Tillage and the environment in sub-tropical Australia-Tradeoffs and challenges

Tillage is defined here in a broad sense, including disturbance of the soil and crop residues, wheel traffic and sowing opportunities. In sub-tropical, semi-arid cropping areas in Australia, tillage systems have evolved from intensively tilled bare fallow systems, with high soil losses, to reduced and no tillage systems. In recent years, the use of controlled traffic has also increased. These conservation tillage systems are successful in reducing water erosion of soil and sediment-bound chemicals. Control of runoff of dissolved nutrients and weakly sorbed chemicals is less certain. Adoption of new practices appears to have been related to practical and economic considerations, and proved to be more profitable after a considerable period of research and development. However there are still challenges. One challenge is to ensure that systems that reduce soil erosion, which may involve greater use of chemicals, do not degrade water quality in streams. Another challenge is to ensure that systems that improve water entry do not increase drainage below the crop root zone, which would increase the risk of salinity. Better understanding of how tillage practices influence soil hydrology, runoff and erosion processes should lead to better tillage systems and enable better management of risks to water quality and soil health. Finally, the need to determine the effectiveness of in-field management practices in achieving stream water quality targets in large, multi-land use catchments will challenge our current knowledge base and the tools available

Distributed parameter hydrology model (ANSWERS) applied to a range of catchment scales using rainfall simulator data II: Application to spatially uniform catchments

The ANSWERS model, modified to include Green and Ampt infiltration, was tested using measured runoff from several tilled, black earth catchments on the eastern Darling Downs, Queensland. Rainfall and runoff data from rainfall simulator plots (1 m2 and 88 m2), and three small catchments (0.07 ha, 0.2 ha and 3.2 ha) were used to test predictions of runoff. Important infiltration parameter values were determined from a separate set of 1 m2 rainfall simulator plots. Other parameter values were measured directly or estimated from published sources. Measured runoff from the simulator plots and catchments was accurately predicted by the modified ANSWERS; a linear regression explained 93% and 81% of the variation between predicted and measured peak runoff rate and runoff volume, respectively. Runoff was accurately predicted with the modified ANSWERS, as processes controlling runoff from the catchments, including infiltration and routing of runoff, were realistically characterised. This allowed parameter values to be derived independently of runoff, and transported to different size catchments without distortion or optimisation

Atrazine degradation and transport in runoff on a Black Vertosol

In Australia communities are concerned about atrazine being detected in drinking water supplies. It is important to understand mechanisms by which atrazine is transported from paddocks to waterways if we are to reduce movement of agricultural chemicals from the site of application. Two paddocks cropped with grain sorghum on a Black Vertosol were monitored for atrazine, potassium chloride (KCl) extractable atrazine, desethylatrazine (DEA), and desisopropylatrazine (DIA) at 4 soil depths (0-0.05, 0.05-0.10, 0.10-0.20, and 0.20-0.30 m) and in runoff water and runoff sediment. Atrazine + DEA + DIA (total atrazine) had a half-life in soil of 16-20 days, more rapid dissipation than in many earlier reports. Atrazine extracted in dilute potassium chloride, considered available for weed control, was initially 34% of the total and had a half-life of 15-20 days until day 30, after which it dissipated rapidly with a half life of 6 days. We conclude that, in this region, atrazine may not pose a risk for groundwater contamination, as only 0.5% of applied atrazine moved deeper than 0.20 m into the soil, where it dissipated rapidly. In runoff (including suspended sediment) atrazine concentrations were greatest during the first runoff event (57 days after application) (85 μg/L) and declined with time. After 160 days, the total atrazine lost in runoff was 0.4% of the initial application. The total atrazine concentration in runoff was strongly related to the total concentration in soil, as expected. Even after 98% of the KCl-extractable atrazine had dissipated (and no longer provided weed control), runoff concentrations still exceeded the human health guideline value of 40 μg/L. For total atrazine in soil (0-0.05 m), the range for coefficient of soil sorption (Kd) was 1.9-28.4 mL/g and for soil organic carbon sorption (KOC) was 100-2184 mL/g, increasing with time of contact with the soil and rapid dissipation of the more soluble, available phase. Partition coefficients in runoff for total atrazine were initially 3, increasing to 32 and 51 with time, values for DEA being half these. To minimise atrazine losses, cultural practices that maximise rain infiltration, and thereby minimise runoff, and minimise concentrations in the soil surface should be adopted

Erosion/productivity modelling of maize farming in the Philippine uplands. Part I: Parameterising the Agricultural Production Systems Simulator

This paper describes the parameterisation of the Agricultural Production Systems Simulator (APSIM) model to simulate open-field farming and intercropping of maize with leguminous shrub hedgerows. Whenever possible, parameters for the model were determined from measured or standard values for the environment of the field trials, while other parameters were derived from previous modelling experience in tropical environments. The remaining parameters were derived using step-wise calibration, where one or two parameters were calibrated against closely related measured data. Once parameterised, APSIM gave acceptable predictions of maize yields and soil loss from open-field farming and hedgerow intercropping. The version of APSIM described in this paper is used to simulate maize yields and soil erosion from open-field farming and hedgerow intercropping in the second paper in this series (Nelson et al., this issue). In the third paper, Nelson et al. (this issue) use cost–benefit analysis to compare the economic viability of hedgerow intercropping relative to traditional open-field farming of maize in relatively inaccessible upland areas

Erosion/productivity modelling of maize farming in the Philippine uplands. Part II: Simulation of alternative farming methods

A version of the Agricultural Production Systems Simulator (APSIM) capable of simulating the key agronomic aspects of intercropping maize between legume shrub hedgerows was described and parameterised in the first paper of this series (Nelson et al., this issue). In this paper, APSIM is used to simulate maize yields and soil erosion from traditional open-field farming and hedgerow intercropping in the Philippine uplands. Two variants of open-field farming were simulated using APSIM, continuous and fallow, for comparison with intercropping maize between leguminous shrub hedgerows. Continuous open-field maize farming was predicted to be unsustainable in the long term, while fallow open-field farming was predicted to slow productivity decline by spreading the effect of erosion over a larger cropping area. Hedgerow intercropping was predicted to reduce erosion by maintaining soil surface cover during periods of intense rainfall, contributing to sustainable production of maize in the long term. In the third paper in this series, Nelson et al. (this issue) use cost–benefit analysis to compare the economic viability of hedgerow intercropping relative to traditional open-field farming of maize in relatively inaccessible upland areas

Evaluation of the interaction between LRRK2 and PARK16 loci in determining risk of Parkinson's disease: analysis of a large multicenter study

A recent study MacLeod et al. has shown that an interaction between variants at the LRRK2 and PARK16 loci influences risk of development of Parkinson's disease (PD). Our study examines the proposed interaction between LRRK2 and PARK16 variants in modifying PD risk using a large multicenter series of PD patients (7715) and controls (8261) from sites participating in the Genetic Epidemiology of Parkinson's Disease Consortium. Our data does not support a strong direct interaction between LRRK2 and PARK16 variants; however, given the role of retromer and lysosomal pathways in PD, further studies are warranted. © 2016 Elsevier Inc