Evolutionary Applications
Evolutionary Applications ISSN 1752-4571
ORIGINAL ARTICLE
Population genetics suggest that multiple invasion
processes need to be addressed in the management plan of a
plant disease vector
Kylie L. Anderson and Bradley C. Congdon
School of Marine and Tropical Biology, James Cook University Cairns, Queensland, Australia
Keywords
colonization, invasion pathway, isolation by
distance, long-distance dispersal,
microsatellites, pest management,
planthopper.
Correspondence
Kylie L. Anderson, School of Marine and
Tropical Biology, James Cook University,
Cairns, Queensland, Australia.
Tel.: +61 428 783 649;
fax: +61 7 40421319;
e-mail: kylie.anderson1@jcu.edu.au
Received: 4 June 2012
In Revised form: 3 January 2013; Accepted: 7
January 2013
doi:10.1111/eva.12051
Abstract
The use of a multidisciplinary approach is becoming increasingly important when
developing management strategies that mitigate the economic and biological
costs associated with invasive pests. A framework of simulated dispersal is combined with life-history information and analyses of population genetic structure
to investigate the invasion dynamics of a plant disease vector, the island sugarcane planthopper (Eumetopina flavipes), through an archipelago of significant
Australian quarantine concern. Analysis of eight microsatellite loci from 648 individuals suggests that frequent, wind-assisted immigration from multiple sources
in Papua New Guinea contributes significantly to repeated colonization of far
northern islands. However, intermittent wind-assisted immigration better
explains patterns of genetic diversity and structure in the southern islands and on
the tip of mainland Australia. Significant population structuring associated with
the presence of clusters of highly related individuals results from breeding in-situ
following colonization, with little postestablishment movement. Results also suggest that less important secondary movements occur between islands; these
appear to be human mediated and restricted by quarantine zones. Control of the
planthopper may be very difficult on islands close to Papua New Guinea given
the apparent propensity for multiple invasion, but may be achievable further
south where local populations appear highly independent and isolated.
Introduction
The environmental and economic costs of biological invasions and pest management are key issues for many countries (Pimentel et al. 1999). Understanding the various
factors contributing to invasion success is important when
seeking to implement effective control strategies for pest
species. Foremost among factors influencing invasion success is the ability of an organism to disperse to new regions
(Lockwood et al. 2007). If an invasive species is regularly
transported along multiple pathways, the probability of its
successful establishment is increased (Kolar and Lodge
2001). Likewise, certain life-history traits such as high
reproductive capability are thought to favour establishment
and spread (Williamson 1996).
Importantly, the dispersal and establishment history
of an organism may be reflected in its spatial pattern of
population genetic structure (Sakai et al. 2001; Excoffier
660
et al. 2009). For example, multiple introductions via
multiple dispersal pathways can increase genetic diversity, and as a consequence, there may be little genetic
constraint to adaptation in a novel environment;
thereby enhancing invasive capability (Kolbe et al.
2004). Not only do population genetic data provide
valuable insight into the genetic consequences of invasion, they also provide information on movement pathways and invasion routes (Congdon et al. 1997; Suhr
et al. 2010; Zepeda-Paulo et al. 2010) and overall invasion potential and pest status (Darling et al. 2008; Jiang
et al. 2010). Taking a genetic approach to the management of invasive species and pests is gathering momentum; when coupled with ecological information on
dispersal and/or colonization mechanisms and life-history characteristics, population genetics analyses provide
a strong basis on which to formulate management strategies (Rollins et al. 2009).
© 2013 The Authors. Published by Blackwell Publishing Ltd. This is an open access article under the terms of the Creative
Commons Attribution License, which permits use, distribution and reproduction in any medium, provided
the original work is properly cited.
Anderson and Congdon
The island sugarcane planthopper, Eumetopina flavipes
Muir (Hemiptera; Delphacidae) is a significant invasive
agricultural pest because it is the only known vector for
Ramu stunt disease of sugarcane (Kuniata et al. 1994). In
1986, Ramu stunt significantly reduced commercial sugar
yields in Papua New Guinea by over 60%, and the disease
and vector remain of commercial significance today (Kuniata et al. 2001). Apparently, disease-free populations of
E. flavipes occur in Australia, but are restricted to northeast Queensland in the Torres Strait islands (TS) and in the
northern peninsula area (NPA) of Cape York (Fig. 1). The
presence of E. flavipes in north-eastern Australia represents
a significant quarantine threat to the commercial production of sugarcane in Australia, which occurs approximately
695 km south of the NPA (Sallam 2009).
Eumetopina flavipes and Ramu stunt disease are thought
to be native to Papua New Guinea (PNG) (Kuniata et al.
1994; Wilson 2004). E. flavipes is widespread throughout
PNG and resides only among the growing leaf rolls of four
common host species of Saccharum; S. ‘hybrids’ grown
mainly in commercial plantations at Ramu Agri-Industries,
S. officinarum and S. edule, which are grown in residential
gardens and S. robustum which grows wild and is highly
abundant in suitable habitat throughout PNG (Paijmans
1976; Magarey et al. 2002). These four host types form a
relatively continuous distribution across the landscape,
probably promoting large and stable E. flavipes populations
(Anderson et al. 2009).
Figure 1 Southern coast of Papua New Guinea, Torres Strait islands
and northern peninsula area, Australia showing potential Papua New
Guinea source populations, E. flavipes TS/NPA sampling locations
(marked with X) and quarantine zones (delimited by dashed lines).
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Genetics and management of an invading pest
A different situation exists in the TS/NPA, where E. flavipes occurs on the only two host plant types present, S.
‘hybrids’ and S. officinarum. Both are commonly cultivated
in local gardens as either single plants, or in small patches
that can contain multiple plants. Sugarcane may also grow
untended and wild at some locations. Both long-term survey data (Gough and Petersen 1984; Chandler and Croft
1986; Allsopp 1991; Grimshaw 1997; Magarey 1997, 2003)
and recent intensive sampling confirm that E. flavipes’ presence in the TS/NPA is highly variable in both space and
time, and that local extinctions and recolonization regularly occur (Anderson et al. 2009).
A number of potential dispersal pathways exist for E. flavipes in the Torres Strait. Simulation modelling suggests that
southward wind-assisted migration of E. flavipes may occur
from PNG into the TS/NPA during the summer monsoon
season, where the resulting number of immigrants per island
is a function of wind direction and distance from PNG
(Anderson et al. 2010). However, there was no significant
linear relationship between predicted immigration and
observed patterns of infestation throughout the TS/NPA
(Anderson et al. 2010). There were a small number of locations where wind-assisted immigration appeared to be a
good predictor of observed infestation, but E. flavipes was
absent at a number of other locations despite immigration
being predicted (Anderson et al. 2010). A number of postcolonization factors could account for the discrepancy. For
some species, these may include natural enemies and competitors, but these appear unlikely to impact on E. flavipes’
distribution and abundance in the TS/NPA. Regular field
surveys revealed that very few natural enemies were noted
and there are no other Eumetopina species present that could
compete for resources, as occurs in PNG. Anderson et al.
