Journal of Geographical Sciences >
Imbalance of inter-provincial forest carbon sequestration rate from 2010 to 2060 in China and its regulation strategy
Cai Weixiang, Master, specialized in ecosystem carbon cycles and regulatory mechanisms. E-mail: caiwx@bjfu.edu.cn |
Received date: 2021-11-15
Accepted date: 2022-04-21
Online published: 2023-01-16
Supported by
National Natural Science Foundation of China(42141004)
National Natural Science Foundation of China(32171544)
National Natural Science Foundation of China(31988102)
Copyright
Forest ecosystem, as a predominant component of terrestrial ecosystems in view of carbon sinks, has a high potential for carbon sequestration. Accurately estimating the carbon sequestration rate in forest ecosystems at provincial level, is a prerequisite and basis for scientifically formulating the technical approaches of carbon neutrality and the associated regulatory policies in China. However, few researches on future carbon sequestration rates (CSRs) for Chinese forest ecosystems for provincial-level regions (hereafter province) have been reported, especially for forest soils. In this study, we quantitatively assessed the carbon sequestration rates of existing forest ecosystems of all the provinces from 2010 to 2060 using the Forest Carbon Sequestration model (FCS), in combination with large quantities of field-measured data in China under three future climate scenarios (RCP2.6, RCP4.5, and RCP8.5). Results showed that CSRs across provinces varied from 0.01 TgC a-1 to 36.74 TgC a-1, with a mean of 10.09 ± 0.43 TgC a-1. Inter-provincial differences have been observed in forest CSRs. Regarding the spatial variations in CSRs on a unit area basis within provinces, the eastern region provinces have a larger capacity for sequestration than the western region, while the western region has greater CSR per unit GDP and per capita. Moreover, there are significant negative correlations between the CSRs per capita in each province and the corresponding GDP per capita, under the assumption that GDP per capita is constant in the future across provinces. In summary, there is a significant regional imbalance in CSR among provinces. Special technological and policy interventions are required to realize carbon sink potential sustainably. An overlap in China’s poorer areas and areas with stronger carbon sinks has indicated that existing policies to support traditional carbon trading are insufficient. Regulatory measures such as “regional carbon compensation” must be adopted urgently in line with the Chinese characteristics, so that people in western or underdeveloped regions can consciously strengthen forest protection and enhance forest carbon sinks through coordinated regional development while ensuring that China’s forests play a greater role in carbon neutrality strategies.
