Please wait a minute...
 
Remote Sensing for Natural Resources    2025, Vol. 37 Issue (6) : 191-200     DOI: 10.6046/zrzyyg.2024321
|
Spatiotemporal evolution and trade-off/synergy analysis of ecosystem services in the Xi’an section of the Qinling Mountains
ZHANG Yiwen1(), LI Fengxia2(), ZHANG Rui1, FENG Xiaogang2, LI Meng2, HU Moqing2
1. School of Resources Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China
2. School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China
Download: PDF(6638 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks    
Abstract  

This study aims to investigate the spatiotemporal evolution and trade-off/synergy relationships of ecosystem services in the Xi'an section of the Qinling Mountains. To this end, it quantitatively assessed the spatiotemporal evolution patterns of four ecosystem services-water yield, soil conservation, carbon reserves, and food supply-from 2003 to 2023 based on the integrated valuation of ecosystem services and trade-offs (InVEST) model. By integrating Spearman's rank correlation coefficient and geographically weighted regression (GWR), this study identified and quantified trade-off/synergy relationships among ecosystem services. Finally, the impacts of changes in land use on ecosystem services were analyzed. The results showed that water yield and soil conservation generally showed a rapidly decreasing trend followed by a slow increase, while carbon reserves and food supply exhibited a slow decline. In addition, synergistic relationships were observed between water yield and soil conservation, between water yield and carbon reserves, and between carbon reserves and soil conservation. In contrast, trade-off relationships were identified between food supply and water production, soil conservation, and carbon reserves. In the study area, increases in forestland and grassland led to a diminution in water yield. The expansion of construction land and the loss of arable land resources directly triggered a reduction in carbon reserves, while an increase in forestland contributed to soil conservation. These findings can provide a scientific basis for the eco-environmental protection and sustainable development of the Qinling area.

Keywords land use change      ecosystem service      integrated valuation of ecosystem services and trade-offs (InVEST) model      tradeoff/synergy     
ZTFLH:  TP79  
Issue Date: 31 December 2025
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Yiwen ZHANG
Fengxia LI
Rui ZHANG
Xiaogang FENG
Meng LI
Moqing HU
Cite this article:   
Yiwen ZHANG,Fengxia LI,Rui ZHANG, et al. Spatiotemporal evolution and trade-off/synergy analysis of ecosystem services in the Xi’an section of the Qinling Mountains[J]. Remote Sensing for Natural Resources, 2025, 37(6): 191-200.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2024321     OR     https://www.gtzyyg.com/EN/Y2025/V37/I6/191
Fig.1  Schematic of the study area
Fig.2  Intensity map of land use change
强度类型 地类流向 判定条件 趋势描述
绝对强度 获取转入 绝对转入强度>平均绝对转入强度 倾向于从地类i获得转入,反之受到抑制
均匀转出 绝对转出强度>平均绝对转出强度 倾向于转出为地类j,反之受到抑制
相对强度 获取转入 相对转入强度>平均相对转入度 相对倾向于从地类i获得转入,反之受到抑制
均匀转出 相对转出强度>平均相对转入度 相对倾向于转出为地类j,反之受到抑制
Tab.1  Criteria for determining land use changes at different intensity types
类型 地上生物
量碳密度
地下生物
量碳密度
土壤碳密度 死亡有机
物碳密度
草地 39.99 97.99 113.17 0.50
耕地 52.68 91.42 122.80 0.70
建设用地 2.83 0.00 88.36 0.00
林地 48.03 131.29 116.34 2.00
水域 3.40 0.00 0.00 0.00
Tab.2  Carbon density data of different land use types (t/hm2)
Fig.3  Spatial distribution map of land use types
类型 2003年 2013年 2023年
