29 4.1.4 Dissolved oxygen Figure 4.4 below shows the dissolved oxygen value for three different sites in July, August, and September. The dissolved oxygen value ranges from 3.66 ± 0.89 mgL to 5.51 ± 0.80 mgL. However, the changes in the reading of dissolved oxygen between sites from July to September 2022 is not significant (p<0.05). Figure 4.4: Dissolved oxygen of the three sites throughout the sampling months. (Error bars denote standard error with n=3)
30 4.1.5 Conductivity Figure 4.5 below shows the conductivity value for three different sites in July, August, and September. The lowest mean value was in August at Site 3 (45.67 ± 0.88 S/cm), and the highest was in September at Site 3 (76.3 ± 1.45 S/cm). The changes in conductivity between sites within the period of sampling is significant (p<0.05). Figure 4.5: Conductivity of water within the three sites throughout the sampling months. (Error bars denote standard error with n=3)
31 4.1.6 Concentration of phosphates Figure 4.6 below shows phosphate concentration for three different sites in July, August, and September. The lowest value was in August at Site 3 (0.00 ± 0.00 mgL-1 ), and the highest was in September at Site 2 (0.45 ± 0.04 mgL-1 ). The changes concentration of phosphate of Site 2 in July and September 2022 significantly increased (p<0.05) with a mean difference of 0.217. In August 2022, phosphate concentration in water decreased significantly (p<0.05) as it flowed from Site 1 to Site 3 with a mean difference of 0.217. In September, the phosphate concentration reduced significantly (p<0.05) as the water flowed from Site 1 to Site 2 and from Site 2 to Site 3, with a mean difference of 0.313 and 0.423, respectively. Figure 4.6: Phosphate concentration within the three sites throughout the sampling months. (Error bars denote standard error with n=3)
32 4.1.7 Concentration of nitrate Figure 4.7 below shows the nitrate concentration for three different sites in July, August, and September. The lowest value was in September at Site 1 (0.40 ± 0.42 mgL-1 ), while the highest was in July at Site 2 (11.38 ± 1.52 mgL-1 ). Site 2 has shown a significant decrease (10.108 ± 0.991 mgL-1 ) in nitrate concentration in July to September 2022 (p<0.05). Whereas the nitrate concentration has significantly decreased (p<0.05) as the water flows from Site 1 to Site 2 and Site 3 in July 2022. Figure 4.7: Nitrate concentration within the three sites throughout the sampling months. (Error bars denote standard error with n=3)
33 4.1.8 Concentration of ammonia Figure 4.8 below shows ammonia concentration for three different sites in July, August, and September 2022. The ammonia concentration recorded from July to September 2022 was ranged between 0.02mgL-1 and 0.56 mgL-1 . However, the changes in the reading of ammonia concentration are not significantly different between sites and months (p>0.05). Figure 4.8: Ammonia concentration of Upper East Wetland, Putrajaya within the three sites throughout the sampling months. (Error bars denote standard error with n=3)
34 4.2 Microalgae diversity Analysis of microalgae diversity in Upper East Wetland, Putrajaya within the sampling period based on microscopic identification, Shannon–Weiner index (H′), Pearson correlation coefficient, Principal component analysis (PCA), and Canonical correlation analysis (CCA) were shown as Figure 4.10 to Figure 4.16 and Table 4.3. 4.2.1 Microscopic identification Twenty-five microalgae species were identified in UE3, UE1 and UN1A. The microalgae species are classified according to their class: Bacillariophyceae, Chlorophyceae, Cyanophyceae, Euglenophyceae and Trebouxiophyceae. Figure 4.10 shows some microalgae species found in sampling sites based on their classifications. Gyrosigma sp., Navicula sp. and Nitzschia sp. belong to Bacillariophyceae. Pediastrum sp., Micrasterias sp., Phytoconis sp., Westella sp., Scenedesmus sp., Ankistrodesmus sp. and Actinastrum sp. belongs to Chlorophyceae. Microcystis sp. and Gomphosphaeria sp. belong to Cyanophyceae. Whereas Chlorella sp. belongs to Trebouxiophyceae, Phacus sp. and Euglena sp. belong to Euglenophyceae. Next, Table 4.1 to 4.3 depicts a list of microalgae species and their classification. Table 4.6 shows the microalgae density based on their class by site and month. Figure 4.14 shows the density of microalgae species by site and by month.
35 Figure 4.9: Some of microalgae species that represents Bacillariophyceae, Chlorophyceae, Cyanophyceae, Euglenophyceae and Trebouxiophyceae. (a) Gyrosigma sp., (b) Navicula sp., (c) Nitzschia sp., (d) Pediastrum sp., (e) Micrasterias sp., (f) Phytoconis sp., (g) Westella sp., (h) Scenedesmus sp., (i) Ankistrodesmus sp., (j) Actinastrum sp., (k) Microcystis sp., (l) Gomphosphaeria sp., (m) Chlorella sp., (n) Phacus sp., and (o) Euglena sp. (Scale bar denotes 10.0 μm)
36 Table 4.3: List of microalgae species found in three different sites in July 2022. Class Site 1 Site 2 Site 3 Bacillariophyceae Navicula sp. Nitzschia sp. Nitzschia sp. Nitzschia sp. Chlorophyceae Ankistrodesmus sp. Chlamydomonas sp. Chlamydomonas sp. Cyanophyceae Anabaena sp. Microcystis sp. Microcystis sp. Microcystis sp. Euglenophyceae Euglena sp. Euglena sp. Trebouxiophyceae Chlorella sp. Chlorella sp. Chlorella sp.
37 Table 4.4: List of microalgae species found in three different sites in August 2022. Class Site 1 Site 2 Site 3 Bacillariophyceae Nitzschia sp. Nitzschia sp. Navicula sp. Tabellaria sp. Chlorophyceae Actinastrum sp. Actinastrum sp. Ankistrodesmus sp. Ankistrodesmus sp. Chlamydomonas sp. Chlamydomonas sp. Closterium sp. Oocystis sp. Pediastrum sp. Phytoconis sp. Scenedesmus sp. Scenedesmus sp. Tetraedron sp. Cyanophyceae Microcystis sp. Microcystis sp. Microcystis sp. Euglenophyceae Euglena sp. Phacus sp. Phacus sp. Trebouxiophyceae Chlorella sp. Chlorella sp.
