不同排放情景下中国西南地区碳汇时空格局及气候影响

鲁庆奥; 顾峰雪; 於琍; 牛保亮; 张远东; 刘世荣

doi:10.12356/j.2096-8884.2022-0021

不同排放情景下中国西南地区碳汇时空格局及气候影响

doi: 10.12356/j.2096-8884.2022-0021

1.
中国林业科学研究院森林生态环境与自然保护研究所，国家林业和草原局森林生态环境重点实验室，北京 100091
2.
中国农业科学院农业环境与可持续发展研究所，农业农村部旱作节水农业重点实验室，北京 100081
3.
中国气象局国家气候中心，北京 100081

基金项目: 国家重点研发计划课题（2021YFD2200401）；国家自然科学基金项目（31971460）

详细信息

作者简介:
鲁庆奥：E-mail: Antlers@caf.ac.cn

通讯作者:
E-mail: zyd@caf.ac.cn

中图分类号: P467
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- 被引次数: 0
出版历程
- 收稿日期: 2022-04-22
- 录用日期: 2022-06-27
- 网络出版日期: 2022-09-22
- 刊出日期: 2022-09-29

Spatial and Temporal Pattern of Carbon Sequestration and Climate Impact in Southwestern China under Different Emission Scenarios

1.
Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, Beijing 100091, China
2.
Key Laboratory of Dryland Agriculture, Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
3.
National Climate Center of China Meteorological Administration, Beijing 100081, China

摘要

摘要: 目的分析2种不同温室气体排放情景下西南地区碳汇时空格局及气候影响，为该区评价未来碳中和能力提供参考。方法基于气候模式BCC-CSM1.1输出的RCP4.5和RCP8.5情景下的模拟气候数据，使用生态系统模型CEVSA2估算未来西南地区净生态系统生产力（NEP）动态，分析温度和降水对NEP变化的影响。结果 2020—2099年RCP4.5和RCP8.5排放情景下西南地区NEP平均值分别为21.49和37.98 g C·m⁻²·a⁻¹。RCP4.5情景下NEP极显著下降，趋势倾向率为−0.24 Tg C·a⁻¹（P ＜ 0.01）；RCP8.5情景下NEP极显著上升，趋势倾向率为0.41 Tg C·a⁻¹（P ＜ 0.01）。在2种情景下单位面积年均NEP为森林＞灌丛＞农田＞草地。RCP4.5情景下NEP总量为森林＞农田＞草地＞灌丛；RCP8.5情景下NEP总量为森林＞农田＞灌丛＞草地。RCP4.5情景下，4种主要植被类型NEP和年均温极显著负相关（P ＜ 0.01），NEP与温度显著负相关的面积占63.5%，与降水显著正相关的面积占21.4%（P ＜ 0.05）。RCP8.5情景下，只有森林NEP与年均温极显著正相关（P ＜ 0.01），NEP与温度显著正相关的面积占34.9%，与降水显著正相关的面积占21.5%（P ＜ 0.05）。结论西南地区未来碳汇动态与排放情景密切相关，RCP4.5情景下，净初级生产力（NPP）温度敏感性低于土壤异氧呼吸（R_h）敏感性，导致西南地区NEP下降；RCP8.5情景下，NPP温度敏感性高于R_h敏感性，导致西南地区NEP上升。与目前相比，RCP8.5情景下西南地区未来碳汇在全国所占比重有较大增长。
- NEP /
- 时空动态 /
- 西南地区 /
- 温室气体排放情景
Abstract: Objective The spatial and temporal pattern of carbon sequestration and climate impact were analysed to provide reference for capacity of regional carbon neutralization in the future in southwestern China under two different greenhouse gas emission scenarios. Methods Based on the simulated data from the climate model BCC-CSM1.1 under the RCP4.5 and RCP8.5 scenarios, the ecosystem model CEVSA2 was used to estimate net ecosystem productivity (NEP) during 2020-2099 in southwestern China, and to examine the effects of temperature and precipitation on NEP changes. Result The mean values of NEP in southwestern China under the RCP4.5 and RCP8.5 scenarios from 2020 to 2099 would be 21.49 and 37.98 g C·m⁻²·a⁻¹, respectively. NEP decreased significantly by −0.24 Tg C·a⁻¹ (P ＜ 0.01) under the RCP4.5 scenario, while NEP increased significantly by 0.41 Tg C·a⁻¹(P ＜ 0.01) under the RCP8.5 scenario during the same period. Under both scenarios, the mean annual NEP would be forest ＞ shrubland ＞ farmland ＞ grassland per unit area. The total amount of NEP under the RCP4.5 scenario would be forest ＞ farmland ＞ grassland ＞ shrubland, and the total amount of NEP under the RCP8.5 scenario would be forest ＞ farmland ＞ shrubland ＞ grassland in the whole southwestern China. Furthermore, there was an extremely significant and negative correlation between NEP and mean annual temperature in four main vegetation types under the RCP4.5 scenario (P ＜ 0.01). The area with a significant and negative correlation between NEP and temperature accounted for 63.5%, while the area with a significant and positive correlation between NEP and precipitation accounted for 21.4% (P ＜ 0.05). Under the RCP8.5 scenario, there was an extremely significant and positive correlation between NEP and mean annual temperature only in forest (P ＜ 0.01). The area with a significant and positive correlation between NEP and temperature accounted for 34.9%, and the area with a significant and positive correlation between NEP and precipitation accounted for 21.5% (P ＜ 0.05). Conclusion The carbon sequestration dynamics in southwestern China are closely related to the emission scenarios. Under the RCP4.5 scenario, the temperature sensitivity of net primary productivity (NPP) is lower than that of soil heterotrophic respiration (R_h), which leads to decrease in NEP in the future. However, under the RCP8.5 scenario, the temperature sensitivity of NPP is higher than that of R_h, which leads to increase in NEP in the future. Compared with the present ratio, carbon sequestration in the study area in the proportion of that in the whole China will increase in the future under the RCP8.5 scenario.
- net ecosystem productivity /
- spatio-temporal dynamics /
- southwestern China /
- scenarios of greenhouse gas emission

