Accuracy and precision of tidal wetland soil carbon mapping in the conterminous United States

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Scientific Reports 8 (2018): 9478, doi:10.1038/s41598-018-26948-7.Tidal wetlands produce long-term soil organic carbon (C) stocks. Thus for carbon accounting purposes, we need accurate and precise information on the magnitude and spatial distribution of those stocks. We assembled and analyzed an unprecedented soil core dataset, and tested three strategies for mapping carbon stocks: applying the average value from the synthesis to mapped tidal wetlands, applying models fit using empirical data and applied using soil, vegetation and salinity maps, and relying on independently generated soil carbon maps. Soil carbon stocks were far lower on average and varied less spatially and with depth than stocks calculated from available soils maps. Further, variation in carbon density was not well-predicted based on climate, salinity, vegetation, or soil classes. Instead, the assembled dataset showed that carbon density across the conterminous united states (CONUS) was normally distributed, with a predictable range of observations. We identified the simplest strategy, applying mean carbon density (27.0 kg C m−3), as the best performing strategy, and conservatively estimated that the top meter of CONUS tidal wetland soil contains 0.72 petagrams C. This strategy could provide standardization in CONUS tidal carbon accounting until such a time as modeling and mapping advancements can quantitatively improve accuracy and precision.Synthesis efforts were funded by NASA Carbon Monitoring System (CMS; NNH14AY67I), USGS LandCarbon and the Smithsonian Institution. J.R.H. was additionally supported by the NSF-funded Coastal Carbon Research Coordination Network while completing this manuscript (DEB-1655622). J.M.S. coring efforts were funded by NSF (EAR-1204079). B.P.H. coring efforts were funded by Earth Observatory (Publication Number 197)

Dataset: Mangrove, tidal wetland and seagrass soil carbon stocks along latitudinal gradients

Coastal and marine ecosystems have the potential to produce and sequester organic carbon at rates that exceed tropical and temperate forests. Recent recognition of the value of these ecosystems as significant carbon sinks has strengthened worldwide interest in their management, conservation, and restoration for the purpose of climate change mitigation. However, many gaps in understanding carbon sequestration in coastal ecosystems remain, creating challenges for the application coastal ecosystem carbon research at local, regional and global scales. A major limitation is the fact that most research on this topic has been conducted in relatively few temperate and tropical ecosystems, despite a tremendous amount of spatial variability in carbon stocks across gradients of climate, hydrology, geomorphology, and tide range. Additionally, a standardized protocol has not been widely utilized, which would enable more rigorous comparison across ecosystems and climates. The main objective of this research was to apply a standardized method for documenting carbon storage in vegetated coastal ecosystems along latitudinal gradients, including mangroves, tidal wetlands, and seagrass beds. Field sites were located in Twin Cays, Belize, three islands in Bocas del Toro, Panama, the Indian River Lagoon, Florida, Wachapreague, Virginia, three sites in San Francisco Bay, California, and three sites in Kachemak Bay, Alaska. At each mangrove and tidal wetland site, six deep soil cores were retrieved using an open faced gouge corer, ranging in depth from 70 to 496 cm and subsampled at set depth ranges. At each seagrass site, a one meter long piston corer was used to retrieve the core and subsampled using syringes. All samples were dried to a constant weight to determine dry bulk density. Samples were ground with a ball grinder and subsamples were burned in a muffle furnace to determine loss on ignition (LOI). For all seagrass samples, organic carbon was determined by differencing the percent carbon from ashed and unashed samples analyzed with an elemental analyzer. A subset of mangrove and tidal wetland samples were analyzed in an elemental analyzer to determine organic carbon and a relationship between LOI and percent carbon was determined and applied to the remaining samples. Total organic carbon was quantified with depth and summed for each core

Scalability and performance tradeoffs in quantifying relationships between elevation and tidal wetland plant communities

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 post-processing 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

Wetland carbon storage controlled by millennial-scale variation in relative sea-level rise