(2009) note that host plant availability varies in the TS/NPA
and is likely to affect the distribution and abundance of E.
flavipes. However, the presence of alternate and/or additional dispersal pathways, such as the human-mediated
movement of infested sugarcane, could easily facilitate
E. flavipes dispersal among island and mainland communities, and contribute to the establishment of new populations.
Should anthropogenic movement of infested sugarcane
occur, then E. flavipes movement should be restricted by
the special quarantine zones that occur between PNG and
mainland Australia. These zones have been established in a
bid to halt the movement of pests and diseases that could
damage Australia’s animal and plant industries (Australian
Government Department of Foreign Affairs and Trade
1985). Movement of ‘declared’ items is permitted within
PNG, the Torres Strait Protected Zone, the Special Quarantine Zone and mainland Australia, but not between zones
(Fig. 1). Sugarcane is a declared item, so effectively, there
should be no anthropogenic movement of sugarcane
between each quarantine zone.
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Genetics and management of an invading pest
In this study, we use microsatellite genetic markers to
evaluate both large- and small-scale population genetic differentiation and connectivity within and among island and
mainland populations of E. flavipes throughout the TS/
NPA. On the basis of previous simulation modelling
(Anderson et al. 2010), we hypothesize that E. flavipes’ primary method of transport into the TS/NPA is long-distance, wind-assisted dispersal from PNG. If so, and in
keeping with predicted patterns for long-distance dispersal,
populations across the TS/NPA should show a decrease in
genetic diversity and association with distance from PNG
source populations, associated with fewer immigrants
reaching peripheral sites (Austerlitz et al. 1997; Gillespie
et al. 2012). Thus, our expectation is that data will not conform to either of the principal theoretical models (stepping-stone or island). Exceptions may suggest that
alternate dispersal pathways are operating, such as humanmediated movement of infested sugarcane between islands.
Therefore, we also test specifically for population genetic
structuring within and among quarantine zones. Given
what is generally known about planthopper colonization
and establishment (Kuno 1979), we suspect that population
growth following immigration will result primarily from
matings among a limited numbers of colonists and subsequently their offspring, and we expect that this effect will
be particularly strong at locations distant from putative
PNG source populations. Thus, we test for family-associated genetic structuring within and among TS/NPA populations.
Eradication of E. flavipes from mainland Australia was
suggested as far back as 1989 (Allsopp 1989), but no action
has been taken. By combining patterns of genetic structure
and connectivity with hypothesized models of dispersal, we
are able to discuss findings of this study from an ‘islandspecific’ approach to the management of this high-risk pest
species in the TS/NPA, as well as demonstrate the benefits
of such an approach in a broader invasive species-management context.
Materials and methods
In 2006 and 2008, E. flavipes surveys were conducted
throughout the TS and NPA. Eumetopina flavipes were collected for genetic analyses from S. officinarum and S.
‘hybrids’ grown at nine TS and two NPA communities;
these communities were termed locations (Table 1). Due
to the haphazard nature of island sugarcane cultivation,
collections were made from what we defined as a host
‘patch’, or a stand of isolated sugarcane, which in some
cases contained a single plant, but in other cases contained
numerous plants grown in such close proximity to each
other that the stalks and leaves were intertwined and
impossible to separate. The vast majority of patches
662
Anderson and Congdon
occurred in residents gardens. E. flavipes sampled from a
single patch were defined as a population (Table 1). Ideally,
25 individuals were collected via aspiration from five randomly selected stalks per patch, and transferred immediately to 100% ethanol. If less than 25 individuals were
available on the five focal stalks, then where possible, further samples were randomly collected from additional
stalks within the same patch. Representative adult subsamples were submitted to Delphacidae taxonomist, G. A. Bellis, Darwin, Australia to confirm identification. Voucher
specimens from four locations, being Bamaga, New Mapoon, Badu and Saibai, were lodged with the Queensland
Museum, Brisbane, Australia.
Due to low sample numbers collected in either year, populations sampled in both 2006 and 2008 were used in the
analyses described below. Each population was assigned a
unique identifier and analysed independently so that temporal variation was identifiable (Table 1).
DNA methods and microsatellite characteristics
Microsatellites were developed specifically for this study
(Table 2). The novel microsatellite and primer sequences
were submitted to GenBank (Locus name and GenBank
accession number respectively: 1-TER-327 JN565018; 2TER-427 JN565019; 3-TER-527 JN565020; 4-TER-627
JN565021; 5-TER-727 JN565022; 6-TER-827 JN565023; 7TER-1027 565024; 8-TER-10 JN565025). Whole insects
were sent to the Australian Genome Research Facility Limited for their standard DNA extraction, PCR amplification
and microsatellite genotyping at eight polymorphic loci.
For PCR, initial denaturing was at 94°C for 5 min, 35
amplification cycles of 94°C for 30 s, annealing temperature (Table 2) for 45 s and 1 min of extension at 72°C,
with a final extension at 72°C for 3 min, with samples held
at 4°C. Applied Biosystems (Victoria, Australia) 3730 DNA
Analyser platform with a GeneScan -500LIZ size standard
was used for electrophoresis. Standard GeneMapper 4.1
software (Applied Biosystems) was used for scoring alleles.
The presence of null alleles, scoring error due to stuttering and large allele dropout were tested using Microchecker
2.2.3 (Van Oosterhout et al. 2004). Cervus 3.0.3 (Kalinowski et al. 2007) was used to estimate the frequency of null
alleles per locus. Linkage disequilibrium was analysed using
the likelihood ratio test, with 10 000 permutations in Arlequin 3.5.1.2 (Excoffier et al. 2005).
Population genetic characterization was done by calculating the expected (HE) and observed heterozygosity (HO)
in Arlequin. Locus-by-locus departure from Hardy–Weinberg equilibrium was tested by determining significance of
the inbreeding coefficient FIS (heterozygosity deficit), with
10 000 permutations in Arlequin. All multiple comparison
P values were corrected for false discovery rate (Benjamini
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Anderson and Congdon
Genetics and management of an invading pest
Table 1. (continued)
Table 1. E. flavipes collection details (n = sample size).
