Showing papers by "Swiss Federal Institute of Aquatic Science and Technology published in 2018"

Function and functional redundancy in microbial systems

Abstract: Microbial communities often exhibit incredible taxonomic diversity, raising questions regarding the mechanisms enabling species coexistence and the role of this diversity in community functioning. On the one hand, many coexisting but taxonomically distinct microorganisms can encode the same energy-yielding metabolic functions, and this functional redundancy contrasts with the expectation that species should occupy distinct metabolic niches. On the other hand, the identity of taxa encoding each function can vary substantially across space or time with little effect on the function, and this taxonomic variability is frequently thought to result from ecological drift between equivalent organisms. Here, we synthesize the powerful paradigm emerging from these two patterns, connecting the roles of function, functional redundancy and taxonomy in microbial systems. We conclude that both patterns are unlikely to be the result of ecological drift, but are inevitable emergent properties of open microbial systems resulting mainly from biotic interactions and environmental and spatial processes.

A critical evaluation of nanopesticides and nanofertilizers against their conventional analogues.

Abstract: Among a wide range of possible applications of nanotechnology in agriculture, there has been a particular interest in developing novel nanoagrochemicals. While some concerns have been expressed regarding altered risk profile of the new products, many foresee a great potential to support the necessary increase in global food production in a sustainable way. A critical evaluation of nanoagrochemicals against conventional analogues is essential to assess the associated benefits and risks. In this assessment, recent literature was critically analysed to determine the extent to which nanoagrochemicals differ from conventional products. Our analysis was based on 78 published papers and shows that median gain in efficacy relative to conventional products is about 20-30%. Environmental fate of agrochemicals can be altered by nanoformulations, but changes may not necessarily translate in a reduction of the environmental impact. Many studies lacked nano-specific quality assurance and adequate controls. Currently, there is no comprehensive study in the literature that evaluates efficacy and environmental impact of nanoagrochemicals under field conditions. This is a crucial knowledge gap and more work will thus be necessary for a sound evaluation of the benefits and new risks that nanoagrochemicals represent relative to existing products.

Plant functional trait change across a warming tundra biome

Abstract: The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

Nanomaterials in the environment: behavior, fate, bioavailability, and effects—an updated review

Abstract: The present review covers developments in studies of nanomaterials (NMs) in the environment since our much cited review in 2008. We discuss novel insights into fate and behavior, metrology, transformations, bioavailability, toxicity mechanisms, and environmental impacts, with a focus on terrestrial and aquatic systems. Overall, the findings were that: 1) despite substantial developments, critical gaps remain, in large part due to the lack of analytical, modeling, and field capabilities, and also due to the breadth and complexity of the area; 2) a key knowledge gap is the lack of data on environmental concentrations and dosimetry generally; 3) substantial evidence shows that there are nanospecific effects (different from the effects of both ions and larger particles) on the environment in terms of fate, bioavailability, and toxicity, but this is not consistent for all NMs, species, and relevant processes; 4) a paradigm is emerging that NMs are less toxic than equivalent dissolved materials but more toxic than the corresponding bulk materials; and 5) translation of incompletely understood science into regulation and policy continues to be challenging. There is a developing consensus that NMs may pose a relatively low environmental risk, but because of uncertainty and lack of data in many areas, definitive conclusions cannot be drawn. In addition, this emerging consensus will likely change rapidly with qualitative changes in the technology and increased future discharges. Environ Toxicol Chem 2018;37:2029-2063. © 2018 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Oxidation Processes in Water Treatment: Are We on Track?

