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Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can enable a mechanistic understanding of coastal ecosystem control points and examine how geographically transferable this knowledge is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium– a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each site, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments. The data described herein aims to characterize the baseline distribution and chemical forms of carbon, nutrients, iron redox and mineralogy across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. This first campaign measures surface water quality parameters (e.g., conductivity, pH, ORP, alkalinity, and total suspended solids); bulk geochemical parameters on water, soil, and sediment samples (e.g., carbon, nutrient, and ionic concentration and composition); physicochemical parameters of sediment and soil (soil pH, conductivity, bulk density, water retention); and the rate of O2 consumption in inundated sediment and soil samples. Future campaigns will focus on building off these baseline datasets to enable a mechanistic understanding of coastal ecosystem biogeochemical control points.

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition of detrital inputs to soil over time – is useful for tracing the net response of SOC at the timescales relevant to climate change not usually discernible from fluxes and stocks alone. Here, we test two hypotheses using a mesic boreal forest climate transect: (1) the SOC diagenetic state is maintained across this climosequence, and (2) the maintenance of the SOC diagenetic state is a consequence of coupled soil C and N cycling, signifying the role of enhanced N cycling supporting SOC inputs that maintain SOC stocks within the warmer-climate forests. Shifts in nonvascular to vascular plant inputs with climate observed in these and other boreal forests highlighted the need to carefully separate biogeochemical indicators of SOC source from those signifying diagenetic alteration. We thus evaluated and applied lignin biomarkers to assess the diagenetic alteration of SOC in these boreal forest organic soils and directly compared the lignin diagenetic state with that of soil organic nitrogen (SON) assessed through amino acid composition. The lignin diagenetic state remained constant across the climate transect, indicating a balance between the input and removal of lignin in these mesic boreal forests. When combined with previous knowledge of these forest ecosystems, including the diagenetic state of SON and direct measures of C fluxes and stocks, the results indicate a coupled increase in C and N cycling with climate warming that supports forest productivity and maintains SOC stocks. This balance could markedly shift as other factors begin to limit forest productivity (e.g., trace nutrients, water) with further climate change or affect forest nutrient allocation (e.g., forest age or compositional change). Further application of the approach presented here could be used to detect the limits of this and other ecosystem–climate feedbacks, by providing a tractable and parameterizable index of the lignin state across large spatial scales, necessary for ecosystem-scale parameterizations.

Earth’s biogeochemical cycles are intimately tied to the biotic and abiotic processing of organic matter (OM). Spatial and temporal variation in OM chemistry is often studied using high resolution mass spectrometry (HRMS). An increasingly common approach is to use ecological metrics (e.g., within-sample diversity) to summarize high-dimensional HRMS data, notably Fourier transform ion cyclotron resonance MS (FTICR MS). However, problems arise when HRMS peak intensity data are used in a way that is analogous to abundances in ecological analyses (e.g., species abundance distributions). Using peak intensity data in this way requires the assumption that intensities act as direct proxies for concentrations, which is often invalid. Here we discuss theoretical expectations and provide empirical evidence why concentrations do not map to HRMS peak intensities. The theory and data show that comparisons of the same peak across samples (within-peak) may carry information regarding variation in relative concentration, but comparing different peaks (between-peak) within or between samples does not. We further developed a simulation model to study the quantitative implications of both within-peak and between-peak errors that decouple concentration from intensity. These implications are studied in terms of commonly used ecological metrics that quantify different aspects of diversity and functional trait values. We show that despite the poor linkages between concentration and intensity, the ecological metrics often perform well in terms of providing robust qualitative inferences and sometimes quantitatively-accurate estimates of diversity and trait values. We conclude with recommendations for using peak intensities in an informed and robust way for natural organic matter studies. A primary recommendation is the use and extension of the simulation model to provide objective, quantitative guidance on the degree to which conceptual and quantitative inferences can be made for a given analysis of a given dataset. Without objective guidance, researchers that use peak intensities are doing so with unknown levels of uncertainty and bias, potentially leading to spurious scientific outcomes.

Numerous initiatives at the national, state, and local levels are focused on addressing the U.S. maternal health crisis. However, most efforts fail to center women’s voices and personal perspectives about pregnancy experiences and complications. This article describes the Illinois Maternal Health Digital Storytelling Project conducted by the University of Illinois at Chicago, in partnership with StoryCenter, a storytelling nonprofit organization based in Berkeley, California. The project aimed to elevate voices (stories) to complement other sources of data on maternal outcomes. We relied on partners to help recruit storytellers with a self-identified perinatal-related challenge. We screened interested individuals using a trauma-informed approach and a social worker provided storytellers with support during the project. Two groups participated in this project, one in 2021 and another in 2022, culminating with 10 digital stories. Both instances were conducted virtually and included group and individual skills-based sessions where storytellers learned to create and edit their digital stories. The storytellers own their digital stories and provided consent to include them in ongoing dissemination efforts. In September 2021, a webpage was launched to house the stories, and this resource is being shared widely. Evaluation efforts of the webpage are ongoing to understand how these digital stories are being used to inform maternal health efforts. Digital stories add richness to ongoing maternal health prevention work and may serve as a powerful tool to elicit understanding among providers, practitioners, and constituents.

Background and Objectives: Preexposure prophylaxis (PrEP) reduces HIV transmission among high-risk individuals. Yet, the HIV epidemic continues to expand among marginalized populations and America’s Southeastern states. Various barriers remain to PrEP uptake, namely provider knowledge and education. We sought to investigate residency training, competency, and prescribing of PrEP among population size. Additionally, we asked program directors to identify barriers to PrEP. Methods: We surveyed family medicine program directors as part of the Council of Academic Family Medicine Educational Research Alliance survey from January 2018 through February 2018. Results: Our survey questions had a 52.9% (276/522) response rate. No programs in rural communities less than 30,000 population (0/27) reported significant PrEP training for their residents; those in nonrural communities of at least 30,000 reported this training more frequently (41/246, 16.7%). Compared to Fischer expected values, the finding was statistically significant (P=.019); using a 75,000 population demarcation lowered significance (P=.192). We found programs that identify significant PrEP training also cite more PrEP prescribing within their practice (OR 7.27, P