Fisheries and Oceans Canada, Northwest Atlantic Fisheries Center, St. John's, Newfoundland and Labrador, Canada.
PLoS One. 2020 May 11;15(5):e0232822. doi: 10.1371/journal.pone.0232822. eCollection 2020.
Populations often show complex spatial and temporal dynamics, creating challenges in designing and implementing effective surveys. Inappropriate sampling designs can potentially lead to both under-sampling (reducing precision) and over-sampling (through the extensive and potentially expensive sampling of correlated metrics). These issues can be difficult to identify and avoid in sample surveys of fish populations as they tend to be costly and comprised of multiple levels of sampling. Population estimates are therefore affected by each level of sampling as well as the pathway taken to analyze such data. Though simulations are a useful tool for exploring the efficacy of specific sampling strategies and statistical methods, there are a limited number of tools that facilitate the simulation testing of a range of sampling and analytical pathways for multi-stage survey data. Here we introduce the R package SimSurvey, which has been designed to simplify the process of simulating surveys of age-structured and spatially-distributed populations. The package allows the user to simulate age-structured populations that vary in space and time and explore the efficacy of a range of built-in or user-defined sampling protocols to reproduce the population parameters of the known population. SimSurvey also includes a function for estimating the stratified mean and variance of the population from the simulated survey data. We demonstrate the use of this package using a case study and show that it can reveal unexpected sources of bias and be used to explore design-based solutions to such problems. In summary, SimSurvey can serve as a convenient, accessible and flexible platform for simulating a wide range of sampling strategies for fish stocks and other populations that show complex structuring. Various statistical approaches can then be applied to the results to test the efficacy of different analytical approaches.
种群通常表现出复杂的时空动态，这给设计和实施有效的调查带来了挑战。不合适的抽样设计可能会导致采样不足（降低精度）和过采样（通过广泛且潜在昂贵的相关指标采样）。在鱼类种群抽样调查中，这些问题很难识别和避免，因为它们往往成本高昂且由多个层次的采样组成。因此，种群估计受到每个采样层次以及分析此类数据所采用的途径的影响。尽管模拟是探索特定抽样策略和统计方法效果的有用工具，但很少有工具可以方便地模拟多阶段调查数据的各种抽样和分析途径。在这里，我们介绍了 R 包 SimSurvey，它旨在简化模拟年龄结构和空间分布种群的过程。该包允许用户模拟在空间和时间上变化的年龄结构种群，并探索一系列内置或用户定义的抽样方案的效果，以再现已知种群的种群参数。SimSurvey 还包括一个从模拟调查数据中估计人口分层均值和方差的函数。我们使用案例研究展示了该软件包的使用，并表明它可以揭示意想不到的偏差来源，并可用于探索此类问题的基于设计的解决方案。总之，SimSurvey 可以作为一个方便、易用且灵活的平台，用于模拟鱼类种群和其他表现出复杂结构的种群的广泛抽样策略。然后可以将各种统计方法应用于结果，以测试不同分析方法的效果。
