Impact of potentially toxic elements on pines in a former ore processing mine: Exploitation of hyperspectral response from needle and canopy scales.

Anthropic potentially toxic element (PTE) releases can lead to persistent pollution in soil. Monitoring PTEs by their detection and quantification on large scale is of great interest. The vegetation exposed to PTEs can exhibit a reduction of physiological activities, structural damage … Such vegetation trait changes impact the spectral signature in the reflective domain 0.4-2.5 µm. The objective of this study is to characterize the impact of PTEs on the spectral signature of two pine species (Aleppo and Stone pines) in the reflective domain and ensure their assessment. The study focuses on nine PTEs: As, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Zn. The spectra are measured by an in-field spectrometer and an aerial hyperspectral instrument on a former ore processing site. They are completed by measurements related to vegetation traits at needle and tree scales (photosynthetic pigments, dry matter, morphometry …) to define the most sensitive vegetation parameter to each PTE in soil. A result of this study is that chlorophylls and carotenoids are the most correlated to PTE contents. Context-specific spectral indices are specified and used to assess metal contents in soil by regression. These new vegetation indices are compared at needle and canopy scales to literature indices. Most of the PTE contents are predicted at both scales with Pearson correlation scores between 0.6 and 0.9, depending on species and scale.

Chronic exposure to trace lead impairs honey bee learning.

Pollutants can have severe detrimental effects on insects, even at sublethal doses, damaging developmental and cognitive processes involved in crucial behaviours. Agrochemicals have been identified as important causes of pollinator declines, but the impacts of other anthropogenic compounds, such as metallic trace elements in soils and waters, have received considerably less attention. Here, we exposed colonies of the European honey bee Apis mellifera to chronic field-realistic concentrations of lead in food and demonstrated that consumption of this trace element impaired bee cognition and morphological development. Honey bees exposed to the highest of these low concentrations had reduced olfactory learning performances. These honey bees also developed smaller heads, which may have constrained their cognitive functions as we show a general relationship between head size and learning performance. Our results demonstrate that lead pollutants, even at trace levels, can have dramatic effects on honey bee cognitive abilities, potentially altering key colony functions and the pollination service.

Unsupervised Monitoring Vegetation after the Closure of an Ore Processing Site with Multi-Temporal Optical Remote Sensing.

Ore processing is a source of soil heavy metal pollution. Vegetation traits (structural characteristics such as spatial cover and repartition; biochemical parameters-pigment and water contents, growth rate, phenological cycle…) and plant species identity are indirect and powerful indicators of residual contamination detection in soil. Multi-temporal multispectral satellite imagery, such as the Sentinel-2 time series, is an operational environment monitoring system widely used to access vegetation traits and ensure vegetation surveillance across large areas. For this purpose, methodology based on a multi-temporal fusion method at the feature level is applied to vegetation monitoring for several years from the closure and revegetation of an ore processing site. Features are defined by 26 spectral indices from the literature and seasonal and annual change detection maps are inferred. Three indices-CIred-edge (CIREDEDGE), IRECI (Inverted Red-Edge Chlorophyll Index) and PSRI (Plant Senescence Reflectance Index)-are particularly suitable for detecting changes spatially and temporally across the study area. The analysis is conducted separately for phyto-stabilized vegetation zones and natural vegetation zones. Global and specific changes are emphasized and explained by information provided by the site operator or meteorological conditions.

Estimating persistent oil contamination in tropical region using vegetation indices and random forest regression.

The persistence of soil contamination after cessation of oil activities remains a major environmental issue in tropical regions. The assessment of the contamination is particularly difficult on vegetated sites, but promising advances in reflectance spectroscopy have recently emerged for this purpose. This study aimed to exploit vegetation reflectance for estimating low concentrations of Total Petroleum Hydrocarbons (TPH) in soils. A greenhouse experiment was carried out for 42 days on Cenchrus alopecuroides (L.) under realistic tropical conditions. The species was grown on oil-contaminated mud pit soils from industrial sites, with various concentrations of TPH. After 42 days, a significant decrease in plant growth and leaf chlorophyll and carotenoid contents was observed for plants exposed to 5-19 g kg-1 TPH in comparison to the controls (p < 0.05). Conversely, pigment contents were higher for plants exposed to 1 g kg-1 TPH (hormesis phenomenon). These modifications proportionally affected the reflectance of C. alopecuroides at leaf and plant scales, especially in the visible region around 550 and 700 nm. 33 vegetation indices were used for linking the biochemical and spectral responses of the species to oil using elastic net regressions. The established models indicated that chlorophylls a and b and ß-carotene were the main pigments involved in the modifications of reflectance (R2 > 0.7). The same indices also succeeded in estimating the concentrations of TPH using random forest regression, at leaf and plant scales (RMSE = 1.46 and 1.63 g kg-1 and RPD = 5.09 and 4.44, respectively). Four out of the 33 indices contributed the most to the models (>75%). This study opens up encouraging perspectives for monitoring the cessation of oil activities in tropical regions. Further researches will focus on the application of our approach at larger scale, on airborne and satellite imagery.

