南京林业大学学报(自然科学版) ›› 2022, Vol. 46 ›› Issue (5): 113-120.doi: 10.12302/j.issn.1000-2006.202101029
收稿日期:
2021-01-23
修回日期:
2021-03-26
出版日期:
2022-09-30
发布日期:
2022-10-19
通讯作者:
杨金艳
基金资助:
ZHANG Ruiting(), YANG Jinyan(), RUAN Honghua
Received:
2021-01-23
Revised:
2021-03-26
Online:
2022-09-30
Published:
2022-10-19
Contact:
YANG Jinyan
摘要:
【目的】从生态系统和全球尺度上考察了树干液流和生物及非生物因子之间的关系,将影响因子参数化以进行全球树干液流的估计,量化比较人为控制环境试验对液流的影响。【方法】采用数据整合分析方法,收集2001—2019年树干液流相关研究数据,从森林生态系统和全球尺度上研究树干液流密度(Fd)对生物和非生物因子的响应,并对树干液流与年平均温度(MAT)、年平均降水量(MAP)、饱和水汽压亏缺(VPD)、光合有效辐射(PAR)、土壤含水率(ρ)等主要影响因子的关系进行多元回归分析。【结果】胸径(DBH)和叶面积指数(LAI)都与Fd在生物群落和全球尺度上高度相关;VPD与Fd呈负相关关系;通过MAT、MAP、VPD、DBH和土壤体积含水率建立参数化模型可以估算树干液流密度;不同控制试验通过影响环境因子,进而影响森林蒸腾。【结论】树干液流主要受到自身生物因子和环境因子的影响并且影响程度因生态系统而异,人为活动可导致环境因子改变进而影响树干液流及蒸腾。
中图分类号:
张瑞婷,杨金艳,阮宏华. 树干液流对环境变化响应研究的整合分析[J]. 南京林业大学学报(自然科学版), 2022, 46(5): 113-120.
ZHANG Ruiting, YANG Jinyan, RUAN Honghua. Meta-analyses of responses of sap flow to changes in environmental factors[J].Journal of Nanjing Forestry University (Natural Science Edition), 2022, 46(5): 113-120.DOI: 10.12302/j.issn.1000-2006.202101029.
表1
北方、温带和热带森林生态系统中树干液流和林分蒸腾的均值、标准差和范围"
森林类型 ecosystem type | 样本量 sample size | 液流速率/(cm·h-1) sap flow rate | 样本量 sample size | 液流密度/(g·m-2·s-1) Fd | 样本量 sample size | 林分年蒸腾/mm annual transpiration | |||
---|---|---|---|---|---|---|---|---|---|
均值±标准差 mean±SD | 范围 range | 均值±标准差 mean±SD | 范围 range | 均值±标准差 mean±SD | 范围 range | ||||
北方森林 boreal forest | 4 | 9.36±2.82 | 6.84~13.34 | 17 | 18.92±13.75** | 4.17~45.56 | 12 | 518.85±324.30 | 176.40~1 093.50 |
温带森林 temperate forest | 20 | 11.95±6.16 | 4.54~24.17 | 47 | 34.28±23.44** | 8.68~108.33 | 36 | 559.20±422.14 | 122.16~1 835.50 |
热带森林 tropical forest | 10 | 12.92±7.21 | 8.30~32.92 | 22 | 23.66±21.00 | 9.94~92.00 | 22 | 572.55±293.24 | 113.05~1 190.00 |
表2
预测全球尺度液流的统计模型"
序号 No. | 自变量 independent variable | 多元线性回归模型 multiple linear regression model | n | RMSE | P | |
---|---|---|---|---|---|---|
1 | δMAT, δMAP, δPAR | dF=1.33 δMAT-0.01 δMAP+0.01 δPAR-24.85 | 37 | 139 | 0.48 | <0.001 |
2 | δMAT, δMAP, δPAR, δVPD | dF=0.99 δMAT-0.01 δMAP+0.25 δPAR-0.07 δVPD+17.45 | 35 | 124 | 0.51 | <0.001 |
3 | δMAT, δMAP, DBH, δLAI | dF=-2.95 δMAT+0.01 δMAP-0.46 DBH+8.26 δLAI+41.91 | 21 | 209 | 0.50 | <0.001 |
4 | δMAT, δMAP, δLAI, δVPD | dF=-4.17 δMAT+0.01 δMAP+7.00 δLAI+2.23 δVPD+48.62 | 21 | 237 | 0.51 | <0.001 |
5 | δMAT, δMAP, δLAI, ρ | dF=-4.58 δMAT-0.01 δMAP+9.12 δLAI-0.90 ρ+79.48 | 16 | 188 | 0.62 | <0.001 |
6 | δMAT, δMAP, δPAR, ρ | dF=-0.31 δMAT-0.001 δMAP-1.25 δPAR-1.06 ρ+62.40 | 21 | 32 | 0.68 | <0.001 |
7 | δMAT, δMAP,DBH, δLAI, ρ | dF=-1.5 δMAT-0.02 δMAP-0.3 DBH+1.95 δLAI-0.7 ρ+80.00 | 15 | 47 | 0.87 | <0.001 |
8 | δMAT, δMAP, DBH, δVPD, ρ | dF=1.06 δMAT-0.01 δMAP-0.64 DBH-6.00 δVPD-1.06 ρ+72.07 | 30 | 47 | 0.75 | <0.001 |
9 | δMAT, δMAP, δPAR DBH, ρ | dF=0.12 δMAT-0.01 δMAP-0.21 DBH-0.66 δPAR-2.02 ρ+113.22 | 19 | 30 | 0.70 | <0.001 |
10 | δMAT, δMAP, δPAR, δVPD, ρ | dF=0.82 δMAT-0.02 δMAP+16.72 δVPD-0.03 δPAR-2.32 ρ+98.76 | 20 | 35 | 0.62 | <0.001 |
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