# Dunnette fire data from Chickaree Lake, Rocky Mountain National Park, Colorado - IMPD USCHK001 #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # NOTE: Please cite original publication, online resource and date accessed when using this data. # If there is no publication information, please cite Investigator, title, online resource and date accessed. # # Description/Documentation lines begin with # # Data lines have no # # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/ # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/fire history/uschk001.txt # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/fire history/uschk001.loi # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/fire history/uschk001.mag # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-14c-dates.zip # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-210Pb-data-params-results.xls # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-210pb-input-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-210pb-params.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-210pb-results-age-model.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-210pb-results-ages.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-calib-dates-tab.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-chron-tab.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-data.xls # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-input-data-tab.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-input-params-tab.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-age-depth-pb210-data-tab.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-biogeochem-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-bsi-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-char-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-char-params.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-char-results.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-loi-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-ms-char-data.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-ms-char-params.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-ms-char-results.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-pollen-counts.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-pollen-counts.xls # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-pollen-percentages.csv # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/uschk001-ch10-radiometric-samples.csv # # Archive: Fire History # # Parameter_Keywords: Charcoal #--------------------------------------- # Contribution_Date # Date: 2016-03-02 #--------------------------------------- # Title # Study_Name: Dunnette fire data from Chickaree Lake, Rocky Mountain National Park, Colorado - IMPD USCHK001 #--------------------------------------- # Investigators # Investigators: Dunnette,P.V.;Higuera,P.E.;McLauchlan,K.K.;Derr,K.M.;Briles,C.E.;Keefe,M.H.; #--------------------------------------- # Description_Notes_and_Keywords # Description: # # # Contact person: Philip E. Higuera; # Contact person email address: phiguera@uidaho.edu; # Sampling date: 2010-08; # Water depth (cm): 790; # Sampling device: modified Livingstone piston corer; # Diameter (cm): 5.0 and 7.6 cm diameter; # # Supplemental Material Data File Content Details (26 files total): # Contents: # I. Biogeochemical Data Files (file count: 1) # II. Biogenic Silica Data Files (file count: 1) # III. Charcoal Data Files (file count: 3) # IV. Chronology Data Files (file count: 14) # V. Loss-on-ignition Data Files (file count: 1) # VI. Magnetic Susceptibility Data Files (file count: 3) # VII. Pollen Data Files (file count: 3) # # Note: All 26 Supplemental Material Data Files of this dataset, listed below, begin with the IMPD code for this dataset: "usck001", and are locate at: # http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/supplemental/ # # I. Biogeochemical Data Files (file count: 1) # # A. uschk001-ch10-biogeochemdata.csv # Biogeochemical Data # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_biogeochemData.csv # # This file includes the following raw data (by column): # 1. core_ID: Sediment core identifier # 2. drive_ID: Drive identifier # 3. top_sam #: Top sample number # 4. bot_sam #: Bottom sample number # 5. top_cm: Top depth of sample (cm) # 6. bot_cm: Bottom depth of sample (cm) # 7. top_age: Top age of sample (cal. yr before CE 1950) # 8. bot_age: Bottom age of sample (cal. yr before CE 1950) # 9. d15N: Nitrogen isotopic composition (delta 15N; per mil) # 10. %N: Percent Nitrogen (by weight) # 11. d13C: Carbon isotopic composition (delta 13C; per mil) # 12. %C: Percent Carbon (by weight) # 13. C:N_atomic_ratio: Ratio of %C to %N (atomic) # 14. bulk_density: Bulk density (dry g wet cm-3) # 15. C_acc: Carbon accumulation rate (g cm-2 yr-1) # 16. MS_SI : Magnetic susceptibility (SI units) # # Missing Values: NaN # Checksum values: # 635 rows (with headers), 16 columns # Column 3 (top_sam #): 58551 # Column 5 (top_cm): 201836 # Column 10 (%N): 626.83 # Column 15 (C_acc): 341.58 # # # II. Biogenic Silica Data Files (file count: 1) # # A. uschk001-ch10-bsi-data.csv # Biogenic Silica Data File # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_BSiData # # This file includes the following raw data (by column): # 1. top_cm: top depth of sample (cm) # 2. bot_cm: bottom depth of sample (cm) # 3. top_age: top age of sample (cal. yr before CE 1950) # 4. bot_age: bottom age of sample (cal. yr before CE 1950) # 5. %BSi: Percent biogenic silica (by weight) # 6. d15NAIR: Nitrogen isotopic composition (delta 15N; per mil) # 7. %N: Percent Nitrogen (by weight) # 8. d13CVPDB_17O_corrected: Carbon isotopic composition delta 13C; per mil) # 9. %C: Percent Carbon (by weight) # 10. C:N_atomic_ratio: Ratio of %C to %N (atomic) # 11. bulk_density: Bulk density (dry g / wet cm3) # # Missing Values: None # Checksum values: # 41 rows (with headers), 11 columns # Column 3 (top_cm): 69935 # Column 5 (%BSi): 1042.45 # Column 10 (C:N): 591.52 # # # III. Charcoal Data Files (file count: 3) # # Three files, described below, provide the raw input data, the parameters used, and the output data for charcoal analysis via the program CharAnalysis (see Dunnette et al. 2014, Materials and Methods, and https://sites.google.com/site/charanalysis/). # # A. uschk001-ch10-char-data.csv # The raw input data # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_charData.csv,. # This file also contains the same information as the charcoal data file for this dataset, which is located at: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/uschk001.txt # # This file includes the following raw data (by column): # 1. cmTop: top depth (cm) of the sample # 2. cmBot: bottom depth (cm) of the sample # 3. ageTop: estimated age at top of sample (cal. yr before CE 1950) # 4. ageBot: estimated age at bottom of sample (cal. yr before CE 1950) # 5. charVol: volume of sediment subsample from which charcoal was prepared (cm3) # 6. charCount: pieces of charcoal counted in the sample (#) # Missing values: None # Checksum values: # 1202 rows (with headers), 6 columns # Column 3 (ageTop): 2446519 # Column 6 (charCount): 38218 # # B. uschk001-ch10-char-params.csv # The parameters used # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_charParams.csv # # See CharAnalysis User's Guide for description of parameters file, available at the web site link above. # Missing values: -9999 (column 3) or blank cell (all others) # Checksum values: # 26 rows (with headers), 5 columns # Column 3 (Parameters): -39779 # # C. uschk001-ch10-char-results.csv # The output data for charcoal analysis # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_charResults.csv # # This file includes the following derived data (reflecting interpolation): # 1. cmTop_i: top depth (cm) of interpolated sample # 2. ageTop_i: bottom depth (cm) of interpolated sample # 3. charCount_i: pieces of charcoal in interpolated sample # 4. charVol_i: volume of interpolated sample # 5. charCon_i: charcoal concentration in interpolated sample (pieces/cm3) # 6. charAcc_i: charcoal accumulation rate, based in interpolated concentration and age (pieces/cm2 yr) # 7. charBkg: background charcoal, Cback, smoothed based on methods selected in _charParams.csv file, (pieces/cm2 yr) # 8. charPeak: peak charcoal, Cpeak, based on methods selected in _charParams.csv file, (pieces/cm2*yr) # 9. thresh1: threshold value (pieces/cm2 yr) based on first threshold entered in _charParams.csv file # 10. thresh2: same as thresh1, but for second threshold entered # 11. thresh3: same as thresh1, but for third threshold entered # 12. threshFinalPos: positive threshold value (pieces/cm2 yr), based on fourth threshold value entered in *charParams.csv file # 13. threshFinalNeg: negative threshold value (pieces/cm2 yr), based on fourth threshold value entered in *charParams.csv file # 14. SNI: signal-to-noise index values, based on threshdFinalPos values # 15. threshGOF: P value from KS goodness-of-fit test between fitted noise distribution and empirical data below the sample-specific threshold # 16. peaks1: samples that exceed thresh1 values are identified by "1"; only the first sample is identified # 17. peaks2: same as peaks1, but for the second threshold value # 18. peaks3: same as peaks1, but for the third threshold value # 19. peaksFinal: same as peaks1, but for the final threshold value # 20. peaksInsig.: peaks that exceeded threshFinalPos (the final threshold), but did not pass the minimum-count test are identified with a "1" # 21. peakMag: peak magnitude is the total pieces of charcoal accumulated in a given peak (pieces/cm2*peak); if a peak is only one sample long, then peak magnitude is simply CHAR minus the positive threshold. If a peak is more than one sample long, then each sample exceeding threshFinal is summed # 22. smPeak Frequ: frequency of peaks (from peaksFinal) smoothed over time, as set in *_charParams.csv file # 23. smFRIs: fire return intervals (from peaksFinal) smoothed over time, as set in *_charParams.csv file # # Missing values: NaN # Checksum values: # 458 rows (with headers), 23 columns # Column 2 (age Top_i): 1014540 # Column 6 (char Acc_i): 753.8938 # Column 19 (peaks Final): 36S # # # IV. Chronology Data Files (file count: 14) # # A. uschk001-ch10_14Cdates.zip # Chronology Data - .zip archive includes the .B00` files output from CALIB # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_14Cdates.zip. # # B. uschk001-ch10-210pb-data.xls # Chronology Data - Microsoft Excel format file containing Pb210 Data, Pb210 Params, and PB210 Results (210Pb Ages, and 210Pb Age Model). # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_210Pb_data.xls. # # c. uschk001-ch10-210pb-input-data.csv # Chronology Data - 210Pb Data # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_210Pb_data.xls, tab: Pb210Data. # # D. uschk001-ch10-210pb-params.csv # Chronology Data - 210Pb Parameter Choices # This data is also contained in usck001-ch10-210pb-data.xls tab: Pb210Params. # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_210Pb_data.xls, tab: Pb210Params. # # E. uschk001-ch10-210pb-results-ages.csv # Chronology Data - 210Pb Ages # This data is also contained in usck001-ch10-210pb-data.xls tab: Pb210Results, table within tab: 210Pb