Indian Journal of Geo Marine Sciences Vol. 49 (07), July 2020, pp. 1229-1237

Temporal variation of condition and prey-predator status for a schilbid catfish Eutropiichthys vacha (Hamilton, 1822) in the Ganges River, northwestern Bangladesh through multi-model inferences

D Khatuna, M Y Hossain*,a, M A Hossenb, O Rahmana, M F Hossainc, M A Islama, M A Rahmana, Z Mawaa, a a d M R Hasan , M A Rahman & R L Vadas JR. aDepartment of Fisheries, Faculty of Agriculture, University of Rajshahi, Rajshahi – 6205, Bangladesh bFaculty of Fisheries, Kagoshima University, 4-50-20 Shimoarata, Kagoshima – 890-0056, Japan cDepartment of Molecular and Functional Genomics, Interdisciplinary Center for Science Research, Shimane University, Matsue – 690-0823, Japan dWashington Department of Fish and Wildlife, Habitat Program, 600 Capitol Way North, Olympia, WA – 98501-1091, USA *[E-mail: [email protected]] Received 29 April 2019; revised 18 June 2019

The current study provide the baseline information on the temporal (monthly) variations of condition through multiple functions (allometric, KA; Fulton’s, KF; relative, KR) and prey-predator status through relative weight (WR) for Eutropiichthys vacha (Hamilton, 1822) from the Ganges River, northwestern Bangladesh over one year. The smallest individuals were 6.5 and 6.2 cm in TL, whereas the largest were 19.9 and 20.6 cm in TL for males and females, respectively. No significant differences were observed in the length frequency distribution, LFDs (p = 0.8152) for both sexes. KF was significantly correlated with TL for both sexes (p < 0.001) and KF was treated as the best condition factor therefore, well- being of E. vachaa. There was no significant correlation among TL vs KA, TL vs KR and TL vs WR for males and females, respectively. But BW showed highly significant correlations with all condition factors, i.e., BW vs KA; BW vs KF; BW vs KR, and BW vs WR (p < 0.001) for both sexes. Additionally, WR revealed no significant dissimilarities from 100 for males (p = 0.432) unlike females (p = 0.023), based on Wilcoxon signed-rank tests, suggesting that habitat was more suitable for males than females for food availability relative to predator presence. Moreover, this study assessed for the first time the effect of temperature and rainfall on monthly KF for E. vacha in the Ganges River. The Pearson correlation test found no significant relation between temperature and KF (r = 0.2226, p = 0.4868 for males; r = 0.2172, p = 0.4977 for females), but significant correlations were found between rainfall and KF (r = 0.6357, p = 0.0263 for males and r = 0.6983, p = 0.0115 for females).

[Keywords: Bangladesh, Eutropiichthys vacha, Ganges River, Multiple condition factors, Rainfall, Relative weight, Temperature]

Introduction in Bangladesh2 and worldwide13, though formerly it Eutropiichthys is a genus of Schilbid catfishes was assessed as critically endangered in Bangladesh14. native to Asia with 7 known species1. In the Ganges Condition factors are the most constructive River, this genus is mostly represented by parameters for assessing the health of fish species and Eutropiichthys vacha (Hamilton 1822) along with E. the whole aquatic community, as well as to act as murius2. E. vacha (generally known as Batchwa functional tools for natural population management Vacha) is considered a freshwater/salt and and conservation15. Moreover, it quantitatively potamodromous species that lives mainly in large assesses the well-being of fish and predicts its future rivers, canals and tidal waters, preferably fine (sandy population success16,17. Moreover, the relative weight 3,4 18,19 or muddy) with beds . It is an indigenous, abundant (WR) can be used to examine fish health . Also, WR species in Bangladesh that also frequents other Asian is crucial to identify the prey-predator interactions of countries such as India, Myanmar, Nepal, Pakistan fishes in a given water body17. and Thailand3,5,6. This catfish bears high commercial Studies of E. vacha have examined including value, and is a popular edible fish due to its excellent length and weight relationship (LWRs and LLRs)8,9,20, flesh7-9 and large fishermen who are fed diverse to use life history characteristics17, temporal variation of sex traditional equipment10-12. The conservational status of ratio, growth pattern and physiological status21, size at E. vacha has been listed as the least concern species sexual maturity based on GSI12, reproduction with 1230 INDIAN J GEO-MAR SCI, VOL 49, NO 07, JULY 2020

