데이터셋 상세
미국
USGS Pacific Tidal Marsh Soil Core Surveys
We conducted vegetation surveys concurrently with elevation surveys at every fourth elevation point (~25% of the elevation points) (Figure 5). We visually assessed percent cover of all plant species within a 0.25 m2 quadrat, and recorded the average and maximum height (measured to the nearest centimeter) of each species. Total plant cover in a plot could exceed 100% due to vegetation layering. Vascular plant nomenclature generally follows Baldwin et al. (2012) and Cook et al. (2013). We located 69 tidal wetland species in 2,154 vegetation plots across the nine estuaries in the study. Common species included Carex lyngbyei, Sarcocornia perennis, Distichlis spicata, Deschampsia cespitosa, Juncus balticus and Potentilla anserina. The frequency of several common species varied markedly across the sites. Distichlis spicata dominated the flora at five of the nine sites, but was relatively uncommon at Port Susan and Grays Harbor. Deschampsia cespitosa, a middle to high marsh tussock-forming species was frequent at the three Oregon sites and at Willapa but much less common in Puget Sound marshes. The high marsh rush, Juncus balticus, was most frequent at Siletz and absent or rare at Willapa and Padilla. Carex lyngbyei occurrence was variable regionally, ranging from >75% frequency at Bull Island to near absence at Padilla (it did not occur in any surveyed plots, but a few plants were observed at the upland margin of the site in late 2014). See appendices for detailed site specific results.We delineated marsh zones using long-term NOAA tidal data combined with our site-specific elevation and water level data and examined plant abundance in these major zones across the sites. At many sites, plant composition tended to vary by zone, but not necessarily in consistent ways across the region. For instance, at Bandon, Sarcocornia perennis was the most abundant high marsh species (with Deschampsia cespitosa most abundant in middle and low marsh), while S. perennis was the most abundant plant in low marsh at Grays Harbor (Carex spp. dominated in mid-marsh and Potentilla anserina dominated high marsh). Vertical zonation of plant assemblages was less pronounced at other sites, including Nisqually where Distichlis spicata had the highest mean cover in all three major marsh zones. Low marsh habitat was common at Bull Island, Willapa, Nisqually, and Port Susan. Common species in this zone included Sarcocornia perennis, Distichlis spicata, Carex lyngbyei, and Triglochin maritima. Middle tidal marsh was present at all of the sites and particularly common at Skokomish. Common species included all of the aforementioned taxa and Deschampsia cespitosa, Juncus balticus and Agrostis stolonifera. High marsh was only common at Bandon, Siletz, Willapa, Grays Harbor and Padilla. Common high marsh species included many species found in other zones, but also included Potentilla anserine and Atriplex prostrata. Transition zone habitat (defined as wetland flooding at least once per year but no more than once per month) was limited at most of our study sites. Zonation of individual species per site are illustrated in the respective appendices.
데이터 정보
연관 데이터
USGS Pacific Tidal Marsh Soil Core Surveys
공공데이터포털
We conducted vegetation surveys concurrently with elevation surveys at every fourth elevation point (~25% of the elevation points) (Figure 5). We visually assessed percent cover of all plant species within a 0.25 m2 quadrat, and recorded the average and maximum height (measured to the nearest centimeter) of each species. Total plant cover in a plot could exceed 100% due to vegetation layering. Vascular plant nomenclature generally follows Baldwin et al. (2012) and Cook et al. (2013). We located 69 tidal wetland species in 2,154 vegetation plots across the nine estuaries in the study. Common species included Carex lyngbyei, Sarcocornia perennis, Distichlis spicata, Deschampsia cespitosa, Juncus balticus and Potentilla anserina. The frequency of several common species varied markedly across the sites. Distichlis spicata dominated the flora at five of the nine sites, but was relatively uncommon at Port Susan and Grays Harbor. Deschampsia cespitosa, a middle to high marsh tussock-forming species was frequent at the three Oregon sites and at Willapa but much less common in Puget Sound marshes. The high marsh rush, Juncus balticus, was most frequent at Siletz and absent or rare at Willapa and Padilla. Carex lyngbyei occurrence was variable regionally, ranging from >75% frequency at Bull Island to near absence at Padilla (it did not occur in any surveyed plots, but a few plants were observed at the upland margin of the site in late 2014). See appendices for detailed site specific results.We delineated marsh zones using long-term NOAA tidal data combined with our site-specific elevation and water level data and examined plant abundance in these major zones across the sites. At many sites, plant composition tended to vary by zone, but not necessarily in consistent ways across the region. For instance, at Bandon, Sarcocornia perennis was the most abundant high marsh species (with Deschampsia cespitosa most abundant in middle and low marsh), while S. perennis was the most abundant plant in low marsh at Grays Harbor (Carex spp. dominated in mid-marsh and Potentilla anserina dominated high marsh). Vertical zonation of plant assemblages was less pronounced at other sites, including Nisqually where Distichlis spicata had the highest mean cover in all three major marsh zones. Low marsh habitat was common at Bull Island, Willapa, Nisqually, and Port Susan. Common species in this zone included Sarcocornia perennis, Distichlis spicata, Carex lyngbyei, and Triglochin maritima. Middle tidal marsh was present at all of the sites and particularly common at Skokomish. Common species included all of the aforementioned taxa and Deschampsia cespitosa, Juncus balticus and Agrostis stolonifera. High marsh was only common at Bandon, Siletz, Willapa, Grays Harbor and Padilla. Common high marsh species included many species found in other zones, but also included Potentilla anserine and Atriplex prostrata. Transition zone habitat (defined as wetland flooding at least once per year but no more than once per month) was limited at most of our study sites. Zonation of individual species per site are illustrated in the respective appendices.
