Seagrass meadows are generally diverse in China and have the same essential ecosystem services as elsewhere. However, an evaluation of seagrass distribution across China is still lacking, and the magnitude and direction of changes in seagrass meadows remains unclear. Our primary objective was to provide a nationwide seagrass distribution map, and to explore the dynamic changes of seagrass population under global climate change. We use simulation studies within the modelling software MaxEnt with 58961 occurrence records and 27 marine environmental variables, to simulate the potential distribution of seagrasses and calculate the area. 7 environmental variables were deleted before the modelling processes based on a correlation analysis to ensure predicted suitability. The predicted area was 790.09 km², which is much larger than the known seagrass distribution in China, and would be increased to 923.62 km² by the year 2100. However, the suitable habitat of almost all seagrass will shift northwest in the future. The sum of individual family will under-predict the national distribution of seagrass, showed a downward trend consistently in the future. Out of all environmental variables, the physical ones (e.g. depth, land distance and sea surface temperature) had the greatest contribution in predicting seagrass distributions, and nutrients (e.g. nitrate, phosphate) ranked among the key influential predictors for habitat suitability in our focal area. As this is a first effort to fill a gap in our understanding of the distribution of seagrass in China, further studies are necessary using both modeling and biological/ecological approaches.

This dataset contains input data for the maxent model, including seagrass occurrence data and marine environment data. There are 4 families, Cymodoceaceae, Hydrocharitaceae, Ruppiaceae, and Zosteraceae, with a total of 22 species of seagrasses distributed in Chinese coastal waters. Hence, this study focused on the species belonging to these families. Seagrass occurrence data were extracted from the Global Biodiversity Information Facility (GBIF, 2017) and Ocean Biogeographic Information System (OBIS, 2017). 27 abiotic variables related to the distribution of seagrasses were chosen as modelling parameters from the Global Marine Environment Datasets (GMED), which are the publicly available climatic, biological, and geophysical environmental layers featuring present, past, and future environmental conditions.