Relating metal exposure and chemical speciation to trace metal accumulation in aquatic insects under natural field conditions
Introduction
Metal bioavailability and toxicity from water-borne exposure generally depend on the activity of the free metal ion, which is controlled by chemical speciation processes (binding to dissolved organic carbon (DOC), inorganic ligands (e.g. Cl−, OH−, CO32−) and the effect of pH), and are largely influenced by other cations (e.g. Na+, Ca2+, Mg2+) and H+ ions competing with trace metals for uptake at particular biological uptake sites (e.g. ion-channels and other transporters in the gills of aquatic organisms) (Hare and Tessier, 1996, Hare and Tessier, 1998, Bervoets and Blust, 2000). The latter concepts are integrated in the Free Ion Activity Model (FIAM), which states that the activity of the free metal ion is a good predictor of both metal availability and toxicity to aquatic organisms (Campbell, 1995), and has been used as the main rationale for the construction of the Biotic Ligand Model (BLM) in order to predict water-borne metal toxicity (Paquin et al., 2002, Niyogi and Wood, 2004).
Over the last decades efforts have been made to determine and predict trace metal speciation in natural waters. This has led to the construction of chemical speciation models such as the Windermere Humic Aqueous Model (WHAM), which enables calculation of the free metal ion concentration and activity in solution, based on water chemistry measurements and equilibrium binding interactions (e.g. pH, temperature, Ca2+, Mg2+, DOC) (Tipping, 1994, Tipping, 1998, Tipping et al., 1998). Although WHAM is currently incorporated in the BLM (Paquin et al., 2002, Niyogi and Wood, 2004), the speciation model has been rarely used to predict metal accumulation in aquatic insects under natural conditions (but see Hare and Tessier, 1996, Hare and Tessier, 1998, Croteau et al., 1998, Ponton and Hare, 2009, Stockdale et al., 2010). Since water chemistry and exposure scenarios can largely vary compared to conditions in the laboratory, relations between metal exposure, chemical speciation and invertebrate body burdens taking into account the influence of major ions and other metals at biological uptake sites should be assessed directly in the field. Recently, studies of Stockdale et al. (2010) and Tipping and Lofts (2013) were able to model metal levels in field-collected aquatic invertebrates using WHAM, considering organisms as humic acids, which corresponded well with measured body burdens. Since accumulated metal levels represent a time-integrated and ecologically-relevant measure of metal exposure and bioavailability, body burdens have gained increasing attention in biomonitoring studies during recent years (Hare and Tessier, 1996, Adams et al., 2011, De Jonge et al., 2013).
The aim of the current study was first to evaluate influences of chemical speciation and water chemistry (pH, DOC and major cation effects) on insect body burdens under natural field conditions, and secondly to evaluate whether WHAM-predicted free metal ion activity and other modulation factors could accurately predict the observed body burdens.
Section snippets
Study area and sampling design
In total 36 headwater streams of the Lake District, Ribbledale, Swaledale and the Howgill Fells, which are all located in the north-west part of England, were sampled as part of an extended field survey (Bass et al., 2008). Some of these sites have been severely metal contaminated from discharge of nearby abandoned mining sites. Samples for the determination of water chemistry were taken on four occasions (March 6–8, March 20–22, April 3–5 and April 17–19, 2006). Separate samples were taken for
Effect of water chemistry on Ni body burdens
Total dissolved Ni concentrations ranged from 0.002 to 1.29 μM (Table 1). WHAM-predicted free Ni ion activities were significantly positively correlated with {H+}, {K+}, {Mg2+} and all other trace metal ions (Table 2). No significant correlation was observed between {Ni2+} and both {Na+} and {Ca2+}. Nickel body burdens ranged from 0.003 (Perlodidae) to 0.68 μmol g− 1 dw (Leuctra sp.) (Table 3). Ni body burdens in Leuctra sp., Simuliidae, Rhithrogena sp. and Perlodidae were generally poorly
Conclusions
Strong relations were observed between insect body burdens and WHAM-calculated free metal ion activities and the competing ions for uptake, which generally provided superior fits compared to metal accumulation as a function of total dissolved metal levels or the free ion alone. Due to the large range in pH observed in the waters of the present study, the effect of H+ ions on insect body burdens was most clearly revealed. In addition, the influence of Na+ on Cu2 + uptake was observed for
Acknowledgement
This research project was funded by the Environment Agency of England and Wales, the European Copper Institute, the European Nickel Industry Association, the International Cadmium Association, the International Zinc Association (Europe), the Rio Tinto and the Scottish Environment Protection Agency (Bass et al., 2008). We thank Edward Tipping and the CEH staff for collecting the invertebrate specimens in the field and performing the water chemistry analyses — Nicholas Kneebone, Alan Lawlor,
References (54)
- et al.
