# Paleo-pCO2 Database Miocene pCO2 Reconstruction Data Derived from Leaf Gas-Exchange Models
#-----------------------------------------------------------------------
#               World Data Service for Paleoclimatology, Boulder
#                                   and
#                      NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# Template Version 4.0
# Encoding: UTF-8
# NOTE: Please cite original publication, NOAA Landing Page URL, dataset and publication DOIs (where available), and date accessed when using downloaded data.
# If there is no publication information, please cite investigator, study title, NOAA Landing Page URL, and date accessed.
#
# Description/Documentation lines begin with '#' followed by a space
# Data lines have no '#'
#
# NOAA_Landing_Page: https://www.ncdc.noaa.gov/access/paleo-search/study/36233
#   Landing_Page_Description: NOAA Landing Page of this file's parent study, which includes all study metadata.
#
# Study_Level_JSON_Metadata: https://www.ncei.noaa.gov/pub/data/metadata/published/paleo/json/noaa-recon-36233.json
#   Study_Level_JSON_Description: JSON metadata of this data file's parent study, which includes all study metadata.
#
# Data_Type: Climate Forcing
#
# Dataset_DOI:
#
# Science_Keywords: Atmospheric Gas Reconstruction
#---------------------------------------
# Resource_Links
#
# Data_Download_Resource: https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/liang2022-latahp-33-stomata_si.txt
#   Data_Download_Description: NOAA Template File; Stomata SI Data
#
#---------------------------------------
# Contribution_Date
#   Date: 2022-03-30
#---------------------------------------
# File_Last_Modified_Date
#   Date: 2022-04-01
#---------------------------------------
# Title
#   Study_Name: Paleo-pCO2 Database Miocene pCO2 Reconstruction Data Derived from Leaf Gas-Exchange Models
#---------------------------------------
# Investigators
#   Investigators: Liang, Jia-Qi; Leng, Qin; Höfig, Daianne.; Niu, Gao; Wang, Li; Royer, Dana; Burke, Kevin; Xiao, Liang; Zhang, Yi; Yang, Hong
#---------------------------------------
# Description_Notes_and_Keywords
#   Description: 
#---------------------------------------
# Publication
#   Authors: Liang, J., Leng, Q., Höfig, D. F., Niu, G., Wang, L., Royer, D. L., Burke, K., Xiao, L., Zhang, Y., and Yang, H.
#   Published_Date_or_Year: 2022
#   Published_Title: Constraining conifer physiological parameters in leaf gas-exchange models for ancient CO2 reconstruction
#   Journal_Name: Global and Planetary Change
#   Volume: 209
#   Edition: 
#   Issue: 103737
#   Pages: 
#   Report_Number: 
#   DOI:  10.1016/j.gloplacha.2022.103737
#   Online_Resource: 
#   Full_Citation: 
#   Abstract: Leaf gas-exchange models are increasingly used to reconstruct ancient atmospheric carbon dioxide (CO2) concentrations. One of these widely used models, the Franks model, requires stomatal size (guard cell width and either guard cell length or pore length), whole-leaf stomatal density, and bulk-leaf carbon isotope composition (d13C) from plant fossils. However, natural variations of these parameters within and across plant leaves have not been assessed closely, hindering the application of this model and the evaluation of its associated uncertainties. Here we investigate the range of variations of these parameters, and evaluate their impact on the output of the Franks model in three conifers (Metasequoia, Sequoia, and Taxodium). We introduce a modified cleared leaf method that allows accurate measurements of stomatal size. We show that among the stomatal size parameters, pore length is the most variable. Whole-leaf stomatal density can be accurately estimated in a representative area in the middle portion of a leaf. Variations of d13C values are only slightly above analytical errors within a leaf and between leaves from a branchlet, but a ~ 1‰ negative shift of d13C during early decay of Metasequoia leaf tissues was observed. Our measured ranges in pore length and whole-leaf stomatal density have the biggest influence on model estimated CO2. To improve model performance, we recommend (1) the use of our modified cleared leaf method to acquire accurate stomatal size and whole-leaf stomatal density measurements from the middle portion of a leaf located at the middle portion of a branchlet; (2) scaling pore length from guard cell length; and (3) a systematic correction of carbon isotope fractionation may be applicable if information regarding tissue decay and fossil preservation is available. We tested our recommendations by reconstructing CO2 from both extant and fossil materials. Franks model-derived CO2 based upon modern leaves collected in 2004 and 2020 (346 and 416 ppm) are close to their targets (378 and 414 ppm) whereas stomatal frequency methods substantially underestimate (285 and 341 ppm). Reconstructed CO2 from the middle Miocene Clarkia deposit (505 and 507 ppm for Metasequoia and Taxodium) are comparable with published results. We conclude that an improved cleared leaf method for accurate measurements of key stomatal parameters and a statistically-informed stomatal counting strategy will improve the performance of the Franks model for reconstructing CO2 using these conifers with wide distributions of fossil records in the Northern Hemisphere since the Cretaceous.
