Int. J. Aquat. Biol. (2019) 7(2): 71-84 ISSN: 2322-5270; P-ISSN: 2383-0956 Journal homepage: www.ij-aquaticbiology.com © 2019 Iranian Society of Ichthyology Original Article Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi Simon Buhungu*1,2, Marcel Donou3, Gaspard Ntakimazi1, Clément Agossou Bonou4, Elie Montchowui2 1Centre de Recherche en Sciences Naturelles et de l’Environnement, Université du Burundi, BP 2700 Bujumbura, Burundi. 2Laboratoire de Recherche en Aquaculture et en Biologie et Ecologie Aquatiques, Ecole d’Aquaculture, Université Nationale d’Agriculture, Benin. 3Laboratoire de Biomathématique et d’Estimation Forestière, Université d’Abomey Calavi, Benin. 4Laboratoire de Recherche en Biologie Appliquée, Ecole Polytechnique d’Abomey-Calavi, Université d’Abomey-Calavi, BP 2009 Cotonou, Benin. s Article history: Received 28 August 2018 Accepted 4 January 2019 Available online 2 5 April 2019 Keywords: Zooplankton Characteristic species Indicator value Kinyankonge Abstract: The objective of this study is to determine the zooplankton species that characterize the Kinyankonge River basin in Burundi. Thus, zooplankton was sampled monthly over a period of 18 months (from July 2015 to June 2016, then from January 2017 to June 2017) at seven stations. The Indicator Value (IndVal) of the identified zooplankton species and the coverage of stations were determined. The results showed that three species characterized significantly the most upstream station whereas the water of the irrigation channel was characterized by 4 species. The waters of the Nyabagere tributary and the wastewater treatment plant are characterized by 1 and 5 species, respectively. Furthermore, the dry season was characterized by 4 singletons and 13 pairs of species, while the rainy season was characterized by 11 pairs of species. Moreover, the group of upstream stations was characterized by 5 species while 3 species characterized the group of downstream stations. These species highlighted by the indicator value method can be used to characterize stations in the Kinyankonge River and provide information on seasonal changes. Introduction Zooplankton plays an important role in aquatic ecosystems (Baloch et al., 2005). It is considered as one of the most important food sources to the aquatic organisms particularly to planktivorous. Zooplankton community constitutes a way of energy flux transfer through aquatic food webs especially between phytoplankton and the high levels (Santos- Wisniewski et al., 2006). Zooplankton species are used as bioindicators of the quality of water in lakes and rivers (El-Bassat and Taylor, 2007; Ahangar et al., 2012), because of their sensitivity to changes in the ecological and environmental conditions of their habitats (Hanazato, 2001; Carignan and Villard, 2002; Niemi and McDonald, 2004; Brito et al., 2011; Güher et al., 2011; Primo et al., 2015). Their identification as characteristic species is a classical method often used in ecology (Legendre and Legendre, 2012). In fact, they early react to a large number of environmental changes. Such species or groups of species are called bioindicators (Parmesan, 2006; Jakhar, 2013; Primo et *Correspondence: Simon Buhungu DOI: https://doi.org/10.22034/ijab.v7i2.484 E-mail: buhusimon@gmail.com al., 2015) and are useful in predicting of the level or degree of pollution before the pollutants cause significant damage (Pai, 2002; Verma, 2002). Their identification can provide an indication of ecosystem health. They can thus act as an early warning system allowing the implementation of intensive conservation strategy to anticipate ecologic catastrophe (Chapin, 2000). In ecology, environmental bioindicators are identified by establishing a strong relationship with some environmental characteristics (Kitching et al., 2000; Davis, 2001). They are now one of tools used by water quality monitoring programs worldwide (Furse et al., 2006; Marchant et al., 2006; Yagow et al., 2006; Borja et al., 2008). Especially, studies on the structure of zooplankton populations can be a tool for analyzing the environmental disturbances to which these organisms are subjected in aquatic environments (Sampaio et al., 2002; Eskinazi-Santanna et al., 2013). Therefore, through their indicator value of their community, the characteristic species can provide an 72 