Hormel Foundation Mower Soil Health Initiative comparative cropland study

Soil Health Indicator Results – Interpreting Tables and Boxplots The tables and boxplot figures in the report compare the results across the three Management Types (Conventional = CV, Soil Health: SH, and Benchmark = BM) together and at different levels of separation:

Tables: This is a basic level summary (example from report, Table 5.1): Table 5.1: Results for Worm Count for All Sites aggregated and by Management Type.

Worm Count (Number/ft3)

All Sites

CV

SH

BM

Number of Samples*

84

30

30

24

Average Median

9.1 7.5

4.3 (- - -) 3

14.1 (+++) 13.5

9.2 (=) 8

*Same BM plots used for both 3S and 3N. The Number of Samples shows how many values were reportable and used for each combination being All Sites (all samples combined) and then separated by Management Type (CV, SH, BM).

The Average is the calculated middle of values when added together. The Median is the middle value collected. We compared the Average and Median to ensure that the averages used in our reporting of results provided a good comparison across all three management types. This is especially important when there were outliers that could have an influence on the average. With the high number of samples collected, a few outliers did not skew the results very much, so the averages were a good comparison in this study.

The (+) and (-) next to the Average is provided to show how the Management Type Averages compared with the All Sites Average.

Underlined indicates where a “notable difference was observed by reviewing medians and adjacent boxplots (See example, next page).

Boxplots) Box-plots (examples, next page) visually display the central values (average and median) as well as how the samples varied (range in values). A video on boxplots can be viewed here; (196) Understanding & Comparing Boxplots (Box and Whisker Plots) - YouTube The boxplot includes a box (middle 25% to 75% of values) and whiskers (lines that extend to the <25% and >75% of values). At the center of each box are displayed the median (center line, actual middle value of samples reported per grouping) and average (x, the calculated average of all values reported per grouping). If there was no overlap of the median line and adjacent boxplot being compared, the results were considered a “noteable difference”. When the median of the boxplots overlapped with an adjacent boxplot (upper or lower part of box, see example above) the results were observed to be different but given the range in the sample values, perhaps a slight to moderately notable difference.

Below is a real example from the report for Worm Count by Management Type. When comparing SH and CV, the median of SH is higher than the top of box for CV, and so considered a “notable difference. When SH is compared with BM, the median for SH is still above the top of box for BM and the median of BM is below the lower half of the box for SH, so also considered at least a “moderately notable difference”.

In addition, we included a gray dashed line that extends across all three boxplots. This is the All Sites average calculated for all the samples (from Table 5.1 above). This line is only meant to be a guide with which to more easily compare visually the results across Individual Sites (i.e., like a fixed in place high-jump bar and which ones performed better or worse or about the same).

Occasionally, there are some values that are displayed as dots that fall outside of the box and whiskers.

These are considered outliers, since these samples were not typical of the range in values reported. These

outliers were reviewed and included if likely the result of normal field conditions encountered during sample collected and noted (e.g. tire tracks) and not due to lab analysis issues.

In this report, we also show results at different levels of separation (All Sites, Individual Sites, Hillslope Position). For example, the set of boxplots on the left show the results for the two hillslope positions together while the set of boxplots on the right display the results when the two hillslope positions are separated into upland (UL) and lowland (LL). Again, the gray dashed line is just an added visual reference to more easily compare results across the different groupings.

Figure 5.1: Boxplots for Worm Count for All Sites for both hillslope positions combined (left) and when separated (on right).

2 - Bulk Density Hormel Founda on - Mower Soil Health Ini a ve Compara ve Cropland Study (2018-2020)

Bulk density (BD) is defined as the propor on of the weight of a soil rela ve to its volume, typically expressed as g/cm3 of soil.

How BD informs soil health: Bulk density can affect infiltra on, available water capacity, soil porosity, roo ng depth/restric ons, root prolifera on and microbial ac vity. Bulk density increases with compac on.

Soils with a bulk density higher than 1.6 g/cm3 tend to restrict root growth.

Sample Collec on: In 2018, 271 samples were collected by students from UWRF. Soil core samples were taken from the 3 to 6 cm depth at 8 points equally spaced along each 350- transect line. All samples were collected during the early part of the growing season, but on different dates (Site 1: July 11, Site 2: July 9, Site 3N and 3S: June 22, Site 4: June 4, Site 7: May 29).

During summer of 2020, BD samples were also collected from deeper within the soil profile at 4-6 inches by the Mower SWCD. This was done due to recent research that used this deeper depth and the interest of comparing the Mower Soil Results with other research. Currently, only the 2018 results are available and are reported here.

