Richard Harper

Soil water repellency (SWR) poses a significant challenge in agriculture by reducing the soil’s ability to absorb water, thereby limiting water infiltration and negatively impacting crop yields. Numerous studies have shown multivariate relationships between the expression of SWR and soil particle size and organic carbon contents. However, the biological effects on soils are often considered in isolation. In this study, we explored the relationships between SWR and various physicochemical and biological properties of 30 soil samples from ten non-irrigated, dryland farms in South Australia, using correlation analysis and Random Forest modelling. Ethanol droplet tests were used to quantify SWR, and key soil properties including clay content, total organic carbon (TOC), pH, total nitrogen, microbial activity (measured via dehydrogenase activity, DHA), and dissolved iron (dFe) were assessed. Soils were grouped into low (Group 1, mean SWR 0.5 M) and high (Group 2, mean SWR 3.0 M) SWR categories based on clear differences in measured SWR values. Significant differences between groups were observed for clay, TOC, dFe, and DHA. Random Forest analysis identified clay and pH as the strongest predictors in Group 1. In Group 2, the model didn’t explain SWR variation. DHA had minimal influence on model performance.

Three solvent extraction methods (Soxhlet, sonication, and accelerated solvent extraction (ASE)) were investigated to develop an efficient technique for isolating and quantifying water repellency-inducing compounds (saturated long-chain (≥ C14) carboxylic acids, alkanes, alcohols, and sterols) from soils. The Soxhlet method was the most efficient at removing organic material from a deep yellow sand under dryland agriculture and grey sand under an Eucalyptus plantation. Although the sonication and ASE methods are time-efficient and facilitate high sample throughput, they were less effective for organic extraction (8.6% and 2.9% for dryland agriculture, 14.0% and 8.9% for plantation). While a range of chemical species from each of the four classes of soil water repellency-inducing compounds were extracted by the three methods, differences in the efficacies of the techniques were identified. Soxhlet extraction consistently recovered greater amounts of carboxylic acids, alcohols, and steroids, whereas ASE removed the largest amount of alkane. However, compounds from all classes were only identified from Soxhlet extracts of both field soils. The results indicate care is needed when comparing concentrations of compounds reported from extractions of water repellent soils using different extraction techniques.

Globally, decline of soil organic carbon (SOC) is a major threat for agricultural systems, especially in tropical environments. Intensive agriculture has reduced SOC levels (25–30 % in some regions), leading to poor soil health, lower crop yields (up to 30 %), and increased emission of carbon dioxide (CO2) and other greenhouse gases (10–20 % ). Carbon (C) farming, which involves sustainable practices such as no-till farming, cover cropping with legumes, agroforestry, recycling of crop residues, and improved grazing regimes, is a sustainable approach to capturing atmospheric CO2 and storing it in the soil and in the case of agroforestry in plant biomass. This review is predominantly concentrated on the soil component. Carbon (C) farming increases SOC by 0.4–1.2 Mg C ha–1 yr–1and can offer ecosystem benefits such as enhanced soil health and increased biodiversity by 15–30 %, improvement in soil water-holding capacity (10–25 %) leading to more sustainable and resilient agricultural systems. Therefore, incentivizing farmers through C credits or payment for ecosystem services (PES) are recommended to support C farming as they directly contribute to improved livelihoods , increased income by 20 % especially in small holder farming systems, and achieving Sustainable Development Goals (SDGs) related to eliminating poverty (SDG 1), zero hunger (SDG 2), promoting good health and well-being (SDG 3) and climate action (SDG 13). Furthermore, cropping systems involving bioenergy crops may contribute to SDG 7 (affordable and clean energy) and SDG 12 (responsible consumption and production), with potential to produce 10–50 GJ ha–1 of renewable energy annually and making it a promising option for sustainable agricultural production and environmental protection.

The increasing threat of soil degradation presents significant challenges to soil health, especially within agroecosystems that are vital for food security, climate regulation, and economic stability. This growing concern arises from intricate interactions between land use practices and climatic conditions, which, if not addressed, could jeopardize sustainable development and environmental resilience. This review offers a comprehensive examination of soil degradation, including its definitions, global prevalence, underlying mechanisms, and methods of measurement. It underscores the connections between soil degradation and land use, with a focus on socio-economic consequences. Current assessment methods frequently depend on insufficient data, concentrate on singular factors, and utilize arbitrary thresholds, potentially resulting in misclassification and misguided decisions. We analyze these shortcomings and investigate emerging methodologies that provide scalable and objective evaluations, offering a more accurate representation of soil vulnerability. Additionally, the review assesses both physical and biological indicators, as well as the potential of technologies such as remote sensing, artificial intelligence, and big data analytics for enhanced monitoring and forecasting. Key factors driving soil degradation, including unsustainable agricultural practices, deforestation, industrial activities, and extreme climate events, are thoroughly examined. The review emphasizes the importance of healthy soils in achieving the United Nations Sustainable Development Goals, particularly concerning food and water security, ecosystem health, poverty alleviation, and climate action. It suggests future research directions that prioritize standardized metrics, interdisciplinary collaboration, and predictive modeling to facilitate more integrated and effective management of soil degradation in the context of global environmental changes.

