paleo data:
  measurement table:
    google work sheet key: ow16mzd
    table name: paleo1measurement1
    missing value: NaN
    d2 h:
      description: terrestrial biomarker
      has chron: 1
      has max value: -140
      has mean value: -157.4231
      has median value: -158
      has min value: -171
      has paleo depth: 1
      inferred material: soil water
      inferred material group: soil water
      inferred material group original: soil water
      instrument: Thermo Trace GC, high-temperature pyrolysis reactor at 1450�C, Thermo Finnigan Delta V isotope ratio mass spectrometer
      iso2k certification: ET
      iso2k primary timeseries: TRUE
      iso2k UI: LS13WASU01
      long name: AD
      measurement material: n-alkane
      measurement material detail: C29
      measurement standard: VSMOW
      measurement table name: measurementTable1
      median res12k: NA
      notes: ; archiveType changed - was originally Lake sediment (LS)
      paleo data table name: s1
      QC certification: ET
      t sid: LS13WASU01B
      uncertainty analytical: 3 permil
      units: permil
      variable name: d2H
      variable name original: dD
      variable type: measured
      is primary: false
      primary age column: false
      has time tsid: MAT7cbe87ad3a
      values: -140
      values: -147
      values: -146
      values: -157
      values: -154
      values: -145
      values: -159
      values: -155
      values: -151
      values: -158
      values: -162
      values: -164
      values: -166
      values: -156
      values: -165
      values: -148
      values: -160
      values: -150
      values: -161
      values: -169
      values: -163
      values: -153
      values: -152
      values: -149
      values: -167
      values: -171
      values: -168
      interpretation:
        basis: The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the ?D values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the ?D record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and rela- tive humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the ?D of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).
        direction: increase
        interp direction: increase
        scope: climate
        seasonality: Growing Season
        variable: effectivePrecipitation
        variable detail: air@surface
        variable detail original: air
        variable group: P/E
      interpretation:
        scope: climate
      interpretation:
        scope: climate
      interpretation:
        basis: Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.
        direction: negative
        inferred material: soil water
        mathematical relation: linear
        rank: 1
        scope: isotope
        seasonality: deleteMe
        variable: effectivePrecipitation
        variable group: EffectiveMoisture
        variable group direction: negative
        variable group original: P_E
        coefficient: NA
        fraction: NA
      interpretation:
        basis: The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the ?D values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the ?D record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).
        direction: negative
        mathematical relation: linear
        rank: 2
        scope: isotope
        seasonality: deleteMe
        variable: effectivePrecipitation
        variable group: EffectiveMoisture
        variable group direction: negative
        variable group original: P_E
        coefficient: NA
        fraction: NA
      interpretation:
        scope: isotope
        coefficient: NA
        fraction: NA
        rank: NA
      has resolution:
        has max value: 90
        has mean value: 22.2597
        has median value: 20
        has min value: 4
        units: AD
      in compilation beta:
        compilation name: iso2k
        compilation version: 0_14_8
        compilation version: 0_15_0
        compilation version: 1_0_0
        compilation version: 1_1_0
        compilation version: 1_1_1
    year:
      description: Year AD
      has max value: 2007
      has mean value: 1221.4744
      has median value: 1225
      has min value: 293
      iso2k primary timeseries: FALSE
      long name: AD
      measurement table name: measurementTable1
      median res12k: NA
      paleo data table name: s1
      t sid: MAT7cbe87ad3a
      units: yr AD
      units original: CE
      variable name: year
      is primary: true
      primary age column: true
      has time tsid: MAT7cbe87ad3a
      values: -57
      values: -53
      values: -48
      values: -43
      values: -37
      values: -31
      values: -25
      values: 3
      values: 11
      values: 19
      values: 36
      values: 73
      values: 93
      values: 133
      values: 153
      values: 173
      values: 194
      values: 214
      values: 244
      values: 264
      values: 274
      values: 314
      values: 334
      values: 354
      values: 374
      values: 394
      values: 414
      values: 434
      values: 454
      values: 474
      values: 494
      values: 504
      values: 514
      values: 524
      values: 534
      values: 554
      values: 574
      values: 605
      values: 695
      values: 755
      values: 775
      values: 805
      values: 835
      values: 875
      values: 895
      values: 915
      values: 935
      values: 955
      values: 975
      values: 995
      values: 1015
      values: 1036
      values: 1056
      values: 1076
      values: 1096
      values: 1126
      values: 1156
      values: 1176
      values: 1196
      values: 1216
      values: 1246
      values: 1266
      values: 1286
archive type: LakeSediment
archive type original: lake sediment
created by: matlab
dataset id: nKM7gKd5MEk3rVGc0XgO
data set name: LS13WASU
dataset version: 1.0.6
google metadata worksheet: ocwxlry
has chron: 0
has depth: 1
has paleo depth: 1
lipdverse link: https://lipdverse.org/data/nKM7gKd5MEk3rVGc0XgO/1_0_6
max year: 1657
min year: -57
n unique ages: 0
original data url: this compilation
lipd version: 1.3
pub: A 1700-year n-alkanes hydrogen isotope record of moisture changes in sediments from Lake Sugan in the Qaidam Basin, northeastern Tibetan Plateau

rank: NA
scope: climate

rank: NA
scope: climate

rank: NA
scope: climate

rank: NA
scope: climate

has max value: 90
has mean value: 22.2597
has median value: 20
has min value: 4
units: AD

rank: NA
scope: climate

rank: NA
scope: climate

rank: NA
scope: climate

rank: NA
scope: climate

has max value: 90
has mean value: 22.2597
has median value: 20
has min value: 4
units: AD