Lab Analysis: In the field, each soil core sample was placed in pre-weighed ns. Samples were then brought to the Soil Lab at UWRF for oven drying. Each Sample was first oven dried at 105 deg C for a minimum of 24 hours to remove the weight of soil moisture so that only the dry weight of soil remained. BD (g/cm3) was calculated by dividing the dry soil mass (g) by the volume of the brass cylinder (cm3) .

Results: The following tables and figures show the 2018 results. In total 271 samples were included in the analysis and reported within the following tables and figures. (See Soil Health Indicator Results – Tables and Boxplots in the documents a ached for informa on on how to interpret these formats).

Across All Sites (all samples), the number of samples reported for CV and SH was similar (Table 2.1); only 1 sample for SH was not reportable (Site 1: SH-LL). Fewer samples were reported for BM since the same plots were used for both 3N and 3S. The calculated average and median values are very close, demonstra ng that using the average provides a good comparison of the following results.

Table 2.1: Results for Bulk Density (BD) for All Sites and by Management Type.

Bulk Density (g/cm3)

All Sites

CV

SH

BM

Number of Samples*

271

96

95

80

Average Median

1.10 1.08

1.10 1.06

1.26 1.25

0.91 0.92

*Same BM plots used for both 3S and 3N.

From Table 2.1 above and Figure 2.1 below (on le ), results for All Sites by Management Type show that average BD was slightly lower (less compact) at CV than SH and both were much more compact than BM. These averages for BD (g/cm3) for CV (1.10) and SH (1.26) are well within acceptable range for bulk density.

BD results typically only become a factor in retarding root penetra on when nearing 1.6. A few samples within both CV and SH Management Types were close to or above that. Those plots are iden fied within the following the Results by Individual Site sec on below.

When results were separated by Hillslope Posi on (Figure 2.1, on right), the upland (UL) plots had much higher average BD than the lowland (LL) plots across all three Management Types.

Figure 2.1: All Sites combined for BD by Management Type (le ) and by Hillslope Posi on (right).

For Individual Sites (Figure 2.2, next page, columns on le ), average BD was lower at CV than SH for 5 of 6 sites; Site 2 being the only excep on. In comparison, average BD was slightly to much lower for BM than either CV or SH, with the biggest difference observed at Site 1.

By Hillslope Posi on (Figure 2.2, columns on right), the upland plots for all six study sites had higher average BD than the lowland plots. There are sample values for BD that are close to or above what is considered detrimental to root growth (1.6) at 5 of 6 Sites (Sites 1, 2, 3S, 3N, and 7) for either CV or SH, or both.

Interes ngly, all were within the upland plots which likely relates to the lower total carbon as compared to the lowland plots.

2-Bulk Density, page 2

Figure 2.2: Individual Site results for Bulk Density (BD).

2-Bulk Density, page 3

2-Bulk Density, page 4

3 - Aggregate Stability Hormel Founda on - Mower Soil Health Ini a ve Compara ve Cropland Study (2018-2020) Aggregate Stability (AgS) is the ability of soil aggregates to maintain form when exposed to wind or water.

How AgS informs soil health: Higher values (reported as % stable frac on) means that the soil is more able to resist erosion due to wind and water. A higher AgS can also mean the soil may have a higher water infiltra on rate.

Sample Collec on: In total, 248 Soil samples were collected during 2018 by students from UW-River Falls.

While the samples at individual sites were collected on different dates, all samples at each Site were collected on the same day (Site 7 - May 29, Site 4 - June 4, Site 3S - June 14, Site 3N - June 22, Sites 1 and 2 July 2). At each plot, 8 samples were collected at evenly spaced points along the 350- transect line. Samples were extracted from the upper 10cm of the soil profile using a hand trowl and placed in zip-lock baggies un l processing. Due to an unusually wet growing season and me constraints, samples were not able to be collected at a few Study Sites and plots (Site 3S-CV samples; Site 3S-SH (2 samples, 1 per hillslope posi on).

Some plots were resampled in 2020; however, only the 2018 results were included in this report.

Lab Analysis: Samples were processed by the Soil Lab at UW-River Falls. Using the method outlined in Kemper and Rosenau (1986), the propor on of stable aggregate (AgS%) is determined through a series of lab procedures and weights.

Kemper W.D and R.C. Rosenau. 1986. Aggregate stability and size distribu on. In Methods of Soil Analysis, 2nd ed., ed. A. Klute. 425-442. Madison, WI: American Society of Agronomy.

During lab analysis, some errors in the applica on of the methods occurred. Hence not all field collected soil samples are included in the results: [Site 3S-SH (2 samples -1 at LL, 1 at UL); Site 1-BM (8 samples at LL)].

Results: The following tables and figures show the 2018 results.Out of the total number of 248 samples collected, 227 samples were reportable (Table 3.1).

