树干液流对环境变化响应研究的整合分析

doi:10.12302/j.issn.1000-2006.202101029

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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

树干液流对环境变化响应研究的整合分析

张瑞婷(), 杨金艳(), 阮宏华

南京林业大学生物与环境学院,江苏南京 210037

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:
国家重大研发计划(2016YFD0600204);江苏省自然科学基金面上项目(BK20181400);南京林业大学科研启动基金(GXL2017013)

Meta-analyses of responses of sap flow to changes in environmental factors

ZHANG Ruiting(), YANG Jinyan(), RUAN Honghua

College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China

Received:2021-01-23 Revised:2021-03-26 Online:2022-09-30 Published:2022-10-19
Contact: YANG Jinyan

摘要/Abstract

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。

关键词: 树干液流, 胸径, 叶面积指数, 饱和水汽压亏缺, 土壤含水率

Abstract:

【Objective】The relationship between sap flow and biotic and abiotic factors was examined at the ecosystem and global scales. The influencing factors were parameterized to estimate the global sap flow, and the impact of human-controlled environmental experiments on sap flow was quantitatively analyzed.【Method】Sap flow data from 106 published studies (2001-2019) were collected for our study by using meta-analysis. The response of the sap flow density (Fd) to biotic and abiotic factors was studied at the ecosystem and global scales, and the relationships among sap flow and different factors including the mean annual temperature (MAT), mean annual precipitation (MAP), saturated vapor pressure deficit (VPD), photosynthetically active radiation (PAR), and the soil moisture content (ρ) was determined using multiple regression.【Result】The diameter at breast height (DBH) and the leaf area index (LAI) were highly correlated with Fd at the ecosystem and global scales. The VPD was negatively correlated with Fd. The Fd was estimated through a parametric model based on MAT, MAP, VPD, DBH and the soil volumetric water content. Different manipulative experiments affected forest transpiration through their effects on the associated environmental factors.【Conclusion】The sap flow is predominantly determined by biological and environmental factors and the degree of influence depends on the ecosystem. Human activities lead to changes in the environmental factors, which in turn affect the sap flow and transpiration.

Key words: sap flow, diameter at breast height, leaf area index, vapor pressure deficit, soil moisture content

中图分类号:

S718.5

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.

图/表 5

表1

图1

图2

图3

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	$R a d j 2$	P
1	δ_MAT, δ_MAP, δ_PAR	d_F=1.33 δ_MAT-0.01 δ_MAP+0.01 δ_PAR-24.85	37	139	0.48	<0.001
2	δ_MAT, δ_MAP, δ_PAR, δ_VPD	d_F=0.99 δ_MAT-0.01 δ_MAP+0.25 δ_PAR-0.07 δ_VPD+17.45	35	124	0.51	<0.001
3	δ_MAT, δ_MAP, D_BH, δ_LAI	d_F=-2.95 δ_MAT+0.01 δ_MAP-0.46 D_BH+8.26 δ_LAI+41.91	21	209	0.50	<0.001
4	δ_MAT, δ_MAP, δ_LAI, δ_VPD	d_F=-4.17 δ_MAT+0.01 δ_MAP+7.00 δ_LAI+2.23 δ_VPD+48.62	21	237	0.51	<0.001
5	δ_MAT, δ_MAP, δ_LAI, ρ	d_F=-4.58 δ_MAT-0.01 δ_MAP+9.12 δ_LAI-0.90 ρ+79.48	16	188	0.62	<0.001
6	δ_MAT, δ_MAP, δ_PAR, ρ	d_F=-0.31 δ_MAT-0.001 δ_MAP-1.25 δ_PAR-1.06 ρ+62.40	21	32	0.68	<0.001
7	δ_MAT, δ_MAP,D_BH, δ_LAI, ρ	d_F=-1.5 δ_MAT-0.02 δ_MAP-0.3 D_BH+1.95 δ_LAI-0.7 ρ+80.00	15	47	0.87	<0.001
8	δ_MAT, δ_MAP, D_BH, δ_VPD, ρ	d_F=1.06 δ_MAT-0.01 δ_MAP-0.64 D_BH-6.00 δ_VPD-1.06 ρ+72.07	30	47	0.75	<0.001
9	δ_MAT, δ_MAP, δ_PAR D_BH, ρ	d_F=0.12 δ_MAT-0.01 δ_MAP-0.21 D_BH-0.66 δ_PAR-2.02 ρ+113.22	19	30	0.70	<0.001
10	δ_MAT, δ_MAP, δ_PAR, δ_VPD, ρ	d_F=0.82 δ_MAT-0.02 δ_MAP+16.72 δ_VPD-0.03 δ_PAR-2.32 ρ+98.76	20	35	0.62	<0.001

