Workshop: Linking remote animal detection and movement data with macrosystem environmental datasets and networks; September, 2018; Front Royal, VA

研讨会：将远程动物检测和运动数据与宏观系统环境数据集和网络联系起来；

• 批准号: 1823498
• 负责人: David Luther
• 金额: $ 4.76万
• 依托单位: George Mason 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: 2018-05-01 至 2020-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823498&HistoricalAwards=false
• 关键词: Workshop; Linking; remote; animal; detection

Technological advances have allowed scientists to collect vast quantities of data on animal occurrences and movements from remote locations in ways that weren?t possible even a generation ago. Examples of technology improving the specificity of animal data are acoustic recordings, camera-traps, radiotelemetry, and geolocators. These data have broadened our knowledge of where individual animals live and their movement patterns. In addition, relatively new technologies such as remote sensing from satellites and aircraft, and observation networks are providing large quantities of environmental data, such as rainfall, vegetation productivity, structure, connectivity and more at landscape and macrosystem scales that were not previously possible. These advances in technology, along with increased connectivity of internet users, have allowed a broader involvement of the public in collecting animal or environmental data. The challenge in many cases has been to link the animal-observations information, being collected by citizens, local groups, as well as national and international agencies, to relevant large-scale environmental datasets. This project addresses these issues in a workshop with experts that have helped advance the new technologies associated with animal detections and environmental data at landscape and macrosystem scales.The explicitly inter-disciplinary nature of the workshop will foster linkages and collaborations that aim to alleviate technical barriers for scaling the information from animal observations to environmental datasets at macrosystem scales. Such barriers currently limit researchers from broadening the scale and scope of their research. There will be a two-day workshop that focuses on how new technologies and capabilities that investigate the distribution and movement of animals can be linked to environmental states and environmental changes at the landscape and macrosystem scales. The workshop will bring together experts in the fields of remote sensing and animal detection with the goal of integrating the various technologies and lay the foundation for a review paper on the potential of combined techniques to answer important questions in ecology and conservation biology.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.

科技进步使科学家能够从偏远地区收集大量动物发生和活动的数据，这在上一代人之前都是不可能的。提高动物数据特异性的技术例子有声学记录、相机陷阱、无线电遥测和地理定位器。这些数据拓宽了我们对单个动物生活在哪里以及它们的运动模式的了解。此外，相对较新的技术，如卫星和飞机遥感以及观测网络，正在提供大量的环境数据，如降雨量、植被生产力、结构、连通性等，这是以前不可能在景观和大系统范围内提供的。这些技术的进步，加上互联网用户连通性的增加，使公众能够更广泛地参与收集动物或环境数据。在许多情况下，挑战在于将公民、地方团体以及国家和国际机构收集的动物观察信息与相关的大规模环境数据集联系起来。该项目在一个与专家一起举办的研讨会上解决了这些问题，这些专家帮助推进了与景观和大系统尺度上的动物检测和环境数据相关的新技术。研讨会的明确跨学科性质将促进联系和合作，旨在减少从动物观察到大系统尺度上的环境数据集的信息的技术障碍。这些障碍目前限制了研究人员扩大他们的研究范围和范围。将有一个为期两天的研讨会，重点是如何将调查动物分布和移动的新技术和能力与景观和大系统尺度上的环境状况和环境变化联系起来。研讨会将汇集遥感和动物探测领域的专家，目标是整合各种技术，并为一篇关于组合技术的潜力的评论论文奠定基础，以回答生态和保护生物学中的重要问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。