Wetland Research & Management — - EPA WAepa.wa.gov.au/sites/default/files/PER_documentation... ·...

WAROONA MINERAL SANDS PROJECT

Baseline Aquatic Ecosystem Surveys and Preliminary Social Water Requirements

prepared for

by

— Wetland Research & Management —

Waroona Mineral Sands Project – Baseline Aquatic Ecosystem Survey & Preliminary SWRs

__________ Wetland Research & Management _________

iii

WAROONA MINERAL SANDS PROJECT

Baseline Aquatic Ecosystem Surveys and Preliminary Social Water Requirements

Report Prepared for:

ILUKA RESOURCES LIMITED GPO Box U1988 Perth WA

By:

Wetland Research & Management 28 William Street, Glen Forrest, WA 6071, Australia

Ph (61 8) 9298 9807, Fax (61 8) 9380 1029, e-mail: [email protected]

Final Report 8/04/2005

Frontispiece: Looking downstream along Ferraro Brook at site FB3.



iv

Study Team Management: Susan Creagh Field Work: Susan Creagh and Lisa Chandler Macroinvertebrate Identification: Lisa Chandler Report: Susan Creagh and Andrew W. Storey Acknowledgements This project was commissioned by Iluka Resources Limited. Lisa Sadler, Shannon Jones and Liz Kerr supported the project and provided flow data and information on environmental management and operations of Iluka within the study area. The authors are grateful to the following Waroona residents who readily granted access to their pastoral leases and offered valuable information on existing and historic hydrology, ecology and water use within the area; Colleen and Ross Archibald, Neil Bruce, Gordon Chaffey, Colin Davis, Fred Fiore, Nigel, Deb and Nola Johns, John Mitchell and Peter and Lindy Ward. Melissa Hopkins and Val English (CALM) are thanked for providing details of threatened ecological communities. Rob Donohue (DoE), Adrian Parker (DoE) and Mark Rivers (Dept. of Agriculture) are thanked for assistance sourcing historic flow records. Finally, Lisa Sadler (Iluka) is thanked for constructive criticism of the final draft report. Recommended Reference Format WRM (2005). Waroona Mineral Sands Project: Baseline Aquatic Ecosystem Surveys and Preliminary Social Water Requirements. Unpublished report by Wetland Research and Management to Iluka Resources Limited. February 2005. Disclaimer This document was based on the best information available at the time of writing. While Wetlands Research and Management (WRM) has attempted to ensure that all information contained within this document is accurate, WRM does not warrant or assume any legal liability or responsibility to any third party for the accuracy, completeness, or usefulness of any information supplied. The views and opinions expressed within are those of WRM and do not necessarily represent Iluka Resources Limited policy. No part of this publication may be reproduced in any form, stored in any retrieval system or transmitted by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of Iluka Resources Limited and WRM.



v

TABLE OF CONTENTS

SUMMARY ....................................................................................................................................................... VII

1. INTRODUCTION............................................................................................................................................. 1 1.1 STUDY OBJECTIVES....................................................................................................................................... 2

2. STUDY AREA................................................................................................................................................... 2 2.1 CLIMATE AND CLIMATE CHANGE.................................................................................................................. 7 2.2 REVIEW OF EXISTING KNOWLEDGE OF THE AQUATIC ECOSYSTEMS ............................................................. 8

2.2.1 History of Irrigation Drains within the Area........................................................................................ 8 2.2.2 Physico-chemistry of Surface and Ground Waters............................................................................. 10 2.2.3 Riparian Vegetation............................................................................................................................ 11 2.2.4 Aquatic Fauna .................................................................................................................................... 13

3. BASELINE SURVEYS OF AQUATIC ECOSYSTEMS ............................................................................ 17 3.1 METHODS.................................................................................................................................................... 17

3.1.1 Physico-chemical Parameters ............................................................................................................ 17 3.1.2 Macroinvertebrates ............................................................................................................................ 17 3.1.3 Fish and Crayfish ............................................................................................................................... 18 3.1.4 Riparian Habitat Assessment.............................................................................................................. 19 3.1.5 Statistical Analyses - PATN................................................................................................................ 19

3.2. RESULTS AND DISCUSSION......................................................................................................................... 19 3.2.1 Riparian Habitat Assessment.............................................................................................................. 19 3.2.2 Physico-chemistry............................................................................................................................... 24 3.2.3 Macroinvertebrates ............................................................................................................................ 27 3.2.4 Fish and Crayfish ............................................................................................................................... 37 3.2.5 Tortoises ............................................................................................................................................. 38

5. SOCIAL WATER REQUIREMENTS.......................................................................................................... 38

6. CONCLUSIONS ............................................................................................................................................. 41 6.1 ECOLOGICAL VALUES ................................................................................................................................. 41

6.1.2 Potential Threats from Mine Activities............................................................................................... 42 6.3 SOCIAL WATER REQUIREMENTS ................................................................................................................. 42

7 RECOMMENDATIONS................................................................................................................................. 43

REFERENCES.................................................................................................................................................... 45

APPENDICES ..................................................................................................................................................... 49 APPENDIX 1. PHOTOGRAPHS OF AQUATIC SAMPLING SITES, OCTOBER/NOVEMBER 2004................................. 51 APPENDIX 2. PATTERN ANALYSIS PACKAGE (PATN) ...................................................................................... 57 APPENDIX 3. KRUSKAL-WALLIS NON-PARAMETRIC TESTS ............................................................................. 59 APPENDIX 4. LIFE-HISTORY STRATEGIES OF FISH AND CRAYFISH RECORDED FROM STUDY AREA ................. 95 APPENDIX 5. HYDROGRAPHS FOR ILUKA SURFACE WATER GAUGING STATIONS............................................. 99



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List of Figures and Tables Figure 1. Location of study sites, mine lease and pit boundaries, gauging stations. .............................................. 2 Figure 2. Cadastral map showing property boundaries within study area and location of TECs and EPPs........... 5 Figure 3. Average annual total rainfall for Waroona townsite ............................................................................... 7 Figure 4. Average monthly rainfall for Waroona townsite .................................................................................... 8 Figure 5. Comparison of salinity (ECond. µS/cm) and nutrient (TN & TP, mg/L) levels with

ANZECC/ARMCANZ (2000) recommended maxima ............................................................................... 25 Figure 6. UPGMA classification dendogram of the 11 sites using standardised physico-chemical parameters. . 26 Figure 7. MDS ordination of the 11 Waroona sites. Ordination used standardised physico-chemical variables 27 Figure 8. Mean (±SE) macroinvertebrate ‘species’ richness at sites surveyed in October 2003.......................... 28 Figure 9. UPGMA classification dendogram of the 11 sites using macroinvertebrate log abundance. ............... 35 Figure 10. (a) MDS ordination of the 11 Waroona sites. Ordination used log abundance of macroinvertebrates35 Figure 11. UPGMA classification dendogram of the Waroona 2004 sites together with Drakesbrook 2003 sites

using macroinvertebrate log abundance. ..................................................................................................... 36 Figure 12. MDS ordination of Waroona 2004 sites together with Drakesbrook 2003 sites. Ordination used log

abundance of macroinvertebrates ................................................................................................................ 37

Table 1. Range in values of basic water quality parameters recorded within the region. .................................... 10 Table 2. Recent records of fish and crayfish within the region............................................................................ 14 Table 3. Species of waterbird recorded from drains adjacent to Waroona Main Drain (Storey et al. 1993 &

WRM 2003) and from within Iluka’s mining lease (GHD 2003)................................................................ 16 Table 4. Description of aquatic fauna sites surveyed in October 2004 ................................................................ 21 Table 5. Physico-chemistry of surface waters in Wealand, Ferraro and Nanga brooks and Upper Mayfield Drain,

October 2004. .............................................................................................................................................. 25 Table 6. ANZECC/ARMCANZ (2000) recommended maxima physico-chemical levels for Western Australian

freshwater ecosystems. ................................................................................................................................ 25 Table 7. Mean annual total phosphorus levels (mg/L) for each trophic category for tropical lotic (flowing)

waters .......................................................................................................................................................... 26 Table 8. Categorisation of trophic status of temperate lotic (flowing) waters, after Wetzel (1975). ................... 26 Table 9. Preliminary presence/absence list of macroinvertebrate taxa collected in Oct. 2004............................. 29 Table 10. Social water requirements – water census of surface water use in Ferraro and Wealand brooks,

conducted in August 2004. .......................................................................................................................... 39



vii

SUMMARY The aquatic fauna, channel morphology and a range of physical and chemical parameters were surveyed at 12 sites in seasonal brooks and drainage channels that traverse Iluka Resources Limited mineral sands mining lease at Waroona. The aquatic fauna survey was conducted in mid October 2004 and represented a baseline study for the area prior to commencement of mining. Surveyed reaches included Ferraro and Wealand brooks in the Upper Mayfield Drain catchment and Nanga Brook, upstream of Drakesbrook Drain. A study of social water use was also undertaken for Ferraro Brook, downstream of a potential water dam site for the mine.

Aquatic macroinvertebrates were collected using qualitative sweeps. Fish were recorded using a combination of methods; sweeps, box traps, electrofisher and direct observation. Qualitative assessments of riparian habitat condition were made on the basis of dominant plant species and erosional characteristics. Riparian Habitat Condition

Brooks and drains within the areas are seasonal with some small, permanent pools maintained by groundwater over summer. The stream landscapes within the study area were considered extremely degraded due to historic clearing of catchment vegetation, drain construction and unrestricted livestock access. Channels at all sites were characterised by extensive erosion, with bank slumping, channel widening and bed down-cutting (to 4 m in Ferraro Brook). Pasture species dominated the riparian understorey vegetation with few other native species present. There were only remnant pockets of mature overstorey; mostly Eucalyptus rudis and Melaleuca spp. Though the regional ecological value of most of the remnant riparian vegetation was considered to be low, local landcare groups have begun streamlining and revegetation of the drains.

Downstream from the mining lease, the drains also flow through two CALM Threatened Ecological Communities (TECs; types 8 & 10a) located 2 km WNW of the mine lease between South Western Highway and the railway. This area has also been listed on the Environmental Protection Authority’s revised draft Register of Protected Wetlands (EPP wetlands). Another small, EPP wetland lies approximately 3.5 km west of the mine boundary and 300 m north of the Ferraro/Wealand Brook confluence.

Potential changes in surface flow regime posed by mine activities and/or (possible) dam construction are not expected to affect the TECs, EPP wetlands or other remnant swamplands which were considered more reliant on groundwater. Any reduction in surface flows is likely to be compensated by overland paddock flows and flows from the unregulated Wealand Brook. A substantial reduction in brook/drain flows coupled with significant groundwater drawdown and lowered soil moisture would need to occur before downstream ecosystems were adversely impacted.

Water Quality

All study sites were characterised by moderate biological water quality, i.e. ‘fresh’ waters (<800 µS/cm; <500 mg/L), with relatively low turbidities (<10 NTU), circum-neutral pH and high daytime dissolved oxygen levels (≥65%). All watercourses were meso-eutrophic. At a number of sites, total nitrogen and total phosphorus levels exceeded recommended maxima for the protection of aquatic ecosystems.



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Aquatic Fauna

A total of 128 taxa were identified and spatial variation in species richness was low; there was no significant difference in taxa richness between the brooks/drains. Fauna was dominated by Insecta (78%), in particular detritivores. Well represented were the Diptera (two-winged flies), Coleoptera (aquatic beetles), Crustacea and Odonata (dragonflies & damselflies). Species diversity was low-moderate and typical of disturbed rural systems on the coastal plain. However, one new species of Chironomidae (Tanypodinae sp. nov.) was recorded from drain sites west of the Highway. There have been few comprehensive studies of the taxonomy and distribution of chironomids in the south-west, making it difficult to confer conservation status on this species. Multivariate analyses (PATN) indicated the macroinvertebrate community structures of upper Ferraro Brook, Nanga Brook, upper Wealand Brook and Upper Mayfield Drain (including channelised sections of Ferraro and Wealand brooks) were distinct from each other. Factors such as turbidity, salinity and water depth appeared to be likely determinants of observed variations in macroinvertebrate community structure.

Three fish species were recorded in low numbers; the western minnow Galaxias occidentalis, the pygmy perch (Edelia vittata) and the introduced Mosquitofish (Gambusia holbrooki). Two species of freshwater crayfish were also collected; gilgies (Cherax quinquecarinatus) and koonacs (Cherax plebejus). All species are widespread throughout the south-west.

There was anecdotal evidence that the numerous semi-permanent swamps and wetlands adjacent to the main channels (including Mullins Sumpland) provide habitat for western long-necked tortoises (Chelodina oblonga).

While the current proposal for mineral sands mining is unlikely to directly affect surface flows, there is the potential for indirect impacts to aquatic fauna through groundwater drawdown, increased sedimentation (pool aggradation) and through possible future dam regulation.

Social Water Requirements

Any changes to surface waters in Ferraro and Wealand brooks and in Upper Mayfield Drain are not expected to affect downstream agricultural properties. Stock and irrigation water is derived from groundwater – bores, wells and soaks. While unlikely, there is some potential for loss of aesthetic (remnant & replanted native vegetation) and recreational (freshwater crayfish) values if surface, groundwater and sheet flows were all significantly reduced. In this case, surface water would need to be artificially supplemented to support local landcare projects. Recommendations

1. Any proposed management/monitoring programmes should seek to prevent further degradation of those areas that retain some ecological value and to facilitate the possible future restoration of degraded areas.

2. Iluka has already formulated programmes for monitoring ground and surface water quality and quantity as well as plans for drainage management. Monitoring sites cover reaches in Ferraro, Nanga and Wealand brooks, both upstream and downstream of proposed mine areas (refer Iluka 2004b). These monitoring programmes should be maintained for the life of the mine and data adequately evaluated.

3. Though winter flows are now greater than would have occurred historically, the seasonality of the flow regime has been maintained. Over summer, some permanent soaks and channel pools should be maintained to provide a summer dry-season refuge for macroinvertebrate species and long-necked tortoises.



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4. To protect habitat for tortoises and freshwater crayfish it is recommended that turbidity in natural streams downstream from mining should not increase by more than 10% above the existing seasonal mean concentration (based on ANZECC/ARMCANZ (2000) guidelines for the protection of aquatic ecosystems). These species may become locally threatened due to loss of breeding habitat, shelter and food resources if mining were to lead to siltation/aggradation of existing small pools and permanently increase turbidity.

5. To supplement Iluka’s ground and surface water monitoring, aquatic ecosystem monitoring is recommended to confirm there are no detrimental impacts from mineral sands mining. Ecosystem monitoring would also assist in determining the success of streamlining projects currently being undertaken by local landcare groups. At least biennial monitoring of aquatic fauna (macroinvertebrates & fish) and associated physico-chemical parameters and riparian vegetation condition is recommended. A sub-set of sites for long-term monitoring could be chosen from sites surveyed in the current study (based on results of PATN analyses), but where possible should correspond to Iluka’s surface water monitoring sites. In total, a minimum of six sites should be chosen to cover both upstream and downstream (of mine operations) reaches along all three brooks.



1

1. INTRODUCTION As part of a proposal to establish a mineral sands mine near the township of Waroona, Iluka Resources Limited (Iluka) commissioned Wetland Research and Management (WRM) to conduct baseline biological surveys of seasonal drainages potentially affected by the mine development. The proposed development is located approximately 110 km south of Perth, on mainly cleared agricultural lands one kilometre north of the township of Waroona and east of the South Western Highway (Figures 1 & 2). The current study will contribute to an Environmental Impact Assessment (EIA) prior to commencement of mining. Groundwater investigations (URS 2002) and terrestrial flora and fauna surveys (GHD 2003) have already been completed. Iluka hopes to begin operations at Waroona in 2006 and continue for approximately five years. It is expected that site rehabilitation would continue for a further four years following mine closure. The mining lease is located in the foothills of the Darling Scarp. There are three brooks that cross the mining lease; Wealand Brook, Ferraro Brook and Nanga Brook. On the coastal plain, Wealand and Ferraro brooks join the Upper Mayfield Drain system, while Nanga Brook forms a major tributary of Drakesbrook Drain. All three brooks are seasonal with flows generally peaking during July-August. Ground and surface waters within the area are used for stock, horticulture and residential supply. There are also at least three Department of Conservation and Land Management (CALM) threatened ecological communities (TEC) located within three kilometres of the main pit. These TECs are likely to be dependent on both overland and groundwater flows. Mine-pit dewatering will be required and is anticipated (URS 2002) to cause localized1 groundwater drawdown. This may reduce baseflows in Ferraro and Nanga brooks and subsequently impact downstream users (URS 2002). The nature of hydraulic connectivity between surface and groundwaters in the area is currently under investigation by Iluka. Dewatering discharge will preferentially be used to meet operational water demands together with scheme water supplied through Harvey Water (Iluka 2004b). Initial mine development plans included the construction of a water dam on Ferraro Brook for storage of dewatering discharge and surface run-off. However, current plans are for the dam to be constructed adjacent to the brook (Iluka 2004b). Iluka plans to redirect all stormwater runoff from operational areas away from existing watercourses and into either the water dam or settling sumps. In a storm event, water will only be released from the water dam into Ferraro Brook. Runoff from undisturbed areas will be diverted into Ferraro and Nanga brooks. Surface and groundwater flow and quality will be monitored both upstream and downstream of all pit areas (Iluka 2004b). Iluka has committed to ensure that mine operations do not affect downstream ecological and social water users and to provide artificial supplementation should adverse impacts occur. To this end, social water requirements for Nanga Brook were assessed by URS in May 2001 (URS 2002). As part of the current study, consideration was given to social impacts that may result from any reduction in flows in Ferraro Brook and Wealand Brook. WRM has also been commissioned to assess the ecological water requirements (EWRs) of the natural part of Ferraro Brook and for the downstream modified channel (drain). Determining EWRs will identify the ecological values of surface waters potentially affected by the proposed development and enable the sustainable yield of the resource to be established. EWR results will be presented in a separate report.

1 It is anticipated that the extent of water table drawdown will be restricted within the boundary of the mine lease and largely limited to within the pit areas (URS 2002).



2

1.1 Study Objectives The aims of the current survey were to:

i. review existing knowledge of all surface water ecosystems within the Waroona project area,

ii. establish baseline environmental conditions in Wealand, Ferraro and Nanga brooks, iii. review the significance of aquatic biota in local and regional context and iv. design a long-term monitoring programme that would allow for future evaluation of

levels of natural variation and assess the impacts of mining.

2. STUDY AREA The area lies within of the Harvey River Drainage Basin and the Waroona Subarea of the Murray Groundwater Area. Surface hydrology is dominated by small seasonal and intermittent brooks, with highly variable flows. A number of farm dams have been constructed on the larger brooks. There are three major drainages:

i. Wealand Brook, the headwater reaches of which cross the north-east corner of the mining lease,

ii. Ferraro Brook, which traverses the lease, flowing between the proposed north and south pits and

iii. Nanga Brook, which lies along the southern boundary. Downstream of the lease, all three brooks flow through numerous small private landholdings and have been channelised; Nanga Brook flows into Drakesbrook Drain while Ferraro and Wealand brooks are tributaries of the Upper Mayfield Drain system (Figure 2). These drains form part of the extensive network of historic irrigation drains that now characterise the Harvey River catchment. The brooks arise in forested regions of the Darling Scarp and flow westward through the foothills (Ridge Hill Shelf) and out across the Pinjarra Plain where they join the irrigation drains. The natural watercourses become progressively more modified and channelised as they cross the Pinjarra Plain. While flows in the more forested upper reaches of the Scarp are determined by rainfall runoff, baseflows in the mid and lower reaches are also strongly linked to groundwater. The groundwater table is shallow and often intersects surface flows in the foothills and Pinjarra Plain. Winter-wet depressions in western parts of the mine lease are interconnected during winter rains. Dunal fringe springs and Mullins Sumpland lies just outside the western boundary and feeds into Nanga Brook. Mullins Sumpland was formed following clearing of the area from agriculture and a subsequent rise in the water table (L. Sadler, pers. comm.). Part of the sumpland will be disturbed by mining and Iluka anticipates that flows from the sumpland will be reduced.

WAROONATOWNSITE

Mullins

Hill StWeir

Ferraro

613054

UMD2

UMD1FB5

WB4

FB4

WB3

FB3

WB2

WB1

FB2

FB1

NB1

MullinsSumpland Springs

Speedway

Hall Road

McNeill Road

South Western Highw

ay

Som

ers

Roa

d

Mayfield Road

Coronation Road

Faw

cett

Roa

d

Storey Road

Peel Road

Wealand Road

Paterson Road

Hill

Str

eet

Peel Road West

Bro

ckm

an R

oad

Whe

ttem

Roa

d

Nanga brook Road

Tatcher Stre

et

Storey Road

Mayfield Road

Coronation Road

Somers Road

Bro

ckm

an R

oad

Ferraro Brook

Nanga Brook

Wealand Brook

ILUKAORIG:DRAWN:

SCALE:DATE: DWG No: FIGURE:

WAROONA

AERIAL PHOTOSTUDY SITES, MINE

LEASE AND GAUGING STATIONS

L.SadlerS.P.

