Integrated fisheries stock assessment models (SAMs) and integrated population models (IPMs) are used in biological and ecological systems to estimate abundance and demographic rates. The approaches are fundamentally very similar, but historically have been considered as separate endeavors, resulting in a loss of shared vision, practice and progress. We review the two approaches to identify similarities and differences, with a view to identifying key lessons that would benefit more generally the overarching topic of population ecology. We present a case study for each of SAM (snapper from the west coast of New Zealand) and IPM (woodchat shrikes from Germany) to highlight differences and similarities. The key differences between SAMs and IPMs appear to be the objectives and parameter estimates required to meet these objectives, the size and spatial scale of the populations, and the differing availability of various types of data. In addition, up to now, typical SAMs have been applied in aquatic habitats, while most IPMs stem from terrestrial habitats. SAMs generally aim to assess the level of sustainable exploitation of fish populations, so absolute abundance or biomass must be estimated, although some estimate only relative trends. Relative abundance is often sufficient to understand population dynamics and inform conservation actions, which is the main objective of IPMs. IPMs are often applied to small populations of conservation concern, where demographic uncertainty can be important, which is more conveniently implemented using Bayesian approaches. IPMs are typically applied at small to moderate spatial scales (1 to 10⁴ km²), with the possibility of collecting detailed longitudinal individual data, whereas SAMs are typically applied to large, economically valuable fish stocks at very large spatial scales (10⁴ to 10⁶ km²) with limited possibility of collecting detailed individual data. There is a sense in which a SAM is more data- (or information-) hungry than an IPM because of its goal to estimate absolute biomass or abundance, and data at the individual level to inform demographic rates are more difficult to obtain in the (often marine) systems where most SAMs are applied. SAMs therefore require more 'tuning' or assumptions than IPMs, where the 'data speak for themselves', and consequently techniques such as data weighting and model evaluation are more nuanced for SAMs than for IPMs. SAMs would benefit from being fit to more disaggregated data to quantify spatial and individual variation and allow richer inference on demographic processes. IPMs would benefit from more attempts to estimate absolute abundance, for example by using unconditional models for capture-recapture data.

综合渔业资源评估模型（SAM）和综合种群模型（IPM）用于生物和生态系统中，以估计丰度和人口比率。这些方法从根本上非常相似，但历史上一直被认为是单独的努力，导致失去共同的愿景、实践和进步。我们回顾了这两种方法，以确定相似点和差异，以期找出对人口生态学这一总体主题更普遍有益的关键经验教训。我们对 SAM（来自新西兰西海岸的笛鲷）和 IPM（来自德国的林聊伯劳）分别进行了案例研究，以突出差异和相似之处。SAM 和 IPM 之间的主要区别似乎是实现这些目标所需的目标和参数估计、种群的规模和空间规模以及各种类型数据的不同可用性。此外，到目前为止，典型的 SAM 已应用于水生生境，而大多数 IPM 源自陆地生境。SAM 通常旨在评估鱼类种群的可持续开发水平，因此必须估计绝对丰度或生物量，尽管有些仅估计相对趋势。相对丰度通常足以了解种群动态并为保护行动提供信息，这是病虫害综合管理的主要目标。IPM 通常应用于受保护问题的小群体，其中人口不确定性可能很重要，使用贝叶斯方法可以更方便地实现这一点。IPM通常应用于小到中等空间尺度（1至10 ⁴ km ²），可以收集详细的纵向个体数据，而SAM通常应用于非常大空间尺度（10 ⁴至10 4 km 2 ）的大型、具有经济价值的鱼类种群。 10 ⁶ km ²），收集详细个人数据的可能性有限。从某种意义上说，SAM 比 IPM 更需要数据（或信息），因为它的目标是估计绝对生物量或丰度，而在个体层面上提供人口统计率的数据更难获得（大多数地对空导弹都应用在海洋）系统中。因此，SAM 比 IPM 需要更多的“调整”或假设，其中“数据说明一切”，因此 SAM 的数据加权和模型评估等技术比 IPM 更加细致。SAM 将受益于适合更分类的数据，以量化空间和个体差异，并允许对人口统计过程进行更丰富的推断。IPM 将受益于更多估计绝对丰度的尝试，例如使用捕获-再捕获数据的无条件模型。