37 Accurate quantification of below-ground biomass (BGB) of woody vegetation is critical to 38 understanding ecosystem function and potential for climate change mitigation from sequestration 39 of biomass carbon. We compiled 2 054 measurements of individual tree and shrub biomass from 40 across a broad range of ecoregions (arid shrublands to tropical rainforests) to develop allometric 41 models for prediction of BGB. We found that the relationship between BGB and stem diameter 42 was generic, with a simple power-law model having a BGB prediction efficiency of 72–93% for 43 four broad plant functional types: (i) shrubs and Acacia trees, (ii) multi-stemmed mallee eucalypts, 44 (iii) other trees of relatively high wood density, and; (iv) a species of relatively low wood density, 45 Pinus radiata. There was little improvement in accuracy of model prediction by including 46 variables (e.g. climatic characteristics, stand age or management) in addition to stem diameter 47 alone. We further assessed the generality of the plant functional type models across 11 contrasting 48 stands where data from whole-plot excavation of BGB were available. The efficiency of model 49 prediction of stand-based BGB was 93%, with a mean absolute prediction error of only 6.5%, and 50 with no improvements in validation results when species-specific models were applied. Given the 51 high prediction performance of the generalised models, we suggest that additional costs associated 52 with the development of new species-specific models for estimating BGB are only warranted when 53 gains in accuracy of stand-based predictions are justifiable, such as for a high-biomass stand 54 comprising only one or two dominant species. However, generic models based on plant functional 55 type should not be applied where stands are dominated by species that are unusual in their 56 morphology and unlikely to conform to the generalised plant functional group models. 57 58 59 Generic allometrics 3 Introduction 60 Both above-ground biomass (AGB) and below-ground biomass (BGB) contribute to the 61 woody vegetation sink within the global carbon budget (Le Quéré et al., 2015). Climate change 62 may result in shifts in the ratio of tree BGB to AGB (e.g. via changes in water deficit that affect 63 partitioning or the size distribution of trees), with far-reaching consequences for the global carbon 64 budget (Ledo et al. 2018). However, BGB cannot be quantified using remote sensing metrics as 65 has been done for the AGB component (Haverd et al., 2013; Mitchard et al., 2013; Chen et al., 66 2015). Therefore, the development of models to explain BGB is critical to informing predictions 67 of biomass yields or biomass carbon stocks (Richards & Evans 2004). 68 BGB can be estimated from AGB at either an individualor stand-level through the use of 69 root-to-shoot ratios (BGB:AGB, Ledo et al., 2018), and this approach has merit when broad-scale 70 AGB estimates are obtained via remote sensing products rather than via field-based assessments. 71 However, this approach has limitations. Estimating BGB based on predictions of AGB are subject 72 to relatively high uncertainties; for example, mean absolute prediction error of AGB was 15–39% 73 and 13% at the individualand stand-level, respectively, for plant functional types across the 74 Australian continent (Paul et al., 2016). In contrast, if BGB of an individual is predicted by 75 applying verified allometric models to field measurement of stem diameter (D), the uncertainty is 76 likely to be much lower because errors in D estimation are relatively small (e.g. 2–7%, Paul et al., 77 2017a). Moreover, BGB:AGB defaults obtained from the average of multiple stands of a given 78 ecosystem (Mokany et al., 2006) do not explicitly account for variations in stand density and the 79 mix of species; both of which influence BGB (Westman & Rogers, 1977; Bernardo et al., 1998; 80 Ritson & Sochacki, 2003; Xue et al., 2011; Gonzalez et al., 2013). Stand-based estimates of BGB, 81 resulting from application of allometric models with D as a predictor variable to each individual 82 within a stand, may inherently account for stand density and species-mix. 83 When developing allometric models for prediction of BGB of woody plants, it is unclear 84 to what extent data should be pooled or separated according to their morphological, phylogenetic 85 Generic allometrics 4 and/or phenological characteristics; variation often encapsulated by classification of species into 86 plant functional types. It is also unclear whether the inclusion of stand characteristics or bioclimatic 87 variables improves the performance of BGB allometric models above that attained when using D 88 alone. A true test of the accuracy of such models is a direct validation at the stand-level by 89 comparing allometry-predicted BGB against that measured through whole-plot excavation. 90 Although such stand-level validation has been undertaken previously by Paul et al. (2014) for 91 young plantings in southern Australia, no such validation has been undertaken for more broadly92 applicable BGB allometric models derived from root data sampled from both planted and natural 93 systems, and across a range of stand ages and ecosystem types. 94 Australia provides a good case study for testing generalised allometric models given its 95 long history of research contributions to BGB data sets (e.g. Forrest, 1969; Baldwin & Stewart, 96 1987; Applegate, 1982) spanning a broad range of ecoregions (i.e. arid shrublands to tropical 97 rainforests) with plant functional types ranging from shrubs and short multi-stemmed trees to some 98 of the largest trees in the world (Sillett et al., 2015; Specht & Specht, 2002, Specht & Specht, 99 2013). Improving the assessment of Australia’s vegetation carbon sink is of global importance as 100 the high inter-annual variability that is characteristic of the global vegetation sink is in large part 101 due to variability in the carbon capture of the semi-arid ecosystems of Australia (Houghton et al., 102 2012; Poulter et al., 2014; Ballantyne et al., 2015). 103 Here we collated destructively-measured BGB datasets from individual trees and shrubs 104 sampled from a broad range of stands from differing climatic regions of Australia, including those 105 in natural ecosystems or otherwise established through human intervention (i.e. planted). We then 106 analysed this data set to assess whether D-based allometric models of BGB were improved: (i) 107 when based on species rather than broader categories such as plant functional groups; and (ii) by 108 the inclusion of stand characteristics (age and management) or climatic variables. Our objectives 109 were firstly to recommend the most appropriate allometric model(s) for estimating BGB in 110 ecosystems across the Australian continent, and secondly to quantify the accuracy of the 111 Generic allometrics 5 recommended model(s) when tested against direct measurements of stand-level BGB obtained 112 using whole-plot excavation across a range of contrasting sites. The recommended models for 113 predicting BGB were applied together with those previously recommended for prediction of AGB 114 (Paul et al., 2016) to provide estimates of BGB:AGB ratios for plant functional types of differing 115 allometry. 116 117