description: depth
has max value: 88.25
has mean value: 41.7628
has median value: 41.75
has min value: 0.25
iso2k primary timeseries: FALSE
long name: AD
measurement table name: measurementTable1
median res12k: NA
paleo data table name: s1
t sid: MAT0bb768872a
units: cm
variable name: depth
is primary: false
primary age column: false
has time tsid: MAT7cbe87ad3a
values: 0.25
values: 0.75
values: 1.25
values: 1.75
values: 2.25
values: 2.75
values: 3.25
values: 5.25
values: 5.75
values: 6.25
values: 7.25
values: 9.25
values: 10.25
values: 12.25
values: 13.25
values: 14.25
values: 15.25
values: 16.25
values: 17.75
values: 18.75
values: 19.25
values: 21.25
values: 22.25
values: 23.25
values: 24.25
values: 25.25
values: 26.25
values: 27.25
values: 28.25
values: 29.25
values: 30.25
values: 30.75
values: 31.25
values: 31.75
values: 32.25
values: 33.25
values: 34.25
values: 35.75
values: 40.25
values: 43.25
values: 44.25
values: 45.75
values: 47.25
values: 49.25
values: 50.25
values: 51.25
values: 52.25
values: 53.25
values: 54.25
values: 55.25
values: 56.25
values: 57.25
values: 58.25
values: 59.25
values: 60.25
values: 61.75
values: 63.25
values: 64.25
values: 65.25
values: 66.25
values: 67.75
values: 68.75
values: 69.75
values: 70.75

description: terrestrial biomarker
has max value: -142
has mean value: -161.8718
has median value: -162
has min value: -180
inferred material: soil water
inferred material group: soil water
inferred material group original: soil water
instrument: Thermo Trace GC, high-temperature pyrolysis reactor at 1450�C, Thermo Finnigan Delta V isotope ratio mass spectrometer
iso2k primary timeseries: FALSE
long name: AD
measurement material: n-alkane
measurement material detail: C27
measurement standard: VSMOW
measurement table name: measurementTable1
median res12k: NA
notes: ; archiveType changed - was originally Lake sediment (LS)
paleo data table name: s1
t sid: LS13WASU01A
uncertainty analytical: 3 permil
units: permil
variable name: d2H
variable name original: dD
variable type: measured
is primary: false
primary age column: false
has time tsid: MAT7cbe87ad3a
values: -147
values: -148
values: -158
values: -155
values: -157
values: -151
values: -142
values: -166
values: -161
values: -169
values: -160
values: -173
values: -177
values: -165
values: -163
values: -153
values: -162
values: -154
values: -168
values: -159
values: -156
values: -170
values: -164
values: -172
values: -150
values: -152
values: -176
values: -180
values: -179
values: -167
values: -174
values: -178
values: -175
interpretation:
  basis: The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the ?D values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the ?D record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and rela- tive humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the ?D of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).
  interp direction: increase
  scope: climate
  seasonality: Growing Season
  variable: effectivePrecipitation
  variable detail: air@surface
  variable detail original: air
  variable group: P/E
interpretation:
  scope: climate
interpretation:
  scope: climate
interpretation:
  basis: Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.
  direction: negative
  inferred material: soil water
  mathematical relation: linear
  rank: 1
  scope: isotope
  seasonality: deleteMe
  variable: effectivePrecipitation
  variable group: EffectiveMoisture
  variable group direction: negative
  variable group original: P_E
  coefficient: NA
  fraction: NA
interpretation:
  basis: The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the dD values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the dD record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).
  direction: negative
  mathematical relation: linear
  rank: 2
  scope: isotope
  seasonality: deleteMe
  variable: effectivePrecipitation
  variable group: EffectiveMoisture
  variable group direction: negative
  variable group original: P_E
  coefficient: NA
  fraction: NA
interpretation:
  scope: isotope
  coefficient: NA
  fraction: NA
  rank: NA
has resolution:
  has max value: 90
  has mean value: 22.2597
  has median value: 20
  has min value: 4
  units: AD
in compilation beta:
  compilation name: iso2k
  compilation version: 0_14_8
  compilation version: 0_15_0
  compilation version: 1_0_0
  compilation version: 1_1_0
  compilation version: 1_1_1

measurement table:
  table name: chron1measurement1
  depth:
    t sid: chron1
    variable name: depth
    description: mid-point depth
    units: cm
    chron name: chron1
    google work sheet key: o2mdon2
    number: 1
    values: 0.25
    values: 1.25
    values: 2.25
    values: 3.25
    values: 4.25
    values: 5.25
    values: 6.25
    values: 7.25
    values: 8.25
    values: 9.25
    values: 27.25
    values: 52.5
    values: 79.75
    values: 97.5
  age14 c:
    t sid: chron2
    variable name: age14C
    description: 14C years before 1950
    units: yr14C BP
    chron name: chron1
    google work sheet key: o2mdon2
    number: 2
    values: NaN
    values: 1350
    values: 2070
    values: 2570
    values: 3000
  age14 cuncertainty:
    t sid: chron3
    variable name: age14Cuncertainty
    description: 14C years uncertainty
    units: yr14C BP
    chron name: chron1
    google work sheet key: o2mdon2
    number: 3
    values: NaN
    values: 30
  age:
    variable name: age
    units: yr14C BP
    number: 4
    t sid: RWPg6tnfuWRN0TKRi
    values: -56
    values: -51
    values: -45
    values: -30
    values: -19
    values: -8
    values: 9
    values: 25
    values: 54
    values: 89
    values: 522
    values: 1019
    values: 1400
    values: 1855
  SD-1:
    units: yr14C BP
    variable name: SD-1
    number: 5
    t sid: Rz6BsJ6IcsPAs3tbW
    values: NaN
    values: 25
    values: 63
    values: 48
model:
  input table:
    id: randomLabId_PMIhQFRJDW
    id: randomLabId_419Ed2yexl
    id: randomLabId_aoPLATjq3i
    id: randomLabId_1C0qaSrYH9
    id: randomLabId_glEIb5uiy1
    id: randomLabId_2f7WSTsJVd
    id: randomLabId_fbaupF8ghw
    id: randomLabId_UmTnDsYPv6
    id: randomLabId_o6wS7TjiF9
    id: randomLabId_NJfaRmTXy3
    id: randomLabId_s02tHGJdbS
    id: randomLabId_Obfj5c8GNm
    id: randomLabId_ZdYL4oBtrn
    id: randomLabId_dCOL5SXBK9
    age: -56
    age: -51
    age: -45
    age: -30
    age: -19
    age: -8
    age: 9
    age: 25
    age: 54
    age: 89
    age: 1350
    age: 2070
    age: 2570
    age: 3000
    error: 1
    error: 30
    depth: 0.25
    depth: 1.25
    depth: 2.25
    depth: 3.25
    depth: 4.25
    depth: 5.25
    depth: 6.25
    depth: 7.25
    depth: 8.25
    depth: 9.25
    depth: 27.25
    depth: 52.5
    depth: 79.75
    depth: 97.5
    cc: 0
    cc: 1
    d r: 0
    d STD: 0
    ta: 33
    ta: 3
    tb: 34
    tb: 4
  methods:
    parameters:
      d.min: 0.25
      d.max: 97.5
      d.by: 5
      depths.file: 0
      acc.mean: 50
      acc.shape: 1.5
      mem.mean: 0.3
      mem.strength: 10
      boundary: NA
      hiatus.depths: NA
      hiatus.max: 10000
      BCAD: 1
      cc: 1
      postbomb: 0
      cc1: IntCal20
      cc2: Marine20
      cc3: SHCal20
      cc4: ConstCal
      depth.unit: cm
      normal: 0
      t.a: 3
      t.b: 4
      delta.r: 0
      d.std: 0
      prob: 0.95
      age.unit: yr
    algorithm: bacon
    version: 2.3
  summary table:
    table name: chron1model1measurement1
    depth:
      variable name: depth
      units: cm
      description: modeled depth
      number: 1
      values: 0.25
      values: 5.25
      values: 10.25
      values: 15.25
      values: 20.25
      values: 25.25
      values: 30.25
      values: 35.25
      values: 40.25
      values: 45.25
      values: 50.25
      values: 55.25
      values: 60.25
      values: 65.25
      values: 70.25
      values: 75.25
      values: 80.25
      values: 85.25
      values: 90.25
      values: 95.25
    age.range low:
      variable name: age.rangeLow
      units: yr BP
      description: low end of the uncertainty range
      uncertainty level: 2.5%
      number: 2
      values: 2004
      values: 1954
      values: 1783
      values: 1345
      values: 1025
      values: 761
      values: 555
      values: 373
      values: 211
      values: 64
      values: -76
      values: -220
      values: -366
      values: -498
      values: -622
      values: -732
      values: -843
      values: -1057
      values: -1221
      values: -1365

