祁连山南坡土地利用变化及碳储量研究

doi:10.16258/j.cnki.1674-5906.2024.09.003

生态环境学报 ›› 2024, Vol. 33 ›› Issue (9): 1353-1361.DOI: 10.16258/j.cnki.1674-5906.2024.09.003

祁连山南坡土地利用变化及碳储量研究

唐建亭¹(), 袁杰¹^,²^,^*(), 陈宗颜¹^,², 李晓燕¹, 孙子婷¹

1.青海师范大学地理科学学院/青藏高原地表过程与生态保育教育部重点实验室/青海省自然地理与环境过程重点实验室，青海西宁 810008
2.青海省人民政府-北京师范大学高原科学与可持续发展研究院，青海西宁 810008

收稿日期:2024-05-23 出版日期:2024-09-18 发布日期:2024-10-18
通讯作者: ^*袁杰。E-mail: yuanjie8903@126.com
作者简介:唐建亭（1999年生），男，硕士研究生，研究方向为地表环境过程。E-mail: 985903468@qq.com
基金资助:
青海省自然科学基金项目(2023-ZJ-907M);青海省“昆仑英才·高端创新创业人才”计划项目(青人才字[2023]01号);青海省“高端创新人才千人计划”(青人才字[2019]06号)

Study on Land Use Change and Carbon Stock on the South Slope of Qilian Mountains

TANG Jianting¹(), YUAN Jie¹^,²^,^*(), CHEN Zongyan¹^,², LI Xiaoyan¹, SUN Ziting¹

1. School of Geography Science, Qinghai Normal University/Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation (Ministry of Education)/Qinghai Provincial Key Laboratory of Physical Geography and Environmental Process, Xining 810008, P. R. China
2. Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province & Beijing Normal University, Xining 810008, P. R. China

Received:2024-05-23 Online:2024-09-18 Published:2024-10-18

摘要/Abstract

摘要：

祁连山区域作为中国西北地区的生态过渡带，其陆地生态系统具有巨大的固碳能力。了解土地利用和碳储量变化并预测其时空演变格局，可为生态固碳提供参考，对优化区域国土空间规划措施和维护生态环境可持续发展具有重要意义。以祁连山南坡为例，基于2000、2010和2020年3期土地利用数据，运用GIS技术分析2000－2020年研究区土地利用变化，在此基础上，利用CA-Markov模型和InVEST模型，通过实地调查与当地政策相结合，选取高程、坡度、坡向、距道路距离、适宜开发性等作为影响性因子，预测2030年研究区土地利用变化下的碳储量格局。结果表明，1）研究区2000－2020年土地利用类型以草地为主，并逐年减少，其次为裸地和林地，建设用地面积最小。同时各用地类型均在发生相互转化，在空间上具有可逆性。在土地利用变化上，建设用地土地利用动态度最快，表明该地区研究时段内城建面积扩张迅速。2）利用CA-Markov模型对研究区2030年土地利用变化进行预测模拟，预测精度Kappa值88.9%，表明该预测模拟在复杂的祁连山区可行。预测显示，2030年祁连山南坡土地利用以草地、裸地和林地为主。耕地、林地、建设用地、湿地和裸地均呈增加趋势，草地呈现减少趋势。3）估算研究区2000、2010和2020年的碳储量分别为4.03×10⁸、4.13×10⁸、4.22×10⁸t。2030年碳储量将达到4.49×10⁸ t，较2020年增长6.40%，碳储量呈稳步增加趋势，主要原因是林地及湿地的扩张，使碳储量的净固持量大于了净释放量，有利于碳的固存。该研究可为祁连山生态环境治理和土地利用管理决策提供科学依据。

关键词: 祁连山南坡, 土地利用, 碳储量, CA-Markov模型, InVEST模型

Abstract:

The Qilian Mountains region in Northwest China is an ecological transition zone with enormous potential for sequestering carbon in its terrestrial ecosystems. For the purpose of ecological carbon sequestration, it is important to comprehend how land use and the carbon stock are changing and to predict the patterns of their spatial and temporal evolution, which is great significance for optimising regional territorial spatial planning measures and maintaining sustainable ecological environment development. Taking the south slope of Qilian Mountains as an example, based on the land use datas of 2000, 2010 and 2020, we used GIS technology to analyse the land use changes in the study area from 2000 to 2020, and based on this, we used CA-Markov model and InVEST model, and selected elevation, slope, carbon stock and carbon stock changes by combining the field survey and local policies. On this basis, the CA-Markov model and InVEST model were used to predict the carbon storage pattern under land use change in the study area in 2030 by combining field investigation and local policies, and selected elevation, slope, aspect, distance from road, and suitable development as influencing factors. The results show: 1) From 2000 to 2020, grassland is the main land use type in the study area, and it decreases year by year, followed by bare land and forest land, and the area of construction land is the smallest. At the same time, all land use types are transforming into each other and are spatially reversible. In terms of land use change, the land use of construction land is the fastest, indicating that the urban construction area expands rapidly during the study period. 2) The CA-Markov model was used to predict and simulate the land use change in the study area in 2030, and the Kappa value of the prediction accuracy is 88.9%, which indicates that the prediction and simulation is feasible in the complex Qilian Mountain area. The prediction shows that in 2030, the land use on the south slope of Qilian Mountains will be dominated by grassland, bare land and forest land. Cultivated land, forest land, construction land, wetland and bare land all show an increasing trend, and grassland shows a decreasing trend. 3) The carbon stock in the study area in 2000, 2010 and 2020 is estimated to be 4.03×10⁸, 4.13×10⁸ and 4.22×10⁸ t. The carbon stock in 2030 will be 4.49×10⁸ t, which is an increase of 6.40% compared with that of 2020, and the stock shows a steady increasing trend, the main reason is the expansion of woodland and wetland, so that the net sequestration of carbon stock is larger than the net release, which is conducive to carbon sequestration. This study can provide scientific basis for the ecological environment management and land use management decision in Qilian Mountains.

