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NCEAS Plant Functional Trait Workshop, March 2008
Grassland Precipitation Project – Methods
Last Updated by: Michal Shuldman 29 MAR 2008
Leah Goldstein ([email protected])
Nathan Kraft ([email protected])
Jordan Okie ([email protected])
Brody Sandel ([email protected])
Michal Shuldman ([email protected]
1. Fertsyn sites (go to person: Nathan Kraft)
DATA
The trait data for these sites was used directly from the file:
Fertsyntraitsall_Jan27_2008.xls
The metadata for these data is in:
Cleland_etal_metadata_datapaper_revise_Jan2008.doc
These files were given to us by Elsa Cleland
CALCULATIONS
1. We determined a species mean relative abundance by averaging the relative
abundance of each species in plots with the same treatments
- We determined a response ratio by dividing the species mean relative abundance
in the watered plots by the control plots (water/control)
2. Sevilleta (go to person: Michal Shuldman)
DATA
The trait data for this site was compiled from other files, the USDA Plants website, and
personal communication with Scott Collins.
The intial data file were:
SEV_drought_AllYears_Subset_28MAR.csv
SEVspeciesdatabase.xls
sevtraitskarentomerge71106.xls
These files were given to us by Elsa Cleland
All of these files are posted on the DGS website (http://traitsdgs.nceas.ucsb.edu/workspace/synthesis-meeting-march-27-31/precipitation-subgroupdata). Here is the procedure we followed in order to add the Sevilleta data into the
Fertsyn trait data file:
1. We combined all of the years of data into one file called: SEV_drought_AllYears.csv
2. We removed all of the dead, rocks, soil, litter, Larrea bases, buckets and -888 (no
plant measurements). Most of this information was in the comments section, but we
deleted the comments column for future files. For Larrea seedlings, some of the info
was coded as LSEED (which we found out from reading the metadata) and we
changed that code to the regular USDA code for Larrea. The file is called:
SEV_drought_AllYears_Subset_28MAR.csv
3. Using an R script (by Brody) added together the seeding in adult records to get
combined cover. In addition, for any species where there was both a fall and spring
record in the same year we used the maximum cover (as per Elsa’s suggestion). This
means that some of the values are from spring and some are from fall. The files are:
Sevilleta data clean.csv (output) and the R script is Sevilleta duplicate row deleter.R
4. Then we deleted all of the Creosote ecosystem-type lots and fixed up some small
errors (e.g. one bucket was missed). With the cleaned up data we found all the species
in the water experiment at Sevilleta that were not in the FertSyn plots.
5. For the new species we made a file with the same traits as the FertSyn data base. We
used a combination of previous trait data from Elsa Cleland, the USDA plants
website, and personal communication with Scott Collins to fill in the traits. Lower
case letters in the file were the ones I added with Scott unless otherwise noted. Here
is the file with the traits of all the Sevilleta species: Sevmergedtraits.xls
6. Then we used the vlookop command in MSExcel to populate the trait data into the
edited cleaned up sevilleta file. The new file is called:
