Publications

Climate change is likely to have a profound influence on C and nitrogen (N) biogeochemical cycling. Increasing temperatures may greatly shorten the period of winter freezing. In extreme scenarios, Arctic soils may remain unfrozen during the winter, when there is permanent darkness. However, there is little information about how these different winter warming scenarios will affect C and N cycling in high Arctic tundra ecosystems. In this study, we assessed the effects of simulated warmer winters on soil C and N dynamics. We collected intact soils cores from two contrasting biomes from Svalbard, namely a moss-dominated peat mire and purple saxifrage-dominated dry tundra heath. In the laboratory, we used an Arctic light regime and three contrasting winter temperature regimes to simulate a range of climate scenarios: (i) current climate in which the soils were frozen in winter and thawed in the summer, (ii) a year 2050 regime in which the soils were both frozen and thawed in winter, and (iii) a 2100 regime in which the soils remained unfrozen during winter. We monitored greenhouse gas (GHG) emissions and nutrients in soil solution throughout a year. Our results revealed that a simulated warmer winter increased CO2 efflux from the peat soil, however, total GHG emissions were not significantly different from the current climate regime. This suggests that the peat soil continues to be a C sink even if microbial decomposition of C was greater than photosynthetic C fixation in winter. We also found that the 2100 climate scenario shifted in tundra ecosystems from purple saxifrage to other plant species by late summer. This was probably due to increased decomposition and the availability of N. We conclude that warmer winters on the future may have minor effects on total soil GHG emissions but that tundra vegetation is more sensitive to change.

Pollution from agriculture has environmental consequences at local and global scales. Managing this pollution is challenging because of diffuse sources and complex relationships between aquatic and atmospheric emissions. We illustrate this for a UK county that has suffered outbreaks of microbial pollution and eutrophication. We surveyed 49 livestock farms covering 12% of total agricultural grazed land. Soil nutrient status and whole-farm nutrient balances were determined, and the environmental impact of alleviating sub-optimal soil pH by liming was estimated at the county level. Only 37% of fields contained more P than was required for satisfactory grass growth, and soil acidity and available K were often limiting production. The mean farm N, P and K balances were similar to a modelled farm in England & Wales and EU indicators for the majority of North West Europe. This suggests that local eutrophication events linked to agriculture are more likely to relate to improper timing of nutrient application rather than over-application. None of the surveyed farmers used nutrient decision support tools, largely due to a lack of awareness and competing sources of information. Liming soils to pH 6.0 was estimated to both reduce N-leaching and N2O emissions; however, the net climate-change impact would be negative as the direct CO2 emissions would exceed CO2 equivalent emissions of not liming by 394% (95% CI 201–21,232). Although liming currently presents a net cost to farmers, a sensitivity analysis suggests that reduced lime cost could lead to economic benefit to farmers but still increased greenhouse gas emissions. The results are applicable to all pasture-based agricultural systems where there is a drive to maintain or increase production through optimal soil and nutrient management. The findings demonstrate an important trade-off between reducing aquatic and atmospheric pollution and agricultural productivity, and the need to improve communication of this trade-off to farmers.

The effects of long-term N and P fertilisation on soil organic nitrogen (SON) turnover are unclear. We sampled soils fertilised by N and/or P since 1843 at Rothamsted Research to investigate the effects of long-term N and P fertilisation on high- or low-molecular-weight SON decomposition and gross N mineralisation. Short-term assays with added 14C-labelled proteins, peptides, and amino acids and gross organic N mineralisation were measured, and the microbial communities and functions were also assessed in parallel. Long-term N fertilisation increased the contents of soil extractable organic N and peptides but decreased organic N-hydrolysing enzyme activities (N-acetyl-β-D-glucosaminidase and leucine aminopeptidase). Fertilisation with P and N accelerated and reduced the decomposition of 14C-labelled organic N compounds, respectively. The decomposition of peptides and amino acids, as labile SON components, was mainly regulated by soil P content because microbial biomass and activity were more sensitive to P fertilisation than to N fertilisation. Gross NH4 +/NO3 − production and consumption were accelerated by 41%–60% under N fertilisation but remained unchanged under P fertilisation compared to the unfertilised treatment. Metagenomic sequencing showed that N fertilisation increased microbial diversity and enriched functional genes associated with organic N decomposition, compared to the unfertilised treatment. P fertilisation had no effect on the abundance of these functional genes. In agricultural practices, it is essential to comprehensively consider the interaction between N and P fertilisation to optimise the cycling and utilisation of SON.

This work investigated the microbial content of nodules from alders to determine how many ribotypes of Frankia were present and which, if any, other bacteria existed within nodes from the nodules. The bacterial content of alder nodules was investigated by 454 sequencing of 16S rDNA genes. Over half of the sequences were from a single ribotype of Frankia, with nearly all other sequences coming from the chloroplast of the host plant, and other sequences (including other ribotypes of Frankia) being at < 1%. It is concluded that a single ribotype of Frankia is the major, although not unique, bacterium present in an individual lobe from an alder nodule.

