城镇化的快速推进加大了人类活动对自然生态系统的干预程度，从而在一定程度上影响着生态系统服务功能，对生态系统的健康发展造成了一定的威胁，实现生态系统服务的可持续发展要加大对生态系统的保护。生态安全格局（Ecological Security Pattern，ESP）关注的是生态过程与功能之间的联系，识别优化生态安全格局是维护生态系统正常功能，是保障区域可持续发展的有效措施，本文以陕西省为研究对象，基于多源遥感数据和社会经济数据评估2000-2020年生态系统服务并构建生态安全格局。本文首先对土地利用变化和所引起的生态系统服务价值（Ecosystem Services Value，ESV）的变化进行分析，在考虑供需影响的前提下来评估生态系统服务稀缺性价值（Ecosystem Services Scarcity Value，ESSV），并对生态系统服务价值的时空演变特征进行分析，选取五个单项生态系统服务功能指标来评估陕西省生态系统服务功能时空变化特征，在对生态系统服务价值和生态系统服务功能评估的基础上，利用最小累积阻力（Minimum Cumulative Resistance, MCR）模型来分析区域生态安全格局并提出优化措施。本文主要结论如下：

（1）陕西省土地利用类型中，耕地、林地和草地的面积占比较大，2020年三种用地类型总面积占全区面积的96.50%，2000-2020年间土地利用总体转移特征为耕地向建设用地和草地转入，2000-2020年土地利用动态度变化最大的类型是建设用地，远远大于其它土地利用类型，达到3.32%，随着城镇化的快速推进，陕西省共有2967.13km²的林地转换为其它地类，在耕地向其它地类转移的过程中，耕地向草地转移的面积达到最大值，为2220.97km²，用地转化主要分布在陕西省的西部宝鸡市陇县和千阳县，究其原因主要是因为退耕还林工程的推进而造成。

（2）近20年来陕西省景观格局变化较大，除散布与并列指数(Interspersion Juxtaposition Index,IJI)和香农均匀度指数（Shannon’s Evenness Index,SHEI）减少外，其它指数均有所增加，景观斑块面积（Class Area，CA）和数量有所增加，说明破碎化程度增加，主要是因为陕西省经济的快速发展造成城镇向外围扩张而导致区域面积的增加，景观丰富度指数（Patch Richness Index，PRI）和景观丰富度密度（Patch Richness Density，PRD）呈上升趋势，说明近20年陕西省景观丰富度增加，物种多样化升高，也代表着破碎程度有所加重，这与城镇化的快速推进有直接关系，区域景观处于破碎化状态分布在研究区的各个地方。2010-2020年是陕西省快速发展期间，人工景观的修建在一定程度上改变了动物迁徙通道，对生态系统产生了一定的影响，陕西省景观分布合理性有待提升，城市内部建设用地分布较为密集，如西安市和榆林市，城镇周边被农田和林地所包围，整体上景观格局空间分布朝着不均衡的方向发展。

（3）陕西省生态系统服务价值呈现出先增加后减少再增加的演变趋势，2000-2010年呈现出增加的趋势，2010-2015年呈现减少的趋势，2015-2020年呈现增加的趋势。2015-2020年间，陕西省生态系统服务价值共增加了3.00×10⁹元。2020年，生态系统服务功能高值区面积占研究区总面积的29.77%，区域整体生态系统服务功能处于较高水平，2000-2020年期间，ESV高值区分布在陕北地区榆林市西北部、汉江流域周围和铜川市北部等地区，ESV低值区主要分布在人口密集的城市中心和农村居民点分布的地区，如西安市市中心、榆林市市中心等。处于次优水平服务功能的斑块以草地为主，主要分布在郊区与农村之间；服务功能低值区主要位于人口密度大且建筑设施较多的地方。研究期间陕西省生态系统服务功能整体上有所减弱，以南部高北部低的空间分布格局为主，研究区内生态系统服务功能高值区大多分布在林地所覆盖的地区和水域周边地区，西安市北部、铜川市南部等地区生态系统服务功能处于较低水平。主要是因为研究区北部经济发展速度高于南部，北部城镇化发展较快、人口密度大且建设用地分布更为密集，而陕西省南部有着更多的耕地和林地，可以看出，生态系统服务功能的高低与城镇化水平在一定程度上呈负相关关系，城镇化水平间接影响着生态系统服务功能。