Assessing Soil Contamination Due to Oil and Gas Production Using Vegetation Hyperspectral Reflectance.

The remote assessment of soil contamination remains difficult in vegetated areas. Recent advances in hyperspectral spectroscopy suggest making use of plant reflectance to monitor oil and gas leakage from industrial facilities. However, knowledge about plant response to oil contamination is still limited, so only very few imaging applications are possible at this stage. We therefore conducted a greenhouse experiment on three species long-term exposed to either oil-contaminated or water-deficient soils. Reflectance measurements were regularly performed at leaf and plant scale over 61 days of exposure. Results showed an increase of reflectance in the visible (VIS), the red-edge and the short-wave infrared (SWIR) under both oil and water-deficit stress exposure. A contrasted response in the near-infrared (NIR) was also observed among species. Spectra underwent transformations to discriminate species' responses to the different treatments using linear discriminant analysis (LDA) with a stepwise procedure. Original and transformed spectra enabled to discriminate the plants' responses to the different treatments without confusion after 61 days. The discriminating wavelengths were consistent with the spectral differences observed. These results suggest differential changes in plant pigments, structure and water content as a response to various stressors, and open up promising perspectives for airborne and satellite applications.

Transfer and Ecotoxicity of Titanium Dioxide Nanoparticles in Terrestrial and Aquatic Ecosystems: A Microcosm Study.

With the advancement in nanotechnology, particularly the use of TiO2 nanoparticles (NPs), there is a need to study their release into the environment and assess the related risk in an environmentally relevant contamination scenario. In the present study, the transfer and toxicity of TiO2 NPs in microcosms mimicking terrestrial and aquatic ecosystems were evaluated. The contaminated soil was prepared by spiking natural soils, with these then used as the basis for all exposure systems including preparation of soil leachates for amphibian exposure. Results demonstrated significant reductions in bacterial (-45%) and archaeal (-36%) nitrifier abundance; significant translocation of Ti to M. truncatula leaves (+422%); significant reductions in plant height (-17%), number of leaves (-29%), and aboveground biomass (-53%); nonsignificant Ti uptake in snail foot and viscera, and excretion in feces; and genotoxicity to X. laevis larvae (+119% micronuclei). Our study highlights a possible risk of engineered TiO2 NPs in the environment in terms of trophic transfer and toxicity in both terrestrial and aquatic environments.

Leaf-associated fungal diversity in acidified streams: insights from combining traditional and molecular approaches.

We combined microscopic and molecular methods to investigate fungal assemblages on alder leaf litter exposed in the benthic and hyporheic zones of five streams across a gradient of increasing acidification for 4 weeks. The results showed that acidification and elevated Al concentrations strongly depressed sporulating aquatic hyphomycetes diversity in both zones of streams, while fungal diversity assessed by denaturing gradient gel electrophoresis (DGGE) appeared unaffected. Clone library analyses revealed that fungal communities on leaves were dominated by members of Ascomycetes and to a lesser extent by Basidiomycetes and Chytridiomycetes. An important contribution of terrestrial fungi was observed in both zones of the most acidified stream and in the hyporheic zone of the reference circumneutral stream. The highest leaf breakdown rate was observed in the circumneutral stream and occurred in the presence of both the highest diversity of sporulating aquatic hyphomycetes and the highest contribution to clone libraries of sequences affiliated with aquatic hyphomycetes. Both methods underline the major role played by aquatic hyphomycetes in leaf decomposition process. Our findings also bring out new highlights on the identity of leaf-associated fungal communities and their responses to anthropogenic alteration of running water ecosystems.

