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Length-weight relationship (LWR) has several applications, namely on fish biology, physiology, ecology and fisheries assessment. In biological studies, LWR enables seasonal variation in fish growth to be followed and the calculation of condition
  All rights reseThis work byWilolud Journalsis li Continental J. Fisheries a © Wilolud Journals, 2014Printed in Nigeria LENGTH WEI COMPOSITION OF  B Fisheries and HydrobiologyUnit, Dep Length-weight relationship physiology, ecology and fis variation in fish growth to b diet composition. Therefo composition of   Brycinus nu  the length-weight relationsh 0.112 TL 2.425 , correlation c allometric growth.Monthly The population (combined respectively (mean 1.79 ± 0. 1.0.Percentage frequency (37.7) followed by green al was in Chironomus larvae ( better than the younger on stomach of   B. nurse suggest on a number of different org growth, make this specie a p KEYWORDS Length-weig nurse Received for Publication: 22 Corresponding AuthorunekeOne of the most commonly used analy The length-weight relationship (LWR) assessments. The length-weight relatio estimations of stock size. This relation can be used in studies of gonad develo 1951). Methods to estimate the lengt estimates obtained from the widely us require the calculation of mean wei relationship (LWR). According to parameterizing yield equations and in aL b ), also known as the allometry coef gain relative to growth in length. Ma populations of the same species, or w reflect changes in the condition of in 1995). On the other hand, sampling rel rved censed under aCreative Commons Attribution 3.0 Unpo 25  nd Aquatic Science 8 (1): 25-34, 2014ISSN: 2 http://www.wiloludjournal.com doi:10.5707/cjfas.2014.  HT RELATIONSHIP, CONDITION FACTOR AN rycinus nurse (CHARACIFORMES: ALESTIDAE ) IN FLOOD RIVER BASIN Uneke Bilikis Iyabo rtmentof Applied Biology, Faculty of BiologicalScienc University, Abakaliki, Nigeria. ABSTRACT  (LWR) has several applications, namely on fish bi eries assessment. In biological studies, LWR enables sea e followed and the calculation of condition indexes relati re length weight relationship, condition factor and rse was studied (January 2010-June 2011). The regressi ip for  B. nurse with size range of 6.3-22.8cm TL was; -efficient (r) was high and the b value showed a ne ondition factor values for  B. nurse were between 1.0 an sex) had highest and lowest K values of 1.3 an 35). The stock was in good condition as K values were f occurrence with  Barbus scale having the highest perce gae (30.8) and  Barbus spp (30.5) while the least perce 13.7). Stomach content indicated that older fish specime s both by body length and weight. The food items i that the speciesis omnivorous. The ability of   B. nurse t anisms in mid Cross River, coupled with the potential fo romising specie for commercial culture.ht relationship, condition factor, diet composition  Br   /02/14Accepted for Publication:30/04/  bi@yahoo.com INTRODUCTION  ses of fisheries data is length-weight relationship (Men   is an important factor in the biological study of fishes nship is particularly important in parameterizing yield ship is helpful for estimating the weight of a fish of a pment, rate of feeding, metamorphosis, maturity and con -weight relationship of fishes are described by Pauly ( ed analytical models, such as virtual population analys ht of individuals per age or length class through th bdurahiman et al . (2004), the LWR is particularl estimations ofstock size. The parameter b of the LWR icient, has an important biological meaning, indicating t rked variability in estimates of b is usually observed ithin the same population at different times. On the one ividuals related to feeding, reproductive or migratory ted factors or calculation methods may often account for ted License. 141  –  4246  DIET TROPICAL  s, Ebonyi State logy, sonal ng to diet on of  TW= ative 3.4. 2.5 bove ntage ntage s fed n the feed r fast  cinus  14 es et al ., 2004). and their stock  quations and in iven length and dition (Le Cren, 1983). Biomass    is (Pope, 1972); e length-weight y important in equation (W = e rate of weight among different hand, this may activities (King the significant  All rights reseThis work byWilolud Journalsis li Uneke:Continental difference in estimates (King 1995). and type of length measure, and amon weight relationships give information Therefore, obtaining accurate LWR pa Length-weight relationships are useful weight from length observations; (ii) c information on stock or organism con important in fisheries management for In fisheries science, the condition fact fish. Condition factor studies take into environment;hence it represents how that heavier fish of a particular length a also a useful index for the monitoring strongly influenced by both biotic and the status of the aquatic ecosystem in of performance, survivorship and rep adopted