Trophic relationships in the recently impounded Bagré reservoir in Burkina Faso

Ecological Modelling 191 (2006) 243–259

Trophic relationships in the recently impounded Bagr´e reservoir in Burkina Faso Maria Concepcion Villanueva a,∗ , Maxime Ouedraogo b , Jacques Moreau a,b b

a INP/ENSAT BP 32607 Auzeville Tolosane, 31 326 Castanet Tolosan, France Maˆıtrise d’Ouvrage de Bagr´e SOCREGE 01 BP Ouagadougou 01, Burkina Faso

Received 25 September 2004; received in revised form 22 April 2005; accepted 29 April 2005 Available online 2 August 2005

Abstract The trophic dynamics of Bagr´e reservoir which has been recently impounded in Burkina Faso was based on the data collected during 1997–1998 period using the Ecopath model and software. Total fish biomass is 22.63 t km−2 and mainly represents trophic levels (TLs) 2 and 3. The trophic food chain is relatively long and the overall transfer efficiency is quite low. Grazing foodweb based on primary producers is prominent in the reservoir ecosystem and detritus plays a less significant role. Seasonal and long-term variations in water quality have significant influences on the lower TLs clearly showing a bottom-up functioning of the ecosystem. Environmental degradations, such as siltation occurring in the lake, suggest possible risks in limiting ecosystem productivity. © 2005 Elsevier B.V. All rights reserved. Keywords: African reservoirs; Ecopath; Reservoir fisheries; Trophic networks

1. Introduction The Bagr´e reservoir in Burkina Faso was initially constructed to reinforce irrigation and alleviate water shortages aside from providing hydroelectricity. The fisheries production is also important in this artificial ecosystem. Reservoirs are characterized by ecosystem instability due to changes in the general status from riverine to lacustrine conditions, eutrophication due ∗

Corresponding author. E-mail addresses: [email protected] (M.C. Villanueva), [email protected] (M. Ouedraogo), [email protected] (J. Moreau). 0304-3800/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolmodel.2005.04.031

to the decomposition of important quantities of submerged plant material, evolution of the composition of the fish community, development of fishing activity. Multiple uses of reservoir resource also bring about changes in the trophic status of the ecosystem. For effective fisheries management in reservoirs suitable predictive models are needed and his has been the recognized by the Department of Fisheries of Burkina Faso when the Bagr´e dam was closed in June 1994. The “Bagr´e Reservoir Fisheries Development Project” was, therefore, carried out in order to assess the potential significance of the reservoir for sustainable exploitation of fishery resources.

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Fig. 1. General map: location of Bagr´e reservoir in Burkina Faso.

Multispecies approaches such as trophic modeling are shown to be useful to assess the fisheries of African and Asian reservoirs and such information is found in small sahelian reservoirs (Baijot et al., 1994) Lake Kariba (Moreau, 1997) in Africa as well as Parakrama Samudra, Sri Lanka (Moreau et al., 2001; Villanueva et al., in press) and Ubolratana reservoir, Thailand (Villanueva et al., in press). This paper aims to describe the trophic structures and flow of Bagr´e reservoir. Focus is attributed to quantitative modeling of this ecosystem to define current community trophodynamic linkages. It is expected that this ecosystem approach will allow to assess the impacts of environmental changes and degradation as well as increase of exploitation on the structure and ecology of the aquatic resources mainly on fish population survivorship, productivity and yields, towards the promotion of sustainable resources management (Walters et al., 1997).

1.1. The Bagr´e reservoir (Fig. 1) The Bagr´e reservoir (latitude 10◦ 45 N, longitude altitude 212 m above sea level. and area of approximately 150 km2 ) is a large shallow (average depth at maximum water level 20 m) reservoir. It is located in a large valley about 150 km from Ouagadougou (the capital city of Burkina Faso) and was created in 1994 by damming the Nakambe River, in the South East of the capital city. The minimum annual water level is about 196 m above sea level. The shoreline development is very high, resulting in a large proportion of the reservoir with less than 3 m depth, where the accumulation of dead trees occurs and limits possibilities of using mobile fishing gears. The dam was left closed for 2 years (1994–1995) after its construction to allow the water level to reach its equilibrium. The total hydroelectric capacity is 16 MW. With regards to the fishing activity, commercial fishing was pro35◦ 20 E,

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hibited for 1 year after the damming and had only been accessible for this fishing activity after its official inaugural ceremony early 1995. The total area varies between 100 and 196 km2 and the volume between 0.88 and 1.7 billions m3 . The average annual inflow from the drainage basin is 1.2 billions m3 . The maximum flow rate at the dam is 1500 m3 s−1 . The lake has an important littoral shallow area partly colonized by macrophytes. The water is alkaline (pH from 6.8 to 8), with a limited mineral content (conductivity is 120 to 143 υS cm−1 . The transparency is low (50–120 cm as measured with the Secchi disk). In this paper, an attempt is made to quantify trophic relationships of this reservoir as they were existing at the end of the 90 s and to assess the possible changes in the trophic structure of this ecosystem under possible seasonal and long-term variations in the water quality. 2. Materials and methods 2.1. The Ecopath software To construct the trophic interactions structure occurring in the ecosystem, we used the steady-state simulation program, Ecopath, developed by Christensen et al. (2000) based on the original model by Polovina (1984) and Polovina and Ow (1985). In structuring the model, the various organisms inhabiting the ecosystem have to be grouped into boxes according to their common physical habitat, similar food preferences and life history characteristics (Yodzis and Winemiller, 1999). The model estimates annual mean biomasses, production and consumption (or ecotrophic efficiency) and flow to the detritus pool of every box considered in the ecosystem. An equilibrium condition is assumed for the period considered where group inputs is equivalent to their outputs. Input data were standardized and units expressed as t km−2 . To establish an equilibrium condition, a system of biomass budget equation is determined for each group considered as: Production-all predation on each group-non-predatory mortality − allexports = 0. Ecopath expresses each term in a budget equation as a linear function of the mean biomass and results into

