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Grant Quantifies Farm Risk Mitigation Through Improved Soil Health

Generating Soil Health Solutions
Generating Soil Health Solutions

Program Contact

Dr. LaKisha Odom

Aria McLauchlan

Aria McLauchlan

Land Core

Year Awarded  2022

FFAR award amount   $715,611

Total award amount   $1,449,610

Location   Grass Valley, CA

Program   Seeding Solutions

Matching Funders   Paul and June Rossetti Foundation, Mighty Arrow Family Foundation, J.M. Kaplan Fund, Great Island Foundation and Records-Johnston Family Foundation

There is no empirical correlation between good soil health practices like cover cropping, reduced tillage and crop rotations and their impacts on crop yields. As a result, agricultural lenders and insurers who price risk do not currently factor in incentives for the risk reduction generated by improved soil health management practices.

Aria McLauchlan
We have discounts for being a good driver and a non-smoker because those behaviors are scientifically proven to mitigate health risks and save insurers money. It’s commonplace across industries to incentivize the adoption of low-risk practices. Healthy soil should be no different. Aria McLauchlan
Land Core Co-founder & Executive Director
Dr. Lawson Connor
We need to quantify the resilience and economic benefits of applying soil health practices, to determine the unaccounted value they provide to financial systems and reward the farmers implementing them appropriately. Dr. Lawson Connor
University of Arkansas Agricultural Economist

Why this research is important?

There is currently no economic rationale agricultural lenders and insurers to offer farmers financial incentives, such as better terms or lower loan rates and insurance prices to producers adopting good soil health practices. Additionally, U.S. tax dollars currently subsidize billions of dollars in crop insurance payouts, largely due to flood and drought, which good soil health practices help mitigate. The U.S. Department of Agriculture’s Risk Management Agency, which is committed to increasing the availability and effectiveness of Federal crop insurance as a risk management tool, does not have a way to reliably quantify field-level risk reduction from good soil health practices that that could potentially save significant taxpayer money.

To solve for this, Land Core is creating an unprecedented market-based, actuarially-sound model that can determine the risk-mitigation benefits and related cost savings associated with specific soil health practices.

What else could this research impact?

The marketplace for agricultural lending and insurance is enormous. Agriculture debt was valued at $467.4 billion in 2022 according to the U.S. Department of Agriculture Economic Research Service, with around $20 billion in new loans issued annually. Capturing even a fraction of this existing market through de-risking represents a large funding potential to spur the transition to a soil-health centered agricultural system.

Risk is a major factor in preventing farmers from adopting soil health management practices. Crop insurance is a major opportunity for change, but insurers can’t provide an incentive or discount without reliable, research-based information. The data this project is generating has the potential to influence insurers to provide incentives to encourage practice adoption. LaKisha Odom, Ph.D.
Scientific Program Director Soil Health

Details About this Research

Land Core Co-founder and Executive Director, Aria McLauchlan, along with a cross-disciplinary research team including agroecologist Dr. Tim Bowles from U.C. Berkeley, statistician Dr. Frederi Viens from Rice University and agricultural economist Dr. Lawson Connor from the University of Arkansas System Division of Agriculture, is examining and correlating over 17 years of data on corn and soybean fields in the U.S. Midwest, including: 1) the adoption of important soil health-building practices, specifically cover cropping, no till/conservation tillage and crop rotations, via remote sensing; 2) estimated corn and soybean yields, via remote sensing and modeling; 3) key environmental variables using publicly-available climate, weather, soil and geological data, and 4) county-level economic data such as input use and crop insurance indemnities.

Utilizing causal inference methods and Bayesian statistics, the researchers are translating this data into a model capable of predicting the likelihood of reduced financial risk at field, farm, county and state levels for corn and soybeans, the dominant crops in the U.S.

The model framework the researchers are developing will answer questions like:

  • How does soil-health management, like increased cover cropping, for example, affect resilience to water stress?
  • How do yields, yield variability and yield trends over time compare in fields with a 5/10/15 year history of soil-health management vs. those with standard practices?
  • What is the likelihood of corn yields dropping 5+ percent below 10-year average under dry conditions on a given field? How does the reduction in management time and input costs improve the overall profitability of a corn yield?
  • How do the yield risk benefits of soil-health management compare to the level of risk implied by commodities market volatility?

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