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Mapping Ponto Caspian Invaders in Great BritainB. Gallardo and D.C. Aldridge

March, 2012

CAMBRIDGEENVIRONMENTAL CONSULTANTS

Mapping Ponto Caspian Invaders in Great BritainBelinda Gallardo, David C. Aldridge

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CAMBRIDGEENVIRONMENTAL CONSULTANTS

Executive summary

In Europe, the extensive network of canals linking all major river catchments and connecting the southern (Black, Azov, Caspian) and northern (Baltic, North) seas has allowed the spread of at least 40 species from the Ponto Caspian area, with important ecological and economic impacts.

A total of 16 Ponto Caspian species have been short-listed by the Environment Agency as potential future invaders of British waters. They include ten gammarids, one isopod, two mysids and three fishes. At least three of them are already present in England: Chelicorophium curvispinum, Hemimysis anomala and Dikerogammarus villosus, although they are confined to isolated populations and still do not present active dispersal. Considering their potential negative ecological and economic impacts, it is vital to prevent the introduction of these 16 species into Great Britain as well as to develop extensive monitoring programmes for their early detection.

The objectives of the present report are: i) to use species distribution models based on climatic conditions to model the potential distribution of 16 Ponto Caspian species in Great Britain allowing prioritization based on their risk levels; ii) to combine the individual distribution models to produce a ‘Heat map’ of Great Britain that allows identifying the most vulnerable regions to multiple invasions; and iii) to narrow down the areas at a higher risk in Great Britain based on observed differences in water chemistry between invaded and un-invaded water-bodies in Europe.

The current distribution of Ponto-Caspian species in Europe shows clear geographic patterns with some species spreading towards the North-East (e.g. Chaetogammarus warpachowski, Dikerogammarus haemobaphesand Neogobius melanostomus), and others towards the North-West (e.g. C. curvispinum, H. anomala and D. villosus). This pattern is most likely related to the corridor they used for dispersal: central (Black Sea-Baltic Sea through Dnieper and Nemunas rivers) or southern (Black Sea-North Sea through the Danube-Main-Rhine waterways).

Species predicted not to be present in Great Britain according to species distribution models based on climatic predictors included three gammarids (Chaetogammarus ischnus, C. warpachowski and Pontogamamrus robustoides) and two fishes (Neogobius gymnotrachelu and Proterorhinus marmoratus). These species are currently distributed towards the North-East of Europe (e.g. rivers Don, Dnieper, Volga, Curonian and Vistula Lakes).

In contrast, species whose suitability was high across large parts of Great Britain included three gammarids (C. curvispinum, D. bispinosus and D. villosus) and the two mysids (H. anomala and Limnomysis benedeni). These species are currently located along the Danube-Rhine corridor, they are widely present in The Netherlands and Belgium, and patchily also in France, which may explain their high suitability in Great Britain. Three of these species, C. curvispinum, D. villosus and H. anomala, are actually already present within their respective high climatic risk areas within GB, which reinforces the results of the models which were generated without the inclusion of the GB sites .

The remaining six species, five gammarids (C. robustum, D. haemobaphes, E. trichiatus, Jaera istri and Obesogammarus obesus) and a fish (N. melanostomus), showed varying predicted distributions across Great Britain, with suitability generally decreasing from North-East to South-West coasts.

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A climatic ‘Heat Map’ combining the results of all 16 species together pointed to the SE of England as the area most vulnerable to multiple invasions from the Ponto Caspian region, and particularly the Thames and Anglian river basin districts and parts of the Severn and Humber.

Alkalinity was the most important factor discriminating un-invaded from invaded water-bodies in Europe. Regression models suggest that alkalinity concentration > 120 mg/L may favour the establishment of Ponto-Caspian invaders. This does not mean that the species cannot survive below this alkalinity concentration, but that the probability of presence is lower. In Great Britain, SE England shows highest alkalinity concentrations, which coincides with the area previously identified in the Heat Map as yielding highest climatic suitability scores for at least 11 of the 16 species investigated.

Considering the similar climatic conditions of South-East England to those of the closest invaded areas in the continent, the location of numerous commercial ports of international relevance, the availability of artificial canals for dispersal, and the high water alkalinity concentration, we can consider SE England – and in particular the Anglian, Thames and Severn Valleys— as the areas under the highest risk of being invaded.

Regarding species, C. curvispinum is possibly one of the most harmful species investigated in this study. The climate and water chemistry of British water is, according to the models, highly suitable for this species which has very effective dispersal abilities through canals and also ship hull and ballast water. In addition, it is closely associated with the zebra mussel, which is currently widespread in Great Britain. C. curvispinum is a habitat engineer that covers the substrate with muddy tubes and filtrates suspended water particles; it has important food web impacts and outcompetes both native and invasive species.

SE England showed particularly high suitability scores for two Dikerogammarus species (D. villosus and D. bispinosus). The two species have many similarities and often displace each other, although D. villosus is believed to be the most aggressive invader.

The suitability of British waters for the two mysids (H. anomala and L. benedeni) is also high. H. anomala prefers brackish waters 0 to 30 m deep and is able to tolerate salinities as high as 19‰ salinity, whereas L. benedeni inhabits shallower waters 0 to 6 m deep with low water current, abundant macrophytes and low salinity (< 5‰). H. anomala may use the extensive network of canals in the Midlands to occupy its potential range in the Thames, Severn and Anglian river basin districts. Both species predate on phytoplankton and zooplankton with potential knock-on effects on food web dynamics.

The zebra mussel, which has established throughout much of England and parts of Wales and Scotland, may act as a factor modifying the habitat conditions making them more suitable for the establishment of other Ponto Caspian species. Most of the 16 species investigated show a preference for zebra mussel beds over other substrate types.

Ship transport is the most likely route of introduction of Ponto Caspian species into Great Britain, although other commercial and recreational activities in rivers and lakes can be also important. Tougher control of water activities in lakes are therefore important to prevent and monitor the appearance of these species.

The Heat and alkalinity maps provide means for a scientifically informed prioritization of species (C. curvispinum, Dikerogammarus spp., H. anomala and L. benedeni) and river basin districts (Thames, Humber, Severn and Anglian) to focus prevention and monitoring efforts.

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1. Introduction

In Europe, the number of established non-native species, especially from the Ponto-Caspian area, has dramatically increased over recent decades, with important ecological and economic impacts. Currently, at least 40 Ponto Caspian species are known to have invaded Europe (Leppäkoski and Olenin 2000), the most characteristic of which is the zebra mussel (Dreissena polymorpha). This mussel has colonized much of Europe over the last two centuries appearing for the first time in Great Britain 1824. Apart from the zebra mussel, another three Ponto Caspian species have established in Great Britain: Cheliocorophium curvispinum, identified in 1935 in the river Avon, near the confluence with the River Severn (Crawford 1935); the bloody-red mysid (Hemimysis anomala) detected in 2004 in the river Trent (Holdich 2006); and more recently the killer shrimp (Dikerogammarus villosus) appeared in the Ouse river in 2010 (MacNeil et al. 2010). D. polymorpha, C. curvispinum and H. anomala are believed to have been introduced in Great Britain through ship transport from German and Dutch ports (bij de Vaate et al. 2002), although other human related factors have been suggested such as use of the mussels as fish bait (Aldridge et al. 2004), and international rowing competitions in the area invaded by the mysid (Stubbington et al. 2008). The origin of D. villosus is still unknown, though it might be related to the intensive recreational and sporting use of the invaded lakes.

Introduction of a non-native species does not mean the species will establish. Propagules introduced through recreational and commercial activities in Great Britain are subject to the environmental conditions of the system being invaded, including the local climate conditions, water chemistry and current, substrate and vegetation type. Therefore, a closer match between the European and British habitat of the species will imply higher possibilities of a successful invasion. Species distribution models are used to measure the climate suitability for an invasive species, by projecting a model of the known species distribution into a region of interest (Guisan and Thuiller 2005). For this reason, species distribution models are especially helpful to locate areas at continental or regional scale which are most climatically similar to the current range of the invasive species, and that are most susceptible to successful colonization in the event of an introduction (Peterson 2003).

