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AusTraits, a curated plant trait database for the Australian flora



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 trait
Technology Type(s) digital curation
Sample Characteristic - Organism Viridiplantae
Sample Characteristic - Location Australia

Machine-accessible metadata file describing the reported data:

Background & Summary

Species traits are essential for comparing ecological strategies among plants, both within any given vegetation and across environmental space or evolutionary lineages1,2,3,4. Broadly, a trait is any measurable property of a plant capturing aspects of its structure or function5,6,7,8. Traits thereby provide useful indicators of species’ behaviours in communities and ecosystems, regardless of their taxonomy8,9,10. Through global initiatives the volume of available trait information for plants has grown rapidly in the last two decades11,12. However, the geographic coverage of trait measurements across the globe is patchy, limiting detailed analyses of trait variation and diversity in some regions, and, more generally, development of theory accounting for the diversity of plant strategies.

One such region where trait data is sparsely documented is Australia; a continent with a flora of c. 28,900 native vascular plant taxa13 (including species, subspecies, varietas and forma). While significant investment has been made in curating and digitising herbarium collections and observation records in Australia over the last two decades (e.g. The Australian Virtual Herbarium houses ~7 million specimen occurrence records;, no complementary resource yet exists for consolidating information on plant traits. Moreover, relatively few Australian species are represented in the leading global databases. For example, the international TRY database12 has measurements for only 3830 Australian species across all collated traits. This level of species coverage limits our ability to use traits to understand and ultimately manage Australian vegetation14. While initiatives such as TRY12 and the Open Traits Network15 are working towards global synthesis of trait data, a stronger representation of Australian plant taxa in these efforts is essential, especially given the high richness and endemicity of this continental flora, and the unique contribution this makes to global floral diversity16,17.

Here we introduce the AusTraits database (hereafter AusTraits), a compilation of plant traits for the Australian flora. Currently, AusTraits draws together 283 distinct sources and contains 997,808 measurements spread across 448 different traits for 28,640 taxa. To assemble AusTraits from diverse primary sources and make data available for reuse, we needed to overcome three main types of challenges (Fig. 1): (1) Accessing data from diverse original sources, including field studies, online databases, scientific articles, and published taxonomic floras; (2) Harmonising these diverse sources into a federated resource, with common taxon names, units, trait names, and data formats; and (3) Distributing versions of the data under suitable license. To meet this challenge, we developed a workflow which draws on emerging community standards and our collective experience building trait databases.

Fig. 1

The data curation pathway used to assemble the AusTraits database. Trait measurements are accessed from original data sources, including published floras and field campaigns. Features such as variable names, units and taxonomy are harmonised to a common standard. Versioned releases are distributed to users, allowing the dataset to be used and re-used in a reproducible way.

By providing a harmonised and curated dataset on 448 plant traits, AusTraits contributes substantially to filling the gap in Australian and global biodiversity resources. Prior to the development of AusTraits, data on Australian plant traits existed largely as a series of disconnected datasets collected by individual laboratories or initiatives.

AusTraits has been developed as a standalone database, rather than as part of the existing global database TRY12, for three reasons. First, we sought to establish an engaged and localised community, actively collaborating to enhance coverage of plant trait data within Australia. We envisioned that a community would form more readily to fill gaps in national knowledge of traits with local ownership of the resource. While we will never have a counterfactual, a vibrant community excited to be part of this initiative has indeed been established and coverage is much higher for Australian species than has been achieved since TRY’s inception. Local ownership also aligns well with funding opportunities and national research priorities, and enables database coordinators to progress at their own speed. Second, we wanted to apply an entirely open-source approach to the aggregation workflow. All the code and raw files used to create the compiled database are available, and this database is freely available via a third party data repository (Zenodo) which is itself built for long term data archiving, with an established API. Finally, we targeted primary data sources, where possible, whereas TRY accepts aggregated datasets. The hope was that this would increase data quality, by removing intermediaries and easier identification of duplicates.

While independent, the overall structure of AusTraits is similar to that of TRY, ensuring the two databases will be interoperable. Both databases are founded on similar principles and terminology18,19. Increasingly, researchers and biodiversity portals are seeking to connect diverse datasets15, which is possible if they share a common foundation.

We envision AusTraits as an on-going collaborative initiative for easily archiving and sharing trait data about the Australian flora. Open access to a comprehensive resource like this will generate significant new knowledge about the Australian flora across multiple scales of interest, as well as reduce duplication of effort in the compilation of plant trait data, particularly for research students and government agencies seeking to access information on traits. In coming years, AusTraits will continue to be expanded, with integrations into other biodiversity platforms and expansion of coverage into historically neglected plant lineages in trait science, such as pteridophytes (lycophytes and ferns). Further, through international initiatives, such as the Open Traits Network, linkages are being forged between plant datasets and a variety of other organismal databases15.


Primary sources

AusTraits version 3.0.2 was assembled from 283 distinct sources, including published papers, field measurements, glasshouse and field experiments, botanical collections, and taxonomic treatments. Initially we identified a list of candidate traits of interest, then identified primary sources containing measurements for these traits, before contacting authors for access. As the compilation grew, we expanded the list of traits considered to include any measurable quantity that had been quantified for at least a moderate number of taxa (n > 20).

For a small subset of sources from herbaria, providing a text description of taxa, we used regular expressions in R to extract measurements of traits from the text. A variety of expressions were developed to extract height, leaf/seed dimensions and growth form. Error checking was completed on approximately 60% of mined measurements by visually inspecting the extracted values relative to the textual descriptions.

Trait definitions

A full list of traits and their sources appears in Supplementary Table 120,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148,149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236,237,238,239,240,241,242,243,244,245,246,247,248,249,250,251,252,253,254,255,256,257,258,259,260,261,262,263,264,265,266,267,268,269,270,271,272,273,274,275,276,277,278,279,280,281,282,283,284,285,286,287,288,289,290,291,292,293,294,295,296,297,298,299,300,301,302,303,304,305,306,307,308,309,310,311,312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327,328,329,330,331,332,333,334,335,336,337,338,339,340,341,342,343,344,345,346,347,348,349,350,351,352,353,354 . The list of sources in AusTraits was developed gradually as new datasets were incorporated, drawing from original source publications and a published thesaurus of plant characteristics19. We categorised traits based on the tissue where it is measured (bark, leaf, reproductive, root, stem, whole plant) and the type of measurement (allocation, life history, morphology, nutrient, physiological). Version 3.0.2 of AusTraits includes 358 numeric and 90 categorical traits.

Database structure

The schema of AusTraits broadly follows the principles of the established Observation and Measurement Ontology18 in that, where available, trait data are connected to contextual information about the collection (e.g. location coordinates, light levels, whether data were collected in the field or lab) and information about the methods used to derive measurements (e.g. number of replicates, equipment used). The database contains 11 elements, as described in Table 1. This format was developed to include information about the trait measurements, taxon, methods, sites, contextual information, people involved, and citation sources.

Table 1 Main elements of the harmonised AusTraits database. See Tables 28 for details on each component.

For storage efficiency, the main table of traits contains relatively little information (Table 2), but can be cross linked against other tables (Tables 38) using identifiers for dataset, site, context, observation, and taxon (Table 1). The dataset_id is ordinarily the surname of the first author and year of publication associated with the source’s primary citation (e.g. Blackman_2014). Trait values were also recorded as being one of several possible value types (value_type) (Table 9), reflecting the type of measurement submitted by the contributor, as different sources provide different levels of detail. Possible values include raw_value, individual_mean, site_mean, multisite_mean, expert_mean, experiment_mean. Further details on the methods used for collecting each trait are provided in a methods table (Table 5).

Table 2 Structure of the traits table, containing measurements of plant traits.
Table 3 Structure of the sites table, containing observations of site characteristics associated with information in traits.
Table 4 Structure of the contexts table, containing observations of contextual characteristics associated with information in traits.
Table 5 Structure of the methods table, containing details on methods with which data were collected, including time frame and source.
Table 6 Structure of the taxonomic_updates table, of all taxonomic changes implemented in the construction of AusTraits. Changes are determined by comparing against the APC (Australian Plant Census) and APNI (Australian Plant Name Index).
Table 7 Structure of the taxa table, containing details on taxa associated with information in the traits table. This information has been sourced from the APC (Australian Plant Census) and APNI (Australian Plant Name Index) and is released under a CC-BY3 license.
Table 8 Structure of the contributors table, of people contributing to each study.
Table 9 Possible value types of trait records.


To harmonise each source into the common AusTraits format we applied a reproducible and transparent workflow (Fig. 1), written in R355, using custom code, and the packages tidyverse356, yaml357, remake358, knitr359, and rmarkdown360. In this workflow, we performed a series of operations, including reformatting data into a standardised format, generating observation ids for each set of linked measurements, transforming variable names into common terms, transforming data into common units, standardising terms (trait values) for categorical variables, encoding suitable metadata, and flagging data that did not pass quality checks. Details from each primary source were saved with minimal modification into two plain text files. The first file, data.csv, contains the actual trait data in comma-separated values format. The second file, metadata.yml, contains relevant metadata for the study, as well as options for mapping trait names and units onto standard types, and any substitutions applied to the data in processing. These two files provide all the information needed to compile each study into a standardised AusTraits format. Successive versions of AusTraits iterate through the steps in Fig. 1, to incorporate new data and correct identified errors, leading to a high-quality, harmonised dataset.

After importing a study, we generated a detailed report which summarised the study’s metadata and compared the study’s data values to those collected by other studies for the same traits. Data for continuous and categorical variables are presented in scatter plots and tables respectively. These reports allow first the AusTraits data curator, followed by the data contributor, to rapidly scan the metadata to confirm it has been entered correctly and the trait data to ensure it has been assigned the correct units and their categorical traits values are properly aligned with AusTraits trait values.


We developed a custom workflow to clean and standardise taxonomic names using the latest and most comprehensive taxonomic resources for the Australian flora: the Australian Plant Census (APC)13 and the Australian Plant Name Index (APNI)361. These resources document all known taxonomic names for Australian plants, including currently accepted names and synonyms. While several automated tools exist for updating taxonomy, such as taxize362, these do not currently include up to date information for Australian taxa. Updates were completed in two steps. In the first step, we used both direct and then fuzzy matching (with up to 2 characters difference) to search for an alignment between reported names and those in three name sets: 1) All accepted taxa in the APC, 2) All known names in the APC, 3) All names in the APNI. Names were aligned without name authorities, as we found this information was rarely reported in the raw datasets provided to us. Second, we used the aligned name to update any outdated names to their current accepted name, using the information provided in the APC. If a name was recorded as being both an accepted name and an alternative (e.g. synonym) we preferred the accepted name, but also noted the alternative records. For phrase names, when a suitable match could not be found, we manually reviewed near matches via web portals such as the Atlas of Living Australia to find a suitable match. The final resource reports both the original and the updated taxon name alongside each trait record (Table 2), as well as an additional table summarising all taxonomic name changes (Table 6) and further information from the APC and APNI on all taxa included (Table 7). Any changes in taxonomy are exposed within the compiled dataset, enabling researchers to review these as needed.

Data Records


Static versions of AusTraits, including version 3.0.2 used in this descriptor, are available via Zenodo363. Data is released under a CC-BY license enabling reuse with attribution – being a citation of this descriptor and, where possible, original sources. Deposition within Zenodo helps makes the dataset consistent with FAIR principles364. As an evolving data product, successive versions of AusTraits are being released, containing updates and corrections. Versions are labeled using semantic versioning to indicate the change between versions365. As validation (see Technical Validation, below) and data entry are ongoing, users are recommended to pull data from release, to ensure results in their downstream analyses remain consistent as the database is updated.

The R package austraits ( provides easy access to data and examples on manipulating data (e.g. joining tables, subsetting) for those using this platform.

Data coverage

The number of accepted vascular plant taxa in the APC (as of May 2020) is around 28,98113. Version 3.0.2 of AusTraits includes at least one record for 26,852 taxa (~93% of known taxa). Five traits (leaf_length, leaf_width, plant_height, life_history, plant_growth_form) have records for more than 50% of known species (Fig. 2a). Across all traits, the median number of taxa with records is 62. Supplementary Table 1 shows the number of studies, taxa, and families with data in AusTraits, as well as the number of geo-referenced records, for each trait. Looking across traits and tissue categories, coverage declined gradually, with moderate coverage(>20%) for more than 50 traits (Fig. 2). Coverage for root, stem and bark traits declined much faster than trait measurements for other plant tissues (Fig. 2b).

Fig. 2

Coverage of traits by taxa. (a) Matrix showing the coverage of taxa for each trait, with yellow indicating presence of data. The figure was generated with a subset of 500 randomly selected taxa. (b) Number of taxa with data for first 100 traits for all traits and separated by tissue.

The most common traits are non geo-referenced records from floras; these are trait values representing a continental or region mean (or spread) and hence are not linked to a location. Yet, geo-referenced records were available for several traits for more than 10% of the flora (Fig. 3a). Coverage is notably higher for geo-referenced measurements of some tissues and trait types - such as bark stems and roots - relative to non-geo-referenced measurements (Fig. 3).