CAI Weixiang , XU Li , LI Mingxu , SUN Osbert Jianxin , HE Nianpeng . Imbalance of inter-provincial forest carbon sequestration rate from 2010 to 2060 in China and its regulation strategy[J]. Journal of Geographical Sciences, 2023 , 33(1) : 3 -17 . DOI: 10.1007/s11442-023-2071-4
Figure 1 The secondary succession theory (Foundation of FCS model) presented the relationship between vegetation biomass and forest age (He et al., 2017). Bt, vegetation biomass (Mg ha-1); Bmax, maximum vegetation biomass; t, forest age (a); and Bto, vegetation biomass at t = t0. |
Table 1 Annual changes of vegetation carbon sequestration rate in Chinese forests by provincial-level region from 2010 to 2060 |
Provincial- level region | Forest area (104 km2) | CSR of forest vegetation (TgC a-1) | |||||
---|---|---|---|---|---|---|---|
2010-2020 | 2020-2030 | 2030-2040 | 2040-2050 | 2050-2060 | Mean±SD | ||
Anhui | 3.12 | 4.96±0.22a† | 4.79±0.30a | 3.39±0.57b | 2.53±0.55b | 1.24±0.78c | 3.38±0.11 |
Beijing | 0.44 | 0.73±0.02ab | 0.83±0.04a | 0.66±0.08b | 0.51±0.08c | 0.21±0.1d | 0.59±0.01 |
Chongqing | 3.46 | 2.58±0.07ab | 2.95±0.20a | 2.92±0.23a | 2.33±0.11b | 1.47±0.41c | 2.45±0.07 |
Fujian | 8.33 | 12.32±0.58a | 11.36±0.79a | 8.07±1.44b | 6.34±1.43bc | 4.80±2.06c | 8.58±0.26 |
Gansu | 2.1 | 0.64±0.04a | 0.73±0.13a | 0.77±0.21a | 0.83±0.16a | 1.01±0.37a | 0.79±0.05 |
Guangdong | 10.67 | 11.82±0.35a | 14.23±0.92b | 12.19±0.97a | 10.08±1.04a | 6.26±1.8c | 10.91±0.29 |
Guangxi | 12.58 | 10.76±0.21a | 11.31±0.84a | 9.8±1.00a | 7.58±0.36b | 6.94±1.46b | 9.28±0.29 |
Guizhou | 6.27 | 0.81±0.06a | 1.63±0.24ab | 2.15±0.37b | 1.76±0.17b | 1.25±0.98ab | 1.52±0.17 |
Hainan | 0.92 | 0.65±0.05a | 0.74±0.04b | 0.62±0.05a | 0.51±0.02c | 0.42±0.07c | 0.59±0.03 |
Hebei | 3.97 | 6.41±0.25ab | 7.36±0.40b | 6.27±0.73ab | 5.02±0.92b | 2.70±1.09c | 5.55±0.12 |
Heilongjiang | 19.77 | 34.89±0.49a | 34.04±0.96a | 27.11±2.15b | 19.42±1.80c | 12.87±3.32d | 25.67±0.91 |
Henan | 2.07 | 2.98±0.06a | 3.10±0.19a | 2.36±0.20b | 1.73±0.15c | 0.25±0.36d | 2.08±0.06 |
Hubei | 6.21 | 8.62±0.09a | 7.93±0.62a | 5.51±0.52b | 3.87±0.20c | 4.29±0.71c | 6.04±0.18 |
Hunan | 8.87 | 9.73±0.10ab | 11.75±0.64c | 10.70±0.71bc | 9.56±0.83ab | 8.98±1.17a | 10.15±0.15 |
Inner Mongolia | 16.26 | 18.75±0.93ab | 22.19±1.54b | 20.17±2.69ab | 18.36±3.99ab | 16.00±4.22b | 19.09±0.40 |
Jiangsu | 0.31 | 0.50±0.02a | 0.48±0.02a | 0.43±0.03b | 0.30±0.03c | 0.42±0.01b | 0.43±0.00 |
Jiangxi | 9.78 | 10.45±0.37a | 12.29±0.68a | 10.80±1.24a | 9.88±1.46a | 6.31±1.98b | 9.94±0.25 |
