PJB-2019-757
Can environmental variability predict woody plant species richness of China at the provincial level?
Yongbin Wu
Abstract
It is predicted that areas with higher environmental variability should have lower species richness because extreme environmental conditions may sweep many species with limited ecological adaptation ability in comparison to those less climate- fluctuating areas. In the present study, we test this prediction by introducing grey system model for ranking provinces of China with different levels of environmental variability. We then use the rank results in terms of rational coefficients to study the spatial correlation between woody plant richness and grey ranking of provinces. We compare two correlation methods: the first one is to perform a simple Pearson’s correlation, while the second method is to perform a sample size-adjusted Pearson’s correlation for the purpose of controlling the biases caused by spatial autocorrelation. The results show that, when spatial autocorrelation is not removed, there is a marginally significant positive correlation between environmental variability degree and woody plant diversity across different provinces of China. However, when the spatial autocorrelation is removed, there is no significance anymore. In both cases, environmental variability of provinces is always positively related to woody plant richness across provinces of China. Principal component analysis on environmental data further confirmed these findings. Overall, high environment-fluctuating provinces can have high woody plant richness. Therefore, the abovementioned prediction is rejected. In conclusion, grey system model offers a simple way to rank ecological data. The correlation test for significance by removing the influence of spatial autocorrelation should be utilized when one compares the correlations between spatially derived variables.
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