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a system of simultaneous equations expressed as: n

Bi


Q P P = Bj DCji + Bi (1 − EEi ) + EXi (1) Bi Bj Bi j=1

where Bi is the biomass of the group i; P/Bi is its production rate (assumed equal to the total mortality, Z) as defined in fisheries sciences (Allen, 1971; L´evˆeque et al., 1977); Bj the biomass of any predator j of the prey i; Q/Bj the food consumption rate of j and is a parameter that expresses food consumption of an age-structured fish population relative to its biomass considering the fact that juveniles are numerous compared to adults and consume much more food (compared to their weight) as documented by Pauly (1986) and Palomares and Pauly (1998); DCji is the fraction of i in the diet of j, expressed in percentage of weight; EEi its ecotrophic efficiency which is the proportion of the ecological production consumed by predators and/or exported (Ricker, 1969) and EXi is the export (i.e. catch) for any group (Christensen et al., 2000). Ecopath has additional routines namely, Ecosim and Ecospace (Walters et al., 1997, 1999). Apart from performing usual mass-balanced models by computing unknown parameters in every equation such as (1), these are simulation routines that provide temporal descriptions of the possible trends that might occur in the ecosystem under various fishing strategies or other possible changes in the ecosystem, as well as spatial trends of its trophic dynamics. Only Ecosim was used in this study in order to assess the possible influence of a decrease of primary production related to increasing siltation in the reservoir. 2.2. Designing the present Ecopath model for Bagr´e reservoir Because of their current and potential future importance for the reservoir management, the following groups were considered: Top predators: fish-eating birds, Crocodiles, Lates niloticus (Linnaeus), Hydrocynus spp., large catfish: Bagrus spp. and Clarias gariepinus (Burchell), as well as Gymnarchus niloticus (Cuvier). It should be noted that the Lates population has been splitted into two groups, juveniles and adults, as suggested by Christensen et al. (2000) when cannibalism occurs as it

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Table 1 Annual catch (t km−2 year−1 ) per specific gear targeting respective fish groups in Lake Bagr´e Group name

Long lines

Adult Lates niloticus Juvenile Lates niloticus Bagrus/Clarias spp Hydrocynus spp. Synodontis spp. Chrysichthys spp. Mormyrids Gymnarchus sp. Auchenoglanis sp. Other zoophagous fishes Alestes spp. Cyprinids O. niloticus S. galilaeus T. zillii

0.100

Total

0.100

Sport fishing

Littoral lines

Littoral nets

0.033 0.040 0.160 0.840 3.360 0.550 5.083

8.076

0.100 1.240 0.017 0.840 0.080 0.256 0.060 0.400

0.017

is the case here and which is similar to what has already been documented by Villanueva and Moreau (2001) in the Lake Victoria (East Africa). Secondary main consumers: Auchenoglanis occidentalis (Valenciennes), Mormyrids: mostly Mormyrus rume (Valenciennes), Chrysichthys nigrodigitatus (Lac´ep`ede), Synodontids (Synodontis schall (Bloch & Schneider) and Hemisynodontis membranaceus (Geoffroy Saint-Hilaire), Alestes spp.: Alestes baremoze (De Joannis) and Brycinus (Alestes) nurse (R¨uppell), “small zoophagous” fish mostly Schilbe spp. contributing to about 0.4% of the actual catch (see below). Primary consumers: Cyprinids (mostly Labeo spp.), Oreochromis niloticus (Linnaeus), Sarotherodon galilaeus (Linnaeus) and Tilapia zillii (Gervais). The following non-fish groups were also considered: zooplankton, zoobenthos, aquatic insects and their larvae, phytoplankton, benthic algae, macrophytes, and detritus. Zooplankton and phytoplankton were splitted into two groups: pelagic and littoral, due to the differential distribution of the fish groups within the reservoir. Other parameters considered for the present Ecopath model have been obtained through the following sources. 2.2.1. The actual catch The estimate of fish production for 1997 and 1998 were obtained from the Department of Fisheries of Burkina Faso. They were gathered with the assistance

2.876

Total 0.100 0.100 1.240 0.017 0.840 0.080 0.256 0.060 0.400 0.033 0.040 0.160 0.840 3.360 0.550

of fishing communities (Ouedraogo, 1999). Several fishing methods are used and their respective contribution to the total catch (in t km−2 year−1 ) is summarized in Table 1. 2.2.2. The production rate For predatory birds and crocodiles, P/B values calculated by Moreau (1997) for Lake Kariba was considered. Data utilized for most of the fish groups come from monthly samples collected from August 1997 to July 1998. Length–frequency data were analyzed using the ELEFAN procedure available in FiSAT II (Gayanilo et al., 2002) in order to estimate asymptotic length (L∞ ) and the von Bertalanffy growth coefficient (K) for each fish species/group analyzed. The instantaneous Z was then estimated based on length-converted catch curves (Gayanilo et al., 2002). According to Allen (1971), under a steady-state condition, the P/B is equal to Z. The instantaneous natural mortality coefficient, M, was computed using the predictive model of Pauly (1980). The fishing mortality coefficient (F) is the difference of Z and M for each group. The results are summarized in Table 2. For juveniles Lates, P/B was estimated based on field samples from fishes less than 2.5 years old based on the growth parameters of adults. For Gymnarchus sp., P/B was obtained using the method of L´evˆeque et al. (1977) based on the species’ expected longevity.

