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The clearing of natural vegetation for agriculture has reduced the capacity of natural systems to provide ecosystem functions. Ecological restoration can restore desirable ecosystem functions, such as creating habitat for animal conservation and carbon sequestration as woody biomass. In order to maintain these beneficial ecosystem functions, restoration projects need to mature into self‐perpetuating communities. Here we compared the ecological attributes of two types of restoration, "active" tree plantings with "passive" natural forest regeneration ("natural regrowth") to existing remnant vegetation in a cleared agricultural landscape. Specifically, we measured differences between forest categories in factors that may predict future restoration failure or ecosystem collapse: aboveground plant biomass and biomass accrual over time (for regrowing stands), plant density and size class distributions, and diversity of functional groups based on seed dispersal and growth strategy traits. We found that natural regrowth and planted forests were similar in many ecological characteristics, including biomass accrual. Despite this, planted stands contained fewer tree recruit and shrub individuals, which may be due to limited recruitment in plantings. If this continues, these forests may be at risk of collapsing into nonforest states after mature trees senesce. Lower shrub density and richness of mid‐story trees may lead to lower structural complexity in planting plots, and alongside lower richness of fleshy‐fruited plant species may reduce animal resources and animal use of the restored stand. In our study region, natural regrowth may result in restored woodland communities with greater conservation and carbon mitigation value. [ABSTRACT FROM AUTHOR]

The article discusses an analysis of global patterns of variation in an individual tree. It examines the allocation of carbon acquired by plants from the atmosphere, studies with contradictory results regarding the causes of stand-level variation, and findings on correlation or interaction between tree size and climatic water deficit.

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). [ABSTRACT FROM AUTHOR]