July 30-1050-Caitlin Caudle
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This study assessed soil health metrics across crop and hay fields in the Piedmont region of North Carolina. Soil samples were taken from 3 depths down to 1 meter across fields under different land management systems. Ten metrics were measured in the field and laboratory to evaluate differences between systems. Most metrics did not detect differences between crop and hay fields. Soil organic carbon and respiration rates differed between depths but not systems. Enzyme assays showed differences between depths and an interaction between system and depth. Standardized soil health measurement protocols need further refinement to be practical and effective at distinguishing management impacts.
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July 30-1050-Caitlin Caudle
- 1. Assessing Soil Health Metrics in the Piedmont of North Carolina Caitlin Caudle, Deanna Osmond, Matthew Ricker, Joshua Heitman, Rachel Cook North Carolina State University
- 2. Importance of Soil Health • Soil serves many important roles in ecosystems • Defined as: – “ The capacity of a soil to function within ecosystem boundaries to sustain biological productivity, maintain environmental quality, and promote plant and animal health.” (Doran and Parkin, 1994) Photos courtesy of USDA NRCS. 2
- 3. Soil Health Metrics • Chemical, physical, and/or biological indicators used to measure processes within soils • Can be measured in the field or in the lab • Little standardization in methodologies used • Ideal indicators and their ideal values are unknown Photo courtesy of USDA NRCS. 3
- 4. USDA-Natural Resources Conservation Service: Dynamic Soil Properties for Soil Health • NRCS provided a standard measurement and sampling protocols to all universities 4
- 5. North Carolina Soil Health Objectives • To identify differences in soil health status across Cecil soils under two extremes of land management systems • To assess proposed indicator variability between systems, within the systems, within fields, and with depth 5
- 6. Experimental Design • All fields mapped Cecil • 3 crop fields; 3 hay fields; 1 forest field • 1 pit dug in one field of each system and characterized • 3 sample locations in each field oriented downslope • Total of 20 sample locations; 9 crop, 9 hay, 2 forest 6
- 7. Sampling Methods • Soils sampled in March 2018 • Cores divided by depth to 100 cm • Bulk samples homogenized and air dried • Natural fabric samples collected and air dried 7 0 – 5 cm Bottom of A Bt1 Bt2 5 – 10 cm
- 8. Methods • Total of 10 metrics measured – 2 in field – 8 in lab • Field metrics completed in each field June 2018 • Lab metrics completed on each sample depth 8
- 9. Indicators 9 Field Methods Metric Measured Units Cornell Sprinkle Infiltrometer Infiltration (simulated rainfall) cm/min Single Ring Infiltration Infiltration (ponded head) cm/h In Field Soil Health Assessment Visual field conditions high/medium/low Lab Methods Metric Measured Units Dry Combustion Soil organic carbon % total Autoclave Citrate Extractable Protein Content Soil protein content mg/g soil p-Nitrophenyl Enzyme Assays (𝛽-glucosidase, 𝛽-glucosaminidase, acid phosphatase, alkaline phosphatase, phosphodiesterase, arylsulfatase) C, N, P, and S cycling mg p-Nitrophenyl /kg soil/hour Wet Macroaggregate Stability using Yoder device Aggregate mean weight diameter mm > 0.5 mm Aggregate Retention Aggregate stability % CO2 Respiration after 4 day Incubation Mineralizable C mg CO2 Permanganate Oxidizable Carbon using 0.02 M KMnO4 and < 2 mm soil Active C mg reactive C/ kg soil Phospholipid Fatty Acid Analysis Microbial community structure pmol/g soil
- 10. Statistical Design • Split-Strip design • Fields were replicates 10 C B A 0-5 cm 5-10 cm Bottom A Bt1 Bt2 C Shoulder Slope Back Slope Foot Slope
- 11. Results • Mixed Model • SAS • 2 field metrics • 14 lab metrics – Included 6 enzyme assays 11
- 12. Indicator System Pedon Depth System* Pedon System* Depth Depth* Pedon System* Depth* Pedon SOC NS NS *** NS NS NS NS CO2 Respiration * NS *** NS NS NS NS POxC NS NS NS ** ** NS NS β-Glucosidase NS NS *** NS *** NS NS β-Glucosaminidase NS NS *** NS NS NS ** Alkaline Phosphatase NS NS *** NS NS NS NS Acid Phosphatase NS NS *** NS *** NS NS Phosphodiesterase NS NS *** NS NS NS NS Arylsulfatase NS NS *** NS *** NS NS ACE Protein NS NS *** NS NS NS NS Aggregate Retention * NS *** NS *** NS NS Mean Weight Diameter NS NS *** NS NS NS NS Sprinkle Infiltrometer NS NS N/A NS N/A N/A N/A Single Ring Infiltration NS NS N/A NS N/A N/A N/A 12
- 13. Soil Organic Carbon Depth 0 0.5 1 1.5 2 2.5 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 %weightC Depth a b c d d 13
- 14. CO2 Respiration 0 10 20 30 40 50 60 70 80 Crop Hay mgCO2Respired System a b 14 0 10 20 30 40 50 60 70 80 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 mgCO2Respired Depth a b c d d
