Comparison of photosynthetic-CO2 response process and models of Leymus chinensis under differing nitrogen addition and mowing conditions

doi:10.11686/cyxb2022401

Abstract

Abstract:

Photosynthesis of plants is affected by grassland management practices such as nitrogen addition and mowing. In this research， the photosynthetic-CO₂ response process of the dominant species， Leymus chinensis， was determined in a controlled field experiment exploring the interaction between nitrogen addition （0， 2， 5， 10， 20 and 50 g N·m^-2·yr^-1） and mowing （mown and unmown） in an Inner Mongolian meadow steppe. Leaf photosynthetic-CO₂ response curves were fitted using a rectangular hyperbolic model， a non-rectangular hyperbolic model， a modified rectangular hyperbolic model and a Michaelis-Menten model in order to define photosynthetic trait responses of L. chinensis to nitrogen addition and mowing. It was found that the initial carboxylation efficiency and photorespiration rate of the non-rectangular hyperbolic model were closest to the measured values. The modified rectangular hyperbola model provided the best fit for CO₂ saturation point， CO₂ compensation point and maximum net photosynthetic rate， and the modified rectangular hyperbolic model the highest goodness of fit. Moderate nitrogen addition increased the net photosynthetic rate， water use efficiency， maximum net photosynthetic rate， initial carboxylation efficiency and CO₂ saturation point， and decreased the CO₂ compensation point， and thereby improved the CO₂ use efficiency of L. chinensis. With the increase of CO₂ concentration， the net photosynthetic rate of L. chinensis with nitrogen concentration of 20 g N·m^-2·yr^-1 with mowing increased， and higher maximum net photosynthetic rate， CO₂ saturation point and water use efficiency was observed， together with a lower CO₂ compensation point. In conclusion， the non-rectangular hyperbolic model and the modified rectangular hyperbolic model were more suitable for fitting L. chinensis CO₂ response curves defining responses to nitrogen addition and mowing. In this experiment conducted on an Inner Mongolian steppe， the photosynthetic capacity of L. chinensis was most efficiently increased by applying 20 g N·m^-2·yr^-1 with mowing. This treatment combination is beneficial to carbon sequestration of the grassland ecosystem.

Key words: Leymus chinensis, nitrogen addition, mowing, photosynthetic-CO₂ response curve, fitting model

Si-qi YANG, Ya-jing BAO, Jia-qi YE, Shuai WU, Meng ZHANG, Meng-ran XU, Yu ZHAO, Xiao-tao LYU, Xing-guo HAN. Comparison of photosynthetic-CO₂ response process and models of Leymus chinensis under differing nitrogen addition and mowing conditions[J]. Acta Prataculturae Sinica, 2023, 32(9): 160-172.

