Dynamic simulation of land use and its response to the ecosystem service value in Puding county from 1973 to 2030
-
摘要: 揭示并预测岩溶山区在不同情景下土地利用变化对生态系统服务价值（ESV）的影响，对于维护区域生态安全、提升ESV以及制定生态保护与修复政策至关重要。文章以西南典型岩溶山区——贵州省普定县为研究对象，基于1973年、1989年、2003年、2010年和2020年5期土地利用数据，采用当量因子法评估各历史时期的ESV，并运用PLUS模型模拟2030年自然演变、生态保护和经济发展3种情景下的土地利用与ESV变化情况。结果表明：（1）过去50年间，普定县耕地面积减少25.08%，林地和建设用地面积显著增加；ESV经历了“先降后升”的过程，1989年降至最低（22.38亿元）；（2）2030年，3种情景下耕地、草地和未利用地面积均有所下降，建设用地面积在中部地区呈现“点—面”式扩张；（3）3种情景下的ESV总量分别高出2020年1.29亿元、2.66亿元和0.88亿元，其中生态保护情景下最高（37.75亿元），经济发展情景下最低（35.97亿元）；（4）ESV在空间分布上呈现“东、西部高，中部低”的格局，且各用地类型ESV均通过敏感性检验，结果具有较高的可信度。Abstract:
Puding county is located in the west-central part of Guizhou Province, covering a total area of 1,091 km². It experiences a humid subtropical monsoon climate, characterized by an average annual precipitation of 1,378.2 mm and an average annual temperature of 15.1 ℃. As of 2021, Puding county had a resident population of 376,300, including an urban population of 144,900, resulting in an urbanization rate of 38.51%. The county’s annual Gross Domestic Product (GDP) was 15.463 billion yuan, with the value added of the primary industry contributing 2.808 billion yuan, reflecting a year-on-year increase of 8.2%. The value added of the secondary industry was 4.785 billion yuan, a year-on-year increase of 10.06%, while the value added of the tertiary industry contributed 7.870 billion yuan, up 11.10%. This region is characterized by the typical development of karst geomorphology, and it frequently faces ecological challenges such as soil erosion and rocky desertification. Therefore, uncovering and predicting the impacts of land use change on Ecosystem Service Value (ESV) in karst mountainous areas under different scenarios is of great significance for maintaining regional ecological security, enhancing the value of ecosystem services, and formulating ecological protection and restoration policies. In order to deeply analyze the land use patterns and their response to ecosystem service value over an extended time series in Puding county, research and discussion were carried out across the three temporal dimensions: past, present, and future. This study aims to provide a scientific foundation and valuable insights for the sustainable development of ecosystems in the study area. Based on five periods of land use data from 1973, 1989, 2003, 2010 and 2020, the equivalent factor method, which incorporates localized adjustments of food prices, was used to assess the ESV for each historical period. Additionally, the PLUS model was applied to simulate land use and ESV changes projected for 2030 under three scenarios, natural evolution, ecological protection, and economic development. The results indicate as follows. (1) The area of cultivated land in Puding county decreased sharply from 1973 to 2020, with a total reduction of 25.08% over the last 50 years. In contrast, the areas