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Sediment Temperature, 2015
This data table contains summary data for temperature time series in near-surface sediments in high and low tidal marsh at 7 sites during 2015. These data support the following in-press publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R., Thorne, K.M., Dugger, B.D., and Takekawa, J.Y., 2017. Inundation, vegetation, and sediment effects on litter decomposition in Pacific coast tidal marshes. Ecosystems.
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Vegetation Composition and Marsh Surface Elevation, 2015
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This data table contains plant composition and marsh surface elevation data for 64 plots where Salicornia pacifica litter was buried at 7 sites in 2015. These data support the following in-press publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R., Thorne, K.M., Dugger, B.D., and Takekawa, J.Y., 2017. Inundation, vegetation, and sediment effects on litter decomposition in Pacific coast tidal marshes. Ecosystems.
Litter Decomposition Rates, 2015
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This data set contains decomposition rates for litter of Salicornia pacifica, Distichlis spicata, and Deschampsia cespitosa buried at 7 tidal marsh sites in 2015. Sediment organic matter values were collected at a subset of sites. These data support the following in-press publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R., Thorne, K.M., Dugger, B.D., and Takekawa, J.Y., 2017. Inundation, vegetation, and sediment effects on litter decomposition in Pacific coast tidal marshes. Ecosystems.
Inundation Experiments, 2014
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This data table contains results for the 2014 mesocosm tests of inundation effects on decomposition. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
Decomposition rates and carbon:nitrogen ratios for different litter types, 2015
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This data table contains mean decomposition rates and mean carbon:nitrogen ratios for different litter types buried in 7 marshes during 2015. Note that C:N data are repeated for low and high marsh areas at each site in the table. These data support the following in-press publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R., Thorne, K.M., Dugger, B.D., and Takekawa, J.Y., 2017. Inundation, vegetation, and sediment effects on litter decomposition in Pacific coast tidal marshes. Ecosystems.
Sediment deposition and accretion data from a tidal salt marsh in South San Francisco Bay, California 2021-2022
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The U.S. Geological Survey, Western Ecological Research Center collected sediment and accretion data at a wave-exposed tidal salt marsh in South San Francisco Bay, California. Sediment traps and feldspar marker horizons (MH) were deployed along transects of increasing distance from the sediment source, at primary, secondary and tertiary marsh channels/bay. Data were collected bi-monthly over two month periods in summer 2021 and winter 2021/2022. Included here are trap and MH plot locations, calculated sediment fluxes at each station by deployment period, annual accretion rates, and covariates associated with sediment deposition and accretion including vegetation structure and elevation. This project aimed to assess the temporal and spatial patterns in sediment deposition in order to better understand sediment delivery and marsh resilience to sea-level rise.
Decomposition of plant litter in Pacific coast tidal marshes, 2014-2015
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Decomposition of plant matter is one of the key processes affecting carbon cycling and storage in tidal wetlands. In this study, we evaluated the effects of factors related to climate change (temperature, inundation) and vegetation composition on rates of litter decay in seven tidal marsh sites along the Pacific coast. In 2014 we conducted manipulative experiments to test inundation effects on litter decay at Siletz Bay, OR and Petaluma marsh, CA. In 2015 we studied decay of litter in high and low elevation marshes at seven Pacific coast sites. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
Tidal hydrologic and constitutent loads from First Mallard Water Quality Station in the Rush Ranch Marsh Complex of the San Francisco Bay Estuarine Research Reserve (SFBNERR) 2016-2018
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The data herein report continuous field measurements and specific discrete sampling events associated with water quality and carbon consitutents – both dissolved and particulate forms. These data were coupled with atmospheric flux measurements during the 2017-18 water year to estimate the net storage of fixed carbon within the marsh on an areal basis. Direct and indirect measurement showed 47 to 59% of fixed carbon is stored on site, and most loss is through dissolved inorganic carbon (DIC) export. Comparing this with other tidal wetlands in the U.S. showed similar rates of loss, and a global meta-analysis showed that lateral loss is a proportionally larger term in coastal wetland carbon budgets, relative to other terrestrial systems.
