Phytoplankton biomass and primary production dynamics in Lake Kariba

Phytoplankton biomass and primary production dynamics

in Lake KaribaNdebele-Murisa M. Regina*†, Musil C. Frank‡ and Raitt L. Miles

Department of Biodiversity and Conservation Biology, University of the Western Cape, Bellville,

Cape Town, South Africa

AbstractThe present study examined spatial, seasonal and depth variations in phytoplankton biomass and primary production

(PP), compared with those reported for other tropical African lakes, to determine whether or not measured phytoplank-

ton changes might be linked to climate warming. The biomass of three major phytoplankton classes (Cyanophyceae;

Chlorophyceae; Bacillariophyceae) and net PP were measured during the midwinter and midsummer at six different

depths at 35 sampling sites distributed across the lake’s five basins. A more rigorous sampling regime was used in the

fifth basin, with phytoplankton biomass and PP rates measured every second month over a 24 month period at six differ-

ent depths at ten sampling sites located in riverine and lacustrine waters. Cyanophyceae, which displayed a gradient of

decreasing biomass from Basins 2 to 5, contributed 69% of the total phytoplankton biomass in the lake’s five basins dur-

ing summer. This percentage was approximately four times greater than that contributed by the Bacillariophyceae and

about ten times greater than that contributed by the Chlorophyceae. During winter, Bacillariophyceae biomass was equiv-

alent to that of the Cyanophyceae, but displayed an opposing gradient of increasing biomass from Basins 1 to 3, with a

subsequent biomass decline from Basins 3 to 5. Chlorophyceae exhibited no distinct biomass gradient across the five

lake basins, being undetectable during winter. The biomass of all three phytoplankton classes and the net PP varied in

magnitude and direction monthly between the lacustrine and riverine waters, with increasing water depth and with no

distinct seasonal patterns being evident. The monthly variations in biomass were related to the thermal stratification

cycle, hydrological gradients and the extent of water mixing, being similar to those reported for other tropical African

lakes. It is noteworthy that total phytoplankton biomass and PP in Lake Kariba have declined by about 95% and 50%,

respectively, since the 1980s. These declines correspond to an upward shift in the depth of the thermocline, associated

with an average temperature increase of 1.9 �C and a 50% reduction in the depth of the euphotic zone, since the 1960s.

Key wordsclimate warming, Lake Kariba, phytoplankton analyser, phytoplankton biomass, primary production.

INTRODUCTIONTropical African lakes exhibit a well-established seasonali-

ty in phytoplankton abundance and biomass (Talling

2001; Ndebele-Murisa et al. 2010). Naturally, oligotrophic

lakes, such as Edward, Kariba, Kivu and Malawi, have a

low phytoplankton biomass and species diversity and

display a seasonal succession of major phytoplankton

classes similar to that seen in Lake Tanganyika, where

Cyanophyceae and Chlorophyceae codominate when the

phytoplankton biomass reaches its peak during the rainy

season, and Bacillariophyceae dominate at turnover dur-

ing the dry season (Evans 1997; Cronberg 1997; Descy

et al. 2005; Sarmento et al. 2006; Guildford et al. 2007;

Ndebele-Murisa et al. 2010).

The composition and abundance of phytoplankton

often reflect the nutrient status of lakes, with examples

being the low Euglenophyceae biomass in Lake Ogelube

*Corresponding author. Email: [email protected]

†Present address: Department of Wildlife and Safari

Management, Private Bag 7724, Chinhoyi University of

Technology, Chinhoyi, Zimbabwe.

‡Present address: Climate Change and Bio-Adaptation

Division, South African National Biodiversity Institute,

Private Bag X7, Claremont 7735, Cape Town, South Africa.

Accepted for publication 14 October 2012.

Doi: 10.1111/lre.12005 � 2013 Wiley Publishing Asia Pty Ltd

Lakes & Reservoirs: Research and Management 2012 17: 275–289

proposed as an indicative of low organic pollution and

the predominance of desmids indicative of oligotrophic

conditions (Nweze 2006). Low nutrient concentrations

have been observed in the normally oligotrophic Lakes

Kariba, Kivu and Malawi. Nevertheless, many African

lakes are now prone to eutrophication resulting in

increased nutrient inflows from anthropogenic activities

in their catchments, as noted from the substantial

increases in primary production (PP) observed in several

tropical African lakes, including Chivero, Malawi and Vic-

toria, and impoundments such as Hartbeespoort Dam, in

which levels of PP have risen by several orders of magni-

tude from previously reported ranges. This situation is a

direct consequence of high nutrient inflows which over-

burden the natural purification systems of these water-

bodies (Robarts 1979, 1984; Mugidde 1993; Ndebele

2003; Mhlanga et al. 2006; Ndebele 2009; Haande et al.

2010).

Cyanophyceae blooms have also been reported in sev-

eral nutrient-enriched impoundments, such as Hartbees-

poort, Erfenis and Allemanskraal Dams in South Africa

(Robarts & Zohary 1986; Van Ginkel & Hohls 1999; Van

Ginkel et al. 2001), shallow tropical Yaounde Municipal

Lake in Cameroon (Kemka et al. 2006) and the South

African Orange River (Janse van Vuuren & Kriel 2008),

wherein nutrient-rich inflows have resulted in a massively

increased phytoplankton biomass dominated by Eugleno-

phyceae and Chlorophyceae. Eutrophication tends to

have more impact on shallow lake systems than on dee-

per tropical lakes such as Lakes Malawi, Victoria and

Kariba. Incidences of localized pollution, for example, are

only occasionally reported in Lakes Malawi and Victoria,

or in Lake Kariba (Feresu & Van Sickle 1989; Magadza

& Dhlomo 1996; Verschuren et al. 1998; Hecky et al.

1999; Odada et al. 2006). The water in Lake Kariba has

changed from an initial eutrophic state to that of its cur-

rent oligotrophic state, with phosphorus limiting its PP

(Moyo 1991; Lindmark 1997; Ndebele-Murisa 2011). The

high concentrations of faecal coliform bacteria recorded

in Zambezi waters above Victoria Falls, however, along

the northern shoreline of Lake Kariba, infer that the lake

waters are shifting towards a mesotrophic condition (Fer-

esu & Van Sickle 1989; Magadza & Dhlomo 1996; Phiri

et al. 2006; Ndebele-Murisa 2011).

Although interannual variations in phytoplankton com-

position and biomass are known to reflect changes in cli-

mate (Lehman et al. 1998), the impact of global warming

projected by climate change models (Hulme 1996; Hulme

et al. 2001; IPCC 2007) on phytoplankton production in

tropical African lakes has not been studied extensively

(Magadza 1994). Most past studies of phytoplankton in

tropical African lakes, such as Lake Volta (John 1986),

Lakes Malawi, Tanganyika and Victoria (Talling 1966;

Hecky & Kling 1981, 1987; Cocquyt & Vyverman 1994,

2005) and other African lakes (Talling et al. 1973; Robarts

& Southall 1977; Melack 1979; Girma & Ahlgren 2009)

did not specifically address climate-driven changes. East

African lakes, however, are potentially highly sensitive to

climate change (Johnson & Odada 1996; Odada et al.

2006; Olaka et al. 2010). Thermal stratification in Lake

Tanganyika, for example, is strongly linked to hydrody-

namic and climatic conditions (Plisnier et al. 1999), with

small climatic variations able to cause wide fluctuations

in the thermocline, which isolates nutrients from the

euphotic zone, thereby affecting phytoplankton biomass

and PP (Lewis 1974; O’Reilly et al. 2003; Verburg &

Hecky 2009). Regional climatic changes around Lake

Tanganyika over the past 80 years have already resulted

in reduced PP (O’Reilly et al. 2003; Stenuite et al. 2007;

Verburg & Hecky 2009; Tierney et al. 2010). These find-

ings are consistent with a modelling study that demon-

strated a close correspondence between phytoplankton

biomass and climate in Lake Tanganyika (Bergamino

et al. 2007).

