Changes of ecological vulnerability under different wetland change patterns: A case study of the transboundary Heilongjiang (Amur) River Basin

doi:10.1016/j.regsus.2026.100351

Abstract

Abstract:

Wetlands are among the most biodiverse and productive ecosystems on the Earth, playing crucial roles in maintaining ecosystem services and achieving sustainable development goals. However, global wetlands have experienced dramatic declines and faced numerous ecological risks over recent decades. The Heilongjiang (Amur) River Basin (HARB) represents a critical wetland distribution area in the mid- and high-latitude zones of the Northern Hemisphere and is a globally significant transboundary river basin; however, it also faces risks of wetland degradation. In this study, we assessed the spatiotemporal dynamics of ecological vulnerability in the transboundary HARB under different wetland change modes (including expansion, stable, and degradation) during 1990-2020 using the exposure-sensitivity-adaptation framework. The Criteria Importance Through Intercriteria Correlation method and Analytic Hierarchy Process model were adopted to determine indicator weights; spatial autocorrelation analysis was used to identify spatial clustering patterns, and the GeoDetector model was employed to detect the core driving factors. The main results are as follows: (1) mean ecological vulnerability index (EVI) of the HARB increased from 30.50 in 1990 to 33.10 in 2000 and declined to 31.00 by 2020, and high EVI values were primarily located in the western and southern regions of the basin; (2) significant differences in EVI were found among China, Mongolia, and Russia, with Mongolia exhibiting the highest EVI, followed by China and then Russia; (3) soil conservation amount had the highest explanatory power, accounting for 63.18% of EVI variation, followed by net primary productivity and habitat quality index; and (4) compared with non-wetland areas, wetland areas exhibited significantly higher EVI, and wetland expansion areas also showed higher EVI than wetland stable and degradation areas. These findings provide a reference framework for evaluating wetland-related ecological vulnerability and offer valuable insights into the sustainable management of similar transboundary river basins worldwide.

Key words: Ecological vulnerability, Wetland change, Exposure-sensitivity-adaptation (ESA) framework, Ecological vulnerability index (EVI), Heilongjiang (Amur), River Basin

WANG Xinyuan, LI Fujia, CHENG Hao, Kirill GANZEY, Dashtseren AVIRMED, ZHAO Ruofan, CHEN Li, LEI Aohan. Changes of ecological vulnerability under different wetland change patterns: A case study of the transboundary Heilongjiang (Amur) River Basin[J]. Regional Sustainability, 2026, 7(3): 100351.

Figures/Tables 11

Fig. 1.

Table 1

Sources and details of the data utilized in this study."

Data name	Data source	Resolution	Time	Usage
Building area	Global Human Settlement (GHS) built-up surface grid (R2023) (Pesaresi et al., 2024)	1000 m	1990, 2000, 2010, and 2020	Building density
Population	GHS population grid (R2023) (Pesaresi et al., 2024)	1000 m	1990, 2000, 2010, and 2020	Population density
Precipitation	Terra Climate (Abatzoglou et al., 2018)	About 4638 m	Per month from 1980 to 2020	Extreme drought, extreme humidity, and soil conservation amount
Drought	Terra Climate (Abatzoglou et al., 2018)	About 4638 m	1990, 2000, 2010, and 2020	Palmer drought index (PDI)
Digital elevation model (DEM)	2020 Space Shuttle Radar Topographic Mission (SRTM) (Jarvis et al., 2008)	90 m	/	Elevation, terrain relief, and slope
Normalized difference vegetation index (NDVI)	The National Oceanic and Atmospheric Administration Climate Data Record of Advanced Very High Resolution Radiometer NDVI (Vermote and NOAA CDR Program, 2019)	About 5566 m	1990, 2000, 2010, and 2020	Fractional vegetation cover (FVC)
Net primary productivity (NPP)	National Ecological Science Data Center (Chen et al., 2019)	About 7000 m	1990, 2000, 2010, and 2019	NPP
Soil erodibility (K) factor	European Soil Data Centre (Gupta et al., 2024)	1000 m	/	Soil conservation amount
Land use	European Space Agency Climate Change Initiative Land Cover program (Copernicus Climate Change Service, 2019)	300 m	1992, 2000, 2010, and 2020	Habitat quality index (HQI)
Protected area distribution	The World Database on Protected Areas (https://www.protectedplanet.net/en/thematic-areas/wdpa?tab=WDPA)	Vector data	1990, 2000, 2010, and 2020	Proportion of protected areas
Wetland distribution	A global wetland map with a detailed classification system at a 30-m resolution (Zhang et al., 2023)	30 m	2000, 2005, 2010, 2015, and 2020	Wetland change patterns
Scope of Heilongjiang (Amur) River Basin (HARB)	Global Change Research Data Publishing & Repository (Huang et al., 2016)	Vector data	/	Study area
Scope of sub-basin of HARB	HydroBASINS (Lehner and Grill, 2013)	Vector data	/	Proportion of protected areas

Table 1

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Table 2

Fig. 3.

Fig. 4.

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Fig. 6.

Fig. 7.

Table 3

Fig. 8.

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Primary goal	General criteria (weight)	Specific criteria (weight)	Direction
Ecological vulnerability	Exposure (0.392)	Building density (0.108)	+
		Population density (0.102)	+
		Extreme drought (0.056)	+
		Extreme humidity (0.065)	+
		PDI (0.061)	+
	Sensitivity (0.417)	Elevation (0.056)	+
		Terrain relief (0.026)	+
		Slope (0.041)	+
		FVC (0.070)	-
		NPP (0.091)	-
		Soil conservation amount (0.133)	-
	Adaptability (0.191)	HQI (0.107)	-
	Adaptability (0.191)	Proportion of protected areas (0.084)	-

Region	Wetland change pattern	Mean value of EVI		Change value of EVI
Region	Wetland change pattern	2000-2010	2010-2020	2000-2010	2010-2020
HARB	Expansion	34.98	34.90	0.00	0.29
	Stable	34.26	34.76	-0.31	0.28
	Degradation	33.91	34.41	0.07	0.35
China	Expansion	37.35	36.87	0.36	-1.23
	Stable	36.15	35.87	0.36	-1.19
	Degradation	36.79	36.32	0.22	-1.62
Russia	Expansion	33.18	33.59	-0.16	1.34
	Stable	33.06	33.97	-0.04	1.33
	Degradation	32.35	33.22	-0.56	1.46