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：翻译的摘要： 在这项工作中，目标是利用来自捕捉-释放调查的数据估计动物种群的数量。我们充分利用先前关于种群结构的知识，针对其行为模式指定一个简明的有限混合模型。推理是在贝叶斯框架下进行的，我们讨论了合适的先验分布的规范，以缓解影响有限混合的标签交换和非识别性问题。我们进行了模拟实验，展示了我们的提议相对于较少具体的替代方案的竞争优势。最后，我们利用从2018年至2020年通过照片识别收集的数据估计了台伯河口（地中海）的普通拟海豚数量。结果提供了有关该种群大小和结构的新见解，并揭示了一些调节种群动力学的生态过程。