Note: For CV and SH, some outliers are present (dots below boxplots). These were reviewed and included since at present there is not a known reason to exclude and there was li le influence on the results. In view of the similarity in results between the calculated averages and median values, the aggregated AgS results by Management Type should s ll provide a rela vely good comparison.

Table 3.1: Results for Aggregate Stability across All Sites and by Management Type.

AgS (%)

All Sites

CV

SH

BM

Number of Samples*

227

73

85

69

Average Median

96.6 97.5

94.5 (-) 94.9

96.6 (=) 97.4

99.0 (++) 99.1

*Note: Same BM plots used for both 3S and 3N. Some samples not included due to lab issues (see above).

By Management Type, average AgS was slightly higher for SH than CV with BM higher than both (Table 3.1, Figure 3.1). When comparing the boxplots, the results of SH are considered significantly higher than CV (See Soil Health Indicator Results – Tables and Boxplots in the a achments for informa on on how to view and interpret these formats).

Figure 3.1: All Sites by Management Type (le ) and then separated by Hillslope Posi on (right).

Comparisons for All Sites by Management Type and Hillslope Posi on

By Hillslope Posi on (Table 3.2, Figure 3.2), the lowland plot averages for each Management Type are slightly higher than the upland posi on; however, the difference is small (<1%). The biggest difference in AgS between Hillslope posi ons is within the CV plots (0.8%), followed by SH (0.2%), while BM had the least difference (0.1%). While the average differences are small, the results between CV and SH are significantly different when the median of SH is compared with the top of the boxplot for CV. .

Table 3.2: Aggregate Stability (AgS) by Management Type and Hillslope posi on*.

AgS

All Sites

CV

SH

BM

Number of Samples

104

123

39

44

39

46

38

31

Hillslope Posi on

UL

LL

UL

LL

UL

LL

UL

LL

96.5 96.5

96.8 97.6

94.1 93.9

94.9 96.2

96.5 97.2

96.7 97.4

98.9 99.0

99.0 99.1

Average Median

*UL = upland, LL = lowland

3-Aggregate Stability, page 2

Individual Sites When results are compared at the Individual Site level, (Table 3.2, Figure 3.2 on le ), the average AgS for SH is higher than CV, but for most, the difference is small. The biggest difference between CV and SH being at Site 1, followed by Site 2.

Figure 3.2: Individual Site Results for AgS by Management Type (le ) and HIllslope Posi on (right).

Note: The boxplot for CV is very long since the outlier is now contained (lower edge).

Note: No CV was collected at Site 3S in 2018.

3-Aggregate Stability, page 3

3-Aggregate Stability, page 4

4 - Soil Organic Carbon (TOC and AC) Hormel Founda on - Mower Soil Health Ini a ve Compara ve Cropland Study (2018-2020) Soil Organic Carbon (SOC): The amount of organic carbon within the upper depth of soil. SOC provides food for bacteria and fungi that in turn provide food for earthworms and other soil microorganisms. This underground microbial community then unlocks soil nutrients and frees carbon through bacterial decomposi on and diges on for plant uptake and growth, thus benefi ng cropland produc vity.

How SOC informs soil health: A soil low in SOC can lead to decreased microbial ac vity and lower nutrient availability for plants as well as lower infiltra on through poor soil aggrega on (low aggregate stability and higher bulk density), causing lower infiltra on rates and lower soil water capacity. These factors can all affect cropland produc vity.

SOC Soil Health Indicators: For this study, SOC was analyzed using two indicators. These are both informa ve for assessing soil health, by viewing carbon available in different ways.

Total Organic Carbon (TOC): A measure of the total available pool of carbon within the top layer of the soil.

Ac ve Carbon (AC): The small frac on (1% to 4%) of TOC that is being ac vely decomposed by bacteria and transformed into a readily available food/energy source for microorganisms.

Sample Collec on: Samples were collected during July 2018 by students from UWRF. All soil samples at each Site were collected on the same day (July 2 for Sites 1 and 2, July 5 for Site 7, July 9 for Site 3S, and July 16 for Sites 3N and 4). For each plot, soil samples were taken from the upper 6 inches of the soil profile at three fixed loca ons (beginning, middle, end) along the 350- transect line within each hillslope plot. Samples were placed in zip-logged bags and temporarily stored at Mower SWCD un l sent out for lab processing.

Note: During 2021, a deeper core was sampled and analyzed (up to 12 inches). Other research has shown that SOM is most prevalent and available to plants within this zone, and the deeper depth provided a more direct comparison with other studies. Only the results of 2018 are available and reported here, with 2021 data currently being prepared.

