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：本研究旨在利用捕获-再捕获调查数据估计动物种群丰度。我们利用关于种群结构的先验知识，针对其行为模式构建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标签切换与非可识别性问题的适当先验设定。通过模拟实验证明，我们的方案相比其他非特异性替代方法具有竞争优势。最后，利用2018年至2020年通过照片识别收集的数据，应用所提模型估算了第勒尼安海台伯河河口的宽吻海豚种群规模。研究结果为种群规模与结构提供了新见解，并揭示了部分调控种群动态的生态过程。