面积/km2 占比/% 面积/km2 占比/% 面积/km2 占比/%
草地 138.85 1.77 25.26 0.32 31.75 0.40
耕地 2 556.74 32.60 1 929.38 24.60 1 977.13 25.21
建设用地 489.82 6.25 633.47 8.08 709.64 9.05
林地 4 638.90 59.14 5 226.24 66.63 5 105.56 65.10
水域 18.86 0.24 28.82 0.37 19.09 0.24
Tab.3  Area and proportion of land use types
年份 草地 耕地 建设用地 林地 水域 综合
2003—2013年 -8.18 -2.45 2.93 1.27 5.28 0.94
2013—2023年 2.57 -0.25 1.20 -0.23 -3.38 0.17
2003—2023年 -7.71 -2.27 4.49 1.01 -0.12 0.88
Tab.4  Dynamics degree of single land use and comprehensive land use (%)
2003年 2023年 转出
总计
草地 耕地 建设用地 林地 水域
草地 19.34 2.75 1.59 108.84 0.23 113.41
耕地 0.43 1 776.73 380.38 399.14 8.21 788.16
建设用地 0.38 114.69 308.59 56.06 3.39 174.52
林地 11.47 81.52 13.06 4 536.28 1.55 107.60
水域 0.03 3.41 5.81 3.60 5.69 12.85
转入总计 12.31 202.37 400.84 567.64 13.38 1 196.54
Tab.5  Land use transfer matrix (km2)
Fig.4  Land use intensity map
Fig.5  Spatiotemporal distribution and variation of water yield in the study area
Fig.6  Spatiotemporal distribution and variation of soil conservation in the study area
Fig.7  Spatiotemporal distribution and variation of carbon storage in the study area
Fig.8  Spatiotemporal distribution and variation of food supply in the study area
Fig.9  Comparative analysis of ecosystem service functions across land use types
Fig.10  Correlation between ecosystem in the study area from 2003 to 2023
Fig.11  Spatial patterns of ecosystem service trade-offs/synergies in the study area from 2003 to 2023
[1] 傅伯杰, 周国逸, 白永飞, 等. 中国主要陆地生态系统服务功能与生态安全[J]. 地球科学进展, 2009, 24(6):571-576.
doi: 10.11867/j.issn.1001-8166.2009.06.0571
[1] Fu B J, Zhou G Y, Bai Y F, et al. The main terrestrial ecosystem services and ecological security in China[J]. Advances in Earth Science, 24(6):571-576.
[2] 戴尔阜, 王晓莉, 朱建佳, 等. 生态系统服务权衡/协同研究进展与趋势展望[J]. 地球科学进展, 2015, 30(11):1250-1259.
doi: 10.11867/j.issn.1001-8166.2015.11.1250
[2] Dai E F, Wang X L, Zhu J J, et al. Progress and perspective on ecosystem services trade-offs[J]. Advances in Earth Science, 2015, 30(11):1250-1259.
doi: 10.11867/j.issn.1001-8166.2015.11.1250
[3] 王建庆. 东南沿海地区城镇土地利用效益评价研究——以浙江省百强县为例[D]. 宁波: 宁波大学, 2014.
[3] Wang J Q. Study on the evaluation of land use efficiency in the town of southeast coastal areas:In case of the top 100 counties in Zhejiang[D]. Ningbo: Ningbo University, 2014.
[4] Song W, Deng X Z. Land-use/land-cover change and ecosystem service provision in China[J]. Science of The Total Environment, 2017,576:705-719.
[5] Shifaw E, Sha J M, Li X M, et al. Ecosystem services dynamics and their influencing factors:Synergies/tradeoffs interactions and implications,the case of upper Blue Nile Basin,Ethiopia[J]. Science of The Total Environment, 2024,938:173524.
[6] Xia H, Yuan S F, Prishchepov A V. Spatial-temporal heterogeneity of ecosystem service interactions and their social-ecological drivers:Implications for spatial planning and management[J]. Resources,Conservation and Recycling, 2023,189:106767.
[7] Zhang J W, Wang M, Liu K, et al. Social-ecological system sustainability in China from the perspective of supply-demand balance for ecosystem services[J]. Journal of Cleaner Production, 2025,497:145039.
[8] 于媛, 韩玲, 李明玉, 等. 哈长城市群生态系统服务时空特征及其权衡/协同关系研究[J]. 水土保持研究, 2021, 28(2):293-300.
[8] Yu Y, Han L, Li M Y, et al. Study on the spatial-temporal characteristics of ecosystem services and tradeoffs/synergies in the Ha-Chang urban agglomeration[J]. Research of Soil and Water Conservation, 2021, 28(2):293-300.
[9] 龙文芹, 职露, 郭娅迪, 等. 西洞庭湖自然保护区2000—2020 年间碳储量时空演变及成因分析[J]. 自然资源遥感, 2024, 36(4):185-192.doi:10.6046/zrzyyg.2023265.
