Estimating carbon loss due to internal decay in living trees using tomography: implications for forest carbon budgets

The world's forests sequester and store vast amounts of atmospheric carbon, playing a crucial role in climate change mitigation. Internal stem decay in living trees results in the release of stored carbon back into the atmosphere, constituting an important, but poorly understood, countervailing force to carbon sequestration. The contribution of internal decay to estimates of forest carbon stocks, though likely significant, has yet to be quantified, given that an accurate method for the non-destructive quantification of internal decay has been lacking. To that end, we present here a novel and potentially transformative methodology, using sonic and electrical resistance tomography, for non-destructively quantifying the mass of stored carbon lost to internal decay in the boles of living trees. The methodology was developed using 72 northern hardwood trees (Fagus grandifolia, Acer saccharum and Betula alleghaniensis) from a late-successional forest in northwestern Connecticut, USA. Using 105 stem disks corresponding to tomographic scans and excised from 39 of the study's trees, we demonstrate the accuracy with which tomography predicts the incidence and severity of internal decay and distinguishes active decay from cavities. Carbon mass fractions and densities, measured and calculated from 508 stem disk wood samples corresponding to density categories, as predicted by sonic tomography, were used with stem disk volumes to generate indirect estimates of stem disk carbon mass accounting for decay, CSD, or assuming no decay, CND; these indirect estimates were compared with direct estimates calculated using stem disk mass, Cmass, and carbon mass fraction data. A comparison of three linear regression models with Cmass as the response variable and CSD or CND as the predictor variable ( C m a s s ∼ C S D , R2 = 0.9733, Model 1; Cmass ∼ CND, R 2 = 0.8918 ) demonstrates the accuracy with which CSD predicts Cmass. Forcing the C m a s s ∼ C S D regression through the origin resulted in improved metrics ( R 2 = 0.9930 , Model 2) for which a null hypothesis that y = x (Model 3) could not be rejected ( p < 0.000 01 ). For each of the study's 72 trees, two estimates of lower bole carbon mass-Cbole, accounting for decay, and C b o l e − N D , assuming no decay-were obtained using all three models, with the difference between Cbole and C b o l e − N D used to estimate the proportion of the lower bole's carbon lost to decay, % C d e c . Overall, tomography identified decay in 47