# Precipitation Dominates the Distribution of Species Richness on the Kunlun-Pamir Plateau
## 5 Conclusions  
We analyzed the species richness pattern in the Kunlun-Pamir Plateau region, taking into account both the productivity hypothesis and the water-energy dynamics hypothesis. From the aspect of the productivity hypothesis, we investigated the correlation between the dynamic habitat indices (DHIs) and the species richness in the Kunlun-Pamir Plateau region. The calculated DHIs by means of five MODIS products correlated less with the mammal, bird, breeding bird and non-breeding bird richness in the Kunlun-Pamir Plateau region. The DHIs based on the FPAR data correlated slightly higher with the mammal, bird, breeding bird and non-breeding bird richness than those based on the other four MODIS product DHIs. Although the cumulative DHIs based on the FPAR conformed more with the richness of the four taxa species compared to the variation based on the FPAR and minimum DHIs based on the FPAR, the multiple regression models for the three variables associated better with the richness of the four species. However, the DHI based on the FPAR correlation coefficients with an abundance of mammals, birds, breeding birds and non-breeding birds were still low, namely 0.24, 0.25, 0.24 and 0.01, respectively. The birds regression model clarified most of the variations in species richness during the four taxa. Regarding the water-energy dynamics hypothesis, the precipitation-related climatic factors dominate the distribution of species richness on the Kunlun-Pamir Plateau; among those, BIO12 had the highest correlations with mammals, birds, breeding birds and non-breeding birds, amounting to 0.24, 0.54, 0.54 and 0.02, respectively, followed by BIO17,-19 and -14. Multiple linear regression models (based on four climate factors) raised the correlations between these factors with the mammals, birds, breeding birds and non-breeding birds (to 0.29). Furthermore, we noticed that the correlation between the species richness and the climatic factors was noticeably higher in the Kunlun-Pamir Plateau than the MODIS-based DHIs. The correlations between the DHIs based on the FPAR and the climate factors increased to 0.32, 0.66, 0.65 and 0.02, respectively, for the multivariate linear regression models. The regression model for birds also explained the majority of the variations in species richness for the four taxa. The water-energy dynamic hypothesis was more appropriate to the Kunlun-Pamir Plateau region. In general, by examining the DHIs and the species richness in specific areas, we suggest a reconstruction of the DHIs appropriate for the region, especially for locations with relatively small spatial scales. In the context of climate change, our results once again highlight the significance of monitoring climate fluctuations in the Kunlun-Pamir region for biodiversity conservation. This will make it easier to evaluate the spatial distribution of species richness and provide an accurate assessment of that distribution. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/rs14246187/s1](https://www.mdpi.com/article/10.3390/rs14246187/s1)]([https://www.mdpi.com/article/10.3390/rs14246187/s1](https://www.mdpi.com/article/10.3390/rs14246187/s1)): Table S1: Coefficient of determination between the individual EVI-based DHIs of the four main taxa; Table S2: Coefficient of determination between the individual GPP-based DHIs of the four main taxa; Table S3: Coefficient of determination between the individual LAI-based DHIs of the four main taxa; Table S4: Coefficient of determination between the individual NDVI-based DHIs of the four main taxa; Table S5: Coefficient of determination between the individual NDVI-based DHIs of the four main taxa. Conceptualization, X.H. and A.B. ; methodology, X.H. and A.B. ; data curation and software, J.Z. ; validation, X.H. and T.Y. ; formal analysis, X.H. and G.Z; resources, X.H. ; data curation, X.H. ; writing--original draft preparation, X.H. and G.Z. ; writing--review and editing, A.B., Y.Y., T.W., V.N., P.D.M. and T.V.d.V. ; visualization, X.H.