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

了解大尺度陆地野生动物群落丰度的确定过程和估计大范围野生动物丰度仍然是一个重大挑战。对于大多数物种来说，调节其分布和种群规模年波动的因素是未知的。这个项目利用了运动敏感相机陷阱作为传感器网络来估计动物丰度的关键创新。这种新方法可以得到任何陆生动物100克的丰度数据，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项目，没有其他项目的典型偏见或数据质量问题，为在大范围内进行可持续的密集抽样工作提供了可能。软件将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？美国的小组将用相机对当地的野生动物群落进行采样。结果数据将使用新的多尺度统计模型进行分析，以发现调节大面积野生动物数量的过程。绘制广阔地区野生动物种群的本地丰度图将是理解土地管理决策和区域气候变化导致的变化机制的关键。通过让市民参与数据收集，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，这不仅为科学家提供了一个工具，也为公众提供了一个了解他们所在地区动物群落的新窗口。

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.