Ecological health analysis of wetlands in the middle reaches of Yangtze River under changing environment

Figures & data

Figure 1. Study area map.

Table 1. Driving data sources.

	Data/Maps	Year	Resolution	Sources
Historical Drive Data	Elevation	2013	30m	https://search.earthdata.nasa.gov/
	Lakes	2015		https://www.webmap.cn/
	Roads	2020		https://www.openstreetmap.org/
	Highway	2020		https://www.openstreetmap.org/
	Railroad	2020		https://www.openstreetmap.org/
	Government			https://lbsyun.baidu.com/
	Gross Domestic Product (GDP)	2015	1km	https://www.resdc.cn/
	Number of Population (POP)	2015	1km	https://www.resdc.cn/
	Soil type		1km	https://www.resdc.cn/
	Precipitation	2015	1km	https://www.resdc.cn/
	Temperature	2015	1km	https://www.resdc.cn/
Multi-Scenario Driven Data	GDP and POP		0.5°×0.5°	Jiang et al. (2022)
	Temperature and precipitation		0.5°×0.5°	https://esgf-node.llnl.gov/search/cmip6/

Figure 2. Proportion of wetlands in historical period in the MYRB based on the remote sensing images.

Figure 3. Area and density index in historical period in the MYRB based on the remote sensing images.

Figure 4. Historical wetland landscape connectivity index in the MYRB based on the remote sensing images.

Figure 5. Historical RSEI in the MYRB based on the remote sensing images.

Figure 6. Proportion of wetlands under different scenarios in the future in the MYRB based on the PLUS.

Figure 7. Area and density index under different scenarios in the MYRB based on the simulation of PLUS.

Figure 8. Wetland connectivity index in the MYRB under different scenarios in the future.

Table 2. RF classification method training and test accuracy.

Classifier	Training Score	Testing Score
RF	0.9857	0.9200

Figure 9. Importance of future simulation features.

Figure 10. Future simulation RSEI.

Jiang, T., B. Su, Y. Wang, et al. 2022. “Shared Socioeconomic Pathways (SSPs) Demographic and Economic Gridded Dataset.” Advances in Climate Change Research 18: 381–383. http://doi.org/10.12006/j.issn.1673-1719.2022.106.

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