Data from: Contrasting CO2 dynamics in seagrass meadows between organic carbon (OC)-rich reef and OC-poor terrestrial sediments: Implications for enhanced alkalinity production
Data files
Jul 16, 2025 version files 21.38 KB
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DS-KT_Benthic_flux_CDR.csv
1.86 KB
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DS-KT_Porewater_and_Sediment.csv
3.91 KB
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DS-KT_Water.csv
7.08 KB
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README.md
8.52 KB
Abstract
This dataset covers the carbonate chemistry of seawater and porewater, sediment carbon content, and benthic alkalinity fluxes and carbon dioxide removal (CDR) in two distinct seagrass meadows: one situated in organic carbon (OC)–rich reef sediments and the other in OC–poor terrestrial sediments. Seawater carbonate chemistry parameters include temperature, salinity, pH, pCO2, dissolved inorganic carbon (DIC), total alkalinity (TA), bicarbonate (HCO3-), carbonate (CO32-), and aragonite saturation state. Porewater parameters include pH, DIC, TA, pCO2, aragonite saturation state, and calcium ion concentration. Sediment characterization covers total organic carbon (TOC), total inorganic carbon (TIC), and total nitrogen (TN). The benthic flux data include measurements taken during the daytime, nighttime, daily, and annually. The carbon dioxide removal capacity of seagrass was calculated from the measured total alkalinity.
GENERAL INFORMATION
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TITLE OF DATASET: Contrasting CO2 Dynamics in Seagrass Meadows between Organic Carbon (OC)-Rich Reef and OC-Poor Terrestrial Sediments: Implications for Enhanced Alkalinity Production
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GEOGRAPHICAL LOCATION OF DATA COLLECTION: Dongsha Island (DS), Taiwan, and Kenting (KT), Taiwan
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FUNDING INFORMATION
Funding Agency: National Science and Technology Council (NSTC)
Funding No.: #112-2611-M-019 -005 and #112-2119-M-019 -008 -
CITATION OF THIS DATA: Chou, W-C, L.-F. Fan, M. B. Natividad, J.-J. Chen, Z.-W. Tang, H.-F. Chen, P.-C. Chen, E.-C. Kong, Y.-Y. Shih, W.-J. Huang, C.-C. Hung. 2024. Contrasting CO2 Dynamics in Seagrass Meadows between Organic Carbon (OC)-Rich Reef and OC-Poor Terrestrial Sediments: Implications for Enhanced Alkalinity Production.
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DATA AND FILE OVERVIEW
A. DS-KT_Water.csvSeawater carbonate chemistry parameters include temperature, salinity, pH, pCO2, dissolved inorganic carbon(DIC), total alkalinity (TA), bicarbonate (HCO3-), carbonate (CO32-), and aragonite saturation state (WAr).
B. DS-KT_Porewater_and_Sediment.csv
Porewater parameters include pH, DIC, TA, pCO2, aragonite saturation state, and calcium ion concentration. Sediment characterization covers total organic carbon (TOC), total inorganic carbon (TIC), and total nitrogen (TN).
C. DS-KT_Benthic_flux_CDR.csv
The benthic flux data include measurements taken during the daytime, nighttime, daily, and annually. The carbon dioxide removal capacity (CDR) of seagrass was calculated from the measured total alkalinity.
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VARIABLE LISTS:
A. DATA SPECIFIC INFORMATION FOR: DS-KT Water.csv
- Number of variables: 15 (Columns A-O)
- Number of rows: 94
- Variable list:
- Year: The year the study was conducted (2021-2022)
- Month of the sampling period
1: January
5: May
9: September
10: October - Date: Day of the month when sampling occurred
- Site: Location of the study sites
DS - Dongsha Island, Taiwan
KT - Kenting, Taiwan - Season: Wet season and dry season
- Time: Specific time interval during which the sample was collected.
