Freshwater Biology (2005) 50, 668–684
doi:10.1111/j.1365-2427.2005.01358.x
Phytoplankton pigments and community composition in Lake Tanganyika J . - P . D E S C Y , * M . - A . H A R D Y , * S . S T E´ N U I T E , * S . P I R L O T , * B . L E P O R C Q , * I . K I M I R E I , † B. SEKADENDE,† S. R. MWAITEGA† AND D. SINYENZA‡ *Laboratory of Freshwater Ecology, URBO, Department of Biology, University of Namur, Namur, Belgium † Tanzanian Fisheries Institute (TAFIRI), Ministry for Tourism, Natural Resources and the Environment, Kigoma, Tanzania ‡ Department of Fisheries (DOF), Ministry of Agriculture, Food and Fisheries, Mpulungu, Zambia
SU M M A R Y 1. A 2-year (2002–2003) survey of chlorophyll and carotenoid pigments is reported for two off-shore stations of Lake Tanganyika, Kigoma (Tanzania) and Mpulungu (Zambia), and from three cruises between those sites. Chlorophyll a concentrations were low (0.3– 3.4 mg m)3) and average chlorophyll a integrated through the 100 m water column were similar for both stations and years (36.4–41.3 mg m)2). Most pigments were located in the 0–60 m layer and decreased sharply downward. Chlorophyll a degradation products (phaeophytins and phaeophorbides) were detected at 100 m depth, whereas carotenoids became undetectable. Temporal and seasonal variation of the vertical distribution of pigments was high. 2. The biomass of phytoplankton groups was calculated from marker pigment concentrations over the 0–100 m water column using the CHEMTAX software. On average for the study period, chlorophytes dominated in the northern station, followed by cyanobacteria T1 (type 1, or Synechococcus pigment type), whereas cyanobacteria T1 dominated in the south. Cyanobacteria T2 (type 2, containing echinenone), presumably corresponding to filamentous taxa, were detected in the rainy season. Diatoms (and chrysophytes) developed better in the dry season conditions, with a deep mixed layer and increased nutrient availability. Very large variation in the vertical distribution of algal groups was observed. 3. Our observations on phytoplankton composition are broadly consistent with those from previous studies. Our pigment data provide evidence for the lake-wide importance of picocyanobacteria and high interannual variation and spatial heterogeneity of phytoplankton in Lake Tanganyika, which may render difficult assessment of long-term changes in phytoplankton driven by climate change. Keywords: HPLC, Lake Tanganyika, phytoplankton, picocyanobacteria
Introduction Several studies have addressed phytoplankton composition and dynamics in large East African lakes, and have provided a basis for understanding the ecology Correspondence: J.-P. Descy, URBO, Department of Biology, 61, rue de Bruxelles, B-5000 Namur, Belgium. E-mail:
[email protected]
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of these pelagic algal communities. In particular, comprehensive records providing qualitative and quantitative data, covering at least 1 year, exist for Lakes Tanganyika (Hecky & Kling, 1981), Victoria (Talling, 1987) and Malawi (Patterson & Kachinjika, 1995). Based on these studies, a common pattern of variation and response to seasonal changes has been described for the phytoplankton of these large lakes (Hecky & Kling, 1987). 2005 Blackwell Publishing Ltd
Phytopigments in Lake Tanganyika In Lake Tanganyika, for instance, the algal succession is characterised by a sharp contrast between the two main seasons (Hecky & Kling, 1987; Hecky, 1991). A chlorophytes-chroococcales assemblage is characteristic of the wet season (October to April), with high light and poor nutrient availability in the shallow epiliminion. In the dry season (May to September), when deep mixing occurs, low light and higher nutrient availability select for diatom dominance. Surface blooms of filamentous cyanobacteria may develop at the end of the dry season, when the water column re-stratifies. A similar seasonal succession was described by Talling (1987) for L. Victoria. However, diatoms and cyanobacteria are dominant in L. Victoria (Talling, 1987), while it is the green/blue-green assemblage that dominates in L. Tanganyika. The Tanganyika phytoplankton record has been completed by cruise samples that allowed addressing longitudinal variation (Hecky & Kling, 1987; Hecky, 1991) and, more recently, vertical distribution of different taxa, including picocyanobacteria (Vuorio et al., 2003). A recent publication on effects of global warming on the lake reported strong declines in phytoplankton biomass and changes in composition (Verburg, Hecky & Kling, 2003). However, comprehensive long-term data on the phytoplankton assemblage and its variation in time and space are still missing; the most complete study (Hecky & Kling, 1987) covered only 1 year at two sites, and only samples from one depth were examined by inverted microscopy, with a resolution too poor to detect the smallest autotrophs. Given the size and the complex hydrodynamics and ecology of large lakes, there is a clear need for techniques allowing processing of numerous samples and for surveys of the water column for long periods of time, which can provide data for addressing interannual variability of phytoplankton biomass and composition. This assessment of variability of phytoplankton in large lakes is a prerequisite for detecting significant long-term changes possibly brought about by climate change. So far, analysis of phytoplankton biomass and composition based on HPLC of phytoplankton pigments has not been used in East African great lakes. The advantages of the technique are well-known from its numerous applications in marine and estuarine systems (Millie, Paerl & Hurley, 1993) and, increasingly, in fresh waters. It has benefited from the 2005 Blackwell Publishing Ltd, Freshwater Biology, 50, 668–684