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi ecological significance to a classification of inspected stations and also highlight the functional characteristics of the studied system (Touzin, 2008). Studies conducted on the Kinyankonge River have shown organic pollution coming from domestic discharges (Buhungu et al., 2017, 2018) and a zooplankton community included rotifers, copepods and cladoceran species (Buhungu et al., 2018). The current study aims to identify, using the method of Indicator Species Analysis, the spatial and seasonal characteristic species of this river basin, based on a determination of their indicator values Materials and Methods Study area and sampling stations: The Kinyankonge River is approximately 6.5 km long. It crosses a nearly slightly populated locality and is characterized by arable land stretches. The soil is marshy and is therefore favorable mainly for rice and fodder cultivation. To conduct this study, seven sampling stations have been selected based on the types of discharges and activities occurring around the river (Fig. 1). The first station S1 (3°20'22.765"S, 29°21'10.655"E, 774.5 m of altitude) is located upstream of the Kinyankonge River. It has been chosen in the Cibitoke district to investigate the river source which receives both wastewater and garbage. The second station S2 (3°20'30.527"S, 29°21'27. 655"E, 774.7 m of altitude) was chosen into the Gikoma Channel to assess the polluting load thrown out in Kinyankonge River. The third station S3 (3°20' 43.598"S, 29°21'27.468"E, 774.8 m of altitude) is located on the Nyabagere River, a tributary of the studied river. In fact, sand is extracted from Nyabagere River for the construction of a new neighborhood located on its shores. Sand removal operations cause a significant degradation of the substrate which is important for the aquatic organisms. On this station, the collected samples have also enabled the evaluation of the pollutants load discharged into the Kinyankonge River. The fourth station S4 (3°20ˊ42.623"S, 29°21ˊ11.275"E, 771.3 m of altitude) is located on the Kinyankonge River, downstream of the mouths of the Nyabagere tributary and the Gikoma Canal. The fifth station S5 (3°21ˊ15.908"S, 29°20ˊ33.745"E, 765.6 m of altitude) is into the discharge channel of the wastewater treatment plant (WWTP) of Buterere discharging their effluents into the Kinyankonge River. The sixth station S6 (3°21ˊ16.657"S, 29°20ˊ32.535"E, 764.5 m of altitude) is positioned after the discharge point of the treatment plant. It receives the waters coming from the blending of WWTP effluents with the Kinyankonge river water. As for the seventh station S7 (3°21'37,346"S, 29°20'22,794"E, 760.5 m of altitude), it is located near the mouth of the Kinyankonge River and Tanganyika Lake. At this station, the river receives effluents from SAVONOR soap factory that are discharged after a physical pretreatment. Sampling: Zooplankton samples were collected monthly over an 18-month period (from July 2015 to June 2016, then from January 2017 to June 2017). They were taken at morning between 7 AM and 11 Figure 1. Geographic situation of sampling stations on Kinyankonge River. 73 Int. J. Aquat. Biol. (2019) 7(2): 71-84 AM using a 50 μm-mesh plankton net. Samples were taken vertically and over the entire water column. At each station, three different points were sampled to constitute a composite sample. The concentrated zooplankton was then recovered in a jar and immediately fixed with 5% formalin. Observation, identification, and enumeration of zooplankton: In the laboratory, each zooplankton sample was concentrated to a volume of 100 ml. Zooplankton species were identified by microscopic observation using N-120/ N-120A light microscope from Ht-0205 Hiprove. This species identification operation was based on the specific morphological characters observable using different determination keys (Dussart, 1967; Pourriot, 1968; Rey and Saint Jean, 1968, 1969; Dussart, 1982). Then, individuals of identified species were also enumerated using a Burker Turk enumeration cell. The enumeration effort was set at 400 individuals for each inventoried species. Thus, the count rate varied according to species abundance and reached 100% of sample for rare species. An extrapolation was then made on total volume of sample, on