Abstract:

Background & Aims: Vegetation plot data play a crucial role in addressing major scientific questions, including community assembly mechanisms and species distribution patterns, as well as responses to global environmental change. However, the widespread use of these data is constrained by factors such as structural discrepancies, restricted access, and duplicate records. Therefore, we identified and summarized ten prominent global public vegetation plot databases through literature review and expert consultations, including GIVD, sPlot, GFBI, BIEN, VegBank, FIA, EVA, BioTIME, ReSurveyEurope, and forestREplot. We compiled datasets across these databases and analyzed their characteristics to enhance data usability and support macroecological research. 

Review Results: As of May 2026, these 10 vegetation plot databases had integrated data from 6.109 million plots, yet significant limitations remained. (1) The spatial distribution was extremely uneven, with plots heavily concentrated in Europe (4..098 million, 67.3%) and North America (1.353 million, 22.2%), while data from other regions were severely scarce. (2) Data structure heterogeneity was high: among the 5.566 million plots with documentation on species completeness, 78.5% (4.370 million) contained complete vascular plant inventories, whereas 21.5% (1.914 million) recorded only woody plants. among the 5.408 million plots with documentation on quantitative species attributes, 62.6%(3.388 million) recorded species cover, while only a small proportion recorded individual counts (33.6%, 1.815 million) or diameter at breast height (DBH)/tree height (33.6%, 1.818 million). (3) Crucial information was widely lacking: among the 5.565 million plots with documentation on georeferencing accuracy, the vast majority (71.0%, 3.952 million) exhibited low accuracy (error > 25 m); among the 4.449 million plots with documentation on environmental factors, overall reporting rates were low, especially for microtopography (5.2%, 0.229 million plots) and soil factors (soil pH, soil depth, and other soil attributes were all below 10%). (4) Long-term monitoring data were scarce: only 14.8% (0.905 million plots) of the plots had resurvey records. 

Conclusions: Future efforts should prioritize filling data gaps in underrepresented regions and promoting the development of globally unified data standards. In addition, China possess 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, data sharing, vegetation plot database, macroecology, community ecology