- 15. 712 713 714 715 716 717 718 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 mgC/kgsoil Depth System*Depth Crop Hay Permanganate Oxidizable Carbon 712 713 714 715 716 717 718 A B C mgC/kgsoil Pedon Pedon*Depth Crop Hay a c b ab ab bc 15 aa a b b c de cd ef f
- 16. Carbon Cycling Enzymes 0 100 200 300 400 500 600 700 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 ugp-nitrophenyl/gsoil/hour Depth B-Glucosidase System*Depth Crop Hay b a c d e ef f f ff 16
- 17. Phosphorus Cycling Enzymes 0 100 200 300 400 500 600 700 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 ugp-nitrphenyl/gsoil/hour Depth Alkaline Phosphatase Depth a b c 17 0 50 100 150 200 250 300 350 400 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 ugp-nitrophenyl/gsoil/hour Depth Acid Phosphatase System*Depth Crop Hay a bc c d de e e e e b
- 18. Structural Stability 0 20 40 60 80 100 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 %retention Depth Aggregate Stability (NRCS) System*Depth Crop Hay a a b cc c cd d d d 18 0 0.5 1 1.5 2 2.5 3 0-5 cm 5-10 cm Bottom of A Bt1 Bt2 mm Depth Mean Weight Diameter (ARS) Depth b a b c c
- 19. Conclusions • Many metrics were not sensitive enough to detect differences between management systems • Metrics meant to represent similar soil processes showed different results • Protocols provided by NRCS required further clarification and standardization • Protocols provided were labor intensive and time consuming, not suitable for high-throughput commercial settings 19
- 20. Acknowledgements • Thank you my committee: Deanna Osmond, Josh Heitman, Matt Ricker, Rachel Cook. • Thank you to Grady Miller for assistance with statistics. • Thank you to Skye Wills and Debbie Anderson of USDA – NRCS for technical guidance and assistance with sampling. • Thank you to the Gardner lab for the use of the lab space. • Special thanks to the Adam Howard, Chris Neiwoehner, and Wes Childres for technical assistance with sampling. • Funding was provided by USDA-NRCS Soil Survey Division. 20
- 21. Questions 21
Notas del editor
- Water filtration Growth medium Source of plant nutrients Habitat for organisms Have definition, but wide variety of soil types and uses make it hard to determine what an ideal or healthy soil function is
- Chemical physical and biological indicators are used to measure specific processes in soils By measuring the processes can measure how well a soil is functioning and theoretically measure the health In field or in lab Haney test CASH co2 example, both include it but have two different protocols Ideal indicators are unknown because the wide range of soil types and functions, making ideal indicator values unknown. Indicator values may change with soil type or management system
- Project is part of the science of soil health initiative NRCS provided a standard measurement and sampling protocol to each university Looking at the map, wide variety of soil type and management systems represented
- Cecil was chosen because it is the state soil of NC and a common soil in agricultural production in NC The two management systems were chosen because of their extreme differences and they are common management systems in the piedmont of NC
- NRSC personnel selected the fields All fields mapped cecil and Management history is known for each field for the past five years NRCS personnel dug the pits and characterized the soil The forest location serves as a baseline Cecil soil that has not experienced any management in five years 3 sample location in each field oriented downslope Slope positions are roughly shoulder slope, back slope, and foot slope Pedons are equidistance apart within each field based on the size of the field, where the map unit is in the field, and the slope of the field Only two forest locations because of equipment limitations
- Sampled in march of 2018 using a giddings probe Natural fabric samples are naturally occurring aggregates or clods that haven’t been disturbed
- Lab metrics completed May 2018 to June 2019
- Infiltration done at each sample location, field assessments done in each field Includes 8 individual protocols, but also measured 5 enzymes. Point out that we measured a variety of physical, chemical, and biological indicators that represented many different processes in the soil such as nutrient cycling, water infiltration, aggregate formation
- Split component is pedons within each field because they are equidistance apart and split could account for the spatial variability
- Show that system and pedon don’t have many significant interactions, most are in depth. But the rest are System*Depth interaction, with just two elsewhere Emphasize that the sections are for indicators measuring similar things, but they do not share any significance patterm. PLFA was not done in our lab.
- Shows a decrease in total SOC with depth, which is an established trend But showed no difference in the systems
- CO2 showed higher respiration in crop, and with the “more is better” thinking would make a cropping system “healthier” than a hay system
- Alkaline phosphatase didn’t work really well on these soils, which was expected as Cecil soils are acidic