Jiangshan Lai, Weijie Zhu, Dongfang Cui, Dayong Fan, Lingfeng Mao
{"title":"The use of R in forestry research","authors":"Jiangshan Lai, Weijie Zhu, Dongfang Cui, Dayong Fan, Lingfeng Mao","doi":"10.1093/jpe/rtad047","DOIUrl":null,"url":null,"abstract":"\n The field of forestry research has greatly benefited from the integration of computational tools and statistical methods in recent years. Among these tools, the programming language R has emerged as a powerful and versatile platform for conducting various aspects of forestry research, from data analysis, modeling to visualization. However, the key trends in general reported R use and patterns in forestry research remains unknown. We conducted an analysis of R and R package usage frequencies across a span of ten years, from 2013 to 2022, within the context of more than 14,800 research articles published in eight top forestry journals. Among these articles, a notable amount of 6,790 (accounting for 45.7%) explicitly utilized R as their primary tool for data analysis. The adoption of R exhibited a linear growth trend, rising from 28.3% in 2013 to 60.9% in 2022. The top five used packages reported were vegan, lme4, nlme, MuMIn, and ggplot2. Diverse journals have their unique areas of emphasis, resulting in disparities in the frequency of R package application among journals. The average number of R packages used per article also shows an increasing trend over time. The study underscores the recognition that R, with its powerful statistical and data visualization capabilities, plays a pivotal role in enabling researchers to conduct in-depth analyses and gain comprehensive insights into various aspects of forestry science.","PeriodicalId":50085,"journal":{"name":"Journal of Plant Ecology","volume":"26 2","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Plant Ecology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/jpe/rtad047","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The field of forestry research has greatly benefited from the integration of computational tools and statistical methods in recent years. Among these tools, the programming language R has emerged as a powerful and versatile platform for conducting various aspects of forestry research, from data analysis, modeling to visualization. However, the key trends in general reported R use and patterns in forestry research remains unknown. We conducted an analysis of R and R package usage frequencies across a span of ten years, from 2013 to 2022, within the context of more than 14,800 research articles published in eight top forestry journals. Among these articles, a notable amount of 6,790 (accounting for 45.7%) explicitly utilized R as their primary tool for data analysis. The adoption of R exhibited a linear growth trend, rising from 28.3% in 2013 to 60.9% in 2022. The top five used packages reported were vegan, lme4, nlme, MuMIn, and ggplot2. Diverse journals have their unique areas of emphasis, resulting in disparities in the frequency of R package application among journals. The average number of R packages used per article also shows an increasing trend over time. The study underscores the recognition that R, with its powerful statistical and data visualization capabilities, plays a pivotal role in enabling researchers to conduct in-depth analyses and gain comprehensive insights into various aspects of forestry science.
近年来,计算工具和统计方法的整合使林业研究领域受益匪浅。在这些工具中,编程语言 R 已成为一个功能强大、用途广泛的平台,可用于开展从数据分析、建模到可视化等各方面的林业研究。然而,R 语言在林业研究中的普遍使用趋势和模式仍不为人知。从 2013 年到 2022 年的十年间,我们对八种顶级林业期刊上发表的 14800 多篇研究文章中的 R 和 R 软件包使用频率进行了分析。在这些文章中,有 6790 篇(占 45.7%)明确使用 R 作为数据分析的主要工具。R的采用率呈线性增长趋势,从2013年的28.3%上升到2022年的60.9%。据报道,使用最多的五个软件包是vegan、lme4、nlme、MuMIn和ggplot2。不同的期刊有其独特的重点领域,这导致了期刊间 R 软件包应用频率的差异。随着时间的推移,每篇文章使用的 R 软件包的平均数量也呈上升趋势。这项研究强调,R 凭借其强大的统计和数据可视化功能,在帮助研究人员进行深入分析和全面了解林业科学的各个方面方面发挥着举足轻重的作用。
期刊介绍:
Journal of Plant Ecology (JPE) serves as an important medium for ecologists to present research findings and discuss challenging issues in the broad field of plants and their interactions with biotic and abiotic environment. The JPE will cover all aspects of plant ecology, including plant ecophysiology, population ecology, community ecology, ecosystem ecology and landscape ecology as well as conservation ecology, evolutionary ecology, and theoretical ecology.