Predatory insects as bioindicators of heavy metal pollution

Environmental Pollution 145 (2007) 339e347 www.elsevier.com/locate/envpol

Predatory insects as bioindicators of heavy metal pollution Matti Nummelin a,*, Martin Lodenius a, Esa Tulisalo a, Heikki Hirvonen a, Timo Alanko b a

Department of Biological and Environmental Sciences, P.O. Box 65, University of Helsinki, FIN-00014, Finland b Statistics Finland, FIN-00022, Finland Received 16 August 2005; received in revised form 23 February 2006; accepted 3 March 2006

Waterstriders, dragon fly larvae, antlion larvae, and ants can be used as heavy metal indicators. Abstract Heavy metal concentrations of different predatory insects were studied near by a steel factory and from control sites. Waterstriders (Gerridae), dragon fly larvae (Odonata), antlion larvae (Myrmeleontidae) and ants (Formicidae) were analyzed by AAS. In most cases the metal concentrations were higher near the factory, but e.g. waterstriders had higher cadmium concentrations in control area. Discriminant analysis clearly reveals that all these insect groups can be used as heavy metal indicators. However, the commonly used ants were the least effective in indicating the differences between the factory and control sites. Waterstriders are good in detecting differences in iron and manganese, but seem to be poor in accumulating nickel and lead. Antlions are efficient in detecting differences in iron. Antlions and ants are effective in accumulating manganese; as well antlions are efficient in accumulating cadmium. Waterstriders are poor in accumulating lead, but antlions and ants are effective. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Formicidae; Gerridae; Myrmeleontidae; Odonata; Steel factory; Tva¨rminne

1. Introduction Several types of organisms have been used as bioindicators of air pollution by heavy metals (e.g. Steinnes, 1989; Migula and Glowacka, 1996). In this study we test the suitability of several relatively sedentary predatory insects as heavy metal bioindicators around a well studied iron and steel factory in Southern Finland (e.g. Monni and Ma¨kinen, 1995). High concentrations of cadmium have previously been reported from Finland in Formicidae (4e7 mg/g) (Yla¨-Mononen et al., 1989) and from spiders (2e8 mg/g) (Nuorteva et al., 1992). Many aquatic invertebrates accumulate cadmium and other metals and some are relatively insensitive to these metals (Jardine et al., 2005; Nummelin et al., 1998; Spehar et al., 1978). * Corresponding author. Present address: Department for Development Policy, Ministry for Foreign Affairs, P.O. Box 176, FIN-00161 Helsinki, Finland. Tel.: þ358 9 1605 6108. E-mail address: [email protected] (M. Nummelin). 0269-7491/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.envpol.2006.03.002

However, insects are fairly little used as bioindicators for metal pollution (see e.g. Kozlov and Whitworth, 2002; Rao and Saxena, 1981; Spehar et al., 1978). Individuals of many species are not easy to collect in quantities large enough or there is a short seasonal supply. Often their origin is unknown due to their flying ability. In all cases also a taxonomic expert is needed to determine the species. The aim of this study is to screen several common predatory, fairly sedentary, both terrestrial and aquatic insect species in southern Finland from a well studied area polluted by metals and from a control area in order to assess their suitability for heavy metal bioindication. Waterstriders have earlier been used as heavy metal indicators (Jardine et al., 2005; Nummelin et al., 1998). Previous studies have also shown that ocean dwelling sea-skaters (Halobates spp.) are suitable bioindicators for cadmium distribution in oceanic surface waters (Cheng et al., 1984; Schulz-Baldes, 1989). Sea-skaters concentrate cadmium in their tissues (Schulz-Baldes and Cheng, 1979) and high concentrations have been measured in sea-skaters from tropical

