Hatay, Turkey. J. Anim. Vet. Adv., 8: 984-994.

Caldwril, B.A., 2003. Watershed protection. Plan Development Guide book, Northeast Georgia Regional Development centre. (internet).

Contreras, J.J., Sarma, S.S.S., Merino-Ibarra, M. and Nandini, S., 2009. Seasonal changes in the Rotifer (Rotifera) diversity from a tropical high altitude reservoir (Valle de Bravo, Mexico). J. environ. Biol., 30: 191-195.

Davies, O.A. and Otene, B.B., 2009. Zooplankton community of Minchida stream, Port Harcourt, River State, Nigeria. Eur. J. Sci. Res., 26: 490-498.

Edward, J.B. and Ugwumba, A.A., 2010. Physico-chemical parameters and plankton community of Egbe Reservoir, Ekiti State, Nigeria. Res. J. biol. Sci., 5: 356-367.

Fantin-Cruz, I., Pedrollo, O., Bonecker, C. C., Motta-Marques, D. and Loverde-Oliveira, S., 2010. Zooplankton density in flood lake (Pantanal-Brazil) using artificial neural networks. Int. Rev. Hydrobiol., 95: 330-342.

Fantin-Cruz, I., Loverde-Oliveira, S., Costa-Bonecker, C., Girad, P. and Motta-Marques, D., 2011. Relationship between the structure of zooplankton community and the water level in a floodplain lake from the Pantanal, Mato Grosso State, Brazil. Acta Scient. Biol. Sci., 33: 271-279.

Gorski, K., Collier, K.J, Duggan, I.C, Taylor, C. M. and Hamilton, D., 2013. Connectivity and complexity of floodplain habitats govern zooplankton dynamics in large temperate river system. Freshwat. Biol., 58: 1458-1470.

HACH, 2003. Water analysis handbook: Hach Chemical Company, Loveland, Colorodo, USA. 1268pp.

Hoberg, P., Lindholm, M., Ramberg, L. and Hessen, D.O., 2002. Aquatic food web dynamics on a floodplain in the Okavango delta, Botswana. Hydrobiologia, 470: 23-30.

Hussain, A., Sulehria, A.Q., Ejaz, M. and Maqbool, A., 2013. Monthly variations in physicochemical parameters of a flood plain reservoir on River Ravi near Balloki Headworks (Pakistan). Biologia (Pakistan), 59: 371-377.

Imoobe, T.O.T., 2012. Diversity and seasonal variation of zooplankton in Okhuo River, a tropical forest river in Edo State, Nigeria. Centrepoint J., 17: 37-51.

Imoobe, T.O.T. and Adeyinka, M.L., 2010. Zooplankton-based assessment of the trophic state of a tropical forest river. Int. J. Fish. Aqucacult., 2: 64-70.

Kamble, S.M., Kamble, A.H. and Narke, S. Y., 2009. Study of physicochemical parameters of Ruti dam, Tal. Ashti, dist. Beed, Maharashtra. J. aquat. Biol., 24: 86-89.

Khan, M.A.G. and Chowdhary, S. M., 1994. Physical and chemical limnology of Lake Kaptai, Bangladesh. Trop. Ecol., 35: 35-51.

Kolo, R.J. and Oladimeji, A.A., 2004. Water quality and some nutrient levels in Shiroro Lake, Niger State, Nigeria. J. aquat. Sci., 19: 99-106.

Koste, W., 1978. Rotatoria. Die Radertiere Mitteleuropas. Ein Bestimmungswerk, begrundet von Max, vol. 1, 2. Voigt Uberordnung Monogononta (Germany), pp. 907.

Lashari, K.H., Naqvi, S.H., Palh, Z.A., Laghari, Z. A., Mastoi, A.A., Sahato, G.A. and Mastoi, G.M., 2014. The effects of physiochemical parameters on planktonic species population of Keenjhar lake, district Thatta, Sindh, Pakistan. Am. J. BioSci., 2: 38-44.

Lansac-TA'ha, F.A., Bonecker, C.C. and VELHO, L. F.M., 2004. Composition, species richness and abundance of the zooplankton community. In: The Upper Parana River and its floodplain: physical aspects, ecology and conservation (eds. S.M. Thomaz, A. A. Agostinho and N. S. Hahn), Backhuys Publishers, Leiden, pp. 145-190.