Lab Analysis: Frozen samples were maintained and sent by expedited delivery to The Soil and Plant Tes ng Lab - University of Missouri. In total, 101 soil samples were analyzed for SOC as TOC% and AC (ppm).

For TOC, the soil samples were oven dried and then combusted to get the frac on of organic material of the total mineral and organic weight and reported as %TOC. For this report, these results were then converted to TOC (US tons/acre-0.5 ) using the average bulk density for each corresponding hillslope plot (UL or LL) and depth of soil core samples collected (0.5 ).

For AC, the POXC method was used (see (Ac ve carbon (POXC): What does it measure? - Agvise Laboratories). The lab reported unit were in Mg/ha. These were converted to parts per million (ppm) for this report.

Since TOC% and Ac ve C (Mg/Kg) are typically well associated, but may not be given certain field condi ons and differences in microbial ac vity, we compared how well the two corresponded from our results (Figure 4.0 below). While there is fairly good correspondence across all samples collected, there is s ll some variability observed. There is higher variability (low associa on) in the CV results (R^2 = 0.19) with a higher degree of associa on for SH and BM (R^2 = 0.95 and 0.93, respec vely).

Figure 4.0: Ac ve C vs TOC at the Mower Study Sites.

Results: The following tables and figures display the 2018 results. See Soil Health Indicator Results – Tables and Boxplots for informa on on how to view and interpret these formats.

The sca erplot and bar graph in the link (Ac ve carbon (POXC): What does it measure? - Agvise Laboratories) show that for agricultural soils in the upper Midwest and Northern Great Plains, AC is typically between 400 ppm to 1000 ppm. Our results fell within those ranges (Table 4.1).

All Sites by Management Type For TOC and AC, averages were only slightly higher for SH than CV with BM averages much higher (Table 4.1 and Figure 4.1 (on le ).

Table 4.1: Results for Total Organic Carbon (TOC) and Ac ve Carbon AC) for All Sites by Management Type.

Soil Organic Carbon (SOC) Number of Samples*

All Sites

CV

SH

BM

101

36

36

29

TOC (US tons/acre-0.5 )

Average Median

26.2 25.8

22.8 (- -) 20.9

26.4 (=) 22.8

30.0 (+) 29.7

AC (ppm)

Average Median

676 689

589 (-) 538

595 (-) 522

886 (++) 788

*Fewer samples collected for BM since the same plots were used for both 3S and 3N.

4-TOC and AC, page 2

All Sites by Management Type and HIllslope Posi on When separated by Management Type and Hillslope Posi on (Table 4.2, Figure 4.1 on right), both TOC and AC were no ceably higher in the lowland (LL) posi on. Most notably, when the results are compared between CV and SH by Hillslope Posi on (Table 4.2, Figure 4.1), SH is significantly higher than CV at both upland and lowland posi ons.

Table 4.2: Results for Total Organic Carbon (TOC) and Ac ve Carbon (AC) by Management Type and Hillslope posi on (UL = upland, LL = Lowland).

Soil Organic Carbon (SOC)

All Sites

CV

SH

BM

Hillslope Posi on

UL

LL

UL

LL

UL

LL

UL

LL

Number of Samples

51

50

18

18

18

18

15

14

TOC (US tons/acre-0.5 )

Average Median

21.9 19.9

30.5 29.9

18.0 18.0

27.6 28.2

19.9 19.6

33.0 32.5

29.1 29.6

30.9 32.2

AC (ppm)

Average Median

535 455

821 797

430 413

744 763

438 427

753 790

772 699

1007 880

Compared with BM, notably, average TOC for SH was higher than BM in the lowland, but lower than BM in the upland (Table 4.2, Figure 4.1).

Figure 4.1: Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) for All Sites for both hillslope posi ons combined (le ) and when separated (on right).

4-TOC and AC, page 3

Individual Sites The following Individual Sites boxplot figures display the results of TOC and AC as a four (4) block grouping with combined results (on le ) by Management Type and then Hillslopes separately (on right).

For TOC, the averages for Combined by Management Type for all six study sites were higher for SH than CV. For BM, TOC was slightly to no ceably higher than either CV or SH at four sites (1, 3S, 3N, and 4), while BM was similar to slightly lower than SH at two sites (2 and 7).

When results are separated by Hillslope Posi on and compared within each Site and Management Type, the upland (UL) plots were consistently lower than the lowland (LL) plots. When comparing across the Management Types, there were a few hillslope plots where the average TOC for CV was higher than SH (UL for 3S, LL for 7).

For AC, results were not as consistent as they were for TOC. When comparing CV and SH, average AC for combined was slightly higher for CV than SH at two sites (3S and 4), about the same for two sites (3N and 7) and slightly higher for SH than CV at only two sites (1 and 2).