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M. Nummelin et al. / Environmental Pollution 145 (2007) 339e347

oceans (Bull et al., 1977; Cheng et al., 1976). Jardine et al. (2005) have recently shown that there is a strong correlation of mercury concentrations in waterstriders and trouts at the same location in a stream. Cadmium, zinc and copper concentrations of antlions in the near vicinity of our study area were studied earlier by Nuorteva (1995). The heavy metals in ants were studied to some extent (Maavara et al., 1994; Nuorteva et al., 1978; Rabitsch, 1997; Stary and Kubiznakova, 1987), and they even were used as a standard method for heavy metal monitoring (Ukonmaanaho et al., 1998). The heavy metal concentrations of dragonfly larvae have been studied earlier by Brown and Pascoe (1988), Currie et al. (1997), Mackie (1989); and Meyer et al. (1986).

heavy metals 1.5 t (only As, Cd, Pb, Zn are included). In 1995 dust, SO2 and NOx emissions decreased due technical improvements in the factory. High concentrations of heavy metals have been measured close to the Koverhar iron and steel factory in small mammals (Pankakoski et al., 1994), pine needles (Hyle, 1979), mosses (Rinne and Ma¨kinen, 1988), and from epiphytic lichens (Helminen et al., 1986; Holmberg, 1989, 1992; Holmberg and Pihlstro¨m, 1992; Linden, 1977). As an unpolluted reference insects were collected from an area located at least three kilometres from the factory towards the prevailing winds (Appendix 1). Most of the waterstrider samples were collected in 1995 (see Nummelin et al., 1998), dragonfly larvae in 1996 and antlions and ants in 1997, also some waterstriders were collected in 1997. All analysed samples consisted of several pooled individuals.

2. Materials and methods

To study which heavy metals best separated/discriminated between control and near factory observations, stepwise discriminant analysis (DA) was used. Significance levels of 0.05 for entry and 0.10 for removal of variables in the stepwise variable selection and the Mahalanobis distance measure were used. The ManneWhitney U-test was used for pairwise comparisons.

2.1. Species studied Waterstriders are predators/scavengers (Jamieson and Scudder, 1977) and thus prone to bioaccumulation. They are often easy to collect in large quantities and species determination is fairly easy on species level (e.g. Andersen, 1996; Vepsa¨la¨inen and Krajewski, 1986). Even the winged individuals do not disperse long distances (Fairbairn, 1986). The species studied in this study: Gerris argentatus Schumm. (body length 6.5e8 mm, sizes according to Linnavuori, 1966) is the smallest Finnish waterstrider species, G. odontogaster (Zett.) (7e8.5 mm) and G. lateralis Schumm. (9e11 mm) are medium sized Finnish waterstriders, and G. thoracicus Schumm. (10e11.5 mm) is somewhat bigger than the other species. Waterstriders (Gerridae) have one and a partial second generation during one summer in southern Finland. Overwintered adults are common during May and June. Newborn adults are common during August (see e.g. Vepsa¨la¨inen, 1974). Vepsa¨la¨inen (1973) has given closer descriptions of the habitat preferences of studied species. Most of the waterstrider samples in this study are the same as in Nummelin et al. (1998). Altogether 14 samples were taken from factory site and 18 samples from control sites (Appendix 1). Antlion larvae are predators occurring in sandy areas and moving very little (Gotelli, 1993; Heinrich and Heinrich, 1984). Antlion species were not determined to species, but both Myrmeleon formicarius L. and M. bore Tjed. are known to occur in the study area (Meinander, 1962). Altogether three antlion samples were taken both from factory site and from control sites (Appendix 1). Antlion sample preparation was tedious due sand grains attached in their hairs. We used abundant distilled water in washing them. Individuals in other studied species were carefully examined that they did not have any extra material attached on them. The studied ant species were Formica lugubris Zett., Lasius niger (L.), Formica rufa-group L. All individuals studied were outside workers. More information on ecology of these ants can be found, e.g. in Collingwood (1979). Altogether five samples were taken from factory site and three samples from control sites (Appendix 1). The studied species of dragonfly larvae were Aeshna juncea L., A. cf. grandis L., Cordulia aenea L., Lestes sponsa Hansemann, Leucorrhinia cf. rubicunda L., L. cf. caudalis Charpentier, and Sympetrum cf. danae Sulzer. More information on the ecology of these dragonfly larvae can be found e.g. in Askew (1988). Altogether eight samples were taken from factory site and four samples from control sites (Appendix 1).

