Effect of Ocean Acidification on Organic and Inorganic Speciation of Trace Metals.

Rising concentrations of atmospheric carbon dioxide are causing acidification of the oceans. This results in changes to the concentrations of key chemical species such as hydroxide, carbonate and bicarbonate ions. These changes will affect the distribution of different forms of trace metals. Using IPCC data for pCO2 and pH under four future emissions scenarios (to the year 2100) we use a chemical speciation model to predict changes in the distribution of organic and inorganic forms of trace metals. Under a scenario where emissions peak after the year 2100, predicted free ion Al, Fe, Cu, and Pb concentrations increase by factors of up to approximately 21, 2.4, 1.5, and 2.0 respectively. Concentrations of organically complexed metal typically have a lower sensitivity to ocean acidification induced changes. Concentrations of organically complexed Mn, Cu, Zn, and Cd fall by up to 10%, while those of organically complexed Fe, Co, and Ni rise by up to 14%. Although modest, these changes may have significance for the biological availability of metals given the close adaptation of marine microorganisms to their environment.

Relationships between riverine and terrestrial dissolved organic carbon: Concentration, radiocarbon signature, specific UV absorbance.

The transfer of dissolved organic carbon (DOC) from land to watercourses plays a major role in the carbon cycle, and in the transport and fate of associated organic and inorganic contaminants. We investigated, at global scale, how the concentrations and properties of riverine DOC depend upon combinations of terrestrial source solutions. For topsoil, subsoil, groundwater and river solutions in different Köppen-Geiger climatic zones, we compiled published and new values of DOC concentration ([DOC]), radiocarbon signature (DO14C), and specific UV absorbance (SUVA). The average value of each DOC variable decreased significantly in magnitude from topsoil to subsoil to groundwater, permitting the terrestrial sources to be distinguished. We used the terrestrial data to simulate the riverine distributions of each variable, and also relationships between pairs of variables. To achieve good matches between observed and simulated data, it was necessary to optimise the distributions of water fractions contributed by each of the three terrestrial sources, and also to reduce the mean input terrestrial [DOC] values, to about 60% of the measured ones. One possible explanation for the required lowering of the modelled terrestrial [DOC] values might be unrepresentative sampling of terrestrial DOC, including dilution effects; another is the loss of DOC during riverine transport. High variations in simulated riverine DOC variables, which match observed data, are due predominantly to variations in source solution values, with a lesser contribution from the different combinations of source waters. On average, most DOC in rivers draining catchments with forest and/or grass-shrub land cover comes in similar amounts from topsoil and subsoil, with about 10% from groundwater. In rivers draining croplands, subsoil and groundwater solutions are the likely dominant DOC sources, while in wetland rivers most DOC is from topsoil.

Long-term effects of atmospheric deposition on British plant species richness.

The effects of atmospheric pollution on plant species richness (nsp) are of widespread concern. We carried out a modelling exercise to estimate how nsp in British semi-natural ecosystems responded to atmospheric deposition of nitrogen (Ndep) and sulphur (Sdep) between 1800 and 2010. We derived a simple four-parameter equation relating nsp to measured soil pH, and to net primary productivity (NPP), calculated with the N14CP ecosystem model. Parameters were estimated from a large data set (n = 1156) of species richness in four vegetation classes, unimproved grassland, dwarf shrub heath, peatland, and broadleaved woodland, obtained in 2007. The equation performed reasonably well in comparisons with independent observations of nsp. We used the equation, in combination with modelled estimates of NPP (from N14CP) and soil pH (from the CHUM-AM hydrochemical model), to calculate changes in average nsp over time at seven sites across Britain, assuming that variations in nsp were due only to variations in atmospheric deposition. At two of the sites, two vegetation classes were present, making a total of nine site/vegetation combinations. In four cases, nsp was affected about equally by pH and NPP, while in another four the effect of pH was dominant. The ninth site, a chalk grassland, was affected only by NPP, since soil pH was assumed constant. Our analysis suggests that the combination of increased NPP, due to fertilization by Ndep, and decreased soil pH, primarily due to Sdep, caused an average species loss of 39% (range 23-100%) between 1800 and the late 20th Century. The modelling suggests that in recent years nsp has begun to increase, almost entirely due to reductions in Sdep and consequent increases in soil pH, but there are also indications of recent slight recovery from the eutrophying effects of Ndep.

Simulating long-term carbon nitrogen and phosphorus biogeochemical cycling in agricultural environments.

Understanding how agricultural practices alter biogeochemical cycles is vital for maintaining land productivity, food security, and other ecosystem services such as carbon sequestration. However, these are complex, highly coupled long-term processes that are difficult to observe or explore through empirical science alone. Models are required that capture the main anthropogenic disturbances, whilst operating across regions and long timescales, simulating both natural and agricultural environments, and shifts among these. Many biogeochemical models neglect agriculture or interactions between carbon and nutrient cycles, which is surprising given the scale of intervention in nitrogen and phosphorus cycles introduced by agriculture. This gap is addressed here, using a plant-soil model that simulates integrated soil carbon, nitrogen and phosphorus (CNP) cycling across natural, semi-natural and agricultural environments. The model is rigorously tested both spatially and temporally using data from long-term agricultural experiments across temperate environments. The model proved capable of reproducing the magnitude of and trends in soil nutrient stocks, and yield responses to nutrient addition. The model has potential to simulate anthropogenic effects on biogeochemical cycles across northern Europe, for long timescales (centuries) without site-specific calibration, using easily accessible input data. The results demonstrate that weatherable P from parent material has a considerable effect on modern pools of soil C and N, despite significant perturbation of nutrient cycling from agricultural practices, highlighting the need to integrate both geological and agricultural processes to understand effects of land-use change on food security, C storage and nutrient sustainability. The results suggest that an important process or source of P is currently missing in our understanding of agricultural biogeochemical cycles. The model could not explain how yields were sustained in plots with low P fertiliser addition. We suggest that plant access to organic P is a key uncertainty warranting further research, particularly given sustainability concerns surrounding rock sources of P fertiliser.

Impact of two centuries of intensive agriculture on soil carbon, nitrogen and phosphorus cycling in the UK.

This paper describes an agricultural model (Roth-CNP) that estimates carbon (C), nitrogen (N) and phosphorus (P) pools, pool changes, their balance and the nutrient fluxes exported from arable and grassland systems in the UK during 1800-2010. The Roth-CNP model was developed as part of an Integrated Model (IM) to simulate C, N and P cycling for the whole of UK, by loosely coupling terrestrial, hydrological and hydro-chemical models. The model was calibrated and tested using long term experiment (LTE) data from Broadbalk (1843) and Park Grass (1856) at Rothamsted. We estimated C, N and P balance and their fluxes exported from arable and grassland systems on a 5km×5km grid across the whole of UK by using the area of arable of crops and livestock numbers in each grid and their management. The model estimated crop and grass yields, soil organic carbon (SOC) stocks and nutrient fluxes in the form of NH4-N, NO3-N and PO4-P. The simulated crop yields were compared to that reported by national agricultural statistics for the historical to the current period. Overall, arable land in the UK have lost SOC by -0.18, -0.25 and -0.08MgCha-1y-1 whereas land under improved grassland SOC stock has increased by 0.20, 0.47 and 0.24MgCha-1y-1 during 1800-1950, 1950-1970 and 1970-2010 simulated in this study. Simulated N loss (by leaching, runoff, soil erosion and denitrification) increased both under arable (-15, -18 and -53kgNha-1y-1) and grass (-18, -22 and -36kgNha-1y-1) during different time periods. Simulated P surplus increased from 2.6, 10.8 and 18.1kgPha-1y-1 under arable and 2.8, 11.3 and 3.6kgPha-1y-1 under grass lands 1800-1950, 1950-1970 and 1970-2010.

Mains water leakage: Implications for phosphorus source apportionment and policy responses in catchments.

