Plant Selection for Ethnobotanical Uses on the Amalfi Coast (Southern Italy) V

Savo et al. Journal of Ethnobiology and Ethnomedicine (2015) 11:58 DOI 10.1186/s13002-015-0038-y JOURNAL OF ETHNOBIOLOGY AND ETHNOMEDICINE RESEARCH Open Access Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy) V. Savo1,2*, R. Joy1,3, G. Caneva2 and W. C. McClatchey4 Abstract 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. Keywords: Ethnobotany, Medicinal flora, Regression analysis, Pearson’s residuals Background of this relationship have puzzled researchers over the Plants and humans are engaged in a dynamic relation- past decades, especially those regarding the reasons be- ship, where plants evolve creating biodiversity and hind plant selection criteria used by different communi- humans develop strategies and solutions. In this rela- ties around the world. In the ethnobotanical framework, tionship, plants evolve secondary metabolites to protect theories have been expressed to explain possible mecha- themselves from being “used” and people find ways to nisms behind this selection (e.g., [1, 2]) and then know- use these metabolites to their advantage. Several aspects ledge transmission [3–5]. One selection criterion that has been hypothesized is * Correspondence: [email protected] based on phylogeny. A non-random distribution of used 1Hakai Institute, Simon Fraser University, 8888 University Drive, Burnaby, BC medicinal plant species across families has been ob- V5A 1S6, Canada served in several parts of the world (e.g., [6–10]). Plants 2Department of Science, University Roma Tre, Viale Marconi 446, 00146 Rome, Italy within the same family, with close evolution ties, more Full list of author information is available at the end of the article © 2015 Savo et al. 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. Savo et al. Journal of Ethnobiology and Ethnomedicine (2015) 11:58 Page 2 of 15 likely share similar secondary compounds [11] which also test the methods using a set of non-medicinal plants may have similar or equal medicinal properties (e.g., (handicraft production, domestic and agro-pastoral prac- [12]) and this has been intuitively discovered by many tices). However, the aim of this paper is not to define traditional communities. Furthermore, plants that are which statistical method is the best one, but to test if evolutionarily closely related have generally more total discrepancies in datasets, sample size, data collection uses than those that are evolutionarily isolated [13]. and floras of reference could affect results in a way that Besides theories that suggest selection criteria based has as large or larger an effect as the selection of the on phylogeny, many others have been hypothesized. Sev- method itself. eral researchers have looked at possible alternative cri- This paper has two main objectives: teria used in selecting medicinal plants (e.g., [14–18]). These are for example based on taste and smell [12, 14, 1) To distinguish whether differences in the selected 17, 19–21] but also shape (e.g., [14]) or different/com- datasets and analytic methods affect results and bined features (e.g., [16, 18, 22]). Another hypothesized might, therefore, lead to different interpretations of criterion, which can apply to different plant uses, follows plant selection criteria. the ethnobotanical apparency theory, which states that 2) Test if the selection for traditional medicinal or non- plants that are more common and/or more available medicinal plants is based on phylogeny, or is based generally have a higher cultural importance than less ap- on other selection criteria (chorology, life form, or parent plants [1, 23, 24]. This selection criterion is based habitat). We want to approach the analysis with an on the fact that some plants are more easily available or alternative hypothesis about selection of plants for visible, not necessarily more useful [25]. use, and not just rely on a blind statistical method. Cultural factors might also be important in selecting plants [26–28]. Other researchers have hypothesized that Research area the selection of medicinal plants could have been influ- The Amalfi Coast is located in Southern Italy (Campa- enced by medical treatises of the past, especially in the nia) on the Southern side of the Sorrento Peninsula Mediterranean area [3, 4, 29–32]. However, some selec- (Fig. 1). The area develops along the coast, but is typified tion criteria must have been involved before these plant by high mountains (up to 1400 m on the sea level) and uses were firstly reported in written documents. steep slopes. These mountains belong to the Lattari Different methods have been developed to validate chain, which constitutes an outcrop of carbonatic strati- these theories. Several statistical analysis methods may fication, mainly composed by limestone, dolomitic lime- be used to analyze ethnobotanical data to highlight stone and Meso-Cenozoic dolomites [40]. whether some taxa are more extensively used than The area has mainly a Mediterranean bioclimate others in a certain flora under the hypothesis that selec- (sensu [41, 42]), stretching into the Temperate biocli- tion criteria are based on phylogeny. In this paper we in- mate in the uplands. Rainfall in the area is rather high vestigate the use of three different statistical methods considering other Tyrrhenian coastal areas of Southern proposed to test whether a specific family is over or Italy (e.g., [43–45]). The average annual rainfall amount under-used in a certain area: residual analysis from lin- along the coast sums up to 1300–1400 mm, and is ear regression [15, 33], the binomial test [2], and a higher in some valleys (1800 mm) [46]. Bayesian approach [34, 35]. Other researchers used also The geophysical diversity creates a multitude of habi- an imprecise Dirichlet modeling [36]. Turi and Murch tats in close proximity, leading to a high plant and plant [37] tested the Native American Ethnobotanical Data- community diversity [47, 48]. This area has indeed base [38] using four statistical methods (linear regres- attracted several botanists and other researchers over sion, Bayesian, binomial and imprecise Dirichlet the centuries (e.g., [49–56]). Human impact has possibly modeling). Kindscher et al. [39] analyzed three statistical contributed to increase this diversity creating a mosaic methods (linear regression, Bayesian, and binomial) of woodlands, maquis, garrigues and pastures, according using a smaller dataset, focusing only on Native Ameri- to the dissimilar utilization of plant communities. In- can medicinal plants used within the state of Kansas. deed, the human presence in the area dates back to the While these methods often give similar results, there are Roman period [57] or even before. During the following differences between them (see [37]) that have

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