Climate Change Impacts on Agricultural Weeds in Western Australia

Pub no. 11/059

www.rirdc.gov.au

11-059 Covers.indd 1 25/10/2011 2:44:38 PM 11-059 Covers.indd 2 25/10/2011 2:44:38 PM

Climate Change Impacts on Agricultural Weeds in Western Australia

by Pippa J Michael, Paul B Yeoh, Noboru Ota and John K Scott

October 2011

RIRDC Publication No. 11/059 RIRDC Project No. AWRC 08-85

ISBN 978-1-74254-243-0 ISSN 1440-6845

Climate change impacts on agricultural weeds in Western Australia Publication No. 11/059 Project No. AWRC 08-85

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Researcher Contact Details

Dr Pippa J Michael Curtin University, Private Mailbag 1, P.O. Northam, W.A. 6401, Australia

Phone: +61 8 9690 1444 Fax: +61 8 9690 1500 Email: [email protected]

In submitting this report, the researcher has agreed to RIRDC publishing this material in its edited form.

RIRDC Contact Details

Rural Industries Research and Development Corporation Level 2, 15 National Circuit BARTON ACT 2600

PO Box 4776 KINGSTON ACT 2604

Phone: 02 6271 4100 Fax: 02 6271 4199 Email: [email protected]. Web: http://www.rirdc.gov.au

Electronically published by RIRDC in October 2011 Print-on-demand by Union Offset Printing, Canberra at www.rirdc.gov.au or phone 1300 634 313

Foreword

Weeds cost Australian agriculture over $4 billion annually through factors such as yield loss and management costs. Although not quantified, the impact of weeds on natural ecosystems has also been recognised as a serious threat to biodiversity. Consequently there is a significant need to understand the factors that influence the distribution, spread and abundance of invasive weed species in agriculture, under both current and future environmental and management conditions.

This project focuses on the weed risk in relation to climate change in the Northern Agricultural Region (NAR) of Western Australia. The region was chosen because it is predicted to experience considerable environmental impact from climate change. It is also one of Australia’s highly productive agricultural regions, generating approximately $1 billion annually.

From a complete list of plant species present within the NAR and buffer zones, the top 20 priority weeds were chosen by an expert panel and put through a detailed weed risk assessment (WRA) based on the ability of weeds to grow in different climates.

The main priority for future research is to extend this study to include an assessment applicable to the whole cropping region of Western Australia.

This project was funded in Phase 1 of the National Weeds and Productivity Research Program, which was managed by the Australian Government Department of Agriculture, Fisheries and Forestry (DAFF) from 2008 to 2010. The Rural Industries Research and Development Corporation (RIRDC) is now publishing the final reports of these projects.

Phase 2 of the Program, which is funded to 30 June 2012 by the Australian Government, is being managed by RIRDC with the goal of reducing the impact of invasive weeds on farm and forestry productivity as well as on biodiversity. RIRDC is commissioning some 50 projects that both extends on the research undertaken in Phase 1 and moves into new areas. These reports will be published in the second half of 2012.

This report is an addition to RIRDC’s diverse range of over 2000 research publications which can be viewed and freely downloaded from our website www.rirdc.gov.au. Information on the Weeds Program is available online at www.rirdc.gov.au/weeds

Most of RIRDC’s publications are available for viewing, free downloading or purchasing online at www.rirdc.gov.au. Purchases can also be made by phoning 1300 634 313.

Craig Burns Acting Managing Director Rural Industries Research and Development Corporation

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Acknowledgments

The authors gratefully acknowledge the input of the following panel members during the prioritisation workshop: Andrew Reeves, Catherine Borger, Jon Dodd, Rod Randal, Sandy Lloyd (Department of Agriculture and Food Western Australia), David Minkey (Western Australian No-Tillage Farmers Association), Mechelle Owen (University of Western Australia) and Kelly Agar (Western Australian Department of Environment and Conservation). Thanks also to Catherine Borger and Andrea Schatral (Curtin University) for their assistance with the detailed weeds risk assessments.

Contents

Foreword ...... iii

Acknowledgments...... iv

Executive summary ...... vii

Introduction ...... 1

Objectives ...... 8

Methodology ...... 9

Results ...... 12

Implications...... 21

Recommendations ...... 23

Appendix: Weed species lists ...... 24

References ...... 33

Tables

Table 1. Shires used to define the Northern Agricultural Region, agricultural buffer and rangeland buffer ...... 2

Table 2. Surveys and databases used to collate a list of species present within the NAR and buffer zones ...... 9

Table 3. South Australian weed risk assessment guide management matrix (Virtue 2008) ...... 11

Table 4. Additional species included in the final ‘high risk agricultural weeds’ list ...... 14

Table 5. High risk agricultural weeds in the NAR. Species highlighted in yellow were deemed ‘too common’ for inclusion in the WRA...... 15

Table 6. Weed risk assessment category scores for top 20 ‘riskiest’ weeds ...... 19

Table 7. Comparative weed risk (CWR) and feasibility of containment (FOC) scores for the 20 riskiest weeds ...... 20

Figures

Figure 1. Shires included in the Northern Agricultural Region (NAR) of Western Australia, and shires designated as the agricultural buffer and the rangeland buffer ...... 3

Figure 2. Climate change projections for 2070 based on the ECHAM5/MPI-OM model, emissions scenario A1B and medium climate sensitivity (CSIRO 2009) ...... 4

Figure 3. Total rainfall and mean surface temperature change between 2010 and 2070 based on the ECHAM5/MPI-OM model, emissions scenario A1B and medium climate sensitivity (CSIRO 2009) .. 5

Figure 4. Map of the NAR indicating field locations from the summer (Michael et al. 2010) and GRDC weeds survey (Michael, unpublished) ...... 10

Figure 5. Flow chart showing the decision process for reduction of weed list (* indicates discrete species) ...... 13

Appendix tables

Appendix table 1. Agricultural weeds of high and medium weed risk present within the NAR and buffer zones ...... 25

Appendix table 2. Non-agricultural weeds of high and medium weed risk present within the NAR and buffer zones ...... 29

Executive summary

What the report is about

This project aimed to assess the impact of climate change on agricultural weed spread by building on the distribution data collected from field surveys of the NAR and neighbouring areas.

Based on the feasibility of containment scores generated by this report, it is possible to determine what course of action could be taken for control of the 20 riskiest weeds as in the NAR.

Where are the relevant industries located in Australia?

In the future, potentially large reductions in rainfall will reduce agricultural yields markedly. Experience has also shown that increased temperatures during the growing seasons of crops are likely to negatively affect yield. In such an eventuality, cropping will become more challenging at the current dry margins of regions with Mediterranean climate, such as south-west Australia, but may expand into areas currently generally too wet for regular cropping. A significant part of the challenge will be the weed regime, which will increase the level of stress faced by crops.

Aims/objectives

This project aimed to assess the impact of climate change on agricultural weed spread by building on the distribution data collected from field surveys of the NAR and neighbouring areas. The research objectives included:

• Applying a weed risk assessment (WRA) model to determine the relative weed threats posed by 20 high-priority species in the survey.

• Developing CLIMEX models for the five ‘riskiest’ species.

• A prediction of the distribution of each weed species in 2070 under an IPCC4 scenario relevant to Australia.

• Developing recommendations for adaptation responses to manage the changed weed threat.

Methods used

Several field surveys and databases were used to develop a complete list of plant species present within the NAR and buffer zones. Each species was then categorised according to its weed risk.

Weed risk assessments on the region’s 20 riskiest weeds were conducted using criteria based on the South Australian weed risk management guide, and a final five species were selected for CLIMEX modelling. The land use chosen for each WRA was a crop–pasture rotation within the NAR.

Results/key findings

Based on the feasibility of containment score, a course of action can be determined for control of each weed. For example, species that are currently widespread and difficult to control have a negligible rating, which suggests that containment is very unlikely and control should be based on ongoing

vii

management. Species which are not currently present within the NAR have a very high chance of containment; therefore, the course of action is to restrain the spread.

Implications for relevant stakeholdersr:

Recommendations

The main priority for future research is to extend this study to include an assessment applicable to the whole cropping region of Western Australia.

The risk assessments are based on the ability of weeds to grow in different climates. Each risk assessment could be augmented by overlays of the weed’s response to different soil types, agricultural practices and other non-climatic factors. However, research would be needed to establish the relevance of those factors to the growth and survival of each weed species.

viii

Introduction

Weeds cost Australian agriculture over $4 billion annually through factors such as yield loss and management costs (Sinden et al. 2004). Although not quantified, the impact of weeds on natural ecosystems has also been recognised as a serious threat to biodiversity. Consequently there is a significant need to understand the factors that influence the distribution, spread and abundance of invasive weed species in agriculture, under both current and future environmental and management conditions.

In the future, potentially large reductions in rainfall will reduce agricultural yields markedly (Stokes and Howden 2008). Experience has also shown that increased temperatures during the growing seasons of crops are likely to negatively affect yield (Battisti and Naylor 2009). In such an eventuality, cropping will become more challenging at the current dry margins of regions with Mediterranean climate, such as south-west Australia, but may expand into areas currently generally too wet for regular cropping (Stokes and Howden 2008). A significant part of the challenge will be the weed regime, which will increase the level of stress faced by crops.

The Northern Agricultural Region

The NAR is one of 56 natural resource management (NRM) regions identified by the Australian Government and state and territory governments based on catchments or bioregions. According to the Northern Agricultural Catchment Council (NACC), the coordinating body for the region, the NAR consists of approximately 7.5 million hectares, of which 70% has been developed for agricultural use, that is controlled by over 2000 landowners (>100 ha).

