Collaborative Research: Field course in next-gen forest survey and monitoring in tropical China

生物多样性的迅速丧失，主要是由于与农业和发展有关的土地使用的变化，这使记录和了解生物多样性的模式及其丧失的潜在影响的努力变得更加紧迫。该项目将把美国研究生，在全国范围内招募，到热带中国四周，他们将与亚洲研究生，在该地区的许多热带国家招募，研究森林管理和恢复问题，并学习使用尖端技术的快速生物调查协议。该课程将在中国科学院的一个著名研究所西双版纳热带植物园进行。该项目将大大增加我们对中国云南西双版纳森林生物多样性的了解，西双版纳拥有独特的物种补充，并受到种植园林扩张的严重压力。已经进行了几项试验，以发展无害环境的混合农林管理系统，并促进在退化和非生产性地点恢复天然林。将利用数字图像、音频和网络共享技术从微观到宏观研究森林生物多样性，并收集环境样本，利用下一代基因测序方法进行分析。该项目将有助于培训生物多样性领域的下一代专家，并将率先采用以现有通用设备为基础的调查方法，以加速收集和分发有关森林状况的有意义数据。由此产生的协议将免费提供，并积极更新和改进。该课程将侧重于国际合作技能的发展，并将通过将于明年秋季提供的“分布式讨论”课程鼓励参与者之间的持续互动。 除了森林恢复的主题之外，该课程还将让学生学习基于网络的实时互动与合作的最佳实践。该项目由生物多样性计划和国际科学与工程办公室联合支持。

The rapid loss of biological diversity, due in large part to changes in land use related to agriculture and development, has lent a new urgency to efforts to document and understand patterns of biodiversity and the potential impacts of its loss. This project will bring US graduate students, recruited nationally, to tropical China for four weeks where they will work with Asian graduate students, recruited from the many tropical countries in the region, to study issues of forest management and restoration and to learn protocols for rapid biological surveys using cutting-edge technologies. The course will be based at the Xishuangbanna Tropical Botanical Garden, a well-established research institute in the Chinese Academy of Sciences. This project will substantially increase our knowledge of the biological diversity of the forests of Xishuangbanna, Yunnan, China, which are home to a unique complement of species and which are under severe pressure from expanding plantation forests. Several experimental trials have been established to develop environmentally-friendly mixed agro-forestry management systems and to promote the restoration of natural forest on degraded and unproductive sites. Digital imagery, audio, and web-based sharing technologies will be used to study forest biodiversity, from micro- to macro-scopic scales, and environmental samples will be collected for analysis using next-generation gene sequencing methods. This project will contribute to the training of the next generation of experts in the field of biodiversity and it will pioneer survey methods based on commonly available equipment to accelerate the collection and distribution of meaningful data about forest condition. The resulting protocols will be freely available and actively updated and improved. The course will focus on the development of international collaboration skills, and continued interaction among participants will be encouraged through a 'distributed discussion' course to be offered in the following fall. Beyond the topic of forest restoration, the course will allow students to learn best practices for live web-based interaction and cooperation.This project is jointly supported by the Dimensions of Biodiversity program and the Office of International Science and Engineering.