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Methods for estimating a critical value for determining the freshwater/estuarine habitat residence of American eels from otolith Sr:Ca data

机译:从耳石Sr:Ca数据估算确定美洲鳗淡水/河口栖息地栖息地的临界值的方法

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摘要

Linear discriminant analysis (LDA) and habitat discrimination critical value (HDCV) methods are alternatives for evaluating the migratory history, such as the proportion of residence in freshwater (%fwr) and estuarine/marine habitats, of individual American eels (Anguilla rostrata) via the analysis of otolith Sr:Ca data. The LDA process requires Sr:Ca data from both freshwater and estuarine/marine groups while the mean + cSD method requires only a freshwater standard. For the two group (freshwater, estuarine/ marine), single predictor variable (Sr:Ca) case, the LDA process defaults to Fisher's linear discriminant where the HDCV equals the average of the group mean Sr:Ca values. The difference between freshwater and estuarine resident eel mean otolith Sr:Ca values, based on 13 published studies and the current study (n = 14), decreased with increasing freshwater group otolith mean (r = 0.80, p < 0.001), reflecting a relatively constant estuarine group mean (r = 0.38, p = 0.17). A process is proposed for estimating a HDCV from freshwater group otolith Sr:Ca mean and SD values based on empirical linear relations between the LDA, HDCV and freshwater mean (n = 14, r = 0.90, p < 0.0001) and c and SD (n = 14, r = -0.89, p < 0.0001) from the equation HDCV = mean + cSD. Variation in the sample sizes of otolith SnCa values used in the discriminant process of estimating a HDCV, while statistically significant, had trivial effect sizes that were likely of little biological consequence. However, larger sample sizes are preferred over smaller sample sizes. Estimates of %fwr increased with increases in the HDCV. Differences in %fwr estimates over a range of HDCVs were highly statistically significant and effect sizes increased with increased HDCV difference. As HDCV levels increased, growth rate estimates increased for a given %fwr value. A HDCV difference of ≤0.5 × 10~(-3) produced a small effect size. Accurate estimation of a HDCV is fundamental to the assessment of the habitat residence and inter-habitat movement of American eels and perhaps of other diadromous fishes and helps minimize bias in dependent estimates of other useful statistics such as the percentage of freshwater residence (%fwr) and growth rate.
机译:线性判别分析(LDA)和栖息地歧视临界值(HDCV)方法是评估美洲鳗(Anguilla rostrata)迁徙历史的迁移历史的替代方法,例如淡水(%fwr)和河口/海洋栖息地的居住比例。耳石Sr:Ca数据的分析。 LDA过程需要淡水和河口/海洋两类的Sr:Ca数据,而均值+ cSD方法仅需要淡水标准。对于两个组(淡水,河口/海洋),单个预测变量(Sr:Ca),LDA过程默认为Fisher线性判别式,其中HDCV等于该组平均Sr:Ca值的平均值。根据13项已发表的研究和当前研究(n = 14),淡水和河口居民鳗鱼平均耳石Sr:Ca值之间的差异随着淡水群体耳石平均数的增加而减小(r = 0.80,p <0.001),这表明恒定河口组平均值(r = 0.38,p = 0.17)。提出了一种基于LDA,HDCV和淡水平均值(n = 14,r = 0.90,p≤0.0001)和c和SD(n = 14,r = 0.90)之间的经验线性关系,根据淡水耳石Sr:Ca平均值和SD值估算HDCV的方法。 n = 14,r = -0.89,p <0.0001)由方程HDCV =平均值+ cSD得出。在估计HDCV的判别过程中使用的耳石SnCa值的样本大小变化虽然具有统计学意义,但影响大小微不足道,可能没有生物学上的意义。但是,较大的样本量比较小的样本量更可取。随着HDCV的增加,%fwr的估计值也会增加。在一系列HDCV中,%fwr估计值的差异具有统计学意义,并且随着HDCV差异的增加,效果大小也随之增加。随着HDCV水平的提高,给定%fwr值的增长率估算值也随之提高。 HDCV差异≤0.5×10〜(-3)产生较小的效果尺寸。 HDCV的准确估算对于评估美洲鳗鱼以及其他过水鱼类的栖息地栖息地和栖息地间迁移至关重要,并且有助于最大程度地减少其他有用统计数据(如淡水栖息地百分比(%fwr))的依存估计中的偏差。和增长率。

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