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Table 2 Demographical and biological features for the fish populations: L∞ is the asymptotic total length and K is the von Bertalanffy growth function (VBGF) coefficient, M is the natural mortality, F is the fishing mortality, W∞ is the asymptotic weight (g), AR is the aspect ratio as inferred by Palomares and Pauly (1998) Species/group

L∞ (cm)

K (year−1)

M (year−1 )

F (year−1 )

W∞ (g)

AR

Adult Lates niloticus Bagrus/Clarias spp. Hydrocynus spp. Synodontis spp. Chrysichthys spp. Mormyrids Auchenoglanis sp. Small zoophagous fishes Alestes spp. Labeo coubie O. niloticus S. galilaeus T. zillii

105 53.0 76 33.0 23.5 38.0 38.5 26.0 32.5 45.0 36.5 34.0 22.5

0.26 0.28 0.25 0.45 0.80 0.38 0.45 0.50 0.64 0.40 0.40 0.48 0.45

0.52 0.65 NA 1.00 1.61 0.86 0.95 1.08 1.29 0.84 0.93 1.04 1.17

0.23 0.25 NA 0.55 0.26 0.13 0.25 0.63 0.35 0.16 0.27 0.65 0.68

20000 1500 4000 860 267 415 703 180 117 2670 870 511 204

1.32 0.90 2.20 2.20 1.90 1.80 1.80 2.00 2.20 2.33 1.32 1.40 1.37

For zooplankton, the P/B values considered were based from Mavuti et al. (1996) which is similar to observations of various authors for Cladocera and Copepods (Irvine and Waya, 1999; Sarvala et al., 1999) which were dominating the zooplankton community observed during the sampling period (M. Ouedraogo, SOCREGE, personal data). The phytoplankton primary production is from Thomas and Ratcliffe (1973) which is similar to recent observations by Thomas et al., (2000) for shallow water bodies in Sahelian region. A similar value was noted in Lake Chad (Talling and Lemoalle, 1998). The contribution of benthic algae to the primary production is about 30% in areas of less than 3 m deep. Light penetrates no more than 2.5 m while the maximum transparency is 1.2 m as measured using a Secchi disk. Thomas et al. (2000) estimated a chlorophyll-a content of 25 mg m−2 which is equivalent to 8.75 g fw m−2 . This figure was incorporated into the model and P/B was computed consequently.

and S. galilaeus, daily food consumptions based on a 24-h cycle observation of stomach contents were computed with the MAXIMs software (Jarre et al., 1991). For other groups, we refer the most probable GE value as suggested by Christensen et al. (2000).

2.2.3. The consumption rate For the fish groups mentioned in Table 2, the Q/B values were obtained by using the predictive model of Palomares and Pauly (1998) which involves the asymptotic weight calculated from the length–weight relationship established from samples collected. The aspect ratio (AR) is based on FISHBASE (Froese and Pauly, 2005). It should be noted that for O. niloticus

2.2.5. The ecotrophic efficiency EE expresses the fraction the production of each group utilized in the ecosystem. It is computed by the software when the biomass is known. It has been fixed to 0.98 for juvenile L. niloticus due to its high contribution in the catch and cannibalism. Otherwise, they enter the adult pool. For Hydrocynus spp. and Gymnarchus sp., it was fixed at a rather low value due to

2.2.4. The diet composition Stomach content analyses for some fish species were carried out within the present project. However, most of the data are based from indications of Lauzanne (1976, 1988) and Baijot et al. (1994). For predatory fishes, the contribution of various fish prey groups has been established as a function of their relative importance in terms of biomass, contributions to the fisheries and their preferred habitat (littoral or pelagic area). For other groups, we refer to various models from Christensen and Pauly (1993) and from Fishbase (Froese and Pauly, 2005). Appendix A shows the relative contribution of each group as prey for the respective group predating on them.

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expected limited exploitation and predation (Ricker, 1969; Christensen and Pauly, 1993; Christensen et al., 2000). A high value (0.9) was considered for insects and zoobenthos due to the expected importance of these groups as food of several fish populations. For benthic algae and macrophytes EE values were set to 0.80 and 0.7, respectively, as they have a limited contribution to the trophic food web. 2.2.6. The biomass The biomass of piscivorous birds was obtained by S. Le Chartier (SOCREGE, pers. data) and an estimated value of crocodile biomass by Games and Moreau (1997) in a protected area was used. For fish groups for which both M and F were known, the B was computed from the actual catch (Y) and F ratio. Zooplankton biomass was adapted from Aka et al. (2000). It is within the range of values recorded from Lake Chad by Talling and Lemoalle (1998). 2.3. Requirements in running the Ecosim simulation In order to run Ecosim, juveniles and adult L. niloticus were segregated according to their size. The maximum size of a juvenile was assumed to be 40 cm (total length) based on experimental fishing by long lines and due to an assessment of reduced predation by the adults upon reaching this size (Ogari and Dadzie, 1988). Significant differences in feeding habits and in spatial distribution are observed as the juveniles are more concentrated along the littoral area. Specific P/B and Q/B were estimated for the adult and juveniles Lates as in Lake Victoria. (Villanueva and Moreau, 2001). The age of transition from juvenile to adult is about 3 years. The average transition ratio from juvenile to adult is 4. This value is achieved by dividing the maximum weight of a juvenile (1 kg) to the average weight of an adult (4 kg) as indicated by Walters et al. (1997) for running an Ecosim simulation. 2.4. Physical forcing of phytoplankton biomass The issue on how abiotic processes mould the structure and organization of aquatic communities must be considered when measuring the bottomup effects of siltation. Ecosim allows assessment of possible influence/s of varying physical conditions