Effects of pH on cadmium and zinc uptake by the midge larvae Chironomus riparius
Aquat Toxicol
(2000) - et al.
The relation between acid volatile sulfides (AVS) and metal accumulation in aquatic invertebrates: implications of feeding behavior and ecology
Environ Pollut
(2010) - et al.
The use of invertebrate body burdens to predict ecological effects of metal mixtures in mining-impacted waters
Aquat Toxicol
(2013) - et al.
The acute toxicity of nickel to Daphnia magna: predictive capacity of bioavailability models in artificial and natural waters
Ecotoxicol Environ Saf
(2008) - et al.
Influence of Ca, humic acid and pH on lead accumulation and toxicity in the fathead minnow during prolonged water-borne lead exposure
Comp Biochem Physiol C
(2006) - et al.
Development of a chronic zinc biotic ligand model for Daphnia magna
Ecotoxicol Environ Saf
(2005) - et al.
Comparison of different predictors of exposure for modeling impacts of metal mixtures on macroinvertebrates in stream microcosms
Aquat Toxicol
(2013) - et al.
Multi-metal interactions between Cd, Cu, Ni, Pb and Zn in water flea Daphnia magna, a stable isotope experiment
Aquat Toxicol
(2008) - et al.
Effect of Na, Ca and pH on simultaneous uptake of Cd, Cu, Ni, Pb, and Zn in the water flea Daphnia magna measured using stable isotopes
Aquat Toxicol
(2009) - et al.
Effects of water chemistry on the chronic toxicity of lead to the cladoceran Ceriodaphnia dubia
Ecotoxicol Environ Saf
(2011)
Effects of chronic waterborne nickel exposure on growth, ion homeostasis, acid-base balance, and nickel uptake in the freshwater pulmonate snail, Lymnaea stagnalis
Aquat Toxicol
Interactive effects of metals in mixtures on bioaccumulation in the amphipod Hyalella azteca
Aquat Toxicol
The biotic ligand model: a historical overview
Comp Biochem Physiol C Toxicol Pharmacol
Trace metal concentrations in aquatic invertebrates: why and so what?
