biomonitoR:用于管理生态数据和计算生物监测指数的R包
Alex Laini1,2, Simone Guareschi3,4, Rossano Bolpagni1
1Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy.
PeerJ
|November 18, 2024
概括
由于工具有限,生物监测数据分析具有挑战性. 新的生物监测R R包简化了生态数据管理和指标计算,有助于环境政策评估和保护工作.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 计算生物学 计算生物学
背景情况:
- 生态数据越来越多,但缺乏处理工具,阻碍了生物监测.
- 当前生物监测分析在数据准备,集成和有限的软件兼容性方面面临着挑战.
- 这些局限性阻碍了有效的生态系统比较,政策评估和保护行动.
研究的目的:
- 引入biomonitoR,一个旨在克服生态数据管理和指标计算方面的技术挑战的R包.
- 为各种生物群体和生态系统的生物监测数据分析提供一个用户友好和集成的环境.
- 支持一个全面和可转移的生物监测工作流程,用于环境管理和保护.
主要方法:
- 开发用于R编程语言的biomonitoR包.
- 实施广泛的生态指数,用于生态和水资源管理.
- 集成可定制的功能用于分类学检查,异质分类学分辨率和数据可视化.
- 包括一个可以从R.直接访问的交互式Web应用程序.
主要成果:
- biomonitoR提供了一个多功能工具箱,解决了关键的生物监测挑战.
- 该包方便对分类学信息进行检查,并支持可变分类学分辨率.
- 它可以计算多个生物指数和用户友好的数据可视化.
- 交互式Web应用程序提高了生物监测社区的可访问性和可用性.
结论:
- biomonitoR显著改善了生物监测生态数据的管理和分析.
- 该方案增强了生物监测信息对环境政策评估和保护的有用性.
- biomonitoR为生态学家,顾问和资源管理人员提供了一个有价值的,用户友好的资源.
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