special reference to probable influence of climate Climate data variability22 and reproduction and feeding habits23. Climate data (temperature and rainfall) were However, studies of any prey-predator status and obtained from Dhaka Meteorological Department, condition factors in this important fishery using Bangladesh. The monthly average values of such multiple models from long-term data sets are abiotic variables were calculated from every day unknown. The purpose of our study is to describe the means for thermistors from different sampling points condition of E. vacha through multiple condition (near Rajshahi region) throughout the Ganges River. factors and prey-predator status through relative weight from the Ganges River of northwestern Statistical analysis Graph Pad Prism 6.5 software was used to perform Bangladesh using multi-models. statistical analyses. The integrity and normality of the Materials and Methods data has been confirmed. The Mann-Whitney U test Study area and sampling was used to compare the distribution of length- This study was performed in the Ganges River, frequency between the genders. The non-parametric northwestern Bangladesh (Lat. 24°35 N; Long. 88°64 E). correlation test was done to justify the relationship Ganges River is a vital source of feeding and between the different condition factors (KA, KF, KR) 22,24 reproduction ground for freshwater fishspecies . and WR with TL and BW. Also the ANCOVA was In total, we collected 1386 individuals (652 males and applied to compare the LWR relationship between the 734 females) of E. vacha during this study. Specimens sexes. Mean relative weight (WR) compared to 29 were collected randomly from monthly sampling 100 using Wilcoxon signed-rank test . The Pearson (100 – 130 specimens/month) using gill (1.8 – 2.2 cm correlation test (parametric) was used to evaluate the mesh size) and cast nets (1.5 – 2.0 cm) catches of relationships between KF and the abiotic factors commercial fishers, as landed along the Ganges River in (temperature and rainfall). All statistical analyzes (a) the Rajshahi region and Pabna region Bangladesh were accepted as 5 % reliable (p < 0.05). during January to December in 2016. The samples were preserved on ice and fixed in a 10 % formalin solution Results upon arrival at the laboratory. Table 1 shows the descriptive statistics for measurements (length (cm) and weight (g)) of Fish measurements E. vacha. The smallest individual was 6.5 cm in TL Sex determination was performed by (i) (in April) and the largest was 19.9 cm in TL (in July) morphometric and meristic features, and (ii) for male E. vacha. Likewise, the minimum and microscopic examination of the gonads. Each maximum weight for males was 1.79 g and 50.56 g in individual, total length (TL) was measured with a these same months, respectively. For females, the measuring board and total body weight (BW) was smallest and largest individuals found in July were measured with a digital scale to an accuracy of 6.2 cm and 20.6 cm TL, respectively. The minimum 0.01 cm and 0.01 g. weight for females was 1.86 g in March, whereas the

Condition factor largest female weight was 56.95 g in July. There is no b 25 KA = W/L , was used to calculated KA . KF was significant differences in length frequency calculated following equation given by Fulton26 as: distributions of E. vacha (Mann-Whitney-U test; 3 KF = 100 × (W / L ). The 100 is used to bring the U = 237546, p = 0.8152) and BW (U = 230623, 27 scaling factor of KF . KR or well-being is a good p = 0.2443) between the sexes. factor for each individual was calculated using the During this study, the minimum and maximum 27 b values of KA were 0.0030 and 0.0236 in February and formula given by Le Cren as: KR = W/(a×L ). November for males, whereas for females were Relative weight (WR) 0.0027 and 0.0272 in February and June, respectively 28 WR was calculated in accordance with Froese as: (Table 2), and there was significant differences of KA WR = (W/WS) × 100; expected standard weight for the between the sexes (Mann-Whitney U-test, U = 94917, b same sample was calculated as: WS = a×L p < 0.0001). The lowest and highest KF values were Where, W is body weight (g); L is total length 0.503 and 0.939 in October and July for males, (cm); WS is standard weight; and a and b values are whereas for females, the values were 0.505 and 1.133 obtained from the length-weight relationships. in October and February, respectively (Table 3 and KHATUN et al.: CONDITION AND PREY-PREDATOR STATUS OF E. VACHA 1231