Quarantine
zone
Location
Population
n
Year
GPS coordinates
NPA
Bamaga
1
26
2006
2
27
2006
3
25
2008
4
25
2008
1
25
2006
2
17
2006
Keriri
1
22
2008
Waiben
1
25
2006
Ngurupai
1
25
2006
2
25
2006
3
21
2008
1
20
2006
2
15
2006
3
9
2006
1
14
2006
2
13
2008
3
9
2008
1
25
2006
2
13
2006
3
25
2008
1
25
2006
2
16
2008
3
25
2008
1
25
2006
2
25
2006
3
25
2008
4
25
2008
10°53′37.97″S
142°23′20.82″E
10°53′22.48″S
142°23′24.92″E
10°53′37.97″S
142°23′20.82″E
10°53′22.48″S
142°23′24.92″E
10°52′10.56″S
142°23′0.35″E
10°52′17.37″S
142°23′8.04″E
10°33′12.83″S
142°13′2.11″E
10°34′55.69″S
142°13′19.49″E
10°35′43.82″S
142°14′57.39″E
10°35′34.85″S
142°14′53.96″E
10°35′38.99″S
142°14′56.96″E
9°45′0.40″S
143°24′52.21″E
9°45′1.71″S
143°24′46.76″E
9°45′5.83″S
143°24′38.94″E
9°57′10.26″S
142°11′32.01″E
9°57′25.00″S
142°11′13.73″E
9°57′25.43″S
142°11′13.23″E
10° 9′1.03″S
142°10′12.33″E
10° 9′0.17″S
142°10′13.14″E
10° 9′20.35″S
142°10′6.00″E
9°25′8.19″S
142°32′29.68″E
9°25′7.01″S
142°31′46.87″E
9°25′8.19″S
142°32′29.68″E
9°22′54.07″S
142°36′42.39″E
9°22′37.29″S
142°37′32.80″E
9°22′52.12″S
142°36′40.99″E
9°22′34.08″S
142°37′25.68″E
New
Mapoon
SQZ
TSPZ
Masig
Mabuiag
Badu
Dauan
Saibai
(continued)
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Quarantine
zone
Location
Population
n
Year
GPS coordinates
Boigu
1
25
2006
2
25
2006
3
11
2008
4
15
2008
9°13′48.63″S
142°13′8.68″E
9°13′50.22″S
142°13′11.74″E
9°13′51.81″S
142°13′13.38″E
9°13′48.93″S
142°13′16.05″E
and Hochberg 1995). The allele size permutation test
described in Hardy et al. (2003) was used to ensure F-statistics were an appropriate measure of population genetic
differentiation for our data. The multilocus RST value was
not significantly higher than the mean pRST (P = 0.564),
therefore, FST was suitable.
Isolation by distance was examined in the first instance
to estimate the magnitude of inter-population gene flow
throughout the TS/NPA. A Mantel test was conducted with
pairwise Slatkin’s linearized FST [FST/(1 FST)] and the natural log of pairwise geographical distances between locations in the TS/NPA (Rousset 1997). Significance was
assessed with 9999 permutations in Arlequin. To calculate
the geographical distances, latitude and longitude coordinates recorded in the TS/NPA on a Garmin GPS 60 device
were uploaded to Google Earth 5.1.3533.1731 (Google Inc.
2009). Pairwise distances between TS/NPA sampling locations were calculated using the Google Earth ruler tool at
‘eye view’ 1 km above the ground for consistency.
To examine the applicability of the wind-immigration
hypothesis, we used linear regression analyses to test for an
effect of geographical distance from known E. flavipes infestations along the southern coast of PNG. E. flavipes has
been recorded on many occasions as abundant on sugarcane grown in the southern coastal PNG villages of Sigabaduru, Mabaduan, Daru and Buzi (Waterhouse et al.
1995; Grimshaw 1999; Magarey et al. 2002) (Fig. 1). We
hypothesized that these populations could easily act as
point immigrant sources for wind-assisted migration into
the TS/NPA. GPS coordinates for each of these four potential source populations along with GPS coordinates for
each sampled TS/NPA infestation were uploaded to Google
Earth. Distances between each TS/NPA population and the
closest PNG village infestation were measured using the
Google Earth ruler tool, as described previously, and used
as the predictor variable in linear regression analyses.
Allelic richness, observed heterozygosity and populationspecific FST were used as dependent variables in the above
regressions. Allelic richness and heterozygosity are important measures of population genetic diversity (Petit et al.
663
Genetics and management of an invading pest
Anderson and Congdon
Table 2. Annealing temperature (Ta), number of alleles (A), inbreeding coefficient (FIS - asterisk (*) indicates significance at P = 0.05), per loci for
eight pairs of novel microsatellite primers.
Loci
Sequence (5′–3′)
Repeat
Clonedallele size
Ta (oC)
A
8-TER-10
F TTTGCTGTCAACTCCCATTG
R GATGAGAGATGACAAGA
F TGAGGCGTGGCTGCTAGT
R CATTTCCATTAGTAATTTTCCCTCA
F TCATTTCAGCAAATTGTGAGC
R CCCTATGATCACTTAGCAACCA
F GGAATACTGGGTGTGAGTTGC
R AATGAGGCCGACTTGTATGC
F GCTCACGTTCAAGCTTCCTC
R GAGGGGAGAGGGAGTGAGAG
F TGCATGGGTAATGAAGTGGA
R GTAATGGACGGGCTACAGGA
F GCCTGGCACTCACATACACA
R TCACTAGCTTGCAGTTTGCTG
F TTCTGGCATACTGGGTGTGA
R CCGGCAGATAGGAGTTTGAG
(AC)3 (AC)24
189
55
25
0.0252
(AC)16
164
52
23
0.1451*
(AC)11 (AC)9
135
52
15
0.0189
(CA)7 (CA)7
170
55
45
0.0415
(CA)10
195
55
24
0.0539
(CA)6 (CA)7 (CA)11
202
52
28
0.0057
(CA)16
122
52
17
0.4747*
(CA)3 (CA)6
153
52
9
0.1334
1-TER-327
2-TER-427
3-TER-527
4-TER-627
5-TER-727
6-TER-827
7-TER-1027
1998), while population-specific FST is particularly useful
for estimating the genetic uniqueness of individual populations within a group of populations, especially when used
in conjunction with allelic richness (Gaggiotti and Foll
2010). Allelic richness was standardized using rarefaction
in the program HP-RARE v June-6-2006 (Kalinowski
2005). Mean population FST was calculated in the program
Geste (Foll and Gaggiotti 2006).
Overall genetic differentiation throughout the TS/NPA
was assessed with FST (Wright 1965) using analysis of
molecular variance (AMOVA). Spatial hierarchical AMOVA
was used to test whether significant genetic differentiation
occurred between quarantine zones within the TS/NPA.
Populations were grouped for the analysis as follows: (i)
mainland Australia (NPA) (Bamaga and New Mapoon),
(ii) Special Quarantine Zone (Keriri, Waiben and Ngurupai) and (iii) Torres Strait Protected Zone (Masig, Mabuiag, Badu, Dauan, Saibai and Boigu). Significance of P
was assessed with 10 000 permutations in Arlequin.
In addition to classic FST analyses, the Bayesian clustering method implemented in Structure v 2.2.3 (Falush et al.
2003) was used to test for evidence of population genetic
structuring, assign individuals to populations and to identify admixed individuals (Falush et al. 2003). As the number of genetic clusters (K) in our data was unknown,
Structure was used to assign individuals into the most
likely K. We evaluated results for K = 1 to K = 33, being
no genetic structure at all (K = 1) to every sampled population being genetically distinct (K = 31). Estimates of K
were based on 10 iterations, each with a burn in of 50 000,
and Markov Chain Monte Carlo (MCMC) lengths of
100 000 using the admixture model and correlated allele
frequencies. The optimal value of K was based on both log
664
FIS
probabilities [Pr (X|K)] and DK (Evanno et al. 2005). Summary outputs were viewed using Structure harvester v 0.6.1
(Earl 2011). Individual assignment to a particular cluster
was based on the largest average proportion of their genotype assigned to a cluster over the 10 iterations.
As we hypothesize that there will be related individuals
within populations, a maximum-likelihood model, Colony
v 2.0.1.1 (Jones and Wang 2010), was used to analyse specifically for genealogical relationships within and between
populations, by reconstructing sibling relationships (sibships). Individuals (n = 648, 7 loci; Locus 6-TER-827 was
not used in the Colony analysis due to the presence of null
alleles, see results) were pooled, and an allelic dropout rate
of 0.1%, and 1.5% for other errors were assumed. Female
monogamy and male polygamy were selected because it
appears unlikely that female planthoppers mate repeatedly,
whereas multiple mating by males is common (Claridge
and Vrijer 1994). Three long and three medium runs were
conducted, each with different random seed numbers.
Results were tested for convergence by plotting the change
in Log-likelihood as a function of the number of iterations
(Jones and Wang 2010), and only inferred sib-ships with a
probability over 0.9 were plotted.
Results
A total of 648 individuals from 31 populations were sampled from locations throughout the TS/NPA (Table 1). All
eight loci were polymorphic, with a total of 186 alleles. No
scoring errors or allele drop out were detected. FIS values at
1-TER-327 and 6-TER-827 were significant (Table 2).
However, the FIS value at 1-TER-327 was closer to the range
of FIS values at other loci, except for 6-TER-827 (see
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Anderson and Congdon
Genetics and management of an invading pest
Figure 2 Relationships between the natural log of geographical distance and Slatkin’s linear genetic distance for E. flavipes on the Torres
Strait islands and northern peninsula area, Australia.
below). Running analyses with and without 1-TER-327 did
not significantly change any outcomes, so this locus was
included in all analyses.
The FIS value at 6-TER-827 was an order of magnitude
larger than that of other loci (Table 2). Furthermore, 77%
of populations showed significant deviation from Hardy–
Weinberg equilibrium at this locus, and Microchecker indicated that it was probably due to the presence of a null
allele. Cervus estimated the frequency of null alleles at 6TER-827 to be 0.52. Consequently, this locus was excluded
from all further analyses. Significant deviation from Hardy
–Weinberg equilibrium occurred at five of seven loci at
Keriri 1, five of seven loci at Mabuiag 1 and six of seven loci
at Dauan 2. However, there was no significant global deficit
of heterozygotes in these populations (multilocus population FIS values not significantly different from zero). Isolation by distance calculations were conducted with and
without these three populations. In no instance did their
inclusion alter result significance, so results presented are
from analyses containing all populations.
Significant linkage disequilibrium occurred in most populations even after correction. This result was not unexpected, given that populations in this study may have been
influenced by evolutionary processes such as founder
effects and inbreeding following introduction, which are
known to cause linkage disequilibrium (Slatkin 2008).
Importantly, no loci were consistently linked across multiple populations, so it was assumed loci assorted independently for statistical testing. A summary of locus variation
can be found in Anderson (2011).
Isolation by distance analysis revealed a significant positive correlation between Slatkin’s linearized FST and the
natural log of geographical distance (Mantel r = 0.15,
P = 0.0003) (Fig. 2). Despite the significance of this relationship, the Mantel r value of 0.15 suggests that geographical distance between populations is a relatively poor
predictor of genetic differentiation. High levels of genetic
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Figure 3 Relationship between distance from the nearest likely Papua
New Guinea source population and (A) mean population allelic richness
(AR) and (B) and mean population genetic differentiation (FST) in the
Torres Strait and northern peninsula area, Australia.
variability were consistently observed between pairwise
Slatkin’s linearized FST values regardless of distance
between populations, suggesting that alternate factors are
probably contributing to the observed genetic structuring.
Mean population allelic richness was significantly negatively related to distance from PNG, with distance explaining 75% of the variation in allelic-richness differences
between sites (Adj R2 = 0.75, F1, 29 = 91.57, P < 0.001;
Fig. 3A). Similarly, observed heterozygosity was significantly negatively related to distance from PNG, with distance explaining 32% of the variation in observed
heterozygosity (Adj R2 = 0.32, F1, 29 = 13.81, P = 0.001).
Thus, population genetic diversity decreases with increasing distance from PNG. Conversely, mean population FST
significantly increased with distance from PNG, which
explains 77% of the variation in FST (Adj R2 = 0.77,
F1, 29 = 101.38, P < 0.001; Fig. 3B). Population genetic
structuring thus increases with distance from PNG.
A global FST of 0.32 (P < 0.001) suggests that significant
population genetic differentiation occurs throughout the
TS/NPA. Of the total variation, 68% occurred within
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Genetics and management of an invading pest
Figure 4 Results from Structure analysis for K = 1–33 populations
sampled throughout Torres Strait and northern peninsula area, Australia, with average log likelihood LnPr (X|K) ( SD) on the primary axis, ∆K
values on the secondary axis.
populations, with the remaining 32% variation among
populations also significant. After correction for false discovery rate, 463 of the 465 population pairwise FST comparisons were significant. Populations sampled in both
years from the same host plant patch were significantly
genetically different between years of sampling (Bamaga 1
and 3 P = 0.043; Bamaga 2 and 4 P < 0.001; Dauan 1 and
3 P = 0.01). Only Badu 1 and 2 (both sampled 2006) and
Saibai 3 and 4 (both sampled 2008) were not significantly
different from each other (pairwise FST = 0.004, P = 0.29;
pair-wise FST = 0.014, P = 0.07, respectively). Results of
the hierarchical AMOVA indicated that significant regional
structuring also occurs, where 16.6% of the overall variation was attributed to quarantine zone. However, only
20.06% variation occurs among populations within quarantine zones, which is low when compared with the
63.34% of variation that occurs within populations
(FST = 0.37; FSC = 0.24, FCT = 0.17; P < 0.001 for each
level of variation). So although significant, grouping
Anderson and Congdon
populations by quarantine zone only weakly explains population genetic structuring in the TS/NPA. The majority of
genetic differentiation is explained at the individual population level.
Structure analyses indicated the highest average log
likelihood occurred at K = 26 ( 11745.70) (Fig. 4).
Using the Evanno method (Evanno et al. 2005), the ∆K
statistic peaked at K = 26 (3.93) (Fig. 4). Examination of
the a plots revealed very little variation, suggesting that
the burn-in and run-times were sufficient for convergence (Falush et al. 2003). Structure results support
those of the AMOVA, suggesting that strong population
genetic structuring occurs in the TS/NPA. Within our
data, strongest support exists for 26 distinct genetic clusters, and close examination of the Structure Q plot
revealed two general patterns (Fig. 5A). First, the majority of individuals were strongly assigned to the population from which they were sampled, and this effect is
strongest on the NPA and for locations in the southern
TS, especially those within the Special Quarantine Zone.
Interestingly, all the individuals sampled from Waiben 1
and all three Ngurupai populations formed a single cluster (Fig. 5A). Second, as distance to PNG decreases,
individuals are much less strongly assigned to the population from which they were sampled because individual
levels of admixture are increasing (Fig. 5A). ∆K also suggests that levels of substructuring occur, with peaks at
K = 3 (3.11) and K = 10 (2.88) (Fig 4). K = 3 was further examined to determine if the clusters contained
populations grouped according to quarantine zone,
which they did (Fig. 5B). Evanno et al. (2005) note that
Structure is able to detect complex hierarchical levels of
genetic structure, but Falush et al. (2003) warn that
while the ultimate K should capture most of that structure, there should be a sound biological reason to
explain it. For our data, the strongest support exists for
K = 26 and K = 3, so we conclude that despite there
Figure 5 Structure Q plots (A) K = 26; (B) K = 3. Populations: Bamaga (Ba), New Mapoon (Nm), Keriri (Ke), Ngurupai (Ng), Masig (Ms), Mabuiag
(Mb), Badu (Bd), Dauan (D), Saibai (Sa) and Boigu (Bo); grouped by northern peninsula area (NPA), Special Quarantine Zone (SQZ), Torres Strait Protected Zone (TSPZ). Sampled individuals are represented by a vertical bar showing the degree of admixture.
666
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Anderson and Congdon
Genetics and management of an invading pest
Figure 6 Plot of best (maximum likelihood) sib-ship assignment (n = 648) in the Torres Strait and northern peninsula area, Australia. The lower half
of the matrix shows pairwise half-sib relationships, while the top half shows pairwise full-sib relationships. Grouped by populations: Bamaga (Ba),
New Mapoon (Nm), Keriri (Ke), Ngurupai (Ng), Masig (Ms), Mabuiag (Mb), Badu (Bd), Dauan (D), Saibai (Sa), Boigu (Bo) and northern peninsula area
(NPA), Special Quarantine Zone (SQZ), Torres Strait Protected Zone (TSPZ).
being some support for K = 10, it may represent yet a
further layer of genetic substructure, but for which there
is no clear biological cause.
The Colony analysis suggests the presence of significant
family structure throughout the TS/NPA; a total of 10 845
dyads (4554 full-sib and 6291 half-sib) occurred with over
0.9 probability. Plots of the change in Log-likelihood values
as a function of the number of iterations from each of the
replicate runs were consistent, indicating that the annealing
procedure produced convergence and was powerful (Jones
and Wang 2010). Individuals were assigned to their correct
sampling location close to the Australian mainland, suggesting a high degree of reliability in the overall assignments (Fig. 6).
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
The sib-ship pattern surrounding Boigu, Saibai and Dauan, all adjacent to the coast of PNG, appears ‘scattered’ as a
result of sib-ships between multiple populations and locations (Fig. 6). Although not the dominant sib-ship pattern,
this scatter effect extends to Badu. In contrast, the pattern
of sib-ships appears ‘linear’ for the remaining islands
mostly as a result of sib-ships occurring between individuals within a single population. To a lesser extent, sib-ships
also occur either between populations within a single location (e.g. between New Mapoon 1–2), or between populations across two locations (e.g. across Waiben and
Ngurupai).
Colony suggests that two individuals sampled from Waiben 1 were full-sibs to the majority of individuals at Nguru667
Genetics and management of an invading pest
pai 3 (patch not present in 2006, present and positive for E.
flavipes in 2008), and many individuals sampled at the two
locations were half-sibs. Waiben and Ngurupai islands are
geographically ‘next door’. When the owner of the sugarcane plants at Ngurupai 3 was interviewed, she stated that
she had obtained her plants from Waiben 1. Similar linear
sib-ships occur across New Mapoon 1–2, Waiben 1 and
Ngurupai 1–2, as well as between Ngurupai 1, 2 and 3. Further examples of such directional across-location sib-ships
are evident between Badu 1–2 and Saibai 1, 2 and 3, where
a number of individuals from Saibai are related at both
full- and half-sib level to the majority of individuals at
Badu 1–2.
Discussion
Eumetopina flavipes populations on islands close to PNG
exhibit significantly higher genetic diversity, higher levels
of admixture and lower population-specific genetic structuring than populations closer to mainland Australia. These
results combined with the apparently random assignment
of individuals from islands close to PNG to clusters by
Structure, and the dominant ‘scattered’ pattern of interpopulation sib-ship relationships observed in this region
supports the founding of these populations by either multiple independent introductions from a number of genetically diverse source populations (Allendorf and Lundquist
2003; Kolbe et al. 2004; Chu et al. 2011), or a single large
highly diverse source (Colautti et al. 2005) in PNG. Eumetopina flavipes also appears to conform to a general expectation of random distribution of founder populations,
which appears the norm for a number of other planthopper
species (Perfect and Cook 1994).
Theoretically, a unidirectional stepping-stone model of
progressive range expansion away from source populations
in PNG should produce a decrease in genetic diversity
along the expansion axis and clear associations among
adjacent populations (Austerlitz et al. 1997; Excoffier et al.
2009). However, pairwise comparisons and Structure clustering of our data suggest this is not the case, with the
majority of individuals clustering into genetically distinct,
independent aggregations corresponding to the population
from which they were sampled. In addition, sib-ships occur
between islands that are not always adjacent, so a consistent
north-to-south, progressive ‘island-hop’ mode of dispersal
is not supported. We suggest that increasingly rare, long
distance founding events by relatively fewer individuals are
responsible for this pattern of interisland variation. This is
in keeping with wind trajectory modelling for E. flavipes
(Anderson et al. 2010), suggesting that long-distance,
wind-assisted dispersal from PNG, rather than interisland
movement, is primarily responsible for E. flavipes immigration into the TS/NPA.
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Anderson and Congdon
If the dispersal mode and distance can be predicted for a
particular taxa, then so too can the resulting spatial patterns of connectivity and divergence upon arrival (Gillespie
et al. 2012). Results from a number of studies that compare
prevailing wind direction with population genetic data in
planthoppers and other arthropods support our findings
that E. flavipes engages in a seasonal migration from PNG.
Analysis of brown planthopper Nilaparvata lugens mtDNA
showed higher haplotype diversity in northern populations;
a result consistent with a seasonal, northward migration
from south-eastern China to Korea as predicted by weather
patterns (Mun et al. 1999). A study on white-backed planthopper Sogatella furcifera found significant genetic differentiation between sampled regions, and patterns of
population clustering suggested that northern S. furcifera
migrated from a number of southern source locations (Liu
et al. 2010). In Australia, levels of admixture across northern and southern Bemisia tabaci populations reflect prevailing wind trajectories at a time of year when the whiteflies
are most active (De Barro 2005). While highly relevant for
sap-feeding pests, patterns of population genetic structuring have been shown to support similar predictions regarding the origin of individuals, dispersal pathways and spread
for a range of other taxa, such as reptiles (Kolbe et al.
2004), mammals (Cote et al. 2012) and birds (Rollins et al.
2009).
A general ‘colonisation syndrome’ has previously been
described for migrating planthoppers, where low initial colonization densities are followed by little local-scale movement and rapid in-situ population growth (Kuno 1979).
For example, limited dispersal of nymphs and adults within
host patches following colonization has been shown to
result in strong aggregations for the planthopper Delphacodes scolochloa (Cronin 2009), and other planthopper species (Perfect and Cook 1994). Our results suggest that E.
flavipes conforms to this colonization syndrome, with population growth being predominantly kin-structured which,
along with apparent relative isolation following colonization, serves to enhance founder effects promoted by wind
immigration to ensure that strong genetic differentiation
between populations persists over time.
Interestingly, previous research noted that different colour forms occurred in the Torres Strait, where dark and
light colour variants were collected from Saibai (Allsopp
1991). Visual inspection of samples collected for this
study by the primary author (K. L. Anderson, unpublished data) revealed that very light colour forms generally occurred on the NPA, while the darker forms
occurred closer to PNG, and samples collected from
PNG and Indonesia appeared much darker again. We
speculate that such colour variation is a result of genetic
divergence due to isolation, and this effect appears to be
strongest among NPA populations.
