A Preliminary Investigation of Phytoplankton and Zooplankton Diversity in Marine Water Ponds, Thatta, Sindh, Pakistan

Phytoplankton serves as primary producers form the base of marine food web. They transfer energy to the higher trophic level species and there is no life in the aquatic system without them. While, zooplankton graze the phytoplankton found in varying depth in the pelagic environment. The occurrence of zooplankton mainly influences the pelagic fishery potentials, like fish grow and survive in those areas where the planktonic organisms are abundant, so that their young ones can get sufficient natural food. Zooplankton indicates ecological condition because they respond changes in the nutrient level and fish population, while population of phytoplankton is totally depending on the numerous environmental factors and varying nutrient transport seasonally (Yaqoob et al., 2013; Martins et al., 2020). It is verified that, plankton fulfill the nutritional requirement of farmed fish and shrimp species and also indicate the productivity of water (Coutinho et al., 2012; Gamboa-Delgado, 2014). The qualitative and quantitative abundance of plankton in a fish and shrimp pond has a great importance to manage the effective aquaculture operation, because they differ from place to place and pond to pond even within the similar location and ecological condition. Water quality of pond is necessary to determine the continuous limnological change and the optimal range of physicochemical parameters of water such as temperature, pH, total hardness, alkalinity, potassium, phosphate, nitrate, sulphate, DO, and BOD show appropriateness of water which are necessary for all aquatic life (Hossain et al., 2007; Durge et al., 2018). Moreover, water quality could directly affect the biological functions of fish such as feeding, breeding, swimming, metabolism and excretion (Shah et al., 2008; Kumar et al., 2017). Therefore, good quality of water is indispensable for better growth, survival and high production of fish for successful aquaculture (Ramanathan and Amsath, 2018). It is consider that, quality of pond water can be deteriorated by providing excessive commercial feed and fertilizers responsible for low concentrations of DO, high concentrations of NH3, NO2 and phosphorus (Tamizhazhagan and Pugazhendy, 2016; Bauer et al., 2017). Also, accumulation of excessive nutrients causes phytoplankton blooms in ponds, which are responsible for the polluted and anoxic condition (Wu et al., 2014). Apart from nutrients, fluctuation in temperature is responsible to curb primary productivity of water (Simmons et al., 2004). Several studies have been reported on the primary productivity and water quality assessment in fresh and brackish water bodies as well as in fish and shrimp ponds by (Hossain et al., 2007; Sahni and Yadav, 2012; Harney et al., 2013; Akter et al., 2015; Abbas et al., 2015; Abbasi et al., 2016; Durge et al., 2018; Ogbuagu et al., 2019; Akinpelu et al., 2019; Martins et al., 2020; Mermillod-Blondin, 2020; Khokhar et al., 2020). Worldwide, the study of planktonic abundance has been done under the priority in aquaculture ponds to assess the health of water but no prior study was reported on marine water ponds situated at Thatta district, Sindh, except coastal water of Arabian Sea, tidal creeks, lakes and fresh water ponds in Pakistan. For that reason, present study was conducted to evaluate the diversity and abundance of phytoplankton and zooplankton along with physicochemical parameters in semi-intensive marine water ponds.

This study was investigated for a period of one year (Jan-Dec, 2019). A total of four semi-intensive marine water ponds (1.3 ha) were selected for proposed study located in Thatta district, Sindh, Pakistan (Figure 1). Seawater was directly pumped into the ponds from canal because water primarily store into the canals from thetidal creek. All ponds were stocked with commercial marine water fish juveniles (Chanos chanos, Acanthopagrus berda, and A. latus) for polyculture.

Water samples were collected monthly between 10.00 AM to 12.00 PM noon. For the quantitative findings of plankton, water (16 liters) from different selected sites was filtered from each pond via conical plankton net (56 micron), and the depth of sampling was 10 to 25 cm. Sample (120 ml) were immediately fixed into plastic bottles with (5%) formalin. Samples were carried out into Aquaculture laboratory (CEMB, University of Karachi) and examined under a compound microscope (100x). Sample analysis was consisting of 1ml subsample for up to 6mL per sample for quantitative measurement through S-R counting chamber suggested by (Welch, 1948). Each row of chamber was carefully inspected and their total number per ml were noted and calculated as a mean value. Micro-pipetting method was used for in depth analysis of plankton by using a glass slide under microscope. Planktons were identified up to the genus level. Following key guide and literatures were used for the identification of plankton (Ward and Whipple, 1959; Newell and Newell, 1963; Pollock, 1998; Castellani and Edwards, 2017).

