This is an additional theme for ggplot2
that generates an inverse black and white color scheme.
ggplot(mtcars, aes(wt, mpg)) + geom_point()
# Add theme_black()
ggplot(mtcars, aes(wt, mpg)) + geom_point(color = "white") + theme_black()
The function chlA
uses the trichromatic equations to convert absorbance values (wavelengths, in nm) to estimates of chlorophyll concentration using the equations from:
Jeffrey, S. W., and G. F. Humphrey. 1975. New spectrophotometric equations for determining chlorophylls a, b, c1 and c2 in higher plants, algae and natural phytoplankton. Biochem Physiol Pflanz BPP:191–194.
The function takes a data.frame
with the following values in the column names (corresponding to wavelengths in the equations in Jeffrey & Humphrey): "480", "510", "630", "647", "664", and "750." Additional arguments include extraction container volume (vol
) and, optionally, area of extration (area
, representing surface area for epiphytic algae).
The function returns the same data.frame
with columns appending for chlorophyll-a, -b, and -c, and phaeopigment concentrations.
This function uses the iNEXT
package to approximate species richness for a given level of sample 'coverage' based on methods in:
Chao, Anne, and Lou Jost. "Coverage-based rarefaction and extrapolation: standardizing samples by completeness rather than size." Ecology 93.12 (2012): 2533-2547.
The function requires a data.frame
or matrix
with species as rows and communities as columns.
The function returns a data.frame
with the observed richness, observed coverage (Chat), observed sample size (N), estimated richness (based on sample coverage), and optionally, richness based on the Chao1 estimator, and/or finally rarefied richness (individual-based subsampling).
fdist
takes a functional trait matrix, and returns an ultrametric distance matrix using the method that best preserves the original (non-ultrametric) distances.
References:
Mouchet, M., Guilhaumon, F., Villéger, S., Mason, N. W., Tomasini, J. A., & Mouillot, D. (2008). Towards a consensus for calculating dendrogram‐based functional diversity indices. Oikos, 117(5), 794-800.
Mérigot, B., Durbec, J. P., & Gaertner, J. C. (2010). On goodness-of-fit measure for dendrogram-based analyses. Ecology, 91(6), 1850-1859.
Modified from:
Updated: 2016-07-27
An interactive map showing site locations and images for the Zostera Experimental Network (ZEN).
Images from: http://www.zenscience.org/.
# Load libraries
library(leaflet)
Map is created using supplementary dataset from:
Lefcheck et al. (2015) "Biodiversity enhances ecosystem multifunctionality across trophic levels and habitats." Nature Communications 6: 6936notep. http://dx.doi.org/10.1038/ncomms7936.
# Load libraries
#devtools::install_github("rstudio/leaflet", ref="feature/color-legend")
library(leaflet)
########### | |
# Calculate a Dunnett's test | |
# using information from a meta-analysis | |
# using definitions at http://davidmlane.com/hyperstat/B112114.html | |
# | |
# Jarrett Byrnes & Jon Lefcheck | |
# 12/8/2013 | |
########### | |
#helper functions |