David LeBauer dlebauer

pft	variable	phylogeny	distn	parama	paramb	n	citation
forb_priors	mort2	plants	gamma	1.47	0.0578	0	LeBauer 2010 Expert Prior
forb_priors	growth_resp_factor	grass	beta	2.63	6.52	0	LeBauer 2010 Expert Prior
forb_priors	fineroot2leaf	grass	lnorm	0.811	0.843	0	Chapin 2002 Principles of Terrestrial Ecosystem Ecology
forb_priors	root_turnover_rate	grass	weibull	1.67	0.657	66	Gill 2000 Global patterns of root turnover for terrestrial ecosystems
forb_priors	seedling_mortality	monocots	beta	3.61	0.433	0	LeBauer 2010 Expert Prior
forb_priors	Vcmax		lnorm	4.51	0.64	19	Wullschleger 1993 Biochemical Limitations to Carbon Assimilation in C3 Plants: A Retrospective Analysis of the A/Ci Curves from 109 Species
forb_priors	root_respiration_rate	angiosperm	gamma	4.95	0.762	36	George 2003 Fine-root respiration in a loblolly pine and sweetgum forest growing in elevated CO2
forb_priors	r_fract	plants	beta	2	4	0	LeBauer 2010 Expert Prior
forb_priors	c2n_leaf	grass	gamma	4.18	0.13	95	Wright 2004 The world-wide leaf economics spectr

Environment comparisons

This folder contains code used to compare setaria growth in different environments.

	{
	"dimensions": {
	"wavelength": 939
	},
	"variables": {
	"wavelength": {
	"shape": ["wavelength"],
	"type": "double",
	"attributes": {
	"long_name": "Hyperspectral Wavelength",

	sum_out <- broom.mixed::tidyMCMC(coda_out, conf.int = TRUE, conf.level = 0.95) %>%
	rename(mean = estimate, sd = std.error, pc2.5 = conf.low, pc97.5 = conf.high) %>%
	mutate(sig = if_else(pc2.5 * pc97.5 > 0, TRUE, FALSE)) # test if UCL and LCL both have the same sign

	years <- data.frame(year_index = 1:length(unique(x$year)), year = unique(x$year))
	states <- data.frame(state_index = 1:length(unique(x$state)), state = unique(x$state))

	sum_rep <- broom.mixed::tidyMCMC(coda_rep, conf.int = TRUE, conf.level = 0.95) %>%
	rename(mean = estimate, sd = std.error, pc2.5 = conf.low, pc97.5 = conf.high) %>%
	separate(term, sep = '\\[\|\\]\|,', into = c('term', 'i', 'j', 'other'), convert = TRUE) %>%

	#CSV downloaded from https://quickstats.nass.usda.gov/results/12827E57-2B20-368C-A91F-1B97FF8F7B35#E2E0BF24-9F88-35DB-8526-8E47D941FDBF
	library(dplyr)
	library(tidyr)
	nass_data <- readr::read_csv("raw_data/E2E0BF24-9F88-35DB-8526-8E47D941FDBF.csv",na = '(D)',
	skip = 1,

	col_names = c(
	"program", "period", "week_ending", "geo_level", "state", "state_ansi",
	"ag_district", "ag_district_code", "county", "county_ansi", "zip_code",
	"region", "watershed_code", "watershed", "commodity", "data_item",

	library(ggplot2)
	library(dplyr)

	download.file(url = 'https://datadryad.org/stash/downloads/file_stream/624637', destfile = 'trait_data.zip', mode = 'wb')

	unzip(zipfile = 'trait_data.zip', unzip = 'unzip')
	s6heights <- readr::read_csv('traits/season_6_traits/season_6_canopy_height_sensor.csv')
	s4heights <- readr::read_csv('traits/season_4_traits/season_4_canopy_height_sensor.csv')

	heights <- bind_rows(s4heights, s6heights)

	select
	t.treatment_id :: text as treatmentDbId,
	t.site_id :: text as observationUnitDbId,
	t.variable_id :: text as observationVariableDbId,
	v.name as observationVariableName,
	t.id :: text as observationDbId,
	t.mean :: text as value,
	t.date as observationTimeStamp,
	s.sitename as observationUnitName,
	t.cultivar_id :: text as germplasmDbId,