Food production covers the most basic human need, and simultaneously is the main driver of anthropogenic environmental impacts. These impacts have resulted in the transgression, during the brief period since the industrial revolution, of the planetary boundaries defining the safe operating space of humanity. A rich research literature quantifies the last 60 years’ fast, heterogeneous, and often unfair development in food supply and related environmental impacts, and how these depend on agro-climatic factors, technology, and trade flows, all of which have greatly changed but with different trajectories around the world. However, these developments lack an integrated approach, and are very poorly quantified before 1961. WHEP will bridge these knowledge gaps, assessing “who has eaten the planet” by answering the questions:
What are the environmental impacts of food production since 1850?
What is the role of trade in food supply and in displacing the responsibilities for these impacts?
How are impacts related to planetary boundaries, food supply and inequality?
These highly ambitious goals are addressed by four objectives:
You can also visit the European project site.
The WHEP project heavily relies on data. We use the R programming language. This repository is built as an R package containing functionality that we think might be useful to share to others as part of the project. This will also include functions for easily downloading the data gathered by the project.
The package is under constant development. Initial stable releases are available from both CRAN and R-universe.
You can install the stable version on CRAN:
install.packages('whep')
You can also install the stable version on R-universe:
install.packages(
"whep",
repos = c("https://eduaguilera.r-universe.dev", "https://cloud.r-project.org")
)
If you want the development version of whep
, you can
install it from GitHub
with:
::pak("eduaguilera/whep") pak
You can read more about the package’s functionalities from the documentation at the reference page.
We try to follow best coding practices, specifically focused on R package creation. The process is roughly summarized in:
renv
R package.R/
directory as
functions.The project is starting with contributors that are still learning about coding and best practices. For this reason we have created a guide explaining most of the things you need from the previous steps, covering both git and R package development. You can find the guide here. Anyone is welcome to contribute, but we highly recommend to go through this guide to become familiar with the workflow if you are still not used to it.