38 Table 4.5: List of microalgae species found in three different sites in September 2022. Class Site 1 Site 2 Site 3 Bacillariophyceae Navicula sp. Navicula sp. Gyrosigma sp. Gyrosigma sp. Pinnularia sp. Chlorophyceae Ankistrodesmus sp. Ankistrodesmus sp. Chlamydomonas sp. Eudorina sp. Micrasterias sp. Neochloris sp. Oocystis sp. Phytoconis sp. Scenedesmus sp. Tetraedron sp. Tetraedron sp. Cyanophyceae Westella sp. Anabaena sp. Aphanocapsa sp. Aphanocapsa sp. Gomphosphaeria sp. Euglenophyceae Microcystis sp. Microcystis sp. Microcystis sp. Trebouxiophyceae Euglena sp.
3 Table 4.6: Density of microalgae based on their class at all sites wi Class July Site 1 Site 2 Site 3 Bacillariophyceae 22 11 67 Chlorophyceae 22 44 0 Cyanophyceae 244 111 122 Euglenophyceae 44 0 22 Trebouxiophyceae 133 33 67
9 ithin sampling months. Mean Density (cells/mL) August September Site 1 Site 2 Site 3 Site 1 Site 2 Site 3 244 44 0 22 0 11 222 67 0 222 33 33 489 2456 389 2389 3333 133 67 11 0 78 0 0 33 11 0 11 0 0
40 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Site 1 Site 2 Site 3 Site 1 Site 2 Site 3 Site 1 Site 2 Site 3 July August September Month Mean Density (%) Actinastrum sp. Anabaena sp. Ankistrodesmus sp. Aphanocapsa sp. Chlamydomonas sp. Chlorella sp. Closterium sp. Eudorina sp. Euglena sp. Gomphosphaeria sp. Gyrosigma sp. Micrasterias sp. Microcystis sp. Navicula sp. Neochloris sp. Nitzschia sp. Oocystis sp. Pediastrum sp. Phacus sp. Phytoconis sp. Pinnularia sp. Scenedesmus sp. Tabellaria sp. Tetraedron sp. Westella sp. Figure 4.10: Density of microalgae in Upper East Wetland, Putrajaya within the three sites throughout the sampling months.
41 4.2.2 Shannon–Weiner index Table 4.7 shows the Shannon–Weiner index (H′) and the microalgae in Upper East Wetland, Putrajaya from July, August, and September 2022. The Shannon-Wiener diversity index ranges between 1.24 until 1.56 in July 2022 with the highest diversity at Site 2, Site 1. As in August 2022, the index ranges between 0 to 1.87 with the highest value at Site 2. In September 2022, the index ranges between 0.06 to 0.80 with the highest diversity at Site 3, Site 3. Thus, this showed that Site 1 has more diversity of microalgae than other sites.
42 Table 4.7: Microalgae indices at Upper East Wetland, Putrajaya from July until September 2022. (Values in bold and with asterisk are the highest value) Month Site Evenness Richness (number of genus) Mean Cell Density (Cells/mL) Shannon diversity index (H) July Site 1 0.87 6 42 1.56* Site 2 0.774 5 18 1.24 Site 3 0.87 5 25 1.40 August Site 1 0.71 14 95 1.87* Site 2 0.13 10 233 0.31 Site 3 1.00 1 35 0.00 September Site 1 0.28 17 245 0.80 Site 2 0.06 3 303 0.06 Site 3 0.80 6 16 1.44*
43 4.2.3 Pearson correlation coefficient Using SPSS version 27, the Pearson Correlation Coefficient was used to determine the correlation between the microalgal species discovered in Site 1, Site 2, and Site 3 and the physicochemical variables. The Table 4.8 displays the Pearson Correlation Coefficient between microalgal species found in Site 1, Site 2, and Site 3 and physicochemical variables from July to September 2022. From the finding, class Cyanophyceae has a significant correlation with phosphate concentration and light intensity (p<0.0.5). Whereas only Trebouxiophyceae is significantly correlated with nitrate and light Intensity (p<0.05).
4 Table 4.8: Pearson correlation coefficients between physicoche to September 2022. (Values in bold and with asterisk Variables NO3 + PO₄³⁻ NH4 Tem NO3 + PO₄³⁻ 0.08 NH4 -0.27 0.10 Temp 0.22 -0.07 -0.14 pH -0.17 0.06 0.28 -0.2 DO 0.02 -0.06 -0.02 0.0 LI 0.61* 0.05 -0.40* 0.2 Cond -0.31 -0.09 0.18 -0.7 Cyan -0.29 0.51* 0.30 -0.2 Chlo -0.18 0.18 -0.10 -0.0 Treb 0.46* -0.21 -0.19 0.2 Eug -0.28 0.14 -0.25 0.0 Baci -0.16 0.15 -0.12 0.1 NO3 -– concentration of nitrate, PO₄³⁻ – concentration of phosphate, NH oxygen, LI – light intensity, Cond – conductivity, Cyan – Cyanophyceae, C Baci– Bacillariophyceae.
4 mical parameters and microalgae class within three sites from July are significantly correlated with significant level alpha 0.05) mp pH DO LI Cond 24 9 0.17 9 -0.26 0.46* 5* 0.16 -0.37 -0.41* 22 0.17 -0.02 -0.41* 0.05 03 0.23 -0.18 -0.20 0.25 2 -0.13 0.05 0.40* -0.07 5 0.16 -0.37 -0.01 0.19 5 0.20 0.06 -0.15 0.07 H4 – concentration of ammonia, Temp – temperature, D.O. – dissolved Chlo– Chlorophyceae, Treb– Trebouxiophyceae, Eug– Euglenophyceae,
45 4.2.4 Principal component analysis Principal component analysis (PCA) was conducted using PAST version 4.03 to observe the relationship between variables and sites. Figure 4.15 below shows the Principal Component Analysis illustrating the relationship between physicochemical parameters and sites from July to September 2022. The Principal Component Analysis (PCA) showed that the first two axes contributed 50.54% of the correlation in physicochemical parameters. The variables positively correlated with the first axis consisted of dissolved oxygen, light intensity, temperature, nitrate concentration and ammonia concentration. The pH, conductivity and ammonia concentration were negatively correlated with the first axis. Next, conductivity and pH have negatively correlated with the second axis, while the other variables were positively correlated. The physicochemical variables in July 2022 is grouped together at the right side of the biplot, indicating a significant different between physicochemical variables compared to the August and September 2022.
