Water Chemistry Data Research Articles

Childhood Lead Exposure and Cognitive Functioning Among Older Adults: Evidence From the Health and Retirement Study

Many children born in the early 20th century were exposed to water-borne lead, a neurotoxin that negatively impacts brain development. While lead exposure has been linked to poor cognition among children and young adults, no population-level research has examined the long-term implications of lead exposure for cognitive functioning in later life. Our study is the first to address this gap by utilizing novel data linkages between the 1940 U.S. Census and the Health and Retirement Study (HRS). Our sample includes respondents who were under age 17 (born 1924-1940) by the time of the decennial enumeration on April 1, 1940. Given that the dominant source of lead exposure was water during this period, we assessed lead exposure by using water chemistry and piping material data for each HRS respondent’s city of residence in 1940. Late-life cognitive functioning for HRS participants (observed 1998-2016) was measured using the Telephone Interview for Cognitive Status. We find that lead exposure during childhood is significantly and negatively associated with cognitive functioning in later life. HRS participants who lived in cities with lead pipes and acidic or alkaline water—the conditions required for lead to leech into municipal water—showed lower levels of cognitive functioning decades later as compared to other participants. This association persisted net of race, gender, childhood socioeconomic status and childhood health. However, the association was largely accounted for by adjusting for educational attainment. This implies that childhood lead exposure impacts later-life cognition via its effect on educational attainment.

The influence of climate on water chemistry states and dynamics in rivers across Australia

AbstractFor effective water quality management and policy development, spatial variability in the mean concentrations and dynamics of riverine water quality needs to be understood. Using water chemistry (calcium, electrical conductivity, nitrate‐nitrite, soluble reactive phosphorus, total nitrogen, total phosphorus and total suspended solids) data for up to 578 locations across the Australian continent, we assessed the impact of climate zones (arid, Mediterranean, temperate, subtropical, tropical) on (i) inter‐annual mean concentration and (ii) water chemistry dynamics as represented by constituent export regimes (ratio of the coefficients of variation of concentration and discharge) and export patterns (slope of the concentration‐discharge relationship). We found that inter‐annual mean concentrations vary significantly by climate zones and that spatial variability in water chemistry generally exceeds temporal variability. However, export regimes and patterns are generally consistent across climate zones. This suggests that intrinsic properties of individual constituents rather than catchment properties determine export regimes and patterns. The spatially consistent water chemistry dynamics highlights the potential to predict riverine water quality across the Australian continent, which can support national riverine water quality management and policy development.

Phosphorus retention and transformation in a dammed reservoir of the Thames River, Ontario: Impacts on phosphorus load and speciation

Extensive efforts are underway to reduce phosphorus (P) export from the Lake Erie watershed. On the Canadian side, the Thames River is the largest tributary source of P to Lake Erie’s western basin. However, the role of dams in retaining and modifying riverine P loading to the lake has not been comprehensively evaluated. We assessed whether Fanshawe Reservoir, the largest dam reservoir on the Thames River, acts as a source or sink of P, using year-round discharge and water chemistry data collected in 2018 and 2019. We also determined how in-reservoir processes alter P speciation by comparing the dissolved reactive P to total P ratio (DRP:TP) in upstream and downstream loads. Annually, Fanshawe Reservoir was a net sink for P, retaining 25% (36 tonnes) and 47% (91 tonnes) of TP in 2018 and 2019, respectively. Seasonally, the reservoir oscillated between a source and sink of P. Net P release occurred during the spring of 2018 and the summers of 2018 and 2019, driven by internal P loading and hypolimnetic discharge from the dam. The reservoir did not exert a strong influence on DRP:TP annually, but ratio increases occurred during both summers, concurrent with water column stratification. Our analysis demonstrates that Fanshawe Reservoir is not only an important P sink on the Thames River, but also modulates the timing and speciation of P loads. We therefore propose that the potential of using existing dam reservoirs to attenuate downstream P loads should be more thoroughly explored alongside source based P mitigation strategies.

