Measuring & monitoring soil carbon. Ermias Aynekulu Betemariam, Keith Shepherd, Richard Coe, Markus Walsh, Tor-G Vagen & Leigh Winowiecki

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1 Measuring & monitoring soil carbon Ermias Aynekulu Betemariam, Keith Shepherd, Richard Coe, Markus Walsh, Tor-G Vagen & Leigh Winowiecki September

2 Issues There is a lack of coherent and rigorous sampling and assessment frameworks that enable comparison of data (i.e. meta-studies) across a wide range of environmental conditions and scales High spatial variability in soil properties Soil monitoring is expensive to maintain Up-scaling Taxonomic soil classification systems provide little information on soil functionality in particular the productivity function (Mueller et al 2010)

3 The protocol contains 1 Why measure soil carbon? 2 What will the protocol deliver? 3 How much will it cost? 4 Sampling 5 Field work 6 Lab work 7 Data analysis Spreadsheet: Sample size determination & sample allocation SOC stock calculations Cost- error analysis 8 Presenting results

4 Sampling design AfricaSoils Sentinel Site based on the Land Degradation Surveillance Framework a spatially stratified, hierarchical, ran d omized sampling framework Sentinel site (100 km 2 ) 16 Clusters (1 km 2 ) 10 Plots (1000 m 2 ) 4 Sub-Plots (100 m 2 )

5 Sampling design Hierarchical sampling design: (a) Represents the 100 km 2 grid divided into 16 clusters (b) Illustrates the 1 km 2 clusters with m 2 plots, (c) Illustrates how the plots are laid out with four subplots

6 Soil sampling Field soil data collection Determining auger-hole volume using sand filling method

7 Soil Infrared Spectroscopy for rapid soil characterization Rapid Low cost Predicts many soil functional properties

8 History { Shepherd KD and Walsh MG. (2002) Development of reflectance spectral libraries for characterization of soil properties. Soil Science Society of America Journal 66:

9 Instrumentation Dispersive VNIR FT-NIR FT-MIR Handheld NIR/MIR Portable Repeatability? External service No validation Benchtop Repeatability *** Self serviceable Validation inbuilt ISO compliant Industry proven Multipurpose Benchtop Repeatability*** No gas purging Some servicing Robotic Validation inbuilt ISO compliant Outperforms NIR Handheld Sample homogeneity? Variable moisture? Repeatability? Still expensive Rapidly developing Need to prepare by developing soil reference libraries

10 Regional Infrared laboratories GEF could use these labs to standardize measurements

11 Why use Infrared? Speed Accuracy Cost Accuracy-It has high precision when comparing results from one instrument to another. Speed-It is fast; it takes approximately 30 sec to scan a sample. The instrument can scan very many samples within a shorter period of time. Cost-It is cheap. No sample preparation or use of chemical reagents is required.

12 Monitoring SOC stock change Think mass not depth Bulk density as confounding variable in comparing SOC stocks (Ellert and Bettany, 1995) Tillage increases the thickness per unit area A management that leads to a DECREASE in bulk density will UNDER ESTIMATES SOC stocks & vice versa C conc.( %) Bulk density(g/c SOC stock m) (Mg/ha) Depth(c m) Error %

13 Monitoring SOC change Cumulative soil mass sampling Comparing SOC stocks between treatments or monitoring over time on equivalent soil mass basis No need to dig pits for deep bulk density Determining auger-hole volume using sand filling method Cumulative soil mass sampling plate: to recover soil samples for measuring soil mass What is the minimum detectable change? What time interval for monitoring?

14 Cost error analysis 95% confidence intervals (t C ha -1 ) of the carbon stock Comparisons of costs of measuring SOC using a commercial lab and NIR Measuring cost of carbon Cost IR is cheaper (<~ 56%) than combustion method particularly for large number of samples Throughput Combustion ~ samples/day NIR ~ 350 samples/day MIR ~ 1000/day $ per sentinel site (baseline)

15 Application test

16 Predicting SOC stocks using soil infrared spectroscopy Partial least squares (PLS) regression analysis

17 Soil depth (cm) Vertical distribution of SOC SOC concentration 0.00 (%) Soil mass (gm) SOC stocks (t ha -1 ) Sub-soils (20 40 cm) sore more carbon: higher soil mass per unit depth than the top soil Due to erosion/ deposition effects, and influence of woody species(agroforestry systems) it recommended to measure SOC stocks up to 50 cm (IPPC= 30 cm) 140

18 Up-scaling: Covariates Remote Sensing and Spatial Data Elevation MODIS 500 m 250 m Vegetation Hydrology Landsat 28.5 m Topographical properties Climate ASTER 15 m Cost surfaces, etc. Legacy data Quickbird 2.4 m 0.6 m

19 Mapping SOC stocks A landscape level SOC stocks mapping can be made using medium resolution satellite imagery such as ASTER and Landsat

20 The protocol used in several projects The protocol is widely used in Africa AfSIS 60 primary sentinel sites 9,600 sampling plots 19,200 standard soil samples ~ 38,000 soil spectra EthioSIS 97 Sentinel sites

21 The protocol used in several projects Effects of range management on soil organic carbon stocks in savanna ecosystems of Burkina Faso & Ethiopia ACIAR project: Rwanda, Uganda, Burundi and Ethiopia The Living Standards Measurement Study (DFID) MARS project: revitalization of cocoa plantations BIODEV (Finland) high carbon project: Sera Leon, Guinean & Mali National initiatives: Rwanda, Cameroon, Kenya, Ethiopia.

22 Top-level tool kit adviser 1 Why measure soil Land health, PES carbon? Project Landscape Current stocks 2 What will the protocol deliver? Change in stocks Interpretation Precision/error Theory Current map Example Change map 3 How much will it cost? 4 Sampling 5 Field work Sampling for baseline Sampling for change Basic sampling Grid + hierarchical Cost-error R-code Spreadsheet Example Spreadsheet Example 6 Lab work 7 Data analysis 8 Presenting results Calculate carbon stocks (Mean ± SE) Change (Mean ± SE) Web-based decision support tool is under development

23 Final remarks In this protocol Error due to of bulk density is addressed: Think mass not depth Cost-effective SOC measurement options are suggested: IR spectroscopy Landscape scale approach is suggested: LDSF-widely applied in Africa A web-based top-level took kit adviser under development Uncertainties & error propagation in measuring SOC stocks, should be addressed Creating synergy between measurement and modelling tools is necessary

24 Thank you Ermias A Betemariam World Agroforestry Centre (ICRAF) e.betemariam@cgiar.org