Ages. # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_210Pb_data.xls, tab: Pb210Results, table within tab: 210Pb Ages. # # F. uschk001-ch10-210pb-results-age-model.csv # Chronology Data - 210Pb Age Model # This data is also contained in usck001-ch10-210pb-data.xls tab: Pb210Results, table within tab: 210Pb Age Model. # This file contains the same information as Dunnette et al. 2014 Supporting Information, CH10_210Pb_data.xls, tab: Pb210Results, table within tab: 210Pb Age Model. # # G. uschk001-ch10-age-depth-data.csv # Supplemental Material: Chronology Data - age-depth data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.csv. # # This file includes the following raw data (by column): # 1. Top depth of sample (cm) # 2. Calibrated age at sample top (cal yr BP) # 3. Upper 95% confidence intervals for data in column two # 4. Lower 95% confidence intervals for data in column two # 5. Sedimentation rate (cm/yr) # 6. Upper 95% confidence intervals for data in column five # 7. Lower 95% confidence intervals for data in column five # 8. Sample resolution (yr/sample) # 9. Upper 95% confidence intervals for data in column eight # 10. Lower 95% confidence intervals for data in column eight # Missing values: None # Checksum values: # 1596 rows (with headers), 10 columns # Column 1 (sampleCm): 642150.9 # Column 2 (calAge): 4679522 # Column 5 (sedAcc): 211.236 # Column 8 (sampleRes): 6860.85 # # H. uschk001-ch10-age-depth-data.xls # Chronology Data - age-depth data in Microsoft Excel file format # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls. # # I. uschk001-ch10-age-depth-input-data-tab # Chronology Data - age-depth input data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls, Tab: InputData # This file also contains the same content as uschk001-ch10-age-depth-data.xls, Tab: InputData (described above). # # J. uschk001-ch10-age-depth-input-params-tab # Chronology Data - age-depth input parameters # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls, Tab: InputParams # This file also contains the same content as uschk001-ch10-age-depth-data.xls, Tab: InputParams (described above). # # K. uschk001-ch10-age-depth-pb210-data-tab # Chronology Data - age-depth pb21 data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls, Tab: pb210Data # This file also contains the same content as uschk001-ch10-age-depth-data.xls, Tab: pb210Data (described above). # # L. uschk001-ch10-age-depth-calib-dates-tab # Chronology Data - age-depth input parameters # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls, Tab: calibDates # This file also contains the same content as uschk001-ch10-age-depth-data.xls, Tab: calibDates (described above). # # M. uschk001-ch10-age-depth-chron-tab # Chronology Data - age-depth input parameters # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_ageDepthData.xls, Tab: chronology # This file also contains the same content as uschk001-ch10-age-depth-data.xls, Tab: chronology (described above). # # N. uschk001-ch10_radiometric-samples.csv # Chronology Data - radiometric samples. # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_radiometricSamples.csv. # This file also contains the same content as the Chronology section of this dataset for the Charcoal, Loss-on-ignition, and Magnetic Susceptibility data files, respectively named uschk001.txt, uschk001.loi, and uschk001.mag, and all located at http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/ # # # V. Loss-on-ignition Data Files (file count: 1) # # A. uschk001-ch10-loi-data.csv # Loss-on-ignition data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_LOI_Data.csv. # This file also contains the same content as the Data section of the Loss-on-ignition file for this dataset, located at: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/uschk001.loi # Note: for usck001.loi, core_ID, drive_id, top_sam#, and bot_sam# have been concatenated into the last column with heading, Notes. # # This file includes the following raw data (by column): # 1. core_ID: Sediment core identification number # 2. drive_ID: Drive identifier # 3. top_sam #: Top sample number # 4. bot_sam #: Bottom sample number # 5. top_cm: top depth of sample (cm) # 6. bot_cm: bottom depth of sample (cm) # 7. top_age: top age of sample (cal. yr before CE 1950) # 8. bot_age: bottom age of sample (cal. yr before CE 1950) # 9. d15N: Nitrogen isotopic composition (delta 15N; per mil) # 10. %N: Percent nitrogen (by weight) # 11. d13C: Carbon isotopic composition (delta 13C; per mil) # 12. %C: Percent carbon (by weight) # 13. C:N_atomic_ratio: Ratio of %C to %N (atomic) # 14. bulk_density: Bulk density (dry g wet cm-3) # 15. LOI_550: Loss on ignition at 550 C (% organic matter; multiply by 100) # 16. LOI_1000: Loss on ignition at 1000 C (% organic matter; multiply by 100) # # Missing Values: None # Checksum values: # 124 rows (with headers), 16 columns # Column 3 (top_samp #): 12010 # Column 5 (top_cm): 31833.7 # Column 10 (%N): 161.05 # Column 15 (LOI_550): 38.63 # # # VI. Magnetic Susceptibility Data Files (file count: 3) # # Three files (Cuschk001-ch10-ms-char-data.csv, uschk001-ch10-ms-char-params.csv, uschk001-ch10-ms-char-results.csv, described below) provide the raw input data, the parameters used, and the output data for peak analysis of magnetic susceptibility (MS) data, using the program CharAnalysis (see Materials and Methods in main text, and web site https://sites.google.com/site/charanalysis/). The column headers for all files are the same as for charcoal analysis (CH10_char* files), but NOTE that the units for MS have been manipulated to be able to be used in CharAnalysis (see below). # # A. uschk001-ch10-ms-char-data.csv # Raw input data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_MS_charData.csv. # This file also contains the same content as the Data section of the Magnetic Susceptibility file for this dataset, locted at: http://www1.ncdc.noaa.gov/pub/data/paleo/firehistory/charcoal/northamerica/uschk001.mag, minus the "dummyVar" column. # # This file Includes the following raw data (by column): # 1. cmTop: top depth (cm) of the sample # 2. cmBot: bottom depth (cm) of the sample # 3. ageTop: estimated age at top of sample (cal. yr before CE 1950) # 4. ageBot: estimated age at bottom of sample (cal. yr before CE 1950) # 5. dummyVar: dummy variable set to 1, to facilitate use in CharAnalysis program # 6. MS_shifted_trans: Shifted MS data (from col. 8), transformed by dividing by the sediment accumulation rate (cm/yr). Thus, when these transformed values are multiplied by the sediment accumulation rate (cm/yr), as done in CharAnalysis, the result is the transformed MS values (column 8). # 7. MS_raw_SI: Raw magnetic susceptibility measurements (SI units) # 8. MS_shifted: Raw MS values, shifted by adding the minimum values in MS_raw_SI to each value, such that the minimum value becomes 0. CharAnalysis cannot work with negative data. # # Missing values: None # Checksum values: # 1477 rows (with headers), 8 columns # Column 3 (ageTop): 3970165 # Column 6 (setRate/MS): 0.3626761 # # B. uschk001-ch10-ms-char-params.csv # The parameters used # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_MS_charParams.csv # # C. uschk001-ch10-ms-char-results.csv # Output data for peak analysis of magnetic susceptibility (MS) data # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_MS_charResults.csv. # # # VII. Pollen Data Files (file count: 3) # # A. uschk001-ch10-pollen-counts.csv # Raw pollen data reported as pollen counts # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_PollenCounts.csv # # B. uschk001-ch10-pollen-counts.xls # Raw pollen data reported as pollen counts (in Microsoft Excel format file) # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_PollenCounts.xls # This file also contains the same content as uschk001-ch10-pollen-counts.csv # # uschk001-ch10-pollen-counts.csv and uschk001-ch10-pollen-counts.xls (described above), include the following raw data (by column): # 1. Sample_ID : Identification of sample, by lake (CH), year (07 or 10), core (1 or 2), and drive (A, B,C,...). # 2. Sample_number: Sample number for each drive # 3. Top_cm: Top depth of each sample (cm) # 4. age_yrBP: Age of each sample, in calibrated years before present (CE 1950) # 5. Pinus hap: Haploxilon Pinus pollen grains counted # 6. Pinud dip: Diploxilon Pinus pollen grains counted # 7. Pinus undiff: Undifferentiated Pinus pollen grains counted # 8. Picea: Picea pollen grains counted 9...112: Column heads are the taxonomic identification for each pollen grain counted # 9. Charcoal: NOT COUNTED # 10. EU: Exotic pollen grains, added as spike. # # Missing values: NaN. # Checksum values: # 46 rows (with headers), 113 columns # Column 2 (sample_number): 6143 # Column 4 (age_yrBP): 86683 # Column 10 (Pseudotsuga/Larix): 42 # Column 113 (EU): 8793 # # C. uschk001-ch10-pollen-percentages.csv # Pollen percentages # This file contains the same content as Dunnette et al. 2014 Supporting Information, CH10_pollenPercentages.csv # # This file includes the following raw data (by column): # 1. Sample_ID : Identification of sample, by lake (CH), year (07 or 10), core (1 or 2), # and drive (A, B, C,...). # 2. Sample_number: Sample number for each drive # 3. Top_cm: Top depth of each sample (cm) # 4. age_yrBP: Age of each sample, in calibrated years before present (CE 1950) # 5. Pinus hap: Haploxilon Pinus pollen grains counted # 6. Pinud dip: Diploxilon Pinus pollen grains counted # 7. Pinus undiff: Undifferentiated Pinus pollen grains counted # 8. Picea: Picea pollen grains counted 9...107: Columns heads are the taxonomic identification for each pollen grain counted # # Missing values: None. # Checksum values: # 46 rows (with headers), 106 columns # Column 2 (sample_number): 6143 # Column 4 (age_yrBP): 86683 # Column 10 (Pseudotsuga/Larix): 12 # Column 102 (Nuphar): 13.19 # #--------------------------------------- # Publication # Authors: Paul V. Dunnette, Philip E. Higuera, Kendra K. McLauchlan, Kelly M. Derr, Christy E. Briles and Margaret H. Keefe # Published_Date_or_Year: 2014 # Published_Title: Biogeochemical impacts of wildfires over four millennia in a Rocky Mountain subalpine watershed # Journal_Name: New Phytologist # Volume: 203 # Issue: # Pages: 900-912 # Report Number: # DOI: 10.1111/nph.12828 # Full_Citation: # Abstract: # Wildfires can significantly alter forest carbon (C) storage and nitrogen (N) availability, but the long-term biogeochemical legacy of wildfires is poorly understood. # # We obtained a lake-sediment record of fire and biogeochemistry from a subalpine forest in Colorado, USA, to examine the nature, magnitude, and duration of decadal-scale, fire-induced ecosystem change over the past c. 4250 yr. The high-resolution record contained 34 fires, including 13 high-severity events within the watershed. # # High-severity fires were followed by increased sedimentary N stable isotope ratios (d15N) and bulk density, and decreased C and N concentrations – reflecting forest floor destruction, terrestrial C and N losses, and erosion. Sustained low sediment C : N c. 20–50 yr post-fire indicates reduced terrestrial organic matter subsidies to the lake. Low sedimentary d15N c. 50–70 yr post-fire, coincident with C and N recovery, suggests diminishing terrestrial N availability during stand development. The magnitude of post-fire changes generally scaled directly with inferred fire severity. # # Our results support modern studies of forest successional C and N accumulation and indicate pronounced, long-lasting biogeochemical impacts of wildfires in subalpine forests. However, even repeated high-severity fires over millennia probably did not deplete C or N stocks, because centuries between high-severity fires allowed for sufficient biomass recovery. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: IIA-0966472 # Grant: #--------------------------------------- # Funding_Agency # Funding_Agency_Name: (P.E.H.) # Grant: #--------------------------------------- # Funding_Agency # Funding_Agency_Name: C. R. Stillinger Forest Science Research Fellowship (P.V.D.) # Grant: #--------------------------------------- # Site Information # Site_Name: Chickaree Lake # Location: Colorado # Country: United States of America # Northernmost_Latitude: 40.334249 # Southernmost_Latitude: 40.334249 # Easternmost_Longitude: -105.84727 # Westernmost_Longitude: -105.84727 # Elevation: 2796 #--------------------------------------- # Data_Collection # Collection_Name: USCHK001 LOI # First_Year: 4508 # Last_Year: -60 # Time_Unit: cal yr BP # Core_Length: # Notes: # # Loss-on-ignition data includes the following raw data(by column) and checksum values: # # 1. top_cm: top depth of sample (cm) # 2. bot_cm: bottom depth of sample (cm) # 3. top_age: top age of sample (cal. yr before CE 1950) # 4. bot_age: bottom age of sample (cal. yr before CE 1950) # 5. d15N: Nitrogen isotopic composition (delta 15N; per mil) # 6. %N: Percent nitrogen (by weight) # 7. d13C: Carbon isotopic composition (delta 13C; per mil) # 8. %C: Percent carbon (by weight) # 9. C:N_atomic_ratio: Ratio of %C to %N (atomic) # 10. bulk_density: Bulk density (dry g wet cm-3) # 11. LOI_550: Loss on ignition at 550 C (% organic matter; multiply by 100) # 12. LOI_1000: Loss on ignition at 1000 C (% organic matter; multiply by 100) # 13. Notes: # core_ID: Sediment core identification number # drive_ID: Drive identifier # top_sam #: Top sample number # bot_sam #: Bottom sample number # Missing Values: None # Checksum values: # 124 rows (with headers), 13 columns # Column 1 (top_cm): 31833.7 # Column 6 (%N): 161.05 # Column 11 (LOI_550): 38.63 # Column 13 (Notes) top_sam #: 12010 #--------------------------------------- # Chronology_Information # Chronology: # For Notes column: # *1 = CAMS: Center for Accelerator Mass Spectrometry, Lawrence Livermore National Laboratory, Livermore, CA. # *2 = 210Pb activity, with standard deviation, or conventional radiocarbon years before present CE 1950, with standard deviation. # *3 = See Materials and Methods for details on 210Pb modeling and calibration of 14C dates. # *4 = Indicates nearly-paired samples from Bulk gyttja gyttja and concentrated charcoal. # # LakeName Top_cm Bot_cm MaterialDated LaboratoryID_*1 210PbActivity_dpm_g-1_OR_14CDate_yr BP_*2 std_dev Modeled_OR_Calibrated_date_calYrBP_*3 95%CI_low 95%CI_hi Notes # Chickaree Lake 0.8 2.4 Bulk gyttja Flett Research 77.33 1.31 -57 -58 -56 na # Chickaree Lake 2.4 3.5 Bulk gyttja Flett Research 77.85 1.18 -53 -53 -52 na # Chickaree Lake 3.5 4.6 Bulk gyttja Flett Research 66.27 0.82 -48 -49 -48 na # Chickaree Lake 4.6 6.7 Bulk gyttja Flett Research 57.99 0.86 -43 -44 -42 na # Chickaree Lake 6.7 8.9 Bulk gyttja Flett Research 45.53 0.71 -37 -38 -36 na # Chickaree Lake 8.9 11 Bulk gyttja Flett Research 45.88 1.09 -31 -32 -30 na # Chickaree Lake 11 13.2 Bulk gyttja Flett Research 30.27 0.63 -23 -25 -22 na # Chickaree Lake 13.2 15.4 Bulk gyttja Flett Research 25.48 0.55 -16 -17 -15 na # Chickaree Lake 15.4 18.6 Bulk gyttja Flett Research 19.88 0.5 -7 -9 -6 na # Chickaree Lake 18.6 20.8 Bulk gyttja Flett Research 23.28 0.47 8 6 10 na # Chickaree Lake 20.8 21.9 Bulk gyttja Flett Research 19.57 0.45 23 20 25 na # Chickaree Lake 21.9 25.1 Bulk gyttja Flett Research 15.9 0.44 30 27 33 na # Chickaree Lake 25.1 26.2 Bulk gyttja Flett Research 12.35 0.37 58 52 63 na # Chickaree Lake 58 59.5 Charcoal CAMS 139054 120 100 150 3 406 na # Chickaree Lake 61.6 62.1 Plant remains CAMS 155252 165 35 173 3 283 na # Chickaree Lake 81.5 83.5 Charcoal CAMS 139055 230 70 233 3 456 *4 # Chickaree Lake 83 83.5 Bulk gyttja CAMS 139056 395 30 466 330 505 *4 # Chickaree Lake 116 117.5 Charcoal CAMS 139057 620 70 601 525 679 *4 # Chickaree Lake 116.5 117 Bulk gyttja CAMS 139058 750 35 686 659 731 *4 # Chickaree Lake 124.5 125 Bulk gyttja CAMS 155253 840 30 746 693 879 na # Chickaree Lake 155 156.5 Charcoal CAMS 139059 1010 50 924 798 1043 na # Chickaree Lake 191 191.5 Bulk gyttja CAMS 155254 1310 30 1251 1181 1291 *4 # Chickaree Lake 191.5 192 Charcoal CAMS 155255 1245 45 1183 1066 1274 *4 # Chickaree Lake 240 240.5 Bulk gyttja CAMS 159645 1810 30 1752 1637 1821 na # Chickaree Lake 290 290.5 Bulk gyttja CAMS 159646 1975 30 1924 1863 1989 na # Chickaree Lake 340 340.5 Bulk gyttja CAMS 159647 2375 35 2410 2344 2665 na # Chickaree Lake 380 380.5 Wood CAMS 155256 2495 35 2580 2392 2719 na # Chickaree Lake 423.5 424 Bulk gyttja CAMS 155257 2685 35 2788 2752 2855 *4 # Chickaree Lake 424 424.5 Charcoal CAMS 155258 2555 35 2661 2503 2747 *4 # Chickaree Lake 452 453 Charcoal CAMS 155259 2740 70 2847 2754 3032 na # Chickaree Lake 488.5 489 Bulk gyttja CAMS 155260 3045 35 3269 3147 3351 na # Chickaree Lake 530 530.5 Bulk gyttja CAMS 159648 3390 30 3636 3565 3704 na # Chickaree Lake 570.5 571 Bulk gyttja CAMS 159649 3805 35 4194 4092 4359 na # Chickaree Lake 605.5 606 Bulk gyttja CAMS 159650 4050 30 4522 4439 4777 na # Chickaree Lake 639.5 640 Bulk gyttja