by ecologists studying fish energetic state and overall quality. reproductive behaviours and success ( (2002) K also gives information when other conditions; when determining t feeding activity of a species to verify condition factor is thus important for management of these species and there Food and feeding habits havebeen kno kinds of food available, season, time o  B. nurse is native to freshwater syst (Boulenger, 2002). This species is commercial value (Erondu and Bow relationship, condition and diet compos MAT  Description of Study Area Nigeria has many inland water bodies The contribution of inland waters suc significant. The bulk of domestic fish total production between 1991 and 2 Cross River is a major component of t area is quite significant (Okoh etal ., State and Cross River State into the between 5 0 57” latitude 5 0 30’20”North Cross River is 3,900,000 ha (Ita et al ., the area. The latter occurs between Oc October. During the rainy season, wat river is brought about by direct precipi and Cross River flood plains.The inu During the dry season, water level is r 2008). rved censed under aCreative Commons Attribution 3.0 Unpo 26  J. Fisheries and Aquatic Science 8 (1): 25-34, 2014 mong the first we quote sample size, length distributio g the second, regression models used for parameter esti on the condition and growth patterns of fish (Mend   rameter estimates is an important factor in the assessme in fishery management for both applied and basic us alculate production and biomass of fish population; an ition at the corporal level. Length-length relationships omparative growth studies (Moutopoulos and Stergiou, r is used in order to compare the “condition”, “fatness” consideration the health and general well-being of a fish airly deep bodied or robust fishes are. And it is based o re in a better physiological condition (Bagenal, 1978). C of feeding intensity, age and growth rates in fish (Oni e abiotic environmental conditions and can be used as an hich the fish live. Individual condition factor is an impo roductive success in fish. More recently, condition fa ating systems under the assumption that they reflect Condition factors have been successful at explaini Barber, 2002, Kondoh and Okuda, 2002). According t omparing two populations with regards to feeding, densi e period of gonadal maturation and when following u whether it is making good use of its feeding source. understanding the life cycle of fish species and contrib ore to the maintenance of equilibrium in the ecosystem. wn to vary for individual fish with respect to size, age, li day, as well as locality in which they are found (Lagler, m in Africa, thriving well in both lacustrine and riv important due to its abundance, widespread distrib aker, 2007). Thus study on this species as regards t ition is inevitable. RIALS AND METHODS   with an estimated of 125,470.82km 2 (12,547,082 ha) (   as lakes and rivers to the fisheries sub-sector of the e production (327,931 tons) (Okoh et al ., 2007) constituti 00 came from inshore coastal, brackish and inland fr e inland waters of South Eastern Nigeria and its role to t 007). Cross River srcinates from Cameroon and flows Atlantic Ocean. The river (Fig. 1) (Okoh et al ., 2007) and 7 0 58” longitude 5 0 30’20” East. The approximate su 1985). The rainy seasonand the dry season are the two ober / November-March, while the former is from Ap r level increases drastically in the river. The rise in wa tation within the catchments areas as well as by inflow ndated soils are composed of sandy with good water re stricted to the main river channel and some flood plain ted License. in the samples mation. Length- s et al ., 2004). t of fish stocks. to (i) estimate /or (iii) provide (LLRs) are also 002).  or wellbeing of   as related to its    n the hypothesis ndition factor is  al ., 1983). It is index to assess rtant component tors have been  an individual’s  g variation in o Lizama et al . ty, climatic, and p the degree of  he study of the tes to adequate fe history stage, 2000). The fish   rine conditions tion, food and o length-weight ta et al ., 1985). onomy is quite ng 86.4% of the shwater waters. e fishery of the through Ebonyi lies in the area face area of the main seasons of  il-September /  ter levels of the rom the Afikpo ention capacity. pools (Okogwu,  All rights reseThis work byWilolud Journalsis li Uneke:Continental Sample and Data Collection Samples were collected monthly for ei  Brycinus nurse (n = 1820) were made b fish samples were collected each mont Cross River basin at Afikpo, Nigeria ( baskets and traps. The samples were so Raji (1998). Fish samples were preserv Standard length (SL) were measured to measurements were made with a FEJ-1 Specimens were dissected, the gut take dish for examination.Fig. 1: Map of Afikpo North Local Go (Okoh et al ., 2007). Morphometric parameters The relationship between length and w W = aTL b (Sparre and Venema, 