SEV_drought_AllYears_Traits_Merge_29MAR.csv
7. Then, Nathan copied and pasted the Sevilleta trait data into the Fertsyn trait data. The
file is called: FerSyn_Sevilleta_Merged_Traits.csv
8. Finally, we calculated the species mean relative abundance and response ratios in R.
CALCULATIONS
1. We determined a species mean relative abundance by averaging the relative
abundance of each species in plots with the same treatments
- We determined a response ratio by dividing the species mean relative abundance
in the watered plots by the control plots (water/control)
3. Precipitation Data (go to person Jordan and Leah)
Sevilleta data taken from field stations website:
http://sev.lternet.edu/data/search/climdb/searchmonthly.php
For SGS site, from field station website:
http://sgs.cnr.colostate.edu/Data/Category/Climate_WaterDynamics/ClmtWtrDyn.htm
1939-2007 Monthly Precipitation Data from ARS Headquarters, CPER
4. USDA Trait Data (go to person Brody)
5. USDA county occurrence and precipitation (go to person Jason Kreitler,
[email protected]))
6. USDA species by county occurrence (go to person David Ackerly,
[email protected])
7. Vegbank (go to person Leah)
We took one dominant species per site (in top 10 for abundance and
representative of site), and selected all plots in vegbank that contained those species. We
saved a file with species abundance data, and a file with plot environmental data in the
natural gradient folder. We looked up Bromus hordeaceuous for Jasper Ridge (Bromus
mollis was not included in the search as of 3/29). Kobresia myosuroides was chosen for
Niwot, but we decided not to include Niwot unless we also had snowfence data from
Toolick Lake. Andropogon gerardii was selected for Konza, Bouteloua eriopoda for
Sevilleta, although more common species were forbs, and for SGS Buchloe dactyloides,
and Bouteloua eriopoda. We also searched for Bouteloua gracilis for Sevellieta, but it
was not present in Vegbank Plots. For Toolick, potential species were Eriophorum
vaginitum, or Vaccinium vitis–ida. There is a file for species composition, and a file for
plot information, including latitude and longitude. Project descriptions for plots were
copied to the file “project descriptions from veg bank plots”, and verified that all were
surveys.
8. Niwot data:
We calculated relative abundance by deleting rock, bare, lichen, and dead, then
calculating for each species : species abundance/total plot abundance.
9. R codes
10. Other?
Traits coding from USDA traits:
See file:
Trait descriptions from USDA plants found at: http://plants.usda.gov/charinfo.html
Summary
Life form (5) life form (e.g Lichen, Fern, etc) We probably dont need to use this column
Annual/Biennial/Perennial(usda_plants[,6]): We used the longest possible life span
Shrub/forb/graminoid: shrub contains all woody species
Active.Growth.Period length: number of season in which the plant is growing
C:N ratio: High=3, Medium=2, Low=1
Summer porosity: leaf air space, Dense=1, Moderate=2, Porous=3
Growth.form: R= Rhizomatous, C=Caespitose, O=Non-clonal: Bunch was caespitose,
Rhizomatous and stoloniferous was R
Growth.rate: Rapid=3, Moderate =2, Slow=1
Height..Mature..feet. ; continuous
Leaf.retention; Evergreen/ Deciduous: Yes (i.e Evergreen only for woody plants) = 1
No (i.e. Decisduous or non-woody plant) = 0
Life span: Long = 3, Moderate = 2, Short = 1
Nitorgen fixation, yes indicates that it fixes nitrogen. We only did this for herbaceous
plants. Woody plants are left blank (no data) b/c there is too much variability. All
fabaceae were given a yes.
Drought tolerance: None =0, Low = 1, Medium =2, High = 3
Moisture use: how much water the species requiresLow=1, Medium=2, High=3
Precipitation min (continuous)
Precip max (continuous)
Shade tolerance: Tolerant = 3, Intermediate = 2, Intolerant = 1
Bloom period: Spring, Summer, Fall, Winter, Indeterminate ; information on early, mid,
or late time within was not included
str(usda_plants[,64])
Active growing period, first season (thex. Spring and summer = spring
#Spring and Summer = spring
#Year Round = year round
#Spring, Summer, Fall = spring
#Spring = spring
#Fall, Winter and Spring = fall
#Spring and Fall = spring
#Summer = summer
#Fall = fall
#blank = blank
#Summer and Fall = Summer
unique(usda_plants[,83]) # vegetative spread rate, this information may already be
covered under growth form/rhizomatous column
str(usda_plants[,83])
#None = 1
#Slow =2
#Moderate =3
#Rapid=4
#Blank=blank
unique(usda_plants[,98]) # native status, indicated for lower 48 states, alaska, hawaii,
puerto rico, virgin islands, Canada, Greenland, St. Pierre and Miquelon, and North
America if non vascular
#If the species is native for any of these areas we should count it as native. If it's not
native at any sites and we have infor on it call it non-native. If no info leave blank
str(usda_plants[,98])
#(N) = NATIVE
# (N?) = NATIVE
# (NI) = NATIVE
# (NI?) = NATIVE
# (GP) = NON-NATIVE
# (GP?) = NON-NATIVE
# (I) = NON-NATIVE
# (I?) = NON-NATIVE
# (N?I?) = NATIVE
# (W) = NON-NATIVE
# (W?) = NON-NATIVE