Impacts of changing scale on Getis-Ord Gi* hotspots of CPUE:a case study of the neon flying squid (Ommastrephes bartramii) in the northwest Pacific Ocean
-
摘要: 空间尺度(渔业网格)不仅影响CPUE全局分布模式,而且影响其局部分布模式及其与海洋环境的关系。在空间多尺度下,本文研究了西北太平洋柔鱼(Ommastrephes bartramii)CPUE热点和冷点分布的尺度关系和尺度效应。将原始渔业数据重采样为从5'×5'到90'×90'的18个空间尺度,以5'的尺度间隔来识别局部聚类簇。论文系统分析了Getis-Ord Gi*热点和冷点的位置、边界、经典统计量随空间尺度的变化。具体地,分析了空间热点和冷点的最小值(Min)、均值(Mean),最大值(Max)、标准差(SD)、变异系数(CV)、偏度、峰度、第一四分位数(Q1)、中位数、第三四分位数(Q3)、面积和质心等统计量的空间尺度影响。在空间尺度影响分析中,主要考虑线性、对数、指数、幂律和多项式等尺度研究中的常见关系。对于热点和冷点,最大值、标准偏差和峰度具有显著的空间尺度关系,其余统计量一部分在热冷点间存在尺度影响的差异,而另一部分没有明确的尺度关系。研究结果表明,由于不同尺度的热点和冷点的边界和位置与原始尺度的边界和位置明显不同,不建议采用大于30'的网格来分析柔鱼资源的局部空间模式。
-
关键词:
- Ommastrephesbartramii /
- 尺度影响 /
- 局部聚类簇 /
- Getis-OrdGi* /
- 空间热点
Abstract: We examined the scale impacts on spatial hot and cold spots of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. The original fishery data were tessellated to 18 spatial scales from 5'×5' to 90'×90' with a scale interval of 5' to identify the local clusters. The changes in location, boundaries, and statistics regarding the Getis-Ord Gi* hot and cold spots in response to the spatial scales were analyzed in detail. Several statistics including Min, mean, Max, SD, CV, skewness, kurtosis, first quartile (Q1), median, third quartile (Q3), area and centroid were calculated for spatial hot and cold spots. Scaling impacts were examined for the selected statistics using linear, logarithmic, exponential, power law and polynomial functions. Clear scaling relations were identified for Max, SD and kurtosis for both hot and cold spots. For the remaining statistics, either a difference of scale impacts was found between the two clusters, or no clear scaling relation was identified. Spatial scales coarser than 30' are not recommended to identify the local spatial patterns of fisheries because the boundary and locations of hot and cold spots at a coarser scale are significantly different from those at the original scale.-
Key words:
- Ommastrephes bartramii /
- scale impacts /
- local clusters /
- Getis-Ord Gi* /
- spatial hotspots
-
Anselin L. 1995. Local indicators of spatial association-LISA. Geogr Anal, 27(2):93-115 Anselin L. 2004. Exploring spatial data with GeoDaTM:a workbook. Urbana, USA:University of Illinois, 61801 Arkhipkin A I, Murzov S A. 1986. Age and growth patterns of dosidicus gigas (Ommastrephidae). In:Ivanov B G, ed. Present State of Fishery for Squids and Prospects of Its Development. Moscow:VNIRO Press, 107-123 Carocci F, Bianchi G, Eastwood P, et al. 2009. Geographic Information Systems to Support the Ecosystem Approach to Fisheries:Status, Opportunities and Challenge. Rome, Italy:Food and Agriculture Organization of the United Nations Chen Xinjun, Chen Yong, Tian Siquan, et al. 2008. An assessment of the west winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Fish Res, 92(2-3):221-230 Chen C S, Chiu T S. 2003. Variations of life history parameters in two geographical groups of the neon flying squid, Ommastrephes bartramii, from the North Pacific. Fish Res, 63(3):349-366 Chen Xinjun, Tian Siquan, Guan Wenjian. 2014. Variations of oceanic fronts and their influence on the fishing grounds of Ommastrephes bartramii in the Northwest Pacific. Acta Oceanol Sin, 33(4):45-54 Ciannelli L, Fauchald P, Chan K S, et al. 2008. Spatial fisheries ecology:Recent progress and future prospects. J Mar Syst, 71(3-4):223-236 Cope J M, Punt A E. 2011. Reconciling stock assessment and management scales under conditions of spatially varying catch histories. Fish Res, 107(1-3):22-38 Ebdon D. 1985. Statistics in Geography:A Practical Approach. 