Robust Indicator Research Articles

Evaluation of addition of chemical and organic fertilizers to irrigation in the production of Prosopis laevigata (Humb. & Bonpl. ex Willd.) M.C. Johnst.

Aim of study: The objective of this study was to evaluate the effects of a chemical fertilizer and two organic fertilizers on the morphometric variables of Prosopis laevigata (Humb. & Bonpl. ex Willd.) M.C. Johnst growth under greenhouse conditions. Area of study: The research was conducted in a greenhouse at the Autonomous University of Aguascalientes in Aguascalientes State, Mexico. Material and methods: Six treatments were evaluated: T1: Control (Water), T2: 19-19-19 (19% nitrogen- 19%phosphorus- 19% potassium) + M. E. (Microelements), T3: 19-19-19 + M. E. + worm leachate, T4: Worm leachate, T5: Nitrogen-fixing bacteria and T6: Nitrogen-fixing bacteria + worm leachate. At the end of the evaluation period, the height and diameter of the seedlings were recorded. The aboveground dry biomass to belowground dry biomass ratio (AGDW/BGDW), robustness index, and Dickson’s quality index were determined. The cost of the different fertilization treatments was also evaluated. Main results: Seedlings in the combined treatments of chemical fertilizer and leachate presented greater height (28.00 cm) and diameter (2.81 cm). The organic fertilizer treatments presented higher robustness index values and AGDW/BGDW ratio, indicating their potential in terms of field performance. However, it should be noted that organic fertilizers are comparatively more expensive than chemical fertilizers. Research highlights: Further experimentation is required to determine the appropriate doses for quality seedlings using organic fertilizers. Producers should create their own organic fertilizers to minimize costs.

ANALYSING MARKET DYNAMICS: REVEALING OBSCURED PATTERNS IN LQ45 STOCKS (2021-2023) USING WARD’S HIERARCHICAL CLUSTERING

This study aimed to address the instability of the Indonesian stock market from 2021 to 2023 by analyzing the LQ45 index, a critical indicator of economic robustness and corporate performance. Hierarchical Ward clustering was employed to categorize LQ45 stocks based on fundamental metrics such as Return, Volume, Price, Price-Earnings Ratio (PER), Earnings Per Share (EPS), and Dividends. Data preprocessing involved feature creation, Max-Abs scaling for normalization, and binary encoding of categorical variables. The optimal number of clusters was identified using dendrograms, revealing two primary clusters: one focusing on core materials and the other on financial services, alongside other industry-specific clusters. This method, characterized by its ability to minimize variance within clusters and determine natural groupings without predefined assumptions, provided valuable insights for financial advisors, policymakers, and investors. The findings offer practical guidance for optimizing decision-making, minimizing risks, and leveraging opportunities within the Indonesian stock market during a period of significant economic uncertainty. By employing this strategy, investors and traders can gain a comprehensive understanding of the current condition of the stock market, offering a thorough comprehension of the connections between equities and the operational and financial issues currently under scrutiny.

Regulating Ethics in Parliaments: Measuring Regime Robustness

Ethics regulation in parliaments has grown significantly over the last decades, as a result of political scandals, public outcry, and policy diffusion promoted by international organizations. Ethics regulatory regimes vary according to the focus of the norms (compliance vs. integrity or transparency vs. sanctions) and according to the degree of externalization of oversight and enforcement mechanisms (external to parliament, internal, or mixed). The mere existence of regulation says little about how strong these regimes are. Drawing on original data collected through an institutional checklist of 21 indicators, we develop an Ethics Regulation Robustness Index to measure the scope of norms, the strictness of sanctions, and the powers granted to oversight and enforcement bodies in 17 European parliaments. Our findings suggest that the externality of the oversight and enforcement is not a good predictor of the robustness of the ethics regulations.

