Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta
Ecological resilience (ER) is considered a key factor in resolving complex human and natural systems conflicts and managing risk during the period of rapid development. However, the importance of landscape patterns for ER is not given enough attention in previous studies. Therefore, we selected the...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
|
| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23005514 |
| _version_ | 1797802864197763072 |
|---|---|
| author | Xiaobin Ma Jinhe Zhang Peijia Wang Leying Zhou Yi Sun |
| author_facet | Xiaobin Ma Jinhe Zhang Peijia Wang Leying Zhou Yi Sun |
| author_sort | Xiaobin Ma |
| collection | DOAJ |
| description | Ecological resilience (ER) is considered a key factor in resolving complex human and natural systems conflicts and managing risk during the period of rapid development. However, the importance of landscape patterns for ER is not given enough attention in previous studies. Therefore, we selected the Yangtze River Delta region as the study area, incorporated landscape patterns into the assessment of ER and proposed the way for identifying ecological sources based on the combination of ecosystem services and landscape patterns. Combining the multidimensional ecological resilience assessment indicators system, we calculated the ER for the Yangtze River Delta region and explored the importance and nonlinear effects of landscape patterns on the ER using a random forest regression model. The results showed that the comparative analysis of ecosystem services and landscape patterns enhanced the scientificity of ecological source identification. We identified 94 ecological sources mainly in the southern of the Yangtze River Delta region, including important mountain ranges and water bodies. In addition, the ER was significantly strengthened by considering the landscape patterns. The random forest regression results indicated the nonlinear relationship between the landscape patterns and the other elements in terms of ER. This study can contribute to a comprehensive and integrated approach to the identification of ecological sources and the evaluation of ER, which can promote the conservation of regional ecological functions. |
| first_indexed | 2024-03-13T05:13:14Z |
| format | Article |
| id | doaj.art-96f81ba68ef441f2b6bd8c05bcee43b6 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-03-13T05:13:14Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-96f81ba68ef441f2b6bd8c05bcee43b62023-06-16T05:08:41ZengElsevierEcological Indicators1470-160X2023-09-01153110409Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River DeltaXiaobin Ma0Jinhe Zhang1Peijia Wang2Leying Zhou3Yi Sun4School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Huangshan Park Ecosystem Observation and Research Station, Ministry of Education, Huangshan 245899, ChinaSchool of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Huangshan Park Ecosystem Observation and Research Station, Ministry of Education, Huangshan 245899, China; Corresponding author at: Department of Land Resources and Tourism Sciences, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing City, Jiangsu Province 210023, PR China.School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Huangshan Park Ecosystem Observation and Research Station, Ministry of Education, Huangshan 245899, ChinaSchool of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Huangshan Park Ecosystem Observation and Research Station, Ministry of Education, Huangshan 245899, ChinaSchool of Geography and Ocean Science, Nanjing University, Nanjing 210023, China; Huangshan Park Ecosystem Observation and Research Station, Ministry of Education, Huangshan 245899, ChinaEcological resilience (ER) is considered a key factor in resolving complex human and natural systems conflicts and managing risk during the period of rapid development. However, the importance of landscape patterns for ER is not given enough attention in previous studies. Therefore, we selected the Yangtze River Delta region as the study area, incorporated landscape patterns into the assessment of ER and proposed the way for identifying ecological sources based on the combination of ecosystem services and landscape patterns. Combining the multidimensional ecological resilience assessment indicators system, we calculated the ER for the Yangtze River Delta region and explored the importance and nonlinear effects of landscape patterns on the ER using a random forest regression model. The results showed that the comparative analysis of ecosystem services and landscape patterns enhanced the scientificity of ecological source identification. We identified 94 ecological sources mainly in the southern of the Yangtze River Delta region, including important mountain ranges and water bodies. In addition, the ER was significantly strengthened by considering the landscape patterns. The random forest regression results indicated the nonlinear relationship between the landscape patterns and the other elements in terms of ER. This study can contribute to a comprehensive and integrated approach to the identification of ecological sources and the evaluation of ER, which can promote the conservation of regional ecological functions.http://www.sciencedirect.com/science/article/pii/S1470160X23005514Landscape patternsMSPARandom forest regression algorithmEcological resilienceEcosystem servicesYangtze River Delta region |
| spellingShingle | Xiaobin Ma Jinhe Zhang Peijia Wang Leying Zhou Yi Sun Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta Ecological Indicators Landscape patterns MSPA Random forest regression algorithm Ecological resilience Ecosystem services Yangtze River Delta region |
| title | Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta |
| title_full | Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta |
| title_fullStr | Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta |
| title_full_unstemmed | Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta |
| title_short | Estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm: Evidence from the Yangtze River Delta |
| title_sort | estimating the nonlinear response of landscape patterns to ecological resilience using a random forest algorithm evidence from the yangtze river delta |
| topic | Landscape patterns MSPA Random forest regression algorithm Ecological resilience Ecosystem services Yangtze River Delta region |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23005514 |
| work_keys_str_mv | AT xiaobinma estimatingthenonlinearresponseoflandscapepatternstoecologicalresilienceusingarandomforestalgorithmevidencefromtheyangtzeriverdelta AT jinhezhang estimatingthenonlinearresponseoflandscapepatternstoecologicalresilienceusingarandomforestalgorithmevidencefromtheyangtzeriverdelta AT peijiawang estimatingthenonlinearresponseoflandscapepatternstoecologicalresilienceusingarandomforestalgorithmevidencefromtheyangtzeriverdelta AT leyingzhou estimatingthenonlinearresponseoflandscapepatternstoecologicalresilienceusingarandomforestalgorithmevidencefromtheyangtzeriverdelta AT yisun estimatingthenonlinearresponseoflandscapepatternstoecologicalresilienceusingarandomforestalgorithmevidencefromtheyangtzeriverdelta |