Table 1 — Descriptive statistics on the length (cm) and weight (g) measurements of male (M) and female (F) Eutropiichthys vacha (Hamilton, 1822) in the Ganges River, northwestern Bangladesh Month Sex n TL (cm) BW (g) Min Max Mean ± SD Min Max Mean ± SD January M 54 7.0 11.0 9.218±1.025 2.67 11.2 6.738±2.123 February 54 6.8 10.4 8.261±0.645 2.20 9.90 4.724±1.300 March 58 7.2 10.5 8.803±0.700 2.53 6.90 4.450±0.896 April 59 6.5 11.8 8.442±1.219 1.79 10.63 4.102±1.948 May 51 9.5 18.0 13.602±2.589 5.39 38.55 18.549±10.212 June 55 9.3 19.6 14.856±3.161 5.45 48.92 25.153±12.909 July 57 8.3 19.9 14.618±3.385 4.83 50.56 24.609±13.659 August 52 9.4 13.0 11.013±1.020 6.13 18.46 10.861±3.366 September 55 9.7 14.6 12.367±1.536 6.23 19.83 13.024±4.178 October 56 9.1 18.0 12.657±2.343 4.33 34.00 13.167±7.556 November 48 9.6 17.6 14.631±2.578 7.01 34.55 21.936±7.620 December 53 11.5 18.7 14.753±2.124 9.80 37.46 19.839±8.255 January F 71 6.4 10.7 9.231±0.845 2.28 10.3 6.738±1.695 February 63 6.9 9.8 8.251±0.670 2.43 8.02 4.796±1.414 March 65 6.3 10.2 8.689±0.642 1.86 6.72 4.343±0.838 April 61 7.1 11.6 9.046±1.095 2.50 10.40 5.168±1.979 May 57 8.7 16.8 12.902±2.380 4.35 31.91 16.448±8.444 June 59 8.3 19.8 13.012±3.252 4.65 43.82 17.027±11.014 July 62 6.2 20.6 13.255±3.905 2.70 56.95 18.841±13.176 August 57 10.2 14.0 12.075±1.107 8.25 22.18 14.566±4.131 September 59 9.6 15.3 12.708±1.649 8.18 23.74 15.754±4.929 October 59 8.8 16.2 12.968±1.994 4.35 25.75 13.461±5.983 November 56 10.1 18.5 13.461±2.315 8.20 36.86 18.566±8.058 December 65 12.0 19.2 15.285±2.059 11.32 41.65 22.965±8.595 n- sample size; TL- total length; BW- body weight; Min- minimum; Max- maximum; SD- standard deviation

Table 2 — Monthly variation of allometric condition factor (KA) of male and female Eutropiichthys vacha (Hamilton, 1822) in the Ganges River (see Table 1 for abbreviations)

Month Sex n Allometric condition factor (KA) Min Max Mean ± SD 95% CL January M 54 0.0063 0.0081 0.0071±0.0004 0.0071–0.0073 F 71 0.0082 0.0101 0.0092±0.0004 0.0091–0.0093 February M 54 0.0030 0.0036 0.0033±0.0001 0.0032–0.0033 F 63 0.0027 0.0033 0.0031±0.0001 0.0030–0.0031 March M 58 0.0175 0.0204 0.0190±0.0007 0.0189– 0.0192 F 65 0.0120 0.0146 0.0134±0.0006 0.0133– 0.0136 April M 59 0.0068 0.0089 0.0078±0.0005 0.0077–0.0080 F 61 0.0050 0.0069 0.0060±0.0004 0.0059–0.0061 May M 51 0.0060 0.0084 0.0069±0.0005 0.0068–0.0071 F 57 0.0067 0.0087 0.0074±0.0004 0.0073–0.0075 June M 55 0.0124 0.0172 0.0147±0.0010 0.0144–0.0150 F 59 0.0155 0.0205 0.0181±0.0012 0.0178–0.0184 July M 57 0.0122 0.0164 0.0142±0.0009 0.0140–0.0145 F 62 0.0216 0.0272 0.0240±0.0012 0.0237–0.0243 August M 52 0.0037 0.0042 0.0040±0.0001 0.0039–0.0040 F 57 0.0047 0.0054 0.0050±0.0002 0.0050–0.0051 September M 55 0.0124 0.0154 0.0137±0.0008 0.0135–0.0139 F 59 0.0223 0.0264 0.0242±0.0009 0.0240–0.0245 October M 56 0.0038 0.0049 0.0043±0.0003 0.0042–0.0044 F 59 0.0046 0.0061 0.0053±0.0003 0.0052–0.0054 November M 48 0.0188 0.0236 0.0206±0.0012 0.0203–0.0210 F 56 0.0178 0.0218 0.0199±0.0011 0.0196–0.0201 December M 53 0.0077 0.0095 0.0086±0.0004 0.0085–0.0087 F 65 0.0086 0.0100 0.0093±0.0004 0.0092–0.0094 1232 INDIAN J GEO-MAR SCI, VOL 49, NO 07, JULY 2020

Table 3 — Monthly variation of Fulton’s condition factor (KF) of male and female Eutropiichthys vacha (Hamilton, 1822) in the Ganges River (see Table 1 for abbreviations)