Aquatic hyphomycete species are screened by the hyporheic zone of woodland streams.

Aquatic hyphomycetes strongly contribute to organic matter dynamics in streams, but their abilities to colonize leaf litter buried in streambed sediments remain unexplored. Here, we conducted field and laboratory experiments (slow-filtration columns and stream-simulating microcosms) to test the following hypotheses: (i) that the hyporheic habitat acting as a physical sieve for spores filters out unsuccessful strategists from a potential species pool, (ii) that decreased pore size in sediments reduces species dispersal efficiency in the interstitial water, and (iii) that the physicochemical conditions prevailing in the hyporheic habitat will influence fungal community structure. Our field study showed that spore abundance and species diversity were consistently reduced in the interstitial water compared with surface water within three differing streams. Significant differences occurred among aquatic hyphomycetes, with dispersal efficiency of filiform-spore species being much higher than those with compact or branched/tetraradiate spores. This pattern was remarkably consistent with those found in laboratory experiments that tested the influence of sediment pore size on spore dispersal in microcosms. Furthermore, leaves inoculated in a stream and incubated in slow-filtration columns exhibited a fungal assemblage dominated by only two species, while five species were codominant on leaves from the stream-simulating microcosms. Results of this study highlight that the hyporheic zone exerts two types of selection pressure on the aquatic hyphomycete community, a physiological stress and a physical screening of the benthic spore pool, both leading to drastic changes in the structure of fungal community.

Litter identity mediates predator impacts on the functioning of an aquatic detritus-based food web.

During past decades, several mechanisms such as resource quality and habitat complexity have been proposed to explain variations in the strength of trophic cascades across ecosystems. In detritus-based headwater streams, litter accumulations constitute both a habitat and a resource for detritivorous macroinvertebrates. Because litter edibility (which promotes trophic cascades) is usually inversely correlated with its structural complexity (which weakens trophic cascades), there is a great scope for stronger trophic cascades in litter accumulations that are dominated by easily degradable litter species. However, it remains unclear how mixing contrasting litter species (conferring both habitat complexity and high quality resource) may influence top-down controls on communities and processes. In enclosures exposed in a second-order stream, we manipulated litter species composition by using two contrasting litter (alder and oak), and the presence-absence of a macroinvertebrate predator (Cordulegaster boltonii larvae), enabling it to effectively exert predation pressure, or not, on detritivores (consumptive versus non-consumptive predation effects). Leaf mass loss, detritivore biomass and community structure were mostly controlled independently by litter identity and mixing and by predator consumption. However, the strength of predator control was mediated by litter quality (stronger on alder), and to a lesser extent by litter mixing (weaker on mixed litter). Refractory litter such as oak leaves may contribute to the structural complexity of the habitat for stream macroinvertebrates, allowing the maintenance of detritivore communities even when strong predation pressure occurs. We suggest that considering the interaction between top-down and bottom-up factors is important when investigating their influence on natural communities and ecosystem processes in detritus-based ecosystems.

Environmental exposure to metallic pollution impairs honey bee brain development and cognition.

Laboratory studies show detrimental effects of metallic pollutants on invertebrate behaviour and cognition, even at low levels. Here we report a field study on Western honey bees exposed to metal and metalloid pollution through dusts, food and water at a historic mining site. We analysed more than 1000 bees from five apiaries along a gradient of contamination within 11 km of a former gold mine in Southern France. Bees collected close to the mine exhibited olfactory learning performances lower by 36% and heads smaller by 4%. Three-dimensional scans of bee brains showed that the olfactory centres of insects sampled close to the mine were also 4% smaller, indicating neurodevelopmental issues. Our study raises serious concerns about the health of honey bee populations in areas polluted with potentially harmful elements, particularly with arsenic, and illustrates how standard cognitive tests can be used for risk assessment.

Benthic algae stimulate leaf litter decomposition in detritus-based headwater streams: a case of aquatic priming effect?