of forest land and construction land increased annually, with increases of 6,338.56 hm2 and 9,408.00 hm2, respectively. (2) The ESV of the study area from 1973 to 2020 was recorded at 3.100 billion yuan, 2.238 billion yuan, 2.598 billion yuan, 3.277 billion yuan, and 3.510 billion yuan, respectively, exhibiting a general fluctuating upward trend. Regarding the ESV of various land types, the ESVs of forest land, grassland, and watershed all showed annual increases from 1989 to 2020, serving as main contributors to the overall increase in ESV. Specifically, in terms of the value of individual ecosystem service functions, hydrological regulation and climate regulation services made the most significant contribution to ESV, with the combined total of these two services accounting for 47.97% of the total ESV. (3) In the natural evolution scenario, the ecological protection scenario, and the economic development scenario projected for 2030, the areas of cultivated land, grassland, and unused land in Puding county are all expected to decline, mainly converted into forested land and construction land. Notably, the area of cultivated land is projected to experience the greatest loss under the ecological protection scenario, amounting to 5,196.42 hm2. The spatial distribution across the three simulation scenarios shows that the area of construction land is point-surface in the central part of the study area. (4) The ESVs for the natural evolution scenario, ecological protection scenario, and economic development scenario are projected to be 3.638 billion yuan, 3.778 billion yuan, and 3.597 billion yuan, respectively, all of which exceed the ESVs recorded for the study area in 2020. From a spatial distribution perspective, the ESVs for Puding county as a whole present the characteristics of being higher in the east and west and lower in the center. Furthermore, the ESV of each land use type has passed the sensitivity test, indicating strong credibility in the results. -
图 2 普定县土地利用时空格局分布
Figure 2. Spatial and temporal pattern distribution of land use in Puding county
图 3 普定县生态系统单一服务功能价值变化
Figure 3. Change of single service function value of ecosystem in Puding county
图 4 不同情境下普定县土地利用变化模拟情况
注：图中1、2、3、4分别代表局部区域放大效果图的序号。
Figure 4. Simulation of land use changes in Puding County under different scenarios
图 5 2030年3个模拟情景下ESV相对于2020年的变化率
a.粮食生产 b.原料生产 c.水资源供给 d.气体调节 e.气候调节 f.净化环境 g.水文调节 h.土壤保持 i.维持养分循环 j.生物多样性 k.美学景观
Figure 5. Rates of changes in ESV of 2030 compared with those in 2020 under three simulation scenarios
图 6 2030年不同情境下普定县ESV空间分布
Figure 6. Spatial distribution of ESV in Puding County under different scenarios in 2030
表 1 主要数据信息
Table 1. Main data information