Levels of corporate environmental strategies in Hungary and the associated environmental management control tools

The research aims to map environmental protection strategies and the related control tools and to identify the links among companies with the largest number of employees and sites in Hungary. The research questions were answered using a questionnaire survey method. The authors used cluster analysis to classify the 205 company strategies into the identified strategy clusters: Leaders, Awakeners, and Laggards. Then, the examined 21 environmental management control tools in the sample were divided into four groups: strategic, administrative, methodological and economic. Economic and strategic methods were the most common in the sample. The authors used cross-tabulation analysis to examine whether there is a statistically proven relationship between belonging to environmental strategy clusters and specific control tools. The analysis showed significant but weak to moderate relationships. According to Cramer’s V and the contingency coefficient, the closest relationship between the tested environmental management control tools and membership in environmental strategy clusters is shown by evaluating investments, assessing the economic viability of environmental strategies, and running an environmental training program for employees. In case of the robust lambda indicator, a significant relationship was found by examining the economics of environmental strategies and identifying environmental success factors and eco-balances. It can be concluded that the companies under examination follow a set of environmental goals, which they have incorporated into their strategic objectives. They use the available environmental management control toolbox to develop their strategies and to monitor their implementation to varying degrees.

Evaluation of Sepsis Severity Using Combined High-Density Lipoprotein and Red Cell Distribution Width Indicators

Aims/Background Sepsis is a life-threatening condition resulting from dysregulated immune responses to infection, leading to organ dysfunction. High-density lipoprotein (HDL) and red cell distribution width (RDW) have shown significant correlations with sepsis severity, yet the combined prognostic value of HDL and RDW in evaluating sepsis severity and outcomes remains unclear. This study examines the relationship between HDL and RDW levels and sepsis severity, as well as evaluates the combined utility of these markers in predicting disease severity and patient outcomes. Methods This retrospective study included 103 patients diagnosed with sepsis. Clinical data, including HDL and RDW levels, were collected for analysis. Patients were divided into shock and non-shock groups based on the presence of septic shock and into survival and death groups based on 30-day in-hospital mortality. Multivariate logistic regression was used to identify factors influencing sepsis severity and prognosis, while the predictive value of HDL in combination with RDW was evaluated using receiver operating characteristic (ROC) curve analysis. Results Multivariate analysis identified sequential organ failure assessment (SOFA) score (OR = 6.566), interleukin-6 (IL-6) (OR = 2.568), HDL (OR = 0.864), and RDW (OR = 4.052) as independent predictors of sepsis severity (p < 0.05 for all). ROC analysis demonstrated that HDL combined with RDW yielded the highest diagnostic accuracy for sepsis severity, with an area under curve (AUC) of 0.962, sensitivity of 97.56%, and specificity of 91.94%. Additionally, SOFA score (OR = 2.354), interleukin-6 (IL-6) (OR = 1.446), HDL (OR = 0.870), and RDW (OR = 3.502) were independent prognostic indicators (p < 0.05 for all). ROC analysis for prognosis showed that HDL combined with RDW had the highest predictive efficacy for the prognosis of sepsis, with an AUC of 0.922, sensitivity of 79.31%, and specificity of 93.24%. Conclusion The combination of HDL and RDW is a robust indicator for the evaluation of sepsis severity and is a valuable prognostic tool for assessing 30-day mortality risk in sepsis patients.

Yes-associated protein-based detection of acute type A aortic dissection and evaluation of therapeutic responses

