Spatial models enable understanding potential redistribution of marine resources associated with ecosystem drivers and climate change. Stock assessment platforms can incorporate spatial processes, but have not been widely implemented or simulation tested. To address this research gap, an international simulation experiment was organized. The study design was blinded to replicate uncertainty similar to a real-world stock assessment process, and a data-conditioned, high-resolution operating model (OM) was used to emulate the spatial dynamics and data for Indian Ocean yellowfin tuna (Thunnus albacares). Six analyst groups developed both single-region and spatial stock assessment models using an assessment platform of their choice, and then applied each model to the simulated data. Results indicated that across all spatial structures and platforms, assessments were able to adequately recreate the population trends from the OM. Additionally, spatial models were able to estimate regional population trends that generally reflected the true dynamics from the OM, particularly for the regions with higher biomass and fishing pressure. However, a consistent population biomass scaling pattern emerged, where spatial models estimated higher population scale than single-region models within a given assessment platform. Balancing parsimony and complexity trade-offs were difficult, but adequate complexity in spatial parametrizations (e.g., allowing time- and age-variation in movement and appropriate tag mixing periods) was critical to model performance. We recommend expanded use of high-resolution OMs and blinded studies, given their ability to portray realistic performance of assessment models. Moreover, increased support for international simulation experiments is warranted to facilitate dissemination of methodology across organizations.

中文翻译：

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“闭着眼睛开车”：评估空间种群评估的国际盲法模拟实验的结果

空间模型有助于了解与生态系统驱动因素和气候变化相关的海洋资源的潜在重新分配。库存评估平台可以纳入空间过程，但尚未广泛实施或模拟测试。为了弥补这一研究空白，组织了一项国际模拟实验。研究设计采用盲法来复制类似于现实世界种群评估过程的不确定性，并使用数据调节的高分辨率操作模型 (OM) 来模拟印度洋黄鳍金枪鱼 ( Thunnus albacares )的空间动态和数据。六个分析小组使用他们选择的评估平台开发了单区域和空间种群评估模型，然后将每个模型应用于模拟数据。结果表明，在所有空间结构和平台上，评估能够充分重现 OM 的人口趋势。此外，空间模型能够估计区域人口趋势，通常反映了 OM 的真实动态，特别是生物量和捕捞压力较高的区域。然而，出现了一致的人口生物量缩放模式，其中空间模型估计的人口规模高于给定评估平台内的单区域模型。平衡简约性和复杂性的权衡很困难，但空间参数化的足够复杂性（例如，允许运动中的时间和年龄变化以及适当的标签混合周期）对于模型性能至关重要。我们建议扩大使用高分辨率 OM 和盲法研究，因为它们能够描绘评估模型的真实性能。此外，有必要增加对国际模拟实验的支持，以促进跨组织的方法传播。