Effective strategies to reduce phosphorus (P)-enrichment of aquatic ecosystems require accurate quantification of the absolute and relative importance of individual sources of P. In this paper, we quantify the potential significance of a source of P that has been neglected to date. Phosphate dosing of raw water supplies to reduce lead and copper concentrations in drinking water is a common practice globally. However, mains water leakage (MWL) potentially leads to a direct input of P into the environment, bypassing wastewater treatment. We develop a new approach to estimate the spatial distribution and time-variant flux of MWL-P, demonstrating this approach for a 30-year period within the exemplar of the River Thames catchment in the UK. Our analyses suggest that MWL-P could be equivalent to up to c.24% of the P load entering the River Thames from sewage treatment works and up to c.16% of the riverine P load derived from agricultural non-point sources. We consider a range of policy responses that could reduce MWL-P loads to the environment, including incorporating the environmental damage costs associated with P in setting targets for MWL reduction, alongside inclusion of MWL-P within catchment-wide P permits.

Developing a critical load approach for national risk assessments of atmospheric metal deposition.

The critical load approach has been proposed for evaluation of the need to reduce atmospheric emissions of metals that lead to transboundary transport and deposition across Europe. The present study demonstrates and evaluates the application of a critical load approach for national-scale risk assessment of metal deposition in the United Kingdom. Critical load maps, calculated using critical limits based on pH-dependent free metal ion activities, are presented. Current concentrations of lead and cadmium in soils are compared with two sets of critical limit values: First, limits based on the reactive soil concentration, and second, a pH-dependent free ion critical limit function, which takes into account variable soil characteristics across the country. The use of these two models leads to different conclusions about which areas of the United Kingdom are at greatest risk, partly because of differences in the range of values of pH and organic matter in soils used in ecotoxicological experiments and in the national database. Critical loads were calculated based on free ion critical limits; the critical loads were lowest in the south and east of the country and were associated with higher soil pH, lower runoff, and lower soil organic matter.

The C:N:P:S stoichiometry of soil organic matter.

The formation and turnover of soil organic matter (SOM) includes the biogeochemical processing of the macronutrient elements nitrogen (N), phosphorus (P) and sulphur (S), which alters their stoichiometric relationships to carbon (C) and to each other. We sought patterns among soil organic C, N, P and S in data for c. 2000 globally distributed soil samples, covering all soil horizons. For non-peat soils, strong negative correlations (p < 0.001) were found between N:C, P:C and S:C ratios and % organic carbon (OC), showing that SOM of soils with low OC concentrations (high in mineral matter) is rich in N, P and S. The results can be described approximately with a simple mixing model in which nutrient-poor SOM (NPSOM) has N:C, P:C and S:C ratios of 0.039, 0.0011 and 0.0054, while nutrient-rich SOM (NRSOM) has corresponding ratios of 0.12, 0.016 and 0.016, so that P is especially enriched in NRSOM compared to NPSOM. The trends hold across a range of ecosystems, for topsoils, including O horizons, and subsoils, and across different soil classes. The major exception is that tropical soils tend to have low P:C ratios especially at low N:C. We suggest that NRSOM comprises compounds selected by their strong adsorption to mineral matter. The stoichiometric patterns established here offer a new quantitative framework for SOM classification and characterisation, and provide important constraints to dynamic soil and ecosystem models of carbon turnover and nutrient dynamics.

Macronutrient processing by temperate lakes: A dynamic model for long-term, large-scale application.

We developed a model of the biogeochemical and sedimentation behaviour of carbon (C), nitrogen (N) and phosphorus (P) in lakes, designed to be used in long-term (decades to centuries) and large-scale (104-105km2) macronutrient modelling, with a focus on human-induced changes. The model represents settling of inflow suspended particulate matter, production and settling of phytoplankton, decomposition of organic matter in surface sediment, denitrification, and DOM flocculation and decomposition. The model uses 19 parameters, 13 of which are fixed a priori. The remaining 6 were obtained by fitting data from 109 temperate lakes, together with other information from the literature, which between them characterised the stoichiometric incorporation of N and P into phytoplankton via photosynthesis, whole-lake retention of N and P, N removal by denitrification, and the sediment burial of C, N and P. To run the model over the long periods of time necessary to simulate sediment accumulation and properties, simple assumptions were made about increases in inflow concentrations and loads of dissolved N and P and of catchment-derived particulate matter (CPM) during the 20th century. Agreement between observations and calculations is only approximate, but the model is able to capture wide trends in the lakewater and sediment variables, while also making reasonable predictions of net primary production. Modelled results suggest that allochthonous sources of carbon (CPM and dissolved organic matter) contribute more to sediment carbon than the production and settling of algal biomass, but the relative contribution due to algal biomass has increased over time. Simulations for 8 UK lakes with sediment records suggest that during the 20th century average carbon fixation increased 6-fold and carbon burial in sediments by 70%, while the delivery of suspended sediment from the catchments increased by 40% and sediment burial rates of N and P by 131% and 185% respectively.

