Breakout Session Slide Pt. 1 Advancing Producer Engagement and MMRV in Ecosystem Services Markets: Lessons Learned from Three Years Conducting Projects – Alana Pacheco and Lars Dyrud will highlight three years of lessons learned from ESMC’s Eco-Harvest market projects and discuss program specifics, opportunities for participation, and private sector advancement of reduced soil sampling costs through the latest in MMRV. Tuesday, February 13, 2:20 - 3:00 p.m.

1. Affordable and
Accurate Primary Soil
Carbon Data
Dr. Lars Dyrud, CEO

2. 1
Reducing ESMC Sampling Costs by 70% with EarthOptics
Key Customer Partnership
ESMC and EO have engaged partnership over last 2 years to maintain accuracy but lower costs
from $15→$4
1H 2023
Program Expands 2X
2H 2023
Continued measurement with
significant cost reductions
1H 2022
Initial Measurement
2H 2022
Co-Developing More Efficient
Sampling Plan
Cost Reduction
Key Value Drivers / ROI 70%
by sample reduction &
improved sampling plans
Improved Reporting
EO Maps enabled
project visibility to
both growers &
corporate partners.
Mapping Bundles
EO enables bundling of
other data products to
increase grower value
ex) TillMapper

3. 2
Vision for Soil Carbon Measurement
Instant, perfect, nearly free….. Carbon accounting

4. 3
Primary Tools for lowering costs while not sacrificing accuracy
1) Transition from field level quantification to project level → Fewer
samples and lower costs
a) Sparse sampling means field and farm level accuracies are lost
2) Senors save the day here
a) EMI/GPR sensors map soil heterogeneity allowing allowing fewer samples to
represent more acres
b) Technologies like active gamma attenuation
3) Think of MRV $ as buying down quantification uncertainty
a) If spatial carbon variability drives 95% of carbon uncertainty and Bulk Density
only 5% don’t spend equal amounts measuring both!
b) Course fragment correction, does not make sense on most fields but drives
significant lab costs
Project level and Sensors

5. 4
Project Level Quantification

6. 5
Bulk Density vs. SOC variability
Bulk Density variability accounts for only
5% of carbon stock variability. This is
due to lower total variability and
significantly larger correlation length
scales

7. 6
How do we accurately quantify highly variable soil?
Try finding a 1 ton
CO2
change in a 2000
ton acre-foot of soil!
The challenge is
similar to measuring
the percentage of
each color in the
American flag with
only spot samples
1
2
3

8. 7
But how are we going weigh carbon on a field or ranch?
1
2
3
Sensors and
satellites allow us
to measure soil
changes even if
they don’t tell us
precisely the
underlying
quantities. Kind of
like a black and
white flag image

9. 8
C-Mapper: Better carbon maps from fewer samples
Sample Fields: % Total Carbon / Bulk Density (g cm-3
)
Mean
error =
0.062
Mean
error =
0.006
● Maps on 1100 acres in MS were made with only 36 carbon samples and 12 BD samples,
would need at least 500 and 100 samples to produce comparable results

10. 9
Simulations on Maps with fewer samples
To determine accuracy
sensitivity to number of
samples we run Monte Carlo
post processing to try all the
options for fewer samples.
Bands show the middle 50% of
those simulations. For the
previous field it shows we could
hit the same accuracy with 20
instead of the 37 samples we
took, next year will take 10
since the model is getting
smarter

11. 10
Project Level Quantification- Field level Quantification using Sensors

12. 11
“Nuclear” Bulk Density
Soil compaction and soil bulk density are gaining in
importance as soil parameters. The standard
measurement with rings is labor intensive and
therefore expensive.
Nuclear density gauges provide an opportunity for
more cost effective soil bulk density measurements
in terms of both lab and labor costs.
Use of nuclear density gauges provides immediate
results from 0-30 cm in short increments.
Nuclear density gauges have been proven to be
more accurate than standard bulk density sample
methodologies by eliminating the possibility of
sample compaction.

13. Thank You
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