Environment
Research insight
May 13, 2021

Dataset from 55 experts engaged in nature conservation in Mozambique

Abstract:

The data of this article is related to the original article entitled “An expert-based approach to assess the potential for local people engagement in nature conservation: The case study of the Niassa National Reserve in Mozambique” [1], published in Journal for Nature Conservation. The dataset is from an online and self-administrated survey with 55 experts aware of conservation policies and incentives under implementation in the Niassa National Reserve (NNR), the largest protected area in the country and third-largest in Africa. The survey included four sections of both compulsory and non-compulsory questions, mostly in closed-ended Likert-scale. In the first section, experts were asked about the main practices that threaten biodiversity conservation in the NNR, the actors who are directly and indirectly responsible for each practice, and the reasons for local people's involvement with those practices. The second section was about the effectiveness and limitations of the current compensation measures to engage local residents with conservation-friendly practices. In the third section, respondents were asked to select new measures to enhance the current conservation status and engage local people more effectively in conservation. The last section was about the socio-economic profile of respondents. The survey was conducted from June to September 2017. The paper includes the survey itself, raw data in an Excel spreadsheet, descriptive analysis, crosstabulation and Post Hoc cellwise tests (goodness of fit). Data are provided for public use and can serve as a benchmark for collaboration in order to conduct more comprehensive research, comparative analysis as well as panel data can be derived. This data can also have applications in other fields such as mathematics, statistics, and computation.


Authors: Aires Afonso Mbanze, Natasha Sofia Ribeiro, Carina Vieira da Silva, José Lima Santos


You can find the dataset here and the original article here.

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