We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.

The soil in terrestrial and coastal blue carbon ecosystems is an important carbon sink. National carbon inventories require accurate assessments of soil carbon in these ecosystems to aid conservation, preservation, and nature-based climate change mitigation strategies. Here we harmonise measurements from Australia’s terrestrial and blue carbon ecosystems and apply multi-scale machine learning to derive spatially explicit estimates of soil carbon stocks and the environmental drivers of variation. We find that climate and vegetation are the primary drivers of variation at the continental scale, while ecosystem type, terrain, clay content, mineralogy and nutrients drive subregional variations. We estimate that in the top 0–30 cm soil layer, terrestrial ecosystems hold 27.6 Gt (19.6–39.0 Gt), and blue carbon ecosystems 0.35 Gt (0.20–0.62 Gt). Tall open eucalypt and mangrove forests have the largest soil carbon content by area, while eucalypt woodlands and hummock grasslands have the largest total carbon stock due to the vast areas they occupy. Our findings suggest these are essential ecosystems for conservation, preservation, emissions avoidance, and climate change mitigation because of the additional co-benefits they provide.

Question: In the Northern Hemisphere, species with dispersal limitations are typically absent from secondary forests. In Australia, little is known about dispersal mechanisms and other traits that drive species composition within post‐agricultural, secondary forest. We asked whether mode of seed dispersal, nutrient uptake strategy, fire response, and life form in extant vegetation differ according to land‐use history. We also asked whether functional traits of Australian species that confer tolerance to grazing and re‐colonisation potential differ from those in the Northern Hemisphere.Location: Delatite Peninsula, NE Victoria, Australia.Methods: The vegetation of primary and secondary forests was surveyed using a paired‐plot design. Eight traits were measured for all species recorded. ANOSIM tests and Non‐metric Multi‐dimensional Scaling were used to test differences in the abundance of plant attributes between land‐use types.Results: Land‐use history had a significant effect on vegetation composition. Specific leaf area (SLA) proved to be the best predictor of response to land‐use change. Primary forest species were typically myrmecochorous phanerophytes with low SLA. In the secondary forest, species were typically therophytes with epizoochorous dispersal and high SLA.Conclusions: The attributes of species in secondary forests provide tolerance to grazing suggesting that disturbance caused by past grazing activity determined the composition of these forests. Myrmecochores were rare in secondary forests, suggesting that species had failed to re‐colonise due to dispersal limitations. Functional traits that resulted in species loss through disturbance and prevented re‐colonisation were different to those in the Northern Hemisphere and were attributable to the sclerophyllous nature of the primary forest.

Modern approaches to predictive ecosystem mapping (PEM) have not thoroughly explored the use of ‘characteristic’ gradients, which describe vegetation structure (e.g., light detection and ranging (lidar)-derived structural profiles). In this study, we apply a PEM approach by classifying the dominant stand types within the Central Highlands region of south-eastern Australia using both lidar and species distribution models (SDMs). Similarity percentages analysis (SIMPER) was applied to comprehensive floristic surveys to identify five species which best separated stand types. The predicted distributions of these species, modelled using random forests with environmental (i.e., climate, topography) and optical characteristic gradients (Landsat-derived seasonal fractional cover), provided an ecological basis for refining stand type classifications based only on lidar-derived structural profiles. The resulting PEM model represents the first continuous distribution map of stand types across the study region that delineates ecotone stands, which are seral communities comprised of species typical of both rainforest and eucalypt forests. The spatial variability of vegetation structure incorporated into the PEM model suggests that many stand types are not as continuous in cover as represented by current ecological vegetation class distributions that describe the region. Improved PEM models can facilitate sustainable forest management, enhanced forest monitoring, and informed decision making at landscape scales.