Estimation of morphometric relationships for flathead sillago, Sillaginopsis panijus (Hamilton, 1822) in the Bay of Bengal (Bangladesh) using multi-linear dimensions

253-257This study on flathead sillago, Sillaginopsis panijus (Hamilton 1822) estimates the first morphometric relationships from the marine ecosystem, Bay of Bengal, Bangladesh using multi-linear dimensions. Additionally, meristic counts for different fin-rays were done. Alltogether, 204 specimens were captured during July 2018 to June 2019 by several gears including seine net and long lines. Morphometric measurements as well as body weight (BW) were recorded for each individual. The LWRs (length-weight relationships) were assessed as: W = a × Lb. Lateral line scales and fin rays were observed by magnifying glass. The LWRs and LLRs (length-length relationships) were found significant (p r2 values being ≥ 0.913 and ≥ 0.952, respectively. Based on r2 values, LWRs by BW vs. SL and for LLRs, TL vs. FL were found as the best model. Fin formula observed for S. panijus is D1 IX; D2 I/24-28; P.17-20; Pv.1/5; A I-II/24-27; C 2/16-18. Scales on lateral line were ~82-86. This investigation should be helpful for resource management in the marine ecosystems of Bangladesh and other subtropical countries

Morphometric and meristic characteristics of Spotted snakehead Channa punctata (Bloch, 1793) in a wetland ecosystem (NW Bangladesh) using multi-linear dimensions

1442-1446This research work affirms the morphometric characters and meristic counts of Channa punctata (Bloch, 1793) in a wetland ecosystem (Gajner Beel) from the northwestern Bangladesh. A sum of 307 specimens of C. punctata were sampled intermittently from the Gajner Beel during July 2017 to December 2018, using different established fishing gears (cast net, gill net and square lift net with mesh size ranges: 1.50-2.50 cm, 1.50-2.00 cm, & ~2.00 cm, respectively). Fin rays were counted by a magnifying glass. Seven diverse morphometric lengths were assessed and BW (body weight) was weighted for each specimen. The fin formula was: dorsal, D. 30-32; pectoral, P1. 15-17; pelvic, P2.5; anal, A. 19-21; and caudal, C. (ii -iv/12-14). Minimum and maximum sizes were 5.80 and 23.00 cm in total length (TL), whereas BWs were1.96 and 126.90 g, respectively. All length-weight relationships (LWRs) were greatly significant (p < 0.001) with r2 ≥ 0.986. Based on r2 value, BW = 0.0112*(TL)2.98 was the most appropriate model among seven equations. Besides, based on r2 values, length-length relationships (LLRs) by TL vs. SL was the finest model among six equations. These findings will help for species identification and further stock/ biomass estimation of C. punctata in the Gajner Beel or connected ecosystems

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Not AvailableEffective fisheries management depend on having an exact assessment of biological parameters, including growth parameters, reproduction, size at sexual maturity (Lm), and stock assessment. The purpose of this research was to estimate the size at sexual maturity (Lm) for 20 fish species belongs to 14 families from a wetland (Gajner Beel) ecosystem in the north-western (NW) Bangladesh through multi-models such as length (Lmax) based empirical model, gonadosomatic index (GSI)-based model, and logistic model using commercial catches from January to December 2018. Also, we assessed the Lm in other water-bodies worldwide. Specimens’ total length (TL) was noted up to 0.1 cm using measuring board body weight (BW) and gonad weight (GW) weighed by digital electronic balance with 0.01 g accuracy. To assess the Lm, maximum body length (Lmax) based empirical model; the relation between TL (total length in cm) vs. GSI (gonadosomatic index in %); and a logistic model were considered. The minimum Lm was 4.64, 3.90, and 4.15 cm for Chanda nama Hamilton, 1822 and the maximum was 25.33, 24.50, and 24.70 cm for Channa striata (Bloch, 1793) through Lmax, GSI, and logistic-based models, respectively. From these three models, the minimum mean Lm was 4.23 cm for C. nama and the maximum was 24.84 cm for C. striata. The Lm with 50.0% species was in 8.80 cm TL. We also calculated the Lm from different bodies of water based on Lmax. This study was generated data of 17 new Lm among 20 species, which are globally absent. Therefore, the study will help develop sustainable management strategies, conservation through the implementation of mesh size based on the size at sexual maturity (Lm).Not Availabl

Correction to: Human ancestry identification under resource constraints -- what can one chromosome tell us about human biogeographical ancestry?

Background: While continental level ancestry is relatively simple using genomic information, distinguishing between individuals from closely associated sub-populations (e.g., from the same continent) is still a difficult challenge. Methods: We study the problem of predicting human biogeographical ancestry from genomic data under resource constraints. In particular, we focus on the case where the analysis is constrained to using single nucleotide polymorphisms (SNPs) from just one chromosome. We propose methods to construct such ancestry informative SNP panels using correlation-based and outlier-based methods. Results: We accessed the performance of the proposed SNP panels derived from just one chromosome, using data from the 1000 Genome Project, Phase 3. For continental-level ancestry classification, we achieved an overall classification rate of 96.75% using 206 single nucleotide polymorphisms (SNPs). For sub-population level ancestry prediction, we achieved an average pairwise binary classification rates as follows: subpopulations in Europe: 76.6% (58 SNPs); Africa: 87.02% (87 SNPs); East Asia: 73.30% (68 SNPs); South Asia: 81.14% (75 SNPs); America: 85.85% (68 SNPs). Conclusion: Our results demonstrate that one single chromosome (in particular, Chromosome 1), if carefully analyzed, could hold enough information for accurate prediction of human biogeographical ancestry. This has significant implications in terms of the computational resources required for analysis of ancestry, and in the applications of such analyses, such as in studies of genetic diseases, forensics, and soft biometrics