variable name: age.rangeHigh
units: yr BP
description: high end of the uncertainty range
uncertainty level: 97.5%
number: 3
values: 2008
values: 1978
values: 1926
values: 1740
values: 1474
values: 1177
values: 919
values: 744
values: 566
values: 381
values: 185
values: 17
values: -108
values: -240
values: -373
values: -509
values: -651
values: -817
values: -960
values: -1114

variable name: age
units: yr BP
description: weighted mean age estimate
number: 4
values: 2005
values: 1961
values: 1842
values: 1566
values: 1252
values: 938
values: 709
values: 541
values: 375
values: 209
values: 43
values: -107
values: -242
values: -375
values: -507
values: -642
values: -779
values: -934
values: -1092
values: -1250

depth: 0.25
depth.units: cm
table name: chron1model1distribution1
age:
  units: yr BP
  variable name: age
  number: 1
  values: -59.1111
  values: -59.0303
  values: -58.9495
  values: -58.8687
  values: -58.7879
  values: -58.7071
  values: -58.6263
  values: -58.5455
  values: -58.4646
  values: -58.3838
  values: -58.303
  values: -58.2222
  values: -58.1414
  values: -58.0606
  values: -57.9798
  values: -57.899
  values: -57.8182
  values: -57.7374
  values: -57.6566
  values: -57.5758
  values: -57.4949
  values: -57.4141
  values: -57.3333
  values: -57.2525
  values: -57.1717
  values: -57.0909
  values: -57.0101
  values: -56.9293
  values: -56.8485
  values: -56.7677
  values: -56.6869
  values: -56.6061
  values: -56.5253
  values: -56.4444
  values: -56.3636
  values: -56.2828
  values: -56.202
  values: -56.1212
  values: -56.0404
  values: -55.9596
  values: -55.8788
  values: -55.798
  values: -55.7172
  values: -55.6364
  values: -55.5556
  values: -55.4747
  values: -55.3939
  values: -55.3131
  values: -55.2323
  values: -55.1515
  values: -55.0707
  values: -54.9899
  values: -54.9091
  values: -54.8283
  values: -54.7475
  values: -54.6667
  values: -54.5859
  values: -54.5051
  values: -54.4242
  values: -54.3434
  values: -54.2626
  values: -54.1818
  values: -54.101
  values: -54.0202
  values: -53.9394
  values: -53.8586
  values: -53.7778
  values: -53.697
  values: -53.6162
  values: -53.5354
  values: -53.4545
  values: -53.3737
  values: -53.2929
  values: -53.2121
  values: -53.1313
  values: -53.0505
  values: -52.9697
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.001
  values: 0.0012
  values: 0.0015
  values: 0.0018
  values: 0.0022
  values: 0.0026
  values: 0.003
  values: 0.0036
  values: 0.0042
  values: 0.0048
  values: 0.0056
  values: 0.0065
  values: 0.0074
  values: 0.0084
  values: 0.0095
  values: 0.0107
  values: 0.012
  values: 0.0133
  values: 0.0147
  values: 0.0162
  values: 0.0177
  values: 0.0192
  values: 0.0207
  values: 0.0222
  values: 0.0237
  values: 0.0251
  values: 0.0264
  values: 0.0276
  values: 0.0287
  values: 0.0297
  values: 0.0304
  values: 0.031
  values: 0.0314
  values: 0.0316

