Aligning quantitative vegetation classification and landscape scale mapping: updating the classification approach of the Regional Ecosystem classification system used in Queensland.
Addicott, Eda, Neldner, Victor, and Ryan, Timothy (2021) Aligning quantitative vegetation classification and landscape scale mapping: updating the classification approach of the Regional Ecosystem classification system used in Queensland. Australian Journal of Botany, 69 (7). pp. 400-413.
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Abstract
Vegetation classification systems form a base for conservation management and the ecological exploration of the patterns and drivers of species’ distributions. A standardised system crossing administrative and geographical boundaries is widely recognised as most useful for broad-scale management. The Queensland Government, recognising this, uses the Regional Ecosystem (RE) classification system and accompanying mapping as a state-wide standardised vegetation classification system. This system informs legislation and policy at local, state and national levels, underpinning decisions that have wide-ranging implications for biodiversity and people’s livelihoods. It therefore needs to be robust from a scientific and legal perspective. The current approach in the RE system for identifying vegetation communities relies on expert-based class definition procedures. This is in contrast to best practice, which is based on quantitative procedures. This paper discusses the RE system in a global context and outlines the updated approach that incorporates quantitative class definition procedures, synthesises the research behind the updated approach and discusses its implications and implementation.
Item ID: | 73032 |
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Item Type: | Article (Research - C1) |
ISSN: | 1444-9862 |
Copyright Information: | © CSIRO 2021 Open Access CC BY. |
Date Deposited: | 16 Mar 2022 01:11 |
FoR Codes: | 31 BIOLOGICAL SCIENCES > 3103 Ecology > 310308 Terrestrial ecology @ 100% |
SEO Codes: | 18 ENVIRONMENTAL MANAGEMENT > 1806 Terrestrial systems and management > 180606 Terrestrial biodiversity @ 100% |
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