MARTINET, DESCLOUX, GUEDANT, and RIMET: Phytoplankton Functional Groups for Ecological Assessment in Young Sub-Tropical Reservoirs: Case Study of the Nam-Theun 2 Reservoir, Laos, South-East Asia

Phytoplankton Functional Groups for Ecological Assessment in Young Sub-Tropical Reservoirs: Case Study of the Nam-Theun 2 Reservoir, Laos, South-East Asia

Abstract

The early stages following the creation of reservoirs are typically physical and biological unstable periods due to the conversion from a lotic to a lentic ecosystem. The sub-tropical Nam Theun 2 Reservoir (Laos) was impounded in 2008. Several limnological parameters were monitored from March 2009 to December 2011 in order to understand the evolution of the phytoplankton community. A strong inter annual variability of hydrodynamic pattern was observed. Rainfall and hydraulic balance were the main physical factors driving the community structure. Periods of highest hydraulic stability led to a phytoplankton biomasses increase. The first assemblages were dominated by the S-C-strategists reaching high biomasses but low diversity. Over the three years, phytoplankton became more diverse due to a diversification of ecological niches, mostly explained by a greater water transparency and a more stable thermal stratification. The applicability of functional groups for biomonitoring in this young sub-tropical reservoir was investigated and compared to a classical taxonomical approach. The dominant functional groups (Lo, A, E, F, N and P) characterized the NT2 Reservoir as meso-oligotrophic with a tolerance to low nutrients supply. Our results support the hypothesis that a functional group approach is more informative than a species-based approach to assess trophic level and dissolved organic carbon concentrations in such reservoirs




INTRODUCTION

The conversion from a lotic to a lentic ecosystem through the creation of a reservoir affects aquatic community composition and specifically phytoplankton assemblages. As primary trophic resources, phytoplanktonic population kinetics describe an important part of energy transfer known to influence productivity and the whole food web (Prygiel and Haury, 2006). For this reason, investigations on this community are considered as basic tools to understand the ecology of aquatic ecosystems and assess the ecological status of a water body (Buzzi et al., 2007; Kaiblinger et al., 2009; Wolfram et al., 2009; Hu et al., 2013). In the recent decades large efforts have been devoted to gain knowledge in phytoplankton interactions with its surrounding environment, especially in temperate lakes (Schindler, 1978). However, it is obvious that existing data and studies on trophic structure are less numerous in tropical than in temperate ecosystems (Jeppesen et al., 1999). Studies on phytoplankton structures and dynamics are therefore fundamental in South Asia, where many reservoirs were constructed in the last 10 years and where the potential of their construction is still high.

Phytoplankton communities in lakes and reservoirs depend on several interactions among chemical, physical and biological factors (Lund, 1965). Reservoirs usually contain a wide array of nutrients which concentrations directly influence phytoplankton biomass and especially green algae (Happey-Wood, 1988). Light, nitrogen (N) and/or phosphorus (P) are often considered as limiting factors (Dillon and Rigler, 1974; Vollenweider and Kerekes, 1980; Coley et al., 1985; Tilzer, 1990). In tropical areas, phytoplankton growth is mostly regulated by the temperature and rainfalls at the seasonal scale (Talling, 2001; Schagerl and Oduor, 2008). Water column stability leading to stratification period also tends to be an important variable stimulating, for instance, green algae growth in the African Lake Tanganyika (Descy et al., 2010). Such factors are themselves functions of the climate and hydrological regimes, the size of the watershed, reservoir basin morphology, volume of outflow, and the food-web structure (Thornthon et al., 1990; Calijuri and Dos Santos, 2001). In some Brazilian reservoirs, it has been revealed that climate, hydrology and retention time were major forcing functions which had a strong effect on phytoplankton and in their succession of communities (Tundisi et al., 2008).

Initially, Grime (1979) stated that pooling the species sharing similar ecological characteristics into functional groups is more useful for ecological studies than using taxonomic groups. According to this approach, finding explanations on the coexistence of certain phytoplankters with certain water bodies coupled with environmental constraints became a challenge (Krienits et al., 1996; Anneville et al., 2002; Crossetti and Bicudo, 2005; Descy et al., 2010). More recently, Finlay and Esteban (2001) asked the following question: why do the species live where they do? Beyond that, several studies emphasize the concept of functional classification on their studies to describe phytoplankton patterns in various aquatic ecosystems (Reynolds et al., 2002; Mieleitner et al., 2008; Padisák et al., 2009; Kruk et al., 2010). Most studies on the applicability of phytoplankton functional groups have been conducted in the temperate climate and their use in the study of tropical reservoirs is even less common (Xiao et al., 2011; Hu et al., 2013), especially in South-East Asia.

Reservoir impoundment modifies key ecological factors by establishing a man-made ecosystem which could dramatically alter its physical, chemical and biological properties. Indeed, the large-scale reservoir constructions had sometimes shown adverse effects in the past, leading to temporary anoxic conditions, eutrophication (Richard et al., 1997; Sabater et al., 2008) and to the development of toxic algal blooms (Mastin et al., 2002). Understanding the major factors structuring phytoplankton communities is thus essential, particularly in young sub-tropical reservoirs and during the early stages following the impoundment. The present study aims at evaluating the phytoplankton community responses to environmental disturbances in a newly impounded sub-tropical reservoir in South-Asia: the Nam Theun 2 (NT2) Reservoir. It is expected that functional groups classification actually offers an interesting tool for i) the ecological assessment at the interannual scale; and ii) for understanding phytoplankton colonization of the reservoir. We also evaluated the benefit of using functional groups compared to a species approach in a young sub-tropical environment. Data from the phytoplankton monitoring program of the NT2 Reservoir carried out from March 2009 to December 2011 were used to address these objectives.

METHODS

Study area

The studied system is the NT2 hydroelectric Reservoir located on the Nakai Plateau (Khammouan Province) in Laos (Fig. 1a). The NT2 Reservoir (Fig. 1b) is defined as a shallow monomictic sub-tropical Reservoir (Chanudet et al., 2012). The catchment area covers a surface of about 489 km2 and the reservoir maximum depth is 38 m (average depth of 11 m) leading to a total volume of 3.9 km3 (EDFDTG, 2012). The reservoir was impounded between May 2008 and February 2009 (Fig. 2) and the power station was commissioned in March 2010. From the beginning of the hydroelectric production period, the reservoir levels vary between 529.30 and 538.06 m above sea level.

Local climate

The sub-tropical climate is characterized by a monsoon regime, with an average rainfall of 2640 mm per year; the temperature and precipitation patterns define three distinctive seasons (Boonsoong et al., 2008; Jung et al., 2008). The warm dry season occurs from March to May. The wet season runs from June to October when 80% of annual precipitation occur and lead to an important natural seasonal disturbance of the water body (Chanudet et al., 2012). The hottest month is June with an average surface water temperature of 29°C. The cool dry season runs from November to February when the water temperature is decreasing. January is the coldest month with an average surface water temperature of 19.8°C.