CAMS 155261 4245 40 4825 4647 4865 na # Chickaree Lake 680.5 681 Bulk gyttja CAMS 159651 4675 35 5399 5322 5567 na # Chickaree Lake 720.5 721 Bulk gyttja CAMS 159652 5175 35 5933 5794 5992 na # Chickaree Lake 763.5 764 Bulk gyttja CAMS 159653 5610 40 6379 6310 6476 na # #--------------------------------------- # Variables # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) ## depth-cm-top Depth,,,cm,,,top depth,,N ## depth-cm-bottom Depth,,,cm,,,bottom depth,,N ## age-calBP-top Age,,,calendar years BP,,Fire History,top of sample,,N ## age-calBP-bottom Age,,,calendar years BP,,Fire History,bottom of sample,,N ## d15N d15N,sediment,,per mil,,Fire History,,,N ## N% Nitrogen,sediment,,percent,,Fire History,,,N ## d13C-per-mil d13C,sediment,,per mil,,Fire History,,,N ## C% Carbon,sediment,,percent,,Fire History,,,N ## C:N_atomic_ratio Carbon/Nitrogen,sediment,,,,Fire History,,,N ## bulk_density Bulk density,sediment,,dry grams per wet cm cubed,,Fire History,,,N ## loi%550org Organic matter,sediment,,percent by weight,,Fire History,,combusted 550 degrees C four 4 hours,N ## loi%1000org Organic matter,sediment,,percent by weight,,Fire History,,combusted 1000 degrees C four 4 hours,N ## notes Notes,,,,,Fire History,,, #------------------------ # Data # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Value: top_cm bot_cm top_age bot_age d15N N% d13C C% C:N_atomic_ratio bulk_density loi%550org loi%1000org notes 0.8 2.9 -60 -54 0.08 2 -27.33 19.07 11.12 0.41 0.38 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 1; bot_sam_#:4 7.8 10.5 -37 -28 -0.3 1.28 -26.03 14.01 12.76 0.34 0.29 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 14; bot_sam_#:18 14.8 16.5 -13 -5 0.19 1.1 -26.82 13.23 14.03 0.4 0.27 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 27; bot_sam_#:29 19.2 20.2 9 16 -0.08 1.41 -27.65 16.64 13.76 0.33 0.33 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 35; bot_sam_#:36 22.4 23.5 30 38 -0.34 1.9 -27.54 21.06 12.93 0.24 0.37 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 41; bot_sam_#:42 25.6 26.7 52 59 -0.31 1.59 -27.37 19.09 14 0.3 0.35 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 47; bot_sam_#:48 28.9 30 69 78 0.09 1.71 -26.5 22.31 15.22 0.27 0.39 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 53; bot_sam_#:54 32.1 33.2 90 97 0.55 1.66 -26.52 19.1 13.42 0.2 0.36 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 59; bot_sam_#:60 35.4 36.5 109 116 0.26 1.69 -27.16 17.51 12.08 0.27 0.33 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 65; bot_sam_#:66 36.5 40.8 116 140 0.15 1.32 -27 14 12.37 0.3 0.27 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 72; bot_sam_#:74 42.4 43.5 148 154 0 0.71 -26.58 7.17 11.78 0.42 0.16 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 78; bot_sam_#:79 43.5 44 154 157 0.9 0.49 -26.45 6.11 14.54 0.71 0.13 0.02 core_ID: CH07; drive_ID: sh; top_sam_#: 80; bot_sam_#:80 46.4 46.9 169 172 0.6 2.03 -29.21 25.81 14.83 0.16 0.42 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 86; bot_sam_#:86 47.9 48.3 177 179 0.58 1.97 -28.53 26.43 15.65 0.16 0.44 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 89; bot_sam_#:89 50.3 51.2 189 193 0.89 1.9 -27.85 26.16 16.06 0.26 0.42 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 94; bot_sam_#:95 53.2 54.1 203 208 0.82 1.87 -27.8 22.99 14.34 0.21 0.4 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 100; bot_sam_#:101 56.1 57 218 223 0.97 1.46 -28.47 16.33 13.04 0.26 0.31 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 106; bot_sam_#:107 59 60 234 239 0.46 1.67 -28.21 20.24 14.13 0.21 0.36 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 112; bot_sam_#:113 62.1 63.1 251 257 0.39 1.76 -28.93 22.62 14.99 0.2 0.4 0.05 core_ID: CH07; drive_ID: sh; top_sam_#: 118; bot_sam_#:119 65.1 66.2 270 276 0.5 1.68 -28.46 19.74 13.7 0.3 0.36 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 124; bot_sam_#:125 68.2 69.2 286 293 0.53 1.92 -26.95 28.08 17.06 0.19 0.46 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 130; bot_sam_#:131 71.3 72.3 310 317 0.62 1.62 -27.88 20.75 14.94 0.19 0.38 0.03 core_ID: CH07; drive_ID: sh; top_sam_#: 136; bot_sam_#:137 74.3 75.4 331 339 0.87 1.73 -28.38 20.04 13.51 0.23 0.36 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 142; bot_sam_#:143 77.4 78.4 353 360 0.52 1.59 -28.32 18.01 13.21 0.28 0.35 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 148; bot_sam_#:149 80.5 81.5 376 383 0.37 2.01 -28.55 24.03 13.93 0.2 0.44 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 154; bot_sam_#:155 83.5 84.5 398 406 0.35 1.89 -28.85 23.09 14.25 0.18 0.42 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 160; bot_sam_#:161 86.5 87.5 421 429 0.5 1.89 -28.93 24.96 15.4 0.23 0.44 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 166; bot_sam_#:167 89.5 90.5 445 452 0.47 1.74 -28.42 22.88 15.3 0.32 0.41 0.04 core_ID: CH07; drive_ID: sh; top_sam_#: 172; bot_sam_#:173 92.5 93.5 468 476 1.1 1.44 -27.98 19.22 15.57 0.13 0.39 0.03 core_ID: CH10; drive_ID: 2A; top_sam_#: 94; bot_sam_#:95 98.5 99.5 515 523 0.96 1.45 -28.17 18.47 14.85 0.16 0.34 0.03 core_ID: CH10; drive_ID: 2A; top_sam_#: 106; bot_sam_#:107 104.5 105.5 563 571 1.25 1.59 -28.15 20.94 15.36 0.16 0.4 0.03 core_ID: CH10; drive_ID: 2A; top_sam_#: 118; bot_sam_#:119 110.5 111.5 610 618 1.06 1.46 -27.06 17.93 14.32 0.14 0.33 0.03 core_ID: CH10; drive_ID: 2A; top_sam_#: 130; bot_sam_#:131 116.5 117.5 657 664 1.02 1.53 -28.57 21.32 16.25 0.16 0.4 0.03 core_ID: CH10; drive_ID: 2A; top_sam_#: 142; bot_sam_#:143 122.5 123.5 702 710 1.05 1.31 -27.24 16.75 14.91 0.19 0.33 0.02 core_ID: CH10; drive_ID: 2A; top_sam_#: 154; bot_sam_#:155 