Fifty agronomic crop farmers implement a cropping system management change to optimize soil C-N-P dynamics on 5,000 acres, increasing soil C by 5 tons/acre in the long-term while reducing nitrate-N leaching by 12 lbs/acre/yr and P runoff by 1 lbs/acre/yr (a 50% reduction of both).
Agricultural soils in the Chesapeake Bay watershed are losing an average of 2 lbs/ac/yr phosphorus (P) in runoff water and 23 lbs/ac/yr N in nitrate leaching, causing severe water quality issues in the Bay. At the same time, soil carbon (C) levels are declining by 95 lbs/ac/yr, negatively impacting soil health and contributing to global climate change. Elemental C-N-P cycles are inextricably linked through the process of growing crops, feeding livestock, and applying manure to agricultural lands, but optimizing the management of these cycles to achieve high soil C levels while minimizing N and P losses is fraught with tradeoffs in heavily concentrated areas of livestock production. This project will engage agronomic crop farmers in Pennsylvania, New York, and Maryland to learn about, evaluate, and improve C-N-P management on their farms. We will conduct research at 20 farms and a long-term research station experiment to identify combinations of management practices, such as planting cover crops, harvesting cover crops for forage, and strategic use of tillage and manure injection, that optimize C-N-P dynamics to achieve high soil C levels while minimizing N and P losses. Pairing the dataset collected from research sites with a cropping system computer model, we will also identify region- and soil-specific benchmark soil organic matter levels that can be achieved under optimal C-N-P management. To supplement our education program of workshops, field days, and webinars, we will develop an online simulation tool for farmers to compare C-N-P dynamics under different management scenarios.
We hypothesize that: (1) there is an upper bound to soil organic matter (SOM) levels that can be achieved when
appropriate nutrient management practices limit manure application rates to environmentally safe levels; (2) the
upper bound for SOM levels will vary based on soil texture and climatic controls on the SOM decomposition rate,
resulting in site-specific targets for SOM levels that farmers can use to evaluate soil management practices; (3)
there are specific combinations of management practices that can raise the upper bound for SOM levels by
allowing greater manure application rates and decreasing SOM decomposition rates.
This project uses on-farm measurements of soil carbon, soil nitrate and ammonium, and soil test phosphorus (Mehlich 3) at multiple depths of the soil horizon (0-5cm, 5-10cm, 10-20cm, 20-40cm, 40-60cm, and 60-80cm) to assess how carbon (C), nitrogen (N), and phosphorus (P) dynamics are coupled. Soil measurements are paired with detailed soil management records to determine how the management practices are related to the measured C-N-P dynamics. By project completion, we will assess C-N-P dynamics on 100 fields from 25 different farms in Maryland, Pennsylvania, and New York. At each farm, roughly 4 fields will be sampled. Farms will be chosen to span a gradient of management practices from conventional tillage to long-term no-tillage, from manure use at various rates to fertility management purely with synthetic fertilizers, cover cropping and no cover cropping, and from simple to diverse rotations. Within each farm, fields will be selected for sampling that show some within farm contrast, such as phase of the crop rotation, cover cropped or non-cover cropped, different fertilizer rates used, etc. We expect the across and within farm variability to generate a broad spectrum of management practices that will allow results to be extrapolated to the majority of agronomic crop production in the northern Chesapeake Bay watershed.
Soil sampling for each field will be conducted with a hydraulically powered soil probe (Figure 1, Ag Probe 9100, AMS, Inc.) that will retrieve a soil core to >80cm deep. Four cores will be collected from each field in random locations but all from within the same dominant NRCS soil map unit. The soil sampler retrieves each core inside a plastic sleeve such that the intact core can be removed from the sampling tube and transported to the lab while protecting soil horizonation and bulk density of the core. Following soil sampling, the plastic sleeves are cut open and each soil core is cut into depth increments of 0-5cm, 5-10cm, 10-20cm, 20-40cm, 40-60cm, and 60-80cm. The depth increments from the four cores taken in each field are composited to create a single sample per horizon per field. The total mass of fresh soil is recorded and a subsample is dried for determination of gravimetric moisture content. A subsample of the fresh soil is immediately extracted for nitrate and ammonium concentrations. Soil samples are then dried, flail milled, and sieved to <2mm. The rock weight in the sieved material is recorded to adjust the soil bulk density. Dried and sieved soil will be measured for Mehlich 3 extractable P and total soil organic carbon.
