GFUS: A global survey of human fire interactions

GFUS: A global survey of human-fire interactions

These files support the publication of "Expert elicitation suggests community-led fire governance can enable effective adaptation to a more flammable world".

The files contain data from a survey of experts on human-fire interactions as well as code used to process and analyse it.

An overview of the files is given below. 

1) Data

Raw survey data are provided by geographic region (1a). Data processed to produce analyses in the associated paper are provided as 1b.

Columns in data files are named by the question of the survey that generated them (Q1b through Q90). The contents of the associated questions that were asked are given in the data_dictionary.xlsx file.

1a) Data - by region

Files in here give survey data grouped by geographic region. Respondents were asked to identify regions which they felt their knowledge applied to. Data here were produced with the script "summarise_by_region". For each question:

- fn1 gives the mean of the question responses for the region

- fn2 gives the shannon entropy of the responses for the region

- fn3 gives the standard deviation for the region

- fn4 gives the number of responses for that question for the region

1b) Data - paper

These are files used to produce the analyses in the paper. 

- GFUS_Processed contains all survey responses without grouping by region. Questions can be identified from the relevant tab in data_dictionary.xlsx

- Gov_compare & LIFE_SH_Fire;  these files allow external comparison of the survey with the DAFI and LIFE literature databases. They give the governance and smallholder components of the survey data as well as relevant data from the LIFE and DAFI literature databases.

- Question meta_data gives information about the type of question asked (binary, numeric) as well as whether questions were about the confidence of previous answers.

- Question_summary gives a summary of data in data-by region grouped by question

- Two shapefiles (Fire_use_shape, record_meta_data) give survey responses by region merged with a shapefile of the geographic regions. Here "regnum", or region number equates to "Q1b_1", which was the survey question asking respondents to identify which regions their answers referred to.

2) Code

3 scripts are provided. Code is written in R.

- Firstly the script that was used to summarise survey responses by geographic region (Summarise_by_region)- Secondly the code used to conduct statistical tests presented in the paper- Thirdly the code used to produce plots in the paper