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吴未,许丽萍,张敏,欧名豪,符海月.不同斑块类型的景观指数粒度效应响应——以无锡市为例.生态学报,2016,36(9):2740~2749 本文二维码信息
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不同斑块类型的景观指数粒度效应响应——以无锡市为例
Impact of landscape metrics on grain size effect in different types of patches: a case study of Wuxi City
投稿时间:2014-05-17  修订日期:2016-02-01
DOI: 10.5846/stxb201405171015
关键词粒度效应  斑块类型  景观指数  Moran's I指数  响应  无锡
Key Wordsgrain size effect  types of patches  landscape metrics  Moran's I index  response  Wuxi City
基金项目中国博士后基金特别资助项目(2010003592);江苏高校哲学社会科学研究一般项目(2015SJD096);南京农业大学中央高校基本科研业务费人文社会科学研究基金配套项目(SKPT2015018)
作者单位E-mail
吴未 南京农业大学土地管理学院, 南京 210095  
许丽萍 南京农业大学土地管理学院, 南京 210095  
张敏 南京农业大学土地管理学院, 南京 210095  
欧名豪 南京农业大学土地管理学院, 南京 210095 mhou@njau.edu.cn 
符海月 南京农业大学土地管理学院, 南京 210095  
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摘要:
斑块类型与景观格局粒度效应响应关系密切。以无锡市为研究区域,针对地区社会经济活动频繁、人为干扰强烈和生态脆弱等特性,以土地利用类型、热力等级和生态贡献为斑块类型划分依据,构建出对应的3种不同景观格局。在相同粒度变化情况下,选用了19个景观水平指数和Moran's I指数,分析了不同景观格局粒度效应的响应情况。结果表明,随粒度变粗:1)土地利用类型、热力等级和生态贡献斑块的部分景观指数响应曲线变化剧烈程度依次减弱;2)3类斑块的Moran's I指数均存在尺度效应。其中,土地利用类型和生态贡献斑块的Moran's I指数存在负相关,热力等级斑块没有。生态贡献斑块响应曲线在正相关区域内变化相对平缓,土地利用类型与热力等级斑块响应曲线变化趋势相反;3)指数反映的第一临界粒度基本一致,但景观指数响应曲线的临界现象更为明显。总体上,不同类型斑块在同一研究区构成的景观格局、指数响应曲线变化趋势和第一临界粒度都较为相似;斑块类型对景观指数粒度效应响应存在影响,但还有待深入探讨。
Abstract:
Grain size effect is a major issue in landscape ecology research. Its importance is determined by the effective and precise transformation of the information and characteristics of a landscape pattern as well as the ecological process embodied during the scaling procedure. A landscape pattern that consists of patches has a close relationship with patch classification. In previous studies, grain size effect was analyzed from the perspective of a landscape pattern generated from one particular patch classification. However, differences in the grain size effect caused by different types of patch classification have been ignored. The aim of this study was to explore the effect of different patch classifications on the grain size effect. We used Wuxi City as a study case because it has undergone rapid urban development, has been subject to dramatic changes in land use, and has a vulnerable environment. Three patch classifications were applied: land use/land cover (LULC), urban heat island (UHI), and ecological contribution (EC). Their matching landscape patterns were generated accordingly. In the LULC pattern, the patches were divided into eight categories: cropland, woodland, grassland, garden land, rivers, lakes and ponds, construction land, marshland, and unused land, which were generated from the 2010 Land-use Updating Map for Wuxi. Patches in the UHI pattern were obtained through the following two main steps: (1) Land surface temperatures (LST) were obtained from Landsat TM using the mono-window algorithm. (2)The mean-standard deviation method was employed to transform LST into a thematic map of five thermal categories: very high, high, middle, low, and very low. EC pattern patches were also generated. The ecological system service value (ESSV) of a patch varies depending on the land-use type. The ESSV of patches representing the same land-use type also vary due to its natural features and disturbance from nearby different land-use patch types. Considering its natural features and the received disturbance, the ESSV for each LULC patch was calculated using the multi-weight factors model in the ARCGIS software. The natural breakpoint method was used to transform the LULC pattern into an EC pattern with three value categories: high, middle, and low. The basic spatial unit was 30 m. The pixels scale on the side of the grid cell enabled another 23 basic cells to be assembled, which represented 40, 50, 60, 70, 80, 90, 100, 120, 150, 180, 210, 240, 270, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000 m. Nineteen landscape metrics, including patch density (PD), largest patch index (LPI), landscape shape index (LSI), area-weighted patch fractal dimension (AWMPFD), perimeter area fractal dimension (PAFRAC), cohesion index (COHESION), division index (DIVISION), mean shape index (MSI), and the global spatial autocorrelation index for Moran's I, were computed to detect the LULC, UHI, and EC patterns at different spatial scales using FRAGSTATS and ARCGIS software. The results showed that increasing the spatial grain size changed the response curves for some of the landscape metrics and altered the Moran's I index values. Furthermore, the different patch classifications altered the grain size effect. However, the critical grain sizes for most of the landscape metrics and Moran's I were the same. There was also an interrelationship between grain size effect and patch classification. However, how and to what degree the differences in patch classification alter the grain size effect needs further study.
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