Increased water temperatures associated with climate

warming might potentially cause a shift in phytoplankton

species composition from Chlorophyceae to Cyanophy-

ceae, which are competitively superior at higher tempera-

tures (IPCC 2007). Microcosm studies have

demonstrated that elevated temperatures suppress total

zooplankton biomass by altering phytoplankton commu-

nity composition towards high-temperature-tolerant spe-

cies, although the total phytoplankton biomass is not

usually altered (Doney 2006). These findings are consis-

tent with observed changes in phytoplankton composition

in temperature-controlled experiments conducted on

phytoplankton cultured in water samples from Lake Chi-

vero, wherein it was found that the water temperatures at

which Cyanophyceae dominated were several degrees

higher than those at which Chlorophyceae were domi-

nant (Sibanda 2003). As water temperatures increase,

algal succession follows a progression from Bacillariophy-

ceae to Chlorophyceae to Cyanophyceae (Plinski & Joz-

wiak 1999). The preponderance of Cyanophyceae at

higher water temperatures has led to concerns that

increased water temperatures attributable to global warm-

ing could result in a decline in the production of palatable

Chlorophyceae, leading to decreased zooplankton produc-

tion and a consequent decline in fish stocks. In fact,

fisheries catch data from Lake Tanganyika indicate signif-

icant negative correlations with climate (ENSO) data over

the last 40 years (Plisnier 2000, 2004; Stenuite et al.

� 2013 Wiley Publishing Asia Pty Ltd

276 N.-M. M. Regina et al.

2007). This suggests moderate warming could destabilize

plankton dynamics, thereby potentially reducing water

quality and food resources for higher trophic levels, such

as planktivorous fish, as observed in shallow cold-water

ecosystems (Strecker et al. 2004).

Analyses of climatic data for the middle Zambezi Val-

ley indicate that warming around Lake Kariba is proceed-

ing at a faster rate than predicted with regional models

(Magadza 2010, 2011; Ndebele-Murisa et al. 2011a,b).

These changes in the thermal properties of the lake are

already reflected in an upward migration of the thermo-

cline (Ndebele-Murisa 2011), pointing to future shifts in

phytoplankton species richness and production, with

potential negative impacts on fish stocks and human live-

lihoods. Accordingly, aims of this study were (i) to exam-

ine season and depth variations in phytoplankton

biomass and PP across the lake and the influence of

riverine inflows on these changes and (ii) to determine

whether or not there have been any changes in phyto-

plankton biomass and PP that might be linked to climate

warming and how these changes compare with those

observed in other tropical African lakes.

METHODS AND MATERIALS

Study areaThe study area was Lake Kariba (16–18�S, 27–29�E), the

third largest manmade lake in the world, and the largest

volumetrically. The lake was formed in 1955 by impound-

ment of the Zambezi River at the Kariba Gorge (Balon &

Coche 1974), being located in the Middle Zambezi Basin,

which is bordered by Zambia in the north and Zimbabwe

in the south.

Experimental design and sampling stationsTwo separate studies measured phytoplankton biomass

and PP at six different depths (0, 2, 5, 10, 15, 20 m) at

total of 35 sampling sites distributed across the entire

length of the lake, from Basin 1 in the south-west to

Basin 5 in the north-east. The maximum sampled depth

of 20 m corresponded to the maximum thermocline

depth in Lake Kariba reported in several past studies

(Magadza et al. 1989). In the first study, phytoplankton

measurements were conducted twice annually, once dur-

ing the lake turnover in midwinter (July 2007) and once

during the lake stratification period in midsummer (Feb-

ruary 2009), at four sampling sites located in Basin 1,

seven in Basin 2, six in Basin 3, eight in Basin 4 and

ten in Basin 5. In the second study, phytoplankton

measurements were conducted at 2 monthly intervals

over a 24 month period extending from March 2007 to

February 2009 along the depth profile described above at

ten sampling sites in Basin 5, which is where the majority

of previous long-term phytoplankton studies were con-

ducted (Ramberg 1984, 1987; Cronberg 1997). Four sam-

pling sites were located in the littoral zones of the lake

basin, in close proximity to the Charara, Gache Gache

and Sanyati River inflows and designated riverine habi-

tats. The other six sampling sites traversed the centre of

the basin, being designated lacustrine habitats. Figure 1

illustrates the locations of all the sampling sites in the

lake.

Phytoplankton biomass and photosyntheticquantum yield

Chlorophyll fluorescence is a very sensitive technique for

assessing phytoplankton biomass in the form of chloro-

phyll content, as well as for distinguishing between differ-

ent phytoplankton classes, such as Bacillariophyceae,

Chlorophyceae and Cyanophyceae. It is based on the spe-

cific fluorescence excitation properties of these differently

pigmented phytoplankton classes (Schreiber 1998). In the

present study, chlorophyll fluorescence measurements

were performed with a Pulse Amplified Modulated Phyto-

plankton (Phyto-PAM) Analyzer (Heinz Walz GMBH,

Effeltrich, Germany; Walz, 2003), which has been success-

fully applied to accurately measure the chlorophyll content

in several tropical lakes, such as Lakes Kivu and Tanganyi-

ka (Salonen et al. 1999; Sarmento et al. 2006; Stenuite

et al. 2007; De Wever et al. 2008). Water samples were col-

lected from each depth zone at each sampling site with a

Ruttner sampler. Photosynthetically active radiation (PAR)

was measured concurrently in situ under clear sky condi-

tions 2 h on both sides of midday (1000–1400 h) at each

depth zone with a quantum sensor (LiCor, Lincoln, NE,

USA) interfaced with the Phyto-PAM Analyzer.

In measuring the chlorophyll biomass of the different

phytoplankton classes, fresh unfiltered 2–3 mL volume

water samples were placed into special 15 mm Ø quartz

cuvettes, optimized for a low background signal corre-

sponding to 0.2 lg chlorophyll L)1. The background sig-

nal was determined from filtered water samples.

Chlorophyll fluorescence in the unfiltered water samples

was excited by the Phyto-PAM light-emitting diodes

(LED), which emit alternating 10 lS light pulses at four

different wavelengths (470, 520, 645 and 665 nm). The

fluorescence pulses were detected by a photomultiplier

and amplified under microprocessor control to provide

four separate continuous signals (four channels). The

chlorophyll biomass was determined on the basis of

chlorophyll fluorescence yield in the quasi-dark state

(Fo) and the quantum yield of photosystem II (PSII)

under a brief pulse of saturating light. The momentary


Primary production dynamics in Lake Kariba 277

fluorescence yield (Ft) obtained with a triggered satura-

tion pulse allowed the determination of increased fluores-

cence (Fm)Ft), with the quantum yield (QY) PSII

corresponding to (Fm)Ft) ⁄ Fm. Blue green (Cyanophy-

ceae), green (Chlorophyceae) and brown (Bacillariophy-

ceae) phytoplankton biomasses were calculated from the

original 4-channel fluorescence data with an online decon-

volution routine, based on previously stored ‘reference

excitation spectra’ determined from pure cultures of

Chlorophyceae and Cyanophyceae. Cultures were iso-

lated by growing pure strains of six species of algae

(Cyanophyceae: Anabaena flos-aquae, Cylindrospermopsis,

Microcystis aeruginosa; Chlorophyceae: Chlorella, Pedia-

strum, Straustrum) in the laboratory over a period of

12 weeks from June 2007 to August 2007. The pure cul-

tures were obtained from the University of Lund through

the Biological Sciences Department of the University of

Zimbabwe. The algae were grown in Bold’s Basal med-

ium (Bischoff and Bold, 1963) and inoculated in water

from Lake Kariba. After 12 weeks, the phytoplankton ana-

lyser was then calibrated to read Cyanophyceae and

Chlorophyceae biomass using the cultured algae.

Primary productionPhytoplankton PP was computed for the water column at

each sampling site for each of the six sampling depths,

using the equation of Gilbert et al. (2000):

PP ¼ u� PAR � 0:156�DL ð1Þ

where PP = primary production [lg O2 m)2 d)1];

u = quantum yield; PAR = photosynthetically active radia-

tion [lmol m)2 s)1]; 0.156 = conversion factor, which

considers the absorption cross-section of photosystem II

in natural phytoplankton populations and the number of

electrons required to produce one molecule of oxygen

(Estevez-Blanco et al. 2006; Kromkamp et al. 2008); and

DL = day length computed from difference between sun-

rise and sunset time at Lake Kariba in the middle of each

month, as sourced from http://www.sollumis.com.

Values were converted to mg C m)2 d)1, assuming a

molecular photosynthetic quotient of 1 (Ganf & Horne

1975; Goto et al. 2008).

Soluble reactive phosphorus and totalnitrogen measurements

Water samples were collected at each sampling site and

depth in 500 mL polythene bottles and immediately fro-

zen. The soluble reactive phosphorus (PO3�4 ) concentra-

tion was determined from these water samples in the

laboratory, using the ammonium molybdate method. The

total nitrogen concentration was determined by the wet

combustion and reduction method, after which the nitrite

concentration also was determined (APHA 1995, Murphy

& Riley 1962).

