不同时间尺度下秘鲁鳀资源量的波动特征

Features of anchoveta (Engraulis ringens) biomass fluctuation at different time scales

海洋渔业资源其资源量在时间上存在波动,了解资源量波动的不同时间尺度特征可为探索资源变动的相关因素提供依据。为此,根据1985—2021年间秘鲁鳀(Engraulis ringens)资源量时间序列,利用自适应噪声的完全集合经验模态分解(complete empirical mode decomposition with adaptive noise, CEEMDAN)的方法,提取资源量波动的不同时间尺度特征,并评价各时间尺度波动对总体资源波动的贡献程度;此外使用交相关分析的方法探究厄尔尼诺和拉尼娜事件对不同时间尺度下秘鲁鳀资源量波动的影响。研究发现,CEEMDAN可将秘鲁鳀资源量时间序列分解成5个本征模态函数(intrinsic mode function, IMF_(1),其中i为分量级数)分量和1个残差项(residual, RES);根据各IMF;分量的周期特征及其对总体资源波动贡献分析结果可知:秘鲁鳀的资源量波动主要受到季节或年间为表征的IMF;波动和代表其年代际变动趋势的RES所控制,其中资源量年代际变动的趋势与东南太平洋洪堡洋流生态系统周期性变动有关;交相关分析结果表明厄尔尼诺和拉尼娜事件主要影响秘鲁鳀资源量年间和年际的波动,其中Ni1o1+2区的海表面温度距平(sea surface temperature anomaly, SSTA)与海洋尼诺指数(oceanic ni1o index, ONI)相比对秘鲁鳀资源量波动的表征作用更为明显,在滞前1.0~1.5年内,其值的偏高可能会对秘鲁鳀资源量产生负影响。

The biomass of marine fishery resources fluctuates in time. Understanding the features of biomass fluctuations at different time scales can provide a perspective in investigating the impacts of relevant factors on biomass variations. Based on the anchoveta(Engraulis ringens) biomass time series from 1985 to 2021, this study used Complete Empirical Mode Decomposition with Adaptive Noise(CEENDAN) to extract anchoveta biomass fluctuations features at different time scales and evaluated their contributions to overall time series. Besides, the results were evaluated with El-Ni1 o and La-Ni1 a events under cross-correlation analysis because these events greatly related with the variations in anchoveta biomass according to previous studies. Results showed the CEEMDAN could decompose the anchoveta biomass time series into five Intrinsic Mode Function(IMF;) and one residual(RES). Anchoveta biomass fluctuations were mainly under the control of its seasonal, annual(IMF_(1)) and inter decadal(RES) variations. RES was found to be associated with the regime shift in Humboldt Current ecosystem at Southeast Pacific Ocean. Cross-correlation analysis revealed El-Ni1 o and La-Ni1 a events could impact the anchoveta biomass fluctuations mainly at annual and inter annual scale. Sea surface temperature anomaly at Ni1 o1+2 region(Ni1 o1+2 index) was believed to play a more obvious role in tracking the anchoveta biomass fluctuations than Oceanic Ni1 o Index. Higher values of the Ni1 o1+2 index within 1.0-1.5 years might have a negative impact on the anchoveta biomass.