Hazard/Risk Assessment

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Bioaccumulation of polycyclic aromatic hydrocarbons by arctic and temperate benthic species

Corresponding Author

Ariadna S. Szczybelski

[email protected]

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

Department of Animal Ecology, Wageningen Environmental Research (Alterra), Wageningen, The Netherlands

Address correspondence to [email protected]

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Noël J. Diepens,

Noël J. Diepens

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

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Martine J. van den Heuvel-Greve,

Martine J. van den Heuvel-Greve

Wageningen Marine Research, Yerseke, The Netherlands

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Nico W. van den Brink,

Nico W. van den Brink

Subdepartment of Toxicology, Department of Agrotechnology and Food Sciences, Wageningen University, Wageningen, The Netherlands

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Albert A. Koelmans,

Albert A. Koelmans

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

Wageningen Marine Research, Yerseke, The Netherlands

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Ariadna S. Szczybelski,

Corresponding Author

Ariadna S. Szczybelski

[email protected]

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

Department of Animal Ecology, Wageningen Environmental Research (Alterra), Wageningen, The Netherlands

Address correspondence to [email protected]

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Noël J. Diepens,

Noël J. Diepens

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

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Martine J. van den Heuvel-Greve,

Martine J. van den Heuvel-Greve

Wageningen Marine Research, Yerseke, The Netherlands

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Nico W. van den Brink,

Nico W. van den Brink

Subdepartment of Toxicology, Department of Agrotechnology and Food Sciences, Wageningen University, Wageningen, The Netherlands

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Albert A. Koelmans,

Albert A. Koelmans

Aquatic Ecology and Water Quality Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

Wageningen Marine Research, Yerseke, The Netherlands

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First published: 18 January 2019

https://doi.org/10.1002/etc.4366

Citations: 17

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Abstract

Increasing oil and gas activities may substantially increase chemical stress to benthic ecosystems in the Arctic, and it is necessary to evaluate such environmental risks in these systems. Risk assessment procedures for oil-related compounds (e.g., polycyclic aromatic hydrocarbons [PAHs]) should address differences in exposure between Arctic and temperate benthos. We compare for the first time the bioaccumulation of PAHs by Arctic benthic invertebrate species with that of temperate species, based on their biota–sediment accumulation factors (BSAFs). Measured PAH BSAFs were generally higher in temperate bivalves (Limecola balthica) than in Arctic bivalves (Macoma calcarea), whereas BSAFs in Arctic polychaetes (Nephtys ciliata) were higher than in temperate polychaetes (Alitta virens). Differences in measured BSAFs were explained by species-specific feeding modes and traits. However, modeled BSAFs revealed that steady state was not likely to be reached in the 28-d tests for all PAHs and organisms. Due to the low numbers of individuals, most species-specific parameters were too uncertain to reveal differences between Arctic and temperate species. The results of the present study suggest that data from temperate species could be used as a surrogate for Arctic species in risk assessment. Environ Toxicol Chem 2019;38:883–895. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

INTRODUCTION

The Arctic has a high sensitivity to oil spill impacts and has limited capacity for natural recovery due to a profound seasonality, mainly dictated by the reduction in sea ice. Sensitivity may be increased by expanding shipping and oil and gas activities, as well as a lack of appropriate oil spill response methods for this area (Protection of the Arctic Marine Environment, Arctic Council 2009). Therefore, biological targets (bioindicators) for priority monitoring during all phases of oil and gas activities should be used, to assess, minimize, and mitigate adverse effects (Protection of the Arctic Marine Environment, Arctic Council 2009; Szczybelski et al. 2016). Petrogenic polycyclic aromatic hydrocarbons (PAHs) constitute a large group of hydrophobic contaminants that have been the focus of previous environmental assessments because of their potential toxicity and bioaccumulation (OSPAR Commission 2002; Bakke et al. 2013). Such chemical properties may be used to select appropriate bioindicators of acute and chronic effects of oil and gas production.

Bioindicators provide knowledge about chemical concentrations in the abiotic environment, and they are also considered particularly useful to monitor trends in oil and gas-related pollution, because they integrate chemical and nonchemical stress, and account for in situ ecological conditions (Martínez-Gómez et al. 2010; Montagna et al. 2013). Arctic benthic systems are characterized by a high trophic diversity, relatively long lifespan, and sedentary lifestyles of species (Renaud et al. 2011), which makes them applicable for monitoring purposes, particularly in areas of oil and gas production. A particularly useful exposure metric to define the bioindicator potential of bioaccumulative chemicals in benthic invertebrates is the biota–sediment accumulation factor (BSAF). The BSAFs of oil and gas-related PAHs can adequately mirror the pollution state of the local Arctic ecosystem near oil and gas activities (DeBlois et al. 2014; Szczybelski et al. 2016). Compared with bioaccumulation (i.e., net result of influx [uptake] and efflux of contaminants) by temperate species, little is known about the bioaccumulation of PAHs from sediment by Arctic benthic species. Cross-chemical extrapolation techniques such as read-across may help to predict PAH bioaccumulation by Arctic species in the absence of experimental data (European Centre for Ecotoxicology and Toxicology of Chemicals 2010). If bioaccumulation was found to be comparable between Arctic and temperate species with similar traits, risk assessment for the Arctic might be simplified by using temperate species data as a surrogate for Arctic species. Therefore, it is useful to explore the potential for reading across 1) Arctic and temperate species and 2) species with different feeding traits and from the same region, with respect to bioaccumulation. Similarity in exposure routes between Arctic and temperate species may not be self-evident, however. For instance, exposure times to contaminants may be longer in Arctic systems, because Arctic species have a longer life-span or biological reaction times are generally slower in polar than in temperate biota (Chapman and Riddle 2005). Clearance of PAHs and their metabolites may also be slower in Arctic invertebrates, because chemical elimination rates are temperature dependent and are affected by seasonal variability in lipid content (Arctic Monitoring and Assessment Programme 2010). Finally, seasonality in the environmental conditions in the Arctic may have a major impact on the physiology of local species (Kędra et al. 2015).

