A dataset of spatial distribution of bioclimatic variables in China at 1 km resolution

Abstract

Bioclimatic variables are indicators reflecting the integrated relationship between living things and climate. They are often used to interprete the relationships between species, vegetations and climate in global change research, and further simulate the geographical distribution patterns of both species and vegetations, as well as their functional characteristics. Regional bioclimate datasets, however, have been rarely reported. Based on an ANUSPIN interpolated dataset (covering temperature, precipitation and sunshine percentage) of 1km-resolution climate variables in China at 30-year basis averaged from 1951 to 1980 and from 1981 to 2010, respectively, we calculated 9 kinds bioclimatic variables in this study, namely mean temperature of the coldest month, mean temperature of the warmest month, absolute maximum temperature, absolute minimum temperature, annual growing degree days above 0°C and 5°C, growing season precipitation, annual drought index and annual moisture index. We plotted their spatial distribution map and analyzed their spatial pattern and trend statistically. Comparative analysis shows that the variation range of corresponding variables is very narrow, and the statistical variables are nearly the same. Therefore, the error of this dataset mainly comes from the spatial distribution dataset of basic climatic factors, and the secondary error in the process is tiny.This dataset provides reasonable environmentally mechanistic explanations for research on the relationships between species, vegetations and climate, and offers a convenient and diverse way for researchers to use bioclimatic variables to simulate species distribution patterns, vegetation structures and functions.