Fig. 3

Number of taxa with trait records by plant tissue and trait category, for data that are (a) Geo-referenced, and (b) Not geo-referenced. Many records without a geo-reference come from botanical collections, such as floras.

Trait records are spread across the climate space of Australia (Fig. 4a), as well as geographic locations (Fig. 4b). As with most data in Australia, the density of records was somewhat concentrated around cities or roads in remote regions.

Fig. 4

Coverage of geo-referenced trait records across Australian climatic and geographic space for traits in different categories. (a) AusTraits’ sites (orange) within Australia’s precipitation-temperature space (dark-grey) superimposed upon Whittaker’s classification of major biomes by climate370. Climate data were extracted at 10" resolution from WorldClim371. (b) Locations of geo-referenced records for different plant tissues.

Overall trait coverage across an estimated phylogenetic tree of Australian plant species is relatively unbiased (Fig. 5), though there are some notable exceptions. One exception is for root traits, where taxa within Poaceae have large amounts of information available relative to other plant families. A cluster of taxa within the family Myrtaceae which are largely from Western Australia have little leaf information available.

Fig. 5

Phylogenetic distribution of trait data in AusTraits for a subset of 2000 randomly sampled taxa. The heatmap colour intensity denotes the number of traits measured within a family for each plant tissue. The most widespread family names (with more than ten taxa) are labelled on the edge of the tree.

Comparing coverage in AusTraits to the global database TRY, there were 76 traits overlapping. Of these, AusTraits tended to contain records for more taxa, but not always; multiple traits had more than 10 times the number of taxa represented in AusTraits (Fig. 6). However, there were more records in TRY for 25 traits, in particular physiological leaf traits. Many traits were not overlapping between the two databases (Fig. 6). We noted that AusTraits includes more seed and fruit nutrient data; possibly reflecting the interest in Australia in understanding how fruit and seeds are provisioned in nutrient-depauperate environments. AusTraits includes more categorical values, especially variables documenting different components of species’ fire response strategies, reflecting the importance of fire in shaping Australian communities and the research to document different strategies species have evolved to succeed in fire-prone environments.

Fig. 6

The number of taxa with trait records in AusTraits and global TRY database (accessed 28 May 2020). Each point shows a separate trait.

Technical Validation

We implemented three strategies to maintain data quality. First, we conducted a detailed review of each source based on a bespoke report, showing all data and metadata, by both an AusTraits curator (primarily Wenk) and the original contributor (where possible). Measurements for each trait were plotted against all other values for the trait in AusTraits, allowing quick identification of outliers. Corrections suggested by contributors were combined back into AusTraits and made available with the next release. Version 3.0.2 of AusTraits, described here, is the sixth release.

Second, we implemented automated tests for each dataset, to confirm that values for continuous traits fall within the accepted range for the trait, and that values for categorical traits are on a list of allowed values. Data that did not pass these tests were moved to a separate spreadsheet (“excluded_data”) that is also made available for use and review.

Third, we provide a pathway for user feedback. AusTraits is an open-source community resource and we encourage engagement from users on maintaining the quality and usability of the dataset. As such, we welcome reporting of possible errors, as well as additions and edits to the online documentation for AusTraits that make using the existing data, or adding new data, easier for the community. Feedback can be posted as an issue directly at the project’s GitHub page (

Usage Notes

Each data release is available in multiple formats: first, as a compressed folder containing text files for each of the main components, second, as a compressed R object, enabling easy loading into R for those using that platform.

Using the taxon names aligned with the APC, data can be queried against location data from the Atlas of Living Australia. To create the phylogenetic tree in Fig. 6, we pruned a master tree for all higher plants366 using the package V.PhyloMaker367 and visualising via ggtree368. To create Fig. 3a, we used the package plotbiomes369 to create the baseline plot of biomes.

Code availability

All code, raw and compiled data are hosted within GitHub repositories under the Trait Ecology and Evolution organisation ( The archived material includes all data sources and code for rebuilding the compiled dataset. The code used to produce this paper is available at


  1. 1.

    Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89 (2014).

    ADS  CAS  PubMed  Article  Google Scholar 

  2. 2.

    Cornwell, W. K. et al. Functional distinctiveness of major plant lineages. J. Ecol. 102, 345–356 (2014).

    Article  Google Scholar 

  3. 3.

    Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167 (2016).

    ADS  PubMed  Article  CAS  Google Scholar 

  4. 4.

    Kunstler, G. et al. Plant functional traits have globally consistent effects on competition. Nature 529, 204 (2016).

    ADS  CAS  PubMed  Article  Google Scholar 

  5. 5.

    Chapin, F. S. III, Autumn, K. & Pugnaire, F. Evolution of suites of traits in response to environmental stress. Am. Nat. 142, S78–S92 (1993).

    Article  Google Scholar 

  6. 6.

    Adler, P. B. et al. Functional traits explain variation in plant life history strategies. Proc. Natl. Acad. Sci. USA 111, 740–745 (2014).

    ADS  CAS  PubMed  Article  Google Scholar 

  7. 7.

    Diaz, S., Cabido, M. & Casanoves, F. Plant functional traits and environmental filters at a regional scale. J. Veg. Sci. 9, 113–122 (1998).

    Article  Google Scholar 

  8. 8.

    Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).

    Article  Google Scholar 

  9. 9.

    Westoby, M. A leaf-height-seed (LHS) plant ecol. Strategy scheme. Plant Soil 199, 213–227 (1998).

    CAS  Article  Google Scholar 

  10. 10.

    Funk, J. L. et al. Revisiting the holy grail: Using plant functional traits to understand ecological processes. Biol. Rev. 92, 1156–1173 (2017).

    PubMed  Article  PubMed Central  Google Scholar 

  11. 11.

    Kattge, J. et al. TRY a global database of plant traits. Glob. Chang. Biol. 17, 2905–2935 (2011).

    ADS  PubMed Central  Article  Google Scholar 

  12. 12.

    Kattge, J. et al. TRY plant trait database enhanced coverage and open access. Glob. Chang. Biol. 26, 119–188 (2020).

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  13. 13.

    CHAH. Australian Plant Census, Centre of Australian National Biodiversity Research. (2020).

  14. 14.

    Kissling, W. D. et al. Towards global data products of Essential Biodiversity Variables on species traits. Nat. Ecol. Evol. 2, 1531–1540 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  15. 15.

    Gallagher, R. V. et al. Open Science principles for accelerating trait-based science across the Tree of Life. Nat. Ecol. Evol. 4, 294–303 (2020).

    PubMed  Article  PubMed Central  Google Scholar 

  16. 16.

    Chapman, A. D. et al. Numbers of living species in Australia and the world. (Australian Government, 2009).

  17. 17.

    Hopper, S. D. & Gioia, P. The Southwest Australian Floristic Region: Evolution and conservation of a global hot spot of biodiversity. Annual Review of Ecology, Evolution, and Systematics 35, 623–650 (2004).

    Article  Google Scholar 

  18. 18.

    Madin, J. et al. An ontology for describing and synthesizing ecological observation data. Ecol. Inform. 2, 279–296 (2007).

    Article  Google Scholar 

  19. 19.

    Garnier, E. et al. Towards a thesaurus of plant characteristics: An ecological contribution. J. Ecol. 105, 298–309 (2017).

    Article  Google Scholar 

  20. 20.

    Adams, M. A. M, P. & Attiwill. Role of Acacia spp. in nutrient balance and cycling in regenerating Eucalyptus regnans F. Muell. forests. I. Temporal changes in biomass and nutrient content. Aust. J. Bot. 32, 205–215 (1984).

    CAS  Google Scholar 

  21. 21.

    Ahrens, C. W. et al. Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change. Ecol. Evo. 10, 232–248 (2019).

    Article  Google Scholar 

  22. 22.

    Australian National Botanic Gardens. The National Seed Bank. (2018).

  23. 23.

    Angevin, T. Species richness and functional trait diversity response to land use in a temperate eucalypt woodland community. (La Trobe University, 2011).

  24. 24.

    Apgaua, D. M. G. et al. Functional traits and water transport strategies in lowland tropical rainforest trees. PLoS One 10, e0130799 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  25. 25.

    Apgaua, D. M. G. et al. Plant functional groups within a tropical forest exhibit different wood functional anatomy. Funct. Ecol. 31, 582–591 (2017).

    Article  Google Scholar 

  26. 26.

    Ashton, D. H. Studies of litter in Eucalyptus regnans forests. Aust. J. Bot. 23, 413–433 (1975).

    CAS  Article  Google Scholar 

  27. 27.

    Ashton, D. H. Phosphorus in forest ecosystems at Beenak, Victoria. The J. Ecol. 64, 171–186 (1976).

    CAS  Google Scholar 

  28. 28.

    Attiwill, P. M. Nutrient cycling in a Eucalyptus obliqua (L’Herit.) forest IV: Nutrient uptake and nutrient return. Aust. J. Bot. 28, 199–222 (1980).

    CAS  Article  Google Scholar 

  29. 29.

    Barlow, B. A., Clifford, H. T., George, A. S. & McCusker, A. K. A. Flora of Australia. (1981).

  30. 30.

    Bean, A. R. A revision of Baeckea (Myrtaceae) in eastern Australia, Malesia and south-east Asia. Telopea 7, 245–268 (1997).

    Article  Google Scholar 

  31. 31.

    Bell, L.C. Nutrient requirements for the establishment of native flora at Weipa. (Comalco Aluminium Ltd., 1985).

  32. 32.

    Bennett, L. T. & Attiwill, P. M. The nutritional status of healthy and declining stands of Banksia integrifolia on the Yanakie Isthmus, Victoria. Aust. J. Bot. 45, 15–30 (1997).

    Article  Google Scholar 

  33. 33.

    Bevege, D. I. Biomass and nutrient distribution in indigenous forest ecosystems. vol. 6 20 (Queensland Department of Forestry, 1978).

  34. 34.

    Birk, E. M. & Turner, J. Response of flooded gum (E. grandis) to intensive cultural treatments: biomass and nutrient content of eucalypt plantations and native forests. For. Ecol. Manage. 47, 1–28 (1992).

    Article  Google Scholar 

  35. 35.

    Blackman, C. J., Brodribb, T. J. & Jordan, G. J. Leaf hydraulic vulnerability is related to conduit dimensions and drought resistance across a diverse range of woody angiosperms. New Phytol. 188, 1113–1123 (2010).

    PubMed  Article  Google Scholar 

  36. 36.

    Blackman, C. J. et al. Leaf hydraulic vulnerability to drought is linked to site water availability across a broad range of species and climates. Ann. Bot. 114, 435–440 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  37. 37.

    Blackman, C. J. et al. The links between leaf hydraulic vulnerability to drought and key aspects of leaf venation and xylem anatomy among 26 Australian woody angiosperms from contrasting climates. Ann. Bot. 122, 59–67 (2018).

    PubMed  PubMed Central  Article  Google Scholar 

  38. 38.

    Bloomfield, K. J. et al. A continental-scale assessment of variability in leaf traits: Within species, across sites and between seasons. Funct. Ecol. 32, 1492–1506 (2018).

    Article  Google Scholar 

  39. 39.

    Bolza, E. Properties and uses of 175 timber species from Papua New Guinea and West Irian. (Victoria (Australia) CSIRO, Div. of Building Research, 1975).

  40. 40.

    Bragg, J. G. & Westoby, M. Leaf size and foraging for light in a sclerophyll woodland. Funct. Ecol. 16, 633–639 (2002).

    Article  Google Scholar 

  41. 41.

    Brisbane Rainforest Action and Information Network. Trait measurements for Australian rainforest species. (2016).

  42. 42.

    Briggs, A. L. & Morgan, J. W. Seed characteristics and soil surface patch type interact to affect germination of semi-arid woodland species. Plant Ecol. 212, 91–103 (2010).

    Article  Google Scholar 

  43. 43.

    Brock, J. & Dunlop, A. Native plants of northern Australia. (Reed New Holland, 1993).

  44. 44.

    Brodribb, T. J. & Cochard, H. Hydraulic failure defines the recovery and point of death in water-stressed conifers. Plant Physiol. 149, 575–584 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Buckton, G. et al. Functional traits of lianas in an Australian lowland rainforest align with post-disturbance rather than dry season advantage. Austral Ecol. 44, 983–994 (2019).

    Article  Google Scholar 

  46. 46.

    Burgess, S. S. O. & Dawson, T. E. Predicting the limits to tree height using statistical regressions of leaf traits. New Phytol. 174, 626–636 (2007).

    CAS  PubMed  Article  Google Scholar 

  47. 47.

    Burrows, G. E. Comparative anatomy of the photosynthetic organs of 39 xeromorphic species from subhumid New South Wales, Australia. Int. J. Plant Sci. 162, 411–430 (2001).

    Article  Google Scholar 

  48. 48.

