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Comparing feeding niche, growth characteristics and exploitation level of the giraffe catfish Auchenoglanis occidentalis (Valenciennes, 1775) in the two largest artificial lakes of northern Ghana Comparing feeding niche, growth characteristics and exploitation level of the giraffe catfish...
Abobi, SM; Oyiadzo, JW; Wolff, M
2019-10-18 00:00:00
African Journal of Aquatic Science 2019, 44(3): 261–272 Copyright © The Author(s) Printed in South Africa — All rights reserved AFRICAN JOURNAL OF AQUATIC SCIENCE ISSN 1608-5914 EISSN 1727-9364 https://doi.org/10.2989/16085914.2019.1628704 Comparing feeding niche, growth characteristics and exploitation level of the giraffe catfish Auchenoglanis occidentalis (Valenciennes, 1775) in the two largest artificial lakes of northern Ghana 1,2,3 3 1,2 SM Abobi * , JW Oyiadzo and M Wolff Faculty of Biology (FB2), University of Bremen, Bremen, Germany Leibniz Centre for Tropical Marine Research (ZMT), Bremen, Germany Department of Fisheries and Aquatic Resources Management, University for Development Studies, Tamale, Ghana *Corresponding author, email: seth.abobi@leibniz-zmt.de/mabobi@uds.edu.gh The stomach contents of the giraffe catfish, Auchenoglanis occidentalis, populations from Lake Bontanga and Lake Tono, two artificial lakes, were analysed, together with length frequency data collected from July 2016 to June 2017, to gain knowledge of the stock bioecology and exploitation status. The feeding characteristics of the giraffe catfish did not differ significantly between the lakes, as revealed by a Wilcoxon rank-sum test (p > 0.05). Insect larvae and algae dominated stomach content, with proportionate contributions of 43.8% and 14.2% in Lake Bontanga and 49.3% and 10.6% in Lake Tono, respectively. In the larger Lake Tono, the growth coefficient (K = 0.34 year) and asymptotic length (L = 38.3 cm) were higher than in Lake Bontanga and the exploitation rate was comparatively low (E = 0.24). This lower exploitation level in Lake Tono agrees with a higher mean catch size of 27.6 cm and a high spawning stock biomass >0.4 of the unfished biomass, as well as a higher spawning stock biomass of 3.12 tonnes −2 km , suggesting that there is scope for an intensification of the fishery. In the smaller Lake Bontanga, the species −1 growth was lower (K = 0.31 yr and L = 28.9 cm) and the stock is fully exploited (E = 0.48). The mean catch size and spawning stock biomass were critically low; 17.2 cm and <0.4 of the unfished biomass, respectively. Accordingly, this stock requires close monitoring to prevent resource depletion. Keywords: Online supplementary material: Introduction Auchenoglanis occidentalis Auchenoglanis occidentalis Auchenoglanis occidentalis Chrysichthys Clarotes A. occidentalis Auchenoglanis African Journal of Aquatic Science Abobi, Oyiadzo and Wolff 6 3 a medium-sized anal fin. The mouth is supported dorsally capacity of 25 × 10 m . Both systems are within the Guinea by the premaxilla and part of the maxilla (Risch 1985). The savanna belt where the most prominent rainy season is species are reported to reach up to 70 cm in length and a from June to October. The lakes were primarily constructed weight of 4.5 kg and its flesh is considered of a fair quality to support irrigation agriculture. The fisheries resources of (Reed 1967; FishBase 2019). Auchenoglanis occidentalis is both lakes have provided livelihood opportunities to fishers mainly omnivorous and an adaptive generalist feeder, with in the riparian communities for the past four decades. Lake strong insectivorous tendency (Paugy and Lévêque 1999; Bontanga has two main landing sites (Voggu and Bontanga), Ouéda et al. 2008). However, its feeding habit and food whereas Lake Tono has five landing sites. The catch at Lake ingestion rate can greatly vary in tandem with the in situ Bontanga is dominated by tilapias (73%), Clarias gariepinus food availability, which could differ between waterbodies. (9%), Brycinus nurse (5.9%), A. occidentalis (3%), The current study aimed at a comparison of the feeding Heterotis niloticus (2.4%) and Mormyrus spp. (2.4%). niche and ecological role of the giraffe catfish and its Other landed species include Malapterurus electricus, exploitation level in two artificial lakes, which differ in Labeo spp., Hemichromis spp., Citharinus citharinus, size, mean depth, water level fluctuation and water Distichodus engycehpalus, Ctenopoma kingsleyae, volume capacity. Lake Tono is a large lake formed by Pellonula leonensis, Polypterus endlicheri and Protopterus two water sources. It has dense aquatic vegetation in the annectens. The total annual catch at Lake Bontanga (from littoral zones, which become inundated during the rainy July 2016 to June 2017) was 105.8 tonnes. Similarly, at season. Lake Tono has larger deep zone areas than Lake Lake Tono, catches were dominated by tilapias (89%), Bontanga. There are also five small islands visible at A. occidentalis (4.1%), Schilbe spp. (3.2), Clarias gariepinus low water levels. Because the giraffe catfish is known to (1.1%) and Hemichromis spp. (1.1%). The rest include occur in both lacustrine and riverine systems (Palomares Pellonula leonensis, Labeo spp., Mormyrus spp., et al. 2003), the population at Lake Tono is expected to Synodontis spp. and Heterotis niloticus. The total catch at have more diverse sources of food, and based on the Lake Tono (from July 2016 to June 2017) was 187.2 tonnes. aforementioned