BackgroundAcute aortic dissection is a lethal cardiovascular emergency; early diagnosis is critically necessary. Novel serum biomarkers can potentially help in early detection and estimation of postoperative outcomes. Yes-associated protein (YAP) is a critical effector of the Hippo pathway, our aim was to explore the association between YAP and the diagnosis and prognosis of AD.MethodsWe prospectively recruited 110 consecutive chest-pain patients [acute type A aortic dissection (ATAAD), n = 60; acute coronary syndrome (ACS), n = 50]. Blood samples were collected to determine levels of YAP and other serum biomarkers, and receiver operating characteristic curves (ROC) were constructed to assess the predictability in early diagnosis of AAD and postoperative major adverse events (MAEs).ResultsYAP concentration was substantially elevated among ATAAD patients [3.45 (3.18, 3.63) vs. 2.44 (2.23, 2.59), P < 0.01]. Moreover, the white blood cell (WBC) count and plasma fibrin D-dimers were remarkably high among ATAAD patients [11.46 (9.57, 14.03) vs. 6.24 (5.10, 7.30), P < 0.01; 2,097.00 (998.75, 3,652.00) vs. 97.00 (67.25, 137.00), P < 0.01]. The serum YAP level held as a good predictive value in early diagnosis of ATAAD. The optimal cutoff value was 3.15 ng/ml, with an AUC of 0.94 (95% CI, 0.90–0.98, P < 0.01), sensitivity of 80% and specificity of 98%. The combined model of YAP, WBC count and D-Dimer exhibited an enhanced predictive power, with an AUC of 0.99 (95% CI, 0.98–1.00, P < 0.01). Serum YAP values at 12 h post-surgery provided the most accurate prediction of postoperative MAEs, with an optimal cutoff value of 3.60 ng/ml, an AUC of 0.89 (95% CI, 0.79–0.99, P < 0.01), and sensitivity and specificity of 88% and 82%, respectively.ConclusionsThe serum YAP concentration is an early and sensitive serum bioindicator for distinguishing AAD from ACS. Moreover, the amount of postoperative circulating YAP is a robust indicator of postoperative MAEs.

Simple ecological indicators benchmark regeneration success of Amazonian forests

Natural regeneration of Amazon forests offers a promising strategy to mitigate forest loss and advance the goals of the UN Decade on Ecosystem Restoration. However, the vast variability in regeneration rates across environmental gradients and over time poses considerable challenges for assessing regeneration success and ecosystem services provision in human-modified landscapes. Here we compiled 448 plots from forest regeneration in the Amazon to investigate the drivers of regrowth capacity and identify robust ecological indicators. By modeling optimal successional trajectories, we estimated reference values for vegetation structure, diversity, and functioning. After 20 years, successful regeneration should reach a minimum basal area of 14 m². ha−¹, at least 34 tree species per 100 individuals, a structural heterogeneity index of 0.27, and 123 Mg.ha−¹ of aboveground biomass. These straightforward indicators and reference values provide a foundational framework for governments and practitioners to assess success and establish targets for Amazon restoration efforts.

Measuring and validating the Ukrainian ethnic coherence instrument

ABSTRACT To assess Ukrainian ethnic coherence, scholars have employed single-item scales such as language preference and national identity. In practice, these approaches can downplay the multidimensional nature of ethnic coherence. To address this concern, I propose a multidimensional theory of Ukrainian ethnic coherence and validate its measure with a survey in government-controlled Ukraine (n = 1,004). The factor analysis validated an 18-item scale composed of four robust indicators: myths of origin and fate, symbols of territory, language as a community symbol, and traditions of collective action. I then assessed the level of shared understanding of the four indicators and their relationship to demographic characteristics. Ethnic Ukrainians demonstrated a high level of shared understanding of myths of origin and fate and language as a community symbol, followed by traditions of collective action. Nevertheless, they demonstrated low agreement about which territorial boundaries represent ethnic Ukrainians. The study also presents socio-economic drivers that influence ethnic coherence.

