Skip to main content

Who should conduct ethnobotanical studies? Effects of different interviewers in the case of the Chácobo Ethnobotany project, Beni, Bolivia

Abstract

Background

That the answers elicited through interviews may be influenced by the knowledge of the interviewer is accepted across disciplines. However, in ethnobotany, there is little evidence to quantitatively assess what impact this effect may have. We use the results of a large study of traditional ecological knowledge (TEK) of plant use of the Chácobo and Pacahuara of Beni, Bolivia, to explore the effects of interviewer identity and knowledge upon the elicited plant species and uses.

Methods

The Chácobo are a Panoan speaking tribe of about 1000 members (300+ adults) in Beni, Bolivia. Researchers have collected anthropological and ethnobotanical data from the Chácobo for more than a century. Here, we present a complete ethnobotanical inventory of the entire adult Chácobo population, with interviews and plant collection conducted directly by Chácobo counterparts, with a focus on the effects caused by external interviewers.

Results

Within this large study, with a unified training for interviewers, we did find that different interviewers did elicit different knowledge sets, that some interviewers were more likely to elicit knowledge similar to their own, and that participants interviewed multiple times often gave information as different as that from two randomly chosen participants.

Conclusions

Despite this, we did not find this effect to be overwhelming—the amount of knowledge an interviewer reported on the research subject had comparatively little effect on the amount of knowledge that interviewer recorded from others, and even those interviewers who tended to elicit similar answers from participants also elicited a large percentage of novel information.

Background

Quantifying the effects of research methods on results is critical to interpreting those results. This could be particularly true of interview-elicited data, for which qualities of the interviewer may have a large effect. Here, we use results of a large, multi-interviewer dataset on plant uses collected in the Bolivian Amazon to assess interviewer effects and their implications. We found that different interviewers elicited different knowledge patterns that some interviewers systematically elicited knowledge from participants more similar to the interviewer’s own knowledge, and that knowledge reported by one participant to different interviewers was dissimilar. However, all interviewers still elicited much novel information, suggesting that while interview data must be treated with care, it is still a valuable tool in documenting knowledge.

That the results of interviews may be influenced by qualities of the interviewer—his or her gender, age, ethnicity and own attitudes or knowledge—is accepted across disciplines [1,2,3,4,5,6,7,8]. This effect has received more attention in fields that tend to have large number of different interviewers, such as public opinion [2, 4, 8, 9]. In ethnobotany, while the interviewer effect is acknowledged as important [7], it has received relatively attention (with the notable exception of interviewer gender (e.g. [10, 11])). To explore the effects of interviewer identity and knowledge on plant species and uses elicited in interviews, we used the results of a large study of traditional ecological knowledge (TEK) of plant use of the Chácobo and Pacahuara of Beni, Bolivia [12].

Given the availability of previous studies [13,14,15,16,17,18,19,20], the Chácobo are an outstanding possibility to study traditional knowledge over time. In many cases, however, comparisons are difficult to make, given the diversity of investigators and objectives. While a wide variety of studies have examined the efficacy of different methods in ethnobotany (e.g., as summarized in [21]), none have so far have quantitatively focused on the effect of a crucial influence on the results—the individual interviewer. Such effects could come hypothetically through informant selection, with different interviewers accessing different segments of the population, through interviewer effects, with different interviewers eliciting different information even from the same individual, and/or through interviewer bias, with interviewers reporting knowledge sets more similar that which they hold themselves.

Here, we hypothesized (1) that, within a large, contemporary study [12], with a unified training for interviewers, different interviewers would still elicit a different quantity and composition of plants and uses, (2) that these differences would be in particular influenced by the reviewer’s own knowledge of plants and their uses, but that (3) individuals interviewed twice by different interviewers would still report similar knowledge, as interviewer effect or bias would be small compared to differences among individual interviewees.

Methods

Study area and ethnobotanical data collection

The Chácobo and their territory (Fig. 1) have been described in detail in our publication on Chácobo plant-use [12]; thus, we do not repeat details on the study area here.

Fig. 1
figure 1

Chácobo territory 2013

Our project [12] explored the current traditional knowledge (TK) on plant use of the Chácobo and Pacahuara in Beni, Bolivia, and had three goals: (1) to discover and document current traditional plant knowledge through interviews and surveys, (2) to inventory the current flora of the region, and (3) to repatriate the acquired knowledge as well as previous data to the community.

