Journal of Applied Ecology 2010, 47, 1310–1319
doi: 10.1111/j.1365-2664.2010.01871.x
Wind-assisted migration potential of the island
sugarcane planthopper Eumetopina flavipes
(Hemiptera: Delphacidae): implications for managing
incursions across an Australian quarantine frontline
Kylie L. Anderson1*, Ted E. Deveson2, Nader Sallam3 and Bradley C. Congdon1
1
School of Marine and Tropical Biology, James Cook University, PO Box 6811, Cairns, Qld 4870, Australia;
Locust Forecasting and Information, Australian Plague Locust Commission, GPO Box 858, Canberra, ACT 2601,
Australia; and 3BSES Limited, PO Box 122, Gordonvale, Qld 4865, Australia
2
Summary
1. The identification of dispersal mechanisms which facilitate particular biological invasions is paramount for the successful management of invasive species. If the dispersal mechanism promotes
high propagule pressure, the probability of successful establishment and spread is enhanced.
2. Invasive species may enter mainland Australia from Papua New Guinea via the Torres Strait
islands, and their dispersal through the region may be assisted by wind. The island sugarcane planthopper Eumetopina flavipes is of particular concern to Australian quarantine authorities. Long-distance, wind-assisted immigration from Papua New Guinea may be responsible for the continued
presence of E. flavipes in the Torres Strait islands and on the tip of mainland Australia. Simulation
was used to predict E. flavipes wind-assisted migration potential from Papua New Guinea into the
Torres Strait islands and mainland Australia. Field studies were used to test the predictions.
3. Wind-assisted immigration from Papua New Guinea was predicted to occur widely throughout
the Torres Strait islands and the tip of mainland Australia, especially in the presence of tropical
depressions and cyclones. Simulation showed potential for a definite, seasonal immigration which
reflected variation in the onset, length and cessation of the summer monsoon.
4. In general, simulation predictions did not explain E. flavipes observed infestations. The discrepancy suggests that post-colonization processes such as the temporal and spatial availability of host
may be equally or more important than possible wind-assisted immigration in determining population establishment, persistence and viability.
5. Despite the potential for wide-spread, annual immigration throughout the Torres Strait islands
and the tip of mainland Australia, E. flavipes control may be possible by managing the cultivation
of host plants on an ongoing annual basis to avoid recolonization, especially prior to or during critical immigration periods.
6. Synthesis and applications. Wind may promote significant incursions of E. flavipes from Papua
New Guinea into northern Australia. Management strategies should consider the relative importance of both pre- and post-invasion processes in determining establishment success, so that
response measures can be implemented at the appropriate stage of invasion. In this way, successful
control may be enhanced, serving to reduce the overall cost of invasion.
Key-words: invasion, island, long-distance dispersal, Papua New Guinea, propagule pressure, sugarcane
Introduction
*Correspondence author. E-mail: kylie.anderson1@jcu.edu.au
The likelihood that a species will successfully colonize a new
region is dependent upon a variety of pre- and post-invasion
ecological processes. Primary amongst the pre-invasion
2010 The Authors. Journal compilation 2010 British Ecological Society
Wind-assisted immigration of an invasive pest 1311
processes is the ability to reach new locations. This ability may
be enhanced through the use of particular dispersal mechanisms (Williamson 1996; Ruiz & Carlton 2003). Should the dispersal mechanism promote high propagule pressure, then
successful arrival, establishment, persistence and spread is far
more likely (Grevstad 1999; Simberloff 2009).
Many studies have focused on post-invasion determinants
of establishment success, and not on pre-invasion processes
(Kolar & Lodge 2001; Puth & Post 2005). If the relative importance of different dispersal mechanisms used by a particular
pest is well understood, there may be a chance to disrupt these
mechanisms and so reduce the risk of new invasions or recolonization (Carlton & Ruiz 2005). Such pre-emptive management is always preferable due to the expense involved in
post hoc reactive control and eradication (Leung et al. 2002;
Hulme 2006).