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

The application of remote sensing data to empirical models of inland surface water chlorophyll-a concentrations (chl-a) has been in development since the launch of the Landsat 4 satellite series in 1982. However, establishing an empirical model using a chl-a retrieval algorithm is difficult due to the spatial heterogeneity of inland lake water properties. Classification of optical water types (OWTs; i.e., differentially observed water spectra due to differences in water properties) has grown in favour in recent years over traditional non-turbid vs. turbid classifications. This study examined whether top-of-atmosphere reflectance observations in visible to near-infrared bands from Landsat 4, 5, 7, and 8 sensors can be used to identify unique OWTs using a guided unsupervised classification approach in which OWTs are defined through both remotely sensed reflectance and surface water chemistry data taken from samples in North American and Swedish lakes. Linear regressions of algorithms (Landsat reflectance bands, band ratios, products, or combinations) to lake surface water chl-a were built for each OWT. The performances of chl-a retrieval algorithms within each OWT were compared to those of global chl-a algorithms to test the effectiveness of OWT classification. Seven unique OWTs were identified and then fit into four categories with varying degrees of brightness as follows: turbid lakes with a low chl-a:turbidity ratio; turbid lakes with a mixture of high chl-a and turbidity measurements; oligotrophic or mesotrophic lakes with a mixture of low chl-a and turbidity measurements; and eutrophic lakes with a high chl-a:turbidity ratio. With one exception (r2 = 0.26, p = 0.08), the best performing algorithm in each OWT showed improvement (r2 = 0.69–0.91, p < 0.05), compared with the best performing algorithm for all lakes combined (r2 = 0.52, p < 0.05). Landsat reflectance can be used to extract OWTs in inland lakes to provide improved prediction of chl-a over large extents and long time series, giving researchers an opportunity to study the trophic states of unmonitored lakes.

Spatial variation of subduction zone fluids during progressive subduction: Insights from Serpentinite Mud Volcanoes

Geological processes at subduction zones control seismicity, plutonism and volcanism, and geochemical cycling between the oceans, crust, and mantle. The down-going plate experiences metamorphism, and the associated dehydration and fluid flow alters the physical properties of the plate interface and mantle wedge, as well as controlling the composition of material descending into the mantle. Any direct study of slab evolution during subduction is inhibited by the prohibitive depths at which these processes occur. To examine these processes we use serpentinite mud volcanoes in the Mariana forearc, that permit sampling of serpentinite materials and their pore waters that ascend from the subduction channel. We present new pore water chemical data from the summit and flanks of three serpentinite mud volcanoes that were drilled during International Ocean Discovery Program Expedition 366 which are reflective of reactions within the crust and mantle during the early, shallow (<20 km) stages of subduction. We show, via thermodynamic modelling, that our new data on the evolution of pore water chemical compositions reflect mineralogical characteristics of a predominately basaltic source from the downgoing Pacific Plate. However, a component from sedimentary sources is likely, especially for those mud volcanoes near the trench. Other potential slab-derived constituents, such as lithospheric serpentinite, carbonate-rich sediments, or seamount basalts with an intraplate geochemical character, are not required to explain our results. Our results indicate that with progressive subduction the lawsonite-epidote mineral transformation boundary at ∼250 °C may help drive slab carbonate destabilisation, despite its apparent thermodynamic stability at such temperatures and projected pressures (∼300 °C and ∼0.6 GPa). New dissolved gas data also point to primary thermodynamic controls over methane/ethane production within the subduction channel as depths-to-slab increase. Our findings provide direct evidence for the progressive mineralogical and chemical evolution of a subducting oceanic plate, which liberates a progressively evolving fluid phase into the subduction channel.

Preliminary conceptual model of the Arjuno Welirang hydrogeological system, and comparison with the Bromo Tengger: An illustration of the hydrogeological systems diversity in volcanic areas

While basaltic volcanic aquifers are well described in the literature, andesitic groundwater systems are less studied. Nevertheless, these aquifers supply a large population in all the subduction areas, where this volcanism mainly occurs. In Indonesia, the growing needs of the population induce an increase of the pressure on such aquifers. We present in this paper the case study of the Arjuno-Welirang, and compare it with a well-known hydrogeological system, the Bromo-Tengger. Based on geological, geomorphological, and water chemistry data, this study highlights the diversity of andesitic history inherent to this kind of volcanism, and its strong implications on the groundwater availability downstream. The aim of this paper is also to show that simple investigations can help building a preliminary conceptual model (PCM) of complex volcanic settings. Such PCM is needed to define further detailed hydrogeological investigations required to set-up aquifer exploitation, management and preservation rules.

Identifying schools at high-risk for elevated lead in drinking water using only publicly available data

Estimating the risk of lead contamination of schools' drinking water at the State level is a complex, important, and unexplored challenge. Variable water quality among water systems and changes in water chemistry during distribution affect lead dissolution rates from pipes and fittings. In addition, the locations of lead-bearing plumbing materials are uncertain. We tested the capability of six machine learning models to predict the likelihood of lead contamination of drinking water at the schools' taps using only publicly available datasets. The predictive features used in the models correspond to those with a proven correlation to the dominant, but commonly unavailable, factors that govern lead leaching: the presence of lead-bearing plumbing materials and water quality conducive to lead corrosion. By combining water chemistry data from public reports, socioeconomic information from the US census, and spatial features using Geographic Information Systems, we trained and tested models to estimate the likelihood of lead contaminated tap water in over 8,000 schools across California and Massachusetts. Our best-performing model was a Random Forest, with a 10-fold cross validation score of 0.88 for Massachusetts and 0.78 for California using the average Area Under the Receiver Operating Characteristic Curve (ROC AUC) metric. The model was then used to assign a lead leaching risk category to half of the schools across California (the other half was used for training). There was good agreement between the modeled risk categories and the actual lead leaching outcomes for every school; however, the model overestimated the lead leaching risk in up to 17% of the schools. This model is the first of its kind to offer a tool to predict the risk of lead leaching in schools at the State level. Further use of this model can help deploy limited resources more effectively to prevent childhood lead exposure from school drinking water.

Conductivity increased in Upper Ohio River Valley streams during the hot and dry summer of 2020

As the climate begins to change, streams are faced with rising water temperatures and prolonged droughts. Droughts can lead to low flow and increases conductivity concentrations in streams, which can cause stressful events for organisms present. We collected water chemistry data at 24 sites over the summer months of 2019 and 2020 to see if there were any significant differences between the years. We sampled streams ranging in size from headwater to 8th order and impairment ranging from biologically healthy to acid mine drainage (AMD) impacted. We found conductivity to be higher at all of our sites in 2020, while 14 of the 24 had warmer water temperatures. In our non-AMD sites, conductivity increased by 100 µS cm-1 in 2020 posing increased stress for organisms present, while sites affected by AMD were always over 1,000 µS cm-1. Rising temperature and increasing conductivity create challenges for sensitive species while more tolerant species become more dominant.

Changes in Water Chemistry and Driving Factors in the Middle and Lower Reaches of the Beijing-Hangzhou Grand Canal