Statistical analysisAs the experimental design was not fully balanced

because of unequal numbers of measurements, a residual

maximum likelihood (REML) variance component analy-

sis (repeated-measures mixed model) was applied to test

for significant differences in measured phytoplankton bio-

masses and PP between seasons, months, lake basins,

water depth and interactions, using the Wald v2 statistics

generated by REML (GENSTAT Discovery Edition 3;

VSL Lty, Hempstead, UK). In the first REML analysis of

Fig. 1. Distribution of sampling

stations in Lake Kariba’s five basins,

with those located in the centre of

the lake designated lacustrine and

those located along the lake margin

in proximity to river inflows

designated riverine.



all 35 sampling sites, lake basins and water depth were

fitted in the fixed model and replicated winter and sum-

mer seasons in the random model. In the second REML

analysis of the ten sampling sites in the Sanyati Basin,

the lacustrine and riverine habitats and water depth were

fitted in the fixed model and replicated months in the

random model. Differences exceeding twice the average

standard error of differences were used to separate signif-

icantly different treatment means at P £ 0.05, based on

the fact that the 5% two-sided critical value is two for a

normal distribution from REML estimates.

A Student’s t-test was used to determine the correla-

tion between phytoplankton biomass and PP, with PAR,

nitrogen and phosphorus concentrations.

RESULTS

Lake basin phytoplankton biomassTotal phytoplankton biomass, and that of Cyanophyceae,

Chlorophyceae and Bacillariophyceae, differed signifi-

cantly (P < 0.001) between the winter and summer sea-

sons and between lake basins (Table 1). The lowest total

phytoplankton biomasses, and those of all three phyto-

plankton groups, were observed in Basin 5 (Fig. 2a–d).

Cyanophyceae and Chlorophyceae biomasses were signif-

icantly (P £ 0.05) different overall, being higher in sum-

mer than in winter, while the converse was true for

Basins 1 to 3 in the total phytoplankton biomass and the

Bacillariophyceae (Fig. 2a–d). There were significant

(P £ 0.05) interactions, however, between seasons and

between lake basins for total phytoplankton biomass and

those of all three phytoplankton groups (Table 1). Signifi-

cantly (P £ 0.05) higher total phytoplankton and Bacillari-

ophyceae biomasses were observed during the winter

than the summer, although they were confined to the first

three and four lake basins, respectively (Fig. 2a,d). In con-

trast, significantly (P £ 0.05) higher Cyanophyceae biomas-

ses were observed in all lake basins in the summer than in

the winter, displaying a gradient of decreasing concentra-

tions from Basins 2 to 5, with undetectable Chlorophyceae

biomasses in all lake basins during the winter (Fig. 2b,c).

Lake basin net PPNet PP differed significantly (P £ 0.05) among lake

basins and significantly (P £ 0.001) with water depth

(Table 1). Net PP was higher overall in the winter than

in the summer, with the highest net PP being observed

in Basin 5 and the lowest in Basin 2 (Fig. 3a). There was

a significant (P £ 0.001) interaction between season and

lake basin, however, as well as between season and

depth, for net PP (Table 1). Significantly (P £ 0.05)

higher winter than summer net PP rates were confined

to Basin 3 (Fig. 3a). A steeper decline in net PP with

increasing water depth was observed during the summer

than in the winter, with significantly (P £ 0.05) higher

summer than winter net PP rates apparent at the water

surface (0 m), although not at any of the sampled water

depths (Fig. 3b).

Sanyati basin phytoplankton biomassTotal phytoplankton biomasses, and those of Cyanophy-

ceae, Chlorophyceae and Bacillariophyceae, differed sig-

nificantly (P £ 0.001) monthly. They also differed

significantly (P < 0.05) between the lacustrine and riverine

waters, and along the water depth profile, for the Cyano-

Table 1. Wald v2 statistics derived from REML (repeated-measures model) for testing the effects of season, lake basin and water depth

and their interactions on different phytoplankton group biomass and net primary production (PP) in Lake Kariba

REML d.f.

Wald v2 statistics

Total phytoplankton Cyanophyceae Chlorophyceae Bacillariophyceae Net PP

Main effects

Season 1 9.61*** 100.03*** 173.31*** 60.41*** 0.63

Basin 4 48.17*** 49.49*** 17.91** 37.30*** 6.79*

Depth 5 2.75 2.19 5.59 5.57 21.99***

Two-way interactions

Season · Basin 4 36.17*** 11.79* 18.98*** 32.59*** 4.88***

Season · Depth 5 2.56 1.61 8.16 3.83 3.69**

Basin · Depth 20 8.12 15.12 10.88 11.11 0.7

Three-way interactions

Season · Basin · Depth 20 15.12 24.69 17.41 8.51 0.959

Values in bold are significant at *P £ 0.05; **P £ 0.01; ***P £ 0.001



phyceae (Table 2). Overall, the highest total phytoplank-

ton, Cyanophyceae and Bacillariophyceae biomasses

occurred in July, with the lowest in June and October. The

highest Chlorophyceae biomasses occurred in January

and March, while Chlorophyceae was undetectable

(<0.1 lg L)1) between May and August and between

November and December (Fig. 4a–d). Cyanophyceae bio-

masses increased with increasing water depth overall, with

peak biomasses observed at the 10 m water depths, with a

subsequent decline at greater water depths (Fig. 5).There

were significant (P £ 0.05) interactions, however, between

month and habitat for total phytoplankton, Cyanophyceae

and Bacillariophyceae biomasses (Table 2), which were

significantly (P £ 0.05) higher in July and November, with

the converse being observed in January (Fig. 4a–c). Chlo-

rophyceae biomasses were significantly (P £ 0.05) higher

in the riverine than in the lacustrine waters in March, with

the converse being observed in January (Fig. 4d). There

also was a significant (P £ 0.001) interaction between

month and water depth for the Cyanophyceae biomass,

which varied monthly with increasing water depth. Peak

Cyanophyceae biomasses, for example, were observed at

the 20 m depth in July, at the 10 m depth in September

and between 0 and 5 m in November (Fig. 5).

Sanyati basin net PPNet PP differed significantly (P £ 0.01) monthly, and with

water depth (Table 2), with the highest overall values

observed in February, October and November, and in the

surface waters (Fig. 6a,b). There were significant

(P < 0.05) interactions between month and habitat, how-

ever, and between month and water depth, for net PP

(Table 2). Significantly (P £ 0.05) higher net PP rates

were observed in the riverine than in the lacustrine

waters in February and October (Fig. 6a). Declines in net

PP, with increasing water depth, were observed in all

months except January, March, June, September and

December. The values did not differ significantly

(P ‡ 0.05) along the depth profile (Fig. 6b). The steepest

declines in net PP with increasing water depth were

observed in February, April, October and November.

Significantly (P £ 0.05) higher values were observed in

the surface waters during these months than in all other

water depths (Fig. 6b).

Total nitrogen and soluble reactive phosphorus con-

centrations in the lake water were positively correlated

with both phytoplankton analyser-enumerated biomasses

and PP in all phytoplankton classes, except in the Chloro-

phyceae and Cyanophyceae for biomass and in the Bacil-

lariophyceae for PP (Table 3).

