The DOI matches its Crossref record; 154 of the 154 references it cites were found in a registry or an index.
Conservation and Subsistence in Small-Scale Societies
Abstract
▪ Abstract Some scholars have championed the view that small-scale societies are conservers or even creators of biodiversity. Others have argued that human populations have always modified their environments, often in ways that enhance short-term gains at the expense of environmental stability and biodiversity conservation. Recent ethnographic studies as well as theory from several disciplines allow a less polarized assessment. We review this body of data and theory and assess various predictions regarding sustainable environmental utilization. The meaning of the term conservation is itself controversial. We propose that to qualify as conservation, any action or practice must not only prevent or mitigate resource overharvesting or environmental damage, it must also be designed to do so. The conditions under which conservation will be adaptive are stringent, involving temporal discounting, economic demand, information feedback, and collective action. Theory thus predicts, and evidence suggests, that voluntary conservation is rare. However, sustainable use and management of resources and habitats by small-scale societies is widespread and may often indirectly result in biodiversity preservation or even enhancement via creation of habitat mosaics.
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Ecology in an anthropogenic biosphere
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Metadata
- Authors
- Smith, E. A., & Wishnie, M.
- Venue
- Annual Review of Anthropology
- Publisher
- Annual Reviews
- Published
- 2000-10
- Volume
- 29
- Issue
- 1
- Pages
- 493-524
- ISSN
- 0084-6570 (ISSN-L)
- 1545-4290
- OpenAlex
- W2163065522
- Cited by
- 425
- References
- 154
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.