BibTex RIS Kaynak Göster

A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006

Yıl 2011, Cilt: 11 Sayı: 2, - , 01.04.2011

Sarawuth Chesoh Chamnein Choonpradub

Öz

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.

Anahtar Kelimeler

Fish assemblage distribution Regression model Lake fishery

Kaynakça

  • Booth, H., Maindonard, J. and Smith, L. 2002. Applying Lee-Carter under conditions of variable mortality decline. Population Studies, 56: 325-336.
  • Chen, Y., Chen, X. and Xu, L. 2008. Developing a size indicator for Şsh populations. Scientia Marina, 72: 221—229.
  • Chesoh, S. and Lim, A. 2008. Forecasting Şsh catches in the Songkhla Lake basin. ScienceAsia, 34: 335—340.
  • Choonhapran, A. 1996. Study on Fisheries Resources and Population Changes in Songkhla Lake: Case study on 3 Şshing 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 Interpretation. Primere Ltd, Plymouth, 144 pp.
  • Dufréne, M. and Legendre, P. 1997. Species assemblages and indicator species: the need for a şexible asymmetrical approach. Ecological Monographs, 67: 345—366.
  • Frédou, T., Ferreira, B.P. and Letourneur, Y. 2006. A univariate and multivariate study of reef Şsheries off northeastern Brazil. ICES Journal of Marine Science, 63: 883—896.
  • Hajisamae, S., Yeesin, P. and Chaimongkol, S. 2006. Habitat utilization by Şshes in a shallow, semi—enclosed estuarine bay in southern Gulf of Thailand. Estuarine, Coastal Shelf Science, 68: 647— 655.
  • 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.
  • Joy, MK. and Death, R.G. 2000. Development and application of a predictive model of riverine Şsh community assemblages in the Taranaki region of the North Island, New Zealand. New Zealand Journal of Marine and Freshwater Research, 34: 243—254.
  • Kangur, K., Park, Y.-S., Kangur, A., Kangur, P. and Lek, S. 2007. Patterning long-term changes of Şsh community in large shallow Lake Peipsi. Ecological Modelling, 203: 34-44.
  • Katselis, G., Koutsikopoulos, C., Dimitriou, E. and Rogdakis, Y. 2003. Spatial patterns and temporal trends in the Şshery landings of the Messolonghi—Etoliko lagoon system (western Greek coast). Scientia Marina, 67: 501—511.
  • Labropoulou, M. and Papaconstantinou, C. 2004. Community structure and diversity of demersal Şsh assemblages: the role of Şshery. Scientia Marina, 682 215—226.
  • Lee, RD. 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 analysis of linear model coefŞcients under contiguity constraints for identifying spatial and temporal Şshing effort patterns. Fisheries Ressearch, 93: 29—38
  • Morris, L. and Ball, D. 2006. Habitat suitability modelling of economically important Şsh species with commercial Şsheries data. ICES Journal of Marine Science, 63: 1590—1603.
  • National Institute of Coastal Aquaculture (NICA) 2007. Annual report 2006. National Institute of Coastal analysis and graphics version 2.6.2 (2008—2—08). Aquaculture. Department of Fisheries, Ministry of [Online] Available: http://cran.r-project.org/doc/ Agriculture and Co-operatives, Bangkok, 102 pp. manuals/R-intro.pdf. (May 20, 2007)
  • Polunin, N.V.C. 2008. Aquatic ecosystems: trends and Welcomme, R.L., Winemiller, K.O. and Cowx, I.G. 2006. global prospects. Cambridge University Press, Fish environmental guilds as a tool for assessment of Cambridge, 499 pp. ecological condition of rivers. River Research
  • Venables, W.N. and Smith, D.M. 2004. An introduction to Applications, 22: 377—396. R: Notes on R: A programming environment for data

A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006

Yıl 2011, Cilt: 11 Sayı: 2, - , 01.04.2011

Sarawuth Chesoh Chamnein Choonpradub

Öz

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.