After the large-scale areas under a high risk of invasion have been defined, local-scale factors such as water chemistry can be used to further narrow down the water-bodies at risk and the likely routes of introduction. Although invasive Ponto Caspian species are tolerant to a wide range of environmental conditions and no clear limits have been yet reported, their fitness and competitive ability must vary along environmental gradients (Hänfling et al. 2011). Consequently, by analysing the current range of distribution and optimum conditions, we can define the combination of environmental features that might be more-or-less favourable to the establishment of Ponto Caspian invaders. For instance, several experiments have shown that invasive crustaceans have an advantage over their native counterparts at high rather than low water conductivities (Wijnhoven et al. 2003, Kestrup and Ricciardi 2009). Alkalinity and pH can affect the moulting process of shrimps and other crustaceans, affecting the hardening of the new carapace (Greenaway 1985). Water pollution (high nitrogen and organic carbon loads) has been also related to the explosion of successful aquatic invasions, which take advantage of the increased ionic concentration and impoverished native communities (Arbačiauskas and Gumuliauskaitė 2007).

A total of 16 Ponto Caspian species has been short-listed by the Environment Agency as potential future invaders of British waters. They include ten gammarids, one isopod, two mysids and three fishes (Table 1). At least three of them are already present in England: C. curvispinum, H. anomala and D. villosus, although they are confined to isolated populations and still do not present widespread dispersal behaviour. Considering their potential negative ecological and economic impacts, it is vital to prevent the introduction of these 16 species into Great Britain as well as to develop extensive monitoring programs for their early detection. In this sense, species distribution models coupled with water chemistry analyses can help to focus prevention and monitoring efforts in the areas under the highest risk of invasion.

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1.1 Objectives

i) To use species distribution models based on climatic conditions – and water chemistry if possible - to model the potential distribution of 16 Ponto Caspian species in Great Britain.

ii) To combine the individual distribution models to produce a ‘Heat Map’ of Great Britain that allows identifying the most vulnerable regions to multiple invasions.

iii) To narrow down the areas at a higher risk in Great Britain based on observed differences in water chemistry between invaded and un-invaded water-bodies in Europe.

2. Methodology

2.1 Species presence

A total of 16 Ponto-Caspian species were selected for analysis(Table 1). Locations (latitude, longitude) where the species are present in Europe were extracted from the Global Biodiversity Information facility (http://data.gbif.org, last accessed 15 February 2012) and a comprehensive literature research (Appendix 1). When the species was reported from a particular stretch of a river (e.g. Danube estuary) a number of random points were manually located within that river stretch. A total of 2785 occurrences were used for further analyses, distributed in 29 countries. Maps including all occurrences used for each species can be consulted in Appendices 2.1 (gammarids and isopod) and 2.2 (mysids and fishes).

Table 1. Species included in the present study. N: number of occurrences found in Europe. Range: countries where the species were located.

Name Common name

Type N Range Present in UK

Chaetogammarus ischnus

Gammarid 60 RU, BE, UK, LI, PO, SVK, HU, AU, GE, FR

NO

Chaetogammarus warpachowski

Gammarid 87 BU, RO, UK, LI, LV, RU, KA, AZ NO

Cheliorophium curvispinum

Gammarid 536 BU, RO, UK, MO, BE, LI, RU, KA, PO, YU, CR, HU, AU, GE, NE, BEL, FR

YES

Cheliorophium robustum

Gammarid 32 RO, UK, BE, YU, HU, SVK, GE, NE NO

Dikerogammarus bispinosus

Gammarid 25 YU, HU, AU, GE, NE NO

Dikerogammarus haemobaphes

Gammarid 196 RU, UK, BE, LI, PO, HU, MO, RO, BU, TU, TU, CR, AU, GE, BE, NE, FR

NO

Dikerogammarus villosus

Killer shrimp Gammarid 356 RO, BU, UK, BE, PO, GE, YU, CR, HU, SVK, AU, CZ, IT, SW, FR, BE, NE

YES

Echinogammarus trichiatus

Gammarid 95 RO, UK, SVK, HU, GE, NE NO

Hemimysis anomala Bloody-red mysid

Mysid 189 RU, UK, RO, MO, YU, CR, BU, FI, LV, LI, SWE, PO, SVK, HU, AU, GE, NE, BE, IT, FR, IR

YES

Jaera istri Isopod 74 RO, BU, YU, HU, SVK, AU, CZ, GE, FR, NE

NO

Limnomysis benedeni Mysid 369 RU, BE, UK, LI, RO, BU, TU, YU, CR, HU, SVK, AU, LV, GE, NE, BE, FR

NO

Obesogammarus obesus

Gammarid 85 RU, UK, RO, MO, BE, BU, YU, HU, CR, AU, GE

NO

Pontogammarus robustoides

Gammarid 192 RU, BE, UK, RO, MO, TU, KA, AZ, LV, LI, PO, GE

NO

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Neogobius melanostomus

Round goby Fish 77 UK, RO, BU, TU, GR, YU, SVK, HU, AU, IT, PO, LV, LI, BE, ES, FI, NE

NO

Neogobius gymnotrachelus

Racer goby Fish 35 UK, RO, MO, BU, TU, YU, CR, HU, SVK, AU, PO, BE

NO

Proterorhinus marmoratus

Tubenose goby

Fish 107 RU, BE, UK, MO, TU, HU, SVK, CR, AU, PO, GE, NE

NO

AZ: Azerbaijan, AU: Austria, BE: Belarus, BEL: Belgium, BU: Bulgaria, CR: Croatia, CZ: Czech Republic, ES: Estonia, FI: Finland, FR: France, GE: Germany, GR: Greece, HU: Hungary, IR: Ireland, IT: Italy, KA: Kazakhstan, LV: Latvia, LI: Lithuania, MO: Moldova, NE: the Netherlands, PO: Poland, RO:Romania, RU: Russia, SVK, Slovakia, SWE: Sweden, SW: Switzerland, TU: Turkey, UK: Ukraine, YU: Yugoslavia.

2.2 Habitat indicators

Climate, geomorphological and water chemistry indicators were used to assess the likelihood of invasion based on the match between habitat conditions of places invaded by the species in Europe and those of Great Britain. The following factors were included in the analyses:

- Climate. Annual temperature, seasonality, temperature of the warmest and coldest months, annual precipitation, precipitation of the driest month and seasonal precipitation were extracted from WorldClim-Global Climate Data (www.worldclime.org). Temperature is known to directly affect the fecundity, reproduction, egg size and survival of gammarids (Sheader 1996, Piscart et al. 2003, Pockl et al. 2003, Wijnhoven et al. 2003); as well as their reproductive period and growth (Devin et al. 2003), and their oxygen consumption (Bruijs et al. 2001). Precipitation patterns determine the availability of water and the frequency of droughts and floods, which can have marked effects on crustaceans.

- Altitude. Also extracted from WorldClim-Global Climate Data. Freshwater species such as those investigated here usually inhabit lowlands so a negative relationship with altitude might be expected.

- Water chemistry. Electrical conductivity, alkalinity, nitrate, pH, dissolved organic carbon and sulphate concentration were extracted from the Geochemical Database of Europe (http://weppi.gtk.fi), the European Environment Agency (http://www.eea.europa.eu/themes/water), and the Environment Agency. Data from these three monitoring networks were collated and interpolated across the whole of Europe using the Inverse Distance Weighting method available in ArcGIS 10. Water chemistry information was deficient for European Eastern countries including Belarus, Ukraine, Romania, Macedonia, Turkey and Russia. Therefore these countries were excluded from the interpolated model.

All maps were scaled to a 30 second resolution (approximately 1km2) and WSG84 projection.

2.3 Species distribution modelling

We used MaxEnt version 3.3 (www.cs.princeton.edu/~schapire/maxent) to develop species distribution models. MaxEnt is a machine-learning algorithm that minimizes the relative entropy between two probability densities (one estimated from the presence data and the other from the background) defined in covariate space (Elith et al. 2010). According to several studies comparing algorithms, MaxEnt is one of the highest performing methods (Elith et al. 2006, Phillips et al. 2006). For this study default modelling parameters (convergence threshold=105, maximum iterations= 500, regularization value B= auto) were used, following Phillips et al. (2006). However, to improve the transferability of models across space, we tried a regularization modifier between 1 and 5 (Phillips and

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Dudik 2008). Regularization reduces the likelihood of overfitting models, thus increasing the ability of models beyond the training region (Medley 2010).

For input, MaxEnt models used the dataset of Ponto Caspian occurrences in Europe and the set of climatic or water chemistry factors that might limit the species' capabilities to survive. Data were split into two sets: 80% of the data was used for modelling and the remaining 20% to test the accuracy of the predictions. Because no absence data was available, a total of 10,000 pseudo-absences were generated from the Europe-wide background. To assess model performance we used the Area Under the ROC Curve (AUC) (Hanley and McNeil 1982), which represents the probability that a random occurrence locality will be classified as more suitable than a random pseudo-absence. A model that performs no better than random will have an AUC of 0.5 whereas a model with perfect discrimination will score 1.

