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Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean
- Journal of Oceanology and Limnology Vol. 35, Issue 4, Pages: 921-935(2017)
- Affiliations：
1. College of Marine Sciences Shanghai Ocean University
2. Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources (Shanghai Ocean University) Ministry of Education
3. National Engineering Research Center for Oceanic Fisheries (Shanghai Ocean University)
4. Collaborative Innovation Center for Distant-water Fisheries
5. School of Geography Planning and Environmental Management University of Queensland
- Author bio：
- Funds：
DOI：10.1007/s00343-017-6036-2
CLC：-
Online First：12 August 2016，
Published：2017
- Accepted：
Scan QR Code
Feng, Y., Chen, X. & Liu, Y. Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean., Chin. J. Ocean. Limnol. 35, 921–935 (2017). https://doi.org/10.1007/s00343-017-6036-2
摘要
Abstract
With the increasing effects of global climate change and fishing activities
the spatial distribution of the neon flying squid (Ommastrephes bartramii) is changing in the traditional fishing ground of 150°–160°E and 38°–45°N in the northwest Pacific Ocean. This research aims to identify the spatial hot and cold spots (i.e. spatial clusters) of O. bartramii to reveal its spatial structure using commercial fishery data from 2007 to 2010 collected by Chinese mainland squid-jigging fleets. A relatively strongly-clustered distribution for O. bartramii was observed using an exploratory spatial data analysis (ESDA) method. The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from 2008 to 2010. The hot and cold spots in 2007 occupied 8.2% and 5.6% of the study area
respectively; these percentages for hot and cold spot areas were 5.8% and 3.1% in 2008
10.2% and 2.9% in 2009
and 16.4% and 11.9% in 2010
respectively. Nearly half (>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8% in 2010
indicating that the hot spot areas are central fishing grounds. A further change analysis shows the area centered at 156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010. Furthermore
the hot spots were mainly identified in areas with sea surface temperature (SST) in the range of 15–20°C around warm Kuroshio Currents as well as with the chlorophyll-a (chl-a) concentration above 0.3 mg/m3. The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O. bartramii and is useful for sustainable exploitation
assessment
and management of this squid.
关键词
Keywords
references
Aldwaik S Z, Pontius Jr R G. 2012. Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition. Landscape and Urban Planning, 106(1): 103–114.
Anselin L. 1995. Local indicators of spatial association-LISA. Geographical Analysis, 27(2): 93–115.
Anselin L. 2005. Exploring Spatial Data with GeoDaTM: A Workbook. Spatial Analysis Laboratory, Department of Geography, University of Illinois at Urbana-Champaign, Urbana, IL.
Bower J R, Ichii T. 2005. The red flying squid (Ommastrephes bartramii): A review of recent research and the fishery in Japan. Fisheries Research, 76(1): 39–55.
Chen C S, Chiu T S. 1999. Abundance and spatial variation of Ommastrephes bartramii (Mollusca: Cephalopoda) in the eastern North Pacific observed from an exploratory survey. Acta Zoologica Taiwanica, 10(2): 135–144.
Chen X J, Cao J, Chen Y, Liu B L, Tian S Q. 2012. Effect of the Kuroshio on the spatial distribution of the red flying squid Ommastrephes Bartramii in the Northwest Pacific Ocean. Bulletin of Marine Science, 88(1): 63–71.
Chen X J, Chen Y, Tian S Q, Liu B L, Qian W G. 2008a. An assessment of the west winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the northwest Pacific Ocean. Fisheries Research, 92(2–3): 221–230.
Chen X J, Liu B L, Chen Y. 2008b. A review of the development of Chinese distant-water squid jigging fisheries. Fisheries Research, 89(3): 211–221.
Chen X J, Tian S Q, Chen Y, Cao J, Ma J. 2011. Fishery Biology for Ommastrephes bartramii in the Northwestern Pacific Ocean. Science Press, Beijing. (in Chinese)
Chun Y W, Griffith D A. 2013. Spatial Statistics and Geostatistics: Theory and Applications for Geographic Information Science and Technology. SAGE, London.