[9] Long W Q, Zhi L, Guo Y D, et al. Spatiotemporal evolution and origin of carbon stock in the West Dongting Lake National Nature Reserve over the last two decades[J]. Remote Sensing for Natural Resources, 2024, 36(4):185-192.doi:10.6046/zrzyyg.2023265.
[10] 崔璐. 秦岭陕西段生态系统服务评估及多情景预测研究[D]. 西安: 长安大学, 2023.
[10] Cui L. Ecosystem service assessment and multi-scenario prediction in the Shaanxi section of the Qinling Mountains[D]. Xi’an: Chang’an University, 2023.
[11] 丘海红, 胡宝清, 张泽. 基于土地利用变化的广西近20年生态系统服务价值研究[J]. 环境工程技术学报, 2022, 12(5):1455-1465.
[11] Qiu H H, Hu B Q, Zhang Z. Study on ecosystem service value of Guangxi in the past 20 years based on land use change[J]. Journal of Environmental Engineering Technology, 2022, 12(5):1455-1465.
[12] 李丹, 周嘉, 战大庆. 黑龙江省耕地时空变化及驱动因素分析[J]. 地理科学, 2021, 41(7):1266-1275.
doi: 10.13249/j.cnki.sgs.2021.07.017
[12] Li D, Zhou J, Zhan D Q. Spatial and temporal changes and driving factors of cultivated land in Heilongjiang Province[J]. Scientia Geographica Sinica, 2021, 41(7):1266-1275.
doi: 10.13249/j.cnki.sgs.2021.07.017
[13] 牛乐乐, 张必成, 贾天忠, 等. 青海省海西州土地利用变化强度分析与稳定性研究[J]. 水土保持学报, 2021, 35(2):152-159.
[13] Niu L L, Zhang B C, Jia T Z, et al. Analysis on intensity and stabi-lity of land use change in Haixi Mongolian and Tibetan Autonomous Prefecture of Qinghai Province[J]. Journal of Soil and Water Conservation, 2021, 35(2):152-159.
[14] 朱灵伟, 陈晨, 彭云飞, 等. 基于LUCC强度图谱的耕地时空演变模式研究[J]. 中国国土资源经济, 2024, 37(12):52-63.
[14] Zhu L W, Chen C, Peng Y F, et al. A study on spatiotemporal evolution patterns of cultivated land based on LUCC intensity chroma-togram[J]. Natural Resource Economics of China, 2024, 37(12):52-63.
[15] 李帅呈, 龚健, 杨建新, 等. 兰西城市群土地利用/覆被变化模式特征——基于强度分析框架[J]. 资源科学, 2023, 45(3):480-493.
doi: 10.18402/resci.2023.03.02
[15] Li S C, Gong J, Yang J X, et al. Characteristics of LUCC patterns of the Lanzhou-Xining urban agglomeration:Based on an intensity analysis framework[J]. Resources Science, 2023, 45(3):480-493.
doi: 10.18402/resci.2023.03.02
[16] 范亚宁, 刘康, 陈姗姗, 等. 秦岭北麓陆地生态系统水源涵养功能的空间格局[J]. 水土保持通报, 2017, 37(2):50-56.
[16] Fan Y N, Liu K, Chen S S, et al. Spatial pattern analysis on water conservative functionality of land ecosystem in northern slope of Qinling Mountains[J]. Bulletin of Soil and Water Conservation, 2017, 37(2):50-56.
[17] 周苹苹, 罗艺, 宋小燕, 等. 基于InVEST-PLUS模型的陕西省水源涵养量估算及预测[J]. 水土保持学报, 2024, 38(3):187-194.
[17] Zhou P P, Luo Y, Song X Y, et al. Estimation and prediction of water conservation capacity in Shaanxi Province based on the InVEST-PLUS model[J]. Journal of Soil and Water Conservation, 2024, 38(3):187-194.
[18] 翟睿洁, 赵文武, 贾立志. 基于RUSLE、InVEST 和USPED 的土壤侵蚀量估算对比研究——以陕北延河流域为例[J]. 农业现代化研究, 2020, 41(6):1059-1068.
[18] Zhai R J, Zhao W W, Jia L Z. A comparative study of soil erosion estimation based on RUSLE,InVEST and USPED models:A case study of Yanhe River Basin in Northern Shaanxi[J]. Research of Agricultural Modernization, 2020, 41(6):1059-1068.