Three MaxEnt models were developed:

I. Climate-only model. Based on temperature and rainfall related variables, and altitude. Including the whole of Europe (35 countries, accounting for the native range of the species).

II. Water chemistry + climate + altitude model. Based on the variables included in the previous model, plus nitrate, alkalinity, conductivity, sulphate, pH and dissolved organic carbon. This model excluded 5 eastern European countries covering part of the native range of the species because of insufficient data available. Results should be therefore taken with caution.

After calibration, models were projected onto Europe to obtain suitability maps, ranging from 0= conditions completely different to those of the current range of the species, to 1= complete match with the current range of the species. Subsequently, we focused on Great Britain for closer examination. The threshold maximizing the sensitivity (i.e. number of presences correctly predicted) and specificity (i.e. number of absences correctly predicted) of the model was used to transform the suitability map into a predicted presence/absence map. Finally, all 16 maps were combined together into a single ‘Heat map’ reflecting the risk of invasion in Great Britain of 1 to 16 species.

2.4 Water chemistry modelling

First, water chemistry characteristics of sites invaded by the 16 species in Europe were extracted from the water chemistry maps using the Extraction tool of ArcView 10.0. Water chemistry characteristics of invaded sites were afterwards summarized by species to identify main differences between species.

To model the water chemistry preferences of Ponto Caspian species, ca. 2700 pseudo-absences were manually generated covering all rivers and lakes not reported to be invaded in South and North Europe (Appendix 3). These are therefore not real absences, as the species might be present in some of those rivers but not yet reported, or the species might be able to colonize them in the future, as Ponto-Caspian species are still dispersing in Europe. However, this generation of pseudo-absences provides the best available approximation to investigate major differences in water chemistry between invaded and un-invaded sites. In comparison with the above species distribution models, where the environmental conditions of presence points are compared with background conditions (by taking a random 10,000 background points), we performed an informed selection of un-invaded water-bodies, based on our expert knowledge about the major areas where the species are not present (e.g. Spain, Portugal, Finland, Norway), or just sporadically present (e.g. UK, Greece, Italy, Sweden).

The response of the species presence/absence to water chemistry was assessed using Generalized Additive Models (GAM, Wood 2008). GAM was chosen instead of other regression procedures because of its ability to deal with non-linear relationships between the response and the set of explanatory variables. The only underlying assumption of GAM is that the functions are additive and the components smooth (Guisan et al. 2002). Response variables in the models included each species presence/absence, while explanatory descriptors included five water chemistry factors

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(alkalinity, pH, nitrate, organic carbon and sulphate). A number of absences equal to the number of presences for each species were randomly chosen amongst the ca. 2700 pseudo-absence points generated at the scale of Europe to achieve a balanced model. A binomial family was chosen for species presence/absence and therefore a logit function used to link response and predictors (Hastie and Tibshirani 1990). An initial ‘full’ model was set using all five water chemistry factors; non-significant predictors were subsequently removed from the analysis to achieve an optimum model where all predictors are significant (also called stepwise backward optimum selection). The adjusted R2 and the percentage of deviance explained by the predictors were used to assess the goodness-of-fit of the final model.

3 Results

Some of the species investigated are widespread in Europe, including C. curvispinum, D. villosus and L. benedeni, all of them with more than 300 reported presences (Table 1). In contrast, species that showed fewer than 50 occurrences in total included C. robustum, D. bispinosus and N. gymnotrachelus (Table 1). It is not clear whether this is caused by a real difference in invasion ability between species, or simply because of lack of detection (or reporting it) in some areas. For instance, the information available for some Eastern European countries such as Yugoslavia, Romania, Bulgaria, Macedonia or Belarus was limited, and when available the description of the species distribution often vague. Difficulties in the identification of species may have also affected the information gathered, as some of the species investigated where originally considered sub-species of others (e.g. D. bispinosus and D. villosus), and therefore taxonomic misidentifications are possible.

There was a clear geographic distinction in the 16 species distribution. To the North of Europe, C. warpachowski, D. haemobaphesand N. melanostomus were spread around the Baltic Sea. C. curvispinum, H. anomala and D. villosus were the ones apparently spreading towards Western Europe, including France, Italy and Great Britain (Appendix 2A and 2B). At least 11 out of the 16 species investigated are present in The Netherlands, a potential gateway of invasive species towards Great Britain across the English Channel.

3.1 Climate suitability of Great Britain for Ponto-Caspian species

Species showed similar bioclimatic ranges, although with slight differences (Table 2). P. robustum and N. melanostomus showed a greater tolerance to high temperatures, up to 32 ˚C and minimum monthly precipitation of less than 10mm; C. ischnus, C. warpachowski and C. curvispinom were able to endure winter temperatures as low as -16 ˚C (note that this is air and not water temperature). The three fishes were found to tolerate relatively high temperatures, average > 26 ˚C.

Table 2: Mean value and range (minimum-maximum) of bioclimatic and altitude conditions at sites invaded by the 16 Ponto Caspian species in Europe. Data extracted from WorldClim maps described in Methods.

Ann

ual T T S

easo

n Max

T

Min

T

Ann

ual P

P

PP

dr

iest

PP

se

aso

n Alti

tud

e

C. ischnus8.12

3.8-11.27.83

6.41-12.824.06

20.7-28.2

-6.18-16.8- -

1.0610.3

484-101730.9021-61

30.9718-39

133.410-542

C. warpa. 7.630.4-11.6

8.767.2-12.3

24.6320.0-31.5

-7.95-16-0

547.4219-766

26.8411-36

26.0117-35

38.120-259

C. curvisp. 9.062.3-13.4

6.504.8-13.1

22.7519.5-31.4

-2.69-18.6-1.3

698.2217-1052

39.5610-72

20.378-51

36.180-916

9

C. robustum 10.617.2-12.5

7.635.41-9.2

26.3721.2-28.8

-3.60-9.4- -0.7

565.7346-778

33.4220-49

22.8715-32

76.810-516

D. bispin. 10.198.4-13.9

6.745.24-7.8

24.8120.7-28.2

-2.42-5.6-0.8

688.7540-894

39.5630-54

21.8814-36

88.040-376

D. haemob.8.72

8.4-13.9

8.125.24-12.23

25.1520.7-30.5

-6.00-5.6-2.4

615.6540-940

33.0830-60

25.9014-47

97.590-555

D. villosus 9.766.6-14.0

6.354.5-9.2

23.5919.9-29.6

-1.99-10.2-2.1

709.8347-1110

42.0419-69

19.548-46

93.170-472

E. trichiatus 9.887.9-11.6

6.455.21-8.5

23.8020.0-28.3

-1.91-4.8-0.5

681.9323-1033

41.0618-68

18.959-30

104.830-723

H. anomala 9.735.2-14.2

6.253.62-10.2

23.4318.2-29.5

-1.79-8.9-2.4

719.9416-1186

41.9721-68

20.447-44

86.630-521

J. istri 10.047.3-11.9

6.865.47-8.4

24.9820.7-29.4

-2.73-6.2- -0.2

653.1458-913

39.0521-58

21.399-41

131.501-559

L. benedeni 9.346.1-14.5

6.245.2-11.2

22.6419.6-31.6

-2.00-10.6-2.2

720.0217-965

41.6311-61

19.399-46

49.900-916

O. obesus9.31

4.0-12.48.81

6.16-12.226.85

21.6-31.4

-6.63-16.3- -

1.5541.4

246-94730.6114-60

24.7215-42

90.790-620

P. robust. 8.433.9-19.0

8.136.0-12.20

24.5419.9-32.5

-6.13-15.3-5.8

583.2216-895

27.552-58

28.7316-85

50.960-795

N. melan. 9.454.5-16.8

8.175.31-9.11

26.1720.3-32.8

-5.64-10.6-6.7

586.1325-1648

30.665-50

28.6915-77

108.860-688

N. gymno. 10.446.3-14.1

7.616.4-9.6

26.3223.4-29.8

-3.74-10.4-1.3

600.3444-769

29.7522-47

28.7518-44

95.660-385

P. marmo. 8.983.4-14.1

8.585.5-12.1

26.3621.6-31.4

-6.61-16.3-1.2

585.1224-1298

31.4612-87

27.2914-38

140.420-605

Ponto Caspian

9.22.2-19

7.013.6-13.1

23.918.2-32.8

-3.5-18.6- 6.7

665216-1648

372-87

227-85

74.40-916

I. Climate-only models

The accuracy values of species distribution models based on climate was high (between 0.937 and 0.990) although the minimum training presence (minimum suitability value of a place where the species is present) was occasionally low (<0.1) suggesting some occurrences were not correctly predicted by the models. This happened overall at presence points located in North Russia, where species were intentionally introduced far from their current European range. Excluding Russia, the minimum suitability of presence points in Europe was high (> 0.3) which suggests the model is reliable in this region. For most species, altitude and minimum temperature of the coldest month were the most important predictors, followed by maximum temperature of the warmest month and precipitation of the driest quarter (Table 3).

