Occurrence of arsenic species in algae and freshwater plants of an extreme arid region in northern Chile, the Loa River Basin

This study reports data on arsenic speciation in two green algae species (Cladophora sp. and Chara sp.) and in five aquatic plants (Azolla sp., Myriophyllum aquaticum, Phylloscirpus cf. desserticola, Potamogeton pectinatus, Ruppia filifolia and Zannichellia palustris) from the Loa River Basin in the Atacama Desert (northern Chile). Arsenic content was measured by Mass Spectrometry coupled with Inductively Coupled Plasma (ICP-MS), after acidic digestion. Liquid Chromatography coupled to ICP-MS was used for arsenic speciation, using both anionic and cationic chromatographic exchange systems. Inorganic arsenic compounds were the main arsenic species measured in all samples. The main arsenic species in the extracts of freshwater algae and plants were arsenite and arsenate, whereas glycerol-arsenosugar (gly-sug), dimethylarsinic acid (DMA) and methylarsonic acid (MA) were present only as minor constituents. Of the samples studied, algae species accumulated more arsenic than aquatic plants. Total arsenic content ranged from 182 to 11,100 and from 20 to 248 mg As kg-1 (d.w.) in algae and freshwater plants, respectively. In comparison with As concentration in water samples, there was hyper-accumulation (>0.1% d.w.) in Cladophora sp

Kinetics of arsenite removal by halobacteria from a highland Andean Chilean Salar

BACKGROUND: The purpose of this study was to identify arsenite-oxidizing halobacteria in samples obtained from Salar de Punta Negra, II Region of Chile. Seven bacterial isolates, numbered as isolates I to VII, grown in a culture medium with 100 ppm as NaAsO(2) (As (III)) were tested. Bacterial growth kinetics and the percent of arsenite removal (PAR) were performed simultaneously with the detection of an arsenite oxidase enzyme through Dot Blot analysis. RESULTS: An arsenite oxidase enzyme was detected in all isolates, expressed constitutively after 10 generations grown in the absence of As (III). Bacterial growth kinetics and corresponding PAR values showed significant fluctuations over time. PARs close to 100% were shown by isolates V, VI, and VII, at different times of the bacterial growth phase; while isolate II showed PAR values around 40%, remaining constant over time. CONCLUSION: Halobacteria from Salar de Punta Negra showed promising properties as arsenite removers under control conditions, incubation time being a critical parameter

Occurrence of Arsenic Species in Algae and Freshwater Plants of an Extreme Arid 1 Region in Northern Chile, the Loa River Basin 2

ABSTRACT 11 This study reports data on arsenic speciation in two green algae species (Cladophora sp. and 12 Chara sp.) and in five aquatic plants (Azolla sp., Myriophyllum aquaticum, Phylloscirpus cf. 30 -One sample (Cladophora sp.) presented hyperaccumulation of As (11,000 mg As kg -

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyze hypothesis generation

A unified conceptual framework for river corridors requires synthesis of diverse site-, method- and discipline-specific findings. The river research community has developed a substantial body of observations and process-specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site-, scale-, and mechanism-specific observations begins the process of synthesis. Machine learning is particularly well-suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a 5th order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively-generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favor the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Occurrence of arsenic species in algae and freshwater plants of an extreme arid region in northern Chile, the Loa River Basin

This study reports data on arsenic speciation in two green algae species (Cladophora sp. and Chara sp.) and in five aquatic plants (Azolla sp., Myriophyllum aquaticum, Phylloscirpus cf. desserticola, Potamogeton pectinatus, Ruppia filifolia and Zannichellia palustris) from the Loa River Basin in the Atacama Desert (northern Chile). Arsenic content was measured by Mass Spectrometry coupled with Inductively Coupled Plasma (ICP-MS), after acidic digestion. Liquid Chromatography coupled to ICP-MS was used for arsenic speciation, using both anionic and cationic chromatographic exchange systems. Inorganic arsenic compounds were the main arsenic species measured in all samples. The main arsenic species in the extracts of freshwater algae and plants were arsenite and arsenate, whereas glycerol-arsenosugar (gly-sug), dimethylarsinic acid (DMA) and methylarsonic acid (MA) were present only as minor constituents. Of the samples studied, algae species accumulated more arsenic than aquatic plants. Total arsenic content ranged from 182 to 11,100 and from 20 to 248 mg As kg-1 (d.w.) in algae and freshwater plants, respectively. In comparison with As concentration in water samples, there was hyper-accumulation (>0.1% d.w.) in Cladophora sp