depth: 1.25
depth.units: cm
table name: chron1model1distribution2
age:
  units: yr BP
  variable name: age
  number: 1
  values: -54.1111
  values: -54.0303
  values: -53.9495
  values: -53.8687
  values: -53.7879
  values: -53.7071
  values: -53.6263
  values: -53.5455
  values: -53.4646
  values: -53.3838
  values: -53.303
  values: -53.2222
  values: -53.1414
  values: -53.0606
  values: -52.9798
  values: -52.899
  values: -52.8182
  values: -52.7374
  values: -52.6566
  values: -52.5758
  values: -52.4949
  values: -52.4141
  values: -52.3333
  values: -52.2525
  values: -52.1717
  values: -52.0909
  values: -52.0101
  values: -51.9293
  values: -51.8485
  values: -51.7677
  values: -51.6869
  values: -51.6061
  values: -51.5253
  values: -51.4444
  values: -51.3636
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depth: 2.25
depth.units: cm
table name: chron1model1distribution3
age:
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probability density:
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depth: 3.25
depth.units: cm
table name: chron1model1distribution4
age:
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probability density:
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depth: 4.25
depth.units: cm
table name: chron1model1distribution5
age:
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probability density:
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depth: 5.25
depth.units: cm
table name: chron1model1distribution6
age:
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probability density:
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depth: 6.25
depth.units: cm
table name: chron1model1distribution7
age:
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probability density:
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depth: 7.25
depth.units: cm
table name: chron1model1distribution8
age:
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probability density:
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depth: 8.25
depth.units: cm
table name: chron1model1distribution9
age:
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  values: 55.2525
  values: 55.3333
  values: 55.4141
  values: 55.4949
  values: 55.5758
  values: 55.6566
  values: 55.7374
  values: 55.8182
  values: 55.899
  values: 55.9798
  values: 56.0606
  values: 56.1414
  values: 56.2222
  values: 56.303
  values: 56.3838
  values: 56.4646
  values: 56.5455
  values: 56.6263
  values: 56.7071
  values: 56.7879
  values: 56.8687
  values: 56.9495
  values: 57.0303
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.001
  values: 0.0012
  values: 0.0015
  values: 0.0018
  values: 0.0022
  values: 0.0026
  values: 0.003
  values: 0.0036
  values: 0.0042
  values: 0.0048
  values: 0.0056
  values: 0.0065
  values: 0.0074
  values: 0.0084
  values: 0.0095
  values: 0.0107
  values: 0.012
  values: 0.0133
  values: 0.0147
  values: 0.0162
  values: 0.0177
  values: 0.0192
  values: 0.0207
  values: 0.0222
  values: 0.0237
  values: 0.0251
  values: 0.0264
  values: 0.0276
  values: 0.0287
  values: 0.0297
  values: 0.0304
  values: 0.031
  values: 0.0314
  values: 0.0316

depth: 9.25
depth.units: cm
table name: chron1model1distribution10
age:
  units: yr BP
  variable name: age
  number: 1
  values: 85.8889
  values: 85.9697
  values: 86.0505
  values: 86.1313
  values: 86.2121
  values: 86.2929
  values: 86.3737
  values: 86.4545
  values: 86.5354
  values: 86.6162
  values: 86.697
  values: 86.7778
  values: 86.8586
  values: 86.9394
  values: 87.0202
  values: 87.101
  values: 87.1818
  values: 87.2626
  values: 87.3434
  values: 87.4242
  values: 87.5051
  values: 87.5859
  values: 87.6667
  values: 87.7475
  values: 87.8283
  values: 87.9091
  values: 87.9899
  values: 88.0707
  values: 88.1515
  values: 88.2323
  values: 88.3131
  values: 88.3939
  values: 88.4747
  values: 88.5556
  values: 88.6364
  values: 88.7172
  values: 88.798
  values: 88.8788
  values: 88.9596
  values: 89.0404
  values: 89.1212
  values: 89.202
  values: 89.2828
  values: 89.3636
  values: 89.4444
  values: 89.5253
  values: 89.6061
  values: 89.6869
  values: 89.7677
  values: 89.8485
  values: 89.9293
  values: 90.0101
  values: 90.0909
  values: 90.1717
  values: 90.2525
  values: 90.3333
  values: 90.4141
  values: 90.4949
  values: 90.5758
  values: 90.6566
  values: 90.7374
  values: 90.8182
  values: 90.899
  values: 90.9798
  values: 91.0606
  values: 91.1414
  values: 91.2222
  values: 91.303
  values: 91.3838
  values: 91.4646
  values: 91.5455
  values: 91.6263
  values: 91.7071
  values: 91.7879
  values: 91.8687
  values: 91.9495
  values: 92.0303
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.001
  values: 0.0012
  values: 0.0015
  values: 0.0018
  values: 0.0022
  values: 0.0026
  values: 0.003
  values: 0.0036
  values: 0.0042
  values: 0.0048
  values: 0.0056
  values: 0.0065
  values: 0.0074
  values: 0.0084
  values: 0.0095
  values: 0.0107
  values: 0.012
  values: 0.0133
  values: 0.0147
  values: 0.0162
  values: 0.0177
  values: 0.0192
  values: 0.0207
  values: 0.0222
  values: 0.0237
  values: 0.0251
  values: 0.0264
  values: 0.0276
  values: 0.0287
  values: 0.0297
  values: 0.0304
  values: 0.031
  values: 0.0314
  values: 0.0316

