Abstract

The global network of eddy-covariance (EC) flux-towers has improved the understanding of the terrestrial carbon (C) cycle, however, the network has a relatively limited spatial extent compared to forest inventory data and plots. Developing methods to use inventory-based and EC flux measurements together with modeling approaches is necessary evaluate forest C dynamics across broad spatial extents. Changes in C stock change (ΔC) were computed based on repeated measurements of forest inventory plots and compared with separate measurements of cumulative net ecosystem productivity (ΣNEP) over four years (2003 – 2006) for Douglas-fir (Pseudotsuga menziesii var menziesii) dominated regeneration (HDF00), juvenile (HDF88 and HDF90) and near-rotation (DF49) aged stands (6, 18, 20, 57 years old in 2006, respectively) in coastal British Columbia. ΔC was determined from forest inventory plot data alone, and in a hybrid approach using inventory data along with litter fall data and published decay equations to determine the change in detrital pools. These ΔC-based estimates were then compared with ΣNEP measured at an eddy-covariance flux-tower (EC-flux) and modelled by the Carbon Budget Model - Canadian Forest Sector (CBM-CFS3) using historic forest inventory and forest disturbance data. Footprint analysis was used with remote sensing, soils and topography data to evaluate how well the inventory plots represented the range of stand conditions within the area of the flux-tower footprint and to spatially scale the plot data to the area of the EC-flux and model based estimates. The closest convergence among methods was for the juvenile stands while the largest divergences were for the regenerating clearcut, followed by the near-rotation stand. At the regenerating clearcut, footprint weighting of CBM-CFS3 ΣNEP increased convergence with EC flux ΣNEP, but not for ΔC. While spatial scaling and footprint weighting did not increase convergence for ΔC, they did provide confidence that the sample plots represented site conditions as measured by the EC tower. Methods to use inventory and EC flux measurements together with modeling approaches are necessary to understand forest C dynamics across broad spatial extents. Each approach has advantages and limitations that need to be considered for investigations at varying spatial and temporal scales.

Highlights

  • The global network of eddy-covariance (EC) flux-towers has improved the understanding of the terrestrial carbon (C) cycle, the network has a relatively limited spatial extent compared to forest inventory data and plots

  • To allow the comparison between measurements from the inventory plots, C budget models, and EC flux-towers, our approach consisted of four steps: first, we found the change in C based on forest inventory ground plot measurements made in 2002 and 2006; second, we developed an additional approach that utilized litterfall data and published decay equations, for a second inventory-based estimate of C stocks change; third, we defined stand attributes at a fine spatial resolution, stratified the site based on stand attributes, and weighted the two inventory plot estimates; and fourth, calculated ΔC

  • The comparison of ΔC from inventory measurements with ΣNEP from CBM-CFS3 and EC flux-tower measurements demonstrated an agreement among the methods in trends across stand seral stage; due to differences in the measurement approaches, there was some divergence in the results

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Summary

Introduction

The global network of eddy-covariance (EC) flux-towers has improved the understanding of the terrestrial carbon (C) cycle, the network has a relatively limited spatial extent compared to forest inventory data and plots. To measure the net exchange of C between land ecosystems and the atmosphere (net ecosystem exchange, NEE, with -NEE referred to as net ecosystem productivity, NEP), a global network of over 400 eddy-covariance (EC) flux stations has been established across a range of ecosystems, building an extensive data record of NEP, in some cases spanning up to two decades. The majority of these towers are located on sites not undergoing major disturbances so the fluxes measured reflect the interaction of weather, vegetation composition, stand age, and seasonal phenology. Estimates of flux-footprint climatology may demonstrate more complex geometries and continuous probability density surfaces to quantify the upwind distribution of weighting factors over long time periods (Chen et al 2009)

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