Work Description

Title: Data from: Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges Open Access Deposited

h
Attribute Value
Methodology
  • We compiled the following datasets for lower Michigan at the county scale from 2008-2019: area under successful (high biomass) overwintering cover crops, EQIP payments for cover crops (and all other EQIP payments), area associated with EQIP contracts for cover crops, CRP payments, crop subsidy and insurance payments, and two environmental factors that affect cover crop growth (growing degree days (GDD) and precipitation). To quantify the area under successful overwintering cover crops, we produced annual maps at 30 m resolution of the main classes of agricultural landcover that are present from September to April. To create these maps, we combined information from two data layers developed by the United States Department of Agriculture (USDA) National Agricultural Statistics Service Information (NASS) and a map of winter cover that we produced using Landsat satellite data. We mapped five classes of agricultural landcover: bare/fallow, winter wheat, alfalfa hay, low biomass cover that represented weedy fallow or unsuccessful cover crops, and high biomass cover that represented successful cover crops (e.g., cereal rye, ryegrass), which obtained appreciable biomass during the overwintering period. For our statistical analyses, we use the overwintering cover crop class as our dependent variable in all regression models. We aggregated these 30 m satellite data to the county scale for each year in two ways. The first quantified the area under overwintering cover crops for all agricultural parcels, and the second measure quantified the overwintering cover crop area only for parcels that were classified as row crops (corn, soybeans, or wheat) for any year from 2008-2019. We used the raster and exactextractr packages in R project software for all data layer creation, calculations, and extraction. Full details of the project and methods can be found in: Surdoval et al. 2024. Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges. Environmental Research Letters.
Description
  • We conducted a mixed-methods study to understand how financial incentive programs impact transitions to cover cropping in Michigan. Michigan farms span a wide range of soil types, climate conditions, and cropping systems that create opportunities for cover crop adoption in the state. We tested the relationship between Environmental Quality Incentives Program (EQIP) payments for cover crops and cover crop adoption between 2008-2019, as measured by remote sensing. Panel fixed effects regressions showed that EQIP increased winter cover crop presence. Every EQIP dollar for cover crops was associated with a 0.01 hectare increase in winter cover, while each hectare enrolled in an EQIP contract for cover crops was associated with a 0.86 – 0.93 hectare increase in winter cover.
Creator
Creator ORCID iD
Depositor
Contact information
Discipline
Funding agency
  • Other Funding Agency
Other Funding agency
  • United States Department of Agriculture National Institute of Food And Agriculture
ORSP grant number
  • 12686966
Keyword
Date coverage
  • 2008-09-01 to 2019-05-01
Citations to related material
  • Surdoval, A., Jain, M., Blair, E., Wang, H., and J. Blesh. In press. Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges.
Resource type
Last modified
  • 03/06/2024
Published
  • 03/06/2024
Language
DOI
  • https://doi.org/10.7302/n9df-av09
License
To Cite this Work:
Surdoval, A., Jain, M., Wang, H., Blesh, J. (2024). Data from: Financial incentive programs and farm diversification with cover crops: Assessing opportunities and challenges [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/n9df-av09

Relationships

This work is not a member of any user collections.

Files (Count: 3; Size: 80.4 KB)

Thumbnailthumbnail-column Title Original Upload Last Modified File Size Access Actions
EQIP_cc_data_dictionary.csv 2024-02-28 2024-03-06 27.3 KB Open Access
EQIP_cc_data.csv 2024-02-28 2024-02-28 36.9 KB Open Access
Surdoval_et_al._2024_Description.docx 2024-02-28 2024-03-06 16.3 KB Open Access

Download All Files (To download individual files, select them in the “Files” panel above)

Best for data sets < 3 GB. Downloads all files plus metadata into a zip file.



Best for data sets > 3 GB. Globus is the platform Deep Blue Data uses to make large data sets available.   More about Globus

Remediation of Harmful Language

The University of Michigan Library aims to describe its collections in a way that respects the people and communities who create, use, and are represented in them. We encourage you to contact us anonymously if you encounter harmful or problematic language in catalog records or finding aids. More information about our policies and practices is available at Remediation of Harmful Language.