Sampling protocol and analyses

Physical, chemical and phytoplanktonic parameters were routinely measured on a monthly basis from March 2009 to the end of 2011 at the Dam site location (RES1 at 50 m from the Dam, Fig. 1b).

A multi-parameters probe (Quanta, Hydrolab) was used to measure physical and chemical variables (e.g., water temperature, dissolved oxygen and saturation, pH and conductivity) at the sampling site in the field. Variables were measured every 0.5 m within the five first metres of the uppermost and 1 m below to describe vertical profiles. In addition, precipitations and hydrological variables were monitored. The water level of the reservoir and the dam outflows were given by the probes deployed at the dam structure. The environmental flow is picked up from the water surface while flood are evacuated using flap gates and radial gates. In that case, the water is spilled from a layer of about 8m from the surface water. The water renewal time were calculated from the reservoir volume and the difference between the outflows and the inflows. Water samples for chemistry analyses, determination of the phytoplankton species and biomass were collected in the euphotic zone defined by Secchi disk depth at the sampling site. The sampling strategy follows an integrated method with 1 L of water collected with a Niskin bottle at 5 equidistant depths from the surface to the bottom of the euphotic layer (x 2.5 Secchi depth as recommended by Poikane, 2009). From the 5 mixed litres, 1 L was collected for Chlorophyll (a) analysis by spectrophotometry (APHA standards, 1995), 500 mL were collected and immediately preserved with a Lugol’s solution (Vollenweider, 1969) for phytoplankton investigations, and 250 mL were collected for chemistry analyses. Measurements were carried out according to American Standards for water quality (APHA, 1995). Total organic carbon (TOC) and dissolved organic carbon (DOC) were analyzed with IR Spectrophotometry after acidification and combustion. For the total suspended solids (TSS), gravimetry was used after filtration at 1.2 μm and drying 2 h at 103-105°C. Total nitrogen (TN) and total phosphorous (TP) were analyzed by spectrophotometry.

At the laboratory, phytoplankton identification and counting were carried out under inverted microscope (objective x40) with sedimentation chambers (Utermöhl, 1958) following the European standard (NF EN 15204). The transect method (diameter) was adopted. Phytoplankton biomass was calculated using cells biovolume and carbon content of each class assuming that the density of the organisms equals that of water (Wetzel and Likens, 2000). Identifications were based on specialized taxonomic literature (Starmach, 1972, 1974, 1983; Bourrelly, 1981, 1985, 1990; Hindàk, 1984, 1988, 1990). The functional group classification proposed by Reynolds et al. (2002) and Padisák et al. (2009) was used for this purpose.

Statistical methods

Diversity index

Using the formula from Shannon-Weaver, the diversity index (H) is calculated for species and functional groups (Shannon and Weaver, 1949).

Multi response permutation procedure

Multi response permutation procedures (MRPPs; Biondini et al., 1985) were computed with the PcOrd software (McCune and Mefford, 2006) to assess the structuring effect of nine variables on phytoplankton communities. These variables were expressed as classes as given in Tab. 1. This analysis calculates an A-statistic, which is a descriptor of within-group homogeneity. This statistic varies between -1 and 1: if the A-statistic approaches 1, the groups are completely different; if the A-statistic approaches 0, the heterogeneity within groups equals what would be expected by chance; if the A-statistic approaches -1 the groups are homogeneous. A P-value is associated to the A-statistic.

Indicator species analysis

Indicator taxa were identified for classes defined for the parameters listed above (seasons, years, pH, TP, TN, DOC, water level, Dam outflows) using the indicator species analysis of Dufrêne and Legendre (1997). This analysis indicates the taxa that are most associated with each pre-defined group. It yields an index calculated on the basis of the abundance and the fidelity of each taxa in each group. If a taxon has a high index in a group, it will be a good indicator of this group. Moreover, this index is tested by means of a Monte-Carlo test; the indices presenting a significant P value (<0.05) are shown for the corresponding taxa. This analysis was computed with the PcOrd software (McCune and Mefford, 2006).

RESULTS

Hydraulic patterns

Over 2009, the reservoir reached its maximum and stable level (538m asl) (Fig. 2). From March 2010, with the starting of the turbines and water intake, the reservoir level fluctuated within the year with the appearance of a drawdown area during the warm dry season followed by a fulfilled period during the wet season (June to October) (Fig. 2). Generally, during the wet season, behind strong rainfalls, water was spilled from the Dam site in order not to exceed reservoir maximum level of 538 m asl. Thereby, the highest renewal of water was reached in June 2011 with 74% of the water renewed during the month whereas the lowest renewal of water was early 2010 with less than 4% of water renewed during February (Fig. 3a).

Physical and chemical results

Generally, the highest total phosphorous and total nitrogen concentrations were measured just after impoundment in 2009. Afterwards (from 2010), only total nitrogen was detectable. After the impoundment period, the highest concentrations were observed in the beginning of the warm-dry season to the end of the wet season, with maximal total nitrogen concentrations occurring for such period (360 μg L−1 - 930 μg L−1) (Tab. 2). Even pH was slightly acid over the study, an increase of pH was noticed during the stratification period.

Phytoplankton results

Overview of the phytoplankton composition

A total of 177 taxa were identified in the 34 samples collected over this study. Two classes were fairly involved in biomass dynamic: Chlorophyta and Dinoflagellates. A variety of chlorophyte taxa (including filamentous and desmids) represented more than 80% of the relative abundances – e.g., Chlorella vulgaris Beyerinck (Beijerinck), Monoraphidium spp. Komárková-Legnerová, Ankistrodesmus spp. Corda, Tetraedron caudatum (Corda) Hansgrig, Tetrastrum komarekii Hindák, Oocystisparva West & G.S. West and Sphaerocystis planctonica (Korshikov) Bourrelly. They were associated with some Dinoflagellates which comprised up to 94% of total biomasses (mainly species belonging to Peridinium spp. Ehrenberg and Gymnodynium spp. Stein). Other classes had much lower biomass commonly reaching 10% of total biomasses: Chrysophyceae (Dinobryon genus Ehrenberg with some Mallomonas spp. Perty and Kephyrion spp. Pascher), Cryptophyceae (Cryptomonas spp. Ehrenberg and Rhodomonas spp. Karsten), Cyanophyceae (Aphanocapsa spp. Nägeli, Limnothrix redekei Meffert and Merismopedia tenuissima Lemmermann) and Diatoms (Cyclotella sp. Kützing, Eunotia sp. Ehrenberg and Rhizosolenia sp. Brightwell).

Dynamics of species and functional groups diversity

Species and functional groups diversities tended to increase over the study period, despite seasonal fluctuations (Fig. 4). Shannon index (H) for species fluctuated from 0.27 in March 2009 up to values reaching approximately 3 in December 2011 (Fig. 4). Similarly, Shannon index for functional groups fluctuated from 0.23 in March 2009 to 1.9 in December 2011 (Fig. 4). Both species and functional group diversity were lower during the wet season, whereas the highest diversity was observed during the warm dry season.