The Soil Wealth and Integrated Crop Protection projects have struck a chord with growers and advisors alike, filling a need in the provision of practical and useful information in a new way for the Australian vegetable industry. The projects have developed innovative approaches to deliver information on soil, pest and disease management to growers. Methods focus on engaging directly with growers and advisors; demonstrating new innovations on the farms of leading growers; social media (Twitter, Facebook and YouTube) and webinars. More conventional methods have also been used, including workshops, farm walks, fact sheets, videos and a central website. This paper discusses the key success factors of the projects in engaging with the target audience and promoting the adoption of research and development drawing on evidence collected through primary data collection and research.

Plants acquire carbon from the atmosphere and allocate it among different organs in response to environmental and developmental constraints (Hodge, 2004; Poorter et al., 2012). One classic example of differential allocation is the relative investment into aboveground vs belowground organs, captured by the root : shoot ratio (R : S; Cairns et al., 1997). Optimal partitioning theory suggests that plants allocate more resources to the organ that acquires the most limiting resource (Reynolds & Thornley, 1982; Johnson & Thornley, 1987). Accordingly, plants would allocate more carbon to roots if the limiting resources are belowground, that is water and nutrients, and would allocate more carbon aboveground when the limiting resource is light or CO2. This theory has been supported by recent research showing that the R : S of an individual plant is modulated by environmental factors (Poorter et al., 2012; Fatichi et al., 2014). However, understanding the mechanisms underpinning plant allocation and its response to environmental factors is an active field of research (Delpierre et al., 2016; Paul et al., 2016), and it is likely that plant size and species composition have an effect on R : S. Accounting for these sources of variation is an important challenge for modelling (Franklin et al., 2012). The hypothesis that aridity controls R : S is supported by experiments on tree seedlings, which report higher R : S values in response to simulated drought treatments (Lambers et al., 2008; Poorter et al., 2012). This hypothesis is also consistent with the observation that trees in arid environments tend to allocate proportionally more biomass to roots, which may improve access to soil water (Nepstad et al., 1994) and act as a protected reservoir of stored carbohydrates to facilitate rapid regrowth following disturbances such as fire that are common in arid regions (Ryan et al., 2011). However, previous meta-analyses have led to contradictory results regarding the causes of stand-level variation in R : S. Mokany et al. (2006) found precipitation was the main control on R : S values; by contrast, Reich et al. (2014) suggested that temperature was the main driver, with R : S largely unrelated to aridity. Yet, previous studies used either data from soil cores (Reich et al., 2014), or a limited amount of data on root biomass from individually excavated trees (Cairns et al., 1997; Mokany et al., 2006), making it impossible to explore individual patterns of R : S variation in response to tree size and environmental conditions. Using the largest global dataset of its kind, here we provide the first analysis of global patterns of variation in individual-tree R : S. We hypothesized that individual R : S varies with environmental conditions, namely climate and management type, and is also determined by intrinsic factors, namely tree size and species. We also aimed to rank the relative contribution of these factors to R : S variation. The global dataset of individual R : S values was compiled from whole-tree harvesting studies (Supporting Information Notes S1 and Fig. S1), the BAAD among them (Falster et al., 2015) [correction added after online publication 23 October 2017: the reference Falster et al. (2015) has been inserted here and in the References section]. The dataset encompasses 409 sites and a total of 3416 trees of 212 species with oven dry weight measurements of both aboveground and belowground biomass, from which we computed the R : S (Fig. 1). The destructively-sampled trees included in the database had diameter-at-breast height (DBH) values ranging from 0.6 to 128 cm (more details in Fig. S1). We fitted linear regression models, using the natural logarithm of R : S, loge(R : S), as the response variable to reduce heteroscedasticity. The explanatory variables that we analysed were tree size, tree species, wood specific gravity, phenology (evergreen, deciduous), and clade (gymnosperm, dicot angiosperm or monocot angiosperm, i.e. palm). Additional factors in the models were bioclimatic region (tropical dry, tropical wet, non-tropical), temperature, precipitation, whether the tree was growing in a natural forest or plantation, and climatic water deficit (MWD, for mean water deficit, in mm yr−1), which is the deficit between monthly rainfall and potential evapotranspiration (Aragão et al., 2007). Additional details about the explanatory variables and methods are in Methods S1. We carried out a stepwise regression analysis, retaining the variables significant at 95%, and selected the best model based on Akaike information criterion (AIC) values. The conditional and marginal variances, R 2 GLMM values, for the final model and variances for each component were calculated using the method proposed by Nakagawa & Schielzeth (2013). All statistical analyses were conducted in R (code reproduced in Notes S2). where DBH is in centimetres, MWD is in millimetres, plantation is a binary 1/0 dummy variable and Species is a species specific random term. The most important factor explaining global tree R : S values was tree size: DBH and DBH2 jointly accounted for 33% of the variance. Mean R : S values decreased with tree size for trees with DBH up to 1 m. For instance, saplings < 2 cm DBH had a mean R : S of 0.43, while trees with DBH 25–30 cm had a value of 0.28. For trees with DBH larger than 1 m, R : S did not vary much (but the sample size for these was small, only 