Month Sex n Fulton’s condition factor (KF) Min Max Mean ± SD 95% CL January M 54 0.616 0.894 0.704±0.067 0.685–0.722 F 71 0.565 0.869 0.694±0.081 0.673–0.715 February M 54 0.621 0.882 0.710±0.068 0.692–0.728 F 63 0.560 1.133 0.716±0.121 0.686–0.747 March M 58 0.573 0.712 0.646±0.034 0.637–0.655 F 65 0.581 0.744 0.655±0.034 0.647–0.664 April M 59 0.564 0.740 0.643±0.044 0.632–0.655 F 61 0.560 0.763 0.667±0.046 0.655–0.679 May M 51 0.574 0.811 0.667±0.045 0.654–0.680 F 57 0.632 0.822 0.699±0.041 0.688–0.710 June M 55 0.720 0.939 0.830±0.042 0.818–0.841 F 59 0.750 0.915 0.838±0.039 0.828–0.847 July M 57 0.700 0.911 0.817±0.051 0.803–0.831 F 62 0.728 0.911 0.828±0.050 0.815–0.841 August M 52 0.738 0.851 0.787±0.031 0.779–0.796 F 57 0.738 0.864 0.804±0.029 0.796–0.815 September M 55 0.598 0.778 0.668±0.047 0.655–0.680 F 59 0.644 0.925 0.749±0.056 0.734-0.763 October M 56 0.503 0.652 0.582±0.036 0.572–0.592 F 59 0.505 0.654 0.575±0.033 0.566–0.584 November M 48 0.575 0.832 0.675±0.063 0.657–0.693 F 56 0.582 0.845 0.724±0.061 0.708–0.740 December M 53 0.526 0.655 0.586±0.029 0.578–0.594 F 65 0.551 0.674 0.615±0.028 0.608–0.622

females, the values were 0.8393 and 1.1765 found in April and May, respectively (Table 4 and Fig. 2), but there was no significant variance between the sexes (Mann-Whitney U-test, U = 233648, p = 0.4486). Moreover, the lowest and highest values of WR were 84.428 and 131.864 in June and May for males, whereas for females, the minimum and maximum values were 83.930 and 117.646 in April and May, respectively (Fig. 3). Table 5 shows the relationships of different condition factors. Among studied condition factors, only KF showed highly significant correlation with TL (rs = -0.3274, p < 0.0001 for males and rs = -0.3779, p < 0.0001 for females), whereas BW showed very highly significant relationships (p < 0.001) with all condition factors for both sexes. The Wilcoxon signed-rank test for WR presented no significant variances with 100 for males (p = 0.432), but statistically significant differ for female E. vacha (p = 0.023) from the Ganges River Fig. 1 — Monthly variation of Fulton’s condition factor (KF) of Eutropiichthys vacha (Hamilton, 1822) in the Ganges river (Fig. 4). The monthly average values of air temperature and Fig. 1). KF was considerably dissimilar between sexes rainfall in the Ganges River are higher from April to (Mann-Whitney U-test, U = 200989, p < 0.0001). October and generally according to the period of Also, the lowest and highest values of KR were 0.8443 highest KF values. Peak rainfall was during June to and 1.1685, both in June for males; whereas for July, which is similar to the peak values of KF for KHATUN et al.: CONDITION AND PREY-PREDATOR STATUS OF E. VACHA 1233

Table 4 — Monthly variation of relative condition factor (KR) of male and female Eutropiichthys vacha (Hamilton, 1822) in the Ganges River (see Table 1 for abbreviations)

Month Sex n Relative condition factor (KR) Min Max Mean ± SD 95% CL January M 54 0.8875 1.1398 1.0077±0.0511 0.9937–1.0216 F 71 0.8959 1.0952 1.0034±0.0469 0.9923–1.0145 February M 54 0.9279 1.1252 1.0168±0.0536 1.0022–1.0314 F 63 0.8864 1.0774 0.9885±0.0458 0.0969–1.0000 March M 58 0.9198 1.0767 1.0016±0.0358 0.9921–1.0110 F 65 0.8958 1.0931 1.0038±0.0448 0.9927–1.0149 April M 59 0.8771 1.1407 1.0038±0.0671 0.9863–1.0213 F 61 0.8393 1.1546 0.9982±0.0690 0.9805–1.0159 May M 51 0.8644 1.2214 1.0078±0.0677 0.9887–1.0268 F 57 0.9020 1.1765 1.0033±0.0586 0.9878–1.0189 June M 55 0.8443 1.1685 1.0006±0.0667 0.9825–1.0186 F 59 0.8547 1.1301 1.0011±0.0642 0.9844–1.0179 July M 57 0.8571 1.1546 1.0021±0.0660 0.9846–1.0196 F 62 0.9001 1.1347 0.9994±0.0491 0.9869–1.0119 August M 52 0.9300 1.0596 0.9904±0.0281 0.9826–0.9983 F 57 0.9301 1.0841 1.0040±0.0319 0.9955–1.0125 September M 55 0.9057 1.1228 0.9986±0.0590 0.9827–1.0146 F 59 0.9166 1.0867 0.9962±0.0380 0.9863–1.0060 October M 56 0.8807 1.1313 1.0021±0.0597 0.9861–1.0180 F 59 0.8764 1.1465 0.9955±0.0574 0.9805–1.0104 November M 48 0.9109 1.1465 1.0015±0.0569 0.9850–1.0181 F 56 0.8972 1.0987 1.0027±0.0543 0.9881–1.0172 December M 53 0.8928 1.1000 0.9952±0.0451 0.9827–1.0076 F 65 0.9224 1.0778 1.0029±0.0409 0.9928–1.0130