46 Figure 4.11: Principal Component Analysis illustrating the relationship between physicochemical variables and three different sites from July to September 2022. Physicochemical parameters: DO; dissolved oxygen, Temp; temperature, Light; light intensity, pH, Conductivity
47 4.2.5 Canonical correlation analysis Canonical correlation analysis (CCA) was run using PAST version 4.0 to determine the correlated coupled patterns between the physicochemical parameters and microalgae density in different sites from July to September 2022. Figure 4.16 below shows the CCA for the eight physicochemical parameters and 25 microalgae species analysed in three sites from July to September 2022. Cyanophyceae frequently recorded at Site 1, Site 2 and Site 3 in all months indicated a close relationship with ammonia concentration and conductivity while being negatively correlated in the second axis. Besides that, Trebouxiophyceae has a positive correlation at the first axis with nitrate concentration and can be found primarily on Site 1 in August. Chlorophyceae positively correlated with light intensity, but the correlation is weak on the first axis. In contrast, Euglenophyceae does not show any correlation between the first and second axes.
48 Figure 4.12: Canonical correlation analysis (CCA) for the eight physicochemical parameters and microalgae class across different sites in different months. Physicochemical parameters: DO; dissolved oxygen, Temp; temperature, Light; light intensity, pH, Conductivity
49 4.3 Amplification of 18S ribosomal RNA Figures 4.17, 4.18, and 4.19 show the DNA banding patterns of the 18s rRNA gene for identifying microalgal species identified in UE3 (Site 1), UE1 (Site 2) and UN1A (Site 3) throughout July, August, and September 2022. In July, gel electrophoresis revealed no bands for microalgal species observed in UE3, UE1 and UN1A. However, a few distinct bands are visible for sampling in August and September 2022.
50 Figure 4.14: Banding patterns of 18S (rRNA) genes of isolated microalgae from UE1, UE3, and UN1A in July 2022. M1: 1kb DNA ladder. M2: 100bp DNA ladder. (-): negative control. Lane 1 to 3: UE1. Lane 4 to 6: UE3. Lane 7 to 9: UN1A. Figure 4.13: Banding patterns of 18S (rRNA) genes of isolated microalgae from UE1, UE3, and UN1A in August 2022. M1: 1kb DNA ladder. M2: 100bp DNA ladder. (-): negative control. Lane 1 to 3: UE1. Lane 4 to 6: UE3. Lane 7 to 9: UN1A.
51 Figure 4.15: Banding patterns of 18S (rRNA) genes of isolated microalgae from UE1, UE3, and UN1A in September 2022. M1: 1kb DNA ladder. M2: 100b p DNA ladder. (-): negative control. Lane 1 to 3: UE1. Lane 4 to 6: UE3. Lane 7 to 9: UN1A.
52 CHAPTER 5 DISCUSSION 5.1 Physicochemical Analysis Water quality of Upper East Wetland, Putrajaya can be assessed by measuring the physicochemical parameters. The physicochemical parameters involved several parameters such as pH, temperature, light intensity, dissolved oxygen, conductivity, phosphate concentration, nitrate concentration, and ammonia concentration. 5.1.1 pH According to statistics from Pusat Perbadanan Putrajaya (2022a), the pH fluctuated between 6.79 and 7.60. In the present study, the pH of the Upper East Wetland of Putrajaya varied from acidic to basic within the sample period at the three different sites. Overall, the change in pH for all sites from July to September is small but does not show any significant difference (p>0.05). The rainfall intensity at Presint 13, Putrajaya, ranged between 0 mm and 11.8 mm from July to September (Table 5.1). As the location of sampling sites in Presint 12, Putrajaya, which is about 13km from Presint 13, Putrajaya, the pH fluctuation can be affected by the rainy weather during the sampling period and the anthropogenic activity conducted the near the study sites. The rainfall is usually acidic, and acid rain causes both lower pH. Acidic rain can cause acidification of the lakes and harm the microbial populations in the water bodies (Chen et al., 2022). Furthermore, the pH of the water bodies tends to drop due to the production of nitrous oxide and the increased amount of water produced by the acidic soils (Chen et al., 2022). Moreover, the natural fluctuations in pH may result from human actions contributing to the pH change—for example, Site 1 location near Palm Garden Golf Club. Using ammonium-rich fertilizers to fertilize turf grass might enhance the acidification potential, reducing pH (Chen et al., 2022). Next, human excrement and waste are also rich in ammonia; hence, the presence of either of these materials in a water body increases ammonia concentration (US EPA, 2015). This source was available in Site 2 possibly due to residential areas near the sites. On top of that, higher pH levels can stimulate microalgal development. As alkalinity rises, diatoms have a competitive disadvantage in environments where Microcystis sp. may rapidly bloom (Zepernick et al., 2021). High pH can be one factor in the abundance of Microcystis sp. in all sites within the sampling periods. However, pH does not significantly correlate with other physicochemical parameters and microalgae genus (p>0.05).