To reveal the Beijing-Hangzhou Grand Canal natural water chemistry characteristics and the influence of human activities, river samples from Xuzhou to Jiaxing were collected in 2019-2020. Simultaneously, the water chemistry data of the canal from 1959 to 1962 and 1975 to 1977 in the Suzhou, Wuxi, and Changzhou sections and the recent social and economic data of the major cities along the canal were collected and analyzed. The results showed that the type of hydrochemistry in the study area was mainly influenced by the weathering of carbonate rocks in the basin, but K++Na+ accounted for 40.39% of the cation equivalent concentration, which was higher than that in ordinary surface water, thereby indicating that the natural hydrochemistry of the canal had been significantly affected by human factors. Spatially, the major ion mass concentrations, total hardness, and total alkalinity of the Grand Canal from Xuzhou station to the downstream area tended to decrease overall, but the parameters at Wuxi and Suzhou stations increased significantly. It was found that Na+ and SO42- were increased by approximately 16 and 12 times and total dissolved solids was increased by nearly 3 times by analyzing the 60 years of water chemistry of the Suzhou, Wuxi, and Changzhou sections. The current (Ca2++Mg2+)/HCO3- ratio in the Suzhou, Wuxi, and Changzhou sections is generally greater than 1, which is significantly higher than that from 1959 to 1962, thereby reflecting the results of human activities. According to the analysis of the social and economic development of the Grand Canal, this change was the result of the accelerated weathering of carbonate rocks in the basin caused by the sulfur oxides discharged by human activities. Further statistical analysis showed that urban domestic sewage and industrial wastewater discharge were the main driving factors causing chemical salinization of natural water in the Grand Canal. This study can provide a scientific basis for coordinating urban development and protecting the water ecological environment of the Grand Canal Basin.

Hydrochemical Zoning and Chemical Evolution of the Deep Upper Jurassic Thermal Groundwater Reservoir Using Water Chemical and Environmental Isotope Data

A comprehensive hydrogeological understanding of the deep Upper Jurassic carbonate aquifer, which represents an important geothermal reservoir in the South German Molasse Basin (SGMB), is crucial for improved and sustainable groundwater resource management. Water chemical data and environmental isotope analyses of δD, δ18O and 87Sr/86Sr were obtained from groundwater of 24 deep Upper Jurassic geothermal wells and coupled with a few analyses of noble gases (3He/4He, 40Ar/36Ar) and noble gas infiltration temperatures. Hierarchical cluster analysis revealed three major water types and allowed a hydrochemical zoning of the SGMB, while exploratory factor analyses identified the hydrogeological processes affecting the water chemical composition of the thermal water. Water types 1 and 2 are of Na-[Ca]-HCO3-Cl type, lowly mineralised and have been recharged under meteoric cold climate conditions. Both water types show 87Sr/86Sr signatures, stable water isotopes values and calculated apparent mean residence times, which suggest minor water-rock interaction within a hydraulically active flow system of the Northeastern and Southeastern Central Molasse Basin. This thermal groundwater have been most likely subglacially recharged in the south of the SGMB in close proximity to the Bavarian Alps with a delineated northwards flow direction. Highly mineralised groundwater of water type 3 (Na-Cl-HCO3 and Na-Cl) occurs in the Eastern Central Molasse Basin. In contrast to water types 1 and 2, this water type shows substantial water-rock interaction with terrestrial sediments and increasing 40Ar/36Ar ratios, which may also imply a hydraulic exchange with fossil formation waters of overlying Tertiary sediments.

Shenandoah Watershed Study‐Virginia Trout Stream Sensitivity Study (SWAS‐VTSSS): Stream water quality and hydrologic monitoring data for mid‐Appalachian headwater streams

