Spatially delineated carbon credit potential and implied nutrient reduction co-benefit: An assessment with integrated ecological and economic modeling framework

Date: 
Sep 2022

Issue

Nutrient reduction outcomes are affected both by initiatives that directly target nutrient losses such as cost-share programs for conservation practices and by initiatives that do not directly target nutrient losses such as the fast-developing carbon markets. Interests in carbon sequestration and greenhouse gas reduction in the agricultural sector have increased dramatically as the federal government and many communities and private companies set zero-carbon goals. The recent “Carbon Science for Carbon Markets” report identified as high-priority research areas to develop scenarios and case studies for farms in different crop reporting districts with diverse natural and human characteristics  to evaluate changes in practices in response to participation in carbon and environmental markets. 

Objective

The overall objective of this proposed cross-disciplinary project is to conduct scenario-based and case study-based assessment of the nutrient reduction potential of various carbon initiatives with integrated ecological and economic modeling that incorporates spatial-temporal variabilities and farmers' responses to different payment scenarios. In order to understand carbon credit potential and related nutrient impacts, the project will seek to understand:

  1. how farm management practices respond to natural variables such as soil and weather conditions and socioeconomic setting. including crop prices and policy incentives;
  2. key interactions of carbon and nitrogen in air-plant-soil-water continuum that affect plant growth and carbon and nutrient cycling; and
  3. how the ecosystem processes and human decisions intertwine to regulate farm production and management systems and their eventual carbon and water quality outcomes.

Through this objective, the team aims to provide farmers and other stakeholders data-based and modeling-based information to facilitate more informed decisions in the pursuit of climate-smart agriculture.

Approach

Methods for the project are based on the objectives, including: 

  • To analyze and predict the temporal and spatial characteristics of conservation practice adoption, focusing on responses to incentive payments, two types of data will be analyzed: (a) farmers’ use of incentive programs, and (b) farmers’ adoption of conservation practices both with and without incentive payments. Researchers will examine the spatial and temporal patterns of participation in incentive programs and the adoption of conservation practices, quantify the impacts of program participation on conservation practice adoption while disentangling their interaction effects and predict the adoption of conservation practices under alternative carbon payment mechanisms, with input from the biogeochemical model
  • To estimate the adoption impacts of carbon incentive payments based on the panel data constructed and the project team’s extensive experience in the assessment of incentive programs. The process-based Dynamic Land Ecosystem Model will be used to quantify the spatial and temporal patterns of nutrient and carbon outcomes, including the impacts of cover crop and conservation tillage on riverine nitrogen loading, soil carbon stock changes and greenhouse gas fluxes based on the past 30 years of historical environmental forcing data and predict future trends. The modeled yield responses to cover crops and conservation tillage will be tested using experimental data from literature review and collaborators.
  • To compare the theoretical and empirical characteristics of different carbon payment strategies and their impacts on farmers’ response. The project will compare three payments that are commonly discussed and used in various ecosystem services provision: practice-based payment (e.g., per-acre payment for the acres of conservation practices adopted), outcome-based payment (e.g., payment per pounds of nitrogen reduced or per tons of carbon sequestered) and commoditization of nutrient and carbon benefits (e.g., price premium for crops grown under certified climate-smart practices). All three payment mechanisms will be assessed under different decision paradigms with economic and simulation models that consider land conversion, insurance coverage and grazing practices.
  • To develop scenarios, and quantify their regional carbon and nutrient outcomes, and economic impacts on farmers, funders and society. Researchers will compare scenarios that are based on different program goals (procuring the maximum amount of carbon versus combined carbon and nutrient benefits for a given fixed budget), payment schemes (e.g., practice-based vs outcome-based payment) and the combination of spatial targeting and practice/outcome-based targeting.
Award Number: 
2022-08

Project Updates

Note: Project reports published on the INRC website are often revised from researchers' original reports to increase consistency.

April 2024

In the US, we gathered a total of 1,574 observations from 119 papers that explored the impacts of cover crop planting on soil organic carbon (SOC) stock, crop yield and N2O emissions, with experimental durations ranging from 1 to 37 years. More measurement data on N leaching is being collected now. We also recorded various agronomic management practices that were implemented on the experimental fields, such as tillage, fertilizer application, irrigation, residue management, crop rotation and the planting and termination dates of cover crops. For soil and climate, we extracted this information directly from a re-analysis database and matched it using the reported coordinates. We analyzed this compiled data using a weighted mixed-effects model to calculate mean effect sizes along with corresponding 95% confidence intervals for each subgroup.

