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Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy)
BACKGROUND: Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretatio...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4508904/ https://www.ncbi.nlm.nih.gov/pubmed/26173678 http://dx.doi.org/10.1186/s13002-015-0038-y |
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author | Savo, V. Joy, R. Caneva, G. McClatchey, W. C. |
author_facet | Savo, V. Joy, R. Caneva, G. McClatchey, W. C. |
author_sort | Savo, V. |
collection | PubMed |
description | BACKGROUND: Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. METHODS: We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson’s residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. RESULTS: The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson’s residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. CONCLUSIONS: Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13002-015-0038-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4508904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45089042015-07-22 Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) Savo, V. Joy, R. Caneva, G. McClatchey, W. C. J Ethnobiol Ethnomed Research BACKGROUND: Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. METHODS: We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson’s residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. RESULTS: The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson’s residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. CONCLUSIONS: Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13002-015-0038-y) contains supplementary material, which is available to authorized users. BioMed Central 2015-07-15 /pmc/articles/PMC4508904/ /pubmed/26173678 http://dx.doi.org/10.1186/s13002-015-0038-y Text en © Savo et al. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Savo, V. Joy, R. Caneva, G. McClatchey, W. C. Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title | Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title_full | Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title_fullStr | Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title_full_unstemmed | Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title_short | Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) |
title_sort | plant selection for ethnobotanical uses on the amalfi coast (southern italy) |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4508904/ https://www.ncbi.nlm.nih.gov/pubmed/26173678 http://dx.doi.org/10.1186/s13002-015-0038-y |
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