Fig. 2 — Monthly variation of relative condition factor (KR) of Fig. 3 — Monthly changes of relative weight (WR) of Eutropiichthys vacha (Hamilton, 1822) in the Ganges river Eutropiichthys vacha in the Ganges river 1234 INDIAN J GEO-MAR SCI, VOL 49, NO 07, JULY 2020

Table 5 — Relationship of condition factors with total length (TL) and body weight (BW) of Eutropiichthys vacha (Hamilton, 1822) from the Ganges River (see Table 1 for abbreviation)

Correlation Sex rs values 95% CL of rs p value Level of significance

TL vs. KA M 0.0287 -0.0504 to 0.1075 0.4642 Ns F 0.0236 -0.0510 to 0.0979 0.5239 Ns

TL vs. KF M -0.3274 -0.3962 to -0.2549 <0.001 *** F -0.3779 -0.4400 to-0.3122 <0.001 ***

TL vs. KR M 0.0301 -0.0491 to 0.1089 0.4430 Ns F 0.0329 -0.0417 to 0.1072 0.3733 Ns

TL vs. WR M 0.0298 -0.0494 to 0.1086 0.4472 Ns F 0.0331 -0.0415 to 0.1074 0.3703 Ns

BW vs. KA M 0.1970 0.1198 to 0.2718 <0.001 *** F 0.1904 0.1176 to 0.2613 <0.001 ***

BW vs. KF M -0.1636 -0.2396 to -0.0857 <0.001 *** F -0.2164 -0.2863 to -0.1442 <0.001 ***

BW vs. KR M 0.2021 0.1251 to 0.2768 <0.001 *** F 0.2035 0.1310 to 0.2739 <0.001 ***

BW vs. WR M 0.2019 0.1248 to 0.2765 <0.001 *** F 0.2037 0.1312 to 0.2741 <0.001 ***

KA - allometric condition factor; KF - Fulton′s condition factor; KR - relative condition factor; WR - relative weight; M - male; F - female; rs - Spearman rank-correlation values; CL - confidence limit; p - shows the level of significance; Ns - not significant; ***very highly significant

Fig. 4 — Relationship between total length (TL) and relative weight (WR) of Eutropiichthys vacha in the Ganges river both males and females. In contrast, air temperature Fig. 5 — Relationships between monthly temperature and mean reached an earlier peak of April to May. To confirm KF for males and females Eutropiichthys vacha in the Ganges the special effects of abiotic factors monthly on KF, river during 2016 Pearson correlation tests were used and there was no significant correlation between temperature and In contrast, there was significant correlation between KF (r = 0.2226, p = 0.4868 for males; r = 0.2172, rainfall and KF for males (r = 0.6357, p = 0.0263) and p = 0.4977 for females), as shown in Figure 5. females (r = 0.6983, p = 0.0115; Fig. 6).

