Sponsor
GS was supported by the National Science Foundation Graduate Research Fellowship under Grant No. (DGE-1848739) the Grand Challenges Initiative Postdoctoral Fellowship of Chapman University, and NASA SMD Bridge Program Seed Funding (BPSF) (80NSSC24K1617). JBF was supported by NASA ECOSTRESS Science and Applications Team (ESAT) (80NSSC23K0309) and NASA SMD Bridge Program Seed Funding (BPSF) (80NSSC24K1617). Support for this research was provided by the Great Lakes Bioenergy Research Center, U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (DE-SC0018409), by the National Science Foundation Long-term Ecological Research Program (DEB 1832042) at the Kellogg Biological Station; Michigan State University AgBioResearch, Department of Geography, Environment, and Spatial Science, and the Environmental Science and Public Policy program.
Published In
Environmental Research Letters
Document Type
Article
Publication Date
12-13-2024
Subjects
Data Mining, Land management
Abstract
As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) within a fine-scale geographic area (30 m). We scaled National Agricultural Statistic Survey land management data to National Land Cover Data cropland extents to assess GWP of cropland management over time and among management units (i.e. counties and production systems). We found that cropland extent alone was not indicative of GWP emissions; rather, rates of management intensity, such as energy and fertilizer use, are greater indicators of anthropogenic GWP. We found production processes for fuel and fertilizers contributed 51.93% of GWP, where 33.58% GWP was estimated from N _2 O emissions after fertilization, and only 13.31% GWP was due to energy consumption by field equipment. This demonstrates that upstream processes in LCA should be considered in NbS with the relative contribution of fertilization to GWP. Additionally, while land cover change had minimal GWP effect, urbanization will replace croplands and forests where NbS are implemented. Fine-scale landscape variations are essential for NbS to identify, as they accumulate within regional and global estimates. As such, this study demonstrates the capability to harness both LCA and fine-resolution imagery for applications in spatiotemporal and socioecological research towards identifying and monitoring NbS.
Rights
Copyright (c) 2024 The Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
Locate the Document
DOI
10.1088/1748-9326/ad959e
Persistent Identifier
https://archives.pdx.edu/ds/psu/42879
Citation Details
Shirkey, G., Anctil, A., John, R., Kolluru, V., Mungai, L., Kashongwe, H., Cooper, L. T., Celik, I., Fisher, J. B., & Chen, J. (2024). Identifying opportunities for nature-based solutions with geospatialized life cycle assessments and fine-scale socioecological data. Environmental Research Letters, 20(1), 014023.