bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
1
2
3
4 Do atmospheric events explain the arrival of an invasive ladybird
5 (Harmonia axyridis) in the UK?
6
7
8 Pilvi Siljamo1*⁋, Kate Ashbrook2⁋ , Richard F. Comont2, Carsten Ambelas Skjøth2
9
10
11
12 ¹ Meteorological Research, Finnish Meteorological Institute, Helsinki, Finland
13 ² School of Science & the Environment, University of Worcester, Worcester, UK
14
15
16 * Corresponding author 17 E-mail: [email protected] (PS) 18 19
20
21 ⁋ These authors contributed equally to this work
22
1 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
23 Abstract 24
25 Species introduced outside their natural range threaten global biodiversity and despite greater
26 awareness of invasive species risks at ports and airports, control measures in place only concern
27 anthropogenic routes of dispersal. Here, we use the Harlequin ladybird, Harmonia axyridis, an
28 invasive species which first arrived in the UK from continental Europe in 2003, to test whether
29 records from 2004 and 2005 were associated with atmospheric events. We used the atmospheric
30 dispersion model SILAM to model the movement of this species from known distributions in
31 continental Europe and tested whether the predicted atmospheric events were associated with the
32 frequency of ladybird records in the UK. We show that the distribution of this species in the early
33 years of its arrival does not provide substantial evidence for a purely anthropogenic introduction and
34 show instead that atmospheric events can better explain this invasion event. Our results suggest that
35 air flows which may assist dispersal over the English Channel are relatively frequent; ranging from
36 once a week from Belgium and the Netherlands to 1-2 times a week from France over our study
37 period. Given the frequency of these events, we demonstrate that atmospheric-assisted dispersal is a
38 viable route for flying species to cross natural barriers.
39
40 Introduction
41 42 Species introduced outside their natural range and which have detrimental effects on native species
43 are known as Invasive Alien Species (IAS) and are recognised as a significant component of
44 environmental change worldwide [1,2]. They have been identified as one of the ‘Evil Quartet’ of
45 major drivers of biodiversity loss worldwide [3], are highlighted in the Millennium (2005) [4] and
46 UK National Ecosystem Assessments (2011) [5], and are the focus of Target 5 of the EU 2020
47 Biodiversity Strategy, including EU regulation 1143/2014 on management of invasive alien species
2 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
48 [6]. The direct costs of invasive alien species have been estimated to be approximately US $1.4
49 trillion, approximately 5% of global GDP [7], with annual costs of £1.7 billion within Britain alone
50 [8].
51 Many species will arrive in a new country but not establish; of those which do establish most do not
52 become invasive [9–12] . Accurate prediction of the timing, effects and identification of species
53 which may become IAS is not currently possible, despite many attempts [13–22].
54 Consequently, efforts have focussed on preventing the arrival and establishment of all non-native
55 species. Hulme et al. (2008) [2] identified six distinct pathways by which species may spread beyond
56 their native ranges: 1) deliberate release; 2) unintentional escape; 3) unintentional contaminant of
57 another commodity; 4) unintentional stowaway on transport; 5) natural dispersal aided by human-
58 made corridors; and 6) unaided natural dispersal. In line with the 2011-2020 CBD Strategic Plan for
59 Biodiversity, most countries have enhanced their border controls [23] in order to better manage
60 pathways 1-4, but natural dispersal from an introduced population (pathways 5 & 6) is very difficult
61 to police, therefore these pathways are likely to become proportionally more important in the future.
62 One of the traits associated with successful establishment and invasion, particularly in insects, has
63 been good dispersal ability [24–26], which enables rapid spread beyond the original point of
64 introduction. This is particularly true of the Harlequin ladybird Harmonia axyridis (Pallas). Native to
65 eastern Asia, it has been widely introduced outside its native range as a biological control agent and
66 has since spread rapidly to colonise North America, much of Europe, several South American
67 countries, and parts of both northern and southern Africa [27]. The species is a strong flier, actively
68 dispersing over several kilometres to overwintering sites each year [28,29]. It was first recorded in
69 Britain in 2003 and 2004, and it was estimated to have dispersed 105 km per year northwards and
70 145 kilometres westwards from 2004 to 2008 [30,31].
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71 Once the species was in Britain, it spread northwards and westwards from the arrival point in the
72 south-east, against the prevailing south-westerly wind direction. For this reason, passive wind-borne
73 transport has been considered unlikely to play a major role in its spread [32][30]. However, as the
74 UK is an island, cut off from the rest of the continent of Europe by the North Sea and English Channel,
75 it has been suggested that the original arrival may have been assisted by wind events [32]. This
76 association between atmospheric events and the arrival of this species has not previously been tested.
77 Here, we investigate whether the arrival of an invasive ladybird, H. axyridis, from continental Europe
78 to Great Britain was assisted by atmospheric events, using numerical weather prediction (NWP)
79 models and atmospheric dispersion models (ADM). As a comparison, we also examined human-
80 mediated routes of import: the association of Harlequin records with seaports and airports.
81
82 Material and Methods 83
84 Ladybird records 85
86 Biological record data was taken from the UK Ladybird Survey, collated from records submitted to
87 iRecord (www.brc.ac.uk/iRecord), the Harlequin Ladybird survey website (www.harlequin-
88 survey.org) and other data submitted to the scheme. This data is freely available on the National
89 Biodiversity Network at https://registry.nbnatlas.org/public/show/dr695. While, the first three records
90 of the Harlequin ladybird in the UK are from 2003, we focused on records from 2004 – 2005, the
91 main period when the species arrived and established in the UK (139 records in 2004; 2081 records
92 in 2005), Only records submitted with sufficient evidence for independent expert verification (a
93 specimen or adequate photograph) were used in the dataset.