differences in environmental characteristics, we hypothesise that the giraffe catfish population in Lake Fish sampling Tono feeds more on plant material and associated insects Fish specimens were collected each month from fishers than their counterparts in Lake Bontanga do and that growth operating in Lake Bontanga and Lake Tono. The fish were conditions might well be more favourable in Lake Tono. caught by nylon monofilament gill nets with mesh sizes The objectives of the study were accordingly to provide ranging from 22 to 57 mm at Lake Bontanga and from information on: (i) the food items ingested by the species 51 to 70 mm at Lake Tono. The twine diameter ranged and their relative abundance in the two lakes; (ii) the von between 0.10 and 0.16 mm. The height of the nets ranged Bertalanffy growth parameters (asymptotic length and from 1 to 2.5 m. Hook and lines were used occasionally growth coefficient) of the species; (iii) the population size to target the species. Fish measurements of standard and (absolute and per area) and (iv) the fisheries exploitation total lengths were done using a fish measuring board to level, biological reference points and length-based the nearest 0.1 cm and specimens were weighed with a indicators for sustainable levels of exploitation. weighing scale to the nearest 0.01 g. Fish samples were Although the stomach analysis was based on occurrence taken for a period of six months from July to December and numerical methods, two complementary approaches 2016 for stomach content analysis, whereas the size were used to analyse the length frequency data. The first frequency data were collected for one full year (from July was based on an analysis of the length frequency data 2016 to June 2017). using the TropFishR software (Mildenberger et al. 2017) in estimating growth parameters and exploitation rates from Stomach content analysis a catch-curve analysis. The second was based on the use Individuals of A. occidentalis from both lakes were obtained of length-based indicators (Froese 2004; Cope and Punt fresh from the fishers and retained in an icebox to prevent 2009) in estimating the spawning potential of the species post-mortem digestion. In the Spanish laboratory of the under the current exploitation regime. University for Development Studies, Nyankpala Campus, Ghana, the fish were dissected, the guts removed and Materials and methods the contents were taken with a dropper, placed on slides and examined under a microscope. Stomach contents Description of the study sites were analysed using the frequency of occurrence and Lake Tono (10°52′48′′ N, 1°9′36′′ W) (Figure 1) is the “points” method of Hyslop (Hyslop 1980). The frequency largest artificial lake in the upper east region of Ghana, of occurrence method estimates the percentage of with a surface area of 18.6 km . Lake Bontanga (9°33′0′′ N, stomachs in a sample containing a given food item, 1°1′12′′ W; Figure 1) is about one-third of this size (6.7 km ), whereas the points method gives the bulk contribution but it is the largest artificial lake in the northern region of of each food item to the total food consumed. The points Ghana. Lake Tono is approximately 210 km away from method is considered one of the most convenient Lake Bontanga. Lake Tono has a length of 3 471 m and a methods for assessing the feeding habits of herbivorous catchment area of 650 km . Its mean depth is 6.6 m and and omnivorous fish species, because, they feed on 6 3 its volume is estimated as 93 ×10 m . Lake Bontanga, microorganisms. It is more complex to measure volumes conversely, has a length of 1 900 m and a catchment area of food items containing microscopic organisms, such as of 165 km , a mean depth of 5.9 m and a water volume algae and diatoms, when using other methods (Zacharia African Journal of Aquatic Science 2019, 44(3): 261–272 263 1°30' W 1°18' W 1°6' W 0°54' W 1°18' W 1°6' W 0°54' W BURKINA FASO (a) (b) Paga 10°54' N Navrongo 10°54' N 10°0' N 10°0' N Lake Tono Chuchuliga Bolgatanga 5 km 5 km 10°41' N 10°41' N 9°48' N 9°48' N Dalun 10°30' N 10°30' N 9°35' N 9°35' N Burkina Faso Zangbulung 11° N Lake Bontanga Kumbungu Legend Town Voggu Ivory Coast Togo District capital 9° N 200 km Regional capital Tolon District GHANA 9°24' N Ghana Road 7° N Nyankpala Tamale AFRICA River/stream 5° N 3° W 0° Figure 1: Map showing the locations of Lake Tono in Kassena Nankana East Municipality (formerly Kassena Nankana Municipality) and Lake Bontanga in Kumbungu District (formerly Tolon-Kumbungu District) and Abdurahiman 2004). Points were given to stomachs The R programming software (Version 3.5.0) was used that were fully filled, half-filled and quarterly filled, for the statistical analysis. Tests for normality were done respectively. Empty stomachs were, however, completely using the Anderson–Darling normality test (Ad.test) and the excluded from the analysis. The total number of points Cramer–von Mises normality test (Cvm.test). The results given to each stomach was subdivided among the food of the normality tests on the food items indicated that the items present, according to their relative contribution to p-values on all food categories by both tests were below the the total stomach content. The percentage composition conventional value of 0.1. Therefore, a comparison of the of each food items was determined by summing up the sample means (between Lake Bontanga and Lake Tono) of points awarded to the item and dividing it by the total points the