Phytoplankton biomass dynamic

In March 2009, biomasses reached their highest value over the monitoring period (Fig. 3b). The biomass was mainly composed of microphytoplankton with a bloom of Dinoflagellates (Peridinium gutwinskii Woloszyńska and Ceratium hirundinella Bergh). Other biomass peaks of lesser magnitude were observed, ranging between 4x103 and 2.5x103 pg L−1 and mostly occurred during transition periods: i) at the end of the wet season, peaks were detected in November 2009 with some Peridinium spp. and in September 2011 with Chlorophyta-Dinoflagellates assemblages. By the end of the warm season and the beginning of the wet season, like in August 2010, high biomasses were maintained by some Dinoflagellates; ii) between warm and wet seasons, in May and June 2011, the high biomass was mainly composed by some small sized taxa - e.g., Crucigeniella spp. Lemmermann, Dictyosphaerium sphagnale Hindák, Oocystis parva, Tetrastrum komarekii and Tetraedron caudatum. There was also a positive correlation between phytoplankton biomass and surface water temperature (Spearman r=0.36, P<0.05).

The lowest biomasses (<1x103 pg L−1) were typically recorded at the peak of the wet season (between June and August 2009) and during the cool dry period (between January and February in 2010 and 2011).

Functional groups dynamic

Phytoplankton communities from NT2 Reservoir were composed by 22 functional groups. The main groups and their different genera are represented in the Tab. 3. The most abundant are Lo, F, A and P; they represented 57%, 10.5%, 4.5% and 4% respectively of the total biomass recorded during the study. The dynamics of the main functional groups are illustrated in Fig. 5 a-c. The functional groups Lo, Y and W2 were dominant at the beginning of the study and steadily decreased throughout the monitoring period. In 2009, the group Lo was strongly dominant contributing up to 82% of total biomass (Fig. 5a). Since April 2009, co-occurrence of two new groups appeared. It concerned Y significantly represented by Cryptomonas reflexa Skuja and W2 group (Trachelomonas spp. Ehrenberg). Between June and July, Y co-occurred with F gathering more than 62% of the total biomass. In October and November 2009, the Dinoflagellates, belonging to group Lo, obviously sustained the biomasses. In 2011, the group Lo declined to 8.4% of total biomass. The association (X1-J) co-dominated the assemblages with the groups (E-F) from the beginning of the 2010 cool dry season (Fig. 5b). They sustained 85% of total biomass in February 2010. During stratification period, the (E-F) assemblages persisted whereas (X1-J) declined. At the end of the wet season, in October, the group A reached 27% of total biomass. We recorded the following sequence: (A-X1-J) à (F-N-P) (Fig. 5c). The associations (A-Lo-E-F-X1-J) dominated the biomasses by the end of 2010.

Although monthly biomasses were generally lower than the previous years, 2011 is marked by the occurrence of new associations groups. In early March, green algae growth was dominated by (E-F-J) assemblages alike in 2010. In June, at the top of stratification period, this association was followed by the group G for the first time. It supported 50% of the total biomass. Generally, during stratification, biomass was sustained by (N-P-F). During heaviest rains, especially in July and in August, the biomasses of all the groups significantly declined. By the end of wet season in October, only (E-F) maintained their growth in association with a relative growth of group G and Lo. In March 2011, at the beginning of the warm dry season, phytoplankton was mainly composed of A-Lo-E and F assemblages.

Structuring effect of environmental parameters on functional group and species abundances

Multi response permutation procedure

Results of MRPP carried out on phytoplankton communities expressed with functional groups and species abundances are shown on Fig. 6. The results show similar trends on functional groups and species assemblage’s structure. For both, the year presents the strongest A-statistic scores (P<0.05). The highest score is obtained with functional groups. Dam outflows are also a significant determinant driver structuring the assemblages (P<0.05). Water level and Dam outflows have more important structuring impact (P<0.05) on species than on functional groups (P>0.05). Functional groups are significantly affected by pH (P<0.05), whereas species are much less impacted by this variable (P>0.05). On the other hand, species are significantly impacted by seasons (P<0.05), whereas functional group are less impacted (P>0.05). DOC also explains phytoplankton communities variability (expressed with functional groups or species). A very significant and positive correlation between DOC concentrations and phytoplankton biomasses is observed (Spearman r=0.49, P<0.0035). Total phosphorous concentrations have no effect on functional groups and species structure. However, total nitrogen concentrations are significantly correlated with functional groups and species (P<0.05).

Indicator species analysis

Indicator value (IndVal) indices and calculations for phytoplankton species and for functional groups were computed for five parameters showing significant results with the MRPP test. The indicator species and functional groups were pooled in four categories according to their inter-annual dynamics (Tab. 4). They were categorized in accordance with the assemblage they belong to such as pioneer, transitional, colonizing and permanent. The functional groups and species presenting a decline of their biomass along the years belong to the pioneer assemblages; those showing a transitory effect were gathered into the transitional; those presenting an increase of their biomass along the year were gathered into the colonizing and those having a stable abundance were considered as permanent”.

The indicator taxa belonging to the pioneer assemblages (Peridinium willei Lo and Cryptomonas reflexa Y) significantly indicated medium to high TN at the beginning to the study. Furthermore, they were good indicators of high pH. All of these species and functional groups are mixotrophic. The indicative species and functional groups of this pioneer assemblage were characterized by mixotrophic and motile traits (e.g., Cryptomonas reflexa, Peridinium sp.). In the transitional groups, X1 and Tetraedron caudatum, were indicators of the year 2010. Group J had an affinity for high DOC during stratification period. The indicators taxa of the colonizing group, were functional groups G, N and also Staurastrum cf. punctulatum which are all heterotrophic taxa. Group N was indicator of very high TN, high pH values and DOC. Some colonial Chlorophyta which belong to group F are an indicator of environmental situations. As shown in Tab. 4, Botryococcus braunii Kützing is an indicator of high pH value, Gloeocystis sp. Nägeli indicates low DOC and Elakatothrix gelatinosa Wille indicates strong water decrease.

We can observe that some species are only indicators of hydrological parameters, e.g., E. gelatinosa, Staurastrum tetracerum Ralfs ex Ralfs is an indicator for low outflows and Staurastrum cf. punctulatum Brébisson has shown a very significant indicative value for the increase of water level.

DISCUSSION

Interannual variability of phytoplankton communities: importance of colonization processes

The successions of the phytoplankton assemblages at NT2 Dam site, reflected a strong interannual variability and these annual changes in phytoplankton community were greater than those detected at the seasonal scale.

