Soil microbial communities are among the most diverse and abundant communities and are essential for carrying out key ecosystem functions including primary productivity, climate regulation and water purification. Despite this, microbial communities have been largely ignored in simulation models, conservation debates and land management practices. This neglect is mainly because (i) microbial communities are considered as functionally redundant, and (ii) there is a lack of theoretical and experimental approaches to disentangle microbial regulation of ecosystem functions from other biotic and abiotic drivers. Consequently, unlike plant and animal diversity, consequence of loss of microbial diversity and shift in microbial composition on ecosystem function is still debated and usually presumed that microbial functions have a high redundancy. That means a loss of microbial diversity and/ or shift in communities do not result into loss of ecosystem functions.
In this presentation, I will highlight that strong linkage between microbial communities and ecosystem functions from microcosm to global scales. Data from the dilution to extinction method were used to demonstrate functional consequences of microbial diversity which indicated a linear or exponential relationship, meaning a loss of diversity leads to either a proportional or higher loss in ecosystem functions. A soil microbial transplant experiment was used to demonstrate the critical role of the microbial community in nutrient cycling and climate regulation. The above, combined with data from field surveys carried out at national and global scales, were performed to confirm the laboratory study findings. This presentation will demonstrate the relationship between microbial diversity is critical for ecosystem functions and holds true at all scales (microcosm to global scale), ecosystems (temperate and drylands) and functional (general or specialised) types.
These findings have consequences beyond soil ecology for our understanding of the whole earth system including a framework to improve simulation model predictions and for better management and conservation policies to maximise terrestrial ecosystem functionality and sustainability.