Nutrient fluxes from domestic wastewater: A national-scale historical perspective for the UK 1800-2010.

Nutrient emissions in human waste and wastewater effluent fluxes from domestic sources are quantified for the UK over the period 1800-2010 based on population data from UK Census returns. The most important drivers of change have been the introduction of the water closet (flush toilet) along with population growth, urbanization, connection to sewer, improvements in wastewater treatment and use of phosphorus in detergents. In 1800, the population of the UK was about 12 million and estimated emissions in human waste were 37kt N, 6.2kt P and 205ktorganicC/year. This would have been recycled to land with little or no sewage going directly to rivers or coastal waters. By 1900, population had increased to 35.6 million and some 145kt N were emitted in human waste but, with only the major urban areas connected to sewers, only about 19kt N were discharged in sewage effluent. With the use of phosphorus in detergents, estimated phosphorus emissions peaked at around 63.5ktP/year in the 1980s, with about 28ktP/year being discharged in sewage effluent. By 2010, population had increased to 63 million with estimated emissions of 263kt N, 43.6kt P and 1460ktorganicC/year, and an estimated effluent flux of 104kt N, 14.8kt P and 63kt organic C. Despite improvements in wastewater treatment, current levels of nutrient fluxes in sewage effluent are substantially higher than those in the early 20th century.

Long-term macronutrient stoichiometry of UK ombrotrophic peatlands.

In this paper we report new data on peat carbon (C), nitrogen (N) and phosphorus (P) concentrations and accumulation rates for 15 sites in the UK. Concentrations of C, N and P measured in peat from five ombrotrophic blanket mires, spanning 4000-10,000years to present were combined with existing nutrient data from ten Scottish ombrotrophic peat bogs to provide the first UK perspective on millennial scale macronutrient concentrations in ombrotrophic peats. Long-term average C, N and P concentrations (0-1.25m) for the UK are 54.8, 1.56 and 0.039wt%, of similar magnitude to the few published comparable sites worldwide. The uppermost peat (0-0.2m) is enriched in P and N (51.0, 1.86, and 0.070wt%) relative to the deeper peat (0.5-1.25m, 56.3, 1.39, and 0.027wt%). Long-term average (whole core) accumulation rates of C, N and P are 25.3±2.2gCm-2year-1 (mean±SE), 0.70±0.09gNm-2year-1 and 0.018±0.004gPm-2year-1, again similar to values reported elsewhere in the world. The two most significant findings are: 1) that a regression model of N concentration on P concentration and mean annual precipitation, based on global meta data for surface peat samples, can explain 54% of variance in N concentration in these UK peat profiles; and 2) budget calculations for the UK peat cores yield an estimate for long-term average N-fixation of 0.8gm-2year-1. Our UK results, and comparison with others sites, corroborate published estimates of N storage in northern boreal peatlands through the Holocene as ranging between 8 and 15Pg N. However, the observed correlation of N% with both mean annual precipitation and P concentration allows a potential bias in global estimates that do not take this into account. The peat sampling data set has been deposited at the NERC Data Centre (Toberman et al., 2016).

Testing WHAM-FTOX with laboratory toxicity data for mixtures of metals (Cu, Zn, Cd, Ag, Pb).

