南海北部海域大眼鲷空间自相关性

Spatial autocorrelation of Priacanthus spp. resources in the northern South China Sea

摘要:

研究经济鱼类分布的空间自相关特征有助于探究种群空间分析的最适尺度，是鱼类种群变动、资源量评估的基础内容。本研究根据2009—2014年渔船信息动态监测网络中的南海北部海域底拖网渔业生产数据，利用全局空间自相关和局部空间自相关等方法，研究了大眼鲷资源空间自相关性的动态变化，同时采用补充增量空间自相关分析(ISA)提高研究结果的准确程度。结果显示：①在整个研究海域内，大眼鲷资源年际间分布呈低密度区域为主，高密度区域较少的分布特征。②增量空间自相关分析表明，大眼鲷资源在76~87 km的尺度范围内表现出强烈的空间自相关性，聚集分布模式具统计学意义。③局部空间自相关分析表明，年际间大眼鲷资源热冷点渔区分布有差异，且资源变动较大；热点渔区主要集中在研究海域中部50~100 m等深线附近，冷点渔区则集中于50 m等深线附近海域。本研究引入增量空间自相关方法探究大眼鲷资源的空间自相关性，为挖掘渔业资源时空分布特征提供了一种新思路。

关键词:大眼鲷;空间自相关;增量空间自相关;热点分析;地理信息科学;底拖网;南海

Abstract:

Understanding the spatial autocorrelation characteristics of the distribution of economic fish is helpful to reveal the distribution pattern of its habitat and the formation mechanism of fishing grounds, which provides a basis for the evaluation and rational exploitation of the resources. Due to long-term overfishing, the fishery resources in the northern South China Sea have declined seriously, especially in the shallow area of 100-m isobath. As an important fishing target of bottom trawling in the South China Sea, the resources of Priacanthus spp. are under great pressure, so exploring the pattern characteristics of the spatial distribution of the resources can provide a certain reference basis for the sustainable utilization and scientific management of the resources. However, some studies denied that the spatial autocorrelation was affected by the spatial scope of the study area, and the spatial autocorrelation varied greatly under different analysis scales, thus weakening the actual effect of fishery resources assessment and scientific management. Therefore, based on the data of bottom trawl fishery in the northern South China Sea by a fishery information network from 2009 to 2014, this study used the methods of global spatial autocorrelation and local spatial autocorrelation to analyze the dynamic changes of spatial autocorrelation of Priacanthus spp. resources. And the incremental spatial autocorrelation analysis was added to improve the accuracy of the research results. The results were as follows: ① the results of global spatial autocorrelation analysis showed that in the whole study area, the interannual resources of Priacanthus spp. were mainly in low-density area and less in high-density area. ② according to the incremental spatial autocorrelation analysis, the resources of Priacanthus spp. showed a strong spatial autocorrelation within the scale of 76-87 km, and showed a significant aggregation distribution pattern. ③ the local spatial autocorrelation analysis showed that the distribution of hot and cold spots of Priacanthus spp. resources varied greatly from year to year, and the hot spot fishing areas were mainly concentrated between the 50-m and 100-m isobath in the middle part of the study area. The cold spot fishing areas were concentrated in the sea area near the 50-m isobath. In this paper, the incremental spatial autocorrelation method was introduced to explore the spatial autocorrelation of Priacanthus spp. resources, which provided a new idea for mining the temporal and spatial distribution characteristics of fishery resources.

Key words:Priacanthus spp.;spatial autocorrelation;incremental spatial autocorrelation;hot spot analysis;geographical information science;bottom trawl;South China Sea