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29 results for “marsh elevation”
Elevation and soil salinity transects at Airport Marsh and Old Beach Road on Sapelo Island, Georgia in 2001
To examine the relationship between elevation and soil characteristics, I sampled two sites on Sapelo Island (Old Beach Road and Airport Marsh) in July of 2001. At each site, I collected 160 soil samples across a transect from the high to the low marsh, and surveyed the relative elevation of each sample location with a theodolite. I determined soil water content gravimetrically, soil organic content by ashing samples, and soil salinity by rehydrating dried soils, adding deionized water, measuring the salinity of the supernatant, and back calculating to the original soil water content.
PIE LTER surface elevation table (SET) pin height data from twelve marsh sites in northeast Massachusetts.
Surface elevation table (SET) measurements from 26 SETs at 9 marsh sites in the Plum Island Sound Long-Term Ecological Research Site in the Great Marsh, Massachusetts. SET measurements are useful for determining the relative elevation change of marsh sediments. Precise measurements of sediment elevation in marshes is useful for determining rates of elevation change in response to changes in sea level.
Surface Elevation Data for the Upper Phillips Creek Marsh at the Virginia Coast Reserve 1998-2025
This dataset contains data from Surface Elevation Tables (SETs), Root SETs (RSET), and Marker Horizons (MH) located at the Virginia Coast Reserve. NOTE: These research plots are highly sensitive to disturbance and should not be approached by anyone not engaged in taking measurements. Mark Brinson, Robert Christian and Linda Blum conceived the experimental design, installed (1997), and measured (1997-2011) the SET and MH. After Mark Brinson died in 2011, Robert Christian and Linda Blum continued SET and MH measurements through 2017. VCR Staff and Keryn Gedan assumed responsibility for SET and MH measurements subsequent to 2017. Linda Blum and Pat Willis installed the RSET (2003). Pat was responsible for measuring the RSET between (2003-2005). Between 2005-2017, Linda Blum was responsible for measuring the RSET in addition to the SET and MH. Subsequent to 2017, Cora Johnson Baird and Keryn Gedan assumed responsibility for RSET measurements.
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.
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
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.
Corrected LIDAR-derived digital elevation model of the Duplin River salt marshes
LIDAR (light detection and ranging) data were acquired on March 9-10, 2009 by the National Center for Airborne Laser Mapping (NCALM) for the Duplin River (35 km2). A 1 m spatial resolution gridded digital elevation models (DEM) was produced from these data. The accuracy of the DEM was assessed using real time kinematic (RTK) GPS ground reference data and elevations were corrected following the method of Hladik and Alber (2012).
Above- and belowground biomass of S. alterniflora in elevational marsh planter experiments, Plum Island, MA, PIE LTER
Spartina is grown in experimental elevation planters placed in draining ponds on the salt marsh platform. The planters are constructed from PVC pipes of varying lengths. All of the PVC pipes are open at the bottom, and flush to the mudflat surface of the pond, resulting in the tops of the pipes being situated at various relative elevations within the tidal range. Plants growing in the shorter PVC pipes are flooded for a longer duration of each tidal cycle than plants growing in the taller PVC pipes. The growth response of S. alterniflora when exposed to different flood frequencies is monitored by monthly estimates of biomass (determined non-destructively from plant heights) and by destructive 'harvesting' of all above- and belowground plant material at the end of the growing season.
Above- and belowground biomass of S. patens in elevational marsh planter experiments, Plum Island, MA, PIE LTER.
Spartina patens is grown in experimental elevation planters placed in draining ponds on the salt marsh platform. The planters are constructed from PVC pipes of varying lengths. All of the PVC pipes are open at the bottom, and flush to the mudflat surface of the pond, resulting in the tops of the pipes being situated at various relative elevations within the tidal range. Plants growing in the shorter PVC pipes are flooded for a longer duration of each tidal cycle than plants growing in the taller PVC pipes. The growth response of S. patens when exposed to different flood frequencies is monitored by destructive 'harvesting' of all above- and belowground plant material at the end of the growing season.
PIE LTER, marsh surface marker horizon measurements at each Surface Elevation Table (SET) site, Rowley, MA.
Marker horizon depth measurements at each Surface Elevation Table (SET) site. Marker horizons are commonly used in conjunction with the SET. Marker horizons measure vertical accretion which predominantly incorporates surface processes.