In detritus-based ecosystems, autochthonous primary production contributes very little to the detritus pool. Yet primary producers may still influence the functioning of these ecosystems through complex interactions with decomposers and detritivores. Recent studies have suggested that, in aquatic systems, small amounts of labile carbon (C) (e.g., producer exudates), could increase the mineralization of more recalcitrant organic-matter pools (e.g., leaf litter). This process, called priming effect, should be exacerbated under low-nutrient conditions and may alter the nature of interactions among microbial groups, from competition under low-nutrient conditions to indirect mutualism under high-nutrient conditions. Theoretical models further predict that primary producers may be competitively excluded when allochthonous C sources enter an ecosystem. In this study, the effects of a benthic diatom on aquatic hyphomycetes, bacteria, and leaf litter decomposition were investigated under two nutrient levels in a factorial microcosm experiment simulating detritus-based, headwater stream ecosystems. Contrary to theoretical expectations, diatoms and decomposers were able to coexist under both nutrient conditions. Under low-nutrient conditions, diatoms increased leaf litter decomposition rate by 20% compared to treatments where they were absent. No effect was observed under high-nutrient conditions. The increase in leaf litter mineralization rate induced a positive feedback on diatom densities. We attribute these results to the priming effect of labile C exudates from primary producers. The presence of diatoms in combination with fungal decomposers also promoted decomposer diversity and, under low-nutrient conditions, led to a significant decrease in leaf litter C:P ratio that could improve secondary production. Results from our microcosm experiment suggest new mechanisms by which primary producers may influence organic matter dynamics even in ecosystems where autochthonous primary production is low.

Mixotrophy in aquatic plants, an overlooked ability.

Aquatic Embryophytes play a key role in the proper functioning of aquatic ecosystems, where carbon (inorganic and organic forms) is pivotal in biogeochemical processes. There is growing awareness that mixotrophy, the direct use of exogenous organic carbon by autotrophs, is a widespread phenomenon and that it has emerged recurrently in the evolution of many autotrophic lineages. Despite living in an environment providing organic matter and presenting many favourable predispositions, aquatic plants from the Embryophytes, except carnivorous ones, have never been deeply investigated for mixotrophy. Here, we address the possibility that aquatic plants may exhibit mixotrophy, a prospect overlooked by research until now, and that this may be much more widespread than imagined under the conventional paradigm of plants considered as strict autotrophs.

Cutting-edge spectroscopy techniques highlight toxicity mechanisms of copper oxide nanoparticles in the aquatic plant Myriophyllum spicatum.

Copper oxide nanoparticles (CuO-NPs) have been increasingly released in aquatic ecosystems over the past decades as they are used in many applications. Cu toxicity to different organisms has already been highlighted in the literature, however toxicity mechanisms of the nanoparticulate form remain unclear. Here, we investigated the effect, transfer and localization of CuO-NPs compared to Cu salt on the aquatic plant Myriophyllum spicatum, an ecotoxicological model species with a pivotal role in freshwater ecosystems, to establish a clear mode of action. Plants were exposed to 0.5 mg/L Cu salt, 5 and 70 mg/L CuO-NPs during 96 h and 10 days. Several morphological and physiological endpoints were measured. Cu salt was found more toxic than CuO-NPs to plants based on all the measured endpoints despite a similar internal Cu concentration demonstrated via Cu mapping by micro particle-induced X-ray emission (µPIXE) coupled to Rutherford backscattering spectroscopy (RBS). Biomacromolecule composition investigated by FTIR converged between 70 mg/L CuO-NPs and Cu salt treatments after 10 days. This demonstrates that the difference of toxicity comes from a sudden massive Cu2+ addition from Cu salt similar to an acute exposure, versus a progressive leaching of Cu2+ from CuO-NPs representing a chronic exposure. Understanding NP toxicity mechanisms can help in the future conception of safer by design NPs and thus diminishing their impact on both the environment and humans.

Interactive effects of metals and carbon nanotubes in a microcosm agrosystem.

Agricultural soils are exposed to multiple contaminants through the use of agrochemicals or sewage sludge, introducing metals, nanomaterials and others. Among nanomaterials, carbon nanotubes (CNTs) are known for their large surface area and adsorption capabilities, possibly modifying other element behavior. However, to date, very little is known about the impacts of such interactions in agrosystems. In this study, we aimed at understanding the transfer and toxicity of contaminants (Cd, Pb, Zn and CNTs) in microcosms including native soil bacteria, earthworms and lettuce. After a 6 week exposure, no effect of the addition of CNTs to metal contaminated soils was detected on bacterial concentration or earthworm growth. However, in lettuce, an interactive effect between CNTs and metals was highlighted: in the soil containing the highest metal concentrations the addition of 0.1 mg kg-1 CNTs led to a biomass loss (-22%) and a flavonoid concentration increase (+27%). In parallel, the addition of CNTs led to differential impacts on elemental uptake in lettuce leaves possibly related to the soil organic matter content. For earthworms, the addition of 10 mg kg-1 CNTs resulted in an increased body elemental transfer in the soil with the higher organic matter content (Pb: + 34% and Zn: + 25%).

