Airborne Light Detection and Ranging (LiDAR) technology uses lasers mounted on aircraft to image the 3-D structure of trees and other objects on the ground. The unprecedented detail of LiDAR data makes it tremendously useful for forest inventory mapping, including mapping forest biomass. Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land.
RMRS Research Forester Andrew Hudak and others are developing relationships between LiDAR estimates and traditional forestry measures collected on the ground to develop maps of forest biomass and predict changes over time. Hudak and his partners used two LiDAR surveys of Moscow Mountain—a 20,000 ha (50,000 acre) actively managed forest landscape in northern Idaho—to map forest biomass in 2003 and 2009. They calculated forest biomass change over the 6-year period, and used the climate-sensitive version of the Forest Vegetation Simulator (Climate-FVS) developed by RMRS Operations Research Analyst Nicholas Crookston to simulate expected effects of climate change on forest productivity over the next 100 years. Managers can benefit from this precise, spatially explicit information for forest planning as climate changes into the future.
Repeat LiDAR surveys are useful for accurately quantifying high resolution, spatially explicit biomass and carbon dynamics in conifer forests.
Harvesting activity from 2003 to 2009 removed more carbon from the Moscow Mountain landscape than was gained through forest growth.
Change in aboveground biomass was related to forest successional status; younger stands gained two- to three-fold less biomass than did more mature stands.
Even the most mature forest stands are valuable carbon sinks, implying that longer harvest rotation cycles are likely to favor higher levels of aboveground carbon storage in mixed conifer forests of Moscow Mountain.
Simulations suggest that Moscow Mountain might experience alarming declines in forest productivity in the future due to decreased tree growth and increased tree mortality induced by climate change.
Decisions about which conifer species to plant following timber harvests can affect long-term carbon sequestration due to variation in growth rates. This study found that Pinus monticola has the highest capacity to sequester carbon, followed by Pinus ponderosa, then Pseudotsuga menziesii, and lastly Larix occidentalis.