Pristine or nearly so, no obvious signs of damage caused by
human activities since European settlement.
VG – Very Good
Some relatively slight signs of damage caused by human
activities since European settlement. For example, some signs
of damage to tree trunks caused by repeated fire, the presence
of some relatively non-aggressive weeds, or occasional vehicle
More obvious signs of damage caused by human activity since
European settlement, including some obvious impact on the
vegetation structure such as that caused by low levels of
grazing or slightly aggressive weeds.
P – Poor
Still retains basic vegetation structure or ability to regenerate
to it after very obvious impacts of human activities since
European settlement, such as grazing, partial clearing, frequent
fires or aggressive weeds.
VP – Very Poor
Areas that are completely or almost completely without native
species in the structure of their vegetation; i.e. areas that are
cleared or ‘parkland cleared’ with their flora comprising weed
or crop species with isolated native trees or shrubs.
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or crop species with isolated native trees or shrubs.
As a tool to assist in the description of vegetation pattern, environmental data from combination of remote
Research Network (TERN) soil layers including;
Total nitrogen, total phosphorus, available water capacity, coarse fragments, bulk
National Aeronautics and Space Administration (NASA) Shuttle Radar Topography Mission (SRTM)
non-void filled SRTM image included where with the use of System for Automated
indices were calculated including; Slope, aspect and topographic wetness index.
Data analyses involved three steps to screen data, define vegetation pattern and to link potential short term
ecological drivers. Prior to vegetation analyse data were subject to pre-processing on combination of nearest
neighbour distance in conjunction with inspection of releve data. The largest distance between two releves
represents the most dissimilar releves. The composition of these releves was then viewed and decision made
to keep or discard.
Classification involves various choices of data transformation, distance measures and clustering algorithms.
Each of these are known to constrain the data (in various ways) and to influence the resulting classification
scheme presented. Much attention has been drawn into the determination of the optimal choice of
transformation, distance and clustering to determine most robust and ecologically meaningful system of plant
APM tested 30 different and most commonly used methods using the OptimClass 1 procedure (Tichy et al.,
2010). The OptimClass 1 procedure was used to evaluate the different choices of classification techniques (S1).
The OptimClass procedure uses the Fishers Phi coefficient (which considers within and between cluster species
occurrences) to determine if a species is ‘faithful’. A classification is good when there are large number of
species which are ‘faithful’, where their distribution is within one cluster (community), and seen as bad if the
species are dispersed across several communities. This process was initiated using the freely available JUICE
program as interface between the vegetation data, PC-ORD (McCune and Mefford, 2006) and OptimClass.
Additionally, this method was used to inform of the nested hierarchical structure of the data and serves
toward delineation of communities, alliances and orders.
Step 2. Description of vegetation units
APM produced ‘fingerprint’ analyses of the vegetation units using JUICE (
). The fingerprint analyses
used defines three important descriptive vegetation descriptive features; (1) diagnostic species, those which
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occur within (mainly) one vegetation type, defined using Fisher’s Phi coefficient value, (2) dominant species, or
those which have a cover >25 (%) of above ground biomass within a plot, and (3) constant species which occur
in 60 % of releves within a community. The fingerprint provides a consistent syllabus for description and
comparison of the defined floristic communities.
Step 3. Determination of underlying vegetation patterns
APM conducted Canonical Correspondence Analyses (CCA) (Leps and Smilauer, 2003) using the robust choice
of hierarchical classification with the environmental data. CCA is a powerful ordination tool used to relate
underlying environmental drivers with second data matrix (vegetation) and can be used to assist in the
description of vegetation pattern.
Terrestrial Vertebrate Fauna Survey Methodology
The fauna field survey was undertaken by Dr Mitch Ladyman (Principal Biologist), Sarah Isbister (Environmental
Biologist) and Arlen Hogan-West (Graduate Biologist) from 22 - 26 November 2016. The survey was designed
to meet the criteria of a Level 1 fauna survey, as defined in the EPA Guidance Statement No. 56 on terrestrial
fauna surveys for environmental impact assessment (EPA, 2004b), Position Statement No. 3 (EPA, 2002) and as
instructed by the DPaW.