the one hand, and the volume of filtered water, on the other hand, to assess the densities per liter of river water. The density was calculated using the following relation: 𝐷 = 1000 ∗ (𝑛𝑖 ∗ 100 𝐴𝑅 ) 𝑉 Where D is the density (expressed in individuals per liter); ni the number of individuals recorded for species i; AR sample analysis rate corresponding to ni; V volume of filtered river water (ml). Data analysis: In order to identify characteristic species, the indicator value of species was calculated and the significance of this value was tested using the Monte Carlo permutation test. This test enables to verify whether the preference of a species for a type of habitat is significantly higher than it is suggested by a random distribution (Dufrêne and Legendre, 1997). The indicator value of species that measures its predictive value as indicator of the conditions prevailing in a station or a season (De Cáceres and Legendre, 2009) is given by the following relation according to Dufrêne and Legendre (1997): IndValij = Aij × Bij × 100 In this relation, Aij = N individuals ij / N individuals i, and represents the specificity, while Bij = N sites ij / N sites j, and corresponds to the fidelity. The indicspecies package of R (R Core Team, 2015) was used for testing singletons and species pairs, which provide better information on habitat ecology. In this study, analyses were limited to singletons and species pairs to limit the complexity of characteristic species identification. This option was done in order to avoid very large numbers of possibilities that could reduce the reliability of the analysis and making them too long (De Cáceres and Legendre, 2009). The coverage of stations, groups of stations and seasons was evaluated by the "strassoc", "coverage" and "plotcoverage" functions that were used for the calculation and graphical representation of the coverage according to the specificity (A) values. For this analysis, only species with fidelity values B > 0.1 were included for eliminating low fidelity species. A comparison was made between singleton coverage and species pairs. All the analyses were performed with the indicspecies package (De Caceres and Legendre, 2009) of the R software (R Core Team, 2015). Results Characteristic species of stations, group of stations and seasons: A total of 36 zooplankton species inventoried in the Kinyankonge River Basin (Buhungu et al., 2018) were used for the identification of characteristic species. Singletons and species pairs considered as characteristics of stations (Table 1), groups of stations (Table 2) and seasons (Table 3) were the significant ones at 5% threshold with indicator value IndVal ≥ 0.50. Thus, no species or pair of species characterized stations S6 and S7. The first station (S1) was characterized by 8 pairs of species and 3 singletons (Lecane luna, L. bulla and Alonella sp.), the second station (S2) by 70 pairs of species and 4 singletons (Polyarthra vulgaris, Brachionus quadridentatus, B. patulus and Philodina sp.), the third station (S3) by one singleton (Keratella tecta), the fourth station (S4) by 2 pairs of species and the fifth 74 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi Table 1. Indicator values (IndVal) of characteristic species of the stations. Stations Species A B IndVal P-value Sig. Station S1 Singletons Leca_lu 0.43 0.94 0.64 0.019 * Leca_bul 0.30 1.00 0.55 0.040 * Alon_sp(¥) 0.59 0.44 0.51 0.002 ** Pairs Alon_sp+Rota_sp(¥) 0.67 0.44 0.55 0.001 *** Leca_lu+Rota_sp(¥) 0.34 0.83 0.53 0.008 ** Leca_bul+Leca_lu(¥) 0.30 0.94 0.53 0.005 ** Leca_lu+Naup(¥) 0.31 0.89 0.53 0.004 ** Alonsp+Brach pat(¥) 0.61 0.44 0.52 0.002 ** Alon_sp+Leca_bul(¥) 0.59 0.44 0.51 0.002 ** Alon_sp+Leca_lu(¥) 0.59 0.44 0.51 0.002 ** Alon_sp+Naup(¥) 0.59 0.44 0.51 0.002 ** Alon_sp+Brach_caly 0.52 0.44 0.48 0.002 ** Alon_sp+Lepa_pat 0.83 0.28 0.48 0.002 ** Anur_fis+Poly_vul 0.59 0.39 0.48 0.007 ** Leca_bul+Lepa_pat 0.37 0.61 0.47 0.069 ns Alon_sp+Brach_quad 0.67 0.33 0.47 0.003 ** Alon_sp+Brach_ang 0.57 0.39 0.47 0.002 ** Alon_sp+Poly_sp 0.97 0.22 0.47 0.003 ** Brach_bid+Leca_lu 0.27 0.78 0.46 0.038 * Brach_ang+Leca_lu 0.25 0.83 0.46 0.040 * Alon_sp+Moin_sp 0.46 0.44 0.45 0.001 *** Anur_fis+Leca_lu 0.44 0.44 0.44 0.025 * Alon_sp+Brach_bid 0.69 0.28 0.44 0.004 ** Cepha_gib+Lepa_pat 0.38 0.50 0.44 0.141 ns Alon_sp+Poly_vul 0.54 