PIE LTER marsh vegetation species composition and elevation along nine transects in 2000 and 2001
We selected 9 transects from a set of 40 marsh surveys conducted in 2000 and 2001 to use as a baseline for monitoring changes in species composition and marsh elevation across a broad spatial scale in the Plum Island Estuary. In the early surveys, latitude, longitude and elevation, as well as salt and brackish marsh vegetation composition were documented using cover classes on individual plots. Results from those surveys have been compiled here.
PIE LTER marsh vegetation species composition and elevation along nine transects in 2021
Salt and brackish marsh vegetation distribution was documented using cover classes (modified Braun-Blanquet) on individual plots along 9 transects in the Plum Island Estuary. The plots were also surveyed for elevation rel mNAVD88 using RTK GPS . The plots and transects had been surveyed for vegetation and elevation in 2001. The re-survey is designed to monitor changes in species composition and marsh elevation across a broad spatial scale over the previous 20 years. The survey will also serve as a baseline for future marsh monitoring work with UAVs.
Measurements of aquatic production and respiration in tidal creeks draining high and low elevation marshes.
Production and respiration measurements of aquatic systems can help to inform calculations of whole system metabolism. These measurements are focused on creeks draining high and low elevation marsh systems to develop a better understanding of connectivity between aquatic production and consumption and coastal salt marshes. Production and respiration were determined by measuring oxygen changes in creek water incubated in light and dark bottles.
June - December 2009 RTK survey of salt marsh plant ground elevations to assess the accuracy of a LIDAR-derived digital elevation model.
Real time kinematic (RTK) GPS survey of ground elevations for six plant species (Spartina alterniflora, Juncus roemerianus, Batis maritima, Distichlis spicata, Salicornia virginica and Borrichia frutescens) and two non-vegetated cover classes (salt pan and intertidal mud) was carried out from June to December 2009 to assess the accuracy of a LIDAR-derived digital elevation model. In total, 1389 ground control points (GCP) were collected for the Duplin River (Sapelo Island) and Blackbeard Creek (Blackbeard Island) salt marshes.
February- March 2010 RTK survey of salt marsh plant ground elevations, plant characteristics and soil properties to support analysis of a LIDAR-derived DEM.
Real time kinematic (RTK) GPS survey of ground elevations for six plant species (Spartina alterniflora, Juncus roemerianus, Batis maritima, Distichlis spicata, Salicornia virginica and Borrichia frutescens) and two non-vegetated cover classes (salt pan and intertidal mud) was carried out from February to March 2010 to assess the accuracy of a LIDAR-derived digital elevation model. In total, 369 ground control points (GCP) were collected for the Duplin River (Sapelo Island) and Blackbeard Creek (Blackbeard Island) salt marshes with associated plant and soil charactistics (soil salinity and water content, soil organic matter, soil redox potential). Data were collected to examine the relationships between marsh soil elevation, plant habitat distribution and soil properties and to support the analysis of a a LIDAR-derived digital elevation model (DEM) and RTK data collect in 2009.
Marsh surface elevation data in fertilization plots of a Spartina alterniflora-dominated salt marsh at Goat Island, North Inlet, Georgetown, SC.
A Surface Elevation Table (SET) is used to measure changes in the elevation of the marsh platform in fertilization plots of a Spartina alterniflora-dominated marsh on the Goat Island, North Inlet, Georgetown, SC.
Elevations of Nine Marshes along the Virginia Coast, 2016-2019
Marsh elevation change was measured in nine sites through Global Positioning System (GPS) Real-Time Kinematic (RTK) surveys using Trimble R7 and R10.2 survey equipment. The data includes a table of processed results, plus raw RINEX inputs for the reference locations for each survey, along with OPUS (Online Positioning User Service) solution files for those reference locations. Additionally, ArcGIS data layers are provided both in a geodatabase and as individual shapefiles. Raw RTK surveys were adjusted based on the OPUS solutions for the fixed reference location associated with each survey. All elevations are relative to NAVD88 with GEOID12B and all horizontal locations use the WGS84 datum.
