[1] KHAN K, SHAH G M, SAQIB Z, et al. Species diversity and distribution of macrophytes in different wetland ecosystems [J/OL]. Applied Sciences, 2022, 12 (9): 4467[2023-01-18]. doi: 10.3390/app12094467.
[2] CHEN Kexin, CONG Pifu, QU Limei, et al. Wetland degradation diagnosis and zoning based on the integrated degradation index method [J/OL]. Ocean & Coastal Management, 2022, 222: 106135[2023-01-18]. doi: 10.1016/j.ocecoaman.2022.106135.
[3] NILSSON C, REIDY C A, DYNESIUS M, et al. Fragmentation and flow regulation of the world’s large river systems [J]. Science, 2005, 308(5720): 405 − 408.
[4] 王立龙, 陆林, 唐勇, 等. 中国国家级湿地公园运行现状、区域分布格局与类型划分[J]. 生态学报, 2010, 30(9): 2406 − 2415.

WANG Lilong, LU Lin, TANG Yong, et al. Running status, distribution pattern and type classification of the state-level wetland parks in China [J]. Acta Ecologica Sinica, 2010, 30(9): 2406 − 2415.
[5] 吴后建, 但新球, 王隆富, 等. 我国湿地公园建设的回顾与展望[J]. 林业资源管理, 2016(2): 39 − 44.

WU Houjian, DAN Xinqiu, WANG Longfu, et al. Review and prospect of wetland park construction in China [J]. Forest Resources Management, 2016(2): 39 − 44.
[6] 林文棋, 武廷海. 变化·规划·情景——变化背景中的空间规划思维与方法[M]. 北京: 清华大学出版社, 2013.

LIN Wenqi, WU Tinghai. Spatial Planning Thinking and Methods in the Context of Changing Scenarios [M]. Beijing: Tsinghua University Press, 2013.
[7] 娄伟. 情景分析理论研究[J]. 未来与发展, 2013, 36(8): 30 − 37.

LOU Wei. The study on scenario analysis theory [J]. Future and Development, 2013, 36(8): 30 − 37.
[8] 赵莉, 杨俊, 李闯, 等. 地理元胞自动机模型研究进展[J]. 地理科学, 2016, 36(8): 1190 − 1196.

ZHAO Li, YANG Jun, LI Chuang, et al. Progress on geographic cellular automata model [J]. Scientia Geographica Sinica, 2016, 36(8): 1190 − 1196.
[9] 吴佩君, 刘小平, 黎夏, 等. 基于InVEST模型和元胞自动机的城市扩张对陆地生态系统碳储量影响评估——以广东省为例[J]. 地理与地理信息科学, 2016, 32(5): 22 − 28.

WU Peijun, LIU Xiaoping, LI Xia, et al. Impact of urban expansion on carbon storage in terrestrial ecosystems based on InVEST model and CA: a case study of Guangdong Province, China [J]. Geography and Geo-Information Science, 2016, 32(5): 22 − 28.
[10] 易武英, 苏维词, 周文龙, 等. 基于元胞自动机模型的贵阳市花溪区生态安全预警模拟研究[J]. 浙江农林大学学报, 2015, 32(3): 369 − 375.

YI Wuying, SU Weici, ZHOU Wenlong, et al. An ecological security early warning simulation city based on the CA Model in Huaxi District of Guiyang City, China [J]. Journal of Zhejiang A&F University, 2015, 32(3): 369 − 375.
[11]

VERBURG P H, SOEPBOER W, VELDKAMP A, et al. Modeling the spatial dynamics of regional land use: the CLUE-S model [J]. Environmental Management, 2002, 30(3): 391 − 405.
[12] 许小亮, 李鑫, 肖长江, 等. 基于CLUE-S模型的不同情景下区域土地利用布局优化[J]. 生态学报, 2016, 36(17): 5401 − 5410.

XU Xiaoliang, LI Xin, XIAO Changjiang, et al. Land use layout optimization under different scenarios by using the CLUE-S model [J]. Acta Ecologica Sinica, 2016, 36(17): 5401 − 5410.
[13] 卞子浩, 马小雪, 龚来存, 等. 不同非空间模拟方法下CLUE-S模型土地利用预测——以秦淮河流域为例[J]. 地理科学, 2017, 37(2): 252 − 258.

BIAN Zihao, MA Xiaoxue, GONG Laicun, et al. Land use prediction based on CLUE-S model under different non-spatial simulation methods: a case study of the Qinhuai River Watershed [J]. Scientia Geographica Sinica, 2017, 37(2): 252 − 258.
[14] 顾汉龙, 马天骏, 钱凤魁, 等. 基于CLUE-S模型县域土地利用情景模拟与碳排放效应分析[J]. 农业工程学报, 2022, 38(9): 288 − 296.

GU Hanlong, MA Tianjun, QIAN Fengkui, et al. County land use scenario simulation and carbon emission effect analysis using CLUE-S model [J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(9): 288 − 296.
[15] 宋歌, 王金朔, 何立恒, 等. 基于CLUE-S模型的西部干旱区土地利用变化情景模拟[J]. 南京林业大学学报(自然科学版), 2013, 37(3): 135 − 139.

SONG Ge, WANG Jinshuo, HE Liheng, et al. Simulation of land use change in western arid region under different scenarios based on the CLUE-S model [J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2013, 37(3): 135 − 139.
[16]

LIN Weibin, SUN Yimin, NIJHUIS S, et al. Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou Metropolitan Area as a case study [J/OL]. Science of The Total Environment, 2020, 739: 139899[2023-01-18]. doi: 10.1016/j.scitotenv.2020.139899.
[17] 李立, 胡睿柯, 李素红. 基于改进FLUS模型的北京市低碳土地利用情景模拟[J]. 自然资源遥感, 2023, 35(1): 1 − 9.

