Search

Carbon farming presents an opportunity for the land sector to generate income and transition to more sustainable land management practices. In Australia, establishing a carbon project and earning carbon credits is complex, with project proponents needing to satisfy eligibility requirements and adhere to rigorous measurement, verification, and reporting protocols of approved methods. To address these challenges, a human centered design (HCD) approach was used to deliver a digital solution, serving landowners' needs related to method discovery and reconfiguring how the methodological and scientific complexity of abatement potentials was delivered. The solution, called LOOC-C (pronounced "Look-see"), supports the discovery of abatement methods that are available for a given land area and provides an initial estimate of the potential quantum of carbon sequestered/emitted and the nature of co-benefits associated with each eligible method. Reporting on LOOC-C development and its observed impact demonstrates the role that human centered digital tools have in promoting land management actions that are both sustainable and reasonable to undertake. It equally demonstrates the power of integrating environmental market and user requirements with a robust design methodology. With similar opportunities in environmental markets globally, additional applications of an HCD approach are proposed. In 2012, the Australian government established the Emissions Reduction Fund (ERF) to reward landowners (via awarding Australian Carbon Credit Units, or ACCUs) for the implementation of management practices that either sequester carbon and/or reduce emissions of greenhouse gases. Rigorous eligibility and method requirements are intended to provide confidence in abatement outcomes, but they introduce significant complexity that participants must overcome. 11 years later, uncertainties in the implementation and ACCU generation potential of ERF projects and implications on productivity/co-benefits have limited uptake and the quantum of ACCU generation of land sector enterprises. Digital tools that support the discovery of options and provide estimated potential outcomes, such as the LOOC-C tool described in this paper (), can generate interest and empowerment, helping to initiate decisions toward market participation. [ABSTRACT FROM AUTHOR]

Abstract: This paper uses a scenario analysis system – Range-ASSESS – to examine the potential for gains and losses of soil carbon in the Australian rangelands as affected by grazing and climate. The analysis involves a factorial examination of the effect of stocking rates and all possible 5-year historical climates between 1889 and 1999. The analysis also looks at the sensitivity of results to the method of calculation of safe carrying capacity, and to the thresholds used to calculate grazing and dryness indices that drive transitions in state and transition models. The analysis showed that different vegetation zones produced different responses to changes in stocking depending upon the spatial distribution of dryness index, nature of carbon state and transition model, rules governing transitions, and relative significance of soil carbon. At a stocking density equivalent to 100% of 1997 levels, the soil carbon loss from rangelands was about 400 Mt C in 40% of the 5-year periods using a sensitive growth deviation threshold to determine dryness index. If a less sensitive threshold was used, potential loss was reduced to about 200 Mt C. If the grazing pressure threshold for a grazing index of four is adjusted to a more generous level, then potential losses in the dry periods are substantially reduced. The analysis is intended to be indicative of a likely approximate outcome rather than a quantitative measure of system response. The results indicate that the interpretation of the effect of the drought-grazing pressure interaction on perennial plant survival, and consequent organic carbon input to soils, is a major source of uncertainty and a critical area for more experimental measurement. [Copyright &y& Elsevier]

Prescribed fire to reduce forest fuels has been routinely applied to reduce wildfire risk in many parts of the world. It has also been proposed that prescribed fire can be used to mitigate greenhouse gas (GHG) emissions. Although prescribed fire creates emissions, if the treatment also decreases the incidence of subsequent wildfires, it is possible for the net outcome to be an emissions decline. Previous studies have suggested prescribed fire, at the frequencies required to materially impact wildfire occurrence, generally leads to net emissions increases. A focus on emissions means any change in carbon storage within the ecosystem remains unaccounted for; because living, dead, and soil carbon pools are characterized by different residence times, a re-distribution of carbon amongst these pools may either reduce or increase long-term ecosystem carbon stores. A full ecosystem carbon model has been developed to investigate the implications of prescribed fire management on total Net Ecosystem Carbon Balance (NECB), inclusive of both emissions and carbon storage. Consistent with previous work, the results suggested limited potential for reducing net GHG emissions through applying prescribed fire, with higher emissions from prescribed fire approximately offset by lower emissions and avoided carbon losses from the subsequent reduction in wildfire frequency. For example, shortening the prescribed fire interval from 25 to 10 years resulted in a NECB sequestration that was typically less than ±0.4 Mg C ha−1 yr−1, or less than approximately 0.1% of the total ecosystem carbon storage. Hence, whilst there was limited opportunity for achieving emission abatement outcomes from changing prescribed fire management, there were no significant emission penalties for doing so. These results suggest land managers should be free to adopt prescribed fire regimes to target specific management outcomes, without significantly impacting net emissions or total ecosystem carbon storage over the long term. • Novel data-driven model of forest fuels, fire, and ecosystem carbon. • Low potential for reducing wildfire emissions through applying prescribed fire (PF). • Increased emissions from PF offset by reduced carbon losses from wildfire. • Potential to modify PF management without adversely impacting total carbon balance. • Managers can adopt different prescribed fire regimes to target specific outcomes. [ABSTRACT FROM AUTHOR]

