浑善达克沙地植被变化定量归因及多情景预测

doi:10.12118/j.issn.1000-6060.2022.302

Abstract

Abstract:

In the context of future global warming, the vegetation in arid and semi-arid regions in China is more sensitive, and the balance between economic development and environmental protection remains challenging. Therefore, it is essential to conduct dynamic monitoring and driving factors assessment of vegetation in those areas. In this study, the spatiotemporal variation of NDVI in Otindag Sandy Land from 2000 to 2020 was first analyzed using Theil-Sen median trend analysis; next, the driving mechanism of NDVI change was analyzed using the Geodetector model. Finally, multiscenario analysis was used to reveal the future change trajectories of vegetation in the area. The results showed that the NDVI of Otindag Sandy Land exhibited upward fluctuation trends within 20 years, and grazing is the main factor affecting the changes in NDVI in Otindag Sandy Land; however, the effect of grazing to NDVI dynamics in the Otindag Sandy Land gradually weakened. In addition, the multiscenario prediction results show that, although the vegetation of Otindag Sandy Land is developing toward restoration, its fragile ecological environment and the vegetation status were still threatened by human activities and climate change. This study provides a theoretical basis for the Otindag Sandy Land ecological construction and restoration, as well as relevant countermeasures and suggestions according to the actual situation.

Key words: trend analysis, geodetector, multi-scenario prediction, NDVI, Otindag Sandy Land

LUO Jiayan, ZHANG Jing, XU Mengran, MO Yu, TONG Liga. Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land[J].Arid Land Geography, 2023, 46(4): 614-624.

Figures/Tables 9

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References 49

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类型I	类型II	指标	代码
自然因素	气候	年均温/℃	TEM
		年降水量/mm	PRE
		年均风速/m·s^-1	WND
	地形	高程/m	ELEV
		坡度/(°)	SLP
		坡向/(°)	ASP
	土壤	土壤类型	SOIL
	植被	植被类型	VGT
人类活动		土地利用类型	LUC
		人口密度/人·km^-2	POP
		牲畜数量/头	SHEEP

情景	情景名称	情景变化参数
惯性发展情景	惯性发展	驱动因子不做处理，遵循NDVI的惯性发展规律
气候变化情景¹	降水增多	调整降水值，将降水的值总体提升25%，其余因子不做处理
	降水降低	调整降水值，将降水的值总体降低25%，其余因子不做处理
	风速提高	调整风速值，将风速的值总体提升25%，其余因子不做处理
	风速降低	调整风速值，将风速的值总体降低25%，其余因子不做处理
经济优先情景²	放牧压力增加	调整牲畜数量，将牲畜数量的值总体提升50%，其余因子不做处理
生态保护情景²	放牧压力减少	调整牲畜数量，将牲畜数量的值总体降低50%，其余因子不做处理

年份	因子
年份	TEM	PRE	WND	ELEV	SLP	ASP	SOIL	VGT	LUC	POP	SHEEP
2001—2005	0.09	0.54	0.53	0.49	0.08	0.04	0.25	0.08	0.14	0.05	0.74
2006—2010	0.12	0.49	0.50	0.42	0.09	0.04	0.25	0.07	0.14	0.02	0.60
2011—2015	0.16	0.54	0.53	0.47	0.08	0.04	0.24	0.08	0.13	0.04	0.64
2016—2020	0.20	0.57	0.54	0.49	0.09	0.03	0.25	0.08	0.13	0.08	0.62

年份	情景	情景名称	植被覆盖区分级
年份	情景	情景名称	低度	较低	中等	较高	高度
2020	-	-	12034	10105	8531	5607	5469
2030（模拟）	惯性发展情景	惯性发展	10527	9141	9976	6916	5187
	气候变化情景	降水增多	7511	9141	9976	6794	8324
		降水降低	12305	10729	7992	5532	5188
		风速提高	12758	10227	7990	5760	5011
		风速降低	8933	9141	9976	6916	6780
	经济优先情景	放牧压力增加	12750	10267	7927	5499	5303
	生态保护情景	放牧压力减少	7249	9141	9976	6916	8464

Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land

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