Testing the generality of above-ground biomass allometry across plant functional types at the continent scale
Paul, KI and Roxburgh, SH and Chave, J and England, JR and Zerihun, A and Specht, A and Lewis, T and Bennett, LT and Baker, TG and Adams, MA and Huxtable, D and Montagu, KD and Falster, DS and Feller, M and Sochacki, S and Ritson, P and Bastin, G and Bartle, J and Wildy, D and Hobbs, T and Armour, JL and Waterworth, R and Stewart, HTL and Jonson, J and Forrester, DI and Applegate, G and Mendham, D and Bradford, M and O'Grady, A and Green, D and Sudmeyer, R and Rance, SJ and Turner, J and Barton, C and Wenk, EH and Grove, T and Attiwill, PM and Pinkard, E and Butler, D and Brooksbank, K and Spencer, B and Snowdon, P and O'Brien, N and Battaglia, M and Cameron, DM and Hamilton, S and McAuthur, G and Sinclair, J, Testing the generality of above-ground biomass allometry across plant functional types at the continent scale, Global Change Biology, 22, (6) pp. 2106-2124. ISSN 1354-1013 (2016) [Refereed Article]
Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84–95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9–356 Mg ha−1). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures).