Impacts of sodic soil amelioration on deep drainage

Groundwater tables are rising beneath irrigated fields in some areas of the Lower Burdekin in North Queensland, Australia. The soils where this occurs are predominantly sodic clay soils with low hydraulic conductivities. Many of these soils have been treated by applying gypsum or by increasing the salinity of irrigation water by mixing saline groundwater with fresh river water. While the purpose of these treatments is to increase infiltration into the surface soils and improve productivity of the root zone, it is thought that the treatments may have altered the soil hydraulic properties well below the root zone leading to increased groundwater recharge and rising water tables. In this paper we discuss the use of column experiments and HYDRUS modelling, with major ion reaction and transport and soil water chemistry-dependent hydraulic conductivity, to assess the likely depth, magnitude and timing of the impacts of surface soil amelioration on soil hydraulic properties below the root zone and hence groundwater recharge. In the experiments, columns of sodic clays from the Lower Burdekin were leached for extended periods of time with either gypsum solutions or mixed cation salt solutions and change s in hydraulic conductivity were measured. Leaching with a gypsum solution for an extended time period, until the flow rate stabilised, resulted in an approximately twenty fold increase in the hydraulic conductivity when compared with a low salinity, mixed cation solution. HYDRUS modelling was used to high light the role of those factors which might influence the impacts of soil treatment, particularly at depth, including the large amounts of rain during the relatively short wet season and the presence of thick low permeability clay layers.

Establishing turf grass increases soil greenhouse gas emissions in peri-urban environments

Urbanization is becoming increasingly important in terms of climate change and ecosystem functionality worldwide. We are only beginning to understand how the processes of urbanization influence ecosystem dynamics and how peri-urban environments contribute to climate change. Brisbane in South East Queensland (SEQ) currently has the most extensive urban sprawl of all Australian cities. This leads to substantial land use changes in urban and peri-urban environments and the subsequent gaseous emissions from soils are to date neglected for IPCC climate change estimations. This research examines how land use change effects methane (CH4) and nitrous oxide (N2O) fluxes from peri-urban soils and consequently influences the Global Warming Potential (GWP) of rural ecosystems in agricultural use undergoing urbanization. Therefore, manual and fully automated static chamber measurements determined soil gas fluxes over a full year and an intensive sampling campaign of 80 days after land use change. Turf grass, as the major peri-urban land cover, increased the GWP by 415 kg CO2-e ha 1 over the first 80 days after conversion from a well-established pasture. This results principally from increased daily average N2O emissions of 0.5 g N2O ha-1 d-1 from the pasture to 18.3 g N2O ha-1 d-1 from the turf grass due to fertilizer application during conversion. Compared to the native dry sclerophyll eucalypt forest, turf grass establishment increases the GWP by another 30 kg CO2-e ha 1. The results presented in this study clearly indicate the substantial impact of urbanization on soil-atmosphere gas exchange in form of non-CO2 greenhouse gas emissions particularly after turf grass establishment.

Optimal adaptive sequential spatial sampling of soil using pair-copulas

A spatial sampling design that uses pair-copulas is presented that aims to reduce prediction uncertainty by selecting additional sampling locations based on both the spatial configuration of existing locations and the values of the observations at those locations. The novelty of the approach arises in the use of pair-copulas to estimate uncertainty at unsampled locations. Spatial pair-copulas are able to more accurately capture spatial dependence compared to other types of spatial copula models. Additionally, unlike traditional kriging variance, uncertainty estimates from the pair-copula account for influence from measurement values and not just the configuration of observations. This feature is beneficial, for example, for more accurate identification of soil contamination zones where high contamination measurements are located near measurements of varying contamination. The proposed design methodology is applied to a soil contamination example from the Swiss Jura region. A partial redesign of the original sampling configuration demonstrates the potential of the proposed methodology.