0.33 0.42 0.006 ** Alon_sp+Fili_ter 0.51 0.33 0.41 0.013 * Cepha_gib+Leca_bul 0.33 0.50 0.41 0.289 ns Anur_fis+Rota_sp 0.49 0.33 0.40 0.035 * Alon_sp+Aspl_sp 0.97 0.17 0.40 0.014 * Alon_sp+Aspl_pri 0.46 0.33 0.39 0.014 * Anur_fis+Brach_pat 0.39 0.39 0.39 0.037 * Anur_fis+Brachquad 0.45 0.33 0.39 0.026 * Anur_fis+Leca_bul 0.33 0.44 0.39 0.115 ns Alon_sp+Plat_quad 0.52 0.28 0.38 0.032 * Alon_sp+Micro_sp 0.61 0.22 0.37 0.019 * Station S2 Singletons Poly_vul 0.80 0.88 0.84 0.003 ** Brach_quad 0.90 0.75 0.82 0.006 *** Brach_pat 0.59 1.00 0.77 0.001 *** Phil_sp 0.42 0.81 0.58 0.010 ** Rota_sp 0.35 0.94 0.58 0.065 ns Aspl_sp 0.74 0.44 0.57 0.069 ns Brach_bid 0.44 0.63 0.52 0.156 ns Kera_trop 0.51 0.44 0.47 0.011 * Moin_sp 0.31 0.69 0.46 0.367 ns Pairs Brachquad+Poly vul(¥) 0.91 0.75 0.83 0.001 *** Brach_quad+Naup(¥) 0.84 0.75 0.79 0.003 ** Brachquad+Rota sp(¥) 0.83 0.75 0.79 0.002 ** Brach_pat+Naup(¥) 0.60 1.00 0.77 0.001 *** Poly_vul+Rota_sp(¥) 0.66 0.88 0.76 0.001 *** Brach_pat+Leca_bul 0.57 1.00 0.76 0.001 *** Naup+Poly_vul 0.65 0.88 0.76 0.002 ** Brach_quad+Phil_sp 0.77 0.69 0.73 0.001 *** 75 Int. J. Aquat. Biol. (2019) 7(2): 71-84 Table 1. Continued. Stations Species A B IndVal P-value Sig. Station S2 Pairs Phil_sp+Poly_vul 0.65 0.81 0.73 0.001 *** Brach_pat+Poly_vul 0.60 0.88 0.73 0.001 *** Fili_ter+Phil_sp 0.64 0.81 0.72 0.001 *** Naup+Rota_sp 0.56 0.94 0.72 0.002 ** Brach_pat+Fili_ter 0.59 0.88 0.72 0.001 *** Brach_pat+Phil_sp 0.59 0.81 0.70 0.001 *** Brach_pat+Rota_sp 0.52 0.94 0.70 0.001 *** Brach_bid+Brach_pat 0.75 0.63 0.69 0.001 *** Brach_pat+Brach quad 0.62 0.75 0.68 0.001 *** Naup+Phil_sp 0.56 0.81 0.68 0.001 *** Brach_quad+Fili_ter 0.60 0.75 0.67 0.004 ** Aspl_pri+Brach_pat 0.53 0.81 0.66 0.001 *** Phil_sp+Rota_sp 0.52 0.81 0.65 0.002 ** Fili_ter+Poly_vul 0.47 0.88 0.64 0.001 *** Brach_pat+Leca_lu 0.43 0.94 0.64 0.001 *** Fili_ter+Rota_sp 0.45 0.88 0.63 0.001 *** Aspl_sp+Brach_quad 0.89 0.44 0.62 0.006 ** Aspl_pri+Brach_quad 0.56 0.69 0.62 0.003 ** Brach_ang+Brach pat 0.44 0.88 0.62 0.001 *** Aspl_sp+Poly_vul 0.87 0.44 0.62 0.022 * Brach_quad+Lecabul 0.49 0.75 0.61 0.003 ** Leca_lu+Moin_sp 0.52 0.69 0.60 0.001 *** Brach_pat+Moin_sp 0.52 0.69 0.60 0.001 *** Aspl_sp+Naup 0.80 0.44 0.59 0.055 ns Brach_bid+Phil_sp 0.70 0.50 0.59 0.005 ** Aspl_sp+Rota_sp 0.79 0.44 0.59 0.044 * Brach_ang+Brach_qud 0.50 0.69 0.59 0.001 *** Aspl_pri+Poly_vul 0.42 0.81 0.59 0.001 *** Aspl_pri+Fili_ter 0.42 0.81 0.59 0.001 *** Moin_sp+Phil_sp 0.61 0.56 0.59 0.001 *** Leca_bul+Poly_vul 0.39 0.88 0.59 0.001 *** Moin_sp+Poly_vul 0.54 0.63 0.58 0.002 ** Fili_ter+Leca_bul 0.38 0.88 0.58 0.001 *** Brach_quad+Lepapat 0.60 0.56 0.58 0.001 *** Leca_bul+Moin_sp 0.48 0.69 0.58 0.001 *** Brach_pat+Lepa_pat 0.53 0.63 0.57 0.002 ** Brach_bid+Naup 0.52 0.63 0.57 0.023 * Brach_pat+Cephagib 0.58 0.56 0.57 0.001 *** Brach_quad+Leca_lu 0.43 0.75 0.57 0.001 *** Aspl_sp+Phil_sp 0.74 0.44 0.57 0.014 * Fili_ter+Leca_lu 0.37 0.88 0.57 0.001 *** Brach_bid+Rota_sp 0.56 0.56 0.56 0.015 * Leca_lu+Phil_sp 0.37 0.81 0.55 0.003 ** Aspl_pri+Rota_sp 0.37 0.81 0.55 0.002 ** Cepha_gib+Moin_sp 0.59 0.50 0.54 0.006 ** Moin_sp+Rota_sp 0.43 0.69 0.54 0.003 ** Aspl_sp+Brach_pat 0.67 0.44 0.54 0.008 ** Leca_bul+Phil_sp 0.36 0.81 0.54 0.003 ** Aspl_pri+Moin_sp 0.47 0.63 0.54 0.001 *** Leca_lu+Poly_vul 0.33 0.88 0.54 0.001 *** Lepa_pat+Phil_sp 0.51 0.56 0.54 0.010 ** Brach_caly+Brachpat 0.33 0.88 0.53 0.002 ** Leca_bul+Rota_sp 0.29 0.94 0.53 0.003 ** 76 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi Table 1. Continued. Stations Species A B IndVal P-value Sig. Station S2 Pairs Aspl_pri+Phil_sp 0.37 0.75 0.52 0.016 * Leca_bul+Naup 0.27 1.00 0.52 0.005 ** Brach_bid+Leca_bul 0.43 0.63 0.52 0.024 * Brach_bid+Fili_ter 0.48 0.56 0.52 0.053 ns Brach_quad+Keratro 0.71 0.38 0.52 0.001 *** Brach_quad+Moinsp 0.47 0.56 0.51 0.001 *** Aspl_pri+Leca_lu 0.32 0.81 0.51 0.004 ** Aspl_sp+Lepa_pat 0.58 0.44 0.51 0.014 * Brach_pat+Kera_trop 0.58 0.44 0.50 0.003 ** Brach_pat+Micro_sp 0.57 0.44 0.50 0.013 * Aspl_pri+Lepa_pat 0.50 0.50 0.50 0.028 * Brach_bid+Kera_trop 0.77 0.31 0.49 0.003 ** Cepha_gib+Phil_sp 0.48 0.50 0.49 0.024 * Aspl_pri+Leca_bul 0.29 0.81 0.49 0.028 * Brach_caly+Leca_lu 0.27 0.88 0.49 0.010 ** Kera_trop+Naup 0.54 0.44 0.49 0.007 ** Brach_ang+Brachbid 0.41 0.56 0.48 0.037 * Brach_quad+Cephagi 0.46 0.50 0.48 0.039 * Aspl_sp+Fili_ter 