Jilin | 8.33 | 15.93±0.24a | 15.87±0.44a | 12.77±0.67b | 8.41±0.71c | 5.56±1.32d | 11.71±0.40 |
Liaoning | 5.57 | 8.12±0.06a | 9.72±0.26a | 9.51±0.80a | 8.60±1.41a | 6.16±1.27b | 8.42±0.18 |
Ningxia | 0.07 | 0.03±0.00a | 0.03±0.00a | 0.04±0.01a | 0.03±0.01a | 0.04±0.02a | 0.03±0.00 |
Qinghai | 0.29 | 0.05±0.00a | 0.07±0.03ab | 0.10±0.04ab | 0.14±0.04b | 0.14±0.05b | 0.10±0.01 |
Shaanxi | 5.92 | 6.23±0.12a | 6.28±0.37a | 5.41±0.43b | 4.12±0.18c | 2.48±0.65d | 4.91±0.13 |
Shandong | 1.83 | 2.21±0.10a | 2.86±0.19a | 2.86±0.36a | 2.79±0.57a | 2.27±0.58a | 2.60±0.04 |
Shanghai | 1.31×10-4 | <0.01a | <0.01a | <0.01a | <0.01a | <0.01a | <0.01 |
Shanxi | 2.49 | 2.56±0.06a | 3.55±0.25b | 3.19±0.28b | 2.66±0.25a | 1.82±0.38c | 2.76±0.05 |
Sichuan | 14.11 | 2.65±0.04a | 3.45±1.21ab | 5.63±2.13ab | 6.92±1.54b | 6.59±3.31b | 5.05±0.45 |
Tianjin | 0.03 | 0.04±0.00ab | 0.05±0.00b | 0.05±0.01b | 0.05±0.01ab | 0.03±0.01a | 0.05±0.00 |
Xizang | 8.49 | 2.39±0.27a | 3.01±0.76ab | 4.10±1.32ab | 4.90±1.56b | 4.26±1.05ab | 3.73±0.07 |
Xinjiang | 2.48 | 0.22±0.02a | 0.28±0.10a | 0.40±0.10a | 0.34±0.28a | 0.60±0.69a | 0.37±0.14 |
Yunnan | 18.99 | 7.14±0.13a | 6.84±2.74a | 9.58±3.99a | 7.23±2.93a | 4.91±2.03b | 7.14±0.10 |
Zhejiang | 6.06 | 8.14±0.43a | 8.47±0.66a | 6.75±1.13ab | 5.57±1.26bc | 3.62±1.57c | 6.51±0.18 |
Total | 189.79 | 193.32±3.35 | 208.2±11.48 | 184.27±21.62 | 152.39±20.79 | 113.91±30.45 | 170.42±4.52 |
† Change in carbon sequestration rate was presented as mean ± 1 standard deviation on invariable forest area and three climate scenarios (RCP2.6, RCP4.5, and RCP8.5), and the same small letters indicate no significant difference in carbon sequestration rates among different periods at p = 0.05 level. |
Table 2 Annual changes of soil carbon sequestration rate in Chinese forests by provincial-level region from 2010 to 2060 |
Provincial- level region | Forest area (104 km2) | CSR of forest soil (TgC a-1) | |||||
---|---|---|---|---|---|---|---|
2010-2020 | 2020-2030 | 2030-2040 | 2040-2050 | 2050-2060 | Mean±SD | ||
Anhui | 3.12 | 2.45±0.05ab† | 3.62±0.12c | 3.48±0.22c | 2.92±0.43b | 2.05±0.30a | 2.90±0.03 |
Beijing | 0.44 | 0.05±0.00a | 0.36±0.02c | 0.45±0.03d | 0.42±0.07cd | 0.26±0.04b | 0.31±0.01 |
Chongqing | 3.46 | 2.13±0.03a | 3.06±0.09b | 3.64±0.11c | 3.6±0.19c | 3.13±0.16b | 3.11±0.01 |
Fujian | 8.33 | 4.06±0.14a | 7.18±0.30b | 7.21±0.53b | 6.29±1.17b | 4.70±0.78a | 5.89±0.08 |
Gansu | 2.1 | 1.21±0.04a | 1.46±0.10ab | 1.45±0.13ab | 1.55±0.21b | 1.73±0.19b | 1.48±0.01 |
Guangdong | 10.67 | 4.89±0.08a | 9.47±0.29bc | 10.74±0.35d | 10.21±1.09cd | 8.57±0.43b | 8.78±0.10 |
Guangxi | 12.58 | 5.91±0.09a | 9.87±0.34b | 11.33±0.44d | 10.99±0.63cd | 10.28±0.48bc | 9.67±0.07 |
