Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China
Landscape pattern significantly impacts habitat quality, especially in cities undergoing rapid urbanization, where landscape patterns are changing dramatically. However, the spatial and temporal driving mechanisms of landscape pattern on habitat quality are still unclear, and the proposed methods of...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-10-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X22008068 |
| _version_ | 1798001156154195968 |
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| author | Jinyu Hu Jiaxin Zhang Yunqin Li |
| author_facet | Jinyu Hu Jiaxin Zhang Yunqin Li |
| author_sort | Jinyu Hu |
| collection | DOAJ |
| description | Landscape pattern significantly impacts habitat quality, especially in cities undergoing rapid urbanization, where landscape patterns are changing dramatically. However, the spatial and temporal driving mechanisms of landscape pattern on habitat quality are still unclear, and the proposed methods of Geographically and Temporally Weighted Regression (GTWR) and Multiscale Geographic Weighted Regression (MGWR) provide possibilities for the exploration of these mechanisms. This study was conducted in Nanjing from 2001 to 2020. Landscape pattern indices indicating aggregation, connectivity, diversity and compactness were calculated using Fragstats from 2001 to 2020. The habitat quality was computed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. By combining two new spatial measurement models, GTWR and MGWR, the spatial and temporal driving mechanisms of landscape patterns on habitat quality were explored. The results show that (1) as Nanjing’s land under construction has expanded, habitat quality has decreased significantly, and the overall landscape pattern has fluctuated drastically. (2) GTWR and MGWR are well-suited to such analysis and provide important insights. (3) Overall, aggregation and compactness were negatively associated with habitat quality in areas of low-quality habitat. Increased connectivity on low habitat substrates had a positive effect on habitat. The increase of diversity in proximity had a positive effect on habitat, while the opposite was true in high habitat zones. (4) As the urbanization level increases, the negative effects of aggregation expand, as do the positive effects of connectivity and diversity. (5) The extent of influence of landscape pattern effects are ranked from largest to smallest: compactness, diversity, connectivity, and aggregation, while the intensity of effects is reversed. Based on these findings, a reference point for urban planners is provided to plan urban landscape patterns in a sustainable and rational manner. It also provides a new means of integrating GTWR and MGWR into the study of landscape ecology. |
| first_indexed | 2024-04-11T11:31:37Z |
| format | Article |
| id | doaj.art-7f8e1cb317364d9898e6c172f20f6ffe |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-11T11:31:37Z |
| publishDate | 2022-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-7f8e1cb317364d9898e6c172f20f6ffe2022-12-22T04:26:07ZengElsevierEcological Indicators1470-160X2022-10-01143109333Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, ChinaJinyu Hu0Jiaxin Zhang1Yunqin Li2School of Landscape Architecture, Nanjing Forestry University, Nanjing 210037, ChinaDivision of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University, Osaka 5620031, Japan; Architecture and design college, Nanchang University, No. 999, Xuefu Avenue, Honggutan New District, Nanchang 330031, China; Corresponding author.Division of Sustainable Energy and Environmental Engineering, Graduate School of Engineering, Osaka University, Osaka 5620031, Japan; Architecture and design college, Nanchang University, No. 999, Xuefu Avenue, Honggutan New District, Nanchang 330031, ChinaLandscape pattern significantly impacts habitat quality, especially in cities undergoing rapid urbanization, where landscape patterns are changing dramatically. However, the spatial and temporal driving mechanisms of landscape pattern on habitat quality are still unclear, and the proposed methods of Geographically and Temporally Weighted Regression (GTWR) and Multiscale Geographic Weighted Regression (MGWR) provide possibilities for the exploration of these mechanisms. This study was conducted in Nanjing from 2001 to 2020. Landscape pattern indices indicating aggregation, connectivity, diversity and compactness were calculated using Fragstats from 2001 to 2020. The habitat quality was computed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model. By combining two new spatial measurement models, GTWR and MGWR, the spatial and temporal driving mechanisms of landscape patterns on habitat quality were explored. The results show that (1) as Nanjing’s land under construction has expanded, habitat quality has decreased significantly, and the overall landscape pattern has fluctuated drastically. (2) GTWR and MGWR are well-suited to such analysis and provide important insights. (3) Overall, aggregation and compactness were negatively associated with habitat quality in areas of low-quality habitat. Increased connectivity on low habitat substrates had a positive effect on habitat. The increase of diversity in proximity had a positive effect on habitat, while the opposite was true in high habitat zones. (4) As the urbanization level increases, the negative effects of aggregation expand, as do the positive effects of connectivity and diversity. (5) The extent of influence of landscape pattern effects are ranked from largest to smallest: compactness, diversity, connectivity, and aggregation, while the intensity of effects is reversed. Based on these findings, a reference point for urban planners is provided to plan urban landscape patterns in a sustainable and rational manner. It also provides a new means of integrating GTWR and MGWR into the study of landscape ecology.http://www.sciencedirect.com/science/article/pii/S1470160X22008068Landscape patternHabitat qualityGeographically and temporally weighted regressionMultiscale geographic weighted regressionUrbanizationDriving mechanism |
| spellingShingle | Jinyu Hu Jiaxin Zhang Yunqin Li Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China Ecological Indicators Landscape pattern Habitat quality Geographically and temporally weighted regression Multiscale geographic weighted regression Urbanization Driving mechanism |
| title | Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China |
| title_full | Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China |
| title_fullStr | Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China |
| title_full_unstemmed | Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China |
| title_short | Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China |
| title_sort | exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on gtwr and mgwr the case of nanjing china |
| topic | Landscape pattern Habitat quality Geographically and temporally weighted regression Multiscale geographic weighted regression Urbanization Driving mechanism |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X22008068 |
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