53 Table 5.1: Rainfall intensity from July to September 2022 at Presint 13 (Perbadanan Putrajaya, 2022b). Date Rainfall (mm) 28th July 2022 0.2 25 th August 2022 11.8 22nd September 2022 0
54 5.1.2 Temperature From the data obtained from Pusat Perbadanan Putrajaya (2022a), the temperature ranged from 27.60 °C to 30.90 °C. On the other hand, the temperature of Site 1, Site 2, and Site 3 have a range mean value from 27.86 °C to 31.33 °C. In August, the temperature of Site 1 and Site 3 increased, but in September, it reduced significantly (p<0.05). Temperature decreases may be due to various environmental factors changing the water temperature, including solar radiation, atmospheric heat transfer, stream confluence, and turbidity. Shallow and surface waters are more susceptible to these influences than deeper waters (Bub, 1993). This environmental factor may be due to the anthropogenic activities conducted near the study sites. Also, the water temperature can be affected by runoff and thermal pollution. Thermal pollution occurs due to runoff from any impervious surfaces. Water that runs off these surfaces absorbs a significant amount of its heat and transfers it to a neighbouring stream or river, raising the temperature of these bodies of water (Perlman, 2013). Municipal or industrial effluents from anthropogenic activities near the sites can cause this contamination. If the discharge temperature is much higher than that of the natural water, the water quality may reduce (Perlman, 2013). Besides, warmer temperatures hinder water mixing, causing microalgae to grow quicker and thicker. Microalgae blooms triggered by rising temperatures may cause harm due to an increase in the quantity or dominance of specific species but not necessarily an increase in toxicity (Ho & Michalak, 2019). 5.1.3 Light intensity July 2022 has the highest light intensity at all three sites. The result may be affected by sunny weather and the sampling time, around 12.30 p.m. As the light intensity increases, the amount of heat produced will increase, causing a decline in the growth rate of microalgae. Stimulating the photo-oxidation process in microalgae by light intensity helps boost the growth rate of microalgae (Jovian et al., 2015). However, the light intensity was recorded the lowest at all three sites in August 2022, as there was moderate rainfall during the sampling, which is 11.8 mm (Perbadanan Putrajaya, 2022b) However, from July to September 2022, light intensity at all locations decreased significantly (p<0.05). Light intensity depends on several factors, such as seasons and cloud cover, which decreases with depth. It also can depend on the time chosen for sampling. Light intensity tends to increase from 100 lux at sunrise to 100 000 lux at midday, then drops until it approaches 0.001 lux on a moonless night (Engelmann & Antkowiak, 2016). The light intensity drops in August and September due to cloudy and rainy weather during the sampling. The seasonal variation in light intensity and temperature could inhibit the process of microalgal bioremediation (Al-Jabri et al., 2020). Cloud cover and less daylight would restrict the rate of microalgal bioremediation (Al-Jabri et al., 2020). Depth plays an essential role in light penetrating the water column; however, the data for depth was not able to be collected due to high tide during the sampling.
55 5.1.4 Dissolved oxygen The dissolved oxygen concentration for all months of sampling at three different sites of Upper East Wetland ranged from 1.88 mgL-1 to 6.72 mgL-1 . Compared with the data measured by Pusat Perbadanan Putrajaya (2022a), the data ranged from 3.08 mgL-1 to 7.12 mgL-1 . The amount of dissolved oxygen in all three sites fluctuated from July to September 2022, but it did not reach the degree of concern. The fluctuation may be due to the number of microalgae, wetland plants, and other freshwater plants in all sites that produce dissolved oxygen by respiration, photosynthesis, and decomposition of organic matter. Most photosynthesis by the shallow plants and the microalgae occurs on the wetland's hypolimnion level. Besides, the excessive growth of microalgae due to high phosphorus concentration can lower dissolved oxygen value. Besides, dissolved oxygen has a low positive correlation with light intensity (p<0.05). The light intensity increases, and the dissolved oxygen could increase; however, the relationship is weak. Because of the necessity for light for underwater photosynthesis, dissolved oxygen production is higher during the day and lower during the night (AlJabri et al., 2021). However, the overgrowth of microalgae on the water's surface can be harmful to aquatic life as the microalgae can consume oxygen and inhibit the sunlight from reaching the aquatic life (Muhammad Imran, Shin & Kim, 2018). 5.1.5 Conductivity Compared with the data obtained from Pusat Perbadanan Putrajaya (2022a), the conductivity recorded for Site 1, Site 2, and Site 3 ranged from 70 µS/cm to 130 µS/cm. However, the only conductivity of Site 3 has significantly increased from August to September 2022 (p<0.05). The fluctuation may happen due to the high number of dissolved salts and inorganic materials in the water, and the presence of additional ions increases the conductivity of water. Furthermore, human activities tend to increase the number of dissolved solids entering waterways, resulting in higher conductivity. The conductivity changes in Site 1 and Site 2, possibly due to human disturbance. According to Wu et al. (2020), conductivity strongly correlates with industrial waste, and this waste disposal may come from the runoff that flows into the sites. For instance, the conductivity was significantly increased from August to September 2022 in Site 3, probably because runoff at the sites is wide open as a public area. Besides that, the conductivity negatively correlated with the temperature and light intensity (p<0.05). The conductivity could decrease as the temperature, and light intensity of sites increased. However, the conductivity usually increased as the water temperature increased. The study by Kim and Steudle (2007) also shows that water conductivity was directly proportional to light intensity. The water temperature affects the conductivity of ions in water as the ions travel more rapidly in warm water (Ammara, Muhammad Shoukat & Asra, 2020).