Guizhou | 6.27 | 3.91±0.09a | 4.36±0.17a | 4.44±0.18a | 4.34±0.39a | 4.33±0.42a | 4.28±0.02 |
Hainan | 0.92 | 0.90±0.00a | 0.95±0.02b | 0.95±0.02b | 0.87±0.03a | 0.76±0.03c | 0.89±0.00 |
Hebei | 3.97 | 1.13±0.06a | 3.79±0.16bc | 4.68±0.29d | 4.46±0.68cd | 3.22±0.44b | 3.46±0.05 |
Heilongjiang | 19.77 | 1.18±0.53a | 13.32±0.70b | 16.56±1.25c | 14.14±1.44b | 10.18±0.83d | 11.08±0.47 |
Henan | 2.07 | 1.61±0.01a | 2.46±0.06b | 2.49±0.08b | 2.16±0.18c | 1.72±0.12a | 2.09±0.01 |
Hubei | 6.21 | 5.60±0.03a | 7.54±0.21b | 7.11±0.18c | 5.93±0.31a | 4.35±0.08d | 6.11±0.04 |
Hunan | 8.87 | 2.92±0.03a | 7.22±0.23b | 9.05±0.28cd | 9.45±0.82c | 8.57±0.31d | 7.44±0.10 |
Inner Mongolia | 16.26 | 1.33±0.24a | 9.6±0.49b | 13.58±1.07c | 14.78±2.90c | 14.07±1.84c | 10.67±0.22 |
Jiangsu | 0.31 | 0.11±0.01a | 0.27±0.00b | 0.33±0.01c | 0.29±0.02b | 0.38±0.01d | 0.28±0.00 |
Jiangxi | 9.78 | 6.61±0.09a | 9.69±0.26b | 10.48±0.50b | 10.33±1.21b | 7.88±0.75c | 9.00±0.11 |
Jilin | 8.33 | 2.74±0.06a | 7.75±0.13b | 8.78±0.30c | 6.82±0.63d | 4.77±0.28e | 6.17±0.12 |
Liaoning | 5.57 | 2.55±0.02a | 3.70±0.07b | 5.76±0.37cd | 6.28±0.95c | 5.15±0.47d | 4.69±0.08 |
Ningxia | 0.07 | 0.01±0.00a | 0.03±0.00b | 0.04±0.00c | 0.04±0.01cd | 0.05±0.01d | 0.03±0.00 |
Qinghai | 0.29 | <0.01a | 0.02±0.01a | 0.04±0.02a | 0.09±0.04b | 0.10±0.02b | 0.05±0.00 |
Shaanxi | 5.92 | 4.14±0.03a | 6.16±0.14b | 6.85±0.19c | 6.45±0.27b | 5.46±0.25d | 5.81±0.01 |
Shandong | 1.83 | 0.17±0.03a | 0.35±0.06a | 1.48±0.15b | 1.90±0.41b | 1.68±0.27b | 1.12±0.03 |
Shanghai | 1.31×10-4 | <0.01a | <0.01a | <0.01a | <0.01a | <0.01a | <0.01 |
Shanxi | 2.49 | 1.06±0.01a | 2.32±0.09b | 2.78±0.12c | 2.72±0.25c | 2.40±0.12b | 2.26±0.02 |
Sichuan | 14.11 | 6.51±0.20a | 7.15±0.76a | 8.09±1.18ab | 9.84±1.69b | 9.90±1.78b | 8.30±0.08 |
Tianjin | 0.03 | 0.01±0.00a | 0.03±0.00b | 0.04±0.00c | 0.04±0.01c | 0.03±0.01bc | 0.03±0.00 |
Xizang | 8.49 | 2.53±0.06a | 2.66±0.36a | 3.43±0.64a | 4.84±1.08b | 4.93±0.56b | 3.68±0.08 |
Xinjiang | 2.48 | 0.74±0.04a | 1.65±0.02b | 1.58±0.08b | 1.36±0.34ab | 1.52±0.84b | 1.37±0.20 |
Yunnan | 18.99 | 18.72±4.64a | 16.63±2.08ab | 15.08±1.95ab | 14.56±2.66ab | 11.8±1.10b | 15.36±0.94 |
Zhejiang | 6.06 | 5.46±0.11a | 7.37±0.24b | 7.39±0.47b | 6.60±0.92b | 4.93±0.69a | 6.35±0.05 |
Total | 189.79 | 90.64±4.20 | 150.03±5.32 | 169.32±9.25 | 164.30±19.38 | 138.90±9.99 | 142.64±0.54 |
† Change in carbon sequestration rate was presented as mean ± 1 standard deviation on invariable forest area and three climate scenarios (RCP2.6, RCP4.5, and RCP8.5), and the same small letters indicate no significant difference in carbon sequestration rates among different periods at p = 0.05 level. |