Figures/Tables 4

References 46

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模型 Model	处理 Treatment	初始羧化效率 Initial carboxylation efficiency （α， mol·m^-2·s^-1）	CO₂饱和点 CO₂ saturation point （C_isat， μmol·mol^-1）	CO₂补偿点 CO₂compensation point （Г， μmol·mol^-1）	最大净光合速率 Maximum net photosynthetic rate （P_nmax， μmol·m^-2·s^-1）	光呼吸速率 Light respiration rate （R_p， μmol·m^-2·s^-1）
实测值 Measured value	AN₀	0.03	1500.00	67.86	12.83	1.74
	AN₂	0.05	600.00	53.44	18.71	2.76
	AN₅	0.04	1000.00	85.18	17.01	3.33
	AN₁₀	0.03	1500.00	64.25	23.26	2.19
	AN₂₀	0.07	1200.00	69.67	27.37	4.76
	AN₅₀	0.06	1000.00	88.56	23.68	5.20
	MN₀	0.06	1000.00	82.54	23.29	4.57
	MN₂	0.05	800.00	75.20	21.19	3.54
	MN₅	0.05	800.00	93.60	22.84	4.93
	MN₁₀	0.07	1000.00	67.53	31.08	4.75
	MN₂₀	0.05	1500.00	54.34	30.46	2.52
	MN₅₀	0.06	1000.00	39.77	21.72	2.20
直角双曲线模型 Rectangular hyperbola model	AN₀	0.05	458.81	67.99	20.23	2.94
	AN₂	0.41	114.68	58.72	33.48	14.10
	AN₅	0.11	331.17	80.92	28.94	6.69
	AN₁₀	0.06	821.86	71.48	41.91	3.62
	AN₂₀	0.19	281.80	67.96	44.09	10.08
	AN₅₀	0.20	259.07	80.41	40.60	11.58
	MN₀	0.15	315.40	78.75	38.43	9.06
	MN₂	0.15	279.86	74.27	34.15	8.50
	MN₅	0.17	289.08	85.28	38.29	10.45
	MN₁₀	0.19	316.26	69.90	50.58	10.68
	MN₂₀	0.08	718.00	65.14	52.96	4.77
	MN₅₀	0.25	173.14	52.86	34.30	9.64
非直角双曲线模型 Non-rectangular hyperbola model	AN₀	0.04	547.10	67.28	18.02	2.33
	AN₂	0.05	456.88	44.46	18.72	2.02
	AN₅	0.04	639.31	80.53	19.67	2.83
	AN₁₀	0.03	862.20	62.54	27.85	2.16
	AN₂₀	0.10	439.99	68.77	36.61	6.33
	AN₅₀	0.05	594.63	84.78	27.18	4.51
	MN₀	0.04	643.40	73.09	25.61	3.28
	MN₂	0.04	621.03	67.44	22.53	2.75
	MN₅	0.05	646.66	89.21	25.14	4.02
	MN₁₀	0.06	618.25	58.70	34.03	3.56
	MN₂₀	0.05	804.71	53.40	35.63	2.52
	MN₅₀	0.05	462.64	30.38	22.52	1.58
直角双曲线修正模型 Modified rectangular hyperbolic model	AN₀	0.04	2330.79	67.34	13.38	2.65
	AN₂	0.09	803.48	58.68	18.42	4.87
	AN₅	0.05	1062.13	83.36	17.28	4.12
	AN₁₀	0.04	1466.33	66.05	23.10	2.63
	AN₂₀	0.15	1572.08	67.93	27.31	8.28
	AN₅₀	0.09	994.45	85.42	23.74	6.79
	MN₀	0.07	1029.66	79.84	23.45	5.05
	MN₂	0.06	982.70	75.20	21.43	4.33
	MN₅	0.07	985.91	92.46	22.90	5.98
	MN₁₀	0.09	1050.25	67.73	31.53	5.96
	MN₂₀	0.06	1398.01	58.38	30.41	3.24
	MN₅₀	0.09	921.82	44.99	21.69	3.78
Michaelis-Menten模型 Michaelis-Menten model	AN₀	-	458.81	67.99	20.23	2.94
	AN₂	-	114.68	58.72	33.48	14.10
	AN₅	-	331.17	80.92	28.94	6.69
	AN₁₀	-	821.86	71.48	41.91	3.62
	AN₂₀	-	281.80	67.96	44.09	10.08
	AN₅₀	-	259.07	80.41	40.60	11.58
	MN₀	-	315.40	78.75	38.43	9.06
	MN₂	-	279.86	74.27	34.15	8.50
	MN₅	-	289.08	85.28	38.29	10.45
	MN₁₀	-	316.26	69.90	50.58	10.68
	MN₂₀	-	718.00	65.14	52.96	4.77
	MN₅₀	-	173.14	52.86	34.30	9.64