56 5.1.6 Concentration of phosphate The highest phosphate concentration in September 2022 for Site 1 was probably due to anthropogenic activity near the sites, such as municipal waste and fertiliser disposal. The fertiliser disposal of golf course greens, possibly from Palm Garden Golf Resort near Site 1. At the same time, municipal waste may come from human waste and runoff near the sites, for instance, the residential area near Site 2. Human faeces, detergents containing phosphorus, and certain industrial and commercial effluents are the primary source of phosphorus in wastewater (Kroiss et al., 2011). In addition, the relationship between fertiliser uses, and water quality degradation in urban watersheds is complex by several factors, including fertiliser inputs, nutrient management and cycling, and nutrient losses (Carey et al., 2012). The phosphate concentration in Site 3 was relatively low may be because of less anthropogenic activity exposure at the site and the remediation of water works effectively. Phosphate concentration in water significantly reduced (p<0.05) as it flowed from Site 2 to Site 3 in August 2022. In September 2022, the phosphate concentration reduced significantly (p<0.05) as the water flowed from Site 1 to Site 3. This decrement is significantly related to the pH concentration measure. From July to September 2022, the pH of all three locations gradually increased from acidic to basic, and the phosphate concentration gradually decreased. The phosphorus binds to calcium, reducing the number of free phosphate ions in the water. At high pH levels, the presence of carbonate ions and dissolved organic carbon in solution had an essential role in stimulating the concentration of phosphates (Cerozi & Fitzsimmons, 2016). 5.1.7 Concentration of nitrate Based on the previous chapter, the nitrate concentration was the highest in July at Site 1. The high nitrate concentration may be due to nutrient pollution, particularly nitrate from excess nitrogen. Besides, nitrates can enter the wetland through urban and organic waste from residential areas and runoff from fertiliser (Singh & Craswell, 2021). This runoff may come from the residential area in Putrajaya Presint 12, near Site 1 and Site 2. However, the nitrate concentration for Site 1 significantly reduced from July to September 2022 (p<0.05). The nitrate concentration has significantly decreased (p<0.05) as the water flowed from Site 1 to Site 3 in July 2022. The reduced concentration happens due to planted wetland plants that absorb the nutrients in the water and transform them into organic molecules for growth. Treatment processes like nitrification, denitrification, sedimentation, and water–plant interfaces can eliminate diverse nitrogenous species (Yousaf et al., 2021). Constructed wetlands can reduce the biological oxygen demand and the quantities of coliform bacteria, nitrogen, phosphorus, and suspended solids by up to 98 per cent (Yousaf et al., 2021). On top of that, the nitrate concentration has shown a moderately positive correlation with light intensity (p<0.05). The nitrate concentration tends to decrease as the light intensity decrease. Light exerts a more decisive influence than soil nitrogen on symbiotic nitrogen fixation, and light modulates the response of symbiotic nitrogen fixation to soil nitrogen availability (Taylor & Menge, 2018).
57 5.1.8 Concentration of ammonia The concentration of ammonia was very high (0.45 ± 0.04 mgL-1 ) in September 2022 for Site 1 compared to other sites from July to September 2022. However, based on the National Water Quality Standards for Malaysia, the reading belongs to Class IIB, which is safe for recreational activities (2006). Ammonia in wastewater is nitrogen in the form of free ammonia and ionic ammonium, mainly resulting from the decomposition of nitrogen-containing organic matter in domestic waste and other industrial effluents, as well as agricultural drainage (Mikkelsen, 2009). Based on the previous chapter, the high ammonia concentration may be due to agricultural fertilisers and industrial waste entering surface water through runoff which is related to the location of Site 1 and Site 2. Even though Site 3 has less human activity exposure, the ammonia concentration fluctuation may result from the nitrification process by the nitrifying bacteria in remediation centre, Site 2. However, it is important to note that the changes in ammonia concentration in three sites within the sampling periods are insignificant (p>0.05). Besides, ammonia concentration has a weak negative correlation with light intensity (p<0.05), which shows that ammonia concentration could decrease with increasing light intensity (Markou & Muylaert, 2016). In addition, ammoniacal nitrogen can induce the growth of microalgae and cyanobacteria. Microalgae utilise ammonia more efficiently than bacteria, reducing the concentration of ammonia in water. However, ammonia can increase the pH level, When the pH of the water exceeds 9, the conversion of most ammonium in the water will lead to poisonous ammonia, which can harm aquatic organisms (Wurts, 2003)
58 5.2 Microalgae diversity Based on the microscopic identification, there were 25 species of microalgae belongs to the classes of Bacillariophyceae, Chlorophyceae, Cyanophyceae, Euglenophyceae, and Trebouxiophyceae. Out of five classes, Cyanophyceae is the dominant class with highest cell density. 5.2.1 Cyanophyceae Based on the microscopic identification, Microcystis sp. from the class Cyanophyceae is the dominant species found in Upper East Wetland, Putrajaya. The domination of cyanobacteria may indicate that the wetland has many excess nutrients and warmer temperatures with intense rainfall patterns. The rainfall intensity ranged between 0 mm and 11.8 mm (Figure 5.1); the highest rainfall intensity was in August 2022. Based on the previous chapter, Cyanophyceae had a high cell density of Microcystis sp. in August 2022. Besides, phosphate concentration also has moderately positive correlates with Cyanophyceae (p<0.05). It shows that with the decrease in phosphate concentration, the number of species of Cyanophyceae will possibly increase. The density of Cyanophyceae significantly increased in Site 2 from July to September 2022 (p<0.05). In September, the density of Cyanophyceae species significantly decreased as the water flowed from Site 2 to Site 3 (p<0.05). The decrease is probably because the phosphate concentration was also decreased as the water flowed from Site 2 to Site 3. Phosphate is released from the sediment, absorbed by Microcystis sp. and stored in the bottom layer (Giannuzzi, 2019). On top of that, the light intensity negatively correlates with Cyanophyceae (p<0.05). For example, the light intensity of Site 2 has significantly decreased from July to September 2022 (p<0.05), whereas the cell density of Microcystis sp. possibly increased. High phytoplankton density causes water column turbidity and low light intensity, favouring cyanobacteria's growth (Sukenik et al., 2009). 5.2.2 Chlorophyceae Chlorophyceae can be found at all sites, for example, Ankistrodesmus sp. and Chlamydomonas sp. The presence of Ankistrodesmus sp. is a good indicator of clean water as they cannot thrive in polluted water bodies. However, the number of species found is very small. Besides that, Chlamydomonas sp. can be found in all sites during the sampling period. This is probably because they can survive in a different setting with different physicochemical parameters. However, if the Chlamydomonas sp. accumulates in the water bodies, it can turn the water green and exhibit fishy smells (Serediak & Huynh, 2011). The colour changes may be related to the abundance of Chlorophyceae in Site 1 and Site 2, as both sites were rich in nutrients, such as nitrogen and phosphate, and contained untreated wastewater. Chlorophyceae plays a significant role in water bodies, and Chlorella sp. can purify municipal wastewater (Kamarudin et al., 2015). Other than that, the cultivation of Chlorella vulgaris is 96.3% proven efficient in removing copper, and Scenedesmus sp. is 97% proven efficient in removing nickel in the wastewater (Al-Jabri et al., 2021).
