ORCID Profile
0000-0003-3552-8481
Current Organisations
CSIRO
,
CSIRO Black Mountain Laboratories
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Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/SR16047
Abstract: Leaching of nitrogen (N) in intensive irrigated agriculture can be a significant loss pathway. Though many studies have focussed on losses of mineral N, and in particular nitrate, dissolved organic N (DON) has received less coverage. In the present study, over a 5-year period (2008–2013), 740kgNha–1 fertiliser was applied to an irrigated cotton–wheat–maize rotation on a cracking clay (grey Vertosol). Deep drainage from the undisturbed soil profile at the site was measured at 2.1m below the soil surface using a variable tension lysimeter. In total, 108mm of drainage occurred during the 5 years and the majority of the drainage and the irrigations occurred during the cotton seasons. The majority of the N loss occurred during the first 3–4 irrigations and neither the N loss nor its composition were affected by the product or timing of the fertiliser application. The N in the drainage was composed of 12.8kgNOx-Nha–1, 8.7 DON-N and 0.1 NH4+-Nkgha–1, which shows that DON is an important component (40%) of the deep drainage N from irrigated Vertosol cotton production systems. Overall the total N flux lost via deep drainage represents 3% of the applied N fertiliser.
Publisher: Elsevier BV
Date: 03-2022
Publisher: Wiley
Date: 07-2015
Abstract: Carbon dioxide off-setting policy in the agricultural sector is focused on manipulating the terrestrial carbon cycle by reafforestation and increasing the retention of carbon within agricultural soils. We quantified the amount of carbon stored in the living and dead biomass and the surface soils of a previously grazed woodland ecosystem. We demonstrate that modification of coarse woody debris management could potentially store 8 to 15 t C ha. This large carbon pool raises the prospect that appropriate management of temperate woodlands to retain coarse woody debris and increase its volume into the future could achieve increased landscape carbon storage.
Publisher: CSIRO
Date: 2018
Publisher: No publisher found
Date: 2014
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/SR15019
Abstract: Mid-infrared (mid-IR) diffuse reflectance spectroscopy can be used to effectively analyse soil, but the preparation of soil s les by grinding is time consuming. Soil s les are usually finely ground to a particle size of less than 0.250 mm because the spectrometer’s beam aperture is approximately 1–2 mm in diameter. Larger particles can generate specular reflections and spectra that do not adequately represent the soil s le. Grinding soil to small particle sizes enables the diffuse reflectance of light and more representative s le measurements. Here, we report on research that investigates the effect that grinding to different particle sizes have on soil mid-IR spectra. Our aims were to compare the effect of grinding soil to different particle sizes (2.000 mm, 1.000 mm, 0.500 mm, 0.250 mm and 0.106 mm) on the frequencies of mid-IR spectra, and compare the effect of these particle sizes on the accuracy of spectroscopic calibrations to predict organic carbon, sand, silt and clay contents. Using the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) National visible–near infrared database, we selected 227 soil s les from the National Soil Archive for our experiments, and designed an experiment whereby each soil s le was ground in triplicate to the different particle sizes. These ground s les were measured using an FT-IR spectrometer with a spectral range of 4000–600 cm–1. Grinding to particle sizes that are ≤2.000 mm reduces subs le variability. Smaller particle sizes produce finer and sharper absorption features, which are related to organic carbon, and clay and sand mineralogies. Generally, better predictions for clay, sand and soil organic carbon contents were achieved using soil that is more finely ground, but there were no statistically significant differences between predictions that use soil ground to 1 mm, 0.5 mm, 0.25 mm. Grinding did not affect predictions of silt content. Recommendations on how much grinding is required for mid-IR analysis should also consider the time, cost and effort needed to prepare the soil s les as well as the purpose of the analysis.
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/SR15171
Abstract: We developed and tested spectroscopic models derived by partial least squares regression (PLSR) using data from the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) national soil database (NatSoil) and soil s les from the Australian National Soil Archive. Models were constructed for 21 soil attributes, and their predictability assessed using the R2, ranged from 0.57 for bicarbonate extractable available phosphorus to 0.92 for the sum of the exchangeable bases. Investigating the spectral library coverage with a suite of 1484 unknown s les from a geochemical survey of Australian catchments, we found that the models could be used to predict many soil attributes in a geographically erse set of s les.
Publisher: CSIRO Publishing
Date: 2020
DOI: 10.1071/SR19021
Abstract: Process-based models capture our understanding of key processes that interact to determine productivity and environmental outcomes. Combining measurements and modelling together help assess the consequences of these interactions, identify knowledge gaps and improve understanding of these processes. Here, we present a dataset (collected in a two-month fallow period) and list potential issues related to use of the APSIM model in predicting fluxes of soil water, heat, nitrogen (N) and carbon (C). Within the APSIM framework, two soil water modules (SoilWat and SWIM3) were used to predict soil evaporation and soil moisture content. SWIM3 tended to overestimate soil evaporation immediately after rainfall events, and SoilWat provided better predictions of evaporation. Our results highlight the need for testing the modules using data that includes wetting and drying cycles. Two soil temperature modules were also evaluated. Predictions of soil temperature were better for SoilTemp than the default module. APSIM configured with different combinations of soil water and temperature modules predicted nitrate dynamics well, but poorly predicted ammonium-N dynamics. The predicted ammonium-N pool empties several weeks after fertilisation, which was not observed, indicating that the processes of mineralisation and nitrification in APSIM require improvements. The fluxes of soil respiration and nitrous oxide, measured by chamber and micrometeorological methods, were roughly captured by APSIM. Discrepancies between the fluxes measured with chamber and micrometeorological techniques highlight difficulties in obtaining accurate measurements for evaluating performance of APSIM to predict gaseous fluxes. There was uncertainty associated with soil depth, which contributed to surface emissions. Our results showed that APSIM performance in simulating N2O fluxes should be considered in relation to data precision and uncertainty, especially the soil depths included in simulations. Finally, there was a major disconnection between the predicted N loss from denitrification (N2 + N2O) and that measured using the 15N balance technique.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 02-2014
Publisher: CSIRO Publishing
Date: 2017
DOI: 10.1071/SR16167
Abstract: This paper explores the importance of the N loss pathways relative to the immobilisation and soil mineral N supply during a cotton season. Despite using an agronomic practice of splitting urea application to reduce losses and an optimal rate (232kg urea-N ha–1) for the experiment, the average fertiliser recovery was 32%, which indicates that soil N mineralisation is a key source of N for irrigated cotton production systems. A large amount of the fertiliser (62kgNha–1) was immobilised in the soil at the end of the season and during the season the soil supplied 159kgNha–1 to the plant via mineralisation. During the season, large N losses occurred from the field via the atmospheric, deep drainage and surface run-off pathways (143kgNha–1). The losses occurred directly after fertilisation, predominantly at the start of the season when the majority of the urea fertiliser was applied (180kg urea-N ha–1). This indicates that the form, placement and timing of the fertiliser did not synchronise with soil and crop N dynamics and irrigation practice. Over the course of the measurement season, based on the N inputs, losses and storage budget, a 42kgNha–1 soil deficit was observed. Further longer term work is required to quantify the magnitude and significance of the soil N stock across different systems.
Location: Australia
No related grants have been discovered for Seija Tuomi.