Abstract: Chemical oxidants have been applied in water treatment for more than a century, first as disinfectants and later to abate inorganic and organic contaminants. The challenge of oxidative abatement of organic micropollutants is the formation of transformation products with unknown (eco)toxicological consequences. Four aspects need to be considered for oxidative micropollutant abatement: (i) Reaction kinetics, controlling the efficiency of the process, (ii) mechanisms of transformation product formation, (iii) extent of formation of disinfection byproducts from the matrix, (iv) oxidation induced biological effects, resulting from transformation products and/or disinfection byproducts. It is impossible to test all the thousands of organic micropollutants in the urban water cycle experimentally to assess potential adverse outcomes of an oxidation. Rather, we need multidisciplinary and automated knowledge-based systems, which couple predictions of kinetics, transformation and disinfection byproducts and their to...

Cryptic species as a window into the paradigm shift of the species concept

Abstract: The species concept is the cornerstone of biodiversity science, and any paradigm shift in the delimitation of species affects many research fields. Many biologists now are embracing a new "species" paradigm as separately evolving populations using different delimitation criteria. Individual criteria can emerge during different periods of speciation; some may never evolve. As such, a paradigm shift in the species concept relates to this inherent heterogeneity in the speciation process and species category-which is fundamentally overlooked in biodiversity research. Cryptic species fall within this paradigm shift: they are continuously being reported from diverse animal phyla but are poorly considered in current tests of ecological and evolutionary theory. The aim of this review is to integrate cryptic species in biodiversity science. In the first section, we address that the absence of morphological diversification is an evolutionary phenomenon, a "process" counterpart to the long-studied mechanisms of morphological diversification. In the next section regarding taxonomy, we show that molecular delimitation of cryptic species is heavily biased towards distance-based methods. We also stress the importance of formally naming of cryptic species for better integration into research fields that use species as units of analysis. Finally, we show that incorporating cryptic species leads to novel insights regarding biodiversity patterns and processes, including large-scale biodiversity assessments, geographic variation in species distribution and species coexistence. It is time for incorporating multicriteria species approaches aiming to understand speciation across space and taxa, thus allowing integration into biodiversity conservation while accommodating for species uncertainty.

Risks, Release and Concentrations of Engineered Nanomaterial in the Environment.

Abstract: For frequently used engineered nanomaterials (ENMs) CeO2-, SiO2-, and Ag, past, current, and future use and environmental release are investigated. Considering an extended period (1950 to 2050), we assess ENMs released through commercial activity as well as found in natural and technical settings. Temporal dynamics, including shifts in release due to ENM product application, stock (delayed use), and subsequent end-of-life product treatment were taken into account. We distinguish predicted concentrations originating in ENM use phase and those originating from end-of-life release. Furthermore, we compare Ag- and CeO2-ENM predictions with existing measurements. The correlations and limitations of the model, and the analytic validity of our approach are discussed in the context of massive use of assumptive model data and high uncertainty on the colloidal material captured by the measurements. Predictions for freshwater CeO2-ENMs range from 1 pg/l (2017) to a few hundred ng/l (2050). Relative to CeO2, the SiO2-ENMs estimates are approximately 1,000 times higher, and those for Ag-ENMs 10 times lower. For most environmental compartments, ENM pose relatively low risk; however, organisms residing near ENM ‘point sources’ (e.g., production plant outfalls and waste treatment plants), which are not considered in the present work, may be at increased risk.

The role of dispersal in river network metacommunities: Patterns, processes, and pathways