42 trees). Saplings and small trees presumably invest more biomass belowground to take up nutrients and water for fast growth and survival (Poorter et al., 2012). The decline in R : S with increasing DBH is also consistent with the fact that as trees age, and DBH increases, nonconductive xylem accumulates disproportionately in aboveground tree parts. MWD accounted for 17% of the variance, and R : S declined with decreasing MWD (Fig. 2). This suggests that plants experiencing water shortage allocate more biomass belowground, in agreement with Mokany et al. (2006) and observations from experiments (Hodge, 2004; Lambers et al., 2008; Poorter et al., 2012), but not with Reich et al. (2014). When MWD was included in the model, both precipitation and temperature became nonsignificant. MWD also explained more variance than precipitation or temperature when these variables were fitted separately in single-factor models (Methods S1). Importantly, the relationship between R : S and both DBH and MWD was nonlinear, as has been observed previously (Mugasha et al., 2013). Many of the tested effects were not statistically significant, presumably because in some instances large variances precluded detection of true differences, and in others because of the absence of an effect. Our analysis does suggest that, after accounting for MWD, variation in R : S did not differ across bioclimatic regions. We detected no correlation or significant interaction between tree size and MWD, which suggests that the effects of these two variables are independent (Methods S1). This is an interesting contrast with the findings of Bennett et al. (2015), who determined that larger trees are more vulnerable to drought than smaller trees: the influence of chronic water deficit (as expressed by MWD) on R : S apparently does not translate to ability to respond to episodic drought. Species identity accounted for only 11% of the variance in R : S, and contrary to previous studies (Mokany et al., 2006; Reich et al., 2014), groupings of species by phenology or clade did not explain any additional variation in R : S (Fig. S2), except that monocotyledons (palms) invest comparatively less biomass in roots. Species can have widely different root architectures (Lynch, 1995), therefore differences in R : S values across species are not surprising. After accounting for species, wood specific gravity was not a significant predictor of R : S. Finally, trees in plantations had lower R : S than trees in natural forests (Fig. S2b), although this effect explained only 2% of the variance in R : S. Plantations are sometimes fertilized, which may result in lower biomass allocation in belowground tissues in response to the greater nutrient availability. Moreover, species in plantations are typically fast-growing and selected for their capacity to produce aboveground biomass quickly. Finally, plantation trees may be more sheltered and the structural support of the roots is less necessary. The remaining 38% of variance that was unexplained may be due in part to soil fertility, which is known to influence R : S (Reynolds & D'Antonio, 1996; Poorter et al., 2012). Other possible sources of variance, not considered due to a lack of data here, include differences in micro-topography, soil properties, particular individual conditions like resprouting, and community structure. Further, differences in methodology for collecting root data (see Fig. S1(2.3)) among studies may account for some of the variance. The main novel finding of this study is that globally, variation in individual tree R : S is largely dominated by two effects: tree size and MWD, which largely support our hypothesis. The increase in R : S in response to increasing climatic water deficit occurs independently of the size dependence in R : S, which supports the hypothesis that moisture availability drives global variation in R : S. With greater aridity, trees invest comparatively more resources to acquire soil water as it becomes a more limiting resource for growth and survival, and to provide a belowground reservoir of stored carbon for rapid regrowth following disturbance. Plasticity in R : S has major implications for our understanding of the contribution of vegetation to the global carbon cycle and responses to climatic change. Some parts of the globe are predicted to experience drying trends, including longer dry seasons, and an increase in the frequency of extreme events and disturbances, while other regions may become wetter or less seasonal (Moss et al., 2010; Intergovernmental Panel on Climate Change (IPCC), 2014). Our new results suggest that any change in water deficit, or in the relative abundance of smaller trees, may result in shifts in biomass allocation, with far-reaching consequences for the global carbon budget. The authors thank the many collaborators involved in data collection, in particular Grahame Applegate, John Larmour, Anthony O'Grady, Peter Ritson, and Tivi Theiveyanthan. The authors acknowledge the bodies that funded part of the data acquisition, including Australia's Department of the Environment and Energy, Alterra Ltd, Fares Rural Pty Ltd. This study was supported by the FP7-PEOPLE-2013-IEF Marie-Curie Action – SPATFOREST and the NERC project (NE/N017854/1). The authors acknowledge Investissement d'Avenir grants of the Agence Nationale de la Recherche (CEBA: ANR-10-LABX-25-01, TULIP: ANR-10-LABX-0041; ANAEE-France: ANR-11-INBS-0001). A.L. and J. Chave initiated the study; A.L. analysed the data and J. Chave compiled the dataset; A.L., J. Chave, K.I.P. and D.F.R.P.B. designed the study and wrote the manuscript; A.L., K.I.P., D.F.R.P.B., J.J.E., C.B., M.B., K.B., J. Chave, T.H.E., J.R.E., A.F., J.J., M.M., K.D.M., G.M., W.A.M., E.P., S.R., C.M.R., R.R-P., S.S., A.S., D.W., C.W., A.Z. and J. Carter contributed ideas, provided written input, and/or data. Fig. S1 World map with data plots and details on the dataset. Fig. S2 Boxplot of R : S values for inter-group comparisons. Methods S1 Extended description of methods, fitted models and model diagnosis Notes S2 R code used in the analyses. Notes S1 Dataset used in the study: tree-by-tree root : shoot dataset; also available in the Figshare achieve doi: 10.6084/m9.figshare.5144164. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