The BSAF has traditionally been used as a metric to assess the bioaccumulation of contaminants from sediment and has been compared across a wide range of aquatic ecosystems (Burkhard et al. 2005; Weisbrod et al. 2009; Selck et al. 2012). If equilibrium partitioning theory applies, BSAF values can be expected to range between 1 and 2 (Boese et al. 1996). This is based on the assumption that chemicals partition between biota lipids and sediment organic carbon. However, equilibrium partitioning theory does not consider the possibility that feeding as a route of uptake may lead to higher than equilibrium steady-state concentrations. To accommodate the situations in which equilibrium partitioning theory does not apply, a kinetic BSAF model can be used (Diepens et al. 2015; Sidney et al. 2016). Potentially, the BSAF may be a useful metric to compare effects of species traits on bioaccumulation, because it can correct for differences in chemical concentration, sediment organic matter, and organism lipid content between the sites or species that are compared. For benthic invertebrates, whose geographic distribution can span to (sub-) Arctic areas, we are aware of only 2 studies reporting BSAFs (Lake et al. 1990; Szczybelski et al. 2016).

The objective of the present study was to compare bioaccumulation between 4 Arctic and 2 temperate species (with different species traits), using 28-d whole-sediment tests (Diepens et al. 2015; Sidney et al. 2016). An additional objective was to assess whether the results can be generalized by using a time-dependent BSAF model, previously used for describing bioaccumulation in temperate marine and freshwater benthic invertebrates (Diepens et al. 2015; Sidney et al. 2016). For the first time, we explore to what extent BSAF is useful as a metric for bioaccumulation in Arctic benthic invertebrate species so that Arctic and temperate species can be compared with respect to bioaccumulation.

MATERIALS AND METHODS

We performed a 28-d sediment bioaccumulation experiment with Arctic species at Kings Bay (Ny-Ålesund, Svalbard, Norway) between September and October 2014 (termed the “Arctic experiment”) and another investigation with temperate species at Wageningen Marine Research (Yerseke, the Netherlands) between July and August 2014 (termed the “temperate experiment”). Sediments in the Arctic and temperate experiments were the same for the same phylum. Emphasis was on simulating environmentally realistic PAH exposure levels, which is achieved by the use of representative species of the macrobenthic community of each climate region, and using field-contaminated sediments. Although ecologically relevant, such a strategy led to a low level of replication during the actual tests due to a low availability of field individuals. This was particularly the case for the Arctic experiment.

Sediment collection and preparation

Because some of the selected Arctic bivalves (Astarte borealis and Macoma calcarea) usually reside in sandy sediment, and the selected Arctic polychaete (Nephtys ciliata) is generally found in sandy mud (Jørgensen et al. 2014), 2 different batches of sediment were manually prepared after sediment collection to ensure an optimal habitat for the test species. Each contained different ratios of muddy and coarse sediment, respectively defined as <0.50- and 0.50- to 1-mm grain size. Bivalve sediment contained two-thirds coarse and one-third muddy sediment, whereas polychaete sediment contained two-thirds muddy and one-third coarse sediment, based on volume. Sediment was collected in the Oosterschelde estuary (The Netherlands; 51°36′13.5″N, 3°47′49.3″E) on 24 to 25 April 2014 and 2 May 2014, and was used to create the sediment treatments for both the Arctic and the temperate experiments. This was done to maximize the homogeneity of treatment exposures among experiments. These sediment mixtures contained background PAH levels and were therefore termed the “low” treatments. In the low bivalve and polychaete treatments, the PAH concentrations differed (Supplemental Data, Tables S1 and S2) due to differences in their mud content and other variables creating sediment heterogeneity; the PAH concentrations were 1 order of magnitude higher than in previously collected sediments at the end of the Arctic species sampling transect (Blomstrandhalvøya Island, Kongsfjorden Bay, Svalbard, Norway; Szczybelski et al. 2016).

From each of these 2 sediment mixtures with low chemical concentration, another 2 sediment treatments were prepared with a higher chemical concentration, termed the “medium” and “high” sediments. The medium treatment contained 5% (vol) harbor sediment (Rotterdam, The Netherlands), and the high treatment contained 10% (vol) harbor sediment. These percentages were used 1) on a precautionary basis because neither the harbor sediment chemical concentrations nor the effect threshold for each of the species were known, and 2) to be able to link the nonlethal effects of chemical concentration to the endpoints studied (Szczybelski et al., 2019). These preparations thus resulted in 6 sediments: 3 for bivalves (bivalve sediment low [BSL], bivalve sediment medium [BSM], and bivalve sediment high [BSH]) and 3 for polychaetes (polychaete sediment low [PSL], polychaete sediment medium [PSM], and polychaete sediment high [PSH]); one of them (BSM) was finally excluded from further analysis due to low numbers of individuals. All sediment treatments were thoroughly mixed with a turbine mixer for approximately 15 min before storage/transport from The Netherlands to Svalbard, and again mixed before use in the exposure experiments. In terms of guidelines for sediment spiking, a short mixing time is acceptable for estuarine sediments because of their homogeneous composition. In all sediment treatments, chemical concentrations and other characteristics (dry wt and organic matter content) were assessed (Supplemental Data, Tables S1 and S2). Due to logistical restraints, the storage time (at 3–7 °C) for sediment treatments was 9 wk longer in the Arctic than in the temperate experiment. It was hypothesized that such a difference in storage time would not significantly affect the partitioning of PAHs between porewater and sediment particles because sediments had been aged for a long time and thus the PAHs were already fully equilibrated (Poot et al. 2014). Prior to the start of exposure, sediment treatments were allowed to stay in contact with filtered seawater at a 1:6 sediment-to-water volume ratio without aeration for 3 d, and with aeration for the following 4 d. Some experimental units in the Arctic experiment were aerated for 12 to 17 d because biota field sampling took place for a longer period than initially expected (the first 3 wk after aeration began).

Collection of test organisms

Based on their feeding habits, sessility, and relative abundance (Word et al. 2014), 4 Arctic benthic species were selected; 3 bivalve species—A. borealis (Schumacher, 1817), M. calcarea (Gmelin, 1791), Nuculana pernula (O.F. Müller, 1771)—and a polychaete species—N. ciliata (O.F. Müller, 1776). These species are primarily abundant in Arctic climate zones, although they are not restricted to this area (Table 1). In addition, 2 temperate benthic species (a bivalve, Limecola balthica [Linnaeus, 1758], and a polychaete, Alitta virens [Sars, 1835], formerly known as Macoma balthica and Nereis virens, respectively) were selected based on their comparable feeding habits, sessility, availability of chronic test protocols, and thus the potential for a comparison with the Arctic species. This was also ensured by using the same sediment type among species with similar feeding traits. We limited the present study to 2 temperate species because we prioritized the comparison of bioaccumulation among Arctic and temperate deposit-feeding bivalves and polychaetes. Because M. calcarea individuals were scarce at the sampling area, a second Arctic deposit feeder (N. pernula) was included. Macoma calcarea may feed both on suspended and sediment organic matter, so an obligate suspension feeder (A. borealis) was also included to estimate the contribution of suspended organic matter to the bioaccumulation of PAHs by M. calcarea.