Elevation Points for Eight Study Areas in Coastal Oregon and Washington, 2012
공공데이터포털
To assess the current topography of tidal marsh at the study sites we conducted survey-grade global positioning system (GPS) surveys between 2009 and 2014 using a Leica RX1200 Real Time Kinematic (RTK) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK GPS network coverage (Padilla, Port Susan, Nisqually, Siletz, Bull Island, and Bandon), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Skokomish, Grays Harbor, and Willapa), rover positions were received in real time from a Leica GS10 antenna base station via radio link. At sites where we used the base station, we adjusted all elevation measurements using an OPUS correction (www.ngs.noaa.gov/OPUS). We used the WGS84 ellipsoid model for vertical and horizontal positioning and referenced positions to a local National Geodetic Survey (NGS) benchmark or a benchmark established by a surveyor (Figure 4). Average measured vertical errors at benchmarks were 1-9 cm throughout the study, comparable to the stated error of the GPS. To measure topographic variation at each site, we surveyed marsh surface elevation along transects perpendicular to the major tidal sediment source, with a survey point taken every 12.5 m; 50 m separated transect lines (Appendix Figs. A1 – I1). We used the Geoid09 model to calculate orthometric heights from ellipsoid measurements (m, NAVD88; North American Vertical Datum of 1988) and projected all points to NAD83 UTM zone 10 using Leica GeoOffice v7.0.1 (Leica Geosystems Inc, Norcross, GA).The feature class contains elevation surveys conducted at the CERCC Bandon marsh study site.
Elevation Points for Eight Study Areas in Coastal Oregon and Washington, 2012
공공데이터포털
To assess the current topography of tidal marsh at the study sites we conducted survey-grade global positioning system (GPS) surveys between 2009 and 2014 using a Leica RX1200 Real Time Kinematic (RTK) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK GPS network coverage (Padilla, Port Susan, Nisqually, Siletz, Bull Island, and Bandon), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Skokomish, Grays Harbor, and Willapa), rover positions were received in real time from a Leica GS10 antenna base station via radio link. At sites where we used the base station, we adjusted all elevation measurements using an OPUS correction (www.ngs.noaa.gov/OPUS). We used the WGS84 ellipsoid model for vertical and horizontal positioning and referenced positions to a local National Geodetic Survey (NGS) benchmark or a benchmark established by a surveyor (Figure 4). Average measured vertical errors at benchmarks were 1-9 cm throughout the study, comparable to the stated error of the GPS. To measure topographic variation at each site, we surveyed marsh surface elevation along transects perpendicular to the major tidal sediment source, with a survey point taken every 12.5 m; 50 m separated transect lines (Appendix Figs. A1 – I1). We used the Geoid09 model to calculate orthometric heights from ellipsoid measurements (m, NAVD88; North American Vertical Datum of 1988) and projected all points to NAD83 UTM zone 10 using Leica GeoOffice v7.0.1 (Leica Geosystems Inc, Norcross, GA).The feature class contains elevation surveys conducted at the CERCC Bandon marsh study site.