Abstract: River networks are hierarchical dendritic habitats embedded within the terrestrial landscape, with varying connectivity between sites depending on their positions along the network. This physical organisation influences the dispersal of organisms, which ultimately affects metacommunity dynamics and biodiversity patterns. We provide a conceptual synthesis of the role of river networks in structuring metacommunities in relation to dispersal processes in riverine ecosystems. We explore where the river network best explains observed metacommunity structure compared to other measurements of physical connectivity. We mostly focus on invertebrates, but also consider other taxonomic groups, including microbes, fishes, plants, and amphibians. Synthesising studies that compared multiple spatial distance metrics, we found that the importance of the river network itself in explaining metacommunity patterns depended on a variety of factors, including dispersal mode (aquatic versus aerial versus terrestrial) and landscape type (arid versus mesic), as well as location-specific factors, such as network connectivity, land use, topographic heterogeneity, and biotic interactions. The river network appears to be less important for strong aerial dispersers and insects in arid systems than for other groups and biomes, but there is considerable variability. Borrowing from other literature, particularly landscape genetics, we developed a conceptual model that predicts that the explanatory power of the river network peaks in mesic systems for obligate aquatic dispersers. We propose directions of future avenues of research, including the use of manipulative field and laboratory experiments that test metacommunity theory in river networks. While field and laboratory experiments have their own benefits and drawbacks (e.g. reality, control, cost), both are powerful approaches for understanding the mechanisms structuring metacommunities, by teasing apart dispersal and niche-related factors. Finally, improving our knowledge of dispersal in river networks will benefit from expanding the breadth of cost-distance modelling to better infer dispersal from observational data; an improved understanding of life-history strategies rather than relying on independent traits; exploring individual-level variation in dispersal through detailed genetic studies; detailed studies on fine-scale environmental (e.g. daily hydrology) and organismal spatiotemporal variability; and synthesising comparative, experimental, and theoretical work. Expanding in these areas will help to push the current state of the science from a largely pattern-detection mode into a new phase of more mechanistically driven research.

Biodegradation of synthetic polymers in soils: Tracking carbon into CO2 and microbial biomass.

Abstract: Plastic materials are widely used in agricultural applications to achieve food security for the growing world population The use of biodegradable instead of nonbiodegradable polymers in single-use agricultural applications, including plastic mulching, promises to reduce plastic accumulation in the environment We present a novel approach that allows tracking of carbon from biodegradable polymers into CO2 and microbial biomass The approach is based on 13C-labeled polymers and on isotope-specific analytical methods, including nanoscale secondary ion mass spectrometry (NanoSIMS) Our results unequivocally demonstrate the biodegradability of poly(butylene adipate-co-terephthalate) (PBAT), an important polyester used in agriculture, in soil Carbon from each monomer unit of PBAT was used by soil microorganisms, including filamentous fungi, to gain energy and to form biomass This work advances both our conceptual understanding of polymer biodegradation and the methodological capabilities to assess this process in natural and engineered environments

Biodiversity increases and decreases ecosystem stability

Abstract: Losses and gains in species diversity affect ecological stability1–7 and the sustainability of ecosystem functions and services8–13. Experiments and models have revealed positive, negative and no effects of diversity on individual components of stability, such as temporal variability, resistance and resilience2,3,6,11,12,14. How these stability components covary remains poorly understood15. Similarly, the effects of diversity on overall ecosystem stability16, which is conceptually akin to ecosystem multifunctionality17,18, remain unknown. Here we studied communities of aquatic ciliates to understand how temporal variability, resistance and overall ecosystem stability responded to diversity (that is, species richness) in a large experiment involving 690 micro-ecosystems sampled 19 times over 40 days, resulting in 12,939 samplings. Species richness increased temporal stability but decreased resistance to warming. Thus, two stability components covaried negatively along the diversity gradient. Previous biodiversity manipulation studies rarely reported such negative covariation despite general predictions of the negative effects of diversity on individual stability components3. Integrating our findings with the ecosystem multifunctionality concept revealed hump- and U-shaped effects of diversity on overall ecosystem stability. That is, biodiversity can increase overall ecosystem stability when biodiversity is low, and decrease it when biodiversity is high, or the opposite with a U-shaped relationship. The effects of diversity on ecosystem multifunctionality would also be hump- or U-shaped if diversity had positive effects on some functions and negative effects on others. Linking the ecosystem multifunctionality concept and ecosystem stability can transform the perceived effects of diversity on ecological stability and may help to translate this science into policy-relevant information. Species richness was found to increase temporal stability but decrease resistance to warming in an experiment involving 690 micro-ecosystems consisting of 1 to 6 species of bacterivorous ciliates that were sampled over 40 days.

