細根與土壤含水率關係之探討：以四湖海岸人工林為例

The Relationship between Fine Roots and Soil Moisture Contents: The Analysis of Szehu Coastal Plantation

洪貞伶(Jenny Hung)

指導教授 ： 邱祈榮

國立臺灣大學/生物資源暨農學院/森林環境暨資源學研究所/碩士(2009年)

https://doi.org/10.6342/NTU.2009.02138

摘要

根區土壤含水率與細根生物量密度之關係是生態水文學的研究重點之一。夏季時，不僅蒸發作用強烈，蒸散作用亦相當旺盛，森林由根區獲取大量的土壤水。水力再分配是細根使土壤含水率增加的現象，會影響植物生態系的土壤含水率。由上述兩個原因，根系分布會影響森林生態系的土壤含水率；再者，土壤含水率會影響根系分布，因此討論細根生物量密度有助於對森林生態水文過程的理解。歷年來國內少有研究探討細根生物量密度與土壤含水率之關係，但細根是森林生態水文學研究的關鍵，我們應當關注細根生物量密度在森林中所扮演的角色。
自2008 年五月中至八月底，在四湖海岸人工林以30 cm 的TDR 土壤水分感測計測量十個點的土壤含水率，分別位於林內、林緣、林外三個區域的內、中、外三個位置，和林外無植被的空地。觀測期中共有8 個土壤乾燥過程。於八月底觀測結束後，在樣點取直徑8.5 cm、深度0∼30 cm 的土柱以獲得細根樣本。土壤含水率之試驗設計為重複觀測混合模式巢式設計，第一層級是林內、林緣、草地三個區域，第二層級是內、中、外三個位置。第一部分的統計分析是以SAS 的混合統計分析程序（MIXED procedure）受制最大概似法（REML）分析土壤乾燥過程第1 日至第9 日的土壤含水率初始值變異數成分（variance components），以探討土壤含水率在林內、林緣、林外之不同區域和內、中、外不同位置是否有差異。第二部分的統計分析是以單因子變異數分析檢定三個區域的細根生物量密度之平均值是否相等。第三部分的統計分析是以線性迴歸法分析細根生物量密度對土壤含水率之影響。結果顯示在夏季的土壤乾燥過程中，從地表到30 cm 深的細根生物量密度每增加1 kg m-3，土壤含水率減少0.02。水力再分配現象在午夜至清晨之間發生，最多使土壤含水率在15 分鐘內增加0.002。

關鍵字

生態水文學 ； 土壤含水率細根 ； 水力再分配 ； 混合模式 ； 巢式設計 ； 迴歸模型

並列摘要

The relationship between the soil moisture content in the root zone and fine-root biomass density is one of the most important parts of the research in Ecohydrology. Not only the evaporation rate but also the transpiration rate is significant in summer. Therefore, forest uptakes large amount of soil moisture through the fine root. Hydraulic redistribution affects the distribution of soil moisture content in plant ecosystem by fine roots. As a result, the root distribution affects the soil moisture content in forest. Moreover, soil moisture contents can influence root distributions. Thus, a discussion on the fine-root biomass density may give us a clear understanding of the process of forest ecohydrology. In Taiwan, there has been little research on the relationship between fine-root biomass densities and soil moisture contents. However, understanding the tree root is the key to forest ecohydrology research. We must focus on the role of fine-root biomass density in forest.
The experiment used 30 cm TDR sensors to measure soil moisture contents at 10 sites in Szehu coastal plantation. There were TDR sensors in each site (Internal, Middle, and External) in each of the 3 areas (Forest, Forest Edge, and Grassland). There was only one TDR sensor on the vacant land. There were 8 soil drying processes of soil moisture from middle May to the end of August 2008. Fine root samples were from the uppermost 30 cm layer soil which were collected by 8.5-diameter-soil-core samplers at these sites at the end of August 2008. The experimental design of soil moisture contents was a repeated nested mixed model. The first class was the area (Forest, Forest Edge, and Grassland), and the second class was the site (Internal, Middle, and External). There were total of 3 kinds of statistical analyses in this investigation. The first part of the statistical analyses, which analysed the variance components of initial values of the soil moisture content of the 1st days up to the 9th days of soil drying processes, were analyzed using the MIXED procedure of SAS, the restricted maximum likelihood (REML) methodology. The first part of the statistical analyses showed whether the soil moisture contents were different not only among the 3 areas, but also among 3 sites. The second part of the statistical analyses, which aimed to know whether the mean fine-root biomass densities among the 3 areas were the same or not, was a one-way ANOVA. The third part of the statistical analyses were linear regressions which aimed to test whether and how fine-root biomass densities were related to soil moisture contents. From this investigation, 1 kg m-3 more fine–root biomass density, 0.02 less soil moisture content in the soil drying processes in summer. Hydraulic redistribution happened between midnight and dawn, and the maximum increase of the soil moisture content in 15 minutes was 0.002.

並列關鍵字

Ecohydrology ； Soil moisture content ； Fine roots ； Hydraulic redistribution ； Mixed model ； Nested design ； Regression model

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