    Butler, D. W., Gleason, S. M., Davidson, I., Onoda, Y. & Westoby, M. Safety and streamlining of woody shoots in wind: an empirical study across 39 species in tropical Australia. New Phytol. 193, 137–149 (2011).

    PubMed  Article  Google Scholar 

  49. 49.

    CAB International. Forestry Compendium. (2009).

  50. 50.

    Caldwell, E., Read, J. & Sanson, G. D. Which leaf mechanical traits correlate with insect herbivory among feeding guilds? Ann. Bot. 117, 349–361 (2015).

    PubMed  PubMed Central  Google Scholar 

  51. 51.

    Canham, C. A., Froend, R. H. & Stock, W. D. Water stress vulnerability of four Banksia species in contrasting ecohydrological habitats on the Gnangara Mound. Western Australia. Plant Cell Envrion. 32, 64–72 (2009).

    Article  Google Scholar 

  52. 52.

    Carpenter, R. J. Cuticular morphology and aspects of the ecology and fossil history of North Queensland rainforest Proteaceae. Bot. J. Linn. Soc. 116, 249–303 (1994).

    Article  Google Scholar 

  53. 53.

    Carpenter, R. J., Hill, R. S. & Jordan, G. J. Leaf Cuticular Morphology Links Platanaceae and Proteaceae. Int. J. Plant Sci. 166, 843–855 (2005).

    Article  Google Scholar 

  54. 54.

    Catford, J. A., Downes, B. J., Gippel, C. J. & Vesk, P. A. Flow regulation reduces native plant cover and facilitates exotic invasion in riparian wetlands. J. Appl. Ecol. 48, 432–442 (2011).

    Article  Google Scholar 

  55. 55.

    Catford, J. A., Morris, W. K., Vesk, P. A., Gippel, C. J. & Downes, B. J. Species and environmental characteristics point to flow regulation and drought as drivers of riparian plant invasion. Divers. Distrib. 20, 1084–1096 (2014).

    Article  Google Scholar 

  56. 56.

    Cernusak, L. A., Hutley, L. B., Beringer, J. & Tapper, N. J. Stem and leaf gas exchange and their responses to fire in a north Australian tropical savanna. Plant Cell Envrion. 29, 632–646 (2006).

    Article  Google Scholar 

  57. 57.

    Cernusak, L. A., Hutley, L. B., Beringer, J., Holtum, J. A. M. & Turner, B. L. Photosynthetic physiology of eucalypts along a sub-continental rainfall gradient in northern Australia. Agric. For. Meteorol. 151, 1462–1470 (2011).

    ADS  Article  Google Scholar 

  58. 58.

    Chandler, G. T., Crisp, M. D., Cayzer, L. W. & Bayer, R. J. Monograph of Gastrolobium (Fabaceae: Mirbelieae). Aust. Syst. Bot. 15, 619–739 (2002).

    Article  Google Scholar 

  59. 59.

    Chave, J. et al. Towards a worldwide wood economics spectrum. Ecol. Lett. 12, 351–366 (2009).

    PubMed  Article  Google Scholar 

  60. 60.

    Cheal, D. Growth stages and tolerable fire intervals for Victoria’s native vegetation data sets. (Victorian Government Department of Sustainability; Environment Melbourne, 2010).

  61. 61.

    Cheesman, A. W., Duff, H., Hill, K., Cernusak, L. A. & McInerney, F. A. Isotopic and morphologic proxies for reconstructing light environment and leaf function of fossil leaves: A modern calibration in the Daintree Rainforest, Australia. Am. J. Bot. 107, 1165–1176 (2020).

    CAS  PubMed  Article  Google Scholar 

  62. 62.

    Chen et al. Plants show more flesh in the tropics: Variation in fruit type along latitudinal and climatic gradients. Ecography 40, 531–538 (2017).

    Article  Google Scholar 

  63. 63.

    Chinnock, R. J. Eremophila and allied genera: A monograph of the plant family Myoporaceae. (Rosenberg, 2007).

  64. 64.

    Choat, B., Ball, M. C., Luly, J. G. & Holtum, J. A. M. Hydraulic architecture of deciduous and evergreen dry rainforest tree species from north-eastern Australia. Trees 19, 305–311 (2005).

    Article  Google Scholar 

  65. 65.

    Choat, B., Ball, M. C., Luly, J. G., Donnelly, C. F. & Holtum, J. A. M. Seasonal patterns of leaf gas exchange and water relations in dry rain forest trees of contrasting leaf phenology. Tree Physiol. 26, 657–664 (2006).

    PubMed  Article  Google Scholar 

  66. 66.

    Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755 (2012).

    ADS  CAS  PubMed  Article  Google Scholar 

  67. 67.

    Chudnoff, M. Tropical timbers of the world. 472 (US Department of Agriculture, Forest Service, 1984).

  68. 68.

    The French agricultural research and international cooperation organization (CIRAD). Wood density data. (2009).

  69. 69.

    Clarke, P. J. et al. A synthesis of postfire recovery traits of woody plants in Australian ecosystems. Sci. Total Environ. 534, 31–42 (2015).

    ADS  CAS  PubMed  Article  Google Scholar 

  70. 70.

    Cooper, W. & Cooper, W. T. Fruits of the Australian tropical rainforest. (Nokomis Editions, 2004).

  71. 71.

    Cooper, W. & Cooper, W. T. Australian rainforest fruits. 272 (CSIRO Publishing, 2013).

  72. 72.

    Cornwell, W. K. Causes and consequences of functional trait diversity: plant community assembly and leaf decomposition. (Stanford University, California, 2006).

  73. 73.

    Centre for Plant Biodiversity Research. EUCLID 2.0: Eucalypts of Australia. (2002).

  74. 74.

    Craven, L. A., A taxonomic revision of Calytrix Labill. (Myrtaceae). Brunonia 10, 1–138 (1987).

    Article  Google Scholar 

  75. 75.

    Craven, L. A., Lepschi, B. J. & Cowley, K. J. Melaleuca (Myrtaceae) of Western Australia: Five new species, three new combinations, one new name and a new state record. Nuytsia 20, 27–36 (2010).

    Google Scholar 

  76. 76.

    Crisp, M. D., Cayzer, L., Chandler, G. T. & Cook, L. G. A monograph of Daviesia (Mirbelieae, Faboideae, Fabaceae). Phytotaxa 300, 1–308 (2017).

    Article  Google Scholar 

  77. 77.

    Cromer, R. N., Raupach, M., Clarke, A. R. P. & Cameron, J. N. Eucalypt plantations in Australia - the potential for intensive production and utilization. Appita J. 29, 165–173 (1975).

    Google Scholar 

  78. 78.

    Cross, E. The characteristics of natives and invaders: A trait-based investigation into the theory of limiting similarity. (La Trobe University, 2009).

  79. 79.

    Crous, K. Y. et al. Photosynthesis of temperate Eucalyptus globulus trees outside their native range has limited adjustment to elevated CO2 and climate warming. Glob. Chang. Biol. 19, 3790–3807 (2013).

    ADS  PubMed  Article  Google Scholar 

  80. 80.

    Crous, K. Y., Wujeska-Klause, A., Jiang, M., Medlyn, B. E. & Ellsworth, D. S. Nitrogen and phosphorus retranslocation of leaves and stemwood in a mature Eucalyptus forest exposed to 5 years of elevated CO2. Front. Plant. Sci. 10, art664 (2019).

    Article  Google Scholar 

  81. 81.

    Cunningham, S. A., Summerhayes, B. & Westoby, M. Evolutionary divergences in leaf structure and chemistry, comparing rainfall and soil nutrient gradients. Ecol. Monogr. 69, 569–588 (1999).

    Article  Google Scholar 

  82. 82.

    Curran, T. J., Clarke, P. J. & Warwick, N. W. M. Water relations of woody plants on contrasting soils during drought: does edaphic compensation account for dry rainforest distribution? Aust. J. Bot. 57, 629–639 (2009).

    Article  Google Scholar 

  83. 83.

    Curtis, E. M., Leigh, A. & Rayburg, S. Relationships among leaf traits of Australian arid zone plants: alternative modes of thermal protection. Aust. J. Bot. 60, 471–483 (2012).

    Article  Google Scholar 

  84. 84.

    Denton, M. D., Veneklaas, E. J., Freimoser, F. M. & Lambers, H. Banksia species (Proteaceae) from severely phosphorus-impoverished soils exhibit extreme efficiency in the use and re-mobilization of phosphorus. Plant Cell Envrion. 30, 1557–1565 (2007).

    CAS  Article  Google Scholar 

  85. 85.

    Desch, H. E. & Dinwoodie, J. M. Timber structure, properties, conversion and use. (Palgrave Macmillan, 1996).

  86. 86.

    de Tombeur, F. et al. A shift from phenol to silica-based leaf defenses during long-term soil and ecosystem development. Ecol. Lett. 24, 984–995 (2021).

    PubMed  Article  Google Scholar 

  87. 87.

    Dong, N. et al. Leaf nitrogen from first principles: field evidence for adaptive variation with climate. Biogeosciences 14, 481–495 (2017).

    ADS  CAS  Article  Google Scholar 

  88. 88.

    Dong, N. et al. Components of leaf-trait variation along environmental gradients. New Phytol. 228, 82–94 (2020).

    CAS  PubMed  Article  Google Scholar 

  89. 89.

    Du, P., Arndt, S. K. & Farrell, C. Relationships between plant drought response, traits, and climate of origin for green roof plant selection. Ecol. Appl. 28, 1752–1761 (2018).

    PubMed  Article  Google Scholar 

  90. 90.

    Du, P., Arndt, S. K. & Farrell, C. Can the turgor loss point be used to assess drought response to select plants for green roofs in hot and dry climates? Plant Soil 441, 399–408 (2019).

    CAS  Article  Google Scholar 

  91. 91.

    Duan, H. et al. Drought responses of two gymnosperm species with contrasting stomatal regulation strategies under elevated [CO2] and temperature. Tree Physiol. 35, 756–770 (2015).

    CAS  PubMed  Article  Google Scholar 

  92. 92.

    Duncan, R. P. et al. Plant traits and extinction in urban areas: a meta-analysis of 11 cities. Glob. Ecol. Biog. 20, 509–519 (2011).

    Article  Google Scholar 

  93. 93.

    Dwyer, J. M. & Laughlin, D. C. Constraints on trait combinations explain climatic drivers of biodiversity: The importance of trait covariance in community assembly. Ecol. Lett. 20, 872–882 (2017).

    PubMed  Article  Google Scholar 

  94. 94.

    Dwyer, J. M. & Mason, R. Plant community responses to thinning in densely regenerating Acacia harpophylla forest. Restor. Ecol. 26, 97–105 (2018).

    Article  Google Scholar 

  95. 95.

    Eamus, D. & Prichard, H. A cost-benefit analysis of leaves of four Australian savanna species. Tree Physiol. 18, 537–545 (1998).

    PubMed  Article  Google Scholar 

  96. 96.

    Eamus, D., Myers, B., Duff, G. & Williams, D. Seasonal changes in photosynthesis of eight savanna tree species. Tree Physiol. 19, 665–671 (1999).

    PubMed  Article  Google Scholar 

  97. 97.

    Myers, B., E., D. & Duff, G. A cost-benefit analysis of leaves of eight Australian savanna tree species of differing life-span. Photosynthetica 36, 575–586 (1999).

    Article  Google Scholar 

  98. 98.

    Edwards, C., Read, J. & Sanson, G. D. Characterising sclerophylly: some mechanical properties of leaves from heath and forest. Oecologia 123, 158–167 (2000).

    ADS  CAS  PubMed  Article  Google Scholar 

  99. 99.

    Edwards, C., Sanson, G. D., Aranwela, N. & Read, J. Relationships between sclerophylly, leaf biomechanical properties and leaf anatomy in some Australian heath and forest species. Plant Biosyst. 134, 261–277 (2000).

    Article  Google Scholar 

  100. 100.

    Schöenenberger, J. et al. Phylogenetic analysis of fossil flowers using an angiosperm-wide data set: proof-of-concept and challenges ahead. Am. J. Bot. 107, 1433–1448 (2020).

    Article  Google Scholar 

  101. 101.

    Esperon-Rodriguez, M. et al. Functional adaptations and trait plasticity of urban trees along a climatic gradient. Urban For. Urban Green. 54, art126771 (2020).

    Article  Google Scholar 

  102. 102.

    Everingham, S. E., Offord, C. A., Sabot, M. E. B. & Moles, A. T. Time travelling seeds reveal that plant regeneration and growth traits are responding to climate change. Ecology 102, e03272 (2020).

    Google Scholar 

  103. 103.

    Falster, D. S. & Westoby, M. Leaf size and angle vary widely across species: what consequences for light interception? New Phytol. 158, 509–525 (2003).

    Article  Google Scholar 

  104. 104.

    Falster, D. S. & Westoby, M. Alternative height strategies among 45 dicot rain forest species from tropical Queensland, Australia. J. Ecol. 93, 521–535 (2005).