128.5 129.5 747 754 1.06 1.5 -27.73 19.48 15.14 0.2 0.37 0.04 core_ID: CH10; drive_ID: 2A; top_sam_#: 166; bot_sam_#:167 134.5 135.5 789 797 0.95 1.2 -27.05 13.81 13.42 0.18 0.28 0.04 core_ID: CH10; drive_ID: 2A; top_sam_#: 178; bot_sam_#:179 140.5 141.5 832 839 1.19 1.23 -26.75 17.35 16.45 0.2 0.32 0.04 core_ID: CH10; drive_ID: 2A; top_sam_#: 190; bot_sam_#:191 151.5 152.5 910 917 0.79 1.7 -28 22.45 15.4 0.14 0.42 0.05 core_ID: CH10; drive_ID: 2B; top_sam_#: 11; bot_sam_#:12 157.5 158.5 954 962 0.78 1.6 -28.84 19.57 14.26 0.16 0.38 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 23; bot_sam_#:24 163.5 164.5 1000 1008 0.79 1.66 -29.22 21.76 15.29 0.13 0.37 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 35; bot_sam_#:36 169.5 170.5 1048 1056 0.95 1.14 -26.95 13.71 14.02 0.18 0.34 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 47; bot_sam_#:48 175.5 176.5 1097 1106 0.76 1.08 -25.3 11.53 12.45 0.2 0.24 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 59; bot_sam_#:60 179.5 180.5 1132 1140 1.53 1.36 -26.03 16 13.72 0.19 0.32 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 67; bot_sam_#:68 183.5 184.5 1167 1176 1.17 1.19 -26.41 14.72 14.43 0.18 0.3 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 75; bot_sam_#:76 186 186.5 1189 1194 0.99 0.92 -26.73 10.34 13.11 0.16 0.23 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 80; bot_sam_#:80 186.5 187 1194 1198 1.34 0.76 -26.83 8.56 13.13 0.18 0.22 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 81; bot_sam_#:81 187 187.5 1198 1203 1.65 1.04 -26.75 11.79 13.22 0.21 0.24 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 82; bot_sam_#:82 187.5 188 1203 1208 1.62 1.07 -26.79 12.12 13.21 0.19 0.25 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 83; bot_sam_#:83 188 188.5 1208 1212 1.65 1.25 -27.08 14.02 13.08 0.21 0.28 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 84; bot_sam_#:84 189 189.5 1217 1222 1.57 1.06 -26.36 11.9 13.09 0.2 0.25 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 86; bot_sam_#:86 190 190.5 1226 1231 1.74 1.03 -26.88 11.69 13.24 0.21 0.24 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 88; bot_sam_#:88 191 191.5 1236 1240 2.07 0.65 -26.24 8.41 15.09 0.38 0.17 0.02 core_ID: CH10; drive_ID: 2B; top_sam_#: 90; bot_sam_#:90 192 192.5 1245 1250 1.76 1.16 -25.9 13.64 13.71 0.16 0.28 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 92; bot_sam_#:92 193 193.5 1254 1259 1.26 1.21 -25.43 14.68 14.15 0.19 0.29 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 94; bot_sam_#:94 194 194.5 1264 1269 1.13 1.11 -25.72 13.38 14.06 0.2 0.27 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 96; bot_sam_#:96 195 195.5 1274 1279 1.11 1.22 -26.01 15.04 14.38 0.19 0.3 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 98; bot_sam_#:98 196 196.5 1283 1288 1.04 1.15 -25.84 13.55 13.74 0.21 0.28 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 100; bot_sam_#:100 198 199 1303 1313 0.42 0.86 -25.72 9.21 12.49 0.14 0.2 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 104; bot_sam_#:105 202 203 1342 1352 1.84 1.09 -26.59 12.22 13.07 0.2 0.26 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 112; bot_sam_#:113 204 205 1362 1372 0.88 1.23 -26.2 13.99 13.26 0.16 0.28 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 116; bot_sam_#:117 206 207 1382 1392 1.47 1.16 -26.85 13.92 13.99 0.2 0.28 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 120; bot_sam_#:121 210 211 1422 1432 1.1 1.42 -26.18 17.24 14.16 0.17 0.34 0.03 core_ID: CH10; drive_ID: 2B; top_sam_#: 128; bot_sam_#:129 216 217 1481 1491 1.51 1.24 -26.38 16.33 15.36 0.16 0.31 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 140; bot_sam_#:141 222 223 1538 1547 1.18 1.21 -26.81 16.07 15.49 0.19 0.31 0.05 core_ID: CH10; drive_ID: 2B; top_sam_#: 152; bot_sam_#:153 228 229 1593 1601 0.56 1.47 -24.66 27.89 22.13 0.16 0.46 0.05 core_ID: CH10; drive_ID: 2B; top_sam_#: 164; bot_sam_#:165 234 235 1643 1651 0.78 1.43 -24.49 30.89 25.19 0.14 0.48 0.05 core_ID: CH10; drive_ID: 2B; top_sam_#: 176; bot_sam_#:177 240 241 1689 1696 1.78 1.27 -26.66 15.71 14.43 0.21 0.3 0.04 core_ID: CH10; drive_ID: 2B; top_sam_#: 188; bot_sam_#:189 251.5 252.5 1762 1768 1.88 1.22 -25.88 15.71 15.02 0.22 0.31 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 11; bot_sam_#:12 257.5 258.5 1794 1800 0.91 1.23 -25.73 14.74 13.98 0.22 0.28 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 23; bot_sam_#:24 263.5 264.5 1825 1829 1.5 1.01 -26.16 12.21 14.1 0.2 0.26 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 35; bot_sam_#:36 270 270.5 1856 1858 1.06 1.13 -25.76 12.87 13.28 0.2 0.26 0.03 core_ID: CH10; drive_ID: 2C; top_sam_#: 48; bot_sam_#:48 276 276.5 1886 1888 0.81 1.11 -26.34 12.31 12.93 0.19 0.24 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 60; bot_sam_#:60 281.5 282.5 1914 1920 1.13 1.29 -26.24 14.56 13.16 0.18 0.29 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 71; bot_sam_#:72 287.5 288.5 1948 1954 1.17 1.37 -25.99 16.77 14.28 0.17 0.33 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 83; bot_sam_#:84 293.5 294.5 1986 1993 1.34 1.22 -25.81 14.72 14.07 0.18 0.29 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 95; bot_sam_#:96 299.5 300.5 2029 2036 1.41 1.36 -25.23 19.06 16.34 0.17 0.34 0.05 core_ID: CH10; drive_ID: 2C; top_sam_#: 107; bot_sam_#:108 306 306.5 2078 2082 1.68 1.08 -27.22 12.31 13.29 0.22 0.24 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 120; bot_sam_#:120 312 312.5 2126 2130 1.44 1.18 -25.64 13.95 13.79 0.19 0.29 0.05 core_ID: CH10; drive_ID: 2C; top_sam_#: 132; bot_sam_#:132 318 318.5 2175 2179 1.48 1.49 -25.9 23.14 18.11 0.2 0.42 