Table 1. Overview of target species and their ecological traits

Experiment	Species	Geographical distribution	Feeding mode
Arctic	Astarte borealis (Schumacher, 1817)	Chukchi Sea^b	Suspension feeder^f
		Barents Sea^c
		Baltic Sea^d^,^e
		Temperature: −2–16 °C
	Macoma calcarea (Gmelin, 1791)	Bering Sea^g	Surface deposit and suspension feeder^f
		Chukchi Sea^b
		Barents Sea^c
		Kara Sea^h
		Baltic Sea^e
		Temperature: −2–12 °C
	Nuculana pernula (O.F. Müller, 1771)	Bering Sea^g	Subsurface deposit feederⁱ
		Barents Sea^c
		Temperature: −2–9 °C
	Nephtys ciliata (O.F. Müller, 1776)	Bering Sea^j	Predator^f
		Barents Sea^c
		Baltic Sea^d^,^e^,^k
		Temperature: –1–14 °C
Temperate	Limecola balthica (Linnaeus, 1758)	Extensive distribution in the northern hemisphere^l	Surface deposit and suspension feeder^l^,^m
	Limecola balthica (Linnaeus, 1758)	Temperature: 0–25 °C	Surface deposit and suspension feeder^l^,^m
	Alitta virens (Sars, 1835)	Cosmpolitan, often found in areas of chronic oil pollutionⁿ	Predator and deposit feeder^o^,^p
	Alitta virens (Sars, 1835)	Temperature: +3–12 °C	Predator and deposit feeder^o^,^p

^a Source: Wikipedia, Institute of Oceanology of the Polish Academy of Sciences (IOPAN).
^b Blanchard et al. (2013)
^c Anisimova et al. (2010)
^d Gusev and Rudinskaya (2014)
^e Gogina et al. (2016)
^f Kędra et al. (2012)
^g Lovvorn et al. (2005)
^h Denisenko et al. (2003)
ⁱ Strand et al. (2003)
^j Oxtoby et al. (2016)
^k Pedersen (1991)
^l McLeod et al. (2007)
^m Decho and Luoma (1991)
ⁿ Lewis and Galloway (2008)
^o McElroy et al. (1990)
^p Oliver et al. (1996)

Permission for sampling of Arctic and temperate species was issued by The Governor of Svalbard and the Province of Zeeland (The Netherlands), respectively. Sampling of Arctic species was performed along a transect from Tønsneset peninsula (79°0′22″N, 11°57′10″E) to Blomstrandhalvøya (78°59′14″N, 11°57′28″E; Svalbard, Norway; Supplemental Data, Figure S1). Limecola balthica were collected at low tide at the Oesterdam (Oosterschelde National Park, The Netherlands, 51°26′24″N, 4°13′16″E), and A. virens were obtained from a professional bait farm, Topsy baits (Wilhelminadorp, The Netherlands).

Experimental design

Arctic and temperate species were acclimatized under test conditions. Arctic species were kept in filtered natural seawater (20 μm) for 2 to 6 d without food; in the temperate experiment, animals were kept in filtered natural seawater (0.20 μm) for 5 d, and were fed once at the start of the acclimatization. Feeding of Arctic species prior to exposure would have notably impacted their feeding behavior and metabolic rate because field sampling took place over 3 wk at the end of the productive season. This means that individuals of the same species were not acclimatized for the same length of time and that their nutritional requirements may have been altered between consecutive weeks. For further details of the acclimatization of test species, see the Supplemental Data.

At the initiation of the Arctic experiment, only subsamples of A. borealis and N. pernula were collected, to assess the initial conditions (termed the “background”). This was not feasible for M. calcarea and N. ciliata due to the low number of individuals. Organisms were allowed to depurate their guts for 24 h in filtered seawater. Samples were stored at –20 °C for later determination of wet weight, lipid fraction (% wet wt), and chemical concentrations (µg/kg wet wt). Sediment samples were also taken at the beginning of the Arctic experiment (Supplemental Data, Table S1) and stored at –20 °C for later determination of dry weight, organic matter content, and chemical concentrations (µg/kg dry wt).

Experimental designs were similar for the Arctic and temperate experiments except for the ambient temperature and photoperiod used. The Arctic experiment was a 28-d test in a temperature-controlled room at 3 °C under a 12:12-h light: dark photoperiod. All planned sediment treatments were run with N. ciliata (PSL, PSM, and PSH; n = 1–3; Table 2). Two treatments (BSL and BSH) were tested with M. calcarea (n = 1–2), and only one treatment (BSH) was tested with A. borealis and N. pernula (n = 2–3; Table 2). The temperate experiment was a 28-d test in a temperature-controlled room at 18 °C under a 16:8-h light: dark photoperiod. All sediment treatments were tested with A. virens (PSL, PSM, and PSH; n = 2–3), and 2 treatments were tested with L. balthica (BSL and BSH; n = 1–3).

Table 2. Overview of the number of experimental units (no.) for Arctic bivalves^a, Arctic polychaetes^b, temperate bivalves^c, and temperate polychaetes^d per sediment treatment

Experiment	Species	Ind./EU^f	Background	BSL	BSH	PSL	PSM	PSH
			Treatment (no.)^e
Arctic	Astarte borealis	25	3	n.t.	3
	Macoma calcarea	40–50	n.t.	1	2
	Nuculana pernula	40–50	1	n.t.	2
	Nephtys ciliata	20	n.t.			1	1	3
Temperate	Limecola balthica	50	3	1	3
Temperate	Alitta virens	16	3			2	2	3

^a A. borealis, M. calcarea, N. pernula
^b N. ciliata
^c L. balthica
^d A. virens
^e Sediment treatments with different levels of polycyclic aromatic hydrocarbon (PAH) contamination are referred to as follows: BSL = low bivalve sediment; BSH = high bivalve sediment; PSL = low polychaete sediment; PSM = medium polychaete sediment; PSH = high polychaete sediment. Background refers to pooled field samples in which individuals were allowed to depurate for 24 h in filtered seawater before storage.
^f Experimental unit (EU) refers to a sediment treatment replicate or aquarium in which a specific number of individuals of a single species are exposed for 28 d to the corresponding sediment treatment, allowed to depurate for 24 h in filtered seawater, and pooled for analytical treatment.
n.t. = not tested.

