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Table 2-1: Vegetation condition rating scale (adapted from Keighery 1994)
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Table 2-1: Vegetation condition rating scale (adapted from Keighery 1994) Vegetation Condition Description E – Excellent Pristine or nearly so, no obvious signs of damage caused by human activities since European settlement.
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 tracks.
G – Good 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.
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.
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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NL D – Completely Degraded 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.
As a tool to assist in the description of vegetation pattern, environmental data from combination of remote sensing and modelling sources was obtained for each quadrat:
Commonwealth Science and Industrial Research Organisation (CSIRO) Terrestrial Ecosystem Research Network (TERN) soil layers including; - Total nitrogen, total phosphorus, available water capacity, coarse fragments, bulk density, sand content, clay content, silt, pH, depth of regolith, depth of soil and effective cation exchange.
digital elevation. - non-void filled SRTM image included where with the use of System for Automated Geoscientific Analyses (SAGA) (Quantum Geographic Information System (QGIS)) various indices were calculated including; Slope, aspect and topographic wetness index. 2.3.1.1 Data analyses 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. Step 1. Evaluation of classification techniques 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 communities. 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.
APM produced ‘fingerprint’ analyses of the vegetation units using JUICE ( Tichý, 2002 ). The fingerprint analyses used defines three important descriptive vegetation descriptive features; (1) diagnostic species, those which
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NL 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.
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.
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 / absence.
X X
X Egernia stokesii badia (Western Spiny-tailed Skink) X X X X
2.3.2.1 Acoustic monitoring 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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NL Table 2-3: Acoustic monitoring survey effort Trap Location No. of Traps No. of Trap Nights Total SM26670
1 1 2 SM28066 1 2 3 Total 2 3 5
Thermal Trigger Fauna Cameras 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.
TC001
1 2 2 TC002 1 2 2 TC003
1 2 2 TC005 1 2 2 Total 4 8 8
Aluminium Box Traps 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).
Site 1
18 4 72 Site 2 19
4 76
Site 3 19
4 76
Site 4 20
4 80
Site 5 20
4 80
Site 6 20
1 20
Site 7 20
1 20
Total 136 22 424
Short Range Endemics Idiosoma nigrum mainly occurs on the upper to lower slopes of ranges, with only small numbers on the crest. I. nigrum has been identified in large numbers on plains, but within this area individuals were restricted to the 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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NL Casuarina and Acacia litter is required, within which the spiders forage (Main, 1987). Habitat of the Project 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.
Site 6 Site 1 Site 2 Site 7 Site 4 Site 3 Site 5 M 59/387 M 59/425 496000
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499000 67 70 00 0 67 71 00 0 67 72 00 0 67 73 00 0 67 74 00 0 Trap site Tenements Document Name: 20170210_Fig2-1_ Biol Report O \\M
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NL 2.3.2.5 Transect Observation Nocturnal Transects 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. Diurnal Transects 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.
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NL 3 VEGETATION RESULTS 3.1 D ESKTOP S URVEY 3.1.1 Climate 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 survey.
Figure 3-1: Monthly Paynes Find Mean Rainfall Leading up to the Survey
Previous Surveys 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.
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ai n fal l (m m Kataloq: seven-day-comment-on-referrals seven-day-comment-on-referrals -> Vegetation, Flora and Wetland Survey at the Wonnerup South Mineral Sands Deposit seven-day-comment-on-referrals -> Flora Survey of Battler Tenements M77/166 & P77/3645 seven-day-comment-on-referrals -> 14 th August 2013 For Extension Hill Pty Ltd: Extension Hill Magnetite Project seven-day-comment-on-referrals -> Figure 19: Eucalyptus desmondensis modelling results seven-day-comment-on-referrals -> Health monitoring program seven-day-comment-on-referrals -> Fauna and Fauna Assemblages Survey of the Kundip and Trilogy Study Sites seven-day-comment-on-referrals -> User Community seven-day-comment-on-referrals -> User Community seven-day-comment-on-referrals -> Fqm nickel australia p ty ltd Yüklə 9,02 Mb. Dostları ilə paylaş:
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