Methane fluxes from four elevation zones in a St. Lawrence Estuary salt marsh
<p>Dataset used in <a href="https://iopscience.iop.org/article/10.1088/2752-664X/ac706a/meta">Spartina alterniflora has the highest methane emissions in a St. Lawrence estuary salt marsh - IOPscience</a>.</p> <p>The dataset contains methane fluxes calculated from gas measurements taken over a 40 or 60 minute period using a dark static chamber method. Methane fluxes were measured at six locations in four elevation zones of a northern salt marsh on the St. Lawrence River estuary at La Pocatière, Quebec (47°22'24.7"N 70°03'26.3"W). Additional environmental data was collected including carbon dioxide fluxes, extractable soil nitrate, extractable soil ammonium, extractable soil dissolved organic carbon, extractable soil total dissolved nitrogen, salinity, temperature, water table depth, soil total organic carbon, soil total nitrogen, soil organic carbon to nitrogen ratio and bulk density. Soil cores were collected from 0-15 cm and used for extractable nutrient analysis, bulk density and soil organic carbon and nitrogen analysis. The work was carried out with funding from the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement 838296, a NSERC Discovery Grant and a Natural Environment Research Council grant number (NE/T012323/1). This dataset is used in a publication entitled <em>Spartina alterniflora</em> has the highest methane emissions in a St. Lawrence Estuary salt marsh in Environmental Research: Ecology (https://doi.org/10.1088/2752- 664X/ac706a), which also contains more details on fieldsite and methodology.</p> <p>Gas samples were collected from dark, static chambers (18L, 26 cm diameter), which were placed onto pre-inserted collars in the vegetated zones (inserted to 2.5 cm, 3 days prior to sampling) or placed directly onto the mudflat. The chambers were insulated and fitted with fans and venting tubes. Gas samples were collected on the 23rd August 2020 from all sites, soil cores were collected between the 24-25th August 2020 and the 19-20th September 2020. Soil samples were collected at 0-15 cm using a 2.5 cm diameter dutch gouge corer.</p> <p>Soil temperature was measured at 10 cm depth using a soil thermometer, (°C, DeltaTrak 11050, Pleasanton, USA), salinity was measured in the laboratory using a portable ATC refractometer. Water table depth was measured using a PVC piezometer, a plastic pipe with tubing was inserted into the piezometer and blown into to determine water table depth through bubbling sound (cm). Soil cores were dried at 60 °C to constant weight and the dry weight over core volume used to calculate bulk density (g cm-3), soil was finely ground and analysed for total organic carbon and total nitrogen (%) using an Elemental Analyser (ThermoFinnigan Flash EA 1112 CN analyser, Carlo Erba, Milan, Italy) with an accuracy of ±5 % for N and ±1 % for C, and a limit of 171 detection of 0.05 % for both N and C. Extractable nitrate+nitrite (assumed to be nitrate) were analysed in soil extractant (2M KCl, 5:1 of extractant to soil) using a microplate reader and methods in Sims et al., 1995 (<a href="https://doi.org/10.1080/00103629509369298">https://doi.org/10.1080/00103629509369298</a>) with a limit of detection of 0.1 ppm and accuracy of ±5%. Extractable dissolved organic carbon and total dissolved nitrogen were analysed in soil extractant (ultrapure water 18.2 MΩ, 5:1 of extractant to soil) on a TOC/TDN analyser (TOC VCSn + TMN-1, Shimadzu, Kyoto, Japan), with a 50 mg C l -1 standard resulting in an accuracy and precision of 3.0 and ±4.4 mg l-1, respectively. CH4 and CO2 concentrations were measured in the gas samples using a gas chromatograph (GC-14, Shimadzu, Kyoto, Japan) fitted with a flame ionisation detector, CO2 was methanised to CH4 before analysis. Standards of CH4 (5.1 ppm) and CO2 (5000 ppm) resulted in an accuracy and precision of 6.6±1.5 and 0.4 ppm, and 5324±324 and 78 ppm, respectively, for CH4 and CO2. Changes in gas concentration over time were converted to fluxes using a linear regression of the linear portion fo the flux and if fluxes were below the minimum detectable concentration difference (see <a href="https://doi.org/10.1002/2017JG003783">https://doi.org/10.1002/2017JG003783</a>), they were set to zero. Results from the experiments were entered into an Excel spreadsheet for ingestion into the Zenodo data repository.</p>
Rates of greenhouse gas (carbon dioxide, methane and nitrous oxide) fluxes, denitrification-derived N2O and N2 fluxes and nitrification-derived N2O fluxes from salt marsh soils in Quebec, Canada and Louisiana, U.S. under ambient and elevated temperature and nutrient loading.
