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The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.
Geophysical datasets sensitive to different physical parameters can be used to improve resolution of Earth's internal structure. Herein, we jointly invert long-period magnetotelluric (MT) data and surface-wave dispersion curves. Our approach is based on a joint inversion using a genetic algorithm for a one-dimensional (1-D) isotropic structure, which we extend to 1-D anisotropic media. We apply our new anisotropic joint inversion to datasets from Central Germany demonstrating the capacity of our joint inversion algorithm to establish a 1-D anisotropic model that fits MT and seismic datasets simultaneously and providing new information regarding the deep structure in Central Germany. The lithosphere/asthenosphere boundary is found at approx. 84 km depth and two main anisotropic layers with coincident most conductive/seismic fast-axis direction are resolved at lower crustal and asthenospheric depths. We also quantify the amount of seismic and electrical anisotropy in the asthenosphere showing an emerging agreement between the two anisotropic coefficients.
In ecology, biodiversity-ecosystem functioning (BEE) research has seen a shift in perspective from taxonomy to function in the last two decades, with successful application of trait-based approaches. This shift offers opportunities for a deeper mechanistic understanding of the role of biodiversity in maintaining multiple ecosystem processes and services. In this paper, we highlight studies that have focused on BEE of microbial communities with an emphasis on integrating trait-based approaches to microbial ecology. In doing so, we explore some of the inherent challenges and opportunities of understanding BEE using microbial systems. For example, microbial biologists characterize communities using gene phylogenies that are often unable to resolve functional traits. Additionally, experimental designs of existing microbial BEE studies are often inadequate to unravel BEE relationships. We argue that combining eco-physiological studies with contemporary molecular tools in a trait-based framework can reinforce our ability to link microbial diversity to ecosystem processes. We conclude that such trait-based approaches are a promising framework to increase the understanding of microbial BEE relationships and thus generating systematic principles in microbial ecology and more generally ecology.