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development of advanced algorithms for calculating the contribution of algal classes, among which the CHEMTAX software (Mackey et al., 1996) has been widely used. Data on marker pigments : chlorophyll a ratios in marine and fresh waters have been accumulating (e.g. Descy et al., 2000; Schlu¨ter et al., 2000; Higgins & Mackey, 2000; Llewellyn & Gibb, 2000) and several experimental studies have addressed their variation according to light and nutrients, in different classes (Goericke & Montoya, 1998; Nicklisch & Woitke, 1999). Provided that technical difficulties such as pigment extraction and preservation in relatively remote tropical regions can be overcome, the technique is promising for the study of phytoplankton in African great lakes. Particularly, automated HPLC analysis of extracts enables comparatively quick analyses and processing of many samples, thereby providing better spatial and temporal resolution than classic microscope techniques in large and complex aquatic systems (Millie et al., 1993; Fietz & Nicklisch, 2004). An additional advantage demonstrated in several studies since the introduction of reverse-phase HPLC analysis for phytoplankton surveys (Mantoura & Llewellyn, 1983), is the detection of very small algae which can be overlooked by microscope examinations (Gieskes & Kraay, 1983). Detecting and correctly assessing biomass and production of these smallest autotrophs is a key to understanding food web processes in oligotrophic systems (Agawin, Duarte & Agusti, 2000). Undoubtedly, the pigment approach has become widely accepted as a technique of choice to look at phytoplankton dynamics at the class level, with a minimum of errors, provided that the pigment ratio variation is taken into account. This paper reports a phytoplankton pigment study conducted in Lake Tanganyika, addressing variations of phytoplankton biomass and composition over 2 years (2002–2003), with three main objectives: (i) tracking variations of the whole assemblage over the 0–100 m water column, in a first attempt to assess the extent of the changes over relatively short time scales (months, years) vs. those over longer periods of time; (ii) addressing longitudinal variation of phytoplankton and its dependence on seasonal factors; and (iii) observing the fate of carotenoids and chlorophyll derivatives in the water column, as indicators of the fate of primary production in this large tropical lake.
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Material and methods Study sites From February 2002 to January 2004, water column samples were taken fortnightly from two offshore stations of Lake Tanganyika (Fig. 1): Kigoma (Tanzania) in the north (0451.26¢S, 2935.54¢E) and Mpulungu (Zambia), in the south (0843.98¢S, 3102.43¢E). These two sampling sites were identical to those used in the FAO/FINNIDA LTR (Lake Tanganyika Research) project (Plisnier et al., 1999). In addition, three cruises were organised from Kigoma to Mpulungu, two in the dry season (10–17 July 2002; 7–13 July 2003) and one in the rainy season (30 January to 7 February 2004), with several sampling sites (Fig. 1). Limnological profiles using CTDs, transparency measurements (Secchi disk depth) and analyses of nutrients were carried out during regular sampling at
the two sites and at all sites during the cruises. Nutrient analyses were done using standard spectrophotometric techniques (A.P.H.A., 1992) or Macherey–Na¨gel analytical kits (Macherey–Na¨gel, Du¨ren, Germany); for inorganic N and P forms, absorbance of coloured samples was measured in 40 or 50 mm cells. Euphotic depth (depth at which light is 1% of subsurface light) was derived from Secchi depth (SD) by calculating the vertical light attenuation coefficient (k ¼ 1.57/SD). The conversion coefficient was obtained by calibration with measurement of PAR downward attenuation with LICOR quantum sensors. Depth of the mixed layer was estimated from the depth of the top of the thermocline, as shown by the temperature and oxygen vertical profiles obtained with the CTDs. Further details can be found in Descy & Gosselain (2004).
Water column sampling and pigment analysis
Fig. 1 Map of Lake Tanganyika, with location of the sampling sites of the regular survey (boxes) and of the research cruise (black dots). The research stations of TAFIRI (Tanzanian Fisheries Institute) at Kigoma and DOF (Department of Fisheries, Zambia) at Mpulungu are also indicated (in frames).
Water column samples were collected with Hydrobios (Kiel, Germany) (5 L) or Go-Flo (General Oceanics Inc., Miami, FL, U.S.A.) (up to 12 L) sampling bottles, every 20 m from the surface down to 100 m. Occasional additional sampling was done at 10 and 30 m, notably during the cruises. Samples for HPLC analysis were obtained from filtration of 3–4 L on Whatman (Maidstone, U.K.) GF/F or Macherey–Na¨gel GF5 filters, of 0.7 lm nominal pore size. The subsequent procedure for pigment extraction and analysis followed Pandolfini et al. (2000) and Descy et al. (2000). Extracts in 90% acetone were then stored in 2 mL amber vials in a freezer (at )25 C) for several months (under the regular sampling scheme) or for 2–3 weeks at most (for the cruise samples), and transported to Belgium on ice in cooler boxes. A total of more than 600 samples were analysed over the 2 years from the two stations. In the rainy season 2003 (February to April), pooled samples from the 0 to 30 m layer were filter-fractionated before collection of the particulate material on the 0.7 lm filters: two subsequent filtrations were carried out on Nytex plankton nets to retain the particles >28 lm and >10 lm, followed by a third filtration on a Millipore membrane of 2 lm pore size. The subsequent treatment was identical to that applied to the non-fractionated samples and allowed estimation of biomass and composition of the following size fractions: >28 lm, 10–28 lm, 2–10 lm and
