Effect of soil waterlogging on below-ground biomass allometric relations in Norway spruce

An increasing importance is assigned to the estimation and verification of carbon stocks in forests. Forestry practice has several long-established and reliable methods for the assessment of aboveground biomass; however we still miss accurate predictors of belowground biomass. A major windthrow event exposing the coarse root systems of Norway spruce trees allowed us to assess the effects of contrasting soil stone and water content on belowground allocation. Increasing stone content decreases root/shoot ratio, while soil waterlogging leads to an increase in this ratio. We constructed allometric relationships for belowground biomass prediction and were able to show that only soil waterlogging significantly impacts model parameters. We showed that diameter at breast height is a reliable predictor of belowground biomass and, once site-specific parameters have been developed, it is possible to accurately estimate belowground biomass in Norway spruce.

Colon extended physiologically based extraction test (CE-PBET) increases bioaccessibility of soil-bound PAH

Assessment of the risk to human health posed by contaminated land may be seriously overestimated if reliant on total pollutant concentration. In vitro extraction tests, such as the physiologically based extraction test (PBET), imitate the physicochemical conditions of the human gastro-intestinal tract and offer a more practicable alternative for routine testing purposes. However, even though passage through the colon accounts for approximately 80% of the transit time through the human digestive tract and the typical contents of the colon in vivo are a carbohydrate-rich aqueous medium with the potential to promote desorption of organic pollutants, PBET comprises stomach and small intestine compartments only. Through addition of an eight-hour colon compartment to PBET and use of a carbohydrate-rich fed-state medium we demonstrated that colon-extended PBET (CE-PBET) in- creased assessments of soil-bound PAH bioaccessibility by up to 50% in laboratory soils and a factor of 4 in field soils. We attribute this increased bioaccessibility to a combination of the additional extraction time and the presence of carbohydrates in the colon compartment, both of which favor PAH desorption from soil. We propose that future assessments of the bioaccessibility of organic pollutants in soils using physiologically based extraction tests should have a colon compartment as in CE-PBET.

Resolving the spatial variability of soil N using fractions of soil organic matter

The spatial variability of soil nitrogen (N) mineralisation has not been extensively studied, which limits our capacity to make N fertiliser recommendations. Even less attention has been paid to the scale-dependence of the variation. The objective of this research was to investigate the scale-dependence of variation of mineral N (MinN, N–NO3− plus N–NH4+) at within-field scales. The study was based on the spatial dependence of the labile fractions of SOM, the key fractions for N mineralisation. Soils were sampled in an unbalanced nested design in a 4-ha arable field to examine the distribution of the variation of SOM at 30, 10, 1, and 0.12 m. Organic matter in free and intra-aggregate light fractions (FLF and IALF) was extracted by physical fractionation. The variation occurred entirely within 0.12 m for FLF and at 10 m for IALF. A subsequent sampling on a 5-m grid was undertaken to link the status of the SOM fractions to MinN, which showed uncorrelated spatial dependence. A uniform application of N fertiliser would be suitable in this case. The failure of SOM fractions to identify any spatial dependence of MinN suggests that other soil variables, or crop indicators, should be tested to see if they can identify different N supply areas within the field for a more efficient and environmentally friendly N management.

Community patterns of soil bacteria and nematodes in relation to geographic distance

Ecosystems consist of aboveground and belowground subsystems and the structure of their communities is known to change with distance. However, most of this knowledge originates from visible, aboveground components, whereas relatively little is known about how soil community structure varies with distance and if this variability depends on the group of organisms considered. In the present study, we analyzed 30 grasslands from three neighboring chalk hill ridges in southern UK to determine the effect of geographic distance (1e198 km) on the similarity of bacterial communities and of nematode communities in the soil. We found that for both groups, community similarity decayed with distance and that this spatial pattern was not related to changes either in plant community composition or soil chemistry. Site history may have contributed to the observed pattern in the case of nematodes, since the distance effect depended on the presence of different nematode taxa at one of the hill ridges. On the other hand, site-related differences in bacterial community composition alone could not explain the spatial turnover, suggesting that other factors, such as biotic gradients and local dispersal processes that we did not include in our analysis, may be involved in the observed pattern. We conclude that, independently of the variety of causal factors that may be involved, the decay in similarity with geographic distance is a characteristic feature of both communities of soil bacteria and nematodes.

Spatial disaggregation and intensity correction of TRMM-based rainfall time series for hydrological applications in dryland catchments

A novel approach is presented for combining spatial and temporal detail from newly available TRMM-based data sets to derive hourly rainfall intensities at 1-km spatial resolution for hydrological modelling applications. Time series of rainfall intensities derived from 3-hourly 0.25° TRMM 3B42 data are merged with a 1-km gridded rainfall climatology based on TRMM 2B31 data to account for the sub-grid spatial distribution of rainfall intensities within coarse-scale 0.25° grid cells. The method is implemented for two dryland catchments in Tunisia and Senegal, and validated against gauge data. The outcomes of the validation show that the spatially disaggregated and intensity corrected TRMM time series more closely approximate ground-based measurements than non-corrected data. The method introduced here enables the generation of rainfall intensity time series with realistic temporal and spatial detail for dynamic modelling of runoff and infiltration processes that are especially important to water resource management in arid regions.