    Article  Google Scholar 

  105. 105.

    Falster, D. S. & Westoby, M. Tradeoffs between height growth rate, stem persistence and maximum height among plant species in a post-fire succession. Oikos 111, 57–66 (2005).

    Article  Google Scholar 

  106. 106.

    Farrell, C., Mitchell, R. E., Szota, C., Rayner, J. P. & Williams, N. S. G. Green roofs for hot and dry climates: Interacting effects of plant water use, succulence and substrate. Ecol. Eng. 49, 270–276 (2012).

    Article  Google Scholar 

  107. 107.

    Farrell, C., Szota, C., Williams, N. S. G. & Arndt, S. K. High water users can be drought tolerant: using physiological traits for green roof plant selection. Plant Soil 372, 177–193 (2013).

    CAS  Article  Google Scholar 

  108. 108.

    Farrell, C., Szota, C. & Arndt, S. K. Does the turgor loss point characterize drought response in dryland plants? Plant Cell Envrion. 40, 1500–1511 (2017).

    CAS  Article  Google Scholar 

  109. 109.

    Feller, M. C. Biomass and nutrient distribution in two eucalypt forest ecosystems. Austral Ecol. 5, 309–333 (1980).

    Article  Google Scholar 

  110. 110.

    Firn, J. et al. Leaf nutrients, not specific leaf area, are consistent indicators of elevated nutrient inputs. Nature Ecol. Evo. 3, 400–406 (2019).

    Article  Google Scholar 

  111. 111.

    Flynn, J. H. & Holder, C. D. A guide to useful woods of the world. (Forest Products Society, 2001).

  112. 112.

    Fonseca, C. R., Overton, J. M. C., Collins, B. & Westoby, M. Shifts in trait-combinations along rainfall and phosphorus gradients. J. Ecol. 88, 964–977 (2000).

    Article  Google Scholar 

  113. 113.

    McDonald, P. G., Fonseca, C. R., Overton, J. M. C. & Westoby, M. Leaf-size divergence along rainfall and soil-nutrient gradients: is the method of size reduction common among clades? Funct. Ecol. 17, 50–57 (2003).

    Article  Google Scholar 

  114. 114.

    Forster, P. I. A taxonomic revision of Alyxia (Apocynaceae) in Australia. Aust. Syst. Bot. 5, 547–580 (1992).

    Article  Google Scholar 

  115. 115.

    Forster, P. I. New names and combinations in Marsdenia (Asclepiadaceae: Marsdenieae) from Asia and Malesia (excluding Papusia). Aust. Syst. Bot. 8, 691–701 (1995).

    Article  Google Scholar 

  116. 116.

    French, B. J., Prior, L. D., Williamson, G. J. & Bowman, D. M. J. S. Cause and effects of a megafire in sedge-heathland in the Tasmanian temperate wilderness. Aust. J. Bot. 64, 513–525 (2016).

    Article  Google Scholar 

  117. 117.

    Froend, R. H. & Drake, P. L. Defining phreatophyte response to reduced water availability: preliminary investigations on the use of xylem cavitation vulnerability in Banksia woodland species. Aust. J. Bot. 54, 173–179 (2006).

    Article  Google Scholar 

  118. 118.

    Funk, J. L., Standish, R. J., Stock, W. D. & Valladares, F. Plant functional traits of dominant native and invasive species in mediterranean-climate ecosystems. Ecology 97, 75–83 (2016).

    PubMed  Article  PubMed Central  Google Scholar 

  119. 119.

    Gallagher, R. V. et al. Invasiveness in introduced Australian acacias: The role of species traits and genome size. Divers. Distrib. 17, 884–897 (2011).

    Article  Google Scholar 

  120. 120.

    Gallagher, R. V. & Leishman, M. R. A global analysis of trait variation and evolution in climbing plants. J. Biogeogr. 39, 1757–1771 (2012).

    Article  Google Scholar 

  121. 121.

    Gardiner, R., Shoo, L. P. & Dwyer John. M. Look to seedling heights, rather than functional traits, to explain survival during extreme heat stress in the early stages of subtropical rainforest restoration. J. Appl. Ecol. 56, 2687–2697 (2019).

    Article  Google Scholar 

  122. 122.

    Geange, S. R. et al. Phenotypic plasticity and water availability: responses of alpine herb species along an elevation gradient. Clim. Change Responses 4, 1–12 (2017).

    Article  Google Scholar 

  123. 123.

    Geange, S. R., Holloway-Phillips, M.-M., Briceno, V. F. & Nicotra, A. B. Aciphylla glacialis mortality, growth and frost resistance: a field warming experiment. Aust. J. Bot. 67, 599–609 (2020).

    Article  Google Scholar 

  124. 124.

    Ghannoum, O. et al. Exposure to preindustrial, current and future atmospheric CO2 and temperature differentially affects growth and photosynthesis in Eucalyptus. Glob. Chang. Biol. 16, 303–319 (2010).

    ADS  Article  Google Scholar 

  125. 125.

    Gleason, S. M., Butler, D. W., Zieminska, K., Waryszak, P. & Westoby, M. Stem xylem conductivity is key to plant water balance across Australian angiosperm species. Funct. Ecol. 26, 343–352 (2012).

    Article  Google Scholar 

  126. 126.

    Gleason, S. M., Butler, D. W. & Waryszak, P. Shifts in leaf and stem hydraulic traits across aridity gradients in eastern Australia. Int. J. Plant Sci. 174, 1292–1301 (2013).

    Article  Google Scholar 

  127. 127.

    Gleason, S. M., Blackman, C. J., Cook, A. M., Laws, C. A. & Westoby, M. Whole-plant capacitance, embolism resistance and slow transpiration rates all contribute to longer desiccation times in woody angiosperms from arid and wet habitats. Tree Physiol. 34, 275–284 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  128. 128.

    Gleason, S. M. et al. Vessel scaling in evergreen angiosperm leaves conforms with Murray’s law and area-filling assumptions: implications for plant size, leaf size and cold tolerance. New Phytol. 218, 1360–1370 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  129. 129.

    Goble-Garratt, E., Bell, D. & Loneragan, W. Floristic and leaf structure patterns along a shallow elevational gradient. Aust. J. Bot. 29, 329–347 (1981).

    Article  Google Scholar 

  130. 130.

    Gosper, C. R. Fruit characteristics of invasive bitou bush, Chrysanthemoides monilifera (Asteraceae), and a comparison with co-occurring native plant species. Aust. J. Bot. 52, 223–230 (2004).

    Article  Google Scholar 

  131. 131.

    Gosper, C. R., Yates, C. J. & Prober, S. M. Changes in plant species and functional composition with time since fire in two mediterranean climate plant communities. J. Veg. Sci. 23, 1071–1081 (2012).

    Article  Google Scholar 

  132. 132.

    Gosper, C. R., Prober, S. M. & Yates, C. J. Estimating fire interval bounds using vital attributes: implications of uncertainty and among-population variability. Ecol. Appl. 23, 924–935 (2013).

    PubMed  Article  PubMed Central  Google Scholar 

  133. 133.

    Gosper, C. R., Yates, C. J. & Prober, S. M. Floristic diversity in fire-sensitive eucalypt woodlands shows a “U”-shaped relationship with time since fire. J. Appl. Ecol. 50, 1187–1196 (2013).

    Article  Google Scholar 

  134. 134.

    Gosper, C. R. et al. A conceptual model of vegetation dynamics for the unique obligate-seeder eucalypt woodlands of south-western Australia. Austral Ecol. 43, 681–695 (2018).

    Article  Google Scholar 

  135. 135.

    Clayton, W. D., Vorontsova, M. S., Harman, K. T. & Williamson, H. GrassBase - The online world grass flora. (2006).

  136. 136.

    Gray, E. F. et al. Leaf:wood allometry and functional traits together explain substantial growth rate variation in rainforest trees. AoB Plants 11, 1–11 (2019).

    Article  Google Scholar 

  137. 137.

    Groom, P. K. & Lamont, B. B. Reproductive ecology of non-sprouting and re-sprouting Hakea species (Proteaceae) in southwestern Australia. In Gondwanan heritage (eds. S.D. Hopper M. Harvey, J. C. & George, A. S.) (Surrey Beatty, Chipping Norton, 1996).

  138. 138.

    Groom, P. K. & Lamont, B. B. Fruit-seed relations in Hakea: serotinous species invest more dry matter in predispersal seed protection. Austral Ecol. 22, 352–355 (1997).

    Article  Google Scholar 

  139. 139.

    Groom, P. K. & Lamont, B. B. Phosphorus accumulation in Proteaceae seeds: A synthesis. Plant Soil 334, 61–72 (2010).

    CAS  Article  Google Scholar 

  140. 140.

    Grootemaat, S., Wright, I. J., van Bodegom, P. M., Cornelissen, J. H. C. & Cornwell, W. K. Burn or rot: leaf traits explain why flammability and decomposability are decoupled across species. Funct. Ecol. 29, 1486–1497 (2015).

    Article  Google Scholar 

  141. 141.

    Grootemaat, S., Wright, I. J., van Bodegom, P. M., Cornelissen, J. H. C. & Shaw, V. Bark traits, decomposition and flammability of Australian forest trees. Aust. J. Bot. 65, 327 (2017).

    Article  Google Scholar 

  142. 142.

    Grootemaat, S., Wright, I. J., van Bodegom, P. M. & Cornelissen, J. H. C. Scaling up flammability from individual leaves to fuel beds. Oikos 126, 1428–1438 (2017).

    Article  Google Scholar 

  143. 143.

    Gross, C. L. The reproductive ecology of Canavalia rosea (Fabaceae) on Anak Krakatau. Indonesia. Aust. J. Bot. 41, 591–599 (1993).

    Article  Google Scholar 

  144. 144.

    Gross, C. L. A comparison of the sexual systems in the trees from the Australian tropics with other tropical biomes–more monoecy but why? Am. J. Bot. 92, 907–919 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  145. 145.

    Grubb, P. J. & Metcalfe, D. J. Adaptation and inertia in the Australian tropical lowland rain-forest flora: Contradictory trends in intergeneric and intrageneric comparisons of seed size in relation to light demand. Funct. Ecol. 10, 512–520 (1996).

    Article  Google Scholar 

  146. 146.

    Grubb, P. J. et al. Monocot leaves are eaten less than dicot leaves in tropical lowland rain forests: Correlations with toughness and leaf presentation. Ann. Bot. 101, 1379–1389 (2008).

    PubMed  PubMed Central  Article  Google Scholar 

  147. 147.

    Guilherme Pereira, C., Clode, P. L., Oliveira, R. S. & Lambers, H. Eudicots from severely phosphorus-impoverished environments preferentially allocate phosphorus to their mesophyll. New Phytol. 218, 959–973 (2018).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  148. 148.

    Guilherme Pereira, C. et al. Trait convergence in photosynthetic nutrient-use efficiency along a 2-million year dune chronosequence in a global biodiversity hotspot.  J. Ecol. 107, 2006–2023 (2019).

    CAS  Article  Google Scholar 

  149. 149.

    Hacke, U. G. et al. Water transport in vesselless Angiosperms: Conducting efficiency and cavitation safety. Int. J. Plant Sci. 168, 1113–1126 (2007).

    Article  Google Scholar 

  150. 150.

    Hall, T. J. The nitrogen and phosphorus concentrations of some pasture species in the Dichanthium-Eulalia Grasslands of North-West Queensland. Rangeland J. 3, 67–73 (1981).

    Article  Google Scholar 

  151. 151.

    Harrison, M. T., Edwards, E. J., Farquhar, G. D., Nicotra, A. B. & Evans, J. R. Nitrogen in cell walls of sclerophyllous leaves accounts for little of the variation in photosynthetic nitrogen-use efficiency. Plant Cell Envrion. 32, 259–270 (2009).

    CAS  Article  Google Scholar 

  152. 152.

    Hassiotou, F., Evans, J. R., Ludwig, M. & Veneklaas, E. J. Stomatal crypts may facilitate diffusion of CO2 to adaxial mesophyll cells in thick sclerophylls. Plant Cell Envrion. 32, 1596–1611 (2009).

    CAS  Article  Google Scholar 

  153. 153.

    Hatch, A. B. Influence of plant litter on the Jarrah forest soils of the Dwellingup region. West. Aust. For. Timber Bur. Leaflet 18 (1955).

  154. 154.

    Hayes, P., Turner, B. L., Lambers, H. & Laliberte, E. Foliar nutrient concentrations and resorption efficiency in plants of contrasting nutrient-acquisition strategies along a 2-million-year dune chronosequence. J. Ecol. 102, 396–410 (2013).

    Article  CAS  Google Scholar 

  155. 155.

    Hayes, P. E., Clode, P. L., Oliveira, R. S. & Lambers, H. Proteaceae from phosphorus-impoverished habitats preferentially allocate phosphorus to photosynthetic cells: an adaptation improving phosphorus-use efficiency. Plant Cell Envrion. 41, 605–619 (2018).