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Anderson and Congdon
Results from the sib-ship and Structure analysis suggest
that secondary movement of E. flavipes occurs between and
within locations via an alternate dispersal pathway. Sibships occur between individuals from Waiben and all three
Ngurupai populations, and Structure clusters the same four
populations together. Anecdotally, the sugarcane plants at
Ngurupai 3, which were not present in 2006, were sourced
from Waiben. Thus, the linear pattern of sib-ships across
these two locations most probably represents human-mediated, directional movement of infested sugarcane. The
movement of live individuals could occur, as adults and
nymphs can survive at least six days on cut sugarcane stalks
(Anderson et al. 2007), and viable eggs present in the leaf
vein can hatch after stalk transplantation (K. L. Anderson,
unpublished data). In addition, populations at New Mapoon 1 and 2 are directly connected via related individuals,
as are populations on Badu 1 and 2 to Saibai 1 through 4;
these relationships also likely represent human-mediated
movements. Significant hierarchical AMOVA and Structure
clustering at K = 3 further support our hypothesis that secondary movements occur and that they are in fact
restricted by quarantine zone.
As for many phytophagous animals, planthoppers are
entirely dependent on the presence of suitable host plants
(Denno and Perfect 1994). Anderson et al. (2009) suggested
that the availability of E. flavipes host plants in the TS/NPA
is severely impacted by local cultivation practices in the following way. Standard practice throughout the islands
appears to involve the annual harvesting and removal of all
sugarcane plants, although variability between locations in
the actual timing of harvest was noted. Leaf material (upon
which E. flavipes resides) is removed from the stalk, dried in
the sun and then burned, while the stalks are cut into smaller pieces and replanted. Levels of postplanting care varied,
and appeared to determine whether the stalk would successfully grow. Long-term detection records indicate that
E. flavipes has been present in the TS/NPA for at least
28 years, despite such cultivation practices. Intensive sampling during this study revealed that within a 2-year period
local extinction/recolonization events occur and may be
driven by cultivation practices as described above that
remove entire host plants, causing the distribution and
abundance of E. flavipes populations to change in both
space and time (see Anderson et al. 2009). Individual populations may thus be transient because of variation in host
plant availability, but long-term regional persistence still
occurs.
Results suggest that long-term persistence is achievable
because at the broadest scale, recolonization is dominated
by wind-assisted, long-distance immigration from PNG,
which may occur annually (Anderson et al. 2010). Humanmediated local movements may also occur, but appear of
relatively less importance. Multiple introductions via the
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Genetics and management of an invading pest
use of multiple dispersal pathways likely enhance an invasive species’ ability to occupy new areas and/or recolonize
invaded areas because of the increased propagule pressure
(Grevstad 1999; Simberloff 2009). This may be especially
true for populations on islands adjacent to PNG, but in
addition, these populations could be more robust to environmental selection pressures due to their high genetic variability, and potential for subsequent rapid evolution and
adaptation (Dlugosch and Parker 2008).
Conversely, the relatively low levels of genetic variation
exhibited by the southern populations might imply limited
persistence over time, which is not the case. Low genetic
diversity within recently invaded populations, as a result of
founder effects, bottlenecks and genetic drift, does not
always appear to be a barrier to successful invasion and
subsequent population growth (Darling et al. 2008; Bai
et al. 2012). This may be especially true for populations
when accompanied by behaviour that enhances establishment and ongoing success, such as kin-structured population growth (Ingvarsson and Giles 1999).
In other systems, eliminating the dispersal pathway and/
or a focus on reducing the size of the source population
have been suggested for pest management (Russell et al.
2009; Zalewski et al. 2010); but neither of these are viable
for E. flavipes in the TS/NPA. Previous research suggests
that cultivation practices that remove host plants (e.g.
annual removal, burning and replanting of stalks as discussed previously) could significantly reduce E. flavipes
infestation, and if publicly encouraged could achieve local
or even regional eradication (Anderson et al. 2009). However, results from this study suggest that only a temporary
reduction in population size may be achievable with such a
strategy, and that permanent eradication of E. flavipes is
unlikely, especially on islands close to PNG given the
apparent propensity for successful invasion.
Our results suggest that the type of management
employed for E. flavipes should be location specific.
This is implied because populations in the northern TS
that exhibit higher levels of genetic diversity will be
more difficult to manage than those on the NPA, principally because of much higher levels of propagule pressure (Lockwood et al. 2007). We suggest that in the
first instance, a one-off, TS/NPA-wide effort focused
entirely on tip pruning, in effect removing E. flavipes
favoured host material, and then followed by annual
monitoring and further location-specific tip pruning if
recolonization is detected, may achieve longer lasting
control. Such a strategy may achieve permanent eradication in the southern TS given the apparent lower
invasion pressure and reproductive isolation. There is
some evidence that quarantine zones restrict gene flow
throughout the region, but ultimately, anthropogenic
movement cannot be prevented. However, a continuing
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Genetics and management of an invading pest
tip-pruning management strategy would reduce the likelihood of an infested stalk being moved.
Invasions are often complex; results from this
research show that E. flavipes is no exception. This
study thus demonstrates how population genetics can
inform an understanding of the drivers of dispersal and
dynamics of population growth, and the relative importance of such factors in a system with multiple immigration pathways, differing levels of multidirectional
movement and extinction/recolonization dynamics all
placed within a highly fragmented landscape. By definition, invasive pest species exhibit characteristics such as
high levels of propagule pressure promoted by the use
of multiple dispersal pathways and genetic and life-history characteristics that favour establishment success
and persistence (Lockwood et al. 2007). Therefore, it
becomes important to incorporate information as we
have into an invasive species management strategy to
ensure that sufficient effort is placed where required,
thus maximizing the likelihood for successful control
outcomes.
Acknowledgements
We thank the Sugar Research Development Corporation
for Postgraduate Scholarship support and operational
funding, the Australian Centre for International Agriculture Research through the Pacific Crops Research Program,
Robert Anderson, Nader Sallam and the TS/NPA Communities and Councils, survey participants, volunteers and a
number of reviewers for valuable comments, which
improved this manuscript.
Data archiving statement
Data for this study are available at the Tropical Data Hub
(TDH), which is located at: https://eresearch.jcu.edu.au/
tdh//.
Literature Cited
Allendorf, F. W., and L. L. Lundquist 2003. Introduction: population
biology, evolution, and control of invasive species. Conservation Biology 17:24–30.
Allsopp, P. G. 1989. Quarantine Survey of Sugarcane on the Torres Strait
Islands 1989. Bureau of Sugar Experiment Stations, Bundaberg.
Allsopp, P. G. 1991. Quarantine survey of sugarcane pests and diseases
on the Torres Strait Islands 1989. Proceedings of Australian Society of
Sugar Cane Technologists 13:83–87.
Anderson, K. L. 2011. Invasion potential of the island sugarcane
planthopper, Eumetopina flavipes (Hemiptera: Delphacidae): vector
of Ramu stunt disease, Ph.D. diss., James Cook University.