一级指标 二级指标 三级指标 数据来源 自然环境 地形因子 高程 地理空间数据云（ https://www.gscloud.cn/ ）坡度 坡向 土壤类型 中国科学院资源环境科学与数据中心（ https://www.resdc.cn/ ）气候因子 年均降水量 中国气象站（ https://www.cma.gov.cn/ ）年均气温 植被因子 归一化指数 地理遥感生态网（ http://www.gisrs.cn/index.html ）社会经济 人口经济 人口数量 中国科学院资源环境科学与数据中心（ https://www.resdc.cn/ ）GDP 夜间灯光 到居民点距离 国家基础地理信息中心（ https://www.webmap.cn/ ）到政府所在地距离 OpenSteeetMap（ https://www.openstreetmap.org/ ）到县中心距离 到铁路距离 到二级道路距离 到三级道路距离 到四级道路距离 土地利用 土地利用强度 马里兰大学（ http://landcover.org/aboutUs/ ）、
地理空间数据云(http://wwwgscloud.cn/ )粮食数据 粮食产量、粮食价格 《安顺市统计年鉴》 ( http://www.anshun.gov.cn/ )、
《全国农产品成本收益资料汇编》(https://www.yearbookchina.com/ )
下载: 导出CSV
表 2 土地利用转移概率矩阵
Table 2. Probability matrix of land use transfer
土地利用情景 土地利用类型 耕地 林地 草地 水域 建设用地 未利用地 自然演变 耕地 0.60 0.27 0.00 0.01 0.12 0.00 林地 0.12 0.80 0.04 0.01 0.03 0.00 草地 0.30 0.51 0.14 0.01 0.04 0.00 水域 0.00 0.00 0.00 0.97 0.02 0.00 建设用地 0.37 0.04 0.00 0.00 0.58 0.00 未利用地 0.10 0.66 0.00 0.10 0.03 0.12 生态保护 耕地 0.57 0.34 0.00 0.00 0.08 0.00 林地 0.12 0.82 0.04 0.01 0.02 0.00 草地 0.26 0.59 0.12 0.01 0.02 0.00 水域 0.00 0.00 0.00 0.97 0.02 0.00 建设用地 0.37 0.04 0.00 0.00 0.58 0.00 未利用地 0.10 0.66 0.00 0.10 0.03 0.12 经济发展 耕地 0.59 0.27 0.00 0.00 0.14 0.00 林地 0.12 0.80 0.04 0.01 0.04 0.00 草地 0.30 0.51 0.13 0.01 0.05 0.00 水域 0.00 0.00 0.00 0.97 0.02 0.00 建设用地 0.38 0.03 0.00 0.00 0.59 0.00 未利用地 0.10 0.65 0.00 0.10 0.03 0.12
下载: 导出CSV
表 3 3种模拟情景的领域权重
Table 3. Domain weights for the three simulation scenarios
情景设置 耕地 林地 草地 水域 建设用地 未利用地 自然演变 0.6 0.4 0.2 0.2 0.7 0.1 生态保护 0.2 1.0 0.9 0.6 0.4 0.1 经济发展 0.7 0.4 0.3 0.2 1.0 0.1
下载: 导出CSV
表 4 普定县各土地利用类型单位面积生态价值当量表
Table 4. Ecological value equivalent per unit area of land use types in Puding county
一级类型 二级类型 耕地 林地 草地 水域 建设用地 未利用地 供给服务 粮食生产 0.85 0.19 0.38 0.80 0.00 0.00 原料生产 0.40 0.43 0.56 0.23 0.00 0.00 水资源供给 0.02 0.22 0.31 8.29 0.00 0.00 调节服务 气体调节 0.67 1.41 1.97 0.77 0.00 0.02 气候调节 0.36 4.23 5.21 2.29 0.00 0.00 净化环境 0.10 1.28 1.72 5.55 0.00 0.10 水文调节 0.27 3.35 3.82 102.24 0.00 0.03 支持服务 土壤保持 1.03 1.72 2.40 0.93 0.00 0.02 维持养分循环 0.12 0.13 0.18 0.07 0.00 0.00 生物多样性 0.13 1.57 2.18 2.55 0.00 0.02 文化服务 美学景观 0.06 0.69 0.96 1.89 0.00 0.01
下载: 导出CSV
表 5 普定县不同土地利用类型ESV系数/元·hm−2
Table 5. ESV coefficients for different land use types in Puding county /yuan·hm−2
一级类型 二级类型 耕地 林地 草地 水域 建设用地 未利用地 供给服务 粮食生产 2216.04 495.35 990.70 2085.68 0.00 0.00 原料生产 1042.84 1121.05 1459.98 599.63 0.00 0.00 水资源供给 52.14 573.56 808.20 21612.86 0.00 0.00 调节服务 气体调节 1746.76 3676.01 5135.99 2007.47 0.00 52.14 气候调节 938.56 11028.03 13582.99 5970.26 0.00 0.00 净化环境 260.71 3337.09 4484.21 14469.41 0.00 260.71 水文调节 703.92 8733.79 9959.12 266549.90 0.00 78.21 支持服务 土壤保持 2685.31 4484.21 6257.04 2424.60 0.00 52.14 维持养分循环 312.85 338.92 469.28 182.50 0.00 0.00 生物多样性 338.92 4093.15 5683.48 6648.11 0.00 52.14 文化服务 美学景观 156.43 1798.90 2502.82 4927.42 0.00 26.07 总计 10454.47 39680.06 51333.80 327477.83 0.00 521.42
下载: 导出CSV
表 6 普定县各类用地面积及占比/hm2
Table 6. Area and proportion of various land types in Puding county/ hm2
