Data from: Sedimentary organic carbon restoration in abandoned bivalve farms via seagrass recolonisation: a case study from the Ria Formosa lagoon

These datasets support the scientific article "Carbon restoration in abandoned bivalve farms via seagrass recolonisation: a case study from the Ria Formosa lagoon" (submitted). It contains detailed data to estimate carbon stocks in bivalve farms and seagrass-colonised abandoned farms in the Ria Formosa lagoon (southern Portugal). The datasets are accompanied by analysis code, available at GitHub repository, allowing for reproducibility and further exploration of the data. The data is composed by 2 datasets with the following variables: data_cores.csv. Contains properties related to the sampling of the sediment cores. core_id_reg [character] - unique core identification code used in the field. category [factor] - present land-use category where the core were sampled (seagrass, oyster_farm, clam_farm). replicate [character] - replicate number of the core in each pond. core_date [date] - date of core collection (YYYY-MM-DD). core_latitude [numeric] - positional latitude of the core in decimal degree WGS84. core_longitude [numeric] - positional longitude of the core in decimal degree WGS84. core_depth [numeric] - depth sampled with the core (in centimeters). sample_length [numeric] - length of the sampled core (in centimeters). compaction_correction_factor [numeric] - fraction of the sample depth interval reduced due to compaction. It is calculated by dividing the core length by the core depth. compaction [numeric] - core compaction in percentage (%). It is calculated as 100*(1 - compaction_correction_factor). data_samples.csv. Contains properties of the sediment samples. core_id_reg [character] - unique core identification code used in the field. category [factor] - present land-use category where the core were sampled (seagrass, oyster_farm, clam_farm). replicate [character] - replicate number of the core in each pond. sample_id [character] - unique sample identification code. depth_middle_uncorrected [numeric] - middle depth of a sampling increment, calculating as the average of depth_min and depth_max (in centimeters), uncorrected for compaction. depth_middle [numeric] - middle depth of a sampling increment, calculating as the average of depth_min and depth_max (in centimeters). Corrected for compaction. depth_min [numeric] - minimum depth of a sampling increment, corrected for compaction (in centimeters). Corrected for compaction. depth_max [numeric] - maximum depth of a sampling increment, corrected for compaction (in centimeters). Corrected for compaction. thickness [numeric] - sample thickness (in centimeters), calculated as depth_max - depth_min. sample_volume [numeric] - volume of the sediment sample, corrected for compaction (in cubic centimeters). flag_volume [boolean] - whether there is any potential error in the sample volume (0 no, 1 yes). sample_dw [numeric] - dry mass of the sample (in grams of dry weight). flag_dw [boolean] - whether there is any potential error in the sample dw (0 no, 1 yes). percentage_organic_matter [numeric] - mass of organic matter relative to sample dry mass, obtained by loss-on-ignition (in percentage of dry weight). sample_loi_pre [numeric] - weight of the sample fraction used for loss-on-ignition (in grams of dry weight). dry_bulk_density [numeric] - dry mass per unit volume of the sample. This is calculated as the sample_dw divided by the sample_dw (in grams of dry weight per cubic centimeter). flag_dbd [boolean] - whether there is any potential error in the dry bulk density (0 no, 1 yes). percentage_organic_matter [numeric] - mass of organic matter relative to sample dry mass (as a percentage of dry weight). flag_om [boolean] - whether there is any potential error in the organic matter content (0 no, 1 yes).