Physicochemical properties of selected pond water were examined on spot before providing test feed and collecting water samples, such as temperature (°C) with thermometer (digital), pH with meter (EzDO 6011, Taiwan), transparency (cm) by Secchi disk, salinity (ppt) by refractometer (Atago, S/Mill-E, 0.100‰, Japan), ammonia and DO (mgL-1) were observed by portable test kits (Merck KGaA, 64271, Germany). Nitrate and phosphate were assessed by Boyd (1981). However, the data was analyzed through the Duncan’s new multiple test range, and were presented as mean with the standard deviation (± SD) described by Steel et al. (1997).

Present study was conducted for a period of one year from January to December, 2019 for the investigation of planktonic abundance along with physicochemical characteristics of marine water ponds. It is noted that, plankton diversity is fluctuated with the physicochemical parameters of the water. So, the physical and chemical environment of the water mainly controls the diversity, species richness and population dynamics of planktons. The combined result of the physicochemical properties is presented in (Table 3). During present study, the average temperature of marine water ponds was recorded in the range of24.5 to 38.4°C. Temperature is one of the important factor that influence the plankton succession by controlling their behavioral characteristics (Welch, 1952). High atmospheric temperature speed up the evaporation rate in the water and induce positive correlation with copepods (zooplankton), because the better development of copepods were notice in warmer monthsand then deteriorate quickly, this coincide with the study of Winkler (2002), Heerkloss et al. (2005), Persaud et al. (2007), Sarkar et al. (2020). Furthermore, 18 to 38.0°C is an optimal range of water temperature for the abundance of plankton, specified by (Pulle and Khan, 2003; Gardner et al., 2008). Transparency is a physical parameter and it directly affects primary productivity of the water and also food web. In this study, transparency of water was recorded in the range of 27.1 to 44.8cm, while pH (7.0 to 8.5) was found in a suitable range as the pond water was well buffered and healthy during whole study period. It is reported that, pH of the pond water is likely to be higher during high photosynthetic activity by planktons (Abbas, 2001). DO value was found slightly higher (5.3 to 7.5 mgL-1) and no harsh effects on plankton was recorded due to less fluctuation in DO. Although, Rukhsana et al. (2021) recommended the optimal range of DO (3.70-8.38 mg/l) for aquaculture ponds alongside Sindh coast. Similar, findings with above parameters were reported by Ali et al. (2007), Akter et al. (2015), Abbasi et al. (2016); Shoaib et al. (2017). They also specified that the temperature of the water may influence the DO level. Alkalinity can directly affect the development of plankton and the total alkalinity of our ponds was recorded in the range of 111.6 to 146.3mgL-1 (Table 3). However, the optimal alkalinity range of an average productive water of pond was 20 to 400 mg per liter as reported by Bhuiyan et al. (1970), Hossain et al. (2007); Martins et al. (2020) and Rukhsana et al. (2021). Nitrates range of our studied ponds was recorded lower (3.9 mg/l to 21.3 mg/l) than recommended range (20 to 100 mg/l) for aquaculture ponds (Pilay, 1992).

A total 61 species of plankton have been recorded from the studied ponds and categorized into 19 groups, out of which 25 species of phytoplankton were grouped into four major groups are presented in (Table 1). Among major groups, the most abundant group was Bacillariophyta comprising 18 species. In which, Rhizosolenia sp. was abundantly found in the month of (FEB31.761% to MAR-40.416%), and both Skeletonema sp. and Chaetoceros sp1 in NOV (18.518% and 31.723%), respectively. Some taxa were found in all months such as (Rhizosolenia sp., Bacillaria sp., and Oscillatoria sp1). However, the other abundant group is Cyanophyta (Oscillatoriasp1) in the month of (MAY-45.721%, JULY-42.011% to AUG-50.710%). Meanwhile, the highest mean % was found in Bacillariophyta (69.815%)>Cyanophyta (28.302%) > Dinoflagellata (1.733%) > Prymnesiophyta (0.149%), mentioned in (Table 4).

