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WG II: Land use change and management effects on soil C stocks

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1 WG II: Land use change and management effects on soil C stocks
639 WG II: Land use change and management effects on soil C stocks Status report Lars Vesterdal, Christopher Poeplau, Axel Don, Jens Leifeld, Bas van Wesemael (WG2) Cost 639 MC meeting University of Limerick May 25, 2010

2 Data needs for reporting?
Too few data per country? Use IPCC default factors? Recent efforts to review and summarize effects of land-use change and management, partly based on meta analyses of GLOBAL data: e.g. Post & Kwon, 2000; Guo & Gifford 2002; Paul et al., 2002; Johnson & Curtis, 2001; Jandl et al., 2007 LUC and MC effects remain to be quantified Need for summary of EU-specific knowledge on LUC and management change – tier 1 methodology for Europe? -but in which form?

3 Environmental Management 33: 507-518 (2004)

4 Carbon response functions as a tool?
Example: afforestation of arable land Mathematical function describing the response of a system The response changes with time West et al. 2004

5 Pros and cons of carbon response functions
WGIV meeting 2008 Represents temporal C dynamics better than IPCC factors May not be the best solution in terms of transparency A solution in terms of economy when used as an alternative to reporting based on systematic inventories. Large variability in soils: systematic sampling may be preferable CRFs may be a relevant alternative for a country with little variability in site conditions. CRFs may also support reporting in cases where net emissions are around zero (i.e. go for cheap solution).

6 Pros of carbon response functions in Cost 639
Such functions will be valuable as 1) a synthesis tool 2) for management and planning guidelines 3) reporting of soil C change.

7 Time line of past activities
April 2007: Meeting in Vienna Spring 2007: Questionnaire on LUC and MC interests/data October 2007: Carbon Response Functions as a tool Feb. 2008: Workshop Udine: Meta-database framework established June 2008: Presentation at WGIV workshop for discussion relevance of CRFs August 27, 2008: EuroSoil 2008 Vienna, workshop 9. Greenhouse gas budget of soils –hotspots of emission.

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10 Time line of past activities
April 2007: Meeting in Vienna Spring 2007: Questionnaire on LUC and MC interests/data October 2007: Carbon Response Functions as a tool Feb. 2008: Workshop Udine: Meta-database framework established June 2008: Presentation at WGIV workshop for discussion relevance of CRFs August 27, 2008: EuroSoil 2008 Vienna, workshop 9. Greenhouse gas budget of soils –hotspots of emission. Nov. 2009: Expert meeting Copenhagen to set the scene for work in GHG-Europe/Cost639 February 2010: STSM/Expert meeting in Zürich for hard work May 2010: WG2 meeting as side event at EGU for discussion of next steps. Poster with first results

11 Focus on LUC European Environmental Agency (2005)

12 The Dataset Quality Criteria:
0<MAT<18, (temperate climate zone – defined by IPCC) Chronosequence, paired plot, mono-site design First hand data At least roughly known land use history, soil information Sampling by depth increments, not by horizons

13 The Dataset Author, Year, Journal Country, Location
MAT, MAP, Elevation, Soil type, Sand/Silt/Clay % Sampling depth LU1: type, age – LU2: type, age Correction y/n C (unit) Bulk density Number of replicates (n) SD/SE Comment (important details, e. g. forest floor y/n…)

14 The Dataset n=101, n(europe)=33

15 The Dataset n(data points) = 869

16 The Dataset Options for CRFs: Cropland to grassland and vice versa
Cropland to forest and vice versa Grassland to forest (Accumulation of forest floor)

17 Data corrections The studies differ widely in quality! Major problems:
Missing bulk density information to calculate stock [t/ha] from concentration [%]  PTF When comparing stocks, the same soil mass has to be compared  Mass Correction

18 Significance? Carbon Response Functions Explaining factors: Age
Soil Texture MAT MAP Sampling Depth Significance?

19 Carbon Response Functions
Grassland to Cropland MAT MAP Wet (>900 mm) Intermediate ( mm) Dry (<600mm) Mean Warm (>10° C) Intermediate (7-10° C) Cold (<7° C) Mean

20 Carbon Response Functions
Cropland to grassland Soils Depth 0-20 cm 0~35 cm 0-70 cm Subsoil (20 cm – bottom)

21 Carbon Response Functions
Forest to Cropland Cropland to Forest MAT Soils Warm (>10° C) Intermediate (7-10° C) Cold (<7° C) Mean Sandy soils Loamy soils Clay soils Mean

22 Carbon Response Functions
Grassland to Forest

23 Mean sampling depth: ~30 (±4.7) cm, time: 100 years
Preliminary Conclusions +25 t/ha (+68 t/ha) +50% (+130%) +5% (+40%) +4 t/ha (+27 t/ha) -45% -66 t/ha +59 t/ha +120% -54 t/ha -36% Mean sampling depth: ~30 (±4.7) cm, time: 100 years

24 Preliminary Conclusions
„Slow in, fast out!“ Site characteristics influence the change rate: sand > loam > clay warm > cold wet > dry topsoil > subsoil

25 Next steps – validation on Belgian LUC data
Land use history Years Source: Van Wesemael (2009)

26 Next steps Validation of CRFs using Belgian regional datasets on LUC (Bas van Wesemael) Writing journal publication (1 or 2) for GCB Contributing to book - Chapter 2 on LUC and GHG dynamics


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