Loverde-Oliveira, S.M., Huszar, V.L.M., Mazzeo, N. and Scheffer, M., 2009. Hydrology-driven regime shifts in a shallow tropical lake. Ecosystems, 12: 807-819.

Mageed, A.A.A. and Heikal, M.T., 2006. Factors affecting seasonal pattern in epilimnion zooplankton community in one of the largest man-made lake in Africa (Lake Nasser, Egypt). Limnologica, 36: 91-97.

Mahar, M.A., Baloch, W.A. and Jafri, S.I.H., 2000. Diversity and seasonal occurrence of planktonic rotifers in Manchar Lake, Sindh, Pakistan. Pakistan J. Fish. 1: 25-32.

Manickam, N., Saravana, B.P., Santhanam, P., Muralisankar, T., Srinivasan, V., Radhakrishnan, S., Vijayadevan, K., Chitrarasu, P. and Jawahar, A., 2014. Seasonal variation of zooplankton diversity in a perennial reservoir at Thoppaiyar, Dharmapuri district, south India. Austin. J. Aquacul. Mar.Biol. 1: 1-7.

Margalef, R. 1951. Diversidad de especies en las comunidales naturales. Publ. Inst. Biol. Apl., 9: 5-27.

Mirza, Z.S., Muhammad, S.N., Beg, M.A. and Malik, I., 2013. Spatial and temporal fluctuations in the physicochemical limnology of Mangla Dam (Pakistan). Pakistan J. Zool., 45: 679-686.

Morrison, G., Fatoki, O.S., Persson, L. and Ekberg, A., 2001. Assessment of the impact of point source of pollution from the sewage treatment plant on the Keiskamma river-PH, electric conductivity, oxygen-demanding substance (COD) and nutrients. Water, S. A., 27: 475-480.

Mustapha, M.K., 2009. Limnological evaluation of the fisheries potentials and productivity of a small shallow tropical African reservoir. Rev. biol. Trop., 57: 1093-1106.

Mustapha, K.M., 2010. Seasonal influence of limnological variables in plankton dynamics of a small, shallow, tropical African reservoir. Asian J. exp. biol. Sci., 1: 60-79.

Neiff, J.J. and Neiff, M., 2003. Planicies de Inundacao Sao Ecotonos? In: Ecotonos nas interfaces dos ecossistemas aquaticos (ed. R. Henry), Sao Carlos, Rima, pp. 29-46.

Nkwuda, G., Nwonumara and Okogwu, O. I., 2013. The impact of flooding on water quality, zooplankton composition, density and biomass in Lake Iyieke, Cross River-Floodplain, Southeastern Nigeria. Zool. Ecol., 23: 138-146.

Okogwu, O.I. and UGWUMBA, A.O., 2013. Seasonal dynamics of phytoplankton in two tropical rivers of varying size and human impact in Southeast Nigeria. Rev. biol. Trop., 61: 1827-1840.

Park, K.S. and Shin, H. W., 2007. Studies on phyto and zooplankton composition and its relation to fish productivity in a west coast fish pond ecosystem. J. environ. Biol., 28: 415-422.

Pennak, R.W., 1978. Fresh water invertebrates of the United States. 2nd Ed. Wiley, New York. 803 pp.

Perry, R., 2003: A guide to the marine plankton of southern California, 3 rd. edition. Ucla Ocean Globe, pp. 1-23.

Pielou, E.C., 1966. The measurement of diversity in different types of biological collections. J. Theoret. Biol. 13: 131-144.

Ratushnyak, A.A., Borisovich, M.G., Vallev, V.S., Ivanov, D. V., Andreeva, M.G. and Trushin, M.V., 2006. The hydrochemicla and hydrobiological analysis of the condition of the kuibyshev reservoir littorals (Republic of Tatarstan, Russia). Ekoloji, 15: 22-28.

Saron, T. and Meitei, L. B., 2013. Seasonal variation of zooplankton population with reference to water quality of Iril River in Imphal. Curr. World Environ., 8: 133-141.

Scholl, K. and Kiss, A., 2008. Spatial and temporal distribution patterns of zooplankton assemblages (Rotifera, Cladocera, Copepoda) in the water bodies of the Gemenc Floodplain (Duna-Drava National Park, Hungary). Opusc. Zool. Budapest, 39: 65-76.