food items followed a non-parametric procedure using a awarded to all stomachs containing food and the resulting Wilcoxon rank-sum test instead of a Student’s t-test. value was expressed as a percentage. It should be noted that points of 10, 5 and 2.5 represent 100%, 50% and Stock assessment approach 25% respective contribution of a food item to the stomach TropFishR (Mildenberger et al. 2017), an R package content of the fish. for tropical fisheries analysis, was used for the stock assessment. TropFishR has enhanced functions of Total number of stomach with a particular food item × 100 Frequency of occurrence of a food item: the FAO-ICLARM Stock Assessment Tools II FISAT II Total number of stomachs with food (Gayanilo et al. 2005). It includes some additional recent Total number of stomach with a particular food item methods. The length frequency data (LFQ) were raised × 100 Total number of stomachs with food to the monthly catches observed for the species before conducting the electronic length frequency analysis Points allocated to a food item: (ELEFAN), catch-curve analysis, virtual population analysis (VPA) and yield per recruit analysis (YPR). The Number of points of the particular food item total weight of A. occidentalis landed at each lake was × 100 Total number of points of all food items observed and recorded for five fishing days per month Number of points of the particular food item × 100 Total number of points of all food items -�K�t-t �+S�t�-S�t �� 0 0 L = L �1–𝑒𝑒 � t ∞ -�K�t-t �+S�t�-S�t �� 0 0 L = L �1–𝑒𝑒 � t ∞ -0.33 0.73 M = 4.118K L -0.33 0.73 M = 4.118K L N = N exp�-�F +M�� i+1 i i N = N exp�-�F +M�� i+1 i i � � F �1- exp�- F +M �� i i C = N i i F +M � � F �1- exp�- F +M �� i i C = N i i F +M GULF OF GUINEA White Volta Total number of stomach with a particular food item × 100 Total number of stomachs with food Number of points of the particular food Abobi, Oyiadzo and Wolff item × 100 Total number of points of all food items and using the average number of fishing days, the total Mortality and exploitation rate catch was extrapolated. The LFQ data were raised to The instantaneous total mortality coefficient (Z) was match up with monthly catches, with the assumption that estimated by means of the linearised length-converted the number and weight of fish measured for the LFQ data catch-curve analysis method incorporated in the TropFishR are an adequate representation of the length distribution package using the relation: Ln(Ni ∕dti) ‘with age t or relative � � � � � � -�K t-t +S t -S t � 0 0 of the total catch for the month. The individual steps of age’, where Ni is t L = he number of L �1–𝑒𝑒 individuals in lengt � h class i t ∞ the length-based stock assessment, outlined by Sparre and dti the time needed by the fish to grow in class i (Pauly and Venema (1998) and for TropFishR by Mildenberger 1990; Pauly et al. 1995). The rate of natural mortality (M) et al. (2017), were implemented within a bootstrapping was estimated according to the empirical equation of Then framework (Schwamborn et al. 2019). This allows to et al. (2015): estimate uncertainty intervals for all parameters and avoid -0.33 0.73 the seed effect (Schwamborn et al. 2019). M = 4.118K L Growth parameters Fishing mortality rate (F) was estimated using the Total length measurements grouped into 1 cm class relationship: F = Z − M. The exploitation rate (E) was intervals were used to assess the growth parameters of obtained from: E = F ∕ Z. Estimated values of E were then the species, using a seasonally oscillating von Bertalanffy compared with a reference value of 0.5, which has been N = N exp�-�F +M�� growth equation (soVBGF) (Pauly and Gaschutz 1979; proposed as an upper level of sustainable exploitation for i+1 i i Somers 1988): fish species (Gulland 1971). The estimated exploitation rates were derived from maximum density values of distributions –(K(t–t )+S(t)−S(t )) 0 0 L = L (1–e ) for each parameter obtained from the linearised length- Total number of stomach with a particular food item t ∞ × 100 converted catch curve, using a bootstrapping approach. Total numbe �r of st �omachs with food F �1- exp�- F +M �� i i C = N where L is the total length of the fish at time t, L is the Although F and M add up to Z on the level of the resamples, i i t ∞ F +M asymptotic length of fish in cm, K the rate at which Lt the maximum density estimates (and medians) do not have approaches L and t is the theoretical age of the fish to add up, because the maximum density of each distribution ∞ 0 when Lt is equal to zero. In S(t) = (CK/2π) sin 2π(t − t ), is determined independently from the other parameters. C is a constant indicating the amplitude of the oscillation, The total mortality (Z) was estimated using both the Total number of stomach with a particular food item × 100 typically ranging from 0 to 1 (a value >1 implies periods of conventional linearised length-converted catch curve and the Total number of stomachs with food Number of points of the particular food item shrinkage in length, which is rare) and t is the fraction of bootstrapping approach. × 100 Total number of points of all food items a year (relative to the age of recruitment, t = 0), where the sine wave oscillation begins (i.e. turns positive). A seasonally Size at first capture oscillating VBGF was used to assess the growth parameters, The size (L ) at which 50% of the fish are retained by the gear, because seasonal changes in the growth of tropical fish have was estimated