Cournane J M, Kritzer J P, Correia S J. 2013. Spatial and temporal patterns of anadromous alosine bycatch in the US Atlantic herring fishery. Fisheries Research, 141: 88–94.
de Smith M J, Goodchild M F, Longley P. 2007. Geospatial ANALYSIS: A Comprehensive Guide to Principles, Techniques and Software Tools. 2nd edn. Troubador Publishing Ltd, Leicester, UK.
Du Y Y, Zhou C H, Shao Q Q, Su F Z. 2002. Extracting spatiotemporal patterns from ocean fishery dataset in East China Sea using spatial cluster. High Technology Letters, 12(1): 91–95. (in Chinese with English abstract)
Feng Y J, Chen X J, Liu Y. 2016. The effects of changing spatial scales on spatial patterns of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. Fisheries Research, 183: 1–12.
Feng Y J, Chen X J, Yang M X, Huo D, Zhu G P. 2014b. An exploratory spatial data analysis-based investigation of the hot spots and variability of Ommastrephes bartramii fishery resources in the northwestern Pacific Ocean. Acta Ecologica Sinica, 34(7): 1841–1850. (in Chinese with English abstract)
Feng Y J, Chen X J, Yang X M, Gao F. 2014c. HSI modeling and intelligent optimization for fishing ground forecasts using a genetic algorithm. Acta Ecologica Sinica, 34(15): 4333–4346. (in Chinese with English abstract)
Feng Y J, Yang M X, Chen X J. 2014a. Analyzing spatial aggregation of Ommastrephes bartramii in the Northwest Pacific Ocean based on Voronoi diagram and spatial autocorrelation. Acta Oceanologica Sinica, 36(12): 74–84. (in Chinese with English abstract)
Fortin M J, Drapeau P, Legendre P. 1989. Spatial autocorrelation and sampling design in plant ecology. Vegetatio, 83(1–2): 209–222.
Getis A, Aldstadt J. 2010. Constructing the spatial weights matrix using a local statistic. In: Anselin L, Rey S J eds. Perspectives on Spatial Data Analysis. Springer, Berlin Heidelberg. p.147–163.
Getis A, Ord J K. 1992. The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3): 189–206.
Goodchild M F. 1986. Spatial Autocorrelation. Geo Books, Norwich.
Gutiérrez N L, Masello A, Uscudun G, Defeo O. 2011. Spatial distribution patterns in biomass and population structure of the deep sea red crab Chaceon notialis in the Southwestern Atlantic Ocean. Fisheries research, 110(1): 59–66.
Ichii T, Mahapatra K, Okamura H, Okada Y. 2006. Stock assessment of the autumn cohort of neon flying squid (Ommastrephes bartramii) in the North Pacific based on past large-scale high seas driftnet fishery data. Fisheries Research, 78(2–3): 286–297.
Ichii T, Mahapatra K, Sakai M, Inagake D, Okada Y. 2004. Differing body size between the autumn and the winter–spring cohorts of neon flying squid (Ommastrephes bartramii) related to the oceanographic regime in the North Pacific: a hypothesis. Fisheries Oceanography, 13(5): 295–309.
Ichii T, Mahapatra K, Sakai M, Wakabayashi T, Okamura H, Igarashi H, Inagake D, Okada Y. 2011. Changes in abundance of the neon flying squid Ommastrephes bartramii in relation to climate change in the central North Pacific Ocean. Marine Ecology Progress Series, 441: 151–164.
Koenig W D, Knops J M H. 1998. Testing for spatial autocorrelation in ecological studies. Ecography, 21(4): 423–429.
Koenig W D. 1999. Spatial autocorrelation of ecological phenomena. Trends in Ecology & Evolution, 14(1): 22–26.
Kulka D W, Pinhorn A T, Halliday R G, Pitcher D, Stansbury D. 1996. Accounting for changes in spatial distribution of groundfish when estimating abundance from commercial fishing data. Fisheries research, 28(3): 321–342.
Kurosaka K, Yamashita H, Ogawa M, Inada H, Arimoto T. 2012. Tentacle-breakage mechanism for the neon flying squid Ommastrephes bartramii during the jigging capture process. Fisheries Research, 121–122: 9–16.
Legendre P. 1993. Spatial autocorrelation: trouble or new paradigm? Ecology, 74(6): 1659–1673.
