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Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

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.

Deadwood represents a significant carbon pool and unique biodiversity reservoir in forests and savannas but has been largely overlooked until recently. Storage and release of carbon from deadwood is controlled by interacting decomposition drivers including biotic consumers (animals and microbes) and abiotic factors (water, fire, sunlight, and freeze–thaw). Although previous research has focused mainly on forests, we synthesize deadwood studies across diverse ecosystems with woody vegetation. As changing climates and land-use practices alter the landscape, we expect accelerating but variable rates of inputs and outputs from deadwood pools. Currently, Earth system models implicitly represent only microbial consumers as drivers of wood decomposition; we show that many other factors influence deadwood pools. Forest management practices increasingly recognize deadwood as an important contributor to forest dynamics, biodiversity, and carbon budgets. Together, emerging knowledge from modeling and management suggests a growing need for additional research on deadwood contributions to carbon storage and greenhouse gas emissions. [ABSTRACT FROM AUTHOR]

Acute hypoxia increases pulmonary arterial (PA) pressures, though its effect on right ventricular (RV) function is controversial. The objective of this study was to characterize exertional RV performance during acute hypoxia. Ten healthy participants (34 ± 10 years, 7 males) completed three visits: visits 1 and 2 included non‐invasive normoxic (fraction of inspired oxygen (FiO2${F_{{\mathrm{i}}{{\mathrm{O}}_{\mathrm{2}}}}}$) = 0.21) and isobaric hypoxic (FiO2${F_{{\mathrm{i}}{{\mathrm{O}}_{\mathrm{2}}}}}$ = 0.12) cardiopulmonary exercise testing (CPET) to determine normoxic/hypoxic maximal oxygen uptake (V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$). Visit 3 involved invasive haemodynamic assessments where participants were randomized 1:1 to either Swan–Ganz or conductance catheterization to quantify RV performance via pressure–volume analysis. Arterial oxygen saturation was determined by blood gas analysis from radial arterial catheterization. During visit 3, participants completed invasive submaximal CPET testing at 50% normoxic V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$ and again at 50% hypoxic V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$ (FiO2${F_{{\mathrm{i}}{{\mathrm{O}}_{\mathrm{2}}}}}$ = 0.12). Median (interquartile range) values for non‐invasive V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$ values during normoxic and hypoxic testing were 2.98 (2.43, 3.66) l/min and 1.84 (1.62, 2.25) l/min, respectively (P < 0.0001). Mean PA pressure increased significantly when transitioning from rest to submaximal exercise during normoxic and hypoxic conditions (P = 0.0014). Metrics of RV contractility including preload recruitable stroke work, dP/dtmax, and end‐systolic pressure increased significantly during the transition from rest to exercise under normoxic and hypoxic conditions. Ventricular–arterial coupling was maintained during normoxic exercise at 50% V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$. During submaximal exercise at 50% of hypoxic V̇O2max${\dot V_{{{\mathrm{O}}_{\mathrm{2}}}{\mathrm{max}}}}$, ventricular–arterial coupling declined but remained within normal limits. In conclusion, resting and exertional RV functions are preserved in response to acute exposure to hypoxia at an FiO2${F_{{\mathrm{i}}{{\mathrm{O}}_{\mathrm{2}}}}}$ = 0.12 and the associated increase in PA pressures. Key points: The healthy right ventricle augments contractility, lusitropy and energetics during periods of increased metabolic demand (e.g. exercise) in acute hypoxic conditions.During submaximal exercise, ventricular–arterial coupling decreases but remains within normal limits, ensuring that cardiac output and systemic perfusion are maintained.These data describe right ventricular physiological responses during submaximal exercise under conditions of acute hypoxia, such as occurs during exposure to high altitude and/or acute hypoxic respiratory failure. [ABSTRACT FROM AUTHOR]

