Effects of zinc on leaf decomposition by fungi in streams : studies in microcosms

The effect of zinc on leaf decomposition by aquatic fungi was studied in microcosms. Alder leaf disks were precolonized for 15 days at the source of the Este River, and exposed to different zinc concentrations during 25 days. Leaf mass loss, fungal biomass (based on ergosterol concentration), fungal production (rates of [1-14C]acetate incorporation into ergosterol), sporulation rates and species richness of aquatic hyphomycetes were determined. At the source of the Este River decomposition of alder leaves was fast and 50% of the initial mass was lost in 25 days. A total of 18 aquatic hyphomycete species were recorded during 42 days of leaf immersion. Articulospora tetracladia was the dominant species, followed by Lunulospora curvula and two unidentified species with sigmoid conidia. Cluster analysis suggested that zinc concentration and exposure time affected the structure of aquatic hyphomycete assemblages, even though richness had not been severely affected. Both zinc concentration and exposure time significantly affected leaf mass loss, fungal production and sporulation, but not fungal biomass. Zinc exposure reduced leaf mass loss, inhibited fungal production and affected fungal reproduction by either stimulating or inhibiting sporulation rates. The results of this work suggested zinc pollution might depress leaf decomposition in streams due to changes in the structure and activity of aquatic fungi.Fundação para a Ciência e a Tecnologia (FCT) – Programa Operacional “Ciência, Tecnologia, Inovação” (POCTI) - POCTI/34024/BSE/2000

When Learners Surpass Their Models: Mathematical Modeling of Learning from an Inconsistent Source

It has been reported in the literature that both adults and children can, to a different degree, modify and regularize the often-inconsistent linguistic input they receive. We present a new algorithm to model and investigate the learning process of a learner mastering a set of (grammatical or lexical) forms from an inconsistent source. The algorithm is related to reinforcement learning and drift-diffusion models of decision making, and possesses several psychologically relevant properties such as fidelity, robustness, discounting, and computational simplicity. It demonstrates how a learner can successfully learn from or even surpass its imperfect source. We use the data collected by Singleton and Newport (Cognit Psychol 49(4):370-407, 2004) on the performance of a 7-year-boy Simon, who mastered the American Sign Language (ASL) by learning it from his parents, both of whom were imperfect speakers of ASL. We show that the algorithm possesses a frequency boosting property, whereby the frequency of the most common form of the source is increased by the learner. We also explain several key features of Simon's ASL. © 2014 Society for Mathematical Biology

Breakdown into nanoscale of graphene oxide: Confined hot spot atomic reduction and fragmentation

Nano-graphene oxide (nano-GO) is a new class of carbon based materials being proposed for biomedical applications due to its small size, intrinsic optical properties, large specific surface area, and easy to functionalize. To fully exploit nano-GO properties, a reproducible method for its production is of utmost importance. Herein we report, the study of the sequential fracture of GO sheets onto nano-GO with controllable lateral width, by a simple, and reproducible method based on a mechanism that we describe as a confined hot spot atomic fragmentation/reduction of GO promoted by ultrasonication. The chemical and structural changes on GO structure during the breakage were monitored by XPS, FTIR, Raman and HRTEM. We found that GO sheets starts breaking from the defects region and in a second phase through the disruption of carbon bonds while still maintaining crystalline carbon domains. The breaking of GO is accompanied by its own reduction, essentially by the elimination of carboxylic and carbonyl functional groups. Photoluminescence and photothermal studies using this nano-GO are also presented highlighting the potential of this nanomaterial as a unique imaging/therapy platform

Resistance, resilience, and patchiness of invertebrate assemblages in native tussock and pasture streams in New Zealand after a hydrological disturbance

We generated hydrological disturbances to investigate the role of disturbance in New Zealand streams in two land uses: native tussock grasslands and exotic pasture catchments. We tested whether physical differences in streambed structure confer higher resistance and resilience in tussock sites than in pasture sites. We also investigated changes in patchiness (at spatial scales larger than 0.06 m(2)) caused by the disturbance. Invertebrate abundance decreased immediately after the disturbance. Species density remained unchanged, but species richness (rarefied) increased. Eight days after the disturbance event, abundance and species richness (rarefied) were similar to those of samples collected immediately before the disturbance. Resistance (measured as decrease in abundance) and resilience (measured as recovery within 8 days) did not differ significantly between the land uses. Patchiness increased in both stream types immediately after the disturbance but decreased to predisturbance levels after 8 days. Disturbance caused a redistribution of individuals among patches, some receiving individuals, others losing individuals, and some remaining unchanged. Our results conform with predictions of the patch dynamics concept and are consistent with results of studies of natural disturbance caused by floods.60673173

Effects of anthropogenic heavy metal contamination on litter decomposition in streams – A meta-analysis

Many streams worldwide are affected by heavy metal contamination, mostly due to past and present mining activities. Here we present a meta-analysis of 38 studies (reporting 133 cases) published between 1978 and 2014 that reported the effects of heavy metal contamination on the decomposition of terrestrial litter in running waters. Overall, heavy metal contamination significantly inhibited litter decomposition. The effect was stronger for laboratory than for field studies, likely due to better control of confounding variables in the former, antagonistic interactions between metals and other environmental variables in the latter or differences in metal identity and concentration between studies. For laboratory studies, only copper + zinc mixtures significantly inhibited litter decomposition, while no significant effects were found for silver, aluminum, cadmium or zinc considered individually. For field studies, coal and metal mine drainage strongly inhibited litter decomposition, while drainage from motorways had no significant effects. The effect of coal mine drainage did not depend on drainage pH. Coal mine drainage negatively affected leaf litter decomposition independently of leaf litter identity; no significant effect was found for wood decomposition, but sample size was low. Considering metal mine drainage, arsenic mines had a stronger negative effect on leaf litter decomposition than gold or pyrite mines. Metal mine drainage significantly inhibited leaf litter decomposition driven by both microbes and invertebrates, independently of leaf litter identity; no significant effect was found for microbially driven decomposition, but sample size was low. Overall, mine drainage negatively affects leaf litter decomposition, likely through negative effects on invertebrates.We thank many authors for providing information that was not available in the primary studies as well as two anonymous reviewers for the comments made on an earlier version of the manuscript. This study was partially supported by the Portuguese Foundation for Science and Technology (FCT) through the strategic project UID/MAR/04292/2013 granted to MARE. Financial support given by the FCT to VF (SFRH/BPD/76482/2011, program POPH/FSE; IF/00129/2014) and SD (SFRH/BPD/47574/2008, SFRH/BPD/109842/2015) is gratefully acknowledged.info:eu-repo/semantics/publishedVersio