LS14FOTI - v1.0.6

Dataset Id: 3Z8BYQsh9EoNBsadmuUP

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L <- lipdR::readLipd("https://lipdverse.org/data/3Z8BYQsh9EoNBsadmuUP/1_0_6/LS14FOTI.lpd")

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iso2k-1_1_2

root

archiveType: LakeSediment

lipdVersion: 1.3

pub
pub1

author: list(name = "Fornace, Kyrstin L. , Hughen, Konrad A. , Shanahan, Timothy M. , Fritz, Sherilyn C. , Baker, Paul A. , Sylva, Sean P.")

journal: Earth and Planetary Science Letters

volume: 408

pages: -8

title: A 60,000-year record of hydrologic variability in the Central Andes from the hydrogen isotopic composition of leaf waxes in Lake Titicaca sediments

doi: 10.1016/j.epsl.2014.10.024

geo

latitude: -16.14

longitude: -69.15

elevation: 3810

siteName: Lake Titicaca

PaleoData columns
year (yr AD)

TSid: MAT24a1c7baff

variableName: year

units: yr AD

description: Year AD

interpretation
1

rank: NA

scope: climate

2

rank: NA

scope: climate

3

rank: NA

scope: climate

4

rank: NA

scope: climate

5

rank: NA

scope: climate

depth (cm)

TSid: MATa2cbe1b687

variableName: depth

units: cm

description: depth

interpretation
1

rank: NA

scope: climate

2

rank: NA

scope: climate

3

rank: NA

scope: climate

4

rank: NA

scope: climate

5

rank: NA

scope: climate

d2H (permil)

TSid: LS14FOTI01B

variableName: d2H

units: permil

description: terrestrial biomarker

interpretation
1

basis: SASM precipitation that falls on the Altiplano is ultimately derived from Atlantic Ocean moisture that has been transported across the Amazon Basin and lifted over the eastern cordillera of the Andes. Altiplano ?Dp thus integrates upstream effects including rainout and moisture recycling over the Amazon Basin, altitude effects associated with upslope moisture transport, and local effects such as the intensity of precipitation (?amount effect?) (Dansgaard, 1964). ... "Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003). Accordingly, the intensity of the SASM is significantly negatively correlated with ?18O (and correspondingly ?D) of modern precipitation in the Cen- tral Andes, as well as throughout much of southern tropical South America (Vuille and Werner, 2005).

direction: decrease

interpDirection: decrease

scope: climate

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: circulationVariable

variableGroup: South American Summer Monsoon precipitation intensity

2

scope: climate

3

scope: climate

4

basis: Results from both observational and modeling studies suggest that the dominant control on modern interannual Andean ?Dp variability is Rayleigh-type fractionation during rainout along the trajectory of moist air masses across the Amazon Basin up to the Andes (e.g., Rozanski et al., 1993; Hoffmann et al., 2003; Vimeux et al., 2005; Vuille and Werner, 2005). Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003).

coefficient: NA

direction: positive

fraction: NA

inferredMaterial: soil water

rank: 1

scope: isotope

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: precipitationIsotope

variableGroup: P_isotope

variableGroupDirection: positive

5

basis: Results from both observational and modeling studies suggest that the dominant control on modern interannual Andean ?Dp variability is Rayleigh-type fractionation during rainout along the trajectory of moist air masses across the Amazon Basin up to the Andes (e.g., Rozanski et al., 1993; Hoffmann et al., 2003; Vimeux et al., 2005; Vuille and Werner, 2005). Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003).

coefficient: NA

direction: negative

fraction: NA

rank: 2

scope: isotope

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: deleteMe

variableGroup: continental effect

6

basis: While the isotopic composition of precipitation appears to be the primary control on the structure of the LT ?Dwax record, it is clear that secondary effects also contribute to this signal. Most notably, the much larger range at LT (102h) than at Illimani (58h) over the past 19 kyr suggests the influence of compounding effects on LT ?Dwax, such as decreased regional precipitation, resulting in a more enriched ?Dp, and low local humidity, which would tend to further enrich plant source water by soil water evaporation and/or leaf transpiration. Since such local evapotranspiration feedbacks would be expected to act in step with ?Dp changes, this would serve to amplify the ?Dwax signal and increase its sensitivity to ?Dp variability.

coefficient: NA

direction: positive

fraction: NA

rank: 3

scope: isotope

variable: evaporation

variableGroup: EffectiveMoisture

variableGroupDirection: negative

variableGroupOriginal: soil water evapotranspiration

d2H (permil)

TSid: LS14FOTI01A

variableName: d2H

units: permil

description: terrestrial biomarker

interpretation
1

basis: SASM precipitation that falls on the Altiplano is ultimately derived from Atlantic Ocean moisture that has been transported across the Amazon Basin and lifted over the eastern cordillera of the Andes. Altiplano ?Dp thus integrates upstream effects including rainout and moisture recycling over the Amazon Basin, altitude effects associated with upslope moisture transport, and local effects such as the intensity of precipitation (?amount effect?) (Dansgaard, 1964). ... "Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003). Accordingly, the intensity of the SASM is significantly negatively correlated with ?18O (and correspondingly ?D) of modern precipitation in the Cen- tral Andes, as well as throughout much of southern tropical South America (Vuille and Werner, 2005).