8 April 2005 150138 ver.00 11:25 000

LegendHM Reserves

Water features Year of photography: 2001 ´0 500 1,000mGauging Station

Study Site

WAROONA

Mayfield Road

South Western H

ighway

Wealand Road

Hall Road

Patterson Road

Broc km

an Road

Mayfield Road

Coronation Road

Som

ers Road

Storey Road

Tallathalla Road

Tall ath alla Ro ad

Peel Road

Nanga brook Road

Fawc ett R

oa d

McN

eill Road

Loc 9

Lot 3

Lot 5

Lot 4

Lot 6

Lot 2

Loc 524

AA 2

Lot 10

AA 34

Loc 409

AA 37

Aa 7

Lot 2

Loc 927

Loc 374

Loc 368

Loc 245

Loc 296 Loc 296

Loc 214

Lot 1

AA 36

AA 8

AA 6

Loc 1255

AA 30 AA 31

Aa 27

Loc 289

Aa 14

Lot 2

Loc 493

Loc 365

Loc 408

Loc 547

Loc 441

Loc 371

Loc 165

Loc 228

c 863

Loc 869

Lot 3

AA 12

Loc 397

AA 13 Aa 15

Loc 481

AA 4AA 1

Aa 17

AA 3

Aa 11

Loc 523

AA 20 AA 26

AA 5

AA 18

Lot 2

Aa 33

Loc 807

AA 35

Loc 882

Aa 9

Lot 2

AA 38

Loc 903

Lot 4

Lot 1

Loc 808

Loc 988

Loc 517

Lot 101

Loc 1217

Loc 407

Loc 381

Loc 159

Loc 246

Loc 364

Loc 421

Loc 216

Loc 411

Loc 432 Loc 433

Loc 370

Loc 164

Loc 255

Loc 520

Loc 336

Loc 806

Lot 5

Loc 412

AA 39

Loc 1182

Loc 382

AA 19

AA 39

Aa 32

AA 10

Loc 382

AA 10

Loc 399

AA 186

Loc 412

Lot 10

Loc 882

Lot 1Lot 2

AA 38

Loc 407

Loc 652

Loc 1255

AA 37AA 1 AA 4 AA 5

Lot 3

Loc 903

AA 3

Loc 1277

Loc 339

R20585

AA 38

AA 186

Loc 805

Loc 988

Loc 1333

Lot 0

Loc 876

Loc 1497

Loc 481

Aa 192 R22912

Loc 336

Fiorenza A

Polinelli G

Look J J & T R

Tognela I D

Tognela I D

Clark R P

Aintree Pty Ltd

Look J J

Leach M C

Mullins G J

Spurge D K

Asia Securites Aust Pty LtdWinavon Pty Ltd

Mullins G J

Asia Securities Aust Pty Ltd

Bruce R D


Ward L E & P W

Caruso S

Maiolo C

Jenkins M F & M E

Curtis D DFiorenza A

Jenkins M F & M E

Ferraro L M

Mitchell J A

Tognela C M & I D

Hodgson M R

Polinelli R

Wyllie Group Pty Ltd

Birch M S

Bruce N R

Pazzano N & N

Iseppi J A & L E

Pazzano JWard L E & P W

Winavon Pty LtdPolinelli A S & G

Bruce N R

Kau P G

Charla Downs Pty Ltd

Mullins E M & L A

Hodgson D J

Sceresini R I

Hull R W & T J

Archibald C H & R A

Poplars Pty Ltd


Fitzpatrick J J



Alba Farms Pty LtdVincent L K & W

Leach P D & S M


Charla Downs Pty Ltd Of Wa

Walmsley J MVincent L K & W

Bruce N R

Fiore F P & Madafferi G


Bowles J H & R A

Goerling M B & R C

Fanto A & I

Piscioneri S E & V Fitzpatrick D J & M B

Wunthree Pty Ltd Wunthree Pty Ltd

Hutchison S W

Archibald R A

Johns C A & N M

Bowles J H & R A

Bowles J H & R A

Caratti S M

Mitchell Nominees Aust Pty Ltd

Tognela F A & S M

Caratti S M


Archibald C H & R A



Hodgson M R


Archibald C H & R A

Charla Downs Pty LtdCharla Downs Pty Ltd

Net EnterprisesWa Pty Ltd

Hodgson D J

Yolande Investments Yolande Investments


Net EnterprisesWa Pty Ltd

Aintree Pty Ltd

Halycon Pty Ltd

Look J J

Hodgson M R


Mitchell Nominees Aust Pty Ltd




Asia Securities AustPty Ltd

Fitzpatrick P F & Iluka Resources Ltd

Wyllie Group Pty Ltd

Hull C A & H C

Brooks E M & Iseppi E M &Valenta K C & Others

Birch M S

Solleone Pty Ltd

Costello D L & D A

Caratti A J & Caratti R J &Bulla Nominees Pty Ltd



Walmsley J M

De Rosa A P & Rosa N P

Fitzpatrick P F &Iluka Resources Ltd

Caratti A J & Caratti R J &Bulla Nominees Pty Ltd

Caratti A J

Archibald C H & R A

Charla Downs Pty Ltd Charla Downs Pty LtdCharla Downs Pty Ltd

Kau P G

Archibald R A

Charla Downs Pty LtdMitchell J A

Mullins E M & L A

Polinelli A S & G

Water & Rivers

Brooks E M & Iseppi E M& Valenta K C & Others

Nanga Brook

Ferraro Brook

Wealand Brook

EPP Wetland#724

Wetland

Wetland

N

ILUKAORIG :

DRAWN :

DATE :

SCALE :

FIGURE :DWG No : 150139 ver.00

1:20 000

8 April 2005

S.P.

L.Sadler

COMMENTSDESIGNNo ORIG: DATE

REVISIONS

CADASTRAL MAPSHOWING PROPERTYBOUNDARIES, TEC'sAND EPP WETLANDS

WAROONA

Legend

ILUKA Properties

HM Reserves

Perth

Bunbury

0 100

KM

Augusta

Map Area

Location Diagram

500 0 500 Meters

Approximate Location of Threatened Ecological Communities



7

2.1 Climate and Climate Change The climate of the region is Mediterranean (Seddon 1972) with hot, dry summers and cool, wet winters. Long-term rainfall records for Waroona Townsite (Station 009614) show the average annual rainfall for the period 1936 - 2003 was 1,019 mm (Figure 3). Maximum rainfall occurs between June - August (winter) with minimum rainfall occurring in January - February (summer). Average annual evaporation rates are around 1,700 – 1,800 mm. Historically, rainfall has been both seasonal and highly predictable. However, south-western Australia has experienced a significant rainfall decline since the 1960/70’s (CSIRO 2001). In the Waroona area, this has resulted in a significant (p < 0.10)2 reduction in mean annual rainfall from pre-1975 years (mean = 1045 mm) compared with post-1975 years (mean = 978 mm) (Figure 3). This reduction in rainfall is most evident in winter months (May - August) with a tendency for slightly higher rainfall in summer (Figure 4). Current CSIRO (2001) models for global warming predict a general increase in temperature for the south-west of between 0.4 - 1.6°C by the year 2030. A decreasing trend (-20% to +5%) in winter and spring rainfall is also predicted and a ±10% change in summer/autumn rainfall. While the intensity of specific winter rainfall events may increase, their duration is expected to decrease. Correspondingly, the duration of drought events and rates of evaporation is also expected to increase. The 20% decrease in south-west rainfall experienced over the last 30 - 40 years has resulted in a 30 - 40% decrease in annual streamflow (WRC 2002). Data specific to a number of south-west catchments support these predictions. The Canning River catchment to the north of the current study area has experienced an 18% reduction in annual rainfall with a corresponding 48% reduction in stream inflow to the Canning Reservoir (Storey et al. 2001). Calculations for the lower Collie River catchment to the south, indicate an 11% reduction in rainfall and a 36% decrease in stream flow (WEC 2002a).

Annual Rainfall @ W aroona (1936-2003)

400

600

800

1000

1200

1400

1600

1935

1940

1945

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Ann

ual R

ainf

all (

mm

)

Mean (1936 - 2003) = 1019mm

Mean (1936 - 1974) = 1045mm

Mean (1975 - 2003) = 978mm

Figure 3. Average annual total rainfall for Waroona townsite for periods 1936 - 2003 (blue line), 1936 - 1974 (orange line) and 1975 - 2003 (green line).

2 t-test, df = 37,23, t-value = 1.522, p = 0.067.



8

Total Monthly Rainfall for W aroona (009614) from 1936 - 2003

0

50

100

150

200

250

Janu

ary

Feb

ruar

y

Mar

ch

Apr

il

May

June

July

Aug

ust

Sep

tem

ber

Oct

ober

Nov

embe

r

Dec

embe

r

Ave

rage

Tot

al M

onth

ly R

ainf

all (

mm

) 1936-2003

1936-1974

1975-2003

Figure 4. Average monthly rainfall for Waroona townsite for periods 1936 - 2003, 1936 - 1974, and 1975 - 2003.

Rainfall records for Waroona indicate a smaller decline in annual rainfall of only 5%. However, records covering the above-average rainfall period of 1915 – 1935 are missing and consequently, calculations of percent reduction in annual rainfall for Waroona will underestimate actual change. Based on the findings of Storey et al (2001) and WEC (2002a), it is likely that the Waroona area has experienced a 35 – 45% reduction in natural streamflow since the mid 1970s.

2.2 Review of Existing Knowledge of the Aquatic Ecosystems 2.2.1 History of Irrigation Drains within the Area

The hydrology of the study area has been extensively modified as a result of clearing for agriculture in the foothills and coastal plain and the construction of drains, diversion structures and farm dams. Prior to European settlement, most of the low-lying lands of the Swan Coastal Plain (including the Pinjarra Plain) between Mandurah and Harvey would have essentially transformed into a vast wetland each winter. Although westward flowing streams and brooks had well defined and stable creek lines in their upper reaches, their flow dispersed and dissipated into a broad, interconnected chain of swamps many kilometres wide (Bradby 1997) across the coastal plain. Only the larger rivers, such as the Murray and Dandalup had clearly defined channels on the coastal plain and even these flooded across the flats in winter. Other main rivers, such as the Serpentine and the Harvey, were well defined in their upper (inland) and lower (coastal) reaches, but their mid reaches consisted of “extensive and impenetrable (paperbark) swamps” without a defined river channel (Bradby 1997). One of the most important attributes of a river system - one that has a dominant influence on the ecological values - is permanence of flow; i.e. whether flows are seasonal or perennial. Prior to European settlement, many of the streams originating on the Darling Scarp were seasonal (Bradby 1997). However, these systems soon became perennial once catchment clearing and logging increased recharge and run-off. By the late 1800s, increased run-off had exacerbated the flooding of the coastal plain swamps.



9

In order to reduce the flooding, drain construction began on the smaller brooks to convert them to deeper, faster flowing channels. In 1901, de-snagging of the lower reaches of the Harvey River commenced in an effort to increase flows from the swamps and constructed drains. At the same time, ring-barking was used as a strategy by settlers in the early 1900s to clear trees in the upstream catchment and initiate/increase summer flows to provide a water supply (Bradby 1977). Construction of the Harvey Main Drain was finally completed in 1934. Today’s largely artificial watercourses of Mayfield, Drakesbrook and Waroona Main drains were in place by the 1950’s (Bradby 1997). These irrigation drains were constructed and maintained (up until the 1980’s) for winter flood relief and summer irrigation sourced from storage dams on the Darling Scarp. The drains resulted in increased soil water flow and nutrient loss and in the late 1980’s, the (then) Water Authority of Western Australia and the Environmental Protection Agency negotiated to place a moratorium on further drain construction and introduce controls on farm drainage (Kinhill 1988, Ruprecht & George 1993). Over-drainage now appears the dominant problem, with large losses of soil water and nutrients in winter months. During the 1990’s, there was widespread support among landholders within the region for management plans that incorporated drainage modification (George & Bradby 1993). Subsequent modifications included the installation of barrages and drainage sumps, to reduce the flow of nutrient-rich waters to the Peel-Harvey Estuary over the spring to autumn period, and the replanting of wetlands along drain peripheries to act as biological filters. Regulation by damming has substantially reduced flows from the forested upland sub-catchments and reduced exchanges between river and floodplain. However, clearing has substantially increased overland flows resulting in a net increase in discharge in the lower rivers compared to the historic (pre-European) conditions. A State Government scheme to provide piped irrigation water was begun during the 1970’s. Following Federal Government reforms on water management, control of the system was ceded to South West Irrigation, a private irrigator’s cooperative now known as Harvey Water. Harvey Water has continued the gradual upgrade to deliver piped water under pressure, all year round. Piped supply has now replaced the historic open drainage channels throughout the Waroona irrigation areas (including the current study area) to provide a more efficient water delivery system. The Drakesbrook drainage system immediately south of the current study area, is an integral part of the Waroona Irrigation scheme, currently supplying approximately 6,000 ML/annum to the scheme, but with an estimated yield of approximately 10,000 ML/annum (WRM 2003). The irrigation scheme is based on storage provided by the Drakesbrook Dam (Lake Moyanup) and Waroona Dam (Lake Navarino), but is also supplemented with releases from the Samson Brook Dam. Total yield from Samson Brook Dam and pipehead dam is approximately 8,600 ML. From 1976 to 2003, on average, 6,090 ML was released to downstream irrigators from Drakesbrook Dam. However, because the distribution of flows amongst the various drainage channels is not gauged, it is not possible to determine the relative contributions of each source to the different parts of the irrigation system, especially as the proportion and dispersion of flows are continually modified to meet demand (WRM 2003). The Water Corporation provides piped residential water to Waroona under the Integrated Water Supply Scheme. Scheme water is sourced from Samson Dam to the east of the township.



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2.2.2 Physico-chemistry of Surface and Ground Waters

There is little specific published information about the quality of surface waters in the study area, though there a number of unpublished reports for the adjacent Samson Brook catchment. These relate to Alcoa’s Willowdale mine (Streamtec 1997, Creagh et al. 2004b) and to Water Corporation’s development of the Samson Brook pipehead dam (Streamtec 2002, Creagh et al. 2004a). WRM (2003) also measured various water quality parameters in the Waroona and Drakesbrook Main drains for Harvey Water in April 2003. This latter study incorporated analysis of nutrient data collected by the Department of Agriculture between 1999 - 2002. The WRC has recorded a suite of water quality variables at gauging station 613054 on Mayfield Drain since 1963. This station is located at a pipe-head dam south of the intersection of Storey and Somers roads, 1.5 km north of the current study area. Table 1 summarizes the water quality results of these previous surveys.

Table 1. Range in values of basic water quality parameters recorded within the region.

Parameter Drakesbrook & Waroona Main

Drainsa

Lower Samson Bk & McKnoe Bkb

Upland (forested) Samson Bkc

613054, Mayfield Sub G Drain, PHD2d

pH 6.8 - 7.3 6.9 - 8.1 5.0 - 7.0 5.7 – 9.0 Water Temperature (oC) 17.1 - 17.9 17.3 - 20.9 10.9 - 16.3 8.3 – 24.0 Turbidity (NTU) 40.6 - 70.3 0.99 - 11.6 0.4 - 1.6 0.49 - 150 Salinity (mg/L TDS) 160 - 190 90 - 110 60 - 90 81 - 585 Conductivity (µs/cm) 209 - 351 175 - 178 151 - 173 124 – 1,412 Dissolved Oxygen (% sat.) 105.1 - 122.1 64.0 - 104.5 86.0 - 129.0 -- Dissolved Oxygen (mg/l) 9.5 - 11.3 5.9 - 9.2 8.3 - 12.4 -- Total Nitrogen (mg/L) <0.01 - 3.0 0.11 - 0.84 0.02 - 0.15 0.46 – 6.3 Total Phosphorus (mg/L) <0.01 - 0.48 <0.01 - 0.03 <0.01 0.02 – 1.1

Sources: a WRM (2003), collected from Drakesbrook Main Drain in Apr. 2003 and Dept. of Agriculture WA weekly/fortnightly records from 1999 – 2002 in the Waroona Main Drain b Streamtec (2002) and Creagh et al. (2004a), data collected in Dec. 2001 and Nov. 2003. c Streamtec (1997) and Creagh et al. (2004b); data collected in Nov. 1995, Aug. 1996 and Nov. 2003. d Water and Rivers Commission gauging station on tributary of Mayfield Drain; records Jun. 1963 – Jun. 2003.

Waters at both forested upland sites and lowland agricultural sites were characterised by relatively high biological quality. In upland Samson Brook, there were no consistent ‘seasonal’ trends. During both base and recessional flow periods, sites were typically characterised by slightly acidic to neutral pH (5.0 – 7.0), high daytime dissolved oxygen content (80 – 130% saturation), low salinity3 (<175 µS/cm), low turbidity (<2 NTU) and low nutrient levels (TN <0.15 mg/L, TP <0.01 mg/L). Water temperatures were strongly linked to ambient air temperature, riparian shading and water depth. There was little variation between sampling years. These upland sites are likely to be similar to the more forested stream reaches above Iluka’s Waroona project area. Across the coastal plain, brook and drain waters tended to be more alkaline with elevated nutrient levels and elevated turbidity, particularly in Waroona, Drakesbrook and Mayfield Main drains. While salinity levels were also slightly higher in these drains, waters remained fresh. Quality of surface waters in these studies was consistent with local groundwater salinity levels. Iluka has monitored ground flows and quality within the vicinity of the mine lease since 1992. Results of monitoring have been detailed by URS (2002). Within the shallow groundwater 3 Defined by the Department of Agriculture, Government of Western Australia (2002) as: fresh <2,700 µS/cm; brackish 2,700 – 9,000 µS/cm; saline 9,000 – 55,000 µS/cm and seawater/extreme >55,000 µS/cm.



11

formations, waters tend to be slightly acidic (pH 5.5 – 7.0) with salinities ranging from fresh to brackish (70 - 3,200 mg/L TDS; ~100 – 5,500 µS/cm). Salinity increases with depth though the aquifers. 2.2.3 Riparian Vegetation

Riparian vegetation is defined as vegetation on any land that adjoins or directly influences a water body. Though riparian zones typically only occupy a small proportion of the landscape, they are usually the most productive, with higher species richness and abundance. Dense shrub understoreys provide habitat for terrestrial fauna such as birds, reptiles and native mammals. Dense macrophyte (e.g. rushes, sedges) beds provide habitat for water birds, frogs, fish and aquatic macroinvertebrates. Loss of these zones leads to loss of biodiversity and can have widespread ramifications downstream; e.g. increased nutrient and sediment loads and increased surface runoff resulting in flooding and channel erosion. Much of the original native vegetation of the foothills of the Waroona - Harvey region (including the current study area) has been cleared for agriculture and very little remains on the Coastal Plain (Beard 1979a,b, Heddle et al. 1980, Streamtec 1997, 2002, WRM 2003, Creagh et al. 2004a,b, GHD 2003). Most of the Coastal Plain native vegetation has been replaced by introduced weed and pasture species. Remnant native vegetation exists only as narrow corridors along road reserves and drainage lines or in pockets as isolated wetlands and swamps (LCCG 2001, Kabay 2002) and even in these instances, the understorey is often degraded. Exotics such as kikuyu (Pennisetum clandestinum), Watsonia (Watsonia spp.) pampas grass (Cortaderia spp.), capeweed (Arctotheca calendula), arum lily (Zantedeschina aethiopica) and cottonbush (Gomphocarpus fruticosus) are common, often encroaching into drainage channels. Historically, riparian zones would have been wide and densely vegetated. Beard (1979a,b) suggested that prior to clearing, the vegetation of the coastal plain would have been characterised by low Melaleuca and Callitris forest or by mosaic woodlands and shrublands dominated by tuart (Eucalyptus gomphocephalus), Acacia spp. and Dryandra sessilis. Streams, swamps and winter-wet depressions would have supported flooded-gum (Eucalyptus rudis), and paperbarks (Melaleuca preissiana & M. rhaphiophylla) over heath (e.g. Astartea fasicularis, Pericalymma ellipticum var. ellipticum, Regelia ciliata, Hypocalymma angustifolium), rushes (Juncus sp, Isolepis spp.) and sedgelands (Lepidosperma spp.). On the foothills and higher ground of the coastal plain this would have graded into jarrah (Eucalyptus marginata) and Banksia low woodlands with B. menziesii, B. attenuata, sheoak (Allocasuarina fraseriana) and prickly bark (Eucalyptus todtiana) over mixed heath. The deeper soils of the foothills would have supported marri (Corymbia calophylla). Nanga, Ferraro and Wealand brooks would have been well shaded by dense, overhanging riparian vegetation, and as such, algal-derived carbon (i.e. autochthonous sources) probably contributed little to the aquatic food web, with most carbon derived from riparian sources (i.e. allochthonous sources such as leaf litter). This has been demonstrated for relatively undisturbed forested headwater streams on the Darling Scarp (Davies 1993, Davies et al. 1998). Remnant paperbark woodlands in coastal plain reaches are also known to play an important ecological role in providing detrital food sources for aquatic invertebrate communities. The high accumulation of leaf litter drives highly productive ecosystems, which in turn provide the potential for these woodlands to act as nutrient sinks (Congdon 1979, Greenaway 1994); an important consideration in riverine systems where nutrient input from agricultural sources is high. Vegetated riparian land in general acts as a buffer to reduce nutrient and sediment loads from diffuse overland flows.



