Data from: The effect of shrub cover on conifer water-use patterns, growth, and response to climate change in the southern Sierra Nevada
Data files
Jan 30, 2024 version files 135.22 KB
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averages.csv
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carbon.csv
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Cookies_averaged_rwl.txt
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Cores_Tucson_12.7.TXT
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Raw_Soil_Data.csv
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README.md
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README.txt
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rwi_by_year.csv
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Shrub-Tree_Water_Use.Rmd
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soil.source.csv
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soil.source.open.csv
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soil.source.shrub.csv
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Supplemental_Prism_Data.csv
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SWE.csv
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Xylem_Water_Data.csv
Abstract
As wildfire increases in size and severity, large areas of forest are undergoing substantial increases in shrub cover. In forests where water is the limiting resource, the paritioning of soil water between shrubs and trees may determine how shrubs affect tree growth and water-stress. We analyzed hydrogen and oxygen isotopes in the xylem water for two conifer species and two shrub species to assess how shrub cover affects the water-uptake patterns of conifers in the southern Sierra Nevada. Further, we analyzed tree growth and stable carbon isotopes in tree rings to assess how shrub cover affects tree growth, intrinsic water-use efficiency and response to climate change.
README
Data and Code for "The effect of shrub cover on conifer water-use patterns, growth, and response to climate change in the southern Sierra Nevada"
Created by Marissa J. Goodwin
Code:
Shrub-Tree Water Use.Rmd = Code for data analysis
Dataframes:
Raw Soil Data.csv - This dataframe contains soil water hydrogen and oxygen data for each growing environment and tree species combination at three soil depths (0-10 cm, 10-20 cm, 20-30 cm). Columns are as follows: "Identifier.1" = unique identifier for each soil sample (some soil samples were analyzed twice), "d18OVsmow" = oxygen isotope ratio, "d2HVsmow" = hydrogen isotope ratio, "Species.Shrub" = Tree Species and growing environment combination (AO = white fir-Open, AS= white fir-Shrub, PO = Jeffrey pine-Open, PS = Jeffrey pine-Shrub), "Site" = Growing Environment (Open = Shrub Absent and Shrub = Shrub Dominant)
Xylem Water Data.csv - This dataframe contains xylem water hydrgoen and oxygen data for all trees and shrubs in each growing environment and at each time period. Columns are as follows: "Sample.ID" = unique identifier for each sample, "d18O"= oxygen isotope ratio, "dD" = hydrogen isotope ratio, "Species" = tree or shrub species (ABCO = white fir, PIJE = Jeffrey pine, ARPA = greenleaf manzanita, CECO = mountain whitethorn), "Site" = growing environment (Open = Shrub Absent and Shrub = Shrub Dominant), "Period" = when the sample was taken (Early Summer = Early June, Late Summer = Late August), and "Type" = plant type (Tree vs Shrub)
averages.csv - This dataframe contains average soil water hydrogen and oxygen isotope values and their standard deviation for each group (Tree Species, Shrub Species, and Soil Depth) by growing environment (Shrub Absent vs. Shrub Dominant) and time period (Early Summer vs Late Summer). Columns are as follows: "Species" = Tree or Shrub Species (also includes soil since this dataframe is used for plotting xylem water values with soil water values), "Type" = sample type (Tree, Shrub or Soil water), " Site" = growing environment, "Group" = same as Species column but with scientific names and soil depths included for plotting, "Name" = group and Time period combined (Soil does not have a time period associated with is since it was only measured in early summer), "Period" = when the sample was taken (Early Summer = Early June, Late Summer = Late August), "o.mean" = average oxygen isotope ratio by group "o.sd" = standard deviation for the oxygen isotope ratio by group, "h.mean" = average hydrogen isotope ratio by group, "h.sd" = standard deviation for the hydrogen isotope ratio by group.
soil.source.csv - This dataframe contains average hydrogen and oxygen isotope values and their standard deviation for each soil depth by growing environment. This dataframe is used for plotting the xylem water values against average soil water values in simmr. Columns are as follow: "Means" = Growing environment and soil depth, "meand18O" = average oxygen isotope ratio, "sdd18O" standard deviation for the oxygen isotope ratio, "meand2H" = average hydrogen isotope ratio, "sdd2H" = standard deviation for the hydrogen isotope ratio.
soil.source.shrub.csv - This dataframe is the same as "soil.source" but only contains soil water averages for the shrub growing environment. Used for calculating source water contributions using the simmer mixing model for trees and shrubs in the shrub dominant growing environment.
soil.source.open.csv - This dataframe is the same as "soil.source" but only contains soil water averages for the open growing environment. Used for calculating source water contributions using the simmer mixing model for trees in the shrub absent growing environment.
