OSU College of Forestry

 

Decay Class 3

Improving Biomass and Carbon Estimates for Coarse and Fine Woody Debris

  USFS

 
 
 
       
Link to Appendices, Tables and Figures
 
HOME
Introduction
Methods
Source of Data
Analysis
Results
Carbon Content
Uncertainties of Mass Estimates
Databases of Density Estimates  
Examples of Use  
Future Needs  
Literature Cited  
Acknowledgments  
Images of Species by Decay Class  
  HJ Andrews Experimental Forest  
  HJ Andrews Experimental Forest  
Future Needs

While the databases we created will be helpful for improving FWD and CWD mass estimates, they have several notable problems that limit their usefulness:

In the case of CWD, it is essential to separate the pieces inventoried into the decay classes. To be effective, the decay classes used in inventories need to be better defined so that they are repeatable. Most decay class systems are based on Douglas-fir decay patterns, however, species can differ in substantial ways. While adjustments inevitably are made in the field, these are not always documented, and therefore uncertainty as to their meaning is introduced. This uncertainty could be reduced by consistently describing decay classes so that actual differences between species and locations can be documented.

A more systematic sampling of CWD for species and locations is needed. Past sampling of CWD density has been ad hoc or related to studies of decomposition rates, the main focus of ecological studies. Ideally all the major species would be studied, the decay classes defined in objective and systematic ways, and the wood density as well as carbon content determined. Currently many major species have not been sampled or decay classes within species have been inadequately sampled (< 5 samples). By sampling the most abundant species uncertainty of mass estimates could be reduced to approximately 5%, a considerable improvement over the current uncertainty which could be as high as 50%.

FWD densities have rarely been sampled and although the current database is a logical starting place, it could be significantly improved. Current publications often do not report sample numbers or variation. Mixtures of species are often reported and while this makes sense when working within a uniform forest type, it is not efficient when mixtures of species change from place to place. A more flexible system might be derived if species values were reported because mixtures could be created continuously from this data structure. The separation of undecayed versus decayed FWD is helpful in estimating density, but separation of FWD into decay classes would reduce uncertainty. It would probably not be reasonable to classify each piece of FWD into a decay class, but a system to characterize decay state quickly would greatly reduce uncertainties in mass estimation of this pool.

Despite the lack of data on carbon concentrations in decaying wood, our review indicated that this variable does not change greatly with size or degree of decay. Compared to the uncertainty related to wood density, carbon concentrations are relatively certain. While additional sampling would be desirable, it would not be a priority relative to wood density.

Finally, it should be noted that most of these improvements are static in nature, that is they can be applied to a set of inventory-based volumes, but they do not allow one to incorporate decomposition induced density reductions over time. To make dynamic adjustments, it would be extremely valuable to know the decomposition rates of FWD and CWD. Knowledge of these rates would also allow one to directly estimate fluxes from a single inventory rather than a series of inventories. This information would also allow one to better interpret why inventory estimates are changing over time.

 
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