
TY  - JOUR
A1  - Sun, D. 
A1  - Hnatiuk, R. J. 
A1  - Neldner, V. J. 
T1  - Review of Vegetation Classification and Mapping Systems Undertaken by Major Forested Land Management Agencies in Australia
JF  - Australian Journal of Botany
JO  - Aust. J. Bot.
Y1  - 1998
VL  - 45
IS  - 6
SP  - 929
EP  - 948
KW  - 
UR  - https://doi.org/10.1071/BT96121 
N2  - This paper provides a detailed review of the major vegetation classification and mapping systems used by the management agencies with primary responsibilities for forested land in Australia. It focuses on the clarification of vegetation units and methodologies used. The paper also provides a comparison of the different nomenclatures against a simplified standard to show how the different systems relate to each other. In Australia, different systems for classifying and describing forest vegetation have been developed by various forest land management agencies to suit their own situations. Most vegetation classification systems reviewed are similar in using floristics and structure as the two primary elements in classifying vegetation types, and all use growth form (physiognomy) to distinguish vegetation units. The classification and mapping systems for wood production purposes differ from those for conservation and environment purposes in several aspects&#8212;wood production classifications emphasise commercial tree species and/or attributes such as height, whereas conservation classifications emphasise ecology, vegetation coverage, and the importance of understorey species. There are three broad strategic approaches in the vegetation classification programs being undertaken by the major forest land management agencies in Australia: (1) conducting a single classification across the whole of the agencies&#8217; land in a State; (2) conducting a vegetation classification at the regional level, but using the same methods in each region; and (3) using different methods depending on the specific objectives of individual studies. This paper highlights the value of accurate quantitative measurements in the field. For example, for the two key structural attributes of height and crown density, the measured raw data can be accommodated by a number of different classification schemes whereas if the raw data consists of only records by predetermined classes, then such accommodation is difficult and loses precision. 
ER  -