表2

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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
森林类型 ecosystem type	样本量 sample size	均值±标准差 mean±SD	范围 range	样本量 sample size	均值±标准差 mean±SD	范围 range	样本量 sample size	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

树干液流对环境变化响应研究的整合分析

Meta-analyses of responses of sap flow to changes in environmental factors

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[1]	宋泽君, 李培培, 袁斓方, 郭小兰, 王德炉. 土壤含水率对蓝莓叶片生理及果实品质的影响[J]. 南京林业大学学报（自然科学版）, 2023, 47(3): 147-156.
[2]	何萍, 于颖, 范文义, 杨曦光. 基于4-Scale模型的人工林郁闭度遥感估测[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 23-30.
[3]	郭常酉, 郭宏仙, 王宝华. 基于气候因子的杉木单木胸径生长模型构建[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 47-56.
[4]	竹磊, 徐军亮, 章异平, 罗鹏飞, 师志强, 候佳玉, 翟乐鑫. 河南洛阳马尾松树干液流昼夜变化特征及其影响因子分析[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 92-100.
[5]	马永春, 佘诚棋, 方升佐. 不同修枝方法对杨树人工林生长、光合叶面积和主干饱满度的影响[J]. 南京林业大学学报（自然科学版）, 2021, 45(4): 137-142.
[6]	魏玉龙, 张秋良. 兴安落叶松林缘天然更新与立地环境因子的相关分析[J]. 南京林业大学学报（自然科学版）, 2020, 44(2): 165-172.
[7]	姚丹丹, 徐奇刚, 闫晓旺, 李玉堂. 基于贝叶斯方法的蒙古栎林单木树高-胸径模型[J]. 南京林业大学学报（自然科学版）, 2020, 44(1): 131-137.
[8]	朱越骅, 潘彪, 於朝广, 殷云龙, 张耀丽. ‘中山杉118’与落羽杉胸径生长及木材密度的比较研究[J]. 南京林业大学学报（自然科学版）, 2019, 43(6): 201-206.
[9]	陈霜霜,秦鹏,顾琪,王舒悰,洪为,时培建,王福升. 景观交错对毛竹林生物量的影响[J]. 南京林业大学学报（自然科学版）, 2017, 41(04): 95-100.
[10]	李程,罗鹏,李志清. 红松天然林胸径生长的空间异质性及其与地形的关系[J]. 南京林业大学学报（自然科学版）, 2017, 41(01): 129-135.
[11]	周克瑜,汪云珍,李记,姜广宇,徐爱俊. 基于Android平台的测树系统研究与实现[J]. 南京林业大学学报（自然科学版）, 2016, 40(04): 95-100.
[12]	刘华,佘春燕,白志强,李倩,刘端,韩燕梁. 喀纳斯保护区西伯利亚云杉树干液流动态变化[J]. 南京林业大学学报（自然科学版）, 2016, 40(01): 65-72.
[13]	于景鑫,刘金成,冯仲科. 森林盗伐的数字摄影测量方法及应用[J]. 南京林业大学学报（自然科学版）, 2015, 39(05): 87-92.
[14]	张宇佳,袁金国,张莎. 2002—2011年河北省植被LAI时空变化特征[J]. 南京林业大学学报（自然科学版）, 2015, 39(01): 86-92.
[15]	邓波,杨万霞,方升佐,李先民. 青钱柳幼龄期生长与木材性状表现及其性状相关分析[J]. 南京林业大学学报（自然科学版）, 2014, 38(05): 113-117.