A number of dispersal mechanisms that may facilitate invasive species movement into Australia have been noted (Stanaway et al. 2001; Pheloung 2003; Lintermans 2004; Floerl &
Inglis 2005). One pathway into northern Australia is from
Papua New Guinea (PNG) through the Torres Strait islands
(TS) (Fig. 1). The Torres Strait encompasses approximately
48, 000 km2 between the southern coast of PNG and the tip of
Cape York, Queensland, Australia. There are over 200 islands
in the Torres Strait, seventeen of which are permanently inhabited by Torres Strait islanders of Melanesian origin. On the tip,
or northern peninsula area (NPA) of Cape York, Australia, a
further five communities of Torres Strait islander as well as
mainland Aborigines occur. Islands ⁄ communities are clustered
into groups based loosely upon geography and cultural
relationships (Fig. 1; Table 2). In keeping with Melanesian
traditions, varying degrees of subsistence agriculture occur in
both the TS and NPA. Gardens can contain a mix of plants
that may act as hosts for exotic pests and diseases that are not
present in commercial production areas on mainland Australia.
The TS are of major concern to Australian quarantine
authorities because of the unique variety of potential dispersal
mechanisms (Walker 1972; Kikkawa, Monteith & Ingram
1981; Lindsay 1987). Very little empirical information exists on
the specific mode of operation of different mechanisms, their
relative importance, and whether successful establishment
could result from invasive species using them. Of these, annual,
north-westerly monsoonal trade winds may be significant
(Farrow & Drake 1978; Farrow et al. 2001). Unlike other
mechanisms, wind may provide the perfect opportunity for a
‘continuing rain of propagules’ from PNG into the TS ⁄ NPA,
thus enhancing the survival of exotic species arriving this way
(Thresh et al. 1983; Simberloff 2009).
The island sugarcane planthopper Eumetopina flavipes Muir
(Hemiptera: Delphacidae) poses a high-risk quarantine threat
to the commercial production of sugarcane in Australia.
E. flavipes is the only known vector for Ramu stunt, a debilitating disease of sugarcane that occurs in PNG, but not Australia
(Shivas & Schneider 1999). Disease-free populations of E. flavipes are established in the leaf whorls of sugarcane grown in
gardens throughout the TS and NPA (Anderson, Sallam &
Congdon 2009). Despite the threat posed by incursions of
Ramu stunt vectored by these populations, virtually nothing is
Fig. 1. Map of southern Papua New Guinea
and Torres Strait and northern peninsula
area of Queensland, Australia, showing traditional island ⁄ community groups.
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
1312 K. L. Anderson et al.
known of E. flavipes dispersal potential. In general, planthoppers rely on wind for migrations over significant distances
(Kisimoto & Rosenberg 1994). Consequently, it has been
hypothesized that wind-assisted, long-distance migration from
PNG may explain, at least in part, the distribution and extinction ⁄ recolonization dynamics of E. flavipes in the TS ⁄ NPA
(Anderson, Sallam & Congdon 2009). This hypothesis remains
untested.
The likelihood and relative magnitude of long-distance,
wind-assisted migration can be determined using trajectory
analyses that incorporate meteorological data and ecological
parameters of the organism of interest (Reynolds et al. 1997).
In this study, such analyses were used to determine if windassisted migration of E. flavipes from PNG into the TS ⁄ NPA
and beyond is possible, and to gain an insight into its potential
frequency and the likely resulting distribution. Information on
mechanisms that contribute to dispersal, and thus impact upon
invasion success, are essential for making informed management decisions. The results from this study will contribute
directly to the development of management options that may
reduce the risk of E. flavipes incursion into commercial Australian sugarcane.
Materials and methods
SOURCE POPULATION
E. flavipes source population was defined as an area of roughly
2500 km2, extending approximately 260 km along the southern coast
of PNG and 100 km inland from the PNG coast, with the Fly River
forming the north-eastern boundary, and the border between PNG
and West Papua forming the western boundary (Fig. 4). The environment is mainly lowland alluvial plains and fans, and freshwater
swamps (Paijmans 1976), and contains an abundance of E. flavipes
‘wild’ host plants, these being Saccharum robustum Brandes & Jeswiet
ex Grassl and S. spontaneum L. which form pure stands in suitable
habitat (Paijmans 1976). As well, E. flavipes has been sampled on
the highly favoured hosts S. edule Hassk., S. officinarum L. and
S. ‘hybrids’ in local village gardens and surrounds (Magarey et al.
2002).
The source population is represented as a grid in the model, and
the distribution of insects within the source population is based on
the number of insects within each grid square (Rochester et al. 1996).
The starting location of each insect inside each grid square is randomly generated (Rochester et al. 1996). In this study, the source
population contained 250 · 10 km2 grid squares, and we nominated
40 insects per 10 km2 grid square, giving a total 10 000 individuals
migrating on each date. The size of the source population was used as
an index of the relative density of possible migrants. In light of
recently published data which shows E. flavipes abundance in PNG
may be as high as 201 adults per plant (Anderson, Sallam & Congdon
2009), the specified 40 insects per 10 km2 may be highly conservative,
especially in areas of high host abundance.