Calibration and bias correction of climate projections for crop modelling: an idealised case study over Europe

Producing projections of future crop yields requires careful thought about the appropriate use of atmosphere-ocean global climate model (AOGCM) simulations. Here we describe and demonstrate multiple methods for ‘calibrating’ climate projections using an ensemble of AOGCM simulations in a ‘perfect sibling’ framework. Crucially, this type of analysis assesses the ability of each calibration methodology to produce reliable estimates of future climate, which is not possible just using historical observations. This type of approach could be more widely adopted for assessing calibration methodologies for crop modelling. The calibration methods assessed include the commonly used ‘delta’ (change factor) and ‘nudging’ (bias correction) approaches. We focus on daily maximum temperature in summer over Europe for this idealised case study, but the methods can be generalised to other variables and other regions. The calibration methods, which are relatively easy to implement given appropriate observations, produce more robust projections of future daily maximum temperatures and heat stress than using raw model output. The choice over which calibration method to use will likely depend on the situation, but change factor approaches tend to perform best in our examples. Finally, we demonstrate that the uncertainty due to the choice of calibration methodology is a significant contributor to the total uncertainty in future climate projections for impact studies. We conclude that utilising a variety of calibration methods on output from a wide range of AOGCMs is essential to produce climate data that will ensure robust and reliable crop yield projections.

Acidity controls on dissolved organic carbon mobility in organic soils

Dissolved organic carbon (DOC) concentrations in surface waters have increased across much of Europe and North America, with implications for the terrestrial carbon balance, aquatic ecosystem functioning, water treatment costs and human health. Over the past decade, many hypotheses have been put forward to explain this phenomenon, from changing climate and land-management to eutrophication and acid deposition. Resolution of this debate has been hindered by a reliance on correlative analyses of time-series data, and a lack of robust experimental testing of proposed mechanisms. In a four-year, four-site replicated field experiment involving both acidifying and de-acidifying treatments, we tested the hypothesis that DOC leaching was previously suppressed by high levels of soil acidity in peat and organo-mineral soils, and therefore that observed DOC increases a consequence of decreasing soil acidity. We observed a consistent, positive relationship between DOC and acidity change at all sites. Responses were described by similar hyperbolic relationships between standardised changes in DOC and hydrogen ion concentrations at all sites, suggesting potentially general applicability. These relationships explained a substantial proportion of observed changes in peak DOC concentrations in nearby monitoring streams, and application to a UK-wide upland soil pH dataset suggests that recovery from acidification alone could have led to soil solution DOC increases in the range 46-126% by habitat type since 1978. Our findings raise the possibility that changing soil acidity may have wider impacts on ecosystem carbon balances. Decreasing sulphur deposition may be accelerating terrestrial carbon loss, and returning surface waters to a natural, high-DOC condition.

Correction of atmospheric delay effects in radar interferometry using a nested mesoscale atmospheric model

The temporal variability of the atmosphere through which radio waves pass in the technique of differential radar interferometry can seriously limit the accuracy with which the method can measure surface motion. A forward, nested mesoscale model of the atmosphere can be used to simulate the variable water content along the radar path and the resultant phase delays. Using this approach we demonstrate how to correct an interferogram of Mount Etna in Sicily associated with an eruption in 2004-5. The regional mesoscale model (Unified Model) used to simulate the atmosphere at higher resolutions consists of four nested domains increasing in resolution (12, 4, 1, 0.3 km), sitting within the analysis version of a global numerical model that is used to initiate the simulation. Using the high resolution 3D model output we compute the surface pressure, temperature and the water vapour, liquid and solid water contents, enabling the dominant hydrostatic and wet delays to be calculated at specific times corresponding to the acquisition of the radar data. We can also simulate the second-order delay effects due to liquid water and ice.

Dispersal of soil-dwelling clover root weevil (Sitona lepidus Gyllenhal, Coleoptera: Curculionidae) larvae in mixed plant communities

Insect pests that have a root-feeding larval stage often cause the most sustained damage to plants because their attrition remains largely unseen, preventing early diagnosis and treatment. Characterising movement and dispersal patterns of subterranean insects is inherently difficult due to the difficulty in observing their behaviour. Our understanding of dispersal and movement patterns of soil-dwelling insects is therefore limited compared to above ground insect pests and tends to focus on vertical movements within the soil profile or assessments of coarse movement patterns taken from soil core measurements in the field. The objective of this study was to assess how the dispersal behaviour of the clover root weevil (CRW), Sitona lepidus larvae was affected by differing proportions of host (clover) and non-host (grass) plants under different soil water contents (SWC). This was undertaken in experimental mini-swards that allowed us to control plant community structure and soil water content. CRW larval survival was not affected either by white clover content or planting pattern or SWC in either experiment; however, lower clover composition in the sward resulted in CRW larvae dispersing further from where they hatched. Because survival was the same regardless of clover density, the proportion of infested plants was highest in sward boxes with the fewest clover plants (i.e. the low host plant density). Thus, there is potential for clover plants over a larger area to be colonised when the clover content of the sward is low.

