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• W3204271812 abstract "This editorial introduces the Australian Journal of Botany special issue ‘Vegetation science for decision-making’. Vegetation science and classification are crucial to understanding Australian landscapes. From the mulga shrublands of the arid interior to the monsoon rain forests of northern Australia, we have culturally and scientifically built upon the delineation of vegetation into recognisable and repeatable patterns. As remote sensing and database capacities increase, this improved capability to measure vegetation and share data also prompts collaboration and synthesis of complex, specialised datasets. Although the task faces significant challenges, the growing body of literature demonstrates a strong discipline. In Australia, purpose-driven products describe vegetation at broad scales (e.g. the National Vegetation Information System, the Terrestrial Ecosystem Research Network). At fine scales however (i.e. that of the vegetation community), no uniform framework or agreed protocols exist. Climate and landform dictate vegetation patterns at broad scales, but microtopography, microclimate and biotic processes act as filters at finer scales. This is the scale where climate-change impacts are most likely to be detected and effected; this is the scale at which a deeper understanding of evolutionary ecology will be achieved, and it is the scale at which species need to be protected. A common language and system for understanding Australian communities and impetus for collecting data at this scale is needed. In the face of ongoing climate and development pressures and an increasingly complex set of tools to manage these threats (e.g. offset policies, cumulative impact assessments), a nationally collaborative approach is needed. It is our hope that this special issue will help to achieve this." @default.
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• W3204271812 date "2021-10-06" @default.
• W3204271812 modified "2023-10-14" @default.
• W3204271812 title "Australian advances in vegetation classification and the need for a national, science-based approach" @default.
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• W3204271812 doi "https://doi.org/10.1071/bt21102" @default.
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