考虑利润、生物多样性和生态系统服务的耕地设计多目标优化模型

IF 2.6 3区 环境科学与生态学 Q2 ECOLOGY
Caleb H. Geissler , Nathan L. Haan , Bruno Basso , Ames Fowler , Douglas A. Landis , Tyler J. Lark , Christos T. Maravelias
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引用次数: 0

摘要

要缓解工业化农业造成的生物多样性和生态系统服务减少的问题,需要更多可持续的农业方法。其中一种方法是在耕地中种植替代作物,这些作物可以支持生物多样性,减少侵蚀和化学径流,并在土壤中固碳。然而,应在何处种植此类作物,以平衡相互竞争的经济和环境目标,这个问题仍然悬而未决。为此,我们开发了一个混合整数二次约束程序,以优化考虑经济、生物多样性、温室气体排放和水质目标的耕地布局。除了作物种植地点外,我们还将空间变化的施肥量作为决策变量。我们还进一步考虑了核心区和不同作物之间的边缘对生物多样性的影响。为了证明该模型的适用性,我们将其应用于一个示例田地,展示了当决策者优先考虑不同目标以及边缘对生物多样性产生不同影响时,最佳耕地设计是如何变化的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-objective optimization model for cropland design considering profit, biodiversity, and ecosystem services
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.
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来源期刊
Ecological Modelling
Ecological Modelling 环境科学-生态学
CiteScore
5.60
自引率
6.50%
发文量
259
审稿时长
69 days
期刊介绍: The journal is concerned with the use of mathematical models and systems analysis for the description of ecological processes and for the sustainable management of resources. Human activity and well-being are dependent on and integrated with the functioning of ecosystems and the services they provide. We aim to understand these basic ecosystem functions using mathematical and conceptual modelling, systems analysis, thermodynamics, computer simulations, and ecological theory. This leads to a preference for process-based models embedded in theory with explicit causative agents as opposed to strictly statistical or correlative descriptions. These modelling methods can be applied to a wide spectrum of issues ranging from basic ecology to human ecology to socio-ecological systems. The journal welcomes research articles, short communications, review articles, letters to the editor, book reviews, and other communications. The journal also supports the activities of the [International Society of Ecological Modelling (ISEM)](http://www.isemna.org/).
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