地类 耕地 林地 草地 水域 建设用地 未利用地 1973年 面积/hm2 48527.36 50608.64 7255.04 645.12 140.80 903.68 占比/% 44.90 46.82 6.71 0.60 0.13 0.84 1989年 面积/hm2 75681.28 22105.60 6179.84 765.44 384.00 3351.04 占比/% 69.77 20.38 5.70 0.71 0.35 3.09 2003年 面积/hm2 58378.24 26677.76 6853.12 1758.72 2060.80 2012.16 占比/% 59.73 27.29 7.01 1.80 2.11 2.06 2010年 面积/hm2 42621.44 49730.56 8209.92 1328.64 4282.88 2229.76 占比/% 39.32 45.88 7.57 1.22 3.95 2.06 2020年 面积/hm2 36354.56 56947.20 3200.00 2152.96 9548.80 302.08 占比/% 33.51 52.48 2.95 1.98 8.80 0.28 1973—2020年面积变化量/hm2 − 12172.80 6338.56 − 4055.05 1507.84 9408.00 −601.60 1973—2020年面积变化率/% −25.08 12.52 −55.89 233.73 6681.82 −66.57
下载: 导出CSV
表 7
普定县各类用地ESV量变化/亿元 Table 7. Changes in the ESV for various land use types in Puding county /108 yuan
土地利用类型 耕地 林地 草地 水域 建设用地 未利用地 总计 1973年 ESV 5.07 20.08 3.72 2.11 0.00 0.0047 31.00 比例% 16.37 64.79 12.02 6.82 0.00 0.02 100.00 1989年 ESV 7.91 8.77 3.17 2.51 0.00 0.0175 22.38 比例% 35.35 39.19 14.17 11.20 0.00 0.08 100.00 2003年 ESV 6.10 10.59 3.52 5.76 0.00 0.0105 25.98 比例% 23.49 40.75 13.54 22.17 0.00 0.04 100.00 2010年 ESV 4.46 19.73 4.21 4.35 0.00 0.0116 32.77 比例% 13.60 60.22 12.86 13.28 0.00 0.04 100.00 2020年 ESV 3.80 22.60 1.64 7.05 0.00 0.0016 35.09 比例% 10.83 64.39 4.68 20.09 0.00 0.00 100.00 1973—2020年ESV变化量 −1.27 2.52 −2.08 4.94 0.00 − 0.0031 4.09 1973—2020年ESV变化率/% −25.08 12.52 −55.89 233.73 0.00 −66.57 98.71
下载: 导出CSV
表 8 不同情境下各土地利用类型面积变化情况
Table 8. Changes in area of each land-use type under different scenarios
用地类型 不同情景用地类型变化/hm2 自然演变情景 生态保护情景 经济发展情景 耕地 − 3313.98 − 5196.42 − 3899.61 林地 1225.26 5453.55 537.66 草地 −319.14 −414.81 −341.64 水域 488.16 468.81 467.64 建设用地 2153.07 −75.69 3470.58 未利用地 −233.46 −235.44 −234.63
下载: 导出CSV
表 9 ESV及敏感性指数（经价值系数修正）
Table 9. ESV and sensitivity indices (corrected for value coefficients)
土地类型 价值系数 ESV/亿元 CS 2020年 自然演变 生态保护 经济发展 2020年 自然演变 生态保护 经济发展 耕地 VC+50% 36.7223 38.1223 39.3924 37.6789 0.1101 0.0958 0.0871 0.0952 VC-50% 32.8911 34.6377 36.1046 34.2554 − − − − 林地 VC+50% 45.9760 47.7924 49.9998 47.2432 0.6418 0.6274 0.6491 0.6270 VC-50% 23.6374 24.9676 25.4972 24.6912 − − − − 草地 VC+50% 35.6199 37.1113 38.4552 36.6927 0.0467 0.0402 0.0374 0.0403 VC-50% 33.9935 35.6487 37.0418 35.2417 水域 VC+50% 38.3112 40.6838 42.0206 40.2374 0.2014 0.2366 0.2263 0.2374 VC-50% 31.3022 32.0762 33.4764 31.6970 − − − − 建设用地 VC+50% 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 VC-50% 0.0000 0.0000 0.0000 0.0000 未利用地 VC+50% 34.8075 36.3802 37.7487 35.9673 4.44515E-05 9.06824E-06 8.46599E-06 9.0027E-06 VC-50% 34.8059 36.3798 37.7483 35.9670 − − − −
下载: 导出CSV
-
[1] 刘志勇, 方朝阳, 蔡振饶, 李慧中, 夏阳, 陈浩. 多情景下鄱阳湖滨湖区生态系统服务价值预测[J]. 环境科学与技术, 2022, 45(7): 218-227.LIU Zhiyong, FANG Chaoyang, CAI Zhenrao, LI Huizhong, XIA Yang, CHEN Hao. Multi-scenario simulation and prediction of ESV for Poyang Lake lakeside area[J]. Environmental Science & Technology, 2022, 45(7): 218-227. [2] 陈金珂, 蒲俊兵, 李建鸿, 张陶. 基于土地利用情景模拟的喀斯特关键带生态系统服务权衡与协同分析: 以蒙自喀斯特断陷盆地为例[J]. 