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Drivers of present and lifetime natural resource use in a tropical biodiversity hotspot
Author(s) -
Reuter K. E.,
Sewall B. J.,
Di Minin E.
Publication year - 2018
Publication title -
animal conservation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.111
H-Index - 85
eISSN - 1469-1795
pISSN - 1367-9430
DOI - 10.1111/acv.12355
Subject(s) - natural resource , geography , biodiversity hotspot , environmental resource management , context (archaeology) , biodiversity , resource (disambiguation) , exploitation of natural resources , socioeconomics , natural resource economics , ecology , biology , economics , computer network , archaeology , computer science
Effective biodiversity conservation requires an understanding of the drivers of natural resource use. Few studies, however, have examined how motivations of natural resource users and attributes of local social organizations affect resource extraction over time. We aimed to identify which characteristics of individuals (taboos, food security, resource‐related income), groups (village size, ease of access to education, proximity to park), and institutions (presence of enforcement mechanisms) best predicted use of multiple types of natural resources near a protected area during the past 1.5 years and during respondents’ lifetimes. Data were collected in 2013 via semi‐structured interviews with 360 people across ten villages along the perimeter of Ankarana National Park (northern Madagascar). All recent and lifetime uses of natural resources examined were higher in villages close to the park and for respondents with a history of earning money from extracting natural resources. In addition, individuals with ancestral meat‐related taboos were less likely to have extracted natural resources over their lifetime, while individuals who recently consumed meat were more likely to have extracted natural resources over the past 1.5 years. All other variables were less important in explaining the use of natural resources. The results highlight that some drivers can be consistently important in predicting natural resource use and that simple models can have relatively high explanatory power even in the context of the (sometimes) illegal extraction of five different types of natural resources.