The use of abandoned or marginally productive land to mitigate greenhouse gas emissions may avoid competition with food and water production. Atriplex nummularia Lindl. is a perennial shrub commonly established for livestock forage on saline land, however, its potential for carbon mitigation has not been systematically evaluated. Similarly, although revegetation is an allowable activity to mitigate carbon within Article 3.4 of the United Nations Framework Convention on Climate Change’s Kyoto Protocol, there is a paucity of information on rates of carbon mitigation in soils and biomass through this mechanism. For six sites where A. nummularia had been established across southern Australia four were used to assess changes in soil carbon storage and four were used to develop biomass carbon sequestration estimates. A generalised allometric equation for above and below ground biomass was developed, with a simple crown volume index explaining 81% of the variation in total biomass. There were no significant differences in soil organic carbon storage to 0.3m or 2m depth compared to existing agricultural land-use. Between 2.2 and 8.3MgCha−1 or 0.2–0.6MgCha−1yr−1 was sequestered in above and below ground biomass and this translates to potential total sequestration of 1.1–3.6TgCyr−1 on saline land across Australia. Carbon income and forage grazing may thus provide a means to finance the stabilization of compromised land.

Nitrous oxide is a potent greenhouse gas. It can also increase ultraviolet radiation transmission and incidence of skin cancers by depleting the ozone layer, and is a waste of applied nitrogen fertiliser. Nitrous oxide emissions from four commercial farms growing processing tomatoes (Solanum lycopersicum) in the Rochester-EchucaBoort area of Victoria, Australia, were monitored during the 2014-15 growing season. Low crop nitrous oxide emissions were measured, ranging from 0.23 to 1.51 kg N2O-N ha(-1) across the four farms. The emissions intensity of the four farms was very low, ranging from 0.0014 to 0.011 kg N2O-N t(-1) fruit. The greatest risk period for nitrous oxide emissions was during plant establishment, due to the reliance on subsurface drip and the need to apply excess water to wet the soil surface. Inadvertently, the application of metham sodium appears to be responsible for reducing average nitrous oxide emissions over the high-risk plant establishment period. In 2015, emissions after planting were 4.5 times greater when no metham sodium was applied. The low measured nitrous oxide emissions meant that the Cool Farm Tool, the main industry reporting tool, produced nitrous oxide emission estimates that were up to 11 times higher than those measured during the 2014-15 season. When compared with other produce, the Australian processing tomato sector is well placed, with very low emissions intensities.

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).