Currently, the defined boundary of the NAR is inconsistent between organisations such as the NACC, the Department of Agriculture and Food WA (DAFWA), Caring for Our Country and the National Action Plan for Salinity and Water Quality. In this study, we have used data from Caring for Our Country (www.nrm.gov.au/apps/projects/town-search.html) to determine the 14 shires located within the NAR (Table 1, Figure 1).

We also retained a buffer zone, which consisted of three rangeland and five agricultural shires, around the NAR. The buffer was included in our study to allow any potential neighbouring weed species to be included, especially as they may be species associated with climates potentially similar to future climates of the NAR.

Table 1. Shires used to define the Northern Agricultural Region, agricultural buffer and rangeland buffer Region Shire Main town Northern Agricultural Region Carnamah Carnamah Chapman Valley Nabawa Coorow Coorow Dalwallinu Dalwallinu Dandaragan Dandaragan Geraldton–Greenough Geraldton Irwin Dongara Mingenew Mingenew Moora Moora Morawa Morawa Mullewa Mullewa Northampton Northampton Perenjori Perenjori Three Springs Three Springs Agricultural buffer Koorda Koorda Mount Marshall Bencubbin Wongan–Ballidu Wongan Hills Gingin Gingin Victoria Plains Calingiri Rangeland buffer Murchison (no town) Shark Bay Denham Yalgoo Yalgoo

Figure 1. Shires included in the Northern Agricultural Region (NAR) of Western Australia, and shires designated as the agricultural buffer and the rangeland buffer

Climate change in the Northern Agricultural Region

The NAR has not been the subject of specific analyses for climate change, and is usually included in studies covering a wider area, such as of the south-west of Australia. Weather records show a decline in early winter rains by up to 30% in the NAR (Hope et al. 2006); early winter is the time of crop seedling establishment. The most recent relevant analysis (Van Ommen & Morgan 2010) indicates that the significant decline of rainfall observed in the south-west is an unusual event most likely related to anthropogenic climate change affecting the meridional circulation south of Australia. However, that study did not include weather stations in the NAR, the nearest being Avondale (Figure S1 in supplementary data from Van Ommen & Morgan 2010). Temperatures in the south-west have increased over the past 50 years, particularly in autumn and winter (IOCI 2002). The OzCLIM Echam5 moderate CO2 scenario (CSIRO 2009) (Figure 2, Figure 3) illustrates the type of change expected by 2070. This model predicts temperature increases of 2.5°C in summer and 1.7°C in winter, and rainfall decreases of 5 mm (16%) in summer and 40 mm (23%) in winter.

A. Change in total winter rainfall (mm) by 2070 B. Change in total summer rainfall (mm) by 2070

C. Change in winter mean surface temperature D. Change in summer mean surface temperature (°C) by 2070 (°C) by 2070

Figure 2. Climate change projections for 2070 based on the ECHAM5/MPI-OM model, emissions scenario A1B and medium climate sensitivity (CSIRO 2009)

A. Summer total rainfall change (mm) between B. Winter total rainfall change (mm) between 2010 2010 and 2070 and 2070

C. Summer mean surface temperature change (°C) D. Winter mean surface temperature change (°C) between 2010 and 2070 between 2010 and 2070

Figure 3. Total rainfall and mean surface temperature change between 2010 and 2070 based on the ECHAM5/MPI-OM model, emissions scenario A1B and medium climate sensitivity (CSIRO 2009)

Selection of priority weeds from the Northern Agricultural Region

When confronted with a large number of detrimental weed species but with limited time and resources, there is a vital need for researchers to use a prioritisation system to make informed decisions on which weeds to investigate. Approaches such as that of Bebawi et al. (2002) and the Weeds of National Significance (WONS) (Thorp and Lynch 2000) have used input from stakeholder groups in order to shortlist large numbers of weeds and produce a reduced list that can be assessed in detail. In the case of Bebawi et al. (2002), an initial list of 246 weeds from the wet and dry tropics was reduced to a more manageable list of 50 weed species using a classification scoring system for priority: high (1.0), high/medium (0.75), medium (0.5), medium/low (0.25) and low (0.125). The scores produced by stakeholder groups were collated for each species, and the top 50 weeds proceeded to the next assessment stage. The WONS process involved each state or territory government nominating priority weeds through a series of workshops: a final list of 71 was assessed as potential WONS candidates (Thorp and Lynch 2000).

The next step in the prioritisation process is to quantitatively assess each weed from the shortlist in detail using a weed risk assessment (WRA) model. WRA is a decision support tool that uses standard, technical criteria to predict whether or not a plant species will become invasive. It compares the species invasiveness with the likely impacts of an invasion. WRA can not only be used to predict new weeds within a particular area, but can also enable researchers to prioritise control programs for existing weed species. Several models developed in Australia enable the ranking of existing weed species and the assessment of new potential weeds within a specific area, including:

• WONS (http://www.weeds.org.au/docs/WONS) • New South Wales Weed Risk Management System (http://www.dpi.nsw.gov.au/agriculture/pests-weeds/weeds/wrm-system) • South Australian weed risk management guide (http://www.dwlbc.sa.gov.au/assets/files/SA_Weed_Risk_Management_Guide.pdf) • Northern Territory WRA system (http://www.nt.gov.au/nreta/natres/weeds/risk/index.html) • Victorian WRA method (http://www.dpi.vic.gov.au/dpi/vro/vrosite.nsf/pages/lwm_pest_plants) • Future Farm Industries CRC Environmental Weed Risk Assessment Protocol (http://www.futurefarmcrc.com.au/weed_risks.html). These models are consistent with the National Post-Border Weed Risk Management Protocol (Virtue et al. 2006). They are also generally similar to one another, allowing comparability of individual species assessments. The Australian WRA process has been trialled in various countries and found to be widely suitable.

Our study used the 2008 South Australian weed risk management guide developed by the Animal and Plant Control Commission, in conjunction with the Animal and Plant Control Boards (Virtue 2008). The South Australian cropping system is climatically the most similar to that of the south-west of Australia and for that reason we considered that the guide was the most appropriate to use for weeds of the NAR. The guide uses a series of questions to determine the invasiveness, impact and potential distribution of a species, which are in turn multiplied to give a comparative weed risk from 0 to 1000. Invasiveness indicates the rate of spread, impacts determine the potential impact the weed has on economic, environmental and social factors, and potential distribution indicates the likely spread of the weed in the given land use. A feasibility of containment score is also determined from a series of questions combining the control cost, current distribution and persistence values of the species.

Control costs are the costs of detection, access and application, current distribution represents how prevalent the weed is, and persistence indicates the length of time required for weed eradication. Further details on each criterion are in the South Australian weed risk management guide (Virtue 2008). Once the comparative weed risk and feasibility of containment score are determined, a matrix is used to recommend a particular weed management action to undertake.

Our aim in selecting a priority list for the NAR was to develop a comprehensive list of weed species present within the NAR based on all known plant species in the region, and then to use a priority- based approach similar to Bebawi et al. (2002) to produce a shortlist that can be assessed by an expert panel. The top 20 priority weeds chosen by the panel were then subjected to a detailed WRA using criteria based on the South Australian weed risk management guide (Virtue 2008), and a final five species were selected for CLIMEX modelling. This comprehensive approach was thus designed to be independent of the authors’ knowledge or interests and to include information from as many sources as possible.

Objectives

1. Applying a WRA model to determine the relative weed threats posed by 20 high-priority species in the survey.

2. Developing CLIMEX models for the five ‘riskiest’ species.

3. A prediction of the distribution of each weed species in 2070 under an IPCC4 scenario relevant to Australia.

4. Developing recommendations for adaptation responses to manage the changed weed threat.

With these objectives, this project is consistent with both the Australian Weeds Strategy objectives 1.4.1 and 1.2.6, and regional strategies through ARWA regional plans for the NAR.

Methodology

Collation of plant species list

Several field surveys and databases produced by the Western Australian Department of Environment and Conservation (DEC), Curtin University (Curtin) and DAFWA (Table 2; Figure 4) were used to develop a complete list of plant species present within the NAR and buffer zones. Each species was then categorised according to its weed risk (high, medium or low) using criteria from Groves et al. (2003), Randall (2007) or a weed expert. If the species was not recorded by either source or was deemed a low risk, it was excluded from the assessment process (Figure 5). Species were then categorised into primarily agricultural or natural system weeds using criteria from Groves et al. (2003) or a weed expert. Additional information was documented for each species, including common name, family, whether the species was native or naturalised to Western Australia, life cycle and reproductive type using relevant literature sources such as Hussey et al. (2007), Groves et al. (2003), Randall (2007) and FloraBase (Western Australian Herbarium 2009).

Table 2. Surveys and databases used to collate a list of species present within the NAR and buffer zones Survey/database Sites Organisation Land use Reference 1 Wetland vegetation DEC aquatic (Lyons et al. 2004) 2 Terrestrial plant survey DEC terrestrial (Gibson et al. 2004) 3 NatureMap DEC terrestrial (DEC 2007) 4 Summer weeds survey 41 Curtin & DAFWA agricultural (Michael et al. 2010) 5 Field survey 461 Curtin & DAFWA agricultural (Michael, unpublished)

Figure 4. Map of the NAR indicating field locations from the summer (Michael et al. 2010) and GRDC weeds survey (Michael, unpublished)

Workshop to determine priority weed species

A one-day workshop was held on 7 August 2009 to assess and rank the list of high and medium risk agricultural and non-agricultural weeds within the NAR and surrounding buffer zones. The ranking was undertaken by an 11-member weed expert panel comprising researchers and extension staff from DAFWA, the Western Australian No-Tillage Farmers Association, CSIRO, the University of Western Australia, Curtin University and DEC. Panel members were first asked to examine the ‘medium risk agricultural weeds’ and ‘non-agricultural weeds’ lists and indicate whether they thought any of those species should be elevated to the ‘high risk agricultural weeds’ list used for final assessment. Members then scored their 20 priority weed species from the final ‘high risk agricultural weeds’ list using either a number from 1 to 20 (1 being highest priority) or a general rating (high, medium or low priority). Ratings were converted to numbers such that high = 1, medium = 2, low = 3. All weeds nominated as top 20 weeds were tallied to see which were of most interest to the group. Nominations for top 20 weeds were also used to produce an average weed risk score and a top weed risk index score.

