Ecological stoichiometry controls the transformation and retention of plant-derived organic matter to humus in response to nitrogen fertilisation

Carbon (C) sequestration in soils is a means for increasing soil organic carbon (SOC) stocks and is a potential tool for climate change mitigation. One recommended management practice to increase SOC stocks is nitrogen (N) fertilisation, however examples of positive, negative or null SOC effects in response to N addition exist. We evaluated the relative importance of plant molecular structure, soil physical properties and soil ecological stoichiometry in explaining the retention of SOC with and without N addition. We tracked the transformation of 13C pulse-labelled buffel grass (Cenchrus ciliaris L.), wheat (Triticum aestivum L.) and lucerne (Medicago sativa L.) material to the <53 μm silt + clay soil organic C fraction, hereafter named “humus”, over 365-days of incubation in four contrasting agricultural soils, with and without urea-N addition. We hypothesised that: a) humus retention would be soil and litter dependent; b) humus retention would be litter independent once litter C:N ratios were standardised with urea-N addition; and c) humus retention would be improved by urea-N addition. Two and three-way factorial analysis of variance indicated that 13C humus was consistently soil and litter dependent, even when litter C:N ratios were standardised, and that the effect of urea-N addition on 13C humus was also soil and litter dependent. A boosted regression analysis of the effect of 44 plant and soil explanatory variables demonstrated that soil biological and chemical properties had the greatest relative influence on 13C humus. Regression tree analyses demonstrated that the greatest gains in 13C humus occurred in soils of relatively low total organic C, dissolved organic C and microbial biomass C (MBC), or with a combination of relatively high MBC and low C:N ratio. The greatest losses in 13C humus occurred in soils with a combination of relatively high MBC and low total N or increasing C:N ratio. We conclude that soil variables involved in soil ecological stoichiometry exert a greater relative influence on incorporating organic matter as humus compared to plant molecular structure and soil physical properties. Furthermore, we conclude that the effect of N fertilisation on humus retention is dependent upon soil ecological stoichiometry.

Is land condition a useful indicator of soil organic carbon stock in Australia?

The grazing lands of northern Australia contain a substantial soil organic carbon (SOC) stock due to the large land area. Manipulating SOC stocks through grazing management has been presented as an option to offset national greenhouse gas emissions from agriculture and other industries. However, research into the response of SOC stocks to a range of management activities has variously shown positive, negative or negligible change. This uncertainty in predicting change in SOC stocks represents high project risk for government and industry in relation to SOC sequestration programs. In this paper, we seek to address the uncertainty in SOC stock prediction by assessing relationships between SOC stocks and grazing land condition indicators. We reviewed the literature to identify land condition indicators for analysis and tested relationships between identified land condition indicators and SOC stock using data from a paired-site sampling experiment (10 sites). We subsequently collated SOC stock datasets at two scales (quadrat and paddock) from across northern Australia (329 sites) to compare with the findings of the paired-site sampling experiment with the aim of identifying the land condition indicators that had the strongest relationship with SOC stock. The land condition indicators most closely correlated with SOC stocks across datasets and analysis scales were tree basal area, tree canopy cover, ground cover, pasture biomass and the density of perennial grass tussocks. In combination with soil type, these indicators accounted for up to 42% of the variation in the residuals after climate effects were removed. However, we found that responses often interacted with soil type, adding complexity and increasing the uncertainty associated with predicting SOC stock change at any particular location. We recommend that caution be exercised when considering SOC offset projects in northern Australian grazing lands due to the risk of incorrectly predicting changes in SOC stocks with change in land condition indicators and management activities for a particular paddock or property. Despite the uncertainty for generating SOC sequestration income, undertaking management activities to improve land condition is likely to have desirable complementary benefits such as improving productivity and profitability as well as reducing adverse environmental impact.

Conversion of sub-tropical native vegetation to introduced conifer forest: Impacts on below-ground and above-ground carbon pools

Land-use change can have a major influence on soil organic carbon (SOC) and above-ground C pools. We assessed a change from native vegetation to introduced Pinus species plantations on C pools using eight paired sites. At each site we determined the impacts on 0–50 cm below-ground (SOC, charcoal C, organic matter C, particulate organic C, humic organic C, resistant organic C) and above-ground (litter, coarse woody debris, standing trees and woody understorey plants) C pools. In an analysis across the different study sites there was no significant difference (P > 0.05) in SOC or above-ground tree C stocks between paired native vegetation and pine plantations, although significant differences did exist at specific sites. SOC (calculated based on an equivalent soil mass basis) was higher in the pine plantations at two sites, higher in the native vegetation at two sites and did not differ for the other four sites. The site to site variation in SOC across the landscape was far greater than the variation observed with a change from native vegetation to introduced Pinus plantation. Differences between sites were not explained by soil type, although tree basal area was positively correlated with 0–50 cm SOC. In fact, in the native vegetation there was a significant linear relationship between above-ground biomass and SOC that explained 88.8% of the variation in the data. Fine litter C (0–25 mm diameter) tended to be higher in the pine forest than in the adjacent native vegetation and was significantly higher in the pine forest at five of the eight paired sites. Total litter C (0–100 mm diameter) increased significantly with plantation age (R2 = 0.64). Carbon stored in understorey woody plants (2.5–10 cm DBH) was higher in the native vegetation than in the adjacent pine forest. Total site C varied greatly across the study area from 58.8 Mg ha−1 at a native heathland site to 497.8 Mg ha−1 at a native eucalypt forest site. Our findings suggest that the effects of change from native vegetation to introduced Pinus sp. forest are highly site-specific and may be positive, negative, or have no influence on various C pools, depending on local site characteristics (e.g. plantation age and type of native vegetation).

Modelling predicts positive and negative interactions between three Australian tropical tree species in monoculture and binary mixture

Computer modelling promises to be an important tool for analysing and predicting interactions between trees within mixed species forest plantations. This study explored the use of an individual-based mechanistic model as a predictive tool for designing mixed species plantations of Australian tropical trees. The `spatially explicit individually based-forest simulator' (SeXI-FS) modelling system was used to describe the spatial interaction of individual tree crowns within a binary mixed-species experiment. The three-dimensional model was developed and verified with field data from three forest tree species grown in tropical Australia. The model predicted the interactions within monocultures and binary mixtures of Flindersia brayleyana, Eucalyptus pellita and Elaeocarpus grandis, accounting for an average of 42% of the growth variation exhibited by species in different treatments. The model requires only structural dimensions and shade tolerance as species parameters. By modelling interactions in existing tree mixtures, the model predicted both increases and reductions in the growth of mixtures (up to +/-50% of stem volume at 7 years) compared to monocultures. This modelling approach may be useful for designing mixed tree plantations.