59 5.2.3 Bacillariophyceae The Bacillariophyceae class consist of Gyrosigma sp. Nitzschia sp., Navicula sp., and Pinnularia sp. The most dominant species found within all sites is the Navicula sp., and the least are Gyrosigma sp. and Pinnularia sp. This may be because Navicula sp. can thrive in the most extensively contaminated areas where other microalgae species cannot survive (Sen et al., 2013). Bacillariophyceae obtain the energy from sunlight during photosynthesis, but they also need a few additional nutrients. Diatoms require silica, phosphate, and nitrogen to form their cell walls. However, in these studies, the silica analysis was not conducted due to insufficient materials of Hach Kit pillow powders. Bacillariophyceae can be found the most in August at Site 1; however, their differences between other classes in each site and month are not significant (p>0.05). Bacillariophyceae also do not correlate with any physicochemical parameters. Navicula sp. and Nitzschia sp. were also recorded and considered pollution indicators given the results of the Palmer pollution index (Palmer, 1969). 5.2.4 Euglenophyceae Euglena sp. were found in all months at Site 1 and Site 3, while Phacus sp. were found at Site 2 and Site 1 in August only. Euglenophyceae can thrive in fresh and brackish organic-rich ponds. Phacus sp. occupy freshwater microhabitats with a high concentration of nitrogen derived by animal excrement, organic matter, and other agricultural intervention (Serediak & Huynh, 2011). Phacus sp. may prefer eutrophicated waters and compete for nutrients with other euglenoid species. Euglena sp. is easily found in polluted freshwater habitats due to high concentration of organic matter (Serediak & Huynh, 2011). Based on the observation during sampling in period of sampling, the water condition at Site 2 and Site 1 was seen as brackish without pungent smell. It would be likely that the water is high in dissolved organic carbon compounds (Serediak & Huynh, 2011). However, class Euglenophyceae does not correlate with any physicochemical parameters and the changes between site and month also not significant. 5.2.5 Trebouxiophyceae Trebouxiophyceae are unicellular or colonial algae that reproduce asexually through autospores or zoospores. Trebouxiophyceae can be found the most in Site 1 in July, but overall, the density fluctuates by site and month. Even though density of Trebouxiophyceae fluctuates, the changes between sites and months are insignificant (p>0.05). Only one species found during the study, which is Chlorella sp., one of the most common species of Trebouxiophyceae and belong to single-celled green algae of the Chlorophyta division. The number of Trebouxiophyceae has a positive correlation with the concentration of nitrate (p<0.05) and light intensity (p<0.05). This shows that nitrate concentration and light intensity contribute directly to the presence of Trebouxiophyceae. Chlorella sp. generate more lipids at high light intensities (Nzayisenga et al., 2020). As a result, as
60 the light intensity were recorded the highest at Site 1 in July 2022, the density of Chlorella sp. was also the highest. Besides, the nitrate concentration positively correlates with light intensity (p<0.05). The nitrate concentration tends to decrease as the light intensity decrease. Chlorella sp. assimilates nitrate or ammonia. Only ammonia is used when both sources are available, and no nitrate is reduced. On top of that, wetland plants perform nitrification and denitrification utilising nitrates (Yousaf et al., 2021) to improve the water quality. 5.3 Trophic level Algal communities require specific environmental niches for development, reproduction, and survival. Based on this information, clusters of distinct algae are classified according to their preferred physicochemical requirements for growth and succession. In July and August 2022, Site 1 had the most remarkable diversity of algae genera among all locations with the highest Shannon–Weiner index. This can be due the nutrient enrichment that helps to boost the microalgae growth (Yusoff, 2016). Site 1, which includes the Palm Garden Golf Resort and the Putrajaya Presint 12 residential subdivision, is one of the water inlets to Putrajaya Lake. Microcystis sp., is commonly known as eutrophic indicator. These compounds are widespread due to Site 1 significance as an inflow of anthropogenic waste from many sources in the surrounding region. The presence of Chlamydomonas sp., reported throughout the sample period in Site 1, showed that the water body was mesotrophic (Yusoff, 2016). However, based on the microalgae density, Site 1 is oligotrophic in July 2022, and mesotrophic in August and September 2022 (Yusoff, 2016). Next, Site 2 has the highest abundance of microalgae density in August and September 2022; however, Site 2 is less diverse compared to Site 1. This is because there is less species found in Site 2 compared in Site 1. Besides, the phosphate and nitrate concentrations were associated with dominating species such as Microcystis sp., Chlorella sp., Euglena sp., Nitzschia sp., and Chlamydomonas sp. Moreover, Site 2 had an abundance of Ankistrodesmus sp. in all three months of sampling, indicating that the water body was mesotrophic (Yusoff, 2016). However, based on the microalgae density, Site 2 is oligotrophic in July 2022, and mesotrophic in August and September 2022 (Yusoff, 2016). Furthermore, the water quality of Putrajaya Lake and Wetland is assessed to meet the class IIB based on the National Water Quality Index for recreational values (Sharip et al., 2016). The parameters assessed are such as dissolved oxygen values should range between 5 and 7 mgL-1 , pH is 6 to 9, ammoniacal nitrogen is 0.3 mgL-1 , biochemical oxygen demand 3 mgL-1 , and chemical oxygen demand 25 mgL-1 (Sharip et al., 2016). Thus, the results of Site 3 are an important consideration in determining the quality of water treatment by the wetland because they act as the last outlet for treated water before flowing into the central wetland. Site 3, the water outlet next to Central Wetland, is where treated waste is released. The microalgae class Chlorophyceae at this point showed that the water body was mesotrophic. Nonetheless, Cyanophyceae, Chlorophyceae, and Bacillariophyceae were the most prevalent and plentiful in the study at Site 3, especially in September 2022 with the highest Shannon–Weiner index. Across the sampling periods, Microcystis sp. was identified as the eutrophic indicator (Yusoff, 2016). There were also other commonly found microalgae, such as Navicula sp, which indicates the
61 eutrophic status. However, based on the microalgae density, Site 3 is oligotrophic in in all months, which indicates a healthy wetland (Yusoff, 2016). Based on the physicochemical variables, the water quality has gradually improved from the remediation by the wetland in July to September 2022, as Site 3 is considered as healthy wetland based on the cell density (Yusoff, 2016). Moreover, most physicochemical results fall within class IIB of the National Water Quality Index. However, the abundance of cyanobacteria, such as Microcystis sp., across all sites would be a significant concern. Several actions to reduce the density of cyanobacteria to prevent cyanobacteria blooms need to be conducted.