to biologic communities through temporal dynamic simulations. For this study, we assumed that seasonal siltation (i.e. drainage of water from the catchment area and agricultural zone during the rainy season) and longterm degradations (i.e. deforestation of catchment area) have negative implications on phytoplankton and benthic algae densities. This assumption is consistent with observations of Cronberg (1989, 1997) that the biomass of phytoplankton varies due to nutrient loadings in the Lake Kariba. In order to drive our ecosystem model from the bottom-up, the biomass of the phytoplankton group had been intentionally decreased. A low value of vulnerability index (0.2) within a 6-year period was fixed for the siltation-scenario.

3. Results The impact on the final results of the possible variability of the input parameters was investigated using the Ecoranger sub-routine (Christensen et al., 2000). Diet composition of some groups was modified, considering that these were of the highest uncertainty compared to other input variables, to achieve an EE less than 1. Results showed that the model is rather tightlyfitted as the simulation gave allocated values which have no remarkable difference from original inputs. A pedigree index of 0.68 was obtained which conforms to the gauge of overall quality discussed by Christensen et al. (2000). The original inputs were further validated by the consistency of gross efficiency (GE) or P/Q values which were within the expected ranges by reference to the diet composition. 3.1. Trophic relationships of groups considered Estimates of biomass, ecotrophic efficiencies, gross conversion rates, food consumption and trophic level (TL) obtained from the input parameters for each group are presented in Table 3. The trophic relationships are summarized in Fig. 2. The total fish biomass in Bagr´e is about 22.63 t km−2 which is also the mean for the whole lake. This is in agreement with the biomass range recorded in Lake Kainji (Nigeria) during its earlier stages after impoundment (Kapetsky and Petr, 1984). The biomass of the littoral fish is similar

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Table 3 Results of the basic parameterization in Ecopath (values in bold estimated from data input for each group considered) No.

Group name

TL

B (t km−2 )

P/B (year−1 )

Q/B (year−1 )

EE

P/Q

FD

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 20 21 22 23 24 25

Fish-eating birds Crocodiles Adult Lates niloticus Juvenile Lates niloticus Bagrus/Clarias spp. Hydrocynus spp. Synodontis spp. Chrysichthys spp. Mormyrids Gymnarchus sp. Auchenoglanis Other zoophagous fishes Brycinus spp. Cyprinids O. niloticus S. galilaeus T. zillii Pelagic zooplankton Littoral zooplankton Insects and larvae Zoobenthos Pelagic Phytoplankton Littoral Phytoplankton Benthic algae Macrophytes Detritus

3.50 3.51 3.52 3.09 3.16 3.29 3.04 2.89 2.9 3.13 2.73 3.02 2.42 2.02 2.03 2.05 2.16 2.11 2.05 2.08 2.03 1.00 1.00 1.00 1.00 1.00

0.02 0.10 0.37 0.44 4.96 0.39 1.53 0.31 1.97 0.75 1.64 0.05 0.12 1.01 3.11 5.17 0.81 1.50 1.50 3.84 9.13 2.20 2.25 8.75 5.44 5.00

0.30 0.25 0.75 2.25 0.90 1.80 1.55 1.87 0.97 1.00 1.20 1.71 1.64 1.00 1.20 1.69 1.85 30.00 30.00 4.00 7.00 180.00 180.00 38.00 5.00 –

47.20 0.80 3.00 7.90 5.25 9.25 11.23 13.29 8.03 6.17 10.16 14.21 16.13 27.52 29.13 35.90 41.80 120.0 120.0 30.00 35.00 – – – – –

0 0 0.482 0.98 0.818 0.750 0.954 0.863 0.955 0.850 0.907 0.956 0.913 0.944 0.928 0.926 0.956 0.406 0.925 0.900 0.900 0.480 0.787 0.800 0.700 0.448

0.006 0.313 0.250 0.329 0.171 0.195 0.138 0.141 0.108 0.162 0.118 0.120 0.102 0.036 0.040 0.047 0.044 0.250 0.250 0.133 0.200 – – – – –

0.216 0.043 0.366 0.712 6.021 0.888 3.539 0.895 3.251 1.040 3.516 0.158 0.404 8.362 28.025 56.331 10.198 80.723 65.369 37.401 91.397 205.99 94.445 84.617 8.158

TL is the trophic level, B is biomass, P/B is the production rate, Q/B is the consumption rate, EE is the ecotrophic efficiency, P/Q is the production/consumption ratio or gross efficiency (GE) and FD is the flow to detritus.