[19] 李倩, 王成军, 冯涛, 等. 基于SD-PLUS耦合模型的陕西省土地利用变化及碳储量多情景预测[J]. 水土保持学报, 2024, 38(3):195-206,215.
[19] Li Q, Wang C J, Feng T, et al. Multi-scenario prediction of land use change and carbon storage in Shaanxi Province based on the SD-PLUS coupled model[J]. Journal of Soil and Water Conservation, 2024, 38(3):195-206,215.
[20] 赵文亮, 贺振, 贺俊平, 等. 基于MODIS-NDVI的河南省冬小麦产量遥感估测[J]. 地理研究, 2012, 31(12):2310-2320.
[20] Zhao W L, He Z, He J P, et al. Remote sensing estimation for winter wheat yield in Henan based on the MODIS-NDVI data[J]. Geographical Research, 2012, 31(12):2310-2320.
[21] 周凡, 周冬梅, 金银丽, 等. 疏勒河流域生态系统服务供需空间匹配特征[J]. 干旱区地理, 2023, 46(3):471-480.
doi: 10.12118/j.issn.1000-6060.2022.337
[21] Zhou F, Zhou D M, Jin Y L, et al. Spatial matching characteristics of supply and demand of ecosystem services in the Shule River Basin[J]. Arid Land Geography, 2023, 46(3):471-480.
doi: 10.12118/j.issn.1000-6060.2022.337
[22] 武文欢, 彭建, 刘焱序, 等. 鄂尔多斯市生态系统服务权衡与协同分析[J]. 地理科学进展, 2017, 36(12):1571-1581.
doi: 10.18306/dlkxjz.2017.12.012
[22] Wu W H, Peng J, Liu Y X, et al. Tradeoffs and synergies between ecosystem services in Ordos City[J]. Progress in Geography, 2017, 36(12):1571-1581.
doi: 10.18306/dlkxjz.2017.12.012
[23] 刘纪远, 宁佳, 匡文慧, 等. 2010—2015年中国土地利用变化的时空格局与新特征[J]. 地理学报, 2018, 73(5):789-802.
doi: 10.11821/dlxb201805001
[23] Liu J Y, Ning J, Kuang W H, et al. Spatio-temporal patterns and characteristics of land-use change in China during 2010—2015[J]. Acta Geographica Sinica, 2018, 73(5):789-802.
[24] 魏培洁, 吴明辉, 贾映兰, 等. 基于InVEST模型的疏勒河上游产水量时空变化特征分析[J]. 生态学报, 2022, 42(15):6418-6429.
[24] Wei P J, Wu M H, Jia Y L, et al. Spatiotemporal variation of water yield in the upstream regions of the Shule River Basin using the InVEST Model[J]. Acta Ecologica Sinica, 2022, 42(15):6418-6429.
[25] 胡文敏, 杨睿瀚, 贾冠宇, 等. 长江流域产水功能对土地利用变化的响应及其驱动因素[J]. 生态学报, 2022, 42(17):7011-7027.
[25] Hu W M, Yang R H, Jia G Y, et al. Response of water yield function to land use change and its driving factors in the Yangtze River Basin[J]. Acta Ecologica Sinica, 2022, 42( 17) :7011-7027.
[26] 贾纪昂, 郭伟玲, 徐刘洋, 等. 耦合PLUS-InVEST-GeoDetector模型的安徽省碳储量时空演变及驱动力分析[J]. 环境科学, 2025, 46(3):1703-1715.
[26] Jia J A, Guo W L, Xu L Y, et al. Spatio-temporal evolution and driving force analysis of carbon storage in Anhui Province coupled with PLUS-InVEST-GeoDetector model[J]. Environmental Science, 2025, 46(3):1703-1715.
[27] Martens B, Miralles D G, Lievens H, et al. GLEAM v4.2a:Global land evaporation amsterdam model dataset[EB/OL].[2025-04-01].https://www.gleam.eu.
url: https://www.gleam.eu
[1] CHEN Qiuji, XIE Mimi, NAN Dandan, LUO Hao. Spatiotemporal evolution and prediction of ecosystem carbon storage in Xianyang City based on the PLUS-InVEST model[J]. Remote Sensing for Natural Resources, 2025, 37(5): 172-182.
