A plot-based analysis of the vegetation of the Northern Territory, Australia: a first assessment within the International Vegetation Classification framework

Aims: To develop an interim classification of the vegetation of the Northern Territory at the International Vegetation Classification (IVC) division (level 4) and macrogroup (level 5) levels. These types are produced to assist in the development of an integrated nationwide plot and floristically based classification of Australia allowing integration within a global perspective. Study Area: The Northern Territory of Australia covers an area of 1.42 million square kilometres, almost 20% of Australia’s land mass. It comprises three distinct climatic zones including tropical, subtropical and arid vegetation types. Methods: We used collated vegetation data held by two organisations: the Northern Territory Government, Department of Environment, Parks and Water Security and the Terrestrial Ecosystem Research Network (a total of 45,710 plots used). We applied semi-supervised quantitative classification methods to define vegetation types at the IVC division and macrogroup levels. Analyses used kR-CLUSTER methods on presence/absence data. Macrogroups were characterised by taxa with the highest frequency of occurrence across plots. Additional analyses were conducted (cluster) to elucidate interrelationships between macrogroups and to assist in the assessment of division level typology. Results: We propose 21 macrogroups and place these within higher thematic levels of the IVC. Conclusions: We found that the IVC hierarchy and associated standard procedures and protocols provide a useful classification tool for Australian ecosystems. The divisions and macrogroups provide a valid framework for subsequent analysis of Northern Territory vegetation types at the detailed levels of the IVC. A consistent typology for the Northern Territory (and hopefully in future, for all of Australia) has numerous benefits, in that they can be used for various applications using a well-structured, systematic and authoritative description and classification that is placed in a continental and global context, readily enabling the one system to be used in studies from the local to global level. Taxonomic reference: Northern Territory Herbarium (2022). Abbreviations: DVT = Definitive Vegetation Type; IVC = International Vegetation Classification; nMDS = non-metric multidimensional scaling; NT = Northern Territory; NTVSD = Northern Territory Vegetation Site Database; NVIS = National Vegetation Information System; WA = Western Australia

Ben Sparrow and Emrys Leitch

Made available by the Northern Territory Library via the Publications (Legal Deposit) Act 2004 (NT).This is a medium resolution survey dataset (1:100 000), mapping vegetation communities for the Eastern and Southern portions of the Finke Bioregion in the Northern Territory and South Australia. It describes vegetation units and their attributes as floristic and environmental data and provides a basis for identifying the extent and distribution of vegetation communities. The accompanying report describes the methods used for collection of new data, the sources of the pre-existing data, contains information on applications of the data and recommendations for future mapping and integration with related datasets

Floristic and structural assessment of Australian rangeland vegetation with standardized plot-based surveys.

We describe and correlate environmental, floristic and structural vegetation traits of a large portion of Australian rangelands. We analysed 351 one hectare vegetation plots surveyed by Australia's Terrestrial Ecosystem Research Network (TERN) using the AusPlots Rangelands standardized method. The AusPlots Rangelands method involves surveying 1010 one meter-spaced point-intercepts (IPs) per plot. At each IP, species were scored, categorised by growth-form, converted to percentage cover as the input for the plot x species matrix. Vegetation structure is depicted by growth-form configuration and relative importance. The floristic and structural distance matrices were correlated with the Mantel test. Canonical correspondence analysis (CCA) related floristic composition to environmental variables sourced from WorldClim, the Atlas of Living Australia and TERN's Soil and Landscape Grid. Differences between clusters were tested with ANOVA while principal component analysis (PCA) ordered the plots within the environmental space. Our plot x species matrix required segmentation due to sparsity and high β-diversity. Based on the ordination of plots latitude within environmental space, the matrix was segmented into three "superclusters": the winter rain and temperate Mediterranean, the monsoonal rain savannas and the arid deserts. Further classification, with the UPGMA linkage method, generated two, four and five clusters, respectively. All groupings are described by species richness, diversity indices and growth form conformation. Several floristic disjunctions were apparent and their possible causes are discussed. For all superclusters, the correspondence between the floristic and the structural or growth form matrices was statistically significant. CCA ordination clearly demarcated all groupings. Aridity, rainfall, temperature, seasonality, soil nitrogen and pH are significant correlates to the ordination of superclusters and clusters. At present, our results are influenced by incomplete sampling. As more sites are surveyed, this pioneer analysis will be updated and refined providing tools for the effective management of Australian rangelands

Scatterplots of climatic variables as sampled by <i>AusPlots</i>.

<p><i>AusPlots</i> (red) are shown in the context of the climate space of the Australian Rangelands as a whole (grey): (a) Mean temperature versus Mean annual precipitation (MAP); (b) Mean maximum temperature of the warmest month versus Precipitation seasonality (coefficient of variation); (c) Precipitation seasonality versus latitude; (d) Mean annual precipitation versus latitude.</p

Location of <i>AusPlots</i> within Australia.

<p>Location of <i>AusPlots</i> within Australia.</p

Regression statistics for Species Abundance Distributions (SADs) along a continental Mean annual precipitation (MAP) gradient for vegetation group subsets.

<p>Regression statistics for Species Abundance Distributions (SADs) along a continental Mean annual precipitation (MAP) gradient for vegetation group subsets.</p

Vegetation groups sampled by <i>AusPlots</i>.

<p>Vegetation groups sampled by <i>AusPlots</i>.</p

Boxplots of climatic variables as sampled by <i>AusPlots</i> and species richness.

<p>Bold line represents median, coloured box the interquartile range, whiskers up to 1.5x interquartile range from median, points outliers: (a) Mean annual precipitation (MAP); (b) Mean temperature; (c) Precipitation seasonality (coefficient of variation); (d) Mean maximum temperature of the warmest month; (e) Species richness (point intercepts); (f) Species richness (vouchers).</p

Components of leaf-trait variation along environmental gradients

•Leaf area (LA), mass per area (LMA), nitrogen per unit area (Narea) and the leaf-internal to ambient CO2 ratio (χ) are fundamental traits for plant functional ecology and vegetation modelling. Here we aimed to assess how their variation, within and between species, tracks environmental gradients. •Measurements were made on 705 species from 116 sites within a broad north–south transect from tropical to temperate Australia. Trait responses to environment were quantified using multiple regression; within- and between-species responses were compared using analysis of covariance and trait-gradient analysis. •Leaf area, the leaf economics spectrum (indexed by LMA and Narea) and χ (from stable carbon isotope ratios) varied almost independently among species. Across sites, however, χ and LA increased with mean growing-season temperature (mGDD0) and decreased with vapour pressure deficit (mVPD0) and soil pH. LMA and Narea showed the reverse pattern. Climate responses agreed with expectations based on optimality principles. Within-species variability contributed 90% for χ, with LMA and Narea intermediate. •These findings support the hypothesis that acclimation within individuals, adaptation within species and selection among species combine to create predictable relationships between traits and environment. However, the contribution of acclimation/adaptation vs species selection differs among traits