中国岩溶, 2023, 42(1): 94-108.CHEN Jinke, PU Junbing, LI Jianhong, ZHANG Tao. Trade-off and synergy of ecosystem services of a karst critical zone based on land use scenario simulation: Take Mengzi karst graben basin as a study case[J]. Carsologica Sinica, 2023, 42(1): 94-108. [3] 欧阳晓, 贺清云, 朱翔. 多情景下模拟城市群土地利用变化对生态系统服务价值的影响: 以长株潭城市群为例[J]. 经济地理, 2020, 40(1): 93-102.OU Yangxiao, HE Qingyun, ZHU Xiang. The influence of simulated land use change in urban agglomeration on ecosystem service value under multiple scenarios: Taking Changsha-Zhuzhou-Xiangtan urban agglomeration as an example[J]. Economic Geography, 2020, 40(1): 93-102. [4] 祁育汀, 张平, 刘雷, 马雪楠, 王欢, 赵娟. 关中平原城市群土地利用结构多情景优化和生态系统服务价值预测[J]. 应用生态学报, 2023, 34(9): 2507-2517.QI Yuting, ZHANG Ping, LIU Lei, MA Xuenan, WANG Huan, ZHAO Juan. Multi-scenario optimization of land use structure and prediction of ecosystem service value in Guanzhong Plain urban agglomeration[J]. Journal of Applied Ecology, 2023, 34(9): 2507-2517. [5] Costanza R, D' Arge R, Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O' Neill R V, Paruelo J, Raskin R G, Sutton P, Belt M V D. The value of the world′s ecosystem services and natural capital[J]. Nature, 1997, 387: 253-260. doi: 10.1038/387253a0 [6] 谢高地, 甄霖, 鲁春霞, 肖玉, 陈操. 一个基于专家知识的生态系统服务价值化方法[J]. 自然资源学报, 2008, 23(5): 911-919.XIE Gaodi, ZHEN Lin, LU Chunxia, XIAO Yu, CHEN Cao. Expert knowledge based valuation method of Ecosystem Services in China[J]. Journal of Natural Resources, 2008, 23(5): 911-919. [7] Liu F L, Yang L, Wang S. Spatial and Temporal Evolution and Correlation Analysis of Landscape Ecological Risks and Ecosystem Service Values in the Jinsha River Basin[J]. Journal of Resources and Ecology, 2023, 14: 914-927. [8] 梁锦桃, 邓艳, 曹建华, 靳振江, 李旭尧. 典型断陷盆地流域生态系统服务价值时空差异研究[J]. 中国岩溶, 2021, 40(3): 476-486.LIANG Jintao, DENG Yan, CAO Jianhua, JIN Zhenjiang, LI Xurao. Temporal and spatial differentiation of the ecosystem service value in typical fault-depression basins[J]. Carsologica Sinica, 2021, 40(3): 476-486. [9] 周道媛, 王娟, 周凤娟. 基于PLUS模型多情景分析的土地利用变化及生态系统服务价值评估: 以福州市为例[J]. 甘肃农业大学学报, 2023, 58(3): 198-209.ZHOU Daoyuan, WANG Juan, ZHOU Fengjuan. Assessment of land use change and ecosystem service value based on multi-scenario analysis of PLUS model: Take Fuzhou City as an example[J]. Journal of Gansu Agricultural University, 2023, 58(3): 198-209. [10] 范利瑶, 文倩, 李青松, 汪潇, 韩婧. 沙颍河流域河南段生态系统服务价值及影响因素评估[J]. 人民黄河, 2023, 45(3): 90-96.FAN Liyao, WEN Qian, LI Qingsong, WANG Xiao, HAN Jing. Evaluation of ecosystem service value and influencing factors in Henan section of Shaying River Basin[J]. Yellow River, 2023, 45(3): 90-96. [11] 荔琢, 蒋卫国, 王文杰, 吕金霞, 邓越. 基于生态系统服务价值的京津冀城市群湿地主导服务功能研究[J]. 自然资源学报, 2019, 34(8): 1654-1665. doi: 10.31497/zrzyxb.20190807LI Zhuo, JIANG Weiguo, WANG Wenjie, LYU Jinxia, DENG Yue. Study on the leading service function of wetland in Beijing-Tianjin-Hebei Urban Agglomeration based on ecosystem service value[J]. Journal of Natural Resources, 2019, 34(8): 1654-1665. doi: 10.31497/zrzyxb.20190807 [12] 胡玉雪, 周旭, 袁稳玲, 张文彬, 敖杨, 王小华. 