Laboratory desorption behaviour, function and elemental composition of commercially marketed silicate minerals used to sequester phosphorus pollution as well as Zeolite, Smectite, and Kaolinite were determined to see whether their use by environmental scientists and water managers in eutrophic waterways has the potential to contribute to longer-term environmental impacts. As expected, lower phosphorus concentrations were observed, following treatment. However, data relating to desorption, environmental fate and bioavailability of phospho-silicate complexes (especially those containing rare earth elements) appear to be underrepresented in product testing and trial publications. Analysis of desorption of phosphate (P) was > 5 μg[P]/L for all three non-commercial samples and 0 > μg[P]/L > 5 for all commercial silicates for a range of concentrations from 0 to 300 μg[P]/L. Based on a review of bioaccumulation data specific to the endangered Cherax tenuimanus (Hairy Marron) and other endemic species, this is significant considering anything > 20 μg[La]/L is potentially lethal to the hairy marron, other crustaceans and even other phyla. Where prokaryotic and eukaryotic effects are underreported, this represents a significant challenge. Especially where product protocols recommend continual reapplication, this is significant because both the forward and reverse reactions are equally important. The users of silicate minerals in water columns should accept the dynamic nature of the process and pay equal attention to both adsorption and desorption because desorption behaviour is an inherent trait. Even if broader desorption experimentation is difficult, expensive and time-consuming, it is a critical consideration nonetheless.

Through clearing and use of fertilizer and legumes, areas of southwestern Australia's unique coastal sand plains can support relatively low-cost dairies. However, the ancient, highly weathered nature of the soils in this region makes the dairies susceptible to a range of threats, including nutrient leaching and erosion. Despite this, Western Australian dairy cows typically produce up to 5,500 L of milk per head annually supported by inorganic nitrogen (N) fertilizer (commonly 50:50 urea and ammonium sulfate) at rates up to <320 kg of N/ha per year. Where hotspots exist (up to 2,000 kg of N/ha per year), total N exceeds pasture requirements. We investigated plant and soil bacteria responses to N fertilizer rates consistent with Australian legislated production practices on dairy farms for pure and mixed swards of white clover (Trifolium repens) and Italian ryegrass (Lolium multiflorum) in a long-term pasture experiment in controlled glasshouse conditions. Although the soil bacterial community structure at phylum level was similar for white clover and Italian ryegrass, relative abundances of specific subgroups of bacteria differed among plant species according to the N fertilizer regimen. Marked increases in relative abundance of some bacterial phyla and subphyla indicated potential inhibition of N cycling, especially for N hotspots in soil. Ammonium concentration in soil was less correlated with dominance of some N-cycling bacterial phyla than was nitrate concentration. Changes in bacterial community structure related to altered nutrient cycling highlight the potential for considering this area of research in policy assessment frameworks related to nutrient loads in dairy soils, especially for N.

Raw soil core physical data used in machine learning algorithms with corresponding spatial remotely sensed data is an emerging science. Using data derived from soil core samples previously collected in Universal Transverse Mercator zone 50 (Western Australia) and remotely sensed data, a model that predicted ground movement (GM) was developed specific to Australian Standards manual AS 1726-2017. This is the first approach for Australian soils and first in the world for soils older than 200 million yr. The model developed reliably predicted GM with 91.1% accuracy. The error obtained from the prediction is within acceptable limits currently used by engineers in calculations concerning soil classification for engineering purposes. Concerning the remotely sensed data analyzed, accuracy of the Atterberg limits method might be improved if additional information about soil structure (layering and horizon) or other variables (seasonal data) are built into this model. This model can be used to save on construction material costs, reduce the potential for human error associated with data collection and sample manipulation, but also fast-track (by up to 6 wk based on current wait times) building approvals while ensuring compliance to the relevant legislation. This platform also reduces the environmental effects of invasive drilling techniques. A requirement within principles of sustainable building practices, and associated with current standards commonly used by structural engineers who may seek better understanding of soil properties in Australia as a software service (with application potential in North America).