Biodiversity Effects on Soil carbon Gain in Annual and Perennial Cropping Systems

Final Report for GNC14-196

Project Type: Graduate Student
Funds awarded in 2014: $6,382.00
Projected End Date: 12/31/2015
Grant Recipient: Michigan State University
Region: North Central
State: Michigan
Graduate Student:
Faculty Advisor:
Dr. Phil Robertson
Michigan State University/ Kellogg Biological Station
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Project Information


Soil carbon (C) is the most important variable in sustaining annual and perennial cropping systems both in terms of increasing crop productivity and enhancing soil health. Recent research shows that crop biodiversity could play an instrumental role in increasing soil C in both annual and perennial based cropping systems due in large part to increased root production. As soil C levels decline in the Mid West due to intensive management practices, utilizing crop diversity as a tool to increase soil C could become a necessity. Furthermore, managing for soil C on-farm can be challenging because it can take years for total C to respond to changes in management. However, the total C pool consists of several different pools that have different turnover times. One pool is the labile C pool or active C that has a short turnover time and changes with crop growth and responds to different management practices. Currently, soil tests available to farmers only represent the total C pool, which may not fully reflect soil health.

Here, we examined the role that plant diversity has on root production and soil carbon dynamics in annual and perennial crops in a controlled cropping systems experiment. We also wanted to address soil biodiversity and managing for soil C on-farm. To do this we sampled 52 farm fields in Michigan and compared the total soil organic matter test to the active C test and determined which test better reflected farmer perceptions of soil organic matter.

Overall, we found that diverse perennial systems produce more fine roots and accumulate more C in the active pool, while annual crops and monoculture perennials produce less roots and accumulate less soil C. This suggests that crop diversity in perennial-based cropping systems should be promoted to replenish soil C for increased soil health and climate change mitigation.

Our on-farm work demonstrates that the total soil organic matter test is insufficient at determining differences in soil C between farmer-described Best vs. Worst fields. In contrast, we found that the active C test revealed significant differences between the Best vs. Worst fields and strongly supported farmer descriptions that we gained through farmer interviews and investigator observations of fields. In the future, commercial and university labs should offer the active C test to better guide farmer management decisions.


Soil fertility management and reductions in crop productivity often stem from inadequate soil organic matter levels on-farm. Midwestern soils have lost between 30 and 50% of historic carbon (C) levels, negatively impacting soil health within agroecosystems (Lal, 2004). Such reductions in soil organic matter have also contributed to enhanced CO2 emissions from agriculture. Thus, restoring soil C levels on farm would improve soil health and crop production as well as increase soil C accumulation, which is important for climate mitigation.


An approach that could be adopted by farmers to significantly build soil C is increasing crop diversity through planting cover crops, incorporating crop rotations, and by planting perennial mixed grass systems in place of fallow land. Plant biodiversity is key to maintaining ecosystem stability and ecosystem function, in large part due to its role in increasing productivity and retaining nutrients (Tilman, 1996). Increasing biodiversity in annual and perennial based systems can lead to increased root production and thus increases in soil organic matter (SOM), which improves soil health and increases cropping productivity.

One problem that farmers often face when testing soil organic matter is that soil C is insensitive to changes in management because it is large (in comparison to annual inputs) and consists of C that has persisted in the soil for periods ranging from days to millennia (Wander, 2004). This means that even after a farmer adopts a more sustainable practice, improvements in soil C could take years to detect. However, researchers have developed tests that can identify changes in the labile portion of soil C, which consists of recently deposited material that typically decomposes within a year and is sensitive to changes in management.

Our goal was to measure soil C on farmer fields in Michigan and communicate with farmers how management practices, including increasing biodiversity in both annual and perennial cropping systems, can affect soil C accrual. We met with farmers individually and in groups to discuss soil testing and certain management practices that could be used to increase soil organic matter and improve overall soil health. Ultimately, we wanted to introduce soil health tests that could be used to inform better management decisions in terms of soil organic matter management.

Project Objectives:

The objectives for this study were two-fold. First, to determine the extent that biodiversity accelerates SOM accrual in both annual and perennial cropping systems. Second, to provide farmers with practical information (soil carbon test results) that will lead to opportunities for better management of soil carbon and potentially lead to more management practices that incorporate increases in crop diversity. 

More specifically:

1A. Determine the effect of biodiversity on fine root production and biomass allocation.