Vegetation survey in a coastal marsh at the Grand Bay National Estuarine Research Reserve, Mississippi
공공데이터포털
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 four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each 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 four 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 July 2018 to January 2020, with one set of NST being deployed for six months. 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 (loss-on-ignition [LOI]). For select sampling periods, ancillary data (water level, elevation, turbidity, and wave data) are also provided in this data release. Data were collected during Field Activities Numbers (FAN) 2018-332-FA (18CCT01), 2018-358-FA (18CCT10), 2019-303-FA (19CCT01, 19CCT02, 19CCT03, and 19CCT04, respectively), and 2020-301-FA (20CCT01). 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/. Data from a related NST study in the GNDNERR (Middle Bay and North Rigolets) can be found in Smith and others (2020). Data collected after the living shoreline (subtidal sill) installation can be found in Terrano and others (2025). 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.
Vegetation survey in a coastal marsh at the Grand Bay National Estuarine Research Reserve, Mississippi
공공데이터포털
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 four study sites (Sites 5, 6, 7, and 8) along the Point Aux Chenes Bay shoreline of the Grand Bay National Estuarine Research Reserve, Mississippi (GNDNERR). These datasets were collected to serve as baseline data prior to the installation of a living shoreline (a subtidal sill). Each 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 four 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 July 2018 to January 2020, with one set of NST being deployed for six months. 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 (loss-on-ignition [LOI]). For select sampling periods, ancillary data (water level, elevation, turbidity, and wave data) are also provided in this data release. Data were collected during Field Activities Numbers (FAN) 2018-332-FA (18CCT01), 2018-358-FA (18CCT10), 2019-303-FA (19CCT01, 19CCT02, 19CCT03, and 19CCT04, respectively), and 2020-301-FA (20CCT01). 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/. Data from a related NST study in the GNDNERR (Middle Bay and North Rigolets) can be found in Smith and others (2020). Data collected after the living shoreline (subtidal sill) installation can be found in Terrano and others (2025). 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.
sanpablodem
공공데이터포털
To assess the current topography of the tidal marshes we conducted survey-grade elevation surveys at all sites between 2009 and 2013 using a Leica RX1200 Real Time Kinematic (RTK)Global Positioning System (GPS) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK network coverage (San Pablo, Petaluma, Pt. Mugu, and Newport), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Humboldt, Bolinas, Morro and Tijuana), rover positions were received in real time from a Leica GS10 antenna base station via radio link. When using the base station, we adjusted all elevation measurements using an OPUS correction (www.ngs.noaa.gov/OPUS). We used the WGS84 ellipsoid model for vertical and horizontal positioning. We verified rover accuracy and precision by measuring positions at local National Geodetic Survey (NGS) benchmarks and temporary benchmarks established at each site (Table 1). Average measured vertical errors at benchmarks were 1-2 cm throughout the study, comparable to the stated error of the GPS. At each site, we surveyed marsh surface elevation along transects oriented perpendicular to the major tidal sediment source, with a survey point taken every 12.5 m; 50 m separated transect lines. We used the Geoid09 model to calculate orthometric heights from ellipsoid values (m, NAVD88; North American Vertical Datum of 1988) and projected all points to NAD83 UTM zone 10 or zone 11 using Leica GeoOffice (Leica Geosystems Inc, Norcross, GA, v. 7.0.1).We synthesized the elevation survey data to create a digital elevation model (DEM) at each site in ArcGIS 10.2.1 Spatial Analyst (ESRI 2013; Redlands, CA) with exponential ordinary kriging methods (5 x 5 mcell size) after adjusting model parameters to minimize the root-mean-square error (RMS). We used elevation models as the baseline conditions for subsequent analyses in this study including tidal inundation patterns, SLR response modeling, and mapping of sites by specific elevation (flooding) zones.