KHATUN et al.: CONDITION AND PREY-PREDATOR STATUS OF E. VACHA 1235

During this study, several condition factors were studied to evaluate the overall health and productivity status of E. vacha in the Ganges River basin, although most of the prior study focused on a single condition factor (i.e., KF). In our study, KA ranged from 0.0076–0.0138 for males and 0.0087–0.0170 for females. But lower KA value was observed as (0.003–0.009) for males, with a mean value of 0.006 ± 0.001 in the Jamuna River of Bangladesh reported by Hossain et al.17 In this study, KF was significantly different for males (0.20 – 0.95) and females (0.51 – 1.13) (p < 0.0001), which may indicate the presence of adult females. KF value was 0.38 – 0.96 for males and 0.33 – 0.94 for females reported by Hossain et al.17, which were not significantly different between the sexes, which may indicate the lack of adult females for that study. Figure 1 showed that mean values of KF increased from April to August for both sexes, which may be due to plentiful food reserves and/or Fig. 6 — Relationships between monthly rainfall (mean in mm) suitable abiotic conditions12,17. Spearman rank- and mean KF for males and females Eutropiichthys vacha in the Ganges river during 2016 correlation test showed that, both males and females KF was significantly associated with TL and BW. Discussion Therefore, KF may be best condition for determining Information on body condition and prey-predator the well-being of this schilbid catfish in the Ganges status of E. vacha in the Ganges River is scant, except River and adjacent aquatic ecosystems. Also in this 17 study, KR was quite similar for males (0.74 – 1.33) from the Jamuna River in Bangladesh . This study, a 17 huge number of specimens with different sizes were and females (0.72 – 1.42) whereas Hossain et al. collected from the Ganges River through traditional reported KR as being significant higher for males fishing gear (gill and cast nets) throughout the year. (0.59 – 1.48) than females (0.54 – 1.16). The range of TL for males 6.2–19.9 cm TL and for In our study, mean relative weight (WR) was females 6.5–20.6 cm TL, but it was impossible to significantly divergent from 100 for females but not sample available catfish outside of this size range. in males, indicating that habitat was more suitable for The maximum length of E. vacha was observed as males to suggest an imbalance for food availability relative to predator presence for E. vacha in the 20.6 cm TL which is higher than the 16.95 cm, 29 previously sampled from Jamuna River17, however Ganges River basin . This may reflect inadequate lower than the largest recorded value of water quality for the E. vacha fishery there. E. vacha (a) 34.0 cm TL from Sindh, Pakistan23 and Furthermore, our WR was highest in May for males (b) globally recorded value of 38.4 cm TL30. and August for females (Fig. 5), when prey-predator The apparently smaller sizes of E. vacha landed in ratios may be highest. Also, WR was very low in the the Ganges River, as well as the apparent absence of month of August for males and February for females, larvae, indicate the need for multiple sampling gears which may specify relatively higher amounts of to improve for this species’ management31. Indeed, predators and/or other physiologic stresses. This is the the absence of both smaller and larger catfish first study to make inferences about prey-predator reflected the selectivity of the fishing gear32,33, rather relationships for E. vacha in the Ganges River, NW than their lack of fishing ground21,34,35. The maximum Bangladesh, but absence of available works dealing length information is very important for estimating with prey-predator relationships for this species the asymptotic length (L∞) and coefficient of fish’s prevents comparisons. growth, as well as for fisheries resource planning and Environmental factors affect the KF for both sexes management36-37. of E. vacha in the Ganges River basin, particularly 1236 INDIAN J GEO-MAR SCI, VOL 49, NO 07, JULY 2020

