|Title:||The auditability of soil carbon at the farm scale|
|Keywords:||The auditability of soil carbon at the farm scale|
|Publisher:||University of Sydney.|
Faculty of Agriculture and Environment.
|Abstract:||Abstract — Auditability of soil carbon at the farm scale. There is a strong and growing interest in restoring degraded soil organic carbon (SOC) stocks in agricultural lands, both for the purpose of generating carbon offsets and for greater farm resilience through increasing the delivery of associated ecosystem services. In order to achieve attribution of carbon offsets to improved SOC management, an efficient method to measure ∆SOC with sufficient statistical confidence is required. However, there is considerable temporal risk associated with non-permanence in conjunction with the requirement to maintain SOC stocks for 100 years. As such, there is a need for an equitable method to attribute carbon offsets that respects both landholders and the atmosphere. To address these ends, this thesis attends to the question of the auditability of soil carbon stocks on farms and ultimately develops a soil carbon auditing protocol. A direct measurement approach is employed with a stratified simple random sampling (StSRS) aimed at whole farms. This design utilises a predicted SOC distribution field to capture all available relationships with the local covariates to enable univariate stratification. This approach was tested on four farms to determine baseline SOC stocks and their uncertainty — finding two of four farms had suitable surveys for repeat measurement under high sequestration rates (0.5 Mg ha-1 yr-1) without alteration (Chapter 3). This Chapter (and portions of the proceeding Chapters) describes and tests some basic elements outlined in the patent entitled 'A Method of Quantifying Soil Carbon — Patent WO 2011150472 A1'. Once a baseline survey has been collected there is a need to optimise stratification of the new SOC prediction field (incorporating updated local information) for repeat measurement using StSRS (Chapter 4). Further from this optimisation the tradeable portion of ∆SOC was linked to the lower confidence bound (exceedance probability) of the estimation — linking the quality of surveys to the awarded offsets. This enabled optimisation on the basis of diminishing returns for increased sampling investment. Further, by relating background SOC spatial variation to plausible sequestration rates, survey intensities and reasonable revisit times; it was found that trading on a lower confidence bound of between 60-70% of the ∆SOC estimate was optimal. A lower confidence bound of 95% was highly unrealistic given the need for reasonable revisit times and sampling intensities and over-penalised direct measurement without logical basis. Concerns over natural SOC variation could be better addressed through the approach to offset generation used to account for non-permanence. Generic advice for sample size based on expert knowledge of the range of SOC was also developed for simple random sampling. Additionally, generic advice on sample size efficiency that could be gained from stratification — dependant on the nature of SOC spatial variation — is also provided. With an eye to enabling easier future design of initial StSRS surveys for areas without prior information, regional mapping of SOC is examined. From this examination it was determined that when using decision trees, mapping average SOC to the desired depth is a more accurate approach than mapping by incremental depths (Chapter 5). To address the stumbling block of non-permanence, the most generically favourable methods for generating carbon offsets from ∆SOC were examined in Chapter 6. From this examination it is suggested that `incrementally weighting offset value evenly through time' rather than `upfront sale of offsets followed by temporal liability'; was the most straightforward and user friendly approach. Additionally, to ensure validity against what the atmosphere actually 'sees', a simple age-dependant correction for awarded offsets in the event of re-emission of stocks is developed. The incremental weighting of offsets allows aggregation to full credits across space to produce a saleable credit with no attendant liabilities to the purchaser and reasonable liability for the seller. From the synthesis of the preceding chapters a SOC auditing protocol is proposed in Chapter 7. Its applicability to the land sector is defined and the strengths and weakness of its support is discussed. Finally, numerous avenues for future research for both academic interest and to improve the system are suggested.|
|Access Level:||Access is restricted to staff and students of the University of Sydney . UniKey credentials are required. Non university access may be obtained by visiting the University of Sydney Library.|
|Rights and Permissions:||The author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.|
|Type of Work:||PhD Doctorate|
|Type of Publication:||Doctor of Philosophy Ph.D.|
|Appears in Collections:||Sydney Digital Theses (University of Sydney Access only)|
|Ichsani_Wheeler_PhD_thesis_UNISYD.pdf||Thesis||6.51 MB||Adobe PDF|
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