Soil Health Risk Model

Overview: The Land Core Risk Model is quantifying the economic risk-mitigation value of specific soil health practices by examining the correlation between the implementation of these practices over time, recovery time after a stress event, and ultimately their impact on yield. Starting with corn and soybeans, the dominant crops in the US, we are focusing on yield as farmers’ economic output.

The model draws on existing soil health practice data from spatial observations, combined with data from in-field experiments, publicly-available climate, weather, soil and geological data, as well as estimated yield data, to inform a statistical model capable of predicting the likelihood of reduced financial risk. This will pave the way for lenders and insurers to develop incentives such as lower-rate loans and discounted insurance to incentivize regenerative practice adoption.

Our goal is to use this model to build a pragmatic, actuarially-sound interactive decision-making tool to inform agricultural finance and insurance, and create the economic rationale for stakeholders to incentivize the adoption of de-risking, soil health practices. This will give lenders and insurers the tool they need to quantify the risk-mitigation impacts of specific soil health practices and develop pricing that reflects the positive impacts of their bottom lines. The tool will also help inform private and public-sector policy development and broaden the needed coalition of support for regenerative agriculture.

Risk Model Preliminary Results

We're thrilled to share that our team’s first academic manuscript, titled “Diversified crop rotations mitigate agricultural losses from dry weather,” has been submitted for peer review!

In the meantime, the "pre-print" manuscript is available on agriRxiv.

The paper explores the ability of more diverse crop rotations to protect against corn yield loss in drought conditions in the midwestern US, and how this soil health practice can be used as a risk-mitigation tool.

Questions about the manuscript? Contact corresponding author Dr. Tim Bowles at timothy.bowles@berkeley.edu

Questions about the Land Core Risk Model Project? Contact rebecca@landcore.org

A big congrats and thank you to the co-authors and the entire team for their continued hard work and dedication to create a more resilient agricultural system.

Thank you as well to our funders, including Foundation for Food & Agriculture Research, USDA National Institute of Food and Agriculture (AFRI) and our network of family foundation supporters, for making this work possible.

Interactive Risk Model Tool (Beta Version)

The development of this tool would not have been possible without the brilliant team from the Schmidt Center for Data Science and the Environment (DSE) at the University of California, Berkeley. Their front- and back-end development expertise helped create the functional user interface of the tool to bring our modeling team’s work to life, and will help many stakeholders across the agricultural industry visualize and analyze the benefits of soil health practices.

Below you will find a link to the interactive tool, as well as a short video walkthrough of the tool features.

 

Are you in farming, ag finance, insurance, policy or conservation, and interested in a tool demo? Contact us and we will add your name to our list for these future demo sessions!

Announcements

Land Core Risk Model Project Team

We have assembled a world-class group of modelers, statisticians, economists, soil scientists and farmers that include:

AGROECOLOGY & QUANTITATIVE ECOLOGY

  • Tim Bowles, Ph.D​.,​ Associate Professor of Agroecology and Sustainable Agricultural Systems, Department of Environmental Science, Policy, and Management, University of California Berkeley; Co-Project Investigator

  • Jiajie Kong, Ph.D., UC Berkeley, Statistics Postdoctoral Researcher

  • Yvonne Socolar, Ph.D., Agroecology, Department of Environmental Science, Policy and Management, UC Berkeley; Model Development Advisor

STATISTICS

  • Frederi Viens, Ph.D., Professor, Department of Statistics, Rice University; Co-Project Investigator

  • Gina Pizzo, Ph.D. Candidate, Department of Statistics and Probability, Michigan State University; Statistical Analyst

  • Sam Manski, Ph.D., Research Associate, Center for Statistical Training and Consulting, Michigan State University; Consulting Analyst 

  • Tyler Bagwell, Ph.D. Candidate, Department of Statistics, Rice University; Summer Graduate Statistical Modeler

  • Tripp Roberts, Ph.D. Candidate, Department of Statistics, Rice University; Summer Graduate Statistical Modeler

AGRICULTURAL ECONOMICS

  • Lawson Connor, Ph.D., Assistant Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas; Co-Project Investigator

  • Eunchun Park, Ph.D., Assistant Professor, Department of Agricultural Economics and Agribusiness, University of Arkansas; Crop Insurance & Statistical Modeler

  • Victor Funes-Leal, Ph.D., University of Arkansas; Farm Management Economist Postdoctoral Researcher

COVER CROP DATA SET DEVELOPMENT

  • Shuo Yu, Ph.D. Candidate, Agricultural and Resource Economics, UC Berkeley; Remote Sensing & Mapping Consultant

DATA MANAGEMENT

  • Leo Pham, Ph.D. Candidate, College of Agriculture & Natural Resources, Michigan State University, MS, Applied Statistics, MSU; Senior Data Scientist, Altice USA; Data Manager

  • Joseph Weaver, Ph.D. Student, Michigan State University; Analytics Platform Consultant

TOOL DEVELOPMENT

  • Shaun Klopfenstein, Founder and CTO, Nesterly; Back-end Engineer

  • Anna Zeman, Expert Principal Product Architect, Amplitude; Product Architect

Project Advisors

  • David Lobell, Ph.D., Professor at Stanford University in the Department of Earth System Science, Stanford Earth; Senior Fellow, Stanford Woods Institute for the Environment; Senior Fellow, Stanford Institute for Economic Policy Research (SIEPR), Stanford University

  • Perry de Valpine, Ph.D., Professor in the Department of Environmental Science, Policy and Management, UC Berkeley

  • Shefali Mehta, Ph.D.​, Founder and Lead Principal, Open Rivers Consulting Associates; Former Deputy Under Secretary for Research, Education and Economics, USDA)

  • Katherine Muller, Ph.D., Biologist, USDA-ARS; Statistical Modeler

  • Maoya Bassiouni, Ph.D., Postdoctoral Researcher, Quantitative Ecosystem Dynamics Lab, Department of Environmental Science, Policy and Management, UC Berkeley

  • Yanghui Kang, Ph.D., Postdoctoral Researcher, UC Berkeley

  • Ben Goldstein, Ph.D., Department of Environmental Science, Policy, & Management, UC Berkeley - Spatial Analysis Advisor

  • Kangogo Sogomo, Masters of Development Engineering, UC Berkeley; Geospatial Data Scientist - Cover Crop Data Advisor

  • Jenette Ashtekar​, Ph.D.​, VP of Sustainability and Regeneration, CiBO Technologies, Inc.

  • Keith Paustian, Ph.D.​, University Distinguished Professor, Department of Soil and Crop Sciences, and Senior Research Scientist at the Natural Resource Ecology Laboratory, Colorado State University

Next steps

  • Build out the tool to include more data and features, and expand it to include other states in the US midwest

  • Develop pilot programs to test the real-world application of the tool

  • Offer tool demo/informational sessions to stakeholder groups to receive and incorporate user feedback

Join Us

We’re seeking partners representing lending, investment and insurance to help inform model development. Partners also have the opportunity to help develop and pilot incentives for producers. Contact us to learn more.

Support the Work

Interested in helping us sustain the continuation of this work to support more resilient agricultural systems? Consider making a tax-deductible donation to Land Core and join us as we put healthy soil at the heart of thriving farms, businesses, communities and food systems.