1B. Document the effect of biodiversity on soil carbon quantity and quality.

2. Measuring the labile soil carbon pool on Michigan farms and discussing results with farmers individually.


Click linked name(s) to expand/collapse or show everyone's info
  • Brendan O'Neill
  • Dr. Phil Robertson


Materials and methods:

Part One: Determine the effect of biodiversity on fine root production and biomass allocation.


   In the fall of 2013, we determined fine root production at two sites in the upper Midwest that contrasted in soil fertility. The study took place in the Biofuel Cropping System Experiment (BCSE) located at Arlington Agricultural Research Station (ARL) in Wisconsin, USA and the Kellogg Biological Station (KBS) Long-Term Ecological Research Site located in Michigan, USA. Both are part of the DOE Great Lakes Bioenergy Research Center. ARL has high fertility soils, whereas KBS has more moderate fertility soils. In-growth cores were used to assess fine root production over the course of the growing season at both sites. Two 2 mm-mesh cores were installed per plot in April 2013 to a depth of 13 cm. In order to quantify root productivity during the growing season, the two cores were harvested in July 2013 and then in November 2013. Once collected, all roots were separated from soil over a 2 mm sieve and dried at 60oC over a two-day period, and weighed. Finally, a fine root to annual net primary productivity index was calculated to determine the effect that biodiversity has on biomass allocation.

Part Two: Document the effect of biodiversity management on soil carbon quantity and quality

     Long-term laboratory incubations were used to estimate the turnover rates of the different soil organic C pools (Paul et al., 1999) over the course of a year (322 days). Soils samples were taken from the BCSE experiment mentioned in part one. The laboratory experiment was a two-site by ten-cropping-system full factorial design. Surface soils (0-10 cm) were analyzed from all systems and subsurface soils (10-25 cm, 25-50 cm, and 50-100 cm) were analyzed in the corn, switchgrass, native grasses, and restored prairie systems. Two analytical replicates were treated as subsamples. Soils were incubated in canning jars and kept in the dark at 25oC. CO2 was measured using an infrared gas absorption IRGA analyzer using Li-8200 software. A C mineralization model was used to fit to CO2 production versus incubation time. Particulate Organic Matter (POM), a method that determines soil C pools through physical size fractionation, was also be carried out on all samples during the summer of 2014.

Part Three: Measuring the labile soil carbon pool on-farm and discussing results with farmers individually.

 Participant selection

     This study was grounded in a participatory action research framework where Michigan farmers, MSU Extension staff, and MSU researchers, in collaboration with Brendan O’Neill (SARE # GNC 14-192) worked together to determine if different soil tests corroborated farmer perceptions of soil organic matter on their farms. Thirteen farms across three counties in Michigan, USA participated in this study (Table 1). The three counties included Isabella (43o60’N, 84o76’W), Presque Isle (45o42’N, 83o81’W), and Van Buren (42o21’N, 85o89’W) and represent three different geographical parts of Michigan, as well as different soil types. Farmers were chosen by Michigan State University (MSU) extension agents based on willingness to participate in interviews and workshops in exchange for free soil testing.


Farm Visits and On-farm soil sampling

       Initial farm visits consisted of meeting with farmers, field observations, soil sampling, and when possible, concise interviews with farmers regarding farm history and soil and crop information. At each farm, we asked farmers to select four fields to include for sampling: a best-performing field (Best), a worst-performing field (Worst), a field of their choice (Choice), and a non-row crop or unmanaged area (NRC). Soils were sampled at the end of May and early June, 2014, spanning three weeks. Five samples were randomly taken from each field. The first sample was taken 4.5 meters from a field edge, while subsequent samples were taken every 4.5 meters by walking diagonally across each field. Samples were taken by digging 15 cm deep pits between cultivated rows and extracting 4 cm wide slices of soil. Next, a trowel was used to cut a rectangular block of soil (15 cm by 10 cm by 4 cm). The five soil samples were composited by field and mixed thoroughly and then put through a 2 mm sieve. In addition, 30 g were kept for the C mineralization test while 40 g were sent to the MSU soil analysis lab for the total SOM test. At each of the five sampling points, two penetrometer readings were also taken at 15 cm and 46 cm depths to determine surface and subsurface compaction. Field observations consisted of taking photographs of the crop and soil and making descriptive field notes on the condition of crops and soils.