Figure 4.2-Site 1: Individual Site 1 Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

4-TOC and AC, page 4

Figure 4.2-Site 2: Individual Site 2 Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

4-TOC and AC, page 5

Figure 4.2- Individual Site 3S Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

Figure 4.2-Site 3N: Individual Site 3N Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

4-TOC and AC, page 6

Figure 4.2-Site 4: Individual Site 4 Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

4-TOC and AC, page 7

Figure 4.2-Site 7: Individual Site 7 Boxplots for Total Organic Carbon (TOC) and Ac ve Carbon (AC) with hillslope posi ons combined (le ) and separated (on right).

4-TOC and AC, page 8

5 - Worm Count Hormel Foundation - Mower Soil Health Initiative Comparative Cropland Study (2018-2020) Worm Count: The density of earthworms (e.g., red worms and nightcrawlers).

How Worm Count Informs Soil Health: The more worms, the more active underground tillers of the soil.

Tunnels made by worms can lessen compaction, increase water infiltration, and improve aeration. Worms also digest decaying plant materials (enriched with bacteria and fungi) to make nutrients more bioavailable for crops throughout the growing season.

Sample Collection: In total, 84 worm counts were collected. Worms were counted in the field from 1 cubic foot of soil (ft3) at 3 points per 50 ft transect (beginning, middle, end) at each plot. Note: no worm counts were collected at Site 7. All worm counts occurred during the growing season.

Results: The following tables and figures show the 2018 results (See Soil Health Indicator Results – Tables and Boxplots in the documents attached for information on how to view and interpret these formats).

Table 5.1: Results for Worm Count for All Sites aggregated and by Management Type.

Worm Count (Number/ft3)

All Sites

CV

SH

BM

Number of Samples*

84

30

30

24

Average Median

9.1 7.5

4.3 (- -) 3

14.1 (+++) 13.5

9.2 (=) 8

*Same BM plots used for both 3S and 3N. Worm Count ranged from 0 to 33 with an All Sites (all samples) average of 9.1 (Table 5.1). The average Worm Count by Management Type was higher for SH than CV. However, there was a large range in the density of worms collected, especially for SH (long box-plot and extended whiskers) with one outlier at BM (dot on boxplot, Figure 5.1).

Figure 5.1: Boxplots for Worm Count for All Sites by Management Type (left) and Hillslope Position (right).

When separated by Hillslope Position, average worm counts at CV were similar between upland and lowland; where, for SH, the results were highly variable, with the average for lowland being slightly higher at the upland position. This was similar for BM, where the average worm count for lowland was slightly higher than for upland as well. There were also a few samples with much higher worm counts than others within each Management Type (dots in figures). Interestingly, the highest worm counts (>20) were all collected at lowland position at SH and BM (SH: Sites 1, 3S, and 4; for BM: Site 3S/3N); whereas, for CV there were very few worms (<5) counted within the lowland plots.

For Individual Sites, Worm Count for SH was higher than CV at all study sites where collected (no worm counts collected at Site 7). The average Worm Count for CV was much lower than SH at three sites (1, 3S, and 3N). Compared with BM, the average worm counts for CV and SH were fairly similar or even above the average worm counts at BM. When comparing the hillslope positions by Management Type at a Site, Site 1 showed the greatest difference in worm count for SH between upland and lowland while worm count for CV was low at both positions. Also at Site 1, the lowland average worm count for SH was >30 and for BM and CV it was <10. For BM, worm count showed the greatest difference between hillslope positions at 3S/3N, where lowland was much higher. In contrast, the average worm count for BM at Site 4 was higher in the upland position and much lower than either SH or CV. Figure 5.2: Boxplots for Worm Count for Individual Sites for both hillslope positions combined (left) and when separated (on right).

5-Worm Count, page 2

5-Worm Count, page 3

Note: No worm counts were collected at Site 7.

5-Worm Count, page 4

6 - Microbial Community Measures Hormel Foundation - Mower Soil Health Initiative Comparative Cropland Study (2018-2020) Microbial Community: The soil microbial community of bacteria, fungi, and other microscopic organisms provide a wide range of functions for soil health, including managing soil fertility, improving soil structure and degrading pesticides, depending on the activity of the microorganisms present.

The following provides a general background on this new emerging area of soil health using microbial community measures: Soil samples are often collected within the dripline of plants (e.g., corn or soybeans) since this is within the active zone where most soil biological activity is known to take place (i.e., where plant roots produce an exudate (sugar water) that feeds the bacteria and fungi to establish a mutually beneficial relationship).

There are various methods that are being tested to identify the types of soil communities present and estimate their abundance. The lab method used for our samples, the Phospholipid Fatty Acid (PLFA) test, has been used by many researchers as a way to separate and identify basic groups and subgroups of soil organisms present. The PLFA method separates proteins and other organic and inorganic materials by a combination of chemical additives and centrifugal force.

