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Community gardens, as common spaces where people gather to grow food, help foster public health, greener urban environments, life-long learning and vibrant communities. However, despite being promoted as sustainable horticulture and conservation agriculture, their soil health and carbon (C) sequestration potential, with implication for climate change mitigation, remains underexplored. This study assessed soil samples collected from raised beds (gardening area) and adjacent bare ground (control) at six community gardens in the Perth metropolitan area, Australia. These sites covered three soil mapping units (SMUs): calcareous deep sands, coloured sand and pale sands The soil in raised beds exhibited superior characteristics than surrounding urban soil including lower bulk density, higher pH buffering capacity, available nutrients including nitrogen (N), phosphorus (P) and potassium (K), cation exchange capacity (CEC), total C and microbial biomass. Notably, we estimated that raised bed soils accumulated significant levels of C in the top 10 cm layer (0.55 kg/m2 or 5.5 T/ha). Our findings also indicate no significant heavy metal contamination in any of the community garden soils. Although the global area of community gardens is marginally small, these results suggest they hold potential for carbon sequestration, especially in urban and peri-urban environments. The improved soil health and C storage potential in community garden soil are largely attributed to the regular application of compost produced within the community gardens. [ABSTRACT FROM AUTHOR]

This paper explores the application and advantages of remote sensing, machine learning, and mid-infrared spectroscopy (MIR) as a popular proximal sensing spectroscopy tool in the estimation of soil organic carbon (SOC). It underscores the practical implications and benefits of the integrated approach combining machine learning, remote sensing, and proximal sensing for SOC estimation and prediction across a range of applications, including comprehensive soil health mapping and carbon credit assessment. These advanced technologies offer a promising pathway, reducing costs and resource utilization while improving the precision of SOC estimation. We conducted a comparative analysis between MIR-predicted SOC values and laboratory-measured SOC values using 36 soil samples. The results demonstrate a strong fit (R² = 0.83), underscoring the potential of this integrated approach. While acknowledging that our analysis is based on a limited sample size, these initial findings offer promise and serve as a foundation for future research. We will be providing updates when we obtain more data. Furthermore, this paper explores the potential for commercialising these technologies in Australia, with the aim of helping farmers harness the advantages of carbon markets. Based on our study's findings, coupled with insights from the existing literature, we suggest that adopting this integrated SOC measurement approach could significantly benefit local economies, enhance farmers' ability to monitor changes in soil health, and promote sustainable agricultural practices. These outcomes align with global climate change mitigation efforts. Furthermore, our study's approach, supported by other research, offers a potential template for regions worldwide seeking similar solutions. [ABSTRACT FROM AUTHOR]

Restoration of coastal wetlands has the potential to deliver both climate change mitigation, called blue carbon, and adaptation benefits to coastal communities, as well as supporting biodiversity and providing additional ecosystem services. Valuing carbon sequestration may incentivize restoration projects; however, it requires development of rigorous methods for quantifying blue carbon sequestered during coastal wetland restoration. We describe the development of a blue carbon accounting model (BlueCAM) used within the Tidal Restoration of Blue Carbon Ecosystems Methodology Determination 2022 of the Emissions Reduction Fund (ERF), which is Australia's voluntary carbon market scheme. The new BlueCAM uses Australian data to estimate abatement from carbon and greenhouse gas sources and sinks arising from coastal wetland restoration (via tidal restoration) and aligns with the Intergovernmental Panel for Climate Change guidelines for national greenhouse gas inventories. BlueCAM includes carbon sequestered in soils and biomass and avoided emissions from alternative land uses. A conservative modeled approach was used to provide estimates of abatement (as opposed to on‐ground measurements); and in doing so, this will reduce the costs associated with monitoring and verification for ERF projects and may increase participation in blue carbon projects by Australian landholders. BlueCAM encompasses multiple climate regions and plant communities and therefore may be useful to others outside Australia seeking to value blue carbon benefits from coastal wetland restoration. [ABSTRACT FROM AUTHOR]