Denitrification losses from an intensively managed sub-tropical pasture: Impact of soil moisture on the partitioning of N2 and N2O emissions

Intensively managed pastures in subtropical Australia under dairy production are nitrogen (N) loaded agro-ecosystems, with an increased pool of N available for denitrification. The magnitude of denitrification losses and N2:N2O partitioning in these agro-ecosystems is largely unknown, representing a major uncertainty when estimating total N loss and replacement. This study investigated the influence of different soil moisture contents on N2 and N2O emissions from a subtropical dairy pasture in Queensland, Australia. Intact soil cores were incubated over 15 days at 80% and 100% water-filled pore space (WFPS), after the application of 15N labelled nitrate, equivalent to 50 kg N ha−1. This setup enabled the direct quantification of N2 and N2O emissions following fertilisation using the 15N gas flux method. The main product of denitrification in both treatments was N2. N2 emissions exceeded N2O emissions by a factor of 8 ± 1 at 80% WFPS and a factor of 17 ± 2 at 100% WFPS. The total amount of N-N2 lost over the incubation period was 21.27 kg ± 2.10 N2-N ha−1 at 80% WFPS and 25.26 kg ± 2.79 kg ha−1 at 100% WFPS respectively. N2 emissions remained high at 100% WFPS, while related N2O emissions decreased. At 80% WFPS, N2 emissions increased constantly over time while N2O fluxes declined. Consequently, N2/(N2 + N2O) product ratios increased over the incubation period in both treatments. N2/(N2 + N2O) product ratios responded significantly to soil moisture, confirming WFPS as a key driver of denitrification. The substantial amount of fertiliser lost as N2 reveals the agronomic significance of denitrification as a major pathway of N loss for sub-tropical pastures at high WFPS and may explain the low fertiliser N use efficiency observed for these agro-ecosystems.

Non-linear response of soil N2O emissions to nitrogen fertiliser in a cotton-fallow rotation in sub-tropical Australia

Nitrogen fertiliser is a major source of atmospheric N2O and over recent years there is growing evidence for a non-linear, exponential relationship between N fertiliser application rate and N2O emissions. However, there is still high uncertainty around the relationship of N fertiliser rate and N2O emissions for many cropping systems. We conducted year-round measurements of N2O emission and lint yield in four N rate treatments (0, 90, 180 and 270 kg N ha-1) in a cotton-fallow rotation on a black vertosol in Australia. We observed a nonlinear exponential response of N2O emissions to increasing N fertiliser rates with cumulative annual N2O emissions of 0.55 kg N ha-1, 0.67kg N ha-1, 1.07 kg N ha-1 and 1.89 kg N ha-1 for the four respective N fertiliser rates while no N response to yield occurred above 180N. The N fertiliser induced annual N2O EF factors increased from 0.13% to 0.29% and 0.50% for the 90N, 180N and 270N treatments respectively, significantly lower than the IPCC Tier 1 default value (1.0 %). This non-linear response suggests that an exponential N2O emissions model may be more appropriate for use in estimating emission of N2O from soils cultivated to cotton in Australia. It also demonstrates that improved agricultural N management practices can be adopted in cotton to substantially reduce N2O emissions without affecting yield potential.

Mapping the risk of soil-transmitted helminthic infections in the Philippines

Background In order to increase the efficient allocation of soil-transmitted helminth (STH) disease control resources in the Philippines, we aimed to describe for the first time the spatial variation in the prevalence of A. lumbricoides, T. trichiura and hookworm across the country, quantify the association between the physical environment and spatial variation of STH infection and develop predictive risk maps for each infection. Methodology/Principal Findings Data on STH infection from 35,573 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was stratified geographically in two major regions: 1) Luzon and the Visayas and 2) Mindanao. Bayesian geostatistical models of STH prevalence were developed, including age and sex of individuals and environmental variables (rainfall, land surface temperature and distance to inland water bodies) as predictors, and diagnostic uncertainty was incorporated. The role of environmental variables was different between regions of the Philippines. This analysis revealed that while A. lumbricoides and T. trichiura infections were widespread and highly endemic, hookworm infections were more circumscribed to smaller foci in the Visayas and Mindanao. Conclusions/Significance This analysis revealed significant spatial variation in STH infection prevalence within provinces of the Philippines. This suggests that a spatially targeted approach to STH interventions, including mass drug administration, is warranted. When financially possible, additional STH surveys should be prioritized to high-risk areas identified by our study in Luzon.