Effects of sample size on sap flux-based stand-scale transpiration estimates

Abstract

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.

Canopy transpiration of a semi arid Pinus canariensis forest at a treeline ecotone in two hydrologically contrasting years

“…In these areas subjected to recurring drought, complex terrain and spatial heterogeneity, sap flow measurements are particularly suitable to assess water use at the stand level (Kume et al, 2010;Wilson et al, 2001). Furthermore, sap flow provides insights into environmental limitations and yields results comparable to that of whole forest ecosystem estimates of water use (Wilson et al, 2001).…”

Seasonal changes of azimuthal, radial, and tree-to-tree variations in sap flux affect stand transpiration estimates in a Cryptomeria japonica forest, central Taiwan

“…The most direct way to calculate E is to measure sap flux in every tree in a plot (e.g., Kelliher et al 1992;Kume et al 2010); however, this is impractical because of the energy use, costs, and maintenance involved. To overcome this difficulty, an efficient sampling strategy is required to obtain precise E estimation.…”

“…Previous studies have determined the optimal sample size for sap flux measurements (Kumagai et al 2005;Kume et al 2010). Furthermore, J s estimates were greatly affected by large trees with greater sapwood area, according to Eq.…”

“…The potential errors caused by radial and tree-to-tree variations in estimating E have been examined by several studies (Hatton et al 1995;Kumagai et al 2005;Ford et al 2007;Kume et al 2010Kume et al , 2012Shinohara et al 2013). These studies predominantly suggested that tree-to-tree variation was the major source of error in estimating E except for that of Hatton et al (1995), who indicated that the effect of within-tree variation was more pronounced in a homogeneous stand than in a heterogeneous stand.…”

Changes in canopy transpiration due to thinning of a Cryptomeria japonica plantation

“…When F d data for a tree were unavailable in a specific period, we filled the data gap using the relationship for F d between the tree and another tree. Using these data, E was estimated as (Kume et al, 2010) ( 1) where a s is the tree sapwood area, n is the number of the trees included in the plot, and A G is the ground area. a s was determined on the basis of measurements of sapwood thickness.…”