- Temperature: Temperature measured in degrees Celsius (°C)
- Salinity: Salinity is measured in PSU (Practical Salinity Units)
- pH at 25: pH measured spectrophotometrically at 25 (°C)
- pCO2(µatm): Partial pressure of Carbon Dioxide (units of microatmospheres, µatm)
- DIC(µmol kg-1) Dissolved Inorganic Carbon (micromoles per kilogram, µmol/kg)
- TA(µmol kg-1) : Total Alkalinity (micromoles per kilogram, µmol/kg)
- HCO3-(µmol kg-1): Bicarbonate values (micromoles per kilogram, µmol/kg)
- CO32-(µmol kg-1): Carbonate values (micromoles per kilogram, µmol/kg)
- WAr: Aragonite saturation state
- Summary rows for statistics:
- Rows 11-13: Mean, SD (Standard Deviation), and Uncertainty for DS, dry season
- Rows 26-28: Mean, SD (Standard Deviation), and Uncertainty for DS, wet season
- Rows 52-54: Mean, SD (Standard Deviation), and Uncertainty for KT, wet season
- Rows 92-94: Mean, SD (Standard Deviation), and Uncertainty for KT, dry season
B. DATA SPECIFIC INFORMATION FOR: DS-KT Porewater and Sediment.csv
- Porewater data
Number of variables: 10 (Columns A-J)
Number of rows 56
Variable list for Porewater data
- Site : Location of the study sites
DS - Dongsha Island, Taiwan
KT - Kenting, Taiwan - Season : Wet season and dry season
- Year/Month: Year and month of the sampling period (2021-2022)
- Depth : Depth of sediment where porewater was sampled (0cm - 20cm)
- pH : acidity of the porewater
- DIC(µmol kg-1) : Dissolved Inorganic Carbon (micromoles per kilogram, µmol/kg)
- TA(µmol kg-1) : Total alkalinity (micromoles per kilogram, µmol/kg)
- pCO2(µatm) : Partial pressure of carbon dioxide in porewater (units of microatmospheres, µatm)
- WAr : Aragonite saturation state (WAr)
- Ca2+ : Calcium ion concentration in porewater (millimolar, mM)
Summary rows for statistics:
- Rows 12-14: Mean, SD (Standard Deviation), and Uncertainty for DS, dry season
- Rows 26-28: Mean, SD (Standard Deviation), and Uncertainty for DS, wet season
- Rows 40-42: Mean, SD (Standard Deviation), and Uncertainty for KT, wet season
- Rows 54-56: Mean, SD (Standard Deviation), and Uncertainty for KT, dry season
2. Sediment data
Number of variables: 7 (Columns M-S)
Number of rows: 8 for DS, 7 for KT
Variable List for Sediment Data
- Site : Location of the study sites
DS - Dongsha Island, Taiwan
KT - Kenting, Taiwan - Season : one season sampling only for each site.
DS sediment was sampled in dry season
KT sediment was sampled in wet season - Year/Month: Year and month of the sampling period
DS: January 2021
KT: March 2023 - Depth (cm) : Depth of sediment where porewater was sampled (in centimeters, 0cm - 20cm)
- TOC(wt %) : Total organic carbon (percentage of dry weight)
- TIC(wt %) : Total inorganic carbon (percentage of dry weight)
- TN(wt %) : Total nitrogen (percentage of dry weight
C. DATA SPECIFIC INFORMATION FOR: DS-KT Benthic flux_CDR.csv
- Original benthic fluxes
- Number of variables: 9 (Columns A-I)
- Number of rows 18 (Rows 1-19)
- Variable list
- Year: Year of the sampling period (2021-2022)
- Month : the month of the sampling period
1: January
5: May
9: September
10: October - Date: Day of the month when sampling occurred
- Site: Location of the study sites
DS: Dongsha Island, Taiwan
KT: Kenting, Taiwan - Season: Dry and wet season
- Period Benthic flux measurement during daytime and nighttime
- Replication: Number of collections during daytime and nighttime
- TA flux (mmol m-2 h-1): Total Alkalinity flux (millimoles per meter square per hour, mmol m-2 h-1)
- DIC flux (mmol m-2 h-1): Dissolved Inorganic Carbon flux (millimoles per meter square per hour, mmol m-2 h-1)
- Daytime- and nighttime fluxes
