The ten most important explanatory variables for the direct health benefits, ecosystem services, advantages small scale clearing, advantages large scale clearing, and disadvantages large scale clearing indices from a BRT analysis

The dataset presents the ten most important explanatory variables for
the direct health benefits, ecosystem services, advantages small scale
clearing, and disadvantages large scale clearing indicies in the
Boosted Regression Tree or BRT analysis. Explanatory variables are
shown in order down each column with their relative importance.  

The data was gathered by interview survey. Two interview surveys were completed.

A survey was conducted in Kalimantan, the Indonesian part of the
island of Borneo. The survey was conducted by 19 local non-governmental
organizations (NGOs) over a period of 15 months from April 2008 to
September 2009, and involved interviews with 6,983 people in 687
villages within the general distribution range of orangutan in
Kalimantan. The original dataset of
6,983 interviews was reduced to 4,973 because of doubts about the reliability of some of the
responses. A further 56 interviews were performed in six villages in the Malaysian State of Sabah.

The survey questionnaire comprised 32 questions and 34 optional
sub-questions that were divided into a number of sections focusing on
basic socio-demographic information, assessment of interviewee
reliability, and questions on perceptions of forest values and wildlife.