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122 results for “Spartina alterniflora”
Above- and below-ground non-structural carbohydrates (NSC) in Spartina alterniflora from 6 permanant plots near the Georgia Coastal Ecosysterms LTER flux tower, on Sapelo Island in Georgia, USA
We studied the dynamics of four non-structural carbohydrates (glucose, fructose, sucrose, and starch) and biomass in 8 different above- and below-ground tissues in Spartina alterniflora over the course of a year in a salt marsh on Sapelo Island, Georgia, USA. Tissue parts sampled included green leaves, green stems, yellow leaves, yellow stems, brown leaves and stem, flowers, belowground biomass from 0-10cm depth and belowground biomass from 10-30cm depth. Samples were collected from tall form S. alterniflora plots near the Georgia Coastal Ecosystems LTER flux tower site monthly between September 2013 and August 2014. This study was conducted to support the development of predictive, mechanistic models of Spartina by providing information on below-ground biomass and its dynamics, and in particular the storage of resources that can be used for spring re-growth.
Spartina alterniflora marsh vegetation data along the Georgia coast used in the Belowground Ecosystem Resiliency Model version 2.0
Study plots (1-m2) were established in eight Spartina alterniflora-dominated marshes (7 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia). At three sites, plots were sampled once each during May, July, August, September, and October of 2016. At all sites, plots were sampled once each during June, August, and November of 2021, February, May, August, and November of 2022, and February of 2023. One long-term (quarterly 2013 to 2023) GCE LTER sampling site is also included. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 and -9 pixel footprints, with 3 plots per pixel footprint. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots. This dataset reflects an update to the "PLT-GCED-2106" dataset (doi: 10.6073/pasta/03f4f78c6498aecca34faf4339591129). This project also utilized data from the "PLT-GCEM-1610" dataset doi: 10.6073/pasta/9746c71b35e9f8c544ea12c601c33949). Those data utilized in this project are duplicated here for completeness.
Spartina alterniflora above- and belowground biomass predictions and inundation intensity as estimated by the Belowground Ecosystem Resiliency Model for U.S. Georgia marshes from 2014 to 2023.
We applied the Belowground Ecosystem Resiliency Model (BERM) to estimate monthly aboveground biomass (AGB) and belowground biomass (BGB) in U.S. Georgia Spartina alterniflora marshes from 2014 to 2023 at 30 m scale. This application involved BERM version 2.0 (https://doi.org/10.5281/zenodo.13306821), which was built using data in the PLT-GCET-2308 dataset (https://dx.doi.org/10.6073/pasta/4a0b715104849d98320fcc34e7cd63a4). Data sources for BERM application included Landsat-8/9, NOAA CO-OPS Station ID: 8670870, Daymet, and USGS 3DEP 2018 DEM. Download and processing steps are described in the BERM code and in metadata methods section. Specific descriptions of data processing are available in model code: https://doi.org/10.5281/zenodo.13306821. Data provided here include model output of AGB estimates, BGB estimates, and calculated inundation intensity. See "Data reporting" method in the metadata for description of data files. For logisitical purposes here we present only select data from the model input and output. All model input data sources as listed in the abstract are publicly available. Model calibration data and code are published as well. Additional predictions not published here include foliar chlorophyll, foliar nitrogen, and leaf area index.
LTREB: Marsh elevation change in control and fertilized plots in a Spartina alterniflora-dominated salt marsh, North Inlet, Georgetown, SC: 1990-2025.
Marsh elevation was measured with a Surface Elevation Table (SET) as a component of a long-term project seeking to understand how salt marsh primary production and sediment chemistry respond to anthropogenic (e.g. eutrophication) and natural (e.g. sea-level rise) environmental change. Feedbacks between plants, sediments, nutrients and flooding were investigated with particular attention to mechanisms that keep marshes in equilibrium with sea level. Other data collected as part of the project include aboveground annual primary productivity, plant biomass, plant density and porewater nutrient concentrations. These data have been used to develop the Marsh Equilibrium Model, an important tool for coastal resource managers. Sampling occurred at 7 Spartina alterniflora-dominated salt marsh sites in North Inlet, a relatively pristine estuary near Georgetown, SC on the SE coast of the United States. North Inlet is a tidally-dominated, bar-built estuary, with a semi-diurnal mixed tide and a tidal range of 1.4m. The 25-km2 estuary is comprised of about 20.5 km2 of intertidal salt marsh and mudflats, and 4.5 km2 of open water. Marsh elevation sampling began in 1990, 1991, 1996 or 2000, depending on the site. Sampling occurred approximately monthly or approximately annually through 2025. The study is on-going. Additionally, some plots were fertilized with nitrogen and phosphorus.