Soil management practices that are documented for each field for the previous 10 years include the crop rotation, crop planting and harvest dates, average crop yields, crop residue removal practices, fertilizer and manure applications (include rate, form, time and method of application), and tillage practices. Management prior to 10 years in the past is documented in generalized form, including crop rotation, use of manure vs. fertilizer, and tillage practices.
Management practices collected about each farm will be used in the Cycles cropping system model to simulate the impacts that crop management have on C and N cycling dynamics. We will use the measured on-farm soil data to check the accuracy of the Cycles model at predicting C and N dynamics. If the model performs well at predicting soil C storage, then we will use the model to make maps across soil types in Pennsylvania, Maryland, and New York, to show benchmark soil C levels for different crop management practices across the gradients of soil texture and climate.
In December 2018 and January 2019, two farms, were sampled in Pennsylvania. The first farm was a large dairy farm with a corn-hay rotation. It has been practicing no-till for 20+ years and cover cropping reliably for 10 years. Four adjacent fields on the farm were sampled in December 2018, two fields during the corn phase of the rotation and two fields during the hay phase of the rotation. The corn fields had a cereal rye cover crop planted and the hay fields were dormant alfalfa/orchardgrass. Both fields had manure spread on them two days before soil sampling. The second farm was an organic farm with a diversified agronomic rotation of corn, wheat, soybeans, and hay. The farm reliably cover crops, performs tillage annually in between crops, and uses poultry litter as a supplemental nitrogen source. The farm has fields that have been under organic management for different periods of time, with the most recently acquired fields transitioning from continuous no-till production to organic management within the last 5 years. Soil samples collected from different depths in 4 fields at each farm were analyzed for organic carbon, soil nitrate and ammonium, Mehlich 3 P, and soil texture (Figures 2 and 3).
At the long-term no-till dairy farm (Figure 2) the soil test P and soil C is stratified at the soil surface. The overall soil test P levels are not excessive, however, owing to the judicious use of manure. In the plow layer, the soil test P levels are within or slightly above the optimum agronomic level according to Penn State soil test interpretation guidelines. Although this is a large dairy farm (1,000+ cows), soil test P levels have not accumulated to excessive levels because the farm has a large land base to distribute the manure across and manure P levels have been reduced through solids separation. Soil nitrate levels in the profile would be considered moderately low relative to previous experience sampling at this time frame. This may be because the farmer uses lower than recommended rates of N fertilizer on his crops, which he has determine are feasible without losing crop yield based on his experience using adaptive N management practices, such as nitrogen fertilizer rate strips. Soil C concentration is quite high in the 0-5cm depth increment and quickly drops off due to stratification. This is common in no-till soils and may limit soil C accumulation due to soil C saturation in the surface layer where organic inputs are deposited.
At the organic farm site, soil C concentration was greater in the topsoil than the subsoil, and more homogenously distributed through the plowlayer than at the no-till site. Soil nitrate levels throughout the profile did not show any obvious bulges of nitrate at depth and overall nitrate concentrations were relatively low. One site had very high ammonium levels throughout the soil profile, which is difficult to explain, but it occurred in the field with the longest history of organic management. Soil test P was well-above the agronomic optimum at all sites owing to the historically heavy use of manure in the crop rotation. However, soil test P levels have been managed to remain below the 200ppm threshold that triggers additional nutrient management restrictions in Pennsylvania.
Soil samples were collected from three additional farms in December 2019, the soil samples have been analyzed for C-N-P parameters, but the results have not been summarized an interpreted.