AbstractThe Shenandoah Watershed Study (established in 1979) and the Virginia Trout Stream Sensitivity Study (established in 1987) serve to increase understanding of hydrological and biogeochemical changes in western Virginia mountain streams that occur in response to acidic deposition and other ecosystem stressors. The SWAS‐VTSSS program has evolved over its 40+ year history to consist of a temporally robust and spatially stratified monitoring framework. Currently stream water is sampled for water quality bi‐hourly during high‐flow events at three sites and weekly at four sites within Shenandoah National Park (SHEN), and quarterly at 72 sites and on an approximately decadal frequency at ~450 sites within the wider western Virginia Appalachian region. Stream water is evaluated for pH, acid neutralizing capacity (ANC), base cations (calcium, magnesium, sodium and potassium ion), acid anions (sulphate, nitrate and chloride), silica, ammonium, and conductivity with a subset of samples evaluated for monomeric aluminium and dissolved organic carbon. Hourly stream discharge (four sites) and in‐situ measurements of conductivity, water and air temperature (three sites) are also measured within SHEN. Here we provide an overview and timeline of the SWAS‐VTSSS stream water monitoring program, summarize the field and laboratory methods, describe the water chemistry and hydrologic data sets, and document major watershed disturbances that have occurred during the program history. Website links and instructions are provided to access the stream chemistry and time‐series monitoring data in open‐access federal databases. The purpose of this publication is to promote awareness of these unique, long‐term data sets for wider use in catchment studies. The water chemistry and hydrologic data can be used to investigate a wide range of biogeochemical research questions and provide key inputs for models of these headwater stream ecosystems. SWAS‐VTSSS is an ongoing program and quality assured data sets are uploaded to the databases annually.

Analysis of localized water chemistry and land use drivers of macroinvertebrate community structure in the Upper Ohio Watershed using multivariate modelling and ordination techniques.

An assessment of land use, water chemistry and macroinvertebrate community data was performed at 20 stream sites in southwestern Pennsylvania and West Virginia’s Northern Panhandle. Project sites were located on streams spanning six different watersheds from a variety of catchment sizes and land use characteristics. Macroinvertebrate community characteristics were analyzed using ordination techniques including Nonmetric Multidimensional Scaling (NMS) and hierarchical agglomerative cluster analysis, and predictive effects of ambient physicochemical stream conditions and watershed land use were evaluated using hierarchical modelling via Integrated Nested Laplace Approximation (INLA). Ordinations showed watershed development, shredder biomass, ambient annual turbidity, and riparian forest cover as primary drivers of dissimilarity between macroinvertebrate communities. INLA models identified significant negative relationships between macroinvertebrate community diversity and ambient annual conductivity, turbidity and watershed development. Results support regionwide water quality assessments citing conductivity and sedimentation as prevailing in-stream stressors, as well as land use characteristics as determining factors of water quality, even at localized scales.

Machine-Learning Methods in Prognosis of Ageing Phenomena in Nuclear Power Plant Components

In the Long-Term Degradation Management (LTDM) project we approach component ageing problems with data-analysis methods. It includes literature review about related work. We have used several data sources: water chemistry data from the Halden reactor, simulator data from the HAMBO simulator, and data from a local coffee machine instrumented with sensors. K-means clustering is used in cluster analysis of nuclear power plant data. A method for detecting trends in selected clusters is developed. Prognosis models are developed and tested. In our analysis ARIMA models and gamma processes are used. Such tasks as classification and time-series prediction are focused on. Methodologies are tested in experiments. The realization of practical applications is made with the Jupyter Notebook programming tool and Python 3 programming language. Failure rates and drifts from normal operating states can be the first symptoms of an approaching fault. The problem is to find data sources with enough transients and events to create prognostic models. Prognosis models for predicting possible developing ageing features in nuclear power plant data utilizing machine learning methods or closely related methods are demonstrated.

Nitrogen Removal via Denitrification in Two Small Reservoirs in Central Wisconsin, U.S.A.

Aquatic ecosystems with long hydraulic residence times (e.g., wetlands and reservoirs) can be important nitrogen (N) sinks via denitrification. The objective of this study was to examine denitrification rates of two small reservoirs (Springville and McDill) in central Wisconsin. Sediments, water chemistry, and discharge data were collected once per month between May and September of 2014 to achieve these objectives. Denitrification rates and microbial biomass carbon were not different between Springville and McDill; however, organic matter was significantly higher in McDill. Average denitrification rates were low at both sites, but ranged widely in Springville (0–23.72 mg N m–2 h–1) and less so in McDill (0.32–12.16 23 mg N m–2 h–1). Low denitrification rates in Springville may be the result of several locations being organic matter limited, whereas the McDill site was likely nitrate limited. Results from this study suggest reservoirs in central Wisconsin that are groundwater fed with sandy substrate have the potential to be nitrate sinks, but variation in the landscape (e.g. land use) and within each reservoir is influencing the magnitude of realized denitrification capabilities.

