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The Non-Clinical Tomography Users Research Network (NoCTURN) was established in 2022 to advance Findability, Accessibility, Interoperability, and Reuse (FAIR) and Open Science (OS) practices in the computed tomographic (CT) imaging community. CT specialists utilize a shared pipeline to create digital representations of real-world objects for research, education, and outreach, and we face a shared set of challenges and limitations imposed by siloing of current workflows, best practices, and expertise. Mirroring the U.S. National Science Foundation’s “10 Big Ideas” of Convergence Research (2016), and in consideration of the White House Office of Science and Technology Policy's Nelson Memorandum (2020), NoCTURN is leveraging input from a broad community of more than 100 CT educators, researchers, curators, and industry stakeholders to propose improvements to data handling, management, and sharing that cut across scientific disciplines and extend beyond. Our primary goal is to develop practical recommendations and tools that link today's CT data to tomorrow's CT discoveries. NoCTURN is working toward this goal by providing a platform to: 1) engage the international scientific CT community via participant recruitment from imaging facilities, academic departments and museums, and data repositories across the globe; 2) stimulate improvements for CT imaging and data management standards that focus on FAIR and OS principles; and 3) work directly with private companies that manufacture the hardware and software used in CT imaging, visualization, and analysis to find common ground in documentation and interoperability that better reflects the OS standards championed by federal funding agencies. The planned deliverables from this three-year grant include a ‘Rosetta Stone’ for CT terminology, an interactive world map of CT facilities, a guide to CT repositories, and ‘Good, Better, Best’ guidelines for metadata and long-term data management. We aim to reduce the barriers to entry that isolate individuals and research labs, and we anticipate that developing community standards and improving methodological reporting will enable long-term, systemic changes necessary to aid those at all levels of experience in furthering their access to and use of CT imaging. 

Abstract This article reviews extant multidisciplinary literature to uncover existing themes and directions in the knowledge of the overlap between natural resource scarcity and illicit supply chain activity. In doing so, the authors present a novel review of this nascent, complex, and multidisciplinary research area. This review has uncovered 127 articles that have not been synthesized or organized in a meaningful way with the supply chain literature. It extracts insights and develops a comprehensive process framework encompassing the following: (a) antecedents associated with natural resource extraction, which foments the opportunity for illicit activity to thrive; (b) resulting economic, social, and environmental outcomes from illicit activity as it relates to natural resource extraction; and (c) potential moderating processes, which either enable or inhibit illicit activity to occur, including firm‐level tactics that businesses can employ to counteract illicit activity throughout the supply chain and to promote sustainable long‐term operations. An extensive agenda is presented suggesting future research paths, methodologies, theories, and potential contributions. 

Abstract Regional warming and associated changes in hydrologic systems pose challenges to water supply management in river basins of the western United States and call for improved understanding of the spatial and temporal variability of runoff. We apply a network of total width, subannual width, and delta blue intensity tree-ring chronologies in combination with a monthly water balance model to identify droughts and their associated precipitationPand temperatureTfootprints in the Truckee–Carson River basin (TCRB). Stepwise regression gave reasonably accurate reconstructions, from 1688 to 1999, of seasonalPandT(e.g.,R²= 0.50 for May–SeptemberT). These were disaggregated to monthly values, which were then routed through a water balance model to generate “indirectly” reconstructed runoff. Reconstructed and observed annual runoff correlate highly (r= 0.80) from 1906 to 1999. The extended runoff record shows that twentieth-century droughts are unmatched in severity in a 300-yr context. Our water balance modeling reconstruction advances the conventional regression-based dendrochronological methods as it allows for multiple hydrologic components (evapotranspiration, snowmelt, etc.) to be evaluated. We found that imposed warming (3° and 6°C) generally exacerbated the runoff deficits in past droughts but that impact could be lessened and sometimes even reversed in some years by compensating factors, including changes in snow regime. Our results underscore the value of combining multiproxy tree-ring data with water balance modeling to place past hydrologic droughts in the context of climate change. Significance StatementWe show how water balance modeling in combination with tree-ring data helps place modern droughts in the context of the past few centuries and a warming climate. Seasonal precipitation and temperature were reconstructed from multiproxy tree-ring data for a mountainous location near Lake Tahoe, and these reconstructions were routed through a water balance model to get a record of monthly runoff, snowmelt, and other water balance variables from 1688 to 1999. The resulting extended annual runoff record highlights the unmatched severity of twentieth-century droughts. A warming of 3°C imposed on reconstructed temperature generally exacerbates the runoff anomalies in past droughts, but this effect is sometimes offset by warming-related changes in the snow regime. 