Simulations of the cropping system management from 1980 through 2018 for the no-till dairy farm were developed in the Cycles model. There was a strong relationship between the model predicted soil C and the measured soil C levels in the 4 field sites (r2=0.94, Figure 4). The model results for the chronology of soil C levels under the farmer’s current management were compared to alternative soil management scenarios, including occasional tillage, continuous tillage, and complete no-tillage from the beginning of the simulation in 1980 (Figure 5). In the occasional tillage scenario, a moldboard plowing event took place once every 6 years at the establishment of alfalfa. In the continuous tillage scenario, tillage took place each spring for establishment of the corn and for the establishment of alfalfa. Results were surprising, in that the scenario with the highest soil C levels was the occasional tillage scenario. This is because the Cycles model uses a carbon saturation model to control soil C storage. In no-till systems, the surface soil layers (0-5cm and 5-10cm) become saturated with carbon and cannot stabilized the high levels of C inputs from manure, cover crop residues, and perennial root systems. Interestingly, in the initial years of transitioning to no-till under the farmers existing management scenario, soil C levels climbed rapidly in the topsoil, but then started to decline as saturation was reached. After about 12 years of continuous no-till, the occasional tillage system started to outperform the no-till system in soil C levels. These results point to important ways in which we need to better understand the limitations of no-till systems for soil C storage. We also need to better understand if there are interactions with the level of C inputs. Its possible that under low C inputs, complete no-tillage is preferable, while under high C inputs, occasional tillage is preferable. These research questions will be assessed through model simulations as part of the project, but on-the-ground studies should be conducted with additional funding to verify the results.
An important component of our education outreach plan is to train farmers in the use of the Cycles cropping system model. We dedicated a significant amount of project resources in 2019 to creating an online interface for the model. Figure 4 shows the timeline feature, one part of the current interface, which allows users to drag and drop different management practices, such as crop planting, tillage, fertilizer, and manure additions onto a calendar. Farmers select the location of the field on a map and the interface will load the soil type for the farm as well as the weather history back to 1980. Users can than “submit” the management scheme created in the timeline to the model and then evaluate the output through various figures that depict soil C and N cycling processes over time.
We had planned to use the online model for a series of small farmer trainings in late-March 2020, however those meetings were canceled at the last minute due to the COVID-19 outbreak. The pandemic restrictions on in-person educational programming have set us back significantly in our educational outreach for this project. Depending on how quickly the pandemic resolves, we may have to pivot to just creating educational training videos of how to use the model, or attempt very limited synchronous remote workshops, which may need to be redirected towards Ag Service Providers rather than farmers since they are more experienced computer users.
We were able to provide a one hour educational training through an online presentation at the 2020 Mid-Atlantic Crop School in November 2020. This training session did not teach the audience how to use the model, rather a short demonstration of the online interface was provided to demonstrate the capabilities. Results of simulations done with the model were then shared through PowerPoint slides. The Ag Service Providers attending the session had positive reviews of the content and expressed interest in attending a more in depth training session about the online model interface.
1. 1,000 agronomic crop farmers learn about the project to optimize soil carbon, nitrogen, and phosphorus (C-NP) inputs and losses and receive an invitation to participate in the educational program and on-farm soil sampling and data collection. (August 2018)
On October 29, 2019, we published a newsletter article in the Penn State Extension Field Crop News describing the research project and inviting farmers to contact us to participate in soil sampling activities and attend educational workshops. The newsletter article was sent to a list-serv of 8000 individuals, which is a composite of farmers and ag service providers. We estimate that 4000 of the list-serv members are farmers. We also promoted the project at a soil health breakfast meeting in Clinton County, PA on January 4, 2020 attended by 12 farmers.