Lennert-Cody C E, Minami M, Tomlinson P K, Maunder M N. 2010. Exploratory analysis of spatial-temporal patterns in length-frequency data: an example of distributional regression trees. Fisheries Research, 102(3): 323–326.
Lichstein J W, Simons T R, Shriner S A, Franzreb K E. 2002. Spatial autocorrelation and autoregressive models in ecology. Ecological Monographs, 72(3): 445–463.
Longley P A, Goodchild M F, Maguire D J, Rhind D W. 2015. Geographic Information Science and Systems. 4th edn. John Wiley & Sons, London.
Mitchell A. 2005. The ESRI guide to GIS analysis, Volume 2: Spatial Measurements and Statistics. Esri Press, Redlands.
Morato T, Hoyle S D, Allain V, Nicol S J. 2010. Seamounts are hotspots of pelagic biodiversity in the open ocean. Proceedings of the National Academy of Sciences of the United States of America, 107(21): 9707–9711.
Nishida T, Chen D G. 2004. Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data. Fisheries Research, 70(2–3): 265–274.
Olivar M P, Quí G, Emelianov M. 2003. Spatial and temporal distribution and abundance of European hake, Merluccius merluccius, eggs and larvae in the Catalan coast (NW Mediterranean). Fisheries Research, 60(2): 321–331.
Peeters A, Zude M, Käthner J, Ünlü M, Kanber R, Hetzroni A, Gebbers R, Ben-Gal A. 2015. Getis-Ord’s hot-and coldspot statistics as a basis for multivariate spatial clustering of orchard tree data. Computers and Electronics in Agriculture, 111: 140–150.
Petitgas P. 2001. Geostatistics in fisheries survey design and stock assessment: models, variances and applications. Fish and Fisheries, 2(3): 231–249.
Polovina J J, Howell E, Kobayashi D R, Seki M P. 2001. The transition zone chlorophyll front, a dynamic global feature defining migration and forage habitat for marine resources. Progress in Oceanography, 49(1–4): 469–483.
Pontius Jr R G, Huffaker D, Denman K. 2004. Useful techniques of validation for spatially explicit land-change models. Ecological Modelling, 179(4): 445–461.
Rivoirard J, Simmonds J, Foote K G. 2000. Geostatistics for Estimating Fish Abundance. John Wiley & Sons, London.
Sokal R R, Oden N L. 1978. Spatial autocorrelation in biology: 2. Some biological implications and four applications of evolutionary and ecological interest. Biological Journal of the Linnean Society, 10(2): 229–249.
Su F Z, Zhou C H, Shi W Z, Du Y Y. 2004. Spatial heterogeneity of demersal fish in East China Sea. Chinese Journal of Applied Ecology, 15(4): 683–686.
Tian S Q, Chen X J, Chen Y, Xu L X, Dai X J. 2009a. Evaluating habitat suitability indices derived from CPUE and fishing effort data for Ommatrephes bratramii in the northwestern Pacific Ocean. Fisheries Research, 95(2–3): 181–188.
Tian S Q, Chen X J, Chen Y, Xu L X, Dai X J. 2009b. Standardizing CPUE of Ommastrephes bartramii for Chinese squid-jigging fishery in Northwest Pacific Ocean. Chinese Journal of Oceanology and Limnology, 27(4): 729–739.
Wang W Y, Zhou C H, Shao Q Q, Mulla D J. 2010. Remote sensing of sea surface temperature and chlorophyll-a: implications for squid fisheries in the north-west Pacific Ocean. International Journal of Remote Sensing, 31(17–18): 4515–4530.
Watanabe H, Kubodera T, Ichii T, Kawahara S. 2004. Feeding habits of neon flying squid Ommastrephes bartramii in the transitional region of the central North Pacific. Marine Ecology Progress Series, 266: 173–184.
Yatsu A, Watanabe T, Mori J, Nagasawa K, Ishida Y, Meguro T, Kamei Y, Sakurai Y. 2000. Interannual variability in stock abundance of the neon flying squid, Ommastrephes bartramii, in the North Pacific Ocean during 1979-1998: impact of driftnet fishing and oceanographic conditions. Fisheries Oceanography, 9(2): 163–170.
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