The Influence of Land Based Activities on the Phytoplankton … · 2020. 8. 20. · classified Ramisi-Vanga system as an oligotrophic system implying that the current level of land

Int. J. Environ. Res., 6(1):151-162, Winter 2012ISSN: 1735-6865

Received 4 Feb. 2011; Revised 19 July 2011; Accepted 26 July 2011

*Corresponding author E-mail: [email protected]

151

The Influence of Land Based Activities on the Phytoplankton Communitiesof Shimoni-Vanga system, Kenya

Kiteresi, L.I.1, Okuku, E.O.1,2*, Mwangi, S. N.1,3, Ohowa, B.1, Wanjeri, V.O.1,Okumu, S. 1 and Mkono, M. 1

1 Kenya Marine and Fisheries Research Institute, P.O. Box 81651, Mombasa, Kenya2 Soil and Water Management Division, Faculty of Bioscience Engineering, Katholike Universiteit

Leuven, Kasteelpark Arenberg 20, B-3001 Heverlee, Belgium3 University of Nairobi, P.O. Box 30197, G.P.O, Nairobi, Kenya

ABSTRACT: Phytoplankton communities play a significant role in the oceanic biological pump by formingthe base of the trophic structure. Increase in nutrients loading affects spatial and temporal distribution ofphytoplankton. This study examined the phytoplankton community structure and ecological indices in relationto nutrients dynamics in both estuarine and oceanic areas of Ramisi-Vanga systems along the Kenyan coast.Surface water samples were collected and analysed for nutrients (PO4

3--P, NO3--N and NH4

+-N) andphytoplankton abundance and community structure. This study reported very diverse phytoplanktoncommunity structure consisting of 88 taxa that were dominated by Chaetoceros sp., Coscinodiscus sp.,Nitzschia sp., Pseudo-nitzschia sp., Alexandrium sp., Protoperidium sp. and Prorocentrum sp that are amongthe potentially harmful algae. Diatoms were the most abundant taxa in Ramisi-Vanga system. Phytoplanktonabundance was found to be higher in the estuarine systems (1182.06±149.14 cells/L) as compared to theoceanic systems (551.99±166.70 cells/L) with high abundance observed in May for oceanic and estuarinesystems. Shannon Weiner’s species diversity index was greater than 2 in both oceanic and estuarine systems.Phytoplankton species’ abundance, composition and diversity were found to be influenced by the availabilityof NH4

+-N, NO3--N and PO4

3--P. Phytoplankton cell density was below 4000 cells/ L, thus, this study hasclassified Ramisi-Vanga system as an oligotrophic system implying that the current level of land basedactivities are not having significant impacts on the phytoplankton communities.

Key words:Phytoplankton, Ecological indices, Diatoms, Dinoflagellates, Nutrients, Flagellates

INTRODUCTIONPhytoplankton form the base of the marine food

chain and as such sustains diverse assemblages ofspecies ranging from microscopic zooplankton to largemarine mammals, seabirds and fish. With just aproportion of less than 1% of the earth’sphotosynthetic biomass, marine phytoplankton isresponsible for more than 45% of the planet’s annualnet primary production (Field et al., 1998). Indeed,phytoplankton is the fuel on which marine ecosystemsrun (Falkowski, 1994; Huppert et al., 2002) throughconversion of inorganic compounds to high- energyrich organic compounds (Lalli and Parsons, 1993).

Coastal environments differ in their physical andhydrographic properties such as depth, tidal mixing or

nutrient loadings and these differences can lead tocomplex phytoplankton dynamics (Cebrian and Valiela,1999). This is further complicated by the fact that waterquality in coastal areas worldwide is constantlychanging in response to rapidly increasing land basedactivities such as fertilizer application, land clearingand waste discharge. The increasing land basedactivities are affecting the spatial and taxonomicdistribution of this important oceanic biota as well astheir photosynthetic activity. The role of land basedactivities is both direct, through changes in oceanchemistry and indirect through climatically inducedalterations in the ocean’s physical circulation(Sarmiento et al., 1998).

