The role of kinship in knowledge about medicinal plants: evidence for context-dependent model-based biases in cultural transmission?

Brito, Camilla de Carvalho de; Júnior, Washington Soares Ferreira; Albuquerque, Ulysses Paulino; Ramos, Marcelo Alves; Silva, Taline Cristina da; Neto, Eraldo Medeiros Costa; Medeiros, Patrícia Muniz de

doi:10.1590/0102-33062018abb0340

Cited by 9 publications

(8 citation statements)

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“…Exponential random graph models (ERGMs) are the primary methods of testing these predictions, because a single ERGM can include configuration variables, node connectivity variables, and node pair variables, which controls for the confounding effects of each variable type (Lusher et al ., 2013). However, several studies have used alternative methods to test predictions using only node pair variables, with interesting results (Salali et al ., 2016; de Brito et al ., 2019; Santoro, Chaves & Albuquerque, 2020). Several predictions involving all three types of variables have been supported in previous ethnobiological studies (Henrich & Broesch, 2011; Labeyrie et al ., 2015; Thomas & Caillon, 2016; Bond & Gaoue, 2020).…”

Section: Advanced Statistical Methods For Hypothesis Testing In Ethno...mentioning

confidence: 99%

Methodological advances for hypothesis‐driven ethnobiology

et al. 2021

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Ethnobiology as a discipline has evolved increasingly to embrace theory-inspired and hypothesis-driven approaches to study why and how local people choose plants and animals they interact with and use for their livelihood. However, testing complex hypotheses or a network of ethnobiological hypotheses is challenging, particularly for data sets with nonindependent observations due to species phylogenetic relatedness or socio-relational links between participants. Further, to account fully for the dynamics of local ecological knowledge, it is important to include the spatially explicit distribution of knowledge, changes in knowledge, and knowledge transmission and use. To promote the use of advanced statistical modelling approaches that address these limitations, we synthesize methodological advances for hypothesis-driven research in ethnobiology while highlighting the need for more figures than tables and more tables than text in ethnobiological literature. We present the ethnobiological motivations for conducting generalized linear mixed-effect modelling, structural equation modelling, phylogenetic generalized least squares, social network analysis, species distribution modelling, and predictive modelling. For each element of the proposed ethnobiologists quantitative toolbox, we present practical applications along with scripts for a widespread implementation. Because these statistical modelling approaches are rarely taught in most ethnobiological programs but are essential for careers in academia or industry, it is critical to promote workshops and short courses focused on these advanced methods. By embracing these quantitative modelling techniques without sacrificing qualitative approaches which provide essential context, ethnobiology will progress further towards an expansive interaction with other disciplines.

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Section: Advanced Statistical Methods For Hypothesis Testing In Ethno...mentioning

confidence: 99%

Methodological advances for hypothesis‐driven ethnobiology

et al. 2021

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“…+ [19] Homophily: genetically similar (closely related) people are more likely to share knowledge [19,44] 4b Descendant of main kinship group (distant kinship)…”

Section: Explanation 4amentioning

confidence: 99%

“…+ [40,45] Homophily: individuals who are patrilineal descendants of the single kinship group that is most common across all four villages are more likely to share knowledge because they are related [19,44] 4c House distance (general kinship) - [39] Homophily: in this region most marriages are patrilocal and nearby houses tend to be related by descent or marriage [46], and are therefore more likely to share knowledge [19,44] 4d Spouse + [19] Homophily: spouses are more likely to share knowledge [19] 4e Village + [39] Homophily: individuals from the same village are all very familiar [46], and may be more likely to also share knowledge [39,47] 4f Gender + [19] Homophily: in this region men and women are historically very socially segregated, unless they are related [46], so knowledge tends to be shared between people of the same gender [19] 4g Age -� if homophily [19]; Homophily: peers are more likely to share knowledge [19] + if prestige [15] Prestige: knowledge is more likely to be shared from older to younger [10,15] 4h…”

Section: Explanation 4amentioning

confidence: 99%

Prestige and homophily predict network structure for social learning of medicinal plant knowledge

Bond

Gaoue

2020

PLoS ONE

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Human subsistence societies have thrived in environmental extremes while maintaining biodiversity through social learning of ecological knowledge, such as techniques to prepare food and medicine from local resources. However, there is limited understanding of which processes shape social learning patterns and configuration in ecological knowledge networks, or how these processes apply to resource management and biological conservation. In this study, we test the hypothesis that the prestige (rarity or exclusivity) of knowledge shapes social learning networks. In addition, we test whether people tend to select who to learn from based on prestige (knowledge or reputation), and homophily (e.g., people of the same age or gender). We used interviews to assess five types of medicinal plant knowledge and how 303 people share this knowledge across four villages in Solomon Islands. We developed exponential random graph models (ERGMs) to test whether hypothesized patterns of knowledge sharing based on prestige and homophily are more common in the observed network than in randomly simulated networks of the same size. We found that prestige predicts five hypothesized network configurations and all three hypothesized learning patterns, while homophily predicts one of three hypothesized network configurations and five of the seven hypothesized learning patterns. These results compare the strength of different prestige and homophily effects on social learning and show how cultural practices such as intermarriage can affect certain aspects of prestige and homophily. By advancing our understanding of how prestige and homophily affect ecological knowledge networks, we identify which social learning patterns have the largest effects on biocultural conservation of ecological knowledge.

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“…Cultural transmission interacts with cognitive processing (see Nairne et al 2007;Eyssartier et al 2008;Santoro et al 2018;Brito et al 2019). For example, people both easily remember and readily share their experience of contaminated foods (Eriksson and Coultas 2014), or a disease outbreak could trigger social learning about medicinal plants which, in turn, increases the likelihood of local populations' survival (Soldati et al 2015).…”

Section: General Processesmentioning

confidence: 99%

Addressing Social-Ecological Systems across Temporal and Spatial Scales: a Conceptual Synthesis for Ethnobiology

et al. 2020

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This article is made publicly available in the institutional repository of Wageningen University and Research, under the terms of article 25fa of the Dutch Copyright Act, also known as the Amendment Taverne. This has been done with explicit consent by the author.Article 25fa states that the author of a short scientific work funded either wholly or partially by Dutch public funds is entitled to make that work publicly available for no consideration following a reasonable period of time after the work was first published, provided that clear reference is made to the source of the first publication of the work.This publication is distributed under The Association of Universities in the Netherlands (VSNU) 'Article 25fa implementation' project. In this project research outputs of researchers employed by Dutch Universities that comply with the legal requirements of Article 25fa of the Dutch Copyright Act are distributed online and free of cost or other barriers in institutional repositories. Research outputs are distributed six months after their first online publication in the original published version and with proper attribution to the source of the original publication.You are permitted to download and use the publication for personal purposes. All rights remain with the author(s) and / or copyright owner(s) of this work. Any use of the publication or parts of it other than authorised under article 25fa of the Dutch Copyright act is prohibited. Wageningen University & Research and the author(s) of this publication shall not be held responsible or liable for any damages resulting from your (re)use of this publication.

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The role of kinship in knowledge about medicinal plants: evidence for context-dependent model-based biases in cultural transmission?

Cited by 9 publications

References 33 publications

Methodological advances for hypothesis‐driven ethnobiology

Methodological advances for hypothesis‐driven ethnobiology

Prestige and homophily predict network structure for social learning of medicinal plant knowledge

Addressing Social-Ecological Systems across Temporal and Spatial Scales: a Conceptual Synthesis for Ethnobiology

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