fevo.2017.00175.

burningHouse

This repository includes the data, analyses and how to reproduce figures found in the article Our house is burning: discrepancy in climate change vs biodiversity coverage in the media by Legagneux et al. (2018) DOI: 10.3389/fevo.2017.00175.

We have used a standard R package to:

1- efficiently assess the quality of our code (here we simply used R CMD check);

2- readily share our code (see installation section below).

We however acknowledge that despite the form of a standard R package, the code presented is more a organized script than a package (i.e. functions included are not general).

Scientists, policy makers, and journalists are three key, interconnected players involved in prioritizing and implementing solutions to mitigate the consequences of anthropogenic pressures on the environment. The way in which information is framed and expertise is communicated by the media is crucial for political decisions and for the integrated management of environmental issues. Here we present a comparative study of scientific literature and press articles addressing climate change and biodiversity. We extensively scrutinized the scientific literature, research funding, and press articles from the USA, Canada, and United Kingdom addressing climate change and biodiversity issues between 1991 and 2016. We found that media coverage of climate change was up to eight times higher compared to biodiversity. This discrepancy could not be explained by different scientific output between the two issues. Moreover, climate change media coverage was often related to specific events whereas no such indication of a connection was found in the case of biodiversity. An international communication strategy is urgently required to raise public awareness on biodiversity issues. We discussed several initiatives that scientists could undertake to better communicate major discoveries to the public and policy makers.

The easiest way is to use the devtools R package. Once installed, use the following commands in your favorite R console:

library(devtools)
install_github('KevCaz/burningHouse')

We collected data, stored them as data frames and listed them below:

events: international events reported on figure 2 (see below);
fundingsUSCA: time series of research fundings (yearly frequency);
newsPaper: number of articles in the newspapers' time series (yearly frequency);
newsNames: names of the newspapers included in the study;
sciPaper: time series of scientific papers (yearly frequency);
sciNames: number of scientific papers we retrieved per journal title.

To manipulate these data frames, the user should first call the data() function like so:

data(newsNames)

The data frame is then usable, for instance:

knitr::kable(newsNames)

yields:

|country |name | |:-------|:-----------------------| |Canada |The Globe and Mail | |Canada |National Post | |Canada |The Toronto Star | |Canada |Winnipeg Free Press | |USA |The New York Times | |USA |USA Today | |USA |The Wall Street Journal | |USA |The Washington Post | |UK |Financial Times | |UK |The Guardian | |UK |The Independent | |UK |The Times |

Also for each dataset, details are provided in the documentation associated. To access this documentation the user can either use ? or help():

?newsNames

Creating the figures below required to 1- collect data and 2- do a peaks detection analysis. Data are available as data frames (listed above) and the peaks detection analysis is presented as a example of the detectPeaks() function we used.

data(sciPapers)
png('inst/fig/ms-figure1a.png', height = 5, width = 7, res = 300, unit = 'in')
  figure1a(
    sciPapers$year,
    sciPapers$records_CC,
    sciPapers$records_BD,
    colCC = "#604a3c", colBD = "#69ab78"
  )
  dev.off()

data(fundingUSCAN)
grDevices::png("inst/fig/ms-figure1b.png", height = 5, width = 7, res = 300, unit = "in")
  figure1b(
    fundingUSCAN$year,
    fundingUSCAN$CC_CA + fundingUSCAN$CC_US,
    fundingUSCAN$BD_CA + fundingUSCAN$BD_US,
    colCC = "#604a3c", colBD = "#69ab78"
  )
grDevices::dev.off()

data(events); data(newsPapers);
grDevices::png(file='inst/fig/ms-figure2.png', width = 8, height = 6, res = 300, unit = 'in')
  figure2(events, newsPapers, colCC = "#604a3c", colBD = "#69ab78")
grDevices::dev.off()