Each member then rated every species with a current and future severity score of 0 to 5 (0 = no impact, 5 = highest severity). The future severity was based on a climate change scenario using the OzCLIM Echam5 moderate CO2 model (CSIRO 2009) for the NAR, which predicts a temperature increase of 2.5°C in summer and 1.7°C in winter, and a rainfall decrease of 5 mm (16%) in summer

and 40 mm (23%) in winter. If a member did not have expertise in a particular weed, they were asked to leave the score blank. Species were ranked using the average future severity score to determine the 20 ‘riskiest’ weeds under the climate change scenario. Discussions were then held as to whether the nominated weeds were priority weeds within agricultural systems in the NAR. For example, a species was removed from consideration if its life cycle made it unlikely to be a weed under current agricultural practices (for example, trees). Weed species were also removed if they were considered currently too widespread and abundant, so that the effect of climate change was unlikely to significantly affect the weed or its management. The final list of 20 riskiest weeds was endorsed by the panel at the conclusion of the workshop.

Weed risk assessment on 20 riskiest weeds

Detailed WRAs were conducted on each of the 20 selected species using the 2008 South Australian weed risk management guide (Virtue 2008). The land use chosen for each WRA was a crop–pasture rotation within the NAR. Management for crops was assumed to be pre-sowing cultivation or knockdown herbicide, pre-emergent spraying at sowing for grasses and broadleaf weeds, and one post-emergent grass/broadleaf spray. No herbicides were assumed to be used in the pasture phase.

Information used to complete each WRA was sourced from a wide variety of sources, including databases such as ISI Web of Knowledge, JSTOR, Agricola, Biological Abstracts and CAB abstracts. If reputable peer-reviewed publications were limited, more general sources were used, such as textbooks (Hussey et al. 2007; Parsons & Cuthbertson 2001), government technical notes (AgMemo, E-weed) and websites (Florabase 2009; AVH 2009). Once all available information was collated for a particular species, a group discussion (Michael, Scott, Yeoh and, if available, a weed expert who had researched the weed in question) was held to review and score each question. Input from additional weed experts and NAR landowners was also incorporated in the discussion. Any questions which were unable to be answered were entered as ‘Don’t know’. This equated to ‘0’ for the comparative weed risk scoring and the maximum mark for feasibility of containment scoring. A final comparative weed risk (CWR) and feasibility of containment (FOC) score was then produced for each species. These scores were used to select one of nine recommended weed management strategies by means of a management matrix developed by Virtue (2008).

Table 3. South Australian weed risk assessment guide management matrix (Virtue 2008) Feasibility of containment Negligible Low Medium High Very high > 113 > 56 > 31 > 14 < 14

Negligible Limited action Limited action Limited action Limited action Monitor < 13

Low Limited action Limited action Limited action Monitor Monitor < 39 isk r Medium Manage sites Manage sites Manage sites Protect sites Contain spread < 101

Weed Weed Destroy High Manage weed Manage weed Protect sites Contain spread infestations < 192 Alert Protect sites & Destroy Very high Manage weed Contain spread Eradicate manage weed infestations > 192

Results

Plant species list and priority weed species of the NAR

A total of 5536 discrete plant species were recorded within the NAR and buffer zones, from an initial collation of 7636 species generated from three main sources (Figure 5). Of those, 54 high risk agricultural weeds, 58 medium risk agricultural weeds (Appendix table 1) and 99 high/medium non-agricultural weeds (Appendix table 2) were identified using criteria from Groves et al. (2003), Randall (2007) or a weed expert. The species on the shortlist of 211 high and medium risk agricultural and non-agricultural weed species were investigated during the prioritisation workshop.

Panel members nominated 11 medium risk agricultural weeds and 17 non-agricultural weeds for inclusion on the high risk agricultural weeds list. A further three species not on any list were also nominated: Chloris truncata, Oncosiphon piluliferum and Oncosiphon suffruticosum. After discussion, all additional 31 species (Table 4) were elevated to the high risk agricultural weeds list, so that 85 species were examined (Table 5).

A total of 50 weed species were nominated at least once as ‘top 20 weeds’; however, 19 species were subsequently removed from consideration because they were deemed already too widespread and abundant and thus not priority weeds for this study (for example, Lolium rigidum and Avena fatua). Of the remaining weeds, the five species considered by the panel to currently have the most severe impact on agricultural systems within the NAR were Carthamus lanatus (3.0), Echium plantagineum (2.9), Rapistrum rugosum (2.8), Cucumis myriocarpus (2.7) and Hordeum marinum (2.7). Under the predicted climate change scenario, the five species considered to potentially have the most severe future impact on agricultural systems within the NAR were Chloris truncata (4.0), Asphodelus fistulosus (3.8), Solanum hoplopetalum (3.6), Carthamus lanatus (3.5) and Tribulus terrestris (3.5). The five weed species thought likely to experience the greatest increase in severity were Oncosiphon piluliferum (1.8), Chloris truncata (1.7), Oncosiphon suffruticosum (1.7), Xanthium spinosum (1.6) and Asphodelus fistulosus (1.5).

No information (6738)

Species recorded in Weed expert/Randall Gibson et al. (2004) assess as not risky (199) (2609) Natives NOT in Groves BUT in Randall (170) Weed expert/Randall assess as risky (13)

Exotics NOT in Groves *High risk BUT in Randall (42) Species recorded in agricultural weeds NatureBase (4889) Groves: high risk (4+5) (159) (54)

*Medium risk All plants recorded in Groves: medium risk (2+3) (169) Groves (548) agricultural weeds (58) 13

Groves: low risk (0+1) (313) *High+medium risk non-agricultural All plants recorded in weeds (99) Groves (93) Weed expert: not risky (0)

Species recorded in Not in Groves BUT agricultural surveys deemed as risky by (138) farmer survey/Randall (9) Weed expert: risky (9)

Not in Groves OR farmer survey OR Randall (36)

Figure 5. Flow chart showing the decision process for reduction of weed list (* indicates discrete species)

Table 4. Additional species included in the final ‘high risk agricultural weeds’ list Nomin- Primarily Species Common name Native Initial risk ations agricultural? 1 Acetosa vesicaria rosy dock high no 1 Argemone ochroleuca Mexican poppy high no 2 Asphodelus fistulosus Onion weed high no 1 Boerhavia coccinea Tarvine Native medium yes 10 Brassica tournefortii wild turnip high no 8 Bromus diandrus Great brome high no 4 Bromus hordeaceus soft brome high no 6 Bromus rubens red brome high no 3 Carrichtera annua Ward’s weed high no 3 Cenchrus ciliaris buffel grass medium no 1 Chloris truncata windmill grass Native n/a n/a 8 Conyza bonariensis flaxleaf fleabane high no 1 Emex spinosa lesser jack medium no 3 Eragrostis curvula African lovegrass high no 3 Helianthus annuus sunflower medium yes 1 Hordeum glaucum northern barley grass medium no 7 Hordeum leporinum barley grass medium yes 2 Hordeum marinum sea barley grass medium yes 1 Lactuca serriola prickly lettuce medium yes 5 Lupinus cosentinii blue lupin high no 7 Malva parviflora marshmallow high no 4 Mesembryanthemum crystallinum iceplant medium no 1 Oncosiphon piluliferum matricaria n/a n/a 1 Oncosiphon suffruiticosum Calomba daisy n/a n/a 2 Solanum elaeagnifolium silverleaf nightshade medium yes 7 Solanum hoplopetalum Afghan thistle Native medium yes 5 Tribulus terrestris caltrop medium yes 1 Verbesina encelioides crown beard medium yes 5 Vulpia bromoides squirrel tail fescue medium yes 3 Vulpia muralis wall fescue medium yes 4 Vulpia myuros rat’s tail fescue high no

Table 5. High risk agricultural weeds in the NAR. Species highlighted in yellow were deemed ‘too common’ for inclusion in the WRA. Weed risk Top weed Current severity Future severity Change Common name Nominations Score Species Family risk index in (n = native) (top 20 weed) Av. Av. Av. (1–20) score Response Response severity (0–5) (0–5) Chloris truncata Poaceae windmill grass (n) 4 11.6 4.2 2.3 3 4.0 3 1.7 Asphodelus fistulosus Asphodelaceae onion weed 3 10.2 2.8 2.0 5 3.8 4 1.5 Solanum hoplopetalum Solanaceae Afghan thistle (n) 6 9.3 5.0 2.5 9 3.6 8 1.0 Carthamus lanatus Asteraceae saffron thistle 6 8.8 4.8 3.0 8 3.5 8 0.5 Tribulus terrestris Zygophyllaceae caltrop 4 8.8 3.2 2.4 8 3.5 7 0.9 Chondrilla juncea Asteraceae skeleton weed 7 9.4 6.0 2.0 7 3.4 7 1.4 Conyza bonariensis Asteraceae flaxleaf fleabane 5 15.0 6.8 2.1 7 3.3 6 1.3 Cucumis myriocarpus Cucurbitaceae prickly paddy melon 10 6.5 5.9 2.7 9 3.3 9 0.6 Hordeum marinum Poaceae sea barley 2 9.5 1.7 2.7 3 3.3 3 0.7 Oncosiphon suffruiticosum Asteraceae Calomba daisy 1 8.0 0.7 1.3 4 3.3 3 1.7

