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Evaluating indices of traditional ecological knowledge: a methodological contribution

BACKGROUND: New quantitative methods to collect and analyze data have produced novel findings in ethnobiology. A common application of quantitative methods in ethnobiology is to assess the traditional ecological knowledge of individuals. Few studies have addressed reliability of indices of tradition...

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Autores principales: Reyes-García, Victoria, Vadez, Vincent, Tanner, Susan, McDade, Thomas, Huanca, Tomás, Leonard, William R
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1459110/
https://www.ncbi.nlm.nih.gov/pubmed/16638119
http://dx.doi.org/10.1186/1746-4269-2-21
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author Reyes-García, Victoria
Vadez, Vincent
Tanner, Susan
McDade, Thomas
Huanca, Tomás
Leonard, William R
author_facet Reyes-García, Victoria
Vadez, Vincent
Tanner, Susan
McDade, Thomas
Huanca, Tomás
Leonard, William R
author_sort Reyes-García, Victoria
collection PubMed
description BACKGROUND: New quantitative methods to collect and analyze data have produced novel findings in ethnobiology. A common application of quantitative methods in ethnobiology is to assess the traditional ecological knowledge of individuals. Few studies have addressed reliability of indices of traditional ecological knowledge constructed with different quantitative methods. METHODS: We assessed the associations among eight indices of traditional ecological knowledge from data collected from 650 native Amazonians. We computed Spearman correlations, Chronbach's alpha, and principal components factor analysis for the eight indices. RESULTS: We found that indices derived from different raw data were weakly correlated (rho<0.5), whereas indices derived from the same raw data were highly correlated (rho>0.5; p < 0.001). We also found a relatively high internal consistency across data from the eight indices (Chronbach's alpha = 0.78). Last, results from a principal components factor analysis of the eight indices suggest that the eight indices were positively related, although the association was low when considering only the first factor. CONCLUSION: A possible explanation for the relatively low correlation between indices derived from different raw data, but relatively high internal consistency of the eight indices is that the methods capture different aspects of an individual's traditional ecological knowledge. To develop a reliable measure of traditional ecological knowledge, researchers should collect raw data using a variety of methods and then generate an aggregated measure that contains data from the various components of traditional ecological knowledge. Failure to do this will hinder cross-cultural comparisons.
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spelling pubmed-14591102006-05-11 Evaluating indices of traditional ecological knowledge: a methodological contribution Reyes-García, Victoria Vadez, Vincent Tanner, Susan McDade, Thomas Huanca, Tomás Leonard, William R J Ethnobiol Ethnomed Research BACKGROUND: New quantitative methods to collect and analyze data have produced novel findings in ethnobiology. A common application of quantitative methods in ethnobiology is to assess the traditional ecological knowledge of individuals. Few studies have addressed reliability of indices of traditional ecological knowledge constructed with different quantitative methods. METHODS: We assessed the associations among eight indices of traditional ecological knowledge from data collected from 650 native Amazonians. We computed Spearman correlations, Chronbach's alpha, and principal components factor analysis for the eight indices. RESULTS: We found that indices derived from different raw data were weakly correlated (rho<0.5), whereas indices derived from the same raw data were highly correlated (rho>0.5; p < 0.001). We also found a relatively high internal consistency across data from the eight indices (Chronbach's alpha = 0.78). Last, results from a principal components factor analysis of the eight indices suggest that the eight indices were positively related, although the association was low when considering only the first factor. CONCLUSION: A possible explanation for the relatively low correlation between indices derived from different raw data, but relatively high internal consistency of the eight indices is that the methods capture different aspects of an individual's traditional ecological knowledge. To develop a reliable measure of traditional ecological knowledge, researchers should collect raw data using a variety of methods and then generate an aggregated measure that contains data from the various components of traditional ecological knowledge. Failure to do this will hinder cross-cultural comparisons. BioMed Central 2006-04-25 /pmc/articles/PMC1459110/ /pubmed/16638119 http://dx.doi.org/10.1186/1746-4269-2-21 Text en Copyright © 2006 Reyes-García et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Reyes-García, Victoria
Vadez, Vincent
Tanner, Susan
McDade, Thomas
Huanca, Tomás
Leonard, William R
Evaluating indices of traditional ecological knowledge: a methodological contribution
title Evaluating indices of traditional ecological knowledge: a methodological contribution
title_full Evaluating indices of traditional ecological knowledge: a methodological contribution
title_fullStr Evaluating indices of traditional ecological knowledge: a methodological contribution
title_full_unstemmed Evaluating indices of traditional ecological knowledge: a methodological contribution
title_short Evaluating indices of traditional ecological knowledge: a methodological contribution
title_sort evaluating indices of traditional ecological knowledge: a methodological contribution
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1459110/
https://www.ncbi.nlm.nih.gov/pubmed/16638119
http://dx.doi.org/10.1186/1746-4269-2-21
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