Evaluation and Prediction of Status of Coastal Ecosystem
Xuncheng Fan 1,   Lili Zhao 1
,   Dongjin He 2  
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College of Urban and Rural Construction, Shaoyang University, Shaoyang, 422000 China
Forestry College, Fujian Agriculture and Forestry University, Fuzhou, 350002 China
Dongjin He   

Forestry College, Fujian Agriculture and Forestry University, China
Submission date: 2021-02-23
Final revision date: 2021-04-20
Acceptance date: 2021-04-27
Online publication date: 2021-09-01
Coastal zones are located at the intersection of the two major ecosystems of ocean and land. Three-fifths of the global population lives in coastal zones, which provide ecological services and are the most economically developed areas. However, the coastal ecosystem is seriously threatened because of long-term human disturbances. In this study, the Ningde coastal zone was selected as the study area. The Pressure-State-Response model and Analytic Hierarchy Process were used to evaluate the ecosystem of the Ningde coastal zone in 2000, 2009, and 2014. The Markov model was used to predict the status of the Ningde coastal zone ecosystem in 2024. Finally, several problems, corresponding countermeasures, and suggestions in the management of the Ningde coastal ecosystem were proposed. The ecosystem status in the coastal zone of Ningde improved continuously from 2000 to 2009. Although the status of the ecosystem declined slightly from 2009 to 2014, it currently remains fair. The status of the Ningde coastal ecosystem will be worse in 2024 than that in 2014, indicating that an increase in the area of forest and grassland and a decrease in the area of dry land and paddy field is not effective. The main problems affecting the coastal ecosystem of Ningde were that the area of aquaculture was blindly expanded and the role of water bodies in protecting the environment was ignored. The forest ecosystem in the coastal zone of Ningde was vulnerable to external disturbance owing to the single species of forest trees and the lack of a large area of land suitable for forests.