Harvest residue management and fertilisation effects on soil carbon and nitrogen in a 15-year-old Pinus radiata plantation forest

Jones, Haydon S.; Beets, Peter N.; Kimberley, Mark O.; Garrett, Loretta G.

doi:10.1016/j.foreco.2011.03.040

Cited by 30 publications

(23 citation statements)

References 31 publications

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“…Some previous studies have indicated the importance of N on C dynamics in forest systems (Cusack et al, 2011;Jones et al, 2011) and tropical regions (Cusack et al, 2011;Huang et al, 2011), as well as on microorganism activities (Keeler et al, 2009;Janssens et al, 2010). If, on the one hand, N addition has been related to an increase in the formation of microbial products with longer soil residence time (Cotrufo et al, 2013), on the other hand, it has been related to higher SOM mineralization rates (Khan et al, 2007).…”

Section: Discussionmentioning

confidence: 99%

Contribution of Eucalyptus Harvest Residues and Nitrogen Fertilization to Carbon Stabilization in Ultisols of Southern Bahia

Oliveira

Silva

Ferreira

et al. 2018

Rev. Bras. Ciênc. Solo

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Eucalyptus forests in southern Bahia (BA) are planted in soils with a sandy surface layer and humid tropical climate, conditions that lead to soil carbon (C) decomposition. Recent studies have shown that nitrogen (N) may be important for soil C stabilization. The aim of this study was to evaluate the contribution of Eucalyptus harvest residues and nitrogen fertilization to C stabilization in Ultisols of southern BA. The experiment was conducted in Eucalyptus clonal plantations cultivated in two regions of Eunápolis, BA, Brazil, with different clay content: southern region (140 g kg -1 of clay) and western region (310 g kg -1 of clay). Five treatments were evaluated: one control (CTR), without Eucalyptus harvest residues and N fertilization, and four treatments with harvest residues combined with four rates of N fertilization: 0, 25, 50, and 100 kg ha N) of particulate organic matter (POM) and mineral-associated organic matter (MAOM) were determined. In the southern region after 36 months, the C-MAOM stocks in the 0.00-0.10 m layer of the CTR decreased by 33 %. The addition of harvest residue followed by 100 kg ha -1 N increased C-POM and N-POM stocks (0.00-0.10 m) compared to the CTR, and the final N-POM stocks and residue-C recovery in the surface soil layer were positively correlated with the increase in N fertilization rates. In the western region, residue maintenance resulted in increased C-MAOM stocks (0.00-0.10 m) compared to the CTR, but an increase in N availability reduced this increment. The increase in N fertilization rates did not alter C stocks, but reduced N stocks of POM and MAOM in the upper soil layer. At the end of the experiment, N fertilizer recovery (0.00-0.60 m) was similar among the regions evaluated. In soil with lower clay content, higher N availability led to higher C and N stocks in the particulate fraction. In soils with high clay content, physical and chemical protections are more important than N fertilization for soil C stabilization, and just maintaining harvest residues may suffice to increase C and N in the more stable SOM fraction.

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Section: Discussionmentioning

confidence: 99%

Contribution of Eucalyptus Harvest Residues and Nitrogen Fertilization to Carbon Stabilization in Ultisols of Southern Bahia

Oliveira

Silva

Ferreira

et al. 2018

Rev. Bras. Ciênc. Solo

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“…In the same way, a system of allocative biomass equations was specified to allocate the estimated total residue biomass in Step 1 to the three subcomponents: res + ε 23 (13) where Y stump , Y branch and Y waste represent for stump, branch, and waste biomass in either fresh or dry weight in kg,Ŷ res represents the corresponding predicted total residue biomass in kg from any of the systems of additive equations, r 21 , r 22 , r 23 and r 24 are coefficients, ε 21 , ε 22 and ε 23 are the error terms.…”

Section: Allocative Biomass Equationsmentioning

confidence: 99%

“…On the other hand, estimates of harvest residue biomass enable the calculation of its energy content and other material properties during subsequent residue processing as an energy source [21]. More importantly, as demonstrated by Smith et al [22], Eisenbies et al [15] and Jones et al [23], these estimates provide the basis for the estimation of nutrient removals by collecting harvest residues for bioenergy and for the evaluation of the long-term implications of the removals on the nutrient budget, site productivity and the sustainability of plantations.…”