Honey bees cannot sense harmful concentrations of metal pollutants in food.

Whether animals can actively avoid food contaminated with harmful compounds through taste is key to assess their ecotoxicological risks. Here, we investigated the ability of honey bees to perceive and avoid food resources contaminated with common metal pollutants known to impair behaviour at low concentrations. In laboratory assays, bees did not discriminate food contaminated with arsenic, lead or zinc and ingested it readily, up to estimated doses of 929.1 µg g-1 As, 6.45 mg g-1 Pb and 72.46 mg g-1 Zn. A decrease of intake and appetitive responses indicating metal detection was only observed at the highest concentrations of lead (3.6 mM) and zinc (122.3 mM) through contact with the antennae and the proboscis. Electrophysiological analyses confirmed that only high concentrations of the three metals in a sucrose solution induced a consistently reduced neural response to sucrose in antennal taste receptors (As: >0.1 µM, Pb: >1 mM; Zn: >100 mM). Overall, cellular and behavioural responses did not provide evidence for specific mechanisms that would support selective detection of toxic metals (arsenic, lead), as compared to zinc, which has important biological functions. Our results thus show that honey bees can avoid metal pollutants in their food only at high concentrations unlikely to be encountered in the environment. By contrast, they appear to be unable to detect low, yet harmful, concentrations found in flowers. Metal pollution at trace levels is therefore a major threat for pollinators.

Mapping leaf metal content over industrial brownfields using airborne hyperspectral imaging and optimized vegetation indices.

Monitoring plant metal uptake is essential for assessing the ecological risks of contaminated sites. While traditional techniques used to achieve this are destructive, Visible Near-Infrared (VNIR) reflectance spectroscopy represents a good alternative to monitor pollution remotely. Based on previous work, this study proposes a methodology for mapping the content of several metals in leaves (Cr, Cu, Ni and Zn) under realistic field conditions and from airborne imaging. For this purpose, the reflectance of Rubus fruticosus L., a pioneer species of industrial brownfields, was linked to leaf metal contents using optimized normalized vegetation indices. High correlations were found between the vegetation indices exploiting pigment-related wavelengths and leaf metal contents (r ≤ - 0.76 for Cr, Cu and Ni, and r ≥ 0.87 for Zn). This allowed predicting the metal contents with good accuracy in the field and on the image, especially Cu and Zn (r ≥ 0.84 and RPD ≥ 2.06). The same indices were applied over the entire study site to map the metal contents at very high spatial resolution. This study demonstrates the potential of remote sensing for assessing metal uptake by plants, opening perspectives of application in risk assessment and phytoextraction monitoring in the context of trace metal pollution.

Disentangling the direct and indirect effects of agricultural runoff on freshwater ecosystems subject to global warming: A microcosm study.

Aquatic ecosystems are exposed to multiple stressors such as agricultural run-off (ARO) and climate-change related increase of temperature. We aimed to determine how ARO and the frequency of its input can affect shallow lake ecosystems through direct and indirect effects on primary producers and primary consumers, and whether warming can mitigate or reinforce the impact of ARO. We performed a set of microcosm experiments simulating ARO using a cocktail of three organic pesticides (terbuthylazine, tebuconazole, pirimicarb), copper and nitrate. Two experiments were performed to determine the direct effect of ARO on primary producers (submerged macrophytes, periphyton and phytoplankton) and on the grazing snail Lymnaea stagnalis, respectively. Three different ARO concentrations added as single doses or as multiple pulses at two different temperatures (22°C and 26°C) were applied. In a third experiment, primary producers and consumers were exposed together to allow trophic interactions. When functional groups were exposed alone, ARO had a direct positive effect on phytoplankton and a strong negative effect on L. stagnalis. When exposed together, primary producer responses were contrasting, as the negative effect of ARO on grazers led to an indirect positive effect on periphyton. Periphyton in turn exerted a strong control on phytoplankton, leading to an indirect negative effect of ARO on phytoplankton. Macrophytes showed little response to the stressors. Multiple pulse exposure increased the effect of ARO on L. stagnalis and periphyton when compared with the same quantity of ARO added as a single dose. The increase in temperature had only limited effects. Our results highlight the importance of indirect effects of stressors, here mediated by grazers and periphyton, and the frequency of the ARO input in aquatic ecosystems.

