{"title":"Coupled analysis of arable land input intensity and output intensity based on sliding windows","authors":"","doi":"10.1016/j.mex.2024.102862","DOIUrl":null,"url":null,"abstract":"<div><p>Sustainable intensification (SI) of agriculture can produce more food to meet the demand of a growing population while considering ecosystem health. The current SI estimation framework ignores the complex coupling between input and output intensity of arable land. A method for coupled analysis of arable land input intensity and output intensity based on sliding windows is proposed. By calculating the correlation coefficient and partial correlation coefficient between input intensity and output intensity in different value ranges as the order parameter, the phase transition and the influence process of input intensity on output intensity can be explained. Meanwhile, a python-based framework is developed.</p><p>An application of the method was made to reveal the interaction process between annual provincial input intensity and output intensity in mainland China. Researchers in many fields may benefit from the method by obtaining a fast way to analysis the coupling relationship between driving and dependent variables in complex systems.</p><ul><li><span>•</span><span><p>New method for SI estimation is presented.</p></span></li><li><span>•</span><span><p>The order parameter of the coupling relationship between input and output intensity is calculated based on sliding windows.</p></span></li><li><span>•</span><span><p>Analysis of coupling relationships between driving and dependent variables in complex systems.</p></span></li></ul></div>","PeriodicalId":18446,"journal":{"name":"MethodsX","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2215016124003145/pdfft?md5=3de0db9fe9ed1f1e0b94e56c4b5c51c4&pid=1-s2.0-S2215016124003145-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MethodsX","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2215016124003145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Sustainable intensification (SI) of agriculture can produce more food to meet the demand of a growing population while considering ecosystem health. The current SI estimation framework ignores the complex coupling between input and output intensity of arable land. A method for coupled analysis of arable land input intensity and output intensity based on sliding windows is proposed. By calculating the correlation coefficient and partial correlation coefficient between input intensity and output intensity in different value ranges as the order parameter, the phase transition and the influence process of input intensity on output intensity can be explained. Meanwhile, a python-based framework is developed.
An application of the method was made to reveal the interaction process between annual provincial input intensity and output intensity in mainland China. Researchers in many fields may benefit from the method by obtaining a fast way to analysis the coupling relationship between driving and dependent variables in complex systems.
•
New method for SI estimation is presented.
•
The order parameter of the coupling relationship between input and output intensity is calculated based on sliding windows.
•
Analysis of coupling relationships between driving and dependent variables in complex systems.
农业可持续集约化（SI）可以生产更多的粮食，满足不断增长的人口需求，同时兼顾生态系统健康。目前的 SI 估算框架忽略了耕地投入强度和产出强度之间复杂的耦合关系。本文提出了一种基于滑动窗口的耕地投入强度和产出强度耦合分析方法。通过计算输入强度和输出强度在不同值范围内的相关系数和偏相关系数作为阶次参数，解释了输入强度对输出强度的相变和影响过程。同时，开发了一个基于 python 的框架，并应用该方法揭示了中国大陆各省年度投入强度与产出强度之间的相互作用过程。该方法为复杂系统中驱动变量和因变量之间耦合关系的快速分析提供了一种新的方法，可使许多领域的研究人员从中受益。
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
