Tree mortality and carbon emission as a function of wildfire severity in south-eastern Australian temperate forests.

Disturbance trends over recent decades indicate that climate change is resulting in increased fire severity and extent in Australia's temperate Eucalyptus forests. As disturbance cycles become shorter and more severe, empirical measurements are required to identify potential change in forest carbon (C) stock and emissions. However, such estimates are rare in the literature. The 2019-2020 wildfires burnt through 6 to 7 million ha of mainly temperate open Eucalyptus forest in south-east Australia, with top down emission estimates ranging from 97 to 130 tonnes CO2 ha-1. Study sites that had been assessed for all aboveground C pools prior to the wildfires, were burnt in January 2020 by wildfire that varied in severity. Here we quantify the impact of high and low/moderate fire severities on tree mortality, C loss and C redistribution and assess implications for future C storage in these temperate Eucalyptus forests. Higher fire severity resulted in greater overstorey tree mortality but not understorey or loss of dead standing trees than in low/moderate severity fires. High severity fires combusted almost twice as much C from live trees (42 Mg C ha-1) as low/moderate severity fires (25 Mg C ha-1), while C loss from dead standing trees was similar among fire severity classes (average 17 Mg C ha-1). Total aboveground C lost across study sites was 42 Mg C ha-1 for high and 47 Mg C ha-1 for low/moderate severity, with an average of 45 Mg C ha-1 equivalent to 15 % (high severity) and 14 % (low/moderate severity) of AGC. Extrapolating our findings to other tall to medium open Eucalyptus forests across Victoria revealed that 37.33 ± 12.25 Tg C (mean ± s.e.) or 152 ± 50 Mg CO2 ha-1 was lost to the atmosphere from the 0.9 million ha of these productive forests, equating to about 20 % of Australia's total net annual emissions.

Future climate impacts on forest growth and implications for carbon sequestration through reforestation in southeast Australia.

Reforestation is identified as one of the key nature-based solutions to deliver carbon dioxide removal, which will be required to achieve the net zero ambition of the Paris Agreement. However, the potential for sequestration through reforestation is uncertain because climate change is expected to affect the drivers of forest growth. This study used the process-based 3-PG model to investigate the effects of climate change on development of above-ground biomass (AGB), as an indicator of forest growth, in regenerating native forests in southeast Australia. We investigated how changing climate affects AGB, by combining historical data and future climate projections based on 25 global climate models (GCMs) for the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways. We found that the ensemble means of 25 GCMs indicated an increase in temperature with large variations in projected rainfall. When these changes were applied in 3-PG, we found an increase in the simulated AGB by as much as 25% under a moderate emission scenario. This estimate rose to 51% under a high emission scenario by the end of the 21st century across nine selected sites in southeast Australia. However, when CO2 response was excluded, we found a large decrease in AGB at the nine sites. Our modelling results showed that the modelled response to elevated atmospheric CO2 (the CO2 fertilization effect) was largely responsible for the simulated increase of AGB (%). We found that the estimates of future changes in the AGB were subject to uncertainties originating from climate projections, future emission scenarios, and the assumed response to CO2 fertilization. Such modelling simulation improves understanding of possible climate change impacts on forest growth and the inherent uncertainties in estimating mitigation potential through reforestation, with implications for climate policy in Australia.

Mapping carbon accumulation potential from global natural forest regrowth.

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy.

Risks to carbon dynamics in semi-arid woodlands of eastern Australia under current and future climates.

