Abstract
Relationships between discrete-return light detection and ranging (LiDAR) data and radiata pine leaf area index (LAI), stem volume, above ground carbon, and carbon sequestration were developed using 10 plots with directly measured biomass and leaf area data, and 36 plots with modelled carbon data. The plots included a range of genetic types established on north- and south-facing aspects. Modelled carbon was highly correlated with directly measured crown, stem, and above ground biomass data, with r = 0.92, 0.97 and 0.98, respectively. LiDAR canopy percentile height (P30) and cover, based on all returns above 0.5 m, explained 81, 88, and 93% of the variation in directly measured crown, stem, and above ground live carbon and 75, 89 and 88% of the modelled carbon, respectively. LAI (all surfaces) ranged between 8.8–19.1 in the 10 plots measured at age 9 years. The difference in canopy percentile heights (P95–P30) and cover based on first returns explained 80% of the variation in total LAI. Periodic mean annual increments in stem volume, above ground live carbon, and total carbon between ages 9 and 13 years were significantly related to (P95–P30), with regression models explaining 56, 58, and 55%, respectively, of the variation in growth rate per plot. When plot aspect and genetic type were included with (P95–P30), the R2 of the regression models for stem volume, above ground live carbon, and total carbon increment increased to 90, 88, and 88%, respectively, which indicates that LiDAR regression equations for estimating stock changes can be substantially improved by incorporating supplementary site and crop data.
Highlights
Radiata pine comprised approximately 90% of the 1.75 million hectares of planted forest estimated to occur in New Zealand in April 2009, a large proportion of which was established on grassland sites of moderate to high fertility predominantly between 1992 and 1998 [1]
Substantial differences in stem volume growth rates were evident among genetic types (Table 3), with GF30 growing approximately 7%, 18%, and 26% faster than the High Density (HD), Puruki Control (PC), and GF2 material, respectively, and 53% faster than the GF7 cuttings
A similar ranking was evident for carbon sequestration, the gain depended on wood density which averaged 316 kg/m3 (GF30), kg/m3(HD), kg/m3 (GF2), and 332 kg/m3 (PC) in breast height outerwood density cores acquired at age 9 [28]
Summary
Radiata pine comprised approximately 90% of the 1.75 million hectares of planted forest estimated to occur in New Zealand in April 2009, a large proportion of which was established on grassland sites of moderate to high fertility predominantly between 1992 and 1998 [1]. A national inventory of carbon stocks in forest that existed prior to 1 January 1990 (Pre-1990 forest) and in new forest that was established on grassland after 31 December 1989 (Post-1989 forest) is providing data for New Zealand to meet its obligations under the Kyoto Protocol and the United. The Post-1989 inventory of Kyoto Compliant forest utilises ground plots established on a 4-km grid, supplemented with discrete-return small footprint airborne LiDAR (Light Detection And Ranging), utilizing a double sampling approach that aims to improve the precision of the national estimate of carbon stock change from 2008 to 2012. The majority of LiDAR-only plots are intended to be acquired along strip samples in 2012
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