Anahtar Kelimeler

Fish assemblage distribution Regression model Lake fishery

Kaynakça

  • Booth, H., Maindonard, J. and Smith, L. 2002. Applying Lee-Carter under conditions of variable mortality decline. Population Studies, 56: 325-336.
  • Chen, Y., Chen, X. and Xu, L. 2008. Developing a size indicator for Şsh populations. Scientia Marina, 72: 221—229.
  • Chesoh, S. and Lim, A. 2008. Forecasting Şsh catches in the Songkhla Lake basin. ScienceAsia, 34: 335—340.
  • Choonhapran, A. 1996. Study on Fisheries Resources and Population Changes in Songkhla Lake: Case study on 3 Şshing 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 Interpretation. Primere Ltd, Plymouth, 144 pp.
  • Dufréne, M. and Legendre, P. 1997. Species assemblages and indicator species: the need for a şexible asymmetrical approach. Ecological Monographs, 67: 345—366.
  • Frédou, T., Ferreira, B.P. and Letourneur, Y. 2006. A univariate and multivariate study of reef Şsheries off northeastern Brazil. ICES Journal of Marine Science, 63: 883—896.
  • Hajisamae, S., Yeesin, P. and Chaimongkol, S. 2006. Habitat utilization by Şshes in a shallow, semi—enclosed estuarine bay in southern Gulf of Thailand. Estuarine, Coastal Shelf Science, 68: 647— 655.
  • 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.
  • Joy, MK. and Death, R.G. 2000. Development and application of a predictive model of riverine Şsh community assemblages in the Taranaki region of the North Island, New Zealand. New Zealand Journal of Marine and Freshwater Research, 34: 243—254.
  • Kangur, K., Park, Y.-S., Kangur, A., Kangur, P. and Lek, S. 2007. Patterning long-term changes of Şsh community in large shallow Lake Peipsi. Ecological Modelling, 203: 34-44.
  • Katselis, G., Koutsikopoulos, C., Dimitriou, E. and Rogdakis, Y. 2003. Spatial patterns and temporal trends in the Şshery landings of the Messolonghi—Etoliko lagoon system (western Greek coast). Scientia Marina, 67: 501—511.
  • Labropoulou, M. and Papaconstantinou, C. 2004. Community structure and diversity of demersal Şsh assemblages: the role of Şshery. Scientia Marina, 682 215—226.
  • Lee, RD. 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 analysis of linear model coefŞcients under contiguity constraints for identifying spatial and temporal Şshing effort patterns. Fisheries Ressearch, 93: 29—38
  • Morris, L. and Ball, D. 2006. Habitat suitability modelling of economically important Şsh species with commercial Şsheries data. ICES Journal of Marine Science, 63: 1590—1603.
  • National Institute of Coastal Aquaculture (NICA) 2007. Annual report 2006. National Institute of Coastal analysis and graphics version 2.6.2 (2008—2—08). Aquaculture. Department of Fisheries, Ministry of [Online] Available: http://cran.r-project.org/doc/ Agriculture and Co-operatives, Bangkok, 102 pp. manuals/R-intro.pdf. (May 20, 2007)
  • Polunin, N.V.C. 2008. Aquatic ecosystems: trends and Welcomme, R.L., Winemiller, K.O. and Cowx, I.G. 2006. global prospects. Cambridge University Press, Fish environmental guilds as a tool for assessment of Cambridge, 499 pp. ecological condition of rivers. River Research
  • Venables, W.N. and Smith, D.M. 2004. An introduction to Applications, 22: 377—396. R: Notes on R: A programming environment for data
Toplam 19 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Sarawuth Chesoh Bu kişi benim

Chamnein Choonpradub Bu kişi benim

Yayımlanma Tarihi 1 Nisan 2011
Yayımlandığı Sayı Yıl 2011 Cilt: 11 Sayı: 2

Kaynak Göster

APA Chesoh, S., & Choonpradub, C. (2011). A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006. Turkish Journal of Fisheries and Aquatic Sciences, 11(2).
AMA Chesoh S, Choonpradub C. A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006. Turkish Journal of Fisheries and Aquatic Sciences. Nisan 2011;11(2).
Chicago Chesoh, Sarawuth, ve Chamnein Choonpradub. “A Model for Clustering Fish Community Structure With Application to Songkhla Lake Bi-Monthly Catches 2003-2006”. Turkish Journal of Fisheries and Aquatic Sciences 11, sy. 2 (Nisan 2011).
EndNote Chesoh S, Choonpradub C (01 Nisan 2011) A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006. Turkish Journal of Fisheries and Aquatic Sciences 11 2
IEEE S. Chesoh ve C. Choonpradub, “A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006”, Turkish Journal of Fisheries and Aquatic Sciences, c. 11, sy. 2, 2011.
ISNAD Chesoh, Sarawuth - Choonpradub, Chamnein. “A Model for Clustering Fish Community Structure With Application to Songkhla Lake Bi-Monthly Catches 2003-2006”. Turkish Journal of Fisheries and Aquatic Sciences 11/2 (Nisan 2011).
JAMA Chesoh S, Choonpradub C. A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006. Turkish Journal of Fisheries and Aquatic Sciences. 2011;11.
MLA Chesoh, Sarawuth ve Chamnein Choonpradub. “A Model for Clustering Fish Community Structure With Application to Songkhla Lake Bi-Monthly Catches 2003-2006”. Turkish Journal of Fisheries and Aquatic Sciences, c. 11, sy. 2, 2011.
Vancouver Chesoh S, Choonpradub C. A Model for Clustering Fish Community Structure with Application to Songkhla Lake Bi-monthly Catches 2003-2006. Turkish Journal of Fisheries and Aquatic Sciences. 2011;11(2).