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Kiteresi L.I. et al.

Plankton are relatively short lived and are known torespond quickly to environmental perturbations suchas point source pollution (Osore, 2003). Zingone etal., (1995) also reported that phytoplankton periodicityis affected by the different sources of land-derivednutrients and by their dilution patterns. Thus,phytoplankton communities could be considered asrecurrent organized systems of organisms respondingin a related way to changes in the environment(Legendre and Legendre, 1998). The factors thatinfluence water quality of the Ramisi-Vanga systemsare natural processes such as rivers’ freshwater supplyand land based activities related to changes in landuse. In this paper, we briefly examine the controls ofwater chemistry on plankton community structure(mainly ecological indices) with an emphasis on theeffects of nutrients dynamics.

MATERIALS & METHODSThis study was conducted in Ramisi-Vanga system

located in the southern part of the Kenyan coast (Fig.1). Sampling was carried out in the estuarine andoceanic systems. Ramisi-Vanga system is a low-lyingcoastal plain submergent complex (below 30m contour)dominated by an extensive cover of mangrove forest,intertidal areas covered with sea grass beds and

shallow water lagoons harboring the coral reefs. Thesecritical systems are inter-linked through exchange ofwater, nutrients and carbon by the tidally controlledcirculation and river discharge (UNEP, 1998). In thisstudy, rivers Umba, Ramisi and Mwena were consideredas estuarine sites characterized by mangroveecosystems with freshwater input whereas Wasini,Kima, Sii Kiromo and Shimoni were considered oceanicsites. The sampling stations were River Umba (U1, U2and U3); R. Ramisi (R1, R2 and R3); R. Mwena (M1,M2, M3 and M4); Wasini (W1, W2 and W3); Kima(K1, K2 and K3), Sii Kiromo (Si1, Si2 and Si3) andShimoni (S1, S2 and S3) (Fig. 1). Samples were collectedfrom the stations in February, March, May, June andAugust in 2009. The choice of sampling periods wasbased on past study elsewhere that had shown thatundisturbed successions of phytoplankton communityapproach competitive exclusion and ecologicalequilibrium after approximately 35 to 60 days (Reynolds,1993). The mid-point of this range, 47.5 days is roughlyin agreement with the sampling intervals adopted.Although phytoplankton populations are not strictlyperiodic and may exhibit sudden collapses that we mayhave sometimes missed, this analogue does at leastprovide a rough justification for the samplingfrequency that was adopted for this study.

Fig. 1. Map showing the sampling stations

Int. J. Environ. Res., 6(1):151-162, Winter 2012

153

Qualitative concentrated samples were collectedby filtering 20 liters of water (collected from just belowthe water surface) through a 20 µm phytoplankton net.For numerical analysis and species identification, 250ml of water samples were fixed in 5% Lugol’s solutionand kept undisturbed for three to four days till completesedimentation was achieved. The samples were furtherconcentrated to a volume of 50 ml and 1 ml (in triplicate)of the concentrated sample transferred into aSedgewick Rafter counting cell mounted on an invertedcompound microscope (Leica DMIL) and counting ofphytoplankton cells carried out in 100 squares of thecell chosen randomly. The results were expressed asthe number of cells per litre. The cell counts were usedto compute the cell density using the Striling, (1985)formula where the plankton density was estimated by:

N = (A * 1000 * C) / (V * F * L)

Where N = No of plankton cell per litre of originalwater,A = Total No. of plankton counted,C = Volume of final concentrate of the sample in ml;V = Volume of a field in mm3F = No. of fields countedL = Volume of original water in litre.

Estimation of the phytoplankton abundance wascarried out by sedimentation method (Utermöhl, 1958).Phytoplankton were identified using identification keysby Carmelo, (1997) and Botes, (2003). Wheneverpossible, identification was carried out to the specieslevel, although in some cases identification was onlypossible to genus level.

