Canadian Journal of Fisheries and Aquatic Sciences, Ahead of Print.
Little attention has been given to optimizing statistical power for monitoring stream fish assemblages. We explored the relationship between temporal variability and statistical power using 34 metrics from fish community data collected annually at six sites over 10 years via electrofishing. Metric variability differed by the life stage and group of species considered, use of abundance or mass data, and data standardization technique. Lower variability was associated with community data, abundance data, and time-based standardizations, while greater variability was associated with young-of-the-year data, mass data, and area-based standardizations. Simulation-based power analysis indicated metric choice, and to a lesser degree, monitoring design (annual, biennial, endpoints, or haphazard sampling) influenced power to detect change. Across a fixed number of surveys (N = 60), endpoints sampling performed best. The N needed to detect change was heavily dependent upon metric choice for all monitoring designs, with the most biologically specific metrics requiring greater N. Large savings in effort and resource expenditure can be obtained utilizing biologically relevant metrics that are robust to temporal noise within an appropriate sampling design.

中文翻译：

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长期监测溪流鱼类组合的可变性和功率的考虑

《加拿大渔业和水生科学杂志》，印刷前。
很少有人关注优化用于监测溪流鱼类种群的统计能力。我们使用电钓鱼法，通过在十年中每年在六个地点每年收集的鱼类群落数据中的34个指标，探索了时间变异性与统计能力之间的关系。度量标准的可变性因所考虑的物种的生命阶段和类别，使用丰度或质量数据以及数据标准化技术而异。较低的变异性与社区数据，丰度数据和基于时间的标准化相关，而较大的变异性与年青数据，大量数据和基于区域的标准化相关。基于仿真的功率分析表明了度量标准的选择，而在较小程度上，监控设计（年度，两年期，端点或偶然性采样）会影响功率以检测变化。在固定数量的调查（N = 60）中，端点采样表现最佳。检测变化所需的N严重依赖于所有监视设计的度量选择，而生物学上最具体的度量则需要更大的N。在适当的范围内利用对时间噪声具有鲁棒性的生物学相关度量，可以节省大量的工作量和资源支出抽样设计。