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.

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a b s t r a c tPlants employ a range of strategies to increase phosphorus (P) availability in soil. Current soil P extraction methods (e.g. Olsen P), however, often fail to capture the potential importance of rhizosphere processes in supplying P to the plant. This has led to criticism of these standard approaches, especially in nonagricultural soils of low P status and when comparing soil types across diverse landscapes. Similarly, more complex soil P extraction protocols (e.g. Hedley sequential fractionation) lack functional significance from a plant ecology perspective. In response to this, we present a novel procedure using a suite of established extraction protocols to explore the concept of a protocol that characterizes P pools available via plant and microbial P acquisition mechanisms. The biologically based P (BBP) extraction was conducted by using four extractions in parallel: (1) 10 mM CaCl 2 (soluble P); (2) 10 mM citric acid (chelate extractable P); (3) phytase and phosphatase solution (enzyme extractable organic P); (4) 1 M HCl (mineral occluded P). To test the protocol, we conducted the analyses on a total of 204 soil samples collected as part of a UK national ecosystem survey (Countryside Survey) in 1998 and repeated again in 2007. In the survey, Olsen P showed a net decline in national soil P levels during this 10 year period. In agreement with these results, soluble P, citrate extractable P and mineral occluded P were all found to decrease over the 10 year study period. In contrast, enzyme extractable organic P increased over the same period likely due to the accumulation of organic P in the mineral soil. The method illustrates a noted shift in P pools over the 10 year period, but no net loss of P from the system. This new method is simple and inexpensive and therefore has the potential to greatly improve our ability to characterise and understand changes in soil P status across complex landscapes.

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Dissolved organic matter (DOM) plays an important role in freshwater biogeochemistry. To investigate the influence of catchment character on the quality and quantity of DOM in freshwaters, 45 sampling sites draining subcatchments of contrasting soil type, hydrology, and land cover within one large upland‐dominated and one large lowland‐dominated catchment were sampled over a 1‐yr period. Dominant land cover in each subcatchment included: arable and horticultural, blanket peatland, coniferous woodland, and improved, unimproved, acid, and calcareous grasslands. The composition of the C, N, and P pool was determined as a function of the inorganic nutrient species (NO3−, NO2−, NH4+, and PO43−) and dissolved organic nutrient (dissolved organic carbon [DOC], dissolved organic nitrogen [DON], and dissolved organic phosphorus [DOP]) concentrations. DOM quality was assessed by calculation of the molar DOC : DON and DOC : DOP ratios and specific ultraviolet absorbance (SUVA254). In catchments with little anthropogenic nutrient inputs, DON and DOP typically composed > 80% of the total dissolved nitrogen (TDN) and total dissolved phosphorus (TDP) concentrations. By contrast, in heavily impacted agricultural catchments DON and DOP typically comprised 5–15% of TDN and 10–25% of TDP concentrations. Significant differences in DOC : DON and DOC : DOP ratios were observed between land cover class with significant correlations observed between both the DOC : DON and DOC : DOP molar ratios and SUVA254 (rs = 0.88 and 0.84, respectively). Analysis also demonstrated a significant correlation between soil C : N ratio and instream DOC : DON/DOP (rs = 0.79 and 0.71, respectively). We infer from this that soil properties, specifically the C : N ratio of the soil organic matter pool, has a significant influence on the composition of DOM in streams draining through these landscapes.