0.53 0.44 0.48 0.044 * Kera_trop+Rota_sp 0.52 0.44 0.48 0.006 ** Fili_ter+Kera_trop 0.52 0.44 0.48 0.006 ** Brach_pat+Trop_sp 0.33 0.69 0.48 0.007 ** Aspl_sp+Aspl_pri 0.59 0.38 0.47 0.024 * Fili_ter+Lepa_pat 0.39 0.56 0.47 0.038 * Brach_ang+Poly_vul 0.27 0.81 0.47 0.040 * Brach_quad+Plat_qua 0.43 0.50 0.46 0.007 ** Brach_ang+Keratrop 0.49 0.44 0.46 0.013 * Kera_trop+Trop_sp 0.48 0.44 0.46 0.007 ** Kera_trop+Leca_lu 0.48 0.44 0.46 0.009 ** Leca_lu+Micro_sp 0.47 0.44 0.45 0.020 * Kera_trop+Poly_vul 0.46 0.44 0.45 0.010 ** Poly_vul+Trop_sp 0.30 0.63 0.43 0.046 * Leca_lu+Trop_sp 0.30 0.63 0.43 0.080 ns Brach_quad+Trop_sp 0.37 0.50 0.43 0.015 * Kera_trop+Leca_bul 0.42 0.44 0.43 0.020 * Brach_caly+Lepapat 0.31 0.56 0.41 0.063 ns Moin_sp+Plat_quad 0.39 0.44 0.41 0.024 * Aspl_pri+Kera_trop 0.39 0.44 0.41 0.024 * Brach_bid+Moin_sp 0.45 0.38 0.41 0.018 * Lepa_pat+Plat_quad 0.38 0.44 0.41 0.024 * Aspl_sp+Leca_lu 0.38 0.44 0.41 0.041 * Brach_pat+Méso_sp 0.88 0.19 0.41 0.048 * Kera_trop+Moin_sp 0.61 0.25 0.39 0.015 * Phil_sp+Trop_sp 0.27 0.56 0.39 0.289 ns Brach_pli+Poly_sp 0.80 0.19 0.39 0.045 * Kera_trop+Micro_sp 0.73 0.19 0.37 0.025 * Station S3 Singletons Kera_tec 0.84 0.44 0.61 0.001 *** Pairs Kera_tec+Rota_sp(¥) 0.85 0.44 0.61 0.001 *** Aspl_pri+Keratec(¥) 0.83 0.44 0.61 0.001 *** Kera_tec+Leca bul(¥) 0.78 0.44 0.59 0.001 *** Kera_tec+Phil_sp(¥) 0.88 0.39 0.59 0.001 *** Brachang+Keratec(¥) 0.78 0.39 0.55 0.001 *** Cepha_gib+Kera_tec 0.77 0.28 0.46 0.008 ** Kera_tec+Lepa_pat 0.76 0.28 0.46 0.005 ** 77 Int. J. Aquat. Biol. (2019) 7(2): 71-84 station (S5) by 17 pairs of species and 5 singletons (B. calyciflorus, B. angularis, Filina terminalis, Microcyclops sp. and Filina sp.) (Table 1). The group of upstream stations (S1, S2, S3 and S4) was characterized by 14 pairs of species and 5 singletons (L. luna, L. bulla, P. vulgaris, B. quadridentatus and B. patulus), while 8 pairs of species and 3 singletons (B. angularis, B. calyciflorus and Tropocyclops sp.) were characteristic of the group of downstream stations (S5, S6 and S7) (Table 2). The Table 1. Continued. Stations Species A B IndVal P-value Sig. Station S4 Pairs Brach_caly+Brach_qu 0.63 0.56 0.59 0.047 * Brach_caly+Poly_vul 0.40 0.83 0.58 0.021 * Aspl_sp+Brach_caly 0.53 0.39 0.46 0.122 ns Brach_caly+Cepha_gi 0.41 0.50 0.45 0.082 ns Cepha_gib+Fili_sp 0.63 0.22 0.38 0.038 * Brach_ang+Cephagib 0.31 0.44 0.37 0.350 ns Aspl_sp+Brach_fal 0.81 0.17 0.37 0.048 * Station S5 Singletons Brach_caly 0.76 0.94 0.85 0.001 *** Brach_ang 0.64 1.00 0.80 0.001 *** Fili_ter 0.53 0.83 0.66 0.003 ** Micro_sp 0.96 0.44 0.65 0.026 * Naup 0.36 1.00 0.60 0.131 ns Fili_sp 0.51 0.50 0.51 0.015 * Trop_sp 0.33 0.72 0.49 0.029 * Méso_sp 0.80 0.28 0.47 0.025 * Pairs Brachang+Brachca(¥) 0.75 0.94 0.84 0.001 *** Brach_caly+Filiter(¥) 0.79 0.83 0.81 0.001 *** Brach_caly+Naup(¥) 0.61 0.94 0.76 0.001 *** Brach_ang+Filiter(¥) 0.65 0.83 0.74 0.002 ** Brach_ang+Naup(¥) 0.48 1.00 0.69 0.001 *** Micro_sp+Naup 0.86 0.44 0.62 0.012 * Brach_caly+Fili_sp 0.72 0.50 0.60 0.001 *** Brach_caly+Micro sp 0.79 0.44 0.59 0.007 ** Fili_sp+Naup 0.69 0.50 0.59 0.004 ** Brach_ang+Micro_sp 0.74 0.44 0.57 0.009 ** Fili_sp+Micro_sp 0.84 0.39 0.57 0.001 *** Brach_ang+Fili_sp 0.61 0.50 0.55 0.002 ** Fili_ter+Micro_sp 0.65 0.44 0.54 0.013 * Brach_caly+Trop_sp 0.42 0.67 0.53 0.004 ** Fili_ter+Naup 0.33 0.83 0.52 0.065 , Brach_caly+Méso_sp 0.92 0.28 0.51 0.010 ** Brach_ang+Méso_sp 0.88 0.28 0.50 0.007 ** Naup+Trop_sp 0.33 0.72 0.49 0.020 * Brach_ang+Trop_sp 0.32 0.72 0.48 0.016 * Fili_ter+Méso_sp 0.82 0.28 0.48 0.011 * Aspl_pri+Brach_caly 0.30 0.72 0.46 0.145 ns Fili_sp+Trop_sp 0.58 0.33 0.44 0.004 ** Micro_sp+Trop_sp 0.60 0.28 0.41 0.033 * Station S6 Pairs Poly_sp+Trop_sp 0.38 0.39 0.39 0.027 * Brach_fal+Fili_sal 1.00 0.11 0.33 0.157 ns Aspl_pri+Fili_sal 0.46 0.22 0.32 0.093 ns Fili_sal+Poly_vul 0.46 0.22 0.32 0.101 ns Station S7 Pairs Anur_fis+Phil_sp 0.27 0.33 0.30 0.350 ns Cepha_gib+Trop_sp 0.24 0.33 0.28 0.651 ns Fili_sp+Scar_lon 0.60 0.11 0.26 0.325 ns Plat_quad+Scar_lon 0.57 0.11 0.25 0.315 ns Anur_fis+Brach_fal 0.52 0.11 0.24 0.357 ns A=specificity, B=fidelity, P-value=probability, Sig= significance level, code of significance: 0.001***; 0.01*; 0. 05*; ns: non significance, (¥): species more significantly characteristic of the station with highest indicator value. 