贵阳市景观格局对生态系统服务价值的影响[J]. 贵州师范大学学报(自然科学版), 2023, 41(5): 34-43.HU Yuxue, ZHOU Xu, YUAN Wenling, ZHANG Wenbin, AO Yang, WANG Xiaohua. The influence of landscape pattern on the value of ecosystem service in Guiyang city[J]. Journal of Guizhou Normal University (Natural Science Edition), 2023, 41(5): 34-43. [13] Grafius D R, Corstanje R, Harris J A. Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis[J]. Landscape Ecology, 2018, 33: 557-573. doi: 10.1007/s10980-018-0618-z [14] Liang X, Guan Q F, Clarke K C, LIU S S, Wang B Y, Yao Y. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: A case study in Wuhan, China[J]. Computers, Environment and Urban Systems, 2021, 85: 101569.1-101569.14. [15] Egoh B N, Reyers B D, Rouget M, Richardsob D M. Identifying priority areas for ecosystem service management in South African grasslands[J]. Journal of Environmental Management, 2011, 92: 1642-1650. [16] 李何英, 何文, 王金叶, 杨帅琦, 姚月锋. 基于PLSR-FLUS-MarKov模型的生态系统服务价值多情景预测: 以漓江流域为例[J]. 水生态学杂志, 2025, 46(1): 203-212.LI Heying, HE Wen, WANG Jinye, YANG Shuaiqi, YAO Yuefeng. Multi-scenario prediction of ecosystem service value based on the PLSR-FLUS-MarKov model: A case study of Lijiang River basin[J]. Journal of Hydroecology, 2025, 46(1): 203-212. [17] 曲艺, 丁建丽, 包青岭, 王颖慧, 许梦珠. 多情景模拟下的新疆生态系统服务价值评估[J]. 环境科学与技术, 2023, 46(4): 195-204.QU Yi, DING Jianli, BAO Qingling, WANG Yinghui, XU Mengzhu. Evaluation of the value of Xinjiang ecosystem services under multi-scenario simulation[J]. Environmental Science and Technology, 2023, 46(4): 195-204. [18] 卢泓杏, 赵宇鸾. 基于生态安全格局的岩溶山地国土空间生态修复关键区识别: 以贵州省关岭县为例[J]. 中国岩溶, 2024, 43(2): 349-363.LU Hongxing, ZHAO Yuluan. Identification of key areas for the ecological restoration of karst mountainous territorial space based on the construction of ecological security pattern: A case study of Guanling, Guizhou Province[J]. Carsologica Sinica, 2024, 43(2): 349-363. [19] 李月, 罗红芬. 黔中喀斯特地区典型县域碳储量时空演变及多情景模拟预测: 以普定县为例[J]. 环境科学, 2024, 45(2): 961-973.LI Yue, LUO Hongfen. Spatio-temporal evolution of carbon reserves and multi-scenario simulation prediction in typical counties in central Guizhou: Take Puding county as an example[J]. Environmental Science, 2024, 45(2): 961-973. [20] 谢向东, 林孝松, 王莹, 涂荣誉, 张吉祥. 基于PLUS模型的重庆市南川区土地利用多情景模拟[J]. 长江科学院院报, 2023, 40(6): 86-92,113.XIE Xiangdong, LIN Xiaosong, WANG Ying, TU Rongyu, ZHANG Jixiang. Multi-scenario simulation of land use in Nanchuan District, Chongqing based on PLUS model[J]. News of Yangtze River Academy of Sciences, 2023, 40(6): 86-92,113. [21] Gounarids D, Chorianopoupos I, Symeonakis E, Koukoulas S. A Random Forest-Cellular Automata modelling approach to explore future land use/cover change in Attica (Greece), under different socio-economic realities and scales[J]. Science of The Total Environment, 2017, 21: 769-776. [22] 杨朔, 苏昊, 赵国平. 基于PLUS模型的城市生态系统服务价值多情景模拟: 以汉中市为例[J]. 