Laboratory analyses: total SOM and active C (C mineralization)

     The Soil and Plant Nutrient Laboratory at MSU utilizes loss on ignition to determine percent SOM. Samples (40 g) were oven dried for 48 hours at 105º C, weighed, then heated in a muffle furnace at 550º C for five hours. SOM was determined by difference in weight:

where SOML.O.I =(DWI-DWo)/DWI x 100; DWI = Oven dry soil weight (dried at 105oC) and DWo = Soil weight after ignition at 550oC.

 Active C was determined via short-term C mineralization incubations. Ten grams of soil were placed in a 237 mL Mason jar, re-wetted and then incubated for 24 hours at 25oC. Two analytical replicates were analyzed per field. Soils were adjusted to 50% water-filled pore-space utilizing the methods described in Franzluebbers et al. (2000). Following the 24-hour incubation, each Mason jar was capped tightly with a lid fitted with a rubber septum. A time zero CO2 reading was taken immediately following capping, by injecting 0.5 mL of headspace into a LI-COR LI-820 infrared gas absorption analyzer (LI-COR Biosciences, Lincoln, NE). Three subsequent readings were taken over 90 minutes and a flux was calculated by regressing the change in CO2 versus incubation period (Robertson et al., 1999).

Individual farmer meeting, workshop, and qualitative analyses

     During the first part of each farmer meeting we asked farmers to describe each of their target fields including characteristics and challenges of each field. Next, we presented both the MSU test results (total SOM) and the active C results to the farmer. The last part of the meeting was unstructured, which allowed for more in depth questioning on farm history, management decisions, and soil testing. Each meeting took place in the winter following our sampling and lasted up to two hours. All meetings were recorded and notes were expanded within 24 hours of each meeting. Recordings were transcribed and analyzed for emerging themes and concepts by reading through transcriptions, writing text summaries, and coding transcripts within Nvivo 10.2 (QSR International, Burlington, MA). To compare test results to field observations and farmer experiences, we wrote summary memos of field characteristics and farmer descriptions and then constructed data matrix displays with extracted text combined with active C results to examine common concepts and themes. In addition, we teamed up with MSU Extension and held a facilitative workshop with a small group of farmers to further discuss how soil health tests that could be used to manage for soil carbon and nitrogen.

Research results and discussion:

*Note Figures and Tables inserted at end of section 

Part One: Determining the effect of biodiversity on fine root production and biomass allocation.


       Determining the effect that biodiversity has on root production is important as fine roots significantly contribute to soil C accumulation. Here, we compared fine root production and belowground biomass allocation in six perennial cropping systems: three monoculture systems (switchgrass, miscanthus, and poplar) and three diverse cropping systems (native grasses-five species mix, an early successional system, and a restored prairie) at a moderate (KBS) and high fertility (ARL) site.

       The native grasses and the restored prairie systems consistently produced greater amounts of fine roots compared to the monoculture systems (especially poplar and miscanthus) at both ARL and KBS (Figure 1 and 2 p<0.05), while in the early successional systems fine root production was generally more similar to the monoculture systems. At ARL, the native grass, early successional community, and restored prairie systems all allocated greater fine root production per aboveground net primary productivity (BNPP:ANPP) compared to the monoculture perennials in 2012 and 2013 (Figure 3). At KBS, the restored prairie and native grass systems had greater BNPP:ANPP indices compared to the monoculture perennials in 2011 and 2012 (Figure 4). These results are consistent with Fornara and Tilman (2008) who found greater fine root production with increased diversity in a long-term biodiversity grassland experiment at the Cedar Creek LTER in northern Minnesota, USA. Furthermore, these results support the diversity-productivity hypothesis and the plant complementarity effect hypothesis, both of which posit that systems with more diversity will have greater root production due to differences in rooting depths caused by a variation in phenology and plant resource demand (Tilman et al., 1996 and Hooper and Vitousek, 1997).

       One explanation for lower fine root production in the early successional system is the greater presence of annual species like Conyza canadensis compared to perennials such as Elymus canadensis, which tend to produce a greater amount of roots (Sainju et al., 1998). At ARL, annuals comprised 6% of total plant composition in the native grasses, 33% in the early successional community, and less than 1% in the restored prairie system. At KBS, annuals accounted for 1% of the native grass system, 79% of the early successional community, and 3% of the restored prairie system. Thus, our findings suggest that diverse systems have greater fine root production, except where annuals are dominant.

