Spatiotemporal change of habitat quality in Hainan Island of China based on changes in land use

Lei, Jinrui; Chen, Yiqing; Li, Linming; Chen, Zongzhu; Chen, Xiaohua; Wu, Tingtian; Li, Yuanling

doi:10.1016/j.ecolind.2022.109707

Cited by 55 publications

(31 citation statements)

References 28 publications

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“…The typical probability is represented by the P-value of Getis-Ord G * i index. 0.01, 0.05, and 0.1 correspond to 99, 95, and 90% of the typical confidence intervals, respectively, indicating the degree of aggregation and differentiation of spatial units' hot spots or cold spots (Lei et al, 2022a).…”

Section: Basin Vector Boundary Datamentioning

confidence: 98%

“…The land use types were categorized into six primary and 20 secondary types according to the national land use classification system based on remote sensing monitoring, including cropland, forestland, grassland, water land, built land, and unused land. After that, the data was converted to grid data (30 × 30 m), with a classification accuracy above 90% (Lei et al, 2022a).…”

Section: Type Data Acquisition and Preprocessingmentioning

confidence: 99%

“…describe the spatial aggregation and anomaly of the spatial distribution pattern of visualized things or phenomena (Lei et al, 2022a). This analysis method is frequently employed in investigating water-related ecosystem services (Yang J. et services in the three major basins.…”

Section: Basin Vector Boundary Datamentioning

confidence: 99%

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Spatial-temporal evolution and driving factors of water yield in three major drainage basins of Hainan Island based on land use change

Lei¹,

Zhang²,

Wu³

et al. 2023

Front. For. Glob. Change

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Tropical rainforests in the central hilly section of Hainan Island are the source of the Nandu, Changhua, and Wanquan rivers, which are crucial for water conservation and ecological protection. The quantitative assessment of water yield in the three basins is beneficial for developing regional water resource protection plans, establishing ecological compensation mechanisms, and maintaining ecological balance. Based on land use data from five periods between 1980 and 2020, this paper adopts the InVEST model and geographic detectors to investigate the spatial-temporal variation characteristics and driving factors of water yield in three major basins of Hainan Island. The results demonstrate that forestland, which makes up more than 70% of the total area in the three basins of Hainan Island, is the predominant land use type. With a depth of 1269.18 mm, Wanquan Basin is the deepest of the three basins, followed by Nandu Basin and Changhua Basin. The total water yield of three basins shows a slightly decreasing trend from 17.991 billion m3 in 1980 to 17.864 billion m3 in 2020. The spatial distribution of water yield is high in the southeast region and low in the northwest region, with strong autocorrelation and significant aggregation. According to geographic detection, land use type is the dominant factor for the spatial differentiation of water yield in the three basins, with a contribution rate of 0.563, and soil type and annual precipitation are important impact factors. The interaction and synergy of soil types and land use types jointly affect the spatial differentiation of water yield in the basin. The results of this study can provide data support and scientific references for biodiversity conservation and ecosystem restoration in the three major basins of Hainan Island.

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Section: Basin Vector Boundary Datamentioning

confidence: 98%

Section: Type Data Acquisition and Preprocessingmentioning

confidence: 99%

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Spatial-temporal evolution and driving factors of water yield in three major drainage basins of Hainan Island based on land use change

Lei¹,

Zhang²,

Wu³

et al. 2023

Front. For. Glob. Change

Self Cite

View full text Add to dashboard Cite

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“…Based on the relevant literature (Wang et al, 2023;Zhao et al, 2022b;Lei et al, 2022;Yang et al, 2021), distance of maximum influence, weight of the threat variables, the type of spatial attenuation, and the sensitivity of each land use type to the threat variables are the primary parameters that need to be adjusted in accordance with the unique circumstances of the research area. Taking into consideration the specific development of Shenzhen, this study defines the artificial surface that have a threatening effect on surface habitats, bare land and cultivated land as threat factors.…”

Section: The Invest Modelmentioning

confidence: 99%

Habitat quality evolution characteristics and multi-scenario prediction in Shenzhen based on PLUS and InVEST models

Wang

Gou

2023

Front. Environ. Sci.

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Based on the PLUS model, research proposed a method to adjust the probability of land use transition to reduce the calculation error of the number of pixels. The refined algorithm is applied to simulate Shenzhen land use situation in 2030 under a progressive scenario using three periods of Shenzhen land use data in 2000, 2010 and 2020. Then, InVEST model was employed to evaluate the distribution situation and future trends of habitat quality in Shenzhen during the study period. Following are the conclusions: 1) The construction land in Shenzhen expanded rapidly and the ecological land gradually shrank during the research period. The proportion of artificial surface area increased by about 45.4% (304.98 km2) within 20 years. 2) By simulating the land use situation of Shenzhen in 2030, the results revealed that the land use change of Shenzhen in the future is mainly concentrated in the central and western regions. 3) The overall average habitat quality of Shenzhen was at a medium level, but the habitat quality showed a continuous degradation trend in each year throughout the study period. Spatially, the habitat quality degradation are mainly concentrated in Shenzhen’s central and western region. 4) Under the natural development scenario, Shenzhen’s habitat quality would experience a sharp decline by 2030. The habitat quality of the conservation area is guaranteed to a certain degree, but the artificial surface expansion outside the area will still affect the habitat quality in the boundary constraint scenario; Only in scenario of ecological priority, the habitat quality of Shenzhen has been restored and improved to a large extent. 5) In order to slow down the degradation trend and improve the regional ecological environment. It is necessary not only to strictly implement various protection boundaries delineated in the context of Territorial Spatial Planning, but also to implement the policy of “Clear waters and green mountains are as good as mountains of gold and silver” in the process of urban development. Government should reasonably control the scale of cities, optimize the ecological compensation mechanism, and implement ecological restoration policies such as returning farmland to forests and returning farmland to grassland.

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“…The study area is an important ecological reserve and food supply area, and its ecological safety and biodiversity should be ensured. Therefore, in order to better promote the ecological governance process of the floodplain area in the future, specifically, we aim to address the following questions in this study [ [28] , [29] , [30] , [31] ]. How did the spatial-temporal changes of land use types and habitat quality in the floodplain area from 2000 to 2020?…”

Section: Introductionmentioning

confidence: 99%

Spatial pattern evolution and prediction scenario of habitat quality in typical fragile ecological region, China: A case study of the Yellow River floodplain area

Zhao

Tang

et al. 2023

Heliyon

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Spatiotemporal change of habitat quality in Hainan Island of China based on changes in land use

Cited by 55 publications

References 28 publications

Spatial-temporal evolution and driving factors of water yield in three major drainage basins of Hainan Island based on land use change

Spatial-temporal evolution and driving factors of water yield in three major drainage basins of Hainan Island based on land use change

Habitat quality evolution characteristics and multi-scenario prediction in Shenzhen based on PLUS and InVEST models

Spatial pattern evolution and prediction scenario of habitat quality in typical fragile ecological region, China: A case study of the Yellow River floodplain area

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