Figure 1.
Thirteen CAO LiDAR mapping blocks were acquired in the southern Peruvian Amazon.
The upper inset shows location of the study region within Peru. The lower inset shows the LiDAR mapping blocks against a map of aboveground carbon density (ACD; Mg C ha−1), which integrates regional variation in geology, topography and canopy physiognomy [20].
Table 1.
Thirteen airborne LiDAR study blocks were used to map depositional-floodplain (DFP) substrates (68, 958 ha) and a variety of erosional terra firme (ETF) substrates (56,623 ha).
Figure 2.
One 13,883 ha Amazonian landscape (block 12;Figure 1) showing (a) the digital terrain model with additional processing to delineate depositional floodplain (DFP; red) and erosional terra firme (ETF; white) substrates; (b) forest canopy height derived from 3-D imaging; and zoom images to indicate differences in height and gap variation within (c) DFP and (d) ETF forests.
Each zoom image is 50 ha in size. Individual crowns are visible in red colors; forest canopy gaps are indicated in blue.
Figure 3.
Canopy structure and gap statistics for CAO mapping block 12 including: (a) the distribution of canopy height for erosional terra firme (ETF) and depositional floodplain (DFP) forests (see Figure 2); (b) the vertical distribution of power-law exponents (λ) for each forest type in block 12; and (c) the gap-size frequency distributions for ETF and DFP forests for canopy gaps at <1 m and <20 m thresholds.
Power-law exponents (λ) and the number of mapped gaps (n) are also provided.
Table 2.
Mean canopy height (± standard deviation) of forests on depositional-floodplain (DFP) and erosional terra firme (ETF) substrates (see Table 1), along with Zeta distribution (power-law) exponents (λ) of the gap-size frequency distributions for each site.
Figure 4.
Graphical representation of size-frequency distributions of canopy gaps on erosional terra firme and depositional floodplain substrates in the southwestern Peruvian Amazon at two height thresholds.
The slopes of these lines are power-law exponents from the Zeta distribution that we estimated using maximum likelihood. Additional details are in Appendices S1 and S2.