At least 5 species were not predicted to be present in Great Britain according to these models, or showed very small and isolated presence patches: C. ischnus, C. warpachowski, P. robustoides, N. gymnotrachelus and P. marmoratus. In contrast, models showed a high climatic suitability across large parts of Great Britain for another 5 species: C. curvispinum, D. bispinosus, D. villosus, H. anomala and L. benedeni. Climate suitability for these species was highest in the East coast of Great Britain and decreased westwards, being generally lower in Wales and Western Scotland. Finally large areas of South-Eastern England showed high suitability scores for C. robustum, D. haemobaphes, E. trichiatus, J. istri, O. obesus and N. melanostomus. Species individual presence/absence maps can be consulted in Appendix 4.

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Table 3. Results from species distribution models performed with the presence of 16 Ponto Caspian species and 6 bioclimatic factors + altitude in Europe. AUC ranges from 0.5= no better than random, to 1= perfect prediction of species’ occurrences. Only variable contributions > 5% are shown. Shaded in red, species predicted to be present in large areas of Great Britain; in orange, species predicted to be present in limited areas of England; in green, species not predicted to be present in Great Britain (or in small isolated patches).

AUC Altitude T season

Max T

Min T

Annual PP

PP season

PP driest

C. ischnus 0.943 10.9 13.1 6.4 40.7 1.8 6.2 17.8

C. warpachowski 0.971 50.5 18.2 19.1 7.3

C. curvispinum 0.949 52.6 5.8 5.7 19.5 9.3 5.9

C. robustum 0.975 29.9 10.8 7.2 39.6

D. bispinosus 0.978 21.4 5.7 46.3 5.6

D. haemobaphes 0.945 32.2 6.1 29.2

18.9 8.7

D. villosus 0.960 19.5 7.8 7.8 47.7 8.6

E. trichiatus 0.990 21.4 11.2

44.7 6 8.3

H. anomala 0.959 23.2 50.4 5.8 8.8

J. istri 0.975 8.9 6.8 56.8 5.5 15.8

L. benedeni 0.964 41.4 24.5 9.1

O. obesus 0.965 28.7 8.4 28.9

11.3 6

P. robustoides 0.967 44.9 14.3 27.2

N. melanostomus 0.948 31.6 25.4 6.3 33.2

N. gymnotrachelus 0.953 17.9 22 17.5

34.3

P. marmoratus 0.937 14 8.9 42.1

24.8 7

T season: temperature seasonality, Max T.: maximum temperature, Min T: minimum temperature, Annual PP: annual precipitation, PP driest: precipitation driest month, PP season: precipitation seasonality.

The individual predicted presence/absence maps were combined together to form a Great Britain ‘Heat map’ showing the number of species predicted to be present (from 1 to 16) (Fig. 1). According to this map, areas under a highest risk of multiple invasions include the Anglian and Thames river basins districts, the eastern part of the Severn and the southern part of the Humber districts. This map is congruent with the current location of the Ponto Caspian species present in Great Britain (Ouse, Trent and Avon rivers in the Anglian, Humber and Severn river basin districts respectively), and the wide spread of the zebra mussel in central-south England.

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Figure 1: ‘Heatmap’ of Ponto Caspian species in Great Britain, based on climatic factors and altitude. The map represents the probability of presence of 16 Ponto Caspian species based on the match between the climatic conditions in Great Britain and those of the European range of the species.

Altitude and minimum temperature were the best predictors in most models. The response of the species suitability to these two factors can be consulted in Figure 2. These graphics are extracted from C. warpachowski’s model, but are representative of the rest of species. As might be expected for freshwater species, suitability is very high at low altitudes and sharply decreases at an altitude > 250 m. With regards to minimum temperature, the species show a unimodal response with varying optima close to 0 ˚C.

Figure 2: General response of Ponto Caspian species’ probability of presence to altitude and minimum temperature according to species distribution models. Data extracted from C. warpachowski.

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II. Water Chemistry + Climate + Altitude models

The models including water chemistry on top of the variables used above showed similar AUC values (0.936-0.987) despite including more predictors (Table 4). Altitude and nitrate concentration were in this case the most important predictors in models, followed by alkalinity and annual temperature. The importance of altitude may be explained by its trade-off with temperature, thus altitude partially accounts for temperature changes.

Species not predicted to be present in Great Britain included again C. ischnus, C. warpachowski, O. obesus, P. robustoides, N. gymnotrachelus and P. marmoratus. On the other hand, C. curvispinum, D. bispinosus, D. villosus, and H. anomala could potentially invade large areas of Great Britain according to these models. Similar distributions to the previous model based on climate variables were obtained, with the exception of L. benedeni whose distribution is dramatically reduced when including water chemistry. In contrast, D. villosus seems to increase its potential range in comparison with the climate-only model. The suitability for C. robustum, D. haemobaphes E. trichiatus, J. istri and N. melanostomus decreased in this case from the east to the west coast (Appendix 5).

Table 4. Results from species distribution models performed with the presence of 16 Ponto Caspian species and a 6 bioclimatic factors, altitude and 5 water chemistry factors in Europe. AUC ranges from 0.5= no better than random, to 1= perfect prediction of species occurrences. Only variables with a contribution > 5% are shown. Shaded in red, species predicted to be present in large areas of Great Britain; in orange, species predicted to be present in limited areas of England; in green, species not predicted to be present in Great Britain (or in small isolated patches).

AUC Alt Annual T

T season

Min T

PP season

Alk. Cond. NO3 SO4 DOC

C. ischnus 0.961 9.2 16.2 8.9 7.8 5.3 48.6

C. warpach. 0.987 25.1 14.5 34.8

7.8 11.1

C. curvispinum 0.956 59.1 12.5 6.1 6.3 7

C. robustum 0.971 27.4 10 6.7 15.4 10.2 11.2 8

D. bispinosus 0.952 18.1 11.2 43.1

6.3 10 5.2

D. haemobaphes

0.959 24.3 15.3 7.1 15.2 13.2 6.6

D. villosus 0.945 28.4 22.8 5.1 20.6 6.7 9.4

E. trichiatus 0.983 18.5 14 18.4 6.5 30.1

H. anomala 0.936 31.1 28.7 7.7 9.6 5.8

J. istri 0.959 12.9 7.1 7.7 5.8 40.8 5.8 12

L. benedeni 0.965 50 6.1 5.9 8.7 6.7 5.3

O. obesus 0.970 16.8 5.5 25.2 6.4 7.3 17 13.6

P. robustoides 0.979 36.7 6.8 12.2 27.4

N. melanostomus

0.938 27.1 17.8 30.8

14.1

N. gymnotrachelus

0.965 17.4 28.8 16.9

30.1

P. marmoratus 0.960 8 8.4 20.1 6.3 43 5.5

13

Alt: altitude, Annual T: annual temperature, T season: temperature seasonality, Min T: minimum temperature, PP season: precipitation seasonality, Alk: alkalinity, Cond: conductivity, NO3: nitrate, SO4: sulphate, DOC: dissolved organic carbon.

The combined ‘Heat map’ looked in this case very similar to the Climate-only Heat map (Fig. 3). A highest number of species are predicted to be present in South East England, comprising the Thames valley, the Anglian, South East and Severn river basin districts.

Figure 3: ‘Heatmap’ of Ponto Caspian species in Great Britain, based on climatic factors, altitude and water chemistry. The map represents the probability of presence of 16 Ponto Caspian species based on the match between the environmental conditions in Great Britain and those of the European range of the species.

Amongst water chemistry indicators, alkalinity and nitrate were consistently the most important predictors of the species presence. The suitability of most species followed the example in Figure 4, including C. curvispinum, C. robustum, C. warpachowski, D. bispinosus, D. villosus, H. anomala, J. istri, L. benedeni, O. Obesus and P. marmoratus.These species’ suitabilities increased almost linearly with alkalinity until reaching an asymptote at values > 400 mg/L. In contrast, suitability decreased steadily with increasing nitrate concentration, being lower than 50% at nitrate values > 25 mg/L.

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Figure 4:Responses of Ponto Caspian species’ probability of presence to alkalinity and nitrate found according to species distribution models.