    CAS  Article  Google Scholar 

  156. 156.

    Henery, M. L. & Westoby, M. Seed mass and seed nutrient content as predictors of seed output variation between species. Oikos 92, 479–490 (2001).

    Article  Google Scholar 

  157. 157.

    Hocking, P. J. The nutrition of fruits of two proteaceous shrubs, Grevillea wilsonii and Hakea undulata, from south-western Australia. Aust. J. Bot. 30, 219–230 (1982).

    CAS  Article  Google Scholar 

  158. 158.

    Hocking, P. J. Mineral nutrient composition of leaves and fruits of selected species of Grevillea from southwestern Australia, with special reference to Grevillea leucopteris Meissn. Aust. J. Bot. 34, 155–164 (1986).

    CAS  Article  Google Scholar 

  159. 159.

    Hong, L. T. et al. Plant resources of south east Asia: Timber trees. World biodiversity Database CD rom series (Springer-Verlag Berlin; Heidelberg GmbH; Co. KG, 1999).

  160. 160.

    Hopmans, P., Stewart, H. T. L. & Flinn, D. W. Impacts of harvesting on nutrients in a eucalypt ecosystem in southeastern Australia. For. Ecol. Manage. 59, 29–51 (1993).

    Article  Google Scholar 

  161. 161.

    Huang, G., Rymer, P. D., Duan, H., Smith, R. A. & Tissue, D. T. Elevated temperature is more effective than elevated CO2 in exposing genotypic variation in Telopea speciosissima growth plasticity: implications for woody plant populations under climate change. Glob. Chang. Biol. 21, 3800–3813 (2015).

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  162. 162.

    Hyland, B. P. M., Whiffin, T., Christophel, D., Gray, B. & Elick, R. W. Australian tropical rain forest plants trees, shrubs and vines. (CSIRO Publishing, 2003).

  163. 163.

    World Agroforestry Centre (ICRAF). The wood density database. (2009).

  164. 164.

    Ilic, J., Boland, D., McDonald, M., G., D. & Blakemore, P. Woody density phase 1 - State of knowledge. National Carbon Accounting System. Technical Report 18. (Australian Greenhouse Office, Canberra, Australia, 2000).

  165. 165.

    Islam, M., Turner, D. W. & Adams, M. A. Phosphorus availability and the growth, mineral composition and nutritive value of ephemeral forbs and associated perennials from the Pilbara, Western Australia. Aust. J. Exp. Agric. 39, 149–159 (1999).

    Article  Google Scholar 

  166. 166.

    Islam, M. & Adams, M. A. Mineral content and nutritive value of native grasses and the response to added phosphorus in a Pilbara rangeland. Trop. Grassl. 33, 193–200 (1999).

    Google Scholar 

  167. 167.

    Jordan, G. J. An investigation of long-distance dispersal based on species native to both Tasmania and New Zealand. Aust. J. Bot. 49, 333–340 (2001).

    Article  Google Scholar 

  168. 168.

    Jordan, G. J., Weston, P. H., Carpenter, R. J., Dillon, R. A. & Brodribb, T. J. The evolutionary relations of sunken, covered, and encrypted stomata to dry habitats in Proteaceae. Am. J. Bot. 95, 521–530 (2008).

    PubMed  Article  PubMed Central  Google Scholar 

  169. 169.

    Jordan, G. J., Carpenter, R. J., Koutoulis, A., Price, A. & Brodribb, T. J. Environmental adaptation in stomatal size independent of the effects of genome size. New Phytol. 205, 608–617 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  170. 170.

    Jordan, G. J. et al. Links between environment and stomatal size through evolutionary time in Proteaceae. Proc. R. Soc. Lond. B Biol. Sci. 287, 20192876 (2020).

    CAS  Google Scholar 

  171. 171.

    Jurado, E. Diaspore weight, dispersal, growth form and perenniality of central Australian plants. J. Ecol. 79, 811–828 (1991).

    Article  Google Scholar 

  172. 172.

    Jurado, E. & Westoby, M. Germination biology of selected central Australian plants. Austral Ecol. 17, 341–348 (1992).

    Article  Google Scholar 

  173. 173.

    Kanowski, J. Ecological determinants of the distribution and abundance of the folivorous marsupials endemic to the rainforests of the Atherton uplands, north Queensland. (James Cook University, Townsville, 1999).

  174. 174.

    Keighery, G. Taxonomy of the Calytrix ecalycata complex (Myrtaceae). Nuytsia 15, 261–268 (2004).

    Google Scholar 

  175. 175.

    Royal Botanic Gardens Kew. Seed Information Database (SID) and Seed Bank Database. (2019).

  176. 176.

    Royal Botanic Gardens Kew. Seed protein data from Seed Information Database (SID) and Seed Bank Database. (2019).

  177. 177.

    Royal Botanic Gardens Kew. Oil content data from Seed Information Database (SID) and Seed Bank Database. (2019).

  178. 178.

    Royal Botanic Gardens Kew. Seed dispersal data from the Seed Information Database (SID) and Seed Bank Database. (2019).

  179. 179.

    Royal Botanic Gardens Kew. Germination data from the Seed Information Database (SID) and Seed Bank Database. (2019).

  180. 180.

    Knox, K. J. E. & Clarke, P. J. Fire severity and nutrient availability do not constrain resprouting in forest shrubs. Plant Ecol. 212, 1967–1978 (2011).

    Article  Google Scholar 

  181. 181.

    Körner, C. & Cochrane, P. M. Stomatal responses and water relations of Eucalyptus pauciflora in summer along an elevational gradient. Oecologia 66, 443–455 (1985).

    ADS  PubMed  Article  Google Scholar 

  182. 182.

    Kooyman, R., Rossetto, M., Cornwell, W. & Westoby, M. Phylogenetic tests of community assembly across regional to continental scales in tropical and subtropical rain forests. Glob. Ecol. Biog. 20, 707–716 (2011).

    Article  Google Scholar 

  183. 183.

    Kotowska, M. M., Wright, I. J. & Westoby, M. Parenchyma abundance in wood of evergreen trees varies independently of nutrients. Front. Plant. Sci. 11, art86 (2020).

    Article  Google Scholar 

  184. 184.

    Kuo, J., Hocking, P. & Pate, J. Nutrient reserves in seeds of selected Proteaceous species from South-western Australia. Aust. J. Bot. 30, 231–249 (1982).

    CAS  Article  Google Scholar 

  185. 185.

    Laliberté, E. et al. Experimental assessment of nutrient limitation along a 2-million-year dune chronosequence in the south-western Australia biodiversity hotspot. J. Ecol. 100, 631–642 (2012).

    Article  CAS  Google Scholar 

  186. 186.

    Lambert, M. J. Sulphur relationships of native and exotic tree species. (Macquarie University, Sydney, 1979).

  187. 187.

    Lamont, B. B., Groom, P. K. & Cowling, R. M. High leaf mass per area of related species assemblages may reflect low rainfall and carbon isotope discrimination rather than low phosphorus and nitrogen concentrations. Funct. Ecol. 16, 403–412 (2002).

    Article  Google Scholar 

  188. 188.

    Lamont, B. B., Groom, P. K., Williams, M. & He, T. LMA, density and thickness: recognizing different leaf shapes and correcting for their nonlaminarity. New Phytol. 207, 942–947 (2015).

    PubMed  Article  Google Scholar 

  189. 189.

    Landsberg, J. Dieback of rural eucalypts: response of foliar dietary quality and herbivory to defoliation. Austral Ecol. 15, 89–96 (1990).

    Article  Google Scholar 

  190. 190.

    Landsberg, J. & Gillieson, D. S. Regional and local variation in insect herbivory, vegetation and soils of eucalypt associations in contrasted landscape positions along a climatic gradient. Aust. J. Ecol. 20, 299–315 (1995).

    Article  Google Scholar 

  191. 191.

    Lawes, M. J., Adie, H., Russell-Smith, J., Murphy, B. & Midgley, J. J. How do small savanna trees avoid stem mortality by fire? The roles of stem diameter, height and bark thickness. Ecosphere 2, 1–13 (2011).

    Article  Google Scholar 

  192. 192.

    Lawes, M. J., Richards, A., Dathe, J. & Midgley, J. J. Bark thickness determines fire resistance of selected tree species from fire-prone tropical savanna in north Australia. Plant Ecol. 212, 2057–2069 (2011).

    Article  Google Scholar 

  193. 193.

    Lawes, M. J., Midgley, J. J. & Clarke, P. J. Costs and benefits of relative bark thickness in relation to fire damage: A savanna/forest contrast. J. Ecol. 101, 517–524 (2012).

    Article  Google Scholar 

  194. 194.

    Lawson, J. R., Fryirs, K. A. & Leishman, M. R. Data from: Hydrological conditions explain wood density in riparian plants of south-eastern Australia. Dryad Digital Repository (2015).

  195. 195.

    Laxton, E. Relationship between leaf traits, insect communities and resource availability. (Macquarie University, 2005).

  196. 196.

    Lee, M. R. et al. Good neighbors aplenty: fungal endophytes rarely exhibit competitive exclusion patterns across a span of woody habitats. Ecology 100, e02790 (2019).

    PubMed  Article  Google Scholar 

  197. 197.

    Leigh, A. & Nicotra, A. B. Sexual dimorphism in reproductive allocation and water use efficiency in Maireana pyramidata (Chenopodiaceae), a dioecious, semi-arid shrub. Aust. J. Bot. 51, 509–514 (2003).

    Article  Google Scholar 

  198. 198.

    Leigh, A., Cosgrove, M. J. & Nicotra, A. B. Reproductive allocation in a gender dimorphic shrub: anomalous female investment in Gynatrix pulchella? J. Ecol. 94, 1261–1271 (2006).

    Article  Google Scholar 

  199. 199.

    Leishman, M. R. & Westoby, M. Classifying plants into groups on the basis of associations of individual traits–Evidence from Australian semi-arid woodlands. J. Ecol. 80, 417–424 (1992).

    Article  Google Scholar 

  200. 200.

    Leishman, M. R., Westoby, M. & Jurado, E. Correlates of seed size variation: A comparison among five temperate floras. J. Ecol. 83, 517–529 (1995).

    Article  Google Scholar 

  201. 201.

    Leishman, M. R., Haslehurst, T., Ares, A. & Baruch, Z. Leaf trait relationships of native and invasive plants: community- and global-scale comparisons. New Phytol. 176, 635–643 (2007).

    CAS  PubMed  Article  Google Scholar 

  202. 202.

    Lemmens, R. H. M. J. & Soerjanegara, I. Prosea, Volume 5/1: Timber Trees - Major Commercial Timbers. (Pudoc/Prosea, 1993).

  203. 203.

    Lenz, T. I., Wright, I. J. & Westoby, M. Interrelations among pressure-volume curve traits across species and water availability gradients. Physiol. Plant. 127, 423–433 (2006).

    CAS  Article  Google Scholar 

  204. 204.

    Leuning, R., Cromer, R. N. & Rance, S. Spatial distributions of foliar nitrogen and phosphorus in crowns of Eucalyptus grandis. Oecologia 88, 504–510 (1991).

    ADS  CAS  PubMed  Article  Google Scholar 

  205. 205.

    Lewis, J. D. et al. Rising temperature may negate the stimulatory effect of rising CO2 on growth and physiology of Wollemi pine (Wollemia nobilis). Funct. Plant. Bio. 42, 836–850 (2015).

    CAS  Article  Google Scholar 

  206. 206.

    Lim, F. K. S., Pollock, L. J. & Vesk, P. A. The role of plant functional traits in shrub distribution around alpine frost hollows. J. Veg. Sci. 28, 585–594 (2017).

    Article  Google Scholar 

  207. 207.

    Lord, J. et al. Larger seeds in tropical floras: Consistent patterns independent of growth form and dispersal mode. J. Biogeogr. 24, 205–211 (1997).

    Article  Google Scholar 

  208. 208.

    Lusk, C. H., Onoda, Y., Kooyman, R. & Gutiurrez-Giron, A. Reconciling species-level vs plastic responses of evergreen leaf structure to light gradients: shade leaves punch above their weight. New Phytol. 186, 429–438 (2010).

    PubMed  Article  Google Scholar 

  209. 209.

    Lusk, C. H., Kelly, J. W. G. & Gleason, S. M. Light requirements of Australian tropical vs. cool-temperate rainforest tree species show different relationships with seedling growth and functional traits. Ann. Bot. 111, 479–488 (2012).

    PubMed  PubMed Central  Article  Google Scholar 

  210. 210.

    Lusk, C. H., Sendall, K. M. & Clarke, P. J. Seedling growth rates and light requirements of subtropical rainforest trees associated with basaltic and rhyolitic soils. Aust. J. Bot. 62, 48–55 (2014).

    Article  Google Scholar 

  211. 211.