Individuals were randomly divided into groups of 16 to 50 individuals/experimental unit (Table 2). Animals were not fed during exposure, although sediment organic matter content (2–6%), and in some cases food supply during acclimatization (for temperate species), prevented body weight (Diepens et al. 2015) and lipid weight loss (Tables 3 and 4) during the experiment. Experimental units were checked daily for mortality (animals at the surface and immobile after poked), and dead organisms were removed daily.

Table 3. Polycyclic aromatic hydrocarbons (mean ± SD; µg/kg lipid wt) in bivalves (Astarte borealis, Macoma calcarea, Nuculana pernula) and polychaetes (Nephtys ciliata) from the Arctic experiment

	M. calcarea		N. ciliata			A. borealis		N. pernula
	BSL	BSH	PSL	PSM	PSH	Background	BSH	Background	BSH
No.	1	2	1	1	3	3	3	1	2
Lipid wt (% wet wt)	0.82	0.84	0.39	0.41	0.45	0.42	0.46	1.71	1.70
PHE	3566 ± 393	2821 ± 287	1402 ± 681	729	2462 ± 941	9697 ± 1482	11746 ± 4998	2457	2792 ± 324
ANT	890 ± 89	718 ± 48	336 ± 143	149	297 ± 120	2384 ± 442	2977 ± 957	359	686 ± 216
FLT	1612 ± 178	3329 ± 1174	2353 ± 788	1771	4468 ± 969	1376 ± 280	8504 ± 4206	374	3192 ± 837
PYR	1314 ± 87	2623 ± 930	1713 ± 530	1384	3758 ± 920	1119 ± 120	6926 ± 3575	346	2828 ± 531
BaA	n.d.	673 ± 240	113 ± 70	77	218 ± 104	n.d.	n.d.	129	1847 ± 70
CHR	7434 ± 6614	470 ± 113	1327 ± 1709	0.15	6425 ± 6647	6164 ± 1276	2926 ± 2658	9860	122 550 ± 158 586
BeP	316 ± 0	957 ± 374	427 ± 178	298	650 ± 129	884 ± 169	2066 ± 2300	183	3222 ± 761
BbF	175 ± 30	658 ± 305	117 ± 78	100	228 ± 69	223 ± 56	845 ± 269	218	2200 ± 586
BghiP	1162 ± 745	50 ± 65	344 ± 454	n.d.	1106 ± 955	1409 ± 2154	n.d.	1192	2953 ± 2925
dBahA	275 ± 2	506 ± 133	166 ± 76	40	n.d.	n.d.	479 ± 233	296	1173 ± 1112
Ind123P	69 ± 40	298 ± 102	34 ± 37	n.d.	n.d.	205 ± 144	421 ± 187	113	1307 ± 283
Σ₁₁PAH	16 933 ± 6714	13 104 ± 3552	8333 ± 267	4550	20 242 ± 9762	34 245 ± 20 336	37 668 ± 17 371	15 526	144 750 ± 156 791

SD = standard deviation; BS = bivalves sediment; PS = polychaetes sediment; L = low treatment; M = medium treatment; H = high treatment; n.d.= at least one sample shows a concentration below the limit of detection; PHE = phenanthrene; ANT = anthracene; FLT = fluoranthene; PYR = pyrene; BaA = benz[a]anthracene; CHR = chrysene; BeP = benzo[e]pyrene; BbF = benzo[b]fluoranthene; BghiP = benzo[ghi]perylene; dBahA = dibenz[a,h]anthracene; Ind123P = indeno(1,2,3-cd)pyrene; PAH = polycyclic aromatic hydrocarbon.

Table 4. Polycyclic aromatic hydrocarbons (mean ± SD; µg/kg lipid wt) in bivalves (Limecola balthica) and polychaetes (Alitta virens) from the temperate experiment

	L. balthica			A. virens
	Background	BSL	BSH	Background	PSL	PSM	PSH
No.	3	1	3	3	2	2	3
Lipid wt (% wet wt)	0.85	0.84	0.78	1.30	0.97	1.71	1.39
PHE	2499 ± 571	2849	2257 ± 165	2497 ± 798	2267 ± 1376	1324 ± 496	2278 ± 2000
ANT	225 ± 60	262	334 ± 102	136 ± 64	108 ± 70	100 ± 27	113 ± 96
FLT	1431 ± 394	2853	3061 ± 685	5421 ± 1780	1596 ± 598	1824 ± 664	3151 ± 1903
PYR	1484 ± 325	3513	4340 ± 1153	1611 ± 530	893 ± 379	1157 ± 419	2034 ± 1254
BaA	680 ± 177	1101	2547 ± 484	n.d.	83 ± 62	134 ± 19	104 ± 51
CHR	863 ± 98	964	11 585 ± 9242	268 ± 278	n.d.	887 ± 1061	n.d.
BeP	937 ± 247	1618	2833 ± 702	125 ± 50	249 ± 220	279 ± 102	475 ± 286
BbF	938 ± 259	1442	2295 ± 432	51 ± 26	100 ± 88	151 ± 26	125 ± 45
BghiP	2216 ± 4746	47	1754 ± 1454	76 ± 66	n.d.	134 ± 134	n.d.
dBahA	717 ± 491	702	1083 ± 818	83 ± 29	115 ± 79	137 ± 36	239 ± 238
Ind123P	452 ± 206	448	839 ± 473	n.d.	68 ± 79	96 ± 56	75 ± 62
Σ₁₁PAH	35 512 ± 56 664	15 799	32 928 ± 13 246	10 360 ± 3099	8005 ± 5818	6223 ± 2229	9371 ± 5439

SD = standard deviation; BS = bivalves sediment; PS = polychaetes sediment; L = low treatment; M = medium treatment; H = high treatment; n.d. = at least one sample shows a concentration below the limit of detection; PHE = phenanthrene; ANT = anthracene; FLT = fluoranthene; PYR = pyrene; BaA = benz[a]anthracene; CHR = chrysene; BeP = benzo[e]pyrene; BbF = benzo[b]fluoranthene; BghiP = benzo[ghi]perylene; dBahA = dibenz[a,h]anthracene; Ind123P = indeno(1,2,3-cd)pyrene; PAH = polycyclic aromatic hydrocarbon.

At the conclusion of the experiments, organisms were allowed to depurate their guts for 24 h in filtered seawater. Animals were weighed, measured for body or shell length, dissected (the bivalves), and pooled by species. Biota samples and samples from each sediment treatment were stored (at –20 °C) and analyzed for the same parameters as in archived samples. Biota and sediment samples from both experiments were shipped frozen in dry ice to Wageningen University (Wageningen, The Netherlands) for chemical analysis.