LTREB: Aboveground biomass, plant density, annual aboveground productivity, plant heights and snail observations in control and fertilized plots in a Spartina alterniflora-dominated salt marsh, North Inlet, Georgetown, SC: 1984-2025
Aboveground biomass and plant density were measured non-destructively as a component of a long-term project seeking to understand how salt marsh primary production and sediment chemistry respond to anthropogenic (e.g. eutrophication) and natural (e.g. sea-level rise) environmental change. Feedbacks between plants, sediments, nutrients and flooding were investigated with particular attention to mechanisms that keep marshes in equilibrium with sea level. Biomass was calculated from plant height measurements using allometric equations. Annual productivity was calculated from approximately-monthly biomass estimates. In addition to plant height measurements, observations of snails in sample plots were recorded. Other data collected as part of the project include marsh surface elevation and porewater nutrient concentrations. These data have been used to develop the Marsh Equilibrium Model, an important tool for coastal resource managers. Sampling occurred at Spartina alterniflora-dominated salt marsh sites in North Inlet, a relatively pristine estuary near Georgetown, SC on the SE coast of the United States. North Inlet is a tidally-dominated, bar-built estuary, with a semi-diurnal mixed tide and a tidal range of 1.4m. The 25-km2 estuary is comprised of about 20.5 km2 of intertidal salt marsh and mudflats, and 4.5 km2 of open water. Sampling began at one location in 1984, and at three additional locations in 1986. Sampling occurred approximately monthly through 2025. The study is on-going. There are four sampling locations at two sites. Two locations are in the low marsh; two locations are in the high marsh. One high marsh location had control sampling plots in addition to plots fertilized with nitrogen and phosphorus.
Porewater nutrient concentrations in control and fertilized plots in a Spartina alterniflora-dominated salt marsh, North Inlet, Georgetown, SC : 1993-2025
Porewater nutrient concentrations were measured as a component of a long-term project seeking to understand how salt marsh primary production and sediment chemistry respond to anthropogenic (e.g. eutrophication) and natural (e.g. sea-level rise) environmental change. Feedbacks between plants, sediments, nutrients and flooding were investigated with particular attention to mechanisms that keep marshes in equilibrium with sea level. Other data collected as part of the project include aboveground macrophyte biomass, plant density, marsh surface elevation and annual above ground primary productivity. These data have been used to develop the Marsh Equilibrium Model, an important tool for coastal resource managers. Sampling occurred at Spartina alterniflora-dominated salt marsh sites in North Inlet, a relatively pristine estuary near Georgetown, SC on the SE coast of the United States. North Inlet is a tidally-dominated, bar-built estuary, with a semi-diurnal mixed tide and a tidal range of 1.4m. The 25-km2 estuary is comprised of about 20.5 km2 of intertidal salt marsh and mudflats, and 4.5 km2 of open water. Sampling began at two locations in December 1993, and at three additional locations in January 1994. Sampling occurred approximately monthly at these 5 locations through 2025. Sampling occurred at a sixth location from 2006 to 2010. The site was a dieback site that had recovered by 2010. At the other sites, the study is on-going. Porewater was collected at multiple depths from diffusion samplers and was analyzed for sulfide, salinity, ammonium, phosphate, and iron concentrations. There are five sampling locations at three sites. Two locations are in the low marsh; three locations are in the high marsh. One high marsh location had control sampling plots in addition to plots fertilized with nitrogen and phosphorus.