Monitoring oil contamination in vegetated areas with optical remote sensing: A comprehensive review.

The monitoring of soil contamination deriving from oil and gas industry remains difficult in vegetated areas. Over the last decade, optical remote sensing has proved helpful for this purpose. By tracking alterations in vegetation biochemistry through its optical properties, multi- and hyperspectral remote sensing allow detecting and quantifying crude oil and petroleum products leaked following accidental leakages or bad cessation practices. Recent advances in this field have led to the development of various methods that can be applied either in the field using portable spectroradiometers or at large scale on airborne and satellite images. Experiments carried out under controlled conditions have largely contributed to identifying the most important factors influencing the detection of oil (plant species, mixture composition, etc.). In a perspective of operational use, an important effort is still required to make optical remote sensing a reliable tool for oil and gas companies. The current methods used on imagery should extend their scope to a wide range of contexts and their application to upcoming satellite-embedded hyperspectral sensors should be considered in future studies.

Submerged macrophyte assessment in rivers: An automatic mapping method using Pléiades imagery.

Submerged macrophyte monitoring is a major concern for hydrosystem management, particularly for understanding and preventing the potential impacts of global change on ecological functions and services. Macrophyte distribution assessments in rivers are still primarily realized using field monitoring or manual photo-interpretation of aerial images. Considering the lack of applications in fluvial environments, developing operational, low-cost and less time-consuming tools able to automatically map and monitor submerged macrophyte distribution is therefore crucial to support effective management programs. In this study, the suitability of very fine-scale resolution (50 cm) multispectral Pléiades satellite imagery to estimate submerged macrophyte cover, at the scale of a 1 km river section, was investigated. The performance of nonparametric regression methods (based on two reliable and well-known machine learning algorithms for remote sensing applications, Random Forest and Support Vector Regression) were compared for several spectral datasets, testing the relevance of 4 spectral bands (red, green, blue and near-infrared) and two vegetation indices (the Normalized Difference Vegetation Index, NDVI, and the Green-Red Vegetation Index, GRVI), and for several field sampling configurations. Both machine learning algorithms applied to a Pléiades image were able to reasonably well predict macrophyte cover in river ecosystems with promising performance metrics (R² above 0.7 and RMSE around 20%). The Random Forest algorithm combined to the 4 spectral bands from Pléiades image was the most efficient, particularly for extreme cover values (0% and 100%). Our study also demonstrated that a larger number of fine-scale field sampling entities clearly involved better cover predictions than a smaller number of larger sampling entities.

Genotypes of the aquatic plant Myriophyllum spicatum with different growth strategies show contrasting sensitivities to copper contamination.

Genotypic variability has been considered for years as a key attribute in species adaptation to new environments. It has been extensively studied in a context of chemical resistance, but remains poorly studied in response to chemical exposure in a context of global change. As aquatic ecosystems are particularly affected by environmental changes, we aimed to study how genotypic variability could inflect the sensitivity of aquatic plants to chemicals. Seven genotypes of Myriophyllum spicatum were exposed to three copper concentrations at 0, 0.15 and 0.5 mg/L. The sensitivity of the different genotypes was assessed through several endpoints such as relative growth rate (RGR) and morphological traits, as well as physiological markers, such as plant biomacromolecular composition. Our results showed that genotypes exhibited significant differences in their life-history traits in absence of chemical contamination. Some trait syndromes were observed, and three growth strategies were identified: (1) biomass production and main shoot elongation, (2) dry matter storage with denser whorls to promote resource conservation and (3) lateral shoot production. An up to eightfold difference in sensitivity for growth-related endpoints was observed among genotypes. Differences in sensitivity were partly attributed to morphological life-history traits. Our results confirm that genotypic variability can significantly affect M. spicatum sensitivity to Cu, and may influence the outcomes of laboratory testing based on the study of one single genotype. We recommend including genotypic variation as an assessment factor in ecological risk assessment and to study this source of variability more in depth as a possible driver of ecosystem resilience.