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94 To provide an estimate of the relative proportion of Harlequin records to the background level of
95 ladybird records submitted over time and ensure that spikes in Harlequin numbers were not just good
96 days for recording ladybirds, we compared the Harlequin records to records of six widespread and
97 abundant ladybird species (Adalia bipunctata (L.), Adalia decempunctata (L.), Calvia
98 quattuordecimguttata (L.), Coccinella septempunctata (L.), Halyzia sedecimguttata (L.) and
99 Propylea quattuordecimpunctata (L.)) over the same time period (4479 records in total).
100 To characterise whether the location of Harlequin records in 2004 and 2005 in the UK (n = 139) were
101 clustered or randomly distributed with respect to ports and airports, we used Ripley’s K-function from
102 package “spatstat” in R. We created two shapefiles, incorporating 59 airports and 31 major ports
103 (Table PORT0103, https://www.gov.uk/government/statistical-data-sets/port01-uk-ports-and-traffic)
104 in England and Wales. To determine whether the Harlequin records were similarly clustered with
105 either airports or ports, we used Monte Carlo simulation with random labelling of points and cross
106 K-function [33].
107
108 SILAM 109
110 To simulate atmospheric movements of the Harlequin ladybirds, we used the atmospheric dispersion
111 model SILAM (http://silam.fmi.fi), which is a meso- to global-scale, mathematical-physical
112 atmospheric composition model. SILAM can use both Lagrangian (random walk particle model) [34]
113 and Eulerian (atmospheric dispersion computed in a grid) [35] approaches. It has been used to
114 calculate air quality [36], dispersion of volcanic ash [37], pollen [38] and pest insects [39] as well as
115 dispersion of radioactive nuclides [40] in both forward and inverse (footprint) mode.
116 The forward atmospheric dispersion models investigate where material will be transported to when
117 the source area is known, whereas the inverse atmospheric dispersion models investigate where the
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118 source area is for observed material. Theoretically, forward atmospheric dispersion equations can be
119 used in inverse calculations, only direction of time is negative [34,41]. The forward atmospheric
120 dispersion outputs particle counts, concentration etc. if the source is known well enough or a
121 dispersion area, which describes the area which is affected by the source. The inverse dispersion
122 outputs probability area (~ footprints), not exact numbers, providing the area where the source could
123 be located within. The source or sources can be located at any point within the probability area and
124 users should evaluate if it is possible (e.g., the source of ladybirds cannot be on the sea). Different
125 data-assimilation methods can reduce the probability area, but they require considerable amounts of
126 observations.
127 Once the material is emitted to the atmosphere, wind transports particles and gases in the atmosphere,
128 and turbulent eddies mix them. Most of the particles (pollen, dust, flying animals, etc.) which are
129 released inside the atmospheric boundary layer stay there, but some of them are able to escape and
130 go higher. The height of the boundary layer depends on weather, but in mid-latitudes it is typically
131 the lowest 1000-2000 metres of the atmosphere.
132 Insects generally fly inside the atmospheric boundary layer. This means that atmospheric dispersion
133 models, dedicated to the modelling of particles originating in this layer, are also useful tools to
134 simulate long-distance movements of small insects. As relatively weak fliers, most small insects
135 largely follow the prevailing wind direction and are capable of only slightly affecting their flight
136 directions [42].
137 The SILAM modelling process requires a source area for the modelled material (particulate matter:
138 PM). Harlequin ladybirds are known to reach a high abundance in urban areas [43], so we took as
139 source areas the larger cities near the north coasts of Belgium (Antwerp, Gent, Bruges, Brussels), the
140 Netherlands (Amsterdam, Hague, Rotterdam) and France (Dunkirk, Lille, Calais, Amiens, Le Havre,
141 Dieppe). Because computational resolution of the model is 0.225° x 0.225° (i.e. about 15 x 25 km),
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142 these point sources cover a large proportion of Belgium and the Netherlands. The European Harlequin
143 data was taken from publicly-available data on GBIF (available at
144 https://www.gbif.org/species/4989904). The SILAM forward Harlequin simulations were divided
145 into two parts: sources in France, and sources in Belgium & the Netherlands. This was because the
146 atmospheric wind events would have needed to blow in different directions in order to deposit
147 Harlequins in the relevant sighting areas from the two putative sources.
148 We modelled dispersal of H. axyridis individuals assuming that they would act similarly to coarse
149 particulate matter (particles with a diameter of up to 10 micrometres, known as PM10). Although the
150 ladybird is heavier than this, it has the ability to fly and thus generate its own lift, an advantage not
151 shared by standard particles. We also tested the PM10 dispersal patterns with those for much finer
152 particles up to 2.5 μm in diameter (PM2.5), which generally show very long-range dispersal. This
153 showed very similar dispersal patterns, but PM10 particles dropped out of the airstream more quickly,
154 resulting in concentrations of PM10 lower further from the source areas when compared to PM2.5.
155 Deposition of ladybirds from the airstream was assumed to also be similar to PM10 particles: in
156 particular, rain was assumed to cause deposition.
157 The first UK records for H. axyridis in 2004 were in late June, so we carried out modelling from the
158 1st June 2004 until 1st October 2004 (the ladybirds largely cease outdoor activity and enter
159 overwintering sites around this time). For 2005, we modelled 1st April-1st October in order to capture
160 both the spring and autumn dispersal periods, as well as the summer activity period. SILAM source
161 points in Europe were modelled as continuously releasing PM10 ladybird particles every day across
162 the two years examined, between 5am and 6pm, UK time.
163 The ladybird’s habit of overwintering inside buildings causes a spike in records in late autumn as they
164 are noticed by householders. There was no way to reliably split these records from those of ladybirds
165 outside, which might be affected by atmospheric events, so we excluded records from the
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166 overwintering period (1st Oct-31st March). We did not model past 2005 as the establishment and
167 rapid spread of the species would have made the distinction between newly-arrived immigrant
168 individuals and existing residents impossibly to quantify.
169 The ECMWF’s operational numerical weather prediction (NWP) model data (Integrated Forecast
170 System – IFS: https://www.ecmwf.int/) served as a source of weather information both in forward
171 and footprint computations. The NWP model is global and thus it covers the whole dispersion area
172 we were interested in (10.5°W-10°E, 45°N-60°N). We used the data as 3-hour time steps (+3 h, +6
173 h, +9 h and +12 h forecast lengths) and with a square grid size of 0.225° and 21 NWP-vertical levels
174 from ground to over 5 km. The most important weather parameters used were 3D-winds (the transport
175 of ladybirds) and rain (influences deposition of ladybirds from the atmosphere).