12

Within the Waroona study area, local landcare groups have begun streamlining4 and replanting native riparian vegetation (shrubs & trees) along drains on private property. This restoration aims to stabilise drains and increase productivity and sustainability (Kabay 2002). By creating vegetation corridors to link isolated remnant vegetation, it is hoped that conservation values will also be improved. In eastern parts of the foothills and on the Darling Scarp, riparian vegetation is less degraded and often still possesses a healthy overstorey. Lateritic soils overlie granitic bed-rock and support a dry sclerophyll forest which is dominated by jarrah (Eucalyptus marginata), with marri (Corymbia calophylla) in some valleys (Shea et al. 1975). This overstorey is sometimes replaced by other eucalyptus species including yarri (E. patens), bullich (E. megacarpa) and flooded-gum (E. rudis) along the creek-lines (Bell & Heddle 1989). Understorey trees are predominantly Banksia spp. with other common species including Allocasuarina fraseriana, grass-trees Xanthorrhoea spp. and Persoonia longifolia (Gardner 1942). Stream banks are characterised by dense sclerophyllous shrubs (e.g. Agonis linearfolia, Hypocalymma angustfolium, Calytrix glutinosa and Hakea costata) and sedges. Threatened Ecological Communities (TECs) and EPA Registered Wetlands (EPPs)

TECs There are three Threatened Ecological Communities (TECs) located 3 km west of the mine area (Figure 2). Community types present are 3a, 8 and 10a as recognised by Gibson et al. (1994). All co-occur within Parkland and Conservation Reserve 31437 that covers a total of about 36 hectares between South Western Highway and the railway (English & Blyth 2000). Community type 3a is dominated by marri (Corymbia caloyphylla) and grass-trees (Kingia australis) and only occupies about ten hectares of the reserve at the end of Hall Road, approximately 800 m north of the South Western Highway road culverts on Wealand Brook. Immediately south of Community type 3a is a small pine plantation. Community types 8 and 10a lie adjacent to the southern end of the plantation and comprise “herb rich shrublands in clay pans” and “shrublands on dry clay flats”, respectively (English & Blyth 2000). There are no DRF or Priority flora recorded within these communities (English & Blyth 2000). CALM has listed community type 3a as Critically Endangered in Western Australia, type 10 as Endangered and type 8 as Vulnerable. All listings are endorsed by the Minister for the Environment. Type 3a is also listed as Endangered under the Commonwealth’s EPBC Act 1999. (M. Hoskins, CALM, pers. comm., 2004). Although there are other occurrences of these types within the Swan Coastal Plain, none are currently located within secure conservation reserves. All three types occur on wetter soils on the Swan Coastal Plain that have historically been cleared for agricultural and urban development. Very little is known about the hydrology of the communities, however type 3a is considered (M. Hoskins, CALM, pers comm., 2004) almost certainly to be dependent on the maintenance of surface and groundwater hydrology. Types 8 and 10a are considered most likely to be dependent on maintenance of surface and possibly groundwater hydrology. All communities occur in low lying sites and would experience seasonal inundation as they are associated with soils that contain “an impervious clay layer that would act as a barrier to drainage of water through the soil” (English & Blyth 2000). Although clearing has resulted in a net increase in overland flows and groundwater recharge, there are likely to be localised reductions in the watertable due to drain construction (English & Blyth 2002). Further changes in surface flow and groundwater level may

4 Grading, re-contouring and re-vegetation of waterways to resemble more natural conditions.



13

alter the period and depth of inundation. Depth to groundwater in the vicinity of the communities in the study area is not known. EPP Wetlands Parkland and Conservation Reserve 31437 is also listed on the Environmental Protection Authority’s revised draft Register of Protected Wetlands under the Revised Draft Environmental Protection (Swan Coastal Plain Wetlands) Policy and Regulations 2004. The EPA policy and regulations were formulated to protect wetlands of high ecological value. Reserve 31437 includes sumpland, identified (but not formally assessed) by Hill et al. (1996) in Wetlands of the Swan Coastal Plain, as Wetland #91, Map Sheet 2032 II NE (Hamel NE). This sumpland and surrounding dampland is bounded to the north and south by channelised sections of Wealand and Ferraro brooks, respectively. Another small, isolated EPP wetland is listed approximately 3.5 km west of the mine boundary and 300 m north of the Ferraro/Wealand brook confluence (Figure 2). This wetland corresponds to sumpland mapped by Hill et al. (1996) and identified as Wetland #37, Map Sheet 2032 II NE (Hamel NE). 2.2.4 Aquatic Fauna

There are no known published scientific data on the ecological state of the area prior to construction of the drains and water supply dams. Seasonal brooks and swamps typically support a different fauna to permanently flowing systems and irrigation drains. Fauna that inhabit seasonal or ephemeral systems must recolonise each year either by migration (from near-by permanent waters), development from resistant life-stages or from reinvasions by aerial adult phases. In south-western Australia, seasonal and ephemeral streams typically support a lower diversity of aquatic invertebrates and fish. Seasonal swamps, however often support a rich diversity and high abundance of aquatic invertebrates due to increased diversity of habitats and high primary production. Oral histories and general comments regarding rivers and wetlands on the Swan Coastal Plain (Seddon, 1972, Bradby, 1997) suggest a system with winter floods regularly inundating the floodplain, a floristically-rich and diverse riparian zone and large numbers of fish, crustaceans and waterbirds. Fish and Crayfish

Prior to European settlement, native fish inhabiting the area likely included species such as western pygmy perch (Edelia vittata), western minnow (Galaxias occidentalis) and nightfish (Bostockia porosa). These species would have recolonised creeks each winter from permanent wetlands on the coastal plain, or from permanent pools within the creek channel. The absence of dams and impoundments would have allowed upstream movement of migratory fish species, such as the western minnow in search of spawning habitat. The freshwater catfish (Tandanus bostocki) was known (Bradby 1997) to be plentiful in adjacent larger rivers that had well defined watercourses (i.e. Serpentine, North Dandalup, Harvey etc). However, it is unlikely that catfish occurred within the Waroona study area, as they would have had to migrate across seasonal swamps and wetlands on the coastal plain to reach the brooks. Similarly, there is no evidence that species more commonly associated with lower riverine/estuarine habitats, such as western hardyhead (Leptatherina wallacei), Swan River/blue



14

spot goby (Pseudogobius olorum) and big headed goby (Afurcagobius suppositus) could have migrated across the flooded coastal plain. However, these species would likely have colonised the Drakesbrook system once it became permanently flowing, following connection to the Harvey River by the Waroona Main Drain. Table 2 lists native and introduced freshwater fish and crayfish species recorded during recent surveys of the area. Of native species recorded, minnows, pygmy perch and nightfish are probably the most common in the southwest. The freshwater cobbler is locally threatened, with numbers much reduced in many coastal plain rivers due to loss of habitat.

Table 2. Recent records of fish and crayfish within the region.

Species

Dra

kes

Bro

ok

Foot

hills

& S

carp

Dra

kesb

rook

M

ain

Dra

in

War

oona

Mai

n D

rain

Sam

son

Bro

ok

Coa

stal

Pla

in

Sam

son

Bro

ok

Dar

ling

Sca

rp

McK

noe

Bro

ok

Dar

ling

Sca

rp

Native Fish Freshwater Cobbler (Tandanus bostockia) Nightfish (Bostokia porosa) Western Minnow (Galaxias occidentalis) Western Pygmy Perch (Edelia vittata)

Introduced Fish Carp/Goldfish (Crassius auratus) Mosquitofish (Gambusia holbrooki) Redfin Perch (Perca fluviatilis) Rainbow Trout (Onychorhyncus mykiss)*

Endemic Crayfish/Shrimps Freshwater Shrimp (Palaemonetes australis) Gilgie (Cherax quinquecarinatus) Marron (Cherax tenuimanus)

Introduced Crayfish Yabbie (Cherax destructor)

*Known to be stocked in Waroona and Drakesbrook dams. Sources: a WRM (2003), b Streamtec (2002) & Creagh et al. (2004a); c Streamtec (1997) & Creagh et al. (2004b). Macroinvertebrates

The aquatic macroinvertebrate fauna of the natural brooks would likely have been comparable to the relatively diverse fauna currently found in undisturbed, seasonal forested streams on the Darling Scarp (Storey et al. 1990, Streamtec 1997, 2002, WRM 2003, Creagh et al. 2004a, b). Recent surveys in the region recorded a total of 107 aquatic macroinvertebrate taxa (‘species’) from upland Samson Brook (Creagh et al. 2004b), 99 from lowland reaches (Creagh et al. 2004a) and 49 from Waroona/Drakesbrook Main drains (WRM 2003). The macroinvertebrate fauna recorded was dominated by Insecta, in particular detritivores but with a high diversity of predatory beetle (Coleoptera) species. Also well represented were two-winged flies (Diptera), caddis-flies (Trichoptera), aquatic worms (Oligochaeta). At upland sites, a greater diversity of caddis-flies, dragonflies (Odonata) and mayflies (Ephemeroptera) was considered indicative of less disturbed and/or ‘healthy’ ecosystems.



15

Endemic, relictual5 species such as the tiny freshwater snail Glacidorbis occidentalis, gripopterygid stoneflies (Plecoptera) and synthemistid dragonflies were also recorded from many sites in the Samson Brook catchment. These species are more typically associated with pristine seasonal creeks and their presence at sites low in the catchment (albeit in very low numbers) may represent a greater tolerance to disturbance than previously suspected. Overall, the surveyed macroinvertebrate fauna was found to be characterised by regional endemics with relatively high densities and moderate biodiversity in the more natural channels. Given the degraded riparian habitat conditions at lowland sites in the Samson Brook catchment, biodiversity was higher than expected. Multivariate analyses indicated water quality parameters such as water depth, temperature, dissolved oxygen and turbidity to be likely determinants macroinvertebrate community structure within the sub-catchments. Streamtec (1998) assessed biodiversity of aquatic macroinvertebrates in the Harvey River to confer ecological ‘significance’ on that system on the assumption that high biodiversity was indicative of good ecological condition. Streamtec (1998) reported high biodiversity in the forested headwater streams (~70 taxa), moderately-low values in the lowland rivers (~20 taxa) and extremely low values in drains and channelised regions of the Harvey River (<15 taxa). Streamtec (1998) further noted that forested upland streams in the Harvey system were characterised by Gondwandic fauna with a dominance of the ‘shredder’ feeding groups. In contrast, the lowland rivers were characterised by cosmopolitan ‘weed’ species with a dominance of ‘collectors’. Three distinct ecological groupings were identified based on macroinvertebrate community structure; the upland forested sites, lowland vegetated sites and drains/channels. These observations support published literature on aquatic fauna of northern jarrah forest streams and coastal plain rivers (Bunn 1985, 1986, 1988; Storey et al. 1990, 1991, Storey & Edward 1989; Streamtec 1998) suggesting that there are fundamental differences between upland fauna (with lineages to ancient Gondwanic species) and more cosmopolitan lowland river fauna. Upland fauna, when associated with forested permanent streams is considered to have higher conservation value compared with that of lowland reaches. Tadpoles

Monitoring by Alcoa’s Frog Watch programme and surveys conducted by Creagh et al. (2004a,b) and GHD (2003) indicate tadpoles likely to be present in the brooks include the slender tree frog (Litoria adelaidensis), Glauert’s froglet (Crinia glauerti), the quaking frog (C. Georgiana), the brown froglet (C. insignifer) the western froglet (C. pseudinsignifera). The western froglet occurs mainly on the Scarp and east of the Darling Range and is replaced by the closely related brown froglet Crinia insignifera on the Swan Coastal Plain. The two hybridise where their ranges adjoin. Preferred habitats of all species range from permanent stream pools and farm dams to ephemeral swamps, inundated road verges and the base of granite outcrops where run-off water collects. Breeding occurs from winter to early summer. Slender tree frogs generally prefer water bodies with dense fringing vegetation. Though all species are currently widespread and abundant throughout the south-west, they are susceptible to fungal infections that have caused high mortality in some south-west frog populations. 5 Relictual or relict fauna: species that have survived relatively unchanged since the southern super-continent of Gondwana existed approximately 144 to 195 mya and included what is now Australia, Africa, Antarctica, South America, India, New Zealand and Madagascar. Relict fauna and relict habitats and microhabitats that support them are considered important and unique elements of the jarrah forest bioregion; i.e. they have significant conservation and National Estate value.



16

Waterbirds

Historically, the foothills probably did not support many species or high abundance of waterbirds because of the small size and heavily vegetated nature of creek lines. However in winter months, the interconnected wetlands on the coastal plain likely supported large numbers of waterbirds such as Pacific black duck, grey teal, blue-billed duck, maned duck, musk duck, darter, white-faced heron, egrets, cormorants, grebes etc. WRM (2003) conducted opportunistic surveys of waterbirds usage in the Waroona and Drakesbrook Main drains in April 2003 and GHD surveyed Iluka’s mining lease in October 2003. A more complete investigation was undertaken by Storey et al. (1993) of 250 ‘wetlands’ (including 19 drains) on the Swan Coastal Plain, detailing results of waterbird surveys conducted every three months over two years on various drainage channels in the Pinjarra to Bunbury region. Largest numbers of waterbirds present in the Waroona area were recorded from Waroona Main Drain (Table 3), in particular between Brockman Road North and Somers Road, and between Coronation Road and Dorsett Road (Storey et al. 1993). Table 3. Species of waterbird recorded from drains adjacent to Waroona Main Drain (Storey et al. 1993 & WRM 2003) and from within Iluka’s mining lease (GHD 2003).

Species

Har

vey

R. a

t C

lifto

n R

d B

ridge

Cor

onat

ion

Rd

Dra

in –

wes

t

War

oona

Mai

n D

rain

Cor

onat

ion

Rd

Brid

ge

May

field

Dra

in

Willi

amso

n R

d D

rain

Iluka

min

ing

leas

e, W

aroo

na

Australian Shelduck (Tadorna tadornoides) Australian White Ibis (Threskiornis aethiopica) Great Egret (Egretta alba) Little Grassbird (Megalurus gramineus) Little Pied Cormorant (Phalacrocorax melanoleucos) Maned Duck (Chenonetta jubata) Pacific Black Duck (Anas superciliosa) Grey Teal Anas gracilis Chenonetta jubata Australian Wood Duck Tachybaptus nocaehollandiae Australasian Grebe White Faced Heron (Ardea novaehollandiae) Yellow-billed Spoonbill (Platalea flavipes) Threskiornis molucca Australian White Ibis (Sacred) Threskiornis spinicollis Straw-necked Ibis

All species recorded are common, ubiquitous and frequently encountered in wetlands on the Swan Coastal Plain. Storey et al. (1993) found the drains in the region supported very little breeding activity and abundances also were low. The main value of drains for waterbirds was considered to be as summer drought refuge, providing permanent water. However, the lack of habitat structure would make the drains unattractive to many species.



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3. BASELINE SURVEYS OF AQUATIC ECOSYSTEMS

3.1 Methods In the current study, a total of 11 sites were selected for surveys of aquatic macroinvertebrates and fish. The choice of study sites was partly determined by ease of access through private landholdings. Eight sites were surveyed in Ferraro Brook, two in Wealand Brook, and one in Nanga Brook (Figure 1). Surveys were conducted on the 19th - 20th October 2004. A range of physico-chemical parameters were measured in conjunction with fauna surveys, together with qualitative assessments of riparian vegetation condition. The sampling protocol for the current survey was designed to form the basis of a longer-term biological-monitoring (biomonitoring) programme using an upstream (control) / downstream (potential impact) design. Surveys conducted prior to mining activities would also provide ‘control’ data for the downstream sites. Sampling for aquatic macroinvertebrates and fish was conducted over two days in mid October (spring) 2004. 3.1.1 Physico-chemical Parameters

Measurements of water quality were made in conjunction with the fauna sampling. Measurements of temperature, dissolved oxygen, and pH were made in situ between the hours of 0800 and 1800 using portable WTW field meters. Undisturbed water samples were taken for laboratory analyses of turbidity, electrical conductivity (Econd.), total nitrogen (TN) and total phosphorus (TP). Laboratory analyses were conducted by the Natural Resources Chemistry Laboratory, Chemistry Centre, WA (a NATA accredited laboratory). Water quality was assessed against the water quality guidelines for the protection of aquatic ecosystems (ANZECC/ARMCANZ 2000). The ANZECC guidelines specify biological, sediment and water quality guidelines for protecting the range of aquatic ecosystems, from freshwater to marine (ANZECC/ARMCANZ 2000). The primary objective of the guidelines is to “maintain and enhance the ‘ecological integrity’ of freshwater and marine ecosystems, including biological diversity, relative abundance, and ecological processes” (ANZECC/ARMCANZ 2000). Stream depth and wetted-width were measured using a graduated pole. Dominant habitat substrates were visually appraised (by surface area) for mineral or other (e.g. vegetation, organic detritus) material. Extent of bank erosion and channel down-cutting was qualitatively assessed. Sedimentation, as pool aggradation, was assessed as the relative amount of fine inorganic material covering the typical bed substrate. Mean sediment depth was calculated from six measurements made at random at each site. A graduated pole, pushed through the sediment to the bed substrate (i.e. to the point of first resistance or ‘first refusal’) was used to approximate depths. Descriptions of overall stream condition were based on categories outlined in WRC (1999). 3.1.2 Macroinvertebrates

Qualitative samples of aquatic macroinvertebrates were collected at all sites using a standard FBA (Freshwater Biological Association) pondnet (250µm mesh size). At each site, a single channel/macrophyte habitat sample was collected over a total distance of 10 m from waters <1 m deep. Samples were immediately preserved in 70% ethanol. In the laboratory, samples were washed and organic sediments, including macroinvertebrates, were separated from the inorganic material by water elutriation. The organic sediments were then washed through 2 mm, 500 µm and 250 µm mesh sieves to partition the sample into ‘larger’



18

and ‘smaller’ fractions. The 500 µm and 250 µm fractions were sorted under a binocular microscope and collected macroinvertebrates stored in 70% ethanol. For each sample, the entire 2 mm and 500 µm fractions were sorted, while 250 µm fractions were sub-sampled by one fifth. Most macroinvertebrates were identified to the lowest taxon possible either by use of keys or by matching specimens to a voucher collection at the School of Animal Biology, The University of Western Australia. An estimate of abundance for each species was made using broad (log10) categories; 1 = 1 individual, 2 = 2 - 10 individuals, 3 = 11 - 100, 4 = 101 - 1000, 5 = >1000. The existence of rare, restricted or endemic species was determined by cross-referencing taxa lists for each site/habitat with an established database (UWA), the Department of Conservation and Land Management (CALM) Wildlife Conservation (Specially Protected Fauna) Notice 2003 (Government Gazette 11 April 2003, pp. 1158-1167) and the 2003 IUCN Red List of Threatened Species (IUCN 2003). Due to the general lack of data on distributions of Australian aquatic macroinvertebrates and taxonomic uncertainties, conclusions on the rarity or otherwise of many macroinvertebrate groups/species cannot be made with certainty. 3.1.3 Fish and Crayfish

Fish and crayfish were sampled by a combination of methods including 250 µm dip nets (in areas of reed beds, bank undercuts and under logs), box traps, electrofisher, or by direct observation. At each site approximately 40 metres of channel was selectively fished using a Smith-Root Model 12-B battery powered backpack electrofisher. The electrofisher was set to 200 volts DC output with a pulse frequency of 70 Hz and each pulse lasting 4 microseconds (mode switches at J4). Electrofishing at each site was typically performed in an upstream direction, shocking in all meso-habitats with the intention of recovering as many species as possible. Shocking was not continuous, but rather the operator would shock, then move to a new habitat before shocking again, and so prevent fish being driven along in front of the electrical field. Box traps were set overnight in the deeper pools at Sites FB2, FB4 and WB3 and cleared each morning. Fish nomenclature follows Allen et al. (2002). All native species were returned live to the water.

Principals of electrofishing: a DC voltage is passed from a negative electrode (cathode) to a positive electrode (anode) whilst the electrodes are emersed in the water. If a fish is caught in the electrical field generated, a process referred to as ‘Galvanotaxis’ occurs. This is the involuntary movement of the fish towards the anode, until it reaches an electrical field strong enough to stun it (‘galvanoarcosis’). The Smith-Root electrofisher uses a pulsed DC current, which is more effective than a flat DC signal because the body of the fish flexes with each pulse, accentuating the involuntary swimming action towards the anode. Once the current is switched-off, or the fish removed from the electrical field, the fish quickly recovers. Some damage to fish may occur if they are caught in a high electrical field close to the anode for an extended period. The operator of the electrofisher carries the anode (in the form of a modified pond net) whilst trailing the cathode (a stainless steel cable approximately 3.5 m long, referred to as a ‘rat tail’). The Smith-Root backpack electrofisher has an effective range of approximately 3 m. Galvanotaxis can be used to ‘pull’ fish and crayfish out from under debris, logs, boulders and bank undercuts.



19

3.1.4 Riparian Habitat Assessment

Brief assessments of local riparian vegetation condition were made on the basis of dominant plant species and relative degree of disturbance such as weed invasion, livestock access and fire etc. The proportion of exposed soils along banks at each site was also estimated. Assessments followed the rapid assessment methodology of Pen and Scott (1995) and WRC (1999). Riparian zones are topographically unique and within the study area they included:

- the land immediately alongside the brooks/drains (including banks and levees), - land that may be seasonally or periodically connected to the brooks via surface runoff (e.g.

gullies and dips) and - wetlands/swamps on brook floodplains which may interconnect with the brooks in times

of flood. 3.1.5 Statistical Analyses - PATN

To identify spatial differences in physico-chemistry and macroinvertebrate community structure, data were classified and ordinated using the CSIRO Pattern Analysis package, PATN (Belbin, 1995) (see Appendix 2). Macroinvertebrate analyses were conducted on species-level log10 abundance classes. Only taxa that occurred at greater than 10% of sites in each data set were included to avoid ‘low-occurrence’ taxa having a disproportionate effect on the results (Gaugh 1982). The relationship between community structure and physico-chemical conditions of the brooks was analysed using a sub-set of the physico-chemical parameters measured.