Due to either a low level of replication of BSL and PSM treatments (Table 2) or to the heterogeneity among PSL replicates in their organic matter content (Supplemental Data, Tables S1 and S2), statistical analyses were only performed with data measured for BSH and PSH treatments. However, all treatments could be used for bioaccumulation modeling.

Chemical analysis

Chemical analysis was conducted according to methods used by Kupryianchyk et al. (2011). The following PAHs were analyzed: phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene (BaA), chrysene, benzo[e]pyrene (BeP), benzo[b]fluoranthene (BbF), benzo[ghi]perylene (BghiP), dibenz[a,h]anthracene (dBahA), and indeno(1,2,3-cd)pyrene (Ind123P). The PAH recoveries were 85 to 94% and 64 to 75% for biota and sediment samples, respectively. Three blanks/each batch of 30 samples were used, and values were corrected for blanks. For further details on extraction, clean-up, and instrumental analysis, see the Supplemental Data.

Data analysis

Lipid-normalized concentrations after 28 d were calculated in biota samples for all available sediment treatments. The BSAFs were calculated as follows:

$urn:x-wiley:14381656:media:etc4366:etc4366-math-0001$ (1)

with C_org being the chemical concentration in the organism (µg/kg wet wt), C_sed the chemical concentration in sediment (µg/kg dry wt), f_lip the fraction of lipids in the organism based on wet weight, and f_OC the fraction of sediment organic carbon based on loss of ignition and an organic carbon/organic matter conversion ratio of 0.40 (Diepens et al. 2015; Sidney et al. 2016).

Lipid-normalized biota concentrations and BSAFs of BSH-exposed bivalves and PSH-exposed polychaetes were checked for normality with Q–Q plots and Shapiro–Wilk tests, and equality of variances with Levene's test. If data were normally distributed, lipid-normalized biota concentrations and BSAFs were tested for species and climate region effect with a one-way analysis of variance or an independent t test, respectively, for each PAH compound. If data were non-normally distributed, they were log-transformed, and when a normal distribution still was not reached, lipid-normalized biota concentrations and BSAFs were tested for species and climate region effect with the Kruskal–Wallis and Mann–Whitney U tests in combination with Kolmogorov–Smirnov Z tests, respectively, for each PAH compound.

Significance level of an overall statistical comparison was set at p ≤ 0.05; for pairwise comparisons among species or chemicals, Bonferroni's and Holm's sequential Bonferroni corrections were applied, respectively. All statistical calculations were performed using SPSS Ver 22.

Bioaccumulation modeling

The usefulness of modeling bioaccumulation in invertebrate lipids was explored according to methods described by Diepens et al. (2015), following previously published models (e.g., Thomann and Komlos 1999). In the absence of background data for all test species, we used background data for N. pernula to model M. calcarea experimental data, and background data for A. borealis to model N. ciliata experimental data. Uncertainties in the correctness of such assumption will only have a relatively small effect on the first term of Supplemental Data, Equation S1. For an explanation of modeling, calculation of 90% confidence intervals (CIs), percentage of uptake through water, and fraction of steady state reached in the bioaccumulation test, the reader is referred to the Supplemental Data.

RESULTS AND DISCUSSION

PAH background concentrations

In the Arctic filter-feeding bivalve A. borealis, average Σ₁₁PAH concentrations when the animals were collected were 9.44 mg/kg lipid weight. Changes of one order of magnitude in A. borealis PAH concentrations were observed for phenanthrene, anthracene, chrysene, and BghiP between September 2014, when samples were collected, and July 2013 (Szczybelski et al. 2016). From these compounds, concentrations of phenanthrene and chrysene were highest (46% of the Σ₁₁PAH) in A. borealis. A significant increase in A. borealis chrysene concentration would comply with generally high 4-ring PAH concentration in sediment surface layers from the inner areas of Kongsfjorden Bay (Pouch et al. 2017). Such an increase was higher for the deposit-feeding bivalve N. pernula than for A. borealis (Table 3) and may be explained by N. pernula's higher capacity to select particles with higher organic matter content in sediments with a low organic content (Włodarska-Kowalczuk and Pearson 2004) such as Blosmstrandhalvøya Island sediments (Szczybelski et al. 2016).

In the temperate bivalve L. balthica, average Σ₁₁PAH concentrations in individuals collected at Oesterdam were 35.51 mg/kg lipid weight (Table 4). Concentrations of pyrene and BaA were below concentrations found in L. balthica collected in the Westerschelde estuary (The Netherlands; Steur et al. 1996). In the temperate polychaete A. virens, Σ₁₁PAH concentrations were lower than in L. balthica (10.36 mg/kg lipid wt; Table 4). This was expected, because A. virens were obtained from an aquaculture farm, and L. balthica were collected in the field.

Effects of Arctic species traits on PAH bioaccumulation

Bioaccumulation

Lipid-normalized Σ₁₁PAH concentrations in Arctic invertebrates in the high treatment were 13.10 mg/kg in M. calcarea, 20.24 mg/kg in N. ciliata, 37.67 mg/kg in A. borealis, and 14.48E1 mg/kg in N. pernula (Table 3). Statistically higher concentrations were observed for anthracene in the filter feeder A. borealis compared with the other Arctic species (p < 0.05; Supplemental Data, Table S9). In addition, the 3- to 4-ring PAHs (phenanthrene, fluoranthene, pyrene, and chrysene) were mainly accumulated by A. borealis, which also agreed with a higher fraction of these compounds in high sediment. The 5- to 6-ring PAHs BeP, BbF, and Ind123P were strongly accumulated (i.e., up to 1 order of magnitude higher than background concentrations) by the deposit feeder N. pernula, which differed from the composition of these compounds in high sediment. This disagreement might be explained by a higher PAH accumulation by N. pernula than the other 2 Arctic bivalves prior to the start of the experiment (Weems et al. 2012), slow PAH excretion (Neff et al. 1987), and nonequilibrium between N. pernula lipid tissue and sediment during the Arctic experiment.