The Windermere humic aqueous model using the toxicity function (WHAM-FTOX ) describes cation toxicity to aquatic organisms in terms of 1) accumulation by the organism of metabolically active protons and metals at reversible binding sites, and 2) differing toxic potencies of the bound cations. Cation accumulation (νi , in mol g(-1) ) is estimated through calculations with the WHAM chemical speciation model by assuming that organism binding sites can be represented by those of humic acid. Toxicity coefficients (αi ) are combined with νi to obtain the variable FTOX (= Σ αi νi ) which, between lower and upper thresholds (FTOX,LT , FTOX,UT ), is linearly related to toxic effect. Values of αi , FTOX,LT , and FTOX,LT are obtained by fitting toxicity data. Reasonable fits (72% of variance in toxic effect explained overall) were obtained for 4 large metal mixture acute toxicity experiments involving daphnids (Cu, Zn, Cd), lettuce (Cu, Zn, Ag), and trout (Zn, Cd, Pb). Strong nonadditive effects, most apparent in results for tests involving Cd, could be explained approximately by purely chemical competition for metal accumulation. Tentative interpretation of parameter values obtained from these and other experimental data suggests the following order of bound cation toxicity: H < Al < (Cu Zn Pb UO2 ) < (Cd Ag). Another trend is a strong increase in Cd toxicity relative to that of Zn as organism complexity increases (from bacteria to fish).

Dissolved trace metal speciation in estuarine and coastal waters: comparison of WHAM/Model VII predictions with analytical results.

The authors apply the chemical speciation model WHAM/Model VII to investigate the distribution of metal species of Fe(III) and the divalent cations of Ni, Cu, Zn, Cd, Hg, and Pb, in the water column of estuaries and coastal areas. The authors compare, for the same locations, measured and modeled free ion and organically bound metal concentrations. The modeled free ion calculations show varying levels of agreement with experimental measurements. Where only natural organic matter is considered as the organic ligand, for Ni, Cd, and Pb, agreement within 1 order of magnitude is found in 122 of 128 comparisons. For Fe and Zn comparisons 12 of 34 (Fe) and 10 of 18 (Zn) agree to within 1 order of magnitude, the remaining modeled values being over 1 order of magnitude higher than measurements. Copper measurements agree within 1 order of magnitude of modeled values in 314 of 533 (59%) cases and are more than 1 order of magnitude lower than modeled values in 202 cases. There is a general tendency for agreement between modeled and measured values to improve with increasing total metal concentrations. There are substantial variations among different analysis techniques but no systematic bias from the model is observed across techniques. It would be beneficial to cross-validate the different analytical methods, in combination with further modeling. The authors also assessed the effect of including an anthropogenic organic ligand (ethylenediamine tetraacetic acid (EDTA)) in the modeling, given its known presence in some coastal environments. Except for Cd, all metals were sensitive to the presence of EDTA, even at a low concentration of 50 nM.

Aged riverine particulate organic carbon in four UK catchments.

The riverine transport of particulate organic matter (POM) is a significant flux in the carbon cycle, and affects macronutrients and contaminants. We used radiocarbon to characterise POM at 9 riverine sites of four UK catchments (Avon, Conwy, Dee, Ribble) over a one-year period. High-discharge samples were collected on three or four occasions at each site. Suspended particulate matter (SPM) was obtained by centrifugation, and the samples were analysed for carbon isotopes. Concentrations of SPM and SPM organic carbon (OC) contents were also determined, and were found to have a significant negative correlation. For the 7 rivers draining predominantly rural catchments, PO14C values, expressed as percent modern carbon absolute (pMC), varied little among samplings at each site, and there was no significant difference in the average values among the sites. The overall average PO14C value for the 7 sites of 91.2 pMC corresponded to an average age of 680 14C years, but this value arises from the mixing of differently-aged components, and therefore significant amounts of organic matter older than the average value are present in the samples. Although topsoil erosion is probably the major source of the riverine POM, the average PO14C value is appreciably lower than topsoil values (which are typically 100 pMC). This is most likely explained by inputs of older subsoil OC from bank erosion, or the preferential loss of high-14C topsoil organic matter by mineralisation during riverine transport. The significantly lower average PO14C of samples from the River Calder (76.6 pMC), can be ascribed to components containing little or no radiocarbon, derived either from industrial sources or historical coal mining, and this effect is also seen in the River Ribble, downstream of its confluence with the Calder. At the global scale, the results significantly expand available information for PO14C in rivers draining catchments with low erosion rates.