3.2. Results and Discussion 3.2.1 Riparian Habitat Assessment

Overall, the brook landscapes were considered extremely degraded (see Table 4) due to past clearing of catchment vegetation for agriculture and unrestricted livestock access. Pasture species typically dominated the riparian understorey vegetation with few other native species present (see Plates 1 – 15 in Appendix 1). Most sites still retained an open remnant overstorey of eucalypts (Eucalyptus rudis and Corymbia calophylla) and/or paperbarks (Melaleuca rhaphiophylla and M. priessiana) in a narrow zone either side of the channel. Site WB1 (Wealand Bk), Site FB1 (Ferraro Bk) and to a lesser extent, Site NB1 (Nanga Brook) on the lower slopes of the Scarp, retained healthy stands of moderately dense remnant native overstorey and sparse to open understorey vegetation with fewer signs of erosion. Of all the brook and drain sites, WB1 and FB1 scored the highest overall environmental rating of ‘poor-moderate’. Channel morphology was relatively good, with reasonable habitat diversity in the form of pool-riffle sequences. However there were few macrophytes other than isolated clumps of sedge and rush at the level of the active channel and some Potamogeton sp. and Lemna sp. in-stream. In areas that weren’t bed-rock controlled, cattle and horse access had resulted in bank erosion and channel widening. Site WB1 on Wealand Brook was infested with cottonbush (Gomphocarpus fruticosus) (Plate 1 Appendix 1), a declared weed which property owners are endeavouring to keep under control (N. Johns pers. comm.). Arum lily (Zantedeschina aethiopica) was also present in mid reaches of Ferraro Brook (e.g. Site FB2) and Nanga Brook (e.g. Site NB1). Mid and lower reaches of Ferraro Brook between the western boundary of the mine lease and South Western Highway (Loc 214 & Lots 4 & 5 in Figure 2) had the lowest assessment code D3 (eroding/freely eroding drain) and an environmental rating of ‘very poor’; e.g. Site FB3. Both natural watercourse and drain sections supported very little or no floodway or verge vegetation and there was unrestricted livestock (dairy cows) access. The narrow channel was extensively



20

down-cut along most of its length, in many places by up to four meters (Plate 9 Appendix 1 & cover photo). There was significant bank under-cutting and slumping. Bed substrates were predominantly gravels and clayey sands overlain with fine organic silts. In 2003, WRC constructed artificial waterfalls along the deepest reaches. The Upper Mayfield Drain west of South Western Highway (e.g. sites UMD 1 & 2) scored an environmental rating of ‘poor’, reflecting the current degraded state of the floodway and verge vegetation, general lack of stream cover, poor bank stability and low habitat diversity (Plates 11 & 12 Appendix 1). Though less down-cut than lower reaches of Ferraro Brook, active bank erosion was evident, particularly channel widening. Bed substrates west of the Highway were typically dominated by clayey sand and silts and in many places the channel bed had eroded down to the underlying coffee rock (Plate 12 Appendix 1). Local landcare groups6 had already begun streamlining and most reaches west of the Highway were fenced to prevent stock access. Native trees and shrubs had recently been planted adjacent to drain banks between the Highway and Somers Road. Local landowners pointed out a number of small permanent pools that occur intermittently along Wealand Brook (i.e. at sites WB2 & WB4), Ferraro Brook (i.e. upstream of site FB3) and Upper Mayfield Drain (i.e. between sites UMD1 & UMD2). Though not confirmed, it is likely that the pool at site FB2 is also permanent. These pools are likely to form important refugia for surface-water dependent macrophytes (e.g. Lemna sp. & Potomageton sp.) and other organisms during the drying phase. Pools at WB2 and FB2 were fringed with a healthy overstorey of Melaleuca rhaphiophylla, but there was little native understorey vegetation. M. rhaphiophylla is common in low-lying winter-wet depressions throughout the south-west. It could not known be ascertained if these pools are a natural occurrence or the result of rising water tables subsequent to land clearing. It is likely, however that the area would have historically contained some permanent water bodies. Though not surveyed in the current study, there were a number of isolated swamps and winter-wet depressions on the ‘floodplain’ of Upper Mayfield Drain that supported dense, healthy overstoreys of M. rhaphiophylla. However, vegetation linkages between these remnant wetlands were, at best, minimal. Surveys conducted by GHD (2003) also found this vicinity supported the healthiest terrestrial vegetation cover and a rich floral and faunal biodiversity. The permanent wetlands pools and are surface expressions of the underlying surficial and superficial groundwaters. Many of the seasonal ‘floodplain’ sumplands and damplands are also likely maintained in part by high water tables. The nature of hydraulic connectivity with deeper aquifers is not well understood. Nor are the contributions of groundwater flow to baseflows in the brooks/drains known. Overland/sheet flows will also play a significant (though unquantified) role in winter flow regimes. Without this knowledge it is not possible to predict with certainty the impact of mine de-watering (and possible dam construction) in the upper catchment on downstream surface flows and wetlands. However, it is expected that existing high overland flows and higher than historic groundwater tables and groundwater recharge would adequately compensate any reduction in winter flows. In seasonal and ephemeral systems, such as the Waroona study area, deep-rooted tree and perennial vegetation are typically phreatophytic (groundwater dependent), but may also use soil moisture and brook/drain flood waters during the wet season (Groom et al. 2000, 2001).

6 Crossing the Boundaries – Southern Peel Partnership Landcare Project.



21 Table 4. Description of aquatic fauna sites surveyed in October 2004 together with results of riparian habitat assessments. *Note: Site FB5 was dry when cross-section surveys were carried out in November 2004 for later EWR modelling.

Site & GPS Co-ordinates Ave. Wetted Width

Ave. Wetted Depth

Max. Wetted Depth

Bed Substrates Site Description Assessment Code

Environmental Rating

Wealand Brook

Site WB1 Most upstream site on Wealand Bk; base of Scarp. Private property – landowner N. & D. Johns (Lot 3). 50 400432E 63 68914N

2.0 m 0.05 m 0.2 m Gravels & clayey sand; overlain with organic silts 4-5 cm deep.

Sparse to open overstorey of Eucalyptus spp. Understorey predominantly pasture species; stock access/trampling (horses); channel heavily encroached by pasture grasses; Lemna spp. providing almost 100% channel cover in parts; waterlogged soils.

C1 – B3 Poor - Moderate

Site WB2 Start of channelised section of Wealand Bk. Private property – landowner F.P. Fiore (Loc. 547). 50 399671E 63 69203N

0.5 m 0.08 0.1 m Sand overlain with silts.; sedimented to 50 cm (silt, anoxic mud).

Permanent pool; cattle access point. Overstorey of sparse paperbark Melaleuca sp. (moderately dense stand of paperbarks upstream), no native understorey other than clumps of sedge at edge of channel & encroaching pasture grasses. Point undercutting; down cut by ~1.5 m on south bank and ~0.5 m on north bank; tree roots scoured. Heavy trampling by cattle; 20-30% bare soils; 30-50% cover of algae and pond weed in-stream.

D1 – C3 Poor

Site WB3 Perched wetland on north side of Wealand Bk between SW Hwy & Railway. Reserve 31437. TEC community type 8. EPP wetland (sumpland). 50 397338E 63 67183N

13.5 m 0.30 0.45 Silt/mud/soft sediment; anoxic layer over clay; claypan.

Ephemeral wetland; dense emergent & submerged macrophytes, sedges & Watsonia spp.; lot of algae. Fringing open to mod-dense paperbarks to north-east. Bounded by drain levee to south and rail embankment to west. Standing water in wetland elevated above level in drain. Minor disturbance – tracks, rubbish dumping.

A3 Good

Site WB4 Wealand Bk, immediately west of Railway. Private property – landowner Mitchell Nominees Aust. Pty Ltd (Loc. 365). 50 397194E 63 69122N

2.5 0.35 0.50 Clay and sand overlain with fine organic silts; anoxic muds; exposed coffe-rock; bedrock/ gravels near road culvert.

Mainly open pasture with a few scattered paperbarks. Trapezoidal channel with series of small pools; banks downcut to 2 m with major undercutting; 40-50% microphyte (Potomageton) & algal cover, some Typha stands; very turbid waters; Oxalis & other pasture weed choked channel; slow flow (max. < 5 cm/s). Channel fenced.

D2 Very Poor

Ferraro Brook

Site FB1 Most upstream site on Ferraro Brook; on Scarp. Mine lease, above pit areas (Loc. 265). 50 400879E 63 67483N

0.40 0.10 0.50 Granite/bedrock controlled; v. fine silt layer, 1% boulders, sand, gravel, rock.

Uphill; mod-steep slope; series of riffles & pools; narrow channel; open-mod dense Melaleuca & scattered euc's; channel incised & downcut to 1.5 m in places (ave. 0.5 m downcut); banks undercut and ± vertical; pasture spp. dominate understorey; max width 1.5 - 2 m (pools & meander bends); 10% filamentous algae; water clear.

B3 Poor - Moderate

Site FB2 Ferraro Bk, base of Scarp. Mine area between North & south pits & above proposed dam site & d/s of gauging station (Loc. 1235). 50 400477E 63 67783N

2.5 0.25 0.50 Gravels & sand. Mod-dense paperbark woodland with scattered E. rudis over pasture grasses. Brook banks down-cut in places to 2+m; 15% filamentous algae, 5% bare soil. Cattle access.

C3 Poor



22

Site FB3 Ferraro Bk on coastal plain east of SW Hwy. Private property – landowner PW & LE Ward/Aintree Pty Ltd (Lot 4). 50 399067E 63 68129N

2.0 0.15 0.5 Granite/bedrock & gravels; fine silt layer in pools.

Dairy farm; much of brook channelised & deeply (4 m) downcut; extensive bank slumping & undercutting; scouring. WRC constructed waterfalls in 2003. Overstorey of open E. rudis & paperbarks; understorey all pasture grasses. No macrophytes.

D3 Very Poor

Site FB4 Ferraro Bk, immediately west of Railway. Private property – landowner Mitchell Nominees Aust. Pty Ltd (Loc. 364). 50 397194E 63 68799N

2.5 0.08 0.15 Sands & exposed coffee-rock

Drain. Open paperbarks over grass spp/pasture; replanted native veg. along northern bank over an area 4-5 m wide (trees <50cm tall). Channel overgrown - grass encroachment 20-30%. Banks down-cut 1.5 m on northern bank and 1 m on southern bank; major undercutting. Clear water.

D2 Very Poor

*Site FB5 At confluence of Ferraro and Wealand brooks. Private properties - landowners N. Bruce (Loc. 411) & Mitchell Nominees Aust. Pty Ltd (Loc. 365) 50 396114E 63 68869N

-- -- -- Clayey sands & exposed coffee-rock; sedimented to 10 cm in places.

Drains. Scattered paperbarks over grass/pasture. A few clumps of sedge at waters edge; ~5% Potomageton sp. & Lemna sp. Trapezoidal channel with series of small, shallow pools. Channel overgrown - grass encroachment 20-30%. Banks down-cut to 1.5 m; major undercutting; some bank slumping. Clear water. Channel fenced. Eleocharis sp. (??E. keigheryi) in Wealand Brook ~60 m u/s of confluence & near fence across channel (x-sect. 15).

D2 Very Poor

Upper Mayfield Drain

Site UMD1 Upper Mayfield Drain, Whettem Rd, ~1km d/s from confluence of Ferraro & Wealand brooks. Private property – landowner CH & RA Archibald (Loc. 408). 50 395344E 63 68917N

3.0 0.35 0.90 Clayey sands and silt over coffee-rock; sedimented to 10 cm in places.

Drain on dairy farm. No remnant vegetation; cleared, open pasture; replanted native veg. (1-2m high) adjacent to banks. Trapezoidal channel; banks down-cut 1.5 m & very steep; major undercutting; channel widening; 5% bare soils. Waters a little turbid; quite fast flowing. Some small shallow pools; groundwater springs downstream.

D2 Very Poor

Site UMD2 Upper mayfield Drain; most downstream site in study area; ~5Km west of SW Hwy, off Somers Rd. Private Property – landowners CH & RA Archibald (Loc. 863). 50 392406E 63 69165N

3.0 0.35 0.75 As for Site UMD1 As for Site UMD1 D2 Very Poor

Nanga Brook

Site NB1 Hill Street weir, main channel of Nanga Bk; within mine lease, adjacent to southern boundary. 50 399953E 63 66849N

2.5 0.35 0.80 Sand/gravel with some overlying organic silts in pools; sedimented to 25 cm deep on inside of meanders.

Adjacent to old piggery; mod-dense overstorey of Melaleuca spp. and open Eucalyptus rudis over pasture grasses; down cut 2+m with major undercutting; tree roots scoured; 30% bare sand; no instream macrophytes; small gravel run by bed; upstream of weir; series of riffles and pools upstream of weir.

C1 Poor



23

Overstorey species, such as M. rhaphiophylla and E. rudis, tend to be more tolerant of water regime extremes both seasonal flooding and moderately deep groundwater drawdown and are often are the only remnant vegetation of former swamps/damplands (Groom et al. 2001). The WRC recently set maximum groundwater drawdown levels for the Gnangara and Jandakot mounds in order to protect remnant vegetation, including M. rhaphiophylla and E. rudis (WRC 2001). A maximum drawdown of 1.5 m in areas of phreatophytic vegetation was set, based on past observations that drawdown of up to 2 m resulted in tree deaths. The maximum was based on the average groundwater level recorded prior to the 1970’s (refer Section 2.1, above). Where this data was not available, 0.5 m was added to the average minimum groundwater level recorded since the 1980’s and then 1.5 m subtracted from this figure to obtain the maximum drawdown level. Declared Rare Flora

A small clump of the emergent macrophyte Eleocharis sp. was opportunistically recorded from Wealand Brook, approximately 1.2 km west of South Western Highway, during cross-sectional surveys for EWR assessments. As the species could not be positively identified as Eleocharis keigheryi, a DRF known to occur in creeks and claypans within the study area (GHD 2003), further investigation by a CALM botanist may be warranted. Plants were located in the drain channel at Site FB5, approximately 60 m upstream from the confluence with Ferraro Brook on property Loc. 411 close to fenceline bordering property Loc. 364 (GPS 32˚48’46”S, 115˚53’25”E; 50 396148E, 63 68931N; WGS84). It is not expected however, that mine activities would impact the population, unless there was a substantial reduction in brook/drain flows coupled with significant groundwater drawdown and lowered soil moisture. Plants were considered at greater risk from stock grazing and drain maintenance dredging. Threatened Ecological Communities (TECs) and EPA Registered Wetlands (EPPs)

Site WB3 (Plate 4 in Appendix 1) was located within Reserve 31437, listed as supporting TEC community type 8 (“herb rich shrublands in clay pans”) and also listed as containing EPP wetlands. The site was within a perched seasonal wetland adjacent to the channelised section of Wealand Brook between South Western Highway and the railway. The wetland was dominated by sedgelands with fringing, open to moderately dense Melaleuca spp. to the north-east and dense stands of Watsonia spp. along the railway embankment to the west. The marri-dominated TEC community type 3a lay to the north, bordered by a stand of pines. Standing water contained within the wetland at the time of sampling was considered the result of clay subsoils and ponding of surface waters behind the rail embankment to the west and the drain levee banks (1.5 – 2 m high) to the south. The surface elevation of this perched wetland was well above the level in the drains (e.g. Plate 5 Appendix 1). Between Wealand and Ferraro drains lay sumpland, identified (but not formally assessed) by Hill et al. (1996) as Wetland #91, Map Sheet 2032 II NE (Hamel NE). Beyond the drains, on dryer clay soils to the south, lay TEC community type 10a. The wetland site, together with the rest of the reserve south to Mayfield Road, was given an environmental rating of ‘good’ with vegetation in healthy condition, but with some disturbance from track and weed encroachments. The area is also used for illegal dumping of refuse. The condition of the other EPP wetland located within the area was not assessed during the current study. It lay in cleared agricultural land, on private property, approximately 300 m north of the confluence of Ferraro and Wealand brooks. The wetland was mapped as sumpland by Hill et al. (1996) and identified as Wetland #37, Map Sheet 2032 II NE (Hamel NE).



24

It is not expected that proposed mining activities would impact TECs or EPPs unless there was a substantial reduction in brook/drain flows coupled with significant groundwater drawdown and lowered soil moisture. 3.2.2 Physico-chemistry

Average water depths recorded in mid October 2004, ranged from 0.05 – 0.35 m, with maximum depths of 0.45 – 0.9 m (refer Table 4). By late November 2003, flows had ceased and channels were beginning to dry. Flow in the brooks and drains is tightly coupled to rainfall; falls of about 50 mm in the upper sub-catchments typically result in flooding of drainage channels west of South Western Highway (G. Chaffey pers. comm.). Even the heavily down-cut sections of Ferraro Brook between the mine boundary and the Highway (e.g. Site FB3) flood most years (P.W Ward pers. comm.) due to the substantial runoff from surrounding paddocks. Though riparian conditions were degraded, all brooks were characterised by moderate biological water quality with circum-neutral pH (6.71 – 7.97), moderate to high dissolved oxygen content (65 – 143.8%), generally low turbidity (<10 NTU) and moderate nutrient levels (Table 5). All surface waters were fresh7 and well within recommended guideline concentrations for protection of aquatic ecosystems (ANZECC/ARMCANZ 2000) (Figure 5). Salinity in the perched wetland at Site WB3 was particularly low (224 µS/cm) likely reflecting the influence of ponded rainfall runoff. Overall, water quality parameters were within ranges previously recorded for surface waters in the region (see Section 2.1.3 above) and most comparable to those in the adjacent lower Samson Brook catchment, though the current study recorded marginally higher salinities. Nutrient levels (TN & TP) at upland sites on Wealand and Ferraro brooks (WB2 & FB2) were relatively high in comparison with the upper limit of recommended guideline concentrations for protection of aquatic ecosystems (ANZECC/ARMCANZ 2000) (Table 6). TN concentrations at WB2 were twice the recommended limit for upland ecosystems. At site WB4, TN levels were approaching the recommended maximum for lowland sites, while TP levels were slightly greater than the recommended maximum (Figure 5). This site lay immediately downstream from the perched wetland site WB3 and TEC type 8, however nutrient status of the wetland was not assessed during the current study. The guideline ecological thresholds reflect concentrations at which problem algal blooms are likely to manifest, with the potential for blooms increasing under conditions of lower flows, high water temperatures and full sunlight. Nutrient levels at all sites were all well below trigger values to maintain irrigation systems (ANZECC/ARMCANZ, 2000). Trophic status was assigned using the categories of Wetzel (1975), OECD (1982) and Salas & Martino (1991). All brook and drain sites were considered meso-eutrophic (Tables 7 & 8). The high nutrient levels are characteristic of agricultural lands throughout south-western Australia and given the condition of the catchments, overall levels were unexpectedly low. Spot measurements of nutrient levels in the water column are not adequate to fully assess the degree of eutrophication in the brooks. Data on both total loads and the potential for release from sediments is required. Spot sampling is usually conducted during medium to low flows (as in the current study), whereas most of the annual load to a river is mobilised during storm events when surface runoff from surrounding lands is at a maximum. The amount of catchment material available is typically much greater just prior to the start of the rainfall season and early wet-season runoff will result in high relative loads. Stage height samplers would be required to sample nutrients during different flow regimes. 7 Fresh defined as <2,700 µS/cm and brackish as 2,700 – 9,000 µS/cm by the Department of Agriculture, Government of Western Australia (2002).



25

Table 5. Physico-chemistry of surface waters in Wealand, Ferraro and Nanga brooks and Upper Mayfield

Drain, October 2004.

Site Time TEMP ECOND. TDS* DO DO pH TURB N Total P Total h °C µS/cm mg/L %sat mg/l pH units NTU mg/L mg/L

WB1 1000 21.1 -- -- 65.0 6.3 6.78 -- -- -- WB2 1230 27.4 468 281 94.5 7.4 7.0 9.0 0.66 0.04 WB3 1320 26.8 -- 94.0 7.4 7.15 -- -- -- WB4 930 19.1 596 358 85.3 7.5 6.71 5.2 1.1 0.08 FB1 840 17.4 -- -- 102.0 9.0 7.21 -- -- -- FB2 1715 20.9 379 227 83.6 7.7 6.89 6.2 0.33 0.03 FB3 1440 19.1 -- -- 96.0 8.9 7.16 -- -- -- FB4 1130 24.7 400 240 143.8 11.9 7.97 7.5 0.4 0.03 FB5 -- -- -- -- -- -- -- -- -- -- UMD1 1120 21.9 -- -- 113.0 9.8 7.19 -- -- -- UMD2 1610 23.7 787 472 118.0 9.8 7.1 2.8 0.46 0.03 NB1 1500 21.6 433 260 90.3 8.2 7.01 4.0 0.38 0.03

*TDS (mg/L) calculated from ECond. (µS/cm) using a correction factor of 0.6. Site FB5 = cross-sectional survey site; not sampled for water quality.

Table 6. ANZECC/ARMCANZ (2000) recommended maxima physico-chemical levels for Western Australian freshwater ecosystems.

Ecosystem Type TP FRP TN NOx NH4+ DO % saturation2 pH

mg/L mg/L mg/L mg/L mg/L Lower Upper Lower Upper

Upland River1 0.02 0.01 0.45 0.2 0.06 90 na 6.5 8.0

Lowland River1 0.065 0.004 1.2 0.15 0.08 80 120 6.5 8.0

Lakes & Reservoirs 0.01 0.005 0.35 0.01 0.01 90 No data 6.5 8.0

Wetlands 0.06 0.03 1.5 0.1 0.04 90 120 7.0 8.5 Na = not applicable 1 All values during base river flow not storm events 2 Derived from daytime measurements; may vary diurnally and with depth.

0

100

200

300

400

500

600

700

800

WB1

WB2

WB3

WB4 FB

1

FB2

FB3

FB4

UM

D1

UM

D2

NB1

µS/c

m

EC (µS/cm) ANZECC EC

0

0.2

0.4

0.6

0.8

1

1.2

1.4

WB1

WB2

WB3

WB4 FB

1

FB2

FB3

FB4

UM

D1

UM

D2

NB1

mg/

L

N total (mg/L) P total (mg/L) ANZECC TN ANZECC TP

Figure 5. Comparison of salinity (ECond. µS/cm) and nutrient (TN & TP, mg/L) levels with ANZECC/ARMCANZ (2000) recommended maxima for the protection of aquatic ecosystems. NB:

recommended TN & TP maxima shown are for lowland sites only.



26

Table 7. Mean annual total phosphorus levels (mg/L) for each trophic category for tropical waters, under the OECD (1982) and CEPIS (Salas & Martino, 1991) classifications (means and range over 2 standard

deviations).

Source Category Oligotrophic Mesotrophic Eutrophic

OECD 0.008 0.0267 0.084 (+ 2 SD) (0.003 – 0.022) (0.08 – 0.091) (0.017 – 0.424) CEPIS 0.021 0.0396 0.1187

(+ 2 SD) (0.010 – 0.045) (0.021 – 0.074) (0.028 – 0.508)

Table 8. Categorisation of trophic status of temperate waters, after Wetzel (1975).

CATEGORY TOTAL P (mg/L)

TOTAL N (mg/L)

INORGANIC N (mg/L)

Ultra-oligotrophic < 0.005 0 - 0.250 0 - 0.200 Oligo-mesotrophic 0.005 - 0.010 0.250 - 0.600 0.200 - 0.400 Meso-eutrophic 0.010 - 0.030 0.300 - 1.10 0.300 - 0.650 Eutrophic 0.030 - 0.100 0.500 - 15 0.500 - 1.500 Hyper-eutrophic > 0.100 > 15 > 1.5

Analyses of Patterns in physico-chemistry - PATN

Spatial patterns in physico-chemistry were investigated using classification and ordination techniques (PATN). UPGMA (Unweighted Pairgroup Arithmetic Averaging) classification of sites on standardised physico-chemical parameters detected five main groupings (Figure 6). The non-parametric analysis of similarities (ANOSIM) package within PATN indicated significant (p<0.01) differences between all five groups. Upland Wealand Brook sites (WB1 & WB2) were distinct from all others, as was the perched wetland (Site WB3) between South Western Highway and the railway. Ferraro brook sites tended to group together, with the exception of Site FB4 on the channelised section of the brook immediately west of the Highway. The Nanga Brook site (NB1) unexpectedly grouped with the more disturbed Upper Mayfield Drain sites (UMD1 & UMD2). Ordination similarly showed a clear separation of these sites in ordination space (Figure 7). UMD1 _ UMD2 |_____________ Group 5 NB1 _____________|_________________________ WB4 _______________________________ | FB3 _______ | | Group 4 FB1 ______|_____________ | | FB2 ___________________|__________|_______|______________ WB3 ____________________________________________________|________ Group 3 FB4 _____________________________________ | Group 2 WB1 ____________________________ | | Group 1 WB2 ___________________________|________|_______________________| | | | | | | 0.0253 0.0730 0.1208 0.1685 0.2163 0.2640

Figure 6. UPGMA classification dendogram of the 11 sites using standardised physico-chemical parameters.



