All articles published in the Web of Science database with the search subject words "(alpine meadow OR alpine meadows OR alpine-cold meadow OR high-cold meadow)" and “alpine meadow research”. The literature search period was set as “1 January 2000 to 31 December 2021". After we cleaned the data and removed duplicates, we obtained a total of 3,607 articles in the field of alpine meadow research. The citation data of these documents were obtained from the Web of Science collection, saved in “plain text” txt format, and then imported into the VOS viewer (Version 1.6.13) software.

VOS viewer software constructs and presents bibliometric maps of distance, size and density differences between nodes based on the co-citation and high-citation principles of the literature. It evaluates the research direction and hotspot of the literature by cluster viewing, overlay viewing and density viewing (Van Eck and Waltman, 2010). VOS viewer runs in Java environment and can import The VOS viewer runs in Java and can import literature in Web of Science format. By clicking “Create” in VOS viewer, the literature is imported into the software, and objects are selected and thresholds are set according to the analysis objectives (Gao et al., 2021). The distance between nodes indicates the closeness and similarity of the subject terms, and the node size represents the frequency of occurrence, and the higher density means the closer the connection and the stronger the relevance (Ling et al., 2020). In this study, the Type of analysis was selected as Co-occurrence, and the Unit of analysis was selected as Keywords, Authors, Organizations and Full counting. The frequency of co-occurrence of keywords is more than 25 times, which is a high frequency word and shows the research hotspots.

In order to make the clustering effect of the network mapping produced by VOS viewer more obvious, the results of VOS viewer were saved in Pajek format, named net., clu. and vec. files respectively. The saved files were then imported sequentially into Pajek software (Pajek software large complex network analysis tool is a powerful tool for studying various complex non-linear networks that exist today. pajek runs in a Windows environment and is used for analysis and visualization operations of large networks with thousands or even millions of nodes (De Nooy et al., 2018) that performs reordering clustering followed by importing into VOS viewer software. The co-cited national geographic visualization plots in the paper were produced by VOS viewer combined with Scimago Graphica software. Plots of the volume of articles issued by year were made by the software Origin Pro 2021.

The year, journal, author, institution, country/region, literature citation and keywords of alpine meadow related literature were analyzed using Microsoft Excel 2016 software, and the authors, institutions, country distribution and collaboration, literature co-citation and keywords were systematically analyzed and visualized using VOS viewer software for bibliometric analysis. The authors, institutions, country distribution and collaboration, literature co-citation and keywords were systematically analyzed and visualized using VOS viewer software (Li and Liu, 2020). Considering the rigor and accuracy of the study, the literature search statistics were searched independently by one researcher and proofread by one researcher.

The year of publication of the 3,607 papers counted shows that the overall number of papers in the field of alpine meadows is on the rise, especially in the last decade with more increments, and the maximum number of papers published in 2021 is 383 (Figure 1). The overall trend of linear growth of the paper issuing articles was demonstrated by linear regression using origin Pro 2021, and the equation was obtained as y = 15.958x-31941 with R ² = 0.8779, indicating into an extremely significant linear relationship. After 2000, alpine meadow research entered the exponential growth stage, that is, alpine meadow research has a mature theoretical foundation and enters the stage of theoretical application.

Analyzing Figure 2, we found that the countries with high publication volume are China, United States, Germany, Japan, France, Australia, and Canada. These countries not only have strong research strength, but also have extensive research cooperation networks, and most of the alpine meadow research results come from these countries. China is the top country in the field of alpine meadow research, far ahead of other countries, because China has the “Qinghai-Tibet Plateau”, which is known as the third pole of the world, and alpine meadows account for 47% of the Qinghai-Tibet Plateau, which facilitates Chinese scholars to conduct research; it also reflects the importance of China in the field of alpine meadow research sideways.

The inter-country cooperation in alpine meadow research was analyzed using VOS viewer software, and the thicker the connecting line, the greater the number of country cooperation. The results show that China has established international cooperation with many countries, and the closest cooperation is with the United States, followed by New Zealand, Japan, and Australia. The results show that countries such as Sweden and Finland have researched in the field of alpine meadows before 2012, countries such as Norway, India, Canada, and Italy acted to research alpine meadows in 2014, and countries such as People r China, New Zealand, and Mongolia researched alpine meadows mainly after 2016 (Figure 3). The density analysis can be found that China and United States have more concentrated research in the field of alpine meadows (Figure 4).

The top three authors with the largest number of publications were Zhou, Huakun (81), Du, Guozhen (80) and Wang, Shiping (74) (Table 1), all from China. Meanwhile, the top 15 authors in the field of alpine meadows were all from China according to the study authorship collaboration. The map shows that in the field of alpine meadows, several collaborative sub-networks have been formed with the above authors as the core, and there are strong academic ties among scholars within the sub-networks, but there are collaborative relationships of varying strengths outside the sub-networks. This indicates that Chinese scholars in the field of alpine meadow research have strong ties within their respective teams, and that cooperation between individual teams needs to be strengthened.

The VOS viewer was used to map the co-occurrence of authors to.the trend of close cooperation within teams and lack of cooperation among teams in the field of alpine meadow research, as shown in the study results, is to some extent detrimental to the development of the field (Figure 5), and only through mutual communication and joint learning can we achieve breakthrough results in the field of alpine meadow research in Qinghai-Tibet. Therefore, there is a need to strengthen the cooperation and connection between various teams and scholars in China.