to what was recorded in Lake Kariba (Moreau, 1997). An EE value of 0.00 was calculated for predatory birds and crocodiles which have no predators and are not hunted. The computed EE is high for most fish groups and often observed higher than 0.9. A particularly low value (0.482) is computed for Adult Lates which is a normal feature for large top predators (Christensen et al., 2000). Lower EE values were estimated for pelagic zooplankton and phytoplankton (0.406 and 0.480, respectively) than for plankton groups in the littoral zone (0.925 and 0.787). This is acceptable due to the absence of pelagic planktophagous fish species that leaves a major portion of the pelagic plankton under utilized. This has been observed in other West African reservoirs such as Lake Kainji and Lake Volta (Kapetsky and Petr, 1984). An EE of 0.448 was obtained for the detritus group

which signifies that this resource is not highly exploited and that the food web is mainly based on primary producers. Globally, P/B ratios are higher for organisms in lower TLs, such as insects, zoobenthos and zooplankton, largely feeding on plant and decaying material and serving as principal links between primary producers and higher consumers. Most fish species showed a M/K ratio higher than 1 which implies a natural mortalitydominated population. This might be in connection with the infancy of the lake and still developing fisheries as well as the relatively high biomass of predators. A wide range of P/Qs of fish groups is observed. Most groups are in the range of zoophagous (0.10–0.19). Higher P/Qs in some groups are associated with their piscivorous feeding habits, even crocodiles. The gross efficiency of juveniles L. niloticus is higher than for adults; a trend already anticipated as a

250 M.C. Villanueva et al. / Ecological Modelling 191 (2006) 243–259 Fig. 2. The Ecopath model of Lake Bagr´e for 1997–1998, in which adult and juvenile Lates niloticus have been separated and indicating the biomass of each group and the major flows connecting them. For clarity, less important flows are omitted as are back flows to the detritus box. The horizontal axis of symmetry of each box is aligned with the functional TL of this box. The numbered value of a TL is a fractional because it depends on the diet composition of this group and on the TLs of its preys (Christensen and Pauly, 1993). Actual catch is displayed.

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general rule by Pauly (1986) and noticed by Villanueva and Moreau (2001). 3.2. Trophic structure analysis Top predators are fish-eating birds, crocodiles and adult Lates (TL = 3.5) followed by Hydrocynus spp. (TL = 3.3). Among other groups, only juvenile Lates, large catfishes and Gymnarchus reach TLs more than 3. Other zoophagous groups, i.e. secondary consumers, are at TLs between 2.4 and 2.9. Ratios of respiration to assimilation (R/A) and production to respiration (P/R) for all group were less than 1. This indicates that the ecosystem is still in the immature stages (Odum, 1969). The mean TL of catches is 2.45 due to the relative importance of primary consumers (Tables 1 and 3) with a low gross efficiency (actual catch/primary production) of about 0.007 when compared to Lake Victoria (Moreau et al., 1993; Villanueva and Moreau, 2001) and other tropical inland water ecosystems (Christensen and Pauly, 1993). According to Lindeman (1942) TL segregation into integers using the trophic aggregation routine of Ecopath showed that most of the fish biomass and catch take place at TL2 or more as summarized on Table 4. 3.3. Trophic network analysis The ecosystem is phytoplankton-based as 63% of the total flow comes from primary producers and only 37% are originating from detritus, a feature of relevance in a deep water body (Christensen and Pauly, 1993) and in recently impounded reservoirs (Kapetsky and Petr, 1984; Talling and Lemoalle, 1998). The highest flow to detritus in the ecosystem was observed from

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the autotrophs, 385.52 t km−2 year−1 , whereas most primary production is incorporated into the food web mostly by zooplankton and zoobenthos. These features are in relationship with the relative importance of riverine zoophagous fish in a newly impounded reservoir. The transfer efficiency is high at any TL. It might be due to the high level of utilization of most groups either by predation or fishery. 3.4. Trophic impact routine The mixed trophic impact routine of Ecopath (Ulanowitcz and Puccia, 1990) which was designed to assess possible influence/s of increasing abundance of all groups by 10% to each considered group was used here. Results showed that most groups have negligible impact on the biomass of other groups except on their respective preys. This observation is particularly true for Bagrus and Clarias spp. (Fig. 3). This might be due to the limited specialization of most zoophagous groups. Any increase in biomass of plankton, benthic and macrophytes groups, however, would have a direct positive influence to their direct predators in the ecosystem. This means that a limited increase of the primary producers during the filling-up phase of the reservoir might have contributed to the development of tilapiine populations and, more generally, of lacustrine primary consumers. The mixed trophic impact routine provided useful descriptions of how short-term variations can affect the whole ecosystem. One limitation, however, is its inability to predict long-term consequences for such varying interactions between the groups, possibly since the diet composition matrix remains unchanged even if densities of each group considered in the ecosystem varies (Christensen and Pauly, 1993).

Table 4 Distribution among the various trophic levels of catch and fish biomass in Lake Bagr´e

3.5. The possible evolution of the ecosystem as assessed with Ecosim

Trophic level (TL)

Catch (t km−2 year−1 )

Contribution of each TL to catch

7 6 5 4 3 2

0 0.005 0.045 0.407 2.633 4.993

0.06 0.56 5.07 32.78 62.15

The forcing functions used are displayed on Figs. 4 and 5. After several iterations, simulations made showed that the effect of these environmental conditions had to be analyzed by reference to the TL of each group. Slight deviations of this index from the default value of 0.3 suggested by Christensen et al. (2000) were made (0.2–0.4) without clearly different results.

