In this work, the goal is to estimate the abundance of an animal population using data coming from capture-recapture surveys. We leverage the prior knowledge about the population's structure to specify a parsimonious finite mixture model tailored to its behavioral pattern. Inference is carried out under the Bayesian framework, where we discuss suitable priors' specification that could alleviate label-switching and non-identifiability issues affecting finite mixtures. We conduct simulation experiments to show the competitive advantage of our proposal over less specific alternatives. Finally, the proposed model is used to estimate the common bottlenose dolphins' population size at the Tiber River estuary (Mediterranean Sea), using data collected via photo-identification from 2018 to 2020. Results provide novel insights on the population's size and structure, and shed light on some of the ecological processes governing the population dynamics.

翻译：本文旨在利用捕获-再捕获调查数据估计动物种群丰度。我们借助关于种群结构的先验知识，针对其行为模式设计了一个简约的有限混合模型。在贝叶斯框架下进行推断，讨论了能够缓解有限混合模型中标签交换和不可识别性问题的合适先验设定。通过模拟实验表明，我们的方法相较于其他替代方案具有竞争性优势。最后，利用2018至2020年间通过照片识别收集的数据，将所提模型应用于地中海台伯河河口的宽吻海豚种群规模估计。结果不仅提供了关于种群规模与结构的新见解，还揭示了部分调控种群动态的生态过程。