Raw data for "Forest structure explains spatial heterogeneity of decadal carbon dynamics in a cool-temperate forest" (Takagi et al. 2024, Environ.Res. Lett. in press)

Supplemental data1
Data used to make Figs 2, 3(upper), and Fig. 2S (n=23,135).
Decadal changes in mean canopy height (ΔMCH) and net biomass (ΔB), and decadal biomass change by growth (ΔG) and by mortality (ΔM) from the year 2004 to 2014 (Fig.2 and Fig. 3(a)) and environmental and forest structural factors (Fig. 2S) with 1-ha spatial resolution. MCH and CHV are ‘mean canopy height’ and ‘canopy height variation’, respectively. Refer ‘Methods’ on how to determine each value, and caption of Fig. 2S for the codes of geology. ‘NA’ for vegetation and geology means there is no representative value for the cell (no category which cover 80% area) or not subjected to the analysis of Fig.5 (plantation).
Supplemental data 2
Data used to make Fig. 3(lower) (n=23,135).
Biomass in 2004 (B2004; Takagi et al., 2015) and decadal changes in net biomass (ΔB), and decadal biomass change by growth (ΔG) and by mortality (ΔM) from the year 2004 to 2014, and two woody residence times (WRTG, WRTM) determined as B2004/ΔG and B2004/(–ΔM), respectively with 1-ha spatial resolution.
Supplemental data 3
Data used to make Fig.4 (n=2704).
11 years average of two vegetation indices, Green ratio (GR) and Normalized Difference Vegetation Index (NDVI), and net biomass change (ΔB), growth (ΔG), and mortality (ΔM). Spatial resolution of ΔB, ΔG, and ΔM was adjusted to that of the two vegetation indices (ca. 330 m × 460 m). ‘NA’ for ΔB, ΔG, and ΔM means that the number of ΔDSM data points in the cell (nΔB, nΔG, and nΔM) is not enough (<80,000) to determine the areal average. Refer ‘Methods’ on how to determine each value.
Takagi et al. (2015) Forest biomass and volume estimation using airborne LiDAR in a cool-temperate forest of northern Hokkaido, Japan. Ecological Informatics, 26, 54-60.