2.2. Study area and sampling The studied polluted sites were situated close to the iron and steel factory near the sea shore in Koverhar, Hanko Peninsula (59  500 N, 23  130 E, Appendix 1) (see e.g. Fritze, 1991; Helio¨vaara et al., 1982; Monni and Ma¨kinen, 1995; Pankakoski et al., 1994). The emissions of the Koverhar iron and steel factory in 1994 were according to the factory’s official report (Fundia Wire Oy Ab, 1995): SO2 1175 t, NOx 554 t, dust 1193 t (large part of this Fe), and

2.3. Statistical analyses

2.4. Chemical analysis All animals were killed in deep freezer and dried in þ60  C temperature for 10 h and then stored at room temperature in plastic tubes. Before the chemical analysis samples were dried overnight at 105  C. The animal samples were weighed 0.5 g or less in glass test tubes and heated in 5 ml of concentrated HNO3 (BDH, Aristar) for 2 h at 50  C, and after that for 16e18 h at 110  C. Five ml of H2O2 (Merck, p.a.) were added, and the samples were heated for an additional 6 h. The samples were filtered and diluted with distilled water to 25 ml. Finally, the concentrations of Al, Cu, Fe, Mn, Zn were analysed by flame atomic absorption spectrophotometer (Varian SpectrAA400) and of Cd, Ni, Pb by graphite furnace AAS (Varian SpectrAA 400 equipped with GTA-96). All the results are reported as concentrations in mg/g of the dry weight.

3. Results The average metal concentrations found in the studied insect groups near by the factory vs. the control area are presented in Table 1 and Fig. 1aeg. Iron concentrations were significantly higher at the factory site than at the control sites in pooled samples of all studied insects (ManneWhitney U-test: Z ¼ 4.41, p < 0.001). On the other hand cadmium concentrations were significantly higher at control sites in pooled samples (Z ¼  3.73, p < 0.001). Other metals did not differ (Mn Z ¼ 1.14, p ¼ 0.26, Zn Z ¼ 0.44, P ¼ 0.65, Cu Z ¼  0.59, p ¼ 0.59). The waterstriders at the factory site had significantly higher iron and manganese concentrations than at the control site, whereas cadmium was significantly higher at the control site (Table 1). In antlions and ants the metal concentrations did not differ significantly between the factory and the control sites. In dragonfly larvae iron and cadmium were significantly higher at the factory site than at the control sites. Looking informally (i.e. regardless of statistical significance) at our empirical results presented in Appendix 1, we can make the following observations: For iron, antlions had higher concentrations both at factory and control than other insect groups at any site.

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Table 1 Heavy metal concentration mean (x) and standard deviation (s.d.) of studied groups at near factory and at control sites Fe

Mn

Zn

Cu

Ni

Cd

Pb

844 514 331 175 3.44 0.001

49 19 35 28 2.87 <0.0031

313 72 277 74 1.465 0.1455

44 9 42 5 0.31129 0.77977

N.D. N.D. N.D. N.D. e e

1.6 0.5 6.2 3.1 4.620 0.001

N.D. N.D. N.D. N.D. e e

Antlions Factory x s.d. Control x s.d. Z p

4400 608 1267 473 1.9675 0.10008

297 81 230 104 10.1819 0.40038

450 27 453 244 0.6644 0.70066

43 10 49 12 0.2201 1.0099

2.8 1.5 1.3 0.2 0.6644 0.70066

3.6 1.0 8.6 5.8 10.0987 0.40038

4.3 1.3 3.9 1.3 0.8301 10.00099

Ants Factory x s.d. Control x s.d. Z p

730 367 266 176 1.6441 0.143

252 155 193 104 0.4530 0.7867

462 253 300 62 0.7556 0.5715

19 6 16 2 0.3015 0.78680

0.5 0.2 0.8 0.4 0.6089 0.57137

4.7 3.5 7.4 3.1 10.0489 0.3937

1.6 0.6 2.0 1.0 0.4530 0.7866

Dragonfly larvae Factory x s.d. Control x s.d. Z p

912 650 116 89 2.71 0.004

6.5 2.1 2.8 0.4 2.55 0.008

97 18 95 27 0.17 0.933

34 11 37 32 0.68 0.570

3.0 1.9 1.0 0.8 2.04 0.048

Waterstriders Factory x s.d. Control x s.d. Z p

0.86 0.29 0.12 0.10 2.717 0.004

1.8 1.0 1.0 1.3 1.54 0.154

ManneWhitney U-test results for the difference between sites (Z ) with exact unadjusted significance levels ( p). Bonferroni adjusted significance levels for the 26 tests would require p < 0.002 to achieve a nominal 5% significance. N.D. ¼ not detected.

For manganese, antlions and ants had higher concentrations than other insect groups, but did not differ from each other. Dragonfly larvae had clearly the lowest values in manganese and zinc at any site. Waterstriders had lower zinc concentrations than antlions at both site. For copper, ants had lower concentrations than other insect groups both at the factory and at the control sites. For nickel, waterstriders had low concentrations, often below detection limit. Also ants had lower nickel concentrations than antlions and dragonfly larvae. For cadmium, dragonfly larvae had lower concentrations than other insect groups. For lead, waterstriders had low values, often below the detection limit. Antlions had higher lead concentrations than ants and dragonfly larvae.

3.1. Prediction of heavy metal pollution by discriminant analysis It thus appears that there are differences in concentrations of metals in the four groups of insects (waterstriders, antlions, ants, dragonfly larvae), both in the response to the sites and between the groups. To analyse site and group differences on the

basis of the metal concentrations, stepwise linear discriminant function analysis was used. 3.2. The pooled sample Due to the differences between insect groups, a discriminant function based on the pooled sample is probably not very representative. Yet, such an estimated discriminant function, with statistically significant coefficients for Zn, Cu, Ni and Cd only, manages to classify correctly 87.9% of the original observations and 84.5% of internally cross-validated observations to either control or factory sites (Table 2). The number of observations is too low for a proper external cross-validation. It is of further interest to estimate the discriminant functions for the insect groups separately. The results are given in Table 3a,b. According to our analysis very different heavy metal combinations best discriminate between factory and control sites. Whereas dragonfly larvae and antlions classify the sites perfectly, waterstriders did well, but ants were poorest in classifying the sites correctly. 3.3. Classifying insects into groups and sites In addition, heavy metal concentrations can be used to classify insects into groups and, to some extent, into site-group

M. Nummelin et al. / Environmental Pollution 145 (2007) 339e347

342

(a)

400,0

(b)

Site

6000

control

Site control

5000

near factory

near factory

300,0

Fe

Mn

4000 200,0

3000 2000

15

100,0 1000 0

0,0 waterstriders antlions

waterstriders antlions

ants dragonfly larvae

Group

(c)

800

ants dragonfly larvae

Group

(d)

Site control

Site

80

control

near factory

near factory

600 60 16

Cu

Zn

15

400

40 24

200 20 0 waterstriders antlions

ants dragonfly larvae

waterstriders antlions

Group

(e)

7,0 6,0

ants

dragonfly larvae

Group

(f)

15,00

Site

Site

control

control

12,00

near factory

near factory

5,0 9,00

Ni

Cd

4,0 3,0

6,00

2,0 1,0

3,00

30 10

0,00

0,0 waterstriders antlions

ants dragonfly larvae

Group

(g)

6,0

Site near factory

Pb

4,0 3,0 2,0

32

1,0

23

0,0 waterstriders antlions

Group

ants dragonfly larvae

Group

control

5,0

waterstriders antlions

ants dragonfly larvae

M. Nummelin et al. / Environmental Pollution 145 (2007) 339e347 Table 2 Standardized canonical discriminant function coefficients function 1 of predatory insect heavy metal concentrations

Zn Cu Ni Cd Const.