Effects of a chain of reservoirs on temporal and spatial variation in water chemistry within an endorheic basin

Reservoirs provide more than 90% of water for agricultural, municipal, and environmental flows in arid regions. Yet, these resources may be compromised if the effects of reservoirs on water chemistry are not considered. This manuscript summarizes water chemistry data collected from May 2014 to October 2018 in the Shiyang Basin, an endorheic basin in arid North-Central China, where samples were collected from a chain of reservoirs, including headwater (mountain), mid-reach (oasis), and lower (desert) reservoirs. All samples consisted of a mixture of Ca-HCO3, Ca (Mg)-HCO3, and Na-SO4(Cl), with concentrations increasing at lower elevations. Stable isotopes indicate that most evaporation occurs in reservoirs, rather than in stream channels. Rock lithology is the primary factor influencing water chemistry in the headwater and mid-reach reservoirs, with the additional influence of imported water from the Yellow River in the mid-reach reservoir. Water quality in the desert reservoir was primarily influenced by evaporative crystallization. We show that these reservoirs are the primary source of hydrochemical transformation in this endorheic basin, affecting both the temporal and spatial variation of water chemistry.

The role of carbonate mineral dissolution in turbidity reduction in an oil sands end pit lake

Surface water turbidity from dispersed clay particles can hinder the development of aquatic ecosystems. One of the primary objectives for proposed oil sands end pit lakes is that they support ecological functions and lake-specific wildlife habitat. However, high surface water turbidity has been observed in the Base Mine Lake cap water, the first full-scale demonstration oil sands end pit lake. Our previous study showed that adjusting the solution pH through carbon dioxide (CO2) addition reduced surface water turbidity in oil sands tailings. Carbonate minerals such as calcite and dolomite were also previously identified in tailings, and thus the goal of this study was to determine the effect of calcite and dolomite dissolution through CO2-mediated pH reduction on turbidity and the stability of suspended clay particles. Calcite dissolution resulted in ∼99% reduction of turbidity. The suspended clay particle stability was analyzed using DLVO (Derjaguin-Landau-Verwey-Overbeek) theory with water chemistry data from this column study. An inverse correlation was observed between the amount of dolomite and the energy barrier values on day 42 of the experiment. These results suggest CO2-mediated calcite dissolution changes the water chemistry and is the most promising treatment condition for the settlement of suspended tailings particles.

Integrating current and historical water chemistry data with long-term piezometric records to develop a regional-scale conceptual flow model: Las Salinas spring, Medina del Campo, Spain

Study regionOld Las Salinas spring in Medina del Campo, Duero river basin, central Spain. Study focusMedina del Campo groundwater body (MCGWB) is a multilayer semiconfined aquifer subject to intensive pumping since the 1970’s, where the current existence of spas where there used to be traditional baths could confirm the existence of deep groundwater flow paths. The old spring of Las Salinas (OSLS) is a saline anomaly in an aquifer with predominance of CaCO3H waters whose occurrence has not yet been formally explained. Long-term geological, geophysical, hydrogeological and hydrochemical records were integrated and complemented with field work to clarify its existence. New hydrological insights for the regionOutcomes led to the conclusion that the hydrochemistry of the Olmedo and Palacio de las Salinas salt baths is associated with the existence of a major threshold in the impervious basement of the aquifer, which intercepted deep regional groundwater flow and caused upwelling to the surface under unperturbed conditions. These results allow for the development of a conceptual flow model at the regional scale that explains the changes in natural water chemistry that have been identified in recent decades.

The legacy of regional industrial activity: Is loon productivity still negatively affected by acid rain?