Extreme disturbance events, such as wildfire and drought, have large impacts on carbon storage and sequestration of forests and woodlands globally. Here, we present a modelling approach that assesses the relative impact of disturbances on carbon storage and sequestration, and how this will alter under climate change. Our case study is semi-arid Australia where large areas of land are managed to offset over 122 million tonnes of anthropogenic carbon emissions over a 100-year period. These carbon offsets include mature vegetation that has been protected from clearing and regenerating vegetation on degraded agricultural land. We use a Bayesian Network model to combine multiple probabilistic models of the risk posed by fire, drought, grazing and recruitment failure to carbon dynamics. The model is parameterised from a review of relevant literature and additional quantitative analyses presented here. We found that the risk of vegetation becoming a net source of carbon due to a mortality event, or failing to realise maximum sequestration potential, through recruitment failure in regenerating vegetation, was primarily a function of rainfall in this semi-arid environment. However, the relative size of an emissions event varied across vegetation communities depending on plant attributes, specifically resprouting capacity. Modelled climate change effects were variable, depending on the climate change projection used. Under 'best-case' or 'most-likely' climate scenarios for 2050, similar or increased projections of mean annual precipitation, associated with a build-up of fuel, were expected to drive an increase in fire activity (a 40-160% increase), but a decrease in drought (a 20-35% decrease). Under a 'worst-case' climate scenario, fire activity was expected to decline (a 37% decrease), but drought conditions remain similar (a 5% decrease). These projected changes to the frequency of drought and fire increase the risk that vegetation used for carbon offsetting will fail to provide anticipated amounts of carbon abatement over their lifetime.

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.

Measurements of stem diameter: implications for individual- and stand-level errors.

Stem diameter is one of the most common measurements made to assess the growth of woody vegetation, and the commercial and environmental benefits that it provides (e.g. wood or biomass products, carbon sequestration, landscape remediation). Yet inconsistency in its measurement is a continuing source of error in estimates of stand-scale measures such as basal area, biomass, and volume. Here we assessed errors in stem diameter measurement through repeated measurements of individual trees and shrubs of varying size and form (i.e. single- and multi-stemmed) across a range of contrasting stands, from complex mixed-species plantings to commercial single-species plantations. We compared a standard diameter tape with a Stepped Diameter Gauge (SDG) for time efficiency and measurement error. Measurement errors in diameter were slightly (but significantly) influenced by size and form of the tree or shrub, and stem height at which the measurement was made. Compared to standard tape measurement, the mean systematic error with SDG measurement was only -0.17 cm, but varied between -0.10 and -0.52 cm. Similarly, random error was relatively large, with standard deviations (and percentage coefficients of variation) averaging only 0.36 cm (and 3.8%), but varying between 0.14 and 0.61 cm (and 1.9 and 7.1%). However, at the stand scale, sampling errors (i.e. how well individual trees or shrubs selected for measurement of diameter represented the true stand population in terms of the average and distribution of diameter) generally had at least a tenfold greater influence on random errors in basal area estimates than errors in diameter measurements. This supports the use of diameter measurement tools that have high efficiency, such as the SDG. Use of the SDG almost halved the time required for measurements compared to the diameter tape. Based on these findings, recommendations include the following: (i) use of a tape to maximise accuracy when developing allometric models, or when monitoring relatively small changes in permanent sample plots (e.g. National Forest Inventories), noting that care is required in irregular-shaped, large-single-stemmed individuals, and (ii) use of a SDG to maximise efficiency when using inventory methods to assess basal area, and hence biomass or wood volume, at the stand scale (i.e. in studies of impacts of management or site quality) where there are budgetary constraints, noting the importance of sufficient sample sizes to ensure that the population sampled represents the true population.

Rapid prediction of particulate, humus and resistant fractions of soil organic carbon in reforested lands using infrared spectroscopy.

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 13C 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 (R2 > 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.

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

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).

Reforestation with native mixed-species plantings in a temperate continental climate effectively sequesters and stabilizes carbon within decades.