Effects of soil conditions and drought on egg hatching and larval survival of the clover root weevil (Sitona lepidus)

Soil-dwelling insect herbivores are significant pests in many managed ecosystems. Because eggs and larvae are difficult to observe, mathematical models have been developed to predict life-cycle events occurring in the soil. To date, these models have incorporated very little empirical information about how soil and drought conditions interact to shape these processes. This study investigated how soil temperature (10, 15, 20 and 25 °C), water content (0.02 (air dried), 0.10 and 0.25 g g−1) and pH (5, 7 and 9) interactively affected egg hatching and early larval lifespan of the clover root weevil (Sitona lepidus Gyllenhal, Coleoptera: Curculionidae). Eggs developed over 3.5 times faster at 25 °C compared with 10 °C (hatching after 40.1 and 11.5 days, respectively). The effect of drought on S. lepidus eggs was investigated by exposing eggs to drought conditions before wetting the soil (2–12 days later) at four temperatures. No eggs hatched in dry soil, suggesting that S. lepidus eggs require water to remain viable. Eggs hatched significantly sooner in slightly acidic soil (pH 5) compared with soils with higher pH values. There was also a significant interaction between soil temperature, pH and soil water content. Egg viability was significantly reduced by exposure to drought. When exposed to 2–6 days of drought, egg viability was 80–100% at all temperatures but fell to 50% after 12 days exposure at 10 °C and did not hatch at all at 20 °C and above. Drought exposure also increased hatching time of viable eggs. The effects of soil conditions on unfed larvae were less influential, except for soil temperature which significantly reduced larval longevity by 57% when reared at 25 °C compared with 10 °C (4.1 and 9.7 days, respectively). The effects of soil conditions on S. lepidus eggs and larvae are discussed in the context of global climate change and how such empirically based information could be useful for refining existing mathematical models of these processes.

The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems.

It is well known that atmospheric concentrations of carbon dioxide (CO2) (and other greenhouse gases) have increased markedly as a result of human activity since the industrial revolution. It is perhaps less appreciated that natural and managed soils are an important source and sink for atmospheric CO2 and that, primarily as a result of the activities of soil microorganisms, there is a soil-derived respiratory flux of CO2 to the atmosphere that overshadows by tenfold the annual CO2 flux from fossil fuel emissions. Therefore small changes in the soil carbon cycle could have large impacts on atmospheric CO2 concentrations. Here we discuss the role of soil microbes in the global carbon cycle and review the main methods that have been used to identify the microorganisms responsible for the processing of plant photosynthetic carbon inputs to soil. We discuss whether application of these techniques can provide the information required to underpin the management of agro-ecosystems for carbon sequestration and increased agricultural sustainability. We conclude that, although crucial in enabling the identification of plant-derived carbon-utilising microbes, current technologies lack the high-throughput ability to quantitatively apportion carbon use by phylogentic groups and its use efficiency and destination within the microbial metabolome. It is this information that is required to inform rational manipulation of the plant–soil system to favour organisms or physiologies most important for promoting soil carbon storage in agricultural soil.

Centennial variations in sunspot number, open solar flux and streamer belt width: 1. correction of the sunspot number record since 1874

We analyse the widely-used international/ Zürich sunspot number record, R, with a view to quantifying a suspected calibration discontinuity around 1945 (which has been termed the “Waldmeier discontinuity” [Svalgaard, 2011]). We compare R against the composite sunspot group data from the Royal Greenwich Observatory (RGO) network and the Solar Optical Observing Network (SOON), using both the number of sunspot groups, N{sub}G{\sub}, and the total area of the sunspots, A{sub}G{\sub}. In addition, we compare R with the recently developed interdiurnal variability geomagnetic indices IDV and IDV(1d). In all four cases, linearity of the relationship with R is not assumed and care is taken to ensure that the relationship of each with R is the same before and after the putative calibration change. It is shown the probability that a correction is not needed is of order 10{sup}−8{\sup} and that R is indeed too low before 1945. The optimum correction to R for values before 1945 is found to be 11.6%, 11.7%, 10.3% and 7.9% using A{sub}G{\sub}, N{sub)G{\sub}, IDV, and IDV(1d), respectively. The optimum value obtained by combining the sunspot group data is 11.6% with an uncertainty range 8.1-14.8% at the 2σ level. The geomagnetic indices provide an independent yet less stringent test but do give values that fall within the 2σ uncertainty band with optimum values are slightly lower than from the sunspot group data. The probability of the correction needed being as large as 20%, as advocated by Svalgaard [2011], is shown to be 1.6 × 10{sup}−5{\sup}.