模型 Model	处理 Treatment	初始羧化效率 Initial carboxylation efficiency （α， mol·m^-2·s^-1）	CO₂饱和点 CO₂ saturation point （C_isat， μmol·mol^-1）	CO₂补偿点 CO₂compensation point （Г， μmol·mol^-1）	最大净光合速率 Maximum net photosynthetic rate （P_nmax， μmol·m^-2·s^-1）	光呼吸速率 Light respiration rate （R_p， μmol·m^-2·s^-1）
实测值 Measured value	AN₀	0.03	1500.00	67.86	12.83	1.74
	AN₂	0.05	600.00	53.44	18.71	2.76
	AN₅	0.04	1000.00	85.18	17.01	3.33
	AN₁₀	0.03	1500.00	64.25	23.26	2.19
	AN₂₀	0.07	1200.00	69.67	27.37	4.76
	AN₅₀	0.06	1000.00	88.56	23.68	5.20
	MN₀	0.06	1000.00	82.54	23.29	4.57
	MN₂	0.05	800.00	75.20	21.19	3.54
	MN₅	0.05	800.00	93.60	22.84	4.93
	MN₁₀	0.07	1000.00	67.53	31.08	4.75
	MN₂₀	0.05	1500.00	54.34	30.46	2.52
	MN₅₀	0.06	1000.00	39.77	21.72	2.20
直角双曲线模型 Rectangular hyperbola model	AN₀	0.05	458.81	67.99	20.23	2.94
	AN₂	0.41	114.68	58.72	33.48	14.10
	AN₅	0.11	331.17	80.92	28.94	6.69
	AN₁₀	0.06	821.86	71.48	41.91	3.62
	AN₂₀	0.19	281.80	67.96	44.09	10.08
	AN₅₀	0.20	259.07	80.41	40.60	11.58
	MN₀	0.15	315.40	78.75	38.43	9.06
	MN₂	0.15	279.86	74.27	34.15	8.50
	MN₅	0.17	289.08	85.28	38.29	10.45
	MN₁₀	0.19	316.26	69.90	50.58	10.68
	MN₂₀	0.08	718.00	65.14	52.96	4.77
	MN₅₀	0.25	173.14	52.86	34.30	9.64
非直角双曲线模型 Non-rectangular hyperbola model	AN₀	0.04	547.10	67.28	18.02	2.33
	AN₂	0.05	456.88	44.46	18.72	2.02
	AN₅	0.04	639.31	80.53	19.67	2.83
	AN₁₀	0.03	862.20	62.54	27.85	2.16
	AN₂₀	0.10	439.99	68.77	36.61	6.33
	AN₅₀	0.05	594.63	84.78	27.18	4.51
	MN₀	0.04	643.40	73.09	25.61	3.28
	MN₂	0.04	621.03	67.44	22.53	2.75
	MN₅	0.05	646.66	89.21	25.14	4.02
	MN₁₀	0.06	618.25	58.70	34.03	3.56
	MN₂₀	0.05	804.71	53.40	35.63	2.52
	MN₅₀	0.05	462.64	30.38	22.52	1.58
直角双曲线修正模型 Modified rectangular hyperbolic model	AN₀	0.04	2330.79	67.34	13.38	2.65
	AN₂	0.09	803.48	58.68	18.42	4.87
	AN₅	0.05	1062.13	83.36	17.28	4.12
	AN₁₀	0.04	1466.33	66.05	23.10	2.63
	AN₂₀	0.15	1572.08	67.93	27.31	8.28
	AN₅₀	0.09	994.45	85.42	23.74	6.79
	MN₀	0.07	1029.66	79.84	23.45	5.05
	MN₂	0.06	982.70	75.20	21.43	4.33
	MN₅	0.07	985.91	92.46	22.90	5.98
	MN₁₀	0.09	1050.25	67.73	31.53	5.96
	MN₂₀	0.06	1398.01	58.38	30.41	3.24
	MN₅₀	0.09	921.82	44.99	21.69	3.78
Michaelis-Menten模型 Michaelis-Menten model	AN₀	-	458.81	67.99	20.23	2.94
	AN₂	-	114.68	58.72	33.48	14.10
	AN₅	-	331.17	80.92	28.94	6.69
	AN₁₀	-	821.86	71.48	41.91	3.62
	AN₂₀	-	281.80	67.96	44.09	10.08
	AN₅₀	-	259.07	80.41	40.60	11.58
	MN₀	-	315.40	78.75	38.43	9.06
	MN₂	-	279.86	74.27	34.15	8.50
	MN₅	-	289.08	85.28	38.29	10.45
	MN₁₀	-	316.26	69.90	50.58	10.68
	MN₂₀	-	718.00	65.14	52.96	4.77
	MN₅₀	-	173.14	52.86	34.30	9.64