Greenhouse gas (GHG) fluxes from livestock grazed pasture soils are highly variable in both space and time but the quantitative importance of the factors regulating this variation remain poorly understood. Our aim was to explore this variability on contrasting extensively (low input) and intensively managed sheep-grazed ‘case-study’ pastures. We quantified (through standard and spatially-informed regressions) the statistical relationships between GHG fluxes (nitrous oxide (N2O), carbon dioxide (CO2) and methane (CH4)) and a range of soil, field and management characteristics. Fluxes of these three GHGs at two study sites were highly variable, but spatial structure (i.e. autocorrelation) was only observed in the variability of N2O fluxes across the intensive site and CO2 fluxes across the extensive site. The regression analyses identified significant GHG predictor variables for the extensive site as: NO3 − (p < 0.001) and vegetation-type (p < 0.01) for N2O (R 2 = 0.57; p = 0.000); NH4 + (p < 0.05), slope (p < 0.05) and elevation (p < 0.01) for CO2 (R 2 = 0.34; p = 0.000); and NO3 − (p < 0.01), NH4 + (p < 0.05) and soil moisture (p < 0.05) for CH4 (R 2 = 0.25; p = 0.005). Significant GHG predictor variables for the intensive site were soil moisture (p < 0.01) and bulk density (p < 0.01) for N2O (R 2 = 0.27; p = 0.005); soil moisture (p < 0.001) for CO2 (R 2 = 0.31; p = 0.001); while none were found for CH4 (R 2 = 0.10; p = 0.655). Key factors driving GHG variation were both site- and GHG-specific, with fluxes controlled by local conditions leading to differences in limiting factors (possibly even at the within-site scale). Our statistical analyses suggest a larger range of driving variables (e.g. air and soil temperature or other soil chemical properties such as total extractable N) may be required to more fully capture the observed variability in the GHG processes considered here, and that it may also be fruitful for future analyses to consider non-linear, non-stationary and interacting relationships across space- and time-scales. Adequacies of each site’s sample design also played a key interpretive role in the GHG processes, requiring further evaluation through additional sampling campaigns.

A major problem for 21st century agriculture is the prospect of P scarcity. Adsorption of PO4 on the soil’s solid phase is the primary mechanism regulating P availability. Release of citrate by roots is generally thought to increase the availability of P, which in turn improves P acquisition by plants. However, the interaction between citrate and PO4 remains poorly understood in soils and conflicting results are found in the literature. Here modeling is used to investigate the effects of citrate adsorption on P availability in a chromic cambisol, a luvisol and two ferralsols over a range of soil pH values. The effect of different levels of exchangeable Ca, soil organic C (SOC), dissolved organic C (DOC) and PO4 fertilization were also tested in order to cover a wider range of environmental conditions. Results showed that the competition of citrate for PO4 binding sites was not the only mechanism regulating P availability. Citrate adsorption can also increase PO4 adsorption through electrostatic interactions with adsorbed Ca2+ ions and actively reduce P availability. More precisely, it was found that the addition of 10μmol citrate kg−1 soil decreased P availability in both chromic cambisol and luvisol. The same trend was predicted by the model with 100μmol of citrate kg−1 soil in the chromic cambisol, whereas available P was found to increase in the luvisol. In contrast, the addition of citrate at these two concentrations always increased P availability in the two ferralsols. Increasing exchangeable Ca further decreased P availability in the chromic cambisol and luvisol, while it further increased available P in ferralsols. Additional sensitivity tests showed that DOC concentration had little influence on these results. In contrast, increasing SOC concentration massively counteracted the deleterious influence of citrate in chromic cambisol, while the effect was amplified in luvisol. In ferralsols, it was mainly observed that the increase of SOC further promoted P availability. To conclude, it was found that citrate can either increase or decrease P availability in soil, depending mainly on the occurrence of 2:1 clay minerals and on the concentrations of citrate, adsorbed Ca, and soil organic C. Special attention should, therefore, be given to possible adverse effects of rhizosphere management for improved P nutrition.

No abstract is provided for this article.

No abstract is provided for this article.

Waterborne and shellfish-borne enteric viruses associated with wastewater-polluted coastal waters (e.g. Norovirus, Hepatitis A/E viruses, Adenovirus) represent a major threat to human health. Improved understanding of the locations and periods of heightened risks can help target mitigation measures and improve public health. We developed a river-estuary-coast model to simulate virus dispersal, driven by point source discharges and river flows in combination with tidal forcing. Viral inputs were based on measured wastewater adenovirus concentrations and the model was implemented with or without viral die-off. We applied the model to the Conwy river (North Wales, UK), through the estuary, to the Irish Sea coast where bathing waters and shellfisheries are known to be prone to viral contamination. Using a suite of scenarios, we showed that river flow was the primary control of viral export to the coast. Since the Conwy catchment is short and steep, and the estuary is small and river-dominated, short-duration high intensity 'flash floods' were shown to transport viruses through the estuary and out to sea, despite dilution or die-off effects. Duplicating flow events (i.e., storm clustering) did not double the virus export since the virus re-entered the estuary on the flood tide. The tidal magnitude and timing of high water relative to peak river flow were also important drivers regulating viral dispersal. A worst-case event simulation (i.e., combining high river flows with high viral loading and high spring tide) resulted in increased concentrations of virus at nearby coasts, although the spatial spread was similar to the previous scenarios. Our results suggest that impact models for predicting and mitigating episodes of poor microbiological water quality may require careful representation of the intensity and timings of river flow when evaluating pathogen exposure risk.