Integrating dead recoveries into capture–recapture models can improve inference on demographic parameters. But dead-recovery data do not only inform on individual fates; they also contain information about individual locations. Open-population spatial capture–recapture (OPSCR) has the potential to fully exploit such data. Here, we present an open-population spatial capture–recapture–recovery model integrating the spatial information associated with dead recoveries. Using simulations, we investigate the conditions under which this extension of the OPSCR model improves inference and illustrate the approach with the analysis of a wolverine (Gulo gulo) dataset from Norway. Simulation results showed that the integration of dead recoveries into OPSCR boosted the precision of all demographic parameters. In addition, the integration of dead-recovery locations boosted the precision of the inter-annual movement parameter, which is difficult to estimate in OPSCR, by up to 40% in case of sparse data. We also detected a 139–367% increase in the probability of models reaching convergence with increasing proportion of dead recoveries when dead-recovery information was integrated spatially, compared with a 30–107% increase when integrating dead recoveries in a non-spatial way. The analysis of the wolverine data showed the same general pattern of improved parameter precision. Overall, our results highlight how leveraging the demographic and spatial information contained in dead-recovery data in a spatial capture–recapture framework can improve population parameter estimation.

中文翻译：

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在开放种群空间捕获-重新捕获模型中整合死亡恢复

将死回收率整合到捕获-再捕获模型中可以改进对人口统计参数的推断。但是死亡恢复数据不仅可以告知个人命运；它们还包含有关各个位置的信息。开放人口空间捕获-再捕获（OPSCR）有可能充分利用这些数据。在这里，我们提出了一个开放种群空间捕获-重新捕获-恢复模型，集成了与死亡恢复相关的空间信息。通过模拟，我们研究了 OPSCR 模型的这种扩展改进推理的条件，并通过对金刚狼( Gulo gulo) 来自挪威的数据集。仿真结果表明，将死回收率整合到 OPSCR 中提高了所有人口统计参数的精度。此外，在数据稀疏的情况下，死点恢复位置的整合将OPSCR中难以估计的年际运动参数的精度提高了40%。我们还检测到，在空间集成死机恢复信息时，随着死机恢复比例的增加，模型达到收敛的概率增加了 139-367%，而以非空间方式集成死机恢复时则增加了 30-107%。对狼獾数据的分析显示了参数精度提高的相同一般模式。全面的，