    Macinnis-Ng, C., McClenahan, K. & Eamus, D. Convergence in hydraulic architecture, water relations and primary productivity amongst habitats and across seasons in Sydney. Funct. Plant. Bio. 31, 429–439 (2004).

    Article  Google Scholar 

  212. 212.

    Macinnis-Ng, C. M. O., Zeppel, M. J. B., Palmer, A. R. & Eamus, D. Seasonal variations in tree water use and physiology correlate with soil salinity and soil water content in remnant woodlands on saline soils. J. Arid Environ. 129, 102–110 (2016).

    ADS  Article  Google Scholar 

  213. 213.

    Marsh, N. R. & Adams, M. A. Decline of Eucalyptus tereticornis near Bairnsdale, Victoria: insect herbivory and nitrogen fractions in sap and foliage. Aust. J. Bot. 43, 39–49 (1995).

    Article  Google Scholar 

  214. 214.

    Maslin, B. WATTLE, Interactive Identification of Australian Acacia. Version 2. (Australian Biological Resources Study, Canberra, 2014).

  215. 215.

    McCarthy, J. K., Dwyer, J. M. & Mokany, K. A regional-scale assessment of using metabolic scaling theory to predict ecosystem properties. Proc. R. Soc. Lond. B Biol. Sci. 286, 20192221 (2019).

    Google Scholar 

  216. 216.

    McClenahan, K., Macinnis-Ng, C. & Eamus, D. Hydraulic architecture and water relations of several species at diverse sites around Sydney. Aust. J. Bot. 52, 509–518 (2004).

    Article  Google Scholar 

  217. 217.

    McGlone, M. S., Richardson, S. J. & Jordan, G. J. Comparative biogeography of New Zealand trees: Species richness, height, leaf traits and range sizes. New Zealand J. Ecol. 34, 137–151 (2010).

    Google Scholar 

  218. 218.

    McGlone, M. S., Richardson, S. J., Jordan, G. J. & Perry, G. L. W. Is there a “suboptimal” woody species height? A response to Scheffer et al. Trends in Ecol. Evo. 30, 4–5 (2015).

    Article  Google Scholar 

  219. 219.

    McIntyre, S., Lavorel, S. & Tremont, R. M. Plant life-history attributes: Their relationship to disturbance response in herbaceous vegetation. The J. Ecol. 83, 31–44 (1995).

    Article  Google Scholar 

  220. 220.

    Meers, T. Role of plant functional traits in determining the response of vegetation to land use change on the Delatite Peninsula, Victoria. (University of Melbourne, 2007).

  221. 221.

    Meers, T. L., Bell, T. L., Enright, N. J. & Kasel, S. Role of plant functional traits in determining vegetation composition of abandoned grazing land in north-eastern Victoria, Australia. J. Veg. Sci. 19, 515–524 (2008).

    Article  Google Scholar 

  222. 222.

    Meers, T. L., Bell, T. L., Enright, N. J. & Kasel, S. Do generalisations of global trade-offs in plant design apply to an Australian sclerophyllous flora? Aust. J. Bot. 58, 257–270 (2010).

    Article  Google Scholar 

  223. 223.

    Meers, T. L., Kasel, S., Bell, T. L. & Enright, N. J. Conversion of native forest to exotic Pinus radiata plantation: response of understorey plant composition using a plant functional trait approach. For. Ecol. Manage. 259, 399–409 (2010).

    Article  Google Scholar 

  224. 224.

    Meier, E. The wood database. (2007).

  225. 225.

    Laliberté, E. et al. Land-use intensification reduces functional redundancy and response diversity in plant communities. Ecol. Lett. 13, 76–86 (2010).

    PubMed  Article  PubMed Central  Google Scholar 

  226. 226.

    Milberg, P. & Lamont, B. B. Seed/cotyledon size and nutrient content play a major role in early performance of species on nutrient-poor soils. New Phytol. 137, 665–672 (1997).

    Article  Google Scholar 

  227. 227.

    Milberg, P., Pérez-Fernández, M. A. & Lamont, B. B. Seedling growth response to added nutrients depends on seed size in three woody genera. J. Ecol. 86, 624–632 (1998).

    Article  Google Scholar 

  228. 228.

    Mokany, K. & Ash, J. Are traits measured on pot grown plants representative of those in natural communities? J. Veg. Sci. 19, 119–126 (2008).

    Article  Google Scholar 

  229. 229.

    Mokany, K., Thomson, J. J., Lynch, A. J. J., Jordan, G. J. & Ferrier, S. Linking changes in community composition and function under climate change. Ecol. Appl. 25, 2132–2141 (2015).

    PubMed  Article  PubMed Central  Google Scholar 

  230. 230.

    Moles, A. T. & Westoby, M. Do small leaves expand faster than large leaves, and do shorter expansion times reduce herbivore damage? Oikos 90, 517–524 (2000).

    Article  Google Scholar 

  231. 231.

    Moles, A. T., Warton, D. I. & Westoby, M. Seed size and survival in the soil in arid Australia. Austral Ecol. 28, 575–585 (2003).

    Article  Google Scholar 

  232. 232.

    Moles, A. T. et al. Putting plant resistance traits on the map: A test of the idea that plants are better defended at lower latitudes. New Phytol. 191, 777–788 (2011).

    PubMed  Article  PubMed Central  Google Scholar 

  233. 233.

    Mooney, H. A., Ferrar, P. J. & Slatyer, R. O. Photosynthetic capacity and carbon allocation patterns in diverse growth forms of Eucalyptus. Oecologia 36, 103–111 (1978).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  234. 234.

    Moore, A. W., Russell, J. S. & Coaldrake, J. E. Dry matter and nutrient content of a subtropical semiarid forest of Acacia harpophylla F. Muell. (Brigalow). Aust. J. Bot. 15, 11–24 (1967).

    Article  Google Scholar 

  235. 235.

    Moore, N. A., Camac, J. S. & Morgan, J. W. Effects of drought and fire on resprouting capacity of 52 temperate Australian perennial native grasses. New Phytol. 221, 1424–1433 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  236. 236.

    Morgan, H. Root system architecture, water use and rainfall responses of perennial species. (Macquarie University, 2005).

  237. 237.

    Muir, A. M., Vesk, P. A. & Hepworth, G. Reproductive trajectories over decadal time-spans after fire for eight obligate-seeder shrub species in south-eastern Australia. Aust. J. Bot. 62, 369–379 (2014).

    Article  Google Scholar 

  238. 238.

    Munroe, S. E. M. et al. The photosynthetic pathways of plant species surveyed in Australia’s national terrestrial monitoring network. Scientific Data 8, 97 (2021).

    PubMed  PubMed Central  Article  Google Scholar 

  239. 239.

    National Herbarium of NSW. Trait measurements for NSW rainforest species from PLantNET. (2016).

  240. 240.

    Nicholson, A., Prior, L. D., Perry, G. L. W. & Bowman, D. M. J. S. High post-fire mortality of resprouting woody plants in Tasmanian Mediterranean-type vegetation. Int. J. Wildland Fire 26, 532–537 (2017).

    Article  Google Scholar 

  241. 241.

    Nicolle, D. A classification and census of regenerative strategies in the eucalypts (Angophora, Corymbia and Eucalyptus - Myrtaceae), with special reference to the obligate seeders. Aust. J. Bot. 54, 391–407 (2006).

    Article  Google Scholar 

  242. 242.

    Nicolle, D. Classification of the Eucalypts (Angophora, Corymbia and Eucalyptus) Version 3. (Currency Creek Arboretum Eucalypt Research, 2018).

  243. 243.

    Niinemets, U., Wright, I. J. & Evans, J. R. Leaf mesophyll diffusion conductance in 35 Australian sclerophylls covering a broad range of foliage structural and physiological variation. J. Exp. Bot. 60, 2433–2449 (2009).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  244. 244.

    Kenny, B., Orscheg, C., Tasker, E., Gill, M. A. & Bradstock, R. NSW Flora Fire Response Database, v2.1. (NSW Department of Planning Industry; Environment, 2014).

  245. 245.

    Northern Territory Herbarium. Flora of the Darwin Region Online. (2014).

  246. 246.

    Onoda, Y., Richards, A. E. & Westoby, M. The relationship between stem biomechanics and wood density is modified by rainfall in 32 Australian woody plant species. New Phytol. 185, 493–501 (2009).

    PubMed  Article  PubMed Central  Google Scholar 

  247. 247.

    O’Reilly-Nugent, A. et al. Measuring competitive impact: Joint‐species modelling of invaded plant communities. J. Ecol. 108, 449–459 (2018).

    Article  Google Scholar 

  248. 248.

    Osborne, C. P. et al. A global database of C4 photosynthesis in grasses. New Phytol. 204, 441–446 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  249. 249.

    Paczkowska G. & Chapman, A.R. The Western Australian flora: A descriptive catalogue. 652 (CALM, Kings Park; Botanic Gardens; Wildflower Society of Western Australia, 2000).

  250. 250.

    Palma, E. et al. Functional trait changes in the floras of 11 cities across the globe in response to urbanization. Ecography 40, 875–886 (2017).

    Article  Google Scholar 

  251. 251.

    Pate, J. S., Rasins, E., Rullo, J. & Kuo, J. Seed nutrient reserves of Proteaceae with special reference to protein bodies and their inclusions. Ann. Bot. 57, 747–770 (1986).

    CAS  Article  Google Scholar 

  252. 252.

    Pearcy, R. W. Photosynthetic gas exchange responses of Australian tropical forest trees in canopy, gap and understory micro-environments. Funct. Ecol. 1, 169–178 (1987).

    Article  Google Scholar 

  253. 253.

    Peeters, P. J. Correlations between leaf structural traits and the densities of herbivorous insect guilds. Biol. J. Linn. Soc. 77, 43–65 (2002).

    Article  Google Scholar 

  254. 254.

    Pekin, B. K., Wittkuhn, R. S., Boer, M. M., Macfarlane, C. & Grierson, P. F. Plant functional traits along environmental gradients in seasonally dry and fire-prone ecosystem. J. Veg. Sci. 22, 1009–1020 (2011).

    Article  Google Scholar 

  255. 255.

    Pickering, C., Green, K., Barros, A. A. & Venn, S. A resurvey of late-lying snowpatches reveals changes in both species and functional composition across snowmelt zones. Alp. Bot. 124, 93–103 (2014).

    Article  Google Scholar 

  256. 256.

    Pickup, M., Westoby, M. & Basden, A. Dry mass costs of deploying leaf area in relation to leaf size. Funct. Ecol. 19, 88–97 (2005).

    Article  Google Scholar 

  257. 257.

    Pollock, L. J., Morris, W. K. & Vesk, P. A. The role of functional traits in species distributions revealed through a hierarchical model. Ecography 35, 716–725 (2011).

    Article  Google Scholar 

  258. 258.

    Pollock, L. J. et al. Combining functional traits, the environment and multiple surveys to understand semi-arid tree distributions. J. Veg. Sci. 29, 967–977 (2018).

    Article  Google Scholar 

  259. 259.

    Prior, L. D., Eamus, D. & Bowman, D. M. J. S. Leaf attributes in the seasonally dry tropics: A comparison of four habitats in northern Australia. Funct. Ecol. 17, 504–515 (2003).

    Article  Google Scholar 

  260. 260.

    Prior, L. D., Bowman, D. M. J. S. & Eamus, D. Seasonal differences in leaf attributes in Australian tropical tree species: family and habitat comparisons. Funct. Ecol. 18, 707–718 (2004).

    Article  Google Scholar 

  261. 261.

    Prior, L. D., Williamson, G. J. & Bowman, D. M. J. S. Impact of high-severity fire in a Tasmainian dry eucalypt forest. Aust. J. Bot. 64, 193–205 (2016).

    Article  Google Scholar 

  262. 262.

    Oxford Forestry Institute. Prospect: The wood database. (2009).

  263. 263.

    Royal Botanic Gardens Kew. Seed Information Database (SID). (2014).

  264. 264.

    Royal Botanic Gardens Sydney. PLantNET. (2014).

  265. 265.

    Royal Botanic Gardens Sydney. PLantNET: NSW flora online. (2014).

  266. 266.

    Read, J. & Sanson, G. D. Characterizing sclerophylly: the mechanical properties of a diverse range of leaf types. New Phytol. 160, 81–99 (2003).

    PubMed  Article  PubMed Central  Google Scholar 

  267. 267.

    Read, J., Sanson, G. D. & Lamont, B. B. Leaf mechanical properties in sclerophyll woodland and shrubland on contrasting soils. Plant Soil 276, 95–113 (2005).

    CAS  Article  Google Scholar 

  268. 268.

    Reid, J. B., Hill, R., Brown, M. & and M. Hovenden. Vegetation of Tasmania. 456 (1999).

  269. 269.

    Reynolds, V. A., Anderegg, L. D. L., Loy, X., HilleRisLambers, J. & Mayfield, M. M. Unexpected drought resistance strategies in seedlings of four Brachychiton species. Tree Physiol. 38, 664–677 (2017).