The 3- to 4-ring PAH (phenanthrene, anthracene, fluoranthene, and pyrene) concentrations were on average 2.5 to 4 times higher in the high-exposed filter feeder A. borealis compared with the deposit-feeding bivalves (M. calcarea and N. pernula). An increase in fluoranthene and pyrene concentrations can be explained by the fact that the concentrations of these PAHs in high sediment were also high (Supplemental Data, Table S1). Concentrations of chrysene were on average 42 times higher in high-exposed N. pernula than A. borealis (Table 3), although the chrysene concentration in high sediment was very low (Supplemental Data, Table S1). In this case, considerably high chrysene concentrations in N. pernula might be explained by the species's ability to ingest sediment to a larger extent than the other Arctic bivalves (Weems et al. 2012) and to retain PAHs, as observed by Neff et al. (1987). In the polychaete N. ciliata, differences in the concentration of phenanthrene, fluoranthene, pyrene, BaA, BbF, and BghiP between the low- and high-exposed individuals reflected the difference in concentrations measured in the low and high sediments (Table 3 and Supplemental Data, Table S1).

No statistical differences in PAH concentrations were found between the deposit-feeding bivalves M. calcarea and N. pernula in the high exposures. However, this conclusion should be viewed with caution because the number of samples available per species was low, resulting in a low statistical power (p ≤ 0.20) for chrysene, BghiP, and dBahA, and the 2 species have different feeding behaviors (Table 1; Sun et al. 2009; Weems et al. 2012; Kędra et al. 2012). Variability in the metabolism of PAHs by some of our target species (A. virens, L. balthica) is well described in the literature (Rust et al. 2004a), with generally higher metabolism rates in temperate polychaetes than in bivalves. Although not evaluated in the present study, an increase in general metabolic activity (Jensen et al. 2012; Carrasco-Navarro et al. 2015) and a moderate production of reactive oxygen in Arctic species at the end of summer (Tschischka et al. 2000; Nahrgang et al. 2013) are suggested as a means to increase efficiency and to prevent the inhibition of PAH biotransformation, respectively. The metabolism of PAHs in Arctic species is expected to be lower than in temperate species due to low temperature and generally low food availability in their environment (Olsen et al. 2007; Chapman 2016).

BSAFs

The BSAFs of PAHs were generally low (i.e., BSAF < 1; Figure 1), and were higher in high-exposed A. borealis than high-exposed N. ciliata (Supplemental Data, Tables S7, S8, and S11). This may be linked to a higher black carbon and amorphous organic matter content in the high sediment of polychaetes compared with bivalves. The strong sorption of the planar PAHs to black carbon (Moermond et al. 2005; Cornelissen et al. 2006) most likely decreased PAH bioavailability in polychaetes, and a higher organic matter content may result in a higher nutritional value of the high sediment of polychaetes and a reduction in polychaete feeding. Harbor sediments are known to contain more black carbon (Cornelissen et al. 2005; Koelmans et al. 2010) than sediments from the collection site in the Oosterschelde National Park, The Netherlands. In particular, the Rotterdam harbor area has been subject to considerable black carbon deposition (Keuken et al. 2015). This is supported by a similar pyrogenic PAH component of bivalves’ and polychaetes’ high-sediment treatments, which may be indicative of black carbon presence in both sediment treatments (Tobiszewski and Namieśnik 2012).

Details are in the caption following the image — **Figure 1**
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Modeled biota–sediment accumulation factors (BSAFs; closed symbols) based on the minimum sum of squares and actual measured BSAFs (open symbols) for different polycyclic aromatic hydrocarbons in Arctic (*Astarte borealis*, *Macoma calcarea*, *Nuculana pernula*, and *Nephtys ciliata*) and temperate species (*Limecola balthica* and *Alitta virens*) exposed to the high treatment. AE = Arctic experiment; TE = temperate experiment.

Effects of temperate species traits on PAH bioaccumulation

Bioaccumulation

Lipid-normalized Σ₁₁PAH concentrations in the high-exposed invertebrates were 32.93 mg/kg in L. balthica and 9.37 mg/kg in A. virens (Table 4). Statistically higher concentrations were observed for BaA and BbF in the high-exposed L. balthica compared with the high-exposed A. virens (p < 1E-3; Supplemental Data, Table S13). This may be related to factors such as higher PAH background concentrations, higher bioavailability, lower elimination rates, longer exposure times, and high food selectivity in L. balthica (Rust et al. 2004b; Diepens et al. 2015).

In L. balthica, PAH concentrations were 2-fold (fluoranthene, BbF, dBahA, Ind123P), 3-fold (pyrene, BeP), or 4-fold (BaA) higher in the high- than in the low-exposed individuals, whereas concentrations were 4 to 10 times higher in the high- than in the low-sediment treatment (Table 4 and Supplemental Data, Table S2). The reasons for such a discrepancy may be either a low PAH uptake from sediment (Beukema et al. 2014; Diepens et al. 2015) or differences in congener-specific absorption efficiencies from sediment in L. balthica (McLeod et al. 2004). In contrast, a 2-fold increase in fluoranthene, pyrene, BeP, and dBahA concentrations was observed for both A. virens and sediment samples between the low and the high treatment.

BSAFs

Polycyclic aromatic hydrocarbons BSAFs were higher in high-exposed L. balthica than in high-exposed A. virens (Figure 1 and Supplemental Data, Tables S7, S8, and S14), which is likely due to differences in biota PAH background concentrations and bioavailability between sediment treatments. The BSAFs were on average 1.5 to 24 times higher in the high-exposed L. balthica than in the high-exposed A. virens. This may be explained by a combination of different factors such as lower PAH bioavailability in A. virens due to a possibly higher black carbon and other organic material content in the high sediment of polychaetes compared with bivalves (Yates et al. 2011), lower sediment ingestion by A. virens compared with L. balthica (Diepens et al. 2015), and/or generally higher PAH biotransformation capacity in polychaetes (Jørgensen et al. 2008).

PAH bioaccumulation among Arctic and temperate species

Bioaccumulation

Good water quality was attained in both experiments (Supplemental Data, Tables S3 and S4), and mortality was negligible for all species except for the N. ciliata exposed to the high treatment (24%), which may have been related to the reproductive and feeding activity of the species during the experiment. Lipid-normalized PAH concentrations were generally higher in the temperate deposit-feeding bivalve (L. balthica) than in the Arctic bivalve (M. calcarea), after exposure to the same sediment treatment (e.g., high). Differences were generally nonsignificant, which in some cases resulted from low statistical power (i.e., fluoranthene, pyrene, chrysene, and BghiP). Only anthracene concentrations were found to be 2 times higher in M. calcarea compared with L. balthica (Figure 2 and Tables 3 and 4). This may be explained by the fact that temperature affects organic matter–water and lipid–water partition coefficients, and thus bioaccumulation and BSAF values if other conditions are the same. Lower temperature has been found to increase PAH affinity to organic matter (Tremblay et al. 2005), and also to decrease lipid partitioning (Koelmans and Jiménez 1994). In the case of M. calcarea, these processes probably played a role, but it was not possible to unambiguously identify the main reason for the apparent difference between the species.