15 Rapistrum rugosum Brassicaceae turnipweed 8 9.7 7.0 2.8 9 3.3 9 0.6

Polygonum aviculare Polygonaceae wireweed 7 6.0 3.8 2.3 9 3.3 9 0.9 Citrullus lanatus Cucurbitaceae Afghan melon 10 7.2 6.5 2.6 10 3.3 10 0.7 Oncosiphon piluliferum Asteraceae matricaria 5 9.5 4.3 1.5 4 3.3 4 1.8 Echium plantagineum Boraginaceae Paterson’s curse 6 9.2 5.0 2.9 7 3.2 6 0.4 Acetosa vesicaria Polygonaceae rosy dock 3 11.2 3.0 1.7 5 3.0 5 1.3 Carrichtera annua Brassicaceae Ward’s weed 1 14.5 1.3 1.6 4 3.0 3 1.0 Mesembryanthemum crystallinum Aizoaceae iceplant 6 8.8 4.8 2.3 6 2.9 4 1.0 Cenchrus ciliaris Poaceae buffel grass 1 14.0 1.3 2.0 5 2.7 5 0.7 Heliotropium europaeum Boraginaceae common heliotrope 3 6.8 1.9 1.7 7 2.6 7 0.9 Eragrostis cilianensis Poaceae stinkgrass none 0.0 1.9 4 2.6 4 0.8 Lupinus cosentinii Fabaceae blue lupin none 0.0 2.5 7 2.5 4 0.3 Amaranthus albus Amaranthaceae tumbleweed none 0.0 1.8 6 2.5 6 0.7 Malva parviflora Malvaceae marshmallow 4 10.5 3.8 2.1 9 2.4 8 0.4 Sisymbrium orientale Brassicaceae Indian hedge mustard 1 1.0 0.1 2.3 7 2.4 7 0.1 Verbesina encelioides Asteraceae crown beard 1 13.0 1.2 2.3 3 2.3 3 0.0

Weed risk Top weed Current severity Future severity Change Common name Nominations Score Species Family risk index in (n = native) (top 20 weed) Av. Av. Av. (1–20) score Response Response severity (0–5) (0–5) Cirsium vulgare Asteraceae spear thistle none 0.0 2.1 7 2.3 7 0.1 Emex spinosa Polygonaceae lesser jack 3 5.0 1.4 1.2 6 2.2 5 1.0 Xanthium spinosum Asteraceae Bathurst burr 3 8.3 2.3 0.6 5 2.2 5 1.6 Pennisetum clandestinum Poaceae kikuyu grass 1 2.0 0.2 1.6 6 2.0 6 0.4 Sisymbrium irio Brassicaceae London rocket 2 9.3 1.7 1.9 8 2.0 8 0.1 Amaranthus powellii Amaranthaceae Powell’s amaranth none 0.0 2.0 3 2.0 3 0.0 Amaranthus viridis Amaranthaceae green amaranth none 0.0 2.0 3 2.0 3 0.0 Avena sterilis Poaceae sterile oat none 0.0 1.7 3 2.0 3 0.3 Bromus hordeaceus Poaceae soft brome none 0.0 2.3 6 2.0 4 0.3 Carduus pycnocephalus Asteraceae slender thistle none 0.0 2.1 7 2.0 7 -0.1 Cirsium arvense Asteraceae Canada thistle none 0.0 1.5 2 2.0 2 0.5

16 Stachys arvensis Lamiaceae staggerweed none 0.0 1.8 3 2.0 3 0.2

Helianthus annuus Asteraceae sunflower 1 4.0 0.4 1.4 7 1.8 6 0.3 Sinapis alba Brassicaceae white mustard none 0.0 1.8 3 1.8 3 0.0 Juncus bufonius Juncaceae toadrush none 0.0 1.9 6 1.7 6 -0.3 Lactuca serriola Asteraceae prickly lettuce 1 2.0 0.2 1.3 7 1.7 6 0.3 Onopordum acaulon Asteraceae stemless onopordon none 0.0 0.8 5 1.6 5 0.8 Solanum elaeagnifolium Solanaceae silverleaf nightshade 1 18.5 1.7 1.4 4 1.5 3 0.0 Carduus tenuiflorus Asteraceae sheep thistle 1 10.0 0.9 1.7 6 1.5 6 -0.2 Euphorbia hirta Euphorbiaceae asthma plant none 0.0 0.3 3 1.5 2 1.0 Spergula arvensis Caryophyllaceae corn spurrey none 0.0 1.0 4 1.5 4 0.5 Moraea miniata Iridaceae two-leaf cape tulip 1 2.0 0.2 1.7 8 1.4 8 -0.3 Chenopodium album Chenopodiaceae fat hen none 0.0 1.6 7 1.4 7 -0.1 Rumex conglomeratus Polygonaceae clustered dock none 0.0 1.4 4 1.4 4 0.0 Sinapis arvensis Brassicaceae charlock none 0.0 1.3 3 1.3 3 0.0 Anagallis arvensis Primulaceae pimpernel 1 11.5 1.0 1.1 5 1.2 5 0.1 Acetosella vulgaris Polygonaceae sorrel none 0.0 1.2 5 1.0 5 -0.2

Weed risk Top weed Current severity Future severity Change Common name Nominations Score Species Family risk index in (n = native) (top 20 weed) Av. Av. Av. (1–20) score Response Response severity (0–5) (0–5) Buglossoides arvensis Boraginaceae corn gromwell none 0.0 1.0 3 1.0 3 0.0 Digitaria sanguinalis Poaceae crab grass none 0.0 1.0 4 1.0 4 0.0 Polygonum bellardii Polygonaceae none 0.0 1.0 1 1.0 1 0.0 Salvia reflexa Lamiaceae mintweed none 0.0 1.0 6 1.0 5 -0.2 Oxalis corniculata Oxalidaceae yellow wood sorrel none 0.0 1.1 5 0.9 5 -0.2 Boerhavia coccinea Nyctaginaceae tarvine (n) none 0.0 0.9 4 0.8 3 0.0 Cyperus brevifolius Cyperaceae kyllinga weed none 0.0 0.5 4 0.8 4 0.3 Alopecurus geniculatus Poaceae marsh foxtail none 0.0 0.3 3 0.7 3 0.3 Alopecurus pratensis Poaceae meadow foxtail none 0.0 0.3 3 0.7 3 0.3 Ammi majus Apiaceae Bishop’s weed none 0.0 0.7 3 0.7 3 0.0 Hypericum perforatum Clusiaceae St John’s wort none 0.0 0.7 6 0.7 6 0.0

17 Mentha pulegium Lamiaceae pennyroyal none 0.0 1.0 5 0.6 5 -0.4

Plantago major Plantaginaceae greater plantain none 0.0 0.4 4 0.4 4 0.0 Lolium rigidum Poaceae annual ryegrass 6 10.3 5.6 4.6 10 4.7 10 0.1 Raphanus raphanistrum Brassicaceae wild radish 7 11.9 7.5 4.6 10 4.5 10 -0.1 Bromus diandrus Poaceae great brome 5 6.3 2.9 3.4 8 4.3 7 0.8 Avena fatua Poaceae wild oat 6 11.3 6.1 3.6 10 4.0 10 0.4 Emex australis Polygonaceae doublegee 10 7.0 6.3 3.7 9 3.9 9 0.3 Hordeum leporinum Poaceae barley grass 6 8.3 4.5 3.3 10 3.8 9 0.7 Lupinus angustifolius Fabaceae narrowleaf lupin 1 3.0 0.3 3.5 6 3.6 6 0.1 Vulpia bromoides Poaceae squirrel tail fescue none 0.0 2.6 7 3.5 5 1.2 Brassica tournefortii Brassicaceae wild turnip 7 10.0 6.4 2.9 9 3.3 8 0.3 Arctotheca calendula Asteraceae capeweed 5 7.4 3.4 3.1 10 3.0 10 -0.1 Bromus rubens Poaceae red brome none 0.0 2.4 5 2.7 3 0.7 Hordeum glaucum Poaceae northern barley grass 1 12.0 1.1 2.0 4 2.6 4 0.6 Vulpia myuros Poaceae rat’s tail fescue 2 5.5 1.0 2.1 5 2.5 2 0.5 Dittrichia graveolens Asteraceae stinkwort 1 1.0 0.1 1.8 8 2.3 8 0.6

Weed risk Top weed Current severity Future severity Change Common name Nominations Score Species Family risk index in (n = native) (top 20 weed) Av. Av. Av. (1–20) score Response Response severity (0–5) (0–5) Acacia farnesiana Fabaceae mimosa bush 1 12.0 1.1 1.1 5 2.0 4 0.9 Vulpia muralis Poaceae wall fescue 1 9.0 0.8 2.3 4 2.0 2 0.5 Eragrostis curvula Poaceae African lovegrass 2 17.5 3.2 1.9 8 1.9 7 -0.1 Argemone ochroleuca Papaveraceae Mexican poppy 1 10.5 1.0 0.9 5 1.6 4 0.5 Sorghum halepense Poaceae Johnson grass 1 1.0 0.1 0.6 5 1.3 5 0.7 182 8.9 146.5 2.1 490 2.5 453 0.4 18

