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克服生物多样性保护中的数据危机。

Overcoming the Data Crisis in Biodiversity Conservation.

机构信息

Department of Ecology, Evolution, and Natural Resources, Rutgers University, 14 College Farm Road, New Brunswick, NJ 08901, USA.

Earth to Ocean Research Group, Department of Biological Sciences, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.

出版信息

Trends Ecol Evol. 2018 Sep;33(9):676-688. doi: 10.1016/j.tree.2018.06.004. Epub 2018 Jul 7.

Abstract

How can we track population trends when monitoring data are sparse? Population declines can go undetected, despite ongoing threats. For example, only one of every 200 harvested species are monitored. This gap leads to uncertainty about the seriousness of declines and hampers effective conservation. Collecting more data is important, but we can also make better use of existing information. Prior knowledge of physiology, life history, and community ecology can be used to inform population models. Additionally, in multispecies models, information can be shared among taxa based on phylogenetic, spatial, or temporal proximity. By exploiting generalities across species that share evolutionary or ecological characteristics within Bayesian hierarchical models, we can fill crucial gaps in the assessment of species' status with unparalleled quantitative rigor.

摘要

当监测数据稀疏时,我们如何跟踪人口趋势?尽管持续存在威胁,但人口下降可能仍未被发现。例如,每 200 种被收获的物种中只有一种被监测。这种差距导致人们对下降的严重程度不确定,并阻碍了有效的保护。收集更多的数据很重要,但我们也可以更好地利用现有信息。对生理学、生活史和群落生态学的先验知识可以用于为种群模型提供信息。此外,在多物种模型中,可以根据系统发育、空间或时间接近程度在分类单元之间共享信息。通过在贝叶斯层次模型中利用具有进化或生态特征的物种之间的共性,可以以前所未有的定量严谨性填补物种状况评估中的关键空白。

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