Atomic and molecular gas as traced by [C II] emission

The latest ALMA and JWST observations provide new information on the birth and evolution of galaxies in the early Universe at the epoch of reionization. Measurements at redshift $ z > 5$ of their cold-gas budget are particularly important because this budget is known to be the main fuel for star formation. A powerful tool for probing the physics characterising galaxies at high redshift is the m$ emission line. Due to its low excitation potential emission can be produced in photodissociation regions, neutral atomic gas, and molecular clouds. To properly capture the cold-gas processes taking place in these environments (molecule formation, self-shielding, dust grain catalysis, and photoelectric and cosmic-ray heating), we made use of a new set of dedicated hydrodynamic simulations ( including time-dependent non-equilibrium chemistry, star formation, stellar evolution, metal spreading, and feedback mechanisms. We were able to accurately track the evolution of and H$_2$ in a cosmological context and predict the contribution of each gas phase to luminosity. We provide formulas that can be used to estimate the mass of molecular and atomic gas from detections. Furthermore, we analysed the evolution of conversion factors with galactic properties, such as stellar metallicity, star formation rate, and stellar mass. We demonstrate that emission is dominated by gas and that most of the luminosity is generated in warm, dense, star-forming regions. We conclude that although predominantly traces atomic rather than molecular gas, the luminosity remains a robust indicator of the H$_2$ mass.

Estimating willingness-to-pay for adaptations to climate change in water resources projects: demonstration for Lesotho irrigation investment

A broad set of tools, frameworks, and guidance documents are available for water resources project planning, design, evaluation, and implementation in an ever-evolving world. The principles underlying most of these resources aim to advance the practice of water systems engineering under uncertainty, preserve and enhance project benefits, and achieve investment goals. Approaches to financial and economic evaluation under climate uncertainty in civil infrastructure investments, in particular, are currently being reviewed by academics and practitioners in the field to assess their ability to deliver resilience, sustainability, and equity. In climate-sensitive projects, adaptation measures that help mitigate the adverse effects of climate change and preserve project benefits are required, and stakeholder willingness-to-pay (WTP) for these must be assessed. Typically, stakeholders and decision-makers utilize the outcomes of economic assessment methods such as cost–benefit analysis (CBA) to justify large capital investments. Synthesizing previous advancements in water resources planning and evaluation, this study illustrates how a CBA framework can be augmented by applying a Climate-informed Robustness Index (CRI). The analytics underpinning the CRI, as well as the summary metric itself, help characterize project climate vulnerability, while conducting CBA with and without potential adaptation measures can be used to estimate WTP of investors for adaptation to the identified climate vulnerabilities. The case study of a planned irrigated agriculture project in Lesotho highlights critical climate conditions for which adaptation measures such as integrated catchment management (ICM) plans can be introduced to safeguard project robustness.

A bespoke water T-maze apparatus and protocol: an optimized, reliable, and repeatable method for screening learning, memory, and executive functioning in laboratory mice.

The Morris Water Maze (MWM) is the most commonly used assay for evaluating learning and memory in laboratory mice. Despite its widespread use, contemporary reviews have highlighted substantial methodological variation in experimental protocols and that the associated testing procedures are acutely (each trial) and chronically (testing across days) stressful; stress impairs attention, memory consolidation and the retrieval of learned information. Moreover, the interpretation of behavior within the MWM is often difficult because of wall hugging, non-spatial swim strategies, floating, and jumping off the escape platform. Together, these issues may compromise the reproducibility, generalizability, and predictability of experimental results, as well as animal welfare. To address these issues, and as an initial proof-of-principle, we first narrowed the spatial dimensions of the MWM by using a T-insert, which constrained and reduced the overall length of time/distance that the animal must swim in order to navigate to the escape platform, thus reducing stress and off-task behavior. Given the robust performance observed across spatial acquisition (learning and memory) as well as during reversal learning (executive function), we further reduced (by 43%) the overall distance and time that the animal must swim in order to find the escape platform in a bespoke standalone Water T-Maze (WTM). We show, across five experiments, procedural refinements to our protocol and demonstrate robust, reliable and reproducible indicators of learning, memory and executive functioning in a task that is also significantly more efficient (3 days of testing within the WTM vs. 11 days of testing within the MWM). Taken together, our WTM apparatus and protocol are a significant improvement over other water-based apparatuses and protocols for evaluating learning, memory, and executive functioning in laboratory mice.