模型 Model	处理 Treatment	均方根误差 Root mean square error （RMSE）	平均绝对误差 Mean absolute error （MAE）	决定系数 Coefficient of determination （R²）
直角双曲线模型 Rectangular hyperbola model	AN₀	0.26	0.20	0.996
	AN₂	2.01	1.45	0.866
	AN₅	1.07	0.74	0.968
	AN₁₀	0.59	0.43	0.994
	AN₂₀	1.18	0.88	0.983
	AN₅₀	1.67	1.18	0.959
	MN₀	1.68	1.10	0.955
	MN₂	1.89	1.24	0.927
	MN₅	2.11	1.42	0.928
	MN₁₀	1.96	1.35	0.965
	MN₂₀	0.86	0.60	0.993
	MN₅₀	1.51	1.05	0.946
非直角双曲线模型 Non-rectangular hyperbola model	AN₀	0.24	0.16	0.997
	AN₂	1.29	0.77	0.949
	AN₅	0.46	0.32	0.994
	AN₁₀	0.13	0.09	1.000
	AN₂₀	1.05	0.68	0.987
	AN₅₀	0.76	0.45	0.992
	MN₀	0.93	0.62	0.987
	MN₂	1.05	0.62	0.978
	MN₅	1.09	0.65	0.982
	MN₁₀	0.84	0.60	0.994
	MN₂₀	0.17	0.11	1.000
	MN₅₀	0.97	0.67	0.979
直角双曲线修正模型 Modified rectangular hyperbolic model	AN₀	0.25	0.17	0.996
	AN₂	0.53	0.38	0.992
	AN₅	0.26	0.20	0.998
	AN₁₀	0.24	0.18	0.999
	AN₂₀	1.11	0.76	0.985
	AN₅₀	0.34	0.26	0.998
	MN₀	0.40	0.24	0.998
	MN₂	0.37	0.29	0.997
	MN₅	0.63	0.44	0.994
	MN₁₀	0.50	0.37	0.998
	MN₂₀	0.30	0.23	0.999
	MN₅₀	0.54	0.31	0.993
Michaelis-Menten模型 Michaelis-Menten model	AN₀	0.26	0.20	0.996
	AN₂	2.01	1.45	0.866
	AN₅	1.07	0.74	0.968
	AN₁₀	0.59	0.43	0.994
	AN₂₀	1.18	0.88	0.983
	AN₅₀	1.67	1.18	0.959
	MN₀	1.68	1.10	0.955
	MN₂	1.89	1.24	0.927
	MN₅	2.11	1.42	0.928
	MN₁₀	1.96	1.35	0.965
	MN₂₀	0.86	0.60	0.993
	MN₅₀	1.51	1.05	0.946

模型 Model	处理 Treatment	均方根误差 Root mean square error （RMSE）	平均绝对误差 Mean absolute error （MAE）	决定系数 Coefficient of determination （R²）
直角双曲线模型 Rectangular hyperbola model	AN₀	0.26	0.20	0.996
	AN₂	2.01	1.45	0.866
	AN₅	1.07	0.74	0.968
	AN₁₀	0.59	0.43	0.994
	AN₂₀	1.18	0.88	0.983
	AN₅₀	1.67	1.18	0.959
	MN₀	1.68	1.10	0.955
	MN₂	1.89	1.24	0.927
	MN₅	2.11	1.42	0.928
	MN₁₀	1.96	1.35	0.965
	MN₂₀	0.86	0.60	0.993
	MN₅₀	1.51	1.05	0.946
非直角双曲线模型 Non-rectangular hyperbola model	AN₀	0.24	0.16	0.997
	AN₂	1.29	0.77	0.949
	AN₅	0.46	0.32	0.994
	AN₁₀	0.13	0.09	1.000
	AN₂₀	1.05	0.68	0.987
	AN₅₀	0.76	0.45	0.992
	MN₀	0.93	0.62	0.987
	MN₂	1.05	0.62	0.978
	MN₅	1.09	0.65	0.982
	MN₁₀	0.84	0.60	0.994
	MN₂₀	0.17	0.11	1.000
	MN₅₀	0.97	0.67	0.979
直角双曲线修正模型 Modified rectangular hyperbolic model	AN₀	0.25	0.17	0.996
	AN₂	0.53	0.38	0.992
	AN₅	0.26	0.20	0.998
	AN₁₀	0.24	0.18	0.999
	AN₂₀	1.11	0.76	0.985
	AN₅₀	0.34	0.26	0.998
	MN₀	0.40	0.24	0.998
	MN₂	0.37	0.29	0.997
	MN₅	0.63	0.44	0.994
	MN₁₀	0.50	0.37	0.998
	MN₂₀	0.30	0.23	0.999
	MN₅₀	0.54	0.31	0.993
Michaelis-Menten模型 Michaelis-Menten model	AN₀	0.26	0.20	0.996
	AN₂	2.01	1.45	0.866
	AN₅	1.07	0.74	0.968
	AN₁₀	0.59	0.43	0.994
	AN₂₀	1.18	0.88	0.983
	AN₅₀	1.67	1.18	0.959
	MN₀	1.68	1.10	0.955
	MN₂	1.89	1.24	0.927
	MN₅	2.11	1.42	0.928
	MN₁₀	1.96	1.35	0.965
	MN₂₀	0.86	0.60	0.993
	MN₅₀	1.51	1.05	0.946

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Comparison of photosynthetic-CO₂ response process and models of Leymus chinensis under differing nitrogen addition and mowing conditions

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