Suppr超能文献

生物多样性研究和监测中的长期数据集:通过时间评估生态群落的变化。

Long-term datasets in biodiversity research and monitoring: assessing change in ecological communities through time.

机构信息

Scottish Oceans Institute, School of Biology, University of St Andrews, St Andrews, Fife KY16 8LB, UK.

出版信息

Trends Ecol Evol. 2010 Oct;25(10):574-82. doi: 10.1016/j.tree.2010.06.016. Epub 2010 Jul 23.

Abstract

The growing need for baseline data against which efforts to reduce the rate of biodiversity loss can be judged highlights the importance of long-term datasets, some of which are as old as ecology itself. We review methods of evaluating change in biodiversity at the community level using these datasets, and contrast whole-community approaches with those that combine information from different species and habitats. As all communities experience temporal turnover, one of the biggest challenges is distinguishing change that can be attributed to external factors, such as anthropogenic activities, from underlying natural change. We also discuss methodological issues, such as false alerts and modifications in design, of which users of these data sets need to be aware.

摘要

对生物多样性丧失率降低的努力进行评估的基础数据的需求日益增长,这凸显了长期数据集的重要性,其中一些数据集的历史与生态学本身一样悠久。我们回顾了使用这些数据集评估群落水平生物多样性变化的方法,并对比了整体群落方法与那些结合不同物种和生境信息的方法。由于所有群落都经历了时间上的更替,最大的挑战之一是区分可以归因于人为活动等外部因素的变化与潜在的自然变化。我们还讨论了这些数据集使用者需要注意的方法学问题,如虚假警报和设计的修改。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验