176 The SILAM harlequin-simulations shown here were computed using Eulerian-SILAM using the same
177 grid as in the NWP model. We used a time step of 15 minutes in the SILAM atmospheric dispersion
178 calculations.
179 Inverse SILAM (‘footprints’) were computed 72 h backwards from the ladybird observations in 2004.
180 Source points (detection points) and direction of calculation (backward in time) were different than
181 in the forward SILAM simulations, but otherwise the model setup was same. We expected that
182 ladybirds arrived at the earliest one day before observations, latest in the middle of the observation
183 day (e.g., obs. 15/8/2004, “collection time” 14/8/2004 00 UTC-15/8/2004 12 UTC), so the collection
184 time was 1.5 days and simulated period (dispersal time plus collection time) was 1.5-3 days backward.
185 However, the SILAM-footprints showed in many cases that the ladybirds arrived earlier than 1.5 days
186 before observations. Thus, we also computed 10 days inverse simulation for the record on the 30th of
187 June, 2004, which is the earliest UK record in 2004. There the collection time was taken as 10 days
188 as well.
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189 The model output information was produced in 10 km square grid cells. The area extended from the
190 45ºN to the 60ºN and from 10.5ºW to 10ºE to cover the UK, Ireland, Belgium, the Netherlands and
191 part of France, Germany, Denmark and Norway. In case of the forward simulations, the output was
192 given as a daily average, whereas in case of the footprints it was hourly.
193 Associating SILAM events with Harlequin arrivals
194 195 We used Generalised Linear Models (GLMs) to determine whether SILAM-predicted atmospheric
196 events from source populations were associated with records of H. axyridis. If these ladybirds were
197 arriving from cross-channel atmospheric events, we would expect to see H. axyridis record numbers
198 to be associated with SILAM-predicted atmospheric events closer to the south-east coastline, with
199 the association reducing with greater distance from the coast. Previous work [44] has found H.
200 axyridis able to fly at up to 60km/hr at high altitudes, and to fly for at least two hours. To allow for
201 any extra flight time (Jeffries et al stopped monitoring at a two-hour flight time cut-off), plus any
202 short-range flights during the collection period, we split the ladybird dataset into two, and compared
203 H. axyridis within 200 km of the continental coastline to records collected further than 200 km from
204 the continental coastline. For both datasets we determined the daily frequency of H. axyridis and the
205 daily frequency of the 6 most commonly recorded ladybirds. A bound vector of daily frequency of
206 Harlequins and the daily frequency of common ladybirds was used as the response variable in GLMs
207 with binomial error structures. We calculated the maximum value of SILAM per day from both
208 source populations for a 7-day window for 51°N 1°E (West Kent coastline) around the ladybird record
209 days and used this as an explanatory variable in the models. We were also interested in the association
210 of records with month, and how this differed between years, therefore a combined value of month
211 and year (i.e. 2004.6 to represent June 2004) was also included as an explanatory value.
212
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213 Results 214
215 Spatial autocorrelation of airports, ports and Harlequin ladybirds 216
217 Bivariate Ripley-K functions suggested that the location of Harlequin records in the first two years
218 of arrival were not associated with airport locations in England and Wales at cluster distances of < 17
219 km (Fig 1a). Harlequin records were also not associated with port locations in England and Wales
220 from 0 – 5 km cluster distances, but showed some association at greater distances (Fig 1b). As the
221 majority of records of Harlequin ladybirds in 2004 and 2005 are located along the south-east
222 coastline, it is likely that the association at greater distances is due to the existence of several major
223 ports in the south-east (Ramsgate, Dover, Felixstowe, Harwich, Ipswich, and Great Yarmouth).
224
225 Fig 1. Monte Carlo K-cross simulations for Harmonia axyridis records. Monte Carlo K-cross
226 simulations (n=1,000) for Harmonia axyridis records in 2004 and 2005 and airports (a) and ports (b).
227 The red dotted line represents what would be expected with the points were randomly distributed; the
228 grey area around this represents the confidence envelope from the Monte Carlo simulations. The
229 black line represents the observed K values; where this line falls within the grey area the points can
230 be described as not associated; however, outside the grey area, the points can be considered to be
231 associated. On the x-axis, r represents cluster distance in metres.
232
233 SILAM events 234
235 Air currents from source populations in France, Belgium and the Netherlands could feasibly have
236 transported H. axyridis individuals across the English Channel, as the first records are located in the
237 south-east, in line with the SILAM predictions (Fig 2). These predictions suggest that 2005 may have
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238 been more favourable for the migration of ladybirds than 2004, as the events were stronger and more
239 frequent in the latter year, especially from Belgium and the Netherlands, where the population appears
240 to be stronger. More favourable winds in the later year can be seen also in Fig 2, where the average
241 potential landing area is larger in 2005 than in 2004.
242
243 Fig 2. SILAM average air current (PM10) predictions. SILAM average air current (PM10)
244 predictions for June to October 2004 (a,b) and 2005 (c,d) for Netherlands & Belgium combined (a,c)
245 and France (b,d). Higher values (inside contours) suggest a high probability of arrival in the UK from
246 source populations due to atmospheric events.
247
248 A more detailed review shows that air flows are suitable for ladybirds to come from Belgium and the
249 Netherlands, on average, once a week (13.9% of days) during June-September 2004, but from France
250 1-2 times a week (20.5% of days). In 2004, the best month to fly over the English Channel was
251 September (23.3% of the days from Belgium and the Netherlands and 20% from France were
252 suitable). In April-September 2005 a higher proportion of days were suitable for ladybirds to cross
253 the English Channel: 17.6% of the days from Belgium and Netherlands and 22.0% of the days from
254 France. September 2005 was particularly favourable for migration from the continental Europe to
255 the UK, with conditions suitable for immigration from Belgium and the Netherlands almost every
256 four days (23.3%) and more than every three days (33.7%) from France. This coincides with
257 observations of H. axyridis becoming more common.
