南极半岛北部南极磷虾渔业空间点格局特征

Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula

南极磷虾作为南极生态系统中的关键物种,在空间分布上常表现出集群特征.这也反映到磷虾渔业生产的空间格局特征上.为了探讨捕捞能力有明显差异的船队在高/低单位捕捞努力量渔获量（CPUE）的情况下空间点分布格局特征及其生态学效应,基于南极半岛北部海域的两艘中国南极磷虾渔船（船A为专业南极磷虾渔船,船B为在智利竹筴鱼渔场与南极磷虾渔场转换的兼作渔船）的磷虾渔业数据,从空间点格局的角度出发,分别从两船的高、低CPUE的空间点格局在不同尺度上聚集特征,高、低CPUE在不同尺度上的二元点格局相关关系,以及CPUE点标记格局下的相关性关系等3个方面进行了分析.Ripley的L函数和标记相关函数分析结果表明： 研究对象在空间窗口所有尺度上的空间格局均表现为聚集性,高、低CPUE下均有聚集发生;在15 km尺度上,聚集强度近最大,在15～50 km尺度下,聚集程度稳定;总体上点格局分布的聚集强度依次为：船A高CPUE〉船B低CPUE〉船B高CPUE〉船A低CPUE.船A高、低CPUE在0~75 km尺度上为正相关关系,在大于75 km尺度上为随机关系;船B在所有尺度上的高、低CPUE均为正相关,说明了低CPUE点事件伴随高CPUE的点事件同步发生,两者在大部分尺度下均显著相关.这是磷虾集群模式的动态性和复杂性造成.船A各点的CPUE值在0～44 km尺度上呈正相关,在44～80 km尺度上呈负相关;船B各点的CPUE值在50～70 km尺度上呈负相关,在其他尺度上无显著相关性;正相关反映了磷虾密集集群的种群分布特性,而负相关表明了磷虾群间由于食物和空间原因存在一定的竞争关系.捕捞能力强的船A和捕捞能力较弱的船B在点格局分布上存在较大差异.专业南极磷虾渔船更适于开展磷虾作业空间点格局分析及相关科学调查工作.

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill （thereafter krill） often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel （Trachurus murphyi） fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort （CPUE）, from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects： （1） the two vessels’ point pattern characteristics of higher CPUEs and lower CPUEs at different scales; （2） correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and （3） correlation patterns of CPUE. Under the analysis derived from the Ripley’s L function and mark correlation function, the results showed that the point patterns of the higher/lower catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A 〉 lower CPUE of vessel B 〉higher CPUE of vessel B 〉 higher CPUE of vessel B. The relationship of the higher and lower CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A’s CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B’s CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.