depth: 27.25
depth.units: cm
table name: chron1model1distribution11
age:
  units: yr BP
  variable name: age
  number: 1
  values: 1076
  values: 1077
  values: 1078
  values: 1079
  values: 1080
  values: 1081
  values: 1082
  values: 1083
  values: 1084
  values: 1085
  values: 1086
  values: 1087
  values: 1088
  values: 1089
  values: 1090
  values: 1091
  values: 1092
  values: 1093
  values: 1094
  values: 1095
  values: 1096
  values: 1097
  values: 1098
  values: 1099
  values: 1100
  values: 1101
  values: 1102
  values: 1103
  values: 1104
  values: 1105
  values: 1106
  values: 1107
  values: 1108
  values: 1109
  values: 1110
  values: 1111
  values: 1112
  values: 1113
  values: 1114
  values: 1115
  values: 1116
  values: 1117
  values: 1118
  values: 1119
  values: 1120
  values: 1121
  values: 1122
  values: 1123
  values: 1124
  values: 1125
  values: 1126
  values: 1127
  values: 1128
  values: 1129
  values: 1130
  values: 1131
  values: 1132
  values: 1133
  values: 1134
  values: 1135
  values: 1136
  values: 1137
  values: 1138
  values: 1139
  values: 1140
  values: 1141
  values: 1142
  values: 1143
  values: 1144
  values: 1145
  values: 1146
  values: 1147
  values: 1148
  values: 1149
  values: 1150
  values: 1151
  values: 1152
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0002
  values: 0.0003
  values: 0.0004
  values: 0.0005
  values: 0.0001
  values: 0.0007
  values: 0.0025
  values: 0.0052
  values: 0.0076
  values: 0.0083
  values: 0.0081
  values: 0.0066
  values: 0.0057
  values: 0.0049
  values: 0.0044
  values: 0.0043
  values: 0.0048
  values: 0.0055
  values: 0.0078
  values: 0.0092
  values: 0.0101
  values: 0.0107
  values: 0.0104
  values: 0.0098
  values: 0.0089
  values: 0.0073
  values: 0.0071
  values: 0.0068
  values: 0.0064
  values: 0.0037
  values: 0.0031
  values: 0.0027
  values: 0.0023
  values: 0.0021
  values: 0.002
  values: 0.0019
  values: 0.0017
  values: 0.0016
  values: 0.0015
  values: 0.0014
  values: 0.0013
  values: 0.0036
  values: 0.0041
  values: 0.0045
  values: 0.0042
  values: 0.0038
  values: 0.0035
  values: 0.0034
  values: 0.0032
  values: 0.004
  values: 0.0046
  values: 0.0051
  values: 0.0053
  values: 0.0061
  values: 0.0065
  values: 0.0069
  values: 0.0072
  values: 0.0082
  values: 0.0088
  values: 0.0093
  values: 0.0099
  values: 0.0105
  values: 0.0114
  values: 0.012
  values: 0.013
  values: 0.0136
  values: 0.0146
  values: 0.0156
  values: 0.0165
  values: 0.0176
  values: 0.0183
  values: 0.0189
  values: 0.0196
  values: 0.02
  values: 0.0202
  values: 0.0198
  values: 0.0193
  values: 0.0185

depth: 52.5
depth.units: cm
table name: chron1model1distribution12
age:
  units: yr BP
  variable name: age
  number: 1
  values: 1829
  values: 1830
  values: 1831
  values: 1832
  values: 1833
  values: 1834
  values: 1835
  values: 1836
  values: 1837
  values: 1838
  values: 1839
  values: 1840
  values: 1841
  values: 1842
  values: 1843
  values: 1844
  values: 1845
  values: 1846
  values: 1847
  values: 1848
  values: 1849
  values: 1850
  values: 1851
  values: 1852
  values: 1853
  values: 1854
  values: 1855
  values: 1856
  values: 1857
  values: 1858
  values: 1859
  values: 1860
  values: 1861
  values: 1862
  values: 1863
  values: 1864
  values: 1865
  values: 1866
  values: 1867
  values: 1868
  values: 1869
  values: 1870
  values: 1871
  values: 1872
  values: 1873
  values: 1874
  values: 1875
  values: 1876
  values: 1877
  values: 1878
  values: 1879
  values: 1880
  values: 1881
  values: 1882
  values: 1883
  values: 1884
  values: 1885
  values: 1886
  values: 1887
  values: 1888
  values: 1889
  values: 1890
  values: 1891
  values: 1892
  values: 1893
  values: 1894
  values: 1895
  values: 1896
  values: 1897
  values: 1898
  values: 1899
  values: 1900
  values: 1901
  values: 1902
  values: 1903
  values: 1904
  values: 1905
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0001
  values: 0.0002
  values: 0.0003
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.0009
  values: 0.001
  values: 0.0012
  values: 0.0013
  values: 0.0015
  values: 0.0016
  values: 0.0017
  values: 0.0018
  values: 0.0019
  values: 0.0021
  values: 0.0022
  values: 0.0023
  values: 0.0026
  values: 0.0028
  values: 0.0031
  values: 0.0035
  values: 0.004
  values: 0.0044
  values: 0.0048
  values: 0.0052
  values: 0.0054
  values: 0.0056
  values: 0.0057
  values: 0.0049
  values: 0.0046
  values: 0.0041
  values: 0.0036
  values: 0.0033
  values: 0.0029
  values: 0.0027
  values: 0.0025
  values: 0.0024
  values: 0.003
  values: 0.0032
  values: 0.0039
  values: 0.0043
  values: 0.0047
  values: 0.006
  values: 0.0065
  values: 0.0069
  values: 0.0072
  values: 0.0075
  values: 0.0078
  values: 0.0079
  values: 0.008
  values: 0.0073
  values: 0.0066
  values: 0.0063
  values: 0.0059
  values: 0.0058
  values: 0.0062
  values: 0.0067
  values: 0.0068
  values: 0.007
  values: 0.0076
  values: 0.0077
  values: 0.0074
  values: 0.0064
  values: 0.0053
  values: 0.0051
  values: 0.0042
  values: 0.005
  values: 0.0038
  values: 0.0037
  values: 0.0034
  values: 0.002
  values: 0.0011
  values: 0

