Pei-Yuan Xin, Tian Tian, Mei-Lu Zhang, Wei-Zheng Han, Yun-Ting Song
{"title":"[Assessment of habitat quality changes and driving factors in Jilin Province based on InVEST model and geodetector].","authors":"Pei-Yuan Xin, Tian Tian, Mei-Lu Zhang, Wei-Zheng Han, Yun-Ting Song","doi":"10.13287/j.1001-9332.202410.026","DOIUrl":null,"url":null,"abstract":"<p><p>Jilin Province is an important ecological security barrier in Northeast China as it is located at the junction of the Northeast forest belts and the northern sand prevention belts. In recent years, Jilin Province has actively carried out ecological protection and restoration projects, resulting in a continuous improvement trend for the overall ecological environment. However, the evolution patterns and mechanisms of habitat quality are largely unkown. We applied the InVEST model and geographic detector method to analyze the changes in habitat quality and evaluate the main driving factors from 2000 to 2020. The results showed that the average habitat quality in Jilin Province showed a slight downward trend, and that the spatial heterogeneity characteristics of habitat quality in east and west gradually increased. The degree of habitat degradation presented a single nuclear radiation pattern centered on Changchun City. Vegetation factors and terrain factors were the first and secondary causes of spatial heterogeneity of habitat quality, respectively. The average habitat quality within the eco-redline of Jilin Province was showing an increasing trend year by year, which was consistent with the overall distribution of regions with extremely high habitat quality levels. There was a local spatial dislocation (the phenomenon of extremely high habitat quality levels not within the eco-redline) in the eastern part of Jilin Province. Our results could provide reference basis for ecosystem protection and the spatial pattern optimization.</p>","PeriodicalId":35942,"journal":{"name":"应用生态学报","volume":"35 10","pages":"2853-2860"},"PeriodicalIF":0.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"应用生态学报","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.13287/j.1001-9332.202410.026","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Environmental Science","Score":null,"Total":0}
引用次数: 0
Abstract
Jilin Province is an important ecological security barrier in Northeast China as it is located at the junction of the Northeast forest belts and the northern sand prevention belts. In recent years, Jilin Province has actively carried out ecological protection and restoration projects, resulting in a continuous improvement trend for the overall ecological environment. However, the evolution patterns and mechanisms of habitat quality are largely unkown. We applied the InVEST model and geographic detector method to analyze the changes in habitat quality and evaluate the main driving factors from 2000 to 2020. The results showed that the average habitat quality in Jilin Province showed a slight downward trend, and that the spatial heterogeneity characteristics of habitat quality in east and west gradually increased. The degree of habitat degradation presented a single nuclear radiation pattern centered on Changchun City. Vegetation factors and terrain factors were the first and secondary causes of spatial heterogeneity of habitat quality, respectively. The average habitat quality within the eco-redline of Jilin Province was showing an increasing trend year by year, which was consistent with the overall distribution of regions with extremely high habitat quality levels. There was a local spatial dislocation (the phenomenon of extremely high habitat quality levels not within the eco-redline) in the eastern part of Jilin Province. Our results could provide reference basis for ecosystem protection and the spatial pattern optimization.