258 We computed the inverse SILAM (footprints) for all H. axyridis records observed before October
259 2004. The SILAM footprints suggested that France could be the source area in 3 cases out of 7,
260 Belgium or Netherlands in 2 of 7 and the source area is unclear in 2 of 7. In many cases, it is likely
261 that the recorded individual had been present for some time before it was recorded, therefore 1.5 days
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262 of collection time only provides a limited snapshot of those records which may be associated with
263 particular atmospheric events, such as the case on 30th June, 2004.
264 Fig 3 shows an example of the 10 days cumulative, backward probability area from Faversham, Kent
265 (51.3° N, 0.9°E) for 30th June, 2004, which was one of the first H. axyridis records in the UK. More
266 detailed analysis shows that the H. axyridis observed on 30th June most likely came to the UK during
267 morning hours on 26th June. Several days before and after that short moment winds did not blow
268 from the continental Europe. In this case, the most probable source area locates in France instead of
269 Belgium or the Netherlands.
270
271 Fig 3. Inverse SILAM simulation. Inverse (footprint) SILAM simulation 10 days backwards from
272 H. axyridis record in Kent (51.3° N, 0.9°E) on 30th June, 2004 expecting continuous collection time.
273 The model demonstrates the potential source areas for the record, with darker areas indicating a
274 greater probability of the source location, though it should be noted that ladybirds could only have
275 originated from terrestrial areas.
276
277 According to SILAM simulation, H. axyridis could fly from France to the UK (Kent and Essex)
278 within 1-3 hours, which is a feasible flying time for ladybirds ( [45] p.348) . It would take longer
279 (4-6 hours) to reach more northern locations like Suffolk and Norfolk from France.
280 Another example is for 2005. On 1st Sept, 2005 there were 13 H. axyridis records, 72% of all observed
281 ladybirds in the UK that day, all of which were within 200 km of the coastline. The SILAM forward
282 simulations from Belgium and the Netherlands (Fig 4a) and from France (Fig 4b) shows that in this
283 case the source was more likely to be located in Belgium and the Netherlands than in France. The
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284 case was also clearly stronger compare to case in the end of June, 2004. Thus, the weather provided
285 an efficient path for Harlequins to arrive in the UK.
286
287 Fig 4. SILAM forward simulations. SILAM forward simulation on 30th August, 2005, 6 UTC - 31st
288 August, 2005, 6 UTC. Source areas locate in a) Belgium and the Netherland and b) in France.
289
290 Association of H. axyridis records and SILAM events 291
292 At distances less than 200 km from the continental coastline, we found that there was an association
293 between the daily maximum SILAM values and the proportion of H. axyridis records (Quasi-binomial
294 GLM: correlation coefficient: 0.42; LR: 4.22, p = 0.04). With greater values of SILAM, higher
295 proportions of H. axyridis records were submitted compared to common native species (Fig 5). There
296 was significant variation in the proportion of H. axyridis records to the combined total of the six
297 common native species over time (Fig 5; LR: 31.94, p < 0.001), with a mean proportion of 0.10 H.
298 axyridis to native species from June to September 2004, but increasing to a mean proportion of 2.53
299 H. axyridis to native species from April to September 2005.
300
301 Fig 5. Mean proportion of H. axyridis records. Mean proportion of H. axyridis records to common
302 species within (black circles) and further than (grey triangles) 200 km from continental coastline with
303 SILAM atmospheric event values. SILAM events have been rounded to nearest 1 decimal place. Error
304 bars represent ±1 S.E.
305
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306 In contrast, at distances greater than 200 km from the continental coastline, we found that there was
307 no association between the daily maximum SILAM values and the proportion of H. axyridis records
308 (Binomial GLM: correlation coefficient: 0.64; LR: 2.79, p = 0.09). However, there was significant
309 variation in the timings of these records (Month & Year: LR: 38.75, p < 0.001), with higher mean
310 proportions of H. axyridis to common native species recorded in May 2005 (0.42), June 2005 (0.43)
311 and September 2005 (0.43) than in July 2005 (0.29) and August 2005 (0.26).
312
313 Discussion 314
315 Invasive alien species are widely recognised as agents of global biotic homogenisation and thus as
316 one of the main challenges to future global biodiversity [46]. The spread of H. axyridis is known to
317 have been assisted by anthropogenic introductions, and some have also alluded to possible
318 atmospheric-assisted dispersal [30,32]. Here, we demonstrate that atmospheric events are a viable,
319 likely and detectable means for this species to have dispersed over a large natural barrier between
320 continental Europe and the UK in 2004 and 2005.
321 We found some clustering of records of H. axyridis with port and airport locations at a regional scale,
322 due to the preponderance of these transport hubs in the south-east near the European continent.
323 However, we found no clustering at small scales, indicating that the species’ records are not clustered
324 in the direct vicinity of ports and airports, as would be the case if these were the primary means of
325 introduction, but were instead scattered more broadly across the southeast of England. It is impossible
326 to rule out the role of anthropogenic transport entirely: indeed, there is considerable anecdotal
327 evidence of ladybirds being moved on ships and other motorised transport [47]. However, the lack
328 of small-scale clustering, combined with the correlation in timing between atmospheric events and
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329 ladybird records, suggests that atmospheric transport is a more likely primary method for the species’
330 arrival.
331 Harmonia axyridis has been reported in 53 countries outside its native range, and when examining
332 the spread of the species it is striking that island nations, and those that have strict detection and
333 prevention systems (e.g. Australia, Cyprus, Iceland, and Malta) unaffected [27,48]. As controls
334 become stricter on anthropogenic transport pathways, it is likely that natural cross-border dispersal
335 from an invasive population will become an increasingly important means of spread for non-native
336 invasive species. Our results indicate that it is possible for H. axyridis to be carried across the English
337 Channel and successfully establish: other small winged animals are likely to be able to undertake
338 similarly-assisted dispersal to the UK and other island nations. Indeed, over the last two decades,
339 there have been many new species that have established in the UK: some good fliers, such as the 20
340 new species of moth [49], but others less associated with flight including the ladybirds
341 Henosepilachna argus, Rhyzobius chrysomeloides, Rhyzobius lopanthae, Rhyzobius forestieri, and
342 Scymnus interruptus [50].
343 Wind-assisted passage from continental Europe may be a particularly important route for species that
344 are more adapted to passively utilising wind currents to disperse, such as moths and juvenile spiders.
