EastWoods-MonitoringPlots

Code for various aspects of management for ecological monitoring in the East Woods

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Overview:

This is designed to be the first step a multi-purpose monitoring plan. In 2017, we will start small with intensive surveys in 4 plots. Measurements in these plots will include (but not limited to) micrometeorology, vegetation inventories, phenology, and tree growth analysis via dendrometer bands. Intended uses of this data include: Comparative phenological analysis among plant functional types (forbs, shrubs, trees) over multiple years and the effects of phenology on micrometerology Comparative phenological analysis between accessioned, open-grown oaks of the Living Collections and native oaks in their natural habitats. Pilot data collection & analysis for 2018 re-inventory of the East Woods and development of monitoring protocol to aid in data-backed adaptive management of the East Woods. 2017 data collection will focus on the effects of fire on vegetation communities and oak regeneration.

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Development:

We welcome contributions from any individual, whether code, documentation, or issue tracking.
All participants are expected to follow the code of conduct for this project.

• Lead: Christy Rollinson, Forest Ecologist, Morton Arboretum, [email protected]

• Collected and/or lab analysis by:

  • Drew Duckett
  • Bethany Zumwalde
  • Note: To add in non-RA personnel

• Contact for data: Christy Rollinson, Forest Ecologist, Morton Arboretum, [email protected]

• Date of data collection 2017- present

• Information about geographic location of data collection The Morton Arboretum East Woods, Lisle, IL

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Plot & Sampling Design:

Plot Selection

• 1 plot in each of 4 stands with no records of harvest in general GIS files:

• 2 stands in black have no records of fire or harvest (although there has likely been both)

Plot Layout

Nested, hierarchical design Big Plot (20 x 20 m): Trees >=10 cm DBH

• Micrometeorology station
  • PAR
  • Air Temperature
  • Air Humidity
  • Soil moisture
  • Soil temperature
• Trees >= 10 cm DBH
  • Tag; record species
  • DBH
  • Location in plot grid
  • Dendroband
  • Core
  • phenology(?)
• Litter traps (x 4) -- to be installed late summer/fall 2017

Sub Plot (5 x 5 m, x3?)

• Saplings <10 cm DBH; > 1.3 m tall
  • DBH, species
  • Map location
  • Height
  • Dendrometer band?
  • Phenology (?)
• Shrubs
  • Tag individuals, species
  • % cover
  • Phenology(?)

Sub-Sub Plot (1 m x 1 m, x3?)

• Forbs/Grasses
  • % cover by species
• Seedlings
  • Count -- new, >1yr old

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Available Data

The following variables are available in our data (code, description, units):

Meteorology Data

Variable	Description	Units
Time	Time at which met station is recorded data point (GMT-05:00)	Date: MM/DD/YYYY H:M:S AM/PM
Plot	the plot where the met station is recording data (e.g. N115, HH115)	°F
Soil_temp	soil temperature	°F
Air_temp	air temperature	character string
Water_content	soil moisture	m3/ m3
Relative_humidity	relative humidity of air	%
PAR	Photosynthetically Active Radiation	uE

Dendrometer Bands

Variable	Description	Units
site	observation site; This should correspond to the name of a Living Collection (e.g. Oak Collection) or designated site as part of the Morton Arboretum group (e.g. King's Woods)	character string
plot	the plot where the dendrometer bands were measured (e.g. N115, HH115)	character string
date_observed	date of observation in field	Date: YYYY-MM-DD
genus	individual genus (e.g. Quercus)	character string
species	individual specific epithet (species; e.g. rubra)	character string
id	identification in local & NPN; if accessioned, use accession ID	character string
observer	last name of observer; if necessary add first/middle initial	character string
date_entered	date data entered into local database	Date: YYYY-MM-DD
data_entry	name of person entering data into local database	character string
dist_from_collar	distance from the edge of the dendroband collar to the initial mark measured by calipers	mm

Leaf Litter

Variable	Description	Units
sorter	last name of person sorting samples; if necessary add first/middle initial	character string
date_collection	date of sample collection in field	Date: YYYY-MM-DD
plot	the plot where the leaf litter was collected (e.g. HH115, B127)	character string
trap_ID	the trap where the leaf litter was collected (e.g. N, W)	character string
genus	individual genus (e.g. Quercus)	character string
species	individual specific epithet (species; e.g. rubra)	character string
oak_group	If unable identify to species rank, denotes if belonging to white or red oak groups	character string
tissue	type of tissue being weighed (e.g. leaf, twig, flower, fruit, etc.)	character string
num_fruit	number of fruit	numeric
num_immature_fruit	num_fruit that is immature	numeric
num_mature_fruit	num_fruit that is mature	numeric
weigher	last name of person weighing samples	character string
date_weighed	date data entered into local database	Date: YYYY-MM-DD
mass	mass of sample weighed	grams (g)
data_entry	last name of person entering data from printed data sheet; if necessary add first/middle initial	character string
notes	any additional notes	character string

Tree Survey

Note: To add in

Plot Survey

Note: To add in

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Workflow (how you should use this repository):

All scripts to be executed are in the "scripts/" directory. Scripts are generally R-based and should generate the dependent file structures as you go If you clone/fork/branch this code for a different system, you will want to adjust these scripts for your particular system. Many of the numbered R scripts will call generalized functions (scripts without numbers). If you're looking for the nuts & bolts of how each step is done, these are the scripts to look at.

Description of Workflow Scripts/Steps

Meteorology

1. MetData_ConsolidatingRawData.R This script takes the raw met data exported from micro-meteorology stations located in four plots in the East Woods of The Morton Arboretum. This script takes the raw exported HoboWare data from each of the four plots and compiles them into one datasheet.
2. Met_QAQC.R This script takes the output file from the MetData_ConsolidatingRawData.R script and uses it to run QAQC analyses.

Dendrometer

1. dendroband_plotting_EW.R This script uses data from dendrometer bands on trees within plots established in the East Woods of The Morton Arboretum. It calculates basal area then converts for growth (mm/day). This script also plots the total movement of the band away from the collar.
2. maps_dendrometer_bands_eastwoods.R This script creates a map of trees with dendrometer bands on them within plots in the East Woods at The Morton Arboretum.
3. maps_dendrometer_bands.R This script creates a map of trees with dendrometer bands on them in the Oak Collection at The Morton Arboretum.
4. dendroband_plotting.R This script was the original plotting script that is not currently in use.

Leaf Litter

1. LeafLitter.R This script extracts data from Google Sheets document and runs initial QAQC on data.