2. 200 farmers sign-up to the project e-mail list to receive notifications of educational events and reports of project results; 20 farmers respond to invitation for on-farm soil sampling and data collection. (October 2018)
We received a very tepid response to our newsletter announcement about the project, unfortunately. Only two individuals, both ag service providers, responded directly to our newsletter article inviting participation in the project. However, through word-of-mouth interactions we were able to promote the project to farmers and recruit interest in soil sampling activities. Through local extension educator and the personal networks of project personnel, in Pennsylvania we have recruited two farmers to participate in soil sampling in winter 2018/2019, three farmers to participate in soil sampling in winter 2019/2020, and four more farmers have volunteered to have their fields soil sampled in winter 2021. In Maryland, project collaborators sampled from research station plots in March 2020 and two on-farm sites in March 2020.
3. 50 farmers attend an on-farm field day (November 2019) and 50 farmers attend a workshop (February 2020) where they learn how C-N-P cycles are coupled, how to evaluate C-N-P dynamics on their farm with soil testing, and how to optimize C-N-P dynamics through cropping system management.
We had to cancel the two workshops that were planned for March 2020 due to the onset of the COVID-19 pandemic. Due to the technical nature of teaching the simulation model, we did not try to pivot these workshops to an online format. We will monitor the resolution of the pandemic and try to reschedule an in-person workshop for farmers when the time is right.
4. 50 farmers attend a webinar and learn how to use an online cropping system model to simulate management effects on C-N-P dynamics. (March 2020)
We provided a one hour presentation during the 2020 Mid-Atlantic Crop School which was attended by 194 ag service providers. The presentation gave a demonstration of the online tool and discussed how to manage soil carbon in relation to nitrogen and phosphorus.
Originally the webinar was planned to be delivered to farmers, but we realized in the process of developing the online model that it may be too difficult for farmers to learn to use the model remotely. Instead, we had an opportunity to provide a training to ag service providers at the Mid-Atlantic Crop School, which served as a gauge to test the reception of the model. It was well received, and we plan to do a more intensive online training with ag service providers remotely sometime in 2021. We will gauge the success of that intensive training with Ag Service Providers, learn from our experience, and then be able to come up with a remote delivery strategy for training farmers that will be positioned for success.
Of the webinar attendees, 99 increased their knowledge of the forms of carbon in the soil, 122 increased their knowledge of factors affecting carbon stabilization, 128 increased their knowledge of methods to measure soil carbon, and 104 increased their knowledge of management practices to increase soil carbon.
99 attendees reported that their likelihood to discuss soil carbon management with their farmer clientele increased as a result of attending the presentation, and they expected to share information from the presentation about soil carbon management with 3,324 farmers managing 2,377,804 acres during the next year.
5. 25 farmers contact a project team member to receive technical support on how to monitor and manage C-N-P dynamics on their farm. (July 2020)
We had a meeting with TeamAg consulting to discuss how to measure soil carbon dynamics as part of the regenerative farming business plans they are developing for their customers. We expect that through this partnership we will be able to reach farmers with managing C, N, P dynamics on their farms.
6. 75 farmers evaluate their soil organic matter levels using an interpretation key (e.g. low, medium, high levels) that accounts for climatic and soil textural controls on soil C storage. (December 2020)
We are in the process of developing our soil organic matter interpretation key and have not released anything to the public to be able to use yet. We expect to have this developed by the end of the project and presented to farmers, but will have limited opportunity to evaluate farmer usage within the project period.
7. 25 farmers use an online cropping system model to simulate management effects on C-N-P dynamics. (December 2020)
We plan to have a training developed to show how to use the online model by the end of the project period, at which point farmers can test scenarios for their farms. We are also working with TeamAg consulting to use the online model to run scenarios for the regenerative farming business plans they develop.
99 ag service providers increased their knowledge of the forms of carbon in the soil, 122 increased their knowledge of factors affecting carbon stabilization, 128 increased their knowledge of methods to measure soil carbon, and 104 increased their knowledge of management practices to increase soil carbon.
99 ag service providers reported that their likelihood to discuss soil carbon management with their farmer clientele increased as a result of attending the presentation, and they expected to share information from the presentation about soil carbon management with 3,324 farmers managing 2,377,804 acres during the next year.