rainfall and river flows. Highest rainfall (monsoon Conservation of Nature, (Bangladesh Country Office, Dhaka) weather) was during June to July (350 – 389 mm 2015, pp. xvi+360. 3 Riede K, Global register of migratory species - from global monthly), which suggests that KF varies with to regional scales. Final Report of the R&D-Projekt 808 05 hydrologic conditions. In contrast, temperature did 081 (Federal Agency for Nature Conservation, Bonn, not vary significantly with KF. The highest air Germany) 2004, pp. 329. 4 Ng H H, Eutropiichthys vacha, The IUCN Red List of temperatures were observed in April to May, when KF was still low. After May, temperature began to Threatened Species 2010, e.T166491A6220391. doi:10.2305/IUCN.UK.2010,4.RLTS.T166491A6220391.en decrease, whereas KF was highest from June to (2010). Downloaded on 05 February 2019. September and peaked during June and July, 5 Talwar P K & Jhingran A G, Inland fishes of India and indicating optimum air temperatures of 32 – 35 °C for adjacent countries, Vol 2, edited by A A Balkema, this warm water species. After September, (Rotterdam, Netherlands) 1991, pp. 541. 6 Menon A G K, Checklist - freshwater fishes of India, temperature began to drop gradually. This is the first Records of the Zoological Survey of India (Occasional Paper study on the effects of temperature and rainfall on KF 175) 1999, pp. 366. for E. vacha, and comparative studies are needed for 7 Hasan M F, Molla A H, Ahsan M S & Alam M T, this catfish species, including (a) rainfall-stream flow Physicochemical properties and fatty acids distribution and air-water thermal relationships and (b) pattern in lipids of Eutropiichthys vacha Hamilton-Buchanan 38 (Family Schilbeidae), Pak J Biol Sci, 5 (2002) 696-698. examination of possible time lags in growth 8 Soomro A N, Baloch W A, Jafri S I H & Suzuki H, Studies responses to abiotic variation. In general, stream flow on length-weight and length-length relationship of catfish and thermal regimes affect the spawning, migration, Eutropiichthyes vacha Hamilton (Schilbeidae- Siluriformes) and growth/recruitment dynamics of game and forage from Indus River, Sindh, Pakistan, Caspian J Environ Sci, 39-44 5 (2007) 143-145. fishes in Eurasia . 9 Hossain M Y, Length-Weight, Length-length relationships Our findings describe the potentially best and condition factor of three schilbid catfishes from the conditions for temperature and rainfall potentials and Padma River, northwestern Bangladesh, Asian Fish Sci, prey-predators status of E. vacha, based on multi- 23 (2010) 329–339. model inferences. The results of our study will 10 Abbas A, Food and feeding habits of freshwater catfish Eutropiichthys vacha (Bleeker), Indian J Sci Res, 1 (2010) 83-86. contribute to improve sustainable management policy 11 Craig J F, Halls A S, Barr J J F & Bean C W, of E. vacha fishery in the Ganges River and other The Bangladesh floodplain fisheries, Fish Res, 66 (2004) aquatic ecosystems in South Asia. 271-286. 12 Hossain M Y, Jewel M A S, Nahar L, Rahman M M, Naif A Acknowledgements & Ohtomi J, Gonadosomatic index-based size at first sexual We are grateful to the TWAS for research grants. maturity of the catfish Eutropiichthys vacha (Hamilton 1822) in the Ganges River (NW Bangladesh), J Appl Ichthyol, 28 Robert L. Vadas Jr. thanks WDFW for the resources (2012a) 601-605. during manuscript preparation, but institutional 13 IUCN, IUCN Red list of threatened species, (Version endorsement is not implied. 2016.1). Downloaded on 03 December 2016. 14 IUCN, Bangladesh, Red book of threatened fishes of Conflict of Interest Bangladesh, edited by S M M H Khan, M M H Khan, R The authors declare that they have no conflicts of Ahmed, J N Banu, S Pavel, I A Neela, M A Islam & A Nishat, (World Conservation Union, Dhaka, Bangladesh) interest for the work. 2000, pp. Xi–116. 15 Sarker U K, Deepak P K & Negi R S, Length-weight Author Contributions relationship of Clown knifefish Chitala chitala (Hamilton, DK & MYH conceive the concept. OR, MRH & 1822) from the River Ganga basin, India, J Appl Ichthyol, ZM carried out sampling and MAH, MAI & MAR 25 (2009) 232-233. 16 Richter T J, Development and evaluation of standard weight carried out data analysis. DK, MAR & MFH write, equations for bridgelip suckers and large scale suckers, N Am review & edit the manuscript. MYH supervised the J Fish Manag, 27 (2007) 936-939. research. RLVJR. supported with resources. 17 Hossain M Y, Rahman M M, Jewel M A S, Hossain M A, Ahamed F, et al., Life history traits of the References critically endangered catfish Eutropiichthys vacha 1 Ng H H, Lalramliana, Lalronunga S & Lalnuntluanga, (Hamilton 1822) in the Jamuna (Brahmaputra River Eutropiichthys cetosus, a new riverine catfish (Teleostei: distributary) River, northern Bangladesh, Sains Malays, Schilbeidae) from northeastern India, J Threat Taxa, 42 (2013) 265-277. 6 (2014) 6073-6081. 18 Rose C J, Relationship between relative weight (WR) and 2 IUCN, Bangladesh, Red list of Bangladesh, Vol 5, immature body composition in walleye, M.S. thesis, Texas Freshwater Fishes, IUCN-International Union for A & M University, College Station, 1989. KHATUN et al.: CONDITION AND PREY-PREDATOR STATUS OF E. VACHA 1237

