Examining the expansion of Spartina alterniflora in coastal wetlands using an MCE-CA-Markov model

被引:13
|
作者
Yan, Dandan [1 ]
Li, Jingtai [1 ]
Xie, Siying [1 ]
Liu, Yao [1 ]
Sheng, Yufeng [1 ]
Luan, Zhaoqing [1 ]
机构
[1] Nanjing Forestry Univ, Coll Biol & Environm, Coinnovat Ctr Sustainable Forestry Southern China, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Spartina alterniflora; suitability maps; MCE-CA-Markov; forecast spatial and temporal; Dafeng Milu National Nature Reserve; CELLULAR-AUTOMATA MODEL; POPULATION EXPANSION; SIMULATION; CLIMATE; GROWTH;
D O I
10.3389/fmars.2022.964172
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The spread of Spartina alterniflora (smooth cordgrass) has put biodiversity and ecosystem function at risk since it was introduced to China just a few decades ago. A better understanding of how the range of S. alterniflora will expand in the future will help manage the invasion of this species in coastal wetlands. However, it is difficult to model the future extent of Spartina saltmarshes in China. To address this issue, we combined multi criteria evaluation with traditional CA Markov model to provide robust forecasting of the spatial expansion of S. alterniflora for the next ten years, at Dafeng Milu National Nature Reserve, Jiangsu, China. Our results showed that, compared with the interpretation results of high-resolution remote sensing images in 2020, the kappa coefficient of verification accuracy was 82.63%, indicating that the MCE-CA-Markov model has good prediction results. Therefore, the model can forecast the expansion process of S. alterniflora over the next ten years. The model predicts that the area of S. alterniflora continued to decrease from 910.25 ha in 2020 to 881.21 ha in 2030. The spatial distribution of S. alterniflora has been decreasing on the landward side while it has been expanding towards the sea on the seaward side. This study provides some suggestions for effective management and control of invasive species, which could be important for wetland biodiversity conservation and resource management.
引用
收藏
页数:13
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