345 The ballooning behaviour of Wasp spiders Argiope bruennichi [51], where individuals are carried by
346 wind-blown silk threads, combined with favourable atmospheric events during the species’ dispersal
347 period, may well have been instrumental in the arrival of this species from continental Europe to the
348 UK in the 1990s. Range-expanding species may also be better-able to exploit favourable weather
349 conditions for dispersal, answering the question of why invasive species newly-arrived in an area can
350 quickly move on elsewhere, but long-time residents do not spread. Higher levels of dispersal by
351 individuals at the edge of populations showing expanding ranges has been demonstrated for H.
352 axyridis in Western Europe: Lombaert et al. [52] show that there is a rapid increase in individual
15 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
353 flight speed over eight years of range expansion. Similar processes have been predicted by several
354 studies of other taxa, e.g., [53–55]. We suggest that the combination of traits associated with greater
355 dispersal potential, together with frequent atmospheric events facilitating long-distance dispersal, is
356 likely to be particularly important for saltatorial population expansion across waterbodies or other
357 large-scale barriers to spread. Once introduced, other factors, such as climate, may play a more
358 influential role in its spread each year [56,57] , although this expansion may also be assisted by
359 smaller-scale atmospheric events.
360 Our results demonstrate that Harlequin ladybirds colonising the UK via atmospheric events had more
361 opportunities to have originated from France, as southerly winds are more common than easterlies.
362 However, from the available evidence, populations of H. axyridis appear to be larger in Belgium than
363 in France and so, despite fewer atmospheric events originating from Belgium, each event has a higher
364 likelihood of bearing ladybirds. This probable influx of individuals from multiple sources has likely
365 contributed to the later successful establishment and spread via intraspecific but interpopulational
366 admixture [58,59].
367 In many invasion events (but not all), source populations can be identified using genetic methods
368 [60]. However, this approach may be affected by sampling errors [61], and it is not predictive in
369 terms of arrival dates or methods. Atmospheric modelling, however, may provide a more rapid
370 assessment of potential source locations when speed is required. Crucially, this approach also
371 provides information on the timing and method of arrival, allowing a better picture of the conditions
372 which facilitate the arrival of non-native species. This data can then be used to predict arrivals,
373 allowing the warning and priming of survey networks, for instance by circulating photographs of the
374 potential arrival with a request for any records which might arise.
375 One major limitation of this approach is that biological records used within the model, and also those
376 used in model evaluation, need to be relatively comprehensive. Biological recording schemes have
16 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
377 increased in presence and reach in the last decade, particularly with the use of online tools, but for
378 novel species there may be a lag between arrival and sufficient records to build an accurate picture of
379 the introduction event. Although there are few Harlequin ladybird records from 2004, it is possible
380 that this species established earlier: three specimens are known from 2003 [32]. As a volunteer survey
381 with (in 2004) relatively limited participation, the network was not particularly sensitive to detecting
382 low numbers of a new species. However, it should be noted that H. axyridis is a large and obvious
383 species which often lives in close proximity to people and is apparent even to non-entomologists.
384 While many countries have tightened their airport security in response to increased knowledge of IAS
385 [23], finding individuals of small species is still challenging, particularly if in personal luggage or
386 live plants. Moreover, individuals assisted by unpredictable atmospheric events to cross large natural
387 barriers bypass these security measures; therefore, a more integrated approach to IAS management
388 should include tracking storm events and subsequent records. These should be used to develop
389 predictive models of periods of high risk of arrival, and surveillance (including working with
390 volunteer recorders) increased. The Harlequin ladybird has had a dramatic impact on native ladybirds
391 in the UK, eating the larvae of many species [27,62,63]; if this invasion had been detected and
392 managed appropriately in the early stages, this may not have occurred.
393 We hope that the ongoing growth in biological recording, with increasing availability of resources
394 and speed of communication of sightings, will make recording schemes a better real-time early
395 warning system for novel arrivals. More recorders, more and faster access to verifiers, better
396 platforms for timely mass publication of sightings (such as social media), along with greater and more
397 accurate public awareness of novel, potentially harmful species, such as the Asian hornet Vespa
398 velutina or Asian Longhorn beetle Anoplophora glabripennis, all make speedy detection,
399 identification and dissemination of new species both more possible and more likely. The GB Non-
400 native Secretariat has a list of many potential invaders [61]; if these species are targeted for public
17 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
401 awareness campaigns, they may be detected before they establish. One such project currently holding
402 off a full-scale invasion is that concerned with the Asian hornet. In 2004, the Asian hornet Vespa
403 velutina was accidentally introduced to south-west France and has spread rapidly, with sightings in
404 Spain [64], Portugal [65], Belgium [66] and Italy [67]). A predator of European honeybees Apis
405 mellifera, arrival of this species has been associated with economic impacts on apiculture and
406 pollinator decline [68]. It was first recorded in the UK in 2016 [69,70] and has been found across the
407 south of England from Cornwall to Kent [70]; using storm events to predict areas in need of enhanced
408 nest surveillance may help to reduce the likelihood of this species becoming established in the UK.
409 Atmosphere is a viable route for invasion, over which we have no control. Given current uncertainty
410 about future climate change, greater frequency of storm events for example, could increase or
411 decrease risk of invasion via this pathway.
