## 4 Discussion and Conclusions
The spatial localization of bird songs using multiple microphone arrays (i.e., an array of arrays) is a promising approach to determine the precise location of vocalizations. A system with three microphone array units estimated the location of two color banded Great-Reed Warbler's song posts in a need marsh with a mean error distance of 5.5 m from the location of the observed song posts [18]. Also, various types of animal vocalization systems based on many microphone units deployed over fields have been proposed recently [25]. [PERSON] et al. successfully 3D triangulated, using a time difference of arrival (TDOA) approach, calls of warblers using a large microphone array unit system in which channels were far apart from each other [26]. However, it could be costly to deploy and calibrate multiple units in field observations. Our approach based on a single but multi-channel array unit, showing good accuracy of azimuth-elevation angles of bird vocalizations, suggest another possibility to better capture bird vocalizations while keeping deployment costs low. Our results show how our observation method could be used to noninvasively monitor rare birds in the field. For example, [PERSON] et al. evaluated the practical effectiveness of localization technology for auditory monitoring of endangered Eurasian bittern (_Botaurus stellaris_) which inhabits wetlands in remote areas with thick vegetation, using a 8-ch microphone array unit [27]. They successfully localized booming calls of at least two malesin a reverberant wetland, surrounded by thick vegetation and riparian trees. In addition to the non-invasiveness to the ecosystem where the target birds inhabit, our recording system has lower deployment cost for field observers. We believe that our monitoring system, given advantages and limitations presented in this study, offers a practical tool for field ecologists, e.g., to estimate abundance and distribution of rare species. However, estimating the distance of sound sources from microphones and two-dimensional (spatial) localization of them are important or essential for more detailed ecological surveys. We think that extracting any complementary information about their distance from separated sounds (e.g., relative amplitude [28]) would be a novel direction to better capture the structure of the soundscape with a single microphone array unit. From another perspective, there is increasing interest and development of sound event localization and detection for various environmental sounds using microphone arrays. For example, the workshop on detection and classification of acoustic scenes and events (DCASE) provided a dataset (STARSS22) for sound source localization and classification of domestic sounds in indoor environments [29]. A competition of sound source localization and classification has been conducted, and participants discuss issues arising from the task (e.g., [11]). Experimental reports on the sound source localization of distant and elevated calls in a forest environment where many species of birds coexist, which was investigated in this study, could contribute to further progress in these fields because it may provide different insights into sound localization in harsher conditions unique to natural acoustic environments. Although camera trap-based animal monitoring combined with object detection algorithms is widely used [30], it is challenging to capture small animals, such as songbirds, because they are basically far distant from the device, and there exists the problem of back-lighting. This experiment shows that it is possible to quantitatively extract the dynamics of the use of niches among species, which could only be described verbally or roughly before, even when the method is based only on azimuth and elevation angle information. The increasing interest and popularity of 3D audio in public has made portable 3D recording equipment more accessible (e.g., Zoom H3-VR; Zoom Inc., GoPro MAX; GoPro Inc.).