2nd ed. London:Wiley-Blackwell Feng Yongjiu, Chen Xinjun, Liu Yan. 2016. The effects of changing spatial scales on spatial patterns of CPUE for Ommastrephes bartramii in the northwest Pacific Ocean. Fish Res, 183:1-12 Feng Yongjiu, Chen Xinjun, Liu Yan. 2017a. Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean. Chin J Oceanol Limnol, 35(4):921-935 Feng Yongjiu, Chen Xinjun, Yang Liu. 2017b. Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model. Chin J Oceanol Limnol:doi: 10.1007/s00343-018-6318-3 Feng Yongjiu, Cui Li, Chen Xinjun, et al. 2017c. A comparative study of spatially clustered distribution of jumbo flying squid (Dosidicus gigas) offshore Peru. J Ocean Univ China, 16(3):490-500 Feng Yongjiu, Liu Yan. 2015. Fractal dimension as an indicator for quantifying the effects of changing spatial scales on landscape metrics. Ecol Indic, 53:18-27 Fosså J H, Mortensen P B, Furevik D M. 2002. The deep-water coral Lophelia pertusa in Norwegian waters:distribution and fishery impacts. Hydrobiologia, 471(1-3):1-12 Gao Feng, Chen Xinjun, Guan Wenjiang, et al. 2016. A new model to forecast fishing ground of Scomber japonicus in the Yellow Sea and East China Sea. Acta Oceanol Sin, 35(4):74-81 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. Berlin, Heidelberg:Springer, 147-163 Getis A, Ord J K. 1996. Spatial analysis and modeling in a GIS environment. In:McMaster R B, Lynn Usery E, eds. A Research Agenda for Geographic Information Science. Boca Raton:CRC Press, 157-196 Gilly W F, Markaida U, Baxter C H, et al. 2006. Vertical and horizontal migrations by the jumbo squid Dosidicus gigas revealed by electronic tagging. Mar Ecol Prog Ser, 324:1-17 Gong Caixia, Chen Xinjun, Gao Feng, et al. 2014. Effect of spatial and temporal scales on habitat suitability modeling:A case study of Ommastrephes bartramii in the northwest pacific ocean. J Ocean Univ China, 13(6):1043-1053 Guinet C, Dubroca L, Lea M A, et al. 2001. Spatial distribution of foraging in female Antarctic fur seals Arctocephalus gazella in relation to oceanographic variables:a scale-dependent approach using geographic information systems. Mar Ecol Prog Ser, 219:251-264 Gutiérrez N L, Masello A, Uscudun G, et al. 2011. Spatial distribution patterns in biomass and population structure of the deep sea red crab Chaceon notialis in the Southwestern Atlantic Ocean. Fish Res, 110(1):59-66 Harford W J, Ton C, Babcock E A. 2015. Simulated mark-recovery for spatial assessment of a spiny lobster (Panulirus argus) fishery. Fish Res, 165:42-53 Huang Jiansheng, Sun Yao, Jia Haibo, et al. 2014. Spatial distribution and reconstruction potential of Japanese anchovy (Engraulis japonicus) based on scale deposition records in recent anaerobic sediment of the Yellow Sea and East China Sea. Acta Oceanol Sin, 33(12):138-144 Jain A K. 2010. Data clustering:50 years beyond K-means. Pattern Recogn Lett, 31(8):651-666 Jennings S, Kaiser M, Reynolds J D. 2009. Marine Fisheries Ecology. New York:John Wiley & Sons Jiang Tao, Chai Chai, Wang Jifang, et al. 2016. Temporal and spatial variations of abundance of phycocyanin- and phycoerythrin-rich Synechococcus in Pearl River Estuary and adjacent coastal area. J Ocean Univ China, 15(5):897-904 Meaden G J, Aguilar-Manjarrez J. 2013. Advances in Geographic Information Systems and Remote Sensing for Fisheries and Aquaculture. Roma, Italy:Food and Agriculture Organization of the United Nations Mitchell A. 2005. The ESRI Guide to GIS Analysis, Volume 2:Spatial Measurements and Statistics. Redlands, CA:Esri Press Mullon C, Fréon P, Cury P. 2005. The dynamics of collapse in world fisheries. Fish Fish, 6(2):111-120 Nishida T, Chen Dinggeng. 