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Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires knowledge of the spatial drivers of river microbiomes. However, understanding of the core microbial processes governing river biogeochemistry is hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we used a community science effort to accelerate the sampling, sequencing and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb profiles the identity, distribution, function and expression of microbial genomes across river surface waters covering 90% of United States watersheds. Specifically, GROWdb encompasses microbial lineages from 27 phyla, including novel members from 10 families and 128 genera, and defines the core river microbiome at the genome level. GROWdb analyses coupled to extensive geospatial information reveals local and regional drivers of microbial community structuring, while also presenting foundational hypotheses about ecosystem function. Building on the previously conceived River Continuum Concept1, we layer on microbial functional trait expression, which suggests that the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures2,3, so that it can be widely accessed across disciplines for watershed predictive modelling and microbiome-based management practices.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats-instructions, templates, and tools for consistently formatting data within a discipline-can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

Communication infuses all dimensions and stages of life, influencing one's self-determination and quality of life. A number of empirical studies have demonstrated that people with severe disabilities continue to develop communication and language skills well into their adult years and make measurable gains when provided with appropriate communication services and supports. Several myths about age, ability, and experiences limit opportunities for persons with severe disabilities. In this paper, we confront and address these myths.

Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community-driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data. (IGSN); physical samples; soil; water; plant; leaf; microbial communities; related identifiers; persistent identifiers.

Dissolved organic matter (DOM) is vital to ecosystem functions, influencing nutrient cycles and water quality. Understanding the processes driving DOM chemistry variation remains a challenge. By examining these processes through a community ecology perspective, we aim to understand the balance between stochastic forces (e.g., random mixing of DOM) and deterministic forces (e.g., systematic loss of certain types of DOM molecules) shaping DOM chemistry. Previous research on stochastic and deterministic influences over DOM chemistry applied null models to aquatic environments and subsurface pore water. Our study extends this to variably inundated riverbed sediments, which are widespread globally. We studied 38 river reaches across biomes, finding that DOM chemistry within most sites was governed by deterministic processes that were highly localized and led to spatial divergence in DOM chemistry within each reach. The degree of determinism varied substantially across reaches and we hypothesized this was related to differences in sediment moisture. Our findings partially supported this, showing that the upper limit of determinism decreased with increasing sediment moisture. We integrated our results with previous studies to develop a post-hoc conceptual model proposing that DOM assemblages become more deterministic along the continuum from river water to saturated sediment pore spaces to drier sediments or soils. This conceptual model aligns with previous work linking DOM chemistry to the Damköhler number and hydrologic connectivity, suggesting generalizable patterns and processes that can be further revealed by quantifying the stochastic-deterministic balance through space, time, and across scales. [ABSTRACT FROM AUTHOR]

Purpose: The United States Society for Augmentative and Alternative Communication and the Patient-Provider Communication Network sought to quantify the impact of utilization of and access to telepractice for the provision of augmentative and alternative communication (AAC) services. The purpose of this article is to summarize findings from two surveys that explored the kinds of AAC services delivered remotely, barriers to AAC addressed through telepractice, and impact of the availability of remote AAC services on people with communication disabilities and their caregivers. Method: The study team developed two online surveys: (a) for speech-language pathologists (SLPs) and (b) for individual AAC clients (or family members in the case of pediatric clients). Results: Survey responses were obtained from 66 SLPs and 90 AAC clients/family members. Access to telepractice allowed clients/family members to overcome both access and financial barriers. Respondents indicated that the availability of AAC telepractice services reduced transportation barriers, increased access to services by appropriately trained clinicians, and improved the outcomes for individuals needing AAC. Conclusions: Telepractice has made it possible for individuals with significant medical challenges, as well as those residing in areas lacking qualified providers, to receive services. Given that both clinicians and clients/families indicated that travel to receive services posed a significant barrier to access medically necessary treatment, the anticipated December 2024 end of Centers for Medicaid and Medicare Services' authorization of reimbursement for telepractice services will be detrimental to many needing AAC services. [ABSTRACT FROM AUTHOR]

Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined. Plain Language Summary: Streambed grain sizes control river hydro‐biogeochemical function by modulating the resistance, speed of water exchange, and nutrient transport at water‐sediment interface. Consequently, quantifying grain sizes and size‐dependent hydro‐biogeochemical parameters is critical for predicting river's function. In natural streams, measuring these sizes and parameters, however, is challenging because grain sizes vary from millimeters to a few meters, change from small creeks to big streams, and could be concealed by complex non‐grain materials such as water, ice, mud, and grasses. All these factors make the size measurements a time‐consuming and high‐uncertain task. We address these challenges by demonstrating a workflow that combines computer vision artificial intelligence (AI), smartphone photos, and new uncertainty quantification theories. The AI performs well across various sizes, locations, and stream environments as indicated by an accuracy metric of 0.98. We apply the AI to extract the grain sizes and their characteristic percentiles for 1,999 photos. These characteristic grain sizes are then input into existing and our new theories to derive the quantities, distributions, and uncertainties of hydrobiogeochemical parameters. The high accuracy of the AI and the success of extracting grain sizes and hydro‐biogeochemical parameters demonstrate the potential to advance river science with computer vision AI and mobile devices. Key Points: Stream sediments bigger than 44 microns can be detected from smartphone photos by You Only Look Once with a Nash–Sutcliffe efficiency of 0.98Quantities, distributions, and uncertainties of streambed grain sizes can be determined from photosImpact of grain size uncertainty on hydrobiogeochemical parameters is examined [ABSTRACT FROM AUTHOR]