干旱区资源与环境, 2022, 36(10): 86-95.YANG Shuo, SU Hao, ZHAO Guoping. Multi-scenario simulation of urban ecosystem service value based on PLUS model: Taking Hanzhong city as an example[J]. Resources and Environment in arid Zone, 2022, 36(10): 86-95. [23] 喇蕗梦, 勾蒙蒙, 李乐, 王娜, 胡建文, 刘常富, 肖文发. 三峡库区生态系统服务权衡时空动态与情景模拟: 以秭归县为例[J]. 生态与农村环境学报, 2021, 37(11): 1368-1377.LA Lumeng, GOU Mengmeng, LI Le, WANG Na, HU Jianwen, LIU Changfu, XIAO Wenfa. Spatiotemporal dynamics and scenarios analysis on trade-offs between ecosystem service in Three Gorges reservoir area: A case study of Zigui county[J]. Journal of Ecology and Rural Environment, 2021, 37(11): 1368-1377. [24] 谢高地, 张彩霞, 张昌顺, 肖玉, 鲁春霞. 中国生态系统服务的价值[J]. 资源科学, 2015, 37(9): 1740-1746.XIE Gaodi, ZHANG Caixia, ZHANG Changshun, XIAO Yu, LU Chunxia. Value of ecosystem services in China[J]. Resource Science, 2015, 37(9): 1740-1746. [25] 隋露, 蒲春玲, 刘志有, 柏鹏飞, 刘涛. 基于PLUS模型的乌鲁木齐市生态服务价值权衡协同探究[J]. 干旱区地理, 2023, 46(1): 159-168.SUI Lu, PU Chunling, LIU Zhiyou, BAI Pengfei, LIU Tao. Collaborative exploration of ecological service value trade-off in Urumqi city based on PLUS model[J]. Geography of Arid Region, 2023, 46(1): 159-168. [26] 谢高地, 鲁春霞, 冷允法, 郑度, 李双成. 青藏高原生态资产的价值评估[J]. 自然资源学报, 2003, 18(2): 189-196.XIE Gaodi, LU Chunxia, LENG Yunfa, ZHENG Du, LI Shuangcheng. Ecological assets valuation of the Tibetan Plateau[J]. Journal of Natural Resources, 2003, 18(2): 189-196. [27] 高星, 杨刘婉青, 李晨曦, 宋昭颖, 王杰. 模拟多情景下白洋淀流域土地利用变化及生态系统服务价值的空间响应[J]. 生态学报, 2021, 41(20): 7974-7988.GAO Xing, YANG Liuwanqing, LI Chenxi, SONG Zhaoying, WANG Jie. Spatial response of land use change and ecosystem service value in Baiyangdian Basin under multiple scenarios[J]. Journal of Ecology, 2021, 41(20): 7974-7988. [28] 杨应增, 周来丰, 夏伟, 王敏姿. 基于土地利用变化的赤水河流域生态系统服务价值变化分析[J]. 环境工程技术学报, 2023, 13(2): 694-703.YANG Yingzeng, ZHOU Laifeng, XIA Wei, WANG Minzi. Analysis of the value change of ecosystem services in the Chishui River Basin based on land use change[J]. Journal of Environmental Engineering Technology, 2023, 13(2): 694-703. [29] 李安林, 周艳, 唐丽毅, 牛乐德, 潘媚. 怒江州土地利用模拟及生态系统服务价值评估: 基于PLUS模型的多情景分析[J]. 中国农业资源与区划, 2023, 44(1): 140-149.LI Anlin, ZHOU Yan, TANG Lliyi, NIU Lede, PAN Mei. Land use simulation and ecosystem service value assessment in Nujiang Prefecture: A multi-scenario analysis based on the PLUS model[J]. Agricultural Resources and Regionalization, 2023, 44(1): 140-149. [30] 赖元长, 李贤伟, 冯帅, 王鹏, 唐骄萍, 赵安玖, 赖家明. 退耕还林工程对四川盆周低山丘陵区生态系统服务价值的影响: 以洪雅县为例[J]. 自然资源学报, 2011, 26(5): 755-768.LAI Yuanchang, LI Xianwei, FENG Shuai, WANG Peng, TANG Jiaoping, ZHAO Anjiu, LAI Jiaming. The impact of the project of returning farmland to forest on the ecosystem service value in the hilly area of Sichuan Basin: Take Hongya County as an example[J]. Journal of Natural Resources, 2011, 26(5): 755-768. [31] 金声甜, 肖文海, 杨胜苏, 赵丹丹. 长江经济带土地利用变化及其生态系统响应[J]. 经济地理, 2020, 40(7): 166-173.JIN Shengtian, XIAO Wenhai, YANG Shengsu, ZHAO Dandan. Land use change and its ecosystem response in the Yangtze River Economic Belt[J]. Economic Geography, 2020, 40(7): 166-173. [32] 胡玉雪, 周旭, 敖杨, 袁稳玲, 张文彬, 王小华. 