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Spatial Analysis of Risks Posed by Root Rot Pathogen, cinnamomi: Implications for Disease Management

DAVID A. KEITH1,2, KEITH L. MCDOUGALL1,3, CHRISTOPHER C. SIMPSON1 AND JILLIAN L. WALSH1

1 NSW Offi ce of Environment & Heritage, PO Box 1967, Hurstville NSW 2220. 2 Australian Wetlands and Rivers Centre, University of , NSW 2052. 3 Department of Environmental Management & Ecology, La Trobe University, PO Box 821, Wodonga, 3689.

Published on 3 September 2012 at http://escholarship.library.usyd.edu.au/journals/index.php/LIN

Keith, D.A., McDougall, K.L., Simpson, C.C. and Walsh, J.L. (2012). Spatial analysis of risks posed by root rot pathogen, : implications for disease management. Proceedings of the Linnean Society of New South Wales 134, B147-B179.

Phytophthora cinnamomi, a soil-borne pathogen that infects the roots of , is listed as a Key Threatening Process under Commonwealth and NSW state biodiversity legislation due to its deleterious effects on native fl ora. In warm temperate eastern , the disease may cause insidious declines in species that have slow rates of population turnover, and thereby threaten their long term persistence. Phytophthora cinnamomi has been known to occur in Royal National Park since the 1970s and systematic surveys for the pathogen were carried out a decade ago. Development of effective management strategies to mitigate the impacts of the disease requires information on the spatial distribution of risks posed by the disease. In this study, we use limited disease survey data to identify areas that are most at risk. We propose and apply a simple risk model in which risks of disease impact are proportional to the product of habitat suitability for the pathogen and abundance of susceptible biota. We modelled habitat suitability of the pathogen from available survey data and found that soil landscapes and topographic variables were the strongest predictors. Susceptible fl ora were concentrated on sandstone plateaus. Disease risks were greatest on the sandstone plateaus and lowest in the shale gullies with intermediate levels of risk on shale ridges and the coastal sand plain. The outcomes of this spatially explicit risk assessment will help inform the development of management strategies and priorities for the disease in the Park. Our approach lends itself to broader application to conservation planning in other landscapes and to other threats to biodiversity.

Manuscript received 11 January 2012, accepted for publication 2 May 2012.

KEYWORDS: disease susceptibility, conservation planning, risk assessment, risk mapping, Royal National Park, species distribution model.

INTRODUCTION and Xanthorrhoeaceae are especially susceptible (McDougall 2006; Figure 1). The threat from P. Phytophthora cinnamomi Rands is a soil-borne cinnamomi is recognised in its listing as a key plant pathogen with a very broad host range. It is threatening process nationally under the Environment damaging to crops and native vegetation in many Protection and Biodiversity Act 1999 and in NSW countries. Genetic evidence suggests that it is a recent under the Threatened Species Conservation Act introduction to Australia (Dobrowolski et al. 2003) 1995. but has been present in most States since at least the Phytophthora cinnamomi spreads by motile early 20th Century (Cahill et al. 2008). spores in moist soil over short distances or by Since the association between infection by P. vegetative growth between roots. Spores also enable cinnamomi and death in native plants in Australia was long distance dispersal in storm run off and creeks, established in the late 1960s (Podger 1968), severe or in soil attached to cars and boots. For this reason, damage in native vegetation has been documented in it is often found beside roads, tracks and other places all Australian States (Cahill et al. 2008). Many plants of soil-disturbance, and waterways. Infection occurs in the families , , when motile spores germinate on or near plant roots MANAGEMENT OF ROOT ROT DISEASE

Figure 1. Sporadic mortality of susceptible plant species (e.g. marginata) in spring is charac- teristic of root rot disease caused by Phytophthora cinnamomi in Royal National Park. or stem bases. These produce vegetative strands highly susceptible species, the impact will commonly (mycelia) that grow in host tissue, destroying water involve major structural change with fl ow-on effects conducting cells. Infected plants therefore typically to habitat-dependent plants and animals (McDougall display drought-like symptoms. Death may occur et al. 2005). Importantly, once introduced to a site where a host is especially susceptible to infection or that favours its life cycle, P. cinnamomi is likely to where other stresses are operating on the host (e.g. persist because of the presence of tolerant hosts and drought or insect attack). The mycelia may then the production of resting spores. Recolonisation of produce sporangia (the structure that releases motile infested sites by susceptible hosts may occur and has spores) or, under unfavourable conditions, a resting been recorded (e.g. Weste et al. 1999; McDougall and spore, which is resistant to drying (Cahill et al. 2008). Summerell 2003) but these colonists will be highly Importantly, P. cinnamomi is not dispersed in the air. vulnerable to further infection and their likelihood Host plants vary in their susceptibility, ranging of long-term survival is low. P. cinnamomi is putting from tolerant (where there are no visible symptoms) many species at risk of extinction (Cahill et al. to highly susceptible (where plants are rapidly killed). 2008). Hosts may be tolerant in some habitats but not others, The susceptibility to infection is known for very or only under some climatic conditions (Shearer & few native Australian species (McDougall 2006) Dillon 2006). The overall impact of P. cinnamomi on but there are taxonomic patterns that can allow the native vegetation is determined by local environmental susceptibility of other species to be inferred (Cahill conditions, host availability and time since infestation et al. 2008). For instance, all species of Andersonia (Cahill et al. 2008). For instance, P. cinnamomi can be (family Ericaceae) in , for which present and have no visual impact if hosts are tolerant, susceptibility is known, are highly susceptible (Wills can have an impact in one area but not another, despite and Keighery 1994), and species of Xanthorrhoea similar susceptible hosts, if environmental conditions (family Xanthorrhoeaceae) tend to be moderately to are not conducive to spread and infection, or the highly susceptible (McDougall 2006). Curiously, all impact can appear minimal long after infestation if Western Australian species of Banksia are moderately susceptible hosts disappear. At sites dominated by to highly susceptible whereas few eastern Australian

B148 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

Banksia species are highly susceptible (McCredie et (Wilson et al. 2003). An understanding of the spatial al. 1985). However, almost all Banksia species are pattern of risks posed to biodiversity by P. cinnamomi susceptible to infection to some extent (Figure 1). will help direct threat abatement actions to areas Extrapolation of susceptibility will not always be where they address the greatest risks. reliable within genera and families but offers a means In this paper we illustrate a method for mapping of assessing likely vulnerability of communities or the spatial pattern of risks by combining a habitat local fl oras to P. cinnamomi. suitability model for the pathogen with a map Site environmental conditions can greatly showing the abundance and diversity of susceptible infl uence the impact of P. cinnamomi (Wilson et al. fl ora. Our study area includes Royal and Heathcote 2000; Cahill et al. 2008). It is able to complete its National Parks, Garrawarra State Conservation Area life cycle under a great range of temperature (mean and adjacent areas, approximately 30 km south of annual temperature > 7°C) and rainfall (> 400 mm / Sydney city (Figure 2). We fi rst developed a habitat annum) conditions. Some soil types, however, have suitability model for the pathogen using data for P. been found to be less favourable to P. cinnamomi cinnamomi presence obtained by Walsh et al. (2006) activity (e.g. those with antagonistic micro-organisms to relate the occurrence of infested soil samples to (Halsall 1982), high fertility (Shearer and Crane a set of spatially explicit environmental predictor 2003), or high pH / high calcium content (Shearer variables. We then produced a distribution map of and Hill 1989)). Putative relationships have also susceptible fl ora by combining vegetation survey been reported between the incidence of P. cinnamomi data with susceptibility ranks for each species and and soil texture, as well as topographic features that weighting species association with mapped vegetation infl uence soil moisture (Wilson et al. 2000; 2003). types using their frequencies of occurrence. Finally, There is no effective, long-term treatment for P. we combined habitat suitability for the pathogen with cinnamomi once it enters an ecosystem. A chemical susceptibility of fl ora to produce a Phytophthora risk (phosphonate) increases plant resistance but can map for the study area - we used this to identify areas be phytotoxic and needs frequent re-application. where threat abatement efforts should be focussed. Prevention is therefore the most important form of management for sites suspected to be free of the pathogen. Preventive measures include routine METHODS surveillance of symptoms, restriction of access when soils are wet and the likelihood of spread is greatest, Phytophthora cinnamomi detection hygiene stations for cleaning shoes or vehicles, Soil sampling of P. cinnamomi within Royal construction of well-drained tracks that will not National Park was conducted in 2001 and 2002 for support the pathogen, or chemical control (Cahill et two distinct projects: a targeted survey of 14 sites, al. 2008). nine containing Xanthorrhoea resinosa and fi ve Phytophthora cinnamomi was fi rst located in containing (); and a Royal National Park in 1974 (Gerrettson-Cornell systematic survey of the plant communities. For the 1986). No importance was attached to its presence targeted survey, soil was sampled from the bases of until recently when deaths of Xanthorrhoea resinosa 20 plants of the target species at each site. Sampling were linked to infection by P. cinnamomi (McDougall was repeated in the following year on two randomly and Summerell 2003). Walsh et al. (2006) found that selected plants at each site, giving a total of 308 samples P. cinnamomi is widespread in Royal National Park, over two years. Each sample consisted of three 100 g concluding that hygiene measures were likely to be subsamples. For the plant community survey, walking ineffective at containing its spread. The pathogen tracks were selected such that they approximately was, however, found not to be ubiquitous or evenly represented the proportional distribution of the distributed. It was, for instance, not located at any fi ve broad vegetation types: heathland/open scrub, sites containing Telopea speciosissima (Waratah), forest, Eucalyptus woodland, wetland and which is typically highly susceptible to P. cinnamomi. rainforest. Along each track, a pair of samples was This suggests that some parts of the Park are still free collected approximately every 150 m, one sample of P. cinnamomi and that preventive measures are from directly adjacent to the track on the downslope worthwhile to protect iconic species such as this and side, and the other approximately 30 m from the track localised or threatened species that may be susceptible. in an upslope direction. In total, 120 pairs of samples Spatial patterns in occurrence of the pathogen may be were collected. All samples were taken from the top investigated using models of habitat suitability that 15 cm of the soil profi le and included root fragments, link observed occurrence to environmental variables as soils near the root zone yield higher populations of

Proc. Linn. Soc. N.S.W., 134, 2012 B149 MANAGEMENT OF ROOT ROT DISEASE

Figure 2. Study area.

P. cinnamomi (Tsao 1983). Equipment was sprayed distribution of P. cinnamomi. The seven predictor with methylated spirits after each sample to ensure variables were: soil landscapes (Hazelton & Tille that inoculum was not transferred between samples. 1990); slope, aspect (sine-tranformed); wetness index Samples were stored in sealed plastic bags and (number of grid cells in the catchment above the focal processed the following day. The baiting technique cell); local topographic position (proportional distance used to isolate P. cinnamomi is described in Walsh between local ridge and local gully); topographic et al. (2006). The presence of P. cinnamomi was position (difference between elevation of focal cell confi rmed by examining selective media containing and mean of neighbouring cells within a 250 m radius); baits under a compound microscope. The location topographic roughness (sum of absolute differences co-ordinates of all sample sites were recorded with a in elevation between the focal cell and neighbouring global positioning system and recorded as present or cells within a 250 m radius). These represent spatial absent depending on the outcomes of baiting tests. proxies for local environmental variables such as soil fertility and pH, site moisture status and temperature Model of habitat suitability that have previously been implicated as having an To model habitat suitability for P. cinnamomi, infl uence on the development and life cycle of the spatial data were assembled within a geographic pathogen (Wilson et al. 2000; Cahill et al. 2008). All information system (GIS) for seven environmental layers were projected onto a standard 25 m grid. variables that we hypothesised may infl uence the

B150 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

To ensure spatial independence of samples, (Table 1). Taxa were ranked as low, moderate or high we pooled samples within pairs from the plant susceptibility based on the severity of symptoms in community survey. The presence-absence records the wild or glasshouse experiments. In some cases, and environmental spatial data were used to construct susceptibility has been inferred from patterns of a Maximum Entropy model (MaxEnt) of habitat plant death observed in the fi eld at sites that were suitability for P. cinnamomi (Phillips et al. 2006). This known to be infested with P. cinnamomi (McDougall approach estimates a target probability distribution of 2006). Those taxa that do not commonly develop occurrence by fi nding a distribution that is closest symptoms regardless of whether colonisation by to uniform, subject to constraints represented by P. cinnamomi occurs were treated as fi eld resistant. observations of presence and absence in relation to Taxa not directly known to be susceptible, but with the predictor variables. The estimated distribution known susceptible congeneric taxa were recorded as maximises agreement with the set of observations, suspected susceptibility. without assuming anything that is not known about A set of 230 fl oristic quadrats collected in a their underlying distribution (Jaynes 1990). MaxEnt stratifi ed systematic survey was used to estimate the performed well in comparative accuracy tests of relative frequency of susceptible plant species in each numerous alternative methods of species distribution vegetation type within the study area (NPWS, unpubl. modelling (Elith et al. 2006). data). A vegetation classifi cation was generated from All seven predictors were included in the initial the data using a cluster analysis (see Tozer et al. 2010 model with a hinging value set to 0.5. Predictor for methods) and a map of the resulting units was variables were excluded from the model if they drafted with the aid of aerial photographs and soil explained less than 5% of variation in the data, given landscape maps. The mean frequency of each plant inclusion of other predictors, or if they were correlated taxon in each vegetation type was calculated from their (r>0.4) with another predictor that explained more occurrences in quadrats assigned to respective types. variation in the data. After checking the range of An index of disease susceptibility was calculated for environmental data values across the study area each vegetation type by summing the frequencies of in relation to the coverage of the training data all susceptible plant taxa and dividing by the sum set, model fi t was evaluated by inspecting the area frequencies of all recorded taxa. A second index was under the receiver operating curve (AUC). A map of calculated from the summed frequencies of only the habitat suitability for P. cinnamomi was produced by moderately and highly susceptible taxa. Both indices projecting the fi nal model onto the study area using were mapped by joining vectors of the values for each the spatial data layers. vegetation type to the attribute table of the vegetation map in a GIS. Ranking species and mapping susceptibility of vegetation The susceptibility of taxa recorded Risk mapping in the study area to infection by P. cinnamomi was Risks to biodiversity from P. cinnamomi at scored using lists of known susceptibility (Weste any given site were assumed to be a function of 2001; McDougall 2006) and personal observations the likelihood of infection by the disease and the susceptibility of vegetation. We therefore produced

Table 1. Descriptions of susceptibility classes of vascular plant taxa to root rot disease caused by Phy- tophthora cinnamomi.

Susceptibility class

Field resistant Of unknown susceptibility Not known to be susceptible but other species in known to be of low to moderate susceptibility Not known to be susceptible but other species in genus known to be highly susceptible Known to be of low susceptibility or susceptible but degree of susceptibility not documented Known to be of moderate susceptibility Known to be of high susceptibility

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Figure 3. Predicted habitat suitability for Phytophthora cinnamomi in the study area. a map of risk by multiplying spatial data layers for slopes than fl at slopes and less likely in deep gullies habitat suitability and the relative susceptibility than shallow gullies, slopes and ridges. indices. More than 95% of the study area was modelled within the range of the training data. The remaining RESULTS area was on steeper slopes than any of the sampled sites. The best model was a relatively poor fi t to the Habitat suitability data with an AUC of 0.69. The best distribution model of P. cinnamomi When projected on a map of the study area, the included three predictor variables. Soil landscape upper Hacking River valley and southern coastal was the most important predictor, explaining 71% of escarpment showed a conspicuously low probability variation, while slope explained a further 20% and of P. cinnamomi presence compared to the surrounding topographic position explained 9%. Sites with clay sandstone plateau (Figure 3). Within the Hacking loam soils derived from Narrabeen Group shales valley itself and also on the sandstone plateau, gullies had lower probability of P. cinnamomi presence than and steep slopes had a subtly lower probability of other soil types. Presence was also less likely on steep presence than other landscape elements.

B152 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

Susceptibility of vegetation shale gullies with intermediate levels of risk on shale Two hundred and eighty-four vascular plant ridges and the coastal sand plain, refl ecting patterns taxa recorded in a systematic vegetation survey of in habitat suitability for the pathogen and distribution the study area were identifi ed as known or suspected of susceptible fl ora, described above. A focus on the to be susceptible to disease caused by P. cinnamomi, most susceptible fl ora (Figure 5b) showed a slightly representing approximately one-quarter of the total greater contrast in risks between different geological vascular fl ora of the reserves (Appendix 1). The parent materials and higher risks in the eastern most widespread dry forest communities heathlands relative to the western sclerophyll forests. had susceptibility scores of 40 or more, while the most widespread heathland community had a susceptibility score of 35 (Table 2). In contrast, DISCUSSION rainforests and estuarine wetlands had the lowest susceptibility scores, generally less than 8, and wet Spatial patterns in disease risks sclerophyll forests and freshwater wetlands generally Phytophthora cinnamomi poses the greatest risk had susceptibility scores of less than 20 (Table 2). to native vegetation in heathlands and dry sclerophyll Of the 284 susceptible taxa, 128 were identifi ed as woodlands of the sandstone plateau, particularly moderately or highly susceptible. The susceptibility on fl at terrain of the plateau surface, ridges and relationships between plant communities based on upper slopes. Rainforests in deep gullies on shale- this subset of taxa were generally similar to those derived soils are at least risk, while wet sclerophyll based on all susceptible taxa except that moderately forests and wetlands are at low levels of risk. These or highly susceptible taxa were more abundantly generalisations hold irrespective of whether the risk represented in heathlands relative to dry sclerophyll analysis includes all species known or suspected to be forests (Table 2). susceptible to the disease or only those that are highly Susceptible plant taxa were most abundant or moderately susceptible. They are also consistent across northern and central parts of the study area with previous reports that disease impacts appear to on the sandstone plateau, and least abundant in be greatest in seasonally dry oligotrophic landscapes the southern part of the area in the upper Hacking (Cahill et al. 2008). valley and along the coastal escarpment (Figure 4). Comparatively low levels of risk were estimated Localised saline wetlands along the shores of Port for heathlands and sclerophyll woodlands on the Hacking also had low abundances of susceptible taxa. Jibbon coastal sand plain relative to adjoining Localised patches with intermediate abundance of sandstone landscapes. This is a surprising result, given susceptible taxa include the Jibbon sand plains in the that sandplain habitats elsewhere have suffered major far northeast of the study area and shale capped ridges impacts from the disease, for example on the Swan at Loftus and Garrawarra farm, respectively, in the coastal plain in southwestern Australia (Shearer & north and south of the study area. Spatial patterns in Hill 1989). Examination of the susceptibility data and the relative abundance of all susceptible species were soil survey data shows that modest levels of estimated similar to those for highly and moderately susceptible risk are driven primarily by the fact that a relatively species (Figure 4a cf. 4b). The main differences were low number of vascular plant taxa recorded in plant on the sandstone plateau. All susceptible taxa were communities of the Jibbon sand plain are currently slightly more abundant on western parts of the plateau known to be susceptible to the disease. Furthermore, dominated by dry sclerophyll forests (Figure 4a). In soil sampling on the sand plain was extremely contrast, moderately and highly susceptible taxa limited. Until more comprehensive soil testing and a were more abundant on eastern parts of the plateau, more comprehensive appraisal of susceptible fl ora is refl ecting the greater frequency of occurrence of these carried out, our inferences about disease risks on the taxa in heathlands, which are more widespread in the Jibbon sand plain should be treated with caution and east, and slightly lower frequencies of these taxa in similar management strategies and priorities should dry sclerophyll forests of sandstone gullies, which are be applied to this area as applied to the high-risk more widespread in the west (Figure 4b). heathlands of the sandstone plateau.

Spatial patterns of risk Limitations of risk assessment Spatial patterns in risks to vegetation posed by Our risk assessment was limited primarily by P. cinnamomi are shown in Figure 5. Risks were the available data. Although the habitat suitability greatest on the sandstone plateaus and lowest in the predictions for P. cinnamomi were largely within

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Table 2. Susceptibility scores (summed frequencies of susceptible taxa) for each vegetation map unit (see DECCW 2010). Map unit codes: DSF- dry sclerophyll forests; FoW forested wetlands; FrW- freshwater wetlands; GL- grasslands; HL- heathlands; RF- rainforests; SW- saline wetlands; WSF- wet sclerophyll forests (after Keith 2004a).

Susceptibility Susceptibility Map unit score Map unit name score (all (moderately& code susceptible highly taxa) susceptible taxa) S_DSF03 Coastal Sand Apple-Bloodwood Forest 18 6 S_DSF04 Coastal Enriched Sandstone Sheltered Forest 20 6 S_DSF05 Coastal Sandstone Exposed Scribbly Gum Woodland 39 19 S_DSF06 Coastal Sandstone Foreshores Forest 16 5 S_DSF07 Coastal Sandstone Gully Moist Heath 44 20 S_DSF08 Coastal Sandstone Riparian Forest 21 8 S_DSF09 Coastal Sandstone Sheltered Peppermint- 39 17 S_DSF13 Southern Sydney Sheltered Forest 26 9 S_DSF14 Sydney Ironstone Bloodwood-Silvertop Ash Forest 37 14 S_DSF15 Woronora Sandstone Exposed Bloodwood Woodland 40 19 S_DSF16 Woronora Sandstone Mallee-Heath Woodland 45 22 S_DSF21 Coastal Sand Bangalay Forest 9 4 S_FoW01 Coastal Alluvial Bangalay Forest 8 2 S_FoW05 Hinterland Riverfl at Paperbark Swamp Forest 3 1 S_FoW08 Estuarine Swamp Oak Forest 0 0 S_FrW01 Coastal Upland Damp Heath Swamp 25 9 S_FrW02 Coastal Upland Wet Heath Swamp 17 8 S_FrW04 Coastal Sand Swamp Paperbark Scrub 4 2 S_FrW05 Coastal Sand Swamp Sedgeland 5 0 S_GL02 Coastal Headland Grassland 5 3 S_HL02 Coastal Tea--Banksia Scrub 8 3 S_HL04 Coastal Sandplain Heath 25 11 S_HL06 Coastal Headland Banksia Heath 20 9 S_HL08 Coastal Sandstone Heath-Mallee 35 18 S_HL09 Coastal Sandstone Plateau Rock Plate Heath 11 7 S_HL10 Hinterland Sandstone Dwarf Apple Heath-Woodland 23 10 S_RF01 Illawarra Escarpment Subtropical Rainforest 1 0 S_RF03 Coastal Warm Temperate Rainforest 3 1 S_RF07 Coastal Escarpment Littoral Rainforest 7 3 S_RF08 Coastal Headland Littoral Thicket 2 0 S_RF09 Coastal Sandstone Riparian Scrub 16 6 S_SW01 Estuarine Mangrove Forest 0 0 S_SW02 Estuarine Saltmarsh 0 0 S_WSF02 Coastal Enriched Sandstone Moist Forest 20 7 S_WSF03 Coastal Sand Littoral Forest 6 2 S_WSF04 Illawarra Escarpment Bangalay-Banksia Forest 11 5 S_WSF05 Illawarra Escarpment Blackbutt Forest 13 4 S_WSF06 Coastal Shale-Sandstone Forest 25 9 S_WSF07 O’Hares Creek Shale Forest 9 3 S_WSF09 Sydney Turpentine-Ironbark Forest 22 5

B154 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

Figure 4. Spatial patterns in the relative abundance of a) all susceptible vascular plant taxa and b) highly and moderately susceptible vascular plant taxa.

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Figure 5. Spatial patterns in risks posed to native vegetation by Phytophthora cinnamomi based on (a) all susceptible taxa and (b) highly and moderately susceptible taxa.

B156 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH the domain of the training data, some of the more susceptibility data to produce a more precise spatial restricted landscape types were not well sampled, representation of risks posed by the pathogen. notably the Jibbon sand plain. In addition, high levels While we caution against interpretation of fi ne of variability and some false negative test outcomes scale spatial patterns in disease risk, and interpretation may be expected due to diffi culties in detecting of risk levels at precise locations, we believe that the the disease, and may have been responsible for the major generalisations about the landscapes and areas mediocre performance of the habitat suitability that are most and least susceptible to the disease model. Consequently, relatively large numbers of (outlined above) are likely to provide a robust basis subsamples may be required to detect the disease (or for disease management, despite the limitations in the confi rm its absence) at any given site. Hierarchical underlying data. This is because frequencies of the Bayesian detectability models are well suited to deal disease recorded in shale gullies were extremely low with these uncertainties by modelling the probability (7% positive test results recorded from 114 locations that the disease is detected given that it is present at a in shale gullies, cf. 23% from 109 locations on site (McCarthy 2008). sandstone plateau and gullies), and few of the known An alternative approach to modelling habitat susceptible species occur within plant communities suitability for the pathogen based on occurrence of shale landscapes. Both of these results contrast in soil survey sites would be to model expression markedly with fi ndings for heathlands and sclerophyll of disease symptoms in vegetation. This would be woodlands on the sandstone plateau. Secondly, the informative for risk assessment because the disease spatial patterns in disease habitat suitability were may not cause signifi cant impacts on plant diversity reinforced by similar patterns in the distribution of in every habitat and location in which a habitat susceptible biota that were derived from independent suitability model predicts it could occur. However, data. Furthermore, the results are corroborated by diagnosis of symptoms can be uncertain because there more general patterns of disease impacts reported may be other causes of plant tissue death and because from other parts of temperate Australia (Cahill et the symptoms can be relatively transient and hence al. 2008). The distinction between sandstone ridges, diffi cult to detect in early stages of infection and upper slopes and gullies is more subtle and together several years after infection when dead remains have with risk assessment for the Jibbon sand plain, decayed. Thus both types of models have strengths warrants more precautionary treatment in the design and limitations. of management strategies until uncertainties can be Outcomes of the risk assessment may also be resolved. sensitive to incomplete data on the susceptibility of Our model did not address the risks of pathogen vascular fl ora to the disease. Precise assessments of introduction. As P. cinnamomi can be spread through susceptibility require experimental inoculation of earthworks and mud on footwear and vehicle tyres, an test plants under a range of environmental conditions association may be expected between infestation and or thorough fi eld investigations. This has not been roadsides, fi re trails, walking tracks and associated done for a large majority of the local fl ora, although drains into bushland. Walsh et al. (2006) failed to the susceptibility ranks for many species in Royal detect diminished infestation over distances of 30 m National Park were assigned by extrapolation from from walking tracks, although a relationship may exist recovery of P. cinnamomi from symptomatic plants over larger distances extending to remote areas that are that were sampled elsewhere (McDougall 2006). more buffered from movement of humans and other This assumes that host susceptibility relationships dispersal agents. Modelling of risks associated with are consistent within taxa across their geographic these relationships would require improved survey distributions. While some intraspecifi c genetic data on the occurrence of P. cinnamomi that is more variation and environmentally regulated variation in evenly stratifi ed in relation to distance and drainage susceptibility may be expected across the distribution from locations of past and present anthropogenic of each host taxon, our approach was precautionary disturbance. Ideally, it would also incorporate data on because it assumes that a species could be susceptible the frequency and pattern of track usage, especially in the study area if symptoms have been recorded on when soil surfaces are saturated after rain, as well as individuals of the same or related species anywhere fi ne-scale drainage patterns. within their broader range. Although we believe that taxonomic patterns of host susceptibility are Disease management suffi ciently strong (Cahill et al. 2008) to justify our Impacts of P. cinnamomi are less conspicuous approach, the models would benefi t from improved in the Sydney region than in parts of south western

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Australia, Victoria and (Cahill et al. vehicles, precautionary track closures, restrictions 2008). Nonetheless, the disease may cause insidious on wet weather use and regular dry-weather track declines in key biota that have major implications maintenance to minimise development of muddy for ecosystem diversity and function, especially on sinks are all appropriate measures to limit disease the sandstone plateau where we have shown that impacts in these circumstances. risks of disease impacts are greatest. For example, populations of Xanthorrhoea resinosa, a major structural component of heathlands on the plateau, CONCLUSIONS are currently undergoing insidious declines related to synergistic effects of fi re and disease (Regan et al. By combining spatial data on habitat suitability 2011). These declines are projected to continue, but for a disease and the distribution of susceptible biota, the rate of decline will depend on how both disease it is possible to carry out a spatial analysis of risks and fi re are managed. There are essentially two posed by disease to support the development of groups of management actions for the disease: those strategies and priorities for disease management. We that seek to minimise spread; and direct treatment were able to construct a disease risk map that is likely of the disease or its effects. The relative merits of to be robust for this general purpose using relatively these options depend on context. For example, Keith limited disease survey data, available vegetation (2004b) found that quarantine measures to limit the survey data, existing data bases on plant susceptibility spread of P. cinnamomi were likely to have little and simple modelling techniques. The axiom of our effect on the viability of highly susceptible approach that risks should be proportional to the barbata populations, whereas direct treatment could product of proneness to a threatening process and be more effective, but only if the treatment reduced abundance of susceptible assets should be widely plant mortality by at least 90%. applicable to other management areas as well as other Although the disease is widespread across the threats to biodiversity. Furthermore this risk model is study area, there still appear to be some areas that are readily transformed into spatial dimensions, providing at considerable risk of impact that are not yet infected. a simple information resource for conservation For example, P. cinnamomi was not recorded at any planning. of the fi ve sites supporting susceptible populations of Telopea speciosissima, despite comprehensive soil sampling. For these and similar sites, hygiene REFERENCES measures, such as restrictions on access during wet conditions and washdown or change of footwear protocols, may help to reduce the risk of infection by Cahill, D.M., Rookes, J.E., Wilson, B.A., Gibson, L. and limiting dispersal of infected mud. McDougall, K.L. (2008). Phytophthora cinnamomi and Australia’s biodiversity: impacts predictions and The habitats most at risk from P. cinnamomi are progress towards control. Turner Review No. 17. widely distributed and are traversed by some of the Australian Journal of 56, 279-310. most popular walking tracks, including the Coast DECCW (2009). Draft Native Vegetation of the Sydney track, Marley track, Winifred Falls track, Curra Moors Metropolitan Catchment Management Authority track and Uloola track, each of which is used by Area. NSW Department of Environment, Climate thousands of walkers each year. High-usage unkerbed Change and Water, Sydney. roadways also traverse the study area; maintenance of Dobrowolski, M.P., Tommerup, I.C., Shearer, B.L. and their verges may increase the likelihood of pathogen O’Brien, P.A. (2003). Three clonal lineages of spread, especially if undertaken during wet weather. Phytophthora cinnamomi in Australia revealed by microsatellites. Phytopathology 93, 695-704. As infections are already scattered along these Elith, J., Graham, C.H., Anderson, R.P. et al. (2006). routes, the major management task will be to limit Novel methods improve prediction of species’ further spread and protect the most valuable assets distributions from occurrence data. Ecography 29, at risk. These routes, because of their high visitation 129–151. rates, also provide opportunities to increase public Gerrettson-Cornell, L. (1986). Phytophthora cinnamomi awareness about the impacts of the disease and in New South Wales. Forestry Commission of New support for research and management initiatives South Wales, Sydney. to minimise its impact. Educational signage, Halsall, D. (1982). A forest soil suppressive to strategically located wash-down stations, adherence Phytophthora cinnamomi and conducive to Phytophthora cryptogea. II. Suppression of to formed tracks, wash-down protocols for offroad sporulation. Australian Journal of Botany 30, 27-37.

