Old coast redwood forests contain the largest amount of biomass of any forest in the world. However, as at least 95 percent of the world’s old-growth redwood forests have been logged at least once, most coast redwood forests today are very young in age. There is a huge potential for restoration to older forest conditions. LiDAR (Light Detection and Ranging) data, which are laser-based remote sensing data, can provide detailed imagery of an entire forest, enabling a more cost-effective and comprehensive picture than traditional field-based surveys. We wanted to test whether these data can be employed both to estimate forest biomass of young redwood forests, as well as to prioritize redwood forest stands as to their need for restoration. We developed multivariate regression relationships between redwood forest stand conditions observed in the field and LiDAR data to predict various forest metrics across the landscape, including stem density, basal area, quadratic mean diameter, stand density index (a measure of crowding), and canopy variability. We then summarized stand density index, coefficient of variation in average canopy height, and trees per acre by stand and used these summary statistics to develop rankings for each stand.
Results/Conclusions
Preliminary results indicate that LiDAR analysis is an effective means of identifying stands that are in jeopardy of slowing growth rates, declining health, and possible mortality, and that are in danger of never reaching late-seral conditions or optimal slope stabilization. Redwood regression equations developed from the LiDAR and field data resulted in an R2 of 0.89 for basal area, 0.90 for quadratic mean diameter, 0.80 for stand density index, and less than 0.50 for trees per acre. For older stands, the stands identified as a high priority for restoration based upon stand density index were often the same as those identified as high priority based upon canopy variability. The results were useful for more than 90 percent of the study area (the exception being some of the youngest stands).
