dat.curtis1998 {metadat} | R Documentation |
Studies on the Effects of Elevated CO2 Levels on Woody Plant Mass
Description
Results from studies examining the effects of elevated CO2 levels on woody plant mass.
Usage
dat.curtis1998
Format
The data frame contains the following columns:
id | numeric | observation number |
paper | numeric | paper number |
genus | character | genus name |
species | character | species name |
fungrp | character | plant functional group |
co2.ambi | numeric | ambient CO2 level (control group) |
co2.elev | numeric | elevated CO2 level (treatment group) |
units | character | units for CO2 exposure levels |
time | numeric | maximum length of time (days) of CO2 exposure |
pot | character | growing method (see ‘Details’) |
method | character | CO2 exposure facility (see ‘Details’) |
stock | character | planting stock code |
xtrt | character | interacting treatment code (see ‘Details’) |
level | character | interacting treatment level codes (see ‘Details’) |
m1i | numeric | mean plant mass under elevated CO2 level (treatment group) |
sd1i | numeric | standard deviation of plant mass underelevated CO2 level (treatment group) |
n1i | numeric | number of observations under elevated CO2 level (treatment group) |
m2i | numeric | mean plant mass under ambient CO2 level (control group) |
sd2i | numeric | standard deviation of plant mass under ambient CO2 level (control group) |
n2i | numeric | number of observations under ambient CO2 level (control group) |
Details
The studies included in this dataset compared the total above- plus below-ground biomass (in grams) for plants that were either exposed to ambient (around 35 Pa) and elevated CO2 levels (around twice the ambient level). The co2.ambi
and co2.elev
variables indicate the CO2 levels in the control and treatment groups, respectively (with the units
variable specifying the units for the CO2 exposure levels). Many of the studies also varied one or more additional environmental variables (defined by the xtrt
and level
variables):
NONE = no additional treatment factor
FERT = soil fertility (either a
CONTROL
,HIGH
, orLOW
level)LIGHT = light treatment (always a
LOW
light level)FERT+L = soil fertility and light (a
LOW
light and soil fertility level)H2O = well watered vs drought (either a
WW
orDRT
level)TEMP = temperature treatment (either a
HIGH
orLOW
level)OZONE = ozone exposure (either a
HIGH
orLOW
level)UVB = ultraviolet-B radiation exposure (either a
HIGH
orLOW
level)
In addition, the studies differed with respect to various design variables, including CO2 exposure duration (time
), growing method (pot
: number = pot size in liters; GRND
= plants rooted in ground; HYDRO
= solution or aeroponic culture), CO2 exposure facility (method
: GC
= growth chamber; GH
= greenhouse; OTC
= field-based open-top chamber), and planting stock (stock
: SEED
= plants started from seeds; SAP
= plants started from cuttings). The goal of the meta-analysis was to examine the effects of elevated CO2 levels on plant physiology and growth and the interacting effects of the environmental (and design) variables.
Concepts
ecology, ratios of means
Author(s)
Wolfgang Viechtbauer, wvb@metafor-project.org, https://www.metafor-project.org
Source
Hedges, L. V., Gurevitch, J., & Curtis, P. S. (1999). The meta-analysis of response ratios in experimental ecology. Ecology, 80(4), 1150–1156. https://doi.org/10.1890/0012-9658(1999)080[1150:TMAORR]2.0.CO;2
(data obtained from Ecological Archives, E080-008-S1, at: https://esapubs.org/archive/ecol/E080/008/)
References
Curtis, P. S., & Wang, X. (1998). A meta-analysis of elevated CO2 effects on woody plant mass, form, and physiology. Oecologia, 113(3), 299–313. https://doi.org/10.1007/s004420050381
Examples
### copy data into 'dat' and examine data
dat <- dat.curtis1998
head(dat)
## Not run:
### load metafor package
library(metafor)
### calculate (log transformed) ratios of means and corresponding sampling variances
dat <- escalc(measure="ROM", m1i=m1i, sd1i=sd1i, n1i=n1i,
m2i=m2i, sd2i=sd2i, n2i=n2i, data=dat)
head(dat)
### meta-analysis using a random-effects model
res <- rma(yi, vi, method="DL", data=dat)
res
### average ratio of means with 95% CI
predict(res, transf=exp, digits=2)
### meta-analysis for plants grown under nutrient stress
res <- rma(yi, vi, method="DL", data=dat, subset=(xtrt=="FERT" & level=="LOW"))
predict(res, transf=exp, digits=2)
### meta-analysis for plants grown under low light conditions
res <- rma(yi, vi, method="DL", data=dat, subset=(xtrt=="LIGHT" & level=="LOW"))
predict(res, transf=exp, digits=2)
## End(Not run)