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Global Trends and Hotspots in Grassland Root Functional Traits Research (2000-2025)

Feng, x. y.; Gao, Y.; Li, q. j.; Yang, t. y.; Yin, J.; Yang, S.; Jiang, h. z.; Wang, t. x.; Wang, c. p.; Zhao, L. L.

2026-02-03 ecology
10.64898/2026.01.31.702986 bioRxiv
Show abstract

Grasslands, as one of the most important terrestrial ecosystems globally, have root functional traits that serve as key indicators of plant responses to environmental changes and hold significant ecological importance. To reveal the current status, research hotspots, and frontier trends in the field of grassland root functional traits, this study analyzed relevant literature from the Web of Science Core Collection database between 2000 and 2025. It employs bibliometric methods and utilizes visualization tools such as CiteSpace for a systematic analysis. The results indicate that research in this field has been continuously increasing since 2000, reflecting a growing research interest. China, the United States, and Germany are the leading countries in terms of publication output. However, collaboration networks among authors, institutions, and countries are still not tight enough to form a truly global cooperative network. Co-occurrence analysis of keywords and literature clustering reveal that the research hotspots in this field are mainly concentrated in six directions: multidimensional characteristics of root functional traits, interactions between root functional traits and climate change, synergistic effects of root functional traits and soil microorganisms, responses of root functional traits to land-use changes, coupling of root functional traits with ecosystem functions, and applications of root functional traits in agriculture and ecological restoration. Future research should focus on promoting innovation and standardization of research methods, conducting long-term monitoring, deeply exploring the mechanisms of root-microbe interactions, implementing cross-scale integrative research and model construction, and building international collaborative networks.

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