depth: 79.75
depth.units: cm
table name: chron1model1distribution13
age:
  units: yr BP
  variable name: age
  number: 1
  values: 2370
  values: 2371
  values: 2372
  values: 2373
  values: 2374
  values: 2375
  values: 2376
  values: 2377
  values: 2378
  values: 2379
  values: 2380
  values: 2381
  values: 2382
  values: 2383
  values: 2384
  values: 2385
  values: 2386
  values: 2387
  values: 2388
  values: 2389
  values: 2390
  values: 2391
  values: 2392
  values: 2393
  values: 2394
  values: 2395
  values: 2396
  values: 2397
  values: 2398
  values: 2399
  values: 2400
  values: 2401
  values: 2402
  values: 2403
  values: 2404
  values: 2405
  values: 2406
  values: 2407
  values: 2408
  values: 2409
  values: 2410
  values: 2411
  values: 2412
  values: 2413
  values: 2414
  values: 2415
  values: 2416
  values: 2417
  values: 2418
  values: 2419
  values: 2420
  values: 2421
  values: 2422
  values: 2423
  values: 2424
  values: 2425
  values: 2426
  values: 2427
  values: 2428
  values: 2429
  values: 2430
  values: 2431
  values: 2432
  values: 2433
  values: 2434
  values: 2435
  values: 2436
  values: 2437
  values: 2438
  values: 2439
  values: 2440
  values: 2441
  values: 2442
  values: 2443
  values: 2444
  values: 2445
  values: 2446
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0002
  values: 0.0001
  values: 0.0003
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.001
  values: 0.0012
  values: 0.0014
  values: 0.0015
  values: 0.0017
  values: 0.0016
  values: 0.0019
  values: 0.0021
  values: 0.0022
  values: 0.0023
  values: 0.0025
  values: 0.0026
  values: 0.0027
  values: 0.0028
  values: 0.0024
  values: 0.003
  values: 0.0034
  values: 0.0036
  values: 0.004
  values: 0.0043
  values: 0.0046
  values: 0.0049
  values: 0.0051
  values: 0.0048
  values: 0.0045
  values: 0.0037
  values: 0.0035
  values: 0.0032
  values: 0.0029
  values: 0.0033
  values: 0.0031
  values: 0.002
  values: 0.0018
  values: 0.0013
  values: 0.0011
  values: 0.0009
  values: 0.0038
  values: 0.0044
  values: 0.0052
  values: 0.0056
  values: 0.0058
  values: 0.0054
  values: 0.0047
  values: 0.0041
  values: 0.0055
  values: 0.0057
  values: 0.0059
  values: 0.0061
  values: 0.0063
  values: 0.0067
  values: 0.0072
  values: 0.0076
  values: 0.0086
  values: 0.0095
  values: 0.0105
  values: 0.0115
  values: 0.0127
  values: 0.0138
  values: 0.0147
  values: 0.0153
  values: 0.0156
  values: 0.0158
  values: 0.0157
  values: 0.0155
  values: 0.0151
  values: 0.0145
  values: 0.0129
  values: 0.0117
  values: 0.0107
  values: 0.0097

depth: 97.5
depth.units: cm
table name: chron1model1distribution14
age:
  units: yr BP
  variable name: age
  number: 1
  values: 2956
  values: 2957
  values: 2958
  values: 2959
  values: 2960
  values: 2961
  values: 2962
  values: 2963
  values: 2964
  values: 2965
  values: 2966
  values: 2967
  values: 2968
  values: 2969
  values: 2970
  values: 2971
  values: 2972
  values: 2973
  values: 2974
  values: 2975
  values: 2976
  values: 2977
  values: 2978
  values: 2979
  values: 2980
  values: 2981
  values: 2982
  values: 2983
  values: 2984
  values: 2985
  values: 2986
  values: 2987
  values: 2988
  values: 2989
  values: 2990
  values: 2991
  values: 2992
  values: 2993
  values: 2994
  values: 2995
  values: 2996
  values: 2997
  values: 2998
  values: 2999
  values: 3000
  values: 3001
  values: 3002
  values: 3003
  values: 3004
  values: 3005
  values: 3006
  values: 3007
  values: 3008
  values: 3009
  values: 3010
  values: 3011
  values: 3012
  values: 3013
  values: 3014
  values: 3015
  values: 3016
  values: 3017
  values: 3018
  values: 3019
  values: 3020
  values: 3021
  values: 3022
  values: 3023
  values: 3024
  values: 3025
  values: 3026
  values: 3027
  values: 3028
  values: 3029
  values: 3030
  values: 3031
  values: 3032
probability density:
  variable name: probabilityDensity
  number: 2
  values: 0.0001
  values: 0.0002
  values: 0.0003
  values: 0.0004
  values: 0.0005
  values: 0.0006
  values: 0.0007
  values: 0.0008
  values: 0.0009
  values: 0.001
  values: 0.0011
  values: 0.0012
  values: 0.0013
  values: 0.0015
  values: 0.0016
  values: 0.0018
  values: 0.002
  values: 0.0023
  values: 0.0026
  values: 0.0028
  values: 0.0031
  values: 0.0034
  values: 0.0037
  values: 0.0039
  values: 0.0041
  values: 0.0042
  values: 0.0043
  values: 0.004
  values: 0.0038
  values: 0.0035
  values: 0.0032
  values: 0.0029
  values: 0.0025
  values: 0.0019
  values: 0.0017
  values: 0.0021
  values: 0.0024
  values: 0.0027
  values: 0.0036
  values: 0.003
  values: 0.0044
  values: 0.0045
  values: 0.0046
  values: 0.0048
  values: 0.0049
  values: 0.0051
  values: 0.0054
  values: 0.0056
  values: 0.0058
  values: 0.0061
  values: 0.0062
  values: 0.0064
  values: 0.0066
  values: 0.0067
  values: 0.0068
  values: 0.0069
  values: 0.0059
  values: 0.0057
  values: 0.0055
  values: 0.0053
  values: 0.0047
  values: 0.0033
  values: 0.0022
  values: 0.0014

measurement table:
  table name: chron2measurement1
  fraction modern:
    t sid: chron4
    variable name: fractionModern
    description: fraction of modern 14C activity
    chron name: chron1
    google work sheet key: o2mdon2
    number: 1
    values: _NaN_
  fraction modern uncertainty:
    t sid: chron5
    variable name: fractionModernUncertainty
    description: fraction of modern 14C activity uncertainty
    chron name: chron1
    google work sheet key: o2mdon2
    number: 2
    values: _NaN_
  delta13 c:
    t sid: chron6
    variable name: delta13C
    description: delta13C of material analyzed for 14C
    units: permil
    chron name: chron1
    google work sheet key: o2mdon2
    number: 3
    values: _NaN_
  delta13 cuncertainty:
    t sid: chron7
    variable name: delta13Cuncertainty
    description: delta13C uncertainty
    units: permil
    chron name: chron1
    google work sheet key: o2mdon2
    number: 4
    values: _NaN_
  thickness:
    t sid: chron8
    variable name: thickness
    description: thickness of sample (along depth axis)
    units: cm
    chron name: chron1
    google work sheet key: o2mdon2
    number: 5
    values: _NaN_
  lab ID:
    t sid: chron9
    variable name: labID
    description: laboratory ID from radiocarbon facility
    chron name: chron1
    google work sheet key: o2mdon2
    number: 6
    values: _NaN_
  material dated:
    t sid: chron10
    variable name: materialDated
    description: material analyzed
    chron name: chron1
    google work sheet key: o2mdon2
    number: 7
    values: _NaN_
  activity:
    t sid: chron11
    variable name: activity
    description: 210Pb, 239+240Pu or 137Cs activity
    units: Bq g-1
    chron name: chron1
    google work sheet key: o2mdon2
    number: 8
    values: _NaN_
  activity uncertainty:
    t sid: chron12
    variable name: activityUncertainty
    description: 210Pb, 239+240Pu or 137Cs activity uncertainty
    units: Bq g-1
    chron name: chron1
    google work sheet key: o2mdon2
    number: 9
    values: _NaN_
  supported activity:
    t sid: chron13
    variable name: supportedActivity
    description: Y if supported 210Pb activity, N if unsupported 210Pb activity
    chron name: chron1
    google work sheet key: o2mdon2
    number: 10
    values: _NaN_
  reservoir age14 c:
    t sid: chron17
    variable name: reservoirAge14C
    description: 14C reservoir age
    units: yr14C BP
    chron name: chron1
    google work sheet key: o2mdon2
    number: 11
    values: _NaN_
  reservoir age14 c uncertainty:
    t sid: chron18
    variable name: reservoirAge14CUncertainty
    description: 14C reservoir age uncertainty
    units: yr14C BP
    chron name: chron1
    google work sheet key: o2mdon2
    number: 12
    values: _NaN_
  use in age model:
    t sid: chron19
    variable name: useInAgeModel
    description: was this date used in the age model?
    chron name: chron1
    google work sheet key: o2mdon2
    number: 13
    values: _NaN_