78 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi dry season was characterized by 13 pairs of species and 4 singletons (L. bulla, Asplanchna priodonta, Brachionus bidentatus and Anuraeopsis fissa) while the rainy season was characterized by 11 pairs (Table 3). Spatial coverage of characteristic species: Station coverage by characteristic species is shown by Figure 2. For each station, coverage of singletons and this of species pairs were compared. The coverage varied from a station to another according to characteristic species recorded. Indeed, the coverage decreased as specificity increased for both singletons and pairs of characteristic species. Therefore, when the selection of characteristic species were made more rigorously, the coverage of a station by the singletons or by the pairs of characteristic species decreased. At station S1, the coverage was total at specificity threshold for A=0.45 for singletons as well as characteristic pairs. At a higher specificity, it noticed that characteristic species number was no more sufficient to cover the entire station. This remark is more pronounced when considering only singletons. As for station S2, the coverage was total at up to A=0.6 for singletons and A=0.75 for species pairs. Station S3 was the least covered. In this station, the coverage was total only A=0.18 for both singletons and species pairs. For stations S4, S6 and S7, singleton coverage decreased before pair coverage. Stations S2 and S5 were covered by many species for both singletons and species pairs. Table 2. Species characteristic of groups of stations. Group of stations Species A B stat Pvalue Sig. Upstream stations Singletons Leca_bul 0.73 1.00 0.86 0.001 *** Leca_lu 0.75 0.84 0.80 0.005 ** Poly_vul (¥) 0.93 0.66 0.78 0.036 * Brach_quad 0.99 0.59 0.76 0.001 *** Brach_pat 0.79 0.70 0.74 0.001 *** Pairs Leca_bul+Rota_sp (¥) 0.72 0.87 0.79 0.001 *** Leca_bul+Leca_lu (¥) 0.74 0.84 0.79 0.001 *** Leca_bul+Naup (¥) 0.72 0.86 0.78 0.002 ** Rota_sp 0.62 0.87 0.74 0.174 ns Leca_lu+Naup (¥) 0.79 0.74 0.77 0.001 *** Aspl_pri+Leca_bul 0.67 0.86 0.76 0.003 ** Leca_lu+Rota_sp 0.77 0.74 0.76 0.001 *** Brach_pat+Leca_bul 0.81 0.70 0.75 0.001 *** Naup+Rota_sp 0.76 0.74 0.75 0.105 ns Brach_quad+Naup 0.98 0.57 0.75 0.001 *** Aspl_pri+Leca_lu 0.77 0.73 0.75 0.001 *** Brach_quad+Leca_bul 0.94 0.59 0.74 0.001 *** Brach_pat+Naup 0.82 0.67 0.74 0.001 *** Aspl_pri+Rota_sp 0.73 0.74 0.74 0.001 *** Naup+Poly_vul 0.86 0.63 0.74 0.048 * Poly_vul+Rota_sp 0.85 0.63 0.73 0.019 * Downstream stations Singletons Brach_ang 0.86 0.93 0.89 0.001 *** Brach_caly 0.98 0.81 0.89 0.001 *** Fili_ter 0.71 0.76 0.73 0.052 ns Naup 0.54 0.94 0.71 0.649 ns Trop_sp 0.65 0.74 0.70 0.013 * Pairs Brachang+Brachcaly (¥) 0.95 0.80 0.87 0.001 *** Brach_caly+Fili_ter (¥) 0.94 0.72 0.82 0.001 *** Brach_caly+Naup (¥) 0.82 0.80 0.81 0.001 *** Brach_ang+Fili_ter (¥) 0.88 0.74 0.81 0.001 *** Brach_ang+Naup (¥) 0.69 0.91 0.79 0.001 *** Brach_caly+Trop_sp 0.79 0.65 0.71 0.001 *** Naup+Trop_sp 0.65 0.70 0.68 0.016 * Brach_ang+Trop_sp 0.65 0.70 0.68 0.019 * A=specificity, B=fidelity, P-value=probability, Sig= significance level, code of significance: 0.001***; 0.01*; 0.05* 79 Int. J. Aquat. Biol. (2019) 7(2): 71-84 Table 3. Seasonal characteristic species. Seasons Species A B stat P-value Sig. Rainy Singletons Moin_sp 0.71 0.51 0.60 0.126 ns Pairs Leca_bul+Rota_sp(¥) 0.63 0.90 0.76 0.008 ** Brach_ang+Rota_sp 0.63 0.84 0.73 0.017 * Brach_caly+Leca_lu 0.65 0.66 0.65 0.043 * Brach_pat+Leca_lu 0.67 0.63 0.65 0.036 * Rota_sp+Trop_sp 0.69 0.58 0.64 0.03 * Fili_ter+Leca_bul 0.56 0.73 0.64 0.203 ns Aspl_pri+Rota_sp 0.52 0.74 0.62 0.371 ns Leca_bul+Moin_sp 0.78 0.48 0.61 0.028 * Leca_lu+Moin_sp 0.77 0.46 0.60 0.034 * Brach_caly+Brach_pat 0.62 0.57 0.60 0.078 ns Brach_pat+Moin_sp 0.83 0.42 0.59 0.012 * Brach_caly+Trop_sp 0.57 0.57 0.57 0.305 ns Brach_pat+Trop_sp 0.76 0.43 0.57 0.03 * Moin_sp+Phil_sp 0.86 0.37 0.57 0.029 * Brach_ang+Kera_trop 1.00 0.20 0.45 0.027 * Brach_caly+Kera_trop 1.00 0.20 0.45 0.019 * Kera_trop+Leca_bul 1.00 0.20 0.45 0.024 * Kera_trop+Leca_lu 1.00 0.20 0.45 0.02 * Plat_quad+Poly_vul 0.58 0.34 0.44 0.401 ns Fili_ter+Kera_trop 1.00 0.18 0.42 0.033 * Kera_trop+Naup 1.00 0.18 0.42 0.034 * Kera_trop+Rota_sp 1.00 0.18 0.42 0.032 * Kera_trop+Trop_sp 1.00 0.18 0.42 0.031 * Micro_sp+Trop_sp 1.00 0.18 0.42 0.024 * Dry