Xiaoqing Yi , Yuhang Wang , Changjun Gao , Jiaojiao Ma , Demin Zhou , Christian J. Sanders , Guangjia Jiang , Zhongwen Hu , Junjie Wang , Haichao Zhou , Wei Li
{"title":"The dynamic driving mechanisms of wetland change from an asynchrony-spatiotemporal perspective: A case study in Pearl River Delta, China","authors":"Xiaoqing Yi , Yuhang Wang , Changjun Gao , Jiaojiao Ma , Demin Zhou , Christian J. Sanders , Guangjia Jiang , Zhongwen Hu , Junjie Wang , Haichao Zhou , Wei Li","doi":"10.1016/j.ecoinf.2024.102979","DOIUrl":null,"url":null,"abstract":"<div><div>The mechanism of wetland distribution (WD) has been well studied, but further research is needed on the mechanism of wetland change (WC). This study developed a model of the impact of changes in human activity (HA) and natural environment factors on WC from an asynchronous–spatiotemporal perspective, integrating remote sensing technologies and partial least squares–structural equation modeling (PLS–SEM). In the model, HA was reflected by economic and population data. The natural environment was reflected by the fundamental natural environment (FNE), which was mainly based on terrain, and the non-stable natural environment (NNE), which was mainly based on hydrological and temperature conditions. The model met the accuracy requirements in the Pearl River Delta (PRD). The results showed that there were differences in the response of WD and WC to driving factors from 1980 to 2020 in the PRD. FNE had a negative impact on WD, however, FNE changes (FNEC) had a positive impact on WC (mainly wetlands decrease). HA could affect NNE and subsequently WD, but NNE changes (NNEC) only began to affect WC after 2010. HA had a negative impact on WD and WC from 1980 to 2010, but both negative and positive impacts existed after 2010. By coupling areas of HA changes (HAC) with wetland decrease, it was found that HA should be restricted in the southeast of Foshan (areas where HA increase led to wetland decrease) to protect wetlands; The junction between Zhaoqing and Foshan (areas where HA decrease lead to wetland decrease) requires investment in improving the natural environment. The model proposed in this study can be applied to other areas with severe wetland degradation from HA and natural conditions, to assist in local wetland restoration and management.</div></div>","PeriodicalId":51024,"journal":{"name":"Ecological Informatics","volume":"86 ","pages":"Article 102979"},"PeriodicalIF":5.8000,"publicationDate":"2024-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ecological Informatics","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1574954124005211","RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The mechanism of wetland distribution (WD) has been well studied, but further research is needed on the mechanism of wetland change (WC). This study developed a model of the impact of changes in human activity (HA) and natural environment factors on WC from an asynchronous–spatiotemporal perspective, integrating remote sensing technologies and partial least squares–structural equation modeling (PLS–SEM). In the model, HA was reflected by economic and population data. The natural environment was reflected by the fundamental natural environment (FNE), which was mainly based on terrain, and the non-stable natural environment (NNE), which was mainly based on hydrological and temperature conditions. The model met the accuracy requirements in the Pearl River Delta (PRD). The results showed that there were differences in the response of WD and WC to driving factors from 1980 to 2020 in the PRD. FNE had a negative impact on WD, however, FNE changes (FNEC) had a positive impact on WC (mainly wetlands decrease). HA could affect NNE and subsequently WD, but NNE changes (NNEC) only began to affect WC after 2010. HA had a negative impact on WD and WC from 1980 to 2010, but both negative and positive impacts existed after 2010. By coupling areas of HA changes (HAC) with wetland decrease, it was found that HA should be restricted in the southeast of Foshan (areas where HA increase led to wetland decrease) to protect wetlands; The junction between Zhaoqing and Foshan (areas where HA decrease lead to wetland decrease) requires investment in improving the natural environment. The model proposed in this study can be applied to other areas with severe wetland degradation from HA and natural conditions, to assist in local wetland restoration and management.
期刊介绍:
The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change.
The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.