3.1 Water chemistry suitability of Great Britain for Ponto-Caspian species

The sites invaded by the 16 species showed similar water chemistry preferences, although again with slight differences (Table 5, Fig. 5). For instance, D. bispinosus registers much higher alkalinity, conductivity and sulphate concentration than the rest of species. In contrast, E. trichiatus, J. istri and H. anomala register lower alkalinity values; and D. haemobaphes, O. obesus and P. marmoratus low conductivity scores. Nitrate scores were highest in the case of C. ischnus and J. Istri, while nitrate was lowest for C. warpachowski, O. obesus and P. robustoides. With regards to pH, N. melanostomus and N. gymnotrachelus showed preference for higher pH than the rest of species.

Table 5: Mean value and range (minimum-maximum) of environmental conditions at sites where the species are reported to inhabit in Europe. Data extracted from interpolated environmental maps described in Methods.

Alk

alin

ity

Con

duct

ivity

Nitr

ate

DO

C

pH Sul

phat

e

C. ischnus241.9

78.8-455.651.58

6.95-91.47

15.581.21-33.84

9.930-40.91

7.676.3-8.2

55.430-116.1

C. warpachowski 248.959.42-454.6

56.884.72-95.39

4.261.16-7.94

12.060-49.48

7.526.38-8.11

34.660-57.29

C. curvispinum 258.530.03-487.1

62.343.61-137.5

9.660.87-32.30

9.530-49.12

7.546.59-8.39

55.340-304.8

C. robustum 256.279.50-437.8

52.7221.75-96.6

10.423.57-23.43

5.632.47-14.0

7.856.89-8.3

52.5215.54-144.8

D. bispinosus 322.0120.5-155.6

68.946.41-94.4

14.884.28-27.1

6.531.29-12.3

7.756.40-8.38

68.6012.77-116.1

D. haemobaphes 227.545.19-460.1

46.573.62-106.7

10.200.99-33.3

9.120-48.97

7.616.38-8.17

53.370-342.16

D. villosus 244.551.60-483.8

57.997.49-164.6

12.010.47-38.91

7.531.07-20.35

7.625.96-8.39

60.348.19-699.3

E. trichiatus 202.960.09-446.1

50.1410.72-124.2

9.772.27-19.3

6.661.59-19.4

7.556.95-8.01

76.8034.84-353.3

H. anomala 221.531.38-460.1

51.194.59-134.7

11.990.64-43.9

7.641.47-46.4

7.595.81-8.34

57.095.57-481.2

J. istri 213.838.87-

51.1213.95-113.3

14.593.05-33.5

4.191.22-10.9

7.656.54-8.32

67.567.28-356.9

15

469.4

L. benedeni 244.451.47-483.8

59.594.45-113.3

9.911.32-33.5

9.830-10.9

7.506.14-8.32

55.130-356.9

O. obesus 232.066.83-454.2

42.783.60-91.75

7.521.06-31.09

5.590-14.54

7.605.61-8.40

35.870-125.66

P. robustoides 257.158.12-467.7

57.094.73-95.9

7.291.16-29.9

11.090-49.2

7.706.37-8.10

46.670-107.4

N. melanostomus 269.954.32-369.6

54.600.58-97.8

11.771.14-58.1

8.171.04-43.35

7.816.80-8.24

53.5012.35-203.2

N. gymnotrachelus 255.3172.1-422.9

55.8531.25-94.6

11.863.05-48.7

7.222.07-14.35

7.887.44-8.25

63.1425.44-137.8

P. marmoratus 238.263.09-467.1

46.303.61-98.8

9.601.06-29.7

6.900-19.7

7.646.23-8.27

44.830-161.6

Ponto Caspian 243.6930.02-487.1

55.880.58-164.6

10.320.47-58.12

8.601.00-49.48

7.605.60-8.39

55.235.57-669.3

16

Figure 5: Boxplot of water chemistry at sites where the 16 Ponto Caspian species are present in Europe. Highlighted in red, boxplots significantly different from the rest according to Tukey post-hoc tests.

A number of pseudo-absence values equal to the total number of Ponto Caspian species presence points (ca. 2700 points) was manually selected from all large European rivers and lakes not invaded by the species. Presence and absence point location can be consulted in Appendix 3. Water chemistry data from presence (all 16 species together) and absence points were extracted and compared (Fig. 6). We observe that alkalinity is significantly higher in presence than absence points (Fig. 6A), while conductivity was generally lower (Fig. 6B). Nitrate, sulphate and organic carbon concentration were also generally higher in presence than in absence points (Fig. 6C-F).

Figure 6: Water chemistry in sites invaded by Ponto Caspian species in Europe and sites that remain un-invaded. Differences between un-invaded (Absence) and invaded (Presence) sites are highly significant (ANOVA, p<0.001) in all cases except for dissolved organic carbon (F1,4957=2.59, p=0.11).

In comparison with the environmental conditions of British waters, alkalinity in England and Wales is generally lower (mean 147.9 mg/L in GB; 243.7 mg/L in EU-invaded places) and conductivity higher (mean 569.0 µS/cm in GB; 55.88 µS/cm in EU-invaded places) than places where the 16 species are known to inhabit in Europe.

Regression models relating the presence/absence of Ponto Caspian species and five water chemistry variables were all significant and showed R2 ranging between 0.390 and 0.753. The deviance explained by the models (percentage of species’ presence-absence variability explained by the factors) was higher than 50% for at least 5 species (shaded in grey in Table 6): D. bispinosus, E. trichiatus, O. obesus, P. robustoides and N. melanostomus. Alkalinity was the most important factor in all models, followed by pH (11 out of 16 models) and nitrate (9 out of 16 models).

Table 6: Results from Generalized Additive Models (GAM) performed between the presence/absence of 16 Ponto Caspian species and 5 water chemistry variables. N: number of observations included in the model. % Dev. Expl.: proportion of data variability explained by the model. R2 (adj): goodness of fit of the model, adjusted for the number of predictors. Sig. Factors: predictors that significantly contributed to the model.

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N % Dev. Expl.

R2 (adj) Sig. Factors

Chaetogammarus ischnus 115 43.5 0.482 Alk+SO4

Chaetogammarus warpachowski

137 49.0 0.514 Alk+pH

Cheliorophium curvispinum 1049 49.7 0.544 Alk+NO3+pH+SO4

Cheliorophium robustum 61 27.4 0.296 AlkDikerogammarus bispinosus 49 50.8 0.560 Alk+pHDikerogammarus haemobaphes 394 33.8 0.390 Alk+pHDikerogammarus villosus 706 38.6 0.424 Alk+NO3+pH+SO4

Echinogammarus trichiatus 189 72.0 0.753 Alk+NO3+DOC+pH+SO4

Hemimysis anomala 379 36.3 0.406 Alk+NO3+pHJaera istri 147 39.1 0.423 Alk+NO3

Limnomysis benedeni 734 49.0 0.536 Alk+NO3+pHObesogammarus obesus 170 63.4 0.694 Alk+NO3+DOC++pHPontogammarus robustoides 335 68.8 0.743 Alk+NO3+DOC+pH+SO4

Neogobius melanostomus 154 57.4 0.652 Alk+NO3+SO4Neogobius gymnotrachelus 70 43.7 0.464 AlkProterorhinus marmoratus 208 44.6 0.485 Alk+DOC+pH+SO4

The response of species presence/absence to water chemistry factors was similar: the probability of presence increased with alkalinity, decreased with pH, showed a unimodal response to nitrate peaking at 10 mg/L approximately, and decreased with sulphate and DOC. Figure 7 shows the response of C. curvispinum’s presence/absence to water chemistry predictors as a representative example of the response showed by the 16 species. In this Figure, the Y-axis represents the logit of the response variable (presence/absence of Ponto Caspian species). The axis is centred on 0, which represents 50% probabilities of the species to be present. In this particular case, positive deviance from the 0-line will represent higher possibilities of presence of Ponto Caspian species, and vice versa. According to these graphs, the probability of presence is high at alkalinity> 120 mg/L, pH< 7.5, nitrate between 2 and 18 mg/L and sulphate< 7.6 mg/L.The decrease in the species probability of presence with pH is nevertheless not in accordance with our knowledge on the species, which do not seem to be limited by high pH. Just to put an example, D. villosus is abundant in Grafham reservoir, which can reach pH of 10. This contradiction can be explained by the non-inclusion of the native range of the species in the models. The pH in the native range of the species around the Black and Caspian is indeed high (>8), while pH is lower in the invaded European range used for the calibration of models, and probably lower than the places used as pseudo-absences, thereby artificially fitting a negative relationship.

