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Extreme weather events are increasing in frequency and magnitude with profound effects on ecosystem functioning. Further, there is now a greater likelihood that multiple extreme events are occurring within a single year. Here we investigated the effect of a single drought, flood or compound (flood + drought) extreme event on temperate grassland ecosystem processes in a field experiment. To assess system resistance and resilience, we studied changes in a wide range of above- and below-ground indicators (plant diversity and productivity, greenhouse gas emissions, soil chemical, physical and biological metrics) during the 8 week stress events and then for 2 years post-stress. We hypothesized that agricultural grasslands would have different degrees of resistance and resilience to flood and drought stress. We also investigated two alternative hypotheses that the combined flood + drought treatment would either, (A) promote ecosystem resilience through more rapid recovery of soil moisture conditions or (B) exacerbate the impact of the single flood or drought event. Our results showed that flooding had a much greater effect than drought on ecosystem processes and that the grassland was more resistant and resilient to drought than to flood. The immediate impact of flooding on all indicators was negative, especially for those related to production, and climate and water regulation. Flooding stress caused pronounced and persistent shifts in soil microbial and plant communities with large implications for nutrient cycling and long-term ecosystem function. The compound flood + drought treatment failed to show a more severe impact than the single extreme events. Rather, there was an indication of quicker recovery of soil and microbial parameters suggesting greater resilience in line with hypothesis (A). This study clearly reveals that contrasting extreme weather events differentially affect grassland ecosystem function but that concurrent events of a contrasting nature may promo

The physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis and some of these attributes have been used as proxies to soil quality. Thus, we investigated: (1) whether appropriate soil quality indicators (SQIs) could be identified in soils of Great Britain, (2) whether conventional soil classification or aggregate vegetation classes (AVCs) could predict SQIs and (3) to what extent do soil types and/ or AVCs act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQI which were named as; soil organic matter (SOM), dissolved organic matter (DOM), soluble N, reduced N, microbial biomass, DOM humification (DOMH). SOM was identified as the most important SQI in the discrimination of both soil types and AVCs. Soil attributes constituting highly to the SOM factor were, microbial quotient and bulk density. The SOM indicator discriminated three soil type groupings and four aggregate vegetation class groupings. Among the soil types, only the peat soils were discriminated from other groups while among the AVCs only the heath and bog classes were isolated from others. However, the peat soil and heath and bog AVC were the only groups that were distinctly discriminated from other groups. All other groups heavily overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types. We conclude that conventionally classified soil types cannot predict the SQIs defined from large areas with differing climatic and edaphic factors. Localised areas with similar climatic and topoedaphic factors may hold promise for the definition of SQI that may predict the soil types or AVCs.

Protein represents a major input of organic matter to soil and is an important source of carbon (C) and nitrogen (N) for microorganisms. Therefore, determining which soil properties influence protein mineralisation in soil is key to understanding and modelling soil C and N cycling. However, the effect of different soil properties on protein mineralisation, and especially the interactions between soil properties, are poorly understood. We investigated how topsoil and subsoil properties affect protein mineralisation along a grassland altitudinal (catena) sequence that contained a gradient in soil type and primary productivity. We devised a schematic diagram to test the key edaphic factors that may influence protein mineralisation in soil (e.g. pH, microbial biomass, inorganic and organic N availability, enzyme activity and sorption). We then measured the mineralisation rate of 14C-labelled soluble plant-derived protein and amino acids in soil over a two-month period. Correlation analysis was used to determine the associations between rates of protein mineralisation and soil properties. Contrary to expectation, we found that protein mineralisation rate was nearly as fast as for amino acid turnover. We ascribe this rapid protein turnover to the low levels of protein used here, its soluble nature, a high degree of functional redundancy in the microbial community and microbial enzyme adaptation to their ecological niche. Unlike other key soil N processes (e.g. nitrification, denitrification), protease activity was not regulated by a small range of factors, but rather appeared to be affected by a wide range of interacting factors whose importance was dependent on altitude and soil depth [e.g. above-ground net primary productivity (NPP), soil pH, nitrate, cation exchange capacity (CEC), C:N ratio]. Based on our results, we hypothesise that differences in soil N cycling and the generation of ammonium are more related to the rate of protein supply rather than limitations in p