A comprehensive analysis of R’s application in ecological research from 2008 to 2023

Abstract The field of ecology has been greatly enhanced by the integration of computational tools and statistical methods, with the programming language R emerging as a pivotal and flexible tool for ecological research. As ecological studies accelerate, understanding the prevalent trends and specific usage patterns of R in recent research is crucial. This study investigated the use of R and its packages in 125 494 scholarly articles published in 40 ecology journals from 2008 to 2023. A total of 52 658 articles (42%) designated R as their principal analytical tool, demonstrating a steady linear growth in its utilization from 10.3% in 2008 to 66.9% in 2023. Twelve R packages, including ‘lme4’, ‘vegan’, ‘nlme’, ‘MuMIn’, ‘ape’, ‘ggplot2’, ‘car’, ‘mgcv’, ‘MASS’, ‘raster’, ‘multcomp’ and ‘lmerTest’, each played a pivotal role in contributing to more than 1000 scholarly articles. The highest usage rate of the 'lme4' package indicates that mixed-effect models have a particularly important role in ecological research, and the application of these models has helped ecologists solve many important scientific problems. Journal-specific package preferences aligned with their scientific domains, while the rise in the average number of R packages per article indicates a trend towards more complex and diverse analytical methods in ecology. Our findings reveal a reciprocal relationship between the development of R and ecological research, underscoring the need for collaboration among quantitative ecologists, R developers and ecologists to further advance both the language and the field. Such collaboration will not only enhance the functionality and versatility of R but also provide robust technical support for the continued progress of ecological research.