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Case Study 1 Canadian Prairies: Soil C management Biophysical information M. Boehm, B. McConkey & H. Janzen Agriculture and Agri-Food Canada How can we.

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Presentation on theme: "Case Study 1 Canadian Prairies: Soil C management Biophysical information M. Boehm, B. McConkey & H. Janzen Agriculture and Agri-Food Canada How can we."— Presentation transcript:

1 Case Study 1 Canadian Prairies: Soil C management Biophysical information M. Boehm, B. McConkey & H. Janzen Agriculture and Agri-Food Canada How can we vertically integrate biophysical, economic, and policy analyses into credible mitigation programs?

2 Kyoto Protocol created a need for GHG mitigation science and policy but, the policy environment was uncertain Would the Kyoto Protocol include sinks? Will Kyoto become international law? Needed “no-regrets” policy options 1

3 1. 1.Soil C management on the Prairies as GHG mitigation - background & national circumstances 2. 2.Current knowledge and models 3. 3.How models can contribute to further understanding Outline 3

4 ~80% of Canadian agricultural land is on the Prairies 4

5 with young grassland soils... Chernozems (Mollisols) with high organic C and N contents Chernozems (Mollisols) with high organic C and N contents 5

6 and young agriculture. Farmers and scientists arrived together Photo: saskinteractive.usask.caPhoto: Henry Janzen 6 Shutt 1910 Indian Head Experimental Farm, 1899

7 and the impact of agriculture on SOC and land quality was documented Photos: saskinteractive.usask.ca 7 190019201940196019802000 0 10 20 30 40 50 Soil C (Mg C ha -1 ) ~ Initial cultivation Ellert and Janzen (unpubl.) Organic C in surface soil (2000 Mg) Cereal-fallow rotation Indian Head Experimental Farm

8 Early research led to recognition that maintaining SOC (soil conservation) is a key to maintaining land quality … 8 No agricultural country has ever prospered for more than a generation or two that has not made provision for maintaining the nitrogen and organic matter content of the soil. John Bracken. 1920 Professor, Univ. Sask. John Bracken. 1920 Professor, Univ. Sask. Photo – Henry Janzen

9 Changes in land management that farmers are making for economic and conservation reasons have become GHG mitigation strategies 9 … and now, SOC is also linked to atmospheric quality ZT SF Million ha Reduced summerfallow Minimum and ZT Permanent cover Forage production

10 But, agriculture most soil sinks only recover CO 2 that was emitted after cultivation – not an offset for fossil emissions Grassland Conventional tillage

11 energy product CO 2 Organicmatter C C Ecosystem boundary Ecosystem boundary NO 3 - N2N2 N2N2 fertilizer energy N N N2ON2O N2ON2O CH 4 and GHG mitigation through land management is more than C sequestration 11 Land has to be managed for net GHG removals Agriculture is a biological production system The C and N cycles are linked

12 Current models and knowledge 12

13 Depth (cm) 1996 to 1999 SOC change (Mg ha -1 ) Prairie Soil Carbon Balance Project Measurements CENTURY Simulation of PSCB fields C factors from long-term experiments IPCC Guidelines (1996) Mean95% C.L 0-15--1.05-- 0-201.02+/-0.670.91-- 0-301.21+/-0.80-- 0.97 Reasonable understanding of SOC change N2O emission rates more uncertain

14 Canadian Economic and Emission Model for Agriculture (CEEMA) Policy tool – estimate national GHG mitigation potential Canadian Regional Agricultural Model + GHG module 13 75 SINK PRAIRIE SOIL ZONES NON- ACTIVITIES BRN D BRN BLK PRAIRIES (Mg CO2 ha -1 yr -1 ) Zero Tillage 0.73 0.73 1.34 0.54 Reduce SF* 0.15 0.16 0.08 Increase forage 0.94 2.44 2.44 Permanent cover 0.88 1.15 3.3 3.3 SINK PRAIRIE SOIL ZONES NON- ACTIVITIES BRN D BRN BLK PRAIRIES (Mg CO2 ha -1 yr -1 ) Zero Tillage 0.73 0.73 1.34 0.54 Reduce SF* 0.15 0.16 0.08 Increase forage 0.94 2.44 2.44 Permanent cover 0.88 1.15 3.3 3.3

15 Mt CO 2 e BAU emissions 35 40 45 50 55 60 65 70 75 199019992010 C management mitigation potential for first commitment period 15 BAU sinks Additional sinks e.g. offset trading

16 Next generation of models – greater spatial and activity resolution NCGAVS - National Greenhouse Gas and Carbon Accounting and Verification System (for agriculture) Component of the national Land Use, Land-use Change and Forestry - Measurement, Accounting and Reporting System  LULUCF MARS Reporting LULUCF sector E/R under the UNFCCC and Kyoto Protocol Mitigation testing Develop factors – eg., for offset system protocols 16

17 SLC Polygon Land Use- Management Database Regional Account (Grouped SLC Polygons) Provincial Account National Account Carbon sink/source and N 2 O Account for SLC Polygon SLC Polygon Land Quality Database Factors - Estimators of  SOC and N 2 O emissions + SLC Land Use-Management- Landscape – N 2 O-  C Database NCGAV System Ag. Census Remote sensing CanSIS 18

18 Soils C and N 2 O Factors CenturyDAYCENTDNDC Empirical data CenturyDAYCENTDNDC 19 Activity changes: Tillage (eg., ZT, minimum till) Summerfallow frequency Perennial crops Crop mix Landscape Activity change History

19 Regional Account (Grouped SLC Polygons) Provincial Account National Account Carbon sink/source and N 2 O Account for SLC Polygon SLC Polygon Land Database SLC Polygon Land Use- Management Database Factors - Estimators of  SOC and N 2 O emissions + SLC Land Use-Management- Landscape – N 2 O-  C Database NCGAV System 21 Scale up or drill down Factor x Area

20 22 What can modeling contribute to what we don’t know yet?

21 It can held us look beyond laboratory research and field plots scale across space and time integrate across systems – net GHG emissions estimate uncertainty 24

22 Integration: Model Farm Research Project 25 systematically integrate what we know predict emissions as a function of farm properties/practices and land quality establish boundaries and assess leakage associated with a change in management address gaps – i.e., research to reduce (large) uncertainty around N 2 O emissions better factors – net GHG emissions/removals and “rules of thumb”

23 National Account Uncertainty Provincial Account Uncertainty Uncertainties in Land Use-Management Uncertainties in Land Information Uncertainties in Factors Estimating uncertainty Monte Carlo Estimation 27

24 Making decisions under uncertainty Is soil carbon management good mitigation policy? Probability (%) National Soil Carbon Account Uncertainty Probability (%) National Soil Carbon Account Uncertainty Probability (%) National Soil Carbon Account Uncertainty 28 Answer will depend on the cost and efficacy of alternatives

25 Representing time Organic C Time Old managementNew management 26 Steady-state? verification? SOC content?

26 200020102020203020402050 0 remove Replace reduce Annual impact of mitigative strategies (relative to business-as-usual) What can our models contribute to what we don’t know yet - new mitigation strategies

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