Abstract
More sustainable agricultural methods are needed to alleviate the decreases in biodiversity and ecosystem services that have occurred because of industrial agriculture. One such method is the inclusion of alternative crops into croplands that can support biodiversity, reduce erosion and chemical runoff, and sequester carbon in the soil. However, the question of where such crops should be planted to balance competing economic and environmental objectives remains open. To this end, we develop a mixed-integer quadratically constrained program to optimize the layout of a cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. We include spatially varying fertilization as a decision variable in addition to crop establishment location. We further include the effect of core area and edges between different crops on biodiversity. To demonstrate the applicability of the model, we apply it to an example field, showing how the optimal cropland design changes as a decision-maker prioritizes different objectives and as edges have different impacts on biodiversity.
Document Type
Article
Publication Date
1-2025
Digital Object Identifier (DOI)
https://doi.org/10.1016/j.ecolmodel.2024.110954
Funding Information
This material is based upon work supported by the Great Lakes Bioenergy Research Center, U.S. Department of Energy, Office of Science, Biological and Environmental Research Program under Award Number DE-SC0018409. Support for this research was provided by the National Science Foundation Long-term Ecological Research Program (DEB 2224712) at the Kellogg Biological Station, and by Michigan State University AgBioResearch.
Repository Citation
Geissler, Caleb H.; Haan, Nathan L.; Basso, Bruno; Fowler, Ames; Landis, Douglas A.; Lark, Tyler J.; and Maravelias, Christos T., "A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services" (2025). Entomology Faculty Publications. 236.
https://uknowledge.uky.edu/entomology_facpub/236
Notes/Citation Information
0304-3800/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/).