BioTIME: A database of biodiversity time series for the Anthropocene

Abstract: Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene.Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record.Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)).Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year.Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.

Environmental effects of ozone depletion, UV radiation and interactions with climate change: UNEP Environmental Effects Assessment Panel, update 2017

Abstract: This assessment, by the United Nations Environment Programme (UNEP) Environmental Effects Assessment Panel (EEAP), one of three Panels informing the Parties to the Montreal Protocol, provides an update, since our previous extensive assessment (Photochem. Photobiol. Sci., 2019, 18, 595-828), of recent findings of current and projected interactive environmental effects of ultraviolet (UV) radiation, stratospheric ozone, and climate change. These effects include those on human health, air quality, terrestrial and aquatic ecosystems, biogeochemical cycles, and materials used in construction and other services. The present update evaluates further evidence of the consequences of human activity on climate change that are altering the exposure of organisms and ecosystems to UV radiation. This in turn reveals the interactive effects of many climate change factors with UV radiation that have implications for the atmosphere, feedbacks, contaminant fate and transport, organismal responses, and many outdoor materials including plastics, wood, and fabrics. The universal ratification of the Montreal Protocol, signed by 197 countries, has led to the regulation and phase-out of chemicals that deplete the stratospheric ozone layer. Although this treaty has had unprecedented success in protecting the ozone layer, and hence all life on Earth from damaging UV radiation, it is also making a substantial contribution to reducing climate warming because many of the chemicals under this treaty are greenhouse gases.

Genetics of Dispersal

Abstract: Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences. Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal-related phenotypes or evidence for the micro-evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment-dependent. By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non-additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non-equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context-dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

Comparing species interaction networks along environmental gradients.

Abstract: Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients.

Emerging pollutants in the EU: 10 years of NORMAN in support of environmental policies and regulations

Abstract: In 2005, the European Commission funded the NORMAN project to promote a permanent network of reference laboratories and research centers, including academia, industry, standardization bodies, and NGOs. Since then, NORMAN has (i) facilitated a more rapid and wide-scope exchange of data on the occurrence and effects of contaminants of emerging concern (CECs), (ii) improved data quality and comparability via validation and harmonization of common sampling and measurement methods (chemical and biological), (iii) provided more transparent information and monitoring data on CECs, and (iv) established an independent and competent forum for the technical/scientific debate on issues related to emerging substances. NORMAN plays a significant role as an independent organization at the interface between science and policy, with the advantage of speaking to the European Commission and other public institutions with the “bigger voice” of more than 70 members from 20 countries. This article provides a summary of the first 10 years of the NORMAN network. It takes stock of the work done so far and outlines NORMAN’s vision for a Europe-wide collaboration on CECs and sustainable links from research to policy-making. It contains an overview of the state of play in prioritizing and monitoring emerging substances with reference to several innovative technologies and monitoring approaches. It provides the point of view of the NORMAN network on a burning issue—the regulation of CECs—and presents the positions of various stakeholders in the field (DG ENV, EEA, ECHA, and national agencies) who participated in the NORMAN workshop in October 2016. The main messages and conclusions from the round table discussions are briefly presented.

