OPEN ACCESS PEER-REVIEWED | RESEARCH ARTICLE

Main Article Content

Authors

BG Hutubessy
VPY Likumahuwa
JW Mosse

Abstract

Fisheries management or conservation requires information on length-weight relationship (LWR) for the fishing regulation and biomass estimation. This study aims to assess LWR estimation using two methods, regular and Bayesian hierarchical approached for big-eye Scad (Selar crumenophthalmus). Samples of big eye Scad were collected at several fish landings around Ambon Island from March to August 2020. Length-weight relationship measurement to obtain the parameters of W = a*Lb was tested using generalized linear model and t-test. The parameter b for monthly sampling was not significantly different (F = 0.77, df = 70, P = 0.89) and showed isometric growth b=3 (t = -1.13, df = 4, P = 0.32). Regular measurement resulted parameter log10(a) = -1.99 (±SD = 1.06) dan b = 3.06 (±SD = 0.084). Bayesian method produced parameter log10(a) = -2.07 (±SD = 0.2365) dan parameter b = 3.21 (±SD = 0.1497). Weight measurement from HB approach was significantly higher than the regular method (t = 1.65; df = 405; P <0.0001), and might produce over-estimated of weight from length data. Discrepancy of these methods was overcome by combining all information of LWR to obtain the best estimation on LWR parameters.


Abstrak


Pengelolaan perikanan atau konservasi memerlukan informasi tentang bobot ikan untuk estimasi biomassa dan regulasi penangkapan. Tujuan penelitian ini adalah untuk membandingkan hubungan panjang-bobot hasil pendekatan hirarki bayesian dengan pengukuran regresi langsung ikan selar bentong, Selar crumenophthalmus. Ikan selar bentong dikoleksi dari lima tempat pendaratan ikan di Pulau Ambon dari bulan Maret hingga Agustus 2020. Pengukuran panjang total dan bobot ikan selar bentong bertujuan untuk memperoleh hubungan panjang-bobot dengan formulasi W = a*Lb. Uji general linear model dipakai untuk menguji parameter b (kemiringan) pada bulan pengamatan yang berbeda. Uji-t satu sampel dipakai untuk menguji pertumbuhan isometrik (b=3). Hasil penghitungan hubungan panjang-bobot berdasarkan pengukuran langsung dibandingkan dengan hasil estimasi dengan pendekatan bayesian dan diuji dengan uji-t. Nilai parameter b dari pengamatan langsung tidak berbeda untuk bulan pengamatan (F = 0,77, df = 70, P = 0,89) dan ikan selar memiliki pola pertumbuhan isometrik, b=3 (t = -1,13, df = 4, P = 0,32). Pengukuran regresi langsung memperoleh parameter log10(a) = -1,99 (±sb = 1,06) dan b = 3,06 (±sb = 0,084). Metode Bayesian menghasilkan parameter log10(a) = -2,07 (±sb = 0,2365) dan parameter b = 3,21 (±sb = 0,1497). Estimasi bobot dengan pendekatan bayesian terlalu tinggi (t = 1,65; df = 405; P < 0,0001), memungkinkan timbulnya bias pada pendugaan biomassa. Hasil ini berarti metode bayesian adalah over estimasi, sehingga perlu banyak data dan info yang digabung untuk menekan bias dalam mengestimasi hubungan panjang-bobot dan biomassa.

Keywords:
Bayesian method; big eye Scad; length-weight relationship;

Downloads article

Download data is not yet available.

Article Details

References

Adyp S. 2017. Biology and consumption trend of bigeye scad. Desertation of School of Biological Science, Universiti Sains Malaysia: Penang, Malaysia.


Andersen KH, Blanchard JL, Fulton EA, Gislason H, Jacobsen NS, Van Kooten T. 2016. Assumptions behind size-based ecosystem models are realistic. ICES Journal of Marine Science, 73(6): 1651–1655. https://doi.org/10.1093/icesjms/fsv211.


Bajer PG, Hayward RS. 2006. A combined multiple-regression and bioenergetics model for simulating fish growth in length and condition. Transactions of the American Fisheries Society, 135(3): 695–710.https://doi.org/10.1577/t05-006.1.


Bharadhirajan P, Mahadevan G, Murugesan P, Murugan S, Pouladi M, Naderi RA. 2019. Relative condition factor, length-weight relationship, and growth of three-spotted flounder, Pseudorhombus triocellatus from Parangipettai Coast, India. Biodiversitas, 20(2): 373–379. https://doi.org/10.13057/biodiv/d200210.


Chodrijah U, Faizah R. 2019. Biologi reproduksi selar bentong (Selar crumenophthalmus Bloch, 1793) di Perairan Kwandang, Gorontalo Utara. BAWAL Widya Riset Perikanan Tangkap, 10(3): 169. https://doi.org/10.15578/bawal.10.3.2018.169-177.


Fonseca VF, Cabral HN. 2007. Are fish early growth and condition patterns related to life-history strategies? Reviews in Fish Biology and Fisheries, 17(4): 545–564. https://doi.org/10.1007/s11160-007-9054-x.


Froese R, Pauly D. 2019. FishBase. World Wide Web electronic publication. .


