| Chilean jack mackerel(Trachurs murphyi) is an important species of oceanic fishery, and widely distributing in the South-east Pacific Ocean. Jack mackerel has been paid more and more concern from many countries for its plentiful stock, and has been taken as a management species by South-east Pacific Regional Fishery Management Organization. In order to execute the responsibility of resources conservation and sustainable utilization to maintenance the rights and interests of China, we have to carry on the research work and survey in depth on Chilean jack mackerel fishing ground and habitat suitability index. The commercial fishing data of Chilean jack mackerel together with marine environment data, including sea surface temperature(SST), sea surface temperature anomaly(SSTA), sea surface salinity(SSS), sea surface height relative to geoid(SSH) and Chlorophyll-a concentration(Chl-a), etc were collected by the paper from 2008 to 2013. The research purpose is to analyze the relationship between marine environment variables and catch per unit effort(CPUE) by Quantile regression analysis, to derive the single factor and multi factorin seasonal habitate suitability index(HSI) models.Analyse and compare optimal model, so as to reveal the distribution of Pacific Ocean southeast of Chilean jack mackerel Trachurus murphyi habitat, temporal and spatial distribution and habitat and Chilean jack mackerel Trachurus murphyi fishing ground and examples of results are proved. The results were as followed:(1) The fishing ground of Chilean jack mackerel is mainly between 32~43°S in south-north distribution and between 79~90°W in east-west distribution. from each catch is mainly came from the water of 80°-83°W, 10°-16°S. Most of the catches are from the water area described above, taking 88.75 per cent and 76.35 per cent of total catches by each.(2) According to the single factor and multi-factors of quantile regression HSI model, the best suitable water area generally appeared during Jun. to August, and the worst is during Dec. to Feb.. However, the HSI area calculated by multi-factorsmethod is bigger than that calculated by single factor method.(3) Two HSI models by use of the single factor and multi-factors are all acceptable. HSI level were divided into 5 ranks: 0~0.2,0.2~0.4,0.4~0.6,0.6~0.8,0.8~1.0. The highest catch appeared in the range of HSI from 0.6 to 0.8. The percentages of two HSI model’s accumulated catch are 85.23% and 51.55%. The highest mean catch per net is in the range from 0.8 to 1.0. The distribution of catch is closely related with the HSI model by use of multi-factors, the indicator(P=0.00026, P<0.001) is better than the other one with quadratic function(P=0.00048, P<0.001).(4) Distribution of fishing ground of 2013 was verified by use of weighted sum. The percentage of accumulated catch was 79.83% in the range of HSI from 0.6 to 1.0 the indicator P=0.00034, P<0.001. The highest mean catch per net, 34.59 ton, is in the range of HSI from 0.8 to 1.0.(5) Comparing with single-factor and multiple-factors HSImodels basing quantile regression, multiple-factors HSI model predict the quality of habitat of Chilean jack mackerel better. The analyzing result indicated that the multiple-factors HSI model can be used as a prediction model for Chilean jack mackerel in South-east Pacific.However, in view of the fact that the measured marine environmental data what can be collected, the single factor HSI model can also be used to predict the distribution of the fishing ground of Chilean jack mackerel in South-east Pacific. |
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