Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

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).

The carbon budget of Pinus radiata plantations in south-western Australia under four climate change scenarios.

We conducted a comprehensive modelling study to estimate future stem wood production and net ecosystem production (NEP) of Pinus radiata D. Don plantations in south-western Australia, a region that is predicted to undergo severe rainfall reduction in future decades. The process-based model CenW was applied to four locations where it had previously been tested. Climate change scenarios under four emission scenarios for the period from 2005 to 2066 were considered, in addition to simulations under the current climate. Results showed that stem wood production and NEP were little affected by moderate climate change. However, under the most pessimistic climate change scenario (Special Report on Emission Scenarios A2), stem wood production and NEP decreased strongly. These results could be explained by the trade-off between the positive effect of rising atmospheric CO(2) on plant water use efficiency and the negative effects of decreasing rainfall and increasing temperatures. Because changes in heterotrophic respiration (R(H)) lagged behind changes in plant growth, and because R(H) rates were increased by higher temperatures, NEP was more negatively affected than stem wood production. Stem wood production and NEP also strongly interacted with location, with the site currently having the wettest climate being least affected by climatic change. These results suggest that realistic predictions of forest production and carbon sequestration potential in the context of climate change require (1) the use of modelling tools that describe the important feedbacks between environmental variables, plant physiology and soil organic matter decomposition, (2) consideration of a range of climate change scenarios and (3) simulations that account for a gradual climate change to capture transient effects.