Characterizing population distribution and abundance over space and time is central to population ecology and conservation of natural populations. However, species distribution models and population dynamic models have rarely been integrated into a single modelling framework. Consequently, fine‐scale spatial heterogeneity is often ignored in resource assessments. We develop and test a novel spatiotemporal assessment framework to better address fine‐scale spatial heterogeneities based on theories of fish population dynamic and spatiotemporal statistics. The spatiotemporal model links species distribution and population dynamic models within a single statistical framework that is flexible enough to permit inference for each state variable through space and time. We illustrate the model with a simulation–estimation experiment tailored to two exploited marine species: snow crab (Chionoecetes opilio, Oregoniidae) in the Eastern Bering Sea and northern shrimp (Pandalus borealis, Pandalidae) in the Gulf of Maine. These two species have different types of life history. We compare the spatiotemporal model with a spatially aggregated model and systematically evaluate the spatiotemporal model based on simulation experiments. We show that the spatiotemporal model can recover spatial patterns in population and exploitation pressure as well as provide unbiased estimates of spatially aggregated population quantities. The spatiotemporal model also implicitly accounts for individual movement rates and can outperform spatially aggregated models by accounting for time‐and‐size varying selectivity caused by spatial heterogeneity. We conclude that spatiotemporal modelling framework is a feasible and promising approach to address the spatial structure of natural resource populations, which is a major challenge in understanding population dynamics and conducting resource assessments and management.

中文翻译：

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一个新颖的时空种群评估框架，以更好地解决细小物种分布：开发和模拟测试

表征种群在空间和时间上的分布和丰富度对于种群生态学和自然种群的保护至关重要。但是，物种分布模型和种群动态模型很少集成到单个建模框架中。因此，在资源评估中经常忽略精细尺度的空间异质性。我们基于鱼类种群动态和时空统计理论，开发并测试了新颖的时空评估框架，以更好地解决精细尺度的空间异质性问题。时空模型在单个统计框架内链接物种分布和种群动态模型，该框架足够灵活以允许通过空间和时间推断每个状态变量。在白令海东部和北部对虾（Pandalus borealis）的Chionoecetes opilio，Oregoniidae），Pandalidae）在缅因湾。这两个物种的生活史类型不同。我们将时空模型与空间聚集模型进行比较，并基于模拟实验系统地评估时空模型。我们表明，时空模型可以恢复人口和开发压力的空间格局，并提供空间聚集人口数量的无偏估计。时空模型还隐含地考虑了个体的运动速率，并且可以通过考虑由空间异质性导致的时间和大小变化的选择性来胜过空间聚集模型。我们得出结论，时空建模框架是解决自然资源种群空间结构的可行且有前途的方法，