Sellami, I., Guermazi, W., Hamza, A., Aleya, L. and Ayadi, H., 2011. Seasonal dynamics of zooplankton community in four Mediterranean reservoirs in humid area (Beni Mtir: north of Tunisia) and semiarid area (Lakhmes, Nabhana, and Sidi Saad: center of Tunisia). J. Therm. Biol., 35: 392-400.

Singh, M.R., Gupta, Asha and Beeteshwari, K., 2010. Physico-chemical factors of water samples from Manipur River System, India. J. appl. Sci. environ. Manage., 14: 85-89.

Samal, N.R., 2001. Physiological and biological characteristics of water of lake Rabindra Sarovar, the National Lake, Kolkata, India. Thesis submitted to School of Water Resource Engineering, Jadavpur University, Kolkata.

Segers, H., 2008. Global diversity of rotifers (Rotifera) in freshwater. Hydrobiologia, 595: 49-59.

Shannon, C.E. and Weaver, W., 1949. The mathematical theory of communication. University of Illinois Press, Urbana, IL, USA.

Sharma, B.K., 2011. Zooplankton diversity of two floodplain lakes (pats) of Manipur, northeast India. Opusc. Zool. Budapest, 42: 185-197

Shashikanth, M., Vijaykumar, K., Rajshekhar, M. and Vasanthkumar, B., 2008. Chemistry of groundwater in Gulbarga district, Karnataka, India. Environ. Monit. Assess., 136: 347-354.

Shinde, S.E., Pathan, T.S. and Sonawane, D. L., 2012. Seasonal variations and biodiversity of zooplankton in Harsool-Savangi Dam, Aurangabad, India. J. environ. Biol., 33: 741-744.

Simpson, E.H., 1949. Measurement of diversity. Nature, 163: 688.

Sulehria, A.Q.K., Qamar, M.F., Haider, S., Ejaz, M. and Hussain, A., 2009a. Seasonal fluctuations of rotifers in a fish pond at district Bahawalnagar, Pakistan. Biologia (Pakistan), 55: 21-28.

Sulehria, A.Q.K., Qamar, M.F., Anjum, R.F., Ejaz, M. and Hussain, A., 2009b. Water quality and Rotifer diversity in the fish pond at district Mianwali, Pakistan. Biologia (Pakistan), 55: 79-85.

Sulehria, A.Q.K and Malik, M.A., 2012. Population dynamics of planktonic rotifers in Balloki Headworks. Pakistan J. Zool., 44: 663-669.

Sulehria, A.Q.K., Mirza, Z.S., Faheem, M. and Zafar, N., 2013. Diversity Indices of epiphytic rotifers of a floodplain. Biologia (Pakistan), 59: 33-41.

Sulehria, A.Q.K. and Malik, M. A., 2013. Diversity indices of pelagic rotifers in Camp Balloki Water Park, Lahore, Pakistan. Turk. J. Zool., 37: 699-705.

Thomaz, S.M., Bini, L.M. and Bozelli, R.L., 2007. Floods increase similarity among aquatic habitats in river-floodplain systems. Hydrobiologia, 579: 1-13.

Ward, J.V. and Tockner, K., 2001. Biodiversity: towards a unifying theme for river ecology. Freshw. Biol., 46: 807-819.

Ward, J.V. and Stanford, J.A., 1995. Ecological connectivity in alluvial river ecosystems and its disruption by flow regulation. River Res. Appl., 11: 105-119.

Ward, H.B. and Whipple, G.C., 1959. Fresh water biology. 2nd Ed. John Wiley and Sons. New York. 1248 pp.

Webber, M.M., Edward, E., Cambell, C. and Webber, D., 2005. Phytoplankton and zooplankton as indicators of water quality in Discover y Bay, Jamaica. Hydrobiologia, 545: 177-193.
COPYRIGHT 2016 Asianet-Pakistan
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Hussain, Altaf; Sulehria, Abdul Qayyum Khan; Ejaz, Muhammad; Maqbool, Asma
Publication:Pakistan Journal of Zoology
Article Type:Report
Geographic Code:9PAKI
Date:Feb 29, 2016
Words:5965
Previous Article:In vitro and in vivo Sensitivity of a Flagellated Protozoan, Histomonas meleagridis, to Metronidazole and Nitarsone.
Next Article:Effect of Polysorbate 80 Through Rabbit's Skin Using Transdermal Patch Loaded with Bisoprolol Fumarate as Model Drug.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |