I. Data Set Descriptors A. Title: Amanda C. Spivak. 2024. Decomposition, porewater, plant and animal collection, and soil temperature data in Airport Marsh, Sapelo Island, 7/2019-7/2020. Georgia Coastal Ecosystems LTER Data Catalog (data set ORG-GCED-2404; /data/ORG-GCED-2404) B. Accession Number: ORG-GCED-2404 C. Description 1. Originator(s): Name: Amanda C. Spivak Address: Marine Science Rm. 164 Marine Sciences Athens, Georgia 30602-3636 Country: USA Email: aspivak@uga.edu 2. Abstract: Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the tea bag index (TBI). Tea bags were buried at 10- and 50- cm along transects sited at lower, middle, and higher elevations that paralleled a headward eroding tidal creek. Plant and animal communities and soil properties were characterized once while replicate tea bags and porewaters were collected 3 and 4 times respectively over one year. 3. Study Type: Directed Study 4. Study Themes: Organic Matter/Decomposition, Marsh Ecology 5. LTER Core Areas: Organic Matter 6. Georeferences: geographic coordinates as data columns 7. Submission Date: Apr 29, 2024 D. Keywords: biogeochemistry, decomposition, ecology, GCE, Georgia, Georgia Coastal Ecosystems, LTER, marshes, organic, Organic Matter, Sapelo Island, USA II. Research Origin Descriptors A. Overall Project Description 1. Project Title: Georgia Coastal Ecosystems LTER - IV 2. Principal Investigators: Name: Merryl Alber Address: Dept. of Marine Sciences University of Georgia Athens, Georgia 30602-3636 Country: USA Email: malber@uga.edu 3. Funding Period: Feb 01, 2019 to Jan 31, 2025 4. Objectives: The GCE-LTER project has four goals. 1) Track environmental and human drivers that can cause perturbations in our focal ecosystems. This will be accomplished this through continuing long-term measurements of climate, water chemistry, oceanic exchange, and human activities on the landscape. 2) Describe temporal and spatial variability in physical, chemical, geological and biological characteristics of the study system (coastal wetland complexes) and how they respond to external drivers. This will be accomplished through field monitoring in combination with remote sensing and modeling. 3) Characterize the ecological responses of intertidal marshes to disturbance. This will be accomplished by ongoing monitoring and experimental work to evaluate system responses to major perturbations in three key marsh habitats (changes in inundation and predator exclusion in Spartina-dominated salt marshes; increases in salinity in fresh marshes; changes in runoff in high marshes), by implementing standardized experimental disturbances along salinity and elevation gradients, and by tracking responses to natural disturbances. 4) Evaluate ecosystem properties at the landscape level (habitat distribution, net and gross primary production, C budgets) and assess the cumulative effects of disturbance on these properties. The project will also develop relationships between drivers and response variables, which can be used to predict the effects of future changes. This will be accomplished through a combination of data synthesis, remote sensing and modeling. 5. Abstract: The Georgia Coastal Ecosystems (GCE) Long Term Ecological Research (LTER) program, based at the University of Georgia Marine Institute on Sapelo Island, Georgia, was established in 2000 to study long-term change in coastal ecosystems. Estuaries (places where salt water from the ocean mixes with fresh water from the land) and their adjacent marshes provide food and refuge for fish, shellfish and birds; protect the shoreline from storms; help to keep the water clean; and store carbon. The GCE LTER researchers study marshes and estuaries to understand how these ecosystems function, to track how they change over time, and to predict how they might be affected by future changes in climate and human activities. They accomplish this by tracking the major factors that can cause long-term change in coastal areas (e.g. sea level, rainfall, upstream development), and measuring the effects of these factors on the study site. They also conduct focused studies