The development and refinement of methods for estimating organic carbon accumulation in biomass and soils during mangrove restoration and rehabilitation can encourage uptake of restoration projects for their ecosystem services, including those of climate change mitigation, or blue carbon. To support the development of a blue carbon method for Australia under the Emission Reduction Fund scheme we investigated; (1) whether carbon accumulation data from natural mangroves could be used to estimate carbon accumulation during restoration; (2) modeling mangrove biomass accumulation; and (3) how modeled carbon accumulation could be achieved over heterogeneous sites. First, we assessed carbon accumulation in soil and biomass pools from the global literature, finding that estimating carbon accumulation using data from natural mangroves provided similar estimates as those for restored or rehabilitated mangroves. We assessed mangrove biomass accumulation from global chronosequence studies, which we used to develop regional models for estimating biomass accumulation with restoration in Australia using values from local natural mangroves. Estimating biomass carbon accumulation using site‐based means of stand biomass provided similar estimates as values estimated through use of regional means values stratified by elevation; and reduced overestimates of biomass carbon accumulation that were based on regional mean values. Modeling soil carbon accumulation over environmentally heterogeneous project sites can apply a similar approach, stratifying over variation in site elevation. Our analysis provides a strategy for modeling blue carbon pools for an Australian blue carbon method that accommodates regional differences and is based on data from natural mangroves. [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]

The soil security concept has been put forward to maintain and improve soil resources inter alia to provide food, clean water, climate change mitigation and adaptation, and to protect ecosystems. A provisional framework suggested indicators for the soil security dimensions, and a methodology to achieve a quantification. In this study, we illustrate the framework for the function soil carbon storage and the two dimensions of soil capacity and soil condition. The methodology consists of (i) the selection and quantification of a small set of soil indicators for capacity and condition, (ii) the transformation of indicator values to unitless utility values via expert-generated utility graphs, and (iii) a two-level aggregation of the utility values by soil profile and by dimension. For capacity, we used a set of three indicators: total organic and inorganic carbon content and mineral associated organic carbon in the fine fraction (MAOC) estimated via their reference value using existing maps of pedogenons and current landuse to identify areas of remnant genosoils (total organic and inorganic carbon) and the 90th percentile for MAOC. For condition we used the same set of indicators, but this time using the estimated current value and comparing with their reference-state values (calculated for capacity). The methodology was applied to the whole of Australia at a spatial resolution of 90 m × 90 m. The results show that the unitless indicator values supporting the function varied greatly in Australia. Aggregation of the indicators into the two dimensions of capacity and condition revealed that most of Australia has a relatively low capacity to support the function, but that most soils are in a generally good condition relative to that capacity, with some exceptions in agricultural areas, although more sampling of the remnant genosoils is required for corroboration and improvement. The maps of capacity and condition may serve as a basis to estimate a spatially-explicit local index of Australia's soil resilience to the threat of decarbonization. • Methodology based on the soil security assessment framework. • Quantification of the capacity and condition of the soil to store carbon. • Spatial estimation of the utility to support carbon storage for three indicators. • Australia has low capacity, but overall good condition to store carbon. • Intensive up-to-date sampling is required to corroborate the results. [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]

This article assesses current and proposed European Union (EU) climate and environmental law, and the legal instruments associated with the Common Agricultural Policy (CAP), to see whether soil carbon sequestration is sufficiently promoted as a promising example of 'climate-smart agriculture'. The assessment shows that current and proposed policies and instruments are inadequate to stimulate large-scale adoption of soil carbon projects across Europe. Given the identified structural flaws, it is likely that this is true for all climate-smart agricultural practices. An alternative approach needs to be developed. Under EU climate policy, agriculture should be included in the EU Emissions Trading System (ETS) by allowing regulated industries to buy offsets from the agricultural sector, following the examples set by Australia and others. The second element of a new approach is aimed at the CAP, which needs to be far more focused on the specific requirements of climate change mitigation and adaptation. Yet, such stronger focus does not take away the need to explore new income streams for farmers from offsets under the ETS, as the CAP will never have sufficient funds for the deep and full transition of Europe's agriculture sector that is needed. [ABSTRACT FROM AUTHOR]