Standardized Coefficients

Unstandardized Coefficients

0.986 0.397 0.489 1.221

0.006 0.029 0.390 0.398 0.479

combinations. Again using linear discriminant analysis, we show that the insect groups are fairly well discriminated and correctly classified. We proceed first by showing graphically how well the first two canonical discriminant functions separate the insect groups for control and near factory observations separately (Figs. 2 and 3). It is seen that discriminant functions classify the insects into groups almost perfectly (Numerically, 96.4% and 82.1% for the control site, 100% and 100% for the factory site). However, when discriminate functions are based on simultaneous grouping into sites and insect groups (eight combination groups), classification turns out to be less reliable. Based on the graph of the first two canonical functions (out of 7) in Fig. 4, only dragonfly larvae and antlions separate control and factory sites well in this exercise. In fact, using all the information (the four first canonical functions cover 99% of the total variation), 87.4% of the original observations and 72.4% of the internally cross-validated observation could be correctly classified into one of the eight groups. Different insect groups accumulated heavy metals differently and in discrimination analysis both in factory and control sites classify studied insect groups very well. 4. Discussion The heavy metal concentrations in waterstrider samples taken in 1995 and 1997 at the same site are very close to each other indicating that there was no general environmental change in the study area during the study years. Also the cadmium, zinc and copper concentrations of ants and antlions overlapped extensively the values reported by Nuorteva (1995) from a close by unpolluted area. Discriminant analysis clearly reveals that all studied insect groups can be used as indicators of heavy metal pollution. Antlions and dragonfly larvae discriminated the factory and control sites perfectly and waterstriders did fairly well. Ants were poorest in discriminating between the factory and control sites. The variance within studied insect group was smaller than

343

between the groups, thus, these groups accumulate differently heavy metals from their environment. This paper gives some hints about the efficiency of the studied predatory insect groups in accumulating different heavy metals. However, this study was not designed to target this question and our results should be taken as preliminary in this aspect. According to our results it seems waterstriders are good in detecting differences in iron and manganese. Waterstriders are more efficient in accumulating iron and manganese and cadmium than dragonfly larvae. On the other hand waterstriders seem to be poor in accumulating nickel and lead. However, the mechanism is unknown and their success in avoiding uptake or having efficient detoxification machinery need further studies. According to our findings antlions seem to be efficient in detecting differences in iron. They also accumulated higher concentrations of iron both in factory and control site than other studied insects. It seems that antlions are alongside with ants effective in accumulating manganese; as well antlions seem to be efficient in accumulating cadmium than waterstrider in factory site, although waterstriders are known to be efficient in accumulating cadmium (Cheng et al., 1976, 1984; Nummelin et al., 1998). Waterstriders are poor in accumulating lead, but antlions and ant seem to effective. Although antlions seem to be better than ants (major prey of antlions) in detecting the differences in heavy metal contents, antlion sample preparation was tedious. In ants discriminant analysis revealed differences in iron, but the predictive power was low. This means that ants are not very good heavy metal indicators. However, according to our results ants seem to be as efficient as antlions in accumulating manganese. On the other hand they seem to be inefficient in accumulating copper. In our study ants were also less effective in accumulating nickel than antlions and dragonfly larvae. It is also known that the heavy metal concentrations of workers of same species of ants vary according to the their task (outside/inside workers, entering/departing the nest) (Maavara et al., 1994; Nuorteva, 1995). Thus, the use of ants as a standard method for heavy metal monitoring should be taken cautiously. According to this study dragonfly larvae seem to be good in detecting differences in iron, manganese and cadmium. They also accumulated higher concentrations of zinc than other insects in all sites. It seems that dragonfly larvae are inefficient in accumulating cadmium or efficient in getting rid of it. This study did not detect any decline in the concentrations of copper and lead with increasing distance from the factory. This type of decline has been detected in mosses in the same area (Rinne and Ma¨kinen, 1988). The high cadmium

Fig. 1. aeg. Box plot of metal concentrations (mg/g) of four studied insect groups near steel factory and control sites. The box plot presentation illustrates the distribution of the observed values in each category. A box consists of upper and lower hinges and a centre line corresponding to the 25th percentile (1. quartile), the 75th percentile (3rd quartile) and the median, respectively. The whiskers outside the box present outliers and are drawn above and below the hinges with length 1.5 times the interquartile range (or to the maximum/minimum value, whichever comes first). 1a e manganese, 1b e iron, 1c e zinc, 1d e copper, 1e e nickel, 1f e cadmium, 1g e lead. Numbers in outliers refer to sample number in Appendix 1.

