SavedAdd your journal

Journals / Turkish Journal of Fisheries and Aquatic Sciences / 2011 / Cilt: 11 - Sayı: 2

Songkhla Gölü’nde 2003-2006 yılları arasında iki aylık peryotlar halinde elde edilen veriler ile balık topluluk yapısının tasnif edilmesi için bir model

Sarawuth CHESOH
Chamnein CHOONPRADUP
Pages
177–184
Publication Date
2022-11-06
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Such models can provide further tools in understanding of fish community structure clusterings in fishery landings.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Monthly catch weights in Songkhla Lake were collected over the period from January 2003 to December 2006, for a total of 126 species.
📊
Key Findings & Data:The first component was represented by the most species of estuarine and marine vertebrates as well as some invertebrates and reflected the fact that set bag net was the gear that resulted in the highest catches.
💡
Conclusion & Impact:Such models can provide further tools in understanding of fish community structure clusterings in fishery landings.
🔬Design:Modeling & Simulation
📍Scope:2003 Verileri
⚙️Variables:Domain Parameters

Abstract

Monthly catch weights in Songkhla Lake were collected over the period from January 2003 to December 2006, for a total of 126 species. Catch weights were first aggregated by species and combination of bi-monthly season of year and catching gear (set bag net, trap, or gill net) and were log-transformed to remove skewness. A regression model containing three species-season/gear components was then used to predict these outcomes. The first component was represented by the most species of estuarine and marine vertebrates as well as some invertebrates and reflected the fact that set bag net was the gear that resulted in the highest catches. The second component mainly represented freshwater fish and some marine invertebrates, and reflected the fact that most of these species were caught by gill nets. The third component focused on the seasonal fluctuations in catch weight. Such models can provide further tools in understanding of fish community structure clusterings in fishery landings.

🔖

Cite This Article

CHESOH, S., CHOONPRADUP, C. (2022). Songkhla Gölü’nde 2003-2006 yılları arasında iki aylık peryotlar halinde elde edilen veriler ile balık topluluk yapısının tasnif edilmesi için bir model. Turkish Journal of Fisheries and Aquatic Sciences, Cilt: 11 - Sayı: 2, 177–184. https://ajindex.com/articles/606070

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (11)

  1. Booth, H., Maindonard, J. and Smith, L. 2002. Applying Lee-Carter under conditions of variable mortality decline. Population Studies, 56: 325-336.
  2. Chen, Y., Chen, X. and Xu, L. 2008. Developing a size indicator for fish populations. Scientia Marina, 72: 221–229.
  3. Chesoh, S. and Lim, A. 2008. Forecasting fish catches in the Songkhla Lake basin. ScienceAsia, 34: 335–340.
  4. Choonhapran, A. 1996. Study on Fisheries Resources and Population Changes in Songkhla Lake: Case study on 3 fishing gears. Technical paper 18/1996, National Institute of Coastal Aquaculture (NICA), Songkhla, Thailand, 32 pp. Clarke, K.R. and Warwick, R.M. 1994. Change in Marine Communities: An Approach to Statistical Analysis and İnterpretation. Prımere Ltd, Plymouth, 144 pp. Dufrêne, M. and Legendre, P. 1997. Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecological Monographs, 67: 345–366. Frédou, T., Ferreira, B.P. and Letourneur, Y. 2006. A univariate and multivariate study of reef fisheries off northeastern Brazil. ICES Journal of Marine Science, 63: 883–896.
  5. Hajisamae, S., Yeesin, P. and Chaimongkol, S. 2006. Habitat utilization by fishes in a shallow, semienclosed estuarine bay in southern Gulf of Thailand. Estuarine, Coastal Shelf Science, 68: 647–655.
  6. Hawkins, C.P., Norris, R.H., Hogue, J.N. and Feminella, J.W. 2000. Development and evaluation of predictive models for measuring the biological integrity of streams. Ecological Applications, 10: 1456–1477.
  7. Joy, M.K. and Death, R.G. 2000. Development and application of a predictive model of riverine fish community assemblages in the Taranaki region of the North Island, New Zealand. New Zealand Journal of Marine and Freshwater Research, 34: 243–254.
  8. Kangur, K., Park, Y.-S., Kangur, A., Kangur, P. and Lek, S. 2007. Patterning long-term changes of fish community in large shallow Lake Peipsi. Ecological Modelling, 203: 34-44.
  9. Katselis, G., Koutsikopoulos, C., Dimitriou, E. and Rogdakis, Y. 2003. Spatial patterns and temporal trends in the fishery landings of the MessolonghiEtoliko lagoon system (western Greek coast). Scientia Marina, 67: 501–511.
  10. Labropoulou, M. and Papaconstantinou, C. 2004. Community structure and diversity of demersal fish assemblages: the role of fishery. Scientia Marina, 68: 215–226.
  11. Lee, R.D. and Carter, L.R. 1992. Modelling and forecasting U.S. mortality. Journal of the American Statistical Association, 87: 659–671. Mahévas, S., Bellanger, L. and Trenkel, V.M. 2008. Cluster