THE LONG-DISTANCE MIGRATION MODEL
The long-distance migration model (Rochester et al. 1996) used in
this study was developed to predict the change in distribution of
Helicoverpa moths following a migration event. Fallout regions
were accurately predicted by the model for a variety of noctuid
moths (Gregg, Del Socorro & Rochester 2001). The model has
since been used to show that winds between 100 and 400 m altitude
were sufficient to transport mosquitoes from PNG into the TS and
onto mainland Australia during the monsoon season (Ritchie &
Rochester 2001), as well as to predict trajectories for identifying the
direction and distance of locust migrations in Australia (Deveson
et al. 2005).
The long-distance migration model uses a number of sub-models
to calculate a resulting distribution following a period of migration,
in the following manner (from Rochester et al. 1996). First, a representative, random sample of ‘insects’ is generated by selecting their
location from a source population defined by the user. Then, each
insect is flown along its trajectory, which is determined by the wind
velocities around it and its responses to environmental conditions
experienced during the flight. The responses are randomly selected
from a set of possible responses (the range of which is specified by the
user), which can change during the flight. The end point of each trajectory is accumulated and passed to the result population distribution sub-model, and once the result distribution remains constant, the
final numbers and distribution of insects is calculated. When the
sub-model parameters are random variables, their values are randomly selected from a uniform probability distribution using the
Generic Spatial Insect Model (GenSIM) random variates generator.
The assignment of arbitrary distributions to the random model
parameters enables the model to be flexible as it examines various
behavioural influences on long-distance migration (Rochester et al.
1996). In doing this, the full range of parameter values and their
impact on flight is examined during the simulations, and is thus
reflected in the resulting distribution.
FLIGHT PARAMETERS
A number of parameters are required by the model in order to calculate flight direction and distance during the simulations. Virtually
nothing is known about E. flavipes migratory capacity, but migratory
flight behaviour is well documented for a range of other planthopper
species. In keeping with the majority of migratory take-offs by planthoppers in tropical regions occurring at dusk (Padgham, Perfect &
Cook 1987), E. flavipes has been observed to move to the stalk tips
of commercial sugarcane at Ramu Agri-Industries, PNG, at dusk
(K. Korowi, unpublished data). For this reason the take-off time
specified in the model was 18Æ30 AEST. The flight bearing offset angle
required by the model allows the simulated flying insects to ‘control’
the direction of flight. In nature, many insects are capable of this, particularly when correcting for crosswind drift (Dingle 1996; Chapman
et al. 2008). However, planthoppers are known to migrate at altitudes
where the wind speed exceeds their flight speed, so their flight
displacement is primarily a function of wind direction and speed
(Kisimoto & Rosenberg 1994; Riley et al. 1994). The offset angle
specified in this study thus allows for nil to minor control over flight
direction during simulations. In the absence of data for E. flavipes,
the remaining parameters were based on ranges published for Nilaparvata lugens Stål and Sogatella furcifera (Horvath) (Ohkubo 1973;
Seino et al. 1987; Watanabe & Seino 1991; Kisimoto & Rosenberg
1994) (Table 1).
SIMULATIONS
The wind sub-model uses outputs from the limited area prediction
system (LAPS) regional atmospheric circulation model run by the
Australian Bureau of Meteorology (BOM) (Puri et al. 1998), and was
first used to generate wind trajectories for each 24-h period between
1 January 2003 to 31 December 2007, from three PNG locations,
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
Wind-assisted immigration of an invasive pest 1313
Table 1. List of estimated Eumetopina flavipes flight parameters
Parameter
Minimum
Maximum
Flight
Flight
Flight
Flight
45
0
1
100
)45
2
24
1000
bearing offset angle (degrees)
speed (m s)1)
duration (h)
altitude (m)
Table 2. Torres Strait island and northern peninsula area locations
sampled for predicted numbers of Eumetopina flavipes from resulting
distribution
Traditional
group
Location
GPS co-ordinates
NPA
Bamaga
New Mapoon
Injinoo
10053¢38.13¢¢S 142023¢20.76¢¢E
10052¢01.38¢¢S 142023¢08.05¢¢E
10054¢32.13¢¢S 142019¢24.57¢¢E
Inner
Muralug
Ngurupai
Waiben
Keriri
10036¢33.57¢¢S
10035¢34.89¢¢S
10034¢55.79¢¢S
10033¢18.37¢¢S
142012¢34.81¢¢E
142014¢53.99¢¢E
142013¢19.49¢¢E
142013¢10.20¢¢E
Western
Moa - Kubin
Moa - St Pauls
Badu
Mabuiag
10014¢02.02¢¢S
10011¢06.68¢¢S
10009¢01.17¢¢S
9057¢25.26¢¢S
142013¢14.27¢¢E
142019¢42.79¢¢E
142010¢12.25¢¢E
142011¢13.88¢¢E
Top Western
Boigu
Dauan
Saibai
9013¢50.34¢¢S 142013¢11.80¢¢E
9025¢08.35¢¢S 142032¢29.76¢¢E
9022¢54.16¢¢S 142036¢42.39¢¢E
Eastern
Ugar
Erub
Mer
9030¢27.72¢¢S 143032¢49.06¢¢E
9035¢08.24¢¢S 143046¢14.67¢¢E
9054¢53.91¢¢S 144002¢29.55¢¢E
Central
Masig
Iama
Poruma
Warraber
9045¢01.82¢¢S
9053¢54.93¢¢S
10003¢00.23¢¢S
10012¢16.69¢¢S
143024¢46.84¢¢E
142046¢06.97¢¢E
143003¢54.22¢¢E
142049¢24.35¢¢E
being Morehead (inland PNG) 8037¢37¢¢S 141038¢19¢¢E, Buji (Coastal
PNG) 9009¢05¢¢S 142014¢17¢¢E, and Daru (Coastal PNG) 9004¢42¢¢S
143012¢36¢¢E. The three locations lie in the north-west, north-east and
south of the source population area, respectively. Each 24-h wind trajectory projection was saved as a graphics file, and visually assessed.
For each 24-h projection, if any of the wind trajectories ran from the
PNG source population into the TS ⁄ NPA, the full model which
incorporated insect flight parameters was run for that date, and the
resulting distribution of immigrants calculated at 21 TS ⁄ NPA locations (Table 2). Alternatively, if all wind trajectories ran in a northerly direction away from the source population, nil immigration into
the TS ⁄ NPA was recorded and the full model was not run. Trajectory
simulations were not possible for several nights in July 2005 or 15
February 2006, because LAPS outputs were unavailable.
DATA ANALYSIS
Differences in predicted patterns of seasonal long-distance, windassisted migration from PNG into the TS ⁄ NPA were investigated by
examining variation in monthly predicted immigration using nonparametric Kruskal–Wallis. This technique was used due to non-normality of the dataset (Quinn & Keough 2006).
The simulated TS ⁄ NPA spatial distribution was examined to determine whether certain TS ⁄ NPA locations or island ⁄ community
groups were at greater risk of immigration than others. First, the
frequency of immigration events was examined. If >0 immigrants
were observed within a location or island ⁄ community group on a
particular day, then it was classified as a ‘hit’, whereas zero immigrants were a ‘miss’. The frequency of hits and misses for each
TS ⁄ NPA location and group were compared using a two-way contingency table analysis, and associated Pearson v2 statistic (Quinn &
Keough 2006). Location data were natural logarithm transformed to
correct to non-normality (Quinn & Keough 2006), and anova and
LSD post hoc tests used to detect any significant difference in the
numbers of predicted immigrants per hit day between locations.
The Welch correction and Tamhane’s post hoc tests were used for the
group anova due to unequal variance (Quinn & Keough 2006).
E. flavipes simulated spatial distribution and abundance was compared to observed infestation at different TS ⁄ NPA locations; the latter were calculated using mean E. flavipes abundance per TS ⁄ NPA
location over time (see Anderson, Sallam & Congdon 2009 for
detailed field sampling methodology). Time constraints at some sampling locations in 2006 meant that all host plants were not sampled as
they were in 2008. To account for the differential sampling effort
between years, E. flavipes 2006 infestation was adjusted to reflect the
infestation expected for the total number of host plants present in that
year (H1), which was calculated as H1 = N1 ⁄ (t1 ⁄ t2), where N1 is the
number of plants sampled in 2006, t1 is the hours spent sampling in
2006, and t2 is the hours spent sampling in 2008. To determine
whether simulated patterns of wind-assisted immigration alone could
explain the observed pattern of infestation, regression analysis was
performed on ln(x + 1) transformed data to correct non-normality.
In addition, a non-parametric Kendall’s tau test was used to determine if any other relationship existed between predicted immigration
and observed infestation (Quinn & Keough 2006).
A wide array of stochastic processes may affect establishment following immigration (Williamson 1996; Lockwood, Hoopes & Marchetti 2007). It is unknown what these might be for E. flavipes. For this
reason, three different establishment probabilities (100%, 30% and
10%) were used to account for these factors in comparisons between
simulated immigration and observed infestation rates. This also effectively examines the changes that would occur as a result of varying
source population (propagule) size during the modelling procedure.
Results
ANNUAL PATTERNS OF WIND-ASSISTED IMMIGRATION
INTO THE TS ⁄ NPA
No immigration was predicted from PNG into the TS ⁄ NPA
from June through to October. For November to May, the
mean total predicted number of immigrants varied significantly between months (v2 = 19Æ96, d.f. = 6, P < 0Æ01;
Fig. 2). Immigration in November occurred in only two of the
five study years, with November experiencing the lowest rates
of all months in which immigration occurred. The highest
immigration was consistently predicted to occur during January, February and March, with average rates between approximately 4000 and 7000 individuals. Predicted numbers of
immigrants did not differ significantly between these three
months between years (v2 = 3Æ140, d.f. = 2, P = 0Æ21). During December, April and May, simulated immigration rates
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
1314 K. L. Anderson et al.
Fig. 2. Mean number of predicted Eumetopina flavipes immigrants per month (±2 SE)
throughout the Torres Strait and northern
peninsula area, Cape York, Australia, from
January 2003 to December 2007.
were lower, but varied considerably more between years. In
December, highly variable numbers of immigrants occurred
every year during the study (between 24 and 5000), while in
April, immigrants occurred in only three of the five years and
numbers were highly variable (between 0 and 7455). Only in
2006 were immigrants predicted in May.
The results suggest that for E. flavipes the migratory season
may begin in December, or occasionally late November, but
that the exact initiation date varies from year to year. The
migratory season usually ends in March, but in some years it
can continue until April. Very rarely would the season end in
May, as it did in 2006. However, in that year severe tropical
cyclone ‘Monica’ traversed Cape York Peninsula and the
Northern Territory of Australia from mid to late April. This
resulted in strong winds from PNG into the TS ⁄ NPA persisting until early May, the only year during the study when they
did so. This finding clearly suggests that extreme weather
events can increase variation in the number of immigrants
reaching the TS ⁄ NPA and lengthen the migratory season for
up to one and a half to two months beyond likely long-term
averages.
SIMULATED SPATIAL PATTERNS OF WIND-ASSISTED
Fig. 3. Model simulation of Eumetopina flavipes trajectories from
Morehead, Buji and Daru, Papua New Guinea, for a 24-h flight from
18.30 AEST on 12 March 2003 where the modelled trajectories end
south of Cairns, Australia.
IMMIGRATION INTO THE TS ⁄ NPA
Wind-assisted migration from the theoretical PNG source
population to all sampled locations in the TS ⁄ NPA appears
possible. Importantly, it was noted during visual assessment of
the 24-h wind trajectory projections, that some trajectories
from PNG end south of Cairns, which is a major commercial
sugarcane production area, as occurred on 12 March 2003
(Fig. 3). In response to this result, BOM Mean Sea Level Pressure (MSLP) weather charts were examined for (i) 12 March
2003 at 4 pm and 10 pm AEST, (ii) 4 am, 10 am and 4 pm on
the 13 March 2003, and (iii) for the 20 days during the study
period where every TS ⁄ NPA location was predicted to receive
immigrants. A number of synoptic scenarios appear to be
responsible. Very long southward trajectories appear to be
associated with a depression or cyclone present further south
over Cape York, and in general, blanket immigration is associated with either (i) a low pressure system or a tropical cyclone
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
Wind-assisted immigration of an invasive pest 1315
in the Gulf of Carpentaria, (ii) a low over the tip of Cape York
Peninsula which produces similar southward movement but
over shorter distances, and (iii) a more complex situation with
lows to the west and east with a ‘trough line’ running across
top of Cape York Peninsula or through the TS.
The proportion of hits differed significantly between
TS ⁄ NPA locations (v2 = 2261Æ50, d.f. = 20, P < 0Æ001) and
island ⁄ community groups (v2 = 2138Æ47, d.f. = 5, P <
0Æ001). This is because not every TS ⁄ NPA location or group
sampled was hit with immigrants on each day. For example,
most Central group locations as well as all Top Western and
Eastern group locations were hit on 12 February 2004
(Fig. 4a), whilst on the 11 March 2005, all locations except
Mer were hit (Fig. 4b).
For hit days only, the mean ln(predicted number of immigrants per year) differed significantly between TS ⁄ NPA
island ⁄ community groups (F5, 44Æ71 = 120Æ88, P < 0Æ001;
Fig. 5). The Top Western group was predicted to receive the
most immigrants per year of all groups, followed by the Eastern, then the Central groups (Tamhane post hoc tests). The
NPA, Inner and Western groups received the fewest immigrants, with numbers of immigrants being relatively similar
(Tamhane post hoc: NPA and Inner P = 0Æ612, Inner and
Western P = 0Æ193, NPA and Western P = 0Æ045; Fig. 5).
This pattern was repeated on a finer scale, as the mean
ln(predicted number of immigrants per year) also differed significantly between locations (F20, 104 = 21Æ57, P < 0Æ001;
Fig. 6). Boigu was predicted to receive the greatest numbers,
which then decreased gradually through the Eastern and Central locations in a south-easterly to southerly direction from
mainland PNG (Fig. 6). The exception to this was Mer island
in the Eastern group, which received lower numbers than
Masig (Central group). Mer lies in the most easterly position
of all TS ⁄ NPA locations and is the furthest location from
PNG in a south-easterly direction (see Fig. 1). The lowest
numbers of immigrants consistently occurred at all locations
within the Western, Inner and NPA groups, decreasing slightly
but not significantly between groups, respectively (LSD post
hoc tests), with increasing distance from PNG (Fig. 6). All of
these locations lie in a southerly directly from the PNG source
population.
(a)
SIMULATED VERSUS OBSERVED INFESTATION
There is no significant linear (F1, 20 = 0Æ50, Adj R2 = )0Æ025,
P = 0Æ49) or monotonic (correlation coefficient = 0Æ12,
P = 0Æ46, n = 21) relationship between the mean predicted
immigration and the mean observed infestation per TS ⁄ NPA
location (Fig. 7). Therefore, in general, the number of
immigrants predicted to reach each location per year due to
wind-aided migration alone does not match observed patterns
of E. flavipes infestation throughout the TS ⁄ NPA.
These data can also be compared to the three hypothetical levels of establishment success. The results indicate that
some individual locations may fit the theoretical relationships. For example, the observed infestations at Saibai,
(b)
Fig. 4. Eumetopina flavipes simulated migration from theoretical
Papua New Guinea (PNG) source population (black shaded area) to
the Torres Strait island and northern peninsula area (NPA) of Cape
York, Australia (D sampling locations), for (a) 12 February 2004 and
(b) 11 March 2005. Light grey to dark grey squares indicates a low to
high abundance, respectively, of potential immigrating Eumetopina
flavipes.
Fig. 5. Mean number of predicted E. flavipes immigrants per year
(±2 SE) by Torres Strait island and northern peninsula area of
Queensland, Australia, traditional island ⁄ community group.
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
1316 K. L. Anderson et al.
across most groups. Importantly, there are a number of
locations in the TS ⁄ NPA with no infestation at all, despite
relatively high rates of predicted immigration.
Discussion
Fig. 6. Mean number of predicted Eumetopina flavipes immigrants
per year (±2 SE) by Torres Strait island and northern peninsula area
of Queensland, Australia, traditional island ⁄ community group.
Bamaga, Ngurupai and Waiben appear consistent with
100% of the predicted immigrants successfully colonizing
these locations (Fig. 7). Similarly, the infestations at Masig
and Erub appear consistent with 30% of the predicted
immigrants successfully establishing (Fig. 7). However, there
does not appear to be a general level of establishment success that would allow the numbers predicted to match
observed infestation throughout the TS ⁄ NPA. Similarly,
within island ⁄ community group, there does not appear to
be a general level of establishment success where the predicted numbers of immigration match the observed infestation. For example, the predicted immigration to all
locations within the NPA group is identical, but the
observed infestation is highly variable; a pattern repeated
The simulation results strongly suggest that wind provides
multiple opportunities for E. flavipes to migrate from PNG
into the TS ⁄ NPA. Although based on general planthopper
flight behaviour, this result could be true for any organism
that migrates with wind assistance. Simulations predict that
immigration should begin in late November or December,
peak between January and March, and rarely continue past
April. This finding is consistent with the frequently observed
movement of large numbers of different insect taxa from
PNG into the TS during the monsoon season (Farrow &
Drake 1978). No immigration was predicted from June
through to October during the dry season, when circulation is
dominated by south-easterly trade winds (Suppiah 1992).