using the ogive selection of the bootstrapped, Number of points of the particular food item frequently been reported, which are attributed to changes in linearised, length-converted catch curve, assuming that the × 100 Total number of points of all food items water temperature, precipitation and/or to the availability of chance of capturing a fish is solely dependent on its length. food (Morales-Nin and Panfili 2005; Herrón et al. 2018). The -�K�t-t �+S�t�-S�t �� 0 0 L = L �1–𝑒𝑒 � bootstrapped ELEFAN with genetic algorithm optimisation Stock size estimates t ∞ (bootstrapped ELEFAN with genetic algorithm (GA)) function Cohort analysis (Jones 1984) was conducted to study of TropFishR (Mildenberger et al. 2017; Schwamborn et al. the dynamics of the fish stocks and to estimate fishing 2019) was used to determine the parameters L and K of mortality for different length groups using the estimated L ∞ ∞ -�K�t-t �+S�t�-S�t �� 0 0 L = L �1–𝑒𝑒 � t ∞ the von Bertalanffy equation. An initial seed value of L was and K values. The annual mean value of F derived through based on L , derived from the mean of the 1% largest fish the length converted catch curve was used as an estimate max -0.33 0.73 M = 4.118K L in the sample and following the equation of Taylor (1958): for the fishing mortality of the last length group (‘terminal L = L /0.95. The VBGF parameters were assessed F’). The last length groups, with low catch numbers, were ∞ max using a moving average (MA) over seven size intervals. grouped into one plus group. Biomass of the different -0.33 0.73 M = 4.118K L Because the VBGF parameters are known to be sensitive length groups was then calculated with the length-weight ∞ to the MA setting (Taylor and Mildenberger 2017), the relationship (LWR) equation, using the constant a and the bootstrapped ELEFAN with a GA function was also rerun for exponent b values, derived from the study data (Table 1). N = N exp�-�F +M�� i+1 i i each assessment with MA over five and nine size intervals, The cohort analysis is based on the following equations: respectively. The genetic algorithm (GA) is an optimisation N = N exp�-�F +M�� approach for growth function fitting, using the open-source i+1 i i software 'R' (Taylor and Mildenberger 2017). � � F �1- exp�- F +M �� The L and K were used to calculate the growth i i C = N i i F +M performance index (Ø’) = logK + 2logL (Pauly and Munro � � F �1- exp�- F +M �� i i 1984) to compare the growth performance of the giraffe C = N i i F +M catfish between the two lakes. The bootstrapping approach where N is the stock size in numbers, C is the catch, F is included in the TropFishR allowed for the estimat ion of the fishing mortality and M is the natural mortality. confidence intervals around the mean growth parameter estimates. The parameter t indicates the fraction of the Relative-yield-per-recruit curve and reference points anchor year where yearly repeating growth curves cross length The fishing mortality that produces the highest biomass equal to zero. per recruit (F ), the fishing mortality that will result in max African Journal of Aquatic Science 2019, 44(3): 261–272 265 50% reduction of the biomass of unexploited population The L values used were taken from studies by Kwarfo- (F ) and a fishing mortality that corresponds to 10% of the Apegyah (2008) and Akongyuure et al. (2017). The 0.5 slope of the yield-per-recruit curve at its origin (F ) were corresponding total lengths at first sexual maturity were 0.1 predicted using the Thompson and Bell model (Thompson 14.8 and 17.8 cm for Lake Bontanga and Lake Tono, and Bell 1934). The model builds on the output of the cohort respectively. analysis with the following input parameters: K (annual • P : is the proportion of fish within a 10% range around opt growth coefficient); t (anchor point); L (asymptotic the optimum length (L ) in the catch, with 100% as anchor ∞ opt length); M (natural mortality); a (constant of LWR); b the reference target, based on the equation: P = % opt (exponent of LWR); L (length at recruitment to fishery); L fish > L − 10% and < L + 10%; where: log(L ) = r 50 opt opt opt and L (selectivity parameters) (Thompson and Bell 1934; 1.053*log(L ) − 0.0565 (Froese and Binohlan 2000). The 75 m Sparre and Venema 1998). The reference points F , F L for the target species based on the equation were max 0.5 opt and F , with their confidence intervals, were used as the 15.0 cm and 18.2 cm at Lake Bontanga and Lake Tono, 0.1 first set of indicators of the exploitation status. respectively. • P : indicates the proportion of 'megaspawners' in the mega Length-based indicators for sustainable fisheries catch, with 30% to 40% as a desired target reference Three indicators proposed by Froese (2004) formed the point, based on the equation: P = % fish > L + 10% mega opt second set of indicators for the assessment of stock status. (Froese 2004). The indicators are: Using a decision tree procedure by Cope and Punt (2009), • P : refers to the proportion of mature fish in the catch, the three proportions were summed (P + P + P ) to mat mat opt mega with 100% as the reference target point, based on the obtain P , which defines indicator values of stock status obj equation: P = % fish in sample > L ; where L is the above spawning stock biomass (SSB) reference points. The mat m m length at first sexual maturity. This suggests that all fish P allows for differentiation of selectivity patterns, because obj should be allowed to spawn at least