GENERAL INFORMATION

1. Title of Dataset: Data from: Will climate change cause the global peatland to expand or contract? Evidence from the habitat shift pattern of Sphagnum mosses

2. Author Information
	Correspondence 
		Name: Rui-Liang Zhu
		Institution: School of Life Sciences, East China Normal University, Shanghai 200241, China；
                                                   Tiantong National Station of Forest Ecosystem, Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai 200241, China
		Email: rlzhu@bio.ecnu.edu.cn

	Co-investigator 1
		Name: Xiao-Ying Ma
		Institution: School of Life Sciences, East China Normal University, Shanghai 200241, China

	Co-investigator 2
		Name: Hao Xu
		Institution: School of Life Sciences, East China Normal University, Shanghai 200241, China

	Co-investigator 3
		Name: Zi-Yin Cao
		Institution: School of Life Sciences, East China Normal University, Shanghai 200241, China

	Co-investigator 4
		Name: Lei Shu
		Institution: School of Life Sciences, East China Normal University, Shanghai 200241, China

3. Geographic location of data collection: Worldwide


DATA & FILE OVERVIEW

1. Description of dataset

These data were generated to predict the potential geographic distribution of six Sphagnum species that dominate peatlands. Files 1-5 are hosted in Zenodo, while file 6 is hosted in Dryad.

2. File List:

File 1 Name: Species_occurrence_record
File 1 Description: Occurrence records used for species distribution modelling. Map lines delineate study areas and do not necessarily depict accepted national boundaries. As the data obtained from some additional sources are copyrighted, they can not be redistributed in Dryad. Please refer to the data source for exact geographic coordinates: GBIF.org (04 February 2021) GBIF Occurrence Download https://doi.org/10.15468/dl.edxfrb, https://www.bryophyteportal.org, https://naturalhistory.si.edu/, http://www.nsii.org.cn, https://www.cvh.ac.cn. Then remove erroneous records, other species records and duplicate records in each grid cell (~10 × 10 km). 

File 2 Name: Environmental_predictors
File 2 Description: Thirty-six environmental factors, including elevation, 19 bioclimatic variables, and 16 soil variables. The elevation and 19 bioclimatic variables with 5 min spatial resolution were obtained from the World Climate Database (version 2.0, http://worldclim.org/) (Fick & Hijmans, 2017), and 16 soil variables were obtained from Harmonized World Soil Database (version 1.2, https://www.fao.org/soils-portal/). All of the environmental variables were resampled at a 5 min spatial resolution. For related environment data and more information on environment variables, please refer to the data sources provided in the file.
		To avoid overfitting of the model owing to the multi-collinearity of environmental variables, we examined the correlation between environmental variables using ArcGIS10.2 and removed the variables with a correlation higher than 0.75. 

File 3 Name: AUC_result_of_the_distribution_model
File 3 Description: AUC result of the distribution model created for six Sphagnum species. The area under the curve (AUC), which is the area under the receiver-operating characteristic (ROC), was used to evaluatethe accuracy of the model. The AUC values range from 0.5 to 1, with higher values indicating the better performance of the model: poor (0.5–0.6), fair (0.6–0.7), good (0.7–0.8), very good (0.8–0.9), and excellent (0.9–1.0).

File 4 Name: Response_curves_of_important_environmental_variables_for_Sphagnum
File 4 Description: Response curves of important environmental variables for S. angustifolium (A-C), S. fuscum (D-F), S. magellanicum s. lato (G-I), S. rubellum (J-L), S. papillosum (M-O), and S. cuspidatum (P-R). Bio11: the mean temperature of the coldest quarter; Bio14: precipitation of the driest month; T_CaCO3: topsoil calcium carbonate.

File 5 Name: The_potential_richness_distribution_of_Sphagnum_species
File 5 The potential richness distribution of six Sphagnum species under current climatic scenario. Map lines delineate study areas and do not necessarily depict accepted national boundaries.

File 6 Name: Sphagnum_potential_distribution
File 6 Description: The maximum entropy model (MaxEnt version 3.4.0; http://www.cs.princeton.edu/; Phillips et al., 2006) was used to predict the current potential geographic distribution of six Sphagnum species that dominate peatlands. In this study, 75% of occurrence data was used for model training, and the remaining 25% was randomly selected for model testing. The maximum number of background points was set to 10000 and the algorithm was run with 3000 iteration, while other values kept as default. Ten replications were performed to assess the average results. 