     These results underscore the importance of plant diversity for promoting soil C sequestration in biofuel and other managed perennial communities.

Part Two: Document the effect of biodiversity management on soil carbon quantity and quality


     In part one, we found that increased biodiversity led to increases in root production. In part two, we expanded on our earlier work to see how biodiversity would influence soil C accumulation in both annual and perennial based cropping systems in both moderate (KBS) and high (ARL) fertility soils.

At KBS, we found substantial differences in active C between the annual monoculture and the perennial polyculture crops but not between the annual and perennial monoculture crops. Active C pools under perennial polycultures were over 2.5 times greater than under continuous corn (Figure 5, p<0.05), and among systems followed the rank order continuous corn (237 μg C g-1 soil) << early successional (500) < restored prairie (638) ≈ native grasses (656). Amongst the perennial monocultures, only the poplar system had 2.5 times more active C than the annual systems. That the poplars at KBS behaved more like the diverse perennial systems than the other monoculture perennials is curious, but is probably because of greater diversity than the other monoculture perennials. Although the poplar system was planted as a monoculture and its overall biomass is dominated by Populus sp., the understory nevertheless contains six different herbaceous species that provide 24% ground cover. Thus, while poplars are the dominant species, the system resembles a polyculture more than a true monoculture. System differences in the slow C pool were less apparent, and there were no significant differences among the systems in the resistant C pool.

Active C pools, at ARL were similar to those at KBS, however, differences amongst systems were insignificant five years post-establishment, except the restored prairie and rotational corn had 3.4 times more active C than other systems. ARL accumulated significantly greater C in the resistant pool compared to KBS at every depth except 50-100 cm. One reason for less differentiation at ARL compared to KBS could be that the mollisols found at ARL are extremely high in soil organic matter. For example, 0-10 cm depth baseline soil C at ARL was 22.4 g C kg-1 compared to 14.3 g C kg-1 at KBS. Thus, Arlington soils could be approaching C saturation, which implies that the system does not have the capacity to stabilize additional C inputs as soil C (Stewart et al., 2007). Sandier soils such as those at KBS may be able to build C at a quicker rate after disturbance or changes in management because they are less likely to be close to their maximum C storage capacity (Anderson-Teixeira et al., 2009; Johnston, 2011). Clay soils, on the other hand, will build C at a much slower rate as C approaches equilibrium (West and Six, 2007). Surface soils at KBS are 63% sand compared to 25% sand at Arlington.

These findings demonstrate that poplars and diverse perennial bioenergy systems are more effective at increasing C in the active pool than no-till annual crops and monoculture perennials, especially in less fertile soils. The fact that I did not find any differences in C accrual between monoculture perennials and no-till annuals suggests that no-till management may be equally advantageous to perenniality. Overall, these findings demonstrate that diverse perennial biofuels grown on marginal lands could lead to significant and rapid increases in C accumulation.

Part Three: Measuring the labile soil carbon pool on-farm and discussing results with farmers individually.

    Several important results arose from our on-farm soil sampling, interviews and workshop with the farmers. As mentioned above, we compared two soil carbon (C) measures on 52 Michigan farmer fields: total soil organic matter (SOM) and active C. Total SOM is widely accessible to farmers via university and commercial laboratories, while C mineralization (active C) is not yet commercially available. Active C tests detected significant differences between the Best vs. Worst fields (Table 2, t-test= 5.8; p<0.0001), while total SOM tests were statistically similar for the Best and Worst fields (t-test=2.8, p=0.07). This finding is significant because the current test that farmers are using to determine soil organic matter dynamics does not decipher differences between their Best and Worst field. To further explore these results, we wanted to match farmers’ descriptions of their fields in regards to soil health and soil organic matter and see if the total soil organic matter test supported those results. The characteristics that farmers used to describe their Best field were strikingly similar across the different farms and counties (Table 3). Eleven out of the thirteen farmers mentioned yield or ‘consistent production’ when asked to describe the qualities of their Best field. Soil health and organic matter were also important characteristics for the Best field, as 70% of the farmers mentioned soil structure, quality, and/or soil nutrients. On the other hand, when describing the Worst field, all of the farmers mentioned something negative about soil quality. Farmer No. 13 stated, “the SOM levels are problematic” and farmer No. 1 said, “the SOM is not as high as the [Best] field.” The significant finding here is that both farmers and investigators (through field observations) noted major differences in soil health between the Best and Worst fields, but those differences did not show up in the total SOM test, while the results from the active C test strongly supported investigator field observations and farmer perceptions of soil C in the Best versus Worst Fields.