Leaf area varies within and between species, and previous work has linked this variation to environment and evolutionary history. However, many previous studies fail to examine both these factors and often are data‐limited.To address this, our study developed a new workflow using machine learning to automate the extraction of leaf area from herbarium collections of Australian eucalypts (Eucalyptus, Angophora and Corymbia). This dataset included 136,599 measurements, expanding existing data on this taxon's leaf area by roughly 50‐fold. Our methods were validated using field standard metrics of accuracy, and comparisons to manual measurements both from the present study and existing datasets.With this dataset for the eucalypt clade, we observed positive relationships between leaf area and mean annual temperature and precipitation similar to those reported for the global flora. However, these relationships were not consistently observed within species, potentially due to gene flow suppressing local adaptation. When we examined these relationships at different phylogenetic levels, the slope of trait–climate associations within lineages converged towards the overall eucalypt slope at shallow phylogenetic scales (5–12 MY), suggesting that effects of gene flow relax just above the species level.The strengthening of trait–climate correlations at evolutionary scales just beyond the intraspecific level may represent a widespread phenomenon across various traits and taxa. Future studies can unveil these relationships with the larger sample sizes of new trait datasets generated through machine learning.Synthesis. Using machine learning, researchers are able to confirm current positive global relationships between leaf area and mean annual temperature and precipitation. Additionally, they were able to take this a step further and examine how it changes across time. Here they saw that at roughly 5–12 million years ago in the phylogenetic tree, the trait–climate slope begins to show significantly less variation. Overall, the study shows the potential of machine learning in ecology, with exciting new potential findings with its use. [ABSTRACT FROM AUTHOR]

Aim: Within C3 plants, photosynthesis is a balance between CO2 supply from the atmosphere via stomata and demand by enzymes within chloroplasts. This process is dynamic and a complex but crucial aspect of photosynthesis. We sought to understand the spatial pattern in CO2 supply–demand balance on a global scale, via analysis of stable isotopes of carbon within leaves (Δ13C), which provide an integrative record of CO2 drawdown during photosynthesis. LocationGlobal. Time period1951–2011. Major taxa studiedVascular plants. Methods: We assembled a database of leaf carbon isotope ratios containing 3,979 species–site combinations from across the globe, including 3,645 for C3 species. We examined a wide array of potential climate and soil drivers of variation in Δ13C. Results: The strongest drivers of carbon isotope discrimination at the global scale included atmospheric pressure, potential evapotranspiration and soil pH, which explained 44% of the variation in Δ13C. Addition of eight more climate and soil variables (each explaining small but highly significant amounts of variation) increased the explained variation to 60%. On top of this, the largest plant trait effect was leaf nitrogen per area, which explained 11% of Δ13C variation. Main conclusions: By considering variation in Δ13C at a considerably larger scale than previously, we were able to identify and quantify key drivers in CO2 supply–demand balance previously unacknowledged. Of special note is the key role of soil properties, with greater discrimination on low-pH and high-silt soils. Unlike other plant traits, which show typically wide variation within sets of coexisting species, the global pattern in carbon stable isotope ratios is much more conservative; there is relatively narrow variation in time-integrated CO2 concentrations at the site of carboxylation among plants in a given soil and climate.

Gross primary production (GPP)-the uptake of carbon dioxide (CO2) by leaves, and its conversion to sugars by photosynthesis-is the basis for life on land. Earth System Models (ESMs) incorporating the interactions of land ecosystems and climate are used to predict the future of the terrestrial sink for anthropogenic CO21 . ESMs require accurate representation of GPP. However, current ESMs disagree on how GPP responds to environmental variations 1,2 , suggesting a need for a more robust theoretical framework for modelling 3,4 . Here, we focus on a key quantity for GPP, the ratio of leaf internal to external CO2 (χ). χ is tightly regulated and depends on environmental conditions, but is represented empirically and incompletely in today's models. We show that a simple evolutionary optimality hypothesis 5,6 predicts specific quantitative dependencies of χ on temperature, vapour pressure deficit and elevation; and that these same dependencies emerge from an independent analysis of empirical χ values, derived from a worldwide dataset of >3,500 leaf stable carbon isotope measurements. A single global equation embodying these relationships then unifies the empirical light-use efficiency model 7 with the standard model of C3 photosynthesis 8 , and successfully predicts GPP measured at eddy-covariance flux sites. This success is notable given the equation's simplicity and broad applicability across biomes and plant functional types. It provides a theoretical underpinning for the analysis of plant functional coordination across species and emergent properties of ecosystems, and a potential basis for the reformulation of the controls of GPP in next-generation ESMs.