An ecotoxicological view on neurotoxicity assessment

Abstract: The numbers of potential neurotoxicants in the environment are raising and pose a great risk for humans and the environment. Currently neurotoxicity assessment is mostly performed to predict and prevent harm to human populations. Despite all the efforts invested in the last years in developing novel in vitro or in silico test systems, in vivo tests with rodents are still the only accepted test for neurotoxicity risk assessment in Europe. Despite an increasing number of reports of species showing altered behaviour, neurotoxicity assessment for species in the environment is not required and therefore mostly not performed. Considering the increasing numbers of environmental contaminants with potential neurotoxic potential, eco-neurotoxicity should be also considered in risk assessment. In order to do so novel test systems are needed that can cope with species differences within ecosystems. In the field, online-biomonitoring systems using behavioural information could be used to detect neurotoxic effects and effect-directed analyses could be applied to identify the neurotoxicants causing the effect. Additionally, toxic pressure calculations in combination with mixture modelling could use environmental chemical monitoring data to predict adverse effects and prioritize pollutants for laboratory testing. Cheminformatics based on computational toxicological data from in vitro and in vivo studies could help to identify potential neurotoxicants. An array of in vitro assays covering different modes of action could be applied to screen compounds for neurotoxicity. The selection of in vitro assays could be guided by AOPs relevant for eco-neurotoxicity. In order to be able to perform risk assessment for eco-neurotoxicity, methods need to focus on the most sensitive species in an ecosystem. A test battery using species from different trophic levels might be the best approach. To implement eco-neurotoxicity assessment into European risk assessment, cheminformatics and in vitro screening tests could be used as first approach to identify eco-neurotoxic pollutants. In a second step, a small species test battery could be applied to assess the risks of ecosystems.

Keeping global warming within 1.5 °C constrains emergence of aridification

Abstract: Aridity—the ratio of atmospheric water supply (precipitation; P) to demand (potential evapotranspiration; PET)—is projected to decrease (that is, areas will become drier) as a consequence of anthropogenic climate change, exacerbating land degradation and desertification 1–6 . However, the timing of significant aridification relative to natural variability—defined here as the time of emergence for aridification (ToEA)—is unknown, despite its importance in designing and implementing mitigation policies 7–10 . Here we estimate ToEA from projections of 27 global climate models (GCMs) under representative concentration pathways (RCPs) RCP4.5 and RCP8.5, and in doing so, identify where emergence occurs before global mean warming reaches 1.5 °C and 2 °C above the pre-industrial level. On the basis of the ensemble median ToEA for each grid cell, aridification emerges over 32% (RCP4.5) and 24% (RCP8.5) of the total land surface before the ensemble median of global mean temperature change reaches 2 °C in each scenario. Moreover, ToEA is avoided in about two-thirds of the above regions if the maximum global warming level is limited to 1.5 °C. Early action for accomplishing the 1.5 °C temperature goal can therefore markedly reduce the likelihood that large regions will face substantial aridification and related impacts. Arid regions are projected to expand in the future. An ensemble of climate model simulations reveals that limiting anthropogenic warming to 1.5 °C instead of 2 °C can markedly reduce the area undergoing, and thus the population exposed to, aridification.

Experimentally Derived Intermediate to Silica-rich Arc Magmas by Fractional and Equilibrium Crystallization at 1·0 GPa: an Evaluation of Phase Relationships, Compositions, Liquid Lines of Descent and Oxygen Fugacity

