Phil Polglase

Calibration of the RothC model to turnover of soil carbon under eucalypts and pines

Abstract The FullCAM model was developed for full carbon accounting in agriculture and forests at project and national scales. For forest systems, FullCAM links the empirical CAMFor model to models of tree growth (3PG), litter decomposition (GENDEC), and soil carbon turnover (RothC). Our objective was to calibrate RothC within the FullCAM framework using 2 long-term forestry experiments where productivity had been manipulated and archived and new soil samples were available for analysis of carbon within the various pools described by RothC. Inputs of carbon to soil at these trials were estimated by calibrating FullCAM to temporal data on above-ground growth, litterfall, and accumulation of litter. Two alternative submodels are available in FullCAM (CAMFor and GENDEC) for predicting decomposition of litter, and thus the input of carbon into the soil. Calibration of RothC was most sensitive to the partitioning of carbon during decomposition of debris between that lost as CO2 and that transferred to soil. Turnover of soil carbon was best simulated when the proportion of carbon lost to CO2 from relatively labile pools of debris was 77% (when simulated by CAMFor) and 95% (when simulated by GENDEC), whereas resistant pools of debris lost about 40% to CO2 during decomposition. Although rates of decomposition of pools of soil carbon were originally developed in RothC for agricultural soils, these constants were found to be also suitable for soils under plantation systems.

Biodiverse Planting for Carbon and Biodiversity on Indigenous Land

Carbon offset mechanisms have been established to mitigate climate change through changes in land management. Regulatory frameworks enable landowners and managers to generate saleable carbon credits on domestic and international markets. Identifying and managing the associated co-benefits and dis-benefits involved in the adoption of carbon offset projects is important for the projects to contribute to the broader goal of sustainable development and the provision of benefits to the local communities. So far it has been unclear how Indigenous communities can benefit from such initiatives. We provide a spatial analysis of the carbon and biodiversity potential of one offset method, planting biodiverse native vegetation, on Indigenous land across Australia. We discover significant potential for opportunities for Indigenous communities to achieve carbon sequestration and biodiversity goals through biodiverse plantings, largely in southern and eastern Australia, but the economic feasibility of these projects depend on carbon market assumptions. Our national scale cost-effectiveness analysis is critical to enable Indigenous communities to maximise the benefits available to them through participation in carbon offset schemes.

Comment on "Australian wood heaters currently increase global warming and health costs"

The recent article by Robinson (2011) “Australian wood heaters currently increase global warming and health costs” compared emissions of greenhouse gases sourced from firewood with heating associated with fossil fuels. The paper challenged the commonly accepted view that because wood heaters use a renewable resource they are greenhouse neutral or potentially greenhouse positive if substitution for fossil fuel is included. Robinson (2011) draws conclusions to the contrary stating that “Claims that wood heating is greenhouse neutral are incorrect”, “...global warming from methane emissions of a wood heater in the living room... are similar to carbon dioxide (CO2) emissions from heating an entire 160 m 2 house with gas’ and that, “...wood heating could be considered to cause more than 10 times as much global warming as gas or reverse cycle–air conditioning”. Below we show these conclusions are incorrect, primarily due to an incomplete life cycle assessment of biomass–based feedstocks. Assumptions on the atmospheric impact of these emissions are also critical to the calculated result.

Using measured stocks of biomass and litter carbon to constrain modelled estimates of sequestration of soil organic carbon under contrasting mixed-species environmental plantings

Reforestation of agricultural land with mixed-species environmental plantings of native trees and shrubs contributes to abatement of greenhouse gas emissions through sequestration of carbon, and to landscape remediation and biodiversity enhancement. Although accumulation of carbon in biomass is relatively well understood, less is known about associated changes in soil organic carbon (SOC) following different types of reforestation. Direct measurement of SOC may not be cost effective where rates of SOC sequestration are relatively small and/or highly spatially-variable, thereby requiring intensive sampling. Hence, our objective was to develop a verified modelling approach for determining changes in SOC to facilitate the inclusion of SOC in the carbon accounts of reforestation projects. We measured carbon stocks of biomass, litter and SOC (0-30cm) in 125 environmental plantings (often paired to adjacent agricultural sites), representing sites of varying productivity across the Australian continent. 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 SOC and its fractions. Uncertainties in both measured and modelled results meant that efficiencies of prediction of SOC across the 125 contrasting plantings were only moderate, at 39-68%. Data-informed modelling nonetheless improved confidence in outputs from scenario analyses, confirming that: (i) reforestation on agricultural land highly depleted in SOC (i.e. previously under cropping) had the highest capacity to sequester SOC, particularly where rainfall was relatively high (>600mmyear-1), and; (ii) decreased planting width and increased stand density and the proportion of eucalypts enhanced rates of SOC sequestration. These results improve confidence in predictions of SOC following environmental reforestation under varying conditions. The calibrated model will be a useful tool for informing land managers and policy makers seeking to understand the dynamics of SOC following such reforestation.