Soil Chemical Analysis

Statistics for Spatial Data.

Evolution and ecology of influenza A viruses.

Remediation of heavy metal(loid)s contaminated soils - To mobilize or to immobilize?

The knowns, known unknowns and unknowns of sequestration of soil organic carbon

The applicability of online trace enrichment with custom-made coated capillaries combined with tandem mass spectrometry was demonstrated for the target analysis of selected pesticides (mainly herbicides, e.g., triazines, phenylureas, and acetanilides) in water. The developed method allows rapid determination of several widely used plant protectants within a total analysis time of 11 min. Good linearity (r ≥ 0.995) was obtained for the selected pesticides in the range of 0.050–50 µg/L. The relative standard deviations (RSDs) of the peak areas were ≤3.8% for spiked Milli-Q water (5 µg/L). The RSDs obtained in analyses of spiked (1 µg/L) water samples (brook water, river water, sewage plant effluent) ranged from 2.9 to 6.8%, indicating low influence of the matrix on enrichment and detection. The detection limits, which ranged from 10 to 90 ng/L, fulfilled the requirements of the European regulations for drinking water. The polyacrylate coating of the extraction capillary showed good stability in the presence of water and acetonitrile and allowed ≥100 extractions with 1 capillary.

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Rapid target analysis for pesticides in water by online coated capillary microextraction combined with liquid chromatography and tandem mass spectrometry.

Soil water repellency (SWR) is a natural phenomenon occurring in soils throughout the world, which impacts upon ecosystem services at multiple temporal and spatial scales (nano to ecosystem scale). In pastures, the development of SWR is primarily determined by the cycling of hydrophobic materials at the soil surface, and is controlled by climate, soil and water management, and soil properties. The complex interactions between these factors make it an intricate system to understand and model. Detailed spatiotemporal characterization of the surface moisture and biomass in pastoral ecosystems would allow for a better understanding of this phenomenon. Normalized Difference Vegetation Index (NDVI) and Synthetic Aperture Radar (SAR) backscatter are good predictors for surface biomass and soil moisture, respectively. Machine learning on remote sensing time series (TS) data shows promise to predict the occurrence of SWR in pastures. This study evaluates the ability of remote sensing TS data to predict the occurrence of SWR in New Zealand pastures, using three machine learning algorithms. Soil water repellency data were collected from 58 pastoral sites. Machine learning models were trained and cross-validated on a monthly aggregated remote sensing and water deficit TS data to predict SWR level. Prediction output from artificial neural networks (ANN), random forest (RF), and support vector machine (SVM) were compared using root mean squared error (RMSE). When using NDVI TS data from 58 site as predictors of SWR, SVM and RF (RMSE = 0.82 and 0.87, respectively) outperformed ANN (RMSE = 1.23). Random forest was used to map SWR magnitude over Hawke’s Bay region in the North Island of New Zealand, and the overall accuracy was equal to 86%. This study is the first investigation implicating remote sensing TS data to predict the occurrence of SWR at the regional scale. Mapping the potential SWR will aid in identifying critical zones of SWR, to attenuate its effect on pastures through adapted management.

Time series of remote sensing and water deficit to predict the occurrence of soil water repellency in New Zealand pastures

Research and Application of Biochar in China

The gas transport parameters, diffusivity and air-filled porosity are crucial for soil aeration, microbial activity and greenhouse gas emission, and directly depend on soil structure. In this study, we analysed the effect of long-term tillage and irrigation practices on the surface structure of an arable soil in New Zealand. Our hypothesis was that topsoil structure would change under intensification of arable production, affecting gas exchange. Intact soil cores were collected from plots under intensive tillage (IT) and direct drill (DD), irrigated or rainfed. In total, 32 cores were scanned by X-ray computed tomography (CT) to derive the pore network >30 µm. The cores were then used to measure soil-gas diffusivity, air-permeability and air-filled porosity of pores close to the resolution of the X-ray CT scans, namely ≥30 µm. The gas measurements allow the calculation of pore-network connectivity and tortuosity parameters, which were compared with the CT-derived structural characteristics. Long-term irrigation had little effect on any of the parameters analysed. Total porosity tended to be lower under IT than DD, whereas the CT-derived porosity was comparable. Both the CT-derived mean pore diameter (MPD) and other morphological parameters, as well as gas measurement-derived parameters, highlighted a less developed structure under IT. The differences in the functional pore-network structure were attributed to SOC depletion and the mechanical disturbance through IT. Significant correlations between CT-derived parameters and functional gas transport parameters such as tortuosity and MPD were found, which suggest that X-ray CT could be useful in the prediction of gas transport.

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Effect of long-term irrigation and tillage practices on X-ray CT and gas transport derived pore-network characteristics

Runoff potential of five herbicides (acetochlor, atrazine, hexazinone, pendimethalin and terbuthylazine) was investigated on a fallow Hamilton clay loam soil with a 10% slope. Twenty-four hours after the herbicide application, simulated rainfall was applied at three intensities. Sediment amounts and herbicide concentrations were determined in the water phase of runoff samples. Herbicide residues attached to sediment were estimated using K d -values determined locally for the Hamilton clay loam soil. Pesticide concentrations were the highest in the first runoff samples and decreased exponentially with further rain. Results show that herbicides were primarily transported in their dissolved forms in runoff, and that losses are dependent on the time to runoff and runoff rates. Rainfall intensity had no significant effect on herbicide losses. In all cases losses were <1% of the amounts applied.

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Karin Müller

Papers

Rapid target analysis for pesticides in water by online coated capillary microextraction combined with liquid chromatography and tandem mass spectrometry.

Time series of remote sensing and water deficit to predict the occurrence of soil water repellency in New Zealand pastures

Research and Application of Biochar in China

Effect of long-term irrigation and tillage practices on X-ray CT and gas transport derived pore-network characteristics

Herbicide runoff studies in an arable soil under simulated rainfall