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Figure7: Results from Generalized Additive Models (GAM) performed between the presence/absence of C. curvispinum in Europe, and water chemistry variables. Y-axis represents the partial residuals of the variable after removing the effect of all other predictor variables (i.e. the individual effect of the variable). Because a binomial family was used, Y-axis units are ‘logits’ centred on a 50% probability of presence (=0). The shaded area delimits error bounds (95% confidence interval). The red dashed red line and arrow highlights the 50% probability of presence threshold.

Results from GAM models were similar though not entirely congruent with response plots extracted from MaxEnt’s species distribution models (Fig. 4). Several procedural reasons could explain differences between both. First, the algorithm used for modelling the response of species to water chemistry is different (maximum entropy vs. generalized additive modelling), and therefore basic assumptions and treatment of variables is different, which would lead to slightly different results. More importantly, the selection of absence points to compare with presence points is fundamentally different. In the case of MaxEnt, a random selection of 10,000 background points is used as ‘pseudo-absences’. Because they are random, some pseudo-absence points will inevitably fall in unsuitable sites (like land patches, mountains, urban areas) and even on invaded sites themselves. In contrast, we performed an informed selection of pseudo-absences for GAM models, locating them in (as far as we know) un-invaded sites. Further, for each species we used a similar number of presence and absence points in each of the 16 species, rather than a fixed 10,000 number, to achieve a balanced model. Although it might still be possible that some of the points used as absence sites are already invaded or will be invaded in the future, this is in our opinion the best approximation we can make to investigate differences between invaded and un-invaded sites. We can therefore consider GAM to provide a more realistic prediction of the differences between invaded and un-invaded sites.

Alkalinity is according to GAM models the main water chemistry factors conditioning the presence of Ponto Caspian species in Europe. Alkalinity values over 120 mg/L correspond in Great Britain to most of England, the eastern part of Wales and a strip along the East coast of Scotland (Fig. 8). This area coincides with the high risk area identified in the climatic ‘Heat map’.

19

Figure 8: Water chemistry characteristics potentially limiting the occurrence of Ponto Caspian species. Water-bodies with alkalinity < 150 mg/L are unlikely to be invaded.

4 Discussion

The current distribution of PontoCaspian species in Europe shows clear geographic patterns with some species spreading towards the North-East (e.g. C. warpachowski, D. haemobaphesand N. melanostomus), and others towards the North-West (e.g. C. curvispinum, H. anomala and D. villosus). Such differences can be caused by the particular tolerance of each species to changing climatic and environmental conditions across Europe, their distinctive dispersal abilities, and the use of different corridors for spread. The 16 species investigated certainly show differences in their environmental tolerance and habitat preferences. For instance, amongst the two mysids investigated, H. anomala is adapted to brackish waters up to 19‰ salinity, while L. benedeni is limited to freshwaters < 6‰ (Kelleher et al. 1999). D. haemobaphes usually advances more upstream than C. ischnus, which stays downstream (Jażdżewski 1980). However, this is more likely to affect the distribution of species at a local scale (e.g. whether they are found in the main river channel, lagoons or the estuary), and not their continental-scale spread. Salinity tolerance can nevertheless affect the survival of species in ballast water and therefore their long-distance introduction. Dispersal strategies can be important, for instance by the middle of the 20th century, C. ischnus, D. haemobaphes, D. villosus and O. obesus reached the middle part of the Volga River spreading upstream more than 4,000 km from their native area (Mordukhai-Boltovskoi 1960, Dedyu 1980).

Although environmental preferences and dispersal abilities of species undoubtedly play a role, the large-scale geographic distribution of species is most likely related to the route they used for dispersal. According to Bij de Vaate et al. (2002), three main corridors are used by Ponto Caspian species for migration in Europe (Fig. 9): the Southern corridor (Black Sea-North Sea through the Danube-Main-Rhine waterways) used by D. haemobaphes, D. villosus, E. trichiatus, J. istri and L. benedeni; the Central corridor (Black Sea-Baltic Sea through Dnieper and Nemunas rivers)

20

successfully used first by C. curvispinum and then by many other Ponto Caspian crustaceans including E. ischnus and P. robustoides; and the Northern corridor (Don-Volga-Balthic Sea), the oldest, dating back to the 18th century, and the one used by D. polymorpha in its spread towards west Europe.

Figure 9.The migration corridors of Ponto Caspian species in Europe.Extracted from Bij de Vaate et al. (2002).

4.1 Climate suitability of Great Britain for Ponto-Caspian species

Species predicted not to be present in Great Britain included three gammarids (C. ischnus, C. warpachowski and P. robustoides) and two fishes (N. gymnotrachelu and P. marmoratus). These species are currently distributed towards the North-East of Europe (e.g. rivers Don, Dnieper, Volga, Curoonian and Vistula Lakes). It is worth highlighting P. marmoratus, the tubenose goby. Even if the suitable area for this species is restricted to the Thames estuary, considering the intense trade and transport activities in this area, we can expect the probabilities of the species being introduced in this particular spot to be high (i.e. high potential propagule pressure) despite its small extension. The high risk of gobies crossing the British channel from The Netherlands has been previously highlighted by a British horizon scanning performed in 2009 (Parrot et al. 2009).The authors warned that when the presence of the tubenose and racer gobies in the lower Rhine reaches a high density they will be more likely to be transported to other ports as hull foulants of ships. Whether the species would be able to spread outside of its climatically suitable area is difficult to say, but invasive species have shown before an extraordinary phenotypic plasticity, often adapting to new climates after a period of acclimatization.

In contrast, species whose suitability was high across large parts of Great Britain included three gammarids (C. curvispinum, D. bispinosusand D. villosus) and the two mysids (H. anomala and L. benedeni). These species are currently located along the Danube-Rhine corridor, they are widely present in The Netherlands and Belgium, and patchily also in France, which may explain their high

21

suitability in Great Britain. Two of these species, C. curvispinum and H. anomala, are actually already present within their respective high climatic risk areas in Great Britain, which reinforces the results of the models. The remaining seven species, six gammarids (C. robustum, D. haemobaphes, E. trichiatus, J. istri and O. obesus) and a fish (N. melanostomus), showed varying distributions across Great Britain, generally decreasing from North-East to South-West coasts.

The suitability of species to colonize Great Britain can be again related to the invasion corridor they have used to spread in Europe. Those species for which Great Britain showed a high climatic suitability are known to spread through the Central corridor (Danube, Main, Rhine rivers); while species not predicted to be present in Great Britain have used the Northern corridor (Dnieper, Don, Volga). The choice of corridor by Ponto Caspian species can be related to their capacity of dispersal through rivers and canals, to their environmental tolerance to the canal conditions, and overall to the canal management itself. Therefore, results from the models should be taken with caution, as we cannot assume fundamental differences in the climatic preferences of species on the grounds of using different corridors for spread.

Considering the similar climatic conditions of South-East England to those of the closest invaded areas in the continent, the location of numerous commercial ports of international relevance and availability of artificial canals for dispersal, we can consider SE England – and in particular the Anglian, Thames, Humber and Severn Valleys - as the areas under the highest risk of being invaded by Ponto Caspian species. The fact that all recent invaders have been located in this area for the first time (e.g. D. villosus in the River Great Ouse, H. anomala in the River Trent, C. curvispinum in the River Severn) reinforces this idea. Moreover, this area corresponds to the range successfully colonized by another Ponto Caspian invader, the zebra mussel.

4.2 Water chemistry suitability of Great Britain for Ponto-Caspian species

4.2.1 Species distribution models

Results from MaxEnt species distribution models incorporating water chemistry factors showed similar results to climate-only models, probably because altitude and minimum temperature were amongst the most important predictors in both cases. Species predicted not to be present in Great Britain were similar, though including in addition O. obesus. Climate suitability for this species was high in limited areas of the East of England, such as the Ouse Wash, Thames Valley and Norfolk coast. When water chemistry was incorporated in the model, the suitability of these areas for O. obesus decreased. On the other hand, the suitability for C. curvispinum, D. bispinosus and H. anomala was still high across large areas of Great Britain when water chemistry was accounted for. However, the suitable area for L. benedeni was significantly reduced. The suitability forD. villosus increased in this case towards the north and west.

Results from the model including water chemistry should be nevertheless taken with caution because of several data-related caveats. First, continuous water chemistry maps were generated by interpolating point data corresponding to single stations and annual means. Although this interpolation technique has been successfully used before to establish a geochemical baseline for Europe (Salminen et al. 2005), it has several drawbacks. First, data used for interpolation is punctual and does not reflect the natural seasonality and inter-annual variation in water chemistry. In the case of the climatic variables, data corresponds to mean values over a long period (1960-1990), and consider monthly and quarterly means. Second, the interpolation of data is obviously more meaningful for climatic variables that show natural smooth gradients, than for water chemistry that can show abrupt changes, not to mention the interpolation of values across land patches. Finally, we have already highlighted the lack of reliable data from Eastern European countries and Russia, which strongly limited the analyses.