Froese R, Thorson JT, Reyes RB. 2014. A Bayesian approach for estimating length-weight relationships in fishes. Journal of Applied Ichthyology, 30(1): 78–85. https://doi.org/10.1111/jai.12299


Froese R, Winker H, Coro G, Demirel N, Tsikliras AC, Dimarchopoulou D, Scarcella G, Probst WN, Dureuil M, Pauly D. 2018. A new approach for estimating stock status from length frequency data. ICES Journal of Marine Science, 75(6): 2004-2015 https://doi.org/10.1093/icesjms/fsy078.


Froese R. 2006. Cube law, condition factor and weight-length relationships: His-tory, meta-analysis and recommen-dations. Journal of Applied Ichthyology, 22(4): 241–253. https://doi.org/10.1111/j.1439-0426.2006.00805.x.


Greig HS, Niyogi DK, Hogsden KL, Jellyman PG, Harding JS. 2010. Heavy metals: Confounding factors in the response of New Zealand freshwater fish assemblages to natural and anthropo-genic acidity. Science of the Total Envi-ronment, 408(16): 3240–3250. https: //doi.org/10.1016/j.scitotenv.2010.04.006.


Hansen EA, Closs GP. 2009. Long-term growth and movement in relation to food supply and social status in a stream fish. Behavioral Ecology, 20(3): 616–623. https://doi.org/10.1093/beheco/arp039.


Hayes JW, Stark JD, Shearer KA. 2000. Development and test of a whole-lifetime foraging and bioenergetics growth model for drift-feeding brown trout. Transactions of the American Fisheries Society, 129(2): 315–332. https://doi.org/10.1577/1548-8659(2000)129<0315:datoaw>2.0.co;2.


Hiddink JG, Johnson AF, Kingham R, Hinz H. 2011. Could our fisheries be more productive? Indirect negative effects of bottom trawl fisheries on fish condition. Journal of Applied Ecology, 48(6): 1441–1449. https://doi.org/10.1111/j.1365-2664.2011.02036.x.


Hilborn R, Rochet M-J, Collie JS, Jennings S, Hall SJ. 2011. Does selective fishing conserve community biodiversity? Pre-dictions from a length-based multi-species model. Canadian Journal of Fisheries and Aquatic Sciences, 68(3): 469–486. https://doi.org/ 10.1139/F10-159.


Hilborn R, Walters CJ. 1992. Quantitative fisheries stock assessment. Quantitative Fisheries Stock Assessment, 49(0): 6221. https://doi.org/10.1007/978-1-4615-3598-0.


Jellyman PG, Booker DJ, Crow SK, Bonnett ML, Jellyman DJ. 2013. Does one size fit all? An evaluation of length-weight relationships for New Zealand’s freshwater fish species. New Zealand Journal of Marine and Freshwater Research. Taylor & Francis, 47(4): 450–468. https://doi.org/10.1080/00288330.2013.781510.


Jennings S, Jennings S, Blanchard JL, Blanchard JL. 2004. Fish abundance with no shing: predictions based on macroecological theory. Journal of Animal Ecology, (Pauly 1995): 632–642. https://doi.org/10.1111/j.0021-8790. 2004.00839.x.


Jisr N, Younes G, Sukhn C, El-Dakdouki MH. 2018. Length-weight relationships and relative condition factor of fish inhabiting the marine area of the Eastern Mediterranean city, Tripoli-Lebanon. Egyptian Journal of Aquatic Research, 44(4): 299–305. https://doi.org/10.1016/ j.ejar.2018.11.004.


Kimmerer W, Avent SR, Bollens SM, Feyrer F, Grimaldo LF, Moyle PB, Nobriga M, Visintainer T. 2005. Variability in length–weight relationships used to estimate biomass of estuarine fish from survey data. Transactions of the American Fisheries Society, 134(2): 481–495. https://doi.org/10.1577/t04-042.1.


Matakupan Hansje, Tuapetel F. 2017. Potensi dan tingkat pemanfaatan ikan kawalinya (Selar spp.) di Pulau Ambon. Amanisal, 6(2): 16–20.


Ndiaye W, Diouf K, Samba O, Ndiaye P, Panfili J, Marbec UMR, Montpellier U De, Bataillon PE. 2015. The length-weight relationship and condition factor of white grouper (Epinephelus aeneus, Geoffroy Saint Hilaire, 1817) at the south-west coast of Senegal, West Africa. International Journal of Advanced Research, 3(3): 145–153.


Rutherford A. 2012. ANOVA and ANCOVA. A GLM Approach. Statistics in Medicine. Wiley. A John Wiley & Sons, Inc. Publication.


Safran P. 1992. Theoretical analysis of the weight-length relationship in fish juveniles. Marine Biology, 112(4): 545–551. https://doi.org/10.1007/BF00346171.


Siwat V, Ambariyanto A, Widowati I. 2016. Biometrics of bigeye scad, Selar crumenophthalmus and shrimp scad, Alepes djedaba from Semarang waters, Indonesia. AACL Bioflux, 9(4): 915–922.


Smith-Vaniz W., Quéro J-C, Desoutter M. 1990. Check-list of the fishes of the eastern tropical Atlantic (CLOFETA). In: J.C. Quero, J.C. Hureau, C. Karrer AP and LS (ed) Volume 2. JNICT, Lisbon; SEI, Paris; and UNESCO, Paris: Lisbon, pp. 729-755.


Thorson JT, Hicks AC, Methot RD. 2015. Random effect estimation of time-varying factors instock synthesis. ICES Journal of Marine Science, 72(1): 178–185. https://doi.org/10.1093/icesjms/fsr174.