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.

该数据集展示了在Boosted Regression Tree（或称BRT，增强回归树）分析中，对直接健康效益、生态系统服务、小规模清除的优点以及大规模清除的缺点十个最重要的解释变量。解释变量按相对重要性依次排列在每个列的下方。数据通过访谈调查收集，共完成两次调查。在婆罗洲岛印尼部分——加里曼丹，由19个当地非政府组织（NGO）在2008年4月至2009年9月的15个月内进行，涉及687个村庄的6,983名居民的访谈，这些村庄位于加里曼丹猩猩的一般分布范围内。由于对部分回应可靠性的怀疑，原始的6,983份访谈数据集被缩减至4,973份。此外，在马来西亚沙巴州的六个村庄进行了56次进一步的访谈。调查问卷包含32个问题和34个可选项，这些选项被划分为多个部分，重点关注基本社会人口信息、访谈者可靠性评估以及对森林价值与野生动物认知的问题。