    Article  CAS  Google Scholar 

  270. 270.

    Rice, K. J., Matzner, S. L., Byer, W. & Brown, J. R. Patterns of tree dieback in Queensland, Australia: The importance of drought stress and the role of resistance to cavitation. Oecologia 139, 190–198 (2004).

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  271. 271.

    Richards, A. E. et al. Physiological profiles of restricted endemic plants and their widespread congenors in the North Queensland wet tropics, Australia. Biol. Conserv. 111, 41–52 (2003).

    Article  Google Scholar 

  272. 272.

    Roderick, M. L., Berry, S. L. & Noble, I. R. The relationship between leaf composition and morphology at elevated CO2 concentrations. New Phytol. 143, 63–72 (1999).

    Article  Google Scholar 

  273. 273.

    Roderick, M. L. & Cochrane, M. J. On the conservative nature of the leaf mass-area relationship. Ann. Bot. 89, 537–542 (2002).

    PubMed  PubMed Central  Article  Google Scholar 

  274. 274.

    Rosell, J. A., Gleason, S., Mendez-Alonzo, R., Chang, Y. & Westoby, M. Bark functional ecology: Evidence for tradeoffs, functional coordination, and environment producing bark diversity. New Phytol. 201, 486–497 (2014).

    PubMed  Article  PubMed Central  Google Scholar 

  275. 275.

    Rye, B. L. A revision of south-western Australian species of Micromyrtus (Myrtaceae) with five antisepalous ribs on the hypanthium. Nuytsia 15, 101–122 (2002).

    Google Scholar 

  276. 276.

    Rye, B. L. A partial revision of the south-western Australian species of Micromyrtus (Myrtaceae: Chamelaucieae). Nuytsia 16, 117–147 (2006).

    Google Scholar 

  277. 277.

    Rye, B. L. Reinstatement of the Western Australian genus Oxymyrrhine (Myrtaceae: Chamelaucieae) with three new species. Nuytsia 19, 149–165 (2009).

    Google Scholar 

  278. 278.

    Rye, B. L. A revision of the Micromyrtus racemosa complex (Myrtaceae: Chamelaucieae) of south-western Australia. Nuytsia 20, 37–56 (2010).

    Google Scholar 

  279. 279.

    Rye, B. L., Wilson, P. G. & Keighery, G. J. A revision of the species of Hypocalymma (Myrtaceae: Chamelaucieae) with smooth or colliculate seeds. Nuytsia 23, 283–312 (2013).

    Google Scholar 

  280. 280.

    Rye, B. L. An update to the taxonomy of some western Australian genera of Myrtaceae tribe Chamelaucieae. 1. Calytrix. Nuytsia 23, 483–501 (2013).

    Google Scholar 

  281. 281.

    Rye, B. L. A revision of the south-western Australian genus Babingtonia (Myrtaceae: Chamelaucieae). Nuytsia 25, 219–250 (2015).

    Google Scholar 

  282. 282.

    Jessop, J. P. & Toelken, H. R. Flora of South Australia, 4th edition, 4 vols. (Government Printer, Adelaide, 1986).

  283. 283.

    Sams, M. A. et al. Landscape context explains changes in the functional diversity of regenerating forests better than climate or species richness. Glob. Ecol. Biog. 26, 1165–1176 (2017).

    Article  Google Scholar 

  284. 284.

    Sauquet, H. et al. The ancestral flower of angiosperms and its early diversification. Nat. Commun. 8, 1–10 (2017).

    Article  CAS  Google Scholar 

  285. 285.

    Schmidt, S. & Stewart, G. R. Waterlogging and fire impacts on nitrogen availability and utilization in a subtropical wet heathland (wallum). Plant Cell Envrion. 20, 1231–1241 (1997).

    Article  Google Scholar 

  286. 286.

    Schmidt, S. & Stewart, G. R. d15N values of tropical savanna and monsoon forest species reflect root specialisations and soil nitrogen status. Oecologia 134, 569–577 (2003).

    ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

  287. 287.

    Schmidt, S., Lamble, R. E., Fensham, R. J. & Siddique, I. Effect of woody vegetation clearing on nutrient and carbon relations of semi-arid dystrophic savanna. Plant Soil 331, 79–90 (2009).

    Article  CAS  Google Scholar 

  288. 288.

    Schulze, E., Kelliher, F. M., Körner, C., Lloyd, J. & Leuning, R. Relationships among maximum stomatal conductance, ecosystem surface conductance, carbon assimilation rate, and plant nitrogen nutrition: A global ecology scaling exercise. Annu. Rev. Ecol. Syst. 25, 629–662 (1994).

    Article  Google Scholar 

  289. 289.

    Schulze, E.-D. et al. Carbon and nitrogen isotope discrimination and nitrogen nutrition of trees along a rainfall gradient in northern Australia. Aust. J. Plant. Physiol. 25, 413–425 (1998).

    Google Scholar 

  290. 290.

    Schulze, E.-D., Turner, N. C., Nicolle, D. & Schumacher, J. Species differences in carbon isotope ratios, specific leaf area and nitrogen concentrations in leaves of Eucalyptus growing in a common garden compared with along an aridity gradient. Physiol. Plant. 127, 434–444 (2006).

    CAS  Article  Google Scholar 

  291. 291.

    Schulze, E.-D., Turner, N. C., Nicolle, D. & Schumacher, J. Leaf and wood carbon isotope ratios, specific leaf areas and wood growth of Eucalyptus species across a rainfall gradient in Australia. Tree Physiol. 26, 479–492 (2006).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  292. 292.

    Turner, N. C., Schulze, E.-D., Nicolle, D., Schumacher, J. & Kuhlmann, I. Annual rainfall does not directly determine the carbon isotope ratio of leaves of Eucalyptus species. Physiol. Plant. 132, 440–445 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  293. 293.

    Schulze, E. D. et al. Stable carbon and nitrogen isotope ratios of Eucalyptus and Acacia species along a seasonal rainfall gradient in Western Australia. Trees 28, 1125–1135 (2014).

    CAS  Article  Google Scholar 

  294. 294.

    Scott, A. J. Vegetation recovery and recruitment processes in south-eastern Australian semi-arid old fields. (La Trobe University, 2010).

  295. 295.

    Sendall, K. M., Lusk, C. H. & Reich, P. B. Trade-offs in juvenile growth potential vs. shade tolerance among subtropical rain forest trees on soils of contrasting fertility. Funct. Ecol. 30, 845–855 (2015).

    Article  Google Scholar 

  296. 296.

    Seng, O. D. Specific gravity of Indonesian Woods and its significance for practical use. (FPRDC Forestry Department, Bogor, Indonesia, 1951).

  297. 297.

    Sjöström, A. & Gross, C. L. Life-history characters and phylogeny are correlated with extinction risk in the Australian angiosperms. J. Biogeogr. 33, 271–290 (2006).

    Article  Google Scholar 

  298. 298.

    Smith, B. Community-level Convergence and Community Structure of temperate Nothofagus forests. (University of Otago, Dunedin, New Zealand, 1996).

  299. 299.

    Smith, R. A., Lewis, J. D., Ghannoum, O. & Tissue, D. T. Leaf structural responses to pre-industrial, current and elevated atmospheric CO2 and temperature affect leaf function in Eucalyptus sideroxylon. Funct. Plant. Bio. 39, 285–296 (2012).

    CAS  Article  Google Scholar 

  300. 300.

    Soliveres, S., Eldridge, D. J., Hemmings, F. & Maestre, F. T. Nurse plant effects on plant species richness in drylands: The role of grazing, rainfall and species specificity. Perspect. Plant Ecol. Evol. Systs. 14, 402–410 (2012).

    Article  Google Scholar 

  301. 301.

    Soper, F. M. et al. Natural abundance (delta15N) indicates shifts in nitrogen relations of woody taxa along a savanna-woodland continental rainfall gradient. Oecologia 178, 297–308 (2014).

    ADS  PubMed  Article  Google Scholar 

  302. 302.

    Specht, R. L. et al. Mediterranean-type ecosystems: A data source book. 248 (Springer, 1988).

  303. 303.

    Specht, R. L. & Rundel, P. W. Sclerophylly and foliar nutrient status of Mediterranean-climate plant communities in southern Australia. Aust. J. Bot. 38, 459–474 (1990).

    Article  Google Scholar 

  304. 304.

    Sperry, J. S., Hacke, U. G., Feild, T. S., Sano, Y. & Sikkema, E. H. Hydraulic consequences of vessel evolution in Angiosperms. Int. J. Plant Sci. 168, 1127–1139 (2007).

    Article  Google Scholar 

  305. 305.

    Staples, T., Dwyer, J. M., England, J. R. & Mayfield, M. M. Productivity does not correlate with species and functional diversity in Australian reforestation plantings across a wide climate gradient. Glob. Ecol. Biog. 28, 1417–1429 (2019).

    Article  Google Scholar 

  306. 306.

    Stewart, G., Turnbull, M., Schmidt, S. & Erskine, P. 13C natural abundance in plant communities along a rainfall gradient: a biological integrator of water availability. Funct. Plant. Bio. 22, 51–55 (1995).

    Article  Google Scholar 

  307. 307.

    Stock, W. D., Pate, J. S. & Rasins, E. Seed developmental patterns in Banksia attenuata R. Br. and B. laricina C. Gardner in relation to mechanical defence costs. New Phytol. 117, 109–114 (1991).

    CAS  Article  Google Scholar 

  308. 308.

    Tait, C. J., Daniels, C. B. & Hill, R. S. Changes in species assemblages within the Adelaide metropolitan area, Australia, 1836–2002. Ecol. Appl. 15, 346–359 (2005).

    Article  Google Scholar 

  309. 309.

    Taseski, G., Keith, D. A., Dalrymple, R. L. & Cornwell, W. K. Shifts in fine root traits within and among species along a small-scale hydrological gradient. (University of New South Wales, 2017).

  310. 310.

    Taylor, D. & Eamus, D. Coordinating leaf functional traits with branch hydraulic conductivity: Resource substitution and implications for carbon gain. Tree Physiol. 28, 1169–1177 (2008).

    PubMed  Article  Google Scholar 

  311. 311.

    Thomas, F. M. & Vesk, P. A. Growth races in The Mallee: Height growth in woody plants examined with a trait-based model. Austral Ecol. 42, 790–800 (2017).

    Article  Google Scholar 

  312. 312.

    Thomas, F. M. & Vesk, P. A. Are trait-growth models transferable? Predicting multi-species growth trajectories between ecosystems using plant functional traits. PLoS One 12, e0176959 (2017).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  313. 313.

    Thompson, I. R. Morphometric analysis and revision of eastern Australian Hovea (Brongniartieae-Fabaceae). Aust. Syst. Bot. 14, 1–99 (2001).

    Article  Google Scholar 

  314. 314.

    Tasmanian Herbarium. Flora of Tasmania Online. (2009).

  315. 315.

    Tng, D. Y. P., Jordan, G. J. & Bowman, D. M. J. S. Plant traits demonstrate that temperate and tropical giant Eucalypt forests are ecologically convergent with rainforest not savanna. PLoS One 8, e84378 (2013).

    ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

  316. 316.

    Toelken, H. R. A revision of the genus Kunzea (Myrtaceae) I. The western Australian section Zeanuk. J. Adel. Bot. Gard. 17, 29–106 (1996).

    Google Scholar 

  317. 317.

    Tomlinson, K. W. et al. Biomass partitioning and root morphology of savanna trees across a water gradient. J. Ecol. 100, 1113–1121 (2012).

    Article  Google Scholar 

  318. 318.

    Tomlinson, K. W. et al. Leaf adaptations of evergreen and deciduous trees of semi-arid and humid savannas on three continents. J. Ecol. 101, 430–440 (2013).

    Article  Google Scholar 

  319. 319.

    Tomlinson, K. W. et al. Seedling growth of savanna tree species from three continents under grass competition and nutrient limitation in a greenhouse experiment. J. Ecol. 107, 1051–1066 (2019).

    Article  Google Scholar 

  320. 320.

    Tremont, R. M. Life-history attributes of plants in grazed and ungrazed grasslands on the Northern Tablelands of New South Wales. Aust. J. Bot. 42, 511–530 (1994).

    Article  Google Scholar 

  321. 321.

    Trudgen, M. E. & Rye, B. L. Astus, a new western Australian genus of Myrtaceae with heterocarpidic fruits. Nuytsia 14, 495–512 (2005).

    Google Scholar 

  322. 322.

    Trudgen, M. E. & Rye, B. L. An update to the taxonomy of some western Australian genera of Myrtaceae tribe Chamelaucieae. 2. Cyathostemon. Nuytsia 24, 7–16 (2014).

    Google Scholar 

  323. 323.

    Turner, J. & Lambert, M. J. Nutrient cycling within a 27-year-old Eucalyptus grandis plantation in New South Wales. For. Ecol. Manage. 6, 155–168 (1983).

    CAS  Article  Google Scholar 

  324. 324.