Linking soil tests to management and expressed interest in soil health testing


      An important theme that emerged during the interviews is that farmers mainly had a positive view of active C and its ability to aid in understanding SOM trends on their fields. An extension of this theme was that farmers raised important questions about active C and gave critical feedback that will be crucial for making soil health testing even more applicable in the future.

       When viewing the active C and total SOM results side by side, farmers immediately comprehended that the two tests were illustrating different trends across the fields. For example, farmer No. 12 said of active C, “it's an eye opening…it’s a different way to look at it.” Other farmers were genuinely shocked by the results, for example the farmer who added gypsum to his field (Farmer No. 4) was surprised when he saw significantly lower C fluxes compared to the other fields, “in the tests that we have, you know like you could look at this booklet that I got right here and you have [total SOM results] right here, [SOM] doesn’t look like it’s a problem”, he goes on to say,

"I’ve thought about putting more organic matter, matter of fact, I’ve thought about trying to find somebody that puts [manure] on this field… but then I go back and look at this, like this number [total SOM] we weren’t looking at that number [active C]. Looking at this [total SOM], you’d say why would I do that…"

This farmer is frustrated because his problematic field (Choice field) and Best field have equal total SOM values. However, results from the active C test reveal that active C values are much lower in the Choice field compared to the Best field. Past total SOM test results have stopped him from adding manure, as he states, “it’s like what am I going to benefit from [adding manure], right?” Instead, his approach has been to invest a large sum of money into gypsum application.

       Several farmers had questions about the active C test. More than one farmer asked, “What is the average value?” Or “What’s the county average?” Or “ How does my C flux compare to the other farms?” Farmer No. 1 questioned how active C could be useful if it varies, “that’s what we need is some sort of a stable number, where as this [active C] you know, can move up and down too much.” Other farmers wanted to know how they could raise active C rates in the Worst field to be on par with the Best field.

       At the end of each meeting, farmers were asked about the value of active C and soil health testing and if being a participant in the study was useful. All farmers expressed future interest in soil health testing. Famer No. 12 explained, “It's neat. I’m glad that I got involved and I think it's going to help us.” In a similar sentiment, farmer No. 6 stated, “I think the more information that we all can get, it's something that we all need to improve the soils and to make it better for the next generation.” Some farmers expressed frustration that active C and other soil health tests are not widely available. For example, Famer No. 7 exclaimed, “this is not only my opinion, but other growers, this is where MSU gets kicked in the you know what…”

       The real validation that farmers were interested in soil health testing is that twelve out of the thirteen farmers asked, “Are you coming back to sample again next spring?”


During the workshop, we presented results from experimental trials at the Kellogg Biological Station and then had a round table discussion on soil health management. In addition, farmers were able to provide feedback on areas where the soil health tests could be improved. Many farmers felt that the soil health tests were beneficial but wanted more information on how it could be directly linked to management practices. 

Figure1_SARE Figure2_SAREFigure3_SAREFigure4_SAREFigure5_SARETable 1_SareTable 2_SARETable 3_SARE


Participation Summary

Educational & Outreach Activities

Participation Summary:

Education/outreach description:


Sprunger, C.D. 2015. Root production and soil carbon accumulation in annual, perennial, and diverse cropping systems. Ph.D. Dissertation. Michigan State University, East Lansing, MI.

Sprunger, C.D. and B.E. O’Neill. Soil health testing on Michigan farms. Kellogg Biological Station: Brown Bag Seminar Series. Oral. January 2015.

O’Neill, B.E. and C.D. Sprunger. Results of soil health tests on Michigan farms. Farming for the Future Conference. Paw Paw, MI. Extension Talk: Oral. March 2015.

O’Neill, B.E. and C.D. Sprunger. Comparing soil health tests with traditional soil. Extension workshop. Mt. Pleasant, MI. February 2015.

O’Neill, B.E. C.D. Sprunger, and G.P. Robertson. Testing for soil health on Michigan Farms. Extension Bulletin. In progress.

Sprunger, C.D., B.E. O’Neill, K.Chung, and G.P Robertson. Farmers’ perceptions of soil organic matter ad reflected by soil testing: Carbon mineralization versus static pools of soil organic matter. In Prep.