The number of published papers by research institutions can represent the research capability of their fields. 2,158 research institutions were listed in 3,607 papers, and the minimum number of 10 papers per institution was set, and 140 institutions were qualified. Chinese Acad Sci ranked first with 1,514 papers, followed by Chinese univ Chinese Acad Sci (575 papers) and Lanzhou university (549 papers) (Table 2).

The analysis of institutional cooperation network mapping showed that there were more local cooperation among research institutions, but less cross-regional cooperation, for example, there was very little cooperation between Qinghai Normal University and various research institutions, and mainly with Chinese Acad Sci and Lanzhou Univ (Figure 6). By superimposing the time of publication on the co-occurrence network of research institutions to obtain the time superimposition of institutions, i.e., different colors correspond to the average year of appearance of institutions in the literature, we can find the evolutionary trend of research institutions in alpine meadows, and Chinese Acad Sci, Qinghai Univ and Beijing Forestry Univ are the main research hotspots in alpine meadows (Figure 7). The trend of evolution of research institutions in alpine meadows can be found.

A total of 12,919 keywords were obtained in 3,607 documents. The accuracy and frequency of keywords are two important factors that affect the accuracy of the results of the co-occurrence method to identify research hotspots in the field (Pan et al., 2018). In order to make the analysis results more accurate, the keywords in the literature were first cleaned and collated, which mainly included the unification of the case and singular and plural of words, full names and abbreviations and synonyms. The cleaned keywords were counted by VOS viewer, and the keywords with frequencies >25 times were set as high-frequency keywords, and the keywords with the highest frequencies but no analysis significance, such as “response” and “impact”, were eliminated. The keyword co-occurrence network mapping, including clustering map, time superposition map, etc., was drawn.

According to the keyword co-occurrence network analysis, the current directional atmosphere of the alpine meadow research field can be divided into five major categories, which are red area, diversity direction; green area, research direction of microorganisms and nutrients such as carbon, nitrogen and phosphorus; blue area, research direction of climate change and soil respiration; purple area, research direction related to gases such as CO₂ and CH₄; yellow area, research direction related to grazing and grassland degradation (Figure 8). The time of publication was superimposed on the keyword co-occurrence network to obtain the keyword time superimposed map (Figure 9), i.e., different colors correspond to the average year of keyword appearance in the literature, and the research evolution trend of the field can be found. sensitivity, soil respiration, nitrogen deposition, N₂O emissions, fungi, bacteria, etc. are the latest research hotspots in alpine meadows.

Smith. (2007) and Ugolini et al. (2015) showed that the number of co-citations indicates the influence, visibility and quality of a publication; however, Walter et al. (2003) noted that the number of citations by others does not indicate the quality of a publication, but rather measures its visibility. Therefore, co-citations of papers can identify scholars and institutions that have made significant contributions to the field or have struggled in the field for a long time, etc.

Analysis of Figure 10 shows that more than ten authors and their teams have certain popularity and influence in the field of alpine meadow research, and there are close collaborations among scholars within their teams; however, there are fewer collaborations among the teams. For example, Huakun Zhou’s team cooperates closely with Xinquan Zhao’s team, Wenying Wang’s team, Shiping Wang’s team, and Fujiang Hou’s team; and rarely with Xianzhou Zhang’s team and Guozhen Du’s team. The former teams are all located in northwestern China, on the one hand, because they are near the Qinghai-Tibetan Plateau, which facilitates cooperation among teams; on the other hand, it shows the lack of interaction between Chinese scholars and the need to strengthen cooperation and contact.

Table 3 shows the top ten co-cited articles in the field of alpine meadows, all with more than 120 co-citations, with the top article published in 2009 with 237 co-citations, followed by 170, and 141 co-citations. The most recent article was published in 2012 by Shiping Wang in ecology on the effects of warming and grazing on alpine meadow soils, with 130 citations. Nowadays, with the global climate change and the presence of herders on the Tibetan plateau, grazing and alpine meadows are inextricably linked, so this article is very informative in the study of alpine meadows.

As can be seen from Figure 11, Chinese Acad Sci is the main institution in terms of co-cited articles and far exceeds other institutions in terms of co-cited articles published. univ Chinese Acad Sci, Lanzhou Univ, and Beijing Normal Univ rank second, third, and fourth, respectively. Qinghai Univ (orange part in the figure) also contributes in the contribution of many Universities (institutions) such as Qinghai normal univ in the field of alpine meadow research cannot be ignored. It also shows that China’s research in the field of alpine meadow research far exceeds that of other international countries.

There are 15 countries with >48 articles among the 80 countries in the co-cited papers. Analysis of the geographical visualization map of co-cited countries (Figure 12) shows that the clustering results in three categories, the first category is dominated by Austria (the blue area), including Germany, the United Kingdom, and Italy, etc.; the second category is composed of countries such as China, the US, Japan and Australia (the purple area), and the third category is Canada (the red area). The thickness of the lines in the graph represents the intensity of cooperation, and it can be seen that the first-ranked China and the second-ranked United States cooperate closely, while other countries have cooperation relationships of varying intensity with each other.