亚热带典型森林生产力及碳利用率的气候变化响应

doi:10.11707/j.1001-7488.LYKX20230622

Abstract

Abstract:

Objective: In this study, the responses of vegetation productivity and carbon use efficiency of different forest ecosystems to climate factors were investigated, which is of great significance for revealing the changes of carbon balance in terrestrial ecosystem and providing scientific basis for the protection and management of subtropical forest ecosystems. Method: Four typical forests, namely evergreen coniferous forest, evergreen broadleaf forest, evergreen conifer-broadleaf mixed forest, and bamboo forest, in the Ganjiang River Basin were targeted. The parameters localized Biome BGC model was used to simulate the gross primary productivity (GPP) and net primary productivity (NPP) from 1970 to 2021, revealing the response of productivity and carbon use efficiency of the four typical forest vegetation to climate factors at interannual and inter-monthly scales. Result: 1) The annual GPP (g·m^–2a^–1) was ranked as evergreen coniferous forest (2 514.6) > evergreen broadleaf forest (2 467.9) > evergreen conifer-broadleaf mixed forest (2 285.0) > bamboo forest (2 040.1). At the interannual scale, bamboo forest GPP was positively correlated with accumulated temperature (r = 0.41, P<0.01). At the inter-monthly scale, the GPP of the four typical forests was positively driven by accumulated temperature (r > 0.99, P<0.01). 2) The annual NPP (g·m^–2a^–1) was ranked as evergreen broadleaf forest (862.4) > bamboo forest (739.2) > evergreen conifer-broadleaf mixed forest (721.1) > evergreen coniferous forest (681.3). At the interannual scale, the NPP of evergreen coniferous forest, evergreen broadleaf forest and evergreen conifer-broadleaf mixed forest was positively driven by precipitation (r > 0.32, P<0.05). At the inter-monthly scale, there was a significant positive correlation between the NPP of evergreen coniferous forest and precipitation (r = 0.59, P<0.05). The NPP of evergreen broadleaf forest was mainly driven by accumulated temperature (r = 0.93, P<0.01). 3) The order of carbon use efficiency at the interannual and inter-monthly scales was sorted as bamboo forest > evergreen broadleaf forest > evergreen conifer-broadleaf mixed forest > evergreen coniferous forest. Compared to NPP, the carbon use efficiency had stronger response to climate change. The carbon use efficiency was negatively driven by accumulated temperature at both interannual and inter-monthly scales (r > 0.51, P<0.01). Conclusion: In summary, accumulated temperature is the main factor driving the productivity and carbon use efficiency of subtropical forest ecosystems. Compared to evergreen coniferous forest and evergreen conifer-broadleaf mixed forest, evergreen broadleaf forest and bamboo forest have stronger carbon sequestration capacity and greater carbon sink potential under the background of climate change.

Key words: vegetation productivity, carbon use efficiency, climate change, Biome-BGC model, Ganjiang River Basin

CLC Number:

Yun Huang,Liliang Xu,Bofu Zheng,Xu Song,Fangqing Hu,Jinqi Zhu,Wei Wan. Responses of Productivity and Carbon Use Efficiency of Typical Subtropical Forests to Climate Change[J]. Scientia Silvae Sinicae, 2025, 61(3): 121-134.

Figures/Tables 12

Fig.1

Table 1

Eco-physiological parameters of different forest types"

