生态系统服务价值空间分布格局的尺度依赖性研究——以甘谷县为例

IF 3.9 2区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Yingying Wu, Xuelu Liu, Qiqi Zhao, Hongyan Liu, Fei Qu, Miaomiao Zhang
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引用次数: 0

摘要

本文旨在筛选生态系统服务价值总量和空间分异的关键尺度和最优尺度,以提高生态系统服务价值评价结果的准确性和可靠性。基于2000 - 2005年、2010年、2015年和2020年的LULC数据,采用等效因子法和非参数检验,分析探讨了甘谷县生态环境价值总值及其临界尺度的变化规律。利用变异系数法和Moran指数法确定了ESV空间分异的最优网格尺度。根据空间自相关分析方法,描述了最优尺度下2000-2020年ESV的空间分布格局。结果表明:(1)2000 ~ 2020年5个时期的生态环境价值总值总体呈上升趋势,且规模增大。在1100 m尺度之后,2000年、2005年和2010年的ESV总量差异不显著。在1000 m尺度之后,2015年和2020年的ESV总量没有显著差异。1100 m栅格尺度是研究有无尺度依赖的ESV总量的统一临界尺度。(2)在ESV总量稳定的情况下,不同水平下ESV的空间分布格局具有显著的尺度依赖性。中等水平的面积比例占主导地位。在1700 m尺度之后,esv的空间分布格局没有显著差异,尺度依赖性消失。1900 ~ 2100 m尺度5周期变异系数值较小。Moran’s I值均为>.5,在1900m尺度达到峰值。1900 m格网尺度是探索ESV空间分布格局的最佳尺度。(3)在最佳尺度下,甘谷县ESV总体上呈现南高北低的分布格局。以中值为主,集中在研究区中北部。2000 - 2020年,中国西南地区ESV空间分布呈现由高向低、由南向北递减的格局,以高-高集聚为主。综上所述,无论是ESV总量还是空间分异尺度都存在显著的尺度依赖性。不同尺度的选择会影响评价结果的准确性。结合具体的研究需求,选择最优的网格尺度,可以为未来甘谷县ESV的科学量化提供前提条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Study on the scale dependence of the spatial distribution pattern of ecosystem service value - a case study of Gangu County, China.

Study on the scale dependence of the spatial distribution pattern of ecosystem service value - a case study of Gangu County, China.

Study on the scale dependence of the spatial distribution pattern of ecosystem service value - a case study of Gangu County, China.

Study on the scale dependence of the spatial distribution pattern of ecosystem service value - a case study of Gangu County, China.

This article aims to screen out the critical and optimal scales of the total value and spatial differentiation of ecosystem service value (ESV) to improve the accuracy and reliability of the ESV assessment results. On the basis of LULC data form 2000 to 2005, 2010, 2015, and 2020, we analyzed and explored the variation in the total value of ESVs and its critical scales in Gangu County by using the equivalent factor method and nonparametric tests. The optimal grid scale for the spatial differentiation of ESV is determined with the help of the method of coefficient of variation and Moran index. The spatial distribution pattern of ESV during the period of 2000-2020 under the optimal scale is described according to the method of spatial autocorrelation analysis. The results show that: (1) The total value of ESV for the five periods from 2000 to 2020 shows an overall upward trend with increasing scale. The total value of ESV in 2000, 2005, and 2010 is not significantly different after the 1100 m scale. The total value of ESV in 2015 and 2020 is not significantly different after the 1000 m scale. The 1100 m grid scale is a uniform critical scale for studying the total value of ESV with or without scale dependence. (2) When the total value of ESV is stabilized, the spatial distribution pattern of ESV under different levels has a significant scale dependence. The area proportion of the medium level is dominant. There is no significant difference in the spatial distribution patterns of ESVs after the 1700 m scale, and the scale dependence disappears. 5-period coefficient of variation values are small in the range of 1900-2100 m scale. Moran's I values are all> 0.5 and reach the peak in the 1900m scale. 1900 m grid scale is the optimal scale for exploring the spatial distribution pattern of ESV. (3) At the best scale, the ESV in Gangu County shows an overall distribution pattern of south-high and north-low. It is dominated by medium values and focused in the middle and north of the study region. From 2000 to 2020, the spatial distribution of ESVs primarily devolved from high to low values and decreased from southern to northern, and ESV is dominated by high-high agglomeration. In summary, there is a significant scale dependence in both the total value of ESV and the scale of spatial differentiation. Different scale choices will affect the accuracy of the evaluation results. Selecting the optimal grid scale in combination with specific research needs can provide a prerequisite for the future scientific quantification of ESV in Gangu County.

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来源期刊
Scientific Reports
Scientific Reports Natural Science Disciplines-
CiteScore
7.50
自引率
4.30%
发文量
19567
审稿时长
3.9 months
期刊介绍: We publish original research from all areas of the natural sciences, psychology, medicine and engineering. You can learn more about what we publish by browsing our specific scientific subject areas below or explore Scientific Reports by browsing all articles and collections. Scientific Reports has a 2-year impact factor: 4.380 (2021), and is the 6th most-cited journal in the world, with more than 540,000 citations in 2020 (Clarivate Analytics, 2021). •Engineering Engineering covers all aspects of engineering, technology, and applied science. It plays a crucial role in the development of technologies to address some of the world''s biggest challenges, helping to save lives and improve the way we live. •Physical sciences Physical sciences are those academic disciplines that aim to uncover the underlying laws of nature — often written in the language of mathematics. It is a collective term for areas of study including astronomy, chemistry, materials science and physics. •Earth and environmental sciences Earth and environmental sciences cover all aspects of Earth and planetary science and broadly encompass solid Earth processes, surface and atmospheric dynamics, Earth system history, climate and climate change, marine and freshwater systems, and ecology. It also considers the interactions between humans and these systems. •Biological sciences Biological sciences encompass all the divisions of natural sciences examining various aspects of vital processes. The concept includes anatomy, physiology, cell biology, biochemistry and biophysics, and covers all organisms from microorganisms, animals to plants. •Health sciences The health sciences study health, disease and healthcare. This field of study aims to develop knowledge, interventions and technology for use in healthcare to improve the treatment of patients.
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