Anderson, K. L., M. Sallam, and B. C. Congdon 2007. Long distance dispersal by Eumetopina flavipes (Hemiptera: Delphacidae), vector of
670
Anderson and Congdon
Ramu stunt: is culture contributing? Proceedings of Australian Society
of Sugar Cane Technologists 29:226–234.
Anderson, K. L., N. Sallam, and B. C. Congdon 2009. The effect of host
structure on the distribution and abundance of the island sugarcane
planthopper, Eumetopina flavipes Muir, vector of Ramu stunt disease
of sugarcane. Virus Research 141:247–257.
Anderson, K. L., T. E. Deveson, N. Sallam, and B. C. Congdon 2010.
Wind-assisted migration potential of the island sugarcane planthopper Eumetopina flavipes (Hemiptera: Delphacidae): implications for
managing incursions across an Australian quarantine frontline. Journal of Applied Ecology 47:1310–1319.
Austerlitz, F., B. JungMuller, B. Godelle, and P. H. Gouyon 1997. Evolution of coalescence times, genetic diversity and structure during colonization. Theoretical Population Biology 51:148–164.
Australian Government Department of Foreign Affairs and Trade 1985.
Treaty Between Australia and the Independent State of Papua New
Guinea Concerning Sovereignty and Maritime Boundaries in the Area
Between the Two Countries, Including the Area Known as Torres
Strait, and Related Matters. Australian Government Publishing Service, Canberra.
Bai, C., Z. Ke, S. Consuegra, X. Liu, and Y. Li 2012. The role of
founder effects on the genetic structure of the invasive bullfrog
(Lithobates catesbeianaus) in China. Biological Invasions 14:1785–
1796.
Benjamini, Y., and Y. Hochberg 1995. Controlling the false discovery
rate: a practical and powerful approach to multiple testing. Journal
Royal Statistical Society: Series B 57:289–300.
Chandler, K. J., and B. J. Croft 1986. Quarantine significance of pests
and diseases of sugarcane on the Torres Strait Islands. Proceedings of
Australian Society of Sugar Cane Technologists 8:129–133.
Chu, D., C. S. Gao, P. De Barro, F. H. Wan, and Y. J. Zhang 2011. Investigation of the genetic diversity of an invasive whitefly (Bemisia tabaci)
in China using both mitochondrial and nuclear DNA markers. Bulletin of Entomological Research 101:467–475.
Claridge, M. F., and P. W. F. Vrijer 1994. Reproductive behaviour: the
role of acoustic signals. In R. F. Denno, and J. T. Perfect eds. Planthoppers: Their Ecology and Management, pp. 216–233. Chapman &
Hall, New York.
Colautti, R. I., M. Manca, M. Viljanen, H. A. M. Ketelaars, H. Burgi, H.
J. Macisaac, and D. D. Heath 2005. Invasion genetics of the eurasian
spiny waterflea: evidence for bottlenecks and gene flow using microsatellites. Molecular Ecology 14:1869–1879.
Congdon, B. C., C. L. Lange, and A. R. Clarke 1997. Geographical variation and gene flow in the eucalyptus defoliating beetle Chrysophtharta
bimaculata (Coleoptera: Chrysomelidae). Journal of Applied Ecology
34:1287–1292.
Cote, H., D. Garant, K. Robert, J. Mainguy, and F. Pelletier 2012. Genetic
structure and rabies spread potential in raccoons: the role of landscape
barriers and sex-biased dispersal. Evolutionary Applications 5:393–404.
Cronin, J. T. 2009. Movement, colonization, and establishment success
of a planthopper of prairie potholes, Delphacodes scolochloa (Hemiptera: Delphacidae). Ecological Entomology 34:114–124.
Darling, J. A., M. J. Bagley, J. O. E. Roman, C. K. Tepolt, and J. B. Geller
2008. Genetic patterns across multiple introductions of the globally
invasive crab genus Carcinus. Molecular Ecology 17:4992–5007.
De Barro, P. J. 2005. Genetic structure of the whitefly Bemisia tabaci in
the Asia-Pacific region revealed using microsatellite markers. Molecular Ecology 14:3695–3718.
Denno, R. E., and J. T. Perfect 1994. Planthoppers: Their Ecology and
Management. Chapman and Hall, New York.
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Anderson and Congdon
Dlugosch, K. M., and I. M. Parker 2008. Founding events in species invasions: genetic variation, adaptive evolution, and the role of multiple
introductions. Molecular Ecology 17:431–449.
Earl, D. A. 2011. Structure Harvester v 0.6.1. http://taylor0.biology.ucla.
edu/structureHarvester/ (accessed 10 May 2011).
Evanno, G., S. Regnaut, and J. Goudet 2005. Detecting the number of
clusters of individuals using the software structure: a simulation study.
Molecular Ecology 14:2611–2620.
Excoffier, L. G., G. Laval, and S. Schneider 2005. Arlequin ver. 3.0: an
integrated software package for population genetics data analysis. Evolutionary Bioinformatics Online 1:47–50.
Excoffier, L., M. Foll, and R. J. Petit 2009. Genetic consequences of range
expansions. Annual Review of Ecology Evolution and Systematics
40:481–501.
Falush, D., M. Stephens, and J. K. Pritchard 2003. Inference of population structure using multilocus genotype data: linked loci and correlated allele frequencies. Genetics 164:1567–1587.
Foll, M., and O. Gaggiotti 2006. Identifying the environmental factors that
determine the genetic structure of populations. Genetics 174:875–891.
Gaggiotti, O., and M. Foll 2010. Quantifying population structure using
the F-model. Molecular Ecology Resources 10:821–830.
Gillespie, R. G., B. G. Baldwin, J. M. Waters, C. I. Fraser, R. Nikula, and
G. K. Roderick 2012. Long-distance dispersal: a framework for
hypothesis testing. Trends in Ecology & Evolution 27:47–56.
Google Inc. 2009. Google Earth Version v 5.1.3533.1731. http://earth.google.com/ (accessed on 25 May 2010).
Gough, N., and R. Petersen 1984. Cane stem borer on Torres Strait
Islands. BSES Bulletin 8:20–21.
Grevstad, F. S. 1999. Experimental invasions using biological control
introductions: the influence of release size on the chance of population establishment. Biological Invasions 1:313–323.
Grimshaw, J. F. 1997. NAQS plant health survey of the northern islands
of the Torres Strait. Unpublished report for the Australian Quarantine
Inspection Service: Cairns, Australia.
Grimshaw, J. F. 1999. Combined extension charter and survey of plant
and animal pests and diseases in coastal communities of the Western
Province of Papua New Guinea. Unpublished report for the Australian Quarantine Inspection Service: Cairns, Australia.
Hardy, O. J., N. Charbonnel, H. Freville, and M. Heuertz 2003. Microsatellite allele sizes: a simple test to assess their significance on genetic
differentiation. Genetics 163:1467–1482.
Ingvarsson, P. K., and B. E. Giles 1999. Kin-structured colonization and
small-scale genetic differentiation in Silene dioica. Evolution 53:605–611.
Jiang, X.-F., W.-J. Cao, L. Zhang, and L.-Z. Luo 2010. Beet webworm
(Lepidoptera: Pyralidae) migration in China: evidence from genetic
markers. Environmental Entomology 39:232–242.
