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理解耕地景观生态安全与多功能性之间的关系:对支持耕地管理决策的启示。

Understanding the Relationships between Landscape Eco-Security and Multifunctionality in Cropland: Implications for Supporting Cropland Management Decisions.

机构信息

School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550001, China.

State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, China.

出版信息

Int J Environ Res Public Health. 2023 Jan 20;20(3):1938. doi: 10.3390/ijerph20031938.

DOI:10.3390/ijerph20031938
PMID:36767302
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9916074/
Abstract

Cropland is an essential strategic resource, for which landscape ecological security and multifunctionality evolution are related to regional stability and sustainable social development. However, few studies have explored the spatial heterogeneity of the coupling between the two from a multiregional and systematic perspective, and the interaction mechanisms have still not been thoroughly analyzed. In this study, a typical karst trough and valley area in the mountainous regions of southwest China was selected as the research object, and by establishing a multi-indicator evaluation system using a landscape pattern index, a multifunctional identification model, a coupled coordination model, and a geodetector model, the spatial variability in the evolutionary characteristics and the coupling and coordination of cropland landscape ecological security (CLES) and cropland multifunctionality (CM) in the mountainous regions of the southwest and their driving mechanisms were explored. The main results were as follows: (1) CLES in the mountainous areas of southwest China has undergone an evolutionary process of first declining and then slowly rising, with the characteristics of "fast declining in the high-value areas and slow rising in the low-value areas", while CM showed a spatial distribution of "high in the northwest and low in the northeast", with positive contributions originating from ecological functions. (2) Over the 20 years, the cropland coupling coordination degree (CCCD) values showed significant spatial heterogeneity, which was regionally expressed as ejective folds (EF) > TF (tight folds) > TLF (trough-like folds) > AF (anticlinorium folds). Low CCCD values were primarily found in the east, whereas high levels were primarily found in the west, with a rapidly diminishing trend. (3) There were differences in the driving mechanisms of CCDD in different landscapes, but GDP was still the determining factor and had a limiting effect. Hence, we call for the adoption of a "function over pattern" approach in areas with more development constraints and a "pattern over function" approach in areas with fewer development constraints. Ultimately, this study will contribute to the formation of a coupled cropland mechanism system described as the "multi-mechanisms drive, multi-elements integrated" system. In conclusion, this study can provide a better understanding of the relationship between cropland patterns and multifunctionality, which can help provide a basis for cropland conservation and landscape planning in similar mountainous areas and promote the achievement of sustainable agricultural development goals in the mountainous areas of southwest China.

摘要

耕地是一种重要的战略资源,其景观生态安全和多功能性演变与区域稳定和可持续社会发展息息相关。然而,从多区域和系统的角度来看,很少有研究探索两者之间的耦合的空间异质性,并且相互作用机制仍未得到彻底分析。在本研究中,选择了中国西南山区的一个典型的喀斯特槽谷地区作为研究对象,通过建立一个使用景观格局指数的多指标评价体系、一个多功能识别模型、一个耦合协调模型和一个地理探测器模型,探讨了山区耕地景观生态安全(CLES)和耕地多功能性(CM)的演变特征及其空间变异性以及它们的耦合和协调及其驱动机制。主要结果如下:(1)中国西南山区的 CLES 经历了先下降后缓慢上升的演变过程,呈现“高值区快速下降,低值区缓慢上升”的特征,而 CM 则表现出“西北高,东北低”的空间分布特征,其正贡献源于生态功能。(2)20 年来,耕地耦合协调度(CCCD)值表现出显著的空间异质性,区域表现为外凸褶皱(EF)>紧密褶皱(TF)>槽状褶皱(TLF)>背斜(AF)。低值 CCCD 主要分布在东部,而高值主要分布在西部,呈递减趋势。(3)不同景观中 CCDD 的驱动机制存在差异,但 GDP 仍然是决定因素,具有限制作用。因此,我们呼吁在发展约束较多的地区采用“功能重于格局”的方法,在发展约束较少的地区采用“格局重于功能”的方法。最终,本研究将有助于形成一个描述为“多机制驱动,多要素综合”系统的耦合耕地机制系统。总之,本研究可以更好地理解耕地格局与多功能性之间的关系,为类似山区的耕地保护和景观规划提供依据,并促进中国西南山区可持续农业发展目标的实现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/e80bd8343627/ijerph-20-01938-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/48f9eab177a2/ijerph-20-01938-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/1f9f29429f2b/ijerph-20-01938-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/102c77bb8060/ijerph-20-01938-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/731d31f72f3c/ijerph-20-01938-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/fcdaad0d6bc0/ijerph-20-01938-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/c4bfa860f32f/ijerph-20-01938-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/a759ee750aa1/ijerph-20-01938-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/013ed63ee820/ijerph-20-01938-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/11fe608c8204/ijerph-20-01938-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/e80bd8343627/ijerph-20-01938-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/48f9eab177a2/ijerph-20-01938-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/1f9f29429f2b/ijerph-20-01938-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/102c77bb8060/ijerph-20-01938-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/731d31f72f3c/ijerph-20-01938-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/fcdaad0d6bc0/ijerph-20-01938-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/c4bfa860f32f/ijerph-20-01938-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/a759ee750aa1/ijerph-20-01938-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/013ed63ee820/ijerph-20-01938-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/11fe608c8204/ijerph-20-01938-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9396/9916074/e80bd8343627/ijerph-20-01938-g009.jpg

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