Correspondence between Scientific and Traditional Ecological Knowledge: Rain Forest Classification by the Non-Indigenous Ribereños in Peruvian Amazonia

• Published in: Biodiversity and conservation Vol. 16; no. 6; pp. 1785 - 1801
• Main Authors: Halme, K. J, Bodmer, R. E
• Format: Journal Article
• Language: English
• Published: Dordrecht Dordrecht : Kluwer Academic Publishers 01.06.2007; Springer Nature B.V
• Subjects: Amazonia; Beta-diversity; Biodiversity; Classification; Conservation biology; ferns and fern allies; Fertility; forest habitats; forest types; Habitats; Indicator species; inventories; peasantry; Rain; rain forests; Rainforests; Shifting cultivation; Slash and burn; Soil texture; Traditional ecological knowledge; tropical rain forests; Vegetation classification; Wildlife habitat; Wildlife management; Amazonia
• DOI: 10.1007/s10531-006-9071-4
• ISSN: 0960-3115

Traditional ecological knowledge (TEK) is a potential source of ecological information. Typically TEK has been documented at the species level, but habitat data would be equally valuable for conservation applications. We compared the TEK forest type classification of ribereños, the non-indigenous rural peasantry of Peruvian Amazonia, to a floristic classification produced using systematically collected botanical data. Indicator species analysis of pteridophytes in 300 plots detected two forest types on non-flooded tierra firme, each associated with distinct soil texture and fertility, and one forest type in areas subject to flooding. Nine TEK forest types were represented in the same set of plots. Each TEK forest type was consistently (>82%) associated with one of the three floristic classes and there were also clear parallels in the ecological characterizations of the forest types. Ribereños demonstrated clear preferences for certain forest types when selecting sites for slash-and-burn agriculture and hunting. Our results indicate that the non-tribal inhabitants of Amazonia possess valuable TEK that could be used in biodiversity inventories and wildlife management and conservation for characterizing primary rain forest habitats in Amazonia.