Effects of sample size on sap flux-based stand-scale transpiration estimates.
In this study, we aimed to assess how sample sizes affect confidence of stand-scale transpiration (E) estimates calculated from sap flux (F(d)) and sapwood area (A(S_tree)) measurements of individual trees. In a Japanese cypress plantation, we measured F(d) and A(S_tree) in all trees (n = 58) within a 20 x 20 m study plot, which was divided into four 10 x 10 subplots. We calculated E from stand A(S_tree) (A(S_stand)) and mean stand F(d) (J(S)) values. Using Monte Carlo analyses, we examined the potential errors associated with sample sizes in E, A(S_stand) and J(S) using the original A(S_tree) and F(d) data sets. Consequently, we defined the optimal sample sizes of 10 and 15 for A(S_stand) and J(S) estimates, respectively, in the 20 x 20 m plot. Sample sizes larger than the optimal sample sizes did not decrease potential errors. The optimal sample sizes for J(S) changed according to plot size (e.g., 10 x 10 and 10 x 20 m), whereas the optimal sample sizes for A(S_stand) did not. As well, the optimal sample sizes for J(S) did not change in different vapor pressure deficit conditions. In terms of E estimates, these results suggest that the tree-to-tree variations in F(d) vary among different plots, and that plot size to capture tree-to-tree variations in F(d) is an important factor. The sample sizes determined in this study will be helpful for planning the balanced sampling designs to extrapolate stand-scale estimates to catchment-scale estimates.
Kume
Tomonori
T
School of Forestry and Resource Conservation, National Taiwan University, Taipei 106-17, Taiwan. kumett@ntu.edu.tw
Tsuruta
Kenji
K
Komatsu
Hikaru
H
Kumagai
Tomo'omi
T
Higashi
Naoko
N
Shinohara
Yoshinori
Y
Otsuki
Kyoichi
K
D029781:Cupressus / Q000502:physiology*; D007564:Japan; D009010:Monte Carlo Method; D018526:Plant Transpiration / Q000502:physiology*; D011156:Population Density; D011891:Rain; D015203:Reproducibility of Results; D018401:Sample Size; D014197:Trees / Q000502:physiology*