Nutrients samples were collected in acidprewashed polyethylene bottles from the surface andstored frozen prior to analysis. The methods describedby Parsons et al., (1984) and APHA, (1998) were usedto analyze ammonium (NH4

+-N), Nitrate + Nitrite {(NO3-

+ NO2-)-N} and orthophosphate (PO4

3--P) in the watersamples. All the chemicals used for analysis were ofanalytical grade and all the glassware were pre-washedin acid before use. PO4

3--P was determined using theascorbic acid method at 885 nm. NH4

+-N wasdetermined using the indophenol method at 630 nmafter at least six hours. Dissolved (NO3

- + NO2-)-N was

determined using cadmium reduction method andmeasured colorimetrically at 543 nm. Analytical qualitycheck was carried out by running procedural blanksalongside the samples as well as through the use of acheck standard.

Phytoplankton data were expressed as ecologicalindices to describe the phytoplankton communitystructure, eutrophication and water quality. The indices

used were species richness, abundance (cell density),Shannon Wiener’s diversity indices and Pielou’sevenness indices.

Species richness was taken as the total number oftaxa found in a sample. Shannon Wiener’s speciesdiversity index (Shannon, 1948) was calculated fromthe taxa and abundance (cells L-1) data for each site oneach sampling occasion. Shannon-Wiener’s speciesdiversity index formula used is described below

H = -Σ ni/N log2 ni/N;Where: ni is the number of individuals of the ithspeciesN is the total number of individuals.Pielou evenness index was calculated as follows;

E = H/ln S;

Where: H is the Shannon Wiener’s species diversityindex and S is the species richness (number of species).

Phytoplankton and nutrients data were categorizedas estuarine and oceanic and subjected to Shapiro Wilknormality test and Levene’s homogeneity of variancetest. Phytoplankton data that were not normallydistributed were log transformed to improve thenormality of the data. Kolmongorov-Smirnovgoodness of fit test for normality was not significantin both the estuarine and oceanic systems (p>0.05).This validated the phytoplankton data for parametricanalysis using one way ANOVA. Species abundance,diversity, richness and evenness indices that showedsignificant difference among sites and months werefurther subjected to post hoc comparisons usingTurkey Honest Significant Difference test. Pearson’scorrelation coefficient was used to test for anyrelationships between nutrients and phytoplanktonindices.

RESULTS & DISCUSSIONA total of 88 taxa were encountered in this study.

79 taxa were recorded in the estuaries whereas 75 taxawere present in the oceanic systems. Phytoplanktonwere grouped either as diatoms, dinoflagellates,flagellates or ‘others’ group (to include all the othergroups rather than the three major groups). Generally,the diatoms were the most diverse group with a totalof 45 taxa, followed by the dinoflagellates, ‘others’groups and flagellates with 20, 17 and 6 taxarespectively (Table 1). Temporally, the abundance ofdiatoms dominated the rest of the phytoplanktongroups throughout the study.

In the estuarine system, the diatoms were the mostabundant group with a mean ± SE of 1858.65±367.61

154

Phytoplankton Communities

Tabl

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sp, C

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155

Int. J. Environ. Res., 6(1):151-162, Winter 2012

cells/L. Diatoms showed a declining trend fromFebruary to March and an increase in cell density inMay (Fig. 2). The months of June and August had thehighest cell density of diatoms (>3000 cells/L). Ingeneral, the most abundant diatom taxa in the estuarinesystems were Coscinodiscus sp (149.95±24.07 cells/L)and Nitzschia sp (116.42 ± 83.155 cells/L). The monthof February had the highest cell densities of(Coscinodiscus sp, Thalassiosira sp andActinoptychus sp.). Coscinodiscus sp. was the mostabundant in May, June and August.

