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Coastal wetlands have two dimensions of vulnerability to sea‐level rise (SLR), a vertical one, in cases where SLR outpaces their capacity to vertically accrete, and a lateral one, in cases where they are restricted from migrating inland by topography and land use. We conducted a meta‐analysis of accretion rates, standardized our analysis by using only¹³⁷Cs based estimates, and used model intercomparison to generate a vertical resilience index, a function of local SLR, tidal range, and tidal elevation category for the tidal wetlands of the contiguous US. We paired the vertical resilience index with a lateral resilience index made up of elevation, water level, and land cover maps, then projected them both into the future using localized SLR scenarios. At the regional scale, the vertical resilience index predicts changes from marsh aggradation to submergence for the coastal US Mid‐Atlantic, Southeast, and portions of the Northeast by 2100. At the sub‐regional scale, there is a geographic tradeoff between vertical and lateral resilience with more northerly wetlands vulnerable to the lack of suitable proportional area to migrate into, and more southerly wetlands vulnerable to accretion deficit. We estimate between 43% and 48% of the existing contiguous US wetland area, almost entirely located in watersheds along the Gulf of Mexico and Mid‐Atlantic coasts, is subject to both vertical and lateral limitations. These vertical and lateral resilience indices could help direct future research, planning, and mitigation efforts at a national scale, as well as supplement more processed informed approaches by local planners and practitioners.

 

Abstract Tidal wetlands provide myriad ecosystem services across local to global scales. With their uncertain vulnerability or resilience to rising sea levels, there is a need for mapping flooding drivers and vulnerability proxies for these ecosystems at a national scale. However, tidal wetlands in the conterminous USA are diverse with differing elevation gradients, and tidal amplitudes, making broad geographic comparisons difficult. To address this, a national-scale map of relative tidal elevation ( Z * MHW ), a physical metric that normalizes elevation to tidal amplitude at mean high water (MHW), was constructed for the first time at 30 × 30-m resolution spanning the conterminous USA. Contrary to two study hypotheses, watershed-level median Z * MHW and its variability generally increased from north to south as a function of tidal amplitude and relative sea-level rise. These trends were also observed in a reanalysis of ground elevation data from the Pacific Coast by Janousek et al. (Estuaries and Coasts 42 (1): 85–98, 2019). Supporting a third hypothesis, propagated uncertainty in Z * MHW increased from north to south as light detection and ranging (LiDAR) errors had an outsized effect under narrowing tidal amplitudes. The drivers of Z * MHW and its variability are difficult to determine because several potential causal variables are correlated with latitude, but future studies could investigate highest astronomical tide and diurnal high tide inequality as drivers of median Z * MHW and Z * MHW variability, respectively. Watersheds of the Gulf Coast often had propagated Z * MHW uncertainty greater than the tidal amplitude itself emphasizing the diminished practicality of applying Z * MHW as a flooding proxy to microtidal wetlands. Future studies could focus on validating and improving these physical map products and using them for synoptic modeling of tidal wetland carbon dynamics and sea-level rise vulnerability analyses. 

Abstract. In the age of big data, soil data are more available and richer than ever, but – outside of a few large soil survey resources – they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study.Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight.Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators.Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication.We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices.Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century. 

Elevation is a major driver of plant ecology and sediment dynamics in tidal wetlands, so accurate and precise spatial data are essential for assessing wetland vulnerability to sea-level rise and making forecasts. We performed survey-grade elevation and vegetation surveys of the Global Change Research Wetland, a brackish microtidal wetland in the Chesapeake Bay estuary, Maryland (USA), to both intercompare unbiased digital elevation model (DEM) creation techniques and to describe niche partitioning of several common tidal wetland plant species. We identified a tradeoff between scalability and performance in creating unbiased DEMs, with more data intensive methods such as kriging performing better than 3 more scalable methods involving postprocessing of light detection and ranging (LiDAR)-based DEMs. The LiDAR Elevation Correction with Normalized Difference Vegetation Index (LEAN) method provided a compromise between scalability and performance, although it underpredicted variability in elevation. In areas where native plants dominated, the sedge Schoenoplectus americanus occupied more frequently flooded areas (median: 0.22, 95% range: 0.09 to 0.31 m relative to North America Vertical Datum of 1988 [NAVD88]) and the grass Spartina patens, less frequently flooded (0.27, 0.1 to 0.35 m NAVD88). Non-native Phragmites australis dominated at lower elevations more than the native graminoids, but had a wide flooding tolerance, encompassing both their ranges (0.19, −0.05 to 0.36 m NAVD88). The native shrub Iva frutescens also dominated at lower elevations (0.20, 0.04 to 0.30 m NAVD88), despite being previously described as a high marsh species. These analyses not only provide valuable context for the temporally rich but spatially restricted data collected at a single well-studied site, but also provide broad insight into mapping techniques and species zonation. 

Soil carbon has been measured for over a century in applications ranging from understanding biogeochemical processes in natural ecosystems to quantifying the productivity and health of managed systems. Consolidating diverse soil carbon datasets is increasingly important to maximize their value, particularly with growing anthropogenic and climate change pressures. In this progress report, we describe recent advances in soil carbon data led by the International Soil Carbon Network and other networks. We highlight priority areas of research requiring soil carbon data, including (a) quantifying boreal, arctic and wetland carbon stocks, (b) understanding the timescales of soil carbon persistence using radiocarbon and chronosequence studies, (c) synthesizing long-term and experimental data to inform carbon stock vulnerability to global change, (d) quantifying root influences on soil carbon and (e) identifying gaps in model–data integration. We also describe the landscape of soil datasets currently available, highlighting their strengths, weaknesses and synergies. Now more than ever, integrated soil data are needed to inform climate mitigation, land management and agricultural practices. This report will aid new data users in navigating various soil databases and encourage scientists to make their measurements publicly available and to join forces to find soil-related solutions.