University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia.
University of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia.
Environ Res. 2021 Jun;197:111087. doi: 10.1016/j.envres.2021.111087. Epub 2021 Mar 31.
Soil erosion can present a major threat to agriculture due to loss of soil, nutrients, and organic carbon. Therefore, soil erosion modelling is one of the steps used to plan suitable soil protection measures and detect erosion hotspots. A bibliometric analysis of this topic can reveal research patterns and soil erosion modelling characteristics that can help identify steps needed to enhance the research conducted in this field. Therefore, a detailed bibliometric analysis, including investigation of collaboration networks and citation patterns, should be conducted. The updated version of the Global Applications of Soil Erosion Modelling Tracker (GASEMT) database contains information about citation characteristics and publication type. Here, we investigated the impact of the number of authors, the publication type and the selected journal on the number of citations. Generalized boosted regression tree (BRT) modelling was used to evaluate the most relevant variables related to soil erosion modelling. Additionally, bibliometric networks were analysed and visualized. This study revealed that the selection of the soil erosion model has the largest impact on the number of publication citations, followed by the modelling scale and the publication's CiteScore. Some of the other GASEMT database attributes such as model calibration and validation have negligible influence on the number of citations according to the BRT model. Although it is true that studies that conduct calibration, on average, received around 30% more citations, than studies where calibration was not performed. Moreover, the bibliographic coupling and citation networks show a clear continental pattern, although the co-authorship network does not show the same characteristics. Therefore, soil erosion modellers should conduct even more comprehensive review of past studies and focus not just on the research conducted in the same country or continent. Moreover, when evaluating soil erosion models, an additional focus should be given to field measurements, model calibration, performance assessment and uncertainty of modelling results. The results of this study indicate that these GASEMT database attributes had smaller impact on the number of citations, according to the BRT model, than anticipated, which could suggest that these attributes should be given additional attention by the soil erosion modelling community. This study provides a kind of bibliographic benchmark for soil erosion modelling research papers as modellers can estimate the influence of their paper.
土壤侵蚀会导致土壤、养分和有机碳流失，从而对农业造成重大威胁。因此，土壤侵蚀建模是规划合适的土壤保护措施和发现侵蚀热点的步骤之一。对该主题的文献计量分析可以揭示研究模式和土壤侵蚀建模的特征，从而有助于确定增强该领域研究所需的步骤。因此，应该进行详细的文献计量分析，包括合作网络和引文模式的调查。更新后的全球土壤侵蚀建模应用追踪器（GASEMT）数据库包含有关引文特征和出版物类型的信息。在这里，我们研究了作者数量、出版物类型和选定期刊对引文数量的影响。广义增强回归树（BRT）模型用于评估与土壤侵蚀建模最相关的变量。此外，还分析和可视化了文献计量网络。本研究表明，土壤侵蚀模型的选择对出版物引用数量的影响最大，其次是建模规模和出版物的 CiteScore。根据 BRT 模型，GASEMT 数据库的其他一些属性，如模型校准和验证，对引文数量的影响可以忽略不计。虽然校准的研究平均比没有进行校准的研究获得约 30%的更多引用是正确的，但实际上，这表明在评估土壤侵蚀模型时，还需要对过去的研究进行更全面的审查，而不仅仅是关注在同一国家或大陆进行的研究。此外，当评估土壤侵蚀模型时，应更加关注现场测量、模型校准、性能评估和建模结果的不确定性。本研究结果表明，根据 BRT 模型，这些 GASEMT 数据库属性对引文数量的影响比预期的要小，这可能表明土壤侵蚀建模社区应该给予这些属性更多的关注。本研究为土壤侵蚀建模研究论文提供了一种文献计量基准，模型可以估计其论文的影响。