62 Table 5.2: Phytoplankton scale for trophic level identification. (Yusoff, 2016) Trophic Level Cell Density (cells/mL) Oligotrophic <100 Oligo-mesotrophic 100-1000 Mesotrophic 1000-5000 Meso-eutrophic 5000-10 000 Eutrophic (mainly blue-green algae) >10 000
63 5.4 Molecular analysis 5.4.1 DNA extraction DNA extraction utilised DNA samples of microalgae from three different locations by using a NucleoSpin Soil DNA isolation kit. The application of DNA isolation techniques should result in the effective extraction of pure DNA and free of impurities (Gupta, 2019). DNA extraction kit can reduce extraction time and able to yield much DNA. Lysing the DNA sample proteins requires using several detergents. When extracting plasmid from protein, buffers are essential to balance pH and stabilise and preserve protein structure while isolating them. From the Macherey-Nagel NucleoSpin Soil DNA isolation kit, only buffer SL1 with the enhancer for DNA separation is utilised out of the two buffers included with the kit because it consistently produced the best DNA extraction results (Soliman et al., 2017). Centrifugation removes any remaining cell debris after this procedure (Gupta, 2019). protease treatment subsequently denatures the proteins. The optimisation process, which included optimising the binding, washing, and elution steps, was critical during the DNA extraction process to ensure the quality of the DNA yield. Furthermore, the amount of DNA yield is affected by the incubation period, population size, and community structure. On top of that, the bead-beating procedure, the kind of beads, and variations in the chemical reagents used could affect the outcome (Soliman et al., 2017). Using Eppendorf BioSpectrometers to measure absorbance suggested a high-quality reading of DNA. Then, only high-quality DNA yields were utilised as templates for the subsequent PCR procedures. 5.4.2 PCR optimization The Polymerase Chain Reaction (PCR) is a very sensitive method for the in vitro amplification of a single or many DNA sequences. The DNA sample was amplified in a PCR thermal cycler equipment, and gel electrophoresis will be used to examine and to characterise DNA fragment characteristics in several contexts and at multiple stages of the cloning process. PCR generates many of copies of a particular DNA fragment or gene, enabling the visual detection and identification of gene sequences based on size and charge (Garibyan & Avashia, 2013). PCR is based on three simple processes that are necessary for each DNA synthesis reaction. The first step is the denaturation of the template into single strands, the second is the annealing of primers to each original strand for new strand synthesis and the third is the extension of the primer-derived new DNA strands. A typical cycling protocol for genomic DNA including a 2-kb amplified region is as follows: 94°C for 5 minutes (initial denaturation), Final extension: 72 °F for 10 minutes Hold: 15°C (Delidow et al., 2023). First, the reaction solution is heated above the melting point of the target DNA's two complementary DNA strands, allowing the strands to separate through a process known as denaturation. This step is essential to melt the template into single strands and remove the secondary structure. In the initial denaturation process, the DNA was denatured for two minutes at 94°C throughout regular cycles. The samples are inserted into the block and subjected to an initial denaturation phase before being kept at the annealing temperature for 2 minutes (Delidow et al., 2023). The reactions for PCR programmes that allow for an initial denaturation before adding the polymerase are built up without a small volume and the Taq (Delidow et al., 2023). The material was
64 heated before separating the two DNA double helix structure strands. As the temperature increases, the original DNA will then be replicated by the Taq polymerase enzyme attaching to the two new growing DNA strands. The quantity of copied DNA molecules doubles with each repetition of these three stages, allowing the primers to hybridise with the template (Garibyan & Avashia, 2013). Next, the PCR proceeds with 30 cycles of 98°C for ten seconds, 62°C for 30 seconds, and 68°C for 1 minute. This process involves the annealing phase, which allows the primers to hybridise into the template. This procedure is performed at a temperature dictated by the strand-melting temperature of the primers and the required specificity (Delidow et al., 2023). The 18S primer act as a particular primer to anneal and amplify the target template from a single-strand DNA sample. Normal reactions involve annealing at 55 °C for one to two minutes. At 60 to 65°C, reactions needing higher rigour can be annealed. Reactions in which the primers have lost specificity can be annealed between 37 and 45 degrees Celsius (Delidow et al., 2023). The extension was the last step of the polymerase chain reaction (PCR). The extension process enables the synthesis of new DNA strands. This step is performed at 72°C for ten minutes, which is ideal for Taq polymerase. The length of the sequence to be amplified dictates the amplification time. Then, it was put on hold at 10°C. 5.4.3 PCR components Microalgae DNA sample, Amplicon PCR Forward Primer 18S, Amplicon PCR Reverse Primer 18S, and Thermo Scientific Phusion Plus Green PCR Master Mix are the crucial components for ensuring the efficacy of amplification PCR output. The Phusion Green Hot Start II High-Fidelity PCR Master Mix aimed to minimise the quantity of pipetting required. For direct loading of PCR products onto a gel, the buffer also comprises a density reagent and two tracking dyes. The forward and reverse primers of Amplicon were small segments of single-stranded DNA that were complementary to the desired DNA sequence area. The forward primer binds to the start codon of the template DNA, whereas the reverse primer binds to the stop codon of the complementary DNA strand (Jaric et al., 2013). Primers should not complement one other or any other primer in the process to prevent primer dimers from forming in PCR. The creation of primer dimers reduces the polymerase chain reaction (PCR) efficiency because they compete with PCR products. The effectiveness of the polymerase chain reaction is highly dependent on the strength of hydrogen bonds between the primer and the template (Jaric et al., 2013). The DNA template consisted of the gene that needed to be amplified, such as the 18s ribosomal RNA (rRNA) gene using 18s primer to identify microalgae species in Upper East Wetland, Putrajaya. Phusion Hot Start II DNA Polymerase, nucleotides, and tailored reaction buffer with MgCl2 are in the master mixture. Two tracking dyes and a density reagent are also included in the solution enabling the direct loading of PCR results onto a gel.
