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Since mid-2018, school students across the world have been leading mass strikes to demand strengthened political action on climate change. This article explores how young people's political participation in the School Strike for Climate movement in Australia was represented in newspaper coverage over a 17-month period (August 2018–December 2019), with particular attention to the representation of young people's emotions and actions. The analysis works with a corpus of 500 articles published in Australian national, state (New South Wales and Victoria), and a select sample of regional and rural newspapers. The corpus is read with affective-discursive attunement to historical representations of children and young people, the politics of emotion, and contemporary media representational politics surrounding climate justice activism. Four dominant characterisations of the young strikers are analysed: ignorant zealots, anxious pawns, rebellious truants, and extraordinary heroes. Alongside these characterisations, we consider how young people speak back to these characterisations, and draw implications for future research with young climate justice activists. [ABSTRACT FROM AUTHOR]

Digital soil maps of soil organic carbon (SOC) sequestration potential resulting from a hypothetical 10% relative increase in long‐term vegetation cover are presented at 100‐m resolution across the state of New South Wales (NSW) in southeast Australia. This land management outcome is considered realistically achievable for many land managers, using strategies such as revegetation, grazing management or crop residue management. A mean state‐wide potential increase of 5.4 Mg ha−1 over the 0‐ to 30‐cm depth interval was derived. Assuming a 20‐year period of re‐equilibration, this equates to an average SOC increase of 0.27 Mg ha−1 year−1. Sequestration potential is systematically influenced by a combination of climate, soil parent material and current vegetation cover, for example only 1.6 Mg ha−1 SOC under dry conditions in sandy, infertile soil material with sparse vegetation cover, compared with 15.9 Mg ha−1 under wet conditions in clay‐rich, fertile soil material with moderate–high vegetation cover. The outputs could be used to identify locations of highest sequestration potential and thereby help prioritize areas and inform decisions on sequestration programmes. Future application of the method at field scale with high levels of accuracy, together with strategic sampling, may provide statistically reliable estimates of carbon sequestration, for application in carbon trading schemes such as Australia's Emissions Reduction Fund. The modelling involved a conceptually transparent 'space‐for‐time substitution' process. Multiple linear regression (MLR) and random forest (RF) modelling techniques were applied, but only MLR gave consistently meaningful results. The apparent failing of RF in this application warrants further examination. [ABSTRACT FROM AUTHOR]

We modelled and mapped the distribution of three principal soil organic carbon (SOC) fractions across New South Wales and gained insights into the factors controlling their distribution. Carbon fractions are important for modelling soil carbon dynamics for carbon accounting, and as a potential indicator of soil quality. We considered particulate organic carbon (POC), humic organic carbon (HOC) and resistant organic carbon (ROC), which represent fractions of increasing bio-chemical stability. A dataset of 427 NSW profiles with mid-infrared (MIR) derived carbon fractions and a set of 16 predictor variables were applied. Random Forest and multiple linear regression techniques were applied, for depth intervals to 30 cm. The derived models and maps were of moderate strength, with validation results revealing Lin's concordance values for the 0–30 cm depth interval of 0.79 for total SOC stocks and 0.60 to 0.74 for the fraction stocks. Maps of mean stocks, and upper and lower 95% prediction intervals are presented. Absolute stocks (in Mg ha−1) of each fraction have a strong linear relationship with total SOC and are controlled by similar environmental and land management factors, normally increasing in a systematic way with increasingly moist climate (considering rainfall and temperatures), increasing mafic lithology (associated with more fertile, clay rich soils) and less disturbed land uses with higher vegetation cover. The environmental factors influencing the relative proportions of each fraction (% of total SOC) are more complex, but climate and lithology appear to be dominant, in addition to depth in profile. An SOC vulnerability index is mapped over the State, identifying areas where the stored carbon is most vulnerable to land management or environmental change. Our findings add to the understanding of factors driving the distribution of soil carbon and its fractions, which may ultimately contribute to more effective climate change mitigation programs. Unlabelled Image • Digital soil maps of three SOC fractions (at 100 m resolution) prepared for NSW • Absolute stocks of SOC fractions have strong linear relationship with total SOC. • All stocks increase with moister climate, more mafic soil and higher vegetation cover. • Relative proportions (% of total SOC) influenced by climate, lithology and depth • SOC vulnerability index mapped over NSW [ABSTRACT FROM AUTHOR]

• MLR and RF were used to estimate current SOC stocks in south-eastern Australia. • Rainfall and minimum temperature were major drivers in determining SOC stocks. • The multi-GCM ensemble means suggested an overall decrease in SOC stocks. • The largest mean decrease of SOC stocks occurs in the high-rainfall alpine regions. Soil organic carbon (SOC) plays a key role in the sequestration of carbon that could otherwise be warming the atmosphere. Climate change including increased temperature and changed rainfall will greatly impact the global SOC cycle. There are still significant gaps in our knowledge of the size of the global SOC pool and how future climate will affect SOC stocks and flows in many parts of the world, including Australia. In this study, we used SOC data in a Digital Soil Mapping framework to predict current and future SOC stocks across the state of New South Wales (NSW) in south-eastern Australia. In the first phase of the study we estimated the current SOC stock using multiple linear regression (MLR) and random forest (RF) modelling, and in the second phase we projected the change of SOC stocks in the near future (2050s) and far future (2090s) under two Shared Socio-economic Pathways (SSPs) scenarios based on 25 global climate models (GCMs) from the Coupled Model Inter-comparison Project Phase 6 (CMIP6). Our spatial modelling showed that estimated current SOC stocks in NSW decreased from east to west. Multi-GCM ensemble means suggested SOC stocks would decrease by 7.6–12.9% under SSP2-4.5 and 9.1–20.9% under SSP5-8.5 across NSW under future climate. The extent of change in SOC stocks varied spatially with the largest mean decrease of SOC stocks occurring in the North Coast and South East (alpine) regions of NSW. Our findings can support decision-making in land management and climate change mitigation strategies in NSW at the regional level. Furthermore, the modelling methods can be applied to other areas where edaphic and landscape properties, land use, and climate data are available. [ABSTRACT FROM AUTHOR]