invit - Australasian Plant Pathology Society

Go to
Table of Contents
EFFICACY OF A RISK MODEL TO PREDICT THE DISTRIBUTION OF
PHYTOPHTHORA CINNAMOMI IN THE GREATER BLUE MOUNTAINS WHA
Z-J. Newby A, B , D.I. Guest B , E.C.Y. Liew A and D. Ramp C
A Botanic Gardens Trust, Mrs Macquaries Road, Sydney, NSW, 2000
B Faculty of Agriculture and the Environment, Biomedical Building – C81, The University of Sydney, NSW, 2006
C School of the Environment, The University of Technology, Sydney, NSW, 2007.
ABSTRACT. A risk model for Phytophthora cinnamomi was developed and tested for the Greater Blue Mountain World
Heritage Area (GBMWHA) in NSW. The management of impacts is limited by knowledge of the distribution of
Phytophthora in these ecosystems, however risk models have the ability to meet part of this gap. We developed a risk model
for P. cinnamomi using climatic, topographical and anthropogenic layers, as well as information on the current known
distribution. The model was constructed in a GIS using Fuzzy analysis and a Weighted Distance Overlay, and was
subsequently tested by sampling across each of the eight reserves. Results indicate a correlation between the rate of
Phytophthora isolation and the risk level in four of the five strata. P. cinnamomi is widespread in the GBMWHA including
remote areas, but is more common in high visitation locations. The model is currently being used by land managers to
identify areas where management activities should be focussed.
INTRODUCTION
The Greater Blue Mountains was designated a World
Heritage Area in 1999 as a centre of ongoing ecological and
biological process as well as a place of in-situ conservation.
The area is home to more than 1500 plants (100 Eucalyptus
spp.) as well as 400 vertebrates, 50 mammals and 265 birds,
many of which have conservation status. Additionally, the
GBMWHA receives over 3 million tourists annually and is
home to another million residents (1). Disease caused by P.
cinnamomi is a direct threat to the GBMWHA.
Management of P. cinnamomi first requires an
understanding of where it occurs or where it is likely occur.
Little was known about the distribution of P. cinnamomi in
the GBMWHA prior to 2008. Distribution modelling can be
utilised to fill this gap and has the advantage of exploring
inaccessible, remote and rugged areas. Here we develop a
model of P. cinnamomi distribution (or risk) and assess its
effectiveness via comprehensive soil sampling.
RESULTS
Phytophthora was found right across the GBMWHA and P.
cinnamomi was found in all levels of risk, except the lowest
risk stratum. The rate of P. cinnamomi isolation increased
with increasing risk, except in the highest risk stratum (level
5) where the rate of isolation decreased to below that of
stratum 3. Other Phytophthora species were found at a
constant rate across all five levels (Figure 1)
100%
90%
80%
70%
60%
50%
40%
371 327 500 857 122
neg
P.sp
P.cinn
MATERIALS AND METHODS
The various environmental layers (Table 1) were inserted
into a GIS and re-scaled using a FUZZY analysis to reflect
their conduciveness to the establishment of P. cinnamomi,
such that the most conducive locations had the highest score.
Layers were weighted and overlaid, then individual risk
scores were summed to produce the risk model.
Table 1: Environmental layers used in the construction of
the model. Layers were re-scaled and weighed as outlined.
Variable Risk score Weight
rainfall
↑ to 600mm; max at 2
≤600mm
Temperature ↑ to max at 21°C; 2
↓beyond 24 ° C
Slope ↑ with ↑ slope 1
Wetness ↑ with ↑ wetness 1
Vehicular corridors; ↓ with distance 1 or 2
Water; Built up areas
Current isolations ↓ with distance 3
The model was then reduced to the sampling area (within
500 m of roads) and the remaining land stratified in five
levels of increasing risk. The GIS was used to randomly
allocate 1915 samples evenly across the five strata.
Soil sampling began in 2010 and continued into 2012,
producing 2176 samples. Each was assessed for the presence
of Phytophthora using the lupin baiting bioassay, and the
resulting data was returned to the GIS.
30%
20%
10%
0%
Strata 1 Strata 2 Strata 3 Strata 4 Strata 5
Figure 1. The distribution of Phytophthora within the
GBMWHA risk strata. Risk level increases from left to
right.
DISCUSSION
The risk model identified a positive correlation between the
rate of Phytophthora isolation and increasing risk from
strata 1 to 4. The apparent failure of the model in the highest
risk stratum could be due to sampling bias, as many of the
sites were inaccessible. Based on the risk factors used to
develop the model, there was a higher likelihood of P.
cinnamomi in the high risk parts of the landscape, however
it was not successfully isolated from the soil. This could be
resolved either by further sampling or the addition or
reweighting of risk factors used in the model. Nevertheless,
the model represents an important new management tool for
Phytophthora dieback in natural ecosystems.
ACKNOWLEDGEMENTS
National Parks and Wildlife Service; Royal Botanic Garden
and Domain Trust; Blue Mountains World Heritage
Institute, The University of Sydney.
REFERENCE
1. DECC, NSW (2008) 2008/491.
7th Australasian Soilborne Diseases Symposium 34