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 144; bot_sam_#:144 323.5 324.5 2220 2228 1.45 1.32 -26.94 17.24 15.23 0.21 0.33 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 155; bot_sam_#:156 329.5 330.5 2269 2277 0.46 1.4 -25.45 18.93 15.77 0.16 0.36 0.05 core_ID: CH10; drive_ID: 2C; top_sam_#: 167; bot_sam_#:168 335.5 336.5 2316 2323 1.15 1.37 -25.91 19 16.17 0.21 0.36 0.05 core_ID: CH10; drive_ID: 2C; top_sam_#: 179; bot_sam_#:180 341.5 342.5 2360 2367 1.29 1.1 -25.22 14 14.84 0.2 0.3 0.04 core_ID: CH10; drive_ID: 2C; top_sam_#: 191; bot_sam_#:192 351.5 352.5 2425 2431 1.02 1.18 -26.03 14.41 14.24 0.24 0.29 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 11; bot_sam_#:12 357.5 358.5 2461 2466 0.84 1.3 -25.79 17.36 15.57 0.22 0.32 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 23; bot_sam_#:24 363.5 364.5 2493 2499 0.71 1.21 -25.76 17.08 16.46 0.2 0.32 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 35; bot_sam_#:36 369.5 370.5 2524 2528 1.08 1.26 -26.29 16.18 14.98 0.2 0.33 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 47; bot_sam_#:48 375.5 376.5 2552 2556 0.95 1.23 -25.95 15.2 14.41 0.22 0.3 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 59; bot_sam_#:60 381.5 382.5 2578 2582 0.51 1.26 -24.4 17.09 15.82 0.17 0.32 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 71; bot_sam_#:72 387.5 388.5 2603 2607 0.5 1.07 -25.08 11.77 12.83 0.16 0.26 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 83; bot_sam_#:84 393.5 394.5 2627 2631 0.36 1.02 -25.76 12.57 14.37 0.2 0.26 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 95; bot_sam_#:96 400 400.5 2652 2654 0.68 0.79 -27 8.04 11.87 0.27 0.18 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 108; bot_sam_#:108 406 406.5 2675 2677 0.52 1.27 -24.5 21.47 19.72 0.19 0.36 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 120; bot_sam_#:120 411 412 2695 2699 0.84 1.38 -25.34 18.41 15.56 0.2 0.34 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 130; bot_sam_#:131 417 418 2719 2723 0.82 1.36 -26.8 17.23 14.77 0.19 0.32 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 142; bot_sam_#:143 423.5 424 2746 2748 0.85 1.1 -28.36 13.48 14.29 0.26 0.26 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 155; bot_sam_#:155 429.5 430 2774 2776 0.47 1.38 -26.38 18.54 15.67 0.24 0.33 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 167; bot_sam_#:167 435 436 2801 2806 0.9 1.43 -26.03 17.93 14.62 0.21 0.34 0.03 core_ID: CH10; drive_ID: 2D; top_sam_#: 178; bot_sam_#:179 441 442 2834 2839 0.66 1.69 -25.61 22.1 15.25 0.22 0.39 0.04 core_ID: CH10; drive_ID: 2D; top_sam_#: 190; bot_sam_#:191 451 451.5 2897 2901 0.53 1.32 -25.93 16.32 14.42 0.26 0.31 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 10; bot_sam_#:10 457 457.5 2942 2946 0.96 1.28 -26.17 16.36 14.91 0.27 0.3 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 22; bot_sam_#:22 463 464 2991 2999 1.37 1.17 -26.27 16.17 16.12 0.28 0.3 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 34; bot_sam_#:35 469 470 3043 3052 0.64 1.19 -26.04 15.78 15.46 0.3 0.3 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 46; bot_sam_#:47 475 476 3099 3108 0.84 1.11 -26.24 14.08 14.79 0.28 0.27 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 58; bot_sam_#:59 481 482 3156 3166 0.49 1.09 -25.79 13.74 14.7 0.27 0.27 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 70; bot_sam_#:71 487.5 488 3220 3225 0.29 1.15 -25.98 14.01 14.21 0.31 0.27 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 83; bot_sam_#:83 493.5 494 3279 3283 1.38 1.12 -26.3 15.95 16.61 0.33 0.3 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 95; bot_sam_#:95 498 499 3323 3333 1.12 1.33 -25.84 18.96 16.62 0.29 0.35 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 104; bot_sam_#:105 504 505 3383 3393 0.54 1.14 -26.62 14.95 15.29 0.29 0.27 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 116; bot_sam_#:117 510 511 3443 3453 0.55 1.31 -27.06 15.9 14.15 0.3 0.31 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 128; bot_sam_#:129 516 517 3500 3510 0.88 1.3 -26.66 16.07 14.42 0.28 0.31 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 140; bot_sam_#:141 522 523 3569 3580 1.92 1.07 -26.12 13.47 14.68 0.29 0.26 0.04 core_ID: CH10; drive_ID: 2E; top_sam_#: 152; bot_sam_#:153 528.5 529 3641 3647 0.86 1.2 -26.36 15.49 15.05 0.31 0.28 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 165; bot_sam_#:165 534.5 535 3710 3716 1.8 0.41 -25.2 6.9 19.78 0.84 0.09 0.01 core_ID: CH10; drive_ID: 2E; top_sam_#: 177; bot_sam_#:177 539.5 540 3769 3775 1.18 0.9 -26.1 11.13 14.42 0.29 0.25 0.03 core_ID: CH10; drive_ID: 2E; top_sam_#: 189; bot_sam_#:189 550 551 3897 3909 0.78 1.13 -25.83 15.24 15.73 0.33 0.29 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 11; bot_sam_#:12 556 557 3970 3982 1.04 1.28 -27.31 15.37 14 0.26 0.31 0.04 core_ID: CH10 ; drive_ID: 2F; top_sam_#: 23; bot_sam_#:24 562 563 4042 4054 1.03 1.13 -26.22 14.17 14.62 0.29 0.28 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 35; bot_sam_#:36 568.5 569 4119 4125 2.09 1.08 -27.16 14.25 15.39 0.28 0.27 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 48; bot_sam_#:48 574.5 575 4187 4193 1.67 1.09 -26.1 14.14 15.13 0.26 0.29 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 60; bot_sam_#:60 580 581 4247 4258 2.14 1.16 -26.05 15.05 15.13 0.25 0.31 0.03 core_ID: CH10; drive_ID: 2F; top_sam_#: 71; bot_sam_#:72 586.5 587 4316 4321 2.28 1.15 -26.32 16.75 16.99 0.29 0.31 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 84; bot_sam_#:84 592.5 593 4378 4383 2 1.09 -26.52 12.67 13.56 0.35 0.26 0.04 core_ID: CH10; drive_ID: 2F; top_sam_#: 96; bot_sam_#:96