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Forest Ecosystems 2015, 2(2): 13 https://doi.org/10.1186/s40663-015-0038-3
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Comparison of carbon-stock changes, eddycovariance carbon fluxes and model estimates in coastal Douglas-fir stands in British Columbia

Show Author's Information Colin J Ferster1( ),  JA(Tony) Trofymow2,4,  Nicholas C Coops1,  Baozhang Chen1,  Thomas Andrew Black3
Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 Burnside Road West, Victoria, BC V8Z 1M5, Canada
Faculty of Land and Food Systems, University of British Columbia, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada
Department of Biology, University of Victoria, PO Box 1700, Station CSC, Victoria, BC V8W 2Y2, Canada
Keywords:
Remote sensing, Forest carbon, Micrometeorology, Biometry, Geographic information systems
Cite this article:
J Ferster C, Trofymow J, C Coops N, et al. Comparison of carbon-stock changes, eddycovariance carbon fluxes and model estimates in coastal Douglas-fir stands in British Columbia. Forest Ecosystems, 2015, 2(2): 13. https://doi.org/10.1186/s40663-015-0038-3
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Abstract Full text About this article
Background

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.

 Methods

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.

 Results

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.

 Conclusions

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.


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Abstract
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About this article

Comparison of carbon-stock changes, eddycovariance carbon fluxes and model estimates in coastal Douglas-fir stands in British Columbia

Show Author's information Colin J Ferster1( ), JA(Tony) Trofymow2,4, Nicholas C Coops1, Baozhang Chen1, Thomas Andrew Black3
Department of Forest Resources Management, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 Burnside Road West, Victoria, BC V8Z 1M5, Canada
Faculty of Land and Food Systems, University of British Columbia, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada
Department of Biology, University of Victoria, PO Box 1700, Station CSC, Victoria, BC V8W 2Y2, Canada

Abstract

Background

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.

 Methods

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.

 Results

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.

 Conclusions

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.

Keywords: Remote sensing, Forest carbon, Micrometeorology, Biometry, Geographic information systems

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Publication history
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Acknowledgements
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Publication history

Received: 18 December 2014
Accepted: 21 April 2015
Published: 07 May 2015
Issue date: June 2015

Copyright

© 2015 Ferster et al.; licensee Springer.

Acknowledgements

Acknowledgements

We thank Bob Ferris, Frank Eichel, and Glenda Russo of the Canadian Forest Service and staff of B.A. Blackwell and Associates for their help processing and collecting National Forest-inventory-style ground plot data. We also thank François Gougeon, CFS, for determining canopy tree density values for the sites and to Graham Stinson, CFS, for the CBM-CFS3 output files used in Wang et al. (2011). We thank the UBC Land and Food Systems Biometeorology and Soil Physics Group, in particular Paul Jassal, Praveena Krishnan, Kai Morgenstern, and Elyn Humphreys for their work processing EC flux data, and Zoran Nesic, Dominic Lessard, Andrew Sauter, and Andrew Hum for their work running and maintaining the EC flux tower sites. We also thank Mark Johnson for his comments and suggestions. Funding for this study was provided by the Canadian Forest Service Pacific Forestry Centre Graduate Student Award, a CFCAS grant to the Canadian Carbon Program (CCP), and Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant to NCC. The LiDAR data were acquired by Benoit St-Onge of the University of Quebec at Montreal as part of an ongoing collaborative project with funds provided by NSERC and BIOCAP.

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