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出 处:《海洋湖沼通报》2007年第3期81-87,共7页Transactions of Oceanology and Limnology
基 金:国家自然科学基金(30271025)资助
摘 要:本文应用蒙特卡罗模拟方法,通过假设不同的生长参数、样本大小和白噪音水平,模拟出不同假设条件下的鱼类种群时间序列的体长频数分布,再应用体长分析方法ELEFAN(e-lectronic length-frequency analysis)与SLCA(Shepherd's length-composition analysis)估算模拟数据的生长参数K和L∞。用总生长特征φ估算求得生长参数的可靠性。模拟结果表明在大多数情况下ELEFAN比SLCA更能准确稳定地估计生长参数。生长速率和极限体长越大,φ估计值的精确度越高。当体长的白噪音水平小于20%时,估计结果较准确。当样本小于60时,样本越大估计结果越准确;当样本大于60时,样本增大对结果影响不大。应用本文的方法估计西非科特迪瓦的法荷水库的长臂虾(Macrobrachium vollenhovenii)真实渔业数据也得到了较好的结果。Monte Carlo simulation was used to generate length-frequency data under different scenarios, such as different values of the growth rate parameter (K), asymptotic length (L∞), sample size and CV level. Two length-based methods ELEFAN and SLCA were applied to estimate K and L∞. The growth performance index(φ) was calculated for comparing different fits of K and L∞. Monte Carlo Simulation analysis showed that in most cases, ELEFAN performed better than SLCA. The higher the K and L∞ are, the more reliable the estimated φ is. When the white noise level is less than about 20%, the estimated parameters are more reliable. When the sample size is large(〉60), the estimated result is more accurates a further increased sample size has little effect on the result. This method was also applied to the published data of fresh-water shrimp(Macrobrachium vollenhovenii) in west A frlca and reliable results were obtained.
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