Generally, Coscinodiscus sp had the highestcell density (145.19±43.73 cells/L) in R. Umba. Pseudo-nitzschia sp. was the most abundant taxa in March.On the spatial scale, Pseudo-nitzschia sp. dominatedin rivers Ramisi and Mwena whereas Nitzchia sp.dominated in rivers Mwena and Umba. Diatomsdominance was observed over the studied period withpeak abundances in June and August and the lowestabundance in March (Fig. 2). The diatoms abundancessignificantly differed (F=11.85; p

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Kiteresi L.I. et al.

while Oscillatoria sp. was most abundant in May, Juneand August. In general Oscillatoria sp. was also themost abundant taxa in river Umba (103.25 +34.35 SEcells/L). The abundance of ‘others’ in the estuarinesystem increased in May and June (Fig. 2). Theflagellates with the least species richness in this studywere the least in abundance in both estuarine andoceanic systems.

Generally, the oceanic system abundances werelower than in the estuarine system (Fig. 3). Leading inabundance in the oceanic system were Alexandriumsp (110.97±16.34 cells/L), Chaetoceros sp (102.34±28.63cells/L) and Protoperidinium sp (65.40±8.75 cells/L).Diatoms were still the most abundant group in theoceanic systems (Fig. 2) with Chaetoceros sp(102.34±28.63 cells/L), Pseudo-nitzchia sp (59.03±17.74cells/L) and Rhizosolenia sp (59.93±13.17 cells/L)dominating. Rhizosolenia sp were most abundant inSii Kiromo (66.08±10.59 cells/L) and Kima (53.65±22.11cells/L) whereas Chaetoceros sp dominated in Wasini(78.19±22.03 cells/L). Rhizosolenia sp. had highest celldensities in June (55.02±6.36 cells/L). Generally,Chaetoceros sp dominance was also observed inAugust (194.85±33.85 cells/L) and May (905.11±161.97cells/L) whereas Pseudo-niztschia sp dominated inFebruary (17.67±3.37 cells/L) and May (874.62±32.39cells/L).

The dinoflagellates abundance was lowest inFebruary (Fig. 2). Protoperidinium sp. was the mostabundant taxa among the dinoflagellates in Sii Kiromo(58.47±8.24 cells/L) and Shimoni (148.25±69.90 cells/

L). In general, Protoperidinium sp. also dominated inFebruary (14.93±3.74 cells/L) and May (407.77±87.65cells/L). Spatially, Wasini area had high abundance ofAlexandrium sp. (194.87±24.76 cells/L). Generally,Alexandrium sp also dominated in June (117.11±20.23cells/L) and August (131.61±23.83 cells/L). Thetemporal variation of dinoflagellates abundance weresignificant (F=23.01; p

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The correlation matr ix between PO43--P

concentrations and most phytoplankton groups (Table3) showed a negative correlation. A similar negativesignificant correlations were observed for NO3

--Nconcentrations and the four phytoplankton groups withsignificant correlations observed for dinoflagellates inriver Umba (r=-0.72; p

158

Phytoplankton Communities

Fig. 3. Phytoplankton groups, species abundance and richness numbers in both the estuarineand oceanic system of the Ramisi-Vanga area

Table 3. Pearson’s correlation between log transformed nutrients concentrations and the phytoplanktongroups in estuarine and oceanic systems

Phytoplankton Group PO43--P NO 3

--N NH 4+-N

Diatoms -0.27 -0.65** 0.36

Dinoflagella tes -0.19 -0.49* 0.28

Flagella tes -0.01 -0.71* 0.63*

Estuar ine

Others 0.08 -0.63** 0.62**

Diatoms 0.64** -0.48* 0.62**

Dinoflagella tes 0.53* -0.60** 0.59**

Flagella tes 0.61* -0.62* 0.82**

Oceanic

Others 0.36 -0.52* 0.18

 * Significant (pÂ0.05)** Significant (pÂ0.01)

