广东省农田生态系统碳源汇效应时空分异及驱动因素

宾津佑; 唐小兵

doi:10.13961/j.cnki.stbctb.2023.03.043

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广东省农田生态系统碳源汇效应时空分异及驱动因素

试验研究

- 广东省农田生态系统碳源汇效应时空分异及驱动因素
- Spatio-temporal Differentiation and Driving Factors of Farmland Ecosystem Carbon Source-Sink Effects in Guangdong Province
- 水土保持通报 2023年43卷第3期页码：382-389
- 作者机构：
  
  1. 广东海洋大学管理学院,广东,湛江,524088
  2. 广东沿海经济带发展研究院,广东,湛江,524088
  3. 湖南省社会科学院,湖南,长沙,410003
- 作者简介：
- 基金信息：
  
  广东省哲学社会科学规划项目“广东沿海经济带海洋资源环境经济系统承载力及协调发展研究”(GD19YYJ03);湖南省社会科学院(湖南省人民政府发展研究中心)哲学社会科学创新工程资助项目“数字乡村发展、农户种植决策与农业碳排放”(23ZFH20)
- DOI：10.13961/j.cnki.stbctb.2023.03.043
  中图分类号： X22;S181
- 纸质出版：2023
- 稿件说明：
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宾津佑, 唐小兵. 广东省农田生态系统碳源汇效应时空分异及驱动因素[J]. 水土保持通报, 2023,43(3):382-389.

Bin Jinyou, Tang Xiaobing. Spatio-temporal Differentiation and Driving Factors of Farmland Ecosystem Carbon Source-Sink Effects in Guangdong Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 382-389.
宾津佑, 唐小兵. 广东省农田生态系统碳源汇效应时空分异及驱动因素[J]. 水土保持通报, 2023,43(3):382-389. DOI： 10.13961/j.cnki.stbctb.2023.03.043.

Bin Jinyou, Tang Xiaobing. Spatio-temporal Differentiation and Driving Factors of Farmland Ecosystem Carbon Source-Sink Effects in Guangdong Province[J]. Bulletin of Soiland Water Conservation, 2023, 43(3): 382-389. DOI： 10.13961/j.cnki.stbctb.2023.03.043.

摘要

[目的] 探究广东省农田生态系统碳源汇效应时空分异及驱动因素，为广东省科学合理制定区域农业减排固碳措施提供参考。[方法] 采用参数估计法、GIS空间分析等方法定量评估2010—2020年广东省农田生态系统碳源汇效应时空演变规律，并借助LMDI因素分解模型探究农田生态系统碳源汇效应空间分异的驱动因素。[结果] ①广东省农田生态系统碳源汇效应水平维持持续向好发展态势，减排增汇效应逐渐凸显。具体表现为：固碳总量呈波动上升态势，稻谷、甘蔗、蔬菜为主要的碳汇作物；碳排放得到有效控制，减排效应日益显现，稻田种植、农资投入为主要的碳源类型；农田生态系统固碳量增长有效抵消了碳排放增长。②广东省农田生态系统碳源汇效应空间分异明显，总体呈相对集聚分布态势，湛江为主要的高碳源—高碳汇地区，低碳源—低碳汇则主要分布在珠三角地区。③经济因素为农田生态系统碳汇提升的关键驱动因素，结构因素表现出两面性且因地而异，效率因素、劳动力因素则表现为抑制作用。[结论] 广东省农田生态系统碳源汇效应水平稳中向好，但区域分异明显，应结合各地经济、结构、效率、劳动力等因素的驱动效应差异，因地制宜制定农业减排固碳措施。

Abstract

[Objective] The spatio-temporal differentiation and driving factors of farmland ecosystem carbon source-sink effects in Guangdong Province were analyzed in order to provide a valuable reference for the scientific and rational formulation of regional agricultural carbon reduction and carbon sequestration measures in the region.[Methods] Quantitative assessment of the spatial-temporal distribution of carbon source-sink effects in farmland ecosystems in Guangdong Province from 2010 to 2020 was conducted by using the parameter estimation method and GIS spatial analysis. The driving factors of spatial differentiation of the carbon source-sink effect in farmland ecosystems were determined by using the LMDI factor decomposition model.[Results] ① The level of carbon source-sink effects in Guangdong Province farmland ecosystems continued to maintain a good

positive development trend

and the effects of reducing emissions and sequestering carbon gradually became prominent. Specifically

the total carbon sequestration fluctuated and increased

and rice

sugarcane

and vegetables were the main carbon sources. Carbon emissions were effectively controlled

and the effect of reducing emissions was becoming increasingly evident. Rice planting and agricultural inputs were the main carbon sources. Moreover

the growth of carbon sequestration in farmland ecosystems effectively offset the growth of carbon emissions. ② The spatial heterogeneity of carbon source-sink effects of farmland ecosystems was obvious

and the overall distribution was relatively clustered. Zhanjiang was the main high-carbon source-high-carbon sink area

while low-carbon source-low-carbon sink areas were mainly found in the Pearl River Delta region. ③ Economic factors were the key driving force causing increased carbon sequestration in farmland ecosystems

while structural factors exhibited inconsistent responses and varied with their locations. Efficiency factors and labor force factors

on the other hand

had a restraining effect.[Conclusion] The carbon source-sink effect of farmland ecosystems in Guangdong Province exhibited a continuous increasing trend overall

but there were significant regional differences. Therefore

measures to reduce emissions and sequester carbon in agriculture should be tailored to local conditions

taking into account the differences in the driving effects of economic

structural

efficiency

and labor force factors in each region.

关键词

Keywords

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