Singletons Brach_ang 0.79 0.85 0.82 0.152 ns Leca_bul 0.71 0.91 0.81 0.025 * Naup 0.71 0.91 0.80 0.14 ns Aspl_pri 0.69 0.91 0.79 0.005 ** Brach_bid 0.91 0.67 0.78 0.001 *** Anur_fis 0.84 0.52 0.66 0.001 *** Poly_vul 0.90 0.42 0.62 0.983 ns Trop_sp 0.49 0.79 0.62 0.438 ns Hexa_sp 0.75 0.24 0.43 0.013 * Pairs Aspl_pri+Naup(¥) 0.68 0.82 0.75 0.011 * Aspl_pri+Brach_bid(¥) 0.84 0.64 0.73 0.001 *** Aspl_pri+Brach_ang(¥) 0.67 0.79 0.73 0.03 * Aspl_pri+Leca_bul(¥) 0.64 0.82 0.73 0.03 * Brach_bid+Naup(¥) 0.84 0.61 0.72 0.001 *** Leca_bul+Naup 0.62 0.82 0.71 0.204 ns Brach_bid+Leca_bul 0.77 0.64 0.70 0.001 *** Brach_ang+Naup 0.59 0.82 0.70 0.427 ns Anur_fis+Aspl_pri 0.85 0.52 0.66 0.001 *** Brach_ang+Brach_bid 0.79 0.55 0.66 0.001 *** Brach_ang+Brach_caly 0.83 0.52 0.65 0.776 ns Anur_fis+Leca_bul 0.84 0.48 0.64 0.001 *** Leca_lu+Naup 0.58 0.70 0.64 0.415 ns Anur_fis+Brach_bid 0.86 0.45 0.63 0.001 *** Anur_fis+Trop_sp 0.78 0.48 0.61 0.001 *** Brach_ang+Leca_lu 0.52 0.70 0.60 0.622 ns Anur_fis+Naup 0.77 0.45 0.59 0.002 ** Brach_caly+Naup 0.60 0.52 0.56 1 ns Anur_fis+Brach_ang 0.78 0.39 0.56 0.004 ** Fili_ter+Hexa_sp 0.75 0.24 0.43 0.011 * 80 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi Coverage of characteristic species according to station groups: The coverage of the group of upstream and downstream stations is shown in Figure 3. It remained maximal (100%) and decreased only beyond a specificity of 0.6 for both groups. In upstream group, this coverage is greater for pairs than for species singletons above 0.6. Downstream station group covers were almost identical for characteristic species pairs and singletons. Coverage of characteristic species according to season: Seasonal coverage by characteristic species is presented in Figure 4. For each season, it compares singletons and pairs of characteristic species. In fact, the cover is much higher during the rainy season than the dry season; it remained maximal (100%) and decreases only beyond a specificity threshold of 0.8. On the other hand, in the dry season, it decreased starting with a specificity of 0.5. The coverage rate was almost identical for both characteristic species pairs and the singletons. However, the coverage seemed to decrease faster in dry season (starting with a specificity of 0.8) than in rainy season. Discussions This study on the identification of zooplankton species characteristic of the Kinyankonge River basin provides a diversity of knowledge on the spatial and seasonal distribution of these species. The use of the indicator value for zooplankton species in the Kinyankonge River basin has made it possible to develop a list of the most significant species for each station, group of stations and season. Singletons and/or pairs of characteristic species were found mostly at stations located in the upstream part of Kinyankonge River. Thus, L. luna, L. bulla, and Alonella sp. were identified as characteristic of the first station (S1) which receives domestic discharges. Likewise, P. vulgaris, B. quadridentatus, B. patulus and Philodina sp. were identified as characteristic of the second station (S2) located into an irrigation channel receiving both agricultural and domestic discharges. Only K. tecta was characteristic of the third station (S3), enriched with suspended matter coming from sand operations. These aforementioned species Table 3. Continued. Seasons Species A B stat P-value Sig. Dry Pairs Brach_ang+Hexa_sp 0.75 0.24 0.43 0.013 * Brach_caly+Hexa_sp 0.75 0.24 0.43 0.013 * Hexa_sp+Naup 0.75 0.24 0.43 0.013 * Fili_sp+Hexa_sp 0.85 0.21 0.42 0.005 ** Brach_caly+Brach_quad 0.85 0.21 0.42 0.934 ns Brach_caly+Cepha_gib 0.66 0.27 0.42 0.953 ns Hexa_sp+Moin_sp 0.96 0.18 0.42 0.001 *** Brach_ang+Brach_pli 0.82 0.21 0.42 0.026 * Hexa_sp+Leca_lu 0.96 0.18 0.42 0.007 ** Hexa_sp+Poly_vul 0.95 0.18 0.42 0.006 ** Hexa_sp+Leca_bul 0.93 0.18 0.41 0.012 * Aspl_sp+Naup 0.92 0.18 0.41 0.923 ns Hexa_sp+Rota_sp 0.91 0.18 0.41 0.012 * Cepha_gib+Hexa_sp 0.96 0.15 0.38 0.01 ** Aspl_sp+Brach_caly 0.79 0.18 0.38 0.845 ns Hexa_sp+Trop_sp 0.92 0.15 0.37 0.006 ** Aspl_pri+Micro_sp 0.80 0.15 0.35 0.74 ns Kera_qua 1.00 0.12 0.35 0.008 ** Brach_bid+Kera_qua 1.00 0.12 0.35 0.008 ** Kera_qua+Leca_bul 1.00 0.12 0.35 0.008 ** Kera_qua+Naup 1.00 0.12 0.35 0.008 ** Kera_qua+Trop_sp 1.00 0.12 0.35 0.008 ** A= specificity, B=fidelity, P-value=probability, Sig=level