For all these reasons, the Heat map based on climate-only variables (Fig. 1) is the most reliable representation of the multiple risk of invasion of Ponto Caspian species in Great Britain.

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4.2.2 Regression models

To further understand, and if possible identify, water chemistry limits to the establishment of Ponto Caspian species, generalized additive regression models (GAM) were performed for each species. In comparison with the previous MaxEnt distribution models, the main advantage of GAMs is the possibility to make an informed selection of absence points, which should improve predictability. These models are used to investigate the response of the species presence/absence to water chemistry, and not to make geographic predictions. Because water chemistry of presence and absence points was extracted from the interpolated maps, data limitations related to the interpolation of water chemistry information across Europe remain.

Alkalinity was the most important factor, included in all models and showing a positive correlation with the species presence. Certainly, alkalinity reflects the availability of CaCO3 in water and therefore affects the formation of a gammarids’ exoskeleton (Greenaway 1985). Salinity limits are often cited in studies of Ponto Caspian species. For instance, D. villosus can survive up to 20‰ (Bruijs et al. 2001), D. haemobaphes tolerates 8‰ (Ponomareva 1975), H. anomala 19‰ (Bacescu 1954), L. benedeni reaches highest abundance at < 5‰ (Wittmann 1995). Other species have been suggested to be tolerant to ‘high salinity’ although not particular thresholds were reported (e.g.C. ischnus), while C. warpachowski and C. curvispinum have been reported amongst the ‘least tolerant’ to salinity (Santagata et al. 2008). A wide salinity tolerance has been indeed suggested as one of the features explaining the successful spread of Ponto Caspian species. For instance Grabowski et al. (2009) argues that river tributaries, by showing a lower conductivity than the main river channel, are less frequently invaded thereby providing refuge for native species. Certainly, looking at the absence points used in this study (Appendix 3) we do note that invasive Ponto Caspian species are less frequent in tributaries than the main channel of large European rivers, which may explain the differences we found in water chemistry between invaded and un-invaded sites. Although we did not have salinity information at a European scale, alkalinity, salinity, hardness and calcium concentration are closely related in freshwaters. Therefore, we can assume that a positive relationship of Ponto Caspian species presence with alkalinity corresponds to a similar positive response to salinity, calcium and hardness. The probability of presence of all species was particularly high at alkalinity values > 120 mg/L, which according to the formulae developed by Davy-Bowker et al. (2008) for UK’s water-bodies, corresponds to approximately 500 µS/cm conductivity or 77 mg/L calcium. This does not mean that the species cannot survive below these particular water quality limits, but that the probability of presence is lower. Similarly, while the models suggest a decrease in the species’ probability of presence at pH>7.5, this implies a lower probability and not absolute survival limits.

At the Great Britain scale, alkalinity is in the optimum range of the species in SE England (Fig. 8), which coincides with the area highlighted by the climate Heat Map (Fig. 1).

4.3 Risk of invasion by species

Table 7 summarizes, for each species results from this study, the migration route (corridor), other relevant habitat factors cited in the literature and a summary of their reported impacts on ecosystems.

Four species are highlighted in this Table (shaded in dark red) as those showing the highest match between the conditions they inhabit in Europe and those of Great Britain. These species were considered to show a high risk of dispersal, establishment and potential to cause important ecological and economic impacts in a recent European risk assessment of aquatic species invasions (Panov et al 2009).

In the first place, C. curvispinum is predicted to be present across most England, and Eastern parts of Wales and Scotland (Appendix 4C). This species is one of the first reported Ponto Caspian invaders

23

in Europe and is now widely distribute, probably using various canals of the Central corridor and ship transport to extend its area of distribution to the Baltic and North Seas (Jażdżewski 1980). It was also intentionally introduced in several Asiatic and European reservoirs of the Soviet Union and Lithuania (Ioffe 1968). Its extraordinary growth potential is featured in the Lower Rhine, where its abundance increased from 2 to 200,000 individuals per m2 in a 3 year period, reaching densities as high as 750,000 individuals per m2 (Van Den Brink et al. 1993). Along with D. haemobaphes, C. curvispinum has been reported to be transported at a rate of >3000 individuals per second in the Volga river (Lyakhov 1958), evidencing a high dispersal ability. In terms of habitat, C. curvispinum prefers shallow brackish waters and frequents solid substrates and richly organic habitats (Kohn and Waterstraat 1990); it is more common upstream in rivers, its abundance increasing with water velocity and depth (Van Den Brink et al. 1993); it has been also found in ecosystems disturbed by anthropogenic pollution (Van Den Brink et al. 1993); and it is often associated with clumps of zebra mussels that offer a good solid base for building the silt tubes it inhabits(Jazdzewski et al. 2002, Devin et al. 2003, Berezina 2007). By creating these silt tubes with suspended particles it removes from suspension,C. curvispinum changes the structure of the substrate and increases water clarity, with important consequences for the rest of the benthic fauna (Van der Velde et al. 2000, bij de Vaate et al. 2002). Along with D. haemobaphes, J. istri and D. villosus, C. curvispinum is an intermediate host to eel parasites (Nesemann and Wittman 1995). C. curvispinum has been reported to outcompete other native species including filter-feeding caddis-flies (Hydropsyche sp.)(Ricciardi and Rasmussen 1998),the isopod Asellus aquaticus (Kinzelbach 1997), the invasive Gammarus tigrinus (Van der Brink et al. 1993) and even zebra mussels (Van der Velde et al. 2000). Considering the high climatic suitability of Great Britain to this species, its reproductive and dispersal abilities, association with zebra mussels, and potential impact as habitat engineer, C. curvispinum is possibly one of the most worrisome species investigated in this study.

SE England showed particularly high suitability scores for two Dikerogammarus species (D. villosus and D. bispinosus). D. villosusis a very successful invader across Europe, while there is not much information on D. bispinosus because it has been often considered a sub-species of D. villosus (Müller et al. 2002). The two species have many similarities and often displace each other. For instance, the larger D. villosus has displaced (through competition and direct predation) other Dikerogammarus species at most of its locations in the upper Danube and Rhine rivers (Müller et al. 2002) and is suspected to have displaced D. bispinosus in the German Danube (Kinzler et al. 2009). Their preferred habitat includes rocky shores and boulders and deep, well-oxygenated waters (Boets et al. 2010). D. villosus can tolerate up to 20‰, its competitive advantage being reduced under low salinity. However, apparently D. bispinosus advances more upstream allowing certain co-existence. Dikerogammarus spp. have been reported to displace native gammarids such as Gammarus pulex, or G. roeseli through direct predation or competition for space and resources (Dick and Platvoet 2000, MacNeil and Platvoet 2005). They can dramatically reduce benthic macroinvertebrate diversity and can even predate on fish eggs (Casellato et al. 2007), although it also constitutes an important food source for fishes.

The suitability of Great Britain for the two mysids investigated was also particularly high. These two species show differences in their habitat use.H. anomala prefers brackish waters 0 to 30 m deep and is able to tolerate salinities as high as 19‰ (Komarova 1991, Kelleher et al. 1999). Because it avoids sunlight, H. anomala aggregates in crevices, rocky caves, under artificial surfaces, and under dense macrophyte stands. In England, Stubbington et al. (2008) noted H. anomala is abundant in lentic waters with abundant shelter, though lotic unsheltered waters are not suitable for establishment, they can still allow dispersal. The authors predicted an extension of the species’ spread in England through the Midland network of canals, which would allow it to occupy its suitable climatic and water chemistry range in the Humber, Thames, Severn and Anglian river basin districts. Similar to other Ponto Caspian species, H. anomala is extremely prolific, reaching mean densities of six individuals per litre in Dutch reservoirs. This has had dramatic effects on the zooplankton and phytoplankton communities in The Netherlands, as H. anomala is an aggressive omnivorous feeder (Ketelaars et al. 1999).In

24

contrast L. benedeni is adapted to low salinity, showing highest density at 0-5‰ and high pH > 8.4 (Semenchenko et al. 2009). It prefers shallower waters, 0-6m, low water current < 0.5 m/s, and uses macrophyte stands for breeding (Kelleher et al. 1999). In contrast to H. anomala, L. benedeni feeds on smaller sized particles including phytoplankton, epiphyton, detritus, and also zebra mussels biodepositions, therefore its potential ecological impact is expected to be much lower than that of other mysids (Gergs et al. 2008).