- Number of variables: 9 (Columns A-J)
- Number of rows: 9 (Rows 21-30)
- Variable list
- Year of the sampling period (2021-2022)
- Month: Month of the sampling period
1: January
5: May
9: September
10: October - Site: Location of the study sites
DS: Dongsha Island, Taiwan
KT: Kenting, Taiwan - Season: Dry and wet season
- Peri : Bethic flux measurement during daytime and nighttime
- TA flux (mmol m-2 h-1): Total Alkalinity flux on an hourly basis (millimoles per meter square per hour, mmol m-2 h-1)
- TA_SD: Total Alkalinity Standard Deviation values
- DIC flux (mmol m-2 h-1): Dissolved inorganic carbon flux on an hourly basis (millimoles per meter square per hour, mmol m-2 h-1)
- DIC_SD Dissolved Inorganic Carbon Standard Deviation values
Daily fluxes
- Number of variables : 8 (Columns A-B, D-E, G-J)
- Number of rows : 5
- Variable list
- Year : Year of the sampling period (2021-2022)
- Month : Month of the sampling period
1: January
5: May
9: September - Site : Location of the study sites
DS: Dongsha Island, Taiwan
KT: Kenting, Taiwan - Season : Dry and wet season
- TA flux (mmol m-2 d-1): Total Alkalinity flux on a daily basis between dry and wet season (millimoles per meter square per day, mmol m-2 d-1)
- TA_SD : Total Alkalinity Standard Deviation values
- DIC flux (mmol m-2 d-1): Dissolved Inorganic Carbon flux on a daily basis between dry and wet season (millimoles per meter square per day, mmol m-2 d-1)
- DIC_SD : Dissolved inorganic carbon Standard Deviation values
Annual Fluxes
- Number of variables : 6 (Columns A, D, G-J)
- Number of rows : 3
- Variable list
- Year : Year of the sampling period (2021-2022)
- Site : Location of the study sites
- DS: Dongsha Island, Taiwan
- KT: Kenting, Taiwan
- TA flux (mmol m-2 d-1): calculated TA flux on an annual basis (millimoles per meter square per day, mmol m-2 d-1)
- TA_SD : Total Alkalinity Standard Deviation values
- DIC flux (mmol m-2 d-1): calculated DIC flux on an annual basis (millimoles per meter square per day, mmol m-2 d-1)
- DIC_SD : Dissolved inorganic carbon Standard Deviation values
Annual CDR
- Number of variables : 3 (Columns D, G-H)
- Number of rows : 3
- Site : Location of the study sites
DS: Dongsha Island, Taiwan;
KT: Kenting, Taiwan - CDR (tCO2eq ha-1 y-1): Calculated Carbon Dioxide Removal tons of carbon dioxide per hectare (ha) per year (y)
A. Sample collection
Seawater samples for TA, DIC, and pH analyses were collected at specific intervals. At the DS site, samples were taken at 06:00, 12:00, and 18:00 daily, while at the KT site, samples were collected at 4-hour intervals. Discrete seawater samples were obtained using a 9-L Nalgene™ HDPE carboy. Within 30 minutes of collection, the seawater samples were transferred into pre-cleaned 350-mL borosilicate bottles upon arrival at the laboratory in Dongsha or Kenting. To arrest biological activity, each sample received an injection of 200 μL of saturated HgCl2 solution, after which they were sealed and transported to the laboratory at the National Taiwan Ocean University. Subsequently, these samples underwent analysis for DIC, TA, and pH measurements.
Porewater samples were acquired using porewater wells, following a modified methodology described by Falter and Sansone (2000). At various sediment depths (2, 4, 6, 8, 12, 16, and 20 cm), 25 mL of pore water was extracted from each well using a Luer-Lok syringe. The sampling procedure and preservation of porewater samples followed the methods outlined in Kindeberg et al. (2020). These porewater samples were also subjected to analysis for DIC, TA, and pH measurements, with additional determination of calcium ion concentrations.