Variability in the onset, length and cessation of the monsoon
season, including associated summer monsoon winds, is complex and closely linked to cycles that include the MaddenJulian oscillation, El Niño ⁄ Southern oscillation phenomenon
and the Quasi-biennial oscillation (Suppiah 1992). The
intricate way that these and other cycles interact to cause
monsoon onset make it very difficult to develop accurate,
predictive models of year–year variation in immigration from
PNG. However, analysis of wind direction and strength associated with particular synoptic events may allow risk alerts at
appropriate times.
On average, cyclones pass through the TS once every eight
or so years (Babbage 1990). Our study spanning five years and
including one cyclone is thus fairly characteristic of average
extreme weather event occurrence. Cyclones are known to
affect monsoon onset (Suppiah 1992), so delayed monsoon ces-
Fig. 7. Relationship between the mean number of predicted Eumetopina flavipes immigrants per year and the mean observed E.
flavipes infestation per year for all TS ⁄ NPA
locations. Lines represent the theoretical
expected infestation should 100%, 30% or
10% of the mean number of predicted immigrants establish (traditional island ⁄ community group symbols: NPA , Inner ,
Western , Central , Top Western ,
Eastern ).
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
Wind-assisted immigration of an invasive pest 1317
sation in April 2006 resulting in a continuation of the immigration season until May of that year, may have been caused by
the presence of TC Monica. As a general observation, a depression or cyclone in the Gulf of Carpentaria or over Cape York
Peninsula establishes suitable wind conditions to allow for
long-distance, widespread immigration from PNG into northern Australia. Such wind conditions were sufficient to carry
mosquitoes from PNG to the NPA for 79% and 57% of the
days during December 1997 and January 1998, respectively
(Ritchie & Rochester 2001). Winds on one particular night
transported mosquitoes a distance of approximately 678 km
(Ritchie & Rochester 2001). For planthoppers, seasonal
displacements in Asia are known to occur annually on
monsoon winds, particularly those associated with frontal
depressions and typhoons (Rosenberg & Magor 1987). The
continuous air currents allow long-distance transport from
several hundreds to thousands of kilometres away from the
source population (Kisimoto 1976; Seino et al. 1987). The
development of a low pressure system in the Gulf of Carpentaria, at the least, was thought to be essential for insect migration from PNG to Cape York (Farrow & Drake 1978). Our
results suggest there is potential for E. flavipes to easily be
transported similar distances without the aid of such systems.
However, when low pressure systems are present, not only
may they extend the immigration season and potentially
promote widespread immigration, they may also potentially
transport E. flavipes south of the NPA to commercial
sugarcane growing regions near Cairns. Of interest is that
E. flavipes has not been detected south of the NPA. Many
factors could be responsible for this anomaly. Perhaps it is
only a matter of time, as was the case with the incursion of
sugarcane smut into the Ord River Irrigation Area in Western
Australia, which was highly suspected to be wind-borne from
Indonesia (Croft & Braithwaite 2006).
Even allowing for minor flight control, it appears that prevailing wind conditions and distance from PNG are ultimately
responsible for the resulting distribution of E. flavipes. The
Top Western group of islands may have received the greatest
number of immigrants because they are close to PNG, and
because trajectories over a range of wind directions, from
north-west through to south-east, contact islands in the group,
particularly Boigu. This finding is consistent with the Top Western islands, of all islands, receiving the greatest numbers of
exotic fruit fly species from PNG (Technical Advisory Panel
on exotic fruit flies for Plant Health Committee and Primary
Industries Standing Committee 2004), and other wind-dispersed organisms like disease-carrying midges and mosquitoes
(Johansen et al. 2003). The predicted frequency of immigrants
per group dwindles as northerly winds become more frequent
and ⁄ or with greater distance from PNG. Farrow & Drake
(1978) suggest that wind trajectories from the Papuan region
would rarely reach Cape York, so that a successful southward
crossing of the TS was unlikely. In contrast, our results suggest
that E. flavipes, at least, may regularly reach the NPA during
the monsoon season, and locations in the Western, Inner and
NPA groups, albeit lower than other groups, may still be at
risk of annual invasion.