interpDirection: decrease

scope: climate

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: circulationVariable

variableGroup: South American Summer Monsoon precipitation intensity

2

scope: climate

3

scope: climate

4

basis: Results from both observational and modeling studies suggest that the dominant control on modern interannual Andean ?Dp variability is Rayleigh-type fractionation during rainout along the trajectory of moist air masses across the Amazon Basin up to the Andes (e.g., Rozanski et al., 1993; Hoffmann et al., 2003; Vimeux et al., 2005; Vuille and Werner, 2005). Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003).

coefficient: NA

direction: positive

fraction: NA

inferredMaterial: soil water

rank: 1

scope: isotope

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: precipitationIsotope

variableGroup: P_isotope

variableGroupDirection: positive

5

basis: Results from both observational and modeling studies suggest that the dominant control on modern interannual Andean ?Dp variability is Rayleigh-type fractionation during rainout along the trajectory of moist air masses across the Amazon Basin up to the Andes (e.g., Rozanski et al., 1993; Hoffmann et al., 2003; Vimeux et al., 2005; Vuille and Werner, 2005). Increased rainout along this trajectory, as well as increased local precipitation in the Andes, results in more depleted ?Dp, consistent with the continentality and amount effects that dominate ?Dp variability throughout most of tropical South America (Vuille et al., 2003).

coefficient: NA

direction: negative

fraction: NA

inferredMaterial: soil water

rank: 2

scope: isotope

seasonality: Dec-Feb

seasonalityOriginal: SH summer

variable: deleteMe

variableGroup: continental effect

6

basis: While the isotopic composition of precipitation appears to be the primary control on the structure of the LT ?Dwax record, it is clear that secondary effects also contribute to this signal. Most notably, the much larger range at LT (102h) than at Illimani (58h) over the past 19 kyr suggests the influence of compounding effects on LT ?Dwax, such as decreased regional precipitation, resulting in a more enriched ?Dp, and low local humidity, which would tend to further enrich plant source water by soil water evaporation and/or leaf transpiration. Since such local evapotranspiration feedbacks would be expected to act in step with ?Dp changes, this would serve to amplify the ?Dwax signal and increase its sensitivity to ?Dp variability.

coefficient: NA

direction: positive

fraction: NA

inferredMaterial: soil water

rank: 3

scope: isotope

variable: evaporation

variableGroup: EffectiveMoisture

variableGroupDirection: negative

variableGroupOriginal: soil water evapotranspiration

ChronData columns
depth (cm)

TSid: chron1

variableName: depth

units: cm

description: mid-point depth

age14C (yr14C BP)

TSid: chron2

variableName: age14C

units: yr14C BP

description: 14C years before 1950

SD (yr14C BP)

TSid: chron3

variableName: SD

units: yr14C BP

description: 14C years uncertainty

fractionModern ()

TSid: chron4

variableName: fractionModern

description: fraction of modern 14C activity

fractionModernUncertainty ()

TSid: chron5

variableName: fractionModernUncertainty

description: fraction of modern 14C activity uncertainty

delta13C (permil)

TSid: chron6

variableName: delta13C

units: permil

description: delta13C of material analyzed for 14C

delta13Cuncertainty (permil)

TSid: chron7

variableName: delta13Cuncertainty

units: permil

description: delta13C uncertainty

thickness (cm)

TSid: chron8

variableName: thickness

units: cm

description: thickness of sample (along depth axis)

labID ()

TSid: chron9

variableName: labID

description: laboratory ID from radiocarbon facility

materialDated ()

TSid: chron10

variableName: materialDated

description: material analyzed

activity (Bq g-1)

TSid: chron11

variableName: activity

units: Bq g-1

description: 210Pb, 239+240Pu or 137Cs activity

activityUncertainty (Bq g-1)

TSid: chron12

variableName: activityUncertainty

units: Bq g-1

description: 210Pb, 239+240Pu or 137Cs activity uncertainty

supportedActivity ()

TSid: chron13

variableName: supportedActivity

description: Y if supported 210Pb activity, N if unsupported 210Pb activity

x210PbModel ()

TSid: chron14

variableName: x210PbModel

description: model used to convert 210Pb activity to age (e.g., constant rate of supply)

age (yr BP)

TSid: chron15

variableName: age

units: yr BP

description: years before 1950 (calibrated age, or ages that dont need calibration)

SD (yr BP)

TSid: chron16

variableName: SD

units: yr BP

description: uncertainty in age

reservoirAge14C (yr14C BP)

TSid: chron17

variableName: reservoirAge14C

units: yr14C BP

description: 14C reservoir age

reservoirAge14CUncertainty (yr14C BP)

TSid: chron18

variableName: reservoirAge14CUncertainty

units: yr14C BP

description: 14C reservoir age uncertainty

useInAgeModel ()

TSid: chron19

variableName: useInAgeModel

description: was this date used in the age model?