to assess how key marsh habitats will respond to major changes expected in the future, including large-scale experiments to evaluate the effects of a) increases in the salinity of the water that floods freshwater marshes (mimicking drought and/or sea level rise), b) changes in water runoff from land into the upland marsh border (mimicking drought or upland development), and c) exclusion of larger organisms in the salt marsh (mimicking long-term declines in predators). During this award they will initiate additional studies to systematically evaluate how coastal wetlands respond to disturbances. Disturbances, or disruptions in the environment, are particularly important to understand in the context of long-term background changes such as increasing sea level, and GCE researchers are working to assess the cumulative effects of multiple disturbances on the landscape. The GCE education and outreach program works to share an understanding of coastal ecosystems with teachers and students, coastal managers, citizen scientist and the general public. 6. Funding Source: NSF OCE 1832178 B. Sub-project Description 1. Site Description a. Geographic Location: Coordinates: b. Physiographic Region: c. Landform Components: d. Hydrographic Characteristics: e. Topographic Attributes: f. Geology, Lithology and Soils: g. Vegetation Communities: h. History of Land Use and Disturbance: none recorded i. Climate: Climate summary for Sapelo Island, Georgia, based on NWS data from 1980-2010: Daily-aggregated Values: Mean (sample standard deviation) mean air temperature: 20.09°C (7.28°C) minimum air temperature: 15.02°C (7.96°C) maximum air temperature: 24.82°C (6.98°C) total precipitation: 3.26mm (10.3mm) Yearly-aggregated Daily Values: Mean (sample standard deviation) total precipitation (1980-2010): 1124mm (266mm) 2. Experimental or Sampling Design a. Design Characteristics: Study plots were established along a tidal creek, with 8 plots at 3 distances from the creekbank edge (near: 0 m, mid: 4 m, and far: 14 m; resulting in 24 plots; S. alterniflora populated all but one plot which was removed from data analyses).Tea bag decay rates and porewater chemistry were measured at two depths (10 and 50 cm) at discrete intervals over one year (July 2019-2020). Soil temperatures were continuously monitored for ~6 months at both depths. This study was conducted alongside that of Wu et al. (2022). b. Permanent Plots: not specified c. Data Collection Duration and Frequency: We buried triplicate rooibos and green tea bags in each of the 24 plots at 10 and 50 cm depth in July 2019. Single replicates were collected after 98 days (~3 months), 188 days (~6 months), and 363 days (~12 months, July 2020). HOBO temperature loggers were deployed in July 2019 and collected 188 days (~6 months) later in January 2020. Only 15 of the 10 cm and 16 of the 50 cm loggers were recovered and the loggers recorded temperature data every 15 minutes. Porewater vials were retrieved two months after deployment (September 2019) reflecting our expectation of dynamic changes during summer, and again at 98, 188, and 363 days, which correspond with the 3- , 6-, and 12- month teabag collections. Soil shear strength, aboveground biomass, belowground biomass, and invertebrate densities were collected once in the summer of 2019. Beginning of Observations: Jul 18, 2019 End of Observations: Jul 14, 2020 3. Research Methods a. Field and Laboratory Methods: Method 1: Decomposition Data Collection -- We used the Tea Bag Index (TBI) from Keuskamp et al. 2013 to measure decay. This method assumes that natural litter is comprised of labile and refractory pools that turnover at different rates and can be represented by Lipton™ green (European Article Number: 87 22700 05552 5) and rooibos (European Article Number: 87 22700 18843 8) teas, respectively. Triplicate bags of each tea type were dried at 60° C and weighed. We then buried in each of the 24 plots at 10 and 50 cm depth in July 2019. Single replicates were collected after 98 days (~3 months), 188 days (~6 months), and 363 days (~12 months, July 2020). Collected tea bags were again dried at 60 °C and mass loss was calculated as the difference between the dried initial and final tea masses, after correcting for contributions from the tea bag, string, and label. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.12097 Method 2: Porewater Collection and Abiotic and Biotic Variable Collections -- All of the following methods were described by Wu et al. 2022, which was done in conjunction with this study: Soil shear strength was measured in the top 4 cm using a field shear vane (GEONOR H-6O). Spartina alterniflora aboveground biomass was estimated based on stem density counts and known masses of representative stems. Belowground biomass was measured by collecting soil cores (10 cm diameter, 30cm depth) centered on a culm of S. alterniflora in each plot and then washing roots and rhizomes free of soil before drying and weighing. The densities of crab burrows (>0.5 cm diameter, all species pooled) and snails (>0.3 cm spire height) were recorded in 0.5 × 0.5 m quadrats at each plot. One passive porewater sipper was deployed in each plot in July 2019 with collection windows at 10 and 50 cm. A single glass scintillation vial, filled with Milli-Q water (18.2 M) and fitted with an open top cap and 50 µm Nitex mesh, was placed upside down in each collection window. Porewater vials were retrieved two months later, reflecting our expectation of dynamic changes during summer, and again at 98, 188, and 363 days, which correspond with the 3- , 6-, and 12- month teabag collections. Collected vials were replaced in the sippers with fresh vials and Milli-Q water. Samples were sealed with solid caps and transported on ice to the University of Georgia Marine Institute where salinity, redox, and pH levels were measured. This sampling approach relies on equilibration of water inside the vial with the surrounding porewater, which happens within one month and was assessed based on salinity readings. Salinity was measured with a handheld refractometer while pH levels and redox potential were measured with a benchtop dual channel pH/ISE meter (Fisherbrand™ Accumet™ XL250, accuracy ±0.002 pH units) and a calibrated pH combination electrode (Fisherbrand™ accuTupH™) or redox oxidation / reduction potential electrode (Mettler Toledo™ InLab™ Redox ORP Electrode), respectively. Redox potential readings (mV) were recorded relative to a reference electrode in a 3.5 M potassium chloride solution and values were subsequently corrected to the standard hydrogen electrode. Https://aslopubs.onlinelibrary.wiley.com/doi/epdf/10.1002/lno.11867 Method 3: Soil Temperature Collection -- Soil temperature at 10 and 50 cm depths was recorded by HOBO loggers (UA-002-08, Onset Computer Corp, accuracy: ± 0.53° C from 0° to 50° C) in 15-minute intervals. Loggers were intercalibrated prior to deployment (SE ± 0.07° C). The loggers were deployed in July 2019 and collected 188 days (~6 months) later in January 2020. Only 15 of the 10 cm and 16 of the 50 cm loggers were recovered. b. Protocols: Method 1: none Method 2: none Method 3: none c. Instrumentation: Method 1: none Method 2: none Method 3: none d. Taxonomy and Systematics: Method 1: not applicable Method 2: not applicable Method 3: not applicable e. Speclies List: f. Permit History: Method 1: not applicable Method 2: not applicable Method 3: not applicable 4. Project Personnel a. Personnel: 1: Amanda C. Spivak 2: Satyatejas Reddy 3: Fengrun Wu 4: Reilly Farrell 5: Steven C. Pennings b. Affiliations: 1: University of Georgia, Athens, Georgia 2: University of Georgia 3: University of Houston, Houston, Texas 4: null 5: University of Houston, Houston, Texas III. Data Set Status and Accessibility A. Status 1. Latest Update: 22-Nov-2024 2. Latest Archive Date: 18-Nov-2024 3. Latest Metadata Update: 22-Nov-2024 4. Data Verification Status: New Submission B. Accessibility 1. Storage Location and Medium: Stored at GCE-LTER Data Management Office Dept. of Marine Sciences Univ. of Georgia Athens, GA 30602-3636 USA on media: electronic data download (WWW) or compact disk 2. Contact Person: Name: Adam Sapp Address: Department of Marine Sciences University of Georgia Athens, Georgia 30602 Country: USA Email: asapp@uga.edu 3. Copyright Restrictions: not copyrighted 4. Restrictions: This information is licensed under a Creative Commons Attribution 4.0 International License (see: https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) has an ethical obligation to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. a. Release Date: Affiliates: Apr 29, 2024, Public: Apr 29, 2026 b. Citation: Data provided by the Georgia Coastal Ecosystems Long Term Ecological Research Project, supported by funds from NSF OCE 1832178 (data set ORG-GCED-2404) c. Disclaimer: The user assumes all responsibility for errors in judgement based on interpretation of data and analyses presented in this data set. 5. Costs: free electronic data download via WWW, distribution on CD may be subject to nominal processing and handling fee IV. Data Structural Descriptors A. Data Set File 1. File Name: ORG-GCED-2404_decompostion_1_0.CSV 2. Size: 288 records 3. File Format: ASCII text (comma-separated value format) 3a. Delimiters: single comma 4. Header Information: 5 lines of ASCII text 5. Alphanumeric Attributes: 6. Quality Control Flag Codes: Q = questionable value, I = invalid value, E = estimated value 7. Authentication Procedures: 8. Calculations: Initial_Wt_Tea: =Initial_Wt_Total-Correction_Factor Final_Wt_Tea: =Dry_Wt__Boat-Weigh_Boat Mass_Loss: Initial_Wt_Tea - Final_Wt_Tea Percent_Loss: =Final_Wt_Tea/Initial_Wt_Tea Percent_Original_Mass: (1-Percent_Loss)*100 Turnover: 1/k_value k_value: calculations vary - see keuskamp et. al. 2013 Labile_fraction: calculations vary - see keuskamp et. al. 2013 Stabilization: calculations vary - see keuskamp et. al. 2013 9. Processing History: Software version: GCE Data Toolbox Version 3.9.10 (23-May-2022) Data structure version: GCE Data Structure 1.1 (29-Mar-2001) Original data file processed: ORG-GCED-2404_decomposition.txt (288 records) Data processing history: 18-Nov-2024: new GCE Data Structure 1.1 created ('newstruct') 18-Nov-2024: 288 rows imported from ASCII data file 'ORG-GCED-2404_decomposition.txt' ('imp_ascii') 18-Nov-2024: 13 metadata fields in file header parsed ('parse_header') 18-Nov-2024: data structure validated ('gce_valid') 18-Nov-2024: updated 1 metadata fields in the Dataset section(s) ('addmeta') 18-Nov-2024: imported Dataset, Project, Site, Study, Status, Supplement metadata descriptors from the GCE Metabase ('imp_gcemetadata') 18-Nov-2024: updated 49 metadata fields in the Dataset, Project, Site, Status, Study, Supplement section(s) ('addmeta') 18-Nov-2024: Variable Type of column Percent_Loss changed from '0' to 'calculation'; Variable Type of column k_value changed from '0' to 'data'; Variable Type of column Percent_Original_Mass changed from '0' to 'calculation'; Variable Type of column Stabalization changed from '0' to 'data'; Variable Type of column Labile_Fraction changed from '0' to 'data'; Variable Type of column Turnover changed from '0' to 'calculation ('ui_editor') 22-Nov-2024: manually edited data set metadata ('ui_editmetadata') 22-Nov-2024: Name of column Stabalization changed to Stabilizatio ('ui_editor') 22-Nov-2024: updated 6 metadata fields in the Data section(s) ('addmeta') 22-Nov-2024: updated 15 metadata fields in the Status, Data sections to reflect attribute metadata ('updatecols') 22-Nov-2024: parsed and formatted metadata ('listmeta') B. Variable Information 1. Variable Name: column 1. Tea_Type column 2. Depth column 3. Location column 4. Plot Number column 5. Month column 6. Distance_from_headward_eroding_creek column 7. Correction_Factor column 8. Initial_Wt_Total column 9. Initial_Wt_Tea column 10. Weigh_Boat column 11. Dry_Wt_Tea_Boat column 12. Final_Wt_Tea column 13. Mass_Loss column 14. Percent_Loss column 15. k_value column 16. Percent_Original_Mass column 17. Stabilization column 18. Labile_Fraction column 19. Turnover 2. Variable Definition: column 1. Type of tea placed in the ground: Red tea or Green tea column 2. Depth of the tea bag placed in the ground column 3. All plots were divided into 3 transects (P, M, C). The label here corresponds to