version: 1.0.6
last version: 1.0.5
curator: nicholas
timestamp: 2025-05-20 16:18:57.51222 UTC
changes:
  paleo interpretation metadata: depth (MAT0bb768872a): interpretation4_scope: '' has been replaced by 'climate'
  paleo interpretation metadata: year (MAT7cbe87ad3a): interpretation4_scope: '' has been replaced by 'climate'

version: 1.0.5
last version: 1.0.4
curator: nicholas
timestamp: 2025-04-17 20:04:39.893137 UTC
changes:
  paleo column metadata: d2H (LS13WASU01A): paleoData_isPrimary: '' has been replaced by 'FALSE'
  paleo column metadata: d2H (LS13WASU01A): paleoData_primaryAgeColumn: '' has been replaced by 'FALSE'
  paleo column metadata: d2H (LS13WASU01B): paleoData_isPrimary: '' has been replaced by 'FALSE'
  paleo column metadata: d2H (LS13WASU01B): paleoData_primaryAgeColumn: '' has been replaced by 'FALSE'
  paleo column metadata: depth (MAT0bb768872a): paleoData_isPrimary: '' has been replaced by 'FALSE'
  paleo column metadata: depth (MAT0bb768872a): paleoData_primaryAgeColumn: '' has been replaced by 'FALSE'
  paleo column metadata: year (MAT7cbe87ad3a): paleoData_isPrimary: '' has been replaced by 'TRUE'
  paleo column metadata: year (MAT7cbe87ad3a): paleoData_primaryAgeColumn: '' has been replaced by 'TRUE'

version: 1.0.4
last version: 1.0.3
curator: nicholas
timestamp: 2025-04-11 16:26:58.206189 UTC
changes:
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_basis: 'Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_direction: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_inferredMaterial: 'soil water' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_mathematicalRelation: 'linear' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_rank: '1' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_scope: 'isotope' has been replaced by 'climate'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_seasonality: 'deleteMe' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variable: 'effectivePrecipitation' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variableGroup: 'EffectiveMoisture' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variableGroupDirection: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variableGroupOriginal: 'P_E' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_basis: 'The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the dD values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the dD record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_direction: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_mathematicalRelation: 'linear' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_rank: '2' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_scope: 'isotope' has been replaced by 'climate'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_seasonality: 'deleteMe' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variable: 'effectivePrecipitation' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variableGroup: 'EffectiveMoisture' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variableGroupDirection: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variableGroupOriginal: 'P_E' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_basis: '' has been replaced by 'Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_direction: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_inferredMaterial: '' has been replaced by 'soil water'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_mathematicalRelation: '' has been replaced by 'linear'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_rank: '' has been replaced by '1'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_scope: '' has been replaced by 'isotope'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_seasonality: '' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_variable: '' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_variableGroup: '' has been replaced by 'EffectiveMoisture'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_variableGroupDirection: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation4_variableGroupOriginal: '' has been replaced by 'P_E'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_basis: '' has been replaced by 'The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the dD values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the dD record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_direction: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_mathematicalRelation: '' has been replaced by 'linear'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_rank: '' has been replaced by '2'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_scope: '' has been replaced by 'isotope'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_seasonality: '' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_variable: '' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_variableGroup: '' has been replaced by 'EffectiveMoisture'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_variableGroupDirection: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation5_variableGroupOriginal: '' has been replaced by 'P_E'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation6_scope: '' has been replaced by 'isotope'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_basis: 'Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_direction: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_inferredMaterial: 'soil water' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_mathematicalRelation: 'linear' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_rank: '1' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_scope: 'isotope' has been replaced by 'climate'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_seasonality: 'deleteMe' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variable: 'effectivePrecipitation' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variableGroup: 'EffectiveMoisture' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variableGroupDirection: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variableGroupOriginal: 'P_E' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_basis: 'The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the ?D values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the ?D record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_direction: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_mathematicalRelation: 'linear' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_rank: '2' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_scope: 'isotope' has been replaced by 'climate'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_seasonality: 'deleteMe' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variable: 'effectivePrecipitation' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variableGroup: 'EffectiveMoisture' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variableGroupDirection: 'negative' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variableGroupOriginal: 'P_E' has been replaced by ''
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_basis: '' has been replaced by 'Variation in vegetation type (shrubs and grass) is the main factor influencing the [d2H of leaf waxes in] sediments of Lake Sugan, because of the dD values of Chenopodiceae shrubs are higher than those of grasses. We can still discuss the moisture history using the hydrogen-isotope record, because the vegetation type would be consistent with hydrological condition. [i.e., Chenopodiaceae shrubs tend to be more abundant in dry climates, and Chenopodiaceae shrubs have a smaller apparent fractionation, so dry climates would not only cause greater evaporative enrichment of plant source water, but more leaf waxes with relatively enriched d2H would be produced by Chenopodiaceae shrubs.] In the arid area of western China, vegetation type is controlled by moisture changes (Wu, 2011). The authors conclude that variations in vegetation type (shrub or grass), which are caused by moisture changes, are the main factor controlling the δD records in the study area.'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_direction: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_inferredMaterial: '' has been replaced by 'soil water'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_mathematicalRelation: '' has been replaced by 'linear'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_rank: '' has been replaced by '1'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_scope: '' has been replaced by 'isotope'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_seasonality: '' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_variable: '' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_variableGroup: '' has been replaced by 'EffectiveMoisture'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_variableGroupDirection: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation4_variableGroupOriginal: '' has been replaced by 'P_E'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation5_basis: '' has been replaced by 'The effective moisture (ratio of precipitation to evaporation) is considered as the main factor controlling the ?D values of lipid n-alkanes in terrestrial plants (Polissar and Freeman, 2010). In a previous study, the ?D record from a loess profile in the Chinese Loess Plateau displayed a strong correlation to changes in the magnetic susceptibility (MS) over the past 130 ka, and the isoto- pic variation was thought to be strongly affected by aridity (Liu and Huang, 2005). Furthermore, a humidity control experiment in the field verified the correlation between D enrichment and relative humidity (McInerney et al., 2011). A study of lipids from the Santa Barbara Basin from the past 1400 years also revealed the dD of mid-chain acids to be partially correlated with existing data of drought severity (Li et al., 2011).'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation5_direction: '' has been replaced by 'negative'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation5_mathematicalRelation: '' has been replaced by 'linear'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation5_rank: '' has been replaced by '2'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation5_scope: '' has been replaced by 'isotope'