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Hazelton, P.A. and Tille, P.J. (1990). Soil Landscapes of following infection by Phytophthora cinnamomi. In the Wollongong-Port Hacking 1:100 000 Sheet. Soil ‘Phytophthora in Forests and Natural Ecosystems’ Conservation Service of NSW, Sydney. (Eds J.A. McComb, G.E.StJ. Hardy and I.C. Jaynes, E.T. (1990). Notes on present status and future Tommerup) pp. 267–268. (Murdoch University Print: prospects. In ‘Maximum entropy and Bayesian Murdoch, Western Australia) methods’ (Eds W.T. Grady Jnr and L.H.Schick) pp. Shearer, B.L. and Dillon, M. (1996). Susceptibility of 1-13. (Kluwer: Drordrecht). plant species in Banksia woodlands on the Swan Keith, D.A. (2004a). ‘Ocean shores to desert dunes: the Coastal Plain, Western Australia, to infection by native vegetation of New South Wales and the ACT’. Phytophthora cinnamomi. Australian Journal of (NSW Department of Environment and Conservation: Botany 44, 433–445. Sydney). Shearer, B.L. and Hill, T.C. (1989). Diseases of Banksia Keith, D.A. (2004b). Australian heath (Epacris woodlands on the Bassendean and Spearwood Dune barbata): viability under management options systems. Journal of the Royal Society of Western for fi re and disease. In ‘Species Conservation and Australia 71, 113-114. Management: case studies’ (Eds. H.R. Akcakaya, Tozer, M.G., Turner, K., Keith, D.A., Tindall, D., Pennay, M.A. Burgman, O. Kindvall, C.C. Wood, P. Sjogren- C., Simpson, C., MacKenzie, B., Beukers, P. and Gulve, J.S. Hatfi eld and M.A. McCarthy) pp. 90-103. Cox, S. (2010). Native vegetation of southeast NSW: (Oxford University Press: Oxford). a revised classifi cation and map for the coast and McCarthy, M.A. (2008). Bayesian methods for ecologists. eastern tablelands. Cunninghamia 11, 359-406. Cambridge University Press, Cambridge. Tsao P. H. (1983) Factors affecting isolation and McCredie, T.A., Dixon, K.W. and Sivasithamparam, quantitation of Phytophthora from soil. In K. (1985). Variability in the resistance of Banksia ‘Phytophthora, Its Biology, , Ecology L. f. species to Phytophthora cinnamomi Rands. and Pathology’ (Eds D.C. Erwin, S. Bartnicki- Australian Journal of Botany 33, 629-637. Garcia and P.H. Tsao) pp. 219-236. (The American McDougall, K.L. (2006). The responses of native Phytopathological Society: St. Paul, Minnesota). Australian plant species to Phytophthora cinnamomi. Walsh, J.L., Keith, D.A., McDougall, K.L., Summerell, Appendix 4. In Management of Phytophthora B.A. and Whelan, R.J. (2006). Phytophthora Root cinnamomi for biodiversity conservation in Australia: Rot: Assessing the potential threat to Australia’s Part 2. National best practice (E. O’Gara, K. Howard, oldest national park. Ecological Management and B. Wilson and G.E.StJ. Hardy) pp. 1-52. (Department Restoration 7, 55-60. of the Environment and Heritage: Canberra). Weste, G. (2001). Interaction between Phytophthora McDougall, K.L., Hobbs, R.J. and Hardy, G.E.StJ. (2005). cinnamomi and Victorian native plant species Distribution of understorey species in forest affected growing in the wild. Australasian Mycologist 20, by Phytophthora cinnamomi in south-western 64-72. Western Australia. Australian Journal of Botany 53, Weste, G., Walchhuetter, T. and Walshe, T. (1999). 813 – 819. Regeneration of Xanthorrhoea australis following McDougall, K.L. and Summerell, B.A. (2003). The epidemic disease due to Phytophthora cinnamomi impact of Phytophthora cinnamomi on the fl ora and in the Brisbane Ranges, Victoria. Australasian Plant vegetation of New South Wales – a re-appraisal. In Pathology 28, 162-169. ‘Phytophthora in Forests and Natural Ecosystems’ Wills, R.T. and Keighery, G.J. (1994). Ecological impact (Eds J.A. McComb, G.E.StJ. Hardy and I.C. of plant disease on plant communities. Journal of the Tommerup) pp. 49-56. (Murdoch University Print: Royal Society of Western Australia 77, 127-132.a Murdoch, Western Australia). Wilson, B.A., Aberton, J. and Cahill, D.M. (2000). Phillips, S.J., Anderson, R.J. and Schapire, R.E. (2006). Relationships between site factors and distribution Maximum entropy modelling of species geographic of Phytophthora cinnamomi in the Eastern Otway distributions. Ecological modelling 190, 231-259. Ranges, Victoria. Australian Journal of Botany 48, Pellow, B.J., Henwood, M.J.and Carolin, R.C. (2009). 247-260. Flora of the Sydney region. Fifth edition. Sydney Wilson, B.A., Lewis, A. and Aberton, J. (2003). Spatial University Press, Sydney. model for predicting the presence of cinnamon Podger, F. D. (1968). Aetiology of jarrah dieback and fungus (Phytophthora cinnamomi) in sclerophyll disease of dry sclerophyll Eucalyptus marginata Sm. vegetation communities in south-eastern Australia. forests in Western Australia. MSc Thesis, University Austral Ecology28, 108-115. of Melbourne. Regan, H.M., Keith, D.A., Regan, T.J., Tozer, M.G. and Tootell, N. (2011). Fire management to combat disease: turning interactions between threats into conservation management. Oecologia 167, 873–882. Shearer, B.L. and Crane, C.E. (2003). The infl uence of soil from a topographic gradient in the Fitzgerald River National Park on mortality of Banksia baxteri

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Appendix 1 Susceptibility to Phytophthora cinnamomi of plant taxa recorded in Royal National Park, Heathcote Na- tional Park and Garrawarra State Conservation Area. Nomenclature follows Pellow et al. (2009). 1 - known or suspected to be susceptible. 0 - not known or suspected to be susceptible (includes taxa with no data). Known susceptibility is based on isolation of the pathogen from plants exhibiting disease symptoms. Suspected sus- ceptibility is based on evidence from a congeneric taxon.

