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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., Measurement(s)plant traitTechnology Type(s)digital curationSample Characteristic - OrganismViridiplantaeSample Characteristic - LocationAustralia Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14545755

As the primary decomposers of organic material in terrestrial ecosystems, fungi are critical agents of the global carbon cycle. Yet our ability to link fungal community composition to ecosystem functioning is constrained by a limited understanding of the factors accounting for different wood decomposition rates among fungi. Here we examine which traits best explain fungal decomposition ability by combining detailed trait-based assays on 34 saprotrophic fungi from across North America in the laboratory with a 5-y field study comprising 1,582 fungi isolated from 74 decomposing logs. Fungal growth rate (hyphal extension rate) was the strongest single predictor of fungal-mediated wood decomposition rate under laboratory conditions, and accounted for up to 27% of the in situ variation in decomposition in the field. At the individual level, decomposition rate was negatively correlated with moisture niche width (an indicator of drought stress tolerance) and with the production of nutrient-mineralizing extracellular enzymes. Together, these results suggest that decomposition rates strongly align with a dominance-tolerance life-history trade-off that was previously identified in these isolates, forming a spectrum from slow-growing, stress-tolerant fungi that are poor decomposers to fast-growing, highly competitive fungi with fast decomposition rates. Our study illustrates how an understanding of fungal trait variation could improve our predictive ability of the early and midstages of wood decay, to which our findings are most applicable. By mapping our results onto the biogeographic distribution of the dominance-tolerance trade-off across North America, we approximate broad-scale patterns in intrinsic fungal-mediated wood decomposition rates.

Selective logging, the targeted harvesting of timber trees in a single cutting cycle, is globally rising in extent and intensity. Short-term impacts of selective logging on tropical forests have been widely investigated, but long-term effects on temporal dynamics of forest structure and composition are largely unknown. Understanding these long-term dynamics will help determine whether tropical forests are resilient to selective logging and inform choices between competing demands of anthropogenic use versus conservation of tropical forests. Forest dynamics can be studied within the framework of succession theory, which predicts that temporal turnover rates should decline with time since disturbance. Here, we investigated the temporal dynamics of a tropical forest in Kibale National Park, Uganda over 45 years following selective logging. We estimated turnover rates in stems, species composition, and functional traits (wood density and diameter at breast height), using observations from four censuses in 1989, 1999, 2006, and 2013, of stems ≥ 10 cm diameter within 17 unlogged and 9 logged 200 × 10 m vegetation plots. We used null models to account for interdependencies among turnover rates in stems, species composition, and functional traits. We tested predictions that turnover rates should be higher and decrease with increasing time since the selective logging event in logged forest, but should be less temporally variable in unlogged forest. Overall, we found higher turnover rates in logged forest for all three attributes, but turnover rates did not decline through time in logged forest and was not less temporally variable in unlogged forest. These results indicate that successional models that assume recovery to pre-disturbance conditions are inadequate for predicting the effects of selective logging on the dynamics of the tropical forest in Kibale. Selective logging resulted in persistently higher turnover rates, which may compromise the carbon storage capacity of Kibale’s forest. Selective logging effects may also interact with effects from other global trends, potentially causing major long-term shifts in the dynamics of tropical forests. Similar studies in tropical forests elsewhere will help determine the generality of these conclusions. Ultimately, the view that selective logging is a benign approach to the management of tropical forests should be reconsidered in the light of studies of the effects of this practice on long-term forest dynamics.

When standing dead trees (snags) fall, they have major impacts on forest ecosystems. Snag fall can redistribute wildlife habitat and impact public safety, while governing important carbon (C) cycle consequences of tree mortality because ground contact accelerates C emissions during deadwood decay. Managing the consequences of altered snag dynamics in changing forests requires predicting when snags fall as wood decay erodes mechanical resistance to breaking forces. Previous studies have pointed to common predictors, such as stem size, degree of decay and species identity, but few have assessed the relative strength of underlying mechanisms driving snag fall across biomes. Here, we analyze nearly 100,000 repeated snag observations from boreal to subtropical forests across the eastern United States to show that wood decay controls snag fall in ways that could generate previously unrecognized forest-climate feedback. Warmer locations where wood decays quickly had much faster rates of snag fall. The effect of temperature on snag fall was so strong that in a simple forest C model, anticipated warming by mid-century reduced snag C by 22%. Furthermore, species-level differences in wood decay resistance (durability) accurately predicted the timing of snag fall. Differences in half-life for standing dead trees were similar to expected differences in the service lifetimes of wooden structures built from their timber. Strong effects of temperature and wood durability imply future forests where dying trees fall and decay faster than at present, reducing terrestrial C storage and snag-dependent wildlife habitat. These results can improve the representation of forest C cycling and assist forest managers by helping predict when a dead tree may fall.

Vessel length is an important but understudied dimension of variation in angiosperm vascular anatomy. Among other traits, vessel length mediates an important tradeoff between hydraulic efficiency and safety that could influence how plants respond to extreme weather with climate change. However, the functional significance of vessel length variation within individual stems is poorly known, in part because existing data analysis methods handle uncertainty in a way that makes vessel length distributions difficult to compare. We provide a solution to this problem through a hierarchical Bayesian framework for estimating vessel lengths and we demonstrate the flexibility of this method by applying it to data from serial cross sections of dye injected stems. Our approach can accelerate data collection and accommodate associated uncertainties by statistically correcting for bias and error that result from subsampling images. We illustrate our analytical framework by estimating and comparing vessel length distributions for 21 woody species characteristic of a North American forest. The best-fit model corrected for both bias due to secondary growth and sampling error within and among species. Vessel length estimates from this model varied by almost an order of magnitude and parameters of these distributions correlated with point estimates derived from a different, commonly used method. Furthermore, we show how key contrasts can be estimated with the Bayesian framework, and in doing so, we show that the shape of the vessel length distribution differed between ring- and diffuse-porous species, suggesting that within-stem vessel length variation corresponds to water stress seasonality and contributes to landscape-level habitat segregation. Our analysis method revealed the importance of within-stem variation in vessel length, and our results complement work on between-species variation in average vessel length, further illuminating how vascular anatomy can influence woody plants’ responses to water stress.

Deadwood, long recognized as playing an important role in storing carbon and releasing it as CO2 in forest ecosystems, is more recently drawing attention for its potential role in the cycling of other greenhouse trace gases. Across three Northeastern and Central US forests, mean methane (CH4) concentrations in deadwood were 23 times atmospheric levels (43.0 μL L−1 ± 12.3; mean ± SE), indicating a lower bound, mean radial wood surface area flux of ~6 × 10−4 μmol CH4 m−2 s−1. Site, decay class, log diameter, and species were all highly significant predictors of CH4 abundance in deadwood, and diameter and decay class interacted as important controls limiting CH4 concentrations in the smallest and most decayed logs. Nitrous oxide (N2O) concentrations were negatively correlated with CH4 (r2 = −0.20, p < 0.001) and on average ~25 % lower than ambient (276.9 nL L−1 ± 2.9; mean ± SE), indicating net consumption of nitrous oxide. Oxygen (O2) concentrations were uniformly near anaerobic (355.8 μL L−1 ±1.2; mean ± SE), and CO2 was elevated from atmospheric (9336.9 μL L−1 ± 600.6; mean ± SE). Most notably, our observations that CH4 concentrations were highest in the least decayed wood, may suggest that methanogenesis is not fuelled by structural wood decomposition but rather by consumption of more labile nonstructural carbohydrates.