Collaborative Research: Navigating the New Arctic (NNA): Soundscape ecology to assess environmental and anthropogenic controls on wildlife behavior

合作研究：航行新北极（NNA）：声景生态学评估环境和人为对野生动物行为的控制

• 批准号: 1839195
• 负责人: Glen Liston
• 金额: $ 39.88万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1839195&HistoricalAwards=false
• 关键词: Collaborative; Research; Navigating; New; Arctic

Across North America, Arctic and boreal regions have been warming at a rate two to three times higher than the global average. At the same time, human development continues to encroach and intensify, primarily due to demand for natural resources, such as oil and gas. The vast and remote nature of Arctic-boreal regions typify their landscapes, environment, wildlife, and people, but their size and isolation also make it difficult to study how their ecosystems are changing. To overcome these challenges, autonomous recording networks can be used to characterize "soundscapes" - a collection of sounds that emanate from landscapes. Unlike traditional observing methods that are expensive, labor-intensive, and logistically challenging, sound-recording networks provide a cost-effective means to both monitor and understand the response of wildlife to environmental and anthropogenic changes across vast areas. One particular challenge with this sound-measurement approach is extracting useful ecological information from the large volumes of soundscape data that are collected. This project will develop the techniques necessary to overcome this challenge.The researchers' goal is to understand the influence of both environmental dynamics and increasing anthropogenic activity on the behavior and phenology of migratory caribou (Rangifer tarandus), waterfowl, and songbird communities in Arctic-boreal Alaska and northwestern Canada. Through co-production of knowledge with local land managers and indigenous communities, the research team will combine field observations, modeling, and analyses that include: (1) soundscape measurements, (2) camera-trap observations, (3) automated soundscape analyses, (4) analyses of camera-trap caribou observations, (5) high-resolution modeling of environmental variables, (6) statistical analyses including wildlife occupancy, diversity, and phenology modeling, and (7) a human-computation game to collect descriptions of our acoustic recordings that allows for the participation of local and Indigenous players of the game. The project will contribute understanding of how both avian communities and caribou populations are responding to spatiotemporal variations in environmental conditions and increasing development of the oil and gas industry in a region where such comprehensive, large-scale research has rarely been possible. Further, at the request of various Tribal organizations, our research will provide insight into how industrial noise influences traditional practices. In addition, our research will provide baseline data on all natural sounds, including data on bird and caribou activity, in the Arctic National Wildlife Refuge prior to oil and gas development. These datasets will be available to inform Indigenous practices and natural resource management, as well as facilitate future Environmental Assessments required by land managers and oil and gas developers.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.

在整个北美，北极和北方地区的变暖速度比全球平均水平高出两到三倍。与此同时，人类发展继续侵蚀和加剧，主要是由于对石油和天然气等自然资源的需求。北极-寒带地区广阔而偏远的性质是其景观、环境、野生动物和人类的典型特征，但其规模和孤立性也使研究其生态系统如何变化变得困难。为了克服这些挑战，自主录音网络可用于表征“音景”-从景观中发出的声音的集合。与昂贵、劳动密集型和后勤挑战性的传统观测方法不同，录音网络提供了一种具有成本效益的手段，可以监测和了解野生动物对广阔地区环境和人为变化的反应。这种声音测量方法的一个特殊挑战是从收集的大量声景数据中提取有用的生态信息。该项目将开发克服这一挑战所需的技术。研究人员的目标是了解环境动态和日益增加的人类活动对北极-北方阿拉斯加和加拿大西北部迁徙驯鹿（Rangifer tarandus），水禽和鸣禽群落的行为和物候的影响。通过与当地土地管理者和土著社区共同生产知识，研究团队将联合收割机结合实地观察，建模和分析，包括：（1）声景测量，（2）相机陷阱观测，（3）自动声景分析，（4）相机陷阱驯鹿观测分析，（5）环境变量的高分辨率建模，（6）统计分析，包括野生动物占有率，多样性和物候建模，以及（7）人类计算游戏，以收集我们的声音记录的描述，允许当地和土著玩家参与游戏。该项目将有助于了解鸟类群落和驯鹿种群如何应对环境条件的时空变化以及石油和天然气工业的日益发展，在这个地区，这种全面，大规模的研究很少可能。此外，应各部落组织的要求，我们的研究将深入了解工业噪音如何影响传统做法。此外，我们的研究将提供所有自然声音的基线数据，包括在石油和天然气开发之前，北极国家野生动物保护区的鸟类和驯鹿活动数据。这些数据集将为土著人的实践和自然资源管理提供信息，并促进土地管理者和石油天然气开发商未来所需的环境评估。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来支持。