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Abrophyllum ornans 00 binervata 10 Acacia binervia 10 Acacia brownii 10 Acacia elongata 10 Acacia fl oribunda 10 Acacia hispidula 10 10 Acacia irrorata subsp. irrorata 10 Acacia linearifolia 00 10 Acacia longifolia subsp. longifolia 10 Acacia longifolia subsp. sophorae 10 Acacia longissima 10 Acacia maidenii 10 10 00 Acacia myrtifolia 10 10 Acacia stricta 10 Acacia suaveolens 10 Acacia terminalis 11 Acacia ulicifolia 10 Acmena smithii 00 Acronychia oblongifolia 00 divaricata 11 Actinotus helianthi 00 Actinotus minor 00 aethiopicum 00 Adiantum formosum 00 Adiantum hispidulum 00 Adiantum silvaticum 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Aegiceras corniculatum 00 subcinereus 00 distyla 11 10 Allocasuarina nana 11 Allocasuarina paludosa 00 11 Allocasuarina verticillata 00 Almaleea paludosa 00 Alphitonia excelsa 10 Alternanthera denticulata 00 Amperea xiphoclada 10 Amphipogon strictus var. strictus 10 10 Angophora fl oribunda 10 10 Anisopogon avenaceus 00 Aotus ericoides 11 Aphanopetalum resinosum 00 Apium prostratum 00 Aristida vagans 00 Aristida warburgii 00 Arthropodium millefl orum 00 Arthropteris tenella 00 00 Asplenium fl abellifolium 00 Asplenium polyodon 00 humifusum 11 Astroloma pinifolium 10 Austrodanthonia monticola 00 Austrodanthonia racemosa var. racemosa 00 Austromyrtus tenuifolia 00 puberula 00 Austrostipa pubescens 10 Avicennia marina subsp. australasica 00 Backhousia myrtifolia 00 Baeckea imbricata 11 Baeckea linifolia 11

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Baloskion gracile 00 subsp. ericifolia 10 subsp. integrifolia 11 10 11 11 10 10 microphylla 11 10 Baumea acuta 00 Baumea articulata 00 Baumea juncea 00 Baumea rubiginosa 00 Baumea teretifolia 00 Bertya pomaderroides 00 Billardiera scandens 00 Blandfordia nobilis 11 Blechnum camfi eldii 00 Blechnum cartilagineum 00 Blechnum indicum 00 Blechnum nudum 00 Blechnum patersonii 00 Blechnum wattsii 00 Boronia ledifolia 11 Boronia parvifl ora 00 Boronia serrulata 11 Bossiaea ensata 11 Bossiaea heterophylla 11 Bossiaea rhombifolia subsp. rhombifolia 11 Bossiaea scolopendria 11 Bossiaea stephensonii 11 Brachyloma daphnoides 10 Brachyscome angustifolia 10 Breynia oblongifolia 00 Brunoniella australis 00 Brunoniella pumilio 00 Burchardia umbellata 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Bursaria spinosa 00 Callicoma serratifolia 00 Callistemon citrinus 00 Callistemon linearis 00 Callistemon subulatus 00 Callitris muelleri 00 Callitris rhomboidea 00 Calochlaena dubia 00 Calystegia marginata 00 Calystegia sepium subsp. roseata 00 Calytrix tetragona 11 Carex appressa 00 Carex breviculmis 00 Carex brunnea 00 Carex gaudichaudiana 00 Carpobrotus glaucescens 00 Cassinia aculeata 00 Cassinia aureonitens 00 Cassinia denticulata 00 Cassinia trinerva 00 Cassytha glabella 00 Cassytha pubescens 00 glauca 00 Caustis fl exuosa 00 Caustis pentandra 00 Caustis recurvata 00 Cayratia clematidea 00 Cenchrus caliculatus 00 Centella asiatica 00 Centrolepis fascicularis 00 Centrolepis strigosa subsp. strigosa 00 00 Ceratopetalum gummiferum 00 Cheilanthes sieberi subsp. sieberi 00 Chloanthes stoechadis 00 Chordifex dimorphus 00 Chordifex fastigiatus 00 Chorizandra cymbaria 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Chorizandra sphaerocephala 00 Christella dentata 00 Chrysocephalum apiculatum 00 Cissus antarctica 00 Cissus hypoglauca 00 moorei 00 Claoxylon australe 00 Clematis aristata 10 Clematis glycinoides var. glycinoides 10 tomentosum 00 defoliatum 00 Comesperma ericinum 10 Comesperma retusum 00 Comesperma sphaerocarpum 00 Comesperma volubile 00 Commelina cyanea 00 ellipticum 10 10 10 Conospermum tenuifolium 10 Convolvulus erubescens 00 Coprosma quadrifi da 00 elatum 00 Coronidium scorpioides 00 Correa alba var. alba 10 Correa refl exa 10 10 Crassula sieberiana 00 Crowea saligna 10 Cryptandra amara 10 Cryptandra ericoides 10 Cryptocarya glaucescens 00 Cryptocarya microneura 00 Cupaniopsis anacardioides 00 Cyathea australis 00 Cyathea leichhardtiana 00 Cyathochaeta diandra 00 Cyclophyllum longipetalum 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Cymbopogon refractus 00 Cyperus enervis 00 Cyperus gracilis 00 Cyperus imbecillis 00 Cyperus polystachyos 00 Cyperus sanguinolentus 00 Cyperus tetraphyllus 00 Dampiera purpurea 10 Dampiera stricta 10 Darwinia diminuta 11 Darwinia fascicularis 11 Darwinia leptantha 00 Davallia solida var. pyxidata 00 acicularis 00 Daviesia alata 11 Daviesia corymbosa 11 Daviesia ulicifolia 10 Dennstaedtia davallioides 00 Desmodium brachypodum 00 Desmodium rhytidophyllum 00 Desmodium varians 00 Dianella caerulea 10 Dianella longifolia 10 Dianella prunina 10 Dianella revoluta var. revoluta 10 Dichelachne crinita 00 Dichelachne micrantha 00 Dichelachne rara 00 Dichondra repens 00 Dicksonia antarctica 00 Digitaria parvifl ora 00 elegans 11 Dillwynia fl oribunda 11 Dillwynia glaberrima 11 Dillwynia ramosissima 11 Dillwynia retorta 11 Dioscorea transversa 00 australis 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Diploglottis cunninghamii 00 Dodonaea triquetra 00 Doodia aspera 00 Doodia caudata 00 00 Doryphora sassafras 00 Drosera auriculata 10 Drosera binata 10 Drosera peltata 10 Drosera pygmaea 10 Drosera spatulata 10 Duboisia myoporoides 00 Echinopogon caespitosus var. caespitosus 00 Echinopogon ovatus 00 Einadia hastata 00 Einadia nutans 00 Elaeocarpus reticulatus 11 Elaeodendron australe 00 Eleocharis acuta 00 Eleocharis sphacelata 00 Empodisma minus 00 Endiandra sieberi 00 Entolasia marginata 00 Entolasia stricta 00 Epacris longifl ora 11 Epacris microphylla 11 Epacris obtusifolia 10 Epacris pulchella 11 Epaltes australis 00 Eragrostis brownii 00 australasius 00 Eryngium vesiculosum 00 10 10 Eucalyptus botryoides <--> saligna 10 Eucalyptus camfi eldii 10 Eucalyptus capitellata 10 Eucalyptus consideniana 10