Other techniques are currently being explored (DNA analysis, direct observation using a microscope). These methods may more accurately identify the organisms present (DNA analysis) or employ a microscope to view soil aggregates directly and provide a way to know the whether soil organisms are active (i.e., by observing movement of bacteria, protozoa, nematodes, lengths of mycorrhizal hyphae) or lying in a dormant state (e.g., round cysts of protozoa or nematodes, spores of mycorrhizal hyphae). This additional knowledge could provide a more accurate and current understanding of the biological component of soil health that provides benefits to plants (i.e., continual unlocking of nutrients and providing access to nutrient pool to plants).

Research in this area is still new on deciding on which soil organism groups or ratios make good soil health metrics. We compared a few different groups for this report (table below); however, there are likely other ones to explore.

For our study, we selected three soil microbial community Indicators:

Microbial Community Measures

What it is

How it can inform Soil Health

Total Microbial Biomass (TMB) (nmole/g)

How much soil mass is made up of micro organisms (bacteria, fungi, protozoa, nematodes, microarthropods).

While this is viewed as a useful measure of soil health conditions, given the understanding that more bacteria is better for decomposition of organic matter and unlocking soil nutrients, it can be challenging to compare across Sites collected at different times of the growing season. Factors such as temperature, precipitation, aerobic and anaerobic soil conditions, and amount of organic material available can interplay in the growth speed of bacteria and so TMB can vary from week to week.

G+/G- Bacteria (ratio)

A ratio between the weight of the proteins of both Gram positive (+) and Gram negative (-) bacteria.

The usefulness of this ratio is still unknown as research is still ongoing in this area. Soils with higher Gram+ bacteria counts may be viewed as healthier than soils with higher Gram- bacteria counts. This may be due to the conditions under which the bacteria are more active and multiplying --or dormant. Gram+ bacteria do better under aerobic conditions (when air is present), and many Grambacteria can tolerate and even thrive under anaerobic conditions (e.g., where air is limited either negatively - such as very wet conditions -- or positively such as inside soybean nodules).

AM Fungi (nmole/g)

Fungi grow underground as filaments of different lengths and inactive spores. A mushroom is the above ground “flower” that disperses the spores.

Arbuscular Mycorrhizal Fungi (AM Fungi) form a symbiotic relationship with plants. The filaments of the fungi grow both within and outside of the roots of plants, thereby essentially extending the root zone and allowing a greater pool of nutrients to be accessed and shuttled back to cropland plants through the AM Fungi filaments.

Sample Collection: 102 Infield soil samples were collected by students from UWRF and UMTC during 2018.

A 6-inch soil core sampler was used to collect 3 samples around the dripline of a singular plant and composited for each soil sample taken from 3 sample positions (beginning, middle, end) along the 350ft transect within each sample plot. All samples were collected the early part of the growing season at the same time samples were collected for BD and AgS. Soil samples were stored in a deep freezer at UMTC until being sent out for lab analysis.

Lab Analysis: In total, 102 soil samples were put on ice and sent via express mail to The Soil and Plant Testing Lab at the University of Missouri for lab analysis using the PLFA soil test.

6- Microbial Community, page 2

Results: The following tables and boxplots display the 2018 results. (See Soil Health Indicator Results – Tables and Boxplots in the documents attached for information on how to view and interpret these formats).

All 102 samples collected were reportable (Table 6.0). Each Management Type had a similar number of samples (Table 6.0). Note: the same BM plots were used for both 3N/3S = 6 fewer samples.

By Management Type, the averages for CV and SH for all three biological measures are very similar.

Compared to BM results, both CV and SH averages are over 2 times lower for TMB and Am Fungi but not much lower for Gram+/Gram- Bacteria.

Table 6.0: Results for three soil biology community measures for All Sites and by Management Type.

Microbial Community Indicators Number of Samples

All Sites

CV

SH

BM

102

36

36

30

TMB (nmole/g)

Average Median

150.3 110.2

103.2 (- -) 102.3

100.1 (- -) 96.8

267.1 (+++) 236.9

Gram+/Gram- Bacteria (Ratio)

Average Median

25.0 25.0

23.1 (-) 23.3

24.2 (-) 25.0

25.7 (+) 28.6

AM Fungi (nmole/g)

Average Median

6.22 4.84

4.30 (- -) 4.20

4.32 (- -) 4.20

10.82 (+++) 10.06

When comparing the calculated averages and medians for each indicator, we see that the the averages for each indicator and their medians are fairly close (Table 6.0 above, Figure 6.0 below), with some larger differences observed (e.g, TMB and Am Fungi for All Sites).