Table 6. Weed risk assessment category scores for top 20 ‘riskiest’ weeds Comparative Feasibility of Potential Current Species Invasiveness Impacts Control costs Persistence weed risk containment distribution distribution Don’t knows Don’t knows Acetosa vesicaria 5.3 1.6 4.0 3.3 1.7 6.4 0 0 Asphodelus fistulosus 4.7 3.2 4.0 3.3 0.4 6.4 1 1 Carrichtera annua 5.3 1.6 4.0 4.0 0.0 5.5 1 0 Carthamus lanatus 7.3 4.2 8.0 2.7 0.9 6.4 3 0 Cenchrus ciliaris 9.3 2.6 8.0 6.7 2.5 8.2 0 0 Chloris truncata 6.0 2.6 6.0 5.3 0.9 6.4 3 0 Chondrilla juncea 6.7 2.6 8.0 7.3 0.9 8.2 0 0 Citrullus lanatus 5.3 4.7 8.0 4.7 6.7 7.3 0 0 Conyza bonariensis 8.0 3.2 8.0 5.3 0.9 7.3 0 0 Cucumis myriocarpus 5.3 4.2 8.0 5.3 6.7 6.4 0 1 Echium plantagineum 6.7 2.6 6.0 6.0 5.0 6.4 0 0 19 Heliotropium europaeum 5.3 6.3 8.0 6.0 0.0 7.3 0 0

Hordeum marinum 5.3 1.6 4.0 5.3 1.3 4.5 4 0 Mesembryanthemum crystallinum 3.3 3.7 6.0 4.7 0.9 6.4 0 1 Oncosiphon piluliferum 6.7 1.6 8.0 4.7 0.0 6.4 2 0 Oncosiphon suffruticosum 5.3 1.6 8.0 5.3 0.0 5.5 2 0 Polygonum aviculare 6.0 2.6 8.0 5.3 2.5 7.3 0 0 Rapistrum rugosum 6.0 4.2 8.0 4.0 0.9 7.3 1 0 Solanum hoplopetalum 6.0 3.7 6.0 8.0 2.1 7.3 1 0 Tribulus terrestris 5.3 5.8 8.0 5.3 2.5 6.4 0 0

The final list of the 20 riskiest weeds (Table 5 highlighted) was endorsed by the panel at the conclusion of the workshop. These species belong to 10 different families, with the Asteraceae (five species) and Poaceae (three species) families being the most common.

Weed risk assessments on 20 riskiest weeds

The WRA determined that, within crop–pasture rotation systems of the NAR, Cenchrus ciliaris (9.7) and Conyza bonariensis (8.0) were the most invasive species and Heliotropium europaeum (6.3) and Tribulus terrestris (5.8) had the greatest potential impact (Table 6). The likely future distribution of each species under climate change ranged from 40% to 80% of the area, and most weeds were suitable to inhabit 80% of the land use. Species with the highest control costs were Solanum hoplopetalum (8.0) and Chondrilla juncea (7.3). Citrullus lanatus (6.7) and Cucumis myriocarpus (6.7) were the most widespread weed species, invading between 60% and 80% of the current land use. The most persistent species were Cenchrus ciliaris (8.2) and Chondrilla juncea (8.2). Several species (Carthamus lanatus, Chloris truncata and Hordeum marinum) recorded three or more ‘Don’t know’ scores.

Weed species that obtained a ‘very high’ comparative weed risk (CWR) score were Heliotropium europaeum (269), Carthamus lanatus (247), Tribulus terrestris (247), Citrullus lanatus (202), Conyza bonariensis (202), Rapistrum rugosum (202) and Cenchrus ciliaris (196) (Table 7). Weed species with a ‘negligible’ feasibility of containment (FOC) score were Citrullus lanatus (226), Cucumis myriocarpus (226), Echium plantagineum (191), Cenchrus ciliaris (136) and Solanum hoplopetalum (121).

Fully detailed WRAs for the 20 riskiest weeds are available from the authors.

Table 7. Comparative weed risk (CWR) and feasibility of containment (FOC) scores for the 20 riskiest weeds Species CWR Rating FOC Rating Action

Acetosa vesicaria 34 Low 35 Medium Limited action Asphodelus fistulosus 59 Medium 9 Very high Contain spread Carrichtera annua 34 Low 1 Very high Monitor Carthamus lanatus 247 Very high 16 High Destroy infestations Cenchrus ciliaris 196 Very high 136 Negligible Manage weed Chloris truncata 95 Medium 31 Medium Protect sites Chondrilla juncea 140 High 55 Medium Protect sites Citrullus lanatus 202 Very high 226 Negligible Manage weed Conyza bonariensis 202 Very high 36 Medium Contain spread Cucumis myriocarpus 180 High 226 Negligible Manage weed Echium plantagineum 105 High 191 Negligible Manage weed Heliotropium europaeum 269 Very high 0 Very high Eradicate Hordeum marinum 34 Low 30 High Limited action Mesembryanthemum crystallinum 74 Medium 27 High Protect sites Oncosiphon piluliferum 84 Medium 1 Very high Contain spread Oncosiphon suffruticosum 67 Medium 1 Very high Contain spread Polygonum aviculare 126 High 97 Low Manage weed Rapistrum rugosum 202 Very high 27 High Destroy infestations Solanum hoplopetalum 133 High 121 Negligible Manage weed Tribulus terrestris 247 Very high 85 Low Protect sites & manage weeds

Implications

An extensive range of flora is present in the NAR and surrounding buffer shires—a total of 5536 distinct species were identified from this study. Using this initial inventory, we developed a shortlist of 211 priority weed species for the NAR, in both agricultural and non-agricultural situations. This process used standardised quantitative criteria from two reputable Australian weed databases: The introduced flora of Australia and its weed status (Randall 2007) and Weed categories for natural and agricultural ecosystem management (Groves et al. 2003). A workshop involving local weed expertise with knowledge of the NAR further reduced the priority list to 85 ‘high risk agricultural weeds’ and ranked them based on future weed risk under the OzCLIM Echam5 moderate CO2 climate change scenario (CSIRO 2009) to produce a final list of the top 20 ‘riskiest’ weeds for the NAR.

Other similar studies such as Bebawi et al. (2002) and the WONS process (Thorp and Lynch 2000) have relied heavily on stakeholder input in order to produce both an initial weed inventory and a shortlist. This dependency on ‘expert input’ may have negatively affected results, as the process was wholly reliant on the current knowledge of the stakeholders involved, whereas using published databases such as those above allowed transparency and reduced subjectivity in the weed selection process. We believe that using expert input only after a shortlist of species was produced using objective criteria greatly improved our prioritisation process, as most experts had knowledge of the large majority of weeds considered. Future weed prioritisations would benefit from the inclusion of similar methodology to subjectively select species for detailed WRAs.

Generally, very few Australian weeds have originated from the native flora (Michael 1994). However, the shortlist of 85 high risk agricultural weeds included several native Western Australian species, Solanum hoplopetalum, Chloris truncata and Boerhavia coccinea. These opportunistic species have spread beyond their native range and invaded agricultural fields.

The South Australian WRA model allowed the use of transparent and objective criteria to comprehensively assess the selected 20 weed species. This model is also consistent with the National Post-Border Weed Risk Management Protocol (Virtue et al. 2006) and will enable comparisons of individual species assessments.

Under a future climate change scenario of annual temperature increases of 1.7–2.5°C and rainfall decreases of 5 mm (16%) in summer and 40 mm (23%) in winter, it is expected that each of the 20 species selected for detailed WRAs would have a significant impact on the crop–pasture rotation systems of the NAR. However, some species produced higher weed risk scores than others under this scenario, such as Heliotropium europaeum, Tribulus terrestris and Carthamus lanatus. Heliotropium europaeum is a highly toxic and competitive summer-growing weed (Lanigan et al. 1978; Howell et al. 1991; Hill et al. 1997) that can produce almost 1.5 million seeds per square metre (Sheppard et al. 1996a). Tribulus terrestris is also a summer-growing weed and can produce up 16,500 spiny burrs per square metre (Boydston 1990), which are readily disseminated by animals or rubber-tyred vehicles (Squires 1979). Summer fallow weeds can significantly reduce subsequent winter crop yields; for example, T. terrestris causes a minimum of 10% yield penalty if not controlled during the fallow period (Fromm and Grieger 2002). Carthamus lanatus is a competitive winter annual with high seed longevity (Quinlivan and Peirce 1968) and has been estimated to cost Australian agriculture around $111 million per year (Grace et al. 2004). It is currently a declared weed of Western Australia, so any movement of plants or seeds is prohibited (DAFWA 2008).

Detailed WRAs of Acetosa vesicaria, Carrichtera annua and Hordeum marinum indicated that they would have a low weed risk in crop–pasture rotations in the NAR under the projected climate change scenario. However, these species are not typically agricultural weeds, so the WRA may have underestimated their potential impact. Acetosa vesicaria is a weed of native vegetation and rehabilitated minesites in semi-arid and arid regions of Australia (Marchant et al. 1987; Schatral and

Osborne 2006; Schatral et al. 2008). Carrichtera annua is predominantly a weed of disturbed native areas, although it can ‘crowd out’ pasture species (Cunningham et al. 1992). Hordeum marinum is a little-known member of the Hordeum genus, which includes several widespread weedy species (for example, H. leporinum).

Based on the feasibility of containment score, we can determine what course of action could be taken for control of each weed. For example, species that are currently widespread and difficult to control, such as Citrullus lanatus and Cucumis myriocarpus, have a negligible rating, which suggests that containment is very unlikely and control should be based on ongoing management. Species such as Oncosiphon piluliferum and Heliotropium europaeum, which are not currently present within the NAR, have a very high chance of containment; therefore, the course of action is to restrain the spread.

Selection of five weed species for CLIMEX modelling

Due to project constraints, only five species could be selected for CLIMEX modelling. Although we were restricted to selecting species based on seed availability, we also wanted to study a diverse range of weed types. Therefore, we chose Chloris truncata (stoloniferous perennial grass), Conyza bonariensis (annual herb with limited or no seed dormancy), Citrullus lanatus (annual summer- growing fleshy-fruited climber), Rapistrum rugosum (annual winter-growing herb) and Solanum hoplopetalum (clonal perennial herb).

