Herbicide residues in Australian grain cropping soils at sowing and their relevance to crop growth.

Herbicides are used extensively in Australian grain cropping systems. Despite occasional observations of herbicide-induced phytotoxicity, there is little information on the persistence and carryover of multiple herbicide classes in cropping soils and the risk to subsequent crops. Two soil surveys were conducted, in 2015 (n = 40) and 2016 (n = 42), across different Australian grain cropping fields prior to sowing of winter crops, and soil samples analysed for herbicide residues (16 analytes in 2015 and 22 analytes in 2016). Samples in 2015 were taken at two depths (0-10 cm and 10-30 cm), whilst samples in 2016 were taken in topsoil (0-10 cm) only, but from two discrete locations in each field. Our research in both years found at least one herbicide (or herbicide metabolite) residue at all sites, with a median of 6 analytes detected in 2015 and 7 analytes detected in 2016. The most frequently detected residues were glyphosate and its primary breakdown product aminomethylphosphonic acid (AMPA), in 87 and 100%, respectively, of topsoil (0-10 cm) samples in 2015, and 67 and 93% of samples in 2016. The median concentration of glyphosate in 2015 was 0.12 mg kg-1, while AMPA was 0.41 mg kg-1. In 2016, median concentrations of glyphosate and AMPA were 0.22 mg kg-1 and 0.31 mg kg-1. Residues of 2,4-dichlorophenoxyacetic acid, trifluralin and diflufenican were also detected in >40% of topsoil samples in both seasons, but with median concentrations of <0.05 mg kg-1. A literature review found limited availability of phytotoxicity thresholds for major grain crops exposed to soilborne herbicide residues. A risk assessment using available thresholds suggested that although up to 29% of fields contained trifluralin residues that could constrain cereal crop growth, and 24% of fields contained residues of phenoxy or sulfonylureas that could affect dicotyledonous crops, the majority of these fields when planted with tolerant crops would be unlikely to be affected by herbicide residues. More work is required to ascertain the spatial distribution, bioavailability and phytotoxicity of residues and residue mixtures to enable a more accurate agronomic risk assessment.

Data for assessment of sediment, soil, and water quality at Ashfield flats reserve, Western Australia.

Sediment and water samples were collected using transects and grids within sampling strata, in 2019, 2020, and 2021 from a riparian reserve adjoining the Swan River estuary in Western Australia. Different sampling designs were used each year, with transects and/or grids designed to assess changes in sediment and water quality across assumed environmental gradients such as salinity or distance from possible contaminant sources. Sediments were from 0-10cm; pH and electrical conductivity were measured on suspensions, 32 elements measured by ICP-OES on HNO3/HCl digests, and microplastics counted microscopically after Fenton digestion and density separation. Surface water was from wetland ponds and stormwater drains, with pH, EC measured in-situ. Filtered acidified water subsamples used to measure nitrate + nitrite and dissolved phosphate spectrophotometrically and 26 elements using ICP-OES. Reported data include metadata and are for 231 sediment/soil samples and 172 water samples, including sampling strata categories and UTM and Longitude-Latitude coordinates. Elemental concentrations have been censored based on blank subtraction and calculated lower detection limits, with censored data presented with missing value codes.

Paradoxical impact of sprawling intra-Urban Heat Islets: Reducing mean surface temperatures while enhancing local extremes.

Extreme heat is one of the deadliest health hazards that is projected to increase in intensity and persistence in the near future. Here, we tackle the problem of spatially heterogeneous heat distribution within urban areas. We develop a novel multi-scale metric of identifying emerging heat clusters at various percentile-based thermal thresholds and refer to them collectively as intra-Urban Heat Islets. Using remotely sensed Land Surface Temperatures, we first quantify the spatial organization of heat islets in cities at various degrees of sprawl and densification. We then condense the size, spacing, and intensity information about heterogeneous clusters into probability distributions that can be described using single scaling exponents (denoted by ß, [Formula: see text], and λ, respectively). This allows for a seamless comparison of the heat islet characteristics across cities at varying spatial scales and improves on the traditional Surface Urban Heat Island (SUHI) Intensity as a bulk metric. Analysis of Heat Islet Size distributions demonstrates the emergence of two classes where the dense cities follow a Pareto distribution, and the sprawling cities show an exponential tempering of Pareto tail. This indicates a significantly reduced probability of encountering large heat islets for sprawling cities. In contrast, analysis of Heat Islet Intensity distributions indicates that while a sprawling configuration is favorable for reducing the mean SUHI Intensity of a city, for the same mean, it also results in higher local thermal extremes. This poses a paradox for urban designers in adopting expansion or densification as a growth trajectory to mitigate the UHI.

Emergent self-similarity and scaling properties of fractal intra-urban heat islets for diverse global cities.

Urban areas experience elevated temperatures due to the urban heat island (UHI) effect. However, temperatures within cities vary considerably and their spatial heterogeneity is not well characterized. Here, we use land surface temperature (LST) of 78 global cities to show that the surface UHI (SUHI) is fractal. We use percentile-based thermal thresholds to identify heat clusters emerging within SUHI and refer to them collectively as intra-urban heat islets. The islets display properties analogous to that of a percolating system as we vary the thermal thresholds. At percolation threshold, the size distribution of these islets in all cities follows a power law, with a scaling exponent (ß) of 1.88 (±0.23,95%CI) and an aggregated perimeter fractal dimension (D) of 1.33 (±0.064,95%CI). This commonality indicates that despite the diversity in urban form and function across the world, the urban temperature patterns are different realizations with the same aggregated statistical properties. Furthermore, we observe the convergence of these scaling exponents as the city sizes increase. Therefore, while the effect of diverse urban morphologies is evident in smaller cities, in the mean, the larger cities are alike. Lastly, we calculate the mean islet intensities, i.e., the difference between mean islet temperature and thermal threshold, and show that it follows an exponential distribution, with rate parameter λ, for all cities. λ varied widely across the cities and can be used to quantify the spatial heterogeneity within SUHIs. In conclusion, we present a basis for a unified characterization of urban heat from the spatial scales of an urban block to a megalopolis.