Greenhouse gas (GHG) accounting of emissions from land use, land-use change, and forestry necessarily involves consideration of landscape fire. This is of particular importance for Australia given that natural and human fire is a common occurrence, and many ecosystems are adapted to fire, and require periodic burning for plant regeneration and ecological health. Landscape fire takes many forms, can be started by humans or by lightning, and can be managed or uncontrolled. We briefly review the underlying logic of greenhouse gas accounting involving landscape fire in the 2020 Australian Government GHG inventory report. The treatment of wildfire that Australia chooses to enact under the internationally agreed guidelines is based on two core assumptions (a) that effects of natural and anthropogenic fire in Australian vegetation carbon stocks are transient and they return to the pre-fire level relatively quickly, and (b) that historically and geographically anomalous wildfires in forests should be excluded from national anthropogenic emission estimates because they are beyond human control. It is now widely accepted that anthropogenic climate change is contributing to increased frequency and severity of forest fires in Australia, therefore challenging assumptions about the human agency in fire-related GHG emissions and carbon balance. Currently, the national inventory focuses on forest fires; we suggest national greenhouse gas accounting needs to provide a more detailed reporting of vegetation fires including: (a) more detailed mapping of fire severity patterns; (b) more comprehensive emission factors; (c) better growth and recovery models from different vegetation types; (d) improved understanding how fires of different severities affect carbon stocks; and (e) improved analysis of the human agency behind the causes of emissions, including ignition types and fire-weather conditions. This more comprehensive accounting of carbon emissions would provide greater incentives to improve fire management practices that reduce the frequency, severity, and extent of uncontrolled landscape fires. [ABSTRACT FROM AUTHOR]

• A comprehensive sensitivity analysis was completed for the FullCAM model. • Carbon stock outputs were most sensitive to background mortality rates, age, site conditions, decomposition/turnover parameters and stand structure. • Model applications showed the importance of background mortality in relation to fire and harvesting. • Sensitivity of FullCAM outputs is very context dependent in relation to age and site conditions. • Implications for further developing FullCAM are discussed. In Australia, the Full Carbon Accounting Model (FullCAM) is used by the Australian Government for international reporting of greenhouse gas emissions and to predict carbon stock changes for carbon abatement projects. Consequently, over the last 20 years, it has been routinely applied at continental, regional and local scales, and has been subject to on-going development to improve its accuracy and representativeness. Given its importance, a sensitivity analysis could facilitate our understanding of model behaviour and aid the planning of future work and data collection. In particular, the sensitivity of a given model parameter is often context dependent such that it depends on the level of other parameters or variables. Key FullCAM parameters have generally been calibrated using data from empirical studies, with differing levels of confidence based on the sample size and data quality. The objective of this study was to apply a sensitivity analysis to examine (i) the sensitivity of FullCAM carbon stock outputs to its parameters and inputs, and how the sensitivity indices compare with the sample sizes used to calculate the respective parameters, (ii) the context dependency in terms of how the sensitivity varies with age, potential maximum biomass (a key FullCAM parameter), and disturbance severity or type, and (iii) to identify the implications for further development of FullCAM for woody vegetation systems. Of the 67 parameters tested, FullCAM carbon stock outputs were most sensitive to background mortality rates, age, potential maximum biomass, climate variability, age of maximum growth, decomposition or turnover parameters, and stand structure (regenerating or mature). The context dependency of the sensitivity analysis followed a consistent pattern depending on two main conditions, such that the sensitivity was higher when (i) the carbon stock was large and (ii) the parameter had a strong influence on that carbon stock. Several strong context dependencies occurred because the size of carbon stocks often vary through space and time within an ecosystem, and different processes (i.e. parameters) are more important at different times and locations. There was a strong context dependency in relation to age and potential maximum biomass, and FullCAM simulations indicated an interaction between fire disturbances and vegetation types. Lastly, background mortality was one of the least available inputs, but one to which FullCAM outputs were very sensitive. FullCAM was applied to show that the long-term contributions of low rates of background mortality to standing dead and debris C stocks were often as large as those from frequent (every 30 years) and intense harvesting and fire events because of the regular (annual) contribution of mortality and its accumulating influence of C stocks. [ABSTRACT FROM AUTHOR]