Recommendations

Priorities for future research include the following.

1. This report focuses on the Northern Agricultural Region of south-west Australia and developed methodologies for determining weed risk under future climates. The main priority for future research is to extend this study to include an assessment applicable to the whole cropping region of Western Australia.

2. The risk assessments are based on the ability of weeds to grow in different climates. Each risk assessment could be augmented by overlays of the weed’s response to different soil types, agricultural practices and other non-climatic factors. However, research would be needed to establish the relevance of those factors to the growth and survival of each weed species.

Appendix: Weed species lists

Appendix table 1. Agricultural weeds of high and medium weed risk present within the NAR and buffer zones Ag Range Species Common name Family NAR Risk Lifecycle Reproduction buffer buffer Acacia farnesiana (L.) Willd. mimosa bush Fabaceae notfound notfound Low High tree Acetosella vulgaris Fourr. sorrel Polygonaceae notfound Med notfound High perennial herb Fl Jun-Dec Adonis microcarpa DC. pheasants eye Ranunculaceae notfound Med notfound Med annual herb Fl Aug-Oct Aerva javanica (Burm.f.) Schult. kapok bush Amaranthaceae notfound notfound Low Med perennial herb Fl Jan-Oct Alopecurus geniculatus L. marsh foxtail Poaceae Low notfound Low High perennial grass Fl Aug-Sep Alopecurus pratensis L. meadow foxtail Poaceae notfound notfound Low High perennial grass Fl Sep-Dec Amaranthus albus L. tumbleweed Amaranthaceae Med notfound notfound High annual herb Fl Dec-May Amaranthus mitchellii Benth. boggabri weed (n) Amaranthaceae notfound notfound Med Med annual herb Fl May Amaranthus powellii S.Watson Powell’s amaranth Amaranthaceae notfound notfound Low High annual herb Fl Feb-Mar Amaranthus viridis L. green amaranth Amaranthaceae Med notfound notfound High annual Fl Nov-Jun, monoecious Ambrosia psilostachya DC. perennial ragweed Asteraceae notfound Med notfound Med perennial herb Fl Feb-May, rhizomes Ammi majus L. Bishop’s weed Apiaceae Low notfound notfound High annual/biennial herb Fl Oct-Dec Anagallis arvensis L. pimpernel Primulaceae High High High High annual herb Fl Feb-Dec 25 Arctotheca calendula (L.) Levyns capeweed Asteraceae High High Med High annual herb Fl Aug-Nov

Asparagus officinalis L. asparagus Asparagaceae notfound Med notfound Med perennial herb Fl Oct-Jan, rhizomes, tuberous Avena fatua L. wild oat Poaceae High High Low High annual grass Fl Aug-Dec Avena sterilis L. sterile oat Poaceae Med notfound Low High annual grass Fl Jul-Oct Bartsia trixago L. Scrophulariaceae High Med notfound Med annual herb Fl Sep-Jan Boerhavia coccinea Mill. tarvine (n) Nyctaginaceae Med Med High Med annual/perennial herb Fl Jan-Dec Brassica napus L. volunteer canola Brassicaceae Med High notfound Med annual/biennial herb Fl Aug-Sep Buglossoides arvensis (L.) I.M.Johnst. corn gromwell Boraginaceae Med notfound notfound High annual herb Flv Jul-No Capsella bursa-pastoris (L.) Medik. Sheppard’s purse Brassicaceae Med notfound notfound Med annual herb Fl Jul-Nov Carduus pycnocephalus L. slender thistle Asteraceae notfound Med notfound High annual herb Fl Oct-Dec Carduus tenuiflorus Curtis sheep thistle Asteraceae notfound Med notfound High annual/biennial herb Fl Sep-Nov Carthamus lanatus L. saffron thistle Asteraceae High Med notfound High annual herb Fl Dec-Apr Cenchrus echinatus L. Walkaway burr Poaceae High Med Low Med annual/perennial Fl Jan-Aug rhizomous Chenopodium album L. fat hen Chenopodiaceae Med Med Low High annual herb Fl Mar-Apr/Oct-Dec Chenopodium murale L. nettleleaf goosefoot Chenopodiaceae Med Med High Med annual herb Fl Apr-Dec Chondrilla juncea L. skeleton weed Asteraceae Med Med notfound High biennial/perennial herb Fl Oct-Feb, rhizomes

Ag Range Species Common name Family NAR Risk Lifecycle Reproduction buffer buffer Cirsium arvense (L.) Scop. Canada thistle Asteraceae Low notfound notfound High perennial herb rhizomous Cirsium vulgare (Savi) Ten. spear thistle Asteraceae notfound Med notfound High biennial herb Fl Jan-Dec Citrullus colocynthis (L.) Schrad. Cucurbitaceae Med High Low Med perennial herb/climber Fl Jan-Oct, tuberous Citrullus lanatus (Thunb.) Matsum. & Nakai Afghan melon Cucurbitaceae High notfound notfound High annual herb/climber Fl Jan-Dec Cotula australis (Spreng.) Hook.f. common cotula Asteraceae High Med notfound Med annual herb Fl Feb/May-Nov Crepis capillaris (L.) Wallr. smooth hawksbeard Asteraceae Med notfound notfound Med annual/biennial herb Fl Dec-Jan Cucumis myriocarpus Naudin prickly paddy melon Cucurbitaceae High High Low High annual herb Fl Jan-May Cyperus brevifolius (Rottb.) Hassk. kyllinga weed Cyperaceae notfound Med notfound High perennial sedge Fl Jan-Dec, rhizomous Cyperus rotundus L. nutgrass Cyperaceae Low Med notfound Med perennial sedge Fl Apr-Jul, rhizomous, tuberous Dactylis glomerata L. cocksfoot Poaceae notfound Med notfound Med perennial grass Fl Jan-Mar Dactyloctenium aegyptium (L.) Willd. button grass Poaceae High notfound notfound Med annual grass Fl Mar/Jul-Sep Datura inoxia Mill. Solanaceae Low notfound notfound Med annual herb Fl Dec-Aug Digitaria sanguinalis (L.) Scop. crab grass Poaceae notfound Med notfound High annual grass Fl Dec-May Diplotaxis muralis (L.) DC. wall rocket Brassicaceae Med notfound Low Med annual/biennial herb Fl Jan-Aug 26 Dittrichia graveolens (L.) Greuter stinkwort Asteraceae High Med notfound High annual herb Fl Jan-Nov

Echium plantagineum L. Paterson’s curse Boraginaceae High High Low High annual/biennial herb Fl Sep-Jan Emex australis Steinh. doublegee Polygonaceae High High High High annual herb Fl Jan-Dec Eragrostis cilianensis (All.) Janch. stinkgrass Poaceae Low Med notfound High annual herb Fl Nov-Jan/Apr-May Eremocarpus setiger (Hook.) Benth. doveweed Euphorbiaceae Med notfound notfound Med annual herb Euphorbia hirta L. asthma plant Euphorbiaceae Med notfound notfound High annual herb Fl Jan-Oct Euphorbia paralias L. sea spurge Euphorbiaceae notfound Med notfound Med perennial herb Fl Oct-Jun Festuca arundinacea Schreb. tall fescue Poaceae Low notfound notfound Med perennial grass rhizomous Foeniculum vulgare Mill. fennel Apiaceae notfound Med notfound Med perennial herb Fl Jul-Jan Gomphocarpus fruticosus (L.) W.T.Aiton narrowleaf cottonbush Asclepiadaceae notfound Med notfound Med perennial herb/shrub Fl Feb-Jul Helianthus annuus L. sunflower Asteraceae Med notfound Low Med annual herb Fl Aug-Apr Heliotropium europaeum L. common heliotrope Boraginaceae notfound notfound Low High annual herb Fl Jan-Dec Holcus lanatus L. Yorkshire fog Poaceae notfound Med notfound Med perennial grass Fl Oct-Mar/Aug Hordeum leporinum Link barley grass Poaceae High High Low Med annual grass Fl Sep-Oct Hordeum marinum Huds. Poaceae Med Med notfound Med annual grass Hypericum perforatum L. St John’s wort Clusiaceae notfound notfound Low High perennial herb Fl Nov-Dec

Ag Range Species Common name Family NAR Risk Lifecycle Reproduction buffer buffer Juncus bufonius L. toadrush Juncaceae High High High High annual herb Fl Sep-Jan Lactuca serriola L. prickly lettuce Asteraceae Med Med notfound Med annual/biennial herb Fl Oct-Feb Lamium amplexicaule L. deadnettle Lamiaceae Low notfound notfound Med annual herb Fl Aug-Oct Lolium multiflorum Lam. Italian ryegrass Poaceae Low Med notfound Med annual/perennial grass Fl Oct-Dec Lolium rigidum Gaudin annual ryegrass Poaceae High High notfound High annual grass Fl Sep-Nov Lupinus angustifolius L. narrowleaf lupin Fabaceae Med Med notfound High annual herb Fl Aug-Nov Melilotus indicus (L.) All. common melilot Fabaceae Med Med Low Med annual/biennial herb Fl Aug-May Mentha pulegium L. pennyroyal Lamiaceae notfound Med notfound High perennial herb Fl Sep/Dec-Mar, rhizomes Moraea miniata Andrews two-leaf cape tulip Iridaceae Med Med notfound High perennial herb Fl Jul-Nov, corms Onopordum acaulon L. stemless onopordon Asteraceae Low notfound notfound High biennial herb Fl Jul/Oct-Dec Orobanche minor Sm. lesser broom rape Scrophulariaceae High High Low Med parasitic herb Fl Sep-Dec Oxalis corniculata L. yellow wood sorrel Oxalidaceae Med Med Low High annual herb Fl May/Aug-Nov Parentucellia latifolia (L.) Caruel common bartsia Scrophulariaceae High High Low Med annual herb Fl Aug-Dec Parentucellia viscosa (L.) Caruel sticky bartsia Scrophulariaceae Med Med notfound Med annual/biennial herb Fl Aug-Feb 27 Paspalum dilatatum Poir. Poaceae Med Med notfound Med perennial grass Fl Oct-Apr, rhizomes