Biomass (t km−2 )

Contribution of each TL to B (%)

0.002 0.020 0.195 1.665 9.613 11.134

0.01 0.09 0.86 7.36 42.48 49.20

252 M.C. Villanueva et al. / Ecological Modelling 191 (2006) 243–259 Fig. 3. The mixed trophic impacts in Lake Bagr´e ecosystem. Impact of an increase (by 10%) in the biomass of the groups on the left on the group mentioned horizontally. Positive impact are shown above the base line, negative impacts below.

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Fig. 4. The seasonal trend of variations of the abundance of primary producers and consequences on some groups (simulated over 4 years). Ordinate: primary production/original primary production on January.

Results showed that groups belonging to the lower TLs are strongly influenced by seasonal variations of primary producers abundance. Parallel oscillating biomasses were observed for both zooplankton and zoobenthos as a consequence of oscillating phytoplankton abundance. Fish populations in TLs 2, 3, 4 (Fig. 6) showed differing magnitudes of oscillating abundance. The magnitude of these oscillations is limited for highest TLs.

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Fig. 5. The long-term variation (over 6 years) of the abundance of primary producers. Primary production /original primary production at the beginning of the scenario to 60% at the end of the scenario.

The long-term scenario of primary production abundance (a total decrease of 35% over 6 years as simulated here) shows a clear decrease of zooplankton and zoobenthos abundances and any other groups feeding directly on them as summarized in Table 5. Other groups are affected at varying degrees and different TLs though to a considerable extent for groups directly feeding on primary producers (see Table 5). Consumption of littoral aquatic vegetation as observed for certain fish species (T. zillii) is an adaptive response to limited food availability. This delays an abrupt decrease

Fig. 6. The seasonal trend of variations of the abundance of primary producers and of some groups of higher TLs (simulated over 4 years).

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Table 5 Example of evolution of biomass (B) and catch (C) of the fish groups after 6 years of decline in primary production abundance by a total of 30% in Lake Bagr´e Original B (t km−2 year−1 )

Group name Adult Lates niloticus Juvenile Lates niloticus Bagrus/Clarias Hydrocynus spp. Synodontis spp. Chrysichthys spp. Mormyrids Gymnarchus sp. Auchenoglanis sp. Other zoophagous Brycinus spp. Cyprinids O. niloticus S. galilaeus T. zillii Total

0.37 0.44 4.96 0.39 1.52 0.31 1.97 0.75 1.64 0.05 0.12 1.00 3.09 5.11 0.81

Final B (t km−2 year−1 ) 0.17 0.206 2.639 0.190 0.738 0.148 1.042 0.411 0.900 0.027 0.076 0.550 1.532 2.627 0.707

22.50

11.96

FB/OB

Original catch (t km−2 year−1 )

Final catch (t km−2 year−1 )

FC/OC

0.46 0.47 0.53 0.49 0.48 0.48 0.53 0.55 0.55 0.50 0.64 0.55 0.50 0.51 0.88

0.10 0.10 1.24 0.02 0.84 0.08 0.26 0.06 0.40 0.03 0.04 0.16 0.84 3.33 0.55

0.05 0.05 0.66 0.01 0.41 0.04 0.13 0.03 0.22 0.02 0.03 0.09 0.41 1.71 0.48

0.46 0.47 0.53 0.49 0.48 0.48 0.53 0.55 0.55 0.50 0.64 0.55 0.50 0.51 0.88

0.64

8.08

4.33

0.54

FB: final biomass; OB: original biomass; FC: final catch; OC: original catch.

in abundance of this species which is also feeding on phytoplankton. Resulting biomass and possible catch for exploited fish groups are summarized in Table 5. The resulting trophic structure of the fish community is shown in Table 6 where contribution of groups belonging to TL2 is relatively important. A detailed analysis of the Ecosim run shows that the current trophic dynamic existing in the ecosystem is stable due to existing plasticity of food preference by each group. This versatility in food preferences allows most groups to exploit other aquatic resources as food despite cases where usual resources exploited become insufficient.

Table 6 Distribution among the various TLs of catch and fish biomass in Lake Bagr´e after 6 years and a reduction of the abundance of primary producers of 30% Trophic level

Catch (t km−2 year−1 )

Biomass (t km−2 )

Contribution (%) of each TL to the fish biomass

6 5 4 3 2

0.001 0.033 0.140 1.290 2.865

0.002 0.033 0.576 3.675 7.677

0.017 0.276 4.815 30.719 64.173

4. Discussion Asian and African continents are rich in inland waters (De Silva, 1996). In most developing countries, we can observe that previous management measures (i.e. dam construction, species introduction, etc.) were done without prior impact assessment on how these procedures would affect the ecosystem later on (Furse et al., 1979b; Pitcher, 1995; De Silva, 1996; Nicholson, 1998). This was the case in the Ubolratana reservoir in Thailand (De Iong and Van Zon, 1993; Baluyut, 1999), Lake Kariba in Zambia and Zimbabwe (Moreau, 1997) or Lake Victoria in East Africa (Kudhonania and Chitamwebwa, 1995) to just cite a few. It is significant to know that human development-related management plans are usually not “pro-ecologic” but aim to improve the economy of these regions. Ecologically sustainable water resources management plans are needed to insure the integrity of these natural resources (Christensen and Pauly, 1997; Richter et al., 2003). The construction of the Bagr´e dam was intended to alleviate both the water supply and the socio-economic conditions in the catchment area and to contribute to the water regulation and minimized depression (SOCREGE, 1999). This was also the case in other ecosystems such as Lake Chilwa (Malawi) where management plans have opted to dam construction to