贵州省生态系统服务价值演变及影响因素分析[J]. 测绘科学, 2023, 48(9): 120-130.HU Yuxue, ZHOU Xu, AO Yang, YUAN Wenling, ZHANG Wenbin, WANG Xiaohua. Analysis of the evolution and influencing factors of ecosystem service value in Guizhou Province[J]. Science of Surveying and Mapping, 2023, 48(9): 120-130. [33] 黄秀雨, 严志强, 胡宝清, 严钦强, 彭定新, 盛凯. 喀斯特地区土地利用及生态系统服务价值空间自相关分析: 以广西百色市为例[J]. 湖北农业科学, 2023, 62(8): 44-53.HUANG Xiuyu, YAN Zhiqiang, HU Baoqing, YAN Qinqiang, PENG Dingxin, SHENG Kai. Spatial autocorrelation analysis of land use and ecosystem service value in karst area: A case study of Baise City, Guangxi[J]. Hubei Agricultural Sciences, 2023, 62(8): 44-53. [34] 郜红娟, 罗绪强, 韩会庆, 王后阵. 贵州山区公路沿线生态系统服务价值变化[J]. 南京林业大学学报(自然科学版), 2016, 40(1): 135-141.GAO Hongjuan, LUO Xuqiang, HAN Huiqing, WANG Houzhen. Changes in ecosystem service value along highways in Guizhou mountainous areas[J]. Journal of Nanjing Forestry University ( Natural Science Edition ), 2016, 40(1): 135-141. [35] Zhang F, Ayinuer Y S J, JingY Q. Assessing and predicting changes of the ecosystem service values based on land use/cover change in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China[J]. Science of the Total Environment, 2019, 656: 1133-1144. doi: 10.1016/j.scitotenv.2018.11.444 [36] 李金雷, 刘欢, 哈斯娜, 陆学岩, 刘旭隆, 王立新, 温璐. 岱海流域土地利用动态模拟及生态系统服务价值测算[J]. 生态学杂志, 2022, 41(2): 343-350.LI Jinlei, LIU Huan, HA Sina, LU Xueyan, LIU Xulong, WANG Lixin, WEN Lu. Dynamic simulation of land use and calculation of ecosystem service value in Daihai River Basin[J]. Journal of Ecology, 2022, 41(2): 343-350. [37] 秦罗义, 白晓永, 王世杰, 周德全, 陈伟燕, 罗光杰, 张斯屿, 崔泽银. 近40年来贵州高原典型区土地利用变化及驱动机制[J]. 山地学报, 2015, 33(5): 619-628.QIN Luoyi, BAI Xiaoyong, WANG Shijie, ZHOU Dequan, CHEN Weiyan, LUO Guangjie, ZHANG Siyu, CUI Zeyin. History of land use change and driving mechanism of typical Guizhou plateau region during 40 years[J]. Mountain Research, 2015, 33(5): 619-628. [38] 马欢, 冯朝阳, 宋婷, 计伟, 杨娇, 李付杰. 1990—2018年赤水河流域土地利用变化分析[J]. 环境工程技术学报, 2021, 11(3): 428-436.MA Huan, FENG Chaoyang, SONG Ting, JI Wei, YANG Jiao, LI Fujie. Study on the characteristics of land use change in Chishui River Basin from 1990 to 2018[J]. Journal of Environmental Engineering Technology, 2021, 11(3): 428-436. [39] 林栋, 马晖玲, 任正超, 李元恒. 基于LUCC的兰州城市生态系统服务价值动态分析[J]. 生态科学, 2016, 35(2): 134-142.LIN Dong, MA Huiling, REN Zhengchao, LI Yuanheng. Dynamic analysis of the service value of Lanzhou urban ecosystem based on LUCC[J]. Ecological Science, 2016, 35(2): 134-142. [40] 白元, 徐海量, 凌红波, 傅荩仪. 塔里木河干流区土地利用与生态系统服务价值的变化[J]. 中国沙漠, 2013, 33(6): 1912-1920.BA Yuan, XU Hailiang, LING Hongbo, FU Jinyi. Changes in land use and ecosystem service value in the mainstream of the Tarim River[J]. Journal of Desert Research, 2013, 33(6): 1912-1920. -
点击查看大图
图(6) / 表(9)
计量
- 文章访问数: 11
- HTML浏览量: 4
- PDF下载量: 2
- 被引次数: 0
