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.

Plants 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 non-agricultural 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 CaCl2 (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

Pharmaceuticals are a ubiquitous group of emerging pollutants of considerable importance due to their biological potency and potential to elicit effects in wildlife and humans. Pharmaceuticals have been quantified in terrestrial, marine, fresh, and transitional waters, as well as the fauna and macro-flora that inhabit them. Pharmaceuticals can enter water ways through different human and veterinary pathways with traditional wastewater treatment, unable to completely remove pharmaceuticals, discharging often unknown quantities to aquatic ecosystems. However, there is a paucity of available information regarding the effects of pharmaceuticals on species at the base of aquatic food webs, especially on phytoplankton, with research typically focussing on fish and aquatic invertebrates. Diatoms are one of the main classes of phytoplankton and are some of the most abundant and important organisms in aquatic systems. As primary producers, diatoms generate ∼40 % of the world's oxygen and are a vital food source for primary consumers. Diatoms can also be used for bioremediation of polluted water bodies but perhaps are best known as bio-indicators for water quality studies. However, this keystone, non-target group is often ignored during ecotoxicological studies to assess the effects of pollutants of concern. Observed effects of pharmaceuticals on diatoms have the potential to be used as an indicator of pharmaceutical-induced impacts on higher trophic level organisms and wider ecosystem effects. The aim of this review is to present a synthesis of research on pharmaceutical exposure to diatoms, considering ecotoxicity, bioremediation and the role of diatoms as bio-indicators. We highlight significant omissions and knowledge gaps which need addressing to realise the potential role of diatoms in future risk assessment approaches and help evaluate the impacts of pharmaceuticals in the aquatic environment at local and global scales.

The flow of carbon (C) through soil is inherently complex due to the many thousands of different chemical transformations occurring simultaneously within the soil microbial community. The accurate modelling of this C flow therefore represents a major challenge. In response to this, isotopic tracers (e.g. 13C, 14C) are commonly used to experimentally parameterise models describing the fate and residence time of individual C compounds within soil. In this study, we critically evaluated the combined use of experimental 14C labelling and mathematical modelling to estimate C turnover times in soil. We applied 14C-labelled alanine and glucose to an agricultural soil and simultaneously measured their loss from soil solution alongside the rate of microbial C immobilization and mineralization. Our results revealed that chloroform fumigation-extraction (CFE) cannot be used to reliably quantify the amount of isotopically labelled 13C/14C immobilised by the microbial biomass. This is due to uncertainty in the extraction efficiency values (kec) within the CFE methodology which are both substrate and incubation time dependent. Further, the traditional mineralization approach (i.e. measuring 14/13CO2 evolution) provided a poor estimate of substrate loss from soil solution and mainly reflected rates of internal microbial C metabolism after substrate uptake from the soil. Therefore, while isotope addition provides a simple mechanism for labelling the microbial biomass it provides limited information on the behaviour of the substrate itself. We used our experimental data to construct a new empirical model to describe the simultaneous flow of substrate-C between key C pools in soil. This model provided a superior estimate of microbial substrate use and microbial respiration flux in comparison to traditional first order kinetic modelling approaches. We also identify a range of fundamental problems associated with the modelling of isotopic-C in soil, including issues with variation in C partitioning within the community, model pool connectivity and variation in isotopic pool dilution, which make interpretation of any C isotopic flux data difficult. We conclude that while convenient, the use of isotopic data (13C, 14C, 15N) has many potential pitfalls necessitating a critical evaluation of both past and future studies