65 5.4.4 PCR screening and troubleshooting After PCR reactions, the PCR products were analysed by agarose gel electrophoresis and observed using a gel documentation system. In this analysis, 18S forward and reverse primers were utilised to amplify target DNA containing the V4 region of the 18s rRNA gene to identify microalgal species in Putrajaya's Upper East Wetland. The sample was performed monthly throughout July, August, and September 2022. As demonstrated in the preceding chapter, there was no amplification in Lanes 1 through 9 during the initial sample, which occurred in July 2022. This was likely caused to the low DNA template concentration. According to Lee et al. (2012) research, there would be no bands present on an agarose gel if the concentration of the DNA template was low. In addition, contamination during the pipetting of the reagents or components was a contributing element to the problem of invisible DNA bands. Next, as demonstrated in the preceding chapter, the 18S primer successfully amplified the targeted DNA region, the 18S ribosomal RNA (rRNA) gene, during the second sampling conducted in August 2022. The samples in Lanes 1, 3, 4, 6, and 7 displayed clear and thick bands, whereas Lanes 2, 5, 9, and the negative control did not. However, the 18S rDNA PCR products produced from extracted DNA samples do not exhibit the predicted size of approximately 400 bp. The PCR was considered failed since the band size was less than 300bp. This may because of contamination during the pipetting process or during DNA extraction and PCR. In the third sample obtained in September 2022, the 18S primer amplified the targeted DNA region, the 18S ribosomal RNA (rRNA) gene, as demonstrated in the previous chapter. From Lanes 1 to 9, Lanes 4 to 9 displayed distinct and thick bands, whereas Lanes 1 to 3 and the negative control exhibited no bands. UE1 and UN1A both showed visible bands. The 18s rDNA PCR products obtained from DNA samples isolated from 1kp DNA Ladder do not exhibit the predicted size of approximately 400 bp. However, the 18s rDNA PCR products produced from DNA samples isolated from 100bp DNA Ladder revealed the expected size of about 400 bp. Therefore, PCR amplification of 18S ribosomal RNA (rRNA) was successful because the DNA bands' size was within the predicted range. Several DNA amplification limitations may affect the failure of PCR screening, which may be due to long periods of storing water samples. When a water sample was stored at four °C for more than a week, there was a rapid loss of detectable PCR product (Gilpin et al., 2013). The filtration of water samples was extended more than one week due to insufficient instruments. Thus, the water sample and the DNA sample can be stored at 20 °C for up to six months, equivalent to extracting DNA immediately (Gilpin et al., 2013). Apart from that, poor storage of the DNA sample may cause the DNA to be degraded. The DNA samples were stored at –80°C until PCR was conducted. Unfortunately, there was an electricity shortage for about 2 hours on 20th October 2022, 4 th November 2022, and 30th December 2022, causing the temperature to rise. Increasing temperature can destabilise the helical helix of double-stranded DNA (Driessen et al., 2014). After all, PCR was the first step in the sequencing analysis of metagenomics. Species identification requires additional work, including purification, a second PCR, and sequencing. The cost of metagenomic sequencing analysis is higher, and all PCR products were placed on a single chip. A comprehensive profile of the environmental sample's biodiversity can be achieved by sequencing the entire target region.
66 CHAPTER 6 SUMMARY, CONCLUSION AND RECOMMENDATIONS FOR FUTURE RESEARCH Physicochemical characteristics and microalgae diversity indicates the water quality of the Upper East Wetland in Putrajaya. There are five microalgae groups recorded: Cyanophyceae, Chlorophyceae, Bacillariophyceae, Trebouxiophyceae, and Euglenophyceae. The abundance of cyanobacteria is related to a decline in phosphate concentration and light intensity. Whereas the abundance of Trebouxiophyceae is possibly related to increasing nitrate concentration and light intensity. Overall, based on the physicochemical parameters and the microalgae diversity, it was found that all three study sites were meso-eutrophic. In Upper East Wetland Putrajaya from July to September 2022, microscopical examinations revealed the presence of 25 different species of microalgae. Site 1 has the highest diversity in microalgae diversity, with the highest Shannon–Weiner index in July and August 2022. Moreover, the most dominant species Microcystis sp., was dominant at all locations, was the dominant species within the three sites from July to September 2022. In September 2022, molecular analysis revealed that 18S ribosomal RNA (rRNA) was effectively amplified using 18S Amplicon forward and reverse primer for microalgae identification, with DNA bands of 400 bp. However, it is crucial to conduct DNA quantification to examine the DNA qualities before conducting PCR, and this will reduce the limitations of DNA amplification and improve the PCR process. This study's molecular analysis revealed that the 18S ribosomal RNA (rRNA) was a viable molecular marker for microalgae identification. It is necessary to do more studies involving purification, second PCR, and DNA sequencing to determine the microalgae species in Upper East Wetland, Putrajaya and compare them with microscopic observations to obtain more accurate results on microalgae diversity. In conclusion, the water quality of Upper East Wetland, Putrajaya, has improved via the constructed wetland system. As a result, the constructed wetland can filter the water to remove the contaminants and harmful chemicals from the water bodies. However, to determine the water quality of Upper East Wetland, Putrajaya, adding several parameters would significantly increase the reliability of this research. For example, the future study should include the parameters like silica concentration, chlorophyll concentration, depth, biochemical oxygen demand, salinity, chemical oxygen demand and turbidity. This study could not assess these parameters due to several unfortunate challenges and technical difficulties. In short, the trophic of Upper East Wetland, Putrajaya can be improved in the future by monitoring and management to preserve its functions and aesthetic values.
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7 APPEN Physicochemical parameters data from Sampling Station Sampling Date Temp. (° C) Site 1 27-Jul-22 28.30 17-Aug-22 30.42 21-Sep-22 30.90 Site 2 27-Jul-22 28.95 17-Aug-22 30.86 21-Sep-22 30.59 Site 3 27-Jul-22 27.60 17-Aug-22 29.45 21-Sep-22 28.88 *Temp – temperature, D.O. – dissolved oxygen, Cond – conductivity