Geospatial and Data Services Manager - Wilson Inlet Seagrass Survey - Points (DWER-113)
공공데이터포털
Wilson Inlet was surveyed in December 2017, April 2018, December 2019, December 2020, December 2021 and December 2022 by underwater drop camera observations and/or observations through a viewing cone. Seagrass distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. The canopy height (in 10 cm intevals) and epiphytic cover (as low, medium, high) was also estimated. Macroalgae distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. At approximately a third of the sites, physical water profiles, photosynthetically active radiation (euphotic depth), and secchi depth were recorded. The datasets making up the seagrass survey data are: Wilson_Seagrass - point dataset Wilson_Seagrass_Extent - polygon showing presence/absence derived from points Wilson_Seagrass_Cover - polygon showing percentage cover derived from points Layers: Wilson_Seagrass_Dec_2017 Wilson_Seagrass where Year = '2017' Wilson_Seagrass_Apr_2018 Wilson_Seagrass where Year = '2018' Wilson_Seagrass_Dec_2019 Wilson_Seagrass where Year = '2019' Wilson_Seagrass_Dec_2020 Wilson_Seagrass where Year = '2020' Wilson_Seagrass_Dec_2021 Wilson_Seagrass where Year = '2021' Wilson_Seagrass_Dec_2022 Wilson_Seagrass where Year = '2022' Wilson_Seagrass_Extent_Dec_2017 Wilson_Seagrass_Extent where Year = '2017' Wilson_Seagrass_Extent_Apr_2018 Wilson_Seagrass_Extent where Year = '2018' Wilson_Seagrass_Extent_Dec_2019 Wilson_Seagrass_Extent where Year = '2019' Wilson_Seagrass_Extent_Dec_2020 Wilson_Seagrass_Extent where Year = '2020' Wilson_Seagrass_Extent_Dec_2021 Wilson_Seagrass_Extent where Year = '2021' Wilson_Seagrass_Extent_Dec_2022 Wilson_Seagrass_Extent where Year = '2022' Wilson_Seagrass_Cover_Dec_2017 Wilson_Seagrass_Cover where Year = '2017' Wilson_Seagrass_Cover_Apr_2018 Wilson_Seagrass_Cover where Year = '2018' Wilson_Seagrass_Cover_Dec_2019 Wilson_Seagrass_Cover where Year = '2019' Wilson_Seagrass_Cover_Dec_2020 Wilson_Seagrass_Cover where Year = '2020' Wilson_Seagrass_Cover_Dec_2021 Wilson_Seagrass_Cover where Year = '2021' Wilson_Seagrass_Cover_Dec_2022 Wilson_Seagrass_Cover where Year = '2022'
Geospatial and Data Services Manager - Wilson Inlet Seagrass Survey - Extent (DWER-115)
공공데이터포털
Wilson Inlet was surveyed in December 2017, April 2018, December 2019, December 2020, December 2021 and December 2022 by underwater drop camera observations and/or observations through a viewing cone. Seagrass distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. The canopy height (in 10 cm intevals) and epiphytic cover (as low, medium, high) was also estimated. Macroalgae distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. At approximately a third of the sites, physical water profiles, photosynthetically active radiation (euphotic depth), and secchi depth were recorded. The datasets making up the seagrass survey data are: Wilson_Seagrass - point dataset Wilson_Seagrass_Extent - polygon showing presence/absence derived from points Wilson_Seagrass_Cover - polygon showing percentage cover derived from points Layers: Wilson_Seagrass_Dec_2017 Wilson_Seagrass where Year = '2017' Wilson_Seagrass_Apr_2018 Wilson_Seagrass where Year = '2018' Wilson_Seagrass_Dec_2019 Wilson_Seagrass where Year = '2019' Wilson_Seagrass_Dec_2020 Wilson_Seagrass where Year = '2020' Wilson_Seagrass_Dec_2021 Wilson_Seagrass where Year = '2021' Wilson_Seagrass_Dec_2022 Wilson_Seagrass where Year = '2022' Wilson_Seagrass_Extent_Dec_2017 Wilson_Seagrass_Extent where Year = '2017' Wilson_Seagrass_Extent_Apr_2018 Wilson_Seagrass_Extent where Year = '2018' Wilson_Seagrass_Extent_Dec_2019 Wilson_Seagrass_Extent where Year = '2019' Wilson_Seagrass_Extent_Dec_2020 Wilson_Seagrass_Extent where Year = '2020' Wilson_Seagrass_Extent_Dec_2021 Wilson_Seagrass_Extent where Year = '2021' Wilson_Seagrass_Extent_Dec_2022 Wilson_Seagrass_Extent where Year = '2022' Wilson_Seagrass_Cover_Dec_2017 Wilson_Seagrass_Cover where Year = '2017' Wilson_Seagrass_Cover_Apr_2018 Wilson_Seagrass_Cover where Year = '2018' Wilson_Seagrass_Cover_Dec_2019 Wilson_Seagrass_Cover where Year = '2019' Wilson_Seagrass_Cover_Dec_2020 Wilson_Seagrass_Cover where Year = '2020' Wilson_Seagrass_Cover_Dec_2021 Wilson_Seagrass_Cover where Year = '2021' Wilson_Seagrass_Cover_Dec_2022 Wilson_Seagrass_Cover where Year = '2022'
Geospatial and Data Services Manager - Wilson Inlet Seagrass Survey - Cover (DWER-114)
공공데이터포털
