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Chris Goulding

Chris Goulding. Calculating the current and future carbon stocks from plot measurements in fast growing plantations. Outline of Presentation. Recap of NZ, the Kyoto Protocol and current situation Plot-based measurements - carbon pools Allometric equations Modelling Carbon Validation.

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Chris Goulding

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  1. Chris Goulding Calculating the current and future carbon stocks from plot measurements in fast growing plantations

  2. Outline of Presentation • Recap of NZ, the Kyoto Protocol and current situation • Plot-based measurements - carbon pools • Allometric equations • Modelling Carbon • Validation

  3. New Zealand27 million ha, 4 million people0.6 mil ha Kyoto forests within 1.8 mil ha

  4. NZ Carbon Accounting System • To measure carbon stocks and stock changes • indigenous forests and shrublands • planted Kyoto and “pre-Kyoto” forests • Reporting under Article 3.3 of the Kyoto Protocol • net carbon stock changes • afforestation, reforestation and deforestation since 1990, • first period 2008 - 2012

  5. What is a Forest? • Cycling between pasture and shrub/forest over the long term on land economically marginal for agriculture • minimum size of • 1 ha • 100 m width • 30 % tree species cover, • and • Potential to reach • 5 m height in situ

  6. Planted Forests4 plot cluster,4x4 km gridremeasured every 3 yrs

  7. Reporting Requirements Amount of C in the following pools : • Above-ground live biomass • Below ground live biomass (roots) • Dead wood (> 10 cm in diameter) • Litter (<10 cm in diameter) • Soil organic matter

  8. Shrubs

  9. DBH,H Temp Soil C:N Silvicultural History Allometric Equations Models Satellite Images Aerial Photos Carbon Density (t C/ha) Forest Area (ha) Carbon Stock (t C) C Accounting in Forests

  10. Tree allometric equations • Functions developed for Radiata pine, Douglas fir, Eucalyptus spp, other spp. • Radiata pine, 737 tree sample, • W = 15.124 + 0.016 D2H • Where • W = above ground biomass (kg) • D = diameter breast height (cm) • H = total tree height (m) • Do not • explicitly account for live crown pruning • take into account regional trends in wood density • forecast the future

  11. Allometric Models

  12. Carbon Prediction System –concept and model inputs • Plot measurement • Dbh, Height, stocking • Age and tending history • Site specific environmental data • Soil nitrogen fertility, air temperature • Silvicultural regime • Likely past/future pruning and thinning regime • 300Index, Wood density and C_Change models

  13. Regime ( p a s t a n d f u t u r e s t o c k i n g / p r u n i n g ) Outerwood Density Top Height Age Stocking Basal Area 300 Index Density Model G r o w t h M o d e l Yield Table ( a n n u a l s t o c k i n g , s t e m v o l u m e & s t e m d e n s i t y ) C-Change Outputs: Annual Carbon Pools Plot data and model system Inputs: Processing:

  14. Carbon yield table For each year, starting at planting, • 300 Index management growth model predicts stem volume increment • “Sheath” wood density model predicts Annual Wood density • C_change compartment allocation model partitions biomass / carbon to carbon pools, including decay. • Model system, by definition, passes through the plot measurement of ht, basal area, pruned height, stocking, thinned trees

  15. Models: 300 Index • Estimates site volume productivity level from plot data and tending history • Applies future tending regime • Predicts stocking, stand height, and gross and net stem volume

  16. Productivity Indices • 300 Index is a productivity index of volume growth. It is the Stem Volume Mean Annual Increment (MAI), at age 30, for a defined reference regime. • Site Index is a height growth productivity index. It is the Mean Top Height (MTH) at a reference age of 20 years. • Both productivity indices are required, and can be derived from plot measurement data.

  17. 300 Index versus Site Index - PSP historic data Volume and Height Productivity are only weakly related

  18. Actual (solid lines) and predicted (dashed lines) BA for a fertile and infertile sites, 3 stockings at each site.

  19. Models: Wood density • Either • measure breast height outerwood density at a known age • estimate breast height outerwood density from mean air temperature and C/N balance • Derive density of stem wood annual growth sheaths from age and stocking

  20. Models: C_Change • Obtains gross stem wood/weight increments by age from volume and density models • Applies expansion factors to estimate total biomass & the carbon fixed • Partitions carbon fixed to live tree components • Calculates component mortality and transfers to dead pools using mortality functions and regime information • Applies decay rates to dead pools

  21. Partitioning of biomass increment to above ground, live-tree components

  22. Predicted carbon stocks

  23. Measured and predicted Above ground carbon 33 plots (95% CI).

  24. Carbon Model validation95% confidence intervalmean prediction error (actual-predicted) 33 plots

  25. Conclusions • Allometric equations and C_change model comparable figures for trees • Model system conditioned by the sample plot measurement • Volume yield model used operationally by managers • Model reduces estimation effort for smaller pools • It enables interpolation between measurements, forecasting and strategic planning.

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