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Table 3 Discriminant analysis of studied insect groups; (a) standardized and unstandardized canonical discriminant function coefficients (included), constant and the number of observations (N) (note: only Fe included in antlions) and (b) percent correctly classified of original grouped cases and of cross-validated cases Waterstriders

(a) Fe Cu Cd Pb Mn Cd Const. N

Antlions

Dragonfly larvae

Unstandardized

Standardized

Unstandardized

Standardized

Unstandardized

0.874 0.646 0.835 0.558

0.002 0.092 0.356 1.772

1.000

0.002

1.000

0.003

4.931 32

32

5.202 6

Waterstriders

(b) %

Ants

Standardized

6

1.757 8

8

Antlions

Standardized

Unstandardized

1.160 1.248

0.666 5.021 6.558 12

12

Ants

Dragonfly larvae

Correctly classified

Correctly classified

Correctly classified

Correctly classified

Original

Cross-validated

Original

Cross-validated

Original

Cross-validated

Original

Cross-validated

96.9

93.8

100.0

100.0

75.0

62.5

100.0

100.0

value seem to persist over the years in the waterstriders collected in the control site. 5. Conclusions We have demonstrated that waterstriders, dragon fly larvae, antlion larvae, and ants can be used as heavy metal

indicators. However, their power to accumulate heavy metals differ. Thus, their ability to discriminate different heavy metal pollutants differ and further studies are needed for detecting differences in efficiency of different insect groups to accumulate different heavy metals. According to our results ants are the weakest group to detect differences in heavy metal pollution.

Canonical Discriminant Functions

Canonical Discriminant Functions

Site: control

Site: near factory

3

Group waterstriders

4

antlions

2

ants antlions

dragonfly larvae dragonfly larvae Group Centroid

2

Function 2

Function 2

1 waterstriders

0

antlions

0 waterstriders

-1

Group ants

waterstriders ants

-2

antlions

-2

ants dragonfly larvae

dragonfly larvae Group Centroid

-3 -4

-2

0

2

4

6

8

-4 10

Function 1 Fig. 2. Canonical discriminant function plot of the four studied insect groups at the control site.

-5

0

5

10

15

Function 1 Fig. 3. Canonical discriminant function plot of the four studied insect groups at the near factory site.

M. Nummelin et al. / Environmental Pollution 145 (2007) 339e347

Tva¨rminne tra¨sket 2 km SE from the factory. Date refers to June, July and August in the years 1995e1997. N.D. ¼ not detected.

Canonical Discriminant Functions site_group

6

4 antlion_control ant_factory ant_control

2

waterstrider_control antlion_control ant_control dragonfly_control waterstrider_factory antlion_factory ant_factory dragonfly_factory

Function 2

Group Centroid waterstrider_control

0

waterstrider_factory antlion_factory

dragonfly_control

-2 dragonfly_factory

-4

-6 -5

0

5

10

345

15

Function 1 Fig. 4. Canonical discriminant function plot of the four studied insect groups by site (control/near factory).

Acknowledgments We are indebted to Dr. Ali Soltanpour, and Mr. Paavo Tamminen for their valuable technical assistance. Family Alfthan, Mss. Pilvi and Tuuli Nummelin as well Ms. Iiris Kalliola assisted greatly by digging antlions. Constructive comments by W.B. Rabitsch helped us to improve our manuscript. The field work was done in Tva¨rminne Zoological Station.