Metal mixture modeling evaluation project: 2. Comparison of four modeling approaches.

As part of the Metal Mixture Modeling Evaluation (MMME) project, models were developed by the National Institute of Advanced Industrial Science and Technology (Japan), the US Geological Survey (USA), HDR|HydroQual (USA), and the Centre for Ecology and Hydrology (United Kingdom) to address the effects of metal mixtures on biological responses of aquatic organisms. A comparison of the 4 models, as they were presented at the MMME workshop in Brussels, Belgium (May 2012), is provided in the present study. Overall, the models were found to be similar in structure (free ion activities computed by the Windermere humic aqueous model [WHAM]; specific or nonspecific binding of metals/cations in or on the organism; specification of metal potency factors or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single vs multiple types of binding sites on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. Because of limitations in the available datasets and the strong interrelationships among the model parameters (binding constants, potency factors, toxicity response parameters), further evaluation of specific model assumptions and calibration strategies is needed.

Dynamic modelling of the long term behaviour of cadmium, lead and mercury in Swiss forest soils using CHUM-AM.

The applicability of the dynamic soil model CHUM-AM was tested to simulate concentrations of Cd, Pb and Hg in five Swiss forest soils. Soil cores of up to 50 cm depth were sampled and separated into two defined soil layers. Soil leachates were collected below the litter by zero-tension lysimeters and at 15 and 50 cm soil depths by tension lysimeters over two years. The concentrations of Cd, Pb and Hg in the solid phase and soil solution were measured by ICP-MS (Cd, Pb) or CV-AFS (Hg). Measured metal concentrations were compared with modelled concentrations using CHUM-AM. Additionally we ran the model with three different deposition scenarios (current deposition; maximum acceptable deposition according to the Swiss ordinance on Air Pollution Control; critical loads according to CLRTAP) to predict metal concentrations in the soils for the next 1000 years. Assuming current loads concentrations of Cd and Pb showed varying trends (increasing/decreasing) between the soils. Soils rich in organic carbon or with a high pH value showed increasing trends in Cd and Pb concentrations whereas the concentrations in the other soils decreased. In contrast Hg concentrations are predicted to further increase in all soils. Critical limits for Pb and Hg will partly be exceeded by current loads or by the critical loads proposed by the CLRTAP but the critical limits for Cd will rarely be reached within the next 1000 years. In contrast, maximal acceptable deposition will partly lead to concentrations above the critical limits for Pb in soils within the next 400 years, whereas the acceptable deposition of Cd will not lead to concentrations above the proposed critical limits. In conclusion the CHUM-AM model is able to accurately simulate heavy metal (Cd, Pb and Hg) concentrations in Swiss forest soils of various soil properties.

Metal and proton toxicity to lake zooplankton: a chemical speciation based modelling approach.

The WHAM-FTOX model quantifies the combined toxic effects of protons and metal cations towards aquatic organisms through the toxicity function (FTOX), a linear combination of the products of organism-bound cation and a toxic potency coefficient for each cation. We describe the application of the model to predict an observable ecological field variable, species richness of pelagic lake crustacean zooplankton, studied with respect to either acidification or the impacts of metals from smelters. The fitted results give toxic potencies increasing in the order H(+) < Al < Cu < Zn < Ni. In general, observed species richness is lower than predicted, but in some instances agreement is close, and is rarely higher than predictions. The model predicts recovery in agreement with observations for three regions, namely Sudbury (Canada), Bohemian Forest (Czech Republic) and a subset of lakes across Norway, but fails to predict observed recovery from acidification in Adirondack lakes (USA).

An intermediate complexity dynamic model for predicting accumulation of atmospherically-deposited metals (Ni, Cu, Zn, Cd, Pb) in catchment soils: 1400 to present.