[2] XING Xiaotian, WANG Qi, ZHAO Jiajun, LIU Pudong, ZHANG Jingyuan. Investigating land use and carbon storage changes in Jinan metropolitan circle based on the InVEST-PLUS coupled model[J]. Remote Sensing for Natural Resources, 2025, 37(4): 118-130.
[3] ZHENG Jiaxin, PEI Xiaolong, SONG Dongyang, TIAN Rui, ZHAO Zhongqiu, BAI Hang. Identification of ecologic zones based on ecosystem service value and ecological risk index from a perspective of spatiotemporal dynamics: A case study of Qinhuangdao City, Hebei Province[J]. Remote Sensing for Natural Resources, 2025, 37(3): 233-244.
[4] LIN Xinyuan, CHENG Yangjian, XIE Wei, LI Chuanqing, NIE Wen. Exploring the ecological effects of land use changes in mining areas under different mining modes based on the Google Earth Engine[J]. Remote Sensing for Natural Resources, 2025, 37(3): 54-64.
[5] CHAI Xinyu, WU Xianwen, CHEN Xiaohui, WANG Yu, ZHAO Xingtao. Multi-scenario simulation and prediction of land use in the Pearl River Delta urban agglomeration using the coupled Markov-FLUS model[J]. Remote Sensing for Natural Resources, 2025, 37(2): 140-147.
[6] HUI Le, WANG Hao, LIU Jiamin, TANG Butian, ZHANG Weijuan. Construction of an ecological security pattern in the Guanzhong Plain based on ecosystem services[J]. Remote Sensing for Natural Resources, 2025, 37(2): 194-203.
[7] CUI Dunyue, WANG Shidong, ZHANG Xuejun. A remote sensing-based study on change in land use and vegetation cover in Xiong’an New Area from 1991 to 2021[J]. Remote Sensing for Natural Resources, 2023, 35(4): 214-225.
[8] TIAN Liulan, LYU Siyu, WU Zhaopeng, WANG Juanjuan, SHI Xinpeng. Changes and spatial conflict measurement of land use in Urumqi City[J]. Remote Sensing for Natural Resources, 2023, 35(4): 282-291.
[9] YANG Lianwei, ZHAO Juan, ZHU Jiatian, LIU Lei, ZHANG Ping. Spatial-temporal change and prediction of carbon stock in the ecosystem of Xi’an based on PLUS and InVEST models[J]. Remote Sensing for Natural Resources, 2022, 34(4): 175-182.
[10] LI Bo, LIN Wenpeng, LI Lubing. SDG15-oriented analysis on the spatiotemporal dynamics of ecosystem services in Qianjiangyuan National Park[J]. Remote Sensing for Natural Resources, 2022, 34(4): 243-253.
[11] LI Jingzhi, WANG Miao, FENG Wenjing, LI Bin. The characteristics and driving factors of spatiotemporal changes in the ecosystem service value in Xiangxi, Hunan, China[J]. Remote Sensing for Natural Resources, 2022, 34(3): 207-217.
[12] YE Qinyu, YANG Shiqi, ZHANG Qiang, WANG Shu, HE Zeneng, ZHENG Yinghui. Analysis on water conservation function using remote sensing method in the Three Gorges Reservoir area (Chongqing section)[J]. Remote Sensing for Natural Resources, 2022, 34(2): 184-193.
[13] LI Xia, LI Jingzhi. Response mechanism of ecosystem service value to urban and rural construction land expansion in the three outlets of the southern Jingjiang River[J]. Remote Sensing for Natural Resources, 2022, 34(2): 278-288.
[14] SONG Qi, FENG Chunhui, MA Ziqiang, WANG Nan, JI Wenjun, PENG Jie. Simulation of land use change in oasis of arid areas based on Landsat images from 1990 to 2019[J]. Remote Sensing for Natural Resources, 2022, 34(1): 198-209.
[15] SANG Xiao, ZHANG Chengye, LI Jun, ZHU Shoujie, XING Jianghe, WANG Jinyang, WANG Xingjuan, LI Jiayao, YANG Ying. Application of intensity analysis theory in the land use change in Yijin Holo Banner under the background of coal mining[J]. Remote Sensing for Natural Resources, 2021, 33(3): 148-155.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
京ICP备05055290号-2
Copyright © 2017 Remote Sensing for Natural Resources
Support by Beijing Magtech