However, when viewing Management Types individually (Figures 6.1, 6.2, 6.3) we see that the averages (x on boxplots) and medians (center line of boxes) are in fairly close agreement, confirming that the averages do provide a relatively good comparison between the three Management Types.

The lack of a difference between these three microbial community measures by Management Type could feasibly be related to an abnormal summer with multiple precipitation events causing anaerobic soil conditions prior to sample collection. Additional data was also collected for a different study in 2019 by the students with the UMN Office of Soil Health. A comparison of the data and results between these two years (2018 and 2019) may provide insight as to whether or not the microbial community results presented here in 2018 may have been impacted by wet soil and potentially anaerobic conditions.

6- Microbial Community, page 3

Figure 6.0: Boxplots of three Microbial Community Measures by Management Type.

Results for Individual Sites 6- Microbial Community, page 4

Total Microbial Biomass (TMB) - Results are very similar between CV and SH, but there were slight differences. At 4 of 6 sites, TMB at CV was slightly to moderately higher than SH--only two sites (Sites 2 and 4) had slightly higher TMB at SH than CV. TMB for BM was much higher than CV or SH at most sites but less so at Sites 4 and 7.

6- Microbial Community, page 5

Gram+/Gram- Bacteria: Averages for SH were slightly higher than CV at most sites, except for Site 2 where CV was slightly higher. For BM, G+/G- Bacteria was higher than CV and SH at all Sites, but only slightly higher at Sites 4 and 7.

Arbuscular Mycorrhizal Fungi (AM Fungi) – The boxplots below show mixed results at the Individual Sites level: at half the sites, SH was higher than CV, while at half the sites, CV was higher than SH. For BM, AM

6- Microbial Community, page 6

Fungi was much higher than either CV or SH at most sites (except for Site 4), with no overlap in the boxplots.

Results by Hillslope position (next page)

By Hillslope Position, there was not much difference for CV and SH for all three indicators. In comparison, BM had higher averages for TMB and Am Fungi in the lowland position, while G+/G- was slightly higher in the upland position.

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The following groups of figures show the results for individual Sites:

6- Microbial Community, page 8

Individual Sites - TMB

Individual Sites - Gram+/Gram- Bacteria

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6- Microbial Community, page 10

Individual Sites - Am Fungi

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7- Infiltration Rate Hormel Foundation - Mower Soil Health Initiative Comparative Cropland Study (2018-2020) Infiltration Rate: The speed at which water moves downward through the soil profile.

How the rate of infiltration informs soil health: Typically, a soil with good soil structure allows for a higher infiltration rate where both air and water move quickly and easily through soil pores ensuring roots are both well-watered and well-aerated. A soil with a low infiltration rate will more often succumb to anoxic conditions as water impedes airflow more often and for longer periods of time during and after precipitation events. Conversely, when infiltration of air and water is better, the rooting depth of cropland plants also tends to be deeper. A longer rooting depth enhances the ability for plants to be more drought resistant as well as providing a deeper access to nutrient pools that are constantly being unlocked and delivered by a healthy microbial ecosystem.

For this study, two different methods were employed to determine infiltration rate: a) Field Saturated Hydraulic Conductivity (Kfs). This method uses a constant head well permeameter (CHWP) technique. The soil is first brought to saturated conditions within the well (ring). After saturation conditions achieve a steady-state of downward movement of water through soil, the rate of infiltration is measured (Kfs in cm/hr). This allows all soil samples, regardless of varying moisture conditions related to proximity in time to precipitation events, to be measured at a similar condition. This is considered a better method of determining soil permeability than the Perc Test (https://dynamicmonitors.com/relationship-of-kfs-to-percolationtime/#:~:text=Field%20Saturated%20Hydraulic%20Conductivity%20a%20True%20Soil%20Characteri stic,of%20soil%20permeability%20than%20the%20outdated%20Perc%20Test). b) Degree of Compaction: This method uses a core penetrometer that when pushed through the soil profile, the device records the depth and a measurement for resistance (i.e., degree of compaction).

This information can be used to infer the degree of infiltration, as highly compacted soils greatly slow down or do not allow for water and air movement, while a less compact soil does. The degree of compaction can change dramatically during the growing season. The nature of the soil in combination with moisture content and mechanical compaction can alter the present condition; therefore, seasonality and proximity to precipitation events can be a factor when comparing multiple sites with varying collection dates using this device. (Soil compaction | UMN Extension).

Sample Collection (2018): Students from UWRF collected the infiltration data at multiple points per Site and at each hillslope position plot. The data was collected during the growing season but at different dates and proximity to precipitation events. The unusual weather and localized factors led to some challenges in interpreting the usability (reportability) of the data collected. Figure 7.1 shows the summer precipitation for 2018 (next page).