Background: One goal of evolutionary developmental biology is to understand the role of development in the origin of phenotypic novelty and convergent evolution. Geckos are an ideal system to study this topic, as they are species-rich and exhibit a suite of diverse morphologies — many of which have independently evolved multiple times within geckos. Results: We characterized and discretized the embryonic development of Lepidodactylus lugubris - an all-female, parthenogenetic gecko species. We also used soft-tissue μCT to characterize the development of the brain and central nervous system, which is difficult to visualize using traditional microscopy techniques. Additionally, we sequenced and assembled a de novo transcriptome for a late-stage embryo as a resource for generating future developmental tools. Herein, we describe the derived and conserved patterns of L. lugubris development in the context of squamate evolution and development. Conclusions: This embryonic staging series, μCT data, and transcriptome together serve as critical enabling resources to study morphological evolution and development, the evolution and development of parthenogenesis, and other questions concerning vertebrate evolution and development in an emerging gecko model. 

Abstract Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regime shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds. These early warning statistics (EWS) have been studied separately but there have been few examples that directly compare temporal and spatial EWS in ecosystem‐scale empirical data. To test these methods, we collected high‐frequency time series and high‐resolution spatial data during a whole‐lake fertilization experiment while also monitoring an adjacent reference lake. We calculated two common EWS, standard deviation and autocorrelation, in both time series and spatial data to evaluate their performance prior to the resulting algal bloom. We also applied the quickest detection method to generate binary alarms of resilience change from temporal EWS. One temporal EWS, rolling window standard deviation, provided advanced warning in most variables prior to the bloom, showing trends and between‐lake patterns consistent with theory. In contrast, temporal autocorrelation and both measures of spatial EWS (spatial SD, Moran's  I) provided little or no warning. By compiling time series data from this and past experiments with and without nutrient additions, we were able to evaluate temporal EWS performance for both constant and changing resilience conditions. True positive alarm rates were 2.5–8.3 times higher for rolling window standard deviation when a lake was being pushed towards a bloom than the rate of false positives when it was not. For rolling window autocorrelation, alarm rates were much lower and no variable had a higher true positive than false positive alarm rate. Our findings suggest temporal EWS provide advanced warning of algal blooms and that this approach could help managers prepare for and/or minimize negative bloom impacts. 

Abstract Many research and monitoring networks in recent decades have provided publicly available data documenting environmental and ecological change, but little is known about the status of efforts to synthesize this information across networks. We convened a working group to assess ongoing and potential cross‐network synthesis research and outline opportunities and challenges for the future, focusing on the US‐based research network (the US Long‐Term Ecological Research network, LTER) and monitoring network (the National Ecological Observatory Network, NEON). LTER‐NEON cross‐network research synergies arise from the potentials for LTER measurements, experiments, models, and observational studies to provide context and mechanisms for interpreting NEON data, and for NEON measurements to provide standardization and broad scale coverage that complement LTER studies. Initial cross‐network syntheses at co‐located sites in the LTER and NEON networks are addressing six broad topics: how long‐term vegetation change influences C fluxes; how detailed remotely sensed data reveal vegetation structure and function; aquatic‐terrestrial connections of nutrient cycling; ecosystem response to soil biogeochemistry and microbial processes; population and species responses to environmental change; and disturbance, stability and resilience. This initial study offers exciting potentials for expanded cross‐network syntheses involving multiple long‐term ecosystem processes at regional or continental scales. These potential syntheses could provide a pathway for the broader scientific community, beyond LTER and NEON, to engage in cross‐network science. These examples also apply to many other research and monitoring networks in the US and globally, and can guide scientists and research administrators in promoting broad‐scale research that supports resource management and environmental policy.