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) 10 10 Eucalyptus luehmanniana 10 Eucalyptus multicaulis 10 Eucalyptus oblonga 10 Eucalyptus obstans 10 subsp. paniculata 10 10 10 10 10 10 10 Eucalyptus scias 10 10 10 10 Euchiton gymnocephalus 00 Eupomatia laurina 00 falcatus var. falcatus 00 Eurychorda complanata 00 Euryomyrtus ramosissima subsp. ramosissima 10 Eustrephus latifolius 00 00 Exocarpos strictus 00 Ficinia nodosa 00 Ficus coronata 00 Ficus obliqua var. obliqua 00 Ficus rubiginosa 00 Ficus superba var. henneana 00 Flagellaria indica 00 Gahnia aspera 00 Gahnia clarkei 00 Gahnia erythrocarpa 00 Gahnia melanocarpa 00 Gahnia microstachya 00 Gahnia radula 00 Gahnia sieberiana 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Galium propinquum 00 Geijera salicifolia 00 Geitonoplesium cymosum 00 Geranium homeanum 00 Geranium solanderi 00 10 10 Gleichenia rupestris 10 Glochidion ferdinandi 00 Glycine clandestina 00 Glycine microphylla 00 Gompholobium glabratum 11 Gompholobium grandifl orum 11 Gompholobium latifolium 11 Gompholobium minus 00 Gonocarpus micranthus 10 Gonocarpus tetragynus 10 Gonocarpus teucrioides 10 Goodenia bellidifolia subsp. bellidifolia 10 Goodenia dimorpha 10 Goodenia hederacea subsp. hederacea 10 Goodenia heterophylla 10 Goodenia ovata 10 Goodenia paniculata 00 Goodenia stelligera 10 Grammitis billardierei 00 buxifolia subsp. buxifolia 11 11 11 11 10 Grevillea parvifl ora subsp. parvifl ora 11 subsp. sericea 11 11 Guioa semiglauca 00 Gymnoschoenus sphaerocephalus 00 Gymnostachys anceps 00 Haemodorum corymbosum 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Haemodorum planifolium 00 dactyloides 10 11 Hakea propinqua 11 11 11 11 Hardenbergia violacea 00 Harmogia densifolia 00 Hedycarya angustifolia 00 Hemarthria uncinata var. uncinata 00 Hemigenia purpurea 00 acicularis 00 Hibbertia aspera subsp. aspera 11 Hibbertia bracteata 11 Hibbertia dentata 11 Hibbertia empetrifolia subsp. empetrifolia 11 Hibbertia fasciculata 11 Hibbertia linearis 11 Hibbertia monogyna 11 Hibbertia nitida 11 Hibbertia obtusifolia 00 Hibbertia riparia 11 Hibbertia scandens 11 Hibbertia serpyllifolia 11 Histiopteris incisa 00 linearis 11 Hovea longifolia 11 Hybanthus monopetalus 10 Hydrocotyle acutiloba 00 Hydrocotyle geraniifolia 00 Hydrocotyle laxifl ora 00 Hydrocotyle sibthorpioides 00 Hydrocotyle tripartita 00 Hymenophyllum cupressiforme 00 Hypericum gramineum 00 Hypericum japonicum 00 Hypolaena fastigiata 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Hypolepis muelleri 00 Hypoxis hygrometrica 00 Imperata cylindrica 00 Indigofera australis 00 Ipomoea brasiliensis 00 Isachne globosa 00 Isolepis cernua 00 Isolepis inundata 00 anemonifolius 10 11 Isotoma fl uviatilis 00 Joycea pallida 00 Juncus continuus 00 Juncus kraussii subsp. australiensis 00 Juncus planifolius 00 Juncus prismatocarpus 00 Juncus usitatus 00 Kennedia rubicunda 11 Korthalsella rubra 00 10 Kunzea capitata 10 Lachnagrostis fi liformis 00 Lagenophora stipitata 00 formosa 10 Lasiopetalum ferrugineum 10 Lasiopetalum parvifl orum 00 Lasiopetalum rufum 10 acuminata 00 Lastreopsis decomposita 00 Lastreopsis microsora subsp. microsora 00 Laxmannia gracilis 00 Legnephora moorei 00 Leionema dentatum 10 Lepidosperma concavum 00 Lepidosperma fi liforme 00 Lepidosperma forsythii 00 Lepidosperma gunnii 00 Lepidosperma latens 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Lepidosperma laterale 00 Lepidosperma limicola 00 Lepidosperma longitudinale 00 Lepidosperma neesii 00 Lepidosperma urophorum 00 Lepidosperma viscidum 00 Leptinella longipes 00 Leptocarpus tenax 00 Leptomeria acida 10 Leptospermum arachnoides 10 Leptospermum continentale 10 Leptospermum grandifolium 10 Leptospermum juniperinum 10 10 Leptospermum morrisonii 10 Leptospermum parvifolium 10 Leptospermum polygalifolium subsp. 10 polygalifolium Leptospermum squarrosum 10 10 Lepyrodia anarthria 00 Lepyrodia scariosa 00 amplexicaulis 11 Leucopogon ericoides 11 Leucopogon esquamatus 11 Leucopogon juniperinus 11 Leucopogon lanceolatus var. lanceolatus 00 Leucopogon microphyllus 11 Leucopogon parvifl orus 10 Leucopogon setiger 11 Leucopogon virgatus 00 linearis 10 Lindsaea microphylla 10 Lissanthe strigosa 11 Livistona australis 00 Lobelia anceps 00 Lobelia andrewsii 00 Lobelia dentata 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Logania albifl ora 10 Lomandra brevis 11 Lomandra confertifolia 00 Lomandra cylindrica 00 Lomandra fi liformis 11 Lomandra fl uviatilis 11 Lomandra glauca 11 Lomandra gracilis 11 Lomandra longifolia 00 Lomandra multifl ora subsp. multifl ora 11 Lomandra obliqua 00 myricoides 10 10 Lophostemon confertus 00 Ludwigia peploides subsp. montevidensis 00 Lycopodium deuterodensum 10 Macrozamia communis 00 Macrozamia spiralis 11 fl avescens 00 Marsdenia rostrata 00 Marsdenia suaveolens 00 Melaleuca armillaris subsp. armillaris 11 11 11 Melaleuca hypericifolia 11 11 11 Melaleuca thymifolia 11 Melodinus australis 00 Mentha satureioides 00 Micrantheum ericoides 00 Microlaena stipoides var. stipoides 00 Micromyrtus ciliata 00 Microsorum scandens 00 Mirbelia rubiifolia 00 Mirbelia speciosa 00 Mitrasacme paludosa 00 Mitrasacme polymorpha 00

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Monotaxis linifolia 10 Monotoca elliptica 10 Monotoca scoparia 11 Morinda jasminoides 00 celastroides 00 00 howittiana 00 Myrsine variabilis 00 squamea subsp. squamea 00 Neolitsea dealbata 00 Notelaea longifolia 00 Notelaea ovata 00 Notelaea venosa 00 Notodanthonia longifolia 00 Olax stricta 10 microphylla 10 Olearia viscidula 10 Omalanthus nutans 00 Opercularia aspera 10 Opercularia diphylla 10 Opercularia hispida 10 Opercularia varia 10 Oplismenus aemulus 00 Oplismenus imbecillis 00 Oxalis chnoodes 00 Oxalis exilis 00 Oxalis perennans 00 Oxalis rubens 00 Ozothamnus diosmifolius 00 Palmeria scandens 00 Pandorea pandorana 00 Panicum simile 00 Parsonsia straminea 00 Paspalidium distans 00 Paspalum distichum 00 Passifl ora herbertiana subsp. herbertiana 00 fragilis 11 Patersonia glabrata 10

