维格沃尔特数据集:将全球古老植物和新植物数据与功能特征和非生物驱动因素联系起来
Ondřej Mottl1,2, Franka Gaiser3, Irena Šímová4,5
1Center for Theoretical Study, Charles University, Jilská 1, CZ-11000, Prague, Czech Republic. ondrej.mottl@gmail.com.
Scientific data
|December 5, 2025
概括
维格沃特集成了全球古老和新生态数据,将植被动态与特征,土壤和气候联系起来. 该资源有助于预测气候和土地利用变化下的生物多样性变化.
科学领域:
- 生态生态学 生态生态学
- 古生态学 古生态学
- 生物多样性科学 生物多样性科学
背景情况:
- 了解长期生物多样性动态对于预测生态系统对全球变化的反应至关重要.
- 整合分散的古生物学和新生态学数据对生态研究来说是一个重大挑战.
- 评估复杂的植被动态需要全面的跨规模数据集.
研究的目的:
- 介绍VegVault,一个跨学科的SQLite数据库,整合跨千年时间尺度的全球基于图片的植被数据.
- 为了全面分析,将各种生态数据与功能特征,土壤和气候信息联系起来.
- 为研究过去和当代生物多样性的研究人员提供准备就绪的资源和R包 ({vaultkeepr}).
主要方法:
- 为生态数据开发一个跨学科的SQLite数据库 (VegVault).
- 整合来自包括BIEN,sPlotOpen和Neotoma在内的来源的基于图片的植被数据.
- 将植被数据与功能特征 (TRY),土壤 (WoSIS) 和气候 (CHELSA) 信息联系起来.
主要成果:
- 在全球和千年规模上,VegVault成功地整合了各种古老和新生态数据.
- 该数据库将植被数据与关键的非生物和生物变量联系起来.
- {vaultkeepr} R 软件包可以简化数据访问和处理.
结论:
- 维格沃特提供了一个独特的,全面的资源,用于生物多样性动态的生态研究.
- 数据库和相关的R包推进了对过去和现在生物多样性模式及其驱动因素的研究.
- 这项工作提高了预测生物多样性对全球气候和土地利用变化的反应的能力.
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