Table7. Summary of species pathways of spread, climate and water chemistry matching according to distribution models and other factors related in the literature (zebra mussel presence, salinity, water current, substrate). The corridor refers to the main pathways of spread of Ponto Caspian species defined by Bij de Vaate (2002). When two corridors are used, they are in order of importance.

Corridor Matching climate

Water chemistry factors

Other Habitat Factors Potential impact

C. ischnus Central NO Alk+ SO4 High salinity, low current, downstream locations, zebra mussel, outcompeted by other Ponto Caspian species

Replaces G. pulex and G. varsoviensis

C. warpachowski

Central NO Alk+ pH High salinity, zebra mussel

C. curvispinum Central

Southern

England Alk+ NO3+ pH+ SO4

Shallow brackish waters, solid substrate, high organic content, high water current, deep waters, upstream locations, zebra mussel

Host to eel parasites, habitat modification, displacement of native (Hydropsyche sp., Asellus aquaticus) and invasive (D. polymorpha, G. tigrinus), food web changes

C. robustum Southern

England Alk

D. bispinosus Southern

England Alk+ pH Upstream locations Outcompeted G. roeselli

D. haemobaphes

Central

Southern

Anglian district

Alk+ pH Lotic waters, deep, upstream locations, macrophytes, solid substrate, salinity up to 8‰, zebra mussel

Host to eel parasites

D. villosus Southern

SE England

Alk+ NO3+ pH+ SO4

Deep water, stony substrate, high salinity

Host to eel parasites Displace other native fauna reducing biodiversity

E. trichiatus Southern

SE England

Alk+ NO3+ DOC+ pH+ SO4

H. anomala Southern

England, E-Wales, E-Scotland

Alk+ NO3+ pH

Crevices, dense macrophyte stands, under artificial surfaces, deep waters, high salinity (up to 19‰), zebra mussel

Predation and displacement of zooplankton (e.g. Anomopoda, Ostracoda, Rotifera ) and phytoplankton

25

J. istri Southern

SE England

Alk+ NO3 Pebbles, brackish waters, high flow, littoral zones

Host to eel parasites

L. benedeni Southern

Great Britain

Alk+ NO3+ pH

Low salinity (<5‰), shallow waters, low water current, high pH, macrophyte stands, zebra mussel

Predation of zooplankton and phytoplankton

O. obesus Southern

Central

Thames Valley and Ouse wash

Alk+ NO3+ DOC+ pH

P. robustoides Central NO Alk+ NO3+ DOC+ pH+ SO4

Donwstream locations, Na > 10-15 mg/L, tolerant to low oxygen, zebra mussel

N. melanostomus

Southern

Central

Thames Valley, Ouse Wash

Alk+ NO3+ SO4

zebra mussel Displacement of other native fish

N. gymnotrachelus

Central NO Alk zebra mussel

P. marmoratus Southern

Central

Thames Valley

Alk+ DOC+ pH+ SO4

zebra mussel

The zebra mussel may act as a factor modifying the invaded range habitat conditions making them more suitable for the establishment of other Ponto Caspian species. Zebra mussels provide habitat complexity, food sources and refuge to Ponto Caspian gammarids, although its filtering activities can increase light penetration and therefore fish predation. Many of the species investigated here have been shown to prefer zebra mussel beds as habitat including P. robustoides, C. warpachowski, L. benedeni, C. curvispinum (Zettler and Daunys 2007), C. ischnus (Van Overdijk et al. 2003, Palmer and Ricciardi 2004), D. haemobaphes(Kobak et al. 2009), D. villosus (Madgwick & Aldridge, 2011), H. anomala and L. benedeni (Gergs et al. 2008). Gobiids have been also reported to favour zebra mussels as prey (Gaygusuz et al. 2007). The zebra mussel is currently distributed in much of England, and localised parts of Wales and the south of Scotland (Fig. 10); and it is experiencing an increase in abundance and spread in relation to increasing water quality and waterway connectivity (Aldridge et al. 2004).

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Figure 10.Presence of zebra mussels (D. polymorpha) in Great Britain. Data extracted from the National Biodiversity Network’s Gateway (NBN, http//:data.nbn.org.uk).

4.5 Conclusions

In this study, we have used multiple modelling techniques to assess the probability of invasion of 16 Ponto Caspian species into Great Britain. Climate suitability maps differed depending on the eastern/western distribution of species in Europe, which has been related to their migration corridor (southern/central). The climatic Heat Map combining all 16 distribution maps together suggests a higher probability of multiple invasions in South and East England, particularly the Thames, Humber, Anglian and Severn river basin districts. In these districts the probability of propagule introduction is also high because of the location of several ports of international relevance, man-made canals and reservoirs intensively used for recreation, fishing, boating and angling, and the wide spread of another Ponto Caspian invader that may facilitate invasions, the zebra mussel. Three of the 16 species have been already introduced into these districts, where efforts to control and prevent invasive Ponto Caspian species should therefore focus in the future. Although freshwater species are obviously more closely related to water chemistry than climate, multiple data limitations of climate+water chemistry distribution models prevents their use in its current form, and suggest climate-only models are more suitable to predict the potential range of species at a European scale.

Regression models identified alkalinity as the most important factor explaining the distribution of Ponto Caspian species, which showed a positive correlation with alkalinity (overall at > 120 mg/L) and pH. Alkalinity is directly related to salinity and calcium concentration. The former has been reported before to provide a competitive advantage to Ponto Caspian species over native species, facilitating their successful establishment and spread. Calcium and pH are also important in the formation of a shrimp’s moult, affecting the hardening of the exoskeleton. Although not free of limitations, regression models using the species presence in Europe and pseudo-absence points manually generated in un-invaded rivers provided the best approximation to disentangle the response of invasive species to water chemistry. Water chemistry limits discussed in this report are nevertheless not absolute survival thresholds, but rather reflect the most favourable or unfavourable conditions for species establishment.

Amongst species, C. curvispinum, two Dikerogammarus spp. (D. bispinosus and D. villosus) and the two mysids (H. anomala and L. benedeni) showed the highest probabilities of invasion into Great Britain. The European climatic range of these species shows a high match with Great Britain; they are affected by alkalinity, pH and nitrate and favoured by the presence of zebra mussels, abundant in central and south England. The potential impacts of these species affect several structural and functional aspects of aquatic ecosystems, including: habitat changes from hard substrate to silt bottom affecting the benthic community (C. curvispinum); changes in water clarity through filtration (C.

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curvispinum); predation on zooplankton and phytoplankton changing their abundance, richness and composition (mysids, and especially H. anomala); displacement of native and invasive species through direct predation (D. villosus) or competition for space and resources (C. curvispinum, Dikerogammarus spp.); food web changes (all species); impoverished diversity and therefore ecological status of water-bodies (all species); and intermediate host to fish parasites (C. curvispinum and Dikerogammarus spp.). Because the introduction and long-distance transport of these species is mostly human-mediated, vector management and outreach programmes to prevent and control the arrival and/or spread of these five species is fundamental. The Heat and alkalinity maps provided in this study provide means for a scientifically informed prioritization of species and river basins for the management of existing and future invasions of Ponto Caspian species.

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6 Appendices

Appendix 1.Literature used to complete the distribution of 16 Ponto Caspian species in Europe.

Alexandrov, B., A. Boltachev, T. Kharchenko, A. Lyashenko, M. Son, P. Tsarenko, V. Zhukinsky, 2007 Trends of aquatic alien species invasions in Ukraine - Aquatic Invasions 8: 215-242

Arbačiauskas K., G. Višinskienė, S. Smilgevičienė, V. Rakauskas, 2011 Non-indigenous macroinvertebrate species in Lithuanian fresh waters, Part 1: Distributions, dispersal and future- Knowledge and Management of Aquatic Ecosystems 402: 12

Arbačiauskas, K., V. Rakauskas, T. Virbickas, 2010 Initial and long-term consequences of attempts to improve fish-food resources in Lithuanian waters by introducing alien peracaridan species: a retrospective overview – Journal of Applied Ichthyology 26: 28-37

Arbačiauskas,K., 2008 Amphipods of the Nemunas River and the Curonian Lagoon, the Baltic Sea Basin: Where and which Native Freshwater Amphipods Persist? - Acta Zoologica Lituanica 18: 10-16

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Appendix 2.1.Occurrence points used for Ponto-Caspian gammarids.

Appendix 2.2.Occurrence points used for Ponto-Caspian mysids and fishes.

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Appendix 3.Presence and absence points used for modeling the correlation of Ponto Caspian species with water chemistry.

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Appendix 4. Results from species distribution models performed with MaxEnt. Models performed with climatic variables only.

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Appendix 5. Results from species distribution models performed with MaxEnt. Models performed with climatic, altitude and water chemistry variables.

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