Laboratori d'Aplicacions Bioacústiques, Universitat Politècnica de Catalunya - BarcelonaTech, Barcelona, Spain.
Instituto de Desenvolvimento Sustentável Mamirauá, Tefé, Brazil.
Sci Rep. 2023 Jul 27;13(1):10801. doi: 10.1038/s41598-023-36518-1.
Using passive acoustic monitoring (PAM) and convolutional neural networks (CNN), we monitored the movements of the two endangered Amazon River dolphin species, the boto (Inia geoffrensis) and the tucuxi (Sotalia fluviatilis) from main rivers to floodplain habitats (várzea) in the Mamirauá Reserve (Amazonas, Brazil). We detected dolphin presence in four main areas based on the classification of their echolocation clicks. Using the same method, we automatically detected boat passages to estimate a possible interaction between boat and dolphin presence. Performance of the CNN classifier was high with an average precision of 0.95 and 0.92 for echolocation clicks and boats, respectively. Peaks of acoustic activity were detected synchronously at the river entrance and channel, corresponding to dolphins seasonally entering the várzea. Additionally, the river dolphins were regularly detected inside the flooded forest, suggesting a wide dispersion of their populations inside this large area, traditionally understudied and particularly important for boto females and calves. Boats overlapped with dolphin presence 9% of the time. PAM and recent advances in classification methods bring a new insight of the river dolphins' use of várzea habitats, which will contribute to conservation strategies of these species.
利用被动声学监测（PAM）和卷积神经网络（CNN），我们监测了两种濒危的亚马逊河豚物种——白海豚（Inia geoffrensis）和淡水豚（Sotalia fluviatilis），它们从主要河流迁徙到马米拉瓦保护区（亚马逊州，巴西）的洪泛区生境（várzea）。我们根据它们回声定位咔哒声的分类，在四个主要区域检测到海豚的存在。使用相同的方法，我们自动检测了船只的通行情况，以估计船只和海豚存在之间可能的相互作用。CNN 分类器的性能很高，回声定位咔哒声和船只的平均精度分别为 0.95 和 0.92。在河流入口和河道处检测到了同步的声学活动高峰，这对应着海豚季节性地进入 várzea。此外，在洪水森林中定期检测到了这些河海豚，表明它们的种群在这片大型传统上研究较少但对白海豚雌性和幼崽特别重要的地区广泛分布。船只与海豚存在重叠的时间为 9%。PAM 和分类方法的最新进展为研究这些物种对 várzea 生境的利用提供了新的视角，这将有助于这些物种的保护策略。