Moving forward, we plan to employ a boosted regression tree model to assess the relative importance of climate, soil and management practices in identifying and quantifying the variations in the responses of SOC sequestration, crop yield, N2O emissions and N leaching to cover crop planting. The model will be used to test scenarios of uncertain weather conditions and predict how they would affect the co-benefit of cover crops to carbon sequestration, greenhouse gas reduction and cleaning water across the US Midwest. We have also explored the adoption and disadoption of cover crops.

Utilizing three waves of a panel survey of Iowa farmers, we examined temporal adoption patterns. We highlighted a set of measurement indicators that categorized farmers into distinct groups that we labeled always adopters, nonadopters, disadopters, later adopters and intermittent adopters. We found that the disadoption rate in a period could be four times as high as the commonly used adoption rate. Compared to one-time measurement of adoption in cross-sectional surveys, longitudinal panel data documents temporal dynamics of adoption patterns and adds nuanced perspectives to adoption-related theories (e.g., the logistic innovation diffusion curve). Moving forward, we will integrate the economics decisionmaking related to such disadoption patterns with our water quality analysis described above to examine the possible roles of policies and carbon programs.

Other activities 

One presentation. 

One funding proposal related to this work has been submitted. 

June 2023

During this project period, the team of social scientists and ecologists with modeling expertise have worked together and decided to use four small catchments in Iowa as our study region for the simulation study, including two catchments in Story County and two in Floyd County to design simulation scenarios that integrate different carbon payment schemes with the land ecosystem model (DLEM 2.0). The scenarios will be designed to simulate the coupled water-N-carbon cycling within the plant-soil-water-river continuum from the grid to the regional level. This model has been extensively validated. We have identified five climate scenarios (historical, normal, dry, wet and dry-wet iterate) to represent the uncertainties that will likely affect carbon and nutrient outcomes.

In conjunction with the objectives of INRC project, we designed a draft protocol for an economics experiment intended to examine risk premium, ambiguity premium and uncertainty premium that farmers require when faced with uncertainties in different carbon payment schemes. We found that all students in our pilot tests exhibited risk aversion, with a positive risk premium. Slightly more than 66% of students exhibited ambiguity aversion. Regarding the impact of risk aversion and ambiguity aversion on conservation adoption, a random utility model can be utilized to account for farmers' heterogeneity. With parameters estimated with the economics experiments, we have preliminarily evaluated how various scenarios of uncertainty affect farmers’ participation decision in cover crops.

In the next project period, we intend to incorporate experimental results on uncertainty magnitude and risk aversion and asses the efficiency and distributional effects of different carbon payment schemes. Some of our preliminary findings are as follows: Result-based payment outperforms practice-based payment under the profit maximization if the risk aversion is not considered However, practice-based payment is more cost-effective when farmers’ risk aversion is taken into account. Bayer Carbon pays $6/acre, which is very low, compared to other companies $20-$30/ton of carbon. The risk premium might have been implicitly taken into account. We intend to look further into the simulation results and experimental outcomes to check the robustness of the preliminary findings.

Other Activities

- Two presentations were made: at the 78th International Annual Conference of the Soil and Water Conservation Society (SWCS), August 6-9, 2023, Des Moines, Iowa “Improving model capability in simulating spatiotemporal variations and flow contributions of nitrate export in tile-drained catchments.” Peiyu Cao, Chaoqun Lu, William Crumpton, Matthew Helmers, David Green, Greg Stenback.

Related Publications/Journal Articles

“Risk and Ambiguity Aversion in Conservation Practice Adoption and the Effectiveness of Carbon Payment Systems.” (With Zhushan Du, Peiyu Cao, and Chaoqun Lu)

 

December 2022

For the first six months of the project, our team of social scientists and ecologists with modeling expertise have worked together to design simulation scenarios that integrate different carbon payment schemes with ecosystem models, DLEM. In conjunction with the objectives of another INRC project (project number 2021-04), we designed a draft protocol for economics experiments intended to examine risk premium, ambiguity premium and uncertainty premium that farmers require when faced with uncertainties in different carbon payment schemes. We found that all students in our pilot tests exhibited risk aversion, with a positive risk premium. Slightly more than 66% of students exhibited ambiguity aversion. Regarding the impact of risk aversion and ambiguity aversion on conservation adoption, we plan to use a random utility to account for farmers' heterogeneity. With parameters estimated with the economics experiments, we will continue in our next project period to evaluate how various scenarios of uncertainty affect farmers’ participation decision in cover crops. Most importantly, in the next project period, we intend to closely work with the ecological model and economics experiments to simulate how nutrient outcomes and carbon outcomes differ by location and by weather conditions.

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