Appendix 1. Nummelin et al. Heavy metal contents of studied samples near factory and control (italics) sites. Studied species G.lat. Gerris lateralis, G.odo. Gerris odontogaster, G.tho. Gerris thoracicus, G.arg. Gerris argentatus, Myrmel. Myrmeleon spp., F. lugu. Formica lugubris, L. niger Lasius niger, F. rufa Formica rufa coll, A. jun. Aeshna juncea, A. gran. Aeshna cf. grandis, C. aen. Cordulia aenea, L. spon. Lestes sponsa, L. rubic. Leucorrhinia cf. rubicunda, L. caud. Leucorrhinia cf. caudalis, S. danae Sympetrum cf. danae, Odon. sp. Odonata sp. No refers to sample number. Dev. st. refers to development stage: ad. adult, f.ad. female adult, m.ad., male adult, f.V. female V-instar juvenile, m.V. male V-instar juvenile, V. V-instar juvenile, juv juvenile. Site refers to sampling site: Synd Syndalen, 1 km SW from the factory; Lap Lappvik bay, 1 km NW from the factory; Tva¨ Tva¨rminne by -village 3 km SW from the factory, Ta¨c Ta¨cktom rivulet, 7 km SW from the factory, La˚nsk La˚ngska¨r island pools, 7 km S from the factory, La˚no¨r La˚ngo¨rn, 12 km SW from the factory, 4 tuul Nelja¨n tuulen tupa, 13 km SW from the factory, Kov W Koverhar, 0.5 km W from the factory; Kov S Koverhar, 0.5 km S from the factory; Tva¨. tra¨

Species

No Dev. st. Site

Date

Fe

Mn

Zn Cu Ni

Cd

Pb

G.lat. G.lat. G.lat. G.lat. G.lat. G.lat. G.lat. G.odo. G.odo. G.tho. G.tho. G.tho. G.tho. G.tho. MEAN ST.DEV G.lat. G.lat. G.lat. G.lat. G.odo. G.odo. G.odo. G.tho. G.tho. G.tho. G.tho. G.tho. G.tho. G.arg. G.arg. G.arg. G. spp. G. tho. MEAN ST.DEV Myrmel Myrmel Myrmel MEAN ST.DEV Myrmel Myrmel Myrmel MEAN ST.DEV F. lugu. F. rufa L. niger F. rufa F. rufa MEAN ST.DEV F. rufa F. rufa L. niger MEAN ST.DEV A. jun.

1 2 3 4 5 6 7 8 9 10 11 12 13 14

ad. f.ad. m.ad. f.V. m.V. f.ad. m.ad. ad. ad. ad. f.ad. m.ad. f.V. m.V.

Synd Synd Synd Synd Synd Lap Lap Tv. tra¨ Lap Lap Lap Lap Lap Lap

Jn 95 Au 95 Au 95 Au 95 Au 95 Au 95 Au 95 Au 95 Au 95 Jn 95 Au 95 Au 95 Au 95 Au 95

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

ad. f.ad. m.ad. V. f.ad. m.ad. V. f.ad. m.ad. f.ad. m.ad. f.V. m.V. f.ad. m.ad. V N.D. N.D.

Ta¨c Ta¨c Ta¨c Ta¨c La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk La˚nsk

Jn 95 Au 95 Au 95 Au 95 Au 95 Au 95 Au 95 Jn 95 Jn 95 Au 95 Au 95 Jl 95 Jl 95 Au 95 Au 95 Au 95 Au 97 Au 97

1160 1500 1550 1500 1700 620 690 380 310 520 380 440 540 530 844 514 620 560 610 690 170 150 200 290 250 250 220 360 350 200 190 220 210 420 331 175 900 1100 1800 1267 473 4000 5100 4100 4400 608 300 420 1200 840 890 730 367 170 160 470 266 176 87

80 65 85 55 50 45 45 70 35 35 30 30 30 30 49 19 125 65 65 55 25 20 20 40 25 25 25 20 20 20 20 15 18 18 35 28 160 350 180 230 104 250 390 250 297 81 100 360 70 330 400 252 155 110 310 160 193 104 2.5

400 365 430 315 290 320 345 420 300 280 220 235 225 235 313 72 470 380 375 345 310 270 265 260 160 230 220 235 225 270 255 245 210 260 277 74 240 720 400 453 244 440 480 430 450 27 250 560 160 560 780 462 253 350 230 320 300 62 100

