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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. It is also used by landowners, companies and researchers, and is therefore regularly applied at local to continental scales. FullCAM is a stand level model with daily, monthly or annual temporal resolutions, depending on the users' preference. FullCAM has been developed over the past 20 years, however, no studies have reviewed and described the current structure, parameters, calibration, and uses of FullCAM, which was the objective of this study. We also discuss the potential for further developments that could improve FullCAM's ability to model responses to disturbances and climate, while also increasing its local accuracy. • FullCAM simulates carbon follows between live biomass, standing dead, debris and soil. • FullCAM is used at local, regional and continental scales, and daily, monthly or annual steps. • FullCAM is used for native forests, woodlands and savannas, as well as plantations. [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]

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 (0–30 cm) 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 (> 600 mm year − 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. [ABSTRACT FROM AUTHOR]

Reforestation of agricultural land with mixed-species environmental plantings (native trees and shrubs) can contribute to mitigation of climate change through sequestration of carbon. Although soil carbon sequestration following reforestation has been investigated at site- and regional-scales, there are few studies across regions where the impact of a broad range of site conditions and management practices can be assessed. We collated new and existing data on soil organic carbon (SOC, 0–30 cm depth, N = 117 sites) and litter ( N = 106 sites) under mixed-species plantings and an agricultural pair or baseline across southern and eastern Australia. Sites covered a range of previous land uses, initial SOC stocks, climatic conditions and management types. Differences in total SOC stocks following reforestation were significant at 52% of sites, with a mean rate of increase of 0.57 ± 0.06 Mg C ha −1 y −1 . Increases were largely in the particulate fraction, which increased significantly at 46% of sites compared with increases at 27% of sites for the humus fraction. Although relative increase was highest in the particulate fraction, the humus fraction was the largest proportion of total SOC and so absolute differences in both fractions were similar. Accumulation rates of carbon in litter were 0.39 ± 0.02 Mg C ha −1 y −1 , increasing the total (soil + litter) annual rate of carbon sequestration by 68%. Previously-cropped sites accumulated more SOC than previously-grazed sites. The explained variance differed widely among empirical models of differences in SOC stocks following reforestation according to SOC fraction and depth for previously-grazed ( R 2 = 0.18–0.51) and previously-cropped ( R 2 = 0.14–0.60) sites. For previously-grazed sites, differences in SOC following reforestation were negatively related to total SOC in the pasture. By comparison, for previously-cropped sites, differences in SOC were positively related to mean annual rainfall. This improved broad-scale understanding of the magnitude and predictors of changes in stocks of soil and litter C following reforestation is valuable for the development of policy on carbon markets and the establishment of future mixed-species environmental plantings. [ABSTRACT FROM AUTHOR]

• A systematic review assessed ecosystem services from trees in grazed dairy enterprises. • Thirty key causal relationships (woody system ≫ mechanism ≫ outcome) were identified. • Linkages between on-farm woody systems and ecosystem services were largely positive. • Results provide strong support for the internal benefits of on-farm tree systems. Intensification of the dairy industry globally, combined with a changing climate, has placed increased pressure on natural capital assets (and the flow of ecosystem services) on farms. Agroforestry is widely promoted as an intervention to address these issues. While some benefits of integrating trees on farms, such as carbon sequestration and biodiversity, are reasonably well known, less is known about other potential benefits, such as on-farm production. Understanding and quantifying these benefits would inform farm planning and decision-making. We used a systematic review approach to analyse the evidence base for biophysical ecosystem services from woody systems (including shelterbelts, riparian plantings, plantations, pasture trees, silvopasture and remnant native vegetation) provided to grazed dairy enterprises. We identified 83 publications containing 123 records that fit our review criteria of reporting on biophysical ecosystem services from woody systems on dairy farms relative to a grazed pasture comparison. For each relationship between a woody system and ecosystem service, we assessed the level of support, strength and predominant direction of evidence, and summarised the causal relationships (woody system ≫ mechanism ≫ outcome). Shelterbelts and riparian plantings were the most commonly reported woody systems. Linkages between woody systems and ecosystem services were largely positive, with the types of services provided and their importance differing among systems. Mean evaluation scores for the strength of the evidence were moderate to strong. However, the number of records for each relationship was often low. Consequently, only eight of the 30 causal pathways identified had high confidence; a further 14 had medium confidence indicating that these have good potential to deliver benefits but warrant further work. Although the evidence here was largely qualitative, our results provide strong support for the internal benefits that natural capital assets, such as on-farm woody systems, can provide to the productivity and resilience of grazed dairy enterprises. [ABSTRACT FROM AUTHOR]

