Aanlyzing spatial aggregation of <em>Ommastrephes bartramii</em> in the Northwest Pacific Ocean based on Voronoi diagram and spatial autocorrelation

Feng Yongjiu; Yang Mingxia; Chen Xinjun

doi:10.3969/j.issn.0253-4193.2014.12.007

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Feng Yongjiu, Yang Mingxia, Chen Xinjun. Aanlyzing spatial aggregation of Ommastrephes bartramii in the Northwest Pacific Ocean based on Voronoi diagram and spatial autocorrelation[J]. Haiyang Xuebao, 2014, 36(12): 74-84. doi: 10.3969/j.issn.0253-4193.2014.12.007

Citation:

Feng Yongjiu, Yang Mingxia, Chen Xinjun. Aanlyzing spatial aggregation of Ommastrephes bartramii in the Northwest Pacific Ocean based on Voronoi diagram and spatial autocorrelation[J]. Haiyang Xuebao, 2014, 36(12): 74-84. doi: 10.3969/j.issn.0253-4193.2014.12.007

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Aanlyzing spatial aggregation of Ommastrephes bartramii in the Northwest Pacific Ocean based on Voronoi diagram and spatial autocorrelation

doi: 10.3969/j.issn.0253-4193.2014.12.007

1.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China;National Distant-water Fisheries Engineering Research Center, Shanghai Ocean University, Shanghai 201306, China;Collaborative Innovation Center for Distant-water Fisheries, Shanghai 201306, China
2.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China

Received Date: 2014-01-02
Rev Recd Date: 2014-03-27

Abstract

Abstract

An integrated method of Voronoi diagram and spatial autocorrelation was used to explore global spatial pattern, local spatial hot spot and its variation of fishery resources abundance of Ommastrephes bartramii in the Northwest Pacific Ocean. The O. bartramii within the boundaries from 38°N to 45°N and 150°E to 160°E from 2007 to 2010 in the Northwest Pacific Ocean was selected as the research subjects, based on the original fishing data of each fishing boat of China. Using an ArcGIS environment, the spatial aggregation patterns of O. bartramii were revealed by using the global spatial autocorrelation statistics of both Moran's I and General G, as well as mapped both spatially and visually. In the fields of fisheries resources and spatial analysis, sea areas with clustered high productivity are hot spots, whereas sea areas with clustered low productivity are cold spots. The local spatial autocorrelation statistics show that, there were 2 hot spots and 1 cold spot in both 2007 and 2009, and there were 1 hot spot and 1 cold spot in 2008, while there were 1 hot spot and 2 cold spot in 2010. These hot or cold spots were distributed along either a north-south or an east-west axis. An overlay map of the four years of hot/cold spots demonstrates that there was 1 strong hot spot, 1 weak hot spot and 1 strong cold spot across the study area. The strong hot/cold spots were always the same spots for each year, while the weak hot spot was changed its state between a hot spot and a cold spot. An analysis of the variation of spatial hot spots based on monthly mean (July to November) sea surface temperature (SST) and monthly mean (July to November) chlorophyll-a concentration (Chl a) demonstrated that, both hot spots and cold spots are central fishing grounds. There is not obvious difference of SST between the hot and cold spots, while the hot and cold spots were observed in the areas with 0.2 to 1.1 mg/m³ Chl a concentration but the Chl a concentration of a cold spot is larger than that of a hot spot.
- spatial hot spot,
- Voronoi diagram,
- spatial autocorrelation,
- Ommastrephes bartramii,
- Northwestern Pacific Ocean

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