Effective conservation and management of animal populations requires knowledge of abundance and trends. For many species, these quantities are estimated using systematic visual surveys. Additional individual‐level data are available for some species. Integrated population modeling (IPM) offers a mechanism for leveraging these data sets into a single estimation framework. IPMs that incorporate both population‐ and individual‐level data have previously been developed for birds, but have rarely been applied to cetaceans. Here, we explore how IPMs can be used to improve the assessment of cetacean populations. We combined three types of data that are typically available for cetaceans of conservation concern: population‐level visual survey data, individual‐level capture–recapture data, and data on anthropogenic mortality. We used this IPM to estimate the population dynamics of the Cook Inlet population of beluga whales (CIBW; Delphinapterus leucas ) as a case study. Our state‐space IPM included a population process model and three observational submodels: (1) a group detection model to describe group size estimates from aerial survey data; (2) a capture–recapture model to describe individual photographic capture–recapture data; and (3) a Poisson regression model to describe historical hunting data. The IPM produces biologically plausible estimates of population trajectories consistent with all three data sets. The estimated population growth rate since 2000 is less than expected for a recovering population. The estimated juvenile/adult survival rate is also low compared to other cetacean populations, indicating that low survival may be impeding recovery. This work demonstrates the value of integrating various data sources to assess cetacean populations and serves as an example of how multiple, imperfect data sets can be combined to improve our understanding of a population of interest. The model framework is applicable to other cetacean populations and to other taxa for which similar data types are available.

中文翻译：

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使用综合种群模型评估鲸类种群：以库克湾白鲸为例。

要有效地保护和管理动物种群，就需要丰富的知识和趋势知识。对于许多物种，这些数量是使用系统的视觉调查估算的。对于某些物种，还可以使用其他个人级别的数据。集成人口建模（IPM）提供了一种机制，可将这些数据集整合到单个估算框架中。先前已经为鸟类开发了结合种群和个体水平数据的病虫害综合防治，但很少将其用于鲸类。在这里，我们探索如何将IPM用于改善鲸类种群的评估。我们结合了对保护鲸类通常可用的三种类型的数据：人口级别的目测数据，个体级别的捕获－再捕获数据以及人为死亡率数据。翠雀）作为案例研究。我们的状态空间IPM包括人口过程模型和三个观测子模型：（1）组检测模型，用于描述根据航测数据估算的组规模；（2）描述单个摄影捕获-捕获数据的捕获-捕获模型；（3）描述历史狩猎数据的泊松回归模型。IPM得出与所有三个数据集一致的人口轨迹的生物学上合理的估计。自2000年以来的估计人口增长率低于恢复中的人口的预期。与其他鲸类种群相比，估计的少年/成年存活率也很低，表明低存活率可能会阻碍康复。这项工作证明了整合各种数据源以评估鲸类种群的价值，并作为如何组合多个不完善的数据集以增进我们对目标种群的了解的示例。该模型框架适用于其他鲸类种群以及具有相似数据类型的其他分类单元。