1998).The relationship between the standar power curve: TL= aSL b (Sparre and Ve WhereW = Body weight in TL = Total length (cSL = Standard lengt b = Slope of the re a = Intercept of th rved censed under aCreative Commons Attribution 3.0 Unpo 27  J. Fisheries and Aquatic Science 8 (1): 25-34, 2014   hteen (18) consecutive months (Jan 2010-Jun 2011). Th y random samples of the catch of the commercial artisin from four sampling locations, Ozizza, Ndibe, Enohia an ig. 1). The catches were made using gill nets, cast nets, li rted and identified to species level using the guides of Ol d in 10% formalin as voucher specimens. Total length ( the nearest 0.1cm with a meter rule measuring board. W 500A electronic compact weighing balance to the nearest n out to remove the stomach. Stomach contents were emp vernment Area showing the sampling locations in the C ight was determined using the power curve: length (SL) and the total length (TL) was also deter nema, 1998). grams m) (cm) gression line (regression constant). regression with the y-axis (regression coefficient). ted License. e samplings of    l fishers. The Uwana in the    ft nets, fishing osebikan and L) and ight 0.1g. tied into a petri ross River basin   ined using the   All rights reseThis work byWilolud Journalsis li Uneke:Continental Regression analysis was used in the est co-efficientof correlation(r). Condition factor Fulton’s condition factor was compute Frequency of occurrence (%F) Analysis was done using frequency of occurrence of food items was expresse %F =number of stomach in which a pa Total number of stomach examin RESULTS Total length-standard length relations The TL-SL relationship of   B. nurse w relationship as SL = 1.128 TL 0.894 (lo indicating a highly significant TL-SL r Fig. 2: Total Length-Standard Length r Total length-total weight relationship Length-weight relationships of the  B. n   and June 2011 ranged from 2.328±0.09 Table 1 Monthly length-weight relation MonthsN Jan 201040Feb 201040Mar 201041Apr 201040May 201041Jun 201041Jul 201040Aug 201041    rved censed under aCreative Commons Attribution 3.0 Unpo 28  J. Fisheries and Aquatic Science 8 (1): 25-34, 2014 imation of the a and b values and the level of significanc according to Pauly (1984) as K = 100W/ L 3   occurrence (Hyslop, 1980). In the frequency of occurre as the percentage of the total number of stomach contai rticular food item occurX 100 ed  hip  ith standard length ranging in size from 5.4 to 20.3 cm (Y) = 0.052 + 0.894 log(X)). Co-efficient of correlatio lationship (Fig. 2). lationship of   B. nurse in the mid Cross River basin, Nig   urse in mid Cross River basin showed that ‘b’ values fro 2 and 2.843±0.085 (Table 1). ship parameters of   B. nurse in mid Cross River basinParametersa ± s.d.b ± s.d.r -0.697±0.1142.485±0.1130.91 -0.243±0.0922.501±0.1090.88 -0.503±0.1192.702±0.1160.88 -0.196±0.1092.370±0.1100.9 -0.088±0.0822.517±0.0840.93 -0.052±0.0702.570±0.0730.97 -0.244±0.1052.723±0.1060.87 -0.172±0.1002.347±0.0980.81 ted License. of the value of  nce method, the ing food. had exponential    n (r) was 0.966, eria.   m January 2010  0 *  3 6 4 *  8 *  7 *  5 7  All rights reseThis work byWilolud Journalsis li Sep 201040Oct 201045Nov 201042Dec 201036Jan 201140Feb 201137Mar 201140Apr 201138May 201140Jun 201141Total723Males304Females419 * P = 0.05 SignificantThe regression of the length-weight rel TL 2.425 (log(Y) =-0.951 + 2.425 log( showed a negative allometric growth.Fig. 3: Total Length-Total Weight relat Condition factor (CF) Monthlycondition factor values for  B. highest and lowest K values of 1.3 an males were 1.2 and 2.8 respectively ( 1.81 ± 0.44) (Fig.4). Condition factor were within the length class 7-8 for m the lengthclass 6-7 for males and leng values were above 1.0. rved censed under aCreative Commons Attribution 3.0 Unpo 29  -0.273±0.0962.420±0.0960.88 -0.100±0.0862.784±0.0890.92 -0.102±0.0762.328±0.0920.91 -0.089±0.1042.810±0.1080.91 -0.453±0.1062.601±0.1240.91 -0.343±0.1102.567±0.1140.9 -0.645±0.1212.802±0.1220.9 -0.214±0.1022.362±0.1100.91 -0.091±0.0872.843±0.0850.9 -0.062±0.0752.686±0.0740.97-0.951±0.0952.426±0.0670.96-0.631±0.0912.784±0.0910.93-0.079±0.0862.242±0.0540.88 ationship for  B. nurse with size range of 6.3-22.8cm TL )) (Fig. 3). Correlation co-efficient (r = 0.961) was hi ionship of   B. nurse in the mid Cross River basin, Nigeria.   nurse were between 1.0 and 3.4. The population (co 2.5 respectively (mean 1.79 ± 0.35). Highest and lowe ean 1.78 ± 0.49) while females had values between 1. alues according to length class showed that highest val les and 20-21 for females respectively. Lowest values ( h class 14-15 for females (Fig. 5). The stock was in goo ted License. 6 2 *  7 *  6 *  2 *  4 *  0 *  4 1 *  9 * 1 * 4 * 9 as; TW= 0.112 h. The b value .   bined sex) had    st values for the and 3.0 (mean es (2.4 and 2.6) 1.1) were within condition as K 
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