IIBR Multidisciplinary: Locating and counting terrestrial wildlife with an open source, automated acoustic survey platform

IIBR 多学科：利用开源自动化声学调查平台定位和统计陆地野生动物

• 批准号: 1935507
• 负责人: Justin Kitzes
• 金额: $ 64.33万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935507&HistoricalAwards=false
• 关键词: IIBR; Multidisciplinary; Locating; counting; terrestrial

An award is made to the University of Pittsburgh to develop an automated acoustic platform for locating and counting terrestrial wildlife. Accurate estimates of wildlife populations are central to research on the effects of global change on biodiversity. Historically, population-level data has been time-consuming and difficult to collect, limiting the number of species and habitats that can be evaluated. Acoustic recorders have the potential to inexpensively gather large-scale data on sound-producing species, including birds, bats, amphibians, and insects. However, most current acoustic surveys are only able to detect the presence or absence of a species and cannot count individual organisms in order to estimate population sizes. This award will support the initial development of an automated, open source acoustic platform to survey terrestrial wildlife populations, with the goal of gathering data at larger scales and with better accuracy than human observers. It will also support the training of at least two graduate students and an educational project that targets undergraduate STEM educator professional development at the interface of biology and data science. The creation of this platform and its release under open source licenses will enable professional ecologists, citizen scientists, and large biodiversity monitoring programs to better detect declines in species populations over time, track shifts in species distributions due to climate change, understand the interacting drivers of biodiversity changes, predict future extinction risks, and develop conservation strategies to protect threatened species.The acoustic survey platform will use GPS time-synchronized recorders to localize sounds in coordinate space. These sound locations will then be used to distinguish and count individual organisms within species. Although applicable to a wide variety of species, the platform will be initially designed for breeding songbirds of the eastern United States. The specific objectives of the award, involving both hardware and software development, include (1) designing an open source, inexpensive field recorder that can collect time-synchronized recordings, (2) developing and training an object-detecting convolutional neural network to identify the boundaries of distinct bird songs in time and frequency, (3) creating a detection-informed time difference of arrival algorithm that localizes each identified bird song in coordinate space and uses this data to count individual birds within species, and (4) completing performance and user testing to evaluate the integrated hardware and software platform. The platform will be evaluated specifically on its ability to estimate breeding bird populations more accurately and precisely than human observers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

匹兹堡大学获得了一个奖项，以开发一个用于定位和计数陆地野生动物的自动声学平台。对野生动物种群的准确估计是研究全球变化对生物多样性影响的核心。从历史上看，种群层面的数据既耗时又难以收集，限制了可供评估的物种和生境数量。声学记录器有可能以低廉的成本收集有关发声物种的大规模数据，包括鸟类、蝙蝠、两栖动物和昆虫。然而，目前大多数声学调查只能检测物种的存在或不存在，而不能计算个体生物以估计种群规模。该奖项将支持一个自动化、开源声学平台的初步开发，以调查陆地野生动物种群，目标是以比人类观察者更大的规模和更高的准确性收集数据。它还将支持至少两名研究生的培训和一个教育项目，该项目的目标是在生物学和数据科学的界面上进行本科STEM教育工作者的专业发展。该平台的创建及其在开源许可下的发布将使专业生态学家，公民科学家和大型生物多样性监测计划能够更好地检测物种种群随时间的下降，跟踪气候变化导致的物种分布变化，了解生物多样性变化的相互作用驱动因素，预测未来的灭绝风险，声学调查平台将使用全球定位系统时间同步记录器在坐标空间中定位声音。然后，这些声音位置将用于区分和计数物种内的个体生物。虽然该平台适用于各种物种，但最初将设计用于美国东部的鸣禽繁殖。该奖项的具体目标涉及硬件和软件开发，包括（1）设计一个开源的，廉价的现场记录器，可以收集时间同步的记录，（2）开发和训练一个对象检测卷积神经网络，以识别不同的鸟鸣在时间和频率上的边界，（3）创建检测通知的到达时间差算法，其在坐标空间中定位每个识别的鸟鸣并且使用该数据来计数物种内的个体鸟，（4）完成性能测试和用户测试，对软硬件集成平台进行评估。该平台将被专门评估其比人类观察员更准确和精确地估计繁殖鸟类种群的能力。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

项目成果

OpenSoundscape: An open‐source bioacoustics analysis package for Python

• DOI: 10.1111/2041-210x.14196
• 发表时间: 2023-08
• 期刊: Methods in Ecology and Evolution
• 影响因子: 6.6
• 作者: Sam Lapp;Tessa A. Rhinehart;Louis Freeland‐Haynes;Jatin Khilnani;Alexandra Syunkova;J. Kitzes

When birds sing at the same pitch, they avoid singing at the same time

当鸟儿以相同的音调唱歌时，它们会避免同时唱歌

• DOI: 10.1111/ibi.13192
• 发表时间: 2023
• 期刊: Ibis
• 影响因子: 2.1
• 作者: Chronister, Lauren M.;Rhinehart, Tessa A.;Kitzes, Justin
• 通讯作者: Kitzes, Justin

Expanding NEON biodiversity surveys with new instrumentation and machine learning approaches

• DOI: 10.1002/ecs2.3795
• 发表时间: 2021-11-01
• 期刊: ECOSPHERE
• 影响因子: 2.7
• 作者: Kitzes, Justin;Blake, Rachael;Yule, Kelsey
• 通讯作者: Yule, Kelsey