27

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

WB1

UM D1

UM D2

FB4

FB3

FB2

FB1 WB4

WB3WB2

NB1

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

Econd.

Turbidity

Ave. Depth

Ave. Width

M ax. Depth

Figure 7. MDS ordination of the 11 Waroona sites. Ordination used standardised physico-chemical variables. Sites are coloured by a posteri groupings from UPGMA classification and figure on left indicates PCC-derived gradients of standardised physico-chemical parameters through ordination space (optimum solution for the ordination was in 3 dimensions with a stress of 0.0769). A number of physico-chemical gradients were influencing the separation of these groups; salinity (Econd.), turbidity, water depth and average channel width. For example, shallow upland Wealand Brook sites had higher turbidity than all other sites, while Upper Mayfield Drain sites and the Nanga Brook site tended to have deeper waters (Figure 7). The Kruskal-Wallis non-parametric one-way analysis of variance test was applied within the PATN package to test for significant differences in physico-chemical variables amongst the five groups identified by the UPGMA classification. Analysis detected significant (p<0.05) between-group differences only for maximum water depth (Appendix 3a). 3.2.3 Macroinvertebrates

Taxonomy and Species Diversity

A systematic list of macroinvertebrate taxa recorded is given in Table 9. A total of 128 taxa were identified and spatial variation in species richness was low (Figure 8); there was no significant difference in taxa richness between the brooks/drains (ANOVA, p>0.05). Between sites, maximum species richness was recorded from the most downstream Upper Mayfield Drain site (UMD2) and from Site WB4 on the channelised section of Wealand Brook (Table 9). This was unexpected given the degraded habitat conditions at these sites and may indicate the presence of more permanent waters. Minimum species richness was recorded from the Nanga Brook site and from the perched wetland site (WB3). Reduced diversity at these sites may have been due to the proximity of Hill Weir and the old piggery on Nanga Brook and to the ephemeral nature of the perched wetland. Aquatic worms (Oligochaeta), water mites (hydracarina), seed shrimps (Ostracoda), copepods, amphipods, black fly and midge larvae (Simulidae & Chrironimidae), water boatmen (Corixidae), diving beetles (Dytiscidae) and water scavenger beetles (Hydrophilidae) were all abundant and common to 90% of sites. ‘Low-occurrence’ taxa (i.e. taxa recorded from <10% of sites) accounted for less than a quarter of all species and included hydroptilid caddis-flies, march/horse fly larva (Tabanidae), and whirly-gig beetles (Macrogyrus sp.).



28

The macroinvertebrate fauna was dominated by Insecta (78%), in particular detritivores but with a high diversity of predatory beetle species. Numerically dominant groups included the two-winged flies (Diptera) with at least 43 species from 13 families and beetles (Coleoptera) with 27 species from six families, followed by Crustacea with at least 11 species from nine families and dragonflies (Odonata) with nine species from four families.

Macroinvertebrate 'Species' Richness

0

10

20

30

40

50

60

70

80

Wealand Bk Ferraro Bk UpperMayfield Drain

Nanga Bk

Num

ber o

f 'sp

ecie

s'

Figure 8. Mean (±SE) macroinvertebrate ‘species’ richness at sites surveyed in October 2003.

Consistent with other surveys of the region (see Storey et al. 1990, Streamtec 1997, 1998 2002, WRM 2003, Creagh et al. 2004a,b), sites appeared to support a low to moderate diversity of aquatic macroinvertebrates, dominated by cosmopolitan species with no species considered rare or restricted in distribution. The taxa recorded were those expected from disturbed watercourses on the coastal plain. The presence or absence of individual species will be governed by a range of interacting factors such as water permanence, lack of in-stream and riparian habitat and water quality that have both direct and indirect influences.

Taxa normally associated with undisturbed, forested upland streams were few or absent. Three introduced snail species were recorded during the study; Lymnaea stagnalis, Physa acuta and Psedosuccinea columella. L. stagnalis was only recorded in low numbers from Upper Mayfield Drain (Site UMD 2), however P. acuta and P.columella were common throughout the study area and are known to be a long-established occupants of wetlands and river systems in other parts of the south-west. All three snails are typically found in slow moving freshwater streams, ponds and dams. P. columella is an intermediate host for liver fluke Fasciola hepatica, a parasite that infests the liver and bile ducts of sheep, cattle and horses. Humans can also be infected by ingesting contaminated plant or animal material. At least one chironomid species new to science was collected; Tanypodinae sp. nov. (D.H. Edward, pers. comm., 2004). This species was present in low numbers at sites WB4, UMD1 and UMD2. Conclusions on the conservation status of this species need to be made with caution as there is little published literature on the chironomid species of Western Australia and their taxonomy is poorly understood. Until more comprehensive surveys are undertaken throughout the south-west, the rarity or otherwise of this species and its tolerance to disturbance will remain unknown.



29

Table 9. Preliminary presence/absence list of macroinvertebrate taxa collected in Oct. 2004. Codes: FB1 – FB4 = Ferraro Brook sites 1 – 4.; NB1 = Nanga Brook site 1; WB1 – WB4 = Wealand Brook sites 1 – 4; UMD1 – UMD2 = Upper Mayfield Drain sites 1 – 2. A = adult stage; F = female; imm = immature; L = larva; P = pupa. Log10 abundance categories: 1 = 1individual; 2 = 2-10 individuals; 3 = 11-100; 4 = 101-1,000; 5 = >1,000.

Sites

TAXA WB1 WB2 WB3 WB4 FB1 FB2 FB3 FB4 UMD1 UMD2 NB1

CNIDARIA HYDROZOA Hydra sp. 1 2 2 -- 2 -- -- -- -- 2 --

NEMATODA Nematoda spp. 2 -- 1 2 -- 1 -- -- -- -- 1 PLATYHELMINTHES

TEMNOCEPHALIDEA Temnocephala sp. -- -- -- -- 1 -- -- -- -- -- -- TURBELLARIA Turbellaria spp. 2 3 2 2 -- -- -- -- 2 2 --

ANNELIDA OLIGOCHAETA Oligochaeta spp. 4 4 -- 3 3 3 3 3 3 3 3

HIRUDINEA Glossophonidae Glossophonidae spp. -- -- -- 2 -- -- -- -- -- 1 -- MOLLUSCA Ancylidae Ferrissia petterdi 2 -- 2 3 1 1 -- 2 2 2 -- Lymnaeidae Pseudosuccinea collumella -- 1 -- -- 2 -- -- 1 2 2 -- Lymnaea stagnalis -- -- -- -- -- -- -- -- -- 2 -- Physidae Physa acuta 4 3 -- 3 3 2 2 4 4 5 -- Planorbidae Isidorella sp. -- -- -- 3 -- -- -- -- 2 -- -- ARTHROPODA ARACHNIDA

ARANAE Aranae spp. -- -- -- -- -- -- -- -- -- 2 -- ACARIFORMES

ORIBATIDA Oribatida spp. -- -- -- 3 3 -- -- 3 4 2 -- HYDRACARINA Hydracarina spp. 2 2 2 3 3 3 -- 3 3 3 2

PSEUDOSCORPIONES Pseudoscorpiones spp. -- -- -- -- -- -- -- 1 -- -- -- COLLEMBOLLA Entomobryoidea spp. -- 2 -- 2 2 3 2 3 2 2 -- Poduroidea spp. 2 2 -- 2 3 3 -- 2 3 3 1 Symphypleona spp. 1 -- -- -- -- 2 -- 1 2 -- 1 CRUSTACEA

AMPHIPODA Ceinidae Austrochiltonia subtenuis -- -- -- 2 3 2 2 3 3 -- -- Paramelitidae Paramelitidae spp. 3 4 -- -- -- -- -- -- -- -- -- Perthidae Perthia acutitelson 3 -- -- 2 2 3 2 1 -- 2 3

CLADOCERA Cladocera spp. 2 2 3 3 -- -- -- -- 3 4 2



30

Sites


COPEPODA Cyclopoida spp. 4 4 3 3 -- 3 2 3 3 4 3 DECAPODA Palaemonidae Palaeomonetes australis -- -- -- -- -- -- -- -- -- 3 --

Parastacidae Cherax quinquecarinatus -- -- -- -- -- -- -- -- 1 -- 2 Cherax plebijuis -- -- -- -- -- -- -- 1 -- 1 -- Parastacidae spp. (imm.) -- -- -- -- -- -- -- -- -- 1 --

ISOPODA Phreatocoidea ?Paramphisopus sp. -- -- 4 3 -- -- -- 3 3 -- -- OSTRACODA Ostracoda spp. 3 3 4 5 4 3 4 4 4 3 2

INSECTA DIPTERA Ceratopogonidae Ceratopogoniinae spp. 3 1 2 1 -- -- -- -- 1 2 --

Forcypomiinae spp. 2 1 -- -- 2 -- 1 -- -- -- 2 Ceratopogonidae spp. (P) 3 -- 2 -- -- -- -- -- -- -- 1

Chironomidae Chironomidae spp. (P) 3 3 2 3 3 3 3 3 3 2 2 Chironominae Chironomus aff. alternans 4 4 2 3 2 3 3 3 3 2 3 Cladopelma curtivalva 1 -- -- -- -- -- -- -- -- -- -- Cryptochironomus griseidorsum 2 1 -- 3 -- 2 2 3 2 2 1 Dicrotendipes ?conjunctus -- -- 2 -- -- -- -- -- 2 1 -- Dicrotendipes sp. -- -- -- -- -- -- -- -- -- 1 -- ?Omisus sp. -- -- -- 1 -- -- -- -- -- -- -- Parachironomus sp. -- -- 2 -- -- -- -- -- -- -- -- Paracladopelma sp. -- -- -- -- 2 3 -- -- -- 1 -- Paratanytarsus grimmii 3 3 3 3 1 2 -- -- 3 4 -- Polypedilum nubifer -- -- 2 -- -- -- -- -- 2 1 -- Polypedilum sp. -- -- 2 1 2 3 2 2 -- 1 3 Polypedilum watsoni -- -- -- -- -- 2 -- -- -- -- -- Rheotanytarsus sp. -- -- -- 2 1 2 -- -- -- -- 3 Riethia sp. -- -- -- -- -- 2 -- -- -- -- -- Stempellina sp. -- -- -- -- -- -- -- -- -- -- 2 Tanytarsus sp. 2 2 2 3 3 3 3 3 3 2 3 Orthocladiinae Botryocladius bibulmun -- -- -- 3 -- -- 1 2 -- -- 3 Corynoneura sp. 2 3 3 3 2 1 -- 3 3 3 -- Cricotopus albitarsis -- 2 -- -- -- 1 -- -- 3 3 -- Cricotopus annuliventris 2 3 2 2 4 3 2 2 3 3 3 Orthocladiinae (V46) spp. -- -- -- 1 -- -- -- -- -- -- --



31

Sites


Orthocladiinae (VK3) spp. -- 2 -- -- -- -- -- -- -- -- -- Orthocladiinae (VSC11) spp. -- -- 2 -- -- -- -- -- -- -- -- Parakiefferiella sp. -- -- -- -- 2 1 -- -- -- 1 -- Paralimnophyes ?pullulus 2 2 1 -- 2 2 -- -- -- -- -- Thienemanniella sp. 2 3 -- 3 2 3 4 3 2 4 4 Tanypodinae Apsectrotanypus ?maculosus -- -- 1 -- -- -- -- -- -- -- -- Larsia ?albiceps 2 -- -- -- -- -- -- -- -- -- -- Paramerina ?levidensis 3 3 2 3 3 3 4 3 2 1 3 Procladius paludicola 2 -- -- 3 2 -- -- 3 2 2 -- Procladius villosimanus 1 -- -- -- -- -- -- -- -- -- -- Tanypodinae spp. (sp. nov.) -- -- -- 2 -- -- -- -- 1 2 -- Culicidae Anopheles sp. 3 -- 3 3 1 -- -- 3 4 2 -- Culex sp. -- 2 -- -- -- -- -- -- -- -- -- Culicidae pupa 2 2 -- 2 -- -- -- 2 3 2 -- Dolichopodidae Dolichopodidae spp. -- 1 -- -- -- -- -- 1 -- 1 1 Empididae Empididae spp. -- -- -- -- -- -- -- -- -- -- 2 Ephydridae Ephydridae spp. 3 -- -- 2 -- -- -- 2 -- -- -- Muscidae Muscidae spp. (pupa) -- -- -- -- -- -- -- -- -- 1 -- Psychodidae Psychodidae spp. -- -- -- 1 1 -- 1 -- 2 2 -- Sciozyiomyidae Sciozyiomyidae spp. -- 2 -- -- -- 1 -- -- -- 1 -- Simulidae Austrosimulium sp. -- -- -- -- -- -- -- -- -- -- 3 Austrosimulium pupa -- -- -- -- -- 1 -- 2 -- -- 2 Cnephia tonnoiri tonnoiri -- -- -- -- -- 1 3 -- -- -- 3 C.t. tonnoiri pupa -- -- -- -- -- -- -- -- -- -- 1 Simulium ornatipes 2 3 1 2 2 3 3 3 3 4 3 S. ornatipes pupa -- 2 -- -- -- 1 1 2 2 3 -- Simulidae spp. (imm.) 2 -- -- -- -- -- -- -- -- -- -- Stratiomyidae Stratiomyidae spp. -- -- -- -- -- -- -- -- 2 -- -- Tabanidae Tabanidae spp. -- -- -- -- -- -- -- -- 1 -- -- Tipulidae Tipulidae spp. 1 1 -- 2 -- 2 2 3 -- -- 1 LEPIDOPTERA Lepidoptera spp. -- -- -- 1 -- -- -- -- -- -- 2 Nymphulinae spp. -- -- -- -- -- -- -- -- -- 2 -- ODONATA



32

Sites


ANISOPTERA Anisoptera spp. (imm.) 2 -- -- -- -- -- -- -- -- -- -- Aeshnidae Hemianax papuensis 1 -- 2 -- -- -- -- -- -- -- -- Hemicorduliidae Hemicordulia tau -- -- -- 2 -- -- -- 2 -- 2 -- Libellulidae Diplacodes bipunctata -- -- 2 -- -- -- -- -- -- -- -- Diplacodes haematodes -- -- -- -- -- -- -- -- -- 2 --

Telephlebiidae ?Telephlebia sp. -- -- -- -- -- -- -- -- -- -- 1

ZYGOPTERA Zygoptera spp. (imm.) 1 -- -- -- -- -- -- -- -- -- -- Coenagrionidae Austrolestes analis -- -- 3 1 -- -- -- -- -- -- --

Diphlebiidae ?Diphlebia sp. -- 1 -- -- -- 1 -- -- -- -- -- TRICHOPTERA Hydrobiosidae Cheumatopsyche sp. -- -- -- -- -- -- -- -- -- -- 2 Hydroptilidae Acritoptila/Hellyethira sp. 3 1 2 2 -- -- -- 2 2 2 -- Oxyethira sp. 1 -- -- -- 2 -- 1 -- -- -- -- Leptoceridae Leptoceridae spp. (imm.) -- -- -- -- -- 1 2 -- -- -- -- Notalina spira -- -- -- -- -- -- -- -- 1 2 -- Oecetis sp. 2 -- -- 3 1 1 2 -- 2 3 -- Triplectides australis 2 -- -- -- 1 -- -- 2 3 3 -- EPHEMEROPTERA Baetidae Centroptilum sp. -- -- -- -- 1 3 2 1 -- -- 2 Caenidae Tasmanocoensis tillyardi -- -- -- -- -- 2 -- -- -- -- 3 Leptophlebiidae Leptophlebiidae spp. -- -- -- -- -- 2 -- 2 -- -- 1 Bibulmena kadjina -- -- -- -- -- 2 -- -- -- -- -- Nousia sp. -- -- -- -- 3 3 3 -- -- -- -- HEMIPTERA Corixidae Corixidae spp. (imm.) 3 2 3 3 1 1 1 3 2 2 1 Agraptocorixa eurynome -- 1 -- -- -- -- -- -- -- -- -- Agraptocorixa parvipunctata -- 1 -- -- -- -- -- -- -- -- -- Agraptocorixa sp. (F) -- 2 -- -- -- 2 -- 2 -- -- -- Diaprecoris sp. (imm.) -- -- 2 -- -- -- -- -- -- 3 -- Micronecta sp. (F) 1 1 1 -- -- -- -- -- -- -- -- Micronecta sp. (imm.) 3 1 2 -- 2 1 -- -- 2 1 -- Micronecta sp.1 -- 2 -- 2 -- -- -- -- -- -- -- Sigara sp. (F) -- 2 -- -- -- -- -- 2 -- -- -- Sigara truncatipala 1 -- 2 1 -- -- -- 1 1 -- --



33

Sites


Hebridae Hebridae spp. (imm.) -- -- -- -- -- -- -- -- -- 1 -- Hebrus axillaris -- -- -- -- -- -- -- -- -- 1 -- Notonectidae Anisops sp. (F) -- 2 3 -- -- -- -- 2 -- -- -- Anisops sp. (imm.) -- -- 1 3 2 1 2 1 2 -- -- Anisops sp. 1 -- 1 2 -- -- -- -- 2 -- -- -- Anisops sp. 2 -- 2 -- -- -- -- -- -- -- -- -- Saldidae Saldula sp. -- -- -- -- 1 -- -- -- -- -- -- COLEOPTERA Carabidae Carabidae spp. -- 1 -- 2 -- -- 2 1 -- 1 -- Dytiscidae Allodessus bistrigatis 1 -- -- -- -- -- -- 2 -- -- -- Hyphydrus elegans 1 -- -- 1 -- -- -- -- -- -- -- Hyphydrus sp. (L) -- -- 1 2 -- -- -- -- -- 1 -- Liodessus dispar 2 3 2 2 1 -- 2 3 3 2 -- Liodessus inornatus 2 2 -- 1 2 2 2 2 1 -- 2 Megaporus howitti 2 2 -- 1 -- 1 2 3 2 2 -- Megaporus sp. (L) -- -- 2 -- -- -- -- -- -- 2 -- Necterosoma darwini 2 3 -- 3 2 2 2 2 -- -- -- Necterosoma sp. (L) 3 3 -- 3 3 3 3 3 2 2 2 Onychohydrus sp. (L) -- -- 1 1 -- -- -- -- -- 1 -- Paroster pallescens 2 3 -- 3 2 -- 2 4 3 3 -- Platynectes decempunctalis -- 1 -- -- 2 -- 1 1 -- -- -- Platynectes sp. (L) 3 3 -- 2 -- 3 2 3 -- 2 -- Rhantus sp. (L) 2 2 -- 2 -- -- -- 2 2 3 -- Rhantus suturalis 2 2 -- -- -- 1 2 2 1 2 -- Sternopriscus marginatus -- -- -- -- -- -- -- -- -- -- 1 Sternopriscus multimaculatus 1 -- 2 -- -- -- -- -- -- -- -- Sternopriscus sp. (F) 1 1 -- 1 -- -- -- 1 -- -- -- Sternopriscus sp. (L) 2 -- -- 2 1 2 1 -- 1 -- 2 Tribe Bidessini spp. (L) 1 -- 2 2 -- -- -- -- 3 -- -- Gyrinidae Aulonogyrus strigosus -- -- -- -- -- -- -- -- -- 1 -- Aulonogyrus/Macrogyrus sp. (L) -- -- -- -- -- -- -- -- -- 2 -- Macrogyrus sp. -- -- -- -- -- -- -- -- -- -- 2 Hydrochidae Hydrochus australis -- -- -- 2 -- -- -- 1 3 2 -- Hydrophilidae Berosus approximans -- 2 1 2 -- -- -- 2 3 2 --



34

Sites


Berosus josephenae (?) -- -- -- 1 -- -- -- -- -- -- -- Berosus sp. (L) 3 -- 2 3 -- -- -- 2 3 3 -- Chasmogenus sp. (L) -- -- -- 2 -- -- -- -- -- -- -- Coelostoma sp. -- -- -- -- -- 1 -- -- -- -- -- Enochrus eyrensis -- 1 -- -- -- -- -- -- -- -- -- Enochrus samae -- 2 -- -- -- -- -- -- 3 2 -- Helochares sp. (L) -- -- -- 2 1 2 1 -- -- -- 2 Limnoxenus sp. (L) 1 3 1 3 2 -- 2 3 3 2 -- Limnoxenus zelandicus -- 2 -- 2 1 -- 1 3 -- 1 -- Paracymus pygmaeus 3 4 2 3 3 3 -- 3 3 2 -- Paracymus sp. (L) 2 2 2 -- -- -- -- -- -- 2 -- Paranacaena sp. 1 -- -- -- -- 1 -- 1 1 -- -- Scirtidae Scirtidae spp. (A) -- -- -- 1 -- -- -- -- -- -- -- Scirtidae spp. (L) -- 1 -- -- -- -- 2 -- -- -- 1

*Total number of ‘species’ 56 56 42 66 47 51 38 55 57 70 40

*The taxonomic listing includes records of larval and pupal stages. Current taxonomy in Australia is not sufficiently well developed to allow identification of all taxa to species level. In many instances it is likely that these stages are the same species as the adult stages recorded from the same location and have been grouped as such for comparisons of species richness between sites. Similarly, for some Coleoptera and Hemiptera species, male adults are required to confirm species-level identifications.



