Evolutions of 30-Year Spatio-Temporal Distribution and Influencing Factors of Suaeda salsa in Bohai Bay, China

被引:15
|
作者
Yin, Hongyan [1 ,2 ,3 ]
Hu, Yuanman [1 ,3 ,4 ]
Liu, Miao [1 ,3 ,4 ]
Li, Chunlin [1 ,3 ]
Chang, Yu [1 ,3 ]
机构
[1] Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Key Lab Terr Ecosyst Carbon Neutral, Shenyang 110016, Peoples R China
[4] Eerguna Wetland Ecosyst Natl Res Stn, Hulun Buir 022250, Peoples R China
基金
中国国家自然科学基金;
关键词
coastal wetland; Suaeda salsa; time series Landsat images; influencing factor analysis; Bohai Bay region; GOOGLE EARTH ENGINE; COASTAL WETLANDS; LAND-COVER; CLASSIFICATION; ESTUARY; REGRESSION; TOLERANCE; PATTERNS; IMAGES; FOREST;
D O I
10.3390/rs14010138
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Suaeda salsa (L.) Pall. (S. salsa) acts as a pioneer species in coastal wetlands due to its high salt tolerance. It has significant biodiversity maintenance, socioeconomic values (e.g., tourism) due to its vibrant color, and carbon sequestration (blue carbon). Bohai Bay region, the mainly distributed area of S. salsa, is an economic intensive region with the largest economic aggregate and population in northern China. The coastal wetland is one of the most vulnerable ecosystems with the urbanization and economic developments. S. salsa in Bohai Bay has been changed significantly due to several threats to its habitat in past decades. In this paper, we analyzed all available archived Landsat TM/ETM+/OLI images of the Bohai Bay region by using a decision tree algorithm method based on the Google Earth Engine (GEE) platform to generate annual maps of S. salsa from 1990 to 2020 at a 30-m spatial resolution. The temporal-spatial dynamic changes in S. salsa were studied by landscape metric analysis. The influencing factors of S. salsa changes were analyzed based on principal component analysis (PCA) and a logistic regression model (LRM). The results showed that S. salsa was mainly distributed in three regions: the Liao River Delta (Liaoning Province), Yellow River Delta (Shandong Province), and Hai River Estuary (Hebei Province, Tianjin). During the past 31 years, the total area of S. salsa has dramatically decreased from 692.93 km(2) to 51.04 km(2), which means that 92.63% of the area of S. salsa in the Bohai Bay region was lost. In the 641.89 km(2) area of S. salsa that was lost, 348.80 km(2) of this area was converted to other anthropic land use categories, while 293.09 km(2) was degraded to bare land. The landscape fragmentation of S. salsa has gradually intensified since 1990. National Nature Reserves have played an important role in the restoration of suitable S. salsa habitats. The analysis results for the natural influencing factors indicated that precipitation, temperature, elevation, and distance to the coastline were considered to be the major influencing factors for S. salsa changes. The results are valuable for monitoring the dynamic changes of S. salsa and can be used as effective factors for the restoration of S. salsa in coastal wetlands.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Factors Influencing the Spatio-Temporal Distribution of Chlorophyll-a in Jinmeng Bay, China
    Wang, Dan
    Kuang, Cuiping
    Wang, Gang
    Liu, Jiantao
    Song, Wei
    Xing, Rongrong
    Zou, Qingping
    [J]. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 2024, 12 (03)
  • [2] Spatio-temporal distribution of NDVI and its influencing factors in China
    Jin, Haoyu
    Chen, Xiaohong
    Wang, Yuming
    Zhong, Ruida
    Zhao, Tongtiegang
    Liu, Zhiyong
    Tu, Xinjun
    [J]. JOURNAL OF HYDROLOGY, 2021, 603
  • [3] Spatio-temporal distribution of vegetation index and its influencing factors——a case study of the Jiaozhou Bay, China
    郑洋
    于格
    [J]. Journal of Oceanology and Limnology, 2017, (06) : 1398 - 1408
  • [4] Spatio-temporal distribution of vegetation index and its influencing factors—a case study of the Jiaozhou Bay, China
    Yang Zheng
    Ge Yu
    [J]. Chinese Journal of Oceanology and Limnology, 2017, 35 : 1398 - 1408
  • [5] Spatio-temporal distribution of vegetation index and its influencing factors——a case study of the Jiaozhou Bay, China
    郑洋
    于格
    [J]. Chinese Journal of Oceanology and Limnology., 2017, 35 (06) - 1408
  • [6] Spatio-temporal distribution of vegetation index and its influencing factors-a case study of the Jiaozhou Bay, China
    Zheng Yang
    Yu Ge
    [J]. CHINESE JOURNAL OF OCEANOLOGY AND LIMNOLOGY, 2017, 35 (06): : 1398 - 1408
  • [7] Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
    Youliang Chen
    Qun Li
    Hamed Karimian
    Xunjun Chen
    Xiaoming Li
    [J]. Scientific Reports, 11
  • [8] Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
    Chen, Youliang
    Li, Qun
    Karimian, Hamed
    Chen, Xunjun
    Li, Xiaoming
    [J]. SCIENTIFIC REPORTS, 2021, 11 (01)
  • [9] Spatio-temporal evolutions and driving factors of wheat and maize yields in China
    Han, Tianfu
    Li, Yazhen
    Qu, Xiaolin
    Ma, Changbao
    Wang, Huiying
    Huang, Jing
    Liu, Kailou
    Du, Jiangxue
    Zhang, Lu
    Liu, Lisheng
    Zhang, Huimin
    [J]. Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2022, 38 (01): : 100 - 108
  • [10] Framework for Spatio-Temporal Distribution of Disasters and Influencing Factors: Exploratory Study of Tianjin, China
    Yang, Weichao
    Hu, De
    Jiang, Xuelian
    Dun, Xuebo
    Hou, Bingtao
    Zheng, Chuanxing
    Chen, Caixia
    Zhuang, Rong
    [J]. SUSTAINABILITY, 2022, 14 (17)