DISCUSSIONCyanophyceae contributed 68.6 ± 1.9% of the total phyto-

plankton biomass in the five basins of the lake during

summer. This value closely corresponded with those

0

2

4

6

8

10 Summer Winter

0

2

4

6

8

10

12Summer Winter

0

5

10

15

Basin 1 Basin 2 Basin 3 Basin 4 Basin 5

Basin 1 Basin 2 Basin 3 Basin 4 Basin 5Basin 1 Basin 2 Basin 3 Basin 4 Basin 5

Basin 1 Basin 2 Basin 3 Basin 4 Basin 5

Summer Winter

0

0.2

0.4

0.6

0.8

1Summer Winter

Tota

l bio

mas

s(μ

g ch

loro

a L

–1)

Chl

orop

hyce

ae b

iom

ass

(μg

L–1 )

Cya

noph

ycea

e bi

omas

s(μ

g L–

1 )B

acill

ario

phyc

eae

biom

ass

(μg–

1 )

(a) (b)

(c) (d)

Fig. 2. Seasonal variations in (a) total phytoplankton biomass and that of (b) Cyanophyceae, (c) Chlorophyceae and (d). Bacillariophyceae in

different basins of Lake Kariba. Average standard error of differences shown by bars.



reported by Ramberg (1987) and Cronberg (1997), which

indicated that Cyanophyceae comprised between 70% and

80% of the total phytoplankton biomass in the entire lake

during the summer rainy season, which extends from

November to February. The highest summertime Cyano-

phyceae percentage of the total phytoplankton biomass

was observed in Basin 5 (84.0%), followed by Basin 1

(72.6%) and Basin 3 (72.3%). The high Cyanophyceae per-

centage in Basin 5 was attributed to localized pollution

from Tilapia fish cage cultures (Troell & Berg 1997;

Ndebele-Murisa & Phiri 2008) and the discharge of par-

tially treated sewage effluent into the lake, estimated to

be 3.6 tonnes day)1 (Mulendema 2000), and in Basin 1

attributed to the nutrient-rich Zambezi River inflow (Mar-

shall 1982). The high Cyanophyceae percentage in Basin

3, however, did not correspond to a reported hydrological

gradient of decreasing water nutrient concentration with

increasing distance from the Zambezi River inflow during

the summer (Coche 1974; Masundire 1997; Cronberg

1997). The high Cyanophyceae percentage in this basin

was attributed to wind-induced wave action along its

exposed shoreline, especially during the hot, dry months

of August to October (Coche 1974), causing upwelling of

nutrients known to stimulate PP (Mtada, 1987; Van Ruth

2009).

Chlorophyceae contributed on average only 8.1 ± 0.8%

of the total phytoplankton biomass in the five lake basins

during summer, contrasting to the observations of Ram-

berg (1987) and Cronberg (1997) that the Chlorophyceae

codominate with Cyanophyceae during summer. Labora-

tory experiments have demonstrated that the optimum

growth temperatures for Chlorophyceae are between 20

and 25 �C (Sibanda 2003; Senerpont-Domis et al. 2007).

Forty-five percentage of the summer water temperatures

(a)

(b)

Fig. 3. Seasonal variations in net primary production in (a)

different basins and (b) water depths of Lake Kariba. Average

standard error of differences shown by bars.

Table 2. Wald v2 statistics derived from REML (repeated-measures model) for testing the effects of month, habitat (riverine vs. lacustrine)

and water depth and their interactions on the different phytoplankton group biomass and net primary production (PP) in Sanyati Basin of

Lake Kariba

REML d.f.

Wald v2 statistics

Total phytoplankton Cyanophyceae Chlorophyceae Bacillariophyceae Net PP

Main effects

Month 11 1 552.46*** 17.65*** 116.29*** 30.79*** 43.96**

Habitat 1 0.01 7.02* 1.60 0.18 2.20

Depth 55 5.88 7.02* 9.44 6.14 38.51***

Two-way interactions

Month · Habitat 11 94.89*** 15.03* 3.08 14.58** 3.45*

Month · Depth 55 76.55 6.87 6.3 11.43 5.41***

Habitat · Depth 5 3.89 6.13 6.09 3.56 0.17

Three-way interactions

Month · Habitat · Depth 55 53.19 7.97 6.68 9.53 1.23

Values in bold are significant at *P £ 0.05; **P £ 0.01; ***P £ 0.001



at or near the surface of Lake Kariba exceeded 25 �C

(Tumbare 2008; Magadza 2011). These high tempera-

tures and photoinhibition of algal photosynthesis by the

high PAR values at the water surface attributable to high

summer light intensities at the water surface (Cronberg

1997) also might explain the lower Chlorophyceae bio-

masses recorded at shallower water depths in the lake in

the late summer (February and March). Photoinhibition

of phytoplankton photosynthesis at solar irradiances

exceeding 2000 lE m)2 s)1 has been observed in the sur-

face waters of Lake Tanganyika, reflecting an increased

fraction of light-acclimated pico phytoplankton in the phy-

toplankton biomass (Stenuite et al. 2009). Similarly,

small-sized (<2 lm), light-acclimated phytoplankton in

the surface water of Lake Malawi account for 30–50% of

the total phytoplankton chlorophyll (Guildford et al.

2007). Ninety-seven percentage of the phytoplankton

quantum yields measured in this study were below 0.83,

indicating the phytoplankton were under some environ-

mental stress (Falkowski & Raven 1997). Although the

precise cause of this stress is unclear, it does seem to be

partly related to photoinhibition of phytoplankton photo-

synthesis, because Chlorophyceae biomasses were signif-

icantly (P £ 0.01) negatively correlated with PAR. The

ability of heterocyst-forming Cyanophyceae to fix

nitrogen might partly explain the absence of a positive

correlation between phytoplankton analyser-enumerated

Cyanophyceae biomasses and lake water nitrogen levels.

0

4

8

12

16

20

24

28

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

Autumn Winter Spring Summer

LC RIV

0

4

8

12

16

20

24

28LC RIV

0

4

8

12

16LC RIV

0

0.5

1

1.5

2

2.5

3

3.5LC RIV




Autumn Winter Spring SummerFeb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan


Cya

noph

ycea

e bi

omas

s(μ

g ch

loro

phyl

l a L

–1)

Bac

illar

ioph

ycea

e bi

omas

s(μ

g ch

loro

phyl

l a L

–1)

Tota

l bio

mas

s(μ

g ch

loro

phyl

l a L

–1)

Chl

orop

hyce

ae b

iom

ass

(μg

chlo

roph

yll a

L–1

)(a) (b)

(c) (d)

Fig. 4. Monthly variations in (a) total phytoplankton biomass and those of (b) Cyanophyceae, (c) Bacillariophyceae and (d) Chlorophyceae in

lacustrine and riverine habitats in the Sanyati Basin of Lake Kariba. Average standard error of differences shown by bars.

Fig. 5. Monthly variations in

Cyanophyceae biomass with water

depth in the Sanyati Basin of Lake

Kariba. Average standard error of

differences shown by bars.



Conversely, the positive correlation observed between

microscopically enumerated Cyanophyceae concentra-

tions and the total nitrogen concentrations might reflect

migration of some flagellated Cyanophyceae up and down

the water column, in response to nutrient supply.

There were distinct seasonal trends in phytoplankton

biomass and PP in Lake Kariba’s Basin 5. Four distinct

peaks in total phytoplankton biomass were observed in

this basin. A July–August peak was observed, concurring

with an August peak normally observed in the lake after

turnover (Masundire 1994, 1997). This resulted from the

release of nutrients trapped in the hypolimnion and

released by break-up of the stratification in June–July

(Ramberg 1987; Masundire 1997). The November and

January peaks were caused by local flooding discharging

nutrient-rich water as run-off into the lake during the

summer rainy season. The March to April peak was a

consequence of annual flooding of the Zambezi River

(FAO, 2009), carrying large quantities of nutrient-rich

sediments into the lake (Marshall 1982). Ramberg (1987)

and Cronberg (1997) also reported two well-defined max-

ima in phytoplankton biomass in the Sanyati Basin. The

first maxima lasted 3–4 months during the summer rainy

season, being comprised mainly of Cyanophyceae (70–

90%) and some Dinophyceae (13%). The second maxima

lasted 1–2 months during the dry winter season, being

comprised of Bacillariophyceae codominating with Cyano-

phyceae (Ramberg 1987; Cronberg 1997). Similarly, a

2 month (July–August) maxima in Bacillariophyceae bio-

mass also were observed in Basin 5 during the dry winter

season in this study. A high Bacillariophyceae biomass

also was measured in this lake basin during the summer

(November–April) rainy season, likely being a conse-

quence of the inability of the phytoplankton analyser to

distinguish between Dinophyceae (yellow algae) and Bac-

illariophyceae (brown algae), as also reported by Hart

and Wragg (2009). In this regard, Cronberg (1997) also

found that dinoflagellate species comprised up to 62% of

the total phytoplankton biomass in Lake Kariba during

the summer season.

The observed seasonal changes in the relative abun-

dance of different phytoplankton classes in Lake Kariba

also are a common feature in other African lakes, exam-

ples being Lakes Malawi, Tanganyika and Victoria, in

which Cyanophyceae dominate during summer stratifica-

tion and Bacillariophyceae dominate during the stratifica-

tion breakdown in winter (Cronberg 1997; Lung’ayia

et al. 2001; Stenuite et al. 2009). Lightly different seasonal

patterns, however, have been reported for other African

lakes. An example is Lake Ogelube in Nigeria, in which

the phytoplankton biomass during the summer rainy sea-

son was comprised mainly of Chlorophyceae, followed in

decreasing order of abundance by Cyanophyceae and

Bacillariophyceae. This sequence changes in the dry win-

(a)

(b)

Fig. 6. Monthly variations in primary production in (a) lacustrine

and riverine habitats and (b) different water depths in the Sanyati

Basin of Lake Kariba. Average standard error of differences shown

by bars.