Sediment samples were collected using an acrylic push core (7 cm diameter; 1 m long) and stored in a -20°C freezer until subsequent analysis. Subsamples, taken at 5 cm intervals from top to bottom, underwent microscopic examination using a Leica WILD M8 microscope and EOS Utility software. The semi-quantitative analysis of major minerals in surface sediment was conducted using X-ray powder diffraction (XRD) with a Bruker D2 Phaser instrument, following methods outlined in previous studies (Chen et al., 2011; Lo et al., 2017). Additionally, each core section was analyzed for total organic carbon (TOC), total inorganic carbon (TIC), and total nitrogen (TN) contents, providing a comprehensive assessment of sediment composition and organic matter content.
Benthic metabolism incubations were conducted within seagrass meadows using specialized benthic chambers positioned at a depth of 1 meter, facilitating the differentiation between light and dark fluxes of total alkalinity (TA) and dissolved inorganic carbon (DIC). The benthic chambers, made of polymethyl methacrylate cylinders with dimensions of 35 cm in diameter and 40 cm in height, were carefully inserted approximately 10 to 15 cm into the sediment. These chambers were equipped with autonomous sensors capable of capturing critical parameters. Within each chamber, individual water circulation pumps ensured representative water sampling while minimizing chemical gradients. Furthermore, the chambers were designed with two sampling ports to facilitate a controlled collection of biological and chemical samples. On average, the chambers held a water volume ranging from 24 to 29 liters. The HOBO U26, with a precision of 0.02 mg L-1 and accuracy of ± 2%, was used to record DO levels, temperature, and light intensity at 10-minute intervals at each site. Complementing this data collection, temperature and light loggers (HOBO Pendant® Temperature/Light 64K Data Loggers) were deployed.
B. Sample analysis
The following methods were used to analyze seawater, porewater, and sediment samples:
- DIC was analyzed using the Non-dispersive infrared method on DIC Analyzer (AS-C3, Apollo SciTech Inc.).
- TA was analyzed using the Gran Titration Method (TA titrator, AS AS-ALK2, Apollo SciTech Inc.).
- pH was analyzed using a spectrophotometer at 25 °C.
- Partial pressure of CO2 (pCO2) and aragonite saturation state (ΩAr) in both seawater and porewater were calculated using DIC, TA, temperature, and salinity data, utilizing the CO2SYS program (Pelletier et al. 2011). The dissociation constants for carbonic acid used in these calculations were derived from the dataset of Mehrbach et al. (1973) and refined by Dickson and Millero (1987), providing accurate and validated results for pCO2 or ΩAr determinations (Wanninkhof et al. 1999).
- Calcium ion concentration was quantified using an inductively coupled plasma mass spectrometry (ICP-MS) system (Agilent 7700×, Agilent Technologies).
- TOC, TIC, and TN were measured using an elemental analyzer (Elementar, Soil TOC® cube, Germany).
- Carbon dioxide removal (CDR) was calculated from the TA benthic fluxes
C. Instrument precision and uncertainty error
- The calibration of both the alkalinity titrator and DIC analyzer was conducted using certified reference materials (CRMs) sourced from Dr. A. Dickson's laboratory at the Scripps Institution of Oceanography. The accuracy and precision of the TA and DIC measurements were equal to or exceeded ±0.15%. The measurement of pH at 25 °C is performed with a precision of 0.005 on the total hydrogen ion concentration scale.
- The uncertainty (error) of pCO2 and ΩAr was determined using the Seacarb package in R, following the methodology outlined by Gattuso et al. (2024).
D. Statistical analysis
The study used Wilcox's robust ANOVA (WR-ANOVA) to account for the heteroscedasticity among habitat groups. Given the skewed distribution of carbonate chemistry observations within seagrass habitats, comparisons between medians, as suggested by Baldry et al. (2020), were used over means. This statistical approach was applied to assess differences in the medians of pH25, pCO2 in situ, DIC, and TA at the DS and HK sites across different seasons. The WR-ANOVA analysis was executed using the "med1way" function from the R package "WRS2" (Mair and Wilcox, 2020). All statistical analyses were conducted in R software v4.1.1 (R Core Team, 2021) with a confidence level of 95%.