The U.S. Department of Agriculture‐Agricultural Research Service's (ARS) Experimental Watershed Network grew from Dust Bowl era efforts of the Soil Conservation Service in the mid‐1930s with the ...establishment of small experimental watersheds. In the 1950s, five watershed research centers with intensively instrumented watersheds at the scale of 100 to 700 km2 were established. Primary network research objectives were to quantify on‐site and downstream effects of conservation practices and develop rainfall‐runoff relationships for design of water conservation structures. With passage of the Clean Water Act in 1972, research objectives have evolved to add a variety of observations relevant to the water quality issues. Many of the watersheds within the network have served, and continue to serve, as core validation sites for satellite sensors. As a result of the network's long history and intensive monitoring, coupled with mission‐driven research, a deep knowledge base of watershed processes has been developed. This has led to the extensive development and validation of numerous watershed models that are in widespread use today. The visionary investments in building and maintaining this network and associated scientific investigations for more than half a century have not only resulted in numerous high‐impact research accomplishments but also a wide array of accomplishments that directly benefit society. The ARS Experimental Watersheds formed the core of the Conservation Effects Assessment Project (CEAP) as well as the recently established Long‐Term Agroecosystem Research (LTAR) network. LTAR will expand the mission of the ARS Watersheds Network to include agricultural intensification, maintaining or improving ecosystem services while enhancing rural prosperity.
Plain Language Summary
Understanding how watersheds respond to precipitation, agricultural management, and other land use changes is critical to maintaining clean water, viable food production, and predicting flood hazards and soil loss from erosion. To understand watershed responses and processes, the Soil Conservation Service, followed by the USDA‐Agricultural Research Service, established experimental watersheds across the United States. These watersheds were instrumented with equipment to make detailed measurements of weather and watershed response. Experiments were designed to observe how runoff, erosion, and water quality might change with changing agricultural practices to change agricultural practices and observe how runoff, erosion, and water quality would change. From these experiments, predictive computer models were developed and tested with data from the watersheds. The watershed observations, the process knowledge developed, and associated research and models have resulted in numerous societal benefits. Billions of dollars of conservation measures and drainage infrastructure investment were guided by these models and methods. The ARS Experimental Watersheds formed the core of the recently established Long‐Term Agroecosystem Research (LTAR) network. LTAR will expand the mission of the ARS Watershed Network to include producing more food on the same amout of land, maintaining or improving ecosystem services (clean water and air, healthy soils, etc.) while enhancing rural prosperity.
Key Points
Agricultural Research Service's Experimental Watersheds and associated mission‐driven research have operated for over half a century
High‐resolution watershed observations and experimentation have produced a deep watershed process knowledge and database
The research network has been critical to developing and validating numerous watershed models and management methods, resulting in extensive societal benefits
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The spatial distribution of lymphocyte clones within tissues is critical to their development, selection, and expansion. We have developed spatial transcriptomics of variable, diversity, and joining ...(VDJ) sequences (Spatial VDJ), a method that maps B cell and T cell receptor sequences in human tissue sections. Spatial VDJ captures lymphocyte clones that match canonical B and T cell distributions and amplifies clonal sequences confirmed by orthogonal methods. We found spatial congruency between paired receptor chains, developed a computational framework to predict receptor pairs, and linked the expansion of distinct B cell clones to different tumor-associated gene expression programs. Spatial VDJ delineates B cell clonal diversity and lineage trajectories within their anatomical niche. Thus, Spatial VDJ captures lymphocyte spatial clonal architecture across tissues, providing a platform to harness clonal sequences for therapy.
To address our climate emergency, “we must rapidly, radically reshape society”—Johnson & Wilkinson, All We Can Save. In science, reshaping requires formidable technical (cloud, coding, ...reproducibility) and cultural shifts (mindsets, hybrid collaboration, inclusion). We are a group of cross‐government and academic scientists that are exploring better ways of working and not being too entrenched in our bureaucracies to do better science, support colleagues, and change the culture at our organizations. We share much‐needed success stories and action for what we can all do to reshape science as part of the Open Science movement and 2023 Year of Open Science.
To address our climate emergency, “we must rapidly, radically reshape society”—Johnson & Wilkinson, All We Can Save. In science, reshaping requires formidable technical (cloud, coding, and reproducibility) and cultural shifts (mindsets, hybrid collaboration, and inclusion). We are a group of cross‐government and academic scientists who are exploring better ways of working and not being too entrenched in our bureaucracies to do better science, support colleagues, and change the culture at our organizations, and we share much‐needed success stories and action for what we can all do to reshape science as part of the Open Science movement and 2023 Year of Open Science.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
J. Neurochem. (2010) 114, 215-225. Neuropeptides are produced from larger precursors by limited proteolysis, first by endopeptidases and then by carboxypeptidases. Major endopeptidases required for ...these cleavages include prohormone convertase (PC) 1/3 and PC2. In this study, quantitative peptidomics analysis was used to characterize the specific role PC1/3 plays in this process. Peptides isolated from hypothalamus, amygdala, and striatum of PC1/3 null mice were compared with those from heterozygous and wild-type mice. Extracts were labeled with stable isotopic tags and fractionated by HPLC, after which relative peptide levels were determined using tandem mass spectrometry. In total, 92 peptides were found, of which 35 were known neuropeptides or related peptides derived from 15 distinct secretory pathway proteins: 7B2, chromogranin A and B, cocaine- and amphetamine-regulated transcript, procholecystokinin, proenkephalin, promelanin concentrating hormone, proneurotensin, propituitary adenylate cyclase-activating peptide, proSAAS, prosomatosatin, provasoactive intestinal peptide, provasopressin, secretogranin III, and VGF. Among the peptides derived from these proteins, ~1/3 were decreased in the PC1/3 null mice relative to wild-type mice, ~1/3 showed no change, and ~1/3 increased in PC1/3 null. Cleavage sites were analyzed in peptides that showed no change or that decreased in PC1/3 mice, and these results were compared with peptides that showed no change or decreased in previous peptidomic studies with PC2 null mice. Analysis of these sites showed that while PC1/3 and PC2 have overlapping substrate preferences, there are particular cleavage site residues that distinguish peptides preferred by each PC.
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The aerodynamic roughness of heat, moisture, and momentum of a natural surface are important parameters in atmospheric models, as they co-determine the intensity of turbulent transfer between the ...atmosphere and the surface. Unfortunately this parameter is often poorly known, especially in remote areas where neither high-resolution elevation models nor eddy-covariance measurements are available. In this study we adapt a bulk drag partitioning model to estimate the aerodynamic roughness length (z0m) such that it can be applied to 1D (i.e. unidirectional) elevation profiles, typically measured by laser altimeters. We apply the model to a rough ice surface on the K-transect (west Greenland Ice Sheet) using UAV photogrammetry, and we evaluate the modelled roughness against in situ eddy-covariance observations. We then present a method to estimate the topography at 1 m horizontal resolution using the ICESat-2 satellite laser altimeter, and we demonstrate the high precision of the satellite elevation profiles against UAV photogrammetry. The currently available satellite profiles are used to map the aerodynamic roughness during different time periods along the K-transect, that is compared to an extensive dataset of in situ observations. We find a considerable spatio-temporal variability in z0m, ranging between 10−4 m for a smooth snow surface and 10−1 m for rough crevassed areas, which confirms the need to incorporate a variable aerodynamic roughness in atmospheric models over ice sheets.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies ...(TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e.
P
< 3.85e−6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes,
RGS19
and
KPTN
, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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