1.5 2.1 2 1.6 1.7 1.9 2 2.1 1.7 0.96 0.86 0.91 1.1 1.4 1.6 0.5 3.8 5.2 5.9 5.2 12.4 10.4 8.5 2.6 1.9 7.6 7.4 3.3 3.1 10.5 9.1 7.4 3.5 4.1 6.2 3.1 7.2 15 3.6 8.6 5.8 4.3 4.0 2.5 3.6 1.0 1.4 9.3 1.0 5.1 6.8 4.7 3.5 5.7 5.5 11 7.4 3.1 0.08

N.D. N.D. N.D. 0.6 0.5 0.6 0.6 N.D. N.D. 0.5 N.D. N.D. N.D. 0.5 ? ? N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.1 1 0.5 N.D. 0.5 N.D. N.D. N.D. 0.5 0.6 1.8 ? ? 5 4.1 2.5 3.9 1.3 3.8 5.9 3.4 4.3 1.3 0.9 1.4 1.4 2.4 1.9 1.6 0.6 1.7 1.2 3.2 2.0 1.0 0.6

33 juv 34 juv 35 juv

La˚no¨r JlAu 97 4 tuul JlAu 97 Tva¨ JlAu 97

36 juv 37 juv 38 juv

Synd JlAu 97 Kov W JlAu 97 Kov S JlAu 97

39 40 41 42 43

Tva¨ Synd Synd Kov W Kov S

ad. ad. ad. ad. ad.

JlAu JlAu JlAu JlAu JlAu

97 97 97 97 97

44 ad. 45 ad. 46 ad.

4 tuul JlAu 97 La˚no¨r JlAu 97 La˚no¨r JlAu 97

47 juv

La˚nsk Jl 96

50 55 60 50 50 45 40 45 40 40 30 35 35 35 44 9 45 55 45 45 40 45 35 40 40 30 35 45 45 45 45 40 42 43 42 5 63 41 42 49 12 33 52 44 43 10 14 15 15 24 28 19 6 17 14 17 16 2 28

N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 0.7 0.6 N.D. N.D. N.D. N.D. ? ? N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. N.D. 1.2 N.D. N.D. ? ? 1.1 1.5 1.3 1.3 0.2 1.0 3.6 3.7 2.8 1.5 0.2 0.6 0.3 0.8 0.6 0.5 0.2 1.1 0.8 N.D. 0.8 0.4 0.9

(Appendix continued on next page)

M. Nummelin et al. / Environmental Pollution 145 (2007) 339e347

346 (Appendix continued ) Species

No Dev. st. Site

A. gran. C. aen. L. spon. MEAN ST.DEV L. spon. L. rubic. L. caud. S. danae Odon. sp. A. jun. A. gran. C. aen. MEAN ST.DEV

48 juv 49 juv 50 juv

La˚nsk Jl 96 La˚nsk Jl 96 La˚nsk Jl 96

51 52 53 54 55 56 57 58

Tv. Tv. Tv. Tv. Tv. Tv. Tv. Tv.

juv juv juv juv juv juv juv juv

Date

tra¨ tra¨ tra¨ tra¨ tra¨ tra¨ tra¨ tra¨

Jl Jl Jl Jl Jl Jl Jl Jl

96 96 96 96 96 96 96 96

Fe 56 250 73 116 89 360 830 690 1800 910 300 410 2000 912 650

Mn 3.4 2.9 2.5 2.8 0.4 5.2 8 8.8 7.8 5.8 4.6 3.1 8.3 6.5 2.1

Zn Cu Ni 85 130 65 95 27 71 83 86 98 130 95 100 110 97 18

24 85 13 37 32 24 30 28 36 50 27 26 50 34 11

0.5 2.1 0.3 1.0 0.8 1.1 1.5 1.7 2.5 6.2 1.6 4.8 4.3 3.0 1.9

Cd 0.05 0.09 0.25 0.12 0.10 1.2 0.8 0.73 0.53 0.68 0.71 1.4 0.81 0.86 0.29

Pb 0.3 2.9 0.2 1.0 1.3 0.9 1.3 1.3 2.7 1.2 0.6 2.9 3.1 1.8 1.0

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