Table 3. t-statistics for Pearson’s correlations between measured

biomass, net primary production (PP) and soluble phosphorus

(PO3�4 ) and total nitrogen concentrations

Parameter Total N PO3�4 PAR

Cyanophyceae

biomass

1.29 )2.29* )1.39

Bacillariophyceae

biomass

4.11*** )0.99 )1.26

Chlorophyceae

biomass

1.29 )2.29* )3.86***

PP )0.0375*** 0.007616*** 0.6114

PAR, photosynthetically active radiation.

Values in bold are significant at *P £ 0.05; **P £ 0.01;

***P £ 0.001



ter season, wherein the relative abundance of Bacillario-

phyceae exceeds that of Cyanophyceae (Nweze 2006).

The measured range of total phytoplankton biomass

in this study in Basin 5 of Lake Kariba of 0.1–

77.7 lg chlorophyll_a L)1 exceeded that of 2–11 lg chlo-

rophyll_a L)1 measured in 1990 by Lindmark (1997), but

was much lower than that of 200–1300 lg chloro-

phyll_a L)1 measured in 1983 by Ramberg (1987) and

Cronberg (1997). This result identified an approximate

95.1% decline in phytoplankton biomass since 1983. Simi-

larly, it was reported that phytoplankton biomass in Lake

Tanganyika declined by 70% between 1975 and 2000 (Ver-

burg et al. 2003), with the decline being accompanied by

substantial changes in phytoplankton composition. The

formerly dominant Cryptophyceae and Chrysophyceae,

which comprised 34% of the total phytoplankton biomass

in the north basin in 1975, were reduced to 3% in 2000

(Verburg et al. 2003). This reduction was accompanied

by a 44% reduction in Bacillariophyceae biomass during

the winter season and an 88% reduction in the summer

season over the 25 year monitoring period (Verburg et al.

2003; Descy et al. 2005). These phytoplankton biomass

changes in Lake Tanganyika have been attributed to

warming of the upper waters over the past century that

have intensified stratification, diminishing mixing of shal-

low and nutrient-rich deeper waters, thereby resulting in

the decreased PP and an expanded anoxic water mass

(Descy et al. 2006). Pico phytoplankton are presently

dominant in Lake Tanganyika as a result, contributing up

to 70% of the total phytoplankton biomass (Descy et al.

2005; Stenuite et al. 2009). This feature also was recently

observed in Lake Kivu (Sarmento et al. 2008), whose

waters have warmed up by an average of 0.5 �C over the

55 year period from 1937 to 2002 as a consequence of

elevated temperatures attributed to global warming (Hal-

bwachs et al. 2002).

Measured total phytoplankton biomass and PP rates in

Lake Kariba compared favourably with those reported for

other oligotrophic African waters, examples being Cleve-

land Dam, and Lakes Albert and George (Table 4), for

which other analytical techniques (light and dark bottle O2

production; 14C uptake) were used to measure PP. Lake

Malawi’s reported average PP of 4600 mg C m)2 day)1

(Guildford et al. 2007), however, and Lake Tanganyika’s

reported current PP of between 340 and 4300 mg

C)2 day)1 (Vuorio et al. 2003; Stenuite et al. 2007) were

both approximately double that measured in Lake Kariba.

Exceptionally elevated PP rates also have been reported

for some eutrophic African lakes, examples being Lake

Chivero, with an average of 23 300 mg C m)2 day)1

(Ndebele & Magadza 2005), and Lake Victoria, with an

average of 29 100 mg C m)2 day)1 (Silsbe 2004). These

exceptionally high PP rates corresponded with an

extraordinary high phytoplankton biomass of 104 mg L)1,

the highest recorded in natural tropical African lakes

(Ochumba & Kibaara 1989; Sarmento et al. 2006).

Despite different analytical methods being applied in

measuring PP in different waterbodies, the results

obtained in this study do suggest a 50% decline in PP in

Lake Kariba from a previously reported average of

0.42 g C m2 day)1 (Cronberg 1997) to the current mea-

sured average of 0.21 ± 0.03 g C m2 day)1. This decline

is attributed to an upward shift in the depth of the ther-

mocline, associated with an average temperature increase

of 1.9 �C (Ndebele-Murisa 2011), and a 50% reduction in

the depth of the euphotic zone from previously reported

depths of 31.8 m between 1965 and 1966 (Coche 1974)

and 17.9 m between 1986 and 1989 (Magadza et al. 1989)

Table 4. Comparison of average biomass (chlorophyll a) and primary production (PP) levels in some major African lakes

Lake Country Year Chlorophyll a (lg L)1) PP (mg C m)2 day)1) Source of data

Kivu DRC ⁄ Rwanda 2003–2005 2.2 620 Sarmento et al. (2009)

Cleveland Zimbabwe 2005–2006 8.2 120 Ndebele (2009)

George Uganda 1967–1968 10.0 134 Ganf (1975)

Kariba Zambia ⁄ Zimbabwe 2007–2009 10.6 206 Ndebele-Murisa (2011)

Tanganyika Tanganyika 2002–2003 6.7 434 Stenuite et al. (2007)

Malawi Malawi 1997–2000 4.0 463 Guildford et al. (2007)

Baringo Kenya 2003 55.0 480 Schager and Oduor (2003)

Nakuru Kenya 2000–2003 16.0 1960 Ballot et al. (2004)

Naivasha Kenya 2000 130.0 2000 Hubble and Harper (2002)

Chivero Zimbabwe 2002–2003 43.0 2330 Ndebele and Magadza (2005)

Victoria Kenya ⁄ Uganda 2001–2002 72.0 2906 Silsbe (2004)



to the current estimated depth of 15 m. The latter value

is derived from a plot of average PP vs. dissolved oxygen

concentration in Lake Kariba, from which was estimated

the compensation depth (Zc) at which oxygen evolution

during photosynthetic carbon assimilation balances respi-

ratory oxygen uptake (Fig. 7).

Diminished phytoplankton production rates also have

been reported for Lakes Kivu and Tanganyika, also being

attributed to upward shifts in the thermocline depth asso-

ciated with warming of the waters, slower mixing rates

and a reduced mixed layer volume (O’Reilly et al. 2003;

Verburg et al. 2003; Descy et al. 2006; Stenuite et al.

2007; Verburg & Hecky 2009). Similarly, decreased PP

rates in Lake Malawi have been attributed to increasing

temperatures, causing a warmer lake and, consequently,

a shallower, more stable thermocline restricting nutrient

fluxes from the hypolimnion to the surface mixed water

layer (Vollmer et al. 2002, 2005; Guildford et al. 2007).

These findings are corroborated by geochemical records

obtained from sediment cores of changes in Lake Malawi

over the past 730 years, attributed to natural climatic

forcing and anthropogenic activities. These seemingly

cosmopolitan declines in PP in African lakes with cli-

mate warming, however, have potentially deleterious

consequences for the fish stocks and related human live-

lihoods (Odada et al. 2006; IPCC 2007; Hecky et al., 2010;

Ndebele-Murisa et al. 2010).

ACKNOWLEDGEMENTSThe financial sponsorship of the International Foundation

for Science (IFS) Grant No. A4598-1 (2008), which

enabled the completion of this study, is gratefully

acknowledged. In addition, the authors acknowledge the

assistance of the University Lake Kariba Research Station

and UZ-VLIR-UOS Aquatic Ecology project, Biological

Sciences Department and the Tropical Resource Ecology

Program of the University of Zimbabwe for their provi-

sion of equipment and assistance in field sampling and

laboratory analyses.

REFERENCESAPHA (1995) Standard Methods, 19th edn. American

Public Health Association, Washington, DC.

Ballot A., Krienitz L., Kotut K. et al. (2004) Cyanobacteria

and Cyanobacterial toxins in three alkaline Rift Valley

lakes of Kenya- Lakes Bogoria, Nakuru and Elmentaita.

J. Plankton. Res. 26, 925–35.

Balon E. K. & Coche A. G. (1974) Lake Kariba: a man-

made tropical ecosystem in Central Africa. Dr. W. Junk

Publishers, The Hague. Biol. Monogr. 24, 1–247.

