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Energy-water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperms species richness in China

Citation

Pandey, Bikram et al. (2021), Energy-water and seasonal variations in climate underlie the spatial distribution patterns of gymnosperms species richness in China, Dryad, Dataset, https://doi.org/10.5061/dryad.0p2ngf1xz

Abstract

Studying the pattern of species richness is crucial in understanding the diversity and distribution of organisms in the earth. Climate and human influences are the major driving factors that directly influence the large-scale distributions of plant species, including gymnosperms. Understanding how gymnosperms respond to climate, topography, and human-induced changes is useful in predicting the impacts of global change. Here, we attempt to evaluate how climatic and human-induced processes could affect the spatial richness patterns of gymnosperms in China. Initially, we divided a map of the country into grid cells of 50 × 50 km2 spatial resolution and plotted the geographical coordinate distribution occurrence of 236 native gymnosperm taxa. The gymnosperm taxa were separated into three response variables: (i) all species, (ii) endemic species, and (iii) non-endemic species, based on their distribution. The species richness patterns of these response variables to four predictor sets were also evaluated: (i) energy-water, (ii) climatic seasonality, (iii) habitat heterogeneity, and (iv) human influences. We performed generalized linear models (GLMs) and variation partitioning analyses to determine the effect of predictors on spatial richness patterns. The results showed that the distribution pattern of species richness was highest in the southwestern mountainous area and Taiwan in China. We found a significant relationship between the predictor variable set and species richness pattern. Further, our findings provide evidence that climatic seasonality is the most important factor in explaining distinct fractions of variations in the species richness patterns of all studied response variables. Moreover, it was found that energy-water was the best predictor set to determine the richness pattern of all species and endemic species, while habitat-heterogeneity has a better influence on non-endemic species. Therefore, we conclude that with the current climate fluctuations as a result of climate change and increasing human activities, gymnosperms might face a high risk of extinction.

Methods

Spatial distribution occurrence data of 236 native taxa of Chinese gymnosperm were obtained from the National Specimen Information Infrastructure (http://www.nsii.org.cn/; accessed between August 2017 and April 2018), Global Biodiversity Information Facility (https://www.gbif.org/; accessed between November, 2017 and February, 2018), Chinese Virtual Herbarium (http://www.cvh.ac.cn/en/; accessed between August, 2017 and April, 2018), and relevant literature. The geographical distribution represent the point location denoted as longitude and latitude. There were 184 species and 52 varieties together represented “all species” while, 114 endemic and 122 non-endemic taxa in China. We used the geographical coordinate occurrence of a species to determine its presence or absence in the locality and plotted it at  the county level. The county-level distribution maps were then transferred into gridded distributions with a spatial resolution of 50 × 50 km2. The number of individual taxa in each grid cell represent the species richness. The data represent here is the species richness of each grid cell including the longitude and latitude of a grid. Numerical One (1) denotes the presence of species while zero (0) is the absence of species in the grid.

Funding

National Key Research and Development Program of China, Award: 2016YFC0502101

Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Award: 2019QZKK0303

National Natural Science Foundation of China, Award: 31961133012

University of Chinese Academy of Sciences Scholarship for International Students, Award: 2017UCAS041

Second Tibetan Plateau Scientific Expedition and Research Program (STEP), Award: 2019QZKK0303