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生态恢复监测研究进展——基于最近三届世界生态恢复大会报告的统计分析

张绍良,刘润,侯湖平*,杨永均   

  1. (中国矿业大学环境与测绘学院, 江苏徐州 221116)
  • 出版日期:2018-06-10 发布日期:2018-06-10

The advances of ecological restoration monitoring: Analysis of the latest three world congresses on ecological restoration.

ZHANG Shao-liang, LIU Run, HOU Hu-ping*, YANG Yong-jun   

  1. (School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, Jiangsu, China).
  • Online:2018-06-10 Published:2018-06-10

摘要: 生态恢复技术选择的可靠性、恢复工程管理的有效性、恢复项目实施效果的可比性以及生态恢复成功的判断标准等均要求对生态恢复的全过程、全要素进行监测,然而全球可共同遵守的生态恢复监测协议仍处于探索中。本文基于最近三届世界生态恢复大会有关生态恢复监测的报告,采用统计分析法综述了生态恢复监测技术、监测协议以及监测指标等的研究进展。在此基础上,预测未来生态恢复监测研究将有如下趋势:(1)监测技术向自动化、智能化和网络化发展、向生态恢复工程的全方位监测方向发展、向技术密集型方向发展、向要素监测与系统监测相结合的方向发展;(2)生态恢复监测指标体系及其标准将取得共识;(3)综合监测和多学科融合的趋势将愈加明显;(4)监测结果的应用将越来越广泛。

关键词: 细菌群落结构, 芒草, PICRUSt分析, 高通量测序

Abstract: Monitoring the whole processes and elements of ecological restoration is required to evaluate the liability of the selection of ecological restoration techniques, the effectiveness ofrestoration project management, the comparability of the implementing effectiveness of restoration projects, and the success criteria of ecological restoration. However, the globally accommodated monitoring protocol of ecological restoration is still under exploration. Based on the reports presented on the latest three world congresses of ecological restoration (SER) and statistical analysis, we reviewed the research progress in monitoring technology, protocol and indicators of ecological restoration. We predict the research trends of the monitoring of ecological restoration would be as follows: (1) Monitoring techniques will develop toward to automation, integration of intelligence and network, all aspects of ecological restoration project, and tech-intensity. (2) The monitoring indicator system and standards of ecological restoration will achieve consensus. (3) The trend of synthetic monitoring and multi-discipline intersection will be more obvious. (4) The monitoring results will be more and more widely used.

Key words: high throughput sequencing, Miscanthus, bacterial community structure, PICRUSt analysis.