Bergamino N., Loisellea S. A., Cozar A., Dattiloa A. M.,

Bracchini L. & Rossi C. (2007) Examining the

dynamics of phytoplankton biomass in Lake Tangany-

ika using empirical orthogonal functions. Ecol. Model.

204, 156–62.

Bischoff H. & Bold H. C. (1963) Phycology studies. IV.

Some soil algae from enchanted rock and related algal

species. University of Texas Publication, Texas. pp. 95.

Coche A. G. (1974) Limnological study of a tropical reser-

voir. In: Lake Kariba, A Man-Made Tropical Ecosystem

in Central Africa (eds E. Balon & A. G. Coche) pp. 1–

247. Biol. Monogr. 24.

Cocquyt C. & Vyverman W. (1994) Composition and

diversity of the algal flora in the East African great

lakes: a comparative survey of lakes Tanganyika,

Malawi (Nyasa) and Victoria. Arch. Hydrobiol. Beih.

Ergebn. Limnol. 44, 161–72.

Cocquyt C. & Vyverman W. (2005) Phytoplankton in

Lake Tanganyika: a comparison of community composi-

tion and biomass off Kigoma with previous studies

27 years ago. J. Great Lakes Res. 31, 535–46.

Cronberg G. (1997) Phytoplankton in Lake Kariba. In:

Advances in the Ecology of Lake Kariba (ed. J. Moreau)

pp. 66–101. University of Zimbabwe Publications, Ha-

rare, Zimbabwe.

De Wever A., Muylaert K., Langlet D. et al. (2008) Differ-

ential response of phytoplankton to additions of nitro-

gen, phosphorus and iron in Lake Tanganyika. Freshw.

Biol. 53, 264–77.

Descy J. P., Hardy M. A., Stenuite S. et al. (2005) Phyto-

plankton pigments and community composition in Lake

Tanganyika. Freshw. Biol. 50, 668–84.

Fig. 7. A plot of primary production against dissolved oxygen in

Lake Kariba’s Sanyati Basin. Zc is the compensation depth at

which oxygen evolution during photosynthetic carbon assimilation

balances respiratory oxygen uptake.



Descy J. P., Andre L., Vyverman W. & Deleersnijder E.

(2006) Climate variability as recorded in Lake Tangany-

ika (CLIMLAKE). Final report to the Scientific Support

Plan for a sustainable development policy (SPSD II)

Global change, ecosystems and biodiversity atmo-

sphere and climate, Brussels.

Doney S. C. (2006) Plankton in a warmer world. Nature

444, 695–6.

Estevez-Blanco P., Cermeno P., Espineira M. & Fernan-

dez E. (2006) Phytoplankton photosynthetic efficiency

and primary production rates estimated from fast repe-

tition rate fluorometry at coastal embayments affected

by upwelling (Rias Baixas, NW of Spain). J. Plankton

Res. 28, 1153–65.

Evans J. H. (1997) Spatial and seasonal distribution of

phytoplankton in an African Rift Valley lake (L. Albert,

Uganda, Zaire). Hydrobiologia 354, 1–16.

Falkowski P. G. & Raven J. A. (1997) Aquatic Photosyn-

thesis. Blackwell Science, Oxford, UK. pp. 375.

Feresu S. B. & Van Sickle J. (1989) Coliforms as a mea-

sure of sewage contamination of the River Zambezi.

J. Appl. Bacteriol. 68, 397–403.

Food and Agricultural Organisation (FAO) Aquasat

(2009) FAO’s information system on water and agricul-

ture – Country profile Zimbabwe. Version 2009.

Accessed at: http://www.fao.org/nr/water/aquastat/

countries/zimbabwe/index.stm on 19 July 2010.

Ganf G. G. (1975) Photosynthetic production and irradi-

ance-photosynthesis relationship of the phytoplankton

from a shallow equatorial lake (Lake George, Uganda).

Oecologia (Berlin) 18, 165–83.

Ganf G. G. & Horne J. A. (1975) Diurnal stratification,

photosynthesis and nitrogen-fixation in a shallow,

equatorial lake (Lake George, Uganda). Freshw. Biol.

5, 13–39.

Gilbert M., Wilhelm C. & Ritcher M. (2000) Bio-optical

modeling of oxygen evolution using in vivo fluores-

cence: comparison of measured and calculated

photosynthesis ⁄ irradiance (P-I) curves in four repre-

sentative phytoplankton species. J. Plant Physiol. 157,

307–14.

Goto N., Kihira M. & Ishida N. (2008) Seasonal distribu-

tion of photosynthetically active phytoplankton using

pulse amplified modulated fluorometry in the large

monomictic Lake Biwa, Japan. J. Plankton. Res. 30,

1169–77.

Guildford S. J., Bootsma H. A., Taylor W. D. & Hecky R.

E. (2007) High variability of phytoplankton photosyn-

thesis in response to environmental forcing in

oligotrophic Lake Malawi ⁄ Nyasa. J. Great Lakes Res.

33, 170–85.

Haande S., Rohrlack T., Seymyalo P. et al. (2010) Phyto-

plankton dynamics and Cyanobacterial abundance in

Murchison Bay of Lake Victoria (Uganda) in relation

to environmental conditions. Limnologica 41, 20–9.

Halbwachs M., Tietze K., Lorke A. & Mudaheranwa C.

(2002) Investigations in Lake Kivu (East Central Africa)

after the Nyiragongo Eruption of January 2002, Specific

Study of the Impact of the Sub-Water Lava Inflow on

the Lake Stability. Final report to the International

Scientific Team, SOLIDARITES, Aide Humanitaire

d’Urgence, Paris, France.

Hart R. C. & Wragg P. D. (2009) Recent blooms of dino-

flagellates Ceratium in Albert Falls Dam (KZN): his-

tory, causes, spatial features and impacts on a

reservoir ecosystem and its zooplankton. Water SA 35,

455–68.

Hecky R. E. & Kling H. J. (1981) The phytoplankton and

proto-zooplankton of the euphotic zone of Lake Tang-

anyika- species composition, biomass, chlorophyll

content, and spatio-temporal distribution. Limnol. Ocea-

nogr. 26, 548–64.

Hecky R. E. & Kling H. J. (1987) Phytoplankton ecology

of the great lakes in the Rift valleys of Central Africa.

Arch. Hydrobiol. Beih. Ergebn. Limnol. 25, 197–228.

Hecky R. E., Kling H. J., Johnson T. C., Bootsma H. A. &

Wilkinson P. (1999) Algal and sedimentary evidence

for recent changes in the water quality and limnology

of Lake Malawi ⁄ Nyassa. Water quality report, Lake

Malawi ⁄ Nyassa ⁄ Niassa biodiversity conservation pro-

ject. SADC ⁄ GEF. pp. 191–214.

Hecky R. E., Mugidde R., Ramla P. S., Talbot M. R. &

Kling G. W. (2010) Multiple stressors cause rapid eco-

system change in Lake Victoria. Freshwat. Biol. 55,

19–42.

Hubble D. S. & Harper D. M. (2002) Phytoplankton com-

munity structure and succession in the water column

of a shallow tropical lake (Lake Naivasha, Kenya).

Hydrobiologia 488 (Developments in Hydrobiology

168), 89–98.

Hulme M. (1996) Climate Change and SOUTHERN

AFRica: An Exploration of Some Potential Impacts and

Implications in the SADC Region. WWF International,

Avenue du Mont Blanc, Gland, Switzerland. pp. 99.

Hulme M., Doherty R., Ngara T., New M. & Lister D.

(2001) African climate change: 1900–2100. Climate Res.

17, 145–68.

Intergovernmental Panel on Climate Change (IPCC), Boko

M., Niang I., Nyong A., Vogel C., Githeko A., Medany

M., Osman-Elasha B., Tabo R. & Yanda P. (2007) Cli-

mate change 2007: africa. impacts, adaptation and vulner-

ability. In Contribution of Working Group II to Fourth



Assessment Report of the Intergovernmental Panel on

Climate Change (eds M. L. Parry, O. F. Canziani, J. P.

Palutikof, P. J. van der Linden & C. E. Hanson) pp. 433–

67. Cambridge University Press, Cambridge, UK.

Janse van Vuuren S. & Kriel G. P. (2008) Cylindrospermop-

sis raciborskii, a toxic invasive Cyanobacterium in south-

ern African freshwaters. Afr. J. Aquat. Sci. 33, 17–26.