Table 3 Annual changes of ecosystem carbon sequestration rate in Chinese forests by provincial-level region from 2010 to 2060 |
Provincial- level region | Forest area (104 km2) | CSR of forest ecosystem (TgC a-1) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2010-2020 | 2020-2030 | 2030-2040 | 2040-2050 | 2050-2060 | Mean±SD | ||||||||
Anhui | 3.12 | 7.41±0.28ab† | 8.41±0.41b | 6.87±0.79a | 5.44±0.98c | 3.28±1.08d | 6.28±0.11 | ||||||
Beijing | 0.44 | 0.78±0.02a | 1.19±0.05b | 1.11±0.11bc | 0.93±0.15ac | 0.47±0.14d | 0.90±0.01 | ||||||
Chongqing | 3.46 | 4.71±0.10a | 6.02±0.29b | 6.56±0.34b | 5.93±0.29b | 4.60±0.57a | 5.56±0.07 | ||||||
Fujian | 8.33 | 16.38±0.71ab | 18.55±1.07b | 15.28±1.97ab | 12.63±2.61bc | 9.49±2.83c | 14.47±0.23 | ||||||
Gansu | 2.1 | 1.85±0.08a | 2.19±0.23ab | 2.21±0.34ab | 2.38±0.36ab | 2.74±0.56b | 2.27±0.05 | ||||||
Guangdong | 10.67 | 16.71±0.43a | 23.69±1.21b | 22.93±1.32bc | 20.3±2.13c | 14.83±2.23a | 19.69±0.22 | ||||||
Guangxi | 12.58 | 16.66±0.29a | 21.17±1.17b | 21.13±1.43b | 18.57±0.95a | 17.22±1.93a | 18.95±0.27 | ||||||
Guizhou | 6.27 | 4.72±0.15a | 5.99±0.40ab | 6.59±0.55b | 6.11±0.55ab | 5.58±1.39ab | 5.80±0.17 | ||||||
Hainan | 0.92 | 1.54±0.05a | 1.69±0.05b | 1.58±0.07ab | 1.38±0.05c | 1.18±0.09d | 1.48±0.03 | ||||||
Hebei | 3.97 | 7.54±0.31ab | 11.15±0.56c | 10.95±1.02c | 9.48±1.61bc | 5.91±1.53a | 9.01±0.12 | ||||||
Heilongjiang | 19.77 | 36.07±0.63a | 47.36±1.66b | 43.67±3.39b | 33.57±3.22a | 23.05±4.11c | 36.74±1.35 | ||||||
Henan | 2.07 | 4.59±0.07a | 5.56±0.25b | 4.85±0.28a | 3.89±0.32c | 1.97±0.47d | 4.17±0.06 | ||||||
Hubei | 6.21 | 14.23±0.11a | 15.47±0.84b | 12.61±0.69c | 9.80±0.50d | 8.64±0.77e | 12.15±0.16 | ||||||
Hunan | 8.87 | 12.65±0.12a | 18.97±0.87b | 19.75±0.98b | 19.02±1.65b | 17.55±1.42b | 17.59±0.10 | ||||||
Inner Mongolia | 16.26 | 20.08±1.16a | 31.79±2.02b | 33.74±3.76b | 33.15±6.89b | 30.07±6.03b | 29.77±0.42 | ||||||
Jiangsu | 0.31 | 0.61±0.03a | 0.76±0.02b | 0.76±0.04b | 0.59±0.05a | 0.80±0.00b | 0.70±0.00 | ||||||
Jiangxi | 9.78 | 17.06±0.46ab | 21.97±0.94c | 21.28±1.74c | 20.21±2.68bc | 14.19±2.72a | 18.94±0.24 | ||||||
Jilin | 8.33 | 18.67±0.30a | 23.62±0.57b | 21.55±0.96c | 15.23±1.34d | 10.32±1.58e | 17.88±0.48 | ||||||
Liaoning | 5.57 | 10.68±0.07a | 13.42±0.32bc | 15.27±1.17c | 14.87±2.36c | 11.32±1.73a | 13.11±0.21 | ||||||
Ningxia | 0.07 | 0.04±0.00a | 0.06±0.01ab | 0.08±0.01bc | 0.08±0.01bc | 0.09±0.03c | 0.07±0.00 | ||||||
Qinghai | 0.29 | 0.05±0.01a | 0.09±0.04a | 0.13±0.06ab | 0.23±0.08b | 0.24±0.07b | 0.15±0.01 | ||||||
Shaanxi | 5.92 | 10.37±0.15a | 12.44±0.51b | 12.26±0.62b | 10.57±0.43a | 7.94±0.89c | 10.72±0.13 | ||||||
Shandong | 1.83 | 2.38±0.12a | 3.21±0.25ab | 4.33±0.51bc | 4.7±0.97bc | 3.95±0.84c | 3.71±0.05 | ||||||