Linear loss of litter over time, 2015
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This table contains data on dry mass remaining in a subset of Salicornia pacifica and Deschampsia cespitosa litter bags removed over a series of time points spanning 6 months. These data support the following publication: Janousek, C.N., Buffington, K.J., Guntenspergen, G.R. et al. Ecosystems (2017). doi:10.1007/s10021-017-0111-6. http://link.springer.com/article/10.1007/s10021-017-0111-6
Chincoteague Bay surface sediment physical parameters data from the spring and fall sampling trips of 2014
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Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center conducted a seasonal collection of surficial sediments from Chincoteague Bay and Tom's Cove, located between Assateague Island and the Delmarva Peninsula in March/April 2014 (2014-301-FA) and October 2014 (2014-322-FA). The sampling efforts were part of a larger U.S. Geological Survey study to assess the effects of storm events on sediment distribution. The objective of this study was to characterize the sediments of Chincoteague Bay in order to create baseline conditions to incorporate with hydrodynamic and sediment transport models in order to evaluate pre- and post-storm (Hurricane Sandy) change. This report serves as an archive for sedimentological data derived from the surface sediment. Data are available for a seasonal comparison between March/April 2014 and October 2014. Downloadable data are available as Excel spreadsheets (sediment samples) and as JPEG files (maps). Additional files include: detailed results of sediment grain size analyses, and formal Federal Geographic Data Committee metadata (data downloads).
Water level data for five sites in the coastal marsh at Grand Bay National Estuarine Research Reserve, Mississippi, from August 2021 through January 2023
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To better understand sediment deposition in marsh environments, scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center (USGS-SPCMSC) selected five marsh study sites (Sites 5, 6, 7, 8, and 9) and four nearshore estuarine study sites (Sites 8S, 8D, 9S, 9D) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve (GNDNERR), Mississippi. This study builds on Smith and others (2020b) and includes datasets collected after the installation of a living shoreline (a subtidal sill [artificial reef]) that was completed in May 2021. Each marsh site consisted of five plots located along a transect perpendicular to the marsh-estuary shoreline at 5-meter (m) increments (5, 10, 15, 20, and 25 m from the shoreline). Each plot contained three to six net sedimentation tiles (NST) that were secured flush to the marsh surface using polyvinyl chloride (PVC) pipe. NST are an inexpensive and simple tool to assess short- and long-term deposition that can be deployed in highly dynamic environments without the compaction associated with traditional coring methods. The NST were deployed for three-month sampling periods, measuring sediment deposition from August 2021 to January 2023. Sediment deposited on the NST were processed to determine physical characteristics, such as deposition thickness, volume, wet weight/dry weight, grain size, and organic content (via loss-on-ignition [LOI]). For select sampling periods, ancillary data (water level, elevation, and vegetation) are also provided in this data release. The estuarine sites consisted of Site 8S (shallow; landward of the subtidal sill), 8D (deep; seaward side of the subtidal sill), as well as 9S and 9D (both sites established adjacent to 8S/8D and the subtidal sill). During select trips water parameters (e.g., waves, water level, and turbidity) were collected at each estuarine site to collect turbidity and wave data. Data presented in this data release were collected under three USGS Field Activities Numbers (FAN; one FAN per year) during thirteen sampling trips (alternate FAN; each sampling trip was assigned a unique alt FAN under the main FAN): 2021-320-FA (21CCT01, 21CCT03, 21CCT04, 21CCT05), 2022-302-FA (22CCT01, 22CCT02, 22CCT03, 22CCT04, 22CCT05, 22CCT06, 22CCT07, 22CCT08) and 2023-301-FA (23CCT01), however, every trip does not contain all data types. This data release also contains data for 2020-323-FA (20CCT02) that was collected as a special collection trip for Hurricane Delta. This data was collected before the subtidal sill was installed and is being published with this data release since pre-subtidal sill data was already published. Additional survey and data details are available from the U.S. Geological Survey Coastal and Marine Geoscience Data System (CMGDS) at, https://cmgds.marine.usgs.gov/. Users can look up USGS FANs in the CMGDS by replacing the FAN in the following url: https://cmgds.marine.usgs.gov/services/activity.php?fan=2022-302-FA. Data from a related NST study in the GNDNERR (Middle Bay and North Rigolets) can be found in Smith and others (2020a). Data collected from before the living shoreline (subtidal sill) installation can be found in Smith and others (2020b). For additional information on data processing and analysis, refer to the accompanying journal publication Smith and others (2025). Please read the full metadata for details on data collection, dataset variables, and data quality.