412
413 Acknowledgements 414
415 The SAPID project of the Academy of Finland supported this study. We would like to thank all the
416 volunteer recorders who have submitted records that made this paper possible, and both David and
417 Helen Roy of the Biological Records Centre who allowed us to use the ladybird dataset. We would
418 also like to thank the many verifiers for the UK Ladybird Survey and the technical support teams at
419 BRC.
420 421 References 422
423 [1] Wittenberg R, Cock MJW, editors. Invasive Alien Species: A Toolkit of Best Prevention and
18 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
424 Management Practices. Wallingford: CAB Internationa; 2001.
425 [2] Hulme PE, Bacher S, Kenis M, Klotz S, Kühn I, Minchin D, et al. Grasping at the routes of
426 biological invasions: a framework for integrating pathways into policy. J Appl Ecol
427 2008;45:403–14. doi:10.1111/j.1365-2664.2007.01442.x.
428 [3] Diamond J. “Normal” extinctions of isolated populations. In: Nitecki MH, editor. Extintions,
429 Chigago: Chicago University Press; 1984, p. 191–246.
430 [4] Millennium Ecosystem Assessment. Ecosystems and Human Well-Being (Synthesis).
431 Washington, DC: 2005.
432 [5] UKNEA. (UK National Ecosystem Assessment), The UK National Ecosystem Assessment:
433 Technical Report). UNEP-WCMC 2011.
434 [6] Combat Invasive Alien Species – Target 5 - Environment - European Commission n.d.
435 http://ec.europa.eu/environment/nature/biodiversity/strategy/target5/index_en.htm (accessed
436 November 9, 2018).
437 [7] Pimentel D, McNair S, Janecka J, Wightman J, Simmonds C, O’Connell C, et al. Economic
438 and environmental threats of alien plant, animal, and microbe invasions. Agric Ecosyst Environ
439 2001;84:1–20. doi:10.1016/S0167-8809(00)00178-X.
440 [8] Williams F, Eschen R, Harris A, Djeddour D, Pratt C, Shaw RS, et al. The economic cost of
441 invasive non-native species on Great Britain. Wallingford: CABI; 2010.
442 [9] Lodge DM. Biological invasions: Lessons for ecology. Trends Ecol Evol 1993;8:133–7.
443 doi:10.1016/0169-5347(93)90025-K.
444 [10] Williamson M, Fitter A. The Varying Success of Invaders. Ecology 1996;77:1661–6.
445 doi:10.2307/2265769.
19 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
446 [11] Davis MA, Thompson K. Eight ways to be a colonizer: two ways to be an invader: a proposed
447 nomenclature scheme for invasion ecology. Bull Ecol Soc Am 2000;81:226–30.
448 [12] Manchester SJ, Bullock JM. The impacts of non-native species on UK biodiversity and the
449 effectiveness of control. J Appl Ecol 2000;37:845–64. doi:10.1046/j.1365-2664.2000.00538.x.
450 [13] Roy HE, Peyton J, Aldridge DC, Bantock T, Blackburn TT, Britton R, et al. Horizon scanning
451 for invasive alien species with the potential to threaten biodiversity in Great Britain. Glob
452 Chang Biol 2014;20:3859–3871. doi:doi: 10.1111/gcb.12603.
453 [14] Turbelin AJ, Malamud BD, Francis RA. Mapping the global state of invasive alien species:
454 patterns of invasion and policy responses. Glob Ecol Biogeogr 2017;26:78–92.
455 doi:10.1111/geb.12517.
456 [15] Lacasella F, Marta S, Singh A, Stack Whitney K, Hamilton K, Townsend P, et al. From pest
457 data to abundance-based risk maps combining eco-physiological knowledge, weather, and
458 habitat variability. Ecol Appl 2017;27:575–88. doi:10.1002/eap.1467.
459 [16] Hulme PE. Climate change and biological invasions: evidence, expectations, and response
460 options. Biol Rev 2017;92:1297–313. doi:10.1111/brv.12282.
461 [17] Roy HE, Hesketh H, Purse B V., Eilenberg J, Santini A, Scalera R, et al. Alien Pathogens on
462 the Horizon: Opportunities for Predicting their Threat to Wildlife. Conserv Lett 2017;10:477–
463 84. doi:10.1111/conl.12297.
464 [18] Dick JTA, Laverty C, Lennon JJ, Barrios-O’Neill D, Mensink PJ, Robert Britton J, et al.
465 Invader Relative Impact Potential: a new metric to understand and predict the ecological
466 impacts of existing, emerging and future invasive alien species. J Appl Ecol 2017;54:1259–
467 67. doi:10.1111/1365-2664.12849.
20 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
468 [19] Rejmánek M. Invasive plants: approaches and predictions. Austral Ecol 2000;25:497–506.
469 doi:10.1046/j.1442-9993.2000.01080.x.
470 [20] Branch GM, Nina Steffani C. Can we predict the effects of alien species? A case-history of the
471 invasion of South Africa by Mytilus galloprovincialis (Lamarck). J Exp Mar Bio Ecol
472 2004;300:189–215. doi:10.1016/J.JEMBE.2003.12.007.
473 [21] THUILLER W, RICHARDSON DM, PYSEK P, MIDGLEY GF, HUGHES GO, ROUGET
474 M. Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global
475 scale. Glob Chang Biol 2005;11:2234–50. doi:10.1111/j.1365-2486.2005.001018.x.
476 [22] Kolar CS, Lodge DM. Ecological predictions and risk assessment for alien fishes in North
477 America. Science 2002;298:1233–6. doi:10.1126/science.1075753.
478 [23] Early R, Bradley BA, Dukes JS, Lawler JJ, Olden JD, Blumenthal DM, et al. Global threats
479 from invasive alien species in the twenty-first century and national response capacities. Nat
480 Commun 2016;7:12485. doi:10.1038/ncomms12485.
481 [24] van Lenteren JC, Loomans AJM, Babendreier D, Bigler F. Harmonia axyridis: an
482 environmental risk assessment for Northwest Europe. From Biol. Control to Invasion Ladybird
483 Harmon. axyridis as a Model Species, Dordrecht: Springer Netherlands; 2007, p. 37–54.
484 doi:10.1007/978-1-4020-6939-0_4.
485 [25] Robinet C, Liebhold AM. Dispersal polymorphism in an invasive forest pest affects its ability
486 to establish. Ecol Appl 2009;19:1935–43.