#---------------------------------------
# Funding_Agency
#   Funding_Agency_Name: 
#   Grant: 
#---------------------------------------
# Site_Information
#   Site_Name: Clarkia_Latah P-33
#   Location: Idaho
#   Northernmost_Latitude: 47
#   Southernmost_Latitude: 47
#   Easternmost_Longitude: -116.3
#   Westernmost_Longitude: -116.3
#   Elevation_m: 
#---------------------------------------
# Data_Collection
#   Collection_Name: Latah P-33 - stomata_si - Liang2022
#   First_Year: 15780000
#   Last_Year: 15780000
#   Time_Unit: calendar year before present
#   Core_Length_m: 
#   Parameter_Keywords: carbon dioxide
#   Notes: reconstruction uses the stomata-franks method
#---------------------------------------
# Chronology_Information 
# Chronology: 
#---------------------------------------
# Variables
# PaST_Thesaurus_Download_Resource: https://www.ncei.noaa.gov/access/paleo-search/skos/past-thesaurus.rdf
#   PaST_Thesaurus_Download_Description: Paleoenvironmental Standard Terms (PaST) Thesaurus terms, definitions, and relationships in SKOS format.
#
# Data variables follow that are preceded by "##" in columns one and two.
# Variables list, one per line, shortname-tab-var components: what, material, error, units, seasonality, data type, detail, method, C or N for Character or Numeric data)
#
#------------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing_Values: 
proxy	first_author_last_name	publication_year	doi	age_ka	Age_uncertainty_pos_ka	Age_uncertainty_neg_ka	CO2_ppm	CO2_uncertainty_pos_ppm	CO2_uncertainty_neg_ppm	person who entered data	email of individual entering the data	Reference of the data product	doi	Sample name	Family	Genus	Species	"Sample Repository"	"Geologic Formation"	Stratigraphic level	Age (Ma)	Age uncertainty, old (Ma)	Age uncertainty, young (Ma)	Age scale (GTS20XX)	How was age determined?	Modern Latitude (decimal degree, south negative)	Modern Longitude (decimal degree, west negative)	Paleo Latitude (decimal degree, south negative)	Paleo Longitude (decimal degree, west negative)	Number of stomatal counts per leaf	Number of leaves comprising CO2 estimate	"Counting Method (Image, microscope)"	"Counting box dimensions (µm × µm)"	# Stomata	# Epidermal Cells	"Sample mean stomatal density (SD, mm-2)"	"Sample mean stomatal index (SI, %)"	SD error (+/- 1 s.e.m.)	SI error (+/- 1 s.e.m.)	Modern Calibration species	"Modern Calibration Regression Equation "	"Calibration Error "	Reported mean CO2	CO2 type	"Reported CO2 Uncertainty (Low)"	"Reported CO2 Uncertainty (High)"	What is the uncertainty range?	What is the distribution of the uncertainties?	general notes
stomata-SI	Liang	2022	10.1016/j.gloplacha.2022.103737	15780	39	39	326	NA	NA	Dana Royer	droyer@wesleyan.edu	Liang, J., Leng, Q., Höfig, D. F., Niu, G., Wang, L., Royer, D. L., Burke, K., Xiao, L., Zhang, Y., and Yang, H., 2022, Constraining conifer physiological parameters in leaf gas-exchange models for ancient CO2 reconstruction: Global and Planetary Change, v. 209, 103737, doi: 10.1016/j.gloplacha.2022.103737.	10.1016/j.gloplacha.2022.103737	NA	Cupressaceae	Metasequoia	sp.	Bryant University	Latah	P-33 site	15.78	15.82	15.74	NA	zircon U-Pb, reported in Hofig et al., 2021, Geology, https://doi.org/10.1130/G48901.1	47.0	-116.3	NA	NA	1	6	microscope	0.04 - 0.16 mm^2	NA	NA	NA	15.77	NA	2.81	Metasequoia glyptostroboides	Beerling et al. (2009)	uncertainties following the resampling procedure in Beerling et al. (2009)	326	median	NA	NA	All of the stomatal indices are higher than what is captured in the present-day calibration; as a result, the percentiles computed with the Monte Carlo simulations are not robust	NA	NA