M.C. Villanueva et al. / Ecological Modelling 191 (2006) 243–259

minimize significant floods and recessions (Chavula, 2000). Artificial aquatic ecosystems are unstable during immature stages due to possible modification in fishing activities, hydrobiological pattern (i.e. adaptation of lacustrine species and upstream migrations of riverine populations) aside from water quality modifications (Kapetsky and Petr, 1984; Karenge and Kolding, 1995a). In such ecosystems, it is important to consider other environmental issues, which have been outlined in the Lake Bagr´e management plan (SOCREGE, 1999). Another important factor to consider is how such changes would affect the aquatic living resources utilizing the ecosystem. Piet (1998) noted the significance of studying the effects of perturbations that can effect modifications in community structures as a function of changing resources levels. The complex linkages in the ecological communities, especially pertaining to the prey–predator relationships within groups, make it challenging to predict both the direct and indirect influences and outcomes of the dam construction (Piet and Vijverberg, 1998; Angelini and Agostinho, 2005). According to Christensen and Pauly (1997) and Piet and Vijverberg (1998), it is indeed significant to include an ecosystem perspective approach in managing aquatic resources. The possibility of analyzing the multi-specific effects of dam installations is vital to prevent further and unexpected management problems in the future and to be sure that such management programs will be effective. Species-based responses should be considered as there would be various factors that would contribute to further unpredicted changes such as modifications in the exploitation level, lifehistory characteristics, potential replenishment of surrounding areas and changes in other species abundance. This entails the capability of fish species to adapt and to persist in these fluctuating ecosystems. Some fish species like Barbus and Clarias are capable of very rapid recovery in newly inundated conditions (Furse et al., 1979a). Kapetsky and Petr (1984) and Talling and Lemoalle (1998) observed from their studies that the primary producers group has a “positive effect” in all other biological groups, especially in recently impounded reservoirs. This, however, do not coincide with observations made by Gamito and Erzini (2005) in the Ria Formosa reservoir (Portugal) where most groups in higher TLs

255

Table 7 Transfer efficiency at various TLs as computed by Ecopath showing the contribution of detritus and primary producers to the trophic network Source

Producers Detritus All flows

TL II

III

IV

V

VI

VII

VIII

11.5 14.5 12.4

12.5 11.9 12.3

12.5 13.0 12.7

12.7 13.2 12.9

12.7 13.3 12.9

12.8 13.3 12.9

13.0

Proportion of total flow originating from detritus: 0.37; transfer efficiencies (calculated as geometric mean for TL II-IV): 12.5; from primary producers: 12.1%; from detritus: 13.1%.

respond positively to an increase in detritus biomass. Villanueva et al. (in press) indicated similar observations in Parakrama Samudra reservoir (Sri Lanka). The majority of the biomass concentration in Bagr´e is observed in TLs 1–3 (Table 4). In the case of Ria Formosa and Parakrama samudra, on the other hand, biomass is concentrated mainly in the producers and herbivore/detritivore levels. Transfer efficiencies were higher in this reservoir, >13.0% (Table 7), than in Ria Formosa (from 0.2 to 6.0%) and Parakrama samudra (from 2.0 to 7.4%). (Gamito and Erzini, 2005; Villanueva et al., in press). Low transfer efficiencies in the two latter ecosystems may be attributed to low diversity of predators compared to Bagr´e. The significance of biodiversity in assuring ecosystem stability had already been evoked by Naeem and Li (1997) and Loreau et al. (2001). Angelini and Agostinho (2005) indicated that high species richness of top predators increases redundancy and mediates decline in transfer efficiencies from one discrete TL to another. This, however, did not coincide with previous observations of Paiva et al. (1994) in a Brazilian reservoir where abundance of aggressive invaders and top predators have detrimentally affected the system’s biologic production and fishery. The possible occurrence of the “trophic cascade” effects should be further elaborated where the increase of primary carnivores can outnumber the herbivores and can result in the increase of phytoplankton abundance which can further lead to eutrophication as the water flow becomes regulated in reservoir conditions (Karenge and Kolding, 1995b). Another response can lead to a reverse case of the trophic cascade where the primary carnivores were heavily fished and resulted

256

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into the increase of herbivorous or benthophagous fishes that limits plant and benthic fauna development (Karenge and Kolding, 1995b). Changes in the cascading effect of the primary production are different when considering either a seasonal pattern variation or a long-term variation. As indicated above, the seasonal pattern of abundance variations of any group seems to be directly related to the trophic status of the group considered. Seasonal variations have been observed to considerably affect the individual growth performance and demography of the fish populations (Hagborg and Welcomme, 1977). These indirect effects could not be taken into consideration here. The diet composition, its modifications based on available resources has to be considered and their influence on the results of the simulations has to be investigated in more details. The possible evolution of the fish community of the Bagr´e reservoir will be influenced by varying intensities of fishing effort with various gears currently utilized, though for simplification purposes, this factor was not considered in the present Ecosim runs. Overexploitation can contribute to the decline of predators in reservoirs such as was the case of Ubolratana reservoir (Chookajorn et al., 1994). Based on the observations of Moss (1979) in Lake Chilwa, however, risks due to overfishing in resilient systems are less compared to possible threats due to catchment erosion, siltation and accumulation of pesticides during agriculture ’reclamation’ or perhaps as irrigation reservoirs. Overfishing may not destroy the fishery but accumulation of toxic chemicals could 1 day do so. The dangers of the accumulation of fertilizers or of directly toxic substances have been clearly demonstrated in open basin lakes or reservoirs (Berg and Kautsky, 1996). This danger is far more acute in closed basin lakes, like Lake Chilwa. Lake Chilwa, its fishes and its fishery may have the resilience to overcome the physico-chemical stresses and climate changes and it must be protected against the untimely ravages of man (Furse et al., 1979b). Issues like pollution control, proper farming practices that minimize surface run-off and subsequent silt load into the lake, use of fertilizers on the adjacent cultivation schemes and a tree plantation campaign should be considered in planning of activities in the Lake Bagr´e catchment area in order to protect the water quality and living aquatic resources.

