To measure landscape pattern metrics traits with changes of grain sizes, and summarize differences of landscape traits in different grain sizes, based on data of land use within the Yanghe Watershed in 1990, 2000 and 2013, landscape pattern metrics were chosen at the levels of class and landscape, and the effects of grain sizes in the range of 20 to 400 m on landscape pattern metrics were analyzed, using Geographic Information System (GIS) and Fragstats software. The functions for landscape pattern metrics and grain sizes were fitted and the variation coefficients of landscape pattern metrics were determined. The results showed that the normalized landscape shape index (NLSI), the aggregation index (AI), and the clumpiness (CLUMPY) for all land-use types at the class level within the Yanghe Watershed in 1990-2013 decreased with increasing of grain sizes and were well fitted by the quadratic polynomial-functions. Similarly, changes of patch density (PD) with grain sizes for farmland, woodland and rural-urban construction land were well fitted by quadratic polynomial functions and those for unused land were well fitted by a negatively linear function. Moreover, among all the landscape pattern metrics, the effective mesh size (MESH) and the normalized landscape shape index (NLSI) were the most sensitive to the changes of grain sizes for water area and rural-urban construction land, respectively. Among all the land-use types within the Yanghe watershed, the water area was the most sensitive to the changes of grain sizes. The AI, CLUMPY, MESH and the mean shape index (SHAPE_MN) for unused land in 2013 were smaller than those in 1990 and 2000, while the NLSI for unused land in 2013 was higher than those in 1990 and 2000. Besides, the yearly differences of the AI, CLUMPY, MESH, NLSI for the
rural-urban construction land in 1990-2013 were completely contrary to those for the unused land. The PD for unused land and rural-urban construction land in 2013 was higher than those in 1990 and 2000. At the landscape level, among all landscape metrics, the PD and LSI were the most sensitive to the changes of grain sizes. The patch richness (PR) did not change with the grain sizes. Changes of the Shannon diversity index (SHDI), the Shannon evenness index (SHEI) and the shape coefficient of variation index (SHAPE_CV) with the grain sizes were complex. Changes of the mean fractal dimension index (FRAC_MN), the SHAPE_MN, the AI, the contagion (CONTAG), the PD, the landscape shape index (LSI) and the cohesion (COHESION) with grain sizes in 2013 were similar to those in 1990 and 2000. The paper concludes that significant scale effects exist in most landscape pattern metrics in the Yanghe Watershed landscape, in addition, different responses to the changing grain size occur with different landscape metrics, and various land use types. The present study could improve the understanding of the changes of landscape pattern at the scale of watershed in the future.
Key words
landscape pattern; land use; scale effect; grain size; watershed
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References
[1] 傅丽华, 谢炳庚, 张晔. 长株潭核心区土地利用生态风险多尺度调控决策[J]. 经济地理, 2012, 32(7): 118-122.
[2] 刘源鑫, 焦峰. 黄土高原丘陵区景观特征与景观指数粒度效应研究[J]. 水土保持研究, 2013, 20(3): 23-27.
[3] 邬建国. 景观生态学: 格局、过程、尺度与等级[M]. 北京: 高等教育出版社, 2000.
[4] 陈永林, 谢炳庚, 李晓青. 长沙市土地利用格局变化的空间粒度效应[J]. 地理科学, 2016, 36(4): 564-570.
[5] 吴未, 许丽萍, 张敏, 等. 不同斑块类型的景观指数粒度效应响应—以无锡市为例[J]. 生态学报, 2016, 36(9): 2740-2749.
[6] 王录仓, 俞菲, 俞洋子, 等. 兰州市市区景观生态格局特征分析[J]. 甘肃农业大学学报, 2012, 47(5): 115-120.
[7] 吕一河, 傅伯杰. 生态学中的尺度及尺度转换方法[J]. 生态学报, 2001, 21(12): 2096-2105.
[8] Corry R C, Lafortezza R, et al. Sensitivity of landscape measurements to changing grain size for fine-scale design and management[J]. Landscape and Engineering, 2007, 3(1): 47-53.
