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CHaPTeR 4 Results
a result of the vegetation type being sampled and the reason for the survey being conducted.
For example, a transect line may be the preferred option in dense vegetation as it provides
greater access, or canopy-only species may be recorded to ground-truth remote-sensed data.
Past vegetation classification studies have precluded surveys that do not conform to State
standards as they have been found to cause interference with the analysis outputs (Keith &
Bedward 1999).
YETI, a relational database used by many organisations to store systematic vegetation survey
data, has a series of tables that can hold detailed information about surveys and plot sites.
Information in these tables include, whom, when and how the survey was conducted; species
records; vegetation structure and dominate species information; details of the physical
environment; and disturbance information. However, the level of detail filled out for each
vegetation survey varies considerably. In this assessment up to half of the vegetation surveys
were missing important metadata such as the year the survey was conducted, the individual or
organisation responsible for collating the data and details of survey methodology. In addition,
different vegetation surveys record different levels of information; for example, one-third of
the surveys did not complete the vegetation strata height and percentage cover and over half
did not provide information on dominant species per strata. Literature reviews were utilised to
fill in metadata gaps, however, information conflicted from one report to another; for example,
the same survey was documented with different dates and survey methodology. The inclusion
of vegetation surveys lacking metadata and supporting documentation in the vegetation
community analysis will be questionable, thus, it is recommended that vital fields (i.e. date,
cover score, plot type and size) within YETI be made mandatory.
Evaluating and assessing survey data for accuracy and completeness is a major and often
underestimated component of any vegetation classification and mapping project. It initially
involves removing inappropriate data, such as duplicate sites and sites with no floristic
information, and will later require the standardisation of cover / abundance scores as well as
checking individual site and species records for accuracy and correctness. An initial assessment
of the data collated for this project revealed that 21% were duplicate plot sites and 1% contained
no floristic information. Duplicate plot site data was the result of collating data from various
sources and databases that may have altered the original survey and site identification name
or code for a specific project purpose. A total of 5415 plot sites have been identified during
the preliminary evaluation as having appropriate floristic information; however, they were
reviewed further to determine their final application within the project. Data evaluation is
a time-consuming process. An easily accessed centralised data repository that contains only
correct and accurate vegetation survey plot data would streamline the evaluation process. NSW
DECC is currently developing such a repository for systematic vegetation surveys conducted
within New South Wales.
A plant species inventory developed from plot sites collated during the data audit process
identified 3647 vascular plant species: this represents 61% of the New South Wales state total
(Hnatiuk 1990). Whilst this region is floristically diverse, 39% of the plant species identified
are represented at less then five plot sites. Approximately 4% of these species are listed as
threatened under either the NSW TSC Act, Commonwealth EPBC Act or listed as a ROTAP
species; however, the remaining 35% are not accounted for. A targeted flora survey completed
in the Brigalow Belt South bioregion by NSW NPWS derived a similar result (NPWS 2002).
The reason for species being recorded infrequently could be due to several reasons, such as a