Table_1_Global Microbiome Diversity Scaling in Hot Springs With DAR (Diversity-Area Relationship) Profiles.XLS
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
The spatial distribution of biodiversity (i.e., the biogeography) of the hot-spring microbiome is critical for understanding the microbial ecosystems in hot springs. We investigated the microbiome diversity scaling (changes) over space by analyzing the diversity-area relationship (DAR), which is an extension to classic SAR (species-area relationship) law in biogeography. We built DAR models for archaea and bacteria with 16S-rRNA sequencing datasets from 165 hot springs globally. From the DAR models, we sketch out the biogeographic maps of hot-spring microbiomes by constructing: (i) DAR profile—measuring the archaea or bacteria diversity scaling over space (areas); (ii) PDO (pair-wise diversity overlap or similarity) profile—estimating the PDO between two hot springs; (iii) MAD (maximal accrual diversity) profile—predicting the global MAD; (iv) LRD/LGD (ratio of local diversity to regional or global diversity) profile. We further investigated the differences between archaea and bacteria in their biogeographic maps. For example, the comparison of DAR-profile maps revealed that the archaea diversity is more heterogeneous (i.e., more diverse) or scaling faster than the bacterial diversity does in terms of species numbers (species richness), but is less heterogeneous (i.e., less diverse) or scaling slower than bacteria when the diversity (Hill numbers) were weighted in favor of more abundant dominant species. When the diversity is weighted equally in terms of species abundances, archaea, and bacteria are equally heterogeneous over space or scaling at the same rate. Finally, unified DAR models (maps) were built with the combined datasets of archaea and bacteria.
Read the peer-reviewed publication