The field survey targeted Malleefowl, Shield-backed Trapdoor Spider (SBTS) and Western Spiny-tailed Skink,
three species protected under the EPBC Act and known to occur in the area. The survey utilised aluminium box
traps, camera traps and acoustic recording devices. All opportunistic observations of other species were
recorded. Table 2-2 outlines target fauna species and the method of trapping employed to determine presence
Table 2-2: Target fauna species and method of trapping
Leipoa ocellata (Malleefowl)
Idiosoma nigrum (Shield-backed Trapdoor Spider)
A total of two full spectrum lossless WAC0 format with Wildlife Acoustics SM2BAT bat detectors (sampling rate
384 kilohertz (kHz), trigger 6 decibels (dB) above background; 48 dB gain) were set to record the acoustic
signatures of the microbats across the project area. Detectors were set up in strategic locations where the
likelihood of detecting bats was significantly increased. Detectors were set to turn on automatically at sunset
and off at sunrise (Table 2-3).
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Scout Guard SG560K-14mHD white light and Reconyx HC500 HyperFire™ Semi-Covert IR were set up in a
drainage line (Table 2-4). The primary focus was on the Western Spiny-tailed Skink.
Table 2-4: Thermal trigger camera survey effort
No. of Traps
No. of Trap Nights
A total of 136 aluminium box traps were set up in various arrays according to the habitat at each site (Table
2-5). Traps were set up in habitats likely to support the Western Spiny-tailed Skink. Some arrays were in a
pseudo linear fashion following an intermittent drainage line, while others were placed around hollow logs or
at the base of trees (Figure 2-1).
Table 2-5: Aluminium box trap survey effort
No. of Traps
No. of Trap Nights
banks of well-established drainage lines. Where the ranges are positioned in an east-west orientation the
burrows can be found on the southern slope. This species prefers to make their burrows in heavy clay soils in
open York Gum (Eucalyptus loxophleba), Salmon Gum (E. salmonophloia), Wheatbelt Wandoo (E. capillosa)
woodland, with Jam (Acacia acuminata) forming a sparse understorey. A thin layer of permanent Eucalyptus,
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area that met these criteria was classified as suitable for I. nigrum.
Other habitat containing some but not all major elements of suitable habitat was classified as marginal habitat.
Searches for Idiosoma nigrum SBTS were undertaken in areas of marginal and suitable habitat. Each search
began with a transect to search for a burrow. Once one burrow was identified a targeted search was carried
out, using the burrow as a centre point from which to radiate outwards. Up to six arms radiating 50 m from the
burrow were determined using compass bearings, and each arm searched for more SBTS burrows. A total of
five searches were undertaken by three field personnel.
Document Name: 20170210_Fig2-1_ Biol Report
Document Name: 20170213_Fig2-2_ Biol Report
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Nocturnal searching comprised vehicle-based searches of all roads and tracks throughout the Project area.
Searches commenced after sunset (approximately 7pm) and typically lasted for more than one hour. On all
occasions hand held spotlights were used to detect arboreal or volant nocturnal fauna, including possums and
owls, and vehicle headlights and spotlights were used to detect ground dwelling reptiles and hawking
nocturnal birds that are often found roosting on the track.
Searches for Malleefowl nests were undertaken by walking transects in suitable habitat. The beginning of each
transect was marked with a hand held Global Positioning System (GPS) unit. Transects were walked by three
personnel, each searching a 20 metre (m) swath width. The location of Malleefowl mounds identified during
the search was recorded with a GPS. The areas searched are shown in Figure 2-3.
Movement between traps and sites on foot increases the likelihood of detection of scats and secondary
evidence of fauna. All evidence observed during daily systematic trap clearing was recorded.
Document Name: 20170210_Fig2-3_ Biol Report
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Leading up to the survey period, monthly total rainfall was above average for May, June, July and August.
Rainfall in September and October was below the average by 12.1 mm and 5.7 mm respectively (BoM, 2016a;
BoM, 2016b). Figure 3-1 illustrates total and mean monthly rainfall at Paynes Find in the six months prior to
The vegetation survey undertaken by Woodman in 2003 identified seven vegetation units in the western half
of the Project area. Most of the vegetation was in very good condition. Woodman concluded the vegetation
was likely to be well represented in the region due to the same landforms occurring on neighbouring pastoral
leases (Woodman, 2003). The vegetation communities are described in Table 3-1 and form a basis for
comparison with the work undertaken for the present survey.