19 Rypel A L & Richter T J, Empirical percentile standard 32 Hossain M Y, Hossen M A, Khatun D, Nawer F, Parvin M F, weight equation for the blacktail redhorse, N Am J Fish et al., Growth, condition, maturity and mortality of the Manag, 28 (2008) 1843-1846. Gangetic leaf fish Nandus nandus (Hamilton, 1822) in the 20 Hossain M Y, Jasmine S, Ibrahim A H M, Ahmed Z F, Ganges River (northwestern Bangladesh), Jordan J Biol Sc, Rahman M M et al., Length-weight and length-length 10 (2017a) 57-62. relationships of 10 small fish species from the Ganges, 33 Nawer F, Hossain M Y, Hossen M A, Khatun D, Parvin M F, Bangladesh, J Appl Ichthyol, 25 (2009) 117-119. et al., Morphometric relationships of the endangered ticto 21 Khatun D, Hossain M Y, Parvin M F & Ohtomi J, barb Pethia ticto (Hamilton, 1822) in the Ganges River (NW Temporal variation of sex ratio, growth pattern and Bangladesh) through multi-linear dimensions, Jordan J Biol physiological status of Eutropiichthys vacha (Schilbeidae) in Sci, 10 (2017) 199-203. the Ganges River, NW Bangladesh, Zool Ecol, 28 (2018) 34 Hossain M Y, Pramanik M N U, Hossen M A, Nawer F, 343-354. Khatun D, et al., Life-history traits of pool barb Puntius 22 Khatun D, Hossain M Y, Nawer F, Mostafa A A & Al-Askar sophore (Cyprinidae) in different ecosystems of Bangladesh, A A, Reproduction of Eutropiichthys vacha (Schilbeidae) in Indian J Geo-Mar Sci, 47 (2018) 1446-1454. the Ganges River (NW Bangladesh) with special reference to 35 Hossen M A, Hossain M Y, Pramanik M N U, Khatun D, potential influence of climate variability, Environ Sci Pollut Nawer F, et al., Population parameters of the minor carp Res, 26 (2019) 10800-10815. Labeo bata (Hamilton, 1822) in the Ganges River of 23 Soomro A N, Baloch W A, Jafri S I H, Burdi G H & Fulanda northwestern Bangladesh, Jordan J Biol Sci, 11 (2018) B, Reproduction and feeding habits of the river catfish 179-186. Eutropiichthys vacha (Hamilton, 1822) (Siluriformes. 36 Azad M A K, Hossain M Y, Khatun D, Parvin M F, Nawer Schilbidae) in an impacted habitat: kotrihydrodam, River F, et al., Morphometric relationships of the tank goby Indus, Pakistan, Our Nature 10 (2012) 269-280. Glossogobius giuris (Hamilton, 1822) in the Gorai River 24 Jones T, Phillips B, Williams C E & Pittock J, Managing using multi-linear dimensions, Jordan J Biol Sci, 11 (2018) rivers wisely: Lesions from WWF’s work for integrated river 81-85. basin management, WWF (World Wildlife Fund) 37 Hossain M Y, Hossen M A, Ali M M, Pramanik M N U, International, Gland, Switzerland, 2003. Nawer F, et al., Life history traits of the endangered carp Botia dario (Cyprinidae) from the Ganges River in 25 Tesch F W, Age and growth, In: Methods for Assessment of northwestern Bangladesh, Pak J Zool, 49 (2017b) 801-809. Fish Production in Fresh Waters, edited by W E Ricker, 38 Vadas R L Jr, Beecher H A, Boessow S N & Kohr J H, (Blackwell Scientific Publications Oxford, UK) 1971, Coastal cutthroat trout red counts impacted by natural water pp. 98-130. supply variations, N Am J Fish Manag, 36 (2016) 900-912. 26 Fulton T W, The rate of growth of fishes, Twenty-second 39 Hynes H B N, The ecology of running waters (Liverpool Annual Report, Part III (Fisheries Board of Scotland, University Press, Liverpool, England) 1970, pp. 555. Edinburgh) 1904, pp. 141-241. 40 Naesje T F, Jonsson B & Sandlund O T, Drift of cisco and 27 Le Cren E D, The length-weight relationship and seasonal whitefish larvae in a Norwegian River, Trans Am Fish Soc, cycle in gonad weight and condition in the perch (Perca 115 (1986) 89-93. fluviatilis), J Anim Ecol, 20 (1951) 201-219. 41 Elliott J M, Pools as refugia for brown trout during two 28 Froese R, Cube law, condition factor and weight length summer droughts: Trout responses to thermal and oxygen relationships: history, meta-analysis and recommendations, stress, J Fish Biol, 56 (2000) 938-948. J Appl Ichthyol, 22 (2006) 241-253. 42 Vadas R L Jr, Instream-flow needs for anadromous 29 Anderson R O & Neumann R M, Length, weight and salmonids and lamprey on the Pacific Coast, with special associated structure indices, In: Fisheries techniques, edited reference to the Pacific Southwest, Environ Monit Assess, 64 by B R Murphy & W D Willis, (American Fisheries Society, (2000) 331-358. Bethesda, Maryland) 1996, pp. 447-482. 43 Lobón-Cerviá J & Mortensen E, Population size in stream- 30 Froese R & Pauly D (eds.) Fishbase, World Wide Web living juveniles of lake-migratory brown trout Salmo trutta electronic publication, Available at: L.: the importance of stream discharge and temperature, Ecol http://www.fishbase.orgversion (07/2019). Freshw Fish, 14 (2005) 394-401. 31 Vadas R L Jr. & Orth D J, A new technique for estimating 44 Nicola G G, Almodóvar A & Elvira B, Influence of the abundance and habitat use of stream fishes, Freshw Ecol, hydrologic attributes on brown trout recruitment in low- 8 (1993) 305-317. latitude range margins, Oecologia, 160 (2009) 515-524.