487 [26] Essl F, Dullinger S, Rabitsch W, Hulme PE, Hülber K, Jarošík V, et al. Socioeconomic legacy
488 yields an invasion debt. Proc Natl Acad Sci U S A 2011;108:203–7.
489 doi:10.1073/pnas.1011728108.
21 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
490 [27] Roy HE, Brown PMJ, Adriaens T, Berkvens N, Borges I, Clusella-Trullas S, et al. The
491 harlequin ladybird, Harmonia axyridis: global perspectives on invasion history and ecology.
492 Biol Invasions 2016;18:997–1044. doi:10.1007/s10530-016-1077-6.
493 [28] Hodek I, Honěk A. Ecology of Coccinellidae. Dordrecht: Springer Netherlands; 1996.
494 doi:10.1007/978-94-017-1349-8.
495 [29] Raak-van den Berg CL, Hemerik L, de Jong PW, van Lenteren JC. Mode of overwintering of
496 invasive Harmonia axyridis in the Netherlands. BioControl 2012;57:71–84.
497 doi:10.1007/s10526-011-9394-2.
498 [30] Brown PMJ, Thomas CE, Lombaert E, Jeffries DL, Estoup A, Lawson Handley L-J. The global
499 spread of Harmonia axyridis (Coleoptera: Coccinellidae): distribution, dispersal and routes of
500 invasion. BioControl 2011;56:623–41. doi:10.1007/s10526-011-9379-1.
501 [31] Roy HE, Adriaens T, Isaac NJB, Kenis M, Onkelinx T, Martin GS, et al. Invasive alien predator
502 causes rapid declines of native European ladybirds. Divers Distrib 2012;18:717–25.
503 doi:10.1111/j.1472-4642.2012.00883.x.
504 [32] Brown PMJ, Roy HE, Rothery P, Roy DB, Ware RL, Majerus MEN. Harmonia axyridis in
505 Great Britain: analysis of the spread and distribution of a non-native coccinellid. BioControl
506 2008;53:55–67. doi:10.1007/s10526-007-9124-y.
507 [33] Juhász L, Hochmair HH. Where to catch ‘em all? – a geographic analysis of Pokémon Go
508 locations. Geo-Spatial Inf Sci 2017;20:241–51. doi:10.1080/10095020.2017.1368200.
509 [34] Sofiev M, Siljamo P, Valkama I, Ilvonen M, Kukkonen J. A dispersion modelling system
510 SILAM and its evaluation against ETEX data. Atmos Environ 2006;40:674–85.
511 doi:10.1016/j.atmosenv.2005.09.069.
22 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
512 [35] Sofiev M, Vira J, Kouznetsov R, Prank M, Soares J, Genikhovich E. Construction of the
513 SILAM Eulerian atmospheric dispersion model based on the advection algorithm of Michael
514 Galperin. Geosci Model Dev 2015;8:3497–522. doi:10.5194/gmd-8-3497-2015.
515 [36] Saarnio K, Aurela M, Timonen H, Saarikoski S, Teinilä K, Mäkelä T, et al. Chemical
516 composition of fine particles in fresh smoke plumes from boreal wild-land fires in Europe. Sci
517 Total Environ 2010;408:2527–42. doi:10.1016/j.scitotenv.2010.03.010.
518 [37] Vira J, Carboni E, Grainger RG, Sofiev M. Variational assimilation of IASI
519 SO<sub>2</sub> plume height and total column retrievals in
520 the 2010 eruption of Eyjafjallajökull using the SILAM v5.3 chemistry transport model. Geosci
521 Model Dev 2017;10:1985–2008. doi:10.5194/gmd-10-1985-2017.
522 [38] Sofiev M, Siljamo P, Ranta H, Linkosalo T, Jaeger S, Rasmussen A, et al. A numerical model
523 of birch pollen emission and dispersion in the atmosphere. Description of the emission module.
524 Int J Biometeorol 2013;57:45–58. doi:10.1007/s00484-012-0532-z.
525 [39] Leskinen M, Markkula I, Koistinen J, Pylkkö P, Ooperi S, Siljamo P, et al. Pest insect
526 immigration warning by an atmospheric dispersion model, weather radars and traps. J Appl
527 Entomol 2011;135:55–67. doi:10.1111/j.1439-0418.2009.01480.x.
528 [40] Paatero J, Vira J, Siitari-Kauppi M, Hatakka J, Holmén K, Viisanen Y. Airborne fission
529 products in the high Arctic after the Fukushima nuclear accident. J Environ Radioact
530 2012;114:41–7. doi:10.1016/j.jenvrad.2011.12.027.
531 [41] Veriankaitė L, Siljamo P, Sofiev M, Šaulienė I, Kukkonen J. Modelling analysis of source
532 regions of long-range transported birch pollen that influences allergenic seasons in Lithuania.
533 Aerobiologia (Bologna) 2010;26:47–62. doi:10.1007/s10453-009-9142-6.
534 [42] Wainwright CE, Stepanian PM, Reynolds DR, Reynolds AM. The movement of small insects
23 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
535 in the convective boundary layer: linking patterns to processes. Sci Rep 2017;7:5438.
536 doi:10.1038/s41598-017-04503-0.
537 [43] Grez AA, Rand TA, Zaviezo T, Castillo-Serey F. Land use intensification differentially
538 benefits alien over native predators in agricultural landscape mosaics. Divers Distrib
539 2013;19:749–59. doi:10.1111/ddi.12027.
540 [44] Jeffries DL, Chapman J, Roy HE, Humphries S, Harrington R, Brown PMJ, et al.
541 Characteristics and Drivers of High-Altitude Ladybird Flight: Insights from Vertical-Looking
542 Entomological Radar. PLoS One 2013;8:e82278. doi:10.1371/journal.pone.0082278.
543 [45] Johnson C. Migration and dispersal of insects by flight. By C. G. Johnson. London (Methuen).
544 London: Methuen; 1969. doi:10.1002/qj.49709640721.
545 [46] Bellard C, Genovesi P, Jeschke JM. Global patterns in threats to vertebrates by biological
546 invasions. Proc R Soc B Biol Sci 2016;283:20152454. doi:10.1098/rspb.2015.2454.