John D. M. (1986) The inland waters of tropical West

Africa. An introduction and botanical review. Arch.

Hydrobiol. Ergebn. Limnol. 23, 1–244.

Johnson T. C. & Odada E. O. (1996) The Limnology, Cli-

matology and Paleoclimatology of the East African

Lakes. Gordon and Breach Publishers, Amsterdam.

Kemka N., Njine T., Togouet S. H. Z. et al. (2006) Eutro-

phication of lakes in urbanized areas: the case of Yao-

unde Municipal Lake in Cameroon, Central Africa.

Lakes Reserv. Res. Manage. 11, 47–55.

Kromkamp J. C., Dijkmana N. A., Peenea J., Simisb S. G.

H. & Gonsb H. J. (2008) Estimating phytoplankton pri-

mary production in Lake Ijsselmeer (The Netherlands)

using variable fluorescence (PAM-FRRF) and C-uptake

techniques. Eur. J. Phycol. 4, 327–44.

Lehman J. T., Litt A. H., Mugidde R. & Lehman D. A.

(1998) Lake Victoria plankton ecology: mixing, depth

and climate-driven control of condition. In: Environ-

mental Change and Response in East African Lakes

(ed. J. T. Lehman) pp. 157–72. Kluwer, Amsterdam.

Lewis M. W. (1974) Primary production in the plankton

community of a tropical lake. Ecol. Monogr. 44, 377–409.

Lindmark G. (1997) Sediments characteristics in relation

to nutrient distribution in littoral and pelagic waters of

Lake Kariba. In: Advances in the Ecology of Lake Kari-

ba (ed. J. Moreau) pp. 11–65. University of Zimbabwe

Publications, Harare, Zimbabwe.

Lung’ayia H., Sitoki L. & Kenyanya M. (2001) The nutri-

ent enrichment of Lake Victoria (Kenyan waters).

Hydrobiologia 458, 75–82.

Magadza C. H. D. (1994) Climate change: some multiple

impacts in Southern Africa. In: Climate Change and

Food Security (ed. T. E. Downing) pp. 662. NATO ASI

Series. Series 1: Global Environmental Change 37.

Magadza C. H. D. (2008) Limnology news from Zimba-

bwe. SILnews 52, 12–3. Available from URL: http://

www.limnology.org/news/silnews52.pdf. Accessed 12

October 2009.

Magadza C. H. D. (2010) Environmental state of Lake

Kariba and Zambezi River Valley: lessons learned and

not learned. Lakes Reserv. Res. Manage. 15, 167–92.

Magadza C. H. D. (2011) Indications of the effects of cli-

mate change on the pelagic fishery of Lake Kariba, Zam-

bia-Zimbabwe. Lakes Reserv. Res. Manage. 16, 15–22.

Magadza C. H. D. & Dhlomo E. J. (1996) Wet seasons

coincidence of coliform bacteria in inshore waters of

Kariba town area. Lakes Reserv.Res. Manage. 2, 89–

96.

Magadza C. H. D., Heinenan A. & Dhlomo E. J. (1989)

Some preliminary results on the limnochemistry of

Lake Kariba, with special reference to nitrogen and

phosphorus. In: Ecology of Lake Kariba (ed. C. H. D.

Magadza) Vegetatio 82, 13–24.

Marshall B. E. (1982) The influence of river flow on pela-

gic sardine catches in Lake Kariba. J. Fish Biol. 20,

465–70.

Masundire H. M. (1994) Seasonal trends in zooplankton

densities in Sanyati basin, Lake Kariba, multivariate

analysis. Hydrobiologia 272, 211–30.

Masundire H. M. (1997) Bionomics and production of

zooplankton and its relevance to the pelagic fishery in

Lake Kariba. Unpublished Ph.D. Thesis, University of

Zimbabwe, Harare, Zimbabwe.

Melack J. M. (1979) Photosynthetic rates in four tropical

African fresh waters. Freshw. Biol. 9, 555–71.

Mhlanga L., Day J., Cronberg C., Chimbari M., Siziba N.

& Annadotter H. (2006) Observations on limnological

conditions associated with a fish kill of Oreochromis nil-

oticus in Lake Chivero following collapse of an algal

bloom. Afr. J. Ecol. 44, 199–208.

Moyo S. M. (1991) Cyanobacterial nitrogen fixation in

Lake Kariba, Zimbabwe. Verh. Int. Ver. Limnol. 24,

1123–7.

Mtada O. S. M. (1987) The influence of thermal stratifica-

tion on pelagic fish yields in Lake Kariba, Zambia/Zim-

babwe. J. Fish Biol. 30, 127–33.

Mugidde R. (1993) The increase in phytoplankton activity

in Lake Victoria (Uganda). Verh. Int. Ver. Limnol. 25,

846–9.

Mulendema B. C. (2000) Recent developments in the

integrated management of the water resources develop-

ments in the Zambezi Basin. In: Management of River

Basins and Dams; The Zambezi River Basin (ed. J. J.

Tumbare) pp. 165–8. Balkema, Rotterdam, The Nether-

lands.

Murphy J. & Riley J. P. (1962) A modified single-solution

method for the determination of phosphorus in natural

waters. Anal. Chim. Acta 27, 31–6.

Ndebele M. R. (2003) Some aspects of the phytoplankton

community of Lake Chivero, Harare, Zimbabwe.

Unpublished M.Sc. Thesis, University of Zimbabwe,

Harare, Zimbabwe.

Ndebele M. R. (2009) Primary production and other lim-

nological aspects of Cleveland Dam, Harare, Zimba-

bwe. Lakes Reserv. Res. Manage. 14, 151–61.



Ndebele M. R. & Magadza C. H. D. (2005) The primary

production of an inland artificial lake in Zimbabwe. Pro-

ceedings, 11th World Lakes Conference: Restoration

and Management of Ecosystems, Nairobi, Kenya, 31

October–4 November 2005.

Ndebele-Murisa M. R. (2011) An analysis of the primary

and secondary production in lake Kariba under a

changing climate. Unpublished PhD Thesis, University

of the Western Cape, South Africa.

Ndebele-Murisa M. R. & Phiri C. (2008) An environmen-

tal audit report for Lake Harvest Fishing Company

(Lmt.), 1st quarter (March 2008). Kariba, Zimbabwe.

Ndebele-Murisa M. R., Musil C. & Raitt L. (2010) A

review of phytoplankton dynamics in tropical African

lakes. S. Afr. J. Sci. 106, 13–8.

Ndebele-Murisa M. R., Mashonjowa E. & Hill T. (2011a)

The implications of a changing climate on the Kapenta

fish stocks of Lake Kariba. Trans. R. Soc. S. Af. 66,

105–19.

Ndebele-Murisa M. R., Mashonjowa E. & Hill T. (2011b)

The declines in the Kapenta fish stocks in Lake Kariba- a

case of climate changing? Trans. R. Soc. S. Af. 66, 220–3.

Nweze N. O. (2006) Seasonal variations in phytoplankton

populations in Ogelube Lake, a small natural West Afri-

can Lake. Lakes Reserv. Res. Manage. 11, 63–72.

Ochumba O. P. & Kibaara D. I. (1989) Observations on

Cyanophyceae algal blooms in the open waters of Lake

Victoria, Kenya Afr. J. Ecol. 27, 23–34.

Odada E. O., Olago D. O. & Ochola W. O. (2006) Envi-

ronment for development: an ecosystem assessment of

Lake Victoria basin environmental and socio-economic

status, trends and human vulnerabilities. UNEP ⁄ PASS.

Olaka L. A., Odada E. O., Trauth M. H. & Olago D. O.

(2010) The sensitivity of East African rift lakes to cli-

mate fluctuations. J. Paleolimnol. 44, 629–44.

O’Reilly C. M., Alin S. R., Plisnier P. D., Cohen A. S. &

MaKee B. A. (2003) Climate change decreases aquatic

ecosystem productivity of Lake Tanganyika, Africa.

Nature 424, 766–8.

Phiri C., Day J., Chimbari M. & Dhlomo E. (2007) Epi-

phytic diatoms associations in a submerged macro-

phyte, Vallisneria aethiopica, in the shallow marginal

areas of Sanyati Basin (Lake Kariba): a preliminary

assessment of their use as biomonitoring tools. Aquat.

Ecol. 41, 169–81.

