农业景观农地和非农绿地斑块属性特征及其结构优化研究——以河南省封丘县为例

Structural attribute and optimization of farmland and non-cropped green-land patches of agricultural landscape: A case study of Fengqiu County, Henan Province

  • 摘要: 现代农业的发展导致大量非农绿地斑块从农业景观中消失, 结构简单、类型单一的农业景观使得农业生态系统功能与服务遭到了严重制约。本研究选择了黄河中下游平原的河南省封丘县为研究区域, 结合遥感影像调查和景观格局分析, 对研究区绿地斑块进行提取和分类, 并着重分析了该区域农田基质大背景下的非农绿地斑块的结构属性特征。研究结果显示, 研究区总体绿地率较低, 绿地斑块总面积较小; 人工林为优势绿地斑块类型, 但多围绕居住区分布, 呈现环状的分布特征; 斑块类型较为简单且空间分布比较分散, 斑块多样性指数较低, 破碎化程度较高。建议加大对研究区绿地斑块的改造, 通过增加斑块类型、设计农田边界、加强不同类型斑块间的连接度等措施, 提高农业景观中绿地斑块的数量与质量。本研究为进一步探讨研究区景观结构的合理布局, 并为今后多功能景观的构建奠定理论与实践基础, 具有重要的研究意义。

     

    Abstract: Agricultural landscape is one of the most important landscape types on the Earth. It is a composite mosaic made up of natural and human-managed patches, providing basic production and living conditions for humans. In agricultural landscape, non-cropped green-land patches or habitats are vital for maintaining biodiversity, functionalities and services of agro- ecosystems. However, these contributions of non-cropped green-land patches are not been fully recognized and understood even up to now. Plenty of evidence show that accelerated development of modern agriculture in the world has led to the disappearance of a large number of non-agricultural green-land patches. Moreover, the structure of agricultural landscape has become increasingly simple, severely damaging the functions and services of agro-ecosystems. Thus the sustainable development of agriculture and even the whole world require an increasing emphasis on the study and examination of the relationships between agricultural productivity and biodiversity, landscape heterogeneity and ecosystem functions and services. The middle and lower reaches of the Yellow River plain is an important grain-producing area in China. The plain has typical agricultural landscape features and provides the conditions for ideal case studies. Fengqiu County is located in the lower reaches of Yellow River in Henan Province, which was selected as case-study area for this research. To analyze the landscape structure, we firstly extracted and classified green-land patches by ArcGIS10.0 based on 2013 remote sensing images. Secondly, we derived vector diagrams of green-land patches to get basic and useful information on non-cropped green-lands in the study area. Then by referencing to the national green space classification standard, non-cropped green-land patches were divided into 3 types — residential green-land, hedge/ditch green-land and artificial forest. In this study, we specifically analyzed the structural attributes of non-cropped green-land patches using Fragstats package. The study results showed that both of the total rates and areas of non-cropped green-lands had low values in the Fengqiu County. The dominant type of non-cropped green-land patches was artificial forests with single structure and sparse vegetation, which was well distributed around residential areas. Residential green space was relatively scattered and broken whereas the connection degree of hedge/ditch green-land was low. The diversity index of non-cropped green-land patches was lower. All these suggested the fragmentation distribution characteristics in the study area. In order to increase the quantity and quality of non-cropped green-land patches in agricultural landscape, it was suggested to build new types and increase the ratio of non-cropped green-lands by adjusting the spatial structure and strengthening the configuration of different landscape elements. The detailed optimization methods of this strategy were given as follows: 1) enhancing landscape heterogeneity by increasing non-cropped green-land patch types; 2) increasing complexity of green-land patch structure by adjusting the proportion of non-cropped green-land patches; and 3) accomplishing rational distribution of landscape structure by optimizing the configuration of non-cropped green-land patches. The results of the study provided scientific bases for further exploration of landscape pattern arrangements and final construction of multifunctional landscapes in the future.

     

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