Abstract: Vegetation plot data play a crucial role in addressing major scientific questions, including theoretical issues such as community assembly mechanisms and species distribution patterns, as well as practical challenges like responses to global environmental change. However, the broad use of these data is constrained by factors such as structural discrepancies, restricted access, and duplicate records. Therefore, this paper identified ten prominent global public vegetation plot databases through literature review and expert consultations, including GIVD, sPlot, BIEN, VegBank, EVA, FIA, GFBI, BioTIME, ReSurveyEurope, and forestREplot. We compiled datasets across these databases and analyzed their characteristics to enhance data usability and support macroecological research.Our results show that, as of May 2026, these 10 vegetation plot databases have integrated data from 6.109 million plots, yet significant limitations remain. First, the spatial distribution is extremely uneven, with plots heavily concentrated in Europe (4.079 million, 67.1%) and North America (1.353 million, 22.1%), while data from other regions are severely scarce. Second, data heterogeneity is high: 78.5% (4.370 million) of the plots contain complete vascular plant checklists, whereas 21.5% (1.914 million) record only woody plants. Species abundance metrics are primarily recorded as cover (63.1%, 3.388 million plots); fewer than 35% of plots record individual counts or diameter at breast height (DBH)/tree height. Third, crucial information is widely lacking: the majority of plots (71.1%, 3.952 million) exhibit low georeferencing precision (error > 25 m), and environmental variables are generally underreported, especially for microtopography (5.2%, 0.229 million plots) and soil factors (soil pH, soil depth, and other soil attributes are all below 10%). Fourth, long-term monitoring data are scarce: only 14.8% (0.905 million plots) of the plots have resurvey records.Future efforts should prioritize filling data gaps in underrepresented regions and promoting the development of globally unified data standards.In addition, China possesses abundant vegetation survey data, but they are scattered across data centers, vegetation monographs, and data papers. For China, an urgent priority is to establish a national standardized data integration platform, promote data sharing through incentives such as data papers, and actively lead the construction of a regional vegetation database covering the entirety of Asia.

Key words: vegetation plot, survey data, database, biodiversity, community ecology