Marsh vegetation data in Spartina alterniflora and Distichlis spicata marshes along the Texas coast, 2022 - 2024
We measured plant biomass and plant physiological metrics in two salt marshes in Bayside, Texas, and Port Aransas, Texas, from 2022 - 2024. Study plots (1-m2) were established in two Spartina alterniflora and Distichlis spicata-dominated salt marshes in the Texas Coastal Bend. At one site, S. alterniflora and D. spicata occurred in monoculture cover, and we established six study plots per species cover. Transects of plots encompassed two Landsat-8 and -9 pixel footprints, with a plot density of 3 plots per satellite pixel footprint. At the second site, both species occurred in intermixed stands. At this site we established seven study plots, and plots were not intentionally co-located with satellite pixel footprints. All plots were sampled once each during August and November of 2022, February, May, August, and November of 2023, and February and May of 2024. In each plot, measurements included plant biomass, plant species, stem density, and stem height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot per species) to measure above- and belowground biomass. We measured plant physiological metrics as foliar chlorophyll, foliar N, and Leaf Area Index. Foliar chlorophyll and foliar N were assessed per species present, and Leaf Area Index was measured once per plot. These measurements were taken in the proximity of the plots. We also measured elevation once at each plot at the start of the study period. At each site, we measured water level with HOBO U20L pressure transducers. We installed a stilling well and placed one transducer above the marsh surface to measure ambient pressure, and one transducer at depth. We used the HOBOware software to calculate water level. Measurements were collected at 15 minute intervals. In instances of ambient pressure equipment failure, ambient pressure
Variation in Landsat 8-estimated land surface temperature with elevation from Spartina alterniflora marsh cross sections in the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) site and Virginia Coast Reserve (VCR) LTER sites for winter and summer observations spanning 2013-2018
We estimated land surface temperature from top of atmosphere brightness temperature provided by Landsat 8's band 10 (a thermal band). We collected these measurements first for Spartina alterniflora dominated marsh near the Georgia Coastal Ecosystems Long Term Ecological Research (GCE-LTER) eddy covariance flux tower. Measurements were collected from pixels along three east-west cross sections that spanned a marsh edge to interior gradient. We extracted Landsat 8 data for all available cloud-free low tide dates during August, September, January and February during the years 2013 to 2018 and associated these with marsh elevation information from a 1 m^2 Digital Elevation Model (DEM), created by Haldik et al 2013, also available from the GCE data catalog (http://dx.doi.org/10.6073/pasta/4c5187ef603f70cd0a77ece24ef0fed9). We rescaled the DEM to the coarser spatial resolution of Landsat 8 (30 x 30 m) where the rescaled elevation was the mean of the constituent DEM values. Ultimately, we used generalized additive models to relate land surface temperature to elevation, while accounting for variation from spatial proximity, transect and sample date. These models revealed that land surface temperature was negatively related to marsh elevation on the marsh platform. We then confirmed the generality of this pattern by rederiving these same relationships for three cross sections of Spartina alterniflora marsh at Virginia Coast Reserve (VCR) LTER for winter sampling dates only (data also included here). DEM data for VCR LTER are available at https://www.vcrlter.virginia.edu/gisdata/LIDAR/USGS2015/. We used custom R functions that can convert Landsat 8 top of atmosphere brightness temperature or top of atmosphere radiance from band 10 data to land surface temperature, which are available at https://github.com/jloconnell/convert_top_of_atmosphere_thermal_to_land_surface_temperature. Currently, a provisional land surface temperature product is available on earthexplorer.usgs.gov, w
Leaf area index for Spartina alterniflora near the GCE-LTER Flux Tower in 2018 and 2019
Leaf area index (LAI) was measured at permanent vegetation plots located in the GCE-LTER Flux Tower site for short and medium form Spartina alterniflora. LAI data were collected using a handheld ceptometer in 2018 and 2019.
Monthly Spartina alterniflora marsh vegetation data for additional sites along the Georgia coast used in the Belowground Ecosystem Resiliency Model
Study plots (1-m2) were established in three Spartina alterniflora-dominated marshes - 2 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia, and sampled once each during May, July, August, September, and October of 2016. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 pixel footprints, with 3 plots per pixel foot print. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height, flowering status and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots.
Annual primary productivity of Spartina alterniflora in control and fertilized plots at Law's Point, Rowley River, Plum Island Ecosystem LTER, MA, 1999-2025.
Annual productivity is estimated from aboveground biomass in Spartina alterniflora-dominated salt marsh plots on the Rowley River within the Plum Island Ecosystems (PIE) LTER site. Aboveground biomass is determined non-destructively.
Porewater nutrient concentrations from control plots and fertilized plots at Spartina alterniflora, S.patens and Typha sp. marshes, Plum Island Ecosystem LTER, MA (1999-2025).
