Vegetation Classification and Survey (VCS) (May 2020)
Montane mire vegetation of the New England Tablelands Bioregion of Eastern Australia
Abstract
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Aims: To use unsupervised techniques to produce a hierarchical classification of montane mires of the study region. Study area: New England Tablelands Bioregion (NETB) of eastern Australia. Methods: A dataset of 280 vascular floristic survey plots placed across the variation in montane mires of the NETB was collated. Vegetation types were identified with the aid of a clustering method based on group averaging and tested using similarity profile analysis (SIMPROF) and through ordinations using Bray-Curtis similarity and non-metric multidimensional scaling (NMDS). A hierarchical schema was developed based on EcoVeg hierarchy and was circumscribed using positive and negative diagnostic taxa via similarity percentage analysis (SIMPER) and importance based on summed cover scores and frequency. Results: We defined one macrogroup to include all montane mire vegetation of the NETB and within these two groups and twelve alliances. Conclusions: Our study re-enforced the separation of bogs from other montane mire systems and confirmed the separation of fens and wet meadows, a distinction that previously had not been independently tested. Based on our results many existing montane mire communities of the NETB have been ill-defined at multiple hierarchical levels, leading to confusion in threat status and mapping. Additionally, nearly half of the alliances we recognise were found to have no correlates within current classification systems, which necessarily has implications for the effectiveness of current conservation planning. Taxonomic reference: PlantNET (http://plantnet.rbgsyd.nsw.gov.au/, accessed June 2016). Abbreviations: BC Act = Biodiversity Conservation Act; EPBC Act = Environmental Protection and Biodiversity Act; NETB = New England Tablelands Bioregion; NMDS = non-metric multidimensional scaling; PCT = plant community type; RE = regional ecosystem; SIMPER = similarity percentage analysis; SIMPROF = similarity profile analysis.