Based on catch data from the bottom trawl survey by eight cruises in offshore of northern South China Sea during 2014-2017, we analyzed the stock density distribution and explored its probability distribution with statistical method, which was further used to estimate the mean stock density in this region. The results showed that the coefficient of variation (CV) for stock density ranged from 0.67 to 1.03 for all the periods, indicating a highly uneven spatial distribution of stock density. The frequency distribution of fishery resource density was characterized by obvious right-skewed, which was dominated by stock density of 0-1000 kg·km-2. The results of one sample Kolmogorov-Smirnov test indicated that three probability distribution patterns were suitable for stock density in this region, including Lognormal, Gamma and Weibull distributions. In terms of the mean stock density estimation, the values from Lognormal showed no statistically significant difference from those from others, but the opposite result was obtained between Gamma and Weibull distributions. Compared with 1960s-1970s, the appropriate probability distribution pattern of stock density has changed from single to multiple types. Variation of the proportion of low catch resulted from the changes in the structure of fishery resources, fishing effort and climate change might cause the alte-ration of probability distribution.
根据2014—2017年南海北部近海8个调查航次渔获量数据,结合统计方法分析该海域渔业资源密度分布特征并探索其适宜概率分布类型,进而估算区域平均资源密度.结果表明:各时期资源密度变异系数(CV)在0.67～1.03,说明该海域渔业资源密度呈较高程度的不均匀空间分布,且渔获资源密度频率分布呈现明显的右偏特征,总体以0～1000 kg·km-2资源密度为主导;单样本Kolmogorov-Smirnov检验结果表明,对数正态、伽玛和韦伯分布是该区域资源密度的适宜分布类型;在海域平均资源密度估算方面,对数正态所得结果与另两个分布类型在统计学上无显著差异,而伽玛和韦伯分布的估计值有显著差异.与1960—1970年代相比,该海域渔业资源密度适宜概率分布型已从单一类型转变为多类型,这主要归于渔业资源结构、捕捞强度以及气候变化等引起的低渔获量比例变化.
Keywords: fishing effort; northern South China Sea; probability distribution; stock density.