[9] 周伟, 钟星, 袁春, 等. 1:10000比例尺土地利用景观指数的粒度效应分析[J]. 中国土地科学, 2010, 24(11): 20-26.
[10]陈睿山, 蔡运龙. 土地变化科学中的尺度问题与解决途径[J]. 地理研究, 2010, 29(7): 1244-1256.
[11]谢作轮, 赵锐锋, 张丽华, 等. 干旱内陆河流湿地景观破碎化模型构建与尺度分析—以黑河中游湿地为例[J]. 自然资源学报, 2015, 30(11): 1834-1845.
[12]陆禹, 佘济云, 陈彩虹, 等. 基于粒度反推法的景观生态安全格局优化—以海口市秀英区为例[J]. 生态学报, 2015, 35(19): 6384-6393.
[13]赵文武, 傅伯杰, 陈利顶. 景观指数的粒度变化效应[J]. 第四纪研究, 2003, 23(3): 326-333.
[14]刘媛媛, 刘学录. 甘肃永登县土地利用景观格局的空间尺度效应[J]. 应用生态学报, 2016, 27(4): 1221-1228.
[15]潘竟虎, 苏有才, 黄永生, 等. 疏勒河中游土地利用与景观格局动态[J]. 应用生态学报, 2012, 23(4): 1090-1096.
[16]Teng M, Zeng L. Responses of landscape metrics to altering grain size in the Three Gorges Reservoir landscape in China[J]. Environmental Earth Sciences, 2016, 75(13): 1-13.
[17]徐兰, 罗维, 周宝同, 等. 基于土地利用变化的农牧交错带典型流域生态风险评价—以洋河为例[J]. 自然资源学报, 2015, 30(4): 580-590.
[18]布仁仓, 胡远满, 常禹, 等. 景观指数之间的相关分析[J]. 生态学报, 2005, 25(10): 2764-2775.
[19]Símová P, Katerina G. Landscape indices behavior: A review of scale effects[J]. Applied Geography, 2012, 34(5): 385-394.
[20]Plexida S G, Sfougaris A I, Ispikoudis I P, et al. Selecting landscape metrics as indicators of spatial heterogeneity: a comparison among Greek landscapes[J]. International Journal of Applied Earth Observation and Geoinformation, 2014, 26(2): 26-35.
[21]He H S, Stephen J V, Mladenoff D J, et al. Effects of spatial aggregation approaches on classified Landsat TM satellite imagery[J]. International Journal of Geographical Information Science, 2002, 16(1):93-109.
[22]周兴东, 于胜文. 空间粒度变化对景观格局指数的影响—以徐州地区为例[J]. 测绘科学, 2009, 34(1): 201-202.
[23]高艳, 毕如田. 涑水河流域景观指数的粒度效应[J]. 中国农学通报, 2010,26(13): 396-400.
[24]陈颐, 林毅伟, 朱志鹏, 等. 莆田市土地利用格局的地形梯度特征变化及尺度效应[J]. 安徽农业大学学报, 2017, 23(1): 102-107.
[25] Zhang N, Li H. Sensitivity and effectiveness and of landscape metric scalograms in determining the characteristic scale of a hierarchically structured landscape[J]. Landscape Ecology, 2013, 28(2): 343-363.
[26]Santiago S, Martínez M J. Landscape patterns simulation with a modified random clusters method[J]. Landscape Ecology, 2000, 15(7): 661-667.
[27]Feng Y, Liu Y. Fractal dimension as an indicator for quantifying the effects of changing spatial scales on landscape metrics[J]. Ecological Indicators, 2015, 53(6):18-27.
[28]邱扬, 杨磊, 王军, 等. 黄土丘陵小流域景观格局指数的粒度效应[J]. 应用生态学报, 2010, 21(5): 1159-1166.
[29]Kelly M, Tuxen K A, Stralberg D, et al. Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time[J]. Ecological Indicators, 2011, 11(2): 263-273.
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