<p>BIO2 = Average day and night temperature difference, average value of the difference between the highest and lowest temperatures in the month, ℃. BIO4 = Temperature seasonality, the standard deviation of the average temperature for each month, amplified by a factor of 100. BIO5 = highest temperature in the warmest month, highest temperature in the warmest month of the year, ℃. BIO8 = Average temperature in the wettest season, the average temperature in the three months of the year with the most precipitation (i.e., the wettest season), ℃. BIO9 = Average temperature in the driest quarter, average temperature in the three months of the year with the least precipitation (i.e., the driest quarter), ℃. BIO14 = Driest monthly precipitation, mm. BIO15 = Precipitation seasonal. BIO18 = warmest season precipitation, mm. Elevation (elev), slope (slope), aspect (aspect) Future data are selected from four shared socio-economic paths (SSPs) under the Medium Resolution Climate Model (BCC-CSM2-MR) in the Sixth International Coupled Model Comparison Project (CMIP6), namely SSP1 -2.6, SSP2 -4.5, SSP3 -7.0 and SSP5 -8.5. </p>
Data from WorldClim version 2.1, which provides history (1970-2000) and the future (2021-2040, 2041-2060, 2061-2080, 2081-2100) Data sets with four resolutions (30 ", 2.5', 5', 10'). Data indicators include monthly climate data of minimum temperature, average temperature and maximum temperature, precipitation, solar radiation, wind speed, water pressure and total precipitation, as well as 19" bioclimate "variables. Elevation data is derived from the STRM data product. Future monthly climate data comes from CMIP6 downscaling, including 9 GCM models and 4 SSPs.
Using SPSS25.0 software, the Pearson correlation coefficient test was carried out on 19 climate factors and 3 terrain factors. When the correlation between the two factors is high (r 0.80), the contribution rate of each factor in the MaxEnt model modeling results was combined to remove variables with small contribution rates. Finally, 11 environmental factors were selected, including average day and night temperature difference (bio2), seasonal change in temperature (bio4), highest temperature in the warmest month (bio5), average temperature in the wettest season (bio8), average temperature in the driest season (bio9), precipitation in the driest month (bio14), precipitation seasonality (bio15), precipitation in the warmest season (bio18), altitude (elev), slope (slope), and aspect (aspect). The construction of a model for predicting the suitable area of soft lithospermum.
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