2017 SWCS Annual Conference July 30-August 2, 2017 Monona Terrace Convention Center

1. Active and labile measures of
soil carbon and nitrogen in
Wisconsin grain- and dairy-
based cropping systems
MATT RUARK, KAVYA KRISHNAN, KALYN DIEDERICH, GREG RICHARDSON,
& FRANCISCO ARRIAGA
DEPT. SOIL SCIENCE

2. What’s labile?
Potentially mineralizable N (PMN) - 7-day anaerobic incubation
(difference in NH4-N)
Potentially mineralizable C (PMC) – 24-hr soil incubation (CO2 burst)
Permanganate oxidizable C (POXC) – chemical extraction; active C
Measure of C and N pools & measure of soil health

3. Are labile C and N pools responsive to
management in Wisconsin?
1. Controlled-experiment approach
◦ Long-term (25+ yr) cropping system trial
◦ Start with same soil, manage differently, see what happens
2. Survey approach
◦ Sample on as many farms as will let us
◦ See if trends emerge among management groups even if we don’t control for soil
texture or other soil factors
Funding sources: USDA-NIFA, NRCS-CIG, Wisconsin Fertilizer Research Council

4. Are labile C and N pools responsive to
management in Wisconsin?
CC = continuous corn CAAA = corn-alfalfa-alfalfa-alfalfa
CS = corn-soybean CAA = corn-alfalfa-alfalfa
CSW = corn-soybean-wheat Pasture
Increase in organic inputs (manure)
Increase in perenniality

5. 0
10
20
30
40
50
60
70
80
90
100
PMN(mgkg-1)
May 15, 2016
0
10
20
30
40
50
60
70
80
90
100
PMN(mgkg-1)
July 16, 2016
Forage-based > grain-based
(larger effected noted mid-season)
PMN
0-15 cm

6. 0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
180.0
200.0
PMC(mgkg-1)
May 15, 2016
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
180.0
200.0
PMC(mgkg-1)
July 15, 2016
Forage-based >= grain-based
(same effect during season)
PMC
0-15 cm

7. 0
300
600
900
POXC(mgkg-1)
May 15, 2016
0
300
600
900
POXC(mgkg-1)
July 15, 2016
Forage-based > grain-based
(effect seen all season)
POXC
0-15 cm

9. Comparison r
PMN vs PMC 0.802
PMN vs POXC 0.846
PMC vs POXC 0.809
Comparison r
SOC vs PMN 0.780
SOC vs POXC 0.795
SOC vs PMC 0.718

10. Are labile C and N pools responsive to
management in Wisconsin?
Survey approach
Collaborating farms participating in
Discovery Farms® Program
140 site years of data, collected
between 2015 and 2017

17. Summary
PMN was the most responsive pool, in terms of both
magnitude and significance.
PMC was only affected by shift to pasture.
POXC has small but significant difference between systems.
Also, it’s the system shift, rather than change in rotation
that drives these soil measures.

18. Summary
No effects using a survey-based approach to sampling.
◦Highlights the need for covariates!
Labile pools tend to be strongly correlated (r>0.7), but not
necessarily overly predictive of each other (r2 =0.4 to 0.6).

19. What’s next
What can we do with these labile pools?
Connection, in part with yield?
Will this work across multiple management and soil variables?
Standardizing soil health measures
Different effects determined at different sampling times.
Need to standardize sampling across all cropping systems.
When is the most important time to sample?
when samples can be taken consistently?
when the maximum value is expressed?

20. Questions?
Comments?
Concerns?