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Abstract We present a study of the double-lined spectroscopic binary HD 21278 that contains one of the brightest main-sequence stars in the youngαPersei open cluster. We analyzed new spectra and reanalyzed archived spectra to measure precise new radial velocity curves for the binary. We also obtained interferometric data using the CHARA Array at Mount Wilson to measure the sky positions of the two stars and the inclination of the ∼2 mas orbit. We determine that the two stars have masses of 5.381 ± 0.084M_⊙and 3.353 ± 0.064M_⊙. From isochrone fits, we find the cluster’s age to be 49  ±  7 Myr (using PARSEC models) or 49.5 ± 6 Myr (MIST models). Finally, we revisit the massive white dwarfs that are candidate escapees from theαPersei cluster to try to better characterize the massive end of the white dwarf initial–final mass relation. The implied progenitor masses challenge the idea that Chandrasekhar-mass white dwarfs are made by single stars with masses near 8M_⊙. 

Abstract We report long-baseline interferometric observations with the CHARA Array that resolve six previously known double-lined spectroscopic binary systems in the Hyades cluster, with orbital periods ranging from 3 to 358 days: HD 27483, HD 283882, HD 26874, HD 27149, HD 30676, and HD 28545. We combine those observations with new and existing radial-velocity measurements, to infer the dynamical masses for the components as well as the orbital parallaxes. For most stars, the masses are determined to be better than 1%. Our work significantly increases the number of systems with mass determinations in the cluster. We find that, while current models of stellar evolution for the age and metallicity of the Hyades are able to reproduce the overall shape of the empirical mass–luminosity relation, they overestimate theV-band fluxes by about 0.1 mag between 0.5 and 1.4M_⊙. The disagreement is smaller inH, and near zero inK, and depends somewhat on the model. We also make use of the TESS light curves to estimate rotation periods for our targets, and detect numerous flares in one of them (HD 283882), estimating an average flaring rate of 0.44 events per day. 

Abstract The seasonal behavior of fluvial dissolved silica (DSi) concentrations, termedDSi regime, mediates the timing of DSi delivery to downstream waters and thus governs river biogeochemical function and aquatic community condition. Previous work identified five distinct DSi regimes across rivers spanning the Northern Hemisphere, with many rivers exhibiting multiple DSi regimes over time. Several potential drivers of DSi regime behavior have been identified at small scales, including climate, land cover, and lithology, and yet the large‐scale spatiotemporal controls on DSi regimes have not been identified. We evaluate the role of environmental variables on the behavior of DSi regimes in nearly 200 rivers across the Northern Hemisphere using random forest models. Our models aim to elucidate the controls that give rise to (a) average DSi regime behavior, (b) interannual variability in DSi regime behavior (i.e., Annual DSi regime), and (c) controls on DSi regime shape (i.e., minimum and maximum DSi concentrations). Average DSi regime behavior across the period of record was classified accurately 59% of the time, whereas Annual DSi regime behavior was classified accurately 80% of the time. Climate and primary productivity variables were important in predicting Average DSi regime behavior, whereas climate and hydrologic variables were important in predicting Annual DSi regime behavior. Median nitrogen and phosphorus concentrations were important drivers of minimum and maximum DSi concentrations, indicating that these macronutrients may be important for seasonal DSi drawdown and rebound. Our findings demonstrate that fluctuations in climate, hydrology, and nutrient availability of rivers shape the temporal availability of fluvial DSi. 

Abstract The 30 yr orbit of the Cepheid Polaris has been followed with observations by the Center for High Angular Resolution Astronomy (CHARA) Array from 2016 through 2021. An additional measurement has been made with speckle interferometry at the Apache Point Observatory. Detection of the companion is complicated by its comparative faintness—an extreme flux ratio. Angular diameter measurements appear to show some variation with pulsation phase. Astrometric positions of the companion were measured with a custom grid-based model-fitting procedure and confirmed with the CANDID software. These positions were combined with the extensive radial velocities (RVs) discussed by Torres to fit an orbit. Because of the imbalance of the sizes of the astrometry and RV data sets, several methods of weighting are discussed. The resulting mass of the Cepheid is 5.13 ± 0.28M_⊙. Because of the comparatively large eccentricity of the orbit (0.63), the mass derived is sensitive to the value found for the eccentricity. The mass combined with the distance shows that the Cepheid is more luminous than predicted for this mass from evolutionary tracks. The identification of surface spots is discussed. This would give credence to the identification of a radial velocity variation with a period of approximately 120 days as a rotation period. Polaris has some unusual properties (rapid period change, a phase jump, variable amplitude, and unusual polarization). However, a pulsation scenario involving pulsation mode, orbital periastron passage, and low pulsation amplitude can explain these characteristics within the framework of pulsation seen in Cepheids. 

