Disturbance of mangrove forests in Guangxi Beilun Estuary during 1990—2020

  • role: First author第一作者
  • Affiliation:

    College of Geography and Marine Science, Yanbian University, Yanji 133002, China

    Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China

  • Email:cg1250498997@163.com
  • Introduction:陈高,研究方向为滨海湿地遥感。E-mail: cg1250498997@163.com
CHEN Gao13,  
  • Affiliation:

    Hainan Forestry Science Research Institute (Mangrove Research Institute, Hainan Province), Haikou 571100, China

ZHONG Cairong2,  
  • Affiliation:

    College of Geography and Marine Science, Yanbian University, Yanji 133002, China

LI Mingyu1,  
  • Affiliation:

    College of Geography and Marine Science, Yanbian University, Yanji 133002, China

YU Zhou1,  
  • Affiliation:

    College of Geography and Marine Science, Yanbian University, Yanji 133002, China

LIU Xinyu1,  
  • role: Corresponding author通信作者
  • Affiliation:

    Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China

  • Email:jiamingming@iga.ac.cn
  • Introduction:贾明明,研究方向为滨海湿地遥感。E-mail: jiamingming@iga.ac.cn
JIA Mingming3*

реферат

Mangrove forests are highly productive ecosystems that maintain coastal ecological balance and biodiversity by providing breeding and nursing grounds for waterfowl, marine, and pelagic species. Mangroves are highly subjected to natural and anthropogenic disturbances, owing to their intermediate position between the terrestrial and marine environments. This study used Landsat imagery to track the temporal and spatial changes of mangrove forests in Guangxi Beilun Estuary National Nature Reserve. The objectives of this study are (1) to monitor spatial distributions and intensities of mangrove forest disturbances during the past 30 years, and (2) to analyze the natural and anthropogenic factors that cause these disturbances in the reserve.This study used the Google Earth Engine (GEE) platform to establish a time series Landsat dataset during 1990—2020. And then, GEE constructed the image dataset stack using the Medoid method for annual best pixel composition. Based on LandTrendr algorithm and the dataset, we studied disturbances of mangrove forests in Guangxi Beilun Estuary National Nature Reserve from 1990 to 2020. GEE enables quick access and processes a massive number of Landsat images in a paralleled process. Specifically, the GEE synchronizes all the Landsat data and provides different levels of processed products, including the top of atmosphere and surface reflectance data. LandTrendr algorithm can be used to detect changes in the time series of satellite images pixel by pixel and capture pixel-level subtle disturbances.The results show that (1) during 1990—2020, the total area of mangrove forest disturbances in the Beilun Estuary Reserve in Guangxi was 45.94 ha. Most disturbances occurred near pearl Bay, and a small amount of disturbances occurred in Beilun estuary; (2) the maximum disturbed area occurred in 2001, which was 12.91 ha, and the minimum disturbed area occurred in 2007, which was 0.09 ha; (3) slight, moderate, and severe disturbances accounted for 57.5%, 29.17%, and 13.33% of the total disturbance, respectively, and the areas are 26.42, 13.40, and 6.13 ha.According to our results and literature reviews, the following conclusions can be drawn: natural and anthropogenic factors cause the disturbance of mangrove forest in Guangxi Beilun Estuary National Nature Reserve. In terms of natural factors, sea level rise, extreme weather, pests and diseases, and invasion of spartina alterniflora have seriously threatened the growth environment of mangroves. In terms of human factors, cultivation ponds and farmland reclamation directly occupy the growth environment of mangroves. Mangroves are also threatened by wastewater from aquaculture ponds and pesticide residues in cultivated land. Parts of the terrigenous mangroves are developed as dikes or other artificial surfaces to attract residents or visitors. This condition has also led to an increase in wastewater from domestic production; not only does it hinder the growth of mangroves, but it also hinders the flow of matter and energy between land and sea. In addition, results of this study can serve as an important scientific basis and fundamental data for formulating mangrove protection and restoration strategies.

ключеви́че слова́

remote sensing;mangroves;protected areas;Google Earth Engine (GEE);Land Trendr algorithm

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