35

Analysis of Patterns in Community Structure - PATN

Spatial patterns in macroinvertebrate community structure were investigated using classification and ordination techniques (PATN). The dendrogram produced by UPGMA (Unweighted Pairgroup Arithmetic Averaging) classification of the log10 abundance data set, separated sites into five groups (Figure 9). The macroinvertebrate community structures of upper Ferraro Brook, Nanga Brook, upper Wealand Brook, Upper Mayfield Drain (including channelised sections of Ferraro and Wealand brooks) and the perched wetland site were distinct from each other. There was a significant (PATN ANOSIM, p <0.01) separation of these five groups within ordination space (Figure 10). UMD1 _ UMD2 |______________ Group 5 WB4 _ | FB4 |_____________|______ WB1 ____________ | Group 4 WB2 ___________|________|______________________________ WB3 __________________________________________________|__________ Group 3 NB1 _______________________________________ | Group 2 FB3 ____________________ | | FB2 _________________ | | | Group 1 FB1 ________________|__|__________________|_____________________| | | | | | | 0.2430 0.3122 0.3814 0.4506 0.5198 0.5890

Figure 9. UPGMA classification dendogram of the 11 sites using macroinvertebrate log abundance.

(a)

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

FB3

WB2

FB1 FB2

WB3

NB1UM D2

WB4

FB4

WB1UM D1

(b)

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

Cnephia sp.

M egaporus howit t iCorynoneura sp.Liodessus disparParoster sp.

Austrochiltonia subtenuis

(c)

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

M ax. depth

Turbidity

Ave. WidthAve. depth

Econd.

Figure 10. (a) MDS ordination of the 11 Waroona sites. Ordination used log abundance of macroinvertebrates. Sites are coloured by a posteri groupings from UPGMA classification and indicating PCC-derived gradients of (b) macroinvertebrate species and (c) physico-chemical parameters through ordination space (optimum solution for the ordination was in 3 dimensions with a stress of 0.1214).



36

Major groupings within the ordination were directly influenced by the abundance of species such as the amphipod Austrochiltonia subtenuis, dipteran larvae (Cnephia tonnoiri tonnoiri and Corynoneura sp.) and three aquatic beetles (Liodessus dispar, Megaporus howitti and Paroster larvae) (Figure 10). The Kruskal-Wallis non-parametric one-way analysis of variance test was applied within the PATN package to test for significant differences in macroinvertebrate log10 abundances amongst the five groups identified by the UPGMA classification. Analysis detected significant (p<0.05) between-group differences in abundances of oligochaete (aquatic worm) and the mayfly Nousia sp. (Appendix 3b). Nousia sp. was only collected from Ferraro Brook east of South Western Highway (i.e. sites FB1, FB2 & FB3). Oligochaetes were not collected from the perched wetland site, but were abundant at all brook/drain sites. Ordination detected significant (p <0.01) gradients for a number of physico-chemical parameters which likely play a major role in the variability of macroinvertebrate community structure amongst sites. These parameters were salinity (Econd.), turbidity, water depth and average channel width (Figure 10). Species data from the Waroona sites was also compared against data collected from Drakesbrook Main Drain by WRM (2003) in April 2003. UPGMA classification of sites again detected five main groupings (Figure 11). Ordination showed a clear separation of these groupings in ordination space (Figure 12). The macroinvertebrate communities were distinct (PATN ANOSIM, p<0.01) for each of Drakesbrook Drain, Ferraro Brook, Nanga Brook and Upper Mayfield Drain. All Wealand Brook sites grouped with the Upper Mayfield Drain sites with the exception of the perched wetland (WB3). The channelised (drain) section of Ferraro Brook (site FB4, west of the Highway) also grouped with the Upper Mayfield Drain sites. The abundance of numerous species contributed to the differences in community structure between these groups (Figure 12). .The Kruskal-Wallis analysis detected significant (p<0.05) between group differences in abundance of 28 species (Appendix 3c). The separation of Drakesbrook Drain sites from Waroona sites was considered mainly due to the more degraded habitat conditions in Drakesbrook Drain resulting in very low species diversity. To a lesser degree, sampling season (i.e. April 2003 vs Oct. 2004) will also influence macroinvertebrate diversity. UMD1 _ UMD2 |____ WB4 ___ | WB1 __|_|__ Group 5 FB4 ______|__ WB2 ________|____________ FB3 _________ | FB1 ________|__ | Group 4 FB2 __________|_________|_______ WB3 ___________________________|_________________________________ Group 3 NB1 __________________________ | Group 2 DB-M2 _______ | | DB-M3 ___ | | | Group 1 DB-M4 __|___|__________________|__________________________________| | | | | | | 0.2140 0.3732 0.5324 0.6916 0.8508 1.0100 Figure 11. UPGMA classification dendogram of the Waroona 2004 sites together with Drakesbrook 2003

sites using macroinvertebrate log abundance.



37

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

Drakesbrook Drain

Nanga Brook

Ferraro BrookWealand Brook &Upper M ayf ield Drain

Wetland (WB3)

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

Empididae sp.L. dispar

Centropt ilum sp.Liodessus inornatusOstracoda spp.

Paroster sp.Corixidae spp.

Coryoneura sp.Paratanytarsus grimmiiParalimnophes ?pullulusHydrochus spp.Tasmanocoenis t illyardi

Hydrochus spp.B.approximansLimnoxenus sp.P. pygmaeus

Figure 12. MDS ordination of Waroona 2004 sites together with Drakesbrook 2003 sites. Ordination used log abundance of macroinvertebrates. Sites are coloured by a posteri groupings from UPGMA classification and indicating PCC-derived gradients of macroinvertebrate species (left) through ordination space (optimum solution for the ordination was in 3 dimensions with a stress of 0.1214).

3.2.4 Fish and Crayfish

Three species of fish were recorded; the western minnow Galaxias occidentalis, the pygmy perch Edelia vittata and the introduced mosquitofish Gambusia holbrooki. Western minnows were only observed in the channelised sections of Ferraro (FB4) and Wealand (WB4) brooks, immediately west of South Western Highway. Mosquitofish were also present at FB4. A single juvenile pygmy perch was recorded from site UMD2 on Upper Mayfield Drain, west of South Western Highway. Western minnows and pygmy perch are the two most widespread and common native fish in the south-west. Both are common in rivers, streams, and lakes, and although they require permanent water, can readily re-invade seasonal wetlands via flood-ways and up seasonal creeks/drains. Western pygmy perch are more typically associated with riparian/emergent vegetation and rarely occur in open water. Both native species feed predominantly on terrestrial and aquatic invertebrates, including freshwater shrimp. One freshwater shrimp species (Palaemonetes australis) and two freshwater crayfish, gilgies (Cherax quinquecarinatus) and koonacs (Cherax plebejus), were collected (Table 9) and were included in the macroinvertebrate analyses above. Freshwater shrimp were only recorded from site UMD2 (the most downstream site on Upper Mayfield Drain) where they were abundant (Table 9). This shrimp is commonly found in large numbers in slow-moving or still permanent waters with dense overhanging vegetation. The few stands of macrophyte and encroaching pasture grasses at site UMD2 offered some habitat. Both crayfish species recorded are regional endemics, widespread throughout the south-west and commonly occur in ephemeral and seasonal waterbodies. Gilgies were recorded in Nanga Brook and Upper Mayfield Drain, while koonacs were also collected from Upper Mayfield Drain and Ferraro Brook. There was anecdotal evidence from local landowners that these crayfish are widespread throughout the brooks and drains. The diet of native freshwater crayfish mostly comprises organic detritus. Unlike marron (Cherax cainii & C. tenuimanus), gilgies and koonacs have both evolved to survive in seasonal waters and can burrow into moist sub-soils or down to the water table.



38

The low numbers and low diversity of fish and crayfish recorded was not unexpected given the, degraded riparian conditions, low diversity of in-stream habitats and seasonal nature of flows. There were no large permanent pools to sustain fish populations over summer and insufficient fringing/trailing vegetation for shelter and spawning. Throughout the south-west, temporary streams have reduced species richness compared with permanent waters, due to seasonal accessibility and limited food supply for young fish (Pusey & Edward 1990, Pen et al. 1993). Further details of the life-history strategies of fish recorded are presented in Appendix 4. 3.2.5 Tortoises

Though not specifically targeted in the current study, there was anecdotal evidence (P. Ward and G. Chuffey pers. comm., 2004) that the numerous semi-permanent swamps and wetlands adjacent to the main channels provide habitat for western long-necked tortoises (Chelodina oblonga). The tortoises also use the swamplands that lie within the proposed main pit area between Ferraro Brook and the Mullins Sumpland. As the swamps dry in summer, the tortoises migrate across paddocks into the small permanent pools scattered along Ferraro Brook (e.g. sites FB3) and Upper Mayfield Drain (e.g. between sites UMD1 & UMD2). Long-necked tortoises inhabit both permanent and seasonal waterbodies and have a wide distribution throughout the south-west. They can migrate relatively long distances overland if local conditions deteriorate (Cogger 1986) or they can burrow into the sediment and aestivate. The tortoises only eat when open water is present and diet includes tadpoles, fish, and invertebrates. In permanent waters, this species has two nesting periods (September-October and December-January) but in seasonal systems, nesting will only occur in spring. Tortoises generally nest in sandy soils and eggs take up to two hundred days to hatch.

5. SOCIAL WATER REQUIREMENTS Part of the current study was to identify social values of Ferraro and Wealand Brooks that could be potential components of EWPs. Aspects investigated included:

- water for domestic and stock water uses, - recreational pursuits, - landscape and aesthetic and - educational or scientific aspects.

Values were assessed through discussions with local landowners and Iluka personnel on 5 - 6th August 2004 and by walkover surveys conducted in conjunction with aquatic fauna surveys. A total of eight landowners were visited. Locations of the properties are shown in Figure 3 and summary of water uses presented in Table 10. While there are no major water supply dams within the study area, there are numerous small farm/residential supply and ornamental dams along Nanga Brook (URS 2002). Along Ferraro and Wealand brooks however, landowners rely on groundwater bores, wells and soaks to water stock over summer. Livestock (cattle and horses) have unrestricted access to brooks and drains on properties east of South Western Highway. West of the highway, electric fences have been installed to facilitate vegetation restoration along many drain reaches and cattle access is only permitted at points.



39

Table 10. Social water requirements – water census of surface water use in Ferraro and Wealand brooks, conducted in August 2004.

LANDOWNER PROPERTIES COMMENTS DRAIN/BROOK WATER USAGE

BORE USAGE BORE DEPTH

Wealand Brook

N. & D. Johns Lot 3

Wealand

Wealand Bk runs through property from Iluka owned property to the east. Brook dries over summer.

Brook not fenced off; access for horses, but horses reliant on permanent soaks over summer. Enjoyed aesthetics of the brook & remnant vegetation on property.

Used to have a spring fed dam that dried subsequent to mineral sands mining by Cable Sands.

No Yes - one for domestic supply.

Concerned that drawdown will cause soaks to dry.

20m

F.P. Fiore Loc 547

Hall Rd

Has owned property for approx. 3 years

Brook flows across SW corner of block & is not fenced off; has permanent pool for cattle. Believes brook flows 4-6 months of year but doesn’t go down to brook much so not really sure.

Doesn’t think mining will worry him.

Hobby farmer, small vineyard.

Cattle use permanent pool over summer.

? ?

R. Polinelli Loc 216

Wealand Rd

Owned property since 1982 (bought from Mr Dawe).

Runs approx 20 cattle, does not live on property, lives on other side of highway further north.

Upper Mayfield Drain starts on this property & a tributary brook flows through NE section of block;

Wealand Brook (channelized) crosses through southern section of block; brook used to flood across paddock so the channel was dug deeper.

No Yes – one. 20m (water @ 6m)

Ferraro Brook

L.E. & P.W. Ward

(Aintree Pty Ltd)

Lot 4, 5 & Loc 214

Wealand Rd

Dairy farm. Ferraro Bk crosses property; drain starts on Loc 214. Discharge from Ferraro Bk about 3x that from Wealand Bk; brook dries out in November, runs 6-8 months of year.

Brook elevation drops down over 3m across his property to the highway.

Brook not fenced; cattle access. Channel down-cut by up to 4m deep; very steep banks; WRC built artificial waterfalls last year (2003). Bankfull each winter; flows bank up due to obstructions at SW Hwy culverts downstream of property.

Brook was cleaned out (de-snagged) in the 1930’s and drains installed.

Observed tortoises moving from brook towards Mullins Sumpland across Peel Rd. Commented that Mullins property was wet all the time but doesn’t flow.

No Ex-Cable Sands bore, now using only 2,000 GL/day.

Not sure if bore affected down-stream properties when Cable Sands were mining; didn’t affect bores on Ward’s property.

Ferraro / Wealand Bk confluence

J. Mitchell

(Mitchell Nominees Aust. Pty Ltd).

Loc 364 & 365

MacNeill / Mayfield Rd

Drain section of Wealand Bk (Mayfield 2) flows thro’ Loc 364 & of Ferraro Bk (Mayfield 1) thro’ Loc 365. Drains only flow in winter with similar discharge tho’ Wealand Bk flows a little longer; flows stop in spring. Both can flood quickly.

Drains fenced & recently replanted with native trees and shrubs.

No

Would like to be on piped irrigation supplied by Harvey Water.

Five wells for continuous supply. Water levels @ 8m; one has bore inside well (6m).

14m



40

LANDOWNER PROPERTIES COMMENTS DRAIN/BROOK WATER USAGE

BORE USAGE BORE DEPTH

(also met with C. Davis lived on the property his whole life until recent sale to Mitchell).

J. Mitchell has planted an extra 1000 trees along Mayfield1 as part of his requirements for screening (planning cattle storage and transport facility).

C. Davis was surprised at this as now there are trees on both sides of drain and no access for excavator if required.

Cable Sand’s bore on Wealand Rd used to draw 12,000 GL/hr for 24 hrs/day (should have been 12,000 GL/hr). Impacted on C. Davis’ bore, but Cable Sands were helpful and came and watered gardens and dug one bore deeper for him.

Some salt patches detected on property.

Can all be used for drinking except one at the back which is slightly salty.

N.R. Bruce

(also spoke with G. Chaffey who works the farm).

Loc 411 & 412

Mayfield Rd

N.R. Bruce has lived on property all his life.

Wealand Bk and Ferraro Bk join together on this property. Fenced off drain and trees but cattle in when fence is down.

G. Chaffey commented Upper Mayfield Drain runs at bankfull each winter & floods several times each year. Drain dries around December; flows very closely coupled with rainfall - 2” in upper catchment is enough to cause flooding.

Don’t mind if drain flows less in winter as currently too much water (sheet flow).

In summer, has observed tortoises moving from wetland on Loc 412 into permanent pools in drain.

No

Thinking of applying for piped irrigation supplied by Harvey Water.

Yes – one.

Bore levels dropped while Cable Sands were mining.

32 – 27m

Upper Mayfield Drain

R.A. & C.H. Archibald Loc 408 Mayfield Rd & Lots 2 & 3 Somers Rd

Upper Mayfield Drain flows thro’ dairy farm. Been on property for 30 years.

C.H. Archibald very involved in Waroona Landcare. Fenced & treed 2/3 of drain through property. Don’t know how successful revegetation will be as hard rock layer just below surface (planted 2 years ago). Adjoining property (A. Fiorenza, Loc 409) not fenced.

Drain dries in December each year; bankfull each winter; floods out road occassionally (next door), but hasn’t done this for 5-10 years. Summer flows downstream maintained by springs neighbour’s (A. Fiorenza).

Flows from Ferraro & Wealand brooks are important to the drain. Rainfall is main source of water in drain.

Don’t mind if drain flows less in winter as currently too much water.

One stock access point.

Concerned about groundwater draw-down.

Wells went dry when Cable Sands mined.



41

The seasonal nature of surface flows in Ferraro and Wealand brooks, means they are not relied upon for agricultural, livestock or domestic supply. In winter, channel and sheet flooding bring too much water to downstream properties, particularly in mid reaches of Ferraro Brook - obstructions in drain culverts at South Western Highway often result in the flooding of 4 m deep reaches upstream (Loc 214 & Lots 4 & 5). Local landowners commented that the brooks and drains typically run at bankfull each winter and drain reaches west of South Western Highway may flood several times during a wet season. The majority of landowners interviewed expressed more concern about groundwater drawdown than about any reduction in surface flows. Recently, local landcare groups have undertaken riparian restoration/replanting works on drains immediately west of South Western Highway. This was viewed as indicative of the aesthetic value placed on the watercourses and the desire to enhance this value by rehabilitation activities. The drains also offered minor recreational value in the form of fishing for gilgies and koonacs by children from Waroona and properties adjacent to the watercourse.

6. CONCLUSIONS

6.1 Ecological Values The riverine ecosystems of Ferraro, Nanga and Wealand brooks and of Upper Mayfield Drain were considered of limited regional conservation value due to drain construction, disturbance of the riparian zones (livestock, weed infested and erosion prone) and loss of in-stream habitat. Channels in both the foothills and coastal plain are incised due to high overland flows from catchment clearing and there is widespread bank erosion. Macroinvertebrate communities at all sites were dominated by cosmopolitan species, typical of lowland rural regions. Only two native fish (western minnows & pygmy perch) were present and only in low numbers – abundances probably being restricted by habitat quantity and quality. In their current condition, it is unlikely that the drains and brooks within the study area provide suitable breeding or nursery habitat for native fishes. Though waterbird species may visit the brooks and drain, the small permanent pools are considered unlikely to provide significant dry-season habitat or breeding habitat. The brooks and drains do however support freshwater crayfish (gilgies & koonacs) of local conservation significance and Waroona landcare groups have recently begun restoration of riparian vegetation to improve the ecological condition of the drains west of South Western Highway. The few permanent pools intermittent along the brooks and drains also offer some summer habitat for long-necked tortoises. While gilgies and koonacs are represented by populations in the adjoining Drakesbrook system, the abundance and distribution of long-necked tortoise within the area is not known. At least one new species of Chironomidae (Tanypodinae sp. nov.) was recorded from drain sites west of the Highway. There have been few comprehensive studies of the taxonomy and distribution of chironomids in the south-west making it difficult to confer conservation status. A type 8 TEC community (“herb rich shrublands in clay pans”) exists within a perched seasonal wetland adjacent to the drains on reserve between the Highway and the railway. The reserve also contains EPP sumplands. These communities currently support healthy stands of remnant vegetation but show some disturbance from track and weed (e.g. Watsonia spp.) encroachments and illegal dumping of refuse.



42

The perched wetland was considered, at least in part, to be artificially maintained by ponding of surface waters behind the rail embankment to the west and the drain levee banks (1.5 – 2 m high) to the south. 6.1.2 Potential Threats from Mine Activities

While the current proposal for mineral sands mining is unlikely to directly affect surface flows, there is the potential for indirect impacts through groundwater drawdown, further vegetation-loss, increased soil nutrients and contaminants and through possible future dam regulation. Since the waterbodies are naturally seasonal, maintenance of summer surface flows in Ferraro and Nanga brooks would not be required to maintain the existing riverine ecosystems. Native fish can re-colonise from more permanent waters in Drakesbrook and Mayfield drains, provided they can negotiate any man-made features such as weirs, v-notch gauging structures and dams. Long-necked tortoises, gilgies and koonacs can all survive in seasonal and ephemeral systems by burrowing into moist sub-soils, but survival will be dependent on depth and extent to which water tables are lowered and the impact to soil moisture content at depth. Similarly, most macroinvertebrates fulfil their entire larval stage within an aquatic environment and as such, may be made locally extinct by any reduction in groundwater flows, if channel pools and sediments dry before the adults emerge; for some species, this may take up to two years. Determination of the extent to which TEC and EPP vegetation was reliant on groundwater, channel water (including overbank flows) and/or sheet flow was beyond the scope of the current study. It is considered unlikely that the vegetation is reliant on surface flow from the drains. The seasonal nature of flow in the drains means vegetation is more likely dependent on groundwater to sustain it over summer. Any reduction in overbank flows during winter would more than likely be compensated by sheet flooding. It is also expected that any reduction in surface flows in Upper Mayfield Drain, below the confluence with Ferraro Brook, would be adequately compensated by flows from the unregulated Wealand Brook. Existing annual flows in Wealand Brook and in downstream reaches of Upper Mayfield Drain could not be adequately assessed due to the absence of gauging stations. Flows downstream of the mine will need to be monitored to ensure adequate volumes of water are actually being maintained and to determine the contribution of catchment runoff to both surface flow and groundwater recharge.

6.3 Social Water Requirements Changes to surface waters in Ferraro and Wealand brooks and in Upper Mayfield Drain are not expected to affect downstream agricultural properties. Stock and irrigation water is derived from groundwater – bores, wells and soaks. While unlikely, there is some potential for loss of aesthetic (remnant & replanted native vegetation) and recreational (freshwater crayfish) values if significant reductions in surface, groundwater and sheet flows were all to occur. In this case, surface water would need to be artificially supplemented to support local landcare projects. Of most concern to landowners was the potential for drawdown to impact groundwater bore/soak supplies on neighbouring and downstream properties.



43

7. RECOMMENDATIONS 1. Any proposed management/monitoring programmes should seek to prevent further

degradation of those areas that retain some ecological value and to facilitate the possible future restoration of degraded areas.

2. Iluka has already formulated programmes for monitoring ground and surface water

quality and quantity as well as plans for drainage management. Monitoring sites cover reaches in Ferraro, Nanga and Wealand brooks, both upstream and downstream of proposed mine areas (refer Iluka 2004b). These monitoring programmes should be maintained for the life of the mine and data adequately evaluated.

3. Though winter flows are now greater than would have occurred historically, the

seasonality of the flow regime has been maintained. Over summer, some permanent soaks and channel pools should be maintained to provide a summer dry-season refuge for macroinvertebrate species and long-necked tortoises.

4. To protect habitat for tortoises and freshwater crayfish it is recommended that turbidity

in natural streams downstream from mining should not increase by more than 10% above the existing seasonal mean concentration (based on ANZECC/ARMCANZ (2000) guidelines for the protection of aquatic ecosystems). These species may become locally threatened due to loss of breeding habitat, shelter and food resources if mining were to lead to siltation/aggradation of existing small pools and permanently increase turbidity. Analyses of macroinvertebrates present indicated turbidity and water depth appear to play a role in structuring the communities within the study area.

