Rapid ecosystem change challenges the adaptive capacity of Local Environmental Knowledge.

Glob Environ Change

Institut de Ciència i Tecnologia Ambientals, Universitat Autònoma de Barcelona, Barcelona, Spain ; Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.

Published: March 2015


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Article Abstract

The use of Local Environmental Knowledge has been considered as an important strategy for adaptive management in the face of Global Environmental Change. However, the unprecedented rates at which global change occurs may pose a challenge to the adaptive capacity of local knowledge systems. In this paper, we use the concept of the shifting baseline syndrome to examine the limits in the adaptive capacity of the local knowledge of an indigenous society facing rapid ecosystem change. We conducted semi-structured interviews regarding perceptions of change in wildlife populations and in intergenerational transmission of knowledge amongst the Tsimane', a group of hunter-gatherers of Bolivian Amazonia ( = 300 adults in 13 villages). We found that the natural baseline against which the Tsimane' measure ecosystem changes might be shifting with every generation as a result of (a) age-related differences in the perception of change and (b) a decrease in the intergenerational sharing of environmental knowledge. Such findings suggest that local knowledge systems might not change at a rate quick enough to adapt to conditions of rapid ecosystem change, hence potentially compromising the adaptive success of the entire social-ecological system. With the current pace of Global Environmental Change, widening the gap between the temporal rates of on-going ecosystem change and the timescale needed for local knowledge systems to adjust to change, efforts to tackle the shifting baseline syndrome are urgent and critical for those who aim to use Local Environmental Knowledge as a tool for adaptive management.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4471143PMC
http://dx.doi.org/10.1016/j.gloenvcha.2015.02.001DOI Listing

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