Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

Microbial-mediated decomposition of soil organic matter (SOM) ultimately makes a considerable contribution to soil respiration, which is typically the main source of CO 2 arising from terrestrial ecosystems. Despite this central role in the decomposition of SOM, few studies have been conducted on how climate change may affect the soil microbial community and, furthermore, on how possible climate-change induced alterations in the ecology of microbial communities may affect soil CO 2 emissions. Here we present the results of a seasonal study on soil microbial community structure, SOM decomposition and its temperature sensitivity in two representative Mediterranean ecosystems where precipitation/throughfall exclusion has taken place during the last 10 years. Bacterial and fungal diversity was estimated using the terminal restriction fragment length polymorphism technique. Our results show that fungal diversity was less sensitive to seasonal changes in moisture, temperature and plant activity than bacterial diversity. On the other hand, fungal communities showed the ability to dynamically adapt throughout the seasons. Fungi also coped better with the 10 years of precipitation/throughfall exclusion compared with bacteria. The high resistance of fungal diversity to changes with respect to bacteria may open the controversy as to whether future 'drier conditions' for Mediterranean regions might favor fungal dominated microbial communities. Finally, our results indicate that the fungal community exerted a strong influence over the temporal and spatial variability of SOM decomposition and its sensitivity to temperature. The results, therefore, highlight the important role of fungi in the decomposition of terrestrial SOM, especially under the harsh environmental conditions of Mediterranean ecosystems, for which models predict even drier conditions in the future.

Abstract. Soil respiration (SR) constitutes the largest flux of CO2 from terrestrial ecosystems to the atmosphere. There still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 72 site-years for 58 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SR MAT), irrespective of the type of ecosystem and biome. This convergence is to be theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q10). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SR MAT corrected for a factor related to P/PET. Our finding indicates that it is sufficient to measure SR MAT for obtaining a highly constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution and interannual variation of soil CO2 emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatio-temporal resolution of a major component of the global carbon cycle.