Diversity (Shannon index) confirms the high inter-annual variability: the assemblages present at the beginning of the impoundment were less diverse, and then progressively increased in diversity. The nascent communities of the NT2 Reservoir appeared to be well adapted to stressful conditions (Reynolds, 1988) of this newly impounded reservoir, which include a decrease of light availability (resulting from high suspended particle concentrations following impoundment). These stressful conditions limited the development of photoautotroph organisms especially green algae. The Lo functional group (Padisák et al., 2009) was dominant at the beginning of the study; it is considered as an S-strategy species (Stress-tolerant). During its impoundment, the NT2 Reservoir received a high amount of suspended particles. In early 2009, even if high water turbidity could limit plankton growth (Cherifi and Loudiki, 2002), the highest phytoplankton biomass was recorded at this time and was related to high organic matter (TSS concentrations and DOC). The Y functional group also had high biomass especially between June and July 2009, when there was a high percentage of water renewal. It is a fast growing, C-strategist algae (colonist, invasive; Reynolds 1980, 1984). These observations are in accordance with Brazilian studies where the functional group Y was known to prefer mixing period and a high turbidity because they had greater adaptability to water column mixing and low transparency conditions (Nabout et al., 2006). As suggested by Olrik (1994), the Lo-Y assemblage has a high probability of early colonization of new planktonic habitats. However the strong outflow and water renewal during the wet season in 2009 represent a cumulation of unfavorable conditions leading to the decline of group Lo, because this group is sensitive to prolonged or deep mixing (Reynolds et al., 2002; Huszar et al., 2003). Consequently, the efficiency of colonization of a young reservoir depends not only on environmental variables but also on the adaptive strategies of different types of algae, which at the end, constitute the ecological response of phytoplankton to environmental variability.

From 2010, the setting of an annual hydrological cycle involved a greater hydraulic stability during the warm dry season (low discharge and late rainfalls), and the increase of light availability. Such conditions favored the NT2 phytoplankton growth (Reynolds, 1998). The phytoplankton community became increasingly complex with new functional and taxonomic groups appearing along the study period. Cardinale (2011) showed that communities with higher biodiversity take advantage of the niche opportunities in an environment. The increase of functional and taxonomic diversity in NT2 Reservoir should therefore be a result of an increase in ecological niches complexity. Hydraulic stability is the major environmental descriptor which explains this niche diversification: the longer period of stratification measured since 2010 and the increase in water transparency offered conditions for a greater number of ecological niches.

Bottom-up factors structuring phytoplankton community in this newly impounded sub-tropical reservoir

Results demonstrate that hydrological balance is a relevant driver in NT2 phytoplankton community which explains its interannual dynamic. During the wet season in 2009 and in 2011, rainfalls and Dam spills might be the cause of turbulences disrupting water column stability. Such phenomenon has involved some changes in the phytoplankton community with a decrease in its biomasses. As shown by Harris and Baxter (1996), in reservoirs with seasonal thermal stratification patterns, inter annual changes in rainfalls could modulate the thermal structure of water column and override regular hydrological events. Subsequently, the hydraulic balance could create turbulences within the water column yielding irregular patterns of phytoplankton variability (Naselli Flores and Barone, 1998). Conversely, the thermal stratification period offers greater hydraulic stability with higher biomass and diversity. A previous study in Liuxihe Reservoir (China) has shown similar trends for tropical systems: two peaks of phytoplankton biomass occurred prior to and at the end of wet season (stratification periods; Xiao et al., 2011).

As seen in other reservoirs, hydrologic regimes may affect phytoplankton biomass and species composition by influencing nutrient dynamics in the water column (Costa et al., 2009). Several authors showed that species have particular preference for nutrients (e.g., Brettum, 1989; Wolfram and Dokulil, 2007). Although the nutrients concentrations are often mentioned as the key elements explaining phytoplankton variability, in the NT2 Reservoir phosphorous played no role in structuring the NT2 phytoplankton community compared to the colonization process. The W2 functional group was indicator of high nutrient concentrations: it is commonly found in mesotrophic ponds and shallow lakes (Reynolds et al., 2002).

How functional groups respond to bottom-up factors in NT2 Reservoir?

Reynolds’ functional classification of freshwater phytoplankton (Reynolds et al., 2002) is probably the most frequently used non-taxonomic approach to group phytoplankton taxa. It has been successfully applied recently to investigate phytoplankton assemblages in South China reservoirs (Xiao et al., 2011; Hu and Xiao, 2012). Nevertheless, as demonstrated by Hu et al., (2013) functional groups can show a high degree of overlapping, but since coda are associated with very detailed environmental templates, this method was helpful in explaining phytoplankton variability in relation to environmental factors. The hydrological parameters (water renewal and outflow) were able to explain this variability. The changes in algal composition and biomass also occurred as a consequence of changes in the environmental conditions (temperature, light and nutrient concentrations) induced by the flush of surface water (Rigosi and Rueda, 2012). In our study, some functional groups were related to different structuring factors (hydrodynamism, DOC, nutrients and pH) and therefore can be of interest for biomonitoring purposes.

According to IndVal analyses, the small green algae were indicator of water level increase. On the other hand, Elakatothrix gelatinosa, a representative species of group F, indicated water level decrease over the stratification period. Colonial Chlorophytes from F group, including Botryococcus, are usually known to be tolerant to stratification, high insolation and low nitrogen and phosphorus concentrations (Goldman and Jassby, 2001). Although DOC varies greatly at the interannual scale, DOC variations were significantly correlated to phytoplankton biomass. High biomass of phytoplankton could coincide with relatively high DOC concentrations because algae can produce DOC (e.g., mucilage) and also because of cell lysis delivering DOC in water. This phenomenon was observed by Thurman (1985) who observed increase of DOC concomitant with high photosynthetic activities. In our study we can assume a direct link between DOC and phytoplankton. However, we cannot conclude if high DOC concentrations provoke or not an increase of the NT2 phytoplanktonic biomass. However, the DOC played a role in structuring the assemblages. In the NT2 Reservoir, during the stratification period a phytoplanktonic succession occurred following a gradient of DOC concentrations from 0 to 4 mg L−1:

limno-2014-3-958-e001.jpg

Primary production is one of the major metabolic pathways by which organic matter is produced and destroyed (Cole et al., 2000). Moreover, because DOC can provide an important source of energy for microorganisms (Tranvik, 1992), DOC can be used as a marker of trophic level resources kinetic in aquatic ecosystem (Janson, 1998; Jones, 1998; Lampert and Sommer, 2007). This study shows that DOC can also be used as a proxy of phytoplankton biomass. Group A is usually considered as good indicators of trophic level thanks to their tolerance for nutrient depletion, especially phosphorus deficiency (Reynolds et al., 2002). This group, represented by Cyclotella and Rhizosolenia, is frequently associated with high light intensity during stratification (Sarmento et al., 2006; Xiao et al., 2011). The longest stratification period and lower water level may account for the group A in the NT2 Reservoir. However, the IndVal analyses showed that the warm season favoured the group G (Eudorina elegans) which belongs to a nutrient-rich habitat in stable water columns found in storage reservoir (Reynolds et al., 2002). According to the MRPP results, pH is determinant important in explaining community structure, especially functional groups (as opposed to species composition). The groups Lo and N occurred preferentially in pH values above 7 from the end of warm dry season and, with moderate disturbance, their occurrence is also reported during the wet season when water level increases. Highest pH values were observed likely due to photosynthetic activity of these groups. For instance, at the beginning of the investigations highest biomass referred to a high photosynthetic activity from the group Lo. Group N also indicated high TN, pH and DOC; this group is usually present in shallow lakes as well as in the epilimnia of stratified lakes (Padisák et al., 2009). Nevertheless, only one species is indicating particular pH values: Botryococcus braunii which has a significant affinity for high pH values. During such period, highest pH values and lowest transparency are indicative of a higher trophic status, even though a relative low nitrate and phosphate concentrations have been measured (Silva et al., 2005).