159

Int. J. Environ. Res., 6(1):151-162, Winter 2012

0.600.65

0.700.750.800.85

0.900.951.00

Feb Mar May Jun Aug

Eve

nnes

s, E

Inde

x

1.501.701.902.102.302.502.702.903.103.303.50

Div

ersi

ty, H

Inde

x

Evenness, E Diversity, H

0.600.650.700.750.800.850.900.951.00

Ramisi Mwena Umba

Eve

nnes

s, e

inde

x

1.501.701.902.102.302.502.702.903.103.303.50

Div

ersi

ty, H

Inde

x

Evenness, E Diversity, H

0.60

0.65

0.70

0.75

0.800.85

0.90

0.95

1.00

Feb May Jun Aug

Eve

nnes

s, E

Inde

x

1.501.701.902.102.302.502.702.903.103.303.50

Div

ersi

ty, H

Inde

x

Evenness, E Diversity, H

0.600.650.700.750.800.850.900.951.00

Wasini Kima SiiKiromo

Shimoni

Eve

nnes

s, E

Inde

x

1.501.701.902.102.302.502.702.903.103.303.50

Div

ersi

ty, H

Inde

x

Evenness, E Diversity, H

Fig. 4. Phytoplankton evenness E, and Shannon H, diversity indices in the Ramisi-Vanga system

0

50

100

150

200

250

300

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Months

Am

ount

(mm

)

)

Fig. 5. Rainfall pattern in Msambweni District (source:District Crop Report December 2010)

x x xxx

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Kiteresi L.I. et al.

Ceratium fusus, Prymnesium sp., Coscinodiscus sp.,Thalassiosira sp., Ceratualina sp., Rhizosolenia sp.,Chaetoceros sp., Pseudo-nitzschia sp., Cylindrothecasp., Guinardia sp., Nitzschia sp., Amphora sp., andFibrocapsa sp. Lyngbya sp. and Oscillatoria sp.

The diatoms dominance in abundance observedin this study could be supported by previous findingsof Zingone et al., (1995) that singled out diatoms asthe abundant taxa in nutrient rich coastal waters. Worthnoting is the high abundances that were observed inMay and June that is characterized by increasedprecipitation which corresponded to increasednutrients levels caused by increase in surface runoff.The dominance of diatoms in the two systems wasalso observed in February and March (that had lowprecipitation hence reduced nutrient influx) could beattributed to their ability to withstand a wide range ofnutrient concentrations. In contrast, dinoflagellates hadlower abundance than the diatoms as they are knownto have unimpressive nutrient-dependent uptake andgrowth that result in poor competitive abilities forinorganic macronutrients (Falkowski and Knoll, 2007)as compared to diatoms and other functionalphytoplankton groups. This also explains the temporalsignificant difference in abundance within this groupin relation to nutrients loading concentrations.

The high abundance of cyanobacteria in the ‘other’phytoplankton group in February and March (that arecharacterized by low precipitation and low nutrientslevels) could be attributed to their nitrogen fixing abilityduring N-limiting situations (Sumich and Morrissey,2004). Cyanobacteria with their characteristic smallsized cells have a competitive advantage undernutrient-limited conditions (Falkowski and Knoll, 2007)due to their high surface to volume ratio; they are alsoable to use organic forms of phosphorus (Labry et al.,2002) and can as such may flourish to form blooms.This further explains why high abundances ofcyanobacteria were observed in Ramisi and Mwenarivers that are known to have low influx of nutrients incomparison to Umba River. It can also be noted thatthe cyanobacteria proliferation was minimal in oceanicareas except in February as most marine cyanobacteriaare especially abundant in intertidal and estuarine areaswith a smaller role in oceanic waters (Sumich andMorrissey, 2004). Oscillatoria sp abundance duringthe months of high precipitation in Umba River and SiiKiromo could be attributed to their tolerance toincreased nutrients concentrations. The flagellates’low abundance in the two systems could be attributedto their motile nature and the ability to move to areaswith favourable conditions.

In general, the increase in phytoplankton groups’abundance corresponded to a decrease in the NO3

--N

concentrations in Ramisi-Vanga system. Findings byYajnik and Sharada, (2003) showed that NO3

--N uptakeby phytoplankton is severely reduced by the presenceof NH4

+-N. The month of May being the onset of therainy season, the high abundance in oceanicphytoplankton as compared to estuarine systems wasattributed to increased influx of nutrients and couldalso be attributed to river inputs that create a thin halinestratification which is favourable for phytoplanktonproduction (Chapelle, 1990). The early rains carry loadsof loose particulate matter which reduces the photiczone in the water column hence the slight reductionphytoplankton abundance in the estuarine system.

