草业学报 ›› 2023, Vol. 32 ›› Issue (9): 160-172.DOI: 10.11686/cyxb2022401
• 研究论文 • 上一篇
杨斯琪1(), 鲍雅静1(), 叶佳琦1,2, 吴帅1, 张萌1, 徐梦冉1, 赵钰1, 吕晓涛3, 韩兴国4,5
收稿日期:
2022-10-07
修回日期:
2022-11-30
出版日期:
2023-09-20
发布日期:
2023-07-12
通讯作者:
鲍雅静
作者简介:
E-mail: byj@dlnu.edu.cn基金资助:
Si-qi YANG1(), Ya-jing BAO1(), Jia-qi YE1,2, Shuai WU1, Meng ZHANG1, Meng-ran XU1, Yu ZHAO1, Xiao-tao LYU3, Xing-guo HAN4,5
Received:
2022-10-07
Revised:
2022-11-30
Online:
2023-09-20
Published:
2023-07-12
Contact:
Ya-jing BAO
摘要:
草原植物光合作用受氮添加和刈割等草原管理措施的影响。依托内蒙古草甸草原的氮添加(0、2、5、10、20和50 g N·m-2·a-1)和刈割(刈割和非刈割)交互处理的野外控制试验,测定其优势物种羊草的光合-CO2响应过程。探究直角双曲线模型、非直角双曲线模型、直角双曲线修正模型和Michaelis-Menten模型对叶片光合-CO2响应曲线的拟合效果,以及光合特性对氮添加和刈割的响应。结果表明:非直角双曲线模型拟合的初始羧化效率和光呼吸速率最接近实测值;直角双曲线修正模型对CO2饱和点、CO2补偿点和最大净光合速率的拟合效果最好;直角双曲线修正模型的拟合优度最高;适度氮添加能提高羊草净光合速率、水分利用效率、最大净光合速率、初始羧化效率和CO2饱和点并降低CO2补偿点,提升羊草对CO2的利用效率;随CO2浓度的升高,氮添加浓度为20 g N·m-2·a-1并刈割的羊草净光合速率增幅较大,具有较高的最大净光合速率、CO2饱和点、水分利用效率和较低的CO2补偿点。综上,非直角双曲线模型和直角双曲线修正模型较适用于氮添加和刈割条件下羊草的CO2响应曲线拟合,在内蒙古草原施氮20 g N·m-2·a-1并刈割最有助于提高羊草光合能力,有利于增大生态系统固碳量。
杨斯琪, 鲍雅静, 叶佳琦, 吴帅, 张萌, 徐梦冉, 赵钰, 吕晓涛, 韩兴国. 氮添加和刈割条件下羊草光合-CO2响应过程及模型比较研究[J]. 草业学报, 2023, 32(9): 160-172.
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.
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 (Cisat, μmol·mol-1) | CO2补偿点 CO2 compensation point (Г, μmol·mol-1) | 最大净光合速率 Maximum net photosynthetic rate (Pnmax, μmol·m-2·s-1) | 光呼吸速率 Light respiration rate (Rp, 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 |
表1 羊草光合-CO2响应曲线参数实测值与拟合值
Table 1 The measured values of photosynthetic-CO2 response curve parameters of L. chinensis and the fitted values by models
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 (Cisat, μmol·mol-1) | CO2补偿点 CO2 compensation point (Г, μmol·mol-1) | 最大净光合速率 Maximum net photosynthetic rate (Pnmax, μmol·m-2·s-1) | 光呼吸速率 Light respiration rate (Rp, 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 |
图1 氮添加和刈割处理下不同CO2响应模型对羊草光合作用-CO2响应曲线的模拟A: 非刈割Unmowing; M: 刈割Mowing; N0: 0 g N·m-2·a-1; N2: 2 g N·m-2·a-1; N5: 5 g N·m-2·a-1; N10: 10 g N·m-2·a-1; N20: 20 g N·m-2·a-1; N50: 50 g N·m-2·a-1. 下同The same below.
Fig.1 Simulation of photosynthetic-CO2 response curves of L. chinensis by different CO2 response models under nitrogen and mowing treatments
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 |
表2 4种CO2响应模型拟合优度对比
Table 2 Comparison of goodness-of-fit on four CO2 response models
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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