（4）陕西省生态源地中，林地、耕地和草地的面积占比较大，尤其在研究区的西南部和东北部这两个区域。髙阻力地区主要分布在城镇建设用地的四周，且该区域的生态安全水平呈现较低的态势，研究期间生态安全水平较低的区域面积有所减少。各级分区中，林地面积占比一直处于最高值。从空间上看，位于研究区北部和南部的生态廊道和生态节点较多，2000-2020年陕西省中水平生态安全区域面积位于第二，低水平生态安全区域面积占比较大，但随着时间的推移其面积不断减少，说明陕西省生态安全水平整体上有所好转。

基于以上研究，建议在制定可持发展政策时，应更多关注有较高潜在生态系统服务 的土地利用类型，继续进行生态修复工程，对于源地实施分级管理，从源头上提高生态 系统服务质量，统筹不同安全等级的区域管理措施，加强跨行政边界的区域合作。本文 研究结果可为决策者制定切实可行的区域可持续发展政策提供科学依据。

关键词：景观格局；生态系统服务；稀缺性；最小累积阻力模型；生态安全格局

研究类型：应用研究

The rapid advancement of urbanization has increased the degree of human intervention in natural ecosystems, thereby affecting the service functions of ecosystems to a certain extent and posing a certain threat to the healthy development of ecosystems. To achieve sustainable development of ecosystem services, it is necessary to increase the protection of ecosystems. The ecological security pattern focuses on the connection between ecological processes and functions. Identifying and optimizing the ecological security pattern is an effective measure to maintain the normal functions of the ecosystem and ensure regional sustainable development. This article takes Shaanxi Province as the research object, evaluates the ecosystem services from 2000 to 2020 based on multi-source remote sensing data and socio-economic data, and constructs an ecological security pattern. This article first analyzes the changes in Ecosystem Service Value (ESV) caused by land use changes, Ecosystem Services Scarcity Value (ESSV) while considering the impact of supply and demand, and analyzes the spatiotemporal evolution characteristics of ecosystem service value. Five single ecosystem service function indicators are selected to evaluate the spatiotemporal changes in ecosystem service function in Shaanxi Province, Based on the evaluation of the value and function of ecosystem services, the minimum cumulative resistance model is used to analyze the regional ecological security pattern and propose optimization measures. The main conclusions of this article are as follows:

(1) Among the land use types in Shaanxi Province, the area of arable land, forest land, and grassland accounts for a relatively large proportion. In 2020, the total area of the three types of land use accounted for 96.50% of the entire area. The overall transfer of land use between 2000 and 2020 was characterized by the transfer of arable land to construction land and forest land. The type with the greatest dynamic change in land use from 2000 to 2020 was construction land, which was much larger than other land use types, reaching 3.32%. With the rapid advancement of urbanization, A total of 2967.13 km² of forest land in Shaanxi Province has

been converted into other land types. During the process of transferring farmland to other land types, the area of farmland to grassland has reached its maximum value of 2220.97 km². The land conversion is mainly distributed in Long County and Qianyang County of Baoji City in western Shaanxi Province, mainly due to the promotion of the project of returning farmland to forests.