The Intermediate Dynamic Model for Metals (IDMM) is a model for prediction of the pools of metals (Ni, Cu, Zn, Cd, Pb) in topsoils of catchments resulting from deposition of metals from the atmosphere. We used the model to simulate soil metal pools from 1400 onwards in ten UK catchments comprising semi-natural habitats, and compared the results with present day observations of soil metal pools. Generally the model performed well in simulating present day pools, and further improvements were made to simulations of Ni, Cu, Zn and Cd by adjusting the strength of metal adsorption to the soils. Some discrepancies between observation and prediction for Pb appeared to be due either to underestimation of cumulative deposition, or to overestimation of the metal pool under 'pristine', pre-industrial conditions. The IDMM provides a potential basis for large scale assessment of metal dynamics in topsoils.

The use of invertebrate body burdens to predict ecological effects of metal mixtures in mining-impacted waters.

The present study investigated whether invertebrate body burdens can be used to predict metal-induced effects on aquatic invertebrate communities. Total dissolved metal levels and four invertebrate taxa (Leuctra sp., Simuliidae, Rhithrogena sp. and Perlodidae) were sampled in 36 headwater streams located in the north-west part of England. Using the River Invertebrate Prediction and Classification System (RIVPACS) taxonomic completeness of invertebrate communities was assessed. Quantile regression was used to relate invertebrate body burdens to a maximum (90th quantile) ecological response, both for all metals separately and in mixtures. Significant relations between Cu, Zn and Pb burdens in Leuctra sp. (Zn, Pb), Simuliidae (Zn, Pb), Rhithrogena sp. (Cu, Zn, Cu+Zn) and Perlodidae (Zn) and both taxonomic completeness (O/E taxa) and Biological Monitoring Working Party index scores (O/E BMWP) were observed. Correspondingly the obtained Cu-Zn mixture model an acceptable impact of 5% change in taxonomic completeness is expected at Rhithrogena sp. body burdens of 1.9µmolg(-1) Cu (121 µg g(-1) Cu) in case of low Zn bioavailability (Rhithrogena sp. Zn body burden of 2.9 µmol g(-1) or 190 µg g(-1)), which will drop to 0.30 µmol g(-1) Cu (19.1 µg g(-1) Cu) in case of higher Zn bioavailability (Zn body burden of 72.6 µmol g(-1) or 4747 µg g(-1)). For Zn, 5% change in taxonomic completeness is expected at Rhithrogena sp. body burdens of 76.4 µmol g(-1) Zn (4995 µg g(-1) Zn) in case of low Cu bioavailability (Cu body burden of 0.19 µmol g(-1) or 12.1 µg g(-1)), which will drop to 6.6 µmol g(-1) Zn (432 µg g(-1) Zn) at higher Cu bioavailability (Cu body burden of 1.74 µmol g(-1) or 111 µg g(-1)). Overall, the present study concludes that invertebrate body burdens can be used to (1) predict metal-induced ecological effects and (2) to derive critical burdens for the protection of aquatic invertebrate communities.

Freshwater DOM quantity and quality from a two-component model of UV absorbance.

We present a model that considers UV-absorbing dissolved organic matter (DOM) to consist of two components (A and B), each with a distinct and constant spectrum. Component A absorbs UV light strongly, and is therefore presumed to possess aromatic chromophores and hydrophobic character, whereas B absorbs weakly and can be assumed hydrophilic. We parameterised the model with dissolved organic carbon concentrations [DOC] and corresponding UV spectra for c. 1700 filtered surface water samples from North America and the United Kingdom, by optimising extinction coefficients for A and B, together with a small constant concentration of non-absorbing DOM (0.80 mg DOCL⁻¹). Good unbiased predictions of [DOC] from absorbance data at 270 and 350 nm were obtained (r² = 0.98), the sum of squared residuals in [DOC] being reduced by 66% compared to a regression model fitted to absorbance at 270 nm alone. The parameterised model can use measured optical absorbance values at any pair of suitable wavelengths to calculate both [DOC] and the relative amounts of A and B in a water sample, i.e. measures of quantity and quality. Blind prediction of [DOC] was satisfactory for 9 of 11 independent data sets (181 of 213 individual samples).