Collaborative Research: Navigating the New Arctic (NNA): Soundscape ecology to assess environmental and anthropogenic controls on wildlife behavior
Collaborative Research: Navigating the New Arctic (NNA): Soundscape ecology to assess environmental and anthropogenic controls on wildlife behavior
批准号:
1839185
负责人:
Johanna Devaney
金额:
$53.56万
依托单位:
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
项目状态:
已结题
起止时间:
2018-09-15 至 2024-08-31
中文摘要
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英文摘要
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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
EDANSA-2019: The Ecoacoustic Dataset from Arctic North Slope Alaska
EANSA-2019:阿拉斯加北极北坡的生态声学数据集
DOI:
10.5281/zenodo.6824272
发表时间:
2022
期刊:
Zenodo
影响因子:
--
作者:
[Çoban, Enis Berk, Perra, Megan, Pir, Dara, Mandel, Michael]
通讯作者:
Mandel, Michael
Towards Large Scale Ecoacoustic Monitoring with Small Amounts of Labeled Data
利用少量标记数据进行大规模生态声学监测
DOI:
10.1109/waspaa52581.2021.9632743
发表时间:
2021
期刊:
IEEE Workshop on Applications of Signal Processing to Audio and Acoustics
影响因子:
--
作者:
[Coban, Enis Berk, Syed, Ali Raza, Pir, Dara, Mandel, Michael I]
通讯作者:
Mandel, Michael I
EAGER: III: Learning with less data: Capitalizing on formal pedagogies and human performance to incorporate domain knowledge into deep learning models
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批准号:2228910
-
项目类别:Standard Grant
-
资助金额:$20.0万
-
财政年份:2022
-
负责人:Johanna Devaney
-
依托单位:
国内基金
海外基金
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