School of Agriculture, Food and Ecosystem Sciences - Research Publications

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    Nitrate Uptake from an Aquifer by Two Plantation Forests: Plausibility Strengthened by Process-Based Modelling
    Smethurst, PJ ; McVicar, TR ; Huth, NI ; Bradshaw, BP ; Stewart, SB ; Baker, TG ; Benyon, RG ; McGrath, JF ; Van Niel, TG (MDPI AG, 2022-02-01)
    Forest plantations can access water from some unconfined aquifers that also contain nitrate at concentrations that could support hydroponic culture, but the separate effects of such additional water and nitrogen availability on tree growth have not hitherto been quantified. We demonstrate these effects using simulation modelling at two contrasting sites supporting Eucalyptus globulus Labill. or Pinus radiata D.Don plantations. The APSIM Eucalyptus and Pinus models simulated plantation growth within 2% of observed growth where the water table was at 4 m depth for eucalypts (height 28 m, MAI 32 m3 ha−1 year−1) and at 23 m for pines (height 37 m, MAI 20 m3 ha−1 year−1). In simulations without an aquifer, observed growth could only be matched using unrealistically high surface soil nitrogen (N) supply, suggesting this is an unlikely mechanism. Simulated aquifer N concentrations, evapotranspiration, and net N mineralization and leaching (emergent properties of modelling) were similar to measured values. These results strengthen the plausibility that aquifer N uptake by plantations could be contributing to tree growth. This hypothesis warrants further research that quantifies these processes at multiple sites. Simulations included growth of herbaceous and tree weed species, and pasture, which demonstrated the utility of the process-based APSIM modelling framework for dynamically simulating carbon, water and N of plantations and other mixed-species systems.
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    Testing the generality of above-ground biomass allometry across plant functional types at the continent scale
    Paul, KI ; Roxburgh, SH ; Chave, J ; England, JR ; Zerihun, A ; Specht, A ; Lewis, T ; Bennett, LT ; Baker, TG ; Adams, MA ; Huxtable, D ; Montagu, KD ; Falster, DS ; Feller, M ; Sochacki, S ; Ritson, P ; Bastin, G ; Bartle, J ; Inildy, D ; Hobbs, T ; Armour, JL ; Waterworth, R ; Stewart, HTL ; Jonsonf, J ; Forrester, DI ; Applegate, G ; Mendhan, D ; Bradford, M ; O'Grady, A ; Green, D ; Sudmeyer, R ; Rance, SJ ; Turner, J ; Barton, C ; Wenk, EH ; Grove, T ; Attiwill, PM ; Pinkard, E ; Butler, D ; Brooksbank, K ; Spencer, B ; Snowdon, P ; O'Brien, N ; Battaglia, M ; Cameron, DM ; Hamilton, S ; Mcauthur, G ; Sinclair, A (WILEY, 2016-06)
    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).
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    Prediction of non-recoverable collapse in Eucalyptus globulus from near infrared scanning of radial wood samples
    Wentzel-Vietheer, M ; Washusen, R ; Downes, GM ; Harwood, C ; Ebdon, N ; Ozarska, B ; Baker, T (SPRINGER, 2013-11)
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    The Allometric Quarter-Power Scaling Model and Its Applicability to Grand Fir and Eucalyptus Trees
    Capes, H ; Maillardet, RJ ; Baker, TG ; Weston, CJ ; McGuire, D ; Dumbrell, IC ; Robinson, AP (SPRINGER, 2017-12)
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    Self-thinning tree mortality models that account for vertical stand structure, species mixing and climate
    Forrester, D ; Baker, TG ; Elms, SR ; Hobi, ML ; Ouyang, S ; Wiedemann, JC ; Xiang, W ; Zell, J ; Pulkkinen, M (ELSEVIER, 2021-05-01)
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    Prescribed fire increases pyrogenic carbon in litter and surface soil in lowland Eucalyptus forests of south-eastern Australia
    Krishnaraj, SJ ; Baker, TG ; Polglase, PJ ; Volkova, L ; Weston, CJ (ELSEVIER SCIENCE BV, 2016-04-15)
    Low intensity prescribed fire is widely practiced in seasonally dry forests in many countries to reduce fuel loads and the risk of uncontrollable wildfires. Associated with low intensity fire is the heating and alteration of organic matter of the litter and surface soil to create pyrogenic carbon (PyC). This study reports changes in total carbon (TC) and PyC in the litter (as char particles) and the top 2cm of soil (as oxidation resistant carbon, PyC) in Eucalyptus obliqua forests in south-eastern Australia. Litter and surface soil were sampled and carbon (C) measured before and immediately after low intensity prescribed fire on the same sites. Post-fire, lightly burnt (FIRE-300) and heavily burnt (FIRE-600) forest floor areas were sampled separately. On average, net loss of 1.55Mgha−1 C (10% of initial) from litter was largely offset by increase of 1.67Mgha−1 C in soil (which was restricted to the 0–2cm layer) with no net change in the initial litter+soil C stock of 21.9Mgha−1C. Concurrently, fire increased PyC by 0.3Mgha−1 in litter and 0.4Mgha−1 in surface soil, which together were equivalent to about 11% of the 6.1Mgha−1C emitted to the atmosphere as a result of the prescribed burn.