Quantifying the spatio-temporal variability of net primary production of the understory species, Sasa senanensis, using multipoint measuring techniques

Forest ecosystems play an important role in determining the sink/source function of photosynthetic productivity. However, most stand-level forest simulation models do not consider the effect of the understory species. As the forest understory conditions such as the light environment and leaf area distribution are spatially and temporally heterogeneous, the scaling up from spatially restricted samples to the entire landscapes requires new approaches for sampling. In order to assess the photosynthetic productivity of the dominant understory vegetation, Sasa senanensis, at different times of the year, we used some easy-to-use measurements to obtain input variables for canopy simulations. Radiometric techniques measuring canopy spectral reflectance provided information on the leaf area distribution (LAI = 1.85 ± 1.17) in a rapid and non-destructive way in the understory. The deciduous forest canopy affected the spatio-temporal variability of the understory productivity. The magnitudes of net primary production (NPP) of Sasa varied between seasons. Sasa switched from net sinks to sources of CO2 while the forest canopy was closed, with increased rates of respiration and decreased rates of photosynthesis. Modeled gross primary production of Sasa was 426 ± 175 gC m−2 year−1. It is likely that the contribution of understory species to ecosystem carbon uptake is high. The annual NPP of Sasa was 23 ± 111 gC m−2 year−1 in cool-temperature deciduous broadleaved forest. This value was underestimated in comparison with the biomass-increment data. The differences might probably be explained by the different number of sampling points. Studies of the forest ecosystem productivities need to consider the spatial and temporal distributions of the resources. Scaling up measurements from leaves and individuals to ecosystems can introduce significant errors if ignored these heterogeneities.