Aim: Termites are a crucial group of macroinvertebrates regulating rates of deadwood decomposition across tropical and subtropical regions. When examining global patterns of deadwood decay, termites are treated as a homogenous group. There exist key biogeographical differences in termite distribution. One such clear distinction is the distribution of fungus‐growing termites (FGT, subfamily Macrotermitinae). Considering that climate will have shaped termite distribution and ecosystem processes, we evaluate the roles of termite distribution (presence of FGT) and climate (aridity) on global patterns in deadwood decay. Location: Between 46° N‐43° S and 175° E‐85° W. Time Period: Present (between 2016 and 2021). Major Taxa Studied: Termites (Blattodea: Termitoidae). Methods: We add salient data to an existing global dataset on deadwood decomposition, including new data from five existing sites and seven additional African sites. We analyse a dataset spanning six continents, 16 countries and 102 experimental sites. Firstly, we evaluate climatic differences (mean annual temperature, mean annual precipitation and mean annual aridity) between sites with and without FGT. Secondly, using aridity as a single comparative climate metric between sites that accounts for temperature and precipitation differences, we examine the interaction between FGT and aridity on global patterns of termite deadwood discovery and decay through multivariate logistic and linear regressions. Results: Termite‐driven decay and wood discovery increased with aridity; however, responses differed between FGT and NFGT sites. Wood discovery increased with aridity in FGT sites only, suggesting a greater role of FGT to deadwood decay in arid environments. On average, both termite discovery and decay of deadwood were approximately four times greater in regions with FGT compared with regions without FGT. Main Conclusions: Termite discovery and decay of deadwood is climate dependent, and higher decay may be through greater discovery of deadwood in FGT sites. Inclusion of biogeographical differences in termite distribution could potentially alter current and future global estimates of deadwood turnover. [ABSTRACT FROM AUTHOR]

Drylands are characterized by high spatial variability in resource availability due to sporadic rainfall, topography of the landscape and important effects of animals. Resource availability gradients may trigger patterns in decomposer population abundances and activity, which could affect ecosystem functions such as decomposition. Here, we examined the influence of resource availability gradients on the importance of termites in the decomposition of wood and grass litter. We placed wood blocks and grass litter baits in bags accessible and inaccessible to termites across wood and grass resource gradients as determined by the presence or absence of a top mammalian predator and across topographic gradients during a 9‐month period in arid Australia. We hypothesized that grass‐eating termite activity would track grass abundance and wood‐eating termite activity would track wood abundance. Termites were the predominant decomposition agent at these sites. Termites contributed to 99.5% of wood decomposition and 83.9% of grass decomposition during our study period. For wood, the termite effect was spatially variable and increased with habitat wood availability, which was greatest on dunes and where top predators were absent. However, the contribution of termites to grass litter decomposition did not track grass availability or termite abundance. The highest effects of termites on grass decomposition rates were found in habitats where the absence of top predators led to low grass availability. Our findings highlight how spatial variability in resources in addition to other factors that we do not document but are known to be influenced by the presence of top predators, such as insectivore predation rates, across the landscape could affect ecosystem functions such as decomposition. [ABSTRACT FROM AUTHOR]