Shanghai | 1.31×10-4 | <0.01a | <0.01a | <0.01a | <0.01a | <0.01a | <0.01 | ||||||
Shanxi | 2.49 | 3.61±0.07a | 5.87±0.33b | 5.98±0.39b | 5.38±0.50b | 4.21±0.48a | 5.01±0.03 | ||||||
Sichuan | 14.11 | 9.17±0.16a | 10.60±1.97ab | 13.72±3.30ab | 16.76±3.17b | 16.50±5.09b | 13.35±0.48 | ||||||
Tianjin | 0.03 | 0.05±0.00a | 0.08±0.01b | 0.09±0.01b | 0.09±0.02b | 0.07±0.02ab | 0.08±0.00 | ||||||
Xizang | 8.49 | 4.92±0.34a | 5.67±1.12a | 7.52±1.96ab | 9.74±2.58b | 9.19±1.57b | 7.41±0.03 | ||||||
Xinjiang | 2.48 | 0.96±0.04a | 1.93±0.12a | 1.98±0.18a | 1.71±0.62a | 2.12±1.53a | 1.74±0.34 | ||||||
Yunnan | 18.99 | 25.86±4.71a | 23.47±3.78a | 24.66±5.67a | 21.80±5.59a | 16.72±3.09b | 22.50±0.99 | ||||||
Zhejiang | 6.06 | 13.60±0.54ab | 15.84±0.89b | 14.14±1.60ab | 12.17±2.18a | 8.55±2.26c | 12.86±0.19 | ||||||
Total | 189.79 | 283.96±3.39 | 358.23±16.67 | 353.59±30.73 | 316.69±40.12 | 252.81±40.39 | 313.06±4.72 |
†Change in carbon sequestration rate was presented as mean ± 1 standard deviation on invariable forest area and three climate scenarios (RCP2.6, RCP4.5, and RCP8.5), and the same small letters indicate no significant difference in carbon sequestration rates among different periods at p = 0.05 level. |
Figure 2 Changes in carbon sequestration rates (CSR) per unit area of forest by province at different periods. Panel a is the period of 2010-2030 and panel b is 2030-2060. Note: This figure has been prepared based on the standard map provided by the Ministry of Natural Resources of the People’s Republic of China, which can be found on the service website (GS (2019)1698). The base map was not modified. |
Figure 3 Annual changes in per capita carbon sequestration rate (CSR) among provinces from 2010-2030 (a) and 2030-2060 (b). Note: This figure has been prepared based on the standard map provided by the Ministry of Natural Resources of the People’s Republic of China, which can be found on the service website (GS (2019)1698). The base map was not modified. |
Figure 4 Changes in forest carbon sequestration rate (CSR) on per unit of GDP among provinces. Note: This figure has been prepared based on the standard map provided by the Ministry of Natural Resources of the People’s Republic of China, which can be found on the service website (GS (2019)1698). The base map was not modified. |
Figure 5 Relationship between per capita forest carbon sequestration rate and GDP per capita at provincial level in China |
Figure 6 Requirement for developing a combination of technologies and novel policies to enhance forest carbon sequestration in a new era. CSR, carbon sequestration rate |
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