In addition, differences between field-sampled L. balthica and M. calcarea, and differences in food selectivity may have led to differences in their general performance during the temperate and Arctic experiments. For instance, in the case of M. calcarea, strong temperature gradients (0–4 °C) described at sampling depth (20 m) within a 2-mo period in late summer (Hanelt et al. 2001; Svendsen et al. 2002) could have increased energy allocation to physiological maintenance in the Arctic bivalves, decreasing their energy budget (Abele et al. 1998; Pörtner et al. 2007), whereas the absence of phytoplankton input in the experiment could have caused a rapid onset of lowered metabolic rate in M. calcarea adults (Prevodnik et al. 2007; Kędra et al. 2012).

The lack of significant differences between the Arctic (N. ciliata) and temperate (A. virens) polychaetes may also be partly due to an insufficient statistical power (i.e., phenanthrene, chrysene, and BghiP). Anthracene, pyrene, BaA, and BbF concentrations in N. ciliata were on average 2 to 3 times higher than in A. virens (Figure 2 and Tables 3 and 4). This may be related to the fact that food conversion can be more effective in N. ciliata under low temperature compared with A. virens (Neuhoff 1979), thus lowering energy loss and improving the Arctic polychaete's fitness. Reproductive and morphological differences between the species can also affect their feeding activity rates and PAH bioaccumulation. A <12-h photophase is known to cause sexual maturity in polychaetes and to reduce their feeding rate (Olive 1978; Lawrence and Soame 2009). It is possible that the feeding rate for the Arctic species N. ciliata was reduced during the period of sampling (8–26 September), when the natural photophase rapidly reaches <12 h (Olive 1978; Graf et al. 1982). In the case of the temperate species A. virens, both farm growing and experimental conditions (photophase > 12 h, 18 °C) inhibited gametogenic development in mature females (Peter et al. 1998).

Under this last assumption, stable feeding activity would have made a PAH assimilation peak possible, which in this case was assumed to have been reached at an earlier exposure time in the temperate polychaete A. virens than in the Arctic polychaete N. ciliata. This can be due to continuous feeding by A. virens, which may not only increase the contact time of the species's intestinal epithelium and coelomic fluids with PAHs (Christensen et al. 2002), and thus increase PAH solubilization, but may also lead to oxidative stress and ultimately to the induction of biotransformation enzymes (Jørgensen et al. 2008; Catalano et al. 2012). Nephtyidae species such as N. ciliata usually have a much smaller gut volume than other deposit-feeding polychaetes and take discrete meals as part of their carnivore diet (Jumars et al. 2015). This may to some extent restrict the species’ PAH absorption (Ahrens et al. 2001), although stable pre-oogenesis conditions (12:12-h light:dark) in the absence of animal food (i.e., Arctic experiment conditions) would make it necessary for the animals to increase their deposit-feeding activity over time to maintain PAH tolerance mechanisms. Although we have no evidence for this explanation, this could have increased the energy budget of A. virens at test initiation and thus its potential for PAH bioaccumulation with respect to N. ciliata.

BSAFs

For 2- to 3-ring PAHs, the BSAFs were higher in the high-exposed M. calcarea than in L. balthica, which, similarly to the differences between PAH lipid-normalized concentrations, could be explained by higher waterborne PAH uptake in M. calcarea. The BSAFs for PAHs were generally higher in the high-exposed N. ciliata than in A. virens. Ranges of BSAFs for all PAHs were <1E-4 to 18, in the order M. calcarea ≈ A. virens < A. borealis < N. ciliata < L. balthica < N. pernula. However, only species exposed to the same sediment treatment (BSH or PSH) under different climatic conditions (Arctic vs temperate) and with the same feeding modes can be directly compared (i.e., M. calcarea vs L. balthica and N. ciliata vs A. virens). The phenanthrene, anthracene, and fluoranthene BSAFs were 2 to 3 times higher in the Arctic bivalve compared with the temperate bivalve (Supplemental Data, Table S7), whereas PAH BSAFs were generally 2 to 17 times higher in the Arctic polychaete compared with the temperate polychaete (Supplemental Data, Tables S8 and S16), which indicates a generally higher PAH uptake from water in the Arctic compared with the temperate species. Similarly to PAH lipid-normalized concentrations, an absence of significant differences in PAH BSAFs between species with the same feeding mode was partly due to low statistical power (Supplemental Data, Table S16).

Modeling PAH bioaccumulation by Arctic and temperate species

The modeled BSAFs matched well with the measured BSAF data. However, the CIs for modeled BSAFs were generally wide for most parameters and species, reflecting the variability in the biological data (Figure 1 and Supplemental Data, Table S17). Complete data sets, with all treatments, were available for N. ciliata and A. virens, and only data for the high treatment were present for all species. This also defines the cases for which parameters were estimated (Supplemental Data, Table S17).

The intercept b in the relation $urn:x-wiley:14381656:media:etc4366:etc4366-math-0002$ , determining the affinity of chemical partitioning to organic carbon, was optimized to a value of 1.07 (0.81–1.33; 90% CI). This is higher than the well-established value of –0.21 for natural sediment (Karickhoff et al. 1979), and can be explained by the efficient binding of PAHs to black carbon present in the sediment (Ruus et al. 2010; Poot et al. 2014). This is consistent with the aforementioned PAH diagnostic ratios indicating pyrogenic PAH sources, and with the fact that many measured BSAF values are smaller than 1. The sorption affinity ratio γ was fitted and appeared to be indistinguishable from 1, whereas the fractions of ingested sediment (parameter β) had 90% CIs extending beyond parameter constraints and were overlapping among species. This finding implies that the present experiments did not identify a difference in sorption to suspended organic matter and sediment organic matter (i.e., $urn:x-wiley:14381656:media:etc4366:etc4366-math-0003$ ), and thus that it does not matter what type of organic matter is ingested. Accordingly, the fraction of ingested sediment (parameter β), was set to 1. This reduced the number of parameters fitted (p = 19; Supplemental Data, Table S17), which yielded narrower CIs for the remaining parameters. Hence, the present model analysis was less rigorous than those provided by Diepens et al. (2015) and Sidney et al. (2016), who detected significant values for β based on larger data sets.