5. To supplement Iluka’s ground and surface water monitoring, aquatic ecosystem

monitoring is recommended to confirm there are no detrimental impacts from mineral sands mining. Ecosystem monitoring would also assist in determining the success of streamlining projects currently being undertaken by local landcare groups. At least biennial monitoring of aquatic fauna (macroinvertebrates & fish) and associated physico-chemical parameters and riparian vegetation condition is recommended. A sub-set of sites for long-term monitoring could be chosen from sites surveyed in the current study (based on results of PATN analyses), but where possible should correspond to Iluka’s surface water monitoring sites. In total, a minimum six sites should be chosen to cover both upstream and downstream (of mine operations) reaches along all three brooks.



45

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APPENDICES



51

Appendix 1. Photographs of aquatic sampling sites.

Plate 1. Site WB1 on Wealand Brook; most upstream site; Johns property; view upstream; cotton bush present; Oct. 2004.

Plate 2. Site WB1 on Wealand Brook; view downstream; Oct. 2004.

Plate 3. Site WB2 on Wealand Brook; Fiore property; view

upstream; permanent pool; Melaleuca rhaphiophylla overstorey in background; Aug. 2004 (photo: L. Kerr).

Plate 4. Perched seasonal wetland site WB3 within TEC on Parkland and Conservation Reserve 31437, between SW Hwy and

rail line; view east; Watsonia in foreground; Melaleuca in background; pine plantation just visible left background.

Plate 5. Channelised sections of Wealand Brook in Parkland and Conservation Reserve 31437, between SW Hwy and rail line; levee banks; adjacent to southern edge of perched wetland site WB3; Oct.

2004.

Plate 6. Site WB4 on channelised section of Wealand Brook west of SW Hwy; Mitchell property; view downstream; replanted Eucalyptus

along southern bank; Aug. 2004 (photo: L. Kerr).



53

Plate 7. Site FB1 on Ferraro Brook, most upstream site; Iluka lease upstream from pit areas; view north-west; Oct. 2004.

Plate 8. Site FB2 on Ferraro Brook; Iluka lease, downstream from Iluka gauging station; view upstream toward dense stand of

Melaleuca rhaphiophylla; Oct. 2004.

Plate 9. Site FB3 on Ferraro Brook; Ward property immediately downstream of mine lease; view upstream; down-cut channel; bank

slumping; pool below artificial water fall; Oct. 2004. Plate 10. Site FB4 on channelised section of Ferraro Brook, west of

SW Hwy; Mitchell property; view downstream; recently planted native vegetation along northern bank; Aug. 2004 (photo L. Kerr).

Plate 11. Site UMD1 on Upper Mayfield Drain; Archibald property;

view downstream; Oct. 2004.

Plate 12. Immediately downstream of site UMD2 on Upper Mayfield Drain; Archibald property; view downstream; bed substrates coffee

rock; levee banks; Oct. 2004.



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Plate 13. Site NB1 at Hill Street Weir on Nanga Brook, adjacent to

old piggery; Iluka lease; view upstream; overstorey of Melaleuca and Eucalyptus; Oct. 2003 (photo: S. Jones).

Plate 14. Downstream from site NB1 on Nanga Brook; Lot 2 Paterson Road; downcut channel; fast flowing waters – rapids; Aug.

2004 (photo: L. Kerr).

Plate 15. Downstream from site NB1; Lot 3 Paterson Road;

ornamental pond fed by pumping from Nanga Brook; Aug. 2004 (photo: L. Kerr).



57

Appendix 2. Pattern Analysis Package (PATN) To identify spatial differences in physico-chemistry and macroinvertebrate community structure, data were classified and ordinated using the CSIRO Pattern Analysis Package, PATN (Belbin 1995; http://www.cse.csiro.au/client_serv/software/patn.htm#system). Analyses were conducted on log10 abundance data and only taxa that occurred in greater than 10% of samples in each data set were included to avoid ‘low-occurrence’ taxa having a disproportionate effect on the output. Prior to ordination and classification, physico-chemical variables were standardised to a scale of zero to one by the equation: xnew = (x-xmin)/xrange, as recommended by Harch (1996) for mixed type variables. This was necessary to set all physico-chemical variables on the same scale and so avoid variables on a higher numerical scale having an over-bearing influence on the ordination/classification analysis. Sites were classified using Unweighted Pairgroup Arithmetic Averaging (UPGMA), an agglomerative hierarchical fusion technique which produces a dendrogram in which sites with similar physico-chemistry/invertebrate assemblages group together. This analysis was performed to identify groupings of sites with similar physico-chemistry/invertebrate communities. Sites were then ordinated using Semi-Strong Hybrid Multidimensional Scaling (SSH MDS) to produce an n-dimensional scatter plot of sites. For each analysis, similarity between sites was determined using the Bray-Curtis association measure. UPGMA groupings were superimposed on the respective ordination plots to assess the distinctiveness of the site groupings. To test the significance of the separation of these groups of sites in ordination space, the Analysis of Similarity (ANOSIM) option in PATN (Belbin 1995) was invoked. The Kruskal-Wallis non-parametric one-way analysis of variance test was applied within the PATN package to test for significant differences in physico-chemical and macroinvertebrate data amongst the groups identified by the UPGMA classification. Finally, the Principal Axis Correlation (PCC) option in PATN was used to place gradients of:

• physico-chemical parameters through the ordination of sites on physico-chemical data, and, • physico-chemical parameters through the ordination of sites on invertebrate data; and • species taxa gradients through the ordination of sites on invertebrate data

Monte Carlo randomisations (n=100) of the data were performed to test the significance of these gradients.



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Appendix 3. Kruskal-Wallis Non-Parametric Tests (a). Results of Kruskal–Wallis non-parametric one-way analysis of variance indicating significant

differences (shading) in standardised physico-chemical parameters between the five groupings defined by PATN for Waroona sites.

Temperature Kruskal-Wallis: 7.7626 df: 4 Probability: 0.1007 0.6350 0.7263 0.8175 0.9088 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1L=D===M=====3--U 2 L---1=======DM========3---U 3 * 4 * 5 *======================*=====================* Conductivity Kruskal-Wallis: 3.3214 df: 4 Probability: 0.5055 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *================*==============* 2 *=========*=========* 3 * 4 * 5 * TDS Kruskal-Wallis: 1.4286 df: 3 Probability: 0.6989 0.4809 0.6107 0.7405 0.8702 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *==============================*==============================* 2 *===================*==================* 3 ATTRIBUTE IS MISSING 4 * 5 * DO % Kruskal-Wallis: 4.6212 df: 4 Probability: 0.3284 0.4520 0.5890 0.7260 0.8630 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----1==========M====D====U3 2 L1=====DM======3-U 3 * 4 * 5 *=============*============* DO mg/L Kruskal-Wallis: 8.2301 df: 4 Probability: 0.0835 0.5294 0.6471 0.7647 0.8824 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---1=========M======* 3 2 L1========*========* 3 * 4 * 5 *======*======* pH Kruskal-Wallis: 4.2121 df: 4 Probability: 0.3781 0.8419 0.8814 0.9210 0.9605 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L1====*===3U 2 L----1==========M=D=========3U 3 * 4 *



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5 *=====*======* Turbidity Kruskal-Wallis: 4.7143 df: 3 Probability: 0.1940 0.3111 0.4833 0.6556 0.8278 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *======*======* 2 *=====*=====* 3 ATTRIBUTE IS MISSING 4 * 5 * N Total Kruskal-Wallis: 0.85714 df: 3 Probability: 0.8358 0.3000 0.4750 0.6500 0.8250 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===*==* 2 *===================================*===================================* 3 ATTRIBUTE IS MISSING 4 * 5 * P Total Kruskal-Wallis: 2.5500 df: 3 Probability: 0.4663 0.3750 0.5312 0.6875 0.8438 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *====================================*==================================* 3 ATTRIBUTE IS MISSING 4 * 5 * Av. Width Kruskal-Wallis: 7.2776 df: 4 Probability: 0.1219 0.2963E-01 0.2722 0.5148 0.7574 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=*3 2 L--1====M=D=U3 3 * 4 * 5 *===*===* Av. Depth Kruskal-Wallis: 8.2476 df: 4 Probability: 0.0829 0.1429 0.3571 0.5714 0.7857 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L---1====================D==M======================3--------U 3 * 4 * 5 *===*==* Max. depth Kruskal-Wallis: 9.6190 df: 4 Probability: 0.0474 0.1111 0.3333 0.5556 0.7778 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L1===DM=====3U 2 * 3 * 4 * 5 *====*===*

NB - L=lower limit; 1=Mean - 1 St.Dev; M=mean;

D=Median; 3=Mean + 1 St.Dev; U=upper limit *=more than one symbol at print position



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(b). Results of Kruskal–Wallis non-parametric one-way analysis of variance indicating significant differences (shading) in macroinvertebrate species abundance between the five groupings defined by PATN for Waroona sites

Hydra sp( 1) Kruskal-Wallis: 3.8143 df: 4 Probability: 0.4317 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 *=================*================* 3 * 4 * 5 *=======================M==================================3------------U Nematoda( 2) Kruskal-Wallis: 1.6944 df: 4 Probability: 0.7917 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 *====================================*==================================* 3 * 4 * 5 *===========M================3-------U Turbella( 3) Kruskal-Wallis: 7.4167 df: 4 Probability: 0.1154 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L--------------1=====================M===========* 3 2 *===========*==========* 3 * 4 * 5 * Oligocha( 4) Kruskal-Wallis: 10.000 df: 4 Probability: 0.0404 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Ferrissi( 5) Kruskal-Wallis: 7.0342 df: 4 Probability: 0.1341 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *=====M=========3------U 2 *=======================*========================* 3 * 4 * 5 L----1==========M=======* 3 Pseudosu( 6) Kruskal-Wallis: 2.8426 df: 4 Probability: 0.5845 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+



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1 L--------------1==============================M========D================* 2 *=================*==================* 3 * 4 * 5 *=======================M==================================3------------U Physa ac( 7) Kruskal-Wallis: 7.9603 df: 4 Probability: 0.0930 0.000 1.250 2.500 3.750 5.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---1=========*==========3--U 2 *======*======* 3 * 4 * 5 1 *====M======3--U Oribatid( 8) Kruskal-Wallis: 6.8877 df: 4 Probability: 0.1419 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----1============*============3---U 2 * 3 * 4 * 5 *=================M=========================3----------U Hydracar( 9) Kruskal-Wallis: 5.7143 df: 4 Probability: 0.2215 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 L-------------1==================================M======================* Entomobr( 10) Kruskal-Wallis: 6.3565 df: 4 Probability: 0.1741 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *=====M=========3------U 2 *=======================*========================* 3 * 4 * 5 1 *=======M==========3---U Poduroid( 11) Kruskal-Wallis: 4.1039 df: 4 Probability: 0.3921 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========*==========* 2 * 3 * 4 * 5 L-------------1==================================M======================*



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Symphypl( 12) Kruskal-Wallis: 1.2245 df: 4 Probability: 0.8740 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=================D========M==============================3-------------U 2 *=================*==================* 3 * 4 * 5 *=======================M==================================3------------U Austroch( 13) Kruskal-Wallis: 5.9375 df: 4 Probability: 0.2039 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------------------1=============================M===========D==========* 2 * 3 * 4 * 5 1 *=======M==========3---U Perthia ( 14) Kruskal-Wallis: 4.6122 df: 4 Probability: 0.3294 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------1===================M======D===========U 3 2 *====================================*==================================* 3 * 4 * 5 1 *=======M==========3---U Cladocer( 15) Kruskal-Wallis: 5.9220 df: 4 Probability: 0.2050 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-----------------1===========================M========D================* 2 * 3 * 4 * 5 * Cyclopoi( 16) Kruskal-Wallis: 7.0879 df: 4 Probability: 0.1313 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *===M=======3----U 2 * 3 * 4 * 5 L-------1=====================M======D===============3-U Cherax s( 17) Kruskal-Wallis: 5.4167 df: 4 Probability: 0.2472 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 *



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4 * 5 * Paramphi( 18) Kruskal-Wallis: 7.6563 df: 4 Probability: 0.1050 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------------1=======================M=============* 3 2 * 3 * 4 * 5 * Ostracod( 19) Kruskal-Wallis: 5.5592 df: 4 Probability: 0.2346 2.000 2.750 3.500 4.250 5.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1=================*================3-----U 2 * 3 * 4 * 5 L----1===========M=======* 3 Ceratopo( 20) Kruskal-Wallis: 6.9551 df: 4 Probability: 0.1383 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1================*=================3------U 2 *========================*======================* 3 * 4 * 5 * Forcypom( 21) Kruskal-Wallis: 7.2639 df: 4 Probability: 0.1226 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *=================*================* 3 * 4 * 5 L------1=============================*============================3-----U Ceratopo( 22) Kruskal-Wallis: 6.8934 df: 4 Probability: 0.1416 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *====================================*==================================* 3 * 4 * 5 * Chironom( 23) Kruskal-Wallis: 6.5625 df: 4 Probability: 0.1609 2.000 2.250 2.500 2.750 3.000



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GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------------------1===============================M================* 2 * 3 * 4 * 5 * Chironom( 24) Kruskal-Wallis: 6.8125 df: 4 Probability: 0.1461 2.000 2.500 3.000 3.500 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-----------1==============M=========* 3 2 * 3 * 4 * 5 L------1================M============* 3 Cryptoch( 25) Kruskal-Wallis: 6.0871 df: 4 Probability: 0.1927 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========*==========* 2 *============*===========* 3 * 4 * 5 L---------1=====================M================* 3 D. ?conj( 26) Kruskal-Wallis: 5.7500 df: 4 Probability: 0.2186 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=================D========M==============================3-------------U 2 * 3 * 4 * 5 * Paraclad( 27) Kruskal-Wallis: 4.1636 df: 4 Probability: 0.3843 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=====M==========3------U 2 * 3 * 4 * 5 L---------1==============================M=======D=====================3U Paratany( 28) Kruskal-Wallis: 5.1616 df: 4 Probability: 0.2711 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-----------------1===========================M========D================* 2 * 3 * 4 * 5 L--1==============*==============3---U



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P. nubif( 29) Kruskal-Wallis: 5.7500 df: 4 Probability: 0.2186 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=================D========M==============================3-------------U 2 * 3 * 4 * 5 * Polypedi( 30) Kruskal-Wallis: 7.9228 df: 4 Probability: 0.0944 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1================*=================3------U 2 * 3 * 4 * 5 1 *=======M==========3---U Rheotany( 31) Kruskal-Wallis: 5.2326 df: 4 Probability: 0.2643 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M====================3---------------U 2 * 3 * 4 * 5 L---1===================*===================3----U Tanytars( 32) Kruskal-Wallis: 7.0536 df: 4 Probability: 0.1331 2.000 2.250 2.500 2.750 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------------------1===============================M================* 2 * 3 * 4 * 5 * Botryocl( 33) Kruskal-Wallis: 4.4964 df: 4 Probability: 0.3430 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=======================D=====M===============================3---------U 2 * 3 * 4 * 5 *=======M===========3---U Corynone( 34) Kruskal-Wallis: 8.6339 df: 4 Probability: 0.0709 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *



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2 *===========*==========* 3 * 4 * 5 L---1===================*===================3----U C. albit( 35) Kruskal-Wallis: 1.9734 df: 4 Probability: 0.7406 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *=======================*========================* 3 * 4 * 5 *=======M===========3---U C. annul( 36) Kruskal-Wallis: 2.2037 df: 4 Probability: 0.6984 2.000 2.500 3.000 3.500 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================*==================* 2 *=================*==================* 3 * 4 * 5 L------1=============================*============================3-----U Parakief( 37) Kruskal-Wallis: 3.7901 df: 4 Probability: 0.4352 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *========M===============3-----------U 2 * 3 * 4 * 5 L------1=============================*============================3-----U Paralimn( 38) Kruskal-Wallis: 7.2571 df: 4 Probability: 0.1229 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 L-------------1==================================M======================* Thienema( 39) Kruskal-Wallis: 4.5421 df: 4 Probability: 0.3376 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----1============*============3---U 2 *========*========* 3 * 4 * 5 L--1==============*==============3-U Parameri( 40) Kruskal-Wallis: 5.1713 df: 4 Probability: 0.2702



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1.000 1.750 2.500 3.250 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------1===================M======D===========U 3 2 * 3 * 4 * 5 1 *=======M==========3---U P. palud( 41) Kruskal-Wallis: 6.5476 df: 4 Probability: 0.1618 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========*==========* 2 *=======================*========================* 3 * 4 * 5 *===============M======================3---------U Tanypodi( 42) Kruskal-Wallis: 6.4167 df: 4 Probability: 0.1701 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L--------------1==============================M========D================* 2 * 3 * 4 * 5 * Anophele( 43) Kruskal-Wallis: 6.5333 df: 4 Probability: 0.1627 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----1============*============3---U 2 *==========================*===========================* 3 * 4 * 5 *=====M========3--U Culicida( 44) Kruskal-Wallis: 9.2500 df: 4 Probability: 0.0551 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *=====M=========3------U 2 * 3 * 4 * 5 * Dolichop( 45) Kruskal-Wallis: 4.1071 df: 4 Probability: 0.3917 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *====================================*==================================* 3 * 4 * 5 *



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Ephydrid( 46) Kruskal-Wallis: 3.1667 df: 4 Probability: 0.5303 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================*========================* 2 *====================================*==================================* 3 * 4 * 5 * Psychodi( 47) Kruskal-Wallis: 4.8681 df: 4 Probability: 0.3011 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L--------------1==============================M========D================* 2 * 3 * 4 * 5 L------1================M============* 3 Sciozyio( 48) Kruskal-Wallis: 1.6235 df: 4 Probability: 0.8046 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *========M===============3-----------U 2 *====================================*==================================* 3 * 4 * 5 *===========M================3-------U Austrosi( 49) Kruskal-Wallis: 4.6783 df: 4 Probability: 0.3219 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M====================3---------------U 2 * 3 * 4 * 5 *=======M===========3---U Cnephia ( 50) Kruskal-Wallis: 7.1111 df: 4 Probability: 0.1301 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 L-1=====================D=======M==============================3--------U Simulium( 51) Kruskal-Wallis: 3.8260 df: 4 Probability: 0.4301 1.000 1.750 2.500 3.250 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1=================*================3-----U



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2 *============*===========* 3 * 4 * 5 L----1===========M=======* 3 Tipulida( 52) Kruskal-Wallis: 1.4439 df: 4 Probability: 0.8365 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=======================D=====M===============================3---------U 2 * 3 * 4 * 5 L---------1=====================M================* 3 Hemicord( 53) Kruskal-Wallis: 6.5625 df: 4 Probability: 0.1609 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------------------1===============================M================* 2 * 3 * 4 * 5 * Acritopt( 54) Kruskal-Wallis: 8.1053 df: 4 Probability: 0.0878 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *========================*======================* 3 * 4 * 5 * Oxyethir( 55) Kruskal-Wallis: 4.7161 df: 4 Probability: 0.3177 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *=================*==================* 3 * 4 * 5 L------1=============================*============================3-----U Oecetis ( 56) Kruskal-Wallis: 3.9236 df: 4 Probability: 0.4164 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------------------1=============================M===========D==========* 2 *=======================*========================* 3 * 4 * 5 1 *=======M===========3----U Triplect( 57) Kruskal-Wallis: 4.1621 df: 4 Probability: 0.3845



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0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------------------1=============================M===========D==========* 2 *=======================*========================* 3 * 4 * 5 *=======M===========3---U Centropt( 58) Kruskal-Wallis: 8.0146 df: 4 Probability: 0.0910 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=====M==========3------U 2 * 3 * 4 * 5 L----1===================*===================3--U Leptophl( 59) Kruskal-Wallis: 2.4444 df: 4 Probability: 0.6546 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 * 3 * 4 * 5 *=======================M==================================3------------U Nousia s( 60) Kruskal-Wallis: 10.000 df: 4 Probability: 0.0404 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Corixida( 61) Kruskal-Wallis: 8.1250 df: 4 Probability: 0.0871 1.000 1.500 2.000 2.500 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================*================* 2 *=================*================* 3 * 4 * 5 * Agraptoc( 62) Kruskal-Wallis: 1.2153 df: 4 Probability: 0.8756 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 *====================================*==================================* 3 * 4 * 5 *=======================M==================================3------------U



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Micronec( 63) Kruskal-Wallis: 5.0406 df: 4 Probability: 0.2832 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------1===================M======D===========U 3 2 *===========*==========* 3 * 4 * 5 L---1===================*===================3----U S. trunc( 64) Kruskal-Wallis: 6.4286 df: 4 Probability: 0.1693 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-----------1==============M=========* 3 2 *=================*==================* 3 * 4 * 5 * Anisops ( 65) Kruskal-Wallis: 4.3397 df: 4 Probability: 0.3620 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------1==========================M=====D===================3--U 2 *=======================*========================* 3 * 4 * 5 L----1===========M=======* 3 Anisops1( 66) Kruskal-Wallis: 4.5000 df: 4 Probability: 0.3425 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 *=================*==================* 3 * 4 * 5 * Carabida( 67) Kruskal-Wallis: 2.4120 df: 4 Probability: 0.6605 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------1=========================*========================3---------U 2 *=================*==================* 3 * 4 * 5 *=======================M==================================3------------U Hyphydru( 68) Kruskal-Wallis: 4.9352 df: 4 Probability: 0.2940 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=================D========M==============================3-------------U



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2 * 3 * 4 * 5 * L.dispar( 69) Kruskal-Wallis: 6.4615 df: 4 Probability: 0.1672 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========*==========* 2 *===========*==========* 3 * 4 * 5 L---1===================*===================3----U L. inorn( 70) Kruskal-Wallis: 7.1991 df: 4 Probability: 0.1257 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----------1=========================*========================3---------U 2 * 3 * 4 * 5 * M. howit( 71) Kruskal-Wallis: 5.9637 df: 4 Probability: 0.2019 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1=================*================3-----U 2 * 3 * 4 * 5 L---1===================*===================3----U N. darwi( 72) Kruskal-Wallis: 4.5701 df: 4 Probability: 0.3343 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=======================D=====M===============================3---------U 2 *===========*==========* 3 * 4 * 5 * Necteros( 73) Kruskal-Wallis: 6.8750 df: 4 Probability: 0.1426 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========*==========* 2 * 3 * 4 * 5 * Onychohy( 74) Kruskal-Wallis: 5.4167 df: 4 Probability: 0.2472