once before they are the authors observed that P had a more consistent obj caught to rebuild and maintain healthy spawning stocks. relationship with spawning stock biomass (SSB) than any Table 1: Descriptive variables and length-weight relationships of Auchenoglanis occidentalis from Lake Bontanga and Lake Tono Variable Symbol Lake Bontanga Lake Tono Total number of specimens n 1 553 798 Total length (cm) TL range 6.3–36.5 12.4–50.2 Body weight (g) BW range 4.3–479.6 17.6–1 400.6 Length at first capture (cm) L (Cl95%) 14.3 (12.4–15.7) 29.07 (24.4–30.7) Mean catch length (cm) L 17.2 27.6 mean Time corresponding to L (yr) t 2.3 3.8 c 50 Constant a (Cl95%a) 0.012 (0.011–0.013) 0.007 (0.006–0.009) Allometric coefficient b (Cl95%b) 2.93 (2.90–2.97) 3.10 (3.06–3.15) Coefficient of determination r 0.9544 0.9528 Bontanga Tono Insect larvae Plant material Algae Digested food Sand and silt Insects Zooplankton Fish parts FOOD ITEMS Figure 2: Frequency of occurrence of food items in the stomachs of Auchenoglanis occidentalis from Lake Bontanga and Lake Tono FREQUENCY OF OCCURRENCE (%) Abobi, Oyiadzo and Wolff of the individual metric (P , P or P ) and that different Table 2: Total points and bulk contribution of food items to the mat opt mega stomach contents of Auchenoglanis occidentalis from Lake Bontanga selectivity patterns in the fishery were associated to a range and Lake Tono of values of P . Once a selectivity pattern is established, obj based on P , threshold values of P , P and/or the L /L obj mat obj opt m ratio point to an estimated probability of the spawning stock Lake Bontanga Lake Tono biomass (SSB) being below established reference points, Total Contribution Total Contribution either 40% or 20% of the unfished spawning stock biomass points (%) points (%) Algae 38.5 14.2 39.5 10.6 (0.4SSB or 0.2SSB) is established. Digested food 50.0 18.5 65.0 17.5 Fish parts 5.0 1.8 4.0 1.1 Results Insect larvae 118.5 43.8 183.5 49.3 Insect parts 9.0 3.3 9.0 2.4 Food spectrum of Auchenoglanis occidentalis Plant material 23.5 8.7 35.0 9.4 Lake Tono had more full and half-full stomachs than Lake Sand and silt 19.5 7.2 24.0 6.5 Bontanga, whereas quarter-filled stomachs were more particles predominant in Lake Bontanga. Of the 72 stomachs of Zooplankton 6.5 2.4 12.0 3.2 A. occidentalis examined from Lake Bontanga, 35% were Total 270.5 100.0 372.0 100.0 empty. Of the 47 stomachs with food, 34.04% were fully filled, 29.8% were half filled and 36.2% were quarter filled. Of the 82 stomachs of A. occidentalis examined from Lake Mortality and exploitation rate Tono, 27% were empty. Of the 73% stomachs containing The populations at Lake Tono had higher natural mortality food, 44.1% were fully filled, 32.2% were half filled and 23.7 than fishing mortality, whereas the reverse is true for were quarter filled. the populations at Lake Bontanga. Consequently, the The food items identified were insect larvae, adult insects, exploitation rate is was significantly higher at Lake Bontanga digested food, fish parts, sand and silt particles, algae, than Lake Tono. The maximum density values suggest other plant material and zooplankton. Insect larvae and that the fish populations are underexploited in Lake Tono, fish parts occurred in 30% and 3.3%, respectively, of the whereas the upper limit of the confidence interval of the total stomachs examined at Lake Bontanga and in 35.6% exploitation rate for the populations at Lake Bontanga is and 3%, respectively, of those examined at Lake Tono above the recommended optimal exploitation level (E = 0.5) (Figure 2). Similarly, insect larvae and fish parts had the (Table 5). The exploitation rates of the fish stock remained highest and the lowest bulk contributions, respectively, unchanged for the populations at Lake Tono, when the to the stomach contents of the fish from Lake Bontanga assessment was rerun with MA setting of five and nine. (43.8% and 1.8%) and Lake Tono (49.3% and 1.1%) However, the exploitation rates for the populations at Lake (Table 2; Figure 3). No significant difference in the bulk Bontanga, when assessed with MA settings of five and nine contribution of food items was found between the stomach size intervals were slightly above the optimal exploitation contents of A. occidentalis from Lake Bontanga and Lake rate (Tables S1 and S2). The total mortality values estimated Tono (Table 3). using the conventional length-converted catch curves (Figure 5) were consistent with those obtained with the Size composition bootstrapped, linearised length-converted catch curves, The A. occidentalis populations at Lake Tono and Lake but with different confidence intervals (Table 5; Figure S3). Bontanga had total length ranges of 12.4 to 50.2 cm and Because the bootstrap approach allowed for unbiased 6.3 to 36.5 cm, respectively (Figure S1). This size range selection of data points in the length-converted catch difference is evident by the estimates of length at first curve for the estimation of total mortality (Z), the results of capture (L ) and mean catch length (L ). Both estimates that approach (Table 5) were used for the yield-per-recruit c mean were significantly higher for Lake Tono than for Lake analysis and stock size estimation. Bontanga. The time corresponding to the L indicates that the mean age of the catch at Lake Bontanga is 2.3 years Stock biomass and 3.8 years at Lake Tono (Table 1; Figure S4). The biomass of A. occidentalis per unit of lake area is −2 substantially higher at