CONCLUSIONS

The NT2 Reservoir displayed a good example of phytoplanktonic successions during the colonization of a recently created habitat. The hydraulic balance was identified as the principal factors that controlled algae development and composition. Intense disturbances (rainfalls, strong discharge and high percentage of water renewed) reduced phytoplankton biomasses and diversity. The impoundment of the reservoir contributed to an increase of water turbidity favouring the dominance of the S-C- strategists (Lo-Y) with low diversity during the first months of this monitoring. The diversification of the phytoplankton community after impoundment is related to a greater hydraulic stability and a water transparency increase.

Our results also demonstrate that the functional groups A, F, X2, J and N are indicator of particular trophic level assessment and DOC concentrations. The NT2 Reservoir can be characterized as a meso-oligotrophic water body where phytoplankton community is principally controlled by the interannual variations of environmental variables and enables describing the following succession: X1-J- (Lo); Lo-(G); P-N; A-X1, which correspond to a transition from mesotrophic to meso-oligotrophic taxa. Our study demonstrates the applicability of functional groups for biomonitoring trophic level. They even better contributes to understand the interannual dynamic than taxonomy level. In the future, the understanding of the relationship between DOC and phyto biomass occurring in the NT2 Reservoir should be further investigated.

ACKNOWLEDGMENTS

This research has been conducted at the Aquatic Environment Laboratory of Nam Theun 2 Power Company in Laos whose Shareholders are Électricité de France, Lao Holding State Enterprise and Electricity Generating Public Company Limited of Thailand.

The authors would like to thank the Nam Theun 2 Power Company (NTPC) for providing the logistic support on site related to field activities. We are also grateful to the team of the Aquatic Environment Laboratory (AEL) for chemistry analyses and their help given during field trips. Finally, we are thankful to Mr. Paul Dumbrell and Ms Léah Bêche, who reviewed and improved this version of the manuscript as a native English-speaking.

REFERENCES

1 

AFNOR, 2006. Water quality. Guidance standard on the enumeration of phytoplankton using inverted microscopy (Utermöhl technique). EN 15204. Afnor: 39 pp.

2 

O Anneville, S Souissi, F Ibanez, V Ginot, JC Druart, N Angeli, 2002. Temporal mapping of phytoplankton assemblages in Lake Geneva: annual and interannual changes in their patterns of succession. Limnol. Oceanogr. 47:1355-1366.

3 

APHA, 1995. Standard methods for examination of water and wastewater, 19th ed. American Public Health Association, Washington DC, USA.

4 

ME Biondini, CD Bonham, EF Redente, 1985. Secondary successional patterns in a sage brush (Artemisia tridentata) community as they relate to soil disturbance and soil biological activity. Vegetation 60:25-36.

5 

B Boonsoong, N Sangpradub, MT Barbour, W Simachaya, 2008. An implementation plan for using biological indicators to improve assessment of water quality in Thailand. Environ. Monit. Assess. 165:205-215.

6 

P Bourrelly, 1981. [Les algues d’eau douce: les algues jaunes et brunes].[Book in French]. . Boubée et Cie: 438 pp.

7 

P Bourrelly, 1985. [Les algues d’eau douce: les algues bleues et rouges].[Book in French]. Boubée et Cie: 512 pp.

8 

P Bourrelly, 1990. [Les algues d’eau douce: les algues vertes].[Book in French]. Boubée et Cie: 572 pp.

9 

P Brettum, 1989. [Algen als Indikatoren für die Gewässerqualität in norwegischen Binnenseen].[Book in German]. NIVA: 102 pp.

10 

F Buzzi, A Dalmiglio, L Garibaldi, E Legnani, A Marchetto, G Morabito, N Salmaso, G Tartari, B Thaler, 2007. [Indici fitoplanctonici per la valutazione della qualità ecologica dei laghi della regione alpina].[Document in Italian]. Ministero dell’Ambiente e della Tutela del Territorio e del Mare.

11 

MC Calijuri, ACA Dos Santos, 2001. Temporal variations in phytoplankton primary production in a tropical reservoir (Barra Bonita, SP - Brazil). Hydrobiologia 445:11-26.

12 

BJ Cardinale, 2011. Biodiversity improves water quality through niche partitioning. Nature 472:86-89.

13 

V Chanudet, V Fabre, T Van Der Kaaij, 2012. Application of a three-dimensional hydrodynamic model to the Nam Theun 2 Reservoir (Lao PDR). J. Great Lakes Res. 38:260-269.

14 

O Cherifi, M Loudiki, 2002. [Variations de la structure trophique du lac-réservoir oligotrophe Bin El Ouidane (Maroc)].[Article in French]. Rev. Sci. Eau 15:193-208.

15 

JJ Cole, ML Pace, SR Carpenter, JF Kitchell, 2000. Persistence of net heterotrophy in lakes during nutrient addition and food web manipulations. Limnol. Oceanogr. 45:1718-1730.

16 

L Costa, VLM Huszar, A Ovalle, 2009. Phytoplankton functional groups in a tropical estuary: hydrological control and nutrient limitation. Estuar. Coasts 32:508-21.

17 

PD Coley, JP Bryant, FS Chapin, 1985. Resource availability and plant antiherbivore defense. Science 230:895-899.

18 

HC Cowles, 1899. Ecological relation of the vegetation on sand dunes of Lake Michigan. Bot. Gaz. 27:95-117.

19 

LO Crossetti, CEM Bicudo, 2005. Structural and functional phytoplankton responses to nutrient impoverishment in mesocosms placed in a shallow eutrophic reservoir (Garças Pond), São Paulo, Brazil. Hydrobiologia 541:71-85.

20 

JP Descy, AL Tarbe, S Stenuite, S Pirlot, J Stimart, J Vanderheyden, B Leporcq, MP Stoyneva, I Kimirei, D Sinyinza, PD Plisnier, 2010. Drivers of phytoplankton diversity in Lake Tanganyika. Hydrobiologia 653:29-44.

21 

PJ Dillon, FH Rigler, 1974. The phosphorus-chlorophyll relationships in lakes. Limnol. Oceanogr. 19:767-773.