Almost sure asymptotic stability of parabolic SPDEs with small multiplicative noise: with application to the perturbed Moore-Greitzer model

In this paper, we investigate the almost-sure exponential asymptotic stability of the trivial solution of a parabolic stochastic partial differential equation (SPDE) driven by multiplicative noise near the deterministic Hopf bifurcation point. We show the existence and uniqueness of the invariant measure under appropriate assumptions, and approximate the exponential growth rate via asymptotic expansion, given that the strength of the noise is small. This approximate quantity can readily serve as a robust indicator of the change of almost-sure stability. We apply the results to a simplified stochastic Moore-Greitzer PDE model in detecting the stall instabilities of modern jet-engine under the impact of multiplicative noise. A better understanding of the instability margin will eventually optimize the jet-engine operating range and thus lead to lighter and more efficient jet-engine design.

Robust competency-based evaluation matrix for directive PMO services in construction projects

The interest in using project management office (PMO) services in organizations to manage their construction projects is growing in light of rising economic, technological, and social developments based on their ability to achieve organizational goals while avoiding risks. Accordingly, organizations use PMO services to manage their technical and financial project issues to periodically evaluate PMO performance and services in a scientific, practical, and measurable way to ensure successful project path via PMO. Therefore, this research aims to develop a performance evaluation system that enables organizations to follow up and evaluate the PMO performance to ensure that PMO manages the organizations’ expectations and goals successfully according to certain quality, scope, and cost. The study builds on significant findings in PMO competence indexes as evaluation matrix, which includes five basic categories with 136 indexes covering the project life cycle. The matrix was developed based on literature analysis and supplemented with experts’ interviews in construction management. The developed robust competency-based index (RCI) for directive PMO supports the organizations to conduct client satisfaction, correction, or partial/total change of the PMO’s competence flow within five construction project life cycle and process, i.e. governance, portfolio, information, execution, and contract issues.

Risk−Based Cost−Benefit Optimization Design for Steel Frame Structures to Resist Progressive Collapse

The design of structures to resist progressive collapse primarily focuses on enhancing structural safety and robustness. However, given the low probability of accidental events, such designs often lead to a negative cost–benefit. To address this problem, this paper uses risk analysis to optimize the progressive collapse resistance design of steel frame structures. The elements’ cross-section design for the progressive collapse resistance of steel frame structures is optimized using genetic algorithms and SAP2000 23, which identify the structural model with the minimum robustness index while ensuring safety. The results show that the risk-based robustness index can effectively assess the cost of progressive collapse design. More importantly, the optimization model can rapidly identify the most cost-effective structural design solution that complies with progressive collapse resistance guidelines, enhancing the simplicity and usability of the structure design optimization process. Additionally, the integration of the SAP2000 API with Python 3.8 automation streamlines the parameterization process, minimizes manual errors, and enhances the precision and efficiency of the structural design optimization. Finally, the model’s effectiveness is validated through a case study, where the refined single-frame structure shows a reduction in initial construction and collapse-related costs by 2.4% and 9.1%, respectively. Meanwhile, the three-dimensional frame shows a 2.9% rise in initial costs but a 13.5% decrease in total collapse-resistant design costs, illustrating the model’s ability to balance safety with cost-effectiveness.