Abstract: Differentiation of hydrous primary, mantle-derived magmas is a fundamental process to generate evolved intermediate to SiO2-rich compositions forming the bulk of the continental and island arc crust. This study focuses on the results of equilibrium and fractional crystallization experiments at 1 0 GPa using two different primary magmas representing deep (90 km) and shallow (35 km) mantle extraction depths. Experiments on a hydrous high-Mg basalt were conducted at graphite-saturated and more oxidized conditions (NNO to NNOþ 2, where NNO is nickel–nickel oxide buffer) to exploit the influence of fO2 on phase assemblages and the evolution of derivative liquids. The liquid line of descent (LLD) was simulated from liquidus to near-solidus conditions ranging from 1330 C to 720 C. H2O contents varied from about 2 0 to more than 10 wt %. The LLD covers the entire compositional range from high-Mg basalt to high-silica rhyolite and evolves from metaluminous to peraluminous compositions at 56–60 wt % SiO2 under oxidizing conditions. The observed crystallization sequences and the LLD reveal contrasting behavior depending on oxidation state, H2O content and equilibrium versus fractional crystallization. Equilibrium crystallization of high-Mg basalt under reducing conditions is initially dominated by olivine fractionation followed by Cr-rich spinel, clinopyroxene (cpx), and orthopyroxene (opx). Finally, between 1060 and 1000 C, amphibole formed by a peritectic reaction consuming cpxþolivine and forming amphiboleþopx, resulting in 16% silica-undersaturated trachy-basaltic liquid. Equilibrium crystallization of the same composition under oxidizing conditions is characterized by strongly enhanced olivine and cpx fractionation and suppression of opx only occurring as a result of the peritectic amphibole-forming reaction at and below 1040 C. The liquid at 980 C is a peraluminous, alkali-poor, high-Al andesite representing 15% residual liquid. Fractional crystallization of the high-Mg basalt under oxidizing conditions evolves through fractionation of early olivine joined by cpx at 1200 C, followed by opx and hercynitic spinel (1140–1080 C) and amphibole at 1050 C coexisting with cpx (and spinel) to 980 C. At 950 C both garnet and plagioclase (plag) join amphibole as liquidus phases. This paragenesis (plus ilmenite and apatite) persists to 750 C with 16% residual liquid relative to the initial basaltic composition. Liquids evolve continuously from basalt to rhyolite, crossing the metaluminous–peraluminous boundary at about 60 wt % SiO2. Fractional crystallization of the basaltic andesite starting material differs at high temperature, where opx and cpx are the liquidus phases (1200–1080 C), followed by amphibole at the expense of opx. Below VC The Author(s) 2018. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. 11 J O U R N A L O F P E T R O L O G Y Journal of Petrology, 2018, Vol. 59, No. 1, 11–58 doi: 10.1093/petrology/egy017 Advance Access Publication Date: 16 February 2018

Prediction Modeling and Mapping of Groundwater Fluoride Contamination throughout India

Abstract: For about the past eight decades, high concentrations of naturally occurring fluoride have been detected in groundwater in different parts of India The chronic consumption of fluoride in high concentrations is recognized to cause dental and skeletal fluorosis We have used the random forest machine-learning algorithm to model a data set of 12 600 groundwater fluoride concentrations from throughout India along with spatially continuous predictor variables of predominantly geology, climate, and soil parameters Despite only surface parameters being available to describe a subsurface phenomenon, this has produced a highly accurate prediction map of fluoride concentrations exceeding 15 mg/L at 1 km resolution throughout the country The most affected areas are the northwestern states/territories of Delhi, Gujarat, Haryana, Punjab, and Rajasthan and the southern states of Andhra Pradesh, Karnataka, Tamil Nadu, and Telangana The total number of people at risk of fluorosis due to fluoride in groundwater is pr

A comparison between ten advanced and soft computing models for groundwater qanat potential assessment in Iran using R and GIS

Abstract: Considering the unstable condition of water resources in Iran and many other countries in arid and semi-arid regions, groundwater studies are very important. Therefore, the aim of this study is to model groundwater potential by qanat locations as indicators and ten advanced and soft computing models applied to the Beheshtabad Watershed, Iran. Qanat is a man-made underground construction which gathers groundwater from higher altitudes and transmits it to low land areas where it can be used for different purposes. For this purpose, at first, the location of the qanats was detected using extensive field surveys. These qanats were classified into two datasets including training (70%) and validation (30%). Then, 14 influence factors depicting the region’s physical, morphological, lithological, and hydrological features were identified to model groundwater potential. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), flexible discriminant analysis (FDA), penalized discriminant analysis (PDA), boosted regression tree (BRT), random forest (RF), artificial neural network (ANN), K-nearest neighbor (KNN), multivariate adaptive regression splines (MARS), and support vector machine (SVM) models were applied in R scripts to produce groundwater potential maps. For evaluation of the performance accuracies of the developed models, ROC curve and kappa index were implemented. According to the results, RF had the best performance, followed by SVM and BRT models. Our results showed that qanat locations could be used as a good indicator for groundwater potential. Furthermore, altitude, slope, plan curvature, and profile curvature were found to be the most important influence factors. On the other hand, lithology, land use, and slope aspect were the least significant factors. The methodology in the current study could be used by land use and terrestrial planners and water resource managers to reduce the costs of groundwater resource discovery.