2004. Incorporating spatial autocorrelation into the general linear model with an application to the yellowfin tuna (Thunnus albacares) longline CPUE data. Fish Res, 70(2-3):265-274 Ord J K, Getis A. 1995. Local spatial autocorrelation statistics:Distributional issues and an application. Geogr Anal, 27(4):286-306 Paulino C, Segura M, Chacón G. 2016. Spatial variability of jumbo flying squid (Dosidicus gigas) fishery related to remotely sensed SST and chlorophyll-a concentration (2004-2012). Fish Res, 173:122-127 Peeters A, Zude M, Käthner J, et al. 2015. Getis-Ord's hot-and cold-spot statistics as a basis for multivariate spatial clustering of orchard tree data. Comput Electron Agr, 111:140-150 Saul S E, Walter Ⅲ J F, Die D J, et al. 2013. Modeling the spatial distribution of commercially important reef fishes on the West Florida Shelf. Fish Res, 143:12-20 Su N J, Sun C L, Punt A E, et al. 2008. Environmental and spatial effects on the distribution of blue marlin (Makaira nigricans) as inferred from data for longline fisheries in the Pacific Ocean. Fish Oceanogr, 17(6):432-445 Swartz W, Sala E, Tracey S, et al. 2010. The spatial expansion and ecological footprint of fisheries (1950 to present). PLoS One, 5(12):e15143 Tian Siquan, Chen Yong, Chen Xinjun, et al. 2010. Impacts of spatial scales of fisheries and environmental data on catch per unit effort standardisation. Mar Freshwater Res, 60(12):1273-1284 Turner M G, O'Neill R V, Gardner R H, et al. 1989. Effects of changing spatial scale on the analysis of landscape pattern. Landscape Ecol, 3(3-4):153-162 Wiens J A. 1989. Spatial scaling in ecology. Func Ecol, 3(4):385-397 Wu Jianguo. 2004. Effects of changing scale on landscape pattern analysis:scaling relations. Landscape Ecol, 19(2):125-138 Xu Jie, Chen Xinjun, Chen Yong, et al. 2016. The effect of sea surface temperature increase on the potential habitat of Ommastrephes bartramii in the Northwest Pacific Ocean. Acta Oceanol Sin, 35(2):109-116 Yang Mingxia, Chen Xinjun, Feng Youjiu, et al. 2013. Spatial variability of small and medium scales, resource abundance of Ommastrephes bartramii in Northwest Pacific. Haiyang Xuebao (in Chinese), 33(20):6427-6435 Yu Wei, Chen Xinjun, Chen Yong, et al. 2015. Effects of environmental variations on the abundance of western winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Acta Oceanol Sin, 34(8):43-51 Yu Wei, Chen Xinjun, Yi Qian, et al. 2016a. Spatio-temporal distributions and habitat hotspots of the winter-spring cohort of neon flying squid Ommastrephes bartramii in relation to oceanographic conditions in the Northwest Pacific Ocean. Fish Res, 175:103-115 Yu Wei, Yi Qian, Chen Xinjun, et al. 2016b. Modelling the effects of climate variability on habitat suitability of jumbo flying squid, Dosidicus gigas, in the Southeast Pacific Ocean off Peru. ICES J Mar Sci, 73(2):239-249
点击查看大图
计量
- 文章访问数: 964
- HTML全文浏览量: 79
- PDF下载量: 1402
- 被引次数: 0