Project Outcomes

Project outcomes:

Parts One and Two: The Impact of Biodiversity on root production and C accumulation

   The effects of crop diversity on aboveground productivity have been extensively studied and are well known; typically crop diversity leads to increased aboveground productivity, especially in low fertility systems (Tilman, 1996; Smith et al., 2008). The effects of crop diversity on belowground production are less well known. Our results demonstrate that diverse perennial cropping systems could be used to increase soil C in low fertility soils and marginal landscapes in particular, which has important implications at multiple scales. In terms of energy policy, cellulosic biofuels grown on marginal lands do not compete with food production (Robertson et al., 2008), have a large climate benefit (Gelfand et al., 2013), can produce biomass yields comparable to corn (Bonin and Lal, 2012; Sanford, in press), and also provide additional ecosystem services such as reduced nitrate leaching (Smith et al., 2013) and biodiversity benefits such as pollination and biocontrol (Werling et al., 2014). To our knowledge, these findings are the first to report that polyculture second-generation biofuels are more effective at accumulating C than monoculture perennials in moderate fertility environments. Relative to corn, polycultures accumulated over twice as much C in the active pool. Furthermore, these findings further suggest that restoring prairies in both high and low fertility soils leads to substantial short-term C sequestration.

     Finally, our results support the notion that C can be accumulated more rapidly in soils lower in fertility. Soil C stocks continue to decline globally and strategies are needed in order to replenish the total C pool. This work demonstrates that diverse systems could be used as a means to sequester C over short and long-term time frames.

Part Three: Farmer perceptions of soil organic matter

Results from our work with MSU Extension and farmers demonstrate that a stronger link between farmer perceptions of SOM and soil testing is needed. Furthermore it would help farmers make more informed decisions on management that could lead to economic and environmental benefits. For instance, farmers in this study invested a large amount of time and money in a variety of management practices in hopes of increasing SOM. In certain cases, the total SOM test hindered farmers from adopting more economically viable practices. In addition, the active C test can be an important indicator of long-term soil C dynamics as well as agronomic performance (Culman, 2013). From an environmental standpoint, scientists and policymakers continuously encourage farmers to adopt best management practices for C sequestration on-farm to offset CO2 emissions from agricultural systems (Jarecki and Lal, 2011). Farmers will be more likely to meet target C sequestration goals if active C or other tests that are sensitive to changes in management are more widely available. Thus, we strongly suggest that the active C test should be offered at commercial and university laboratories.


Economic Analysis

No economic analysis was conducted for this project.

Farmer Adoption

   While there was no formal farmer adoption analysis conducted in this study, through interviews and evaluations it is clear that farmers valued the information gained from the soil health testing. Over 90% of the farmers that we met with, wanted to continue soil testing using the soil health metrics that were introduced to them during the study. Other farmers stated that soil health tests should be available at commercial and university laboratories. Our study found that if these soil health tests are made commercially available, then farmers will incorporate the tests as part of there soil testing regimen.


Areas needing additional study

Our work demonstrated that biodiversity in perennial cropping systems increases root production and C accumulation in the active C pool. Now that we have demonstrated this in an experimental setting, it will be necessary to test this further on farmer fields.

   The next phase of our on-farm work should involve linking the soil tests to management and not just farmer judgement of fields. While the active C test results can better reflect farmer perceptions compared to total SOM, soil scientists need to work with extension educators to make active C more interpretable before it can be useful to farmers when they are making management decisions. During farmer meetings, farmers mentioned that active C was difficult to follow because of its dynamic nature in comparison to total SOM. This critique is important because other studies have illustrated that active C can change within a given growing season based on crop growth and fertilizer application (Culman et al., 2013). If samples are taken at different points during the growing season, it could be difficult to make informative comparisons from year to year. Thus, farmers should test for active C either in the spring before planting or in the fall after harvest. This recommendation is similar to with the Cornell soil health lab sampling instructions, where farmers are encouraged to sample once in late fall ( Other farmers asked what the average active C rates were for the county, across different soil types, and in different cropping systems. These types of aggregated results are not yet known for active C and will require further research. Overall, this study shows that farmers see value in the active C test along with other soil health indicators and are interested in using soil health testing in the future. Finally, future research should explore how the active C test can be used to inform soil management plans and how to make the active C test more available and understandable to farmers.

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.