version: 1.0.3
last version: 1.0.2
curator: nicholas
timestamp: 2025-04-09 20:48:13.391694 UTC
notes: Updated lipdverse database entry with a changed file.
changes:
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation1_seasonality: 'growing season? (not stated)' has been replaced by 'Growing Season'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation1_variable: 'P/E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation1_seasonality: 'growing season? (not stated)' has been replaced by 'Growing Season'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation1_variable: 'P/E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  chron data table: Column 'RWPg6tnfuWRN0TKRi', with variable name 'age', was added to the dataset
  chron data table: Column 'Rz6BsJ6IcsPAs3tbW', with variable name 'SD-1', was added to the dataset
  chron data table: Column 'chron10', with variable name 'materialDated', was added to the dataset
  chron data table: Column 'chron11', with variable name 'activity', was added to the dataset
  chron data table: Column 'chron12', with variable name 'activityUncertainty', was added to the dataset
  chron data table: Column 'chron13', with variable name 'supportedActivity', was added to the dataset
  chron data table: Column 'chron17', with variable name 'reservoirAge14C', was added to the dataset
  chron data table: Column 'chron18', with variable name 'reservoirAge14CUncertainty', was added to the dataset
  chron data table: Column 'chron19', with variable name 'useInAgeModel', was added to the dataset
  chron data table: Column 'chron4', with variable name 'fractionModern', was added to the dataset
  chron data table: Column 'chron5', with variable name 'fractionModernUncertainty', was added to the dataset
  chron data table: Column 'chron6', with variable name 'delta13C', was added to the dataset
  chron data table: Column 'chron7', with variable name 'delta13Cuncertainty', was added to the dataset
  chron data table: Column 'chron8', with variable name 'thickness', was added to the dataset
  chron data table: Column 'chron9', with variable name 'labID', was added to the dataset
  chron data table: Column 'LS13WASU-chron-NA1', with variable name 'age', was removed from the dataset
  chron data table: Column 'LS13WASU-chron-NA2', with variable name 'SD-1', was removed from the dataset

version: 1.0.2
last version: 1.0.1
curator: nicholas
timestamp: 2025-04-09 18:29:59.75706 UTC
notes: Changes made as part of LiPDverse vocabulary standardization process
changes:
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation1_seasonality: 'growing season? (not stated)' has been replaced by 'Growing Season'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation1_variable: 'P/E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation2_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01A): interpretation3_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation1_seasonality: 'growing season? (not stated)' has been replaced by 'Growing Season'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation1_variable: 'P/E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation2_variable: 'P_E' has been replaced by 'effectivePrecipitation'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_seasonality: 'unknown' has been replaced by 'deleteMe'
  paleo interpretation metadata: d2H (LS13WASU01B): interpretation3_variable: 'P_E' has been replaced by 'effectivePrecipitation'

version: 1.0.1
last version: 1.0.0
curator: nicholas
timestamp: 2025-04-08 17:32:58.8052 UTC
notes: Changes made as part of LiPDverse vocabulary standardization process
changes:
  paleo column metadata: d2H (LS13WASU01A): paleoData_longName: '' has been replaced by 'AD'
  paleo column metadata: d2H (LS13WASU01B): paleoData_longName: '' has been replaced by 'AD'
  paleo column metadata: depth (MAT0bb768872a): paleoData_longName: '' has been replaced by 'AD'
  paleo column metadata: year (MAT7cbe87ad3a): paleoData_units: 'AD' has been replaced by 'yr AD'
  paleo column metadata: year (MAT7cbe87ad3a): paleoData_longName: '' has been replaced by 'AD'

A 1700-year n-alkanes hydrogen isotope record of moisture changes in sediments from Lake Sugan in the Qaidam Basin, northeastern Tibetan Plateau
author: Wang, Z. , Liu, W. , Liu, Z. , Wang, H. , He, Y. , Zhang, F.
citation: Wang, Z., Liu, W., Liu, Z., Wang, H., He, Y. and Zhang, F.: A 1700-year n-alkanes hydrogen isotope record of moisture changes in sediments from Lake Sugan in the Qaidam Basin, northeastern Tibetan Plateau, The Holocene, 23(9), 1350–1354, doi:10.1177/0959683613486941, 2013.
doi: 10.1177/0959683613486941
issue: 9
journal: The Holocene
page: -4
pub data url: doi.org
publisher: SAGE Publications
type: journal-article
volume: 23
year: 2013

longitude: 93.95
latitude: 38.8667
elevation: 2800
geometry type: Point
site name: Lake Sugan