22 

M Dufrêne, P Legendre, 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol. Monogr. 67:345-366.

23 

EDF-DTG, 2012. Report: Nakai Reservoir on the Nam Theun River, capacity curve calculation, 2012 data. Grenoble: 9 pp.

24 

BJ Finlay, GF Esteban, 2001. Exploring Leeuwenhoek’s legacy: the abundance and diversity of protozoa. Int. Microbiol. 4:125-133.

25 

JP Grime, 1979. Plant strategies and vegetation processes. 4. J. Wiley & Sons, New York: 254 pp.

26 

CR Goldman, AD Jassby, 2001. Primary productivity, phytoplankton and nutrient status in Lake Baikal, p. 111-125. In: M. Munawar, R.E. Hecky (eds.), Exploring the great lakes of the world: food-web, health and integrity. Backhuys Publishers.

27 

VM Happey-Wood, 1988. Ecology of freshwater planktonic green algae, p. 175-226. In: C.D. Sandgreen (ed.), Growth and reproductive strategies of freshwater phytoplankton. Cambridge University Press.

28 

GP Harris, G Baxter, 1996. Interannual variability in phytoplankton biomass and species composition in a subtropical reservoir. Freshwater Biol. 35:545-560.

29 

F Hindák, 1984. Studies on chlorococcal algae (Chlorophyceae) III. Biologicke Práce: 320 pp.

30 

F Hindák, 1988. Studies on chlorococcal algae (Chlorophyceae) IV. Biologicke Práce: 264 pp.

31 

F Hindák, 1990. Studies on chlorococcal algae (Chlorophyceae) V. Biologicke Práce: 226 pp.

32 

R Hu, LJ Xiao, 2012. Functional classification of phytoplankton assemblages in reservoir of Guangdong Province, South China. In: B-P. Han and Z. Lui (eds.), Tropical and Subtropical reservoir limnology in China. Monogr. Biol. 91:59-70.

33 

R Hu, B Han, L Naselli-Flores, 2013. Comparing biological classifications of freshwater phytoplankton: a case study from South China. Hydrobiologia 701:219-233.

34 

V Huszar, C Kruk, N Caraco, 2003. Steady-state assemblages of phytoplankton in four temperate lakes (NE USA). Hydrobiologia 502:97-109.

35 

M Janson, 1998. Nutrient limitation and Bacteria - Phytoplancton interactions in humic lakes. In: D.O. Hessen and L.J. Tranvik (eds.), Aquatic humic substances. Ecol. Stud. 133:177-195.

36 

E Jeppesen, M SØndergaard, N Mazzeo, M Meerhoff, CC Branco, V Huszar, F Scasso, 1999. Lake restoration and biomanipulation in temperate lakes: relevance for subtropical and tropical lakes, p. 341-359. In: M.V. Reddy (ed.), Tropical Eutrophic lakes: their restoration and management. CRC Press.

37 

RI Jones, 1998. Phytoplankton, primary production and nutrient cycling. In: D.O. Hessen, L.J. Tranvik (eds.), Aquatic humic substances. Ecol. Stud. 133:145-175.

38 

SW Jung, VV Nguyen, QH Nguyen, YJ Bae, 2008. Aquatic insect faunas and communities of a mountain stream in Sapa Highland, northern Vietnam. Limnology 9:219-229.

39 

C Kaiblinger, O Anneville, R Tadonleke, F Rimet, JC Druart, J Guillard, MT Dokulil, 2009. Central European water quality indices applied to long-term data from peri-alpine lakes: test and possible improvements. Hydrobiologia 633:67-74.

40 

L Krienits, P Kasprazak, R Koschel, 1996. Long-term study on the influence of eutrophication, restoration and biomanipulation on the structure and development of phytoplankton communities in Feldberger Haussee (Baltic Lake District, Germany). Hydrobiologia 330:89-110.

41 

C Kruk, VLM Huszar, ETH Peeters, S Bonilla, L Costa, M Lürling, CS Reynolds, M Scheffer, 2010. A morphological classification capturing functional variation in phytoplankton. Freshwater Biol. 55:614-627.

42 

W Lampert, U Sommer, 2007. Limnoecology: the ecology of lakes and streams, 2. Oxford University Press: 324 pp.

43 

JWG Lund, 1965. The ecology of the freshwater phytoplankton. Biol. Rev. 40:231-293.

44 

BJ Mastin, JH Rodgers Jr, TL Deardorff, 2002. Risk evaluation of cyanobacteria-dominated algal blooms in a North Louisiana reservoir. J. Aquat. Ecosyst. Stress Recov. 9:103-114.

45 

B McCune, J Mefford, 2006. PC-ORD. Multivariate Analysis of Ecological Data, ver. 5.18. MjM Software, Gleneden Beach.

46 

J Mieleitner, M Borsuk, HR Burgi, P Reichert, 2008. Identifying functional groups of phytoplankton using data from three lakes of different trophic state. Aquat. Sci. 70:30-46.

47 

JC Nabout, IS Nogueira, LG Oliveira, 2006. Phytoplankton community of floodplain lakes of the Araguaia River, Brazil, in the rainy and dry seasons. J. Plankton Res. 28:181-193.

48 

L Naselli Flores, R Barone, 1998. Phytoplankton dynamics in two reservoirs with different trophic state (Lake Rosamarina and Lake Arancio, Sicily, Italy). Hydrobiologia 369-370:163-178.

49 

K Olrik, 1994. Phytoplankton ecology: determining factors for the distribution of phytoplankton in freshwater and the sea. Danish Ministry of Environment: 183 pp.

50 

J Padisák, LO Crossetti, L Naselli-Flores, 2009. Use and misuse in the application of the phytoplankton functional classification: a critical review with updates. Hydrobiologia 621:1-19.

51 

S Poikane, 2009. Water Framework Directive intercalibration technical report. Part 2: Lakes. EUR 28838 EN/2, Office for Official Publications of the European Communities, Luxembourg.

52 

J Prygiel, J Haury, 2006. Monitoring methods based on algae and macrophytes, p. 155-170. In: G. Ziglio, M. Siligardi, G. Flaim G (eds.), Biological monitoring of rivers: applications and perspectives. J. Wiley & Sons.

53 

CS Reynolds, 1980. Phytoplankton assemblages and their periodicity in stratifying lake systems. Holartic Ecol. 3:141-159.

54 

CS Reynolds, 1984. Phytoplankton periodicity: the interactions of form, function and environmental variability. Freshwater Biol. 14:11-142.

55 

CS Reynolds, 1988. Functional morphology and the adaptative strategies of freshwater phytoplankton, p. 388-433. In: C.D. Sandgren (ed.), Growth and reproductive strategies of freshwater phytoplankton. Cambridge University Press.

56 

CS Reynolds, 1998. What factors influence the species composition of phytoplankton in lakes of different trophic status. Hydrobiologia 369-370:11-26.