Soil water repellency (SWR) is a major agro-ecological soil management issue caused by hydrophobic organic compounds that hinder soil water absorption and affect soil function. Recent modelling studies indicate that climate change will increase the severity of SWR, compounding these effects. This study investigated the effects of climatic and soil factors on SWR in surface (0–10 cm) soils from 355 sites under uniform land-use across an area of 60,000 km2 in south-western Australia, a region with a Mediterranean climate. There were marked gradients in temperature (mean minimum temperature (Meanmin, 7.7–12.2 °C), mean maximum temperature (Meanmax, 19.0–22.9 °C), rainfall (507–1443 mm/year) and pan evaporation (Evap, 1169–1772 mm/year) across the sites. SWR was measured in the laboratory on oven dried samples using the ethanol droplet test. Boosted regression tree analysis showed that 10 soil variables explained 78 % of the variance in SWR, with clay, silt and OC contents the main contributors. Incorporating the four climatic variables explained 84 % of the variance of SWR, with Meanmax the major contributing factor. Thus, while soil properties dominated the expression of SWR, climate had a secondary impact. Meanmax however, was inversely related to SWR, suggesting that rising temperatures due to climate change could result in a reduction in SWR. Furthermore, given the strong relationship between SWR and OC content, climate mitigation projects aimed at enhancing soil OC storage may inadvertently increase the expression and severity of SWR. Recognition of this should be included in soil carbon mitigation project protocols.

Fire is a distinctive factor in forest ecosystems. While uncontrolled wildfires can cause significant damage, prescribed burning is widely used as a management tool. However, despite the growing threat of forest water stress under climate change, there is a lack of concrete evidence on the impact of fire on water stress in forest ecosystems. This study utilized Landsat time-series remote sensing data combined with the Infrared Canopy Dryness Index (ICDI) to monitor changes in canopy dryness patterns across the eucalyptus-dominated Northern Jarrah Forest of southwestern Australia. The forest was chosen due to its exposure to a changing climate characterized by decreasing rainfall and more frequent droughts, signs of water stress in otherwise drought-resilient trees, and its well-documented fire management history. Analysis of ICDI patterns over the period from 1988 to 2024 revealed a clear overall trend of increasing water stress, coinciding with a small overall decline in annual rainfall in the 10,000 km2 study area. Furthermore, by examining five prescribed burns and five wildfires, we found that NDVI-assessed canopy cover recovered rapidly in fire-affected areas, typically within one to three years, depending on fire severity. However, ICDI water stress levels were reduced for approximately 7–8 years following low-severity prescribed burns and more than 20 years after high-severity wildfires. These findings suggest the potential of prescribed burning as a tool to mitigate water stress in vulnerable forest landscapes, particularly in regions prone to drought and climate change. Additionally, the study underscores the effectiveness of the ICDI in monitoring forest water stress and its potential for broader applications in forest management and climate adaptation strategies.

Mass conversion of native vegetation to agricultural land-use triggered secondary salinity, a hydrological imbalance, which has damaged more than 1.75 million ha of farmland in south-western Australia. Various types of reforestation have been proposed and tested to restore the hydrological balance, however the economic returns from these cannot compete with existing farm practice and land-holders thus have a reluctance to adopt. An alternative approach has been to reforest abandoned saline areas with salinity and/or water-logging tolerant trees to avoid displacement of farming activities. This reforestation approach is explicitly effective for carbon mitigation and thus finding appropriate tree species is essential. To select suitable tree species, three eucalypt species were planted adjacent to a salt scald in Wickepin, Western Australia, and their survival and growth on a site with saline soil and a shallow (< 1 m depth) saline ground water system. Survival and growth of Eucalyptus sargentii and E. salubris in the saline discharge areas were comparable to those in a non-saline area, and reforestation by these species can thus avoid land competition with farming activities and minimize opportunity costs. The biomass increment of E. sargentii was about three times higher than that of E. salubris in the saline areas (3.43 vs 1.12 Mg ha−1 year−1) over a 9.25 years period, and therefore E. sargentii can sequester more carbon (6.3 vs 2.1 Mg-CO2e ha−1 year−1) and mitigate hydrological imbalance within a much smaller reforestation area than E. salubris. Considering land use efficiency, cost-effectiveness and carbon mitigation efficiency, E. sargentii is the recommended tree species for reforestation to mitigate secondary salinity in Western Australia.

Canopy water content is a fundamental indicator for assessing the level of plant water stress. The correlation between changes in water content and the spectral reflectance of plant leaves at near-infrared (NIR) and short-wave infrared (SWIR) wavelengths forms the foundation for developing a new remote sensing index, the Infrared Canopy Dryness Index (ICDI), to monitor forest dryness that can be used to predict the consequences of water stress. This study introduces the index, that uses spectral reflectance analysis at near-infrared wavelengths, encapsulated by the Normalized Difference Infrared Index (NDII), in conjunction with specific canopy conditions as depicted by the widely recognized Normalized Difference Vegetation Index (NDVI). Development of the ICDI commenced with the construction of an NDII/NDVI feature space, inspired by a conceptual trapezoid model. This feature space was then parameterized, and the spatial region indicative of water stress conditions, referred to as the dry edge, was identified based on the analysis of 10,000 random observations. The ICDI was produced from the combination of the vertical distance (i.e., under consistent NDVI conditions) from an examined observation to the dry edge. Comparisons between data from drought-affected and non-drought-affected control plots in the Australian Northern Jarrah Forest affirmed that the ICDI effectively depicted forest dryness. Moreover, the index was able to detect incipient water stress several months before damage from an extended drought and heatwave. Using freely available satellite data, the index has potential for broad application in monitoring the onset of forest dryness. This will require validation of the ICDI in diverse forest systems to quantify the efficacy of the index.