Metal mining and smelting in Sudbury, Ontario, Canada, began in the 1880s and peaked in the 1950s and 1960s. By the mid-1970s, thousands of lakes had been acidified by sulfur dioxide (SO2) emitted from Sudbury metal smelters. Common loons (Gavia immer) are top predators in lakes across Ontario, and lake acidification has resulted in loss of prey for developing chicks and declines in common loon breeding productivity. Acidifying emissions have declined greatly since the 1960s, but many lakes remain acidic. We evaluated chemical recovery and loon breeding success in 69 single-loon-pair (small), variably acidified lakes near Sudbury using 38 years of loon survey and water chemistry data (1982–2019). Lake pH increased, particularly in lakes that were more acidic and closer to Sudbury, but 65% of lakes that were highly acidic in the 1980s remained below pH 6.0 (where biological damage can occur) in 2019. Furthermore, over half of our study lakes showed hydrochemical properties indicative of acid impairment (e.g., high relative sulfate levels, low base cation concentrations, high aluminum and manganese concentrations). More acidic lakes were associated with lower loon productivity, and overall, loon breeding effort and success declined over four decades on these lakes. The legacy of acid rain continues to negatively impact small lakes near Sudbury, and we hypothesize that loons may be more vulnerable to population declines in areas throughout their range that were directly and heavily degraded due to acidifying emissions.

A Series of Data-Driven Hypotheses for Inferring Biogeochemical Conditions in Alkaline Lakes and Their Deposits Based on the Behavior of Mg and SiO2

Alkaline (pH &gt; 8.5) lakes have been common features of Earth’s surface environments throughout its history and are currently among the most biologically productive environments on the planet. The chemistry of alkaline lakes favors the deposition of aluminum-poor magnesian clays (e.g., sepiolite, stevensite, and kerolite) whose chemistry and mineralogy may provide a useful record of the biogeochemistry of the lake waters from which they were precipitated. In this forward-looking review, we present six data-driven, testable hypotheses devoted to furthering our understanding of the biogeochemical conditions in paleolake waters based on the geochemical behavior of Mg and SiO2. In the development of these hypotheses, we bring together a compilation of modern lake water chemistry, recently published and new experimental data, and empirical, thermodynamic, and kinetic relationships developed from these data. We subdivide the hypotheses and supporting evidence into three categories: (1) interpreting paleolake chemistry from mineralogy; (2) interpreting the impact of diatoms on alkaline lake sedimentation; and (3) interpreting depositional mineralogy based on water chemistry. We demonstrate the need for further investigation by discussing evidence both for and against each hypothesis, which, in turn, highlights the gaps in our knowledge and the importance of furthering our understanding of the relevant geological and biological systems. The focused testing of these hypotheses against modern occurrences and the geologic record of alkaline lakes can have profound implications for the interpretation of the paleo-biogeochemistry and paleohabitability of these systems on Earth and beyond.

The impacts of Marcellus Shale gas drilling accidents on amphibians in a Pennsylvania fen

Gas drilling into the Marcellus Shale play has been linked to environmental issues, including potential impacts on wildlife. In 2009, three separate accidents occurred at two gas well sites in central Pennsylvania, USA that resulted in high levels of contaminants in Wallace Mine Fen and a headwater stream that flows through the fen. We collected water chemistry, vegetation, and amphibian data at the impacted fen and at a control fen in 2012 and 2013 to determine similarity of sites and the impacts of the contaminants. We also reviewed water chemistry reports generated by the Pennsylvania Department of Environmental Protection for data collected shortly after the accidents occurred to provide insight on the nature of the accidents. Ordinations of vegetation data, as well as water chemistry, showed that the two wetlands are similar and dominated by the same plant species and water chemistry. Historically, both wetlands provided habitat for amphibians. However, unlike in pre-accident amphibian data, we detected virtually no amphibians in the impacted Wallace Mine Fen, suggesting that amphibians were possibly negatively affected by gas-drilling accidents.