HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Trace metals associated with nanoparticles are known to possess reactivities that are different from their larger-size counterparts. However, the relative importance of small relative to large particles for the overall distribution and biouptake of these metals is not as well studied in complex environmental systems. Here, we have examined differences in the long term fate and transport of ceria (CeO) nanoparticles of two different sizes (3.8 vs 185 nm), dosed weekly to freshwater wetland mesocosms over 9 months. While the majority of CeO particles were detected in soils and sediments at the end of nine months, there were significant differences observed in fate, distribution, and transport mechanisms between the two materials. Small nanoparticles were removed from the water column primarily through heteroaggregation with suspended solids and plants, while large nanoparticles were removed primarily by sedimentation. A greater fraction of small particles remained in the upper floc layers of sediment relative to the large particles (31% vs 7%). Cerium from the small particles were also significantly more bioavailable to aquatic plants (2% vs 0.5%), snails (44 vs 2.6 ng), and insects (8 vs 0.07 μg). Small CeO particles were also significantly reduced from Ce(IV) to Ce(III), while aquatic sediments were a sink for untransformed large nanoparticles. These results demonstrate that trace metals originating from nanoscale materials have much greater potential than their larger counterparts to distribute throughout multiple compartments of a complex aquatic ecosystem and contribute to the overall bioavailable pool of the metal for biouptake and trophic transfer.

Despite the rapid rise in diversity and quantities of engineered nanomaterials produced, the impacts of these emerging contaminants on the structure and function of ecosystems have received little attention from ecologists. Moreover, little is known about how manufactured nanomaterials may interact with nutrient pollution in altering ecosystem productivity, despite the recognition that eutrophication is the primary water quality issue in freshwater ecosystems worldwide. In this study, we asked two main questions: (1) To what extent do manufactured nanoparticles affect the biomass and productivity of primary producers in wetland ecosystems? (2) How are these impacts mediated by nutrient pollution? To address these questions, we examined the impacts of a citrate-coated gold nanoparticle (AuNPs) and of a commercial pesticide containing Cu(OH) nanoparticles (CuNPs) on aquatic primary producers under both ambient and enriched nutrient conditions. Wetland mesocosms were exposed repeatedly with low concentrations of nanoparticles and nutrients over the course of a 9-month experiment in an effort to replicate realistic field exposure scenarios. In the absence of nutrient enrichment, there were no persistent effects of AuNPs or CuNPs on primary producers or ecosystem productivity. However, when combined with nutrient enrichment, both NPs intensified eutrophication. When either of these NPs were added in combination with nutrients, algal blooms persisted for >50 d longer than in the nutrient-only treatment. In the AuNP treatment, this shift from clear waters to turbid waters led to large declines in both macrophyte growth and rates of ecosystem gross primary productivity (average reduction of 52% ± 6% and 92% ± 5%, respectively) during the summer. Our results suggest that nutrient status greatly influences the ecosystem-scale impact of two emerging contaminants and that synthetic chemicals may be playing an under-appreciated role in the global trends of increasing eutrophication. We provide evidence here that chronic exposure to Au and Cu(OH) nanoparticles at low concentrations can intensify eutrophication of wetlands and promote the occurrence of algal blooms.

Summary Trait‐based approaches offer a way to predict changes in community structure along environmental gradients using measurable properties of individuals. Promoted as being generalizable across systems, trait‐based approaches benefit from information about the environmental drivers of trait variation, how they interact and how they change with scale. However, for most diverse, natural communities, it is largely unknown whether the relationships between leaf‐level traits and interacting environmental drivers (e.g. fire, water availability) are influenced by the scale of trait aggregation. We show that landscape‐level differences in community composition in a diverse, fire‐dependent pine savanna are explained by a small subset of species groups that are strongly correlated with soil moisture and elevation, but are insensitive to the time since the last fire. We used a trait‐based approach to show that significant variation in the community‐weighted mean (CWM) of specific leaf area (SLA) and leaf dry matter content (LDMC), two traits known to drive community structure and function, was explained by a small set of factors including the time since the last fire, soil moisture, precipitation and Shannon diversity. We show that statistical inference about the environmental drivers of community traits is radically altered when using CWMs computed with landscape‐level rather than plot‐level means, even over modest spatial scales. Synthesis: Environmental drivers of community composition across the landscape differed from those explaining trait composition. CWM traits were strongly influenced by interactions between drivers. Fire, in particular, strongly mediated the effect of other environmental variables on LDMC, showing that strong environmental gradients cannot be considered independently when assessing their effects on functional traits. The importance of environmental variables such as fire was lost when using landscape‐level trait means, highlighting the importance of local trait variation. This suggests caution when using traits from distant populations to make inferences about local processes, especially across strong gradients.