Assessing structural robustness of composite I-girder bridges through a work-based approach and nonlinear numerical analyses

This paper presents a structural robustness assessment of I-girder bridges through non-linear numerical analysis. Experimental tests were conducted on two scaled bridge specimens, one intact and the other damaged, subjected to asymmetric loading conditions. A nonlinear finite element model was established and validated by comparing it with experimental results in load-displacement and load-strain curves. This paper proposes a new work-based robustness assessment method and corresponding robustness index. Also, parametric studies on the effects of the vertical position of the crossbeam along girder height and the effect of crossbeam cross-section under asymmetrical loading were performed and compared using load-displacement curves. Based on the proposed method, the robustness of two, three, and four I-girder bridges was found to be 0.133, 0.296, and 0.415 with their threshold values equal to 0.269, 0.283, and 0.283 respectively. It is concluded that three I-girder bridges should be considered robust according to the proposed robustness index. The rectangular cross-section of the crossbeam showed improved post-fracture behavior for the studied model in this research based on load-displacement curves predicted by FE analysis, while crossbeam position along girder height can influence the overall post-fracture behavior of bridge structure depending on damage scenarios.

Age at onset as an index of genetic heterogeneity in major psychiatric and substance use disorders.

Robust clinical indices of etiologic heterogeneity for psychiatric disorders are rare. We investigate whether age at onset (AAO) reflects genetic heterogeneity, utilizing Genetic Risk Ratios (GRR) derived from Family Genetic Risk Scores (FGRS). We examined, in individuals born in Sweden 1940-2003, whether AAO for five primary disorders -- drug use disorder (DUD), alcohol use disorder (AUD), major depression (MD), bipolar disorder (BD), and schizophrenia (SZ)-- was associated with varying levels of GRRs with a range of informative secondary disorders and traits. Our disorders displayed a varying pattern of change of GRRs with increasing AAO. At one end was SZ, where all GRRs rose with increasing AAO meaning that SZ became increasing genetically heterogeneous with later AAO. The most balanced disorder was AUD where, with increasing AAO, GRRs rose for AD, BD, and MD and declined for DUD, CB, and ADHD. That is, at young AAO, AUD had high levels of genetic risk for other externalizing disorders while at older AAO, high genetic risk for internalizing disorders were more prominent. MD was at the continuum's other end where all GRRs, except for AD, decreased with higher AAO, meaning that MD became increasingly genetically homogeneous with later AAO. Genetic heterogeneity was robustly associated with AAO across our five primary disorders with substantial inter-disorder differences in the observed patterns. In particular, young AAO was associated with maximal genetic homogeneity for SZ and DUD while older AAO had greater genetic homogeneity for MD with AUD falling in between.

Intelligent characterization and robustness quantification of frozen soil strength images using a multi-module fusion strategy

In frozen wall engineering, traditional detection methods are difficult to implement for real-time monitoring of strength parameters, due to their intermittent nature. This makes it difficult to provide timely warnings and effective responses to potential risks of frozen walls, highlighting the urgent need for a method that can continuously and accurately monitor the strength of frozen walls. An image data-driven intelligent identification method for frozen soil strength based on convolutional neural networks is proposed. By capturing images of cured samples from multiple angles and conducting uniaxial compressive strength tests, the collected strength data were divided into 12 categories, creating an image dataset for deep learning model training. A Resnet-34 deep learning model combined with global attention and downsampling showed excellent performance in comparison with a series of basic models, with an accuracy of 93.3 % and no overfitting. The accuracy of the deep learning model was assessed using adversarial attack and defense strategies, serving as an indicator of robustness. The improved model exhibited better robustness in comparative analyses. Using SHapley Additive exPlanations (SHAP) value analysis, the feature extraction process of the convolutional neural network in recognizing frozen soil strength was investigated and clarified, confirming the model's ability to identify and extract key features in frozen soil images, such as particle size, texture, cracks, and ice crystal distribution patterns. This technology offers a cutting-edge method for real-time tracking of frozen wall conditions and early disaster warnings, significantly enhancing the safety and success rate of construction projects under freezing conditions.