Key words: the south slope of Qilian Mountains, land use, carbon storage, CA-Markov model, InVEST model

中图分类号:

X144

唐建亭, 袁杰, 陈宗颜, 李晓燕, 孙子婷. 祁连山南坡土地利用变化及碳储量研究[J]. 生态环境学报, 2024, 33(9): 1353-1361.

TANG Jianting, YUAN Jie, CHEN Zongyan, LI Xiaoyan, SUN Ziting. Study on Land Use Change and Carbon Stock on the South Slope of Qilian Mountains[J]. Ecology and Environment, 2024, 33(9): 1353-1361.

图/表 12

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土地利用类型及数据来源	碳密度/(t∙hm⁻²)
土地利用类型及数据来源	地上部	地下部	土壤	死亡有机物
耕地 (Zhu et al., 2021)	4.56	7.45	64.39	0
林地 (宋洁等, 2021; Zhao et al., 2019)	40.72	23.20	408.02	6.52
草地 (Zhao et al., 2019)	0.86	5.38	148.95	1.29
建设用地	0	0	0	0
湿地 (Zhu et al., 2021)	0	0	249.71	0
裸地 (Zhao et al., 2019)	0.63	4.95	111.10	0

土地利用类型及数据来源	碳密度/(t∙hm⁻²)
土地利用类型及数据来源	地上部	地下部	土壤	死亡有机物
耕地 (Zhu et al., 2021)	4.56	7.45	64.39	0
林地 (宋洁等, 2021; Zhao et al., 2019)	40.72	23.20	408.02	6.52
草地 (Zhao et al., 2019)	0.86	5.38	148.95	1.29
建设用地	0	0	0	0
湿地 (Zhu et al., 2021)	0	0	249.71	0
裸地 (Zhao et al., 2019)	0.63	4.95	111.10	0

土地利用类型	影响因子
土地利用类型	高程/m	影响函数	坡度/(°)	影响函数	坡向/(°)	影响函数	适宜开发性	道路距离/m
耕地	2500‒3400	Signmoidal递减	5‒14	J-shaped递减				≤3000
林地	3100‒3800	Signmoidal递减	15‒41	Signmoidal递减	157‒248	J-shaped递减	现有地禁止变动
草地	2700‒4700	Signmoidal递减	5‒35	J-shaped递减
建设用地	2257‒3800	Signmoidal递减	0‒10	Signmoidal递减			现有地禁止变动	≤3000
湿地	禁止转换		禁止转换		禁止转换		禁止转换	禁止转换
裸地	2257‒3800	Signmoidal递减	0‒10	Signmoidal递减
冰川和永久积雪	禁止转换		禁止转换		禁止转换		禁止转换	禁止转换

土地利用类型	影响因子
土地利用类型	高程/m	影响函数	坡度/(°)	影响函数	坡向/(°)	影响函数	适宜开发性	道路距离/m
耕地	2500‒3400	Signmoidal递减	5‒14	J-shaped递减				≤3000
林地	3100‒3800	Signmoidal递减	15‒41	Signmoidal递减	157‒248	J-shaped递减	现有地禁止变动
草地	2700‒4700	Signmoidal递减	5‒35	J-shaped递减
建设用地	2257‒3800	Signmoidal递减	0‒10	Signmoidal递减			现有地禁止变动	≤3000
湿地	禁止转换		禁止转换		禁止转换		禁止转换	禁止转换
裸地	2257‒3800	Signmoidal递减	0‒10	Signmoidal递减
冰川和永久积雪	禁止转换		禁止转换		禁止转换		禁止转换	禁止转换

土地利用类型	耕地	林地	草地	建设用地	湿地	裸地	冰川和永久积雪
耕地	45204.48	128.88	1321.2	3094.38	233.19	5.58	0
林地	52.74	60232.5	15616.08	0	59.13	677.43	34.56
草地	10160.28	90917.57	1862377.02	6957.63	19065.96	165137.85	35155.26
建设用地	191.88	0	47.52	2118.69	8.46	0.81	0
湿地	360	134.82	12169.62	119.43	15458.22	106.74	71.01
裸地	10.35	846	7607.79	3.6	9.81	11271.96	1648.26
冰川和永久积雪	0	553.14	3929.58	0	0	3115.8	32909.94

祁连山南坡土地利用变化及碳储量研究

Study on Land Use Change and Carbon Stock on the South Slope of Qilian Mountains

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图/表 12

参考文献 31

相关文章 15

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检测项	值域
Chi square	360274368
df	49
P-Level	0
Cramer’V	0.6798
Overall kappa	0.8899

土地利用类型	2020年现状面积/hm²	占比/ %	2030年预测面积/hm²	占比/ %	增幅/ %
耕地	55979.73	2.32	67777.02	2.81	21.1
林地	152612.91	6.34	253840.86	10.5	66.3
草地	1903068.81	79.0	1631786.22	67.7	−14.3
建设用地	12293.73	0.51	33933.42	1.41	176
湿地	34834.77	1.45	46527.66	1.93	33.6
裸地	180316.17	7.49	288778.95	12.0	60.2
冰川和永久积雪	69819.03	2.90	86193	3.58	23.5

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