Additional data collection (2021): Thankfully, follow-up collection occurred during 2021 with additional field data provided by the University of Minnesota supported by a USDA/NRCS Conservation Innovation Grant (CIG, Conservation Innovation Grants | NRCS (usda.gov). The information is currently in analysis and will be presented in a later report (not in this report).

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Figure 7.1a: Date and amount of precipitation events during summer 2018.

Figure 7.1b: Date and amount of precipitation events during summer 2019.

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Initial Data Review and Analysis: The 2018 data was initially analyzed by students at UWRF for reportability (i.e., real field conditions or equipment/user error). Data was collected over different dates and months, which led to highly variable results across sites and between and within hillslope position plots.

The following provides information on how the 2018 data was determined to be usable (reportable) or not. a) Degree of Compaction: Due to the unusually wet conditions experienced in 2018 and the high alteration of the plow layer due to wheel traffic and recent tillage, the measurements recorded were very erratic in nature and hard to interpret from field-to-field (study site-to-study site). Since preceding precipitation events and moisture content can contribute to variable outcomes at sample points, within plots, and between sites, this data was determined to be presently a low-confidence indicator (not providing a very trustworthy comparison between Management Types). b) Infiltration Rate (Kfs); During the process of screening the data by students at UWRF, some values were found to be extremely high or low (negative values). These values were scrutinized for user error, field conditions at the time of sampling, or the range of measurement confidence for the SATURO Infiltrometer (0.0038 cm/hr to 115 cm/hr). See online at: SATURO Tech Specs | METER Group, Inc. USA. Since some natural field situations can result in high infiltration (very good soil structure and pore space development, worm or small animal tunnels, plow shear), these high infiltration rates (>115 cm/hr) were included. With the negative values, since the reason was unknown (e.g., user error, field condition, or mechanical error), these were excluded from the reportable values used in the analysis.

Results: In total, 124 samples are included in the 2018 results reported here. Please note: we converted Kfs from cm/hr (machine data collected units) to inches/hr for the tables and figures in this report. See document “Interpreting Results - Boxplots and Tables” for more information.

Infiltration rate (Kfs) values for All Sites (all samples) ranged from 0.00 in/hr to 98.2 in/hr with an average of 13.3 in/hr (Table 7.1). Not all Management Types had an equal number of samples that were reportable (discussed above).

By Management Type, there was a considerable difference between the average infiltration rates. Average Kfs was significantly higher for CV than SH, and both were much lower than BM (Table 7.1 and Figure 7.2).

Table 7.1: Results for Infiltration Rate across All Sites and by Management Type.

Infiltration Rate (Kfs) (inches/hr)

All Sites

CV

SH

BM*

Number of Samples

124

48

43

33*

Average Median

13.3 7.7

12.3 (-) 5.9

4.2 (- - -) 2.3

26.7 (+++) 24.6

*Same BM plots used for both 3S and 3N. 7- Infiltration Rate, page 3

Outliers are also present (dots far above boxplots). For BM the only one identified was near 80 in/hr. For CV, the four outlier values were between 40 to 100 Kfs in/hr. In comparison, the highest SH value was only at 16 Kfs in/hr.

Figure 7.2: All Sites (all samples) combined for Infiltration Rate (Kfs) by Management Type.

These higher infiltration rates in CV vs. SH plots relate to the mechanical action of tillage fluffing the soil.

What the infiltration test did not account for is the massivity (lack of structure) commonly encountered in CV plots at the 4-5 inch depth. Gravitational water often was observed perching above this depth after significant rainfall events. Perching was not detected in SH plots, likely related to better connectivity of macro-pores as indicated by much higher Structure Index scores. (See Results Table in Executive Summary and results for Structure Index in attachments). Higher levels of macropore connectivity will more effectively conduct gravitational water vertically into sub-surface soil horizons. This indicator should be reconsidered for its utility as a “soil health” indicator given the temporal condition and not the long-term condition of the soil structure.

Individual Site Results Results for Individual Sites (Figure 7.3, next page) are very similar to the results for All Sites, where average Kfs was higher for CV than SH with BM higher than both. Interestingly, the highest infiltration rates (>50 in/hr) were all within the upland plots for CV (Sites 1, 4, and 7) and for BM the highest value was an upland plot (Site 3S) while the next highest values were all located in the lowland position l (Sites 2 and 7). The highest value for SH was at a lowland plot (Site 4).

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Figure 7.3: Individual Site Results for Infiltration Rate (Kfs).

Please note: The additional data collection in 2021 will be good to compare with these 2018 results reported here. The 2021 results will be forthcoming and included in a future report.

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