Lake Tono (3.12 tonnes km ) than −2 Growth parameters Lake Bontanga (1.82 tonnes km ) (Table 5). The asymptotic length (L for the fish populations at Lake ∞) Bontanga is approximately 10 cm lower than the estimate Biological reference points for the populations at Lake Tono. Although K was close The F values are similar for both systems, whereas F 0.1 max in range for both systems (Table 4; Figure 4), the growth for Lake Tono is more than twice as high as the value for performance index is substantially higher at Lake Tono. Lake Bontanga. Similarly, the F of Lake Tono is higher 0.5 The estimates of the parameter t indicate that August than Lake Bontanga (Table 5). anchor and September are the months close to the hatching period, where the yearly repeating growth curves cross Length-based indicators (LBI) the length equal to zero for the populations at Lake Tono The proportion of immature fish in the catches was higher in and Lake Bontanga, respectively. The confidence intervals Lake Bontanga than Lake Tono. Although the fish exploitation around the growth parameters were similar for both at Lake Tono met the 100% target reference for P , the mat systems (Table 4; Figures S2 and S3). proportion of fish within the P range was very low (0.4%) opt African Journal of Aquatic Science 2019, 44(3): 261–272 267 Algae Insect larvae Insect parts Digested food Plant material Sand and silt Zooplankton Fish parts Bontanga Tono Bontanga Tono Bontanga Tono Bontanga Tono LAKE Figure 3: Mean point distribution of food items found in the stomach Auchenoglanis occidentalis from Lake Bontanga and Lake Tono. Points 10, 5 and 2.5 represent stomachs that are fully filled, half-filled and quarterly filled, respectively. The lower quartile, median (grey line), mean (black line) and upper quartile are indicated. Table 3: Wilcoxon rank sum test with continuity correction and mean points of food items for Auchenoglanis occidentalis from the Lake Bontanga and Lake Tono artificial lake systems. It should be noted that because of limited data, fish parts were not included in the comparisons Food items Mean points ± SD Mean points ± SD Wilcoxon p-value of food items from of food items from rank-sum test (0.05) Lake Bontanga Lake Tono Algae 2.14 ± 1.48 2.63 ± 1.32 95.5 0.147 Digested food 3.33 ± 2.04 4.06 ± 2.06 100.0 0.435 Insect larvae 3.29 ± 2.03 3.82 ± 1.96 704.5 0.147 Insects 1.00 ± 0.25 1.50 ± 0.84 14.5 0.121 Plant materials 1.38 ± 1.05 1.52 ± 0.76 161.5 0.343 Sand and silt 1.50 ± 1.00 1.71 ± 1.25 82.5 0.686 Zooplankton 0.81 ± 0.37 1.33 ± 0.79 20.5 0.130 α at 5% significance level (Table 6). Additionally, the catches at Lake Tono were full biomass, whereas the stock at Lake Tono had a spawning of large-sized A. occidentalis, with the P being above the stock biomass above this reference point (Table 6; Figure 6). mega desired target range of 30% to 40%. Lake Bontanga had a higher proportion of fish within the P than Lake Tono. Discussion opt Moreover, the P value for Lake Bontanga was within the mega desired target range. The decision tree analysis indicated that Feeding habits of Auchenoglanis occidentalis the spawning stock biomass of the stock at Lake Bontanga The food items recorded in this study for the giraffe was below the reference point of 40% of the unfished catfish Auchenoglanis occidentalis are similar to MEAN POINTS 75 25 25 Abobi, Oyiadzo and Wolff Table 4: Parameter estimates of seasonalised von Bertalanffy growth equation for Auchenoglanis occidentalis specimens from Lake Bontanga and Lake Tono assessed with the bootstrapped electronic length frequency analysis with genetic algorithm function of TropFishR. Estimates based on length frequency samples collected from July 2016 to June 2017. Maximum, maximum density, and Lower and Upper denote 95% confidence interval of the estimates Lake Bontanga Lake Tono Parameter Symbol Maximum Lower Upper Maximum Lower Upper Asymptotic length L (cm) 28.91 27.19 35.62 38.27 36.25 42.25 Coefficient of growth rate K (yr) 0.31 0.12 0.43 0.34 0.19 0.48 t 0.72 0.12 0.87 0.60 0.20 0.77 anchor C 0.68 0.16 0.93 0.49 0.25 0.83 t 0.45 0.14 0.78 0.73 0.24 0.82 Growth performance index Ø 2.41 1.93 2.74 2.70 2.40 2.93 (b) (a) 0.6 0.8 0.5 0.6 0.4 0.3 0.4 0.2 0.2 0.1 25 30 35 36 38 40 42 44 L (cm) L (cm) ∞ ∞ Figure 4: Scatter histogram of bootstrapped ELEFAN with genetic algorithm optimisation for Auchenoglanis occidentalis collected from (a) Lake Bontanga and (b) Lake Tono. Dots represent estimated L and K (growth parameters of the von Bertalanffy equation) per resampled length frequency catch data (b) (a) Z = 1.04 ± 0.08 Z = 0.73 ± 0.03 6 6 y = 13.2 − 1.24x y = 11.9 − 0.72x 2 2 r = 0.945 r = 0.974 2 2 0 0 0 2 4 6 8 10 2 4 6 8 10 12 RELATIVE AGE (years − t ) Figure 5: Linearised length-converted catch curves for Auchenoglanis occidentalis collected from (a) Lake Bontanga and (b) Lake Tono −1 K (yr ) ln (Ni/dt) −1 K (yr ) African Journal of Aquatic Science 2019, 44(3): 261–272 269 Table 5: Mortalities (Z, M and F), exploitation rate (E), biological reference points of fishing mortality (F , F , max 0.1 F ) and stock size estimates of Auchenoglanis occidentalis from Lake Bontanga and Lake Tono. Lower and upper 0.5 denote 95% confidence interval of the estimates. Estimates were based on a bootstrapping approach Lake Bontanga Lake Tono Parameter Maximum Lower Upper Maximum Lower Upper Z 1.04 0.38 1.62 0.73 0.44 1.04 M 0.47 0.27 0.74 0.55 0.36 0.73 F 0.50 0.09 0.90 0.17 0.01 0.42 E 0.48 0.24 0.56 0.23 0.02 