Reforestation has large potential for mitigating climate change through carbon sequestration. Native mixed-species plantings have a higher potential to reverse biodiversity loss than do plantations of production species, but there are few data on their capacity to store carbon. A chronosequence (5-45 years) of 36 native mixed-species plantings, paired with adjacent pastures, was measured to investigate changes to stocks among C pools following reforestation of agricultural land in the medium rainfall zone (400-800 mm yr(-1)) of temperate Australia. These mixed-species plantings accumulated 3.09 ± 0.85 t C ha(-1) yr(-1) in aboveground biomass and 0.18 ± 0.05 t C ha(-1) yr(-1) in plant litter, reaching amounts comparable to those measured in remnant woodlands by 20 years and 36 years after reforestation respectively. Soil C was slower to increase, with increases seen only after 45 years, at which time stocks had not reached the amounts found in remnant woodlands. The amount of trees (tree density and basal area) was positively associated with the accumulation of carbon in aboveground biomass and litter. In contrast, changes to soil C were most strongly related to the productivity of the location (a forest productivity index and soil N content in the adjacent pasture). At 30 years, native mixed-species plantings had increased the stability of soil C stocks, with higher amounts of recalcitrant C and higher C:N ratios than their adjacent pastures. Reforestation with native mixed-species plantings did not significantly change the availability of macronutrients (N, K, Ca, Mg, P, and S) or micronutrients (Fe, B, Mn, Zn, and Cu), content of plant toxins (Al, Si), acidity, or salinity (Na, electrical conductivity) in the soil. In this medium rainfall area, native mixed-species plantings provided comparable rates of C sequestration to local production species, with the probable additional benefit of providing better quality habitat for native biota. These results demonstrate that reforestation using native mixed-species plantings is an effective alternative for carbon sequestration to standard monocultures of production species in medium rainfall areas of temperate continental climates, where they can effectively store C, convert C into stable pools and provide greater benefits for biodiversity.

Electrical capacitance as a rapid and non-invasive indicator of root length.

Measurement of tree root systems by conventional methods is a Herculean task. The electrical capacitance method offers a rapid and non-destructive alternative, but it has largely been restricted to herbaceous species. The Dalton Model has been the main concept for understanding equivalent root circuitry; it proposed that roots were cylindrical capacitors with epidermis and xylem being the external and internal electrodes. Capacitance (C) therefore varied in proportion to root surface area (A), mass (M), length (L) and relative permittivity of the plant tissue ε(r). We used the capacitance method on forest and plantation trees (13 to circa 100 y.o.) in situ to test hypotheses derived from implicit assumptions about tree-root-soil circuitry. We concluded: C was not confounded by intermingled root systems; C was strongly related to diameter at breast height (DBH); C was less strongly related to DBH for multiple species at the same site; and C was a poor indicator of DBH, M and L across species, ages and sites. We proposed that ε(r) was proportional to root tissue density ρ and fitted a model with P < 0.05 and R(2) = 0.70 when the three immature (13 y.o.) trees were excluded. There was no significant difference (P = 0.28) between the parameters of the tree model (excluding the immature trees) and one of the same form fitted to data from bean (Vicia faba L.; R(2) = 0.55). Together, the data sets suggested (R(2) = 0.94; n = 26) that there may exist a general relationship of this form applied over two orders of magnitude of L.

A comment on the quantitative significance of aerobic methane release by plants.

A recent study by Keppler et al. (2006; Nature 439, 187-191) demonstrated CH4 emission from living and dead plant tissues under aerobic conditions. This work included some calculations to extrapolate the findings from the laboratory to the global scale and led various commentators to question the value of planting trees as a greenhouse mitigation option. The experimental work of Keppler et al. (2006) appears to be largely sound, although some concerns remain about the quantification of emission rates. However, whilst accepting their basic findings, we are critical of the method used for extrapolating results to a global scale. Using the same basic information, we present alternative calculations to estimate global aerobic plant CH4 emissions as 10-60 Mt CH4 year-1. This estimate is much smaller than the 62-236 Mt CH4 year-1 reported in the original study and can be more readily reconciled within the uncertainties in the established sources and sinks in the global CH4 budget. We also assessed their findings in terms of their possible relevance for planting trees as a greenhouse mitigation option. We conclude that consideration of aerobic CH4 emissions from plants would reduce the benefit of planting trees by between 0 and 4.4%. Hence, any offset from CH4 emission is small in comparison to the significant benefit from carbon sequestration. However, much critical information is still lacking about aerobic CH4 emission from plants. For example, we do not yet know the underlying mechanism for aerobic CH4 emission, how CH4 emissions change with light, temperature and the physiological state of leaves, whether emissions change over time under constant conditions, whether they are related to photosynthesis and how they relate to the chemical composition of biomass. Therefore, the present calculations must be seen as a preliminary attempt to assess the global significance from a basis of limited information and are likely to be revised as further information becomes available.