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图 1 西南地区高程和植被分布

Figure 1. Elevation and vegetation distribution in southwestern China

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图 2 两种情景下西南地区2020—2099年平均NEP空间分布

Figure 2. Spatial distribution of mean annual NEP from 2020 to 2099 in southwestern China under two scenarios

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图 3 西南地区2020—2099年NEP总量年际变化

Figure 3. Interannual variation of total NEP in southwestern China during 2020-2099

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图 4 两种情景下NEP变化趋势的空间分布及显著性检验

Figure 4. Spatial distribution and significance test of NEP changing trend under two scenarios

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图 5 两种情景下年均温和年降水量距平变化

Figure 5. Variation of mean annual temperature and precipitation anomaly under two scenarios

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图 6 两种情景下NEP与气象因子相关性的空间分布及其显著性检验

Figure 6. Spatial distribution and significance test of correlation coefficient between NEP and meteorological factors under two scenarios

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图 7 两种情景下西南地区NPP和R_h随温度和时间的变化

Figure 7. NPP and R_h changed with temperature and time under two scenarios

下载: 全尺寸图片幻灯片

表 1 未来各时间段西南地区年均NEP

Table 1. Mean annual NEP in southwestern China during different periods in the future

年均NEP Mean annual NEP	森林 Forest		灌丛 Shrubland		草地 Grassland		农田 Farmland		总和 Total
年均NEP Mean annual NEP	单位面积 Unit area/ (g C·m⁻²)	总量 Total/ (Tg C)	单位面积 Unit area/ (g C·m⁻²)	总量 Total/ (Tg C)	单位面积 Unit area/ (g C·m⁻²)	总量 Total/ (Tg C)	单位面积 Unit area/ (g C·m⁻²)	总量 Total/ (Tg C)	单位面积 Unit area/ (g C·m⁻²)	总量 Total/ (Tg C)
2020—2099（RCP4.5）	33.69	18.94	14.40	2.44	11.37	2.86	13.25	4.20	21.52	28.44
2020—2099（RCP8.5）	62.28	35.01	24.95	4.24	16.23	4.11	22.00	6.97	38.04	50.33
2025—2035（RCP4.5）	35.88	20.18	16.71	2.84	16.29	4.09	13.41	4.29	23.73	31.40
2025—2035（RCP8.5）	39.58	22.26	17.93	3.05	15.54	3.91	8.37	2.63	24.12	31.85
2055—2065（RCP4.5）	37.23	20.92	13.58	2.31	9.00	2.26	11.43	3.59	22.03	29.08
2055—2065（RCP8.5）	67.72	38.07	30.50	5.18	20.25	5.14	19.82	6.30	41.34	54.69
面积百分比 Percentage of area/%	42.53		12.98		19.19		23.70		98.40

下载: 导出CSV

表 2 两种情景下主要植被类型NEP趋势倾向率与气象因子的相关性

Table 2. Correlation between NEP trend rate and meteorological factors of main vegetation types under two scenarios

情景 Scenarios	NEP相关参数 NEP related parameters	森林 Forest	灌丛 Shrubland	草地 Grassland	农田 Farmland
RCP4.5	NEP趋势倾向率 NEP trend tendency rate/(Tg C·10a⁻¹)	−2.009^***	−1.490^**	−0.979^*	−1.892
	NEP与年均温相关系数 Correlation coefficient between NEP and mean annual temperature	−0.608^**	−0.675^**	−0.445^**	−0.326^**
	NEP与年降水量相关系数 Correlation coefficient between NEP and annual precipitation	0.351^**	0.354^**	−0.33	0.755^**

RCP8.5	NEP趋势倾向率 NEP trend tendency rate/(Tg C·10a⁻¹)	6.579^***	0.938	0.409	0.393
	NEP与年均温相关系数 Correlation coefficient between NEP and mean annual temperature	0.703^**	−0.076	−0.136	−0.158^**
	NEP与年降水量相关系数 Correlation coefficient between NEP and annual precipitation	−0.024	0.274^**	0.143	0.681^**
注： NEP趋势倾向率中表示趋势显著性检验，其他表示相关显著性检验，，P＜0.05；，P＜0.01；*，P＜0.001。In parameter of NEP tendency rate, indicates a trend significance test, and others * indicate a correlation significance test, , P＜0.05; , P＜0.01; **, P＜0.001.

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