Here we present 'APCalign', an R package and accompanying browser-sourced application to align and update scientific names for Australian vascular plants to the most likely currently accepted name in the Australian Plant Census (APC) or a name in the Australian Plant Names Index (APNI). Scientific names are the label assigned to unique taxon concepts by the scientific community, but this common terminology is most useful if a taxon concept is consistently referred to by the same name. These links can be broken because of either spelling mistakes or taxonomic changes. Automated tools are required to resolve taxon lists, aligning and updating long lists of possibly erroneous scientific names to the most likely currently accepted names. It is essential that tools specific to the APC/APNI be developed, because these lists specify an endorsed national-level nomenclature used in government legislation and include the uniquely Australian concept of phrase names, absent in global taxonomic datasets. To align input names to names within the APC or APNI, 'APCalign' works progressively through a sequence of checks that combine different permutations of the input name, exact versus fuzzy matches, matches that consider the entire name input versus a subset of words, and character strings that indicate a name can be resolved only to a genus or family. The aligned names are then, when possible, updated to a currently accepted taxon concept within the APC. This package should facilitate all research outputs that require diverse scientific name lists to be merged or outdated lists to be updated. To facilitate communication, research projects, biodiversity assessments and nurseries across Australia should use the scientific names accepted by the Australian Plant Census (APC), Australia's national taxonomic standard for vascular plants. Here we present 'APCalign', an R package and browser-sourced application to efficiently align and update lists of scientific names for Australian vascular plants to the most likely currently accepted name. This package will be useful for all research outputs that require diverse scientific name lists to be updated. Image by Elizabeth Wenk. [ABSTRACT FROM AUTHOR]

With changing climate, many species are projected to move poleward or to higher elevations to track suitable climates. The prediction that species will move poleward assumes that geographically marginal populations are at the edge of the species' climatic range. We studied Pinus coulteri from the center to the northern (poleward) edge of its range, and examined three scenarios regarding the relationship between the geographic and climatic margins of a species' range. We used herbarium and iNaturalist.org records to identify P. coulteri sites, generated a species distribution model based on temperature, precipitation, climatic water deficit, and actual evapotranspiration, and projected suitability under future climate scenarios. In fourteen populations from the central to northern portions of the range, we conducted field studies and recorded elevation, slope and aspect (to estimate solar insolation) to examine relationships between local and regional distributions. We found that northern populations of P. coulteri do not occupy the cold or wet edge of the species' climatic range; mid-latitude, high elevation populations occupy the cold margin. Aspect and insolation of P. coulteri populations changed significantly across latitudes and elevations. Unexpectedly, northern, low-elevation stands occupy north-facing aspects and receive low insolation, while central, high-elevation stands grow on more south-facing aspects that receive higher insolation. Modeled future climate suitability is projected to be highest in the central, high elevation portion of the species range, and in low-lying coastal regions under some scenarios, with declining suitability in northern areas under most future scenarios. For P. coulteri, the lack of high elevation habitat combined with a major dispersal barrier may limit northward movement in response to a warming climate. Our analyses demonstrate the importance of distinguishing geographically vs. climatically marginal populations, and the importance of quantitative analysis of the realized climate space to understand species range limits.

Changes in climate projected for the 21st century are expected to trigger widespread and pervasive biotic impacts. Forecasting these changes and their implications for ecosystem services is a major research goal. Much of the research on biotic responses to climate change has focused on either projected shifts in individual species distributions or broad-scale changes in biome distributions. Here, we introduce a novel application of multinomial logistic regression as a powerful approach to model vegetation distributions and potential responses to 21st century climate change. We modeled the distribution of 22 major vegetation types, most defined by a single dominant woody species, across the San Francisco Bay Area. Predictor variables included climate and topographic variables. The novel aspect of our model is the output: a vector of relative probabilities for each vegetation type in each location within the study domain. The model was then projected for 54 future climate scenarios, spanning a representative range of temperature and precipitation projections from the CMIP3 and CMIP5 ensembles. We found that sensitivity of vegetation to climate change is highly heterogeneous across the region. Surprisingly, sensitivity to climate change is higher closer to the coast, on lower insolation, north-facing slopes and in areas of higher precipitation. While such sites may provide refugia for mesic and cool-adapted vegetation in the face of a warming climate, the model suggests they will still be highly dynamic and relatively sensitive to climate-driven vegetation transitions. The greater sensitivity of moist and low insolation sites is an unexpected outcome that challenges views on the location and stability of climate refugia. Projections provide a foundation for conservation planning and land management, and highlight the need for a greater understanding of the mechanisms and time scales of potential climate-driven vegetation transitions.