Nitrous oxide (N2O) emissions contribute 6% of the global warming effect and are derived from the activity of soil-based microorganisms involved in nitrification and denitrification processes. There is a paucity of greenhouse gas emissions data for Australia’s horticulture industry. In this study we investigated N2O flux from two deciduous fruit tree crops, apples and cherries, in two predominant growing regions in eastern Australia, the Huon Valley in southern Tasmania (Lucaston – apples and Lower Longley – cherries), and high altitude northern New South Wales (Orange – apples and Young – cherries). Estimated from manual chamber measurements over a 12-month period, average daily emissions were very low ranging from 0.78gN2O-Nha–1day–1 in the apple orchard at Lucaston to 1.86gN2O-Nha–1day–1 in the cherry orchard in Lower Longley. Daily emissions were up to 50% higher in summer (maximum 5.27gN2O-Nha–1day–1 at Lower Longley) than winter (maximum 2.47gN2O-Nha–1day–1 at Young) across the four trial orchards. N2O emissions were ~40% greater in the inter-row than the tree line for each orchard. Daily flux rates were used as a loss estimate for annual emissions, which ranged from 298gN2O-Nha–1year–1 at Lucaston to 736gN2O-Nha–1year–1 at Lower Longley. Emissions were poorly correlated with soil temperature, volumetric water content, water filled porosity, gravimetric water content and matric potential – with inconsistent patterns between sites, within the tree line and inter-row and between seasons. Stepwise linear regression models for the Lucaston site accounted for less than 10% of the variance in N2O emissions, for which soil temperature was the strongest predictor. N2O emissions in deciduous tree crops were among the lowest recorded for Australian agriculture, most likely due to low rates of N fertiliser, cool temperate growing conditions and highly efficient drip irrigation systems. We recommend that optimising nutrient use efficiency with improved drainage and a reduction in soil compaction in the inter-row will facilitate further mitigation of N2O emissions.

European colonization precipitated the first industrial transformation of Australian landscapes. We review the evolution of the environmental and societal setting of Australian landscapes since this first industrial transformation, the emergence of drivers precipitating a second industrial transformation, and what it will take to adapt. In concert with climate change and growing societal expectations of environmental stewardship, we identify six emerging economies for ecosystem services - carbon, water, food, energy, amenity and mining - which will exert transformational pressure on land use and management. The requirements for transformational adaptation - to thrive within environmental limits - include: fostering new partnerships between government, science, the private sector, and local communities to support local adaptation; identifying critical environmental limits and rationalizing environmental laws; establishing innovative social processes and adaptive governance; and developing innovative, well-supported market-based and community-based incentives.

There is significant pressure on irrigators to improve on-farm water use. A range of objective irrigation scheduling methods, such as soil monitoring, evaporation and decision support tools, have been developed to address this need. We examined how these tools have been adopted by Australian irrigators using data from an Australian Bureau of Statistics water survey of 7,280 irrigators in 2003. A total of 2.2 million hectare's were irrigated in 2002-2003 with irrigated pasture accounting for 39% of the area irrigated and 36% of the water consumed by agriculture. Cotton, grape and fruit irrigators, who account for 27% of the water used for irrigation, are the biggest users of objective scheduling methods. But still only one quarter to a third of growers are using these methods. For most irrigated crops the use of objective irrigation scheduling methods increases with farm size. The exceptions being pasture and sugar, where the use of objective irrigation scheduling methods remains low irrespective of the farm size. The major users of objective irrigation scheduling tools are where enterprise profitability is directly linked to improved crop water management, such as cotton, grape and fruit production. Other industries, particularly pasture, will lag in the use of these tools because the profitability of their enterprisers is not as sensitive to water management. Until new drivers emerge then it is unlikely that these enterprises will invest in tools to improve irrigation management. With drought and increased competition water reducing allocations, and the increased focus on river and ecosystem health, we may be seeing some of the new drivers emerge.