参数 Parameter	单位 Units	常绿针叶林 Evergreen coniferous forest （ECF）	常绿阔叶林 Evergreen broadleaf forest (EBF)	竹林 Bamboo forest (BF)
叶片和细根年周转率 Annual leaf and fine root turnover fraction	a^?1	0.26	0.5	0.675^b
活立木年周转率 Annual live wood turnover fraction	a^?1	0.7	0.7	0.7
整株植物死亡率 Annual whole-plant mortality fraction	a^?1	0.005	0.005	0.005
植物火烧死亡率 Annual fire mortality fraction	a^?1	0.005	0.002	0.005
细根与叶片碳分配比 (Allocation) fine root C∶leaf C	—	1.4	1.2^a	1
新茎与新叶碳分配比 New stem C∶new leaf C	—	2.2	2.2	1.8
新活木与新总木碳分配比 New live wood C∶new total wood C	—	0.071	0.16	0.1
新根与新茎的碳分配比 New root C∶new stem C	—	0.29	0.3	0.42
当前生长比例 Current growth proportion	—	0.5	0.5	0.5
叶片碳氮比 C∶N of leaves	—	44.86*	37.21*	24.30*
凋落物碳氮比 C∶N of leaf litter, after retranslocation	—	93	49	93
细根碳氮比 C∶N of fine roots	—	71.03*	59.90*	52.81*
活木质组织碳氮比 C∶N of live wood	—	71.03*	59.90*	52.81*
死木质组织碳氮比 C∶N of dead wood	—	702^*	480^*	729
凋落物中易分解物质比例 Labile proportion in leaf litter	—	0.31	0.32	0.32
凋落物中纤维素比例 Cellulose proportion in leaf litter	—	0.45	0.44	0.44
凋落物中木质素比例 Lignin proportion in leaf litter	—	0.24	0.24	0.24
细根中易分解物质比例 Labile proportion in fine root	—	0.34	0.3	0.3
细根中纤维素比例 Cellulose proportion in fine root	—	0.44	0.45	0.45
细根中木质素比例 Lignin proportion in fine root	—	0.22	0.25	0.25
死木质组织中纤维素比例 Cellulose proportion in dead wood	—	0.71	0.76	0.76
死木质组织中木质素比例 Lignin proportion in dead wood	—	0.29	0.24	0.24
冠层截留系数 Canopy water interception coefficient	LAI^?1d^?1	0.045	0.01^a	0.041
冠层消光系数 Canopy light extinction coefficient	—	0.51	0.7	0.269 8^c
叶面积与投影叶面积指数比 Leaf area to projected leaf area index ratio	—	2.6	2	2
冠层比叶面积 Canopy specific leaf area (projected area basis)	m²·kg^?1	5.20*	9.34*	17.18*
阴生叶和阳生叶的比叶面积比例 Ratio of shaded SLA∶sunlit SLA	—	2	2	2
Rubisco酶中叶氮含量 Leaf N content in Rubisco enzyme	—	0.08	0.06	0.06
最大气孔导度 Maximum stomatal conductance (projected area basis)	m·s^?1	0.006	0.005	0.006^d
表皮层导度 Cuticular conductance (projected area basis)	m·s^?1	0.000 06	0.000 01	0.000 01
边界层导度 Boundary layer conductance (projected area basis)	m·s^?1	0.09	0.01	0.01
气孔开始缩小时的叶片水势 Leaf water potential when stomata begin to close	MPa	–0.65	–0.6	–0.6
气孔完全闭合时的叶片水势 Leaf water potential when stomata are completely closed	MPa	–2.5	–3.9	–3.9
气孔开始缩小时的饱和水汽压差 VPD when stomata begin to close	Pa	610	1 800	930
气孔完全闭合时饱和水汽压差 VPD when stomata are completely closed	Pa	3 100	4 100	4 100

Table 1

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Table 2

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森林类型 Forest type	研究区域 Study area	时间 Period	模型 Model	NPP/(g·m^?2a^–1)	参考文献 Reference
常绿针叶林 Evergreen coniferous forest （ECF）	江西千烟洲 Qianyanzhou, Jiangxi	1985—2005	Biome-BGC	343.3~906.4	马泽清等, 2008
	江西千烟洲 Qianyanzhou, Jiangxi	1993—2004	Biome-BGC	453~828	曾慧卿等, 2008
	赣江流域 Ganjiang River Basin	1998—2012	CASA	657	李双元等, 2014
	三峡库区 Three Gorges Reservoir area	1981—2014	Biome-BGC	262.9~807.7	Chen et al., 2019
	赣江流域 Ganjiang River Basin	1970—2021	Biome-BGC	357.2~916.9	本研究This study
常绿阔叶林 Evergreen broadleaf forest （EBF）	江西省 Jiangxi Province	2001	BEPS	620.1~1 273.4	Feng et al., 2007
	江西泰和县 Taihe County, Jiangxi	1998—2012	CASA	985	戴尔阜等, 2015
	浙江天目山 Tianmu Mountains, Zhejiang	1984—2014	CASA	739	Chen et al., 2017
	赣江流域 Ganjiang River Basin	1970—2021	Biome-BGC	662.9~1 036.1	本研究This study
针阔混交林 Evergreen conifer-broadleaf mixed forest （MIX）	浙江省 Zhejiang Province	1999	TRIPLEX	784.5	Zhang et al., 2008
	中国 China	1993—2011	—	330~920	陈雅敏等, 2012
	中国东南部 Southeast China	2001—2010	—	656.6	崔林丽等, 2016
	赣江流域 Ganjiang River Basin	1970—2021	Biome-BGC	596.8~871.2	本研究This study
竹林 Bamboo forest （BF）	福建省 Fujian Province	2005	Biome-BGC	739.6	李慧等, 2008
	浙江天目山 Tianmu Mountains, Zhejiang	1984—2014	CASA	740	Chen et al., 2017
	浙江安吉 Anji, Zhejiang	2011—2014	TRIPLEX	747~911	Chen et al., 2018
	赣江流域 Ganjiang River Basin	1970—2021	Biome-BGC	579.3~849.1	本研究This study

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Responses of Productivity and Carbon Use Efficiency of Typical Subtropical Forests to Climate Change

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