After obtaining consent from CIRABO (Central Indígena de la Región Amazónica de Bolivia), and before starting fieldwork, we conducted a community meeting in May 2013, involving representatives of all 27 villages in the Chácobo Territory, in order to obtain prior informed consent from all communities. This session included the repatriation of the results of previous studies [20, 21]. In addition, during the project, all available material on Chácobo plant use was translated to Spanish and repatriated [22, 23]. The Chácobo community itself chooses 12 local counterparts to be trained as ethnobotanical interviewers and plant collectors. In September 2013, we conducted a 2-week workshop on ethnobiological methods and plant collection, training the 12 selected counterparts, 10 of which finally acted as interviewers. Training was conducted directly in the field in the central village of Alto Ivón, and involved theoretical exercises (overview on methodology of interviews, collection and herbarium techniques), as well as extensive practical exercises (structuring and testing of questionnaires, test interviews among the participants, field interviews with local community members, plant collection in the field, preparation of herbarium specimens, plant and artifact collection in the local community, data-basing, and initial data analysis).

From November 2013 to May 2015, the 10 Chácobo interviewers collected ethnobotanical information from 301 Chácobo participants (150 women, 151 men, representing almost the entire adult Chácobo population), and over 1500 plant samples were collected. Prior to starting the interviews, every interviewer obtained prior oral informed consent from each participant. Chácobo participants were divided into five age classes (18–30 years old: 58 men, 52 women; 31–40 years old: 31 men, 36 women; 41–50 years old: 35 men, 36 women; 51–60 years old: 15 men, 7 women; and > 60 years old: 12 men, 19 women). Because the study attempted to interview the whole adult Chácobo population, there was originally no emphasis on achieving a balanced age or gender distribution. All interviews were conducted at the homes of the participants by asking participants to freelist their plant knowledge following [24]. All plant uses were categorized following [24]. All interviews were preferably conducted in Chácobo. In a few cases where participants were not fully fluent in Chácobo, interviewers used Spanish as common language. The plant material was collected under permission from the Ministry of Environment and Water of the Plurinational State of Bolivia and was identified and deposited at the National Herbarium of Bolivia (LPB) under the collection numbers of the Chácobo collectors. Nomenclature follows www.TROPICOS.org. Use descriptions were coded after the fact into subcategories and, for some analyses, into six major categories: fodder, fuel, medical, cultural, construction, tool, and food.

All work was carried out following the International Society for Ethnobiology Code of Ethics [25], and under the framework provided by the Nagoya Protocol on Access to Genetic Resources and Fair and equitable sharing of benefits arising from their use of the Convention on Biological Diversity, the Chácobo community retains the copyright of the traditional knowledge of all informants. Any commercial use of any of the information requires prior consensus with informants and communities, and an agreement on the distribution of benefits.

Data analysis

To examine the extent of interviewer identity on the content of answers elicited, we first asked how the aggregate communities of plants, uses, and unique combinations of plants and use-categories (hereafter “plant-use combinations”) elicited by each interviewer differed. To do this, we ordered informant interviews using non-metric multi-dimensional scaling on distance matrices for plants, uses, and plant-use combinations and tested how well interviewer explained the location of the informant interviews in the resulting ordinations, in comparison to other possible explanatory characteristics, including gender, ethnicity, and age of informant, using the R package vegan [26].

In order to assess whether the interviewer knowledge influenced the quantity of answers elicited, we compared aggregate knowledge sets elicited by each interviewer across interviewers, and for those who were also themselves interviewed, to the knowledge sets they themselves reported, as discussed in depth by [27,28,29,30].

To examine how interviewer knowledge influenced the composition of answers, we considered just the subset of data including informants who were interviewed twice, and interviewers who were also themselves interviewed. For each interviewer, we used the locations of informant interviews they had conducted (“interviewer-elicited”), compared to the same informants interviewed by another (“other-elicited”). We considered the average vector from the location of other-elicited interviews to the interviewer-elicited to be a measure of “interviewer effect”. Then, we examined whether interviewers (a) tended to elicit communities of answers more similar to their own answers, by comparing the distance from interviewers own answers to the centroids of the interviewer-elicited answers and of the other-elicited answers, and (b) tended to elicit communities of answers more similar to one another, by comparing the total pairwise distances among interviewer-elicited answers and among other-elicited answers.

To examine how greatly the answers of informants changed in repeat interviews, for each informant who had been interviewed more than once, we compared the ordination location of each interview, quantifying the distance between these two locations as “intra-informant difference”. Such “intra-informant” differences have been elucidated in comparative studies [27,28,29,30]. We used the average of these distances, compared to the average of all pairwise distances between interviews “inter-informant difference”, to measure the scale of interviewer effects across the population. To assess the impact of these effects on the overall knowledge base, we calculated the number of unique instances and total mentions for species, uses, and plant-use combinations that were elicited by the interviewer but not reported by him or her, as a metric of novel information that elicited, beyond any effect of the interviewer’s own knowledge set.

Results

In accord with our first hypothesis, we did find that interviewers as individuals elicited distinct communities of plants (Fig. 