Plinski M. & Jozwiak T. (1999) Temperature and N:P

ratio as factors causing blooms of blue-Cyanophyceae

algae in the Gulf of Gdansk. Oceanoplongia 41, 73–80.

Plisnier P.-D. (2000) Recent climate and limnology

changes in Lake Tanganyika. Verh. Int. Ver. Limnol.

27, 1–4.

Plisnier P.-D. (2004) Probable impact of climate and

ENSO on Lake Tanganyika. Bull. Seance Acad. R. Sci.

Outre-Mer 50, 185–96.

Plisnier P.-D., Chitamwebwa D., Mwape L., Tshibangu K.,

Langenberg V. & Coenen E. (1999) Limnological

annual cycle inferred from physical-chemical fluctua-

tions at three stations of Lake Tanganyika. Hydrobiolo-

gia 407, 45–58.

Ramberg L. (1984) Phytoplankton gradients in the rainy

season in Lake Kariba. Verh. Int. Ver. Limnol. 22,

1590–3.

Ramberg L. (1987) Phytoplankton succession in the

Sanyati basin, Lake Kariba. Hydrobiologia 153, 193–

202.

Robarts R. D. (1979) Underwater light penetration, chlo-

rophyll a and primary production in a tropical African

lake (Lake Mcllwaine, Rhodesia). Arch. Hydrobiol. 86,

423–44.

Robarts R. D. (1984) Factors controlling primary produc-

tivity in a hypereutrophic lake (Hartbeespoort Dam,

South Africa). J. Plankton. Res. 6, 91–105.

Robarts R. D. & Southall G. C. (1977) Nutrient limitation

of phytoplankton growth in seven tropical man-made

lakes, with special reference to Lake Mcllwaine, Rhode-

sia. Arch. Hydrobiol. 79, 1–35.

Robarts R. D. & Zohary T. (1986) The influence of a

Cyanobacterial hyperscum on the heterotrophic activity

of planktonic bacteria in a hypereutrophic lake. Appl.

Environ. Microbiol. 51, 609–13.

Salonen K., Sarvala J., Jarvinen M. et al. (1999) Phyto-

plankton in Lake Tanganyika - vertical and horizontal

distribution of in vivo fluorescence. Hydrobiologia 407,

89–103.

Sarmento H., Isumbisho M. & Descy J. P. (2006) Phyto-

plankton ecology of Lake Kivu (eastern Africa). J. Plank-

ton. Res. 28, 815–29.

Sarmento H., Unrein F., Isumbisho M., Stenuite S., Gasol

J. & Descy J. P. (2008) Abundance and distribution of

picoplankton in tropical, oligotrophic Lake Kivu, East-

ern Africa. Freshw. Biol. 53, 756–71.

Sarmento H., Unrein F., Isumbisho M. et al. (2009)

Phytoplankton ecology of Lake Kivu (Eastern Africa):

biomass, production and elemental ratios. Verh. Int.

Ver. Limnol. 30, 709–13.

Schager M. & Oduor S. O. (2003) On the limnology of

Lake Baringo (Kenya): II. Pelagic primary production

and algal composition of Lake Baringo, Kenya. Hydro-

biologia 506, 297–303.

Schreiber U. (1998) Chlorophyll fluorescence, new instru-

ments for special Applications. In: Photosynthesis,

Mechanisms and Effects, Vol. 5 (ed G. Garab) pp.



4253–8. Kluwer Academic Publishers, Dordrecht, The

Netherlands.

Senerpont-Domis L., Mooij W. & Huisman J. (2007) Cli-

mate-induced shifts in an experimental phytoplankton

community: a mechanistic approach. Hydrobiologia

584, 403–13.

Sibanda P. (2003) The possible effects of global warming

on the growth of algae. Unpublished B.Sc. Thesis, Uni-

versity of Zimbabwe, Harare, Zimbabwe.

Silsbe G. M. (2004) Phytoplankton production in Lake

Victoria, East Africa. Unpublished M.Sc. Thesis, Uni-

versity of Manitoba, Canada.

Stenuite S., Pirlot S., Hardy M. A. et al. (2007) Phyto-

plankton production and growth rate in Lake Tanganyi-

ka: evidence of a decline in primary productivity in

recent decades. Freshw. Biol. 52, 2226–39.

Stenuite S., Tarbe A.-L., Sarmento H. et al. (2009) Photo-

synthetic picoplankton in Lake Tanganyika: biomass

distribution patterns with depth, season and basin.

J. Plankton. Res. 12, 1513–44.

Strecker A. L., Cobb T. P. & Vinebrooke R. D. (2004)

Effects of experimental greenhouse warming on phyto-

plankton and zooplankton communities in fishless

alpine ponds. Limnol. Oceanogr. 49, 1182–90.

Talling J. F. (1966) The annual cycle of stratification and

phytoplankton growth in Lake Victoria (East Africa).

Int. Rev. ges. Hydrobiol. 51, 545–621.

Talling J. F. (2001) Environmental controls on the function-

ing of shallow tropical lakes. Hydrobiologia 458, 1–8.

Talling J. F., Wood R. B., Prosser M. V. & Baxter R. M.

(1973) The upper limit of photosynthetic productivity

by phytoplankton: evidence from Ethiopian Soda lakes.

Freshw. Biol. 3, 53–76.

Tierney J. E., Mayes M. T., Meyer N. et al. (2010) Late-

twentieth-century warming in Lake Tanganyika unprec-

edented since AD500. Nat. GeoSci. 3, 422–5.

Tilahun G. & Ahlgren G. (2010) Seasonal variations in

phytoplankton biomass and primary production in the

Ethiopian Rift Valley lakes Ziway, Awassa and Chamo-

The basis for fish production. Limnol. 40, 330–42.

Troell M. & Berg H. (1997) Cage fish farming in the tropi-

cal Lake Kariba, Zimbabwe: impact and biogeochemical

changes in sediment. Aquacult. Res. 28, 527–44.

Tumbare J. M. (2008) Infrastructure management in a

changing environment. The case of Kariba dam. In:

Towards Climate Change Adaptation. Building Adapta-

tive Capacity in Managing African Transboundary River

Basins (ed. T. Petermann) pp. 142–56. InWEnt, Ger-

many.

Van Ginkel C. E. & Hohls B. C. (1999) Toxic algae in

Erfenis and Allemanskraal dams. Occasional report by

the Institute for Quality Studies, Department of Water

Affairs and Forestry. Rep. No. N ⁄ C400 ⁄ 03 ⁄ DEO ⁄ 1999.

Van Ginkel C. E., Hohls B. C. & Vermark E. (2001) A

Ceratium hirundinella (O.F. Muller) bloom in Hart-

beespoort Dam, South Africa. Water SA 27, 269–76.

Van Ruth P. D. (2009) Spatial and temporal variation of

primary and secondary productivity in the East Great

Australian Bight. Unpublished M.Sc. Thesis, University

of Adelaide, Australia.

Verburg P. & Hecky R. E. (2009) The physics of the

warming of Lake Tanganyika by climate change. Lim-

nol. Oceanogr. 54, 2418–30.

Verburg P., Hecky R. E. & Kling H. (2003) Ecological

consequences of a century of warming in Lake Tang-

anyika. Science 301, 505–7.

Verschuren D., Edgington D. N., Kling H. J. & Johnson

T. C. (1998) Silica depletion in Lake Victoria: sedimen-

tary signals at offshore stations. J. Great Lakes Res. 24,

118–30.

Vollmer M. K., Weiss R. F. & Bootsma H. A. (2002) Ven-

tilation of Lake Malawi. In: The East African Great

Lakes: Limnology, Paleolimnology and Biodiversity

(eds E. O. Odada & D. O. Olago) pp. 209–33. Kluwer

Academic Publishers, The Netherlands.

Vollmer M. K., Bootsma H. A., Hecky R. E. et al. (2005)

Deep-water warming trend in Lake Malawi, East Africa.

Limnol. Oceanogr. 50, 727–32.

Vuorio K., Nuottajarvi M., Kalevi S. & Sarvala J. (2003)

Spatial distribution of phytoplankton and picocyano-

bacteria in Lake Tanganyika in March and April 1998.

Aquat. Ecosyst. Health Manage. 6, 263–78.

Walz H. (2003) Phytoplankton Analyzer Phyto-PAM and

Phyto-Win Software V 1.45, System Components and

Principles of Operation. � Heinz Walz GmbH, Ger-

many. pp. 47–64.



Phytoplankton biomass and primary production dynamics in Lake Kariba

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