• Biomass, litterfall, decomposition and soil carbon data were collated. • Data was sourced from decades of research in plantations and farm forestry. • These data informed the model predicting carbon in tree plantings across Australia. • Biomass, litterfall and decomposition data first constrained the model. • The model was then efficiently calibrated for prediction of litter and soil carbon. Understanding carbon sequestration from tree planting and management activities is important for contributing to the mitigation of climate change. Although rates of growth and resulting sequestration of carbon in live above-ground biomass are relatively well understood in various woody plantings and commercial plantations in Australia, less is known about associated changes in live below-ground biomass, and the turnover and decomposition of biomass, and hence, resulting changes in carbon stocks of litter and soil. Our objective was to develop a modelling approach for predicting these processes and the resulting changes in litter and soil carbon following the establishment and/or management of tree plantings (EMTP) to facilitate their inclusion in carbon abatement projects. We reviewed and collated data on allocation of biomass, litterfall, litter decomposition, litter/harvest residue mass and soil organic carbon (N = 5,655 estimates). Data were sourced from existing field studies of woody plantings (mixed-species environmental and mallee eucalypt), commercial plantations (hardwood and softwood) and in some cases, eucalypt-dominant native forests. After constraining a carbon accounting model to observed measures of growth, allocation of biomass, and rates of litterfall and litter decomposition, the model was calibrated to maximise the efficiency of prediction of litter and soil pools. Although large uncertainties in 'observed' results meant that precision of prediction in any given data source was relatively poor, model predictions had negligible overall bias. The size and diversity of datasets applied in the process of calibration improved overall confidence in model predictions of litter and soil carbon pools. The calibrated model will therefore be a useful tool for informing land managers and policy makers seeking to understand on-site dynamics of all carbon pools, and hence, the total contribution to carbon abatement of different EMTP projects in Australia. [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]

Understanding the drivers of soil organic carbon (SOC) change over time and confidence to predict changes in SOC are essential to the development and long-term viability of SOC trading schemes. This study investigated temporal changes in total SOC, total nitrogen (N), and carbon (C) fractions (particulate organic carbon - POC, resistant organic carbon - ROC and humus organic carbon - HOC) over a 16-year period for four contrasting farming systems in a low rainfall environment (424 mm) at Condobolin, Australia. The farming systems were 1) conventional tillage mixed farming (CT); 2) reduced tillage mixed farming (RT); 3) continuous cropping (CC); and 4) perennial pasture (PP). The SOC dynamics were also modelled using APSIM C and N modules, to determine the accuracy of this model. Results are presented in the context of land managers participating in Australian climate change mitigation schemes. There was an increase in SOC for all farming systems over the first 12 years (total organic C, TOC% at 0–10 cm increased from 1.33% to 1.77%), which was predominately in the POC% fraction (POC% at 0–10 cm increased from 0.14% to 0.5%). Between 2012 and 2015, there was a decrease in SOC back to starting levels (TOC = 1.22% POC = 0.12% at 0–10 cm) in all systems. The PP system had higher TOC%, POC% and HOC% levels on average and higher SOC stocks to 30 cm depth at the final measurement in 2015 (PP = 30.43 t C ha−1; cropping systems = 23.71 t C ha−1), compared to the other farming systems. There was a decrease in TN% over time in all farming systems except PP. The average C:N increased from 14.1 in 1999 to 19.7 in 2012, after which time the SOC levels decreased and C:N dropped back to 15.8. The temporal change in SOC was not able to be represented by the AusFarm model. There are three important conclusions for policy development: 1) monitoring temporal changes in SOC over 12 years did not indicate long-term sequestration, required to assure "permanence" in SOC trading (i.e. 25–100 years) due to the susceptibility of POC to degradation; 2) without monitoring SOC in reference land uses (e.g. CT cropping system as a control in this experiment) it is not possible to determine the net carbon sequestration, and therefore the true climate change mitigation value; and 3) modelling SOC using AusFarm/APSIM, does not fully represent the temporal dynamics of SOC in this low rainfall environment. • Short-term increases in soil C may not represent long-term persistence. • POC increases rapidly but is susceptible to degradation. • Monitoring soil C in reference and changed land uses better predicts abatement. [ABSTRACT FROM AUTHOR]