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• 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]

To combat global warming and biodiversity loss, we require effective forest restoration that encourages recovery of species diversity and ecosystem function to deliver essential ecosystem services, such as biomass accumulation. Further, understanding how and where to undertake restoration to achieve carbon sequestration and biodiversity conservation would provide an opportunity to finance ecosystem restoration under carbon markets. We surveyed 30 native mixed‐species plantings in subtropical forests and woodlands in Australia and used structural equation modeling to determine vegetation, soil, and climate variables most likely driving aboveground biomass accrual and bird richness and investigate the relationships between plant diversity, aboveground biomass accrual, and bird diversity. We focussed on woodland and forest‐dependent birds, and functional groups at risk of decline (insectivorous, understorey‐nesting, and small‐bodied birds). We found that mean moisture availability strongly limits aboveground biomass accrual and bird richness in restoration plantings, indicating potential synergies in choosing sites for carbon and biodiversity purposes. Counter to theory, woody plant richness was a poor direct predictor of aboveground biomass accrual, but was indirectly related via significant, positive effects of stand density. We also found no direct relationship between aboveground biomass accrual and bird richness, likely because of the strong effects of moisture availability on both variables. Instead, moisture availability and patch size strongly and positively influenced the richness of woodland and forest‐dependent birds. For understorey‐nesting birds, however, shrub cover and patch size predicted richness. Stand age or area of native vegetation surrounding the patch did not influence bird richness. Our results suggest that in subtropical biomes, planting larger patches to higher densities, ideally using a diversity of trees and shrubs (characteristics of ecological plantings) in more mesic locations will enhance the provision of carbon and biodiversity cobenefits. Further, ecological plantings will aid the rapid recovery of woodland and forest bird richness, with comparable aboveground biomass accrual to less diverse forestry plantations. [ABSTRACT FROM AUTHOR]

Aim: Understanding biodiversity–ecosystem function (BEF) relationships in forest systems is crucial for effective forest management and restoration, yet testing these relationships is often limited by biased diversity patterns in forestry plantings (biased towards commercially valuable species) and uncontrollable diversity in mature natural forests. Multispecies reforestation plantings present a valuable opportunity to investigate BEF relationships in woody systems, especially across large environmental gradients. Location: Reforestation plantings across the arable region of Australia. Time period: 1951–2012. Major taxa studied: Three hundred and sixty‐four woody plant species. Methods: We examined relationships between productivity and diversity using inventory data from 977 plots in 386 multispecies reforestation plantings. Diversity was estimated using observed species richness and three functional diversity indices calculated from four functional traits: specific leaf area, wood density, seed mass and maximum attainable height. We modelled how plot‐level biomass accumulation (a productivity proxy) correlated with these diversity indices, as well as age since planting, plant density and three environmental variables: solar radiation, moisture availability and soil sand content. These models were fitted across Australia and, separately, within eight groups of plantings with similar environmental conditions. Results: We found no correlation between diversity and productivity, regardless of the diversity metric or spatial scale used (continent‐wide or within environment groups). Instead, productivity was best explained by local environmental conditions and plant density. Main conclusions: A positive relationship between diversity and productivity was not evident in planted forests across a wide range of Australian woodland and forest systems, at least in the first few decades of growth. Our findings suggest that the positive relationship between diversity and productivity commonly reported in experimental settings should not be assumed for all systems and conditions. [ABSTRACT FROM AUTHOR]