Jones, O. R., and J. L. Wang 2010. COLONY: a program for parentage
and sibship inference from multilocus genotype data. Molecular Ecology Resources 10:551–555.
Kalinowski, S. T. 2005. HP-Rare: a computer program for performing
rarefaction on measures of allelic diversity. Molecular Ecology Notes
5:187–189.
Kalinowski, S., M. Taper, and T. Marshall 2007. Revising how the computer program CERVUS accommodates genotyping error increases
success in paternity assignment. Molecular Ecology 16:1099–1106.
Kolar, C. S., and D. M. Lodge 2001. Progress in invasion biology: predicting invaders. Trends in Ecology & Evolution 16:199–204.
Kolbe, J. J., R. E. Glor, L. R. G. Schettino, A. C. Lara, A. Larson, and J. B.
Losos 2004. Genetic variation increases during biological invasion by
a Cuban lizard. Nature 431:177–181.
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672
Genetics and management of an invading pest
Kuniata, L. S., G. R. Young, E. Pais, P. Jones, and H. Nagaraja 1994. Preliminary observations on Eumetopina sp. (Hemiptera: Delphacidae) as
a vector of Ramu Stunt disease of sugarcane in Papua New Guinea.
Journal of the Australian Entomological Society 33:185–186.
Kuniata, L. S., K. J. Chandler, and K. T. Korowi 2001. Management of
sugarcane pests at Ramu, Papua New Guinea. Proceedings of International Society of Sugar Cane Technologists 24:382–388.
Kuno, E. 1979. Ecology of the brown planthopper in temperate regions.
In International Rice Research Institute, ed. Brown Planthopper:
Threat to Rice Production in Asia, pp. 45–50. International Rice
Research Institute, Manila, Phillipines.
Liu, J. N., F. R. Gui, and Z. Y. Li 2010. Genetic diversity of the planthopper, Sogatella furcifera in the Greater Mekong Subregion detected by
inter-simple sequence repeats (ISSR) markers. Journal of Insect Science 10:52.
Lockwood, J. L., M. Hoopes, and M. Marchetti 2007. Invasion Ecology.
Blackwell Publishing, Oxford.
Magarey, R. C. 1997. Quarantine survey of some Torres Strait Islands in
1996. Proceedings of Australian Society of Sugar Cane Technologists
19:51–53.
Magarey, R. C. 2003. Travel Report Survey no. 4 Torres Strait and Cape
York Peninsula 10–19 June 2003. Unpublished report for the BSES
Ltd: Tully, Australia.
Magarey, R. C., S. Suma, Irawan, L. S. Kuniata, and P. G. Allsopp 2002.
Sik na binatang bilong suka - diseases and pests encountered during a
survey of Saccharum germplasm ‘in the wild’ in Papua New Guinea.
Proceedings of Australian Society of Sugar Cane Technologists 24:219
–227.
Mun, J. H., Y. H. Song, K. L. Heong, and G. K. Roderick 1999.
Genetic variation among Asian populations of rice planthoppers,
Nilaparvata lugens and Sogatella furcifera (Hemiptera: Delphacidae): mitochondrial DNA sequences. Bulletin of Entomological
Research 89:245–253.
Paijmans, K. 1976. New Guinea Vegetation. Australian National University Press, Canberra.
Perfect, J. T., and A. G. Cook 1994. Rice planthopper population dynamics: a comparison between temperate and tropical regions. In R. F.
Denno, and J. T. Perfect, eds. Planthoppers: Their Ecology and Management, pp. 282–301. Chapman and Hall, Inc., New York.
Petit, R. J., A. El Mousadik, and O. Pons 1998. Identifying populations
for conservation on the basis of genetic markers. Conservation Biology 12:844–855.
Pimentel, D., L. Lach, R. Zuniga, and D. Morrison 1999. Environmental
and Economic Costs Associated with Non-indigenous Species in the
United States. College of Agriculture and Life Sciences, Cornell University, Ithaca, New York.
Rollins, L. A., A. P. Woolnough, A. N. Wilton, R. Sinclair, and W. B.
Sherwin 2009. Invasive species can’t cover their tracks: using microsatellites to assist management of starling (Sturnus vulgaris) populations
in Western Australia. Molecular Ecology 18:1560–1573.
Rousset, F. 1997. Genetic differentiation and estimation of gene flow
from F-statistics under isolation by distance. Genetics 145:1219–1228.
Russell, J. C., J. W. B. Mackay, and J. Abdelkrim 2009. Insular pest control within a metapopulation context. Biological Conservation
142:1404–1410.
Sakai, A. K., F. W. Allendorf, J. S. Holt, D. M. Lodge, J. Molofsky, K. A.
With, S. Baughman et al. 2001. The population biology of invasive
species. Annual Review of Ecology and Systematics 32:305–332.
Sallam, N. 2009. Eumetopina Flavipes Incursion Management Plan Version 1 - MN09001. BSES Ltd, Meringa, Australia.
671
Genetics and management of an invading pest
Simberloff, D. 2009. The role of propagule pressure in biological invasions. Annual Review of Ecology and Systematics 40:81–102.
Slatkin, M. 2008. Linkage disequilibrium - understanding the evolutionary past and mapping the medical future. Nature Reviews Genetics
9:477–485.
Suhr, E. L., D. J. O’Dowd, S. W. McKechnie, and D. A. Mackay 2010.
Genetic structure, behaviour and invasion history of the Argentine ant
supercolony in Australia. Evolutionary Applications 4:471–484.
Van Oosterhout, C., W. F. Hutchinson, D. P. M. Wills, and P. Shipley
2004. MICRO-CHECKER: software for identifying and correcting
genotyping errors in microsatellite data. Molecular Ecology Notes
4:535–538.
Waterhouse, B. W., J. F. Grimshaw, and B. K. Vogelzang 1995. Report on
the NAQS joint survey of the Western Province, Papua New Guinea, 22
May - 05 June 1995, plants component. Unpublished report for the
Australian Quarantine and Inspection Service: Mareeba, Australia.
672
Anderson and Congdon
Williamson, M. 1996. Biological Invasions. Chapman & Hall, London.
Wilson, M. R. 2004. Biology and distribution of the sugarcane planthopper genus Eumetopina (Hemiptera; Auchenorrhyncha; Delphacidae).
Paper read at XII International Congress of Entomology, at Brisbane,
Australia.
Wright, S. 1965. The interpretation of population structure by F-statistics with special regards to systems of mating. Evolution 19:393–420.
Zalewski, A., A. Michalska-Parda, M. Bartoszewicz, M. Kozakiewicz, and
M. Brzezinski 2010. Multiple introductions determine the genetic
structure of an invasive species population: American mink Neovison
vison in Poland. Biological Conservation 143:1355–1363.
Zepeda-Paulo, F. A., J. C. Simon, C. C. Ramirez, E. Fuentes-Contreras, J.
T. Margaritopoulos, A. C. C. Wilson, C. E. Sorenson et al. 2010. The
invasion route for an insect pest species: the tobacco aphid in the New
World. Molecular Ecology 19:4738–4752.
© 2013 The Authors. Published by Blackwell Publishing Ltd 6 (2013) 660–672