In general, BSAFs decreased or remained at a constant value with increasing octanol–water partition coefficient (log K_OW; Figure 1 and Supplemental Data, Figure S2), which agrees with earlier findings (Diepens et al. 2015; Sidney et al. 2016). One explanation, as discussed by Diepens et al. (2015), may be that steady state was only reached for phenanthrene, anthracene, fluoranthene, and pyrene in M. calcarea and L. balthica during the 28-d experiment (Supplemental Data, Table S18).

However, for 2 chemicals (chrysene and BghiP), high BSAF values were measured and predicted, which was not in line with the other values and expected trends with log K_OW. This can be explained by the high chrysene and BghiP background concentrations in the organisms, at the start of the experiment (Tables 3 and 4), as well as low clearance rates.

Because particle ingestion may be a dominant PAH uptake route in benthic organisms (Selck et al. 2012), ingestion rates (I) were fitted and expressed on an organic matter basis. In general, ingestion rates were low or even 0 (Figure 3 and Supplemental Data, Table S17). For Arctic species, a low ingestion rate would be expected, because metabolic rates are reduced and growth rates are constrained in cold-adapted stenotherms (Pörtner et al. 2007). However, comparison of our data for the temperate species L. balthica and A. virens with previously published data shows that these values are below the lower 90% CI boundary and below the range of 0.13 to 0.62 kg_OM × kg_Lipids⁻¹ × d⁻¹ reported by Thomann et al. (1992). We speculate that the low apparent ingestion rates may be caused by a high nutritional value of the sediment, resulting in the dominance of dermal uptake.

For M. calcarea and A. borealis, the values for the proportionality parameter a in log k_e = −log K_OW + a, required to calculate the elimination rate constant (k_e), were either (respectively) overlapping or higher than previously published CIs for L. balthica (Supplemental Data, Table S17). For N. ciliata, the a values were higher than previously published CIs for A. virens (Diepens et al. 2015). The magnitudes of a for the temperate species L. balthica were higher than previously published CIs for polychlorinated biphenyls (PCBs; McLeod et al. 2008; Diepens et al. 2015). For A. virens, magnitudes of a were lower than previously published CIs for PCBs (Diepens et al. 2015), although it should be noted that PAHs are often considered to be metabolized more easily than PCBs (Rust et al. 2004a; Jørgensen et al. 2008).

The relative importance of chemical uptake pathways depends on the species, the chemical, the treatment, and the estimated value of the ingestion parameter (Supplemental Data, Table S17). In all cases in which the ingestion parameter fitted rates were 0, the contribution of the organic matter ingestion pathway was consequently modeled as 0%. In the high treatment, N. pernula and A. virens showed 100% uptake from organic matter ingestion, whereas for A. borealis, M. calcarea, and N. ciliata, the model suggested 100% uptake from water (Supplemental Data, Table S19). For L. balthica, the chemical uptake from sediment increased with increasing log K_OW. These patterns and values agree with earlier published data (McLeod et al. 2007, 2008; Diepens et al. 2015). Although lower elimination and ingestion rates for Arctic species compared with their temperate counterparts may be expected, this cannot be seen from the present data and parameters. Because the present bioaccumulation data set was not large enough for model validation purposes, as it was in previous modeling studies (Diepens et al. 2015; Sidney et al. 2016), we ascribe these lower rates to the higher variability and uncertainty in the present bioaccumulation data.

CONCLUSIONS AND IMPLICATIONS

The present study showed significant differences in PAH bioaccumulation among temperate species with different feeding traits, and for anthracene among Arctic species. Due to the low availability of field individuals, there was a general lack of significant differences partly related to low statistical power (e.g., chrysene and BghiP). However, differences between Arctic and temperate species with similar feeding traits were significant for some of the PAHs among polychaetes. Bioaccumulation of PAHs from sediment was generally higher in the Artic polychaete N. ciliata than in the temperate A. virens. On the other hand, the temperate deposit-feeding bivalve L. balthica accumulated PAHs to a greater extent from sediment than its Arctic counterpart M. calcarea. Consequently, bioaccumulation metrics experimentally determined in temperate species might be too conservative in the risk assessment for similar Arctic species and in other cases might be too moderate.

The time-dependent BSAF model shows that model parameters did not significantly differ among species and climate regions, which is supported by the generally nonsignificant differences in PAH bioaccumulation between Arctic and temperate species. This finding implies that although modeling has been shown to be a valid tool in earlier work (Diepens et al. 2015; Sidney et al. 2016), insufficient data for an appropriate parametrization limited the insights provided by modeling in the present study. Field validation of bioaccumulation models, for which data assumptions are built on temperate species data, will, however, require Arctic standard single-species tests for further characterization of sediment bioaccumulation mechanisms, such as contaminant uptake and elimination routes, under local conditions.

The present study used sediments and conditions mimicking Arctic and temperate environmental conditions, and used Arctic and temperate species with pairwise matching functional groups. Differences in bioaccumulation in a direct comparison of the 2 climate regions’ characteristics were observed, which, however, were not statistically significant due to considerable variability in the biological control data, and similarity in exposure routes. This means that a cautionary note should be sounded on the use of temperate benthic species as a surrogate for Arctic benthic species in bioaccumulation assessment. It could also be a reasonable approach to consider the use of safety factors (e.g., 10) to extrapolate from temperate to Arctic species.

Supplemental Data

The Supplemental Data are available on the Wiley Online Library at DOI: 10.1002/etc.4366.

Acknowledgement

The authors thank A. Meldahl (who was captain of the research vessel MS Teisten of Kings Bay [Ny-Ålesund, Svalbard, Norway] in the summer of 2014), M. Loonen, B. Frederiks, L. Sidney, V. Mohaupt, T. Dupeyron, K. Binder, A. Roman, and W. van Duin for their assistance with logistics and sampling. M. Włodarska-Kowalczuk, M. Kędra, H. Hillewaert, and A. Semenov are acknowledged for granting us permission to use the image files in Table 1. Equinor (grant SAP 4502687550) and the Wageningen UR TripleP@Sea innovation program (grant KB-14-007) are acknowledged for funding the Development of Arctic Biological Indicators (ARCIND) Project.

Data Accessibility

For access to data, please contact the corresponding author ([email protected]).

Supporting Information

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Citing Literature

Volume38, Issue4

April 2019

Pages 883-895

Bioaccumulation of polycyclic aromatic hydrocarbons by arctic and temperate benthic species

Abstract

INTRODUCTION