基于PLUS-InVEST模型的新疆碳储量时空演变与预测

doi:10.13866/j.azr.2025.09.15

Abstract

Abstract:

Under the “dual carbon” background, exploring the spatiotemporal evolution of carbon storage and future scenario predictions is of great significance for maintaining ecological balance, promoting high-quality regional development, and achieving the goal of “carbon neutrality.” As an ecologically fragile and climate-sensitive region, simulating past and future land use changes and carbon storage in Xinjiang can support the effective simulation of emission reduction strategies and ecosystem restoration efforts. This study, based on the sustainable development theory, integrates the PLUS-InVEST model to comprehensively assess land use changes and their impact on carbon storage in Xinjiang from 1990 to 2050. The main findings are summarized as follows. (1) From 1990 to 2020, the land use in Xinjiang was primarily composed of unused land and grassland, accounting for over 67% and 23% of the total land area, respectively. Both categories showed a decreasing trend, while other land types exhibited an increasing trend. (2) Grassland is the primary contributor to carbon storage in Xinjiang, and its degradation is the main cause of carbon storage loss. Between 1990 and 2020, grassland degradation resulted in a carbon storage loss of 224.16 t. (3) By 2050, under the ecological protection scenario, carbon storage is expected to increase by 6.19×10⁷ t. in contrast, under the economic priority scenario, it is projected to decrease by 3.52× 10⁷ t. Through a quantitative evaluation of 30 years of past and projected future land use changes and their impacts on carbon storage, this study provides reliable reference materials and accurate data support for Xinjiang's land management decision-making.

Key words: land use change, carbon storage, PLUS model, InVEST model

ZHANG Kun, WU Xinping, LIU Yongqiang, ZHANG Lifang, QIN Yan, YANG Yulu, GAN Hui. Spatiotemporal evolution and prediction of carbon storage in Xinjiang using the PLUS-InVEST model[J].Arid Zone Research, 2025, 42(9): 1715-1725.

Figures/Tables 11

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References 33

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数据类型	数据名称	分辨率	数据来源
土地利用数据	CLCD	30 m×30 m	武汉大学（https://zenodo.org）
社会经济因子	GDP	1 km×1 km	资源环境科学与数据中心（https://www.resdc.cn）
社会经济因子	人口数据	1 km×1 km	资源环境科学与数据中心（https://www.resdc.cn）
距离因子	到城市距离	1 km×1 km	OpenStreetMap （https://www.openstreetmap.org/）
	到水域距离	1 km×1 km
	到车站距离	1 km×1 km
	到高速公路距离	1 km×1 km
	到主干道路距离	1 km×1 km
	到次干道路距离	1 km×1 km
自然因子	年均降水	1 km×1 km	资源环境科学与数据中心（https://www.resdc.cn）
	年均气温	1 km×1 km
	土壤类型	1 km×1 km
	DEM	30 m×30 m	地理空间数据云（http://www.gscloud.cn）
	坡度	30 m×30 m
	坡向	30 m×30 m

土地利用类型	地上碳密度	地下碳密度	土壤碳密度
耕地	1.32	14.21	80.22
林地	36.32	20.67	137.12
草地	7.49	13.33	73.93
水域	2.92	0	0
建设用地	3.26	2.09	15.67
未利用地	2.82	1.25	30.84

发展情景	地类	耕地	林地	草地	水域	建设用地	未利用地
自然发展	耕地	1	0	1	0	0	0
	林地	1	1	0	0	0	0
	草地	1	1	1	1	1	1
	水域	1	0	1	1	1	1
	建设用地	0	0	0	1	1	0
	未利用地	1	0	1	1	1	1
生态保护	耕地	1	1	1	1	0	1
	林地	0	1	1	0	0	0
	草地	0	1	1	0	0	0
	水域	1	1	1	1	0	1
	建设用地	1	1	1	1	1	1
	未利用地	1	1	1	1	0	1
经济优先	耕地	1	0	0	0	1	0
	林地	0	1	0	0	1	0
	草地	0	0	1	0	1	0
	水域	0	0	0	1	1	1
	建设用地	0	0	0	0	1	0
	未利用地	0	0	0	0	1	1

土地利用类型	碳储量/t
	1990年	2000年	2010年	2020年	2050年
	1990年	2000年	2010年	2020年	自然发展情景	生态保护情景	经济优先情景
耕地	496.04	540.85	677.02	759.02	934.71	702.54	730.46
林地	192.75	270.06	317.92	336.50	384.89	385.50	337.51
草地	3423.11	3348.20	3309.66	3198.95	2977.34	3263.36	3182.21
水域	3.97	3.89	4.55	4.21	4.02	3.64	3.78
建设用地	0.23	0.65	1.62	2.66	3.17	1.52	5.52
未利用地	2009.72	2008.98	1968.61	1976.51	1985.84	1985.82	1985.86

Spatiotemporal evolution and prediction of carbon storage in Xinjiang using the PLUS-InVEST model

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