Clearly, uncertainties are an issue in predictive modelling,
and error and bias can cause predictions to fail (Regan, Colyvan & Burgman 2002). In this case, the impact of altering some
model parameters (for example to reflect natural abundance
variation in the source population) may lead only to over or
under-estimation of individuals in the resulting distribution.
As discussed earlier, the resulting distribution is primarily driven by wind, not arbitrary decisions made during the modelling process. Therefore the predictive power of the model itself
is high, and distributional inferences are unlikely to be incorrect (Johnson & Gillingham 2008).
Overall, our results demonstrate a high potential for widespread, wind-assisted immigration from PNG into the
TS ⁄ NPA. There are some locations where wind-assisted immigration alone appears to be a good predictor of observed infestation. It may be that levels of immigration are sufficient at
those locations to ensure that establishment is highly successful. In general however, the predicted distribution does not
match the observed patterns of infestation throughout the
TS ⁄ NPA. Importantly, E. flavipes is absent at some locations,
despite predicted wind-assisted immigration and abundant
host plants. These findings suggest that alternate factors may
influence establishment in the TS ⁄ NPA. On-island processes
and or propagule pressure provided by other immigration
pathways may be of equal, or greater relative importance in
determining the distribution and abundance of E. flavipes in
the TS ⁄ NPA.
Of the biotic factors that influence establishment and persistence, especially for phytophagous insects like E. flavipes, the
distribution and availability of host is among the most important (Hanski 1998; Loxdale & Lushai 1999). Host abundance
and stability varies considerably throughout the TS ⁄ NPA due
to location specific cultivation practices, and for this reason it
has been suggested as a major, if not the most, important determinant of E. flavipes establishment success (Anderson, Sallam
& Congdon 2009). The general discrepancy between predicted
immigration and observed infestation further supports this
hypothesis. However, there are still exceptions to this generality, with a number of locations known to have high host availability that have either no E. flavipes, or populations that
‘blink’ in and out of existence (Anderson, Sallam & Congdon
2009).
Anthropogenic movement of infested sugarcane may also
contribute, at least in part, to recolonization and supplementation of existing infestations (Anderson, Sallam & Congdon
2007). The relative importance of human-mediated transport
in the TS ⁄ NPA is unknown, so from a management perspective the monitoring of such pathways must remain a priority.
Allsopp (1991) suggested eradication of E. flavipes in the
TS ⁄ NPA may be in order, and this may be achievable by pruning all leaf whorls off sugarcane plants at all locations simultaneously (Anderson, Sallam & Congdon 2009). Simulation
results suggest such a programme is unlikely to be successful
over time because there may be potential for replenishment of
populations annually during the monsoon season. Examination of the levels of sugarcane cultivation at locations where
host is present but E. flavipes is not may provide the clue as to
2010 The Authors. Journal compilation 2010 British Ecological Society, Journal of Applied Ecology, 47, 1310–1319
1318 K. L. Anderson et al.
how to keep populations at bay. Management of the wind vector itself is impossible. However, wind-borne immigration into
the TS ⁄ NPA from PNG appears predictable during certain
months of the year. Ongoing, annual management of host
plants either prior to or during critical immigration periods
may be used to effectively limit establishment, as well as reducing the size of existing infestations. Such a strategy may also
curtail the potential for stepping-stone type movements
between islands.
In conclusion, wind may be an important dispersal vector
for E. flavipes that could allow significant incursions into and
throughout the TS ⁄ NPA. E. flavipes is known to recolonize
certain TS ⁄ NPA locations following local extinction (Anderson, Sallam & Congdon 2009), and results suggest windassisted migration may contribute to such recolonization as
well as supplementation of existing populations. Despite this,
on-island dynamics of host availability may be as, if not more,
important than wind-assisted immigration in determining
establishment and levels of recurring infestation at specific
locations. In a bid to narrow down forces that may affect E.
flavipes invasion potential, research on alternate transport
pathways and on-island processes is ongoing.
Acknowledgements
This research was funded by the Sugar Research and Development Corporation and the Australian Centre for International Agriculture Research. Sincere
thanks are owed to all survey participants and volunteers, especially TS and
NPA Councils. We also thank Myron Zalucki, Wayne Rochester, Haikou
Wang, Jacqueline Balston, Hugh Dingle and Robert Anderson for their valuable support. Additionally, we thank the reviewers for comments which greatly
improved this manuscript.
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Received 26 May 2010; accepted 17 August 2010
Handling Editor: Quentin Paynter
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