State of the climate in 2017

Abstract: In 2017, the dominant greenhouse gases released into Earth's atmosphere-carbon dioxide, methane, and nitrous oxide-reached new record highs. The annual global average carbon dioxide concentration at Earth's surface for 2017 was 405.0 ± 0.1 ppm, 2.2 ppm greater than for 2016 and the highest in the modern atmospheric measurement record and in ice core records dating back as far as 800 000 years. The global growth rate of CO2 has nearly quadrupled since the early 1960s. With ENSO-neutral conditions present in the central and eastern equatorial Pacific Ocean during most of the year and weak La Nina conditions notable at the start and end, the global temperature across land and ocean surfaces ranked as the second or third highest, depending on the dataset, since records began in the mid-to-late 1800s. Notably, it was the warmest non-El Nino year in the instrumental record. Above Earth's surface, the annual lower tropospheric temperature was also either second or third highest according to all datasets analyzed. The lower stratospheric temperature was about 0.2°C higher than the record cold temperature of 2016 according to most of the in situ and satellite datasets. Several countries, including Argentina, Uruguay, Spain, and Bulgaria, reported record high annual temperatures. Mexico broke its annual record for the fourth consecutive year. On 27 January, the temperature reached 43.4°C at Puerto Madryn, Argentina-the highest temperature recorded so far south (43°S) anywhere in the world. On 28 May in Turbat, western Pakistan, the high of 53.5°C tied Pakistan's all-time highest temperature and became the world-record highest temperature for May. In the Arctic, the 2017 land surface temperature was 1.6°C above the 1981-2010 average, the second highest since the record began in 1900, behind only 2016. The five highest annual Arctic temperatures have all occurred since 2007. Exceptionally high temperatures were observed in the permafrost across the Arctic, with record values reported in much of Alaska and northwestern Canada. In August, high sea surface temperature (SST) records were broken for the Chukchi Sea, with some regions as warm as +11°C, or 3° to 4°C warmer than the longterm mean (1982-present). According to paleoclimate studies, today's abnormally warm Arctic air and SSTs have not been observed in the last 2000 years. The increasing temperatures have led to decreasing Arctic sea ice extent and thickness. On 7 March, sea ice extent at the end of the growth season saw its lowest maximum in the 37-year satellite record, covering 8% less area than the 1981-2010 average. The Arctic sea ice minimum on 13 September was the eighth lowest on record and covered 25% less area than the long-term mean. Preliminary data indicate that glaciers across the world lost mass for the 38th consecutive year on record; the declines are remarkably consistent from region to region. Cumulatively since 1980, this loss is equivalent to slicing 22 meters off the top of the average glacier. Antarctic sea ice extent remained below average for all of 2017, with record lows during the first four months. Over the continent, the austral summer seasonal melt extent and melt index were the second highest since 2005, mostly due to strong positive anomalies of air temperature over most of the West Antarctic coast. In contrast, the East Antarctic Plateau saw record low mean temperatures in March. The year was also distinguished by the second smallest Antarctic ozone hole observed since 1988. Across the global oceans, the overall long-term SST warming trend remained strong. Although SST cooled slightly from 2016 to 2017, the last three years produced the three highest annual values observed; these high anomalies have been associated with widespread coral bleaching. The most recent global coral bleaching lasted three full years, June 2014 to May 2017, and was the longest, most widespread, and almost certainly most destructive such event on record. Global integrals of 0-700-m and 0-2000-m ocean heat content reached record highs in 2017, and global mean sea level during the year became the highest annual average in the 25-year satellite altimetry record, rising to 77 mm above the 1993 average. In the tropics, 2017 saw 85 named tropical storms, slightly above the 1981-2010 average of 82. The North Atlantic basin was the only basin that featured an above-normal season, its seventh most active in the 164-year record. Three hurricanes in the basin were especially notable. Harvey produced record rainfall totals in areas of Texas and Louisiana, including a storm total of 1538.7 mm near Beaumont, Texas, which far exceeds the previous known U.S. tropical cyclone record of 1320.8 mm. Irma was the strongest tropical cyclone globally in 2017 and the strongest Atlantic hurricane outside of the Gulf of Mexico and Caribbean on record with maximum winds of 295 km h-1. Maria caused catastrophic destruction across the Caribbean Islands, including devastating wind damage and flooding across Puerto Rico. Elsewhere, the western North Pacific, South Indian, and Australian basins were all particularly quiet. Precipitation over global land areas in 2017 was clearly above the long-term average. Among noteworthy regional precipitation records in 2017, Russia reported its second wettest year on record (after 2013) and Norway experienced its sixth wettest year since records began in 1900. Across India, heavy rain and flood-related incidents during the monsoon season claimed around 800 lives. In August and September, above-normal precipitation triggered the most devastating floods in more than a decade in the Venezuelan states of Bolivar and Delta Amacuro. In Nigeria, heavy rain during August and September caused the Niger and Benue Rivers to overflow, bringing floods that displaced more than 100 000 people. Global fire activity was the lowest since at least 2003; however, high activity occurred in parts of North America, South America, and Europe, with an unusually long season in Spain and Portugal, which had their second and third driest years on record, respectively. Devastating fires impacted British Columbia, destroying 1.2 million hectares of timber, bush, and grassland, due in part to the region's driest summer on record. In the United States, an extreme western wildfire season burned over 4 million hectares; the total costs of $18 billion tripled the previous U.S. annual wildfire cost record set in 1991.