5. Conclusion Ecopath allowed us to comprehend the organization and trophic transfers among biological groups in the Bagr´e reservoir. Some food sources are still clearly underutilized, mainly along the pelagic areas. Groups belonging to the lower TLs are more sensitive to predation changes by higher fish groups showing an ecosystem functioning with the bottom-up effect. Fish-eating birds and crocodiles have a limited impact on the fish community. The system is still in its immature stages (sensu Odum). The fish biomass (223 kg ha−1 ) is similar to what was measured in Lake Kainji, an immature shallow reservoir. A common observation in such ecosystems is the rapid increase in actual catch, even for a large Sahelian reservoir (80 kg ha−1 year−1 ). Ecosim has been useful in incorporating seasonal and prey availability changes in our study. The system showed a high sensitivity to seasonal variations influencing abundance of primary producers. Zooplankton and zoobenthos are consequently affected with some delay. A limited eutrophication was observed to have a possible beneficial effect on the whole food web and trophic structure. An increase of the primary production due to allochtonous input of nutrient from catchment area might contribute to the evolution of the fish community from a riverine to a lacustrine one. Increasing siltation, however, would lead to a decrease of the abundance of all groups and consequently, with differing degrees, on the behavior and availability of these living resources for predation by other groups and/or for the fisheries.

Acknowledgements The authors are grateful to the Department of Fisheries of Burkina Faso for the assistance provided during the implementation of the “Lake Bagr´e Fisheries Development Project” and for the data provided for this contribution. The authors gratefully acknowledge Villy Christensen for valuable comments especially during model construction and validation and two anonymous referees who have collectively improved the quality of this work.

Appendix A. Diet composition of the groups as incorporated into the Ecopath model Prey\predator

1

2

3

0.010 0.040 0.150 0.020 0.100 0.040

0.010 0.040 0.050 0.050 0.100 0.040 0.050

0.020 0.080 0.070 0.050 0.100 0.020 0.050 0.015 0.050 0.005

0.020 0.010 0.050 0.100 0.300 0.050

0.010 0.010 0.040 0.050 0.200 0.050

0.090

4

5

6

0.005 0.030

0.020 0.065 0.020 0.040 0.010 0.020 0.020 0.050

0.030 0.200 0.250 0.050

0.005 0.010 0.025 0.050 0.160 0.030

0.025 0.050 0.010 0.030 0.010 0.050 0.015 0.040 0.001 0.002 0.018 0.030 0.050 0.010

0.005 0.020 0.200 0.200 0.050

0.004 0.010 0.002

0.005 0.003

0.100 0.050 0.500

0.050 0.100 0.400

0.060 0.050 0.150

0.400 0.100 0.420

0.002

0.050

0.110 1.000

0.210 1.000

1.000

0.033 1.000

0.050 0.010 1.000

0.020 1.000

7

8

0.020

0.010

0.010

0.010 0.010

0.100 0.100 0.600

9

10

11

0.030 0.030 0.020 0.010 0.001 0.030 0.020 0.020 0.001 0.005 0.015 0.120 0.295 0.040 0.100 0.350 0.400

0.050 0.005 0.230

0.010

0.020 0.050

0.050

0.030

0.024

0.100

0.100

1.000

1.000

1.000

12

13

14

15

16

17

0.010 0.010

0.030

0.020

0.050 0.050 0.050

18

19

20

21

0.050

0.050 0.010 0.020

0.010

0.750 0.100

0.050 0.300

0.020 0.350

0.020 0.005 0.010 0.010

0.005 0.005 0.015 0.005 0.100 0.100 0.500

0.050

0.050 0.100 0.050 0.100

1.000

1.000

0.050 0.300 0.500

0.350 0.050

0.100

0.030 0.400 0.250 0.220

0.750 0.150

0.025

0.250 0.050 0.250 0.050

0.050 0.800 0.030 0.100

0.100

1.000

1.000

1.000

1.000

0.050

0.020

0.850

0.050

0.140 0.140 0.500 0.070

0.050

0.100

0.570

0.600

1.000

1.000

1.000

1.000

1.000

1.00

M.C. Villanueva et al. / Ecological Modelling 191 (2006) 243–259

Fish-eating birds Crocodiles Adult Lates niloticus Juvenile Lates Bagrus/Clarias spp. Hydrocynus spp. Synodontis spp. Chrysichthys sp. Mormyrids Gymnarchus sp. Auchenoglanis sp. Small zoophagous Alestes spp. Cyprinids O. niloticus S. galilaeus T. zillii Pelagic Zooplankton Littoral Zooplankton Aquatic insects Zoobenthos Pelagic Phytoplankton Littoral Phytoplankton Benthic algae Macrophytes Detritus Import Sum

257

258

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