0.40 F 1.04 0.68 2.05 1.00 0.66 1.84 0.1 F 1.86 1.24 4.37 4.14 2.25 7.00 max F 0.59 0.39 1.39 0.89 0.54 1.72 0.5 N 369 127 227 215 2 994 478 550 517 359 142 16 709 314 B 12.17 7.09 124.18 57.97 43.68 1 880.40 those found by Ikongbeh et al. (2014), who reported which insects find conditions suitable for reproduction that A. occidentalis from Lake Akata, Nigeria, fed on in the lakes. The ecological niche for the giraffe catfish a variety of food items ranging from insect larvae to is very similar in both lakes, as evidenced by the similar algae and considered A. occidentalis to be omnivorous. food spectrum found through the stomach analysis. The Auchenoglanis occidentalis from Lake Bontanga and generally higher stomach fullness and lower proportion Lake Tono systems fed more on insect larvae than on of empty stomachs found for Lake Tono might be algae. The high percentage of insect larvae encountered indicative of better food conditions in this lake. in the stomachs of A. occidentalis from Lake Tono and Although Ouéda et al. (2008) reported seasonal shift Lake Bontanga supports the findings of Eccles (1992), in the diets of the fish population in a Sahelo-Soudanian according to whom A. occidentalis occurs in shallow artificial lake (Loumbila, Burkina Faso), a recent study waters with a muddy bottom, where insects occur by Chukwuemeka et al. (2015) noted that there was no in the benthic zone of the aquatic environment and remarkable difference in food composition of the species consequently their larvae are prone to be preyed on by population in Lake Tagwai, Minna Niger State, Nigeria, A. occidentalis. Our findings also confirmed a study by between the dry and rainy season months. Additional Chukwuemeka et al. (2015), which indicated that the studies on the species’ feeding ecology are required, stomach contents of A. occidentalis population in Lake especially in the semi-arid lakes of sub-Saharan Africa, in Tagwai, Minna Niger State, Nigeria, were dominated by order to gain a better understanding of the seasonal profile insects (31.75%), fish (12.70%), chyme (20.63%), plant of the feeding behaviour of A. occidentalis. material (20.63%), protozoa (1.59%) and soil (12.70%). The dominance of insect larvae among the food items in Growth parameter estimates both systems as observed from July to December could Although K was similar in both lakes, L greatly differed be related to the high rainfall that occurs during the between the lakes, with a higher value in Lake Tono flood and post-flood seasons of northern Ghana, during (Table 4) resulting in a substantially higher growth performance estimate for this lake. This might reflect real differences in attainable sizes between lakes in relation Table 6: Proportions of mature fish (P ), optimum-sized fish mat to lake size and stock density, but could also have been (P ), larger than optimum size fish (P ) and P ( = P + P opt mega obj mat opt the result of the higher fishing pressure in Lake Bontanga, + P ) for Auchenoglanis occidentalis from Lake Bontanga and mega causing a greater depletion of larger fish close to the Lake Tono based on the indicators proposed by Froese (2004) and size of L . Overall, the estimated growth performance the formulas described in Methods. Stock condition interpretation indexes for the giraffe catfish in Lake Bontanga and is based on a decision tree proposed by Cope and Punt (2009), Lake Tono are lower than the one (Ø’ = 2.92) reported aimed to assess whether spawning stock biomass (SSB) is above for Lake Bangweulu, Zambia (Cosmas 1992). Moreover, (>) or below (<) a reference point (RP) of 0.4 unfished biomass. The last column indicates the estimated probability of SB being the estimate of the asymptotic length (L = 52.8) in Lake lower than 0.4 of unfished biomass, based on the same authors Bangweulu is far higher, possibly as a result of differences in fisheries impact and environmental conditions among Lake Bangweulu and Lake Bontanga and Lake Tono. Lake Lake Variable Bontanga Tono Fisheries exploitation and biological reference points P 0.77 1.00 mat The exploitation of A. occidentalis in Lake Tono appeared P 0.26 0.004 opt to be low and it seems that fishing pressure could be P 0.68 0.99 mega increased to achieve higher yields. At Lake Bontanga, to P 1.70 1.99 obj the contrary, the stock already seemed fully exploited, if Stock condition interpretation SB < RP SB > RP not slightly overexploited, and an additional increase in the Probability 100% 0% species’ exploitation rate is not advisable. Abobi, Oyiadzo and Wolff (a) Lake Bontanga (b) Lake Tono 10 20 30 40 50 TOTAL LENGTH (cm) Figure 6: Size distribution of Auchenoglanis occidentalis landings observed from July 2016 to June 2017 at Lake Bontanga and Lake Tono. The vertical lines represent the length-based reference values: length at first maturity (dashed line), optimum length L (dotted line) and opt starting length of mega-spawners (‘dot-dashed’ line) The estimates using the YPR model indicated that pressure on the large individuals. For Lake Bontanga, to the fishing mortality rates of the stocks in both systems the contrary, the pressure on immature individuals would were below the rates (F values) predicted to maximise have to be reduced in order to attain a sustainable fishery. max equilibrium yield per recruit for the stocks under the model Froese (2004) proposed reducing percentage of mature assumption that continues recruitment would prevail, and fish in the catch by 100% as