the given transect. column 4. Plot Number column 5. Month the tea bag was placed in the ground column 6. Distance from the headward eroding creek of the plot column 7. (weight of tea bag and string) column 8. total weight of the tea bag and string column 9. weight of the tea column 10. weight of the weigh boat column 11. dried weight of the tea and weigh boat column 12. dry weight of the tea column 13. mass lost from inital weight of the tea to the final weight of the tea column 14. percent of tea loss over time column 15. decomposition rate of the tea column 16. percent of the original mass of the tea remaining column 17. stabilization factor column 18. labile fraction column 19. turnover time of the tea mass 3. Units of Measurement: column 1. none column 2. cm column 3. none column 4. none column 5. none column 6. m column 7. g column 8. g column 9. g column 10. g column 11. g column 12. g column 13. g column 14. % column 15. 1/d column 16. % column 17. none column 18. none column 19. d 4. Data Type a. Storage Type: column 1. string column 2. floating-point column 3. string column 4. integer column 5. integer column 6. floating-point column 7. floating-point column 8. floating-point column 9. floating-point column 10. floating-point column 11. floating-point column 12. floating-point column 13. floating-point column 14. floating-point column 15. floating-point column 16. floating-point column 17. floating-point column 18. floating-point column 19. floating-point b. Variable Codes: Location: C = Creek, M = Middle, P = Platform c. Numeric Range: column 1. (none) column 2. 10 to 50 column 3. (none) column 4. 1 to 24 column 5. 3 to 12 column 6. 0.68 to 23.07 column 7. 0.25108 to 0.25384 column 8. 1.8856 to 2.31 column 9. 1.6318 to 2.0589 column 10. 1.023 to 1.3001 column 11. 1.4544 to 3.0976 column 12. 0.2015 to 1.8309 column 13. -0.03248 to 1.5243 column 14. 0.0527 to 0.94528 column 15. 0.0003708 to 0.014739 column 16. 5.4719 to 101.6459 column 17. -0.048978 to 0.9043 column 18. 0.0528 to 0.75519 column 19. 67.8459 to 2696.8331 d. Missing Value Code: 5. Data Format a. Column Type: column 1. text column 2. numerical column 3. text column 4. numerical column 5. numerical column 6. numerical column 7. numerical column 8. numerical column 9. numerical column 10. numerical column 11. numerical column 12. numerical column 13. numerical column 14. numerical column 15. numerical column 16. numerical column 17. numerical column 18. numerical column 19. numerical b. Number of Columns: 19 c. Decimal Places: column 1. 0 column 2. 0 column 3. 0 column 4. 0 column 5. 0 column 6. 2 column 7. 5 column 8. 4 column 9. 4 column 10. 4 column 11. 4 column 12. 4 column 13. 4 column 14. 2 column 15. 4 column 16. 4 column 17. 4 column 18. 4 column 19. 4 6. Logical Variable Type: column 1. free text (none) column 2. data (continuous) column 3. coded value (none) column 4. nominal (discrete) column 5. datetime (discrete) column 6. data (continuous) column 7. data (continuous) column 8. data (continuous) column 9. data (continuous) column 10. data (continuous) column 11. data (continuous) column 12. data (continuous) column 13. calculation (continuous) column 14. calculation (continuous) column 15. data (continuous) column 16. calculation (continuous) column 17. data (continuous) column 18. data (continuous) column 19. calculation (continuous) 7. Flagging Criteria: column 1. none column 2. none column 3. none column 4. none column 5. none column 6. none column 7. none column 8. none column 9. none column 10. none column 11. none column 12. none column 13. none column 14. none column 15. none column 16. none column 17. none column 18. none column 19. none C. Data Anomalies: V. Supplemental Descriptors A. Data Acquisition 1. Data Forms: 2. Form Location: 3. Data Entry Validation: B. Quality Assurance/Quality Control Procedures: C. Supplemental Materials: D. Computer Programs: E. Archival Practices: F. Publications: not specified G. History of Data Set Usage 1. Data Request History: not specified 2. Data Set Update History: none 3. Review History: none 4. Questions and Comments from Users: none