Resource information
An important consideration when interpreting eddy-covariance (EC) flux-tower measurements is the spatial distribution of forest land surface cover and soil type within the EC flux-tower footprint. At many EC flux-tower sites, there is a range of geospatial data available with the ability to estimate the spatial distribution of forest land cover and soils. Developing methods that utilize multiple geospatial data sets will result in more thorough estimates of ecosystem C stock distributions. The objective of this study was to develop, apply, and validate methods to obtain comprehensive estimates of the spatial distribution of ecosystem C stock components from live-tree, detritus, and soil pools within an EC flux-tower footprint. First, a set of geospatial data sets was collected and assessed for its predictive ability for the measured aboveground C stocks. Next, large tree and snag aboveground C stocks were estimated using two methods: (i) a geospatial regression model, and (ii) most similar neighbor (k-MSN) spatial prediction methodology, and the results were compared with those of a multiple linear regression model using light detection and ranging (LiDAR) data alone. Finally, we applied the spatial prediction methodology to estimate the spatial distribution of other C stock components (including soil C and woody debris).