57 

CS Reynolds, V Huszar, C Kruk, L Naselli-Flores, S Melo, 2002. Towards a functional classification of the freshwater phytoplankton. J. Plankton Res. 24:417-428.

58 

S Richard, A Arnoux, P Cerdan, 1997. [Evolution de la qualité physico-chimique des eaux de la retenue et du tronçon aval depuis le début de la mise en eau du barrage de Petit- Saut].[Article in French]. Hydroecol. Appl. 1-2:57-83.

59 

A Rigosi, FJ Rueda, 2012. Hydraulic control of short-term successional changes in the phytoplankton assemblage in stratified reservoirs. Ecol. Eng. 44:216-226.

60 

S Sabater, J Artigas, C Durân, M Pardos, A.M Romaní, E Tornés, 2008. Longitudinal development of chlorophyll and phytoplankton assemblages in a regulated large river (the Ebro River). Sci. Total Environ. 404:196-206.

61 

H Sarmento, M Isumbisho, JP Descy, 2006. Phytoplankton ecology of Lake Kivu (Eastern Africa). J. Plankton Res. 28:815-829.

62 

M Schagerl, SO Oduor, 2008. Phytoplankton community relationship to environmental variables in the three Kenyan Rift Valley saline-alkaline lakes. Mar. Freshwater Res. 59:125-136.

63 

DW Schindler, 1978. Factors regulating phytoplankton production and standing crop in the world’s freshwaters. Limnol. Oceanogr. 23:478-486.

64 

CA Silva, S Train, LC Rodrigues, 2005. Phytoplankton assemblages in a Brazilian subtropical cascading reservoir system. Hydrobiologia 537:99-109.

65 

CE Shannon, W Weaver, 1949. The mathematical theory of communication. University of Illinois Press: 144 pp.

66 

K Starmach, 1972. [Chlorophyta III]. In: K. Starmach (ed.) [Flora Słodkowodna Polski]. [Book in Polish]. Polska Akademia Nauk, Instytut botaniki.

67 

K Starmach, 1974. [Cryptophycea Dinophycea Raphidophycea]. In: K. Starmach (ed.) [Flora Słodkowodna Polski]. [Book in Polish]. Polska Akademia Nauk, Instytut botaniki.

68 

K Starmach, 1983. [Euglenophyta]. In: K. Starmach (ed.) [Flora Słodkowodna Polski]. [Book in Polish]. Polska Akademia Nauk, Instytut botaniki.

69 

JF Talling, 2001. Environmental controls on the functioning of shallow tropical lakes. Hydrobiologia 458:1-8.

70 

KW Thornthon, BL Kimmel, FE Payne, 1990. Reservoir limnology: ecological perspectives. Wiley: 246 pp.

71 

EM Thurman, 1985. Academic organic geochemistry of natural waters. Martinus Nijhoff/Dr.W. Junk: 68 pp.

72 

MM Tilzer, 1990. Specific properties of large lakes, p 39-43. In: M.M. Tilzer, C. Serruya (eds.), Large lakes: ecological structure and function. Springer.

73 

LJ Tranvik, 1992. Allochthonous dissolved organic matter as an energy source for pelagic bacteria and the concept of the microbial loop. Hydrobiologia 229:107-114.

74 

JG Tundisi, T Matsumura-Tundisi, DS Abe, 2008. The ecological dynamics of Barra Bonita (Tietê River, SP, Brazil) reservoir: implications for its biodiversity. Braz. J. Biol. 68:1079-1098.

75 

H Utermöhl, 1958. [Zur Vervolkomnung der quantitativen Phytoplankton: Methodik].[Article in German]. Int. Ver. Theor. Angew. 9:1-38.

76 

RA Vollenweider, 1969. A manual on methods for measuring primary production in aquatic environments, 12. Blackwell Scientific: 213 pp.

77 

RA Vollenweider, JJ Kerekes, 1980. Background and summary results of the OECD cooperative programme on eutrophication. OECD Publ.: 290 pp

78 

RG Wetzel, GE Likens, 2000. Limnological analyses, 3. Springer: 429 pp.

79 

G Wolfram, MT Dokulil, 2007. [Leitfaden zur Erhebung der biologischen Qualitätselemente. Teil B2, Phytoplankton]. [Book in German]. Lebensministerium Austria: 50 pp.

80 

G Wolfram, C Argillier, J De Bortoli, F Buzzi, A Dalmiglio, MT Dokulil, E Hoehn, A Marchetto, PJ Martinez, G Morabito, M Reichmann, S Remec-Rekar, U Riedmuller, C Rioury, J Schaumburg, L Schulz, G Urbanic, 2009. Reference conditions and WFD compliant class boundaries for phytoplankton biomass and chlorophyll-a in Alpine lakes. Hydrobiologia 633:45-58.

81 

LJ Xiao, T Wang, R Hu, BP Han, S Wang, X Qian, J Padisák, 2011. Succession of phytoplankton functional groups regulated by monsoonal hydrology in a large canyon-shaped reservoir. Water Res. 45:5099-5109.

Fig. 1.

a) Map of South East Asia with the location of the Nam Theun 2 Reservoir in Laos. b) Map of the NT2 Reservoir and of the sampling site RES1 (Latitude 17°59’51.01’’N Longitude 104°57’9.96’’E).

limno-2014-3-958-g001.jpg
Fig. 2.

Graph of hydrological data illustrating the reservoir water level and the outflow from the dam. On the left axis, solid black line corresponds to the reservoir level (m above sea level). On the right axis, dash grey line corresponds to the outflow from the dam site (m3 s−1).

limno-2014-3-958-g002.jpg
Fig. 3.

a) Hydrological characteristics of the NT2 Reservoir following the percentage of monthly water renewed (black square) with rainfall (grey bar) and b) phytoplankton biomass evolution (black dot) from March 2009 to December 2011. CD, cool dry season; WD, warm dry season; W, wet season.

limno-2014-3-958-g003.jpg
Fig. 4.

Dynamic of the Shannon-Weaver diversity index (black dot) for species (black triangle) and functional groups (black square) from March 2009 to December 2011.

limno-2014-3-958-g004.jpg
Fig. 5.

Evolution of the cumulated relative biomasses expressed in percentage of total biomass (% of μg L−1) for the different assemblages identified overt the study. a) Relative biomasses of some pioneers functional groups (Y, Lo and W2). b) Relative biomasses of some transitional functional groups (F, X1 and J). c) Relative biomasses of some functional groups (A E G N and P).

limno-2014-3-958-g005.jpg
Fig. 6.

Temporal and environmental parameters structuring the phytoplankton communities when expressed as species biomass or functional-groups biomasses. The A-statistic (calculated by an MRPP) provides an assessment of the communities heterogeneity for temporal descriptors as years, months, seasons, for chemical parameters as pH, total nitrogen (TN), total phosphorous (TP), dissolved organic carbon (DOC), and hydrological parameters as water level (WL), outflows from the dam (Outflows).

limno-2014-3-958-g006.jpg
Tab. 1.