Olivine Ni isotopes of Ni-Cu deposits in NW China: A potential sulfide segregation indicator in basaltic magmatic systems

Sulfide segregation from silicate magmas is essential in forming magmatic sulfide deposits, but a robust Ni-isotopic indicator has been lacking. This study investigates the Ni isotopic compositions of olivine and coexisting sulfide from three magmatic Ni-Cu deposits in East Tianshan, NW China, to reveal the behavior of Ni isotopes during magmatic differentiation and sulfide segregation processes. The δ60/58Ni values in olivine separates (+0.15 to +0.68 ‰, median 0.40 ‰) are notably higher than typical mantle and basalt values (+0.11 to +0.23 ‰). Decreased Ni at the rim of Fe-Mg unzoned olivine indicates certain degrees of post-crystallization Fe-Ni diffusion between sulfide and olivine. The intragrain diffusion modeling results show that the δ60/58Ni values in olivine can change up to 0.5 ‰ to 1 ‰ when the diffusional modification of Ni extends to the core. However, the observed thin Ni gradient at the rim and relatively flat Ni profiles in the cores of the olivine samples suggest limited kinetic modifications. Moreover, the δ60/58Ni values negatively correlate with the Ni content and Ni/Co ratio in olivine. The sulfide separates are isotopically lighter than the coexisting olivine grain, with δ60/58Niolivine – δ60/58Nisulfide values ranging from +0.10 to +0.40 ‰ (median +0.22 ‰). Given minimal Ni isotope fractionation between olivine and silicate melt, the observed Ni isotopic differences between olivine and sulfides are attributed to Ni isotope fractionation between silicate melt and sulfide melt at magmatic temperatures, efficiently incorporating isotopically light Ni into the sulfide melt. The sulfide segregation-driven Ni isotope fractionation aligns with the distinct Ni isotopic compositions observed in olivine grains from two highly differentiated mafic units of the Huangshandong deposit with different sulfide evolution histories. Olivine grains from mineralized gabbronorite have higher δ60/58Ni values (+0.68 ‰, Phase III) than those from sulfide-barren olivine gabbro (δ60/58Ni = +0.23 ‰, Phase I). Systematic stratigraphic Ni isotope variations in the Huangshanxi olivine from intervals with varying degrees of sulfide segregation and magma replenishment further support this interpretation. These findings demonstrate that Ni isotopes in olivine are reliable for tracing sulfide segregation, provided that diffusional modification is carefully assessed. With limited diffusional modification, the widespread isotopically heavy Ni signature in olivine (δ60/58Ni > 0.3 ‰) serves as a valuable indicator for sulfide segregation and exploring magmaticNi-Cu deposits.

Wind fragility modeling of transmission tower-line system based on threat-dependent structural robustness index

Wind fragility modeling of transmission tower-line system based on threat-dependent structural robustness index

Application of selenium isotopes to define selenium bioreduction in coal waste rock: Elk Valley, British Columbia

Anthropogenic sources of selenium (Se), including coal mining, can release Se to the environment and raise Se concentrations in receiving waters above drinking water and aquatic limits. Selenium bioreduction can be an important control to reduce dissolved selenate concentrations. This extensive study investigated the application of Se stable isotope ratios (δ82Se) of dissolved selenate to identify Se bioreduction in saturated and unsaturated mine rock piles (MRPs) located in the Elk Valley, Canada. The study included in situ and laboratory column experiments, where methanol was added to promote bioreduction. Results showed that selenate concentrations often are not reliable indicators of bioreduction. However, elevation of δ82Se relative to the selenate sources in all environments provided a robust indicator of widespread selenate bioreduction. Native microbes were shown to use both methanol and natural carbon sources as an electron donor for selenate bioreduction. Variability in the magnitude of apparent isotopic fractionation in column experiments was attributed to physical and microbiological heterogeneity, while variability in apparent isotopic fractionation from in situ experiments was attributed to the entrainment of small masses of background selenate into the experiment. Due to the uncertainty in apparent epsilon values, the extent of bioreduction can only be estimated with limited confidence. Despite uncertainties, however, the application of δ82Se is valuable in guiding the management of Se in mine environments.