Conversion of pastures to plantation forests has been proposed as a means to increase rates of carbon (C) sequestration from the atmosphere thereby reducing net greenhouse gas emissions from human activities. However, several studies have indicated that soil C stocks decrease after planting conifer (mainly pine) trees into pasture. This loss of soil C detracts from the role that plantation forests can play in net C sequestration. Here, we used a paired site (a grazed native pasture with the C4 grass Themeda triandra dominant, and an adjacent 16-year-old Pinus radiata plantation) to compare all C and nitrogen (N) pools (including soil, litter on the floor, below-ground and above-ground biomass) in the two ecosystems and to estimate the rate of C sequestration after the land use change from the native pasture to the pine plantation. Soil C and N stocks from soil surface down to 1m under the pine plantation were significantly less than under the native pasture by 20% (57.3MgCha−1 vs. 71.6MgCha−1) and 15% (5.6MgNha−1 vs. 6.7MgNha−1), respectively. Much more C and N was stored in litter on the floor in the pine plantation than in the native pasture (8.0MgCha−1 vs. 0.03MgCha−1, and 119.0kgNha−1 vs. 0.9kgNha−1), and in biomass (95.0MgCha−1 vs. 2.5MgCha−1 and 411.5kgNha−1 vs. 62.8kgNha−1). Carbon stored in coarse tree roots was alone sufficient to compensate the C loss from soil after the land use change. Much more C and N was deposited annually to above-ground litter in the pine plantation than in the native pasture (2.18MgCha−1year−1 vs. 0.22MgCha−1year−1, and 32.8kgNha−1year−1 vs. 5.9kgNha−1year−1), but less to below-ground litter (through fine root death) (2.71MgCha−1year−1 vs. 3.57MgCha−1year−1 and 38.9kgNha−1year−1 vs. 81.4kgNha−1year−1). The shift in net primary production from below-ground dominance to above-ground dominance after planting trees onto the pasture, and the slower turnover of litter in the plantation, played a key role in the reduction in soil C in the plantation ecosystem. In conclusion, planting pine trees onto a native temperate Australian pasture sequestered a significant amount of C (net 86MgCha−1, averaging 5.4MgCha−1year−1) from the atmosphere in 16 years despite the loss of 14MgCha−1 from the soil organic matter.

Wood density, a gross measure of wood mass relative to wood volume, is important in our understanding of stem volume growth, carbon sequestration and leaf water supply. Disproportionate changes in the ratio of wood mass to volume may occur at the level of the whole stem or the individual cell. In general, there is a positive relationship between temperature and wood density of eucalypts, although this relationship has broken down in recent years with wood density decreasing as global temperatures have risen. To determine the anatomical causes of the effects of temperature on wood density, Eucalyptus grandis W. Hill ex Maiden seedlings were grown in controlled-environment cabinets at constant temperatures from 10 to 35 degrees C. The 20% increase in wood density of E. grandis seedlings grown at the higher temperatures was variously related to a 40% reduction in lumen area of xylem vessels, a 10% reduction in the lumen area of fiber cells and a 10% increase in fiber cell wall thickness. The changes in cell wall characteristics could be considered analogous to changes in carbon supply. Lumen area of fiber cells declined because of reduced fiber cell expansion and increased fiber cell wall thickening. Fiber cell wall thickness was positively related to canopy CO2 assimilation rate (Ac), which increased 26-fold because of a 24-fold increase in leaf area and a doubling in leaf CO2 assimilation rate from minima at 10 and 35 degrees C to maxima at 25 and 30 degrees C. Increased Ac increased seedling volume, biomass and wood density; but increased wood density was also related to a shift in partitioning of seedling biomass from roots to stems as temperature increased.

We used measures of plant size, distribution and root core data to evaluate capability of the model of Ammer and Wagner [2] for spatially explicit prediction of fine root biomass (FRB) in Eucalyptus populnea-dominaied woodlands from xeric and mesic regions of Australia. Tree diameter and height were tested as proxy variables for plant size. For the xeric site, which had no understorey grass cover, both the height- and diameter-based models gave reasonable estimates of FRB. However, the height-model provided a better match to the measured data than the diameter-model. For the mesic site, which had a substantial ground cover dominated by C4-grasses whose contribution to FRB could not be captured by the model, neither the height- nor the diameter- model was able to predict FRB satisfactorily. This was also the case even when the contribution of the C4-grasses to FRB was estimated and accounted for after δ13C analysis of fine root samples. Overall, while it is evident that the model can be a useful tool for estimating FRB from aboveground stand inventory in both even-aged plantations and compositionally complex natural vegetation, it is also clear that it does not always provide satisfactory prediction, e.g., the mesic site. Thus, to improve the wider applicability of the model further work is needed to identify why it fails and situations it is likely to be useful.

Summary Branch-related defects can significantly decrease the quality of plantation eucalypt logs grown for solid-wood products. In this study we examined the effect of initial spacing on branching characteristics of 5-y-old plantation-grown Eucalyptus grandis and E. pilularis on the North Coast of New South Wales. For each sample tree all branches on the lower stem (the butt log, 0.3–6 m) were assessed for diameter, angle and condition. Trees were sampled in plots grown at four initial planting densities: 838 (3 m x 4 m), 1111 (3 m x 3 m), 1667 (3 x 2 m) and 3333 (3 m x 1 m) trees ha-1. The butt log of both species contained 55–70 branches, regardless of the initial density. Initial density did not affect branch formation, but it did affect the subsequent growth and persistence of branches. Lower initial density increased both the mean branch diameter and the number of large branches (> 2.5 cm diameter) per tree in both species. Branch size also increased with height up the stem, but the rate of increase was not different between densities. A major difference between species was that E. pilularis had more small dead branches that had not been shed. A single spacing prescription is possible for both species because there was no difference between species in the relationship between large branches and density.