Coastal wetlands (mangrove, tidal marsh and seagrass) sustain the highest rates of carbon sequestration per unit area of all natural systems primarily because of their comparatively high productivity and preservation of organic carbon within sedimentary substrates. Climate change and associated relative sea-level rise (RSLR) have been proposed to increase the rate of organic-carbon burial in coastal wetlands in the first half of the twenty-first century4, but these carbon-climate feedback effects have been modelled to diminish over time as wetlands are increasingly submerged and carbon stores become compromised by erosion. Here we show that tidal marshes on coastlines that experienced rapid RSLR over the past few millennia (in the late Holocene, from about 4,200 years ago to the present) have on average 1.7 to 3.7 times higher soil carbon concentrations within 20 centimetres of the surface than those subject to a long period of sea-level stability. This disparity increases with depth, with soil carbon concentrations reduced by a factor of 4.9 to 9.1 at depths of 50 to 100 centimetres. We analyse the response of a wetland exposed to recent rapid RSLR following subsidence associated with pillar collapse in an underlying mine and demonstrate that the gain in carbon accumulation and elevation is proportional to the accommodation space (that is, the space available for mineral and organic material accumulation) created by RSLR. Our results suggest that coastal wetlands characteristic of tectonically stable coastlines have lower carbon storage owing to a lack of accommodation space and that carbon sequestration increases according to the vertical and lateral accommodation space created by RSLR. Such wetlands will provide long-term mitigating feedback effects that are relevant to global climate-carbon modelling

Tea Bag Index S and k data of tidal wetland sites

Tidal wetlands, such as tidal marshes and mangroves, are hotspots for carbon sequestration. The preservation of organic matter (OM) is a critical process by which tidal wetlands exert influence over the global carbon cycle and at the same time gain elevation to keep pace with sea-level rise (SLR). The present study provides the first global-scale field-based experimental evidence of temperature and relative sea level effects on the decomposition rate and stabilization of OM in tidal wetlands. The study was conducted in 26 marsh and mangrove sites across four continents, utilizing commercially available standardized OM. While effects on decomposition rate per se were minor, we show unanticipated and combined negative effects of temperature and relative sea level on OM stabilization. Across study sites, OM stabilization was 29 % lower in low, more frequently flooded vs. high, less frequently flooded zones. OM stabilization declined by ~ 90 % over the studied temperature gradient from 10.9 to 28.5 °C, corresponding to a decline of ~ 5 % over a 1 °C temperature increase. Additionally, data from the long-term ecological research site in Massachusetts, US show a pronounced reduction in OM stabilization by > 70 % in response to simulated coastal eutrophication, confirming the high sensitivity of OM stabilization to global change. We therefore provide evidence that rising temperature, accelerated SLR, and coastal eutrophication may decrease the future capacity of tidal wetlands to sequester carbon by affecting the initial transformations of recent OM inputs to soil organic matter

Tea Bag Index S and k data of tidal wetland sites, means overview

Coverage: EVENT LABEL: * LATITUDE: 40.800000 * LONGITUDE: 0.730000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 53.400000 * LONGITUDE: 5.800000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 38.100000 * LONGITUDE: -122.480000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 38.200000 * LONGITUDE: -122.470000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 54.000000 * LONGITUDE: 8.890000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 45.100000 * LONGITUDE: -66.430000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 31.500000 * LONGITUDE: 121.960000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 40.800000 * LONGITUDE: 0.850000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 9.400000 * LONGITUDE: -82.240000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 9.400000 * LONGITUDE: -82.120000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 9.400000 * LONGITUDE: -82.200000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 42.700000 * LONGITUDE: -70.840000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 43.800000 * LONGITUDE: -69.920000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: -37.700000 * LONGITUDE: -57.430000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 54.600000 * LONGITUDE: 18.510000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 53.400000 * LONGITUDE: 5.770000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 38.700000 * LONGITUDE: -76.710000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 38.900000 * LONGITUDE: -76.550000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 48.100000 * LONGITUDE: -69.790000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 38.200000 * LONGITUDE: -122.030000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 53.500000 * LONGITUDE: 6.240000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 54.600000 * LONGITUDE: 8.840000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 53.800000 * LONGITUDE: 7.720000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 42.700000 * LONGITUDE: -70.830000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 16.833300 * LONGITUDE: -88.100000 * LOCATION: Caribbean Sea * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 45.450000 * LONGITUDE: 12.310000 * LOCATION: Venice, Italy * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 40.800000 * LONGITUDE: 0.620000 * METHOD/DEVICE: Multiple investigations EVENT LABEL: * LATITUDE: 37.580000 * LONGITUDE: -75.650000 * LOCATION: North Atlantic Ocea