<p>Dataset used in <a href="https://link.springer.com/article/10.1007/s10533-023-01104-0?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20231214&utm_content=10.1007/s10533-023-01104-0#citeas">Elevated temperature and nutrients lead to increased N<sub>2</sub>O emissions from salt marsh soils from cold and warm climates</a>.</p> <p>The dataset contains fluxes calculated from headspace gas samples taken over a 24 hour period from intact soil cores, as well as corresponding environmental data. Intact soil cores (0-15 cm depth, 2.5 cm diameter) were taken at five sampling locations along a 20 m transect using a soil auger or piston corer. Samples were collected along a transect in four marsh sites in Quebec, Canada (La Pocatière: 47°22'24.7"N 70°03'26.3"W) and Louisiana, U.S. (Barataria Basin: 29°33'47.3"N 90°04'22.8"W and 29°29'52.2"N 89°55'00.2"W) from two vegetation types (<em>Sporobolus alterniflorus</em> formerly known as <em>Spartina alterniflora </em>and<em> Sporobolus pumilus</em> formerly known as<em> Spartina patens</em>). In Quebec, the two vegetation zones were in the same marsh whereas in Louisiana two separate marshes, dominated by the relevant vegetation, were chosen. Soil samples were collected on the 20-21<sup>st</sup> July 2021 from Louisiana and the 9-10<sup>th</sup> August 2021 from Quebec. Environmental data was collected including <em>in-situ</em> soil temperature and salinity, and gravimetric soil moisture, extractable soil dissolved organic carbon (DOC), extractable soil total dissolved nitrogen (TDN), extractable soil nitrate, extractable soil ammonium, extractable soil soluble reactive phosphate, soil total carbon, soil total nitrogen, soil carbon to nitrogen ratio, soil d<sup>13</sup>C and soil d<sup>15</sup>N determined from additional 0-15 cm core samples. This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement no. 838296, a NSERC Discovery Grant and a Natural Environment Research Council grant number (NE/T012323/1).</p> <p>Stable <sup>15</sup>N tracers were added to the intact soil cores so that at each location, at each treatment level (ambient and elevated, described below), there was one core receiving no tracer for greenhouse gas fluxes, one core receiving <sup>15</sup>N-NO<sub>3</sub><sup>‑ </sup>for denitrification rates and one core receiving <sup>15</sup>N-NH<sub>4</sub><sup>+</sup> for nitrification rates. The cores were incubated at ambient temperature (16 ℃ and 28.1 ℃ for Quebec and Louisiana, respectively) and nutrient concentrations (3.2 NO<sub>3</sub><sup>-</sup>, 2.0 NH<sub>4</sub><sup>+</sup>; 2.9 NO<sub>3</sub><sup>-</sup>, 2.5 NH<sub>4</sub><sup>+</sup>; 0.5 NO<sub>3</sub><sup>-</sup>, 7.3 NH<sub>4</sub><sup>+ </sup>and 5.7 NO<sub>3</sub><sup>-</sup>, 2.8 NH<sub>4</sub><sup>+</sup> mg g wet soil<sup>-1</sup> for Quebec <em>S. alterniflorus</em>, Quebec <em>S. pumilus</em>, Louisiana <em>S. alterniflorus</em> and Louisiana <em>S. pumilus</em>, respectively), and elevated temperature (ambient temperature +5 ℃) and nutrient concentration (double ambient concentration). Gas samples were collected from the headspace of 0-15 cm intact cores in a 20 cm high PVC pipe, capped at the top and bottom to create a 5 cm headspace. Gas samples were analysed for greenhouse gases (GHGs: N<sub>2</sub>O, CH<sub>4</sub>, CO<sub>2</sub>) and <sup>15</sup>N in denitrification-derived N<sub>2</sub>O, denitrification-derived N<sub>2</sub> and nitrification-derived N­<sub>2</sub>O.