Parameters expressed as class for the Multi response permutation procedures analyses.

Parameter Class Number of samples
Year Class 1: 2009 10
Class 2: 2010 12
Class 3: 2011 12
Seasons Class 1: cool dry 10
Class 2: warm dry 9
Class 3: wet 15
Month Class 1: January 2
Class 2: February 2
Class 3: March 3
Class 4: April 3
Class 5: May 3
Class 6: June 3
Class 7: July 3
Class 8: August 3
Class 9: September 3
Class 10: October 3
Class 11: November 3
Class 12: December 3
pH 5 ≤ class 1 < 6 5
6 ≤ class 2 < 6.5 7
6.5 ≤ class 3 <7 17
7 ≤ class 4 and more 5
Ptot (mg P L−1) Class 1 < 0.01 24
0,01 ≤ class 2 < 0,025 3
0,025 ≤ class 3 < 0,05 4
4 ≤ class 4 3
Ntot Class 1 < 0 9
(mg N L−1) 0,01 ≤ class 2 < 0,5 8
0,5 ≤ class 3 < 0,8 8
0,8 ≤ class 4 9
DOC 0 < class 1 <1 5
(mg C L−1) 1 ≤ class 2 < 2 7
2 ≤ class 3 < 3 12
3 ≤ class 4 10
Water level - 2.05 < class 3 ≤ - 1 12
variation (m) -1 < class 2 ≤ - 0.3 4
-0.3< class 1 ≤ 0.15 9
0.15< class 4 ≤ 1 5
1< class 5 < 5 4
Dam output class 1 ≤ 63.5 15
(m3 s−1) 63.5 <class 2 ≤ 2305 10
2305 < class 3 ≤ 15100 6
15100 < class 4 3

[i] DOC, dissolved organic carbon.

Tab. 2.

Summary of physical and chemical data measured at the sub-surface in Nam Theun 2 Reservoir at the dam site location, with medians of annual values from 2009-2011 and stratification period (from March to September) (Median [Min-Max]).

2009 2010 2011
Annual values Stratification period Annual values Stratification period Annual values Stratification period
Water temperature
(°C)
26.7
(19-27.9)
27.5
(25.4-27.9)
26.4
(20.8-29.6)
28.8
(22.6-29.6)
24.2
(19.5-29.3)
27.8
(20.1-29.3)
pH 6.5
(5.8-7.1)
6.75
(5.9-7.1)
6.7
(5.8-6.9)
6.7
(6.4-6.9)
6.8
(5.8-7.7)
6.9
(5.9-7.7)
Dissolved O2 (mg L−1) 4.1
(0.9-7.4)
5.15
(3.6-7.4)
6.2
(2.1-7.7)
7.1
(3.7-7.7)
6.4
(3.8-8.8)
7.4
(4.5-8.8)
TSS
(mg L−1)
3.6
(1.4-8.9)
3.8
(1.4-8.9)
3.7
(1.2-9.0)
3.8
(1.2-9.0)
1.8
(0.7-4.5)
2.5
(0.7-4.5)
Secchi depth (m) 1.7
(1.2-2.5)
1.7
(1.3-2.5)
1.8
(1.2-2.2)
1.8
(1.3-1.9)
2.1
(1.5-2.6)
1.95
(1.25-2.4)
TP
(μg L−1)
0
(0-270)
12
(0-270)
0* 0* 0*
(0-80)
0
(0-30)
TN
(μg L−1)
130
(0-570)
0
(0-230)
500
(0-1000)
730
(0-930)
780
(0-1550)
765
(360-930)

[i] TSS, total suspended solids; TP, total phosphorous; TN, total nitrogen.

[ii] *Below detection limit.

Tab. 3.

The main functional groups found in NT2 Reservoir with the representative genera in accordance with their periods of occurrence.

Group code Genus included in the group Period of occurrence
Lo Peridinium From cool season up to warm and dry season
Y Cryptomonas, Gymnodynium Cool dry season - Wet season
W2 Trachelomonas Mainly in 2009
A Cyclotella, Rhizosolenia June in 2010 and Sept.- Dec. in 2010 and in 2011
X1 Ankistrodesmus, Monoraphidium Dry season in 2010 and 2011
X2 Kephyrion, Rhodomonas Cool dry season - Wet season
J Crucigenia, Crucigeniella, Tetraedron, Tetrastrum, Coelastrum, Scenedesmus Dry season: Feb.- Mar. in 2010 and Nov. 10 - Jan. 11
N Cosmarium, Staurodesmus, Staurastrum April 2010; July-Aug. 2010 and Sept. 2010 Jan. 2011; April-July 2011 and Oct. 2011
P Closterium, Fragilaria Sept. 2009; July-Aug. 2010 and June-Aug. 2011
G Eudorina, Gonium Warm dry season in 2011 (March-May)
E Dinobryon, Mallomonas Jan.-Feb. 2010; May-June 2010; Feb.- April 2011; Aug.- Sept. 2011 and Nov.- Dec. 2011
F Botryococcus, Dictyosphaerium, Kirchneriella, Oocystis, Sphaerocystis June-July 2009; Sept. 2009; Dec. 2009 - July 2010; Sept. 2010 - Dec.2011
Tab. 4.

Indicator species and functional groups of the different parameters, calculated with the IndVal analysis. In the table, species and functional groups were sorted based on their interannual dynamic: pioneer (decrease of their relative abundance), transitional (increase and then decrease of their relative abundance), colonizing (increase) and permanent assemblages (stable relative abundance).

Indication IndVal P value Mixotrophy
Pioneer
Lo High pH 75.4 0.020 Yes
Medium TN 72.5 0.009
Peridinium willei High TN 39 0.023 Yes
Cryptomonas reflexa 2009 61.8 0.003 Yes
Transitional
X1 2010 50.1 0.005 No
J High DOC 46.4 0.037 No
Tetraedron caudatum 2010 60.4 0.010 No
Colonising
G (composed by Eudorina elegans) 2011 41.7 (33.3) 0.006 (0.027) No
Warm season 30.2 (31.3) 0.039 (0.011)
X2 (composed by Rhodomonas minuta) 2011 58.9 (58.1) 0.014 (0.009) Yes
N (composed by Staurastrum tetracerum) Very high DOC 69.8 (62.1) 0.005 (0.006)
Very high TN 74.8 (58.1) 0.002 (0.006)
High pH 63.1 0.02 No
(Low outflow) (65.0) (0.010)
Staurastrum cf. punctulatum Increase of level 60.0 0.003 No
Permanent (species belonging to group F)
Botryococcus braunii 2011 58.3 0.001 No
High pH 53.8 0.008
Gloeocystis sp. Low DOC 40.0 0.015 No
Elakatothrix gelatinosa Sharp level decrease 44.1 0.025 No
Small Chlorophyceae Low outflow 40.5 0.021 No
Very high TN 28.7 0.009

[i] DOC, dissolved organic carbon; TN, total nitrogen.

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