a target and as a simple were again lower than the rates which would maintain indicator, with the potential to allow more stakeholders to 50% of the stock biomass, denoting that the stocks are participate in fisheries management. The target indicator not overexploited in Lake Tono. However, considering suggests that all (100%) fish should be allowed to spawn our estimates of the current exploitation rates in both at least once before they are caught, in order to rebuild systems, the stock at Lake Bontanga does not appear and maintain healthy spawning stocks. The proportion of to be underexploited (see also below the confirming LBI 23% of immature fish in the catches at Lake Bontanga, analysis). The stocks in this lake should be monitored and the low percentage of spawners in the population, every two years, where possible, to assess changes in might accordingly imply a current situation of both growth exploitation and to improve management advice. and recruitment overfishing. Length-based indicators (LBI) Stock biomass Although the stock at Lake Tono has a spawning stock The estimates of the stock size show that per unit area, biomass above the reference point, indicating a state of Lake Tono had nearly double the species population uncritical and sustainable fisheries, more yield could be biomass than Lake Bontanga. This supports our findings obtained if exploitation within the L range is increased to with regard to the low current exploitation level, and the opt 20% or 30%, although simultaneously reducing the fishing recommendation that the current exploitation rate of the FREQUENCY African Journal of Aquatic Science 2019, 44(3): 261–272 271 species at Lake Tono could be increased to increase ORCID the yield. The estimate of the biomass of Auchenoglanis −2 in Bagré reservoir in Burkina Faso is 1.64 tonnes km SM Abobi https://orcid.org/0000-0001-5538-8573 (Villanueva et al. 2006), comparable with that of the stock size in Lake Bontanga. The low fishing pressure References and higher biomass of the species in Lake Tono might Akongyuure DN, Amisah S, Agyemang TK. 2017. Gillnet selectivity be attributed to lower market availability around the Lake estimates for five commercially important fish species in Tono Tono area for the species’ exploitation. The Navrongo Reservoir, Northern Ghana. Lakes and Reservoirs: Research market, which is the closest to Lake Tono, has not yet and Management t 22: 278–289. had much demand for smoked fish (the principal form of Berra T. 2001. Freshwater fish distribution. San Diego, California, commercialisation), compared with the Tamale market, USA: Academic Press. which is supplied by Lake Bontanga. Boyd I. 2002. Estimating food consumption of marine predators: The larger biomass of Lake Tono accordingly seems to Antarctic fur seals and macaroni penguins. Journal of Applied be a reflection of good growth conditions, stemming from Ecology 39: 103–119. a rich food supply and low fishing pressure allowing the Cope JM, Punt AE. 2009. Length-based reference points for population to flourish. data-limited situations: applications and restrictions. Marine and Coastal Fisheries 1: 169–186. Cosmas L. 1992. Population dynamics of the main commercial Conclusion species of the Bangweulu fishery. MSc thesis, University of Kuopio, Zambia. The giraffe catfish, Auchenoglanis occidentalis, populations Chukwuemeka VI, Tsadu SM, Ojutiku RO, Kolo RJ. 2015. in both systems exhibited omnivorous feeding behaviour, Seasonal Profile of the Feeding Ecology of Auchenoglanis feeding more on insect larvae and as bottom feeders. occidentalis from Tagwai Lake, Minna Niger State, Nigeria. Substantial amount of sand and silt particles were found World Academy of Science, Engineering and Technology. in their stomach contents. The study did not reveal any International Science of Animal and Veterinary Sciences 9. significant difference in the bulk contribution of the food Dankwa HR, Abban EK, Teugels GG. 1999. Freshwater fishes items from the Lake Bontanga and the Lake Tono artificial of Ghana: identification, distribution, ecological and economic importance. Annales Science Zoologique (Vol. 283). Tervuren, systems, but found a generally higher stomach fullness in Belgique: Musee Royal de Afrique Centrale. Lake Tono. Eccles DH. 1992. FAO species identification sheets for fishery The population size and stock density of A. occidentalis purposes. Field guide to the freshwater fishes of Tanzania. Rome, was larger in Lake Tono and the growth performance was Italy: United Nations FAO Fisheries and Aquaculture Department. better. Here the species attains substantially larger sizes FAO. 2009. The state of world fisheries and aquaculture 2008. and the estimated growth performance index exceeded Rome, Italy: United Nations FAO Fisheries and Aquaculture that of Lake Bontanga (2.70 compared with 2.41 for Department. Lake Bontanga). The exploitation rate of the species in FishBase. 2019. Froese R., Pauly D. (Eds). FishBase. World Wide Lake Tono is low. Complementarily, the LBI analysis and Web electronic publication: http: //www fishbase org. [Accessed the estimates of the stock size indicate that the fishing 12 February 2019]. Froese R. 2004. Keep it simple: three indicators to deal with mortality could be greatly enhanced (about doubled) to overfishing. Fish and Fisheries 5: 86–91. increase yield at Lake Tono, whereas at Lake Bontanga, Froese R, Binohlan C. 2000. 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