of significance, code of significance: 0.001***; 0.01*; 0.05* 81 Int. J. Aquat. Biol. (2019) 7(2): 71-84 establish themselves in waters characterized by high dissolved oxygen level and high transparency (Buhungu et al., 2018). For downstream stations, only station S5, which receives highly organic and mineralized effluents from wastewater treatment plant, was characterized by B. calyciflorus, B. angularis, F. terminalis, Microcyclops sp. and Filina sp. These species are characteristic of eutrophication environments (Baloch et al., 2005). Furthermore, the combination of stations revealed Figure 2. Coverage rates of characteristic species stations. Figure 3. Coverage rates of characteristic species according to station groups. 82 Buhungu et al./ Identification of characteristic zooplankton species in the Kinyankonge River basin, Burundi that 5 species (L. luna, L. bulla, P. vulgaris, B. quadridentatus and B. patulus) characterized the upstream stations, while 3 species (B. calyciflorus, B. angularis and Tropocyclops sp.) characterized downstream stations which waters were polluted by organic matter (Buhungu et al., 2017, 2018). In addition, the analysis of the indicator value for B. calyciflorus and B. angularis revealed that these species are pollutant-resistant. These results confirm those of Starling (2000) which showed that zooplankton species richness decreases with eutrophication degree in rivers and lakes. Similar results were found by Pedrozo and Rocha (2005) showing tolerance of B. calyciflorus and B. angularis to organic pollution and confirming several rotifers belonging to genera Brachionus, Keratella and Fillina are characteristic of organic-enriched environments (Isumbisho et al., 2006; Moshood, 2009; Ahmad et al., 2011). It is important to notice that rotifers were the most abundant zooplankton species identified in this study, in both rainy and dry season, in upstream as well as downstream stations. They were distributed according to downstream-upstream gradient since much more characteristic species were recorded at upstream. This abundance of rotifers species can be justified by their opportunistic nature, giving them the ability to better withstand changes of environmental conditions and of the availability of food resources (Dumont, 1977; Matsumura-Tundisi et al., 1990; Zébazé et al., 2004; Bonecker et al., 2007). Moreover, the river waters were characterized by singletons of rotifer species (L. bulla, A. priodonta, B. bidentatus and A. fissa) only during the dry season in which they were abundant. This may be due to the decreasing of water flow, creating thus favorable conditions for zooplankton egg-laying and hatching. In fact, in a river, the permanent renewal of the water does not favor the abundance of zooplankton (Ouattara et al., 2001). A strong water current enhance turbidity which, by decreasing light penetration into the water, reduces the production of phytoplankton organisms and, thereby, limits the development of their predators which are zooplanktonic organisms (Ouattara et al., 2001, 2007). On the other hand, season coverage seemed to decrease faster in the dry season than in the rainy season. This can be due to the fact that there are no other dry season characteristic species and the probability of finding it is low or even null (Walther and Moore, 2005). Conclusion This study highlighted zooplankton species that significantly characterized the sampling stations in the Kinyankonge River basin. The indicator species analysis method has identified the species that characterize each station, each group of stations, as well as seasons. It also pointed out the characteristic species favoured by dry season. Their absence in the mentioned season could be due to the environment disturbance by human activities. This study provides therefore important information for future researches Figure 4. Seasonal coverage rates for characteristic species. 83 Int. J. Aquat. Biol. (2019) 7(2): 71-84 about the specific composition of zooplankton at a given station and at a given time. Acknowledgements The authors thank the Government of Burundi for its scholarship and internship program which funded this research. References Ahangar I.A., Mir M.F., Saksena D.N., Ahangar M.A. (2012). 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