    Turner, N. C., Schulze, E.-D., Nicolle, D. & Kuhlmann, I. Growth in two common gardens reveals species by environment interaction in carbon isotope discrimination of Eucalyptus. Tree Physiol. 30, 741–747 (2010).

    CAS  PubMed  Article  Google Scholar 

  325. 325.

    Veneklaas, E. J. & Poot, P. Seasonal patterns in water use and leaf turnover of different plant functional types in a species-rich woodland, south-western Australia. Plant Soil 257, 295–304 (2003).

    CAS  Article  Google Scholar 

  326. 326.

    Venn, S. E., Green, K., Pickering, C. M. & Morgan, J. W. Using plant functional traits to explain community composition across a strong environmental filter in Australian alpine snowpatches. Plant Ecol. 212, 1491–1499 (2011).

    Article  Google Scholar 

  327. 327.

    Venn, S., Pickering, C. & Green, K. Spatial and temporal functional changes in alpine summit vegetation are driven by increases in shrubs and graminoids. AoB Plants 6, plu008 (2014).

    PubMed  PubMed Central  Article  Google Scholar 

  328. 328.

    Vesk, P. A., Leishman, M. R. & Westoby, M. Simple traits do not predict grazing response in Australian dry shrublands and woodlands. J. Appl. Ecol. 41, 22–31 (2004).

    Article  Google Scholar 

  329. 329.

    Vesk, P. A. & Yen, J. D. L. Plant resprouting: How many sprouts and how deep? Flexible modelling of multispecies experimental disturbances. Perspect. Plant Ecol. Evol. Systs. 41, 125497 (2019).

    Article  Google Scholar 

  330. 330.

    Vlasveld, C., O’Leary, B., Udovicic, F. & Burd, M. Leaf heteroblasty in eucalypts: biogeographic evidence of ecological function. Aust. J. Bot. 66, 191–201 (2018).

    Article  Google Scholar 

  331. 331.

    Western Australian Herbarium. FloraBase: The Western Australian flora. (1998).

  332. 332.

    Western Australian Herbarium. FloraBase: The Western Australian flora. (2016).

  333. 333.

    Warren, C. R., Tausz, M. & Adams, M. A. Does rainfall explain variation in leaf morphology and physiology among populations of red ironbark (Eucalyptus sideroxylon subsp. tricarpa) grown in a common garden? Tree Physiol. 25, 1369–1378 (2005).

    PubMed  Article  PubMed Central  Google Scholar 

  334. 334.

    Warren, C. R., Dreyer, E., Tausz, M. & Adams, M. A. Ecotype adaptation and acclimation of leaf traits to rainfall in 29 species of 16-year-old Eucalyptus at two common gardens. Funct. Ecol. 20, 929–940 (2006).

    Article  Google Scholar 

  335. 335.

    Weerasinghe, L. K. et al. Canopy position affects the relationships between leaf respiration and associated traits in a tropical rainforest in Far North Queensland. Tree Physiol. 34, 564–584 (2014).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  336. 336.

    Wells, J. A. Phylogeny and inter-relations of ecological traits and seed dispersal in rainforest plants: Exploring aspects of functional diversity in primary and secondary rainforests in Australia’s Wet Tropics. (University of Queensland, 2012).

  337. 337.

    Westman, W. E. & Roggers, R. V. Nutrient stocks in a subtropical eucalypt forest, North Stradbroke Island. Austral Ecol. 2, 447–460 (1977).

    Article  Google Scholar 

  338. 338.

    Westoby, M. et al. Seed size and plant growth form as factors in dispersal spectra. Ecology 71, 1307–1315 (1990).

    Article  Google Scholar 

  339. 339.

    Westoby, M. & Wright, I. J. The leaf size – twig size spectrum and its relationship to other important spectra of variation among species. Oecologia 135, 621–628 (2003).

    ADS  PubMed  Article  PubMed Central  Google Scholar 

  340. 340.

    Wheeler, J. R., Marchant, N. G. & Lewington, M. Flora of the south west: Bunbury, Augusta, Denmark. (Australian Biological Resources Study; University of Western Australia Press, 2002).

  341. 341.

    White, M., Sinclair, S. & Frood, D. Victorian Vital Attributes Database. (Department of Environment, Land, Water; Planning, Victoria, 2020).

  342. 342.

    Williams, N. S. G., Morgan, J. W., McDonnell, M. J. & McCarthy, M. A. Plant traits and local extinctions in natural grasslands along an urban-rural gradient. J. Ecol. 93, 1203–1213 (2005).

    Article  Google Scholar 

  343. 343.

    Wills, J. et al. Tree leaf trade-offs are stronger for sub-canopy trees: leaf traits reveal little about growth rates in canopy trees. Ecol. Appl. 28, 1116–1125 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  344. 344.

    Wilson, P. G. & Rowe, R. A revision of the Indigofereae (Fabaceae) in Australia. 2. Indigofera species with trifoliolate and alternately pinnate leaves. Telopea 12, 293–307 (2008).

    Article  Google Scholar 

  345. 345.

    Wright, I. J. et al. A survey of seed and seedling characters in 1744 Australian dicotyledon species: Cross-species trait correlations and correlated trait-shifts within evolutionary lineages. Biol. J. Linn. Soc. 69, 521–547 (2000).

    Article  Google Scholar 

  346. 346.

    Wright, I. J., Reich, P. B. & Westoby, M. Strategy shifts in leaf physiology, structure and nutrient content between species of high- and low-rainfall and high- and low-nutrient habitats. Funct. Ecol. 15, 423–434 (2001).

    Article  Google Scholar 

  347. 347.

    Wright, I. J. & Westoby, M. Leaves at low versus high rainfall: Coordination of structure, lifespan and physiology. New Phytol. 155, 403–416 (2002).

    PubMed  Article  PubMed Central  Google Scholar 

  348. 348.

    Wright, I. J., Westoby, M. & Reich, P. B. Convergence towards higher leaf mass per area in dry and nutrient-poor habitats has different consequences for leaf life span. J. Ecol. 90, 534–543 (2002).

    Article  Google Scholar 

  349. 349.

    Wright, I. J., Falster, D. S., Pickup, M. & Westoby, M. Cross-species patterns in the coordination between leaf and stem traits, and their implications for plant hydraulics. Physiol. Plant. 127, 445–456 (2006).

    CAS  Article  Google Scholar 

  350. 350.

    Wright, I. J. et al. Stem diameter growth rates in a fire-prone savanna correlate with photosynthetic rate and branch-scale biomass allocation, but not specific leaf area. Austral Ecol. 44, 339–350 (2018).

    Article  Google Scholar 

  351. 351.

    Yates, C. J. et al. Mallee woodlands and shrublands: the mallee, muruk/muert and maalok vegetation of Southern Australia. in Australian Vegetation (Cambridge University Press, 2017).

  352. 352.

    Zanne, A. E. et al. Data from: Towards a worldwide wood economics spectrum. Dryad (2009).

  353. 353.

    Zieminska, K., Butler, D. W., Gleason, S. M., Wright, I. J. & Westoby, M. Fibre wall and lumen fractions drive wood density variation across 24 Australian angiosperms. AoB Plants 5, plt046 (2013).

    PubMed Central  Article  CAS  Google Scholar 

  354. 354.

    Zieminska, K., Westoby, M. & Wright, I. J. Broad anatomical variation within a narrow wood density range - A study of twig wood across 69 Australian Angiosperms. PLoS One 10, e0124892 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  355. 355.

    R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, 2020).

  356. 356.

    Wickham, H. et al. Welcome to the tidyverse. Journal of Open Source Software 4, 1686 (2019).

    ADS  Article  Google Scholar 

  357. 357.

    Stephens, J. Yaml: Methods to convert r data to YAML and back (r package version 2.1. 13). (2014).

  358. 358.

    FitzJohn, R. Remake: Make-like build management. R package version 0.2.0. (2016).

  359. 359.

    Xie, Y. Dynamic documents with R and Knitr. (2015).

  360. 360.

    Allaire, J. et al. Rmarkdown: Dynamic documents for R. R package version 0.5.1. (2015).

  361. 361.

    CHAH. Australian Plant Name Index (continuously updated), Centre of Australian National Biodiversity Research. ( (14/05/2020), 2020).

  362. 362.

    Chamberlain, S. A. & Szöcs, E. Taxize: Taxonomic search and retrieval in R. F1000Res. 2, 191 (2013).

    PubMed  PubMed Central  Article  Google Scholar 

  363. 363.

    Falster, D. et al. AusTraits: a curated plant trait database for the Australian flora. Zenodo (2021).

  364. 364.

    Wilkinson, M. D. et al. The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3 (2016).

  365. 365.

    Falster, D. S., FitzJohn, R. G., Pennell, M. W. & Cornwell, W. K. Datastorr: A workflow and package for delivering successive versions of ‘evolving data’ directly into R. GigaScience 8, giz035 (2019).

    PubMed  PubMed Central  Article  Google Scholar 

  366. 366.

    Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).

    PubMed  Article  PubMed Central  Google Scholar 

  367. 367.

    Jin, Y. V.PhyloMaker: Make phylogenetic hypotheses for vascular plants, etc.. R package version 0.1.0. (2020).

  368. 368.

    Yu, G., Smith, D. K., Zhu, H., Guan, Y. & Lam, T. T.-Y. Gtree: An r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecol. Evo. 8, 28–36 (2017).

    Article  Google Scholar 

  369. 369.

    Stefan, V. & Levin, S. Plotbiomes: Plot Whittaker biomes with ggplot2. R package version (2020).

  370. 370.

    Whittaker, R. H. Communities and ecosystems. (MacMillan Publishers, 1975).

  371. 371.

    Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article  Google Scholar 

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We acknowledge the work of all Australian taxonomists and their supporting institutions, whose long-term work on describing the flora has provided a rich source of data for AusTraits, including: Australian National Botanic Gardens; Australian National Herbarium; Biodiversity Science, Parks Australia; Centre for Australian National Biodiversity Research; Department of Biodiversity, Conservation and Attractions, Western Australia; Department of Environment, Land, Water and Planning, Victoria; Flora of Australia; Kew; National Herbarium of NSW; National Herbarium of Victoria; Northern Territory Herbarium; NSW Department of Planning, Industry, and Environment; Queensland Herbarium; State Herbarium of South Australia; Tasmanian Herbarium; and the Western Australian Herbarium. We gratefully acknowledge input from the following persons who contributed to data collection Sophia Amini, Julian Ash, Tara Boreham, Ross Bradstock, Willi A. Brand, Amber Briggs, John Brock, Don Butler, Robert Chinnock, Peter Clarke, Derek Clayton, Steven Clemants, Harold Trevor Clifford, Michelle Cochrane, Bronwyn Collins, Alessandro Conti, Wendy Cooper, William Cooper, Ian Cowie, Lyn Craven, Ian Davidson, Derek Eamus, Judy Egan, Chris Fahey, Paul Irwin Forster, John Foster, Tony French, Allison Frith, Ronald Gardiner, Malcolm Gill, Ethel Goble-Garratt, Peter Grubb, Chris Guinane, TJ Hall, Monique Hallet, Tammy Haslehurst, Foteini Hassiotou, John Herbohn, Peter Hocking, Jing Hu, Kate Hughes, Muhammad Islam, Ian Kealley, Greg Keighery, James Kirkpatrick, Kirsten Knox, Luka Kovac, Kaely Kreger, John Kuo, Martin Lambert, Dana Lanceman, Michael Lawes, Claire Laws, Emma Laxton, Liz Lindsay, Daniel Montoya Londono, Christiane Ludwig, Ian Lunt, Mary Maconochie, Karen Marais, Bruce Maslin, Riah Mason, Richard Mazanec, Elissa McFarlane, Huw Morgan, Peter Myerscough, Des Nelson, Dominic Neyland, Mike Olsen, Corinna Orscheg, Jacob McC. Overton, Paula Peeters, George Perry, Aaron Phillips, Loren Pollitt, Rob Polmear, Hugh Possingham, Aina Price, Thomas Pyne, R.J.Williams, Barbara Rice, Jessica L. Rigg, Bryan Roberts, Miguel de Salas, Anna Salomaa, Inge Schulze, Waltraud Schulze, Andrew John Scott, Alison Shapcott, Veronica Shaw, Luke Shoo, Anne Sjostrom, Santiago Soliveres, Amanda Spooner, George Stewart, Jan Suda, Catherine Tait, Daniel Taylor, Ian Thompson, Hellmut R. Toelken, Malcolm Trudgen, W.E Westman, Erica Williams, Kathryn Willis, J. Bastow Wilson, Jian Yen. We thank H Cornelissen, H Poorter, SC McColl-Gausden, and one anonymous reviewer for feedback on an earlier draft, and K Levett for advice on data structures. This work was supported by fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910). The AusTraits project received investment (, from the Australian Research Data Commons (ARDC). The ARDC is funded by the National Collaborative Research Infrastructure Strategy (NCRIS).

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