Porewater samples from five marsh locations in the Plum Island Ecosystems (PIE) LTER site were collected and analyzed for salinity as well as ammonium, phosphate, sulfide and chloride concentrations throughout the growing season. Three sites (a Typha-dominated brackish marsh, a Spartina alterniflora-dominated salt marsh, and a S. patens-dominated salt marsh) are part of a long term study, and include fertilized and non-fertilized sample plots. Two additional, non-fertilized marsh sites, are located on Nelson Island, near Stackyard Road within the Parker River National Wildlife Refuge.
Change in marsh surface elevation measured with a Surface Elevation Table (SET) at control and fertilized plots at Spartina alterniflora, S.patens and Typha sp. marshes, Plum Island Ecosystems LTER, MA (1999-2025).
A Surface Elevation Table (SET) is used to measure changes in the elevation of the marsh surface at three long term marsh control and fertilization experimental research sites. The sites include one Typha-dominated brackish marsh, one Spartina alterniflora-dominated salt marsh, and one S. patens-dominated salt marsh. Sites are located on the Rowley and upper Parker Rivers in the Plum Island Ecosystems (PIE) LTER.
Surface Elevation Table (SET) data (pin heights) from control and fertilized plots at Spartina alterniflora, S. patens and Typha sp. marshes, Plum Island Ecosystems LTER, MA (1999-2025).
A Surface Elevation Table (SET) is used to measure changes in the elevation of the marsh surface at three long term marsh fertilization experimental research sites. The sites include one Typha-dominated brackish marsh, one Spartina alterniflora-dominated salt marsh, and one S. patens-dominated salt marsh. Sites are located on the Rowley and upper Parker Rivers in the Plum Island Ecosystems (PIE) LTER site.
Plant heights at control and fertilized plots in a Spartina alterniflora-dominated marsh, Law's Point, Rowley River, Plum Island Ecosystem LTER, MA (1999-2025).
Plant heights are measured during the growing season in permanent plots at a Spartina alterniflora-dominated salt marsh on the Rowley River within the Plum Island Ecosystems (PIE) LTER site. Plant heights are converted to plant weight using an algorithm to generate a non-destructive estimate of aboveground plant biomass.
Aboveground plant biomass and density in control and fertilized plots in a Spartina alterniflora-dominated marsh, Rowley River, Plum Island Ecosystem LTER, MA (1999-2025).
Aboveground plant biomass and density is determined non-destructively during the growing season in permanent control and fertilized plots in a Spartina alterniflora-dominated salt marsh at Laws Point on the Rowley River within the Plum Island Ecosystems (PIE) LTER site.
Eddy flux measurements during 2015 from low marsh site (Spartina alterniflora) within Shad Creek catchment, Rowley, Massachusetts.
We deployed an eddy covariance system to measure ecosystem-atmosphere exchange of CO2 above a low marsh system (Spartina alterniflora) located within the Shad creek catchment off Plum Island Sound, Rowley MA. The data represents CO2 exchange for all July to October 2015. This site was established in 2015.
Eddy flux measurements during 2016 from low marsh site (Spartina alterniflora) within Shad Creek catchment, Rowley, Massachusetts, PIE LTER.
We deployed an eddy covariance system to measure ecosystem-atmosphere exchange of CO2 above a low marsh system (Spartina alterniflora) located within the Shad creek catchment off Plum Island Sound, Rowley MA. The data represents CO2 exchange for all July to October 2016. This site was established in 2015.
Eddy flux measurements during 2017 from low marsh site (Spartina alterniflora) within Shad Creek catchment, Rowley, Massachusetts, PIE LTER.
We deployed an eddy covariance system to measure ecosystem-atmosphere exchange of CO2 above a low marsh system (Spartina alterniflora) located within the Shad creek catchment off Plum Island Sound, Rowley MA. The data represents CO2 exchange for all July to October 2017. This site was established in 2015.
Plant heights from permanent plots in a Spartina alterniflora-dominated marsh, Nelson Island, Parker River National Wildlife Refuge, Plum Island Ecosystems LTER, MA (2019-2025).
Plant heights are measured during the growing season in permanent plots at a Spartina alterniflora-dominated salt marsh on Nelson Island, Parker River National Wildlife Refuge, within the Plum Island Ecosystems (PIE) LTER site. Plant heights are converted to plant weight using an algorithm to generate a non-destructive estimate of aboveground plant biomass.
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