The clearing of natural vegetation for agriculture has reduced the capacity of natural systems to provide ecosystem functions. Ecological restoration can restore desirable ecosystem functions, such as creating habitat for animal conservation and carbon sequestration as woody biomass. In order to maintain these beneficial ecosystem functions, restoration projects need to mature into self‐perpetuating communities. Here we compared the ecological attributes of two types of restoration, "active" tree plantings with "passive" natural forest regeneration ("natural regrowth") to existing remnant vegetation in a cleared agricultural landscape. Specifically, we measured differences between forest categories in factors that may predict future restoration failure or ecosystem collapse: aboveground plant biomass and biomass accrual over time (for regrowing stands), plant density and size class distributions, and diversity of functional groups based on seed dispersal and growth strategy traits. We found that natural regrowth and planted forests were similar in many ecological characteristics, including biomass accrual. Despite this, planted stands contained fewer tree recruit and shrub individuals, which may be due to limited recruitment in plantings. If this continues, these forests may be at risk of collapsing into nonforest states after mature trees senesce. Lower shrub density and richness of mid‐story trees may lead to lower structural complexity in planting plots, and alongside lower richness of fleshy‐fruited plant species may reduce animal resources and animal use of the restored stand. In our study region, natural regrowth may result in restored woodland communities with greater conservation and carbon mitigation value. [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]

The article discusses an analysis of global patterns of variation in an individual tree. It examines the allocation of carbon acquired by plants from the atmosphere, studies with contradictory results regarding the causes of stand-level variation, and findings on correlation or interaction between tree size and climatic water deficit.

Reforestation of agricultural lands with mixed-species environmental plantings can effectively sequester C. While accurate and efficient methods for predicting soil organic C content and composition have recently been developed for soils under agricultural land uses, such methods under forested land uses are currently lacking. This study aimed to develop a method using infrared spectroscopy for accurately predicting total organic C (TOC) and its fractions (particulate, POC; humus, HOC; and resistant, ROC organic C) in soils under environmental plantings. Soils were collected from 117 paired agricultural-reforestation sites across Australia. TOC fractions were determined in a subset of 38 reforested soils using physical fractionation by automated wet-sieving and 13 C nuclear magnetic resonance (NMR) spectroscopy. Mid- and near-infrared spectra (MNIRS, 6000–450 cm −1 ) were acquired from finely-ground soils from environmental plantings and agricultural land. Satisfactory prediction models based on MNIRS and partial least squares regression (PLSR) were developed for TOC and its fractions. Leave-one-out cross-validations of MNIRS-PLSR models indicated accurate predictions ( R 2 > 0.90, negligible bias, ratio of performance to deviation > 3) and fraction-specific functional group contributions to beta coefficients in the models. TOC and its fractions were predicted using the cross-validated models and soil spectra for 3109 reforested and agricultural soils. The reliability of predictions determined using k -nearest neighbour score distance indicated that >80% of predictions were within the satisfactory inlier limit. The study demonstrated the utility of infrared spectroscopy (MNIRS-PLSR) to rapidly and economically determine TOC and its fractions and thereby accurately describe the effects of land use change such as reforestation on agricultural soils. [ABSTRACT FROM AUTHOR]

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha−1). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). [ABSTRACT FROM AUTHOR]