The species abundance, composition anddiversity of phytoplankton communities in this studycorresponded to nutr ients levels although thebiogeochemical functioning of this area is largelyunknown. Nutrient influx during the early rains in Mayled to increase in phytoplankton abundance in theoceanic systems which later reduced in June. Thedecrease in abundance in June was accompanied byan increase in diversity index, species richness andevenness index due to favourable conditions forproliferation of diverse phytoplankton taxa. The lowspecies richness in the oceanic system in comparisonto the estuarine system both temporally and spatiallymay have been controlled by abiotic and biotic factorsproviding equilibrium between accumulation and lossof species over time (Fischer, 1960). Species evennesswas lowest in River Ramisi which on the other handhad the highest species richness and abundance. Thismeant that a few taxa dominated the phytoplanktoncommunity in this estuarine system. The contrary wasobserved in River Mwena that could be an indicationof favorable environmental condition encouraging faircompetition among the phytoplankton communitiesleading to overlapping niches and efficient resourceutilization. In general, the species diversity indexrevealed good species equitability in Ramisi - Vangasystem that ranged from 2 to 3. Shimoni village whichis adjacent to ocean, receives runoffs and leachate fromland based activities thus increased nutrientsconcentrations unlike the other sites which are withinWasini channel that experience frequent dilution/mixingwith the nutrient depleted oceanic water. In the oceanicsystem, phytoplankton periodicity is affected by thedifferent sources of land-derived nutrients and by theirdilution patterns (Zingone et al., 1995). This enabledthe more tolerant species to highly proliferate inShimoni area as it has been reported elsewhere thatphytoplankton composition generally change withnutrient loadings and in response to pollutant levelsbecause of different nutrient needs and sensitivitiesto contaminants (U.S. EPA, 2000). High disturbances

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can suppress or eliminate many members of thecommunity which in turn lowers the species richnessindex. The few species that will be favoured in suchspecies shift always thrive in high numbers and thiscould be the possible explanation for the observedhigh abundance that corresponded to low speciesrichness in this study.

According to the classification scheme proposedby Siokou-Frangou and Pagou, (2000); Pagou, (2000),the Ramisi-Vanga system with phytoplankton celldensities ranging only from 194.96 to 3919.6 cells/Lcould be classified as oliogotrophic. Oligotrophicsystems are defined by this scheme to be systems withphytoplankton cell densities less than 6000 cell/L.

CONCLUSIONIn conclusion, diatoms dominance was observed

in Ramisi-Vanga system. The wide distribution andhigh abundance of diatoms reported in this study isindicative of a conducive environment for active growthand survival of other forms of lives. The cleardominance of diatoms in the study areas, both inabundance and diversity also suggests the presenceof a clean environment. On the other hand, the presenceof bloom causative taxa in high abundance is a signalof potential blooms within the Ramisi- Vanga systemeven during periods of reduced nutrients input. Thesepotential HABs species serves in this study as an earlywarning on possible toxins contamination of seafoodfor human use. Ramisi-Vanga system has beenclassified in this study as an oligotrophic system andas such this study concludes that the currently levelof land based activities are not having adverse effectson the phytoplankton communities of this system.

ACKNOWLEDGEMENTFunding for this work was provided through SEED

funds (Kenya Marine and Fisheries Research Institute,KMFRI) and RAF 7008 Project (International AtomicEnergy Agency, IAEA). We are greatly indebted to theDirectors of these Institutions for supporting this work.We also appreciate the efforts of KMFRI staff thatassisted in field samples collection and analysis in oneway or the other. We acknowledge the efforts of theanonymous reviewer who tirelessly and promptlycritiqued this work.

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