Soil organisms provide crucial ecosystem services that support human life. However, little is known about their diversity, distribution, and the threats affecting them. Here, we compiled a global dataset of 60 sampled earthworm communities from over 7000 sites in 56 countries to predict patterns in earthworm diversity, abundance, and biomass. We identify the environmental drivers shaping these patterns. Local species richness and abundance typically peaked at higher latitudes, while biomass peaked in the tropics, patterns opposite to those observed in aboveground organisms. Similar to many aboveground taxa, climate variables were more important in shaping earthworm communities than soil properties or habitat 65 cover. These findings highlight that, while the environmental drivers are similar, conservation strategies to conserve aboveground biodiversity might not be appropriate for earthworm diversity, especially in a changing climate.

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Ecological processes regulating soil carbon (C) and nitrogen (N) cycles are still poorly understood, especially in the world’s largest agricultural frontier in Southern Amazonia. We analyzed soil parameters in samples from pristine rainforest and after land use change to pasture and crop fields, and correlated them with abundance of functional and phylogenetic marker genes (amoA, nirK, nirS, norB, nosZ, nifH, mcrA, pmoA, and 16S/18S rRNA). Additionally, we integrated these parameters using path analysis and multiple regressions. Following forest removal, concentrations of soil C and N declined, and pH and nutrient levels increased, which influenced microbial abundances and biogeochemical processes. A seasonal trend was observed, suggesting that abundances of microbial groups were restored to near native levels after the dry winter fallow. Integration of the marker gene abundances with soil parameters using path analysis and multiple regressions provided good predictions of biogeochemical processes, such as the fluxes of NO3, N2O, CO2, and CH4. In the wet season, agricultural soil showed the highest abundance of nitrifiers (amoA) and Archaea, however, forest soils showed the highest abundances of denitrifiers (nirK, nosZ) and high N, which correlated with increased N2O emissions. Methanogens (mcrA) and methanotrophs (pmoA) were more abundant in forest soil, but methane flux was highest in pasture sites, which was related to soil compaction. Rather than analyzing direct correlations, the data integration using multivariate tools provided a better overview of biogeochemical processes. Overall, in the wet season, land use change from forest to agriculture reduced the abundance of different functional microbial groups related to the soil C and N cycles; integrating the gene abundance data and soil parameters provided a comprehensive overview of these interactions. Path analysis and multiple regressions addressed the need for more comprehensive approaches to improve our mechanistic understanding of biogeochemical cycles.