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).

Group physical therapy for veterans with knee osteoarthritis: study design and methodology

Physical therapy (PT) is a key component of treatment for knee osteoarthritis (OA) and can decrease pain and improve function. Given the expected rise in prevalence of knee OA and the associated demand for treatment, there is a need for models of care that cost-effectively extend PT services for patients with this condition. This manuscript describes a randomized clinical trial of a group-based physical therapy program that can potentially extend services to more patients with knee OA, providing a greater number of sessions per patient, at lower staffing costs compared to traditional individual PT. Participants with symptomatic knee OA (n = 376) are randomized to either a 12-week group-based PT program (six 1 h sessions, eight patients per group, led by a physical therapist and physical therapist assistant) or usual PT care (two individual visits with a physical therapist). Participants in both PT arms receive instruction in an exercise program, information on joint care and protection, and individual consultations with a physical therapist to address specific functional and therapeutic needs. The primary outcome is the Western Ontario and McMasters Universities Osteoarthritis Index (self-reported pain, stiffness, and function), and the secondary outcome is the Short Physical Performance Test Protocol (objective physical function). Outcomes are assessed at baseline and 12-week follow-up, and the primary outcome is also assessed via telephone at 24-week follow-up to examine sustainability of effects. Linear mixed models will be used to compare outcomes for the two study arms. An economic cost analysis of the PT interventions will also be conducted.

Capture of agricultural surplus water determines the productivity and scale of new low-rainfall woody crop industries

This paper presents a conceptual model for estimating the maximum scale of biomass processing industry that may be supported by woody crops grown in the medium and low rainfall agricultural regions of southern Australia. The model integrates paddock scale economics, water capture by woody crops, conversion of water to woody biomass, and estimation of suitable area. It enables estimates to be made of the maximum scale of implementation of commercial woody crops in various climatic regions, and the maximum amount of woody biomass that could be produced commercially within an economic transport distance of a processing facility. To demonstrate the utility of the model, potential biomass supply is estimated for 2 Western Australian wheatbelt towns, Merredin and Narrogin. These estimates are compared with the feedstock requirements of a range of different processing industries. This paper demonstrates that the rate of converting water to biomass and water capture biomass price are key determinants of the potential scale of biomass crops and processing industries in the southern Australian wheat and wool belts and hence the potential contribution of woody crops to dryland salinity management.