Tree rings reveal globally coherent signature of cosmogenic radiocarbon events in 774 and 993 CE.

Abstract: Though tree-ring chronologies are annually resolved, their dating has never been independently validated at the global scale Moreover, it is unknown if atmospheric radiocarbon enrichment events of

Integrated ecological–economic fisheries models—Evaluation, review and challenges for implementation

Abstract: Marine ecosystems evolve under many interconnected and area-specific pressures. To fulfil society's intensifying and diversifying needs while ensuring ecologically sustainable development, more effective marine spatial planning and broader-scope management of marine resources is necessary. Integrated ecological–economic fisheries models (IEEFMs) of marine systems are needed to evaluate impacts and sustainability of potential management actions and understand, and anticipate ecological, economic and social dynamics at a range of scales from local to national and regional. To make these models most effective, it is important to determine how model characteristics and methods of communicating results influence the model implementation, the nature of the advice that can be provided and the impact on decisions taken by managers. This article presents a global review and comparative evaluation of 35 IEEFMs applied to marine fisheries and marine ecosystem resources to identify the characteristics that determine their usefulness, effectiveness and implementation. The focus is on fully integrated models that allow for feedbacks between ecological and human processes although not all the models reviewed achieve that. Modellers must invest more time to make models user friendly and to participate in management fora where models and model results can be explained and discussed. Such involvement is beneficial to all parties, leading to improvement of mo-dels and more effective implementation of advice, but demands substantial resources which must be built into the governance process. It takes time to develop effective processes for using IEEFMs requiring a long-term commitment to integrating multidisciplinary modelling advice into management decision-making.

Transforming data into knowledge for improved wastewater treatment operation : A critical review of techniques

Abstract: The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic computer-based method development during the last two decades. The most cited techniques are artificial neural networks, principal component analysis, fuzzy logic, clustering, independent component analysis and partial least squares regression. Even though there has been progress on techniques related to the development of environmental decision support systems, knowledge discovery and management, the research sector is still far from delivering systems that smoothly integrate several types of knowledge and different methods of reasoning. Several limitations that currently prevent the application of computer-based techniques in practice are highlighted.