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Grassland in Qinghai as the main type of ecosystem in this region is located in arid and semi-arid areas. The ecosystem is fragile and sensitive to climate change. Grassland ecosystem not only provides essential ecological and life functions for human society but also plays a vital role in mitigating and adapting to climate change. The empirical literature on grassland ecosystem services value (ESV) does not consider the impact of climate change and regional economic development level factors, which prevents policymakers from making appropriate decisions. This paper aims to analyze the influencing factors of grassland ESV assessment, and, based on the meta-prediction model, account the grassland ESV in Qinghai province.

To understand the value of grassland ecosystem services in China under climate change, this paper used 61 research literature on the evaluation of grassland ESV in China, including a total of 564 value observations to establish a value transfer database. Based on the meta-analysis method, this study has constructed a value transfer model, to evaluate the grassland ESV in Qinghai province, and an interpretation model, which can analyze if the independent variables affect the grassland ESV significantly.

The study finds that the evaluation methods, types of ecosystem service functions, climate change and grassland types can affect the grassland ESV significantly. Based on the meta-regression prediction model to evaluate the grassland ESV in Qinghai is US$1,542.67/ha/year. It indicates several targeted approaches to increase the grassland ESV, and climate change also has a specific impact on the value of grassland ecosystem services.

This study provides a scientific basis for grassland management related to the development of grasslands and ecological compensation, as well as promote the sustainable development of grassland ecosystems.

This paper contributes to the field of grassland ESV assessment in at least three aspects; first, it innovatively introduces the meta-analysis to carry out an integrated analysis of previous research results; second, it includes a broader set of influence variables in the analysis, including meteorological and economic factors; and third, it establishes a methodological basis for the field of grassland ESV accounting.

This study aims to provide a systematic and complete knowledge map for use by researchers working in the field of research data. Additionally, the aim is to help them quickly understand the authors' collaboration characteristics, institutional collaboration characteristics, trending research topics, evolutionary trends and research frontiers of scholars from the perspective of library informatics.

The authors adopt the bibliometric method, and with the help of bibliometric analysis software CiteSpace and VOSviewer, quantitatively analyze the retrieved literature data. The analysis results are presented in the form of tables and visualization maps in this paper.

The research results from this study show that collaboration between scholars and institutions is weak. It also identified the current hotspots in the field of research data, these being: data literacy education, research data sharing, data integration management and joint library cataloguing and data research support services, among others. The important dimensions to consider for future research are the library's participation in a trans-organizational and trans-stage integration of research data, functional improvement of a research data sharing platform, practice of data literacy education methods and models, and improvement of research data service quality.

Previous literature reviews on research data are qualitative studies, while few are quantitative studies. Therefore, this paper uses quantitative research methods, such as bibliometrics, data mining and knowledge map, to reveal the research progress and trend systematically and intuitively on the research data topic based on published literature, and to provide a reference for the further study of this topic in the future.