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0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Paroster( 75) Kruskal-Wallis: 8.3354 df: 4 Probability: 0.0800 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *===M=======3----U 2 *========*========* 3 * 4 * 5 L------1================M============* 3 P. decem( 76) Kruskal-Wallis: 2.8438 df: 4 Probability: 0.5843 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *========M===============3-----------U 2 *=================*==================* 3 * 4 * 5 L------1=============================*============================3-----U Platynec( 77) Kruskal-Wallis: 5.0000 df: 4 Probability: 0.2873 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------1==========================M=====D===================3--U 2 * 3 * 4 * 5 L---------1==============================M=======D=====================3U Rhantus ( 78) Kruskal-Wallis: 9.2500 df: 4 Probability: 0.0551 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *=====M=========3------U 2 * 3 * 4 * 5 * R. sutur( 79) Kruskal-Wallis: 4.6385 df: 4 Probability: 0.3264 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L--------------1==============================M========D================* 2 * 3 * 4 *



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5 L------1=============================*============================3-----U Sternopr( 80) Kruskal-Wallis: 6.0714 df: 4 Probability: 0.1939 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Sternopr( 81) Kruskal-Wallis: 3.2292 df: 4 Probability: 0.5202 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=================D========M==============================3-------------U 2 *====================================*==================================* 3 * 4 * 5 1 *===========M================3-----U Tribe Bi( 82) Kruskal-Wallis: 4.0874 df: 4 Probability: 0.3943 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=======================D=====M===============================3---------U 2 *===========*===========* 3 * 4 * 5 * Hydrochu( 83) Kruskal-Wallis: 9.4479 df: 4 Probability: 0.0508 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1=================*================3-----U 2 * 3 * 4 * 5 * B. appro( 84) Kruskal-Wallis: 7.9145 df: 4 Probability: 0.0948 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 1 *=====M=========3------U 2 *=======================*========================* 3 * 4 * 5 * Berosus ( 85) Kruskal-Wallis: 7.0503 df: 4 Probability: 0.1333 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+



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1 L------1==========M====* 2 *====================================*==================================* 3 * 4 * 5 * E. samae( 86) Kruskal-Wallis: 3.0833 df: 4 Probability: 0.5440 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L=======================D=====M===============================3---------U 2 *=======================*========================* 3 * 4 * 5 * Helochar( 87) Kruskal-Wallis: 6.0162 df: 4 Probability: 0.1979 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 * 3 * 4 * 5 1 *===========M================3-----U Limnoxen( 88) Kruskal-Wallis: 6.0110 df: 4 Probability: 0.1983 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L------1==========M====* 2 *========================*======================* 3 * 4 * 5 L---------1=====================M================* 3 L. zelan( 89) Kruskal-Wallis: 2.9765 df: 4 Probability: 0.5618 0.000 0.7500 1.500 2.250 3.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L--------1===========================*==========================3-------U 2 *=======================*========================* 3 * 4 * 5 L----1==========M=======* 3 P. pygma( 90) Kruskal-Wallis: 5.3962 df: 4 Probability: 0.2490 0.000 1.000 2.000 3.000 4.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L----1=======M====* 3 2 *========*=======* 3 * 4 * 5 L----------1=========================M=================* 3 Paracymu( 91) Kruskal-Wallis: 7.0536 df: 4 Probability: 0.1331



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0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=================M===============================3---------------------U 2 * 3 * 4 * 5 * Paranaca( 92) Kruskal-Wallis: 1.4881 df: 4 Probability: 0.8287 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *====================================*==================================* 3 * 4 * 5 *=======================M==================================3------------U Scirtida( 93) Kruskal-Wallis: 2.0104 df: 4 Probability: 0.7338 0.000 0.5000 1.000 1.500 2.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *========M===============3-----------U 2 *=================*==================* 3 * 4 * 5 *=======================M==================================3------------U

NB - L=lower limit; 1=Mean - 1 St.Dev; M=mean; D=Median; 3=Mean + 1 St.Dev; U=upper limit *=more than one symbol at print position



78

(c). Results of Kruskal–Wallis non-parametric one-way analysis of variance indicating significant differences (shading) in macroinvertebrate species abundance between the groupings defined by PATN for Waroona sites vs Drakesbrook sites. Hydra sp( 1) Kruskal-Wallis: 4.2370 df: 4 Probability: 0.3749 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Turbella( 2) Kruskal-Wallis: 9.8403 df: 4 Probability: 0.0432 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 * Nematoda( 3) Kruskal-Wallis: 3.0952 df: 4 Probability: 0.5420 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 *=======================M==================================3------------U 3 * 4 * 5 L-------------1==================================M======================* Oligocha( 4) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Ferrissi( 5) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 * Pseudosu( 6) Kruskal-Wallis: 4.9111 df: 4 Probability: 0.2965



79

0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Physa ac( 7) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Oribatid( 8) Kruskal-Wallis: 4.9111 df: 4 Probability: 0.2965 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Hydracar( 9) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 *=======================M==================================3------------U Entomobr( 10) Kruskal-Wallis: 9.8403 df: 4 Probability: 0.0432 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 * Poduroid( 11) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 *



80

4 * 5 * Symphypl( 12) Kruskal-Wallis: 4.2370 df: 4 Probability: 0.3749 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Palaeomo( 13) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 * 3 * 4 * 5 L-------------1==================================M======================* Cherax s( 14) Kruskal-Wallis: 4.9111 df: 4 Probability: 0.2965 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 L-------------1==================================M======================* Austroch( 15) Kruskal-Wallis: 7.3125 df: 4 Probability: 0.1203 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Perthia ( 16) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * Cladocer( 17) Kruskal-Wallis: 6.9333 df: 4 Probability: 0.1395 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+



81

1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 L-------------1==================================M======================* Cyclopoi( 18) Kruskal-Wallis: 3.6667 df: 4 Probability: 0.4530 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * Paramphi( 19) Kruskal-Wallis: 6.1750 df: 4 Probability: 0.1865 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Ostracod( 20) Kruskal-Wallis: 7.9444 df: 4 Probability: 0.0936 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 *=======================M==================================3------------U Ceratopo( 21) Kruskal-Wallis: 1.0505 df: 4 Probability: 0.9020 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 L-------------1==================================M======================* Chironom( 22) Kruskal-Wallis: 7.9444 df: 4 Probability: 0.0936 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 *=======================M==================================3------------U



82

Cryptoch( 23) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 L-------------1==================================M======================* D. ?conj( 24) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 * Paraclad( 25) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Paratany( 26) Kruskal-Wallis: 7.3125 df: 4 Probability: 0.1203 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 * P. nubif( 27) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 * P. sp V3( 28) Kruskal-Wallis: 7.3125 df: 4 Probability: 0.1203 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================*



83

2 * 3 * 4 * 5 * Rheotany( 29) Kruskal-Wallis: 6.1750 df: 4 Probability: 0.1865 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Cladotan( 30) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Botryocl( 31) Kruskal-Wallis: 3.9000 df: 4 Probability: 0.4197 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 *=======================M==================================3------------U 3 * 4 * 5 * Corynone( 32) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * C. albit( 33) Kruskal-Wallis: 3.1417 df: 4 Probability: 0.5344 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Parakief( 34) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164



84

0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Paralimn( 35) Kruskal-Wallis: 4.9111 df: 4 Probability: 0.2965 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Thienema( 36) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Parameri( 37) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * P. palud( 38) Kruskal-Wallis: 7.3125 df: 4 Probability: 0.1203 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 *=======================M==================================3------------U 3 * 4 * 5 * Tanypodi( 39) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 *



85

5 * Anophele( 40) Kruskal-Wallis: 7.4286 df: 4 Probability: 0.1149 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 *=======================M==================================3------------U 3 * 4 * 5 * Culicida( 41) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Dolichop( 42) Kruskal-Wallis: 6.1750 df: 4 Probability: 0.1865 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Empidida( 43) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Ephydrid( 44) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Psychodi( 45) Kruskal-Wallis: 3.0952 df: 4 Probability: 0.5420 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+



86

1 L-------------1==================================M======================* 2 L-------------1==================================M======================* 3 * 4 * 5 *=======================M==================================3------------U Sciozyio( 46) Kruskal-Wallis: 1.9697 df: 4 Probability: 0.7413 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 *=======================M==================================3------------U 3 * 4 * 5 * Austrosi( 47) Kruskal-Wallis: 4.2370 df: 4 Probability: 0.3749 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 *=======================M==================================3------------U 3 * 4 * 5 L-------------1==================================M======================* Cnephia ( 48) Kruskal-Wallis: 9.3232 df: 4 Probability: 0.0535 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * Tipulida( 49) Kruskal-Wallis: 2.8889 df: 4 Probability: 0.5766 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 L-------------1==================================M======================* 3 * 4 * 5 *=======================M==================================3------------U Hemicord( 50) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Cheumato( 51) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113



87

0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Acritopt( 52) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Oxyethir( 53) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Oecetis ( 54) Kruskal-Wallis: 5.4167 df: 4 Probability: 0.2472 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 *=======================M==================================3------------U Triplect( 55) Kruskal-Wallis: 4.9111 df: 4 Probability: 0.2965 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 *=======================M==================================3------------U 3 * 4 * 5 * Centropt( 56) Kruskal-Wallis: 9.6296 df: 4 Probability: 0.0472 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 * 3 * 4 *



88

5 * Tasmanoc( 57) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 *=======================M==================================3------------U 3 * 4 * 5 * Leptophl( 58) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 *=======================M==================================3------------U 3 * 4 * 5 * Nousia s( 59) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Corixida( 60) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Agraptoc( 61) Kruskal-Wallis: 1.9697 df: 4 Probability: 0.7413 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 *=======================M==================================3------------U 3 * 4 * 5 * Micronec( 62) Kruskal-Wallis: 7.3125 df: 4 Probability: 0.1203 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+



89

1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 * S. trunc( 63) Kruskal-Wallis: 7.6074 df: 4 Probability: 0.1071 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * Anisopss( 64) Kruskal-Wallis: 7.9444 df: 4 Probability: 0.0936 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * Anisops1( 65) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 * Hyphydru( 66) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 * L. dispa( 67) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * L. inorn( 68) Kruskal-Wallis: 9.6296 df: 4 Probability: 0.0472



90

0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 * M. howit( 69) Kruskal-Wallis: 10.472 df: 4 Probability: 0.0332 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * N. darwi( 70) Kruskal-Wallis: 8.0476 df: 4 Probability: 0.0898 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * Necteros( 71) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * Onychohy( 72) Kruskal-Wallis: 5.6465 df: 4 Probability: 0.2272 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 * 3 * 4 * 5 * Paroster( 73) Kruskal-Wallis: 10.472 df: 4 Probability: 0.0332 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 *



91

4 * 5 * P. decem( 74) Kruskal-Wallis: 3.9000 df: 4 Probability: 0.4197 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 L-------------1==================================M======================* 3 * 4 * 5 * Platynec( 75) Kruskal-Wallis: 7.4286 df: 4 Probability: 0.1149 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 * Rhantus ( 76) Kruskal-Wallis: 13.000 df: 4 Probability: 0.0113 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 * 3 * 4 * 5 * R.sutura( 77) Kruskal-Wallis: 7.4286 df: 4 Probability: 0.1149 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 L-------------1==================================M======================* 3 * 4 * 5 * Sternopr( 78) Kruskal-Wallis: 6.9333 df: 4 Probability: 0.1395 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * Sternopr( 79) Kruskal-Wallis: 7.4286 df: 4 Probability: 0.1149 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+



92

1 *====================================*==================================* 2 * 3 * 4 * 5 * Tribe Bi( 80) Kruskal-Wallis: 6.1750 df: 4 Probability: 0.1865 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Hydrochu( 81) Kruskal-Wallis: 6.9333 df: 4 Probability: 0.1395 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 * 3 * 4 * 5 * B. appro( 82) Kruskal-Wallis: 9.8403 df: 4 Probability: 0.0432 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 * Berosus ( 83) Kruskal-Wallis: 9.8403 df: 4 Probability: 0.0432 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L---------------------------------1==========================M==========* 2 * 3 * 4 * 5 * E.samae ( 84) Kruskal-Wallis: 4.7273 df: 4 Probability: 0.3164 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 *



93

Helochar( 85) Kruskal-Wallis: 9.6296 df: 4 Probability: 0.0472 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *===========M==========================3--------------------------------U 2 * 3 * 4 * 5 * Limnoxen( 86) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * L.zeland( 87) Kruskal-Wallis: 5.4167 df: 4 Probability: 0.2472 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 L-------------1==================================M======================* 2 L-------------1==================================M======================* 3 * 4 * 5 * P. pygma( 88) Kruskal-Wallis: 10.304 df: 4 Probability: 0.0356 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 * 2 L-------------1==================================M======================* 3 * 4 * 5 * Paracymu( 89) Kruskal-Wallis: 6.1750 df: 4 Probability: 0.1865 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 * 3 * 4 * 5 * Paranaca( 90) Kruskal-Wallis: 3.1417 df: 4 Probability: 0.5344 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *====================================*==================================* 2 *=======================M==================================3------------U 3 *



94

4 * 5 * Scirtida( 91) Kruskal-Wallis: 3.9000 df: 4 Probability: 0.4197 0.000 0.2500 0.5000 0.7500 1.000 GRP +-----------------+-----------------+-----------------+-----------------+ 1 *=======================M==================================3------------U 2 *=======================M==================================3------------U 3 * 4 * 5 *

NB - L=lower limit; 1=Mean - 1 St.Dev; M=mean; D=Median; 3=Mean + 1 St.Dev; U=upper limit *=more than one symbol at print position



95

Appendix 4. Life-History Strategies of Fish and Crayfish Recorded from Study Area Fish

Three species of fish were recorded from Willowdale North and included the native western minnow and two introduced species; rainbow trout and mosquitofish. Western minnow Galaxias occidentalis During the current study, western minnows were only observed in the channelised sections of Ferraro (FB4) and Wealand (WB4) brooks, immediately west of South Western Highway. Western minnows are one of the most widely distributed endemic species in south-west Western Australia, with a range extending from Winchester, about 150km north of Perth, to Waychinicup Creek, 80km east of Albany (Allen et al. 2002). Within this area, the western minnow occurs in rivers, streams, lakes, pools, and it readily invades seasonal creeks and swamps connected to permanent water. It is often found at the base of waterfalls (and V-notch gauging weirs) where the water is fast flowing and well oxygenated. This may indicate a preference for these conditions, or reflect fish that are prevented from continued upstream movement by a physical barrier. Fish have been observed jumping through V-notch weirs and ‘crawling’ up wet rock faces in an attempt to traverse barriers (ARL 1990). Morgan (pers. comm.) suggests that western minnows maybe able to pass over barriers of up to ~20 cm height and are able to swim in water as shallow as 1 cm. The species likes both open water and enclosed areas amongst riparian vegetation and does not appear to have a strong preference for specific habitat or substrate types (Thorburn 1999). Terrestrial insects form a major component of the diet, although dipteran larvae and pupae, and microcrustacea (cladocera & copepods) are also consumed. Recent work suggests that the western minnow feeds at night on freshwater shrimp (Fairhurst unpub. dat., cited Morgan et al., 1998). A study of this species in the Collie River reported that at the end of the first year, males and females grow to approximately 70 and 75mm respectively, and 90 and 100mm at the end of their second year. They are sexually mature at the end of their first year, and some fish survive to spawn in the following year and a very limited number into a third, fourth and even a fifth year. Fish move upstream into tributaries (particularly seasonal creeks that start to flow) to spawn on flooded vegetation. This occurs between June and late September, with a peak in August when water temperatures start to increase. Females produce approximately 900 eggs, although fecundity increases with age. Watts et al. (1995) studied the genetic structure of the Western minnow in the Canning and North Dandalup River systems, and observed that populations on the Darling Scarp and Swan Coastal Plain were separate and non-mixing. It was suspected that scarp populations moved into tributary creeks on the scarp to breed, whilst coastal plain populations moved into drains and wetlands on the coastal plain.

Western pygmy perch (Edelia vittata)

In the current study, only a single juvenile perch was recorded from site UMD2 on Upper Mayfield Drain. However, the western pygmy perch, together with the western minnow, is known to be the most widely distributed endemic fish species in the south-west of Western Australia, with a range from Moore River, north of Perth, to Philipps River, east of Albany (Allen et al. 2002). This species is common in rivers, streams, and lakes, and readily re-invades seasonal wetlands via flood-ways and up seasonal creeks/drains. Western pygmy perch are often associated with riparian/emergent vegetation and rarely occur in open water. They feed primarily



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on small benthic invertebrates, especially dipteran larvae, ostracods, copepods and Trichoptera (caddisflies) larvae, but also terrestrial insects (Pen et al. 1993). During winter, western pygmy perch move from rivers into either adjacent flooded areas or tributary streams, and spawn between late winter and late spring (Pen & Potter 1991) or later (Shipway 1949) in flooded riparian vegetation (Pusey, unpublished data). Densities in main rivers fall sharply at the time of this movement and the habitats provided by winter flooding appear to be very important for spawning and growth of juveniles (Pen & Potter 1991). Spawning continues over a period of about five months throughout spring, when there is a decrease in rainfall and creek water levels decline. Western pygmy perch migrate into flooded plains adjacent to the main channels between mid winter and late spring to spawn (Pen & Potter 1991) where hatching of the eggs is temperature dependent, requiring a range of 16 - 22°C. The use of flood waters along the main channels of rivers rather than tributary streams ensures the success of this protracted spawning strategy. It may also reduce the pressure on food resources in tributary streams which are the main spawning habitat of Galaxias occidentalis and B. porosa (Pen & Potter 1991). Differences in spawning times and habitats, time of maximum feeding activity and the differential use of aquatic and terrestrial food resources amongst these three species probably reduce the probability of inter-specific competition. The species requires predictable winter/spring flooding to ensure breeding success and strong recruitment. Reduced flooding and low water levels in tributary streams may increase the probability of competition between this species and western minnows. Mosquitofish Gambusia holbrooki Mosquitofish were introduced under government authority to fresh waters around Perth in 1936 (Mees 1977) to control mosquitoes. Mosquitofish are now widespread and abundant in south-west streams and reservoirs (Morgan et al. 1998), dominating the fish fauna in lowland areas (Pusey et al. 1989). They are widely regarded as a pest in Australian waters (Myers 1975; Arthington and Lloyd 1989). Pusey et al. (1989) suggested that natural winter spates regularly reduce the population density of mosquitofish to low levels, thus permitting the coexistence of this exotic species and small indigenous species with similar habitat and dietary requirements. The breeding strategy of mosquitofish is extremely effective; they bear live young and out-compete native fish, especially in degraded systems and harass and nip the fins of other small fish. It is now widespread throughout all states, except Tasmania, and has been implicated in the decline of several small native species. Females can grow to approximately 6 cm in length and males around 3.5 cm. There is also evidence that mosquitofish are not as effective in mosquito control as are the native fish they displace. Mosquitofish are a declared noxious species in Western Australia and it is illegal to hold or translocate this fish. It is now widespread throughout all states, except Tasmania and has been implicated in the decline of several small native species. Where mosquitofish are abundant, the numbers of native fish (e.g. Western Minnow) are often greatly reduced. There is also evidence that mosquitofish are not as effective in mosquito control as are the native fish they displace. Mosquitofish are a declared noxious species in Western Australia and it is illegal to hold or translocate this fish.



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In other south-west river systems, breeding is known to take place during spring, summer and autumn, once water temperatures exceed 15 – 16°C. Preferred habitat is wetlands and wide, deep, slow flowing reaches of rivers. Freshwater Crayfish

Gilgies Cherax quinquecarinatus To date, most studies of gilgies have been either taxonomic or related to the potential for aquaculture. Little is understood of their general biology and ecology. Gilgies exploit almost the full range of freshwater environments, and can be found in habitats that range from semi-permanent swamps to deep rivers (Austin & Knott 1996). Gilgies tend to occur in the shallower pools and along the margins of larger pools. These crayfish have a well developed burrowing ability, digging short burrows under stones on the stream bed or in the banks along the margins (Shipway 1951). In this way, gilgies are able to withstand periods of low water level by retreating into burrows until flows return. However, soils within the burrows must remain moist. A study on the microhabitat characteristics of marron, gilgies and the introduced yabby within the Canning River system near Perth, determined that gilgies are more commonly found in areas with higher flow velocity and dissolved oxygen concentrations than marron, Cherax cainii (Lynas et al. IN PRESS). Decline in population numbers and breeding capacity of gilgies is the result of overfishing and land management practices that have resulted in degradation of water quality (eutrophication, salinisation, pesticide contamination) and loss of in-stream habitat (water abstraction, pool aggradation, de-snagging). Koonacs Cherax plebejus Koonacs, Cherax plebejus, have a more inland distribution throughout the south-west, extending into the wheatbelt. They are often found in seasonal rivers and swamps that dry up over the summer and also in ponded flood waters. They have a highly developed burrowing behaviour which allows them to avoid desiccation during dry periods, by digging down to groundwater. They build capped burrows, in which they mate and spawn before returning to the surface in autumn/winter once stream flows begin. Feeding and growth occurs during winter and early spring. Owing to the fact that koonacs are not widely exploited for aquaculture, little is known of their reproductive biology.



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Appendix 5. Hydrographs for Iluka Surface Water Gauging Stations

Hill Street - Long term rainfall and flow rates

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J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

1995 1996 1997 1998 1999 2000 2001 2002

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Hill Street - Long term trends in daily discharge

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Mullins - Long term daily discharge trends

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Mar

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May

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Jul-9

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Oct

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Jul-9

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Jul-9

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Mullins - Long term flow rates

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J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

1994 1995 1996 1997 1998 1999 2000

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Ferraro Brook - Long term rainfall and flow rates

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450000J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D

1995 1996 1997 1998 1999 2000 2001 2002

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Ferraro Brook - Long term trends in daily discharge

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(m3)

2001 - data incomplete - station not operating



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