Wilson Inlet was surveyed in December 2017, April 2018, December 2019, December 2020, December 2021 and December 2022 by underwater drop camera observations and/or observations through a viewing cone. Seagrass distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. The canopy height (in 10 cm intevals) and epiphytic cover (as low, medium, high) was also estimated. Macroalgae distribution and cover (as percentage cover in categories: 0, 0-10%, 10-25%, 25-50%, 50-75%, 75-90%, 90-100%) were recorded. At approximately a third of the sites, physical water profiles, photosynthetically active radiation (euphotic depth), and secchi depth were recorded. The datasets making up the seagrass survey data are: Wilson_Seagrass - point dataset Wilson_Seagrass_Extent - polygon showing presence/absence derived from points Wilson_Seagrass_Cover - polygon showing percentage cover derived from points Layers: Wilson_Seagrass_Dec_2017 Wilson_Seagrass where Year = '2017' Wilson_Seagrass_Apr_2018 Wilson_Seagrass where Year = '2018' Wilson_Seagrass_Dec_2019 Wilson_Seagrass where Year = '2019' Wilson_Seagrass_Dec_2020 Wilson_Seagrass where Year = '2020' Wilson_Seagrass_Dec_2021 Wilson_Seagrass where Year = '2021' Wilson_Seagrass_Dec_2022 Wilson_Seagrass where Year = '2022' Wilson_Seagrass_Extent_Dec_2017 Wilson_Seagrass_Extent where Year = '2017' Wilson_Seagrass_Extent_Apr_2018 Wilson_Seagrass_Extent where Year = '2018' Wilson_Seagrass_Extent_Dec_2019 Wilson_Seagrass_Extent where Year = '2019' Wilson_Seagrass_Extent_Dec_2020 Wilson_Seagrass_Extent where Year = '2020' Wilson_Seagrass_Extent_Dec_2021 Wilson_Seagrass_Extent where Year = '2021' Wilson_Seagrass_Extent_Dec_2022 Wilson_Seagrass_Extent where Year = '2022' Wilson_Seagrass_Cover_Dec_2017 Wilson_Seagrass_Cover where Year = '2017' Wilson_Seagrass_Cover_Apr_2018 Wilson_Seagrass_Cover where Year = '2018' Wilson_Seagrass_Cover_Dec_2019 Wilson_Seagrass_Cover where Year = '2019' Wilson_Seagrass_Cover_Dec_2020 Wilson_Seagrass_Cover where Year = '2020' Wilson_Seagrass_Cover_Dec_2021 Wilson_Seagrass_Cover where Year = '2021' Wilson_Seagrass_Cover_Dec_2022 Wilson_Seagrass_Cover where Year = '2022'
Digital Elevation Models for eight study areas in coastal Oregon and Washington, 2012
공공데이터포털
To assess the current topography of tidal marsh at the study sites we conducted survey-grade global positioning system (GPS) surveys between 2009 and 2014 using a Leica RX1200 Real Time Kinematic (RTK) rover (±1 cm horizontal, ±2 cm vertical accuracy; Leica Geosystems Inc., Norcross, GA; Figure 4). At sites with RTK GPS network coverage (Padilla, Port Susan, Nisqually, Siletz, Bull Island, and Bandon), rover positions were received in real time from the Leica Smartnet system via a CDMA modem (www.lecia-geosystems.com). At sites without network coverage (Skokomish, Grays Harbor, and Willapa), rover positions were received in real time from a Leica GS10 antenna base station via radio link. At sites where we used the base station, we adjusted all elevation measurements using an OPUS correction (www.ngs.noaa.gov/OPUS). We used the WGS84 ellipsoid model for vertical and horizontal positioning and referenced positions to a local National Geodetic Survey (NGS) benchmark or a benchmark established by a surveyor (Figure 4). Average measured vertical errors at benchmarks were 1-9 cm throughout the study, comparable to the stated error of the GPS. To measure topographic variation at each site, we surveyed marsh surface elevation along transects perpendicular to the major tidal sediment source, with a survey point taken every 12.5 m; 50 m separated transect lines (Appendix Figs. A1 – I1). We used the Geoid09 model to calculate orthometric heights from ellipsoid measurements (m, NAVD88; North American Vertical Datum of 1988) and projected all points to NAD83 UTM zone 10 using Leica GeoOffice v7.0.1 (Leica Geosystems Inc, Norcross, GA).In ArcGIS 10.2.1 Spatial Analyst (ESRI 2013, Redlands, CA), we created a digital elevation model (DEM) for each site using each sites survey elevation data points. We processed the elevation point data with exponential ordinary kriging methods (5 x 5 m cell size) while adjusting model parameters to minimize the root-mean-square (RMS) error to create the best model fit for the DEM (Table 2). We used elevation models as the baseline conditions for subsequent analyses including tidal inundation patterns, SLR response modeling, and mapping of sites by specific elevation (flooding) zones.