Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Data release for Monarch Habitat as a Component of Multifunctional Landscape Restoration Using Continuous Riparian Buffers

Metadata Updated: July 6, 2024

Stabilizing the eastern, migratory population of monarch butterflies (Danaus plexippus) is expected to require substantial habitat restoration on agricultural land in the core breeding area of the Upper Midwestern U.S. Previous research has considered the potential to utilize marginal land for this purpose because of its low productivity, erodible soils, and high nutrient input requirements. This strategy has strong potential for restoring milkweed (Asclepias spp.), but may be limited in terms of its ability to generate additional biophysical and socioeconomic benefits for local communities. Here we explore the possibility of restoring milkweed via the creation of continuous riparian buffer strips around perennial and intermittent streams throughout the region. We use a GIS-based analysis to consider the potential of several different buffer-width scenarios to meet milkweed restoration targets. We further estimate the ability of these habitat areas to provide additional functionality in the form of crop pollination and water quality regulation across the entire region. Finally, we estimate the conservative economic value of these ecosystem services and compare it with the lost value of crops associated with each scenario. Results suggest that riparian buffers could be used to meet 10-43% of the total milkweed restoration target of 1.3 billion new stems with moderate management. The value of water quality and pollination benefits provided by buffers is estimated to exceed costs only for our smallest buffer-width scenario, with a cost-benefit ratio of 1:2.05. Larger buffer widths provide more milkweed, but costs to farmers exceed the benefits we were able to quantify. The large-scale restoration of multifunctional riparian corridors thus has the potential to add milkweed stems while also providing a variety of other valuable benefits. This suggests the potential to leverage monarch habitat restoration efforts for the benefit of a wider variety of species and a broader coalition of beneficiaries.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/1ba88b5f5ae26bd77afc38cc9fc60ff4
Identifier USGS:5d122bbde4b0941bde56e7c0
Data Last Modified 20200820
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 2a3043df-7fae-460d-82d0-cf28a0707f0b
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -98.318663,39.791821,-80.518964,49.376613
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash c88b78039a6dad12ffaf63922338a48e74fa7d291ce33ae81d984cf805fc37d6
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -98.318663, 39.791821, -98.318663, 49.376613, -80.518964, 49.376613, -80.518964, 39.791821, -98.318663, 39.791821}

Didn't find what you're looking for? Suggest a dataset here.