(2) In the past 20 years, the landscape pattern in Shaanxi Province has undergone significant changes. Except for the decrease in the Interspersion Juxtaposition Index (IJI) and Shannon's Evenness Index (SHEI), other indices have all increased. The area and number of landscape patches have also increased, indicating an increase in fragmentation, mainly due to the rapid economic development of Shaanxi Province, which has led to the expansion of towns to the periphery and an increase in regional area, The Patch Richness Index (PRI) and Patch Richness Density (PRD) are showing an upward trend, indicating an increase in landscape richness and species diversity in Shaanxi Province in the past 20 years. This also indicates an increase in fragmentation, which is directly related to the rapid advancement of urbanization. The regional landscape is in a fragmented state and distributed in various parts of the study area. 2010-2020 is a period of rapid development in Shaanxi Province. The construction of artificial landscapes has changed animal migration channels to a certain extent and has had a certain impact on the ecosystem. The rationality of landscape distribution in Shaanxi Province needs to be improved, and the distribution of construction land within cities is relatively dense, such as Xi'an and Yulin. The surrounding areas of cities are surrounded by farmland and forest land, and the overall spatial distribution of landscape patterns is developing in an uneven direction. (3) The value of ecosystem services in Shaanxi Province shows an evolutionary trend of first increasing, then decreasing, and then increasing. It showed an increasing trend from 2000 to 2010, a decreasing trend from 2010 to 2015, and an increasing trend from 2015 to 2020. Between 2015 and 2020, the value of ecosystem services in Shaanxi Province increased by a total of 3.00 × 10⁹ yuan. In 2020, the area of high value ecosystem service areas accounted for 29.77% of the total area of the research area, and the overall ecosystem service function of the region was at a high level. During the period from 2000 to 2020, ESV high value areas were distributed in the northwest of Yulin City, around the Han River Basin, and in the northern part of Tongchuan City in northern Shaanxi Province. ESV low value areas were mainly distributed in densely populated urban centers and rural residential areas, such as the center of Xi'an City Yulin City Center, etc. The patches with suboptimal service functions are mainly grassland, mainly distributed between suburbs and rural areas; Low value service areas are mainly located in areas with high population density and abundant building facilities. During the study period,

the overall ecosystem service function of Shaanxi Province has weakened, with a spatial distribution pattern of high in the south and low in the north. The high value areas of ecosystem service function in the study area are mostly distributed in the areas covered by forest land and surrounding water areas. The ecosystem service function in areas such as the northern part of Xi'an City and the southern part of Tongchuan City is at a relatively low level. The main reason is that the economic development speed in the northern part of the study area is higher than that in the southern part. The urbanization development in the northern part is faster, the population density is higher, and the distribution of construction land is more dense. However, there is more arable land and forest land in the southern part of Shaanxi Province. It can be seen that the level of ecosystem service function is negatively correlated with the level of urbanization to a certain extent, and the level of urbanization indirectly affects the ecosystem service function.

(4) In the ecological source areas of Shaanxi Province, the area of forest land, arable land, and grassland is relatively large, especially in the southwest and northeast regions of the research area. High resistance areas are mainly distributed around urban construction land, and the ecological security level in this area shows a low trend. During the study period, the area with low ecological security level has decreased. At all levels of zoning, the proportion of forest land area has always been at the highest value. From a spatial perspective, there are many ecological corridors and nodes located in the north and south of the research area. From 2000 to 2020, the area of medium level ecological security areas in Shaanxi Province ranked second, while the area of low level ecological security areas accounted for a relatively large proportion. However, with the passage of time, the area continued to decrease, indicating that the overall level of ecological security in Shaanxi Province has improved.

Based on the above research, it is suggested that when formulating sustainable development policies, more attention should be paid to land use types with high potential for ecosystem services, ecological restoration projects should continue, graded management should be implemented for source areas, the quality of ecosystem services should be improved from the source, regional management measures with different security levels should be coordinated, and regional cooperation across administrative boundaries should be strengthened. The research findings of this article can provide scientific basis for decision-makers to formulate practical and feasible regional sustainable development policies.

Key words:  landscape pattern; Ecosystem services; Scarcity; Minimum cumulative resistance model; Ecological security pattern

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