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Forest related changes and GHG emissions
Turkey study tour Eric Arets
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Carbon sequestration in LULUCF
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Reporting and accounting of LULUCF
CP2
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Forest land Forest definition
forests are patches of land exceeding 0.5 ha with a minimum width of 30 m; with tree crown cover of at least 20% and; tree height at least 5 metres, or, if this is not the case, these thresholds are likely to be achieved at the particular site This definition conforms to the FAO reporting Includes areas normally forming part of the forest area, which are temporally unstocked as a result of human intervention or natural causes
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Carbon stocks in forests
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NFI data provide the basis
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Changes in forest cover
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Afforestation - Reforestation
UNFCCC Reported under L-FL, until new land-use changes occur 20 year transition: FL-FL KP-LULUCF Once AR, remains AR, unless D Includes forests < 20 yr (L-FL) and FL-FL after 20 yrs AR
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Deforestation UNFCCC Reported under FL-L, until
new land-use changes occur 20 year transition: L-L KP-LULUCF Once D, remains D Includes emissions resulting from land-use changes after D
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Forest Management UNFCCC: FL-FL
+ L-FL after 20 years transition (afforestation/reforestation) - FL-L (deforestation) KP-LULUCF Forestland in 1990 Area only decreasing over time
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Areas
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Emissions in Forests
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Questions?
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Periodically repeated inventories:
1e forest statistics 2e forest statistics 3e forest statistics 4e forest statistics HOSP MFV 6e Dutch Forest Inventory
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Waar? Sample plots: 1 per 100ha Same locations as MFV
Half of the plots permanent Variable radius
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Observations in the field
Terrain variables (Owner), dominant tree species, age class, size class, management type, etc. Tree variables Angle and distance to midpoint (permanent sample points only) Tree species Diameter at breast height Tree social status Harvested/dead/rotten (for repeated measurements) Sample trees Height, shape, quality
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Some numbers 87 plots access denied 116 plots could not be reached
3344 plots visited 3190 plots measured 1235 permanent sample points remeasured About 120ha forest measured in total 85243 tree diameters 7934 tree heights
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Dataset is publicly available as Access database
All plot- and tree measurements are online Owner is listed as category (private/state forest service, etc.) Database includes an update of the MFV data Exact locations are not in the database due to privacy reasons, just the km2 gridcel where it is located
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Eigendom
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Management type
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Mengvorm
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Average standing volume
Standing dead: from 3.6 to 6.4 m3/ha Lying dead: from 5.3 to 6.8 m3/ha
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Increment
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Harvest (about 50% of increment)
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Age class distribution
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Total volume by diameter class
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Conclusions Coniferous share Harvest: 64%
Area, volume and increment: about 50% Regeneration: 25% Transition from conifers (Scots pine) towards broadleaves (oak/beech/birch) Poplar is decreasing fast Relatively much birch, red oak and only little pedunculate oak in the regeneration About 40% of the permanent sample plots was not harvested Standing volume has increased substantially Increments seems to be decreasing
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Ongoing work Analysis of harvest patterns of different owners
Why did owners not harvest on the permanent plots? General questionnaire on aims and attitudes of owners at all plots Development of diameter-class model at the plot level Use of data in models and scenarios
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Open questions Regeneration: is the method OK, how to present it, what can be concluded? It seems trees contain slightly more volume than 10 years ago at the same diameter. Is it statistically significant? Are they higher now at the same diameter? Combination with remote sensing to do spatial extrapolation Can the methods be improved and/or optimised before next round?
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The best reasons not to measure a plot:
Nudist camping Located on a prison area Can only be reached with a helicopter Can only be reached via a meadow with bulls Forest with wild animals like zebra kangaroo etc. Harnass needed against blackberries Swamp >1,5 m deep
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Questions?
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