547 [47] Roy H, Brown P, Frost R, Poland R. Ladybirds (Coccinellidae) of Britain and Ireland. Centre
548 for Ecology & Hydrology Natural Environment Research Council (NERC); 2011.
549 [48] Camacho-Cervantes M, Ortega-Iturriaga A, del-Val E. From effective biocontrol agent to
550 successful invader: the harlequin ladybird ( Harmonia axyridis ) as an example of good ideas
551 that could go wrong. PeerJ 2017;5:e3296. doi:10.7717/peerj.3296.
552 [49] Fox R, Conrad KF, Parsons MS, Warren MS, Woiwod I. The state of Britain’s larger moths
553 2006.
554 [50] Roy H, Lewington R, Brown P. Field Guide to the Ladybirds of Great Britain and Ireland.
555 Bloomsbury Wildlife; 2018.
556 [51] Walter A, Bliss P, Moritz RFA, Moritz RFA. The wasp spider Argiope bruennichi (Arachnida,
24 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
557 Araneidae): ballooning is not an obligate life history phase. J Arachnol 2005;33:516–22.
558 doi:10.1636/04-78.1.
559 [52] Lombaert E, Estoup A, Facon B, Joubard B, Grégoire J-C, Jannin A, et al. Rapid increase in
560 dispersal during range expansion in the invasive ladybird Harmonia axyridis. J Evol Biol
561 2014;27:508–17. doi:10.1111/jeb.12316.
562 [53] Travis* JMJ, Dytham C. Evolutionary ecology research. vol. 4. Evolutionary Ecology; 1999.
563 [54] Burton OJ, Phillips BL, Travis JMJ. Trade-offs and the evolution of life-histories during range
564 expansion. Ecol Lett 2010;13:1210–20. doi:10.1111/j.1461-0248.2010.01505.x.
565 [55] Shine R, Brown GP, Phillips BL. An evolutionary process that assembles phenotypes through
566 space rather than through time. Proc Natl Acad Sci U S A 2011;108:5708–11.
567 doi:10.1073/pnas.1018989108.
568 [56] Kumschick S, Fronzek S, Entling MH, Nentwig W. Rapid spread of the wasp spider Argiope
569 bruennichi across Europe: a consequence of climate change? Clim Change 2011;109:319–29.
570 doi:10.1007/s10584-011-0139-0.
571 [57] Krehenwinkel H, Tautz D. Northern range expansion of European populations of the wasp
572 spider Argiope bruennichi is associated with global warming-correlated genetic admixture and
573 population-specific temperature adaptations. Mol Ecol 2013;22:2232–48.
574 doi:10.1111/mec.12223.
575 [58] Facon B, Crespin L, Loiseau A, Lombaert E, Magro A, Estoup A. Can things get worse when
576 an invasive species hybridizes? The harlequin ladybird Harmonia axyridis in France as a case
577 study. Evol Appl 2011;4:71–88. doi:10.1111/j.1752-4571.2010.00134.x.
578 [59] Lawson Handley L-J, Estoup A, Evans DM, Thomas CE, Lombaert E, Facon B, et al.
25 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
579 Ecological genetics of invasive alien species. BioControl 2011;56:409–28.
580 doi:10.1007/s10526-011-9386-2.
581 [60] ESTOUP A, GUILLEMAUD T. Reconstructing routes of invasion using genetic data: why,
582 how and so what? Mol Ecol 2010;19:4113–30. doi:10.1111/j.1365-294X.2010.04773.x.
583 [61] MUIRHEAD JR, GRAY DK, KELLY DW, ELLIS SM, HEATH DD, MACISAAC HJ.
584 Identifying the source of species invasions: sampling intensity vs. genetic diversity. Mol Ecol
585 2008;17:1020–35. doi:10.1111/j.1365-294X.2008.03669.x.
586 [62] Roy HE, Adriaens T, Isaac NJB, Kenis M, Onkelinx T, Martin GS, et al. Invasive alien predator
587 causes rapid declines of native European ladybirds. Divers Distrib 2012;18:717–25.
588 doi:10.1111/j.1472-4642.2012.00883.x.
589 [63] Comont RF, Roy HE, Harrington R, Shortall CR, Purse B V. Ecological correlates of local
590 extinction and colonisation in the British ladybird beetles (Coleoptera: Coccinellidae). Biol
591 Invasions 2014;16:1805–17. doi:10.1007/s10530-013-0628-3.
592 [64] López S, González M, Goldarazena A. Vespa velutina Lepeletier, 1836 (Hymenoptera:
593 Vespidae): first records in Iberian Peninsula. EPPO Bull 2011;41:439–41. doi:10.1111/j.1365-
594 2338.2011.02513.x.
595 [65] Grosso-Silva J, Maia M. Vespa velutina Lepeletier, 1836 (Hymenoptera, Vespidae), new
596 species for Portugal. Arq Entomolóxicos 2012:53–4.
597 [66] Rome Q. Spread of the invasive hornet Vespa velutina Lepeletier, 1836, in Europe in 2012
598 (Hym., Vespidae). Bull Soc Entomol Fr 2013;118:21–2.
599 [67] CABI. Vespa velutina (Asian Hornet). Invasive Species Compend 2018.
600 https://www.cabi.org/isc/datasheet/109164.
26 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.
601 [68] Monceau K, Bonnard O, Thiéry D. Vespa velutina: a new invasive predator of honeybees in
602 Europe. J Pest Sci (2004) 2014;87:1–16. doi:10.1007/s10340-013-0537-3.
603 [69] Asian Hornet, Vespa velutina - GB non-native species secretariat n.d.
604 http://www.nonnativespecies.org/factsheet/factsheet.cfm?speciesId=3826 (accessed
605 November 8, 2018).
606 [70] Asian hornet: UK sightings in 2018 - GOV.UK n.d.
607 https://www.gov.uk/government/news/asian-hornet-uk-sightings-in-2018 (accessed June 7,
608 2019).
609
610
27 bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. bioRxiv preprint doi: https://doi.org/10.1101/681452; this version posted June 24, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license.