Pennisetum clandestinum Chiov. kikuyu grass Poaceae Low notfound notfound High perennial grass Fl Oct-Mar, rhizomes, stolons Pennisetum villosum Fresen. feathertop Poaceae Low notfound notfound Med perennial grass Fl Feb-Oct, rhizomes Plantago major L. greater plantain Plantaginaceae notfound Med notfound High perennial herb Fl Oct-Feb Poa annua L. winter grass Poaceae Med Med Low Med annual grass Fl Aug-Feb Polygonum aviculare L. wireweed Polygonaceae High High notfound High annual herb Fl Oct-May Polygonum bellardii All. Polygonaceae notfound Med notfound High herb Fl Nov-Mar Polygonum plebeium R. Br. small knotweed (n) Polygonaceae notfound notfound Low Med annual herb Fl Jun/Nov Raphanus raphanistrum L. wild radish Brassicaceae High High Med High annual herb Fl Apr-Nov Rapistrum rugosum (L.) All. turnipweed Brassicaceae High notfound notfound High annual/biennial herb Fl May/Aug-Nov Reseda lutea L. cutleaf mingonette Resedaceae Low notfound notfound Med perennial herb Fl Nov-Dec Rumex brownii Campd. swamp dock Polygonaceae Low notfound notfound Med perennial herb Fl Oct-Dec/Apr-May Rumex conglomeratus Murray clustered dock Polygonaceae notfound Med notfound High perennial herb Fl Oct-Feb Salsola australis R.Br. rolypoly (n) Chenopodiaceae High Med Med Med shrub Fl Mar-Sep Salvia reflexa Hornem. mintweed Lamiaceae Med notfound notfound High annual herb Fl Oct-Apr Sinapis alba L. white mustard Brassicaceae Med notfound notfound High annual herb

Ag Range Species Common name Family NAR Risk Lifecycle Reproduction buffer buffer Sinapis arvensis L. charlock Brassicaceae Low notfound notfound High annual herb Sisymbrium irio L. London rocket Brassicaceae Med High Med High annual/biennial herb Fl Jul-Dec Sisymbrium orientale L. Indian hedge mustard Brassicaceae High High Med High annual/biennial herb Fl Mar-Nov Solanum elaeagnifolium Cav. silverleaf nightshade Solanaceae notfound Med notfound Med perennial herb Fl Nov-Mar Solanum hoplopetalum Bitter & Summerh Afghan thistle (n) Solanaceae High High notfound Med perennial herb Fl Jan-Mar/Sep-Nov, clonal Solanum hystrix R.Br. Afghan thistle Solanaceae Low notfound notfound Med perennial herb clonal Solanum nigrum L. black berry nightshade Solanaceae Med Med High Med perennial herb/shrub Fl Jan-Dec Sorghum halepense (L.) Pers. Johnson grass Poaceae Low notfound notfound High perennial grass Fl Aug-Feb Spergula arvensis L. corn spurrey Caryophyllaceae Med Med notfound High annual herb Fl Jun-Nov Stachys arvensis L. staggerweed Lamiaceae Low notfound notfound High annual herb Fl Apr-Oct Taraxacum officinale F.H.Wigg. dandelion Asteraceae notfound Med notfound Med perennial herb Fl Jan-Dec Tribulus terrestris L. caltrop Zygophyllaceae High High Low Med annual herb Fl Jan-Dec Trifolium lappaceum L. Fabaceae notfound Med notfound Med annual herb Fl Nov-Dec Trifolium scabrum L. rough clover Fabaceae notfound Med notfound Med annual herb Fl Sep-Nov 28 Triticum aestivum L. volunteer wheat Poaceae High High notfound Med annual grass Fl Apr-Aug

Typha domingensis Pers. bulrush Typhaceae Med Med Low Med perennial herb Fl May-Sep, rhizomes Typha orientalis C.Presl bulrush Typhaceae Low notfound notfound Med perennial herb Fl Nov-Jan, rhizomes Urtica urens L. small nettle Urticaceae Med notfound notfound Med annual herb Fl Jul-Nov Verbascum virgatum Stokes twiggy mullein Scrophulariaceae Low Med notfound Med biennial herb Fl Jan-Dec Verbesina encelioides (Cav.) A.Gray crown beard Asteraceae Med Med notfound Med annual herb Fl Feb-Jul/Dec Vulpia bromoides (L.) Gray squirrel tail fescue Poaceae Med Med notfound Med annual grass Fl Sep-Dec Vulpia muralis (Kunth) Nees Poaceae Med Med Low Med annual grass Fl Aug-Dec Xanthium spinosum L. Bathurst burr Asteraceae Low notfound notfound High annual herb Fl Jan-Jun

Appendix table 2. Non-agricultural weeds of high and medium weed risk present within the NAR and buffer zones Common name Ag Range Species Family NAR Risk Lifecycle Reproduction (n = native) buffer buffer Acetosa vesicaria (L.) A.Love rosy dock Polygonaceae Med Med High High annual herb Fl Jul-Sep Alternanthera pungens Kunth khaki weed Amaranthaceae Med notfound notfound High annual/perennial herb Fl Dec-Jul, stolons Argemone ochroleuca Sweet Mexican poppy Papaveraceae Med notfound High High annual herb Fl Feb-Mar/Jul-Nov Asphodelus fistulosus L. onion weed Asphodelaceae Med Med Med High annual/biennial herb Fl Jun-Oct Avena barbata Link bearded oat Poaceae High High Low High annual grass Fl Aug-Dec Avena sativa L. common oat Poaceae Med Med notfound Medium annual grass Fl Oct Bidens bipinnata L. bipinnate beggartick Asteraceae Low notfound Low Medium annual herb Fl Mar-Sep Brassica tournefortii Gouan wild turnip Brassicaceae High High High High annual herb Fl Jun-Nov Briza maxima L. blowfly grass Poaceae High High notfound Medium annual grass Fl Sep-Oct Briza minor L. shivery grass Poaceae Med Med Med Medium annual grass Fl Sep-Oct Bromus catharticus Vahl prairie grass Poaceae Med Med notfound High annual/biennial grass Fl Sep-Jan Bromus diandrus Roth great brome Poaceae High High Low High annual grass Fl Aug-Nov Bromus hordeaceus L. soft brome Poaceae High Med notfound High annual grass Fl Aug-Nov 29 Bromus madritensis L. Madrid brome Poaceae High High notfound Medium annual grass Fl Sep-Nov

Bromus rubens L. red brome Poaceae High High Low High annual grass Fl Aug-Oct Carpobrotus edulis (L.) N.E.Br. hottentot fig Aizoaceae Med Med notfound Medium perennial herb Fl Jul-Oct Carrichtera annua (L.) DC. Ward’s weed Brassicaceae Med notfound notfound High annual herb Fl Sep-Nov Cenchrus ciliaris L. buffel grass Poaceae Med notfound Med Medium perennial grass Fl Feb-Oct Cenchrus longispinus (Hack.) Fernald spiny burrgrass Poaceae Low notfound notfound Medium perennial grass Cenchrus setiger Vahl birdwood grass Poaceae Med notfound Low Medium perennial grass Fl Apr-May Centaurium erythraea Rafn common centaury Gentianaceae Med Med notfound Medium annual/biennial herb Fl Oct-Apr Centaurium pulchellum (Sw.) Druce Gentianaceae Low Med notfound Medium annual herb Fl Oct-Nov Cerastium glomeratum Thuill. mouseear chickweed Caryophyllaceae High High Low Medium annual herb Fl Aug-Dec Chrysanthemum coronarium L. Asteraceae Med notfound notfound Medium annual herb Fl Aug-Nov Conyza bonariensis (L.) Cronquist flaxleaf fleabane Asteraceae Med notfound Low High annual herb Fl Jan-Dec Crassula thunbergiana Schult. Crassulaceae Med notfound notfound High annual herb Fl Oct Ehrharta calycina Sm. perennial veld grass Poaceae High Med Low Medium perennial grass Fl Mar-Apr/Aug-Sep Ehrharta longiflora Sm. annual veld grass Poaceae High High Med Medium annual grass Fl Jul-Nov Emex spinosa (L.) Campd. lesser jack Polygonaceae Med notfound notfound Medium annual herb Fl Jul, Sep

Common name Ag Range Species Family NAR Risk Lifecycle Reproduction (n = native) buffer buffer Eragrostis curvula (Schrad.) Nees African lovegrass Poaceae High High notfound High perennial grass Fl Aug/Nov-May Erodium botrys (Cav.) Bertol. long storksbill Geraniaceae Med High notfound Medium annual herb Fl Aug-Nov Erodium cicutarium (L.) L’Her. common storksbill Geraniaceae High High High High annual/biennial herb Fl May-Oct Euphorbia terracina L. Geraldton carnation weed Euphorbiaceae Med Med notfound High perennial herb Fl Aug-Dec Ferraria crispa Burm. black flag Iridaceae Med notfound notfound Medium perennial herb Fl Jul-Nov, corms Fumaria capreolata L. whiteflower fumitory Fumariaceae Med Med notfound Medium annual herb Fl Aug-Nov Fumaria densiflora DC. denseflower fumitory Fumariaceae Med notfound notfound Medium annual herb Geranium dissectum L. Geraniaceae Low notfound notfound Medium annual herb Fl Oct-Nov Geranium molle L. dove’s foot cranesbill Geraniaceae Low Med notfound Medium annual/perennial herb Fl Oct-Nov Gladiolus caryophyllaceus (Burm.f.) Poir. wild gladiolus Iridaceae Med Med notfound Medium perennial herb, corms Fl Aug-Nov Heliotropium curassavicum L. smooth heliotrope (n) Boraginaceae Med notfound High Medium annual/perennial herb Fl May-Jan Hordeum glaucum Steud. Northern barley grass Poaceae Med High Low Medium annual grass Fl Jul-Nov Hypochaeris glabra L. smooth catsear Asteraceae High High High High annual/perennial herb Fl Jan-Dec Juncus acutus L. spiny rush Juncaceae Med Med notfound Medium perennial herb Fl Aug-Nov/May, rhizomes 30 Juncus capitatus Weigel capitate rush Juncaceae High Med notfound High annual herb Fl Sep-Dec