Environ Pollut
Cadmium, zinc and the uptake of calcium by two crabs, Carcinus maenas and Eriocheir sinensis
Aquat Toxicol
Toxicity of proton–metal mixtures in the field: linking stream macroinvertebrate species diversity to chemical speciation and bioavailability
Aquat Toxicol
WHAM — a chemical-equilibrium model and computer code for waters, sediments, and soils incorporating a discrete site electrostatic model of ion-binding by humic substances
Comput Geosci
Metal mixture toxicity to aquatic biota in laboratory experiments: application of the WHAM-FTOX model
Aquat Toxicol
Modelling the chemical speciation of trace metals in the surface waters of the Humber system
Sci Total Environ
Metal accumulation by stream bryophytes, related to chemical speciation
Environ Pollut
Accumulation of Al, Mn, Fe, Cu, Zn, Cd and Pb by the bryophyte Scapania undulata in three upland waters of different pH
Environ Pollut
Utility of tissue residues for predicting effects of metals on aquatic organisms
Integr Environ Assess Manag
Environmental quality standards for trace metals in the aquatic environment
Evaluation of microwave-heating digestion and graphite-furnace atomic-absorption spectrometry with continuum source background correction for the determination of iron, copper and cadmium in brine shrimp
J Anal At Spectrom
Differences in dissolved cadmium and zinc uptake among stream insects: mechanistic explanations
Environ Sci Tech
Bioaccumulation dynamics and exposure routes of Cd and Cu among species of aquatic mayflies
Environ Toxicol Chem
Interaction between trace metals and aquatic organisms: a critique of the free-ion activity model
Cited by (19)
Voltammetric methods for speciation analysis of trace metals in natural waters
2021, Trends in Environmental Analytical ChemistryCitation Excerpt :Assessing the form of metal species is essential as this affects the degree of adsorption to suspended matter, the migration rate to sediments and overall transport within aquatic systems [16]. For example, researches have shown that compared with the total dissolved concentration, the free ion concentration of metals is more closely related to their bioavailability and toxicity to zooplankton and phytoplankton [17,18]. Dissolved metal species have historically been the main focus of research on trace metals in natural waters.
The use of WHAM-F<inf>TOX</inf>, parameterized with laboratory data, to simulate zooplankton species richness in acid- and metal- contaminated lakes
2021, Aquatic ToxicologyCitation Excerpt :The WHAM speciation code (UK Centre for Ecology and Hydrology, 2020) is used to calculate cation binding, assuming equilibrium with the bathing solution. The model has provided reasonable fits of laboratory toxicity data (Tipping and Lofts, 2013, 2015), and the approach is supported by field evidence; measured metal (Al, Ni, Cu, Zn, Cd, Pb) contents of stream bryophytes (Tipping et al., 2008), and macroinvertebrates (Stockdale et al., 2010; Tipping and Lofts, 2013; De Jonge et al., 2014) are correlated with WHAM-calculated loadings of HA. Secondly, an appropriate field variable has to be simulated.
Watershed-scale distributions of heavy metals in the hyporheic zones of a heavily polluted Maozhou River watershed, southern China
2020, ChemosphereCitation Excerpt :Hyporheic zones (HZ) are the areas in the watershed with a strong river and groundwater exchange that can accumulate heavy metals either through the deposition of metal-associated particles from river water or sorption and precipitation from aqueous phase during the river water and groundwater exchange (Bai et al., 2012; Islam et al., 2015; Yu et al., 2017; Zhang et al., 2017). While the accumulation processes in the HZ clean up heavy metals in river and groundwater, the sediment-associated heavy metals are subject to transformation and speciation changes that may release back to river and groundwater, affecting water quality and threatening ecological health (Bradley et al., 1981; De Jonge et al., 2014; Lin et al., 2016; Rosado et al., 2016; Tang et al., 2016). Extensive researches have been performed to investigate the heavy metal concentrations and processes influencing heavy metal distribution in the HZ (Kumar et al., 2015; Lin et al., 2016; Yin et al., 2016; Feng et al., 2017; Gui et al., 2017; Yu et al., 2017; Liu et al., 2018; Samanta and Dalai, 2018).
Competitive interactions among H, Cu, and Zn ions moderate aqueous uptake of Cu and Zn by an aquatic insect
2019, Environmental PollutionCitation Excerpt :Thus, Na demand was achieved at low pH. To our knowledge, experimental studies of competitive interactions between protons, Cu, and Zn in aquatic insects have not been conducted. Evidence of H+ as a competitive ion is supported by modeling metal body burdens in aquatic insects from lakes and streams waters (Croteau et al., 1998; De Jonge et al., 2014; Hare and Tessier, 1996; Stockdale et al., 2010), although the modeling results are dependent on the how the binding site(s) is conceptualized (Balistrieri et al., 2015). The inhibitory mechanism implicit to the modeling structure hasn't been confirmed experimentally for either Cu or Zn.