Autotrophic and heterotrophic microbes in stream biofilms dominate biogeochemical cycling and rely on nutrient and energy resources for growth and productivity. In the boreal forest, variation in these resources can originate from permafrost distribution and controls competition for nutrients between stream autotrophs and heterotrophs. We investigated which resources control nutrient uptake and metabolism in headwater stream biofilms of subarctic Alaska, USA, and how resource availability affects competition for inorganic nutrients. We hypothesized that the competitive outcome between autotrophs and heterotrophs for inorganic nutrients would be dependent on availability of organic C, or inorganic nutrients (N and P). To test our hypotheses, we measured resource limitation at the patch and reach scales along a permafrost gradient in interior Alaska. At the patch scale, nutrient diffusing substrata revealed that, secondary to light, N and P were colimiting to autotrophic growth, whereas C was primarily limiting to heterotrophic respiration. In the presence of labile C, heterotrophs exhibited a larger response to nutrient enrichment and outcompeted autotrophs for inorganic nutrients. At the reach scale, light availability had the largest influence on nutrient uptake, but inorganic nutrients were also important. The positive response to increased nutrient and C availability at the patch scale suggests that the predicted increase in exports into fluvial networks with permafrost degradation will alter biofilm structure and function. Ultimately, biofilm communities will shift to more heterotroph-dominated patches if heterotrophs outcompete autotrophs for inorganic nutrients. As permafrost thaws and nutrients and organic C mobilize into streams, nutrient uptake dynamics and competition within biofilms will be altered, affecting nutrient use and export. 

Real-time monitoring usingin-situsensors is becoming a common approach for measuring water-quality within watersheds. High-frequency measurements produce big datasets that present opportunities to conduct new analyses for improved understanding of water-quality dynamics and more effective management of rivers and streams. Of primary importance is enhancing knowledge of the relationships between nitrate, one of the most reactive forms of inorganic nitrogen in the aquatic environment, and other water-quality variables. We analysed high-frequency water-quality data fromin-situsensors deployed in three sites from different watersheds and climate zones within the National Ecological Observatory Network, USA. We used generalised additive mixed models to explain the nonlinear relationships at each site between nitrate concentration and conductivity, turbidity, dissolved oxygen, water temperature, and elevation. Temporal auto-correlation was modelled with an auto-regressive–moving-average (ARIMA) model and we examined the relative importance of the explanatory variables. Total deviance explained by the models was high for all sites (99%). Although variable importance and the smooth regression parameters differed among sites, the models explaining the most variation in nitrate contained the same explanatory variables. This study demonstrates that building a model for nitrate using the same set of explanatory water-quality variables is achievable, even for sites with vastly different environmental and climatic characteristics. Applying such models will assist managers to select cost-effective water-quality variables to monitor when the goals are to gain a spatial and temporal in-depth understanding of nitrate dynamics and adapt management plans accordingly. 

Riverine silicon (Si) plays a vital role in governing primary production, water quality, and carbon sequestration. The Global Aggregation of Stream Silica (GlASS) database was constructed to assess changes in riverine Si concentrations and fluxes, their relationship to available nutrients, and to evaluate mechanisms driving these patterns. GlASS includes dissolved Si (DSi), dissolved inorganic nitrogen, and dissolved inorganic phosphorus concentrations at daily to quarterly time steps, daily discharge, and watershed characteristics for rivers with drainage areas ranging < 1 km2 to 3 million km2 and spanning eight climate zones, mainly in the northern hemisphere. Data range between years 1963 and 2023. GlASS uses publicly available datasets, ensuring transparency and reproducibility. Original data sources are cited, data quality assurance workflows are public, and input files to a common load estimator are provided. 

Key Points We compared tools for describing streamflow timeseries, including streamflow metrics, wavelet, and Fourier analysis Each method indicated streamflow data are structured: variability at short timescales is negatively correlated with long timescales Globally, dams were less correlated with streamflow regime than catchment size and climate were