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High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Patersonia longifolia 11 11 Pelargonium australe 00 Pelargonium inodorum 00 Pellaea falcata 00 Pellaea paradoxa 00 Peperomia blanda var. fl oribunda 00 Peperomia tetraphylla 00 Persicaria decipiens 00 Persicaria praetermissa 00 lanceolata 11 Persoonia laurina 11 00 00 11 pulchella 11 11 squamulosum 11 buxifolia 00 Philotheca salsolifolia 00 Philotheca scabra subsp. scabra 00 Philydrum lanuginosum 00 Phragmites australis 00 Phyllanthus gunnii 00 Phyllanthus hirtellus 00 Phyllota phylicoides 11 Pimelea linifolia 10 Pittosporum multifl orum 00 Pittosporum revolutum 00 Pittosporum undulatum 00 Planchonella australis 00 Plantago debilis 00 Platycerium bifurcatum 00 Platylobium formosum 11 Platysace ericoides 10 Platysace lanceolata 00 Platysace linearifolia 10 Platysace stephensonii 10

B174 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Plectranthus parvifl orus 00 Poa affi nis 00 Poa labillardierei var. labillardierei 00 Poa poiformis var. poiformis 00 Podocarpus spinulosus 10 Polymeria calycina 00 Polyosma cunninghamii 00 Polyscias elegans 10 Polyscias murrayi 10 Polyscias sambucifolia 10 Polystichum australiense 00 Pomaderris andromedifolia 00 Pomaderris discolor 00 Pomaderris elliptica subsp. elliptica 00 Pomaderris ferruginea 00 Pomaderris intermedia 00 Pomaderris lanigera 00 Pomax umbellata 00 Poranthera corymbosa 00 Poranthera ericifolia 00 Poranthera microphylla 00 Potamogeton tricarinatus 00 Pratia purpurascens 00 densa 11 Prostanthera incisa 11 Prostanthera linearis 11 Pseudanthus pimeleoides 00 Pseuderanthemum variabile 00 Psilotum nudum 00 Psychotria loniceroides 00 Pteridium esculentum 10 Pteris tremula 00 Ptilothrix deusta 00 blakelyi 11 Pultenaea daphnoides 11 Pultenaea dentata 11 Pultenaea fl exilis 11 Pultenaea hispidula 11

Proc. Linn. Soc. N.S.W., 134, 2012 B175 MANAGEMENT OF ROOT ROT DISEASE

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Pultenaea linophylla 11 Pultenaea parvifl ora 00 Pultenaea retusa 11 Pultenaea scabra 10 Pultenaea stipularis 11 Pultenaea tuberculata 11 rupestris 00 Ranunculus inundatus 00 Ranunculus lappaceus 00 Rhagodia candolleana subsp. candolleana 00 Rhodamnia rubescens 10 Rhytidosporum procumbens 00 Ricinocarpos pinifolius 00 Ripogonum album 00 Rorippa gigantea 00 Rubus moluccanus var. trilobus 00 Rubus parvifolius 00 Rubus rosifolius 00 Rulingia hermanniifolia 00 Rumex brownii 00 Samolus repens 00 Santalum obtusifolium 00 Sarcocornia quinquefl ora subsp. quinquefl ora 00 Sarcopetalum harveyanum 00 Scaevola ramosissima 10 Schelhammera undulata 00 Schizaea bifi da 00 Schizaea fi stulosa 00 Schizaea rupestris 00 Schizomeria ovata 00 Schoenus apogon 00 Schoenus brevifolius 00 Schoenus ericetorum 00 Schoenus imberbis 00 Schoenus lepidosperma subsp. pachylepis 00 Schoenus melanostachys 00 Schoenus moorei 00 Scolopia braunii 00

B176 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Selaginella uliginosa 10 Senecio bipinnatisectus 00 Senecio hispidulus 00 Senecio lautus 00 Senecio linearifolius 00 Senecio minimus 00 Sigesbeckia orientalis subsp. orientalis 00 Sloanea australis 00 Smilax australis 00 Smilax glyciphylla 00 Solanum americanum 00 Solanum aviculare 00 Solanum prinophyllum 00 Solanum stelligerum 00 Sowerbaea juncea 00 Sphaerolobium vimineum 10 Spinifex sericeus 00 Sporadanthus gracilis 00 Sporobolus virginicus 00 11 Stackhousia viminea 00 salignus 00 Stephania japonica var. discolor 00 Stylidium graminifolium 11 Stylidium laricifolium 00 Stylidium lineare 11 Stylidium productum 11 Styphelia trifl ora 11 Styphelia tubifl ora 11 Styphelia viridis subsp. viridis 11 paludosum 00 subsp. glomulifera 00 Synoum glandulosum subsp. glandulosum 00 Syzygium australe 00 Syzygium oleosum 10 Syzygium paniculatum 00 Tasmannia insipida 11 Telopea speciosissima 11

Proc. Linn. Soc. N.S.W., 134, 2012 B177 MANAGEMENT OF ROOT ROT DISEASE

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Tetragonia tetragonioides 00 Tetraria capillaris 00 Tetrarrhena turfosa 00 Tetratheca ericifolia 11 Tetratheca neglecta 11 Tetratheca shiressii 11 Tetratheca thymifolia 11 Thelionema umbellatum 00 Themeda australis 10 Thysanotus juncifolius 10 Thysanotus tuberosus subsp. tuberosus 10 Todea barbara 00 Toona ciliata 00 Trachymene incisa subsp. incisa 00 Trema tomentosa var. aspera 00 Tricoryne elatior 00 Tricoryne simplex 00 Tricostularia paucifl ora 00 Triglochin procera 00 Triglochin striata 00 neriifolia 00 Tristaniopsis collina 00 00 Trochocarpa laurina 10 Trophis scandens subsp. scandens 00 Tylophora barbata 00 Urtica incisa 00 Utricularia australis 00 Utricularia dichotoma 00 Utricularia laterifl ora 00 Utricularia uliginosa 00 Vernonia cinerea var. cinerea 00 Veronica plebeia 00 Villarsia exaltata 00 Viminaria juncea 00 Viola betonicifolia subsp. betonicifolia 00 Viola hederacea 00 Viola sieberiana 00

B178 Proc. Linn. Soc. N.S.W., 134, 2012 D.A. KEITH, K.L. McDOUGALL, C.C. SIMPSON AND J.L. WALSH

High, moderate or High or moderate Taxon low susceptibility to susceptibility to Phytophthora (known or Phytophthora (known or suspected) suspected) Wahlenbergia gracilis 00 Westringia fruticosa 00 Wilkiea huegeliana 00 Woollsia pungens 10 Xanthorrhoea arborea 11 Xanthorrhoea latifolia subsp. latifolia 11 Xanthorrhoea macronema 11 Xanthorrhoea media 11 Xanthorrhoea resinosa 11 Xanthosia pilosa 00 Xanthosia tridentata 00 Xerochrysum bracteatum 00 pyriforme 10 Xyris gracilis 00 Xyris operculata 00 Zieria compacta 00 Zieria laevigata 00 Zieria pilosa 00 Zieria smithii 00 Zornia dyctiocarpa var. dyctiocarpa 00

Proc. Linn. Soc. N.S.W., 134, 2012 B179 B180