Similarly, Harrison et al. (1997) and Yaqoob et al. (2013) reported the dominant phytoplankton species belonging to Bacillariophya group from the tidal creeks of Pakistan, and also indicating the export of nutrients from tidal creeks to coastal waters of Pakistan during NE monsoon winds. Although, some authors mentioned that the dominant group of phytoplankton is Cyanophyta as compared to Bacillariophyta by (Hossain et al., 2007; Erondu and Solomon, 2017; Martins et al., 2020). Because, Cyanophyta usually grow at high temperature while Bacillariphyta under low light or temperature as reported by (Vincent, 2009; Dai et al., 2012; Bellinger and Sigee, 2015; Kumar et al., 2017), this statement is similar to our study results.

Table 1: Monthly distribution of Phytoplankton population (percentage of the total) in marine water ponds.

About 36 zooplankton species belonging to fifteen major groups are presented in (Table 2). The most dominant group was found Copepoda (78.927%) mentioned in (Table 4). The abundancy of copepod species have been reported globally by many authors (Hossain et al., 2007; Ajuonu et al., 2011; Erondu and Solomon, 2017; Huang et al., 2020). However, 68% to 74.9% copepod abundance was reported from Pakistani coastal areas (Yaqoob et al., 2013; Abbasi et al., 2016). Among copepods, the dominant order was Calanoida > Cyclopoida > Harpacticoida, and they were abundant in different months, while their females carrying egg sacs in different months. Present study coincides with the results of (Jacobsen and Dangles, 2017). Although, nauplii stage of copepods was abundantly found in the month of (FEB-39.895% to MAY 36.639%). Although, other dominant occurrences of zooplankton were medusa in the month of (JAN-67.049%), while their mean % was 7.576 after copepods (Table 4), Tintinnida (NOV30.707%) and Foraminiferans (OCT-10.311% to NOV-10.054%). Some taxa found in all months such as copepoda, nematoda and other unspecified taxa (unidentified eggs), shown in (Table 2). Our results indicated various planktonic forms specifies healthy ecological condition of the marine water fish ponds.

Overall percentage of phytoplankton and zooplankton diversity were recorded during sampling and their monthly distribution is presented in (Tables 5). The highest abundancy of phytoplankton was found in the month of November (18.559%), while zooplankton in the month of July (16.560%). The lowest abundancy

Table 2: Monthly distribution of Zooplankton population (percentage of the total) in marine water ponds.

Table 3: Physicochemical properties of marine water ponds.

was found in the month of December (2.51 and 0.41%, respectively), because a short period of light in winter months resulting a sharp decline of primary producers and then zooplankton as reported by (Sommer et al., 1986). According to Brien and Noyelles (1974), who observed nutrient concentration with planktic population in nutrient rich ponds, revealed that density of phytoplankton is totally depend on the environmental factors and seasonal nutrient transport into ponds while zooplankton density is totally reliant on the phytoplankton. The difference in planktonic population in our ponds might be due to the presence of variable amount of nutrient inputs in different months. Additionally, changing physicochemical properties of water causes fluctuation in abundance of plankton, because Pakistani water receives domestic, agriculture and industrial discharge that contain high amount of dissolve nutrients, specified by (Harrison et al., 1997; Abbas, 2001; Abbasi et al., 2016).

Table 4: Mean percentage of Phytoplankton and Zooplankton in marine water ponds (Jan-Dec, 2019).

Table 5: Average month wise distribution (%) of plankton in marine water ponds (Jan-Dec, 2019).

In conclusion, the studied marine water fish ponds showed differ but high abundancy of planktons in different months because they receives nutrient rich water from tidal creek. Thus, present study will be supportive to farmers because ponds are productive and suitable for pisciculture activities. However, detailed study is needed by using different fertilizers linked with primary productivity and total production of these ponds.

Authors are grateful for PARC-ALP project (AS010-2021-23) entitled “Commercialization of the fish culture technology development in coastal region of Pakistan” for providing funding and facilities.

The current study investigates the phytoplankton and zooplankton diversity in marine water ponds will be supportive to farmers for pisciculture activities.

Asma Fatima: Performed the experiment, data analysis, and manuscript writing;

Ghulam Abbas: Supervised the research, helped in experimental setup and data analysis;

Shahnaz Rashid: Reviewed and edited the manuscript.

The authors have declared no conflict of interest.