Branch related defects are the major cause of degrade ill eucalypts grown for solid wood. The effects of pruning Oil the growth and branch occlusion in Eucalyptus cloeziana, E. pilularis, E. dunnii and E. grandis were studied. Trees of each species were pruned to remove 30% of the green crown at 3.5 years of age. Diameters and the state of all branches in two 0.5 in sections of trunk were assessed at one, two and four years after pruning. Growth rates were unaffected two years after pruning in all species. In all species, except E. cloeziana, the rate of occlusion of dead branches was not significantly different between pruned and unpruned branches. In contrast, the greatest difference in Occlusion rates was between pruned and unpruned live branches. Eucalyptus grandis and E. dunnii showed high early rates of occlusion compared with E. pilularis and E. cloeziana for the first year. The occlusion rates of unpruned branches generally showed a positive correlation between branch size and time to occlusion. Relationships were more complex in species that self-pruned less efficiently. Since occlusion rates ill dead branches (printed and unpruned) were similar, there would be little benefit in pruning dead branches and it may increase susceptibility to decay entry and the occurrence of loose knots. Pruning only green branches may be difficult in efficient self-pruning species.

The rate of leaf CO2 assimilation (A l) and leaf area determine the rate of canopy CO2 assimilation (A c) can be thought proportional to assimilate supply for growth and structural requirements of plants. Partitioning of biomass within plants and anatomy of cells within stems can determine how assimilate supply affects both stem growth and wood density. We examined the response of stem growth and wood density to reduced assimilate supply by pruning leaf area. Removing 42% of the leaf area of Eucalyptus grandis Hill ex Maiden seedlings did not stimulate leaf-level photosynthesis (A l) or stomatal conductance, contrary to some previous studies. Canopy-level photosynthesis (A c) was reduced by 41% immediately after pruning but due almost solely to continued production of leaves, and was only 21% lower 3 weeks later. Pruning consequently reduced seedling biomass by 24% and stem biomass by 18%. These reductions in biomass were correlated with reduced A c. Pruning had no effect on stem height or diameter and reduced wood density to 338 kg m−3 compared to 366 kg m−3 in control seedlings. The lower wood density in pruned seedlings was associated with a 10% reduction in the thickness of fibre cell walls, and as fibre cell diameter was invariant to pruning, this resulted in smaller lumen diameters. These anatomical changes increased the ratio of cross-sectional area of lumen to area cell wall material within the wood. The results suggest changes to wood density following pruning of young eucalypt trees may be independent of tree volume and of longer duration.

In eucalypts the reduction in CO2 assimilation and total leaf area at low phosphorus (P) supply is not associated with lower leaf total P concentrations. We tested the hypothesis that the leaf concentration of inorganic phosphorus ([Pi]) may be a better indicator of P nutrition status in Eucalyptus grandis W. Hill ex Maiden by growing seedlings in P deficient soil supplemented with P supplies ranging from 3 to1000mgkg−1. Height, biomass accumulation, gas exchange, chlorophyll fluorescence and concentrations of total P ([Pt]), organic P ([Po]) and [Pi] of the last fully expanded leaves were measured when harvested at 19 weeks. All parameters of growth increased with larger applications of soil P with most becoming saturated at additions of 500mgPkg−1 soil. Soil P supply had larger effects on biomass and canopy leaf area, by both increased in leaf initiation and expansion, than on CO2 assimilation (A). Leaf [Pt] and [Po] concentrations were largely invariant to soil P supply and were not correlated with any of the measured growth and photosynthetic parameters. By contrast, leaf [Pi] increased from 171 to 398mgkg−1 with increasing soil P supply. Furthermore, number of leaves, total leaf area and seedling biomass increased exponentially with leaf [Pi], while individual leaf area and A increased linearly with leaf [Pi], and quantum yield of photosystem II similarly increased, and non-photochemical quenching decreased, with increasing leaf [Pi]. The response of A to internal CO2 concentration (Ci) indicated that at lower P supplies A became increasingly restricted by limitations associated with Rubisco and RuBP regeneration. Stomatal limitation may in part be masking the full effect of P supply on A as Ci declined with either increasing soil P or leaf [Pi] supply. We conclude that leaf [Pi] was a potentially better indicator than [Pt] or [Po] for correlating the effects of soil P supply on growth and photosynthesis of E. grandis. Furthermore, as A achieved at saturating Ca increased with increasing P supply leaf [Pi], these findings suggest that a greatly increased rate of canopy assimilation could be achieved at higher P supply in response to the expected increase in global CO2 levels.