Cores_Tucson_12.7.txt = text file with raw ring width data (unit=mm) for each tree and year. RWL file is generated using WinDendro. Only 11 of the 40 trees were cored (data for the other 29 trees can be found in "Cookies_averaged_rwl.txt"). Unique identifiers (ex. AS8) include the tree species (A=white fir, P=Jeffrey pine), growing environment (S=shrub, O=Open) and tree number.
Cookies_averaged_rwl.txt = text file with raw ring width data (unit=mm) for each tree and year. RWL file is generated using WinDendro. This dataframe contains data for the 29 out of 40 trees where we collected cross sections. Unique identifiers (ex. AS8) include the tree species (A=white fir, P=Jeffrey pine), growing environment (S=shrub, O=Open) and tree number.
rwi by year.csv - This dataframe contains raw ring width data (unit=mm) for each tree and year growth (ex. row 1 is the trees first year of growth). Unique identifiers (ex. AS8) include the tree species (A=white fir, P=Jeffrey pine), growing environment (S=shrub, O=Open) and tree number.
carbon.csv - This dataframe contains carbon isotope data for each tree and year from 2016 to 2021. Columns are as follows: "Sample ID" = unique identifier for each sample. The unique identifier contains tree species (A=white fir, P=Jeffrey pine), growing environment (S = Shrub, O = Open), tree number, and wood type (Earlywood = E, and Latewood = L). Most trees/years had both earlywood and latewood sampled, but 27 trees had earlywood and latewood sampled together. These are denoted as ".B" for both types of wood.
Column "d13C" = carbon isotope ratio.
SWE.csv - This dataframe contains snow water equivalent data for April 1st from 2015 to 2021 for three different sites in the southern Sierra Nevada located near the Teakettle Experimental Forest. Data was obtained from the USDA NRCS National Water and Climate Center database. Columns are as follows: "Date" = Date of Snow Water Equivalent measurement, "Year" = year of snow water equivalent measurement, "TW SWE (mm)" = Tamarack Summit SWE in millimeters, "UBC SWE (mm)" = Upper Burnt Corral SWE in millimeters, "WWM SWE (mm)" = West Woodchuck meadow SWE in millimeters, "Mean.SWE" = average SWE of all three sites, "SD.SWE" = SWE standard deviation for all three sites.
Supplmental PRISM Data.csv - This dataframe contains monthly precipitation data (mm) for the Teakettle Experimental Forest from 2000 to 2021.
Note - blank cells indicate no data was available for that site and time point. There are four sites/time points that do not have data: TS (4/1/2015), WWM (4/1/2015), TS (4/1/2020), WWM (4/1/2021). Averages were calculated without these points.
Supplemental Prism Data.csv - This dataframe contains monthly precipitation data (mm) for the Teakettle Experimental Forest from 2000 to 2021. Columns are as follows: "Date" = year and month, "ppt(mm)" = precipitation totals in millimeters, "Water Year" = water year precipitation fell during (water year is includes October to September). Blank cells mean no data is available for this site.
Methods
Xylem samples were collected from two conifer species (Abies concolor and Pinus jeffreyi) and two shrub species (Arctostaphylos patula and Ceanothus cordulatus) in the southern Sierra Nevada. Soil samples were collected near a subset of the sampled trees. Xylem water and soil water were extracted using a cryogenic vacuum distillation and analyzed for hydrogen and oxygen stable isotopes.
Trees of both conifer species were cored or cross-sectioned after xylem samples were collected. Tree-ring analysis was used to calculate age and growth for each tree and carbon isotope analysis was performed on wood samples obtained from each tree core/cross section.