Collaborative Research: Processes Determining the Abundance of Terrestrial Wildlife Communities Across Large Scales

合作研究：大规模确定陆地野生动物群落丰度的过程

• 批准号: 1065749
• 负责人: Zhihai He
• 金额: $ 37.42万
• 依托单位: University of Missouri-Columbia
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1065749&HistoricalAwards=false
• 关键词: Collaborative; Research; Processes; Determining; Abundance

Understanding the processes determining abundance of terrestrial wildlife communities across large scales and estimating the abundance of wildlife across large areas remain a major challenge. For most species, the factors that regulate their distribution and yearly fluctuations in population size are unknown. This project takes advantage of the key innovation of using motion sensitive camera traps as a network of sensors for estimating animal abundance. This new approach can produce abundance data for any terrestrial animal 100g, typically ~60% of the terrestrial animals in the eastern USA. Furthermore, the method is amenable to citizen science programs, without the biases or data quality issues typical of other programs, opening the possibility of a sustainable dense sampling effort across large areas. Software will be developed efficiently enter and to manage camera images and associated data. Using standardize field techniques citizen?s groups will sample their local wildlife communities with cameras. The resulting data will be analyzed using new multi-scale statistical models to discover the processes regulating wildlife abundance over large areas. Mapping the local abundance of wildlife populations across broad areas will be key to understanding the mechanisms responsible for changes resulting from land-management decisions and regional climate variation. By involving citizens in data collection this project will be helping local wildlife populations. All data and images will be made freely available online, providing a tool not only for scientists, but also to give the public a new window into the animal communities of their region.

了解大规模确定陆地野生动物群落丰度的过程和估计大面积野生动物丰度仍然是一个重大挑战。 对大多数物种来说，调节其分布和种群规模年度波动的因素尚不清楚。 该项目利用了使用运动敏感相机陷阱作为估计动物丰度的传感器网络的关键创新。这种新方法可以为任何100克的陆生动物产生丰度数据，通常约占美国东部陆生动物的60%。此外，该方法适用于公民科学计划，没有其他计划典型的偏见或数据质量问题，为大面积可持续密集采样工作提供了可能性。软件将被开发有效地输入和管理相机图像和相关数据。使用标准化的现场技术公民？研究小组将用照相机对当地的野生动物群落进行取样。将使用新的多尺度统计模型分析由此产生的数据，以发现调节大面积野生动物丰度的过程。绘制广泛地区野生动物种群的本地丰度图将是了解土地管理决策和区域气候变化导致变化的机制的关键。通过让公民参与数据收集，该项目将帮助当地野生动物种群。所有数据和图像都将在网上免费提供，不仅为科学家提供了一个工具，也为公众提供了一个了解其所在地区动物群落的新窗口。