This study provides an international perspective on mathematics by examnnng mathematics self-concept, achievement, and the desire to enter a career involving mathematics among eighth graders in 49 countries. Using data from the Trends in International Mathematics and Science Study, this study shows that self-concept in mathematics is more closely related to the desire to enter a career using mathematics than achievement is. Further, while gender differences in mathematics self-concept are smaller in more egalitarian countries, both girls and boys have lower mathematics self-concepts and less interest in mathematics careers in these countries. These findings reveal a policy paradox: policies aimed at training the next generation of STEM professionals often highlight the need to close the gender gap, but countries with smaller gender gaps have fewer boys and girls interested in mathematics-intensive careers. We conclude by highlighting the importance of disentangling instrumental and expressive aspects of gender inequality in STEM fields.

The National Joint Committee for the Communication Needs of People With Severe Disabilities (NJC) reviewed literature regarding practices for people with severe disabilities in order to update guidance provided in documents originally published in 1992. Changes in laws, definitions, and policies that affect communication attainments by persons with severe disabilities are presented, along with guidance regarding assessment and intervention practices. A revised version of the Communication Bill of Rights, a powerful document that describes the communication rights of all individuals, including those with severe disabilities is included in this article. The information contained within this article is intended to be used by professionals, family members, and individuals with severe disabilities to inform and advocate for effective communication services and opportunities.

Aerobic respiration of organic matter is a key metabolic process influencing carbon (C) biogeochemistry in aquatic ecosystems. Anthropogenic and environmental perturbations to stream ecosystem metabolism can have deleterious effects on downstream water quality. Various environmental features of rivers also influence stream metabolism, including physical (e.g., discharge, light, flow regimes) and chemical factors (nutrients, organic matter) and watershed characteristics (e.g., stream size or drainage area, land use). The relative proportion of surface water contact with benthic sediments has been considered the primary driver of ecosystem processes, including ecosystem respiration (ER). While aquatic ecosystem respiration occurs in the water column (ERwc) and in benthic sediments—including surficial and subsurface sediments (ERsed)—ERsed has long been assumed to be the primary contributor to whole-river ecosystem respiration (ERtot). Recent studies show, however, that somewhere along the river continuum (e.g., 5th–9th order), rivers transition from being dominated by benthic processes to being dominated by water column processes. Yet few metabolism studies have parsed contributions from the water column (ERwc) to ERtot, making it difficult to evaluate the relative magnitude and importance of ERwc across the river continuum and across biomes. In this study, we used the Yakima River basin, Washington, USA, to increase our understanding of basin-scale variation in ERwc. We collected ERwc data and water chemistry samples in triplicate at 47 sites in the Yakima River basin distributed across Strahler stream orders 2–7 and different hydrological and biophysical settings during summer baseflow conditions in 2021. We found that observed ERwc rates were consistently slow throughout the basin during baseflow conditions, ranging from −0.11–0.03 mg O2 L⁻1 d⁻1, and were generally at the very slow end of the range of published ERwc literature values. When compared to reach-scale ERtot rates predicted for rivers across the conterminous United States (CONUS), the very slow ERwc rates we observed throughout the Yakima River basin indicate that ERwc is likely a small component of ERtot in this basin. Despite these slow rates, ERwc nonetheless shows spatial variation across the Yakima River basin that was well explained by watershed characteristics and water chemistry. Multiple linear regression model results show that nitrate (NO3-N), dissolved organic carbon (DOC), and temperature together explained 41.5 % of the spatial variation in ERwc. Supporting the findings of other studies, we found that ERwc increased linearly with increasing NO3-N, increasing DOC, and increasing temperature. We hypothesize that low concentrations of nutrients, DOC, and low temperatures in the water column, coupled with low TSS concentrations, likely contribute to the slow ERwc rates observed throughout the Yakima River basin. Because ERtot measurements integrate contributions from water column respiration and sediment-associated respiration (ERsed), estimating ERtot in cold, clear, low nutrient rivers like those in the Yakima River basin with very slow ERwc will essentially measure contributions from ERsed. [ABSTRACT FROM AUTHOR]