</p> <p>Soil temperature (YSI 30, Baton Rouge, USA or DeltaTrak 11050, Pleasanton, USA) and porewater salinity (YSI 30, Baton Rouge, USA or portable ATC refractometer) were measured in-situ or in the laboratory using the portable refactometer. Additional soil samples were used for multiple analyses; one subsample was extracted with ultrapure water (18.2 MΩ) for DOC and TDN analysis, one subsample was extracted with 2M KCl for NO<sub>3</sub><sup>-</sup> and NH<sub>4</sub><sup>+</sup>, one subsample was extracted with Olsen-P solution (0.5 M NaHCO<sub>3</sub>, pH 8.5), for soluble reactive phosphate analysis and one subsample was weighed and dried for soil moisture and then finely ground and analysed for total carbon, total nitrogen, d<sup>13</sup>C and d<sup>15</sup>N.</p> <p>N<sub>2</sub>O, CH<sub>4</sub> and CO<sub>2</sub> concentrations were measured in the gas samples using a gas chromatograph interfaced with a PAL3 autosampler (Agilent 7890A, Agilent Technologies Ltd, USA) fitted with a flame ionisation detector (FID) for CH<sub>4</sub> analysis and a micro electron capture detector (mECD) for N<sub>2</sub>O analysis. CO<sub>2</sub> was methanised to CH<sub>4</sub> before analysis on the FID. The instrument precision as the relative standard deviation was < 5 % for all of the gases, while the minimum detectable concentration difference (MDCD) was 9 ppb N<sub>2</sub>O, 72 ppb CH<sub>4 </sub>and 31 ppm CO<sub>2</sub>. Potential GHG fluxes were calculated from the linear portion or where the highest production was observed in the concentration-time series ( https://doi.org/10.2134/jeq2003.2436). If fluxes were below the MDCD they were set to zero see (https://doi.org/10.1002/2017JG003783). The <sup>15</sup>N content of the N<sub>2</sub> and N<sub>2</sub>O was determined using a continuous flow isotope ratio mass spectrometer (Elementar Isoprime PrecisION; Elementar Analysensysteme GmbH, Hanau, Germany) coupled with a trace-gas pre-concentrator inlet with autosampler (isoFLOW GHG; Elementar Analysensysteme GmbH, Hanau, Germany), with a standard deviation of d<sup>15</sup>N < 0.05 %. Extractable dissolved organic carbon and total dissolved nitrogen were analysed in soil extractant (ultrapure water 18.2 MΩ, 7:1 of extractant to soil) on a TOC/TDN analyser (TOC VCSn + TMN-1, Shimadzu, Kyoto, Japan), with 50 mg C l<sup>-1</sup> and 10 mg l<sup>-1</sup> standards resulting in accuracy and precision of 0.3 and ±0.3 mg C l<sup>-1</sup>, and 0.5 and ±0.3 mg N l<sup>-1</sup>, respectively. Extractable nitrate+nitrite (assumed to be nitrate) and ammonium were analysed in soil extractant (2M KCl, 5:1 of extractant to soil) using a microplate reader and methods in Sims et al., 1995 (<a href="https://doi.org/10.1080/00103629509369298">https://doi.org/10.1080/00103629509369298</a>) with a limit of detection of 0.1 ppm and accuracy of ±5 %. Extractable phosphate was analysed in soil extractant (Olsen-P solution 0.5M NaHCO­<sub>3</sub>, pH 8.5, 10:1 of extractant to dry soil) using a microplate reader and methods in Jeannotte et al., 2004 (https://doi.org/10.1007/s00374-004-0760-4) with a limit of detection of 1 mg P l<sup>-1</sup> and accuracy of ±6 %. Soil total carbon, total nitrogen, d<sup>13</sup>C and d<sup>15</sup>N analysis was performed using a continuous flow isotope ratio mass spectrometer (Elementar Isoprime PrecisION; Elementar Analysensysteme GmbH, Hanau, Germany) coupled with an elemental analyser (EA) inlet (vario PYRO cube; Elementar Analysensysteme GmbH, Hanau, Germany). The precision was < 5 % for both C and N and the precision as a standard deviation was < 0.06 % for both d<sup>13</sup>C and d<sup>15</sup>N. Results from the experiments were entered into an Excel spreadsheet for ingestion into the Zenodo data repository.</p>
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