Real-time forecasting of pesticide concentrations in soil.

Forecasting pesticide residues in soils in real time is essential for agronomic purposes, to manage phytotoxic effects, and in catchments to manage surface and ground water quality. This has not been possible in the past due to both modelling and measurement constraints. Here, the analytical transient probability distribution (pdf) of pesticide concentrations is derived. The pdf results from the random ways in which rain events occur after pesticide application. First-order degradation kinetics and linear equilibrium sorption are assumed. The analytical pdfs allow understanding of the relative contributions that climate (mean storm depth and mean rainfall event frequency) and chemical (sorption and degradation) properties have on the variability of soil concentrations into the future. We demonstrated the two uncertain reaction parameters can be constrained using Bayesian methods. An approach to a Bayesian informed forecast is then presented. With the use of new rapid tests capable of providing quantitative measurements of soil concentrations in the field, real-time forecasting of future pesticide concentrations now looks possible for the first time. Such an approach offers new means to manage crops, soils and water quality, and may be extended to other classes of pesticides for ecological risk assessment purposes.

Global warming in the context of 2000 years of Australian alpine temperature and snow cover.

Annual resolution reconstructions of alpine temperatures are rare, particularly for the Southern Hemisphere, while no snow cover reconstructions exist. These records are essential to place in context the impact of anthropogenic global warming against historical major natural climate events such as the Roman Warm Period (RWP), Medieval Climate Anomaly (MCA) and Little Ice Age (LIA). Here we show for a marginal alpine region of Australia using a carbon isotope speleothem reconstruction, warming over the past five decades has experienced equivalent magnitude of temperature change and snow cover decline to the RWP and MCA. The current rate of warming is unmatched for the past 2000 years and seasonal snow cover is at a minimum. On scales of several decades, mean maximum temperatures have undergone considerable change ≈ ± 0.8 °C highlighting local scale susceptibility to rapid temperature change, evidence of which is often masked in regional to hemisphere scale temperature reconstructions.

Noise-Driven Return Statistics: Scaling and Truncation in Stochastic Storage Processes.

In countless systems, subjected to variable forcing, a key question arises: how much time will a state variable spend away from a given threshold? When forcing is treated as a stochastic process, this can be addressed with first return time distributions. While many studies suggest exponential, double exponential or power laws as empirical forms, we contend that truncated power laws are natural candidates. To this end, we consider a minimal stochastic mass balance model and identify a parsimonious mechanism for the emergence of truncated power law return times. We derive boundary-independent scaling and truncation properties, which are consistent with numerical simulations, and discuss the implications and applicability of our findings.

Linking Eco-Energetics and Eco-Hydrology to Select Sites for the Assisted Colonization of Australia's Rarest Reptile.

Assisted colonization-the deliberate translocation of species from unsuitable to suitable regions-is a controversial management tool that aims to prevent the extinction of populations that are unable to migrate in response to climate change or to survive in situ. The identification of suitable translocation sites is therefore a pressing issue. Correlative species distribution models, which are based on occurrence data, are of limited use for site selection for species with historically restricted distributions. In contrast, mechanistic species distribution models hold considerable promise in selecting translocation sites. Here we integrate ecoenergetic and hydrological models to assess the longer-term suitability of the current habitat of one of the world's rarest chelonians, the Critically Endangered Western Swamp Tortoise (Psuedemydura umbrina). Our coupled model allows us to understand the interaction between thermal and hydric constraints on the foraging window of tortoises, based on hydrological projections of its current habitat. The process can then be repeated across a range of future climates to identify regions that would fall within the tortoise's thermodynamic niche. The predictions indicate that climate change will result in reduced hydroperiods for the tortoises. However, under some climate change scenarios, habitat suitability may remain stable or even improve due to increases in the heat budget. We discuss how our predictions can be integrated with energy budget models that can capture the consequences of these biophysical constraints on growth, reproduction and body condition.

Assessing the impact of regional rainfall variability on rapid pesticide leaching potential.

The timing and magnitude of rainfall events are known to be dominant controls on pesticide migration into streams and groundwater, by triggering rapid flow processes, such as preferential flow and surface runoff. A better understanding of how regional differences in rainfall impact rapid leaching risk is required in order to match the scale at which water regulation occurs. We estimated the potential amount of rapid leaching, and the frequencies of these events in a case study of the southwest of Western Australia, for one soil type and a range of linearly sorbing, first order degrading chemicals. At the regional scale, those chemicals with moderate sorption and long half lives were the most susceptible to rapid transport within a year of application. Within the region, this susceptibility varied depending upon application time and seasonality in storm patterns. Those chemicals and areas with a high potential for rapid transport on average, also experience the greatest inter-annual variability in rapid leaching, as measured by the coefficient of variation. The timing and frequencies of rapid leaching events appeared to strongly relate to an area's relative susceptibility to rapid leaching. In the study region the results also suggested that frontal rainfall dominates rapid leaching along the western and southern coasts while convective thunderstorms play a greater role in the arid east.