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Lake trophic state is a key ecosystem property that integrates a lake’s physical, chemical, and biological processes. Despite the importance of trophic state as a gauge of lake water quality, standardized and machine-readable observations are uncommon. Remote sensing presents an opportunity to detect and analyze lake trophic state with reproducible, robust methods across time and space. We used Landsat surface reflectance data to create the first compendium of annual lake trophic state for 55,662 lakes of at least 10 ha in area throughout the contiguous United States from 1984 through 2020. The dataset was constructed with FAIR data principles (Findable, Accessible, Interoperable, and Reproducible) in mind, where data are publicly available, relational keys from parent datasets are retained, and all data wrangling and modeling routines are scripted for future reuse. Together, this resource offers critical data to address basic and applied research questions about lake water quality at a suite of spatial and temporal scales.

 

Abstract We present preliminary results from our long-baseline interferometry (LBI) survey to constrain the multiplicity properties of intermediate-mass A-type stars within 80 pc. Previous multiplicity studies of nearby stars exhibit orbital separation distributions well fitted with a lognormal with peaks >15 au, increasing with primary mass. The A-star multiplicity survey of De Rosa et al., sensitive beyond 30 au but incomplete below 100 au, found a lognormal peak around 390 au. Radial velocity surveys of slowly rotating, chemically peculiar Am stars identified a significant number of very close companions with periods ≤5 days, ∼0.1 au, a result similar to surveys of O- and B-type primaries. With the improved performance of LBI techniques, we can probe these close separations for normal A-type stars where other surveys are incomplete. Our initial sample consists of 27 A-type primaries with estimated masses between 1.44 and 2.49 M ⊙ and ages 10–790 Myr, which we observed with the MIRC-X instrument at the CHARA Array. We use the open-source software CANDID to detect five companions, three of which are new, and derive a companion frequency of 0.19 − 0.06 + 0.11 over mass ratios of 0.25–1.0 and projected separations of 0.288–5.481 au. We find a probability of 10 −6 that our results are consistent with extrapolations based on previous models of the A-star companion population over the mass ratios and separations sampled. Our results show the need to explore these very close separations to inform our understanding of stellar formation and evolution processes. 

We observed HD 19467 B with JWST’s NIRCam in six filters spanning 2.5–4.6μm with the long-wavelength bar coronagraph. The brown dwarf HD 19467 B was initially identified through a long-period trend in the radial velocity of the G3V star HD 19467. HD 19467 B was subsequently detected via coronagraphic imaging and spectroscopy, and characterized as a late-T type brown dwarf with an approximate temperature ∼1000 K. We observed HD 19467 B as a part of the NIRCam GTO science program, demonstrating the first use of the NIRCam Long Wavelength Bar coronagraphic mask. The object was detected in all six filters (contrast levels of 2 × 10⁻⁴to 2 × 10⁻⁵) at a separation of 1.″6 using angular differential imaging and synthetic reference differential imaging. Due to a guide star failure during the acquisition of a preselected reference star, no reference star data were available for post-processing. However, reference differential imaging was successfully applied using synthetic point-spread functions developed from contemporaneous maps of the telescope’s optical configuration. Additional radial velocity data (from Keck/HIRES) are used to constrain the orbit of HD 19467 B. Photometric data from TESS are used to constrain the properties of the host star, particularly its age. NIRCam photometry, spectra, and photometry from the literature, and improved stellar parameters are used in conjunction with recent spectral and evolutionary substellar models to derive the physical properties of HD 19467 B. Using an age of 9.4 ± 0.9 Gyr inferred from spectroscopy, Gaia astrometry, and TESS asteroseismology, we obtain a model-derived mass of 62 ± 1M_J, which is consistent within 2σwith the dynamically derived mass of${81}_{-12}^{+14}$M_J.

 

Pressing environmental research questions demand the integration of increasingly diverse and large‐scale ecological datasets as well as complex analytical methods, which require specialized tools and resources.

Computational training for ecological and evolutionary sciences has become more abundant and accessible over the past decade, but tool development has outpaced the availability of specialized training. Most training for scripted analyses focuses on individual analysis steps in one script rather than creating a scripted pipeline, where modular functions comprise an ecosystem of interdependent steps. Although current computational training creates an excellent starting place, linear styles of scripting can risk becoming labor‐ and time‐intensive and less reproducible by often requiring manual execution. Pipelines, however, can be easily automated or tracked by software to increase efficiency and reduce potential errors. Ecology and evolution would benefit from techniques that reduce these risks by managing analytical pipelines in a modular, readily parallelizable format with clear documentation of dependencies.

Workflow management software (WMS) can aid in the reproducibility, intelligibility and computational efficiency of complex pipelines. To date, WMS adoption in ecology and evolutionary research has been slow. We discuss the benefits and challenges of implementing WMS and illustrate its use through a case study with thetargets rpackage to further highlight WMS benefits through workflow automation, dependency tracking and improved clarity for reviewers.

Although WMS requires familiarity with function‐oriented programming and careful planning for more advanced applications and pipeline sharing, investment in training will enable access to the benefits of WMS and impart transferable computing skills that can facilitate ecological and evolutionary data science at large scales.

 

Abstract Inner-shell photoelectron spectroscopy provides an element-specific probe of molecular structure, as core-electron binding energies are sensitive to the chemical environment. Short-wavelength femtosecond light sources, such as Free-Electron Lasers (FELs), even enable time-resolved site-specific investigations of molecular photochemistry. Here, we study the ultraviolet photodissociation of the prototypical chiral molecule 1-iodo-2-methylbutane, probed by extreme-ultraviolet (XUV) pulses from the Free-electron LASer in Hamburg (FLASH) through the ultrafast evolution of the iodine 4d binding energy. Methodologically, we employ electron-ion partial covariance imaging as a technique to isolate otherwise elusive features in a two-dimensional photoelectron spectrum arising from different photofragmentation pathways. The experimental and theoretical results for the time-resolved electron spectra of the 4d 3/2 and 4d 5/2 atomic and molecular levels that are disentangled by this method provide a key step towards studying structural and chemical changes from a specific spectator site.