Lepidium africanum (Burm.f.) DC. rubble peppercress Brassicaceae Med Med notfound Medium annual/perennial herb Fl Apr/Sep/Dec Limonium sinuatum (L.) Mill. perennial sea lavender Plumbaginaceae Med Med notfound Medium perennial herb Fl Jan–May/Sep–Dec Lupinus albus L. volunteer lupin Fabaceae Med notfound notfound High annual herb Fl Aug-Oct Lupinus cosentinii Guss. blue lupin Fabaceae High Med Low High annual herb Fl Aug-Nov Lythrum hyssopifolia L. lesser loosestrife Lythraceae Med Med Low Medium annual herb Fl Sep-Jan Malva parviflora L. marshmallow Malvaceae High Med High High annual/perennial herb Fl Mar/Jul-Nov Medicago laciniata (L.) Mill. Fabaceae Med notfound notfound High annual herb Fl Aug-Oct Medicago polymorpha L. burr medic Fabaceae Med High High High annual herb Fl Jan-Feb/May-Nov Mesembryanthemum crystallinum L. iceplant Aizoaceae Med High Med Medium annual/biennial herb Fl Sep-Dec Moraea flaccida (Sweet) Steud. cape tulip Iridaceae Med Med notfound High perennial herb Fl Sep-Nov, corms Nothoscordum gracile (Aiton) Stearn Alliaceae Med notfound notfound Medium perennial herb Fl Oct-Jan, bulbs Opuntia stricta Haw. common prickly pear Cactaceae Low notfound notfound Medium shrub Oxalis glabra Thunb. Oxalidaceae Med Med notfound Medium perennial herb Fl May-Aug, bulbs Oxalis pes-caprae L. soursob Oxalidaceae Med Med Med High perennial herb Fl Jun-Oct, , bulbs, rhizomes Oxalis purpurea L. largeflower wood sorrel Oxalidaceae Med Med notfound High perennial herb Fl May-Sep, bulbs

Common name Ag Range Species Family NAR Risk Lifecycle Reproduction (n = native) buffer buffer Papaver rhoeas L. field poppy Papaveraceae Low notfound notfound High annual herb Fl Sep-Oct Parkinsonia aculeata L. parkinsonia Fabaceae Low notfound notfound High tree/shrub Paspalum distichum L. water couch Poaceae Med notfound notfound Medium perennial grass Fl Dec-Apr Pelargonium capitatum (L.) L’Her. rose pelargonium Geraniaceae Low Med notfound Medium perennial herb Fl Feb-Apr/Aug-Dec Petrorhagia dubia velvet pink Caryophyllaceae High High Low Medium annual herb Fl Mar/Jul-Dec Phalaris canariensis L. canary grass Poaceae Med notfound notfound High annual grass Fl Sep-Oct Phalaris minor Retz. lesser canary grass Poaceae Med Med High High annual grass Fl Aug-Nov Polypogon monspeliensis (L.) Desf. annual barbgrass Poaceae Med High High Medium annual grass Fl May-Nov Prosopis pallida (Willd.) Kunth algaroba Fabaceae Low High notfound High tree/shrub Reseda luteola L. wild mingonette Resedaceae Med Med notfound Medium perennial herb Fl May/Nov-Jan Romulea rosea (L.) Eckl. Guildford grass Iridaceae Med High notfound High perennial herb Fl Aug-Nov, corms Rumex crispus L. curled dock Polygonaceae Med Med notfound High perennial herb Fl Jun-Dec Rumex obtusifolius L. broadleaf dock Polygonaceae Low notfound notfound High perennial herb Fl Dec-Apr Rumex pulcher L. fiddle dock Polygonaceae Low Med notfound High perennial herb Fl Sep-Dec 31 Setaria verticillata (L.) P.Beauv. whorled pigeon grass Poaceae Med notfound Low Medium annual grass Fl Dec-Jun

Silene gallica L. Caryophyllaceae High High Med Medium annual herb Fl Jul-Dec Solanum linnaeanum Hepper & P.- Solanaceae Low notfound notfound High shrub Fl Jan-May/Aug/Oct M.L.Jaeger Sonchus oleraceus L. sowthistle Asteraceae High High Med High annual herb Fl Jan-Dec Stellaria media (L.) Vill. chickweed Caryophyllaceae Med Med notfound High annual herb Fl Jun-Oct Tamarix aphylla (L.) H.Karst. apple pine Tamaricaceae Low notfound Low Medium tree Trachyandra divaricata (Jacq.) Kunth Asphodelaceae Med Med notfound Medium perennial herb Fl Aug-Nov Trifolium angustifolium L. narrowleaf clover Fabaceae Low Med notfound Medium annual herb Fl Sep-Jan Trifolium arvense L. hare foot clover Fabaceae High Med notfound Medium annual herb Fl Jun-Jan Trifolium campestre Schreb. hop clover Fabaceae Med Med notfound Medium annual herb Fl Aug-Jan Trifolium cernuum Brot. drooping flower clover Fabaceae Med Med notfound Medium annual herb Fl Sep-Dec Trifolium cherleri L. cupped clover Fabaceae Med Med notfound Medium annual herb Fl Aug-Nov Trifolium dubium Sibth. suckling clover Fabaceae Med Med notfound Medium annual herb Fl Aug-Dec Trifolium glomeratum L. cluster clover Fabaceae Med Med notfound Medium annual herb Fl Aug-Dec Trifolium hirtum All. rose clover Fabaceae Med Med notfound Medium annual herb Fl Aug-Mar Trifolium repens L. white clover Fabaceae Med Med notfound Medium annual herb Fl Jul-Nov

Common name Ag Range Species Family NAR Risk Lifecycle Reproduction (n = native) buffer buffer Trifolium striatum L. knotted clover Fabaceae Low notfound notfound Medium annual herb Fl Oct-Mar Trifolium subterraneum L. subterranean clover Fabaceae High High notfound Medium annual herb Fl Aug-Nov Trifolium tomentosum L. Fabaceae High High notfound Medium annual herb Fl Aug-Nov/Feb-Mar Ursinia anthemoides (L.) Poir. ursinia Asteraceae High High Low Medium annual herb Fl Jul-Dec Vellereophyton dealbatum (Thunb.) white cudweed Asteraceae High Med notfound Medium annual/perennial herb Fl Jan-Dec Hilliard & B.L.Burtt Vicia benghalensis L. purple vetch Fabaceae Med notfound notfound Medium annual/perennial herb Fl Apr/Aug-Nov Vulpia fasciculata (Forssk.) Samp. Poaceae Low notfound notfound Medium annual grass Fl Sep-Dec Vulpia myuros (L.) C.C.Gmel. rat’s tail fescue Poaceae High High Low High annual grass Fl Jul-Nov Wahlenbergia capensis (L.) A.DC. cape bluebell Campanulaceae High High notfound Medium annual herb Fl Sep-Nov Zaluzianskya divaricata (Thunb.) Walp. spreading night phlox Scrophulariaceae High High Low Medium annual herb Fl Aug-Oct 32

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45 11-059 Covers.indd 3 25/10/2011 2:44:38 PM 11-059 Covers.indd 3 25/10/2011 2:44:38 PM Climate Change Impacts on Agricultural Weeds in Western Australia by Pippa J Michael, Paul B Yeoh, Noboru Ota and John K Scott

This project focuses on the weed risk in relation to climate change in that both extends on the research undertaken in Phase 1 and moves into the Northern Agricultural Region (NAR) of Western Australia. The new areas. These reports will be published in the second half of 2012. region was chosen because it is predicted to experience considerable This report is an addition to RIRDC’s diverse range of over 2200 research environmental impact from climate change. It is also one of Australia’s publications which can be viewed and freely downloaded from our highly productive agricultural regions, generating approximately $1 website www.rirdc.gov.au. Information on the Weeds Program is available billion annually.This project was funded in Phase 1 of the National online at www.rirdc.gov.au/weeds Weeds and Productivity Research Program, which was managed by the Australian Government Department of Agriculture, Fisheries and Most of RIRDC’s publications are available for viewing, free Forestry (DAFF) from 2008 to 2010. The Rural Industries Research and downloading or purchasing online at www.rirdc.gov.au. Purchases can Development Corporation (RIRDC) is now publishing the final reports also be made by phoning 1300 634 313. of these projects. Phase 2 of the Program, which is funded to 30 June 2012 by the Australian Government, is being managed by RIRDC with the goal of reducing the impact of invasive weeds on farm and forestry productivity as well as on biodiversity. RIRDC is commissioning some 50 projects

This publication can be viewed at our website—www.rirdc.gov.au. Contact RIRDC: Ph: 02 6271 4100 All RIRDC books can be purchased from: Level 2, 15 National Circuit Fax: 02 6271 4199 Barton ACT 2600 Email: [email protected] web: www.rirdc.gov.au www.rirdc.gov.au PO Box 4776 Kingston ACT 2604

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