LI Li, HU Ruike, LI Suhong. Simulations of the low-carbon land use scenarios of Beijing based on the improved FLUS model [J]. Remote Sensing for Nature Resources, 2023, 35(1): 1 − 9.
[18]

CHEN Xin, HE Xinyi, WANG Siyuan. Simulated validation and prediction of land use under multiple scenarios in Daxing District, Beijing, China, based on GeoSOS-FLUS model [J/OL]. Sustainability, 2022, 14(18): 11428[2023-02-18]. doi: 10.3390/su141811428.
[19] 胡丰, 张艳, 郭宇, 等. 基于PLUS和InVEST模型的渭河流域土地利用与生境质量时空变化及预测[J]. 干旱区地理, 2022, 45(4): 1125 − 1136.

HU Feng, ZHANG Yan, GUO Yu, et al. Spatial and temporal changes in land use and habitat quality in the Weihe River Basin based on the PLUS and InVEST models and predictions [J]. Arid Land Geography, 2022, 45(4): 1125 − 1136.
[20] 李琛, 高彬嫔, 吴映梅, 等. 基于PLUS模型的山区城镇景观生态风险动态模拟[J]. 浙江农林大学学报, 2022, 39(1): 84 − 94.

LI Chen, GAO Binpin, WU Yingmei, et al. Dynamic simulation of landscape ecological risk in mountain towns based on PLUS model [J]. Journal of Zhejiang A&F University, 2022, 39(1): 84 − 94.
[21] 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: a case study of Hanzhong City [J]. Journal of Arid Land Resources Environment, 2022, 36(10): 86 − 95.
[22]

LIANG Xun, GUAN Qingfeng, CLARKE K, et al. Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model: a case study in Wuhan, China [J/OL]. Computers, Environment and Urban Systems, 2021, 85: 101569[2023-01-18]. doi: 10.1016/j.compenvurbsys.2020.101569.
[23] 舒晓艺. 南流江流域土地利用/覆被变化模拟研究[D]. 南宁: 南宁师范大学, 2021.

SHU Xiaoyi. Simulation Research on Land Use/Cover Change in Nanliu River Basin [D]. Nanning: Nanning Normal University, 2021.
[24] 是丽娜. 基于生态伦理的湿地旅游可持续发展研究——以溱湖国家湿地公园为例[D]. 南京: 南京林业大学, 2018.

SHI Lina. Research on Sustainable Development of Wetland Tourism Based on Ecological Ethics: a Case Study of Qinhu Lake National Park [D]. Nanjing: Nanjing Forestry University, 2018.
[25] 曹林. 溱湖国家湿地公园WebGIS系统的设计与开发[D]. 南京: 南京林业大学, 2008.

CAO Lin. Design and Development of Information System of Qin Lake National Wetland Park Based on WebGIS [D]. Nanjing: Nanjing Forestry University, 2008.
[26] 泰州市姜堰区人民政府. 姜堰区国土空间规划近期实施方案 [EB/OL]. 2021-05-10[2022-11-21]. http://zrzy.jiangsu.gov.cn/gtapp/nrglIndex.action?type=2&messageID=ff80808179404a4e017955b7265e061c.

Taizhou Jiangyan District People’ s Government. Jiangyan District Territorial Space Planning Implementation Plan [EB/OL]. 2021-05-10[2022-11-21]. http://zrzy.jiangsu.gov.cn/gtapp/nrglIndex.ction?type=a2&messageID=ff80808179404a4e017955b7265e061c.
[27] 江苏省林业局. 江苏省湿地保护规划(2015—2030年) [EB/OL]. 2021-11-19[2022-11-21]. http://fzggw.jiangsu.gov.cn/art/2015/4/30/art_83784_10119305.html.

Jiangsu Forestry Bureau. Wetland Protection Plan of Jiangsu Province (2015−2030) [EB/OL]. 2021-11-19[2022-11-21]. http://fzggw.jiangsu.gov.cn/art/2015/4/30/art_83784_10119305.html.
[28] 泰州市姜堰区人民政府. 泰州市姜堰区国民经济和社会发展第十四个五年规划和二〇三五年远景目标纲要[EB/OL]. 2021-01-21[2022-11-21]. http://www.jiangyan.gov.cn/zfxxgk/fdzdgknr/ghxx/sswgh/ztgh/art/2021/art_48825098368e4bfe9102293f42daaf06.html.

Taizhou Jiangyan District People’s Government. The 14th Five-Year Plan for National Economic and Social Development of Jiangyan District of Taizhou City and the Outline of the Long-term Goals for 2035 [EB/OL]. 2021-01-21[2022-11-21]. http://www.jiangyan.gov.cn/zfxxgk/fdzdgknr/ghxx/sswgh/ztgh/art/2021/art_48825098368e4bfe9102293f42daaf06.html.
[29] 张鹏, 李良涛, 苏玉姣, 等. 基于PLUS和InVEST模型的邯郸市碳储量空间分布特征研究[J]. 水土保持通报, 2023, 43(3): 338 − 348.

ZHANG Peng, LI Liangtao, SU Yujiao, et al. Spatial and temporal distribution charactersitics of carbon storage in Handan City based on PLUS AND InVEST models [J]. Bulletin of Soil and Water Conservation, 2023, 43(3): 338 − 348.
[30] 刘锋, 杨木壮, 赵冠伟, 等. 基于土地利用变化的广州市碳排放效应分析——以近20 a为例[J]. 农业与技术, 2022, 42(4): 73 − 79.

LIU Feng, YANG Muzhuang, ZHAO Guanwei, et al. Carbon emission effect of Guangzhou based on land use change: a case study of recent 20 years [J]. Agriculture Technology, 2022, 42(4): 73 − 79.