Section: Introductionmentioning

confidence: 99%

Product and Residue Biomass Equations for Individual Trees in Rotation Age Pinus radiata Stands under Three Thinning Regimes in New South Wales, Australia

Wang

Ximenes

et al. 2017

Forests

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Using data from 239 trees that were destructively sampled and completely weighed in the field, four systems of nonlinear additive equations were developed for the estimation of product and residue fresh and dry weight of individual trees in rotation age (28 to 42 years) Pinus radiata stands under three thinning regimes: unthinned (T0), one thinning (T1) and two thinnings (T2). To cater for all practical applications, the four systems of equations included diameter at breast height overbark (DBHOB) as the only independent variable or both DBHOB and total tree height as predictors either with or without the incorporation of dummy variables for stand types. For all systems, the property of additivity was guaranteed by placing constraints on the structural parameters of the system equations. The parameter estimates were obtained by the generalized methods of moments (GMM) following a comparison with weighted nonlinear seemingly unrelated regression (WNSUR). Based on the predicted values from the system that had DBHOB as the predictor and dummy variables for stand types, the percentage of total tree fresh weight accounted for by residues increased from 14.8% to 20.5%, from 15.6% to 22.2% and from 13.9% to 18.7% for trees in the T0, T1 and T2 stands, respectively, as DBHOB increased from 15 to 70 cm. The corresponding changes in the percentage of residue dry weight were from 15.1% to 16.1%, from 15.7% to 17.1% and from 14.9% to 15.8% for the three stand types. In addition, two systems of allocative equations were developed to allocate the predicted product and residue biomass to their respective subcomponents. The system of allocative equations for product biomass predicted that sawlogs with bark accounted for 83% to 85% of product fresh weight and 82% to 87% of product dry weight over the same range of DBHOB. The predicted allocation of total residue dry weight to stump changed little, between 12% and 13%, over the same diameter range, but it was slightly higher for trees with DBHOB between 30 and 45 cm. The predicted allocation of total residue biomass to branches increased from 18% to 65% in fresh weight and from 18% to 57% in dry weight and that to waste decreased from 71% to 27% in fresh weight and from 70% to 32% in dry weight as DBHOB increased from 15 to 70 cm. Among the five biomass components, prediction accuracy was the lowest for pulpwood and waste. The systems of additive and allocative biomass equations developed in this study provided the first example of how the two approaches could be used together for the estimation of total tree, major and sub-component biomass. They will provide forest management with an enhanced capacity to more accurately estimate product and residue biomass of rotation age trees and thus to include the production of biomass for renewable energy generation in their management systems for P. radiata plantations.

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“…The biomass removal treatments applied at both sites were stem-only harvesting (SO), whole tree harvesting (WT) and whole tree harvesting plus forest floor removal (FF). Biomass and nutritional data were collected from Tarawera 16 years after planting, and 15 years after planting at Kinleith (Jones et al, 2008;Jones et al, 2011;Oliver et al, 2011). A fertilization treatment was also applied at both sites, although comprehensive data were only available regarding N pool sizes at the Kinleith site (Jones et al, 2011), which received 950 kg N ha −1 over the period between the ages of 1 and 6.…”

Section: Data Used To Assess Model Performancementioning

confidence: 99%

A nutrient balance model (NuBalM) to predict biomass and nitrogen pools in Pinus radiata forests

Smaill

Clinton

Höck

2011

Forest Ecology and Management

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Harvest residue management and fertilisation effects on soil carbon and nitrogen in a 15-year-old Pinus radiata plantation forest

Cited by 30 publications

References 31 publications

Contribution of Eucalyptus Harvest Residues and Nitrogen Fertilization to Carbon Stabilization in Ultisols of Southern Bahia

Contribution of Eucalyptus Harvest Residues and Nitrogen Fertilization to Carbon Stabilization in Ultisols of Southern Bahia

Product and Residue Biomass Equations for Individual Trees in Rotation Age Pinus radiata Stands under Three Thinning Regimes in New South Wales, Australia

A nutrient balance model (NuBalM) to predict biomass and nitrogen pools in Pinus radiata forests

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