Wood density influences both the physiological function and economic value of tree stems. We examined the relationship between phosphorus (P) supply and stem wood density of Eucalyptus grandis Hill ex Maiden seedlings grown with varying soil P additions and determined how changes in wood anatomy and biomass partitioning affect the relationship. Plant height, stem diameter and total biomass increased by 400-500% with increasing P supply. Stem wood density decreased sharply from 520 to 380 kg m(-3) as P supply increased to 70 mg P kg(soil) (-1). Further increases in P supply to 1000 mg P kg(soil) (-1) had no effect on wood density. The increase in wood density at low soil P supply arose principally from enhanced secondary wall thickening of stem fiber cells. Cell wall thickness increased from 3.6 to 4.5 microm as soil P supply decreased. Because fiber cell diameter was independent of soil P (12 microm +/- 0.3), the proportion of the stem occupied by cell wall material increased as P supply declined. The enhanced secondary wall thickening of stem fiber cells at low P supply was not associated with changes in whole-plant biomass partitioning. Instead, low P supply appeared to alter biomass partitioning within the stem in favor of secondary wall thickening. Thus, increased wood density in E. grandis seedlings grown at low P soil supply was associated with inhibited stem cambial activity, resulting in an increased proportion of photoassimilates available for secondary wall thickening of fiber cells.

In vegetated terrestrial ecosystems, carbon in below- and aboveground biomass (BGB, AGB) often constitutes a significant component of total-ecosystem carbon stock. Because carbon in the BGB is difficult to measure, it is often estimated using BGB to AGB ratios. However, this ratio can change markedly along resource gradients, such as water availability, which can lead to substantial errors in BGB estimates. In this study, BGB and AGB sampling was carried out in Eucalyptus populnea-dominated woodland communities of northeast Australia to examine patterns of BGB to AGB ratio and vertical root distribution at three sites along a rainfall gradient (367, 602, and 1,101 mm). At each site, a vegetation inventory was undertaken on five transects (100 × 4 m), and trees representing the E. populnea vegetation structure were harvested and excavated to measure aboveground and coarse-root (diameter of at least 15 mm) biomass. Biomass of fine and small roots (diameter less than 15 mm) at each site was estimated from 40 cores sampled to 1 m depth. The BGB to AGB ratio of E. populnea-dominated woodland plant communities declined from 0.58 at the xeric end to 0.36 at the mesic end of the rainfall gradient. This was due to a marked decline in AGB with increased aridity whereas the BGB was relatively stable. The vertical distribution of fine roots in the top 1 m of soil varied along the rainfall gradient. The mesic sites had more fine-root biomass (FRB) in the upper soil profile and less at depth than the xeric site. Accordingly, at the xeric site, a much larger proportion of FRB was found at depth compared to the mesic sites. The vertical distribution patterns of small roots of the E. populnea woodland plant communities were consistently )-shaped, with the highest biomass occurring at 15–30-cm depth. The potential significance of such a rooting pattern for grass–tree and shrub–tree co-existence in these ecosystems is discussed. Overall, our results revealed marked changes in BGB to AGB ratio of E. populnea woodland communities along a rainfall gradient. Because E. populnea woodlands cover a large area (96 M ha), their contribution to continental-scale carbon sequestration and greenhouse gas emission can be substantial. Use of the rainfall-zone-specific ratios found in this study, in lieu of a single generic ratio for the entire region, will significantly improve estimates of BGB carbon stocks in these woodlands. In the absence of more specific data, our results will also be relevant in other regions with similar vegetation and rainfall gradients (that is, arid and semiarid woodland ecosystems).

A fundamental tool in carbon accounting is tree-based allometry, whereby easily measured variables can be used to estimate aboveground biomass (AGB). To explore the potential of general allometry we combined raw datasets from 14 different woodland species, mainly eucalypts, from 11 sites across the Northern Territory, Queensland and New South Wales. Access to the raw data allowed two predictor variables, tree diameter (at 1.3-m height; D) and tree height (H), to be used singly or in various combinations to produce eight candidate models. Following natural log (ln) transformation, the data, consisting of 220 individual trees, were re-analysed in two steps: first as 20 species–site-specific AGB equations and, second, as a single general AGB equation. For each of the eight models, a comparison of the species–site-specific with the general equations was made with the Akaike information criterion (AIC). Further model evaluation was undertaken by a leave-one-out cross-validation technique. For each of the model forms, the species–site-specific equations performed better than the general equation. However, the best performing general equation, ln(AGB) = –2.0596 + 2.1561 ln(D) + 0.1362 (ln(H))2, was only marginally inferior to the species–site-specific equations. For the best general equation, back-transformed predicted v. observed values (on a linear scale) were highly concordant, with a slope of 0.99. The only major deviation from this relationship was due to seven large, hollow trees (more than 35% loss of cross-sectional stem area at 1.3 m) at a single species–site combination. Our best-performing general model exhibited remarkable stability across species and sites, when compared with the species–site equations. We conclude that there is encouraging evidence that general predictive equations can be developed across sites and species for Australia’s woodlands. This simplifies the conversion of long-term inventory measurements into AGB estimates and allows more resources to be focused on the extension of such inventories.