Those are difficult times, and I am not going to talk about #covid19 and its interactions with science, academia, ecology, society, well-being or climate as enough has been already said.  But I thought it’s a good moment to share a collaborative playlist the lab has created just for fun. Because “quien canta su mal espanta“*. Thanks to all the lab members and close collaborators for sharing your good music taste. Enjoy, stay safe, take care of yourself and your loved ones and sing aloud!

• “who sings his evil scares”

I have a new scarf depicting the temperatures of the last 100 years in Barcelona. The warmer the colors, the hotter the temperatures. This was a very cool project we did with my wife (she is the artist, I just crunched the numbers). It’s not only super pretty but a great conversation opener. Especially for young people, who suddenly realize all their life has been warmer than it used to be. I love it. But it’s ironic that winters are getting shorter and milder and I can’t use my scarf as much as I would like.

Showing off my new scarf to my beloved friends.

It has been inspired by the knit linen stitch version of the Tempestry Project. Every year is represented by four rows in linen stitch (right side, wrong side, rs, ws), in a color that represents the mean temperature of that year. Data comes from the Barcelona meteorological observatory ;  (which has more than 200 years of monthly mean temperature data!)

We categorized the temperatures in 7 categories and selected 7 colors within a blue-red gradient. Here is the lines pattern we used starting on 1918 and ending in 2018. “1” represents the colder years, “7” the warmer years:

1 3 4 2 2 3 1 4 4 4 3 4 3 1 2 4 2 2 5 3 2 2 1 3 5 3 5 2 6 5 6 5 2 4 4 2 4 1 2 3 3 2 5 2 2 4 2 3 4 3 1 3 2 1 3 2 2 3 2 2 3 1 4 4 5 2 3 4 4 5 6 6 3 4 3 6 6 3 7 5 5 6 6 5 7 5 4 7 6 5 7 4 7 6 6 7 7 7 7 7

The code I used to convert temperature to colors is as follows:

#read the data:
bcn <- read.table(url("http://static-m.meteo.cat/wordpressweb/wp-content/uploads/2019/01/01160205/Barcelona_TM_m_1780_2018.txt"))
head(bcn)

#Create a dataframe with mean anual temperatures per year
d <- data.frame(year = bcn$V1, mean_t = rowMeans(bcn[,2:13]))

#select the last 100 years (use more if you want a longer scarf)
d <- tail(d,100)

#create a nice color gradient from blue to red (7 colors)
mypal <- colorRampPalette(c( "blue", "red" ))(7)
mypal

[1] “#0000FF” “#2A00D4” “#5500AA” “#7F007F” “#AA0055” “#D4002A” “#FF0000”

#Create a function to convert numbers to colors
map2color<-function(x,pal,limits=NULL){
if(is.null(limits)) limits=range(x)
pal[findInterval(x,seq(limits[1],limits[2],length.out=length(pal)+1), all.inside=TRUE)]
}
colors <- map2color(d$mean_t,mypal)

#visualize it
barplot(height = rep(1,length(d$mean_t)), col = colors)

#and extract the row numbers, 
#as.numeric(as.factor(colors))

1 3 4 2 2 3 1 4 4 4 3 4 3 1 2 4 2 2 5 3 2 2 1 3 5 3 5 2 6 5 6 5 2 4 4 2 4 1 2 3 3 2 5 2 2 4 2 3 4 3 1 3 2 1 3 2 2 3 2 2 3 1 4 4 5 2 3 4 4 5 6 6 3 4 3 6 6 3 7 5 5 6 6 5 7 5 4 7 6 5 7 4 7 6 6 7 7 7 7 7

Thise are all available years from 1780 to 2018, FYI:

A conversation today at lunch time made me think about some notes I took on this topic, which I reproduce here:

Jonathan Foley gave a pretty convincing talk at ESA 2013 showing that meat consumption is unsustainable for the environment (i.e. land use + CO2 emissions). This was “the straw that broke the camel’s back”* for me and since then I reduced my meat consumption quite drastically.

However, I read a few days ago this paper showing that changing meat for vegetables and fruits can be even worse if you take also into account water footprint and energy use (e.g. transport and storage). I skip the details, but the bottom line is that the story is complicated and the best way to save the world is to reduce calorie intake and eat lots of grains. Here is Figure 2 from the paper (the paper style and figures are quite poor, by the way).

It’s hard because even if you want to do the best is not easy. Is it better for the environment to use bacon or eggplant with my pasta? No idea!**. If I knew the Y axe of the following graph things would be easier.

*this is what google suggest for translating “la gota que colma el vaso”.

**Is the bacon from pigs next door? Is the eggplant from Nicaragua?

I’m in Sweden, it’s been snowing for two weeks now, reaching -20 and all the stuff, and I am happy. However, I can stop noticing that swedish guys at my department have no beards. All came perfectly shaved everyday, and take note that I am in an ecology department! My only explanation is that this is his quetzal tail. Only by showing that they have enough energy to bike for 30 minutes at -10 without the protection of a beard they have the possibility to find an appropriate mate. Things got that far that I am afraid that is becoming fixated at the population level, and his beards are becoming thinner. I plan to ignore the other alfa males this winter and show proudly my thick beard, even at expenses of my fitness.