基于PLUS模型的艾比湖流域景观生态风险分析及预测

doi:10.12118/j.issn.1000-6060.2024.320

Abstract

Abstract:

The evaluation of landscape ecological risk is an emerging interdisciplinary field combining geography and ecology, with significant importance for regional environmental assessment and land resource planning. This study focuses on the Ebinur Lake Basin, Xinjiang, China using remote sensing data on land use from 1990, 2000, 2010, and 2020 to quantitatively analyze dynamic land use changes over three decades. The landscape ecological risk index and geostatistical methods were applied to assess the degree and spatiotemporal variation of ecological risks in the basin. Additionally, the PLUS model was used to simulate and predict the spatial distribution of land use and ecological risks under multiple 2030 scenarios. The results revealed the following: (1) Grassland and bare land dominate the basin, covering over 70% of the area, while shrubland and wetlands occupy smaller areas. Between 1990 and 2020, farmland and impervious surfaces expanded significantly, while grassland area shrank, representing the main land use changes. (2) From 1990 to 2020, the global landscape ecological risk, indicated by the Moran index (Moran’s I), showed a significant positive trend, with risks increasing and exhibiting a clustering effect, following a spatial distribution pattern of “low at the edges, high in the center”. (3) By 2030, land use changes in the basin are expected to stabilize, with grassland and bare land remaining dominant. (4) The spatial distribution of ecological risks in 2030 under different scenarios aligns with historical trends. Among these scenarios, the ecological protection scenario is most effective at mitigating risks while balancing socioeconomic development, making it ideal for achieving sustainable development.

Key words: land use, landscape ecological risk, PLUS forecast, multi-scenario simulation, Ebinur Lake Basin

ZHANG Zihan, WANG Jinjie, DING Jianli, ZHANG Jinming, GE Xiangyu. Analysis and prediction of landscape ecological risk in Ebinur Lake Basin based on PLUS model[J].Arid Land Geography, 2025, 48(2): 308-322.

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数据类型	数据名称	数据来源
基础数据	土地利用数据	武汉大学黄昕教授团队制作的中国30 m分辨率年度土地覆盖产品，产品整体精度为79.31%（https://zenodo.org/records/4417810）
	行政边界数据	中国科学院资源环境与数据中心（https://www.resdc.cn/）
社会经济数据	人口	Worldpop（https://hub.worldpop.org/）
	GDP	中国科学院资源环境与数据中心（https://www.resdc.cn/）
	距一级道路距离	OpenStreetMap（https://www.openstreetmap.org） OpenStreetMap（https://www.openstreetmap.org） OpenStreetMap（https://www.openstreetmap.org） OpenStreetMap（https://www.openstreetmap.org） OpenStreetMap（https://www.openstreetmap.org）
	距二级道路距离
	距三级道路距离
	距铁路距离
	距高速距离
气候环境数据	高程	地理空间数据云（https://www.gscloud.cn/）
	坡度	地理空间数据云（https://www.gscloud.cn/）
	年降水量	中国科学院资源环境与数据中心（https://www.resdc.cn/）中国科学院资源环境与数据中心（https://www.resdc.cn/）中国科学院资源环境与数据中心（https://www.resdc.cn/）中国科学院资源环境与数据中心（https://www.resdc.cn/）
	年均气温
	土壤类型数据
	NDVI

土地利用类型	1990年		2000年		2010年		2020年
土地利用类型	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%
农田	3709.40	7.83	4678.50	9.87	6384.30	13.47	7383.80	15.58
森林	511.10	1.08	728.00	1.54	897.10	1.89	1039.02	2.19
灌木	0.09	0.00	0.01	0.00	0.01	0.00	0.05	0.00
草地	29115.40	61.45	27175.50	57.36	26707.50	56.37	25238.50	53.27
水域	1113.40	2.35	1268.30	2.68	1464.00	3.09	1512.10	3.19
冰川积雪	1390.90	2.94	1211.00	2.56	1300.10	2.74	1185.50	2.50
裸地	11514.10	24.30	12177.70	25.70	10238.40	21.61	10384.50	21.92
不透水地表	25.80	0.05	141.20	0.30	388.80	0.82	636.70	1.34
湿地	0.89	0.002	0.86	0.002	0.82	0.002	0.88	0.002

土地利用类型	单一土地利用动态度/%
土地利用类型	1990—2000年	2000—2010年	2010—2020年	1990—2020年
农田	2.61	3.65	1.57	3.30
森林	4.25	2.32	1.58	3.45
灌木	-7.97	-3.13	42.73	-0.89
草地	-0.67	-0.17	-0.55	-0.44
水域	1.39	1.54	0.33	1.19
冰川积雪	-1.29	0.74	-0.88	-0.49
裸地	0.57	-1.59	0.14	-0.33
不透水地表	45.15	17.53	6.38	79.54
湿地	-0.64	-0.49	0.72	-0.15

生态风险等级	1990年		2000年		2010年		2020年
生态风险等级	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%
低生态风险	8892.86	18.76	6970.40	14.71	6261.86	13.21	5659.81	11.94
较低生态风险	15431.70	32.56	16789.40	35.42	20668.50	43.60	20459.90	43.16
中等生态风险	10864.90	22.92	10391.70	21.92	7805.86	16.47	7793.12	16.44
较高生态风险	6997.43	14.76	7851.17	16.56	6700.01	14.13	7172.48	15.13
高生态风险	5213.46	11.00	5397.66	11.39	5964.09	12.58	6315.05	13.32

土地利用类型	自然发展情景		城镇发展情景		生态保护情景		耕地保护情景
土地利用类型	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%
农田	8250.15	17.41	8125.64	17.15	7344.16	15.50	8268.81	17.45
森林	1173.89	2.48	1173.78	2.48	1212.53	2.56	1173.92	2.48
灌木	0.06	0.00	0.05	0.00	0.05	0.00	0.07	0.00
草地	24008.80	50.67	23996.60	50.65	25515.40	53.85	24010.00	50.67
水域	1555.44	3.28	1555.06	3.28	1550.53	3.27	1555.46	3.28
冰川积雪	1235.62	2.61	1221.42	2.58	1212.16	2.56	1234.31	2.61
裸地	10401.40	21.95	10400.70	21.95	9883.60	20.86	10401.40	21.95
不透水地表	755.25	1.59	907.36	1.92	661.68	1.40	736.69	1.55
湿地	0.42	0.00	0.42	0.00	0.89	0.00	0.37	0.00

Analysis and prediction of landscape ecological risk in Ebinur Lake Basin based on PLUS model

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生态风险等级	自然发展情景		城镇发展情景		生态保护情景		耕地保护情景
生态风险等级	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%	面积/km²	占比/%
低生态风险	5977.28	12.61	5891.53	12.43	6088.50	12.84	5886.65	12.42
较低生态风险	20865.60	43.02	20957.40	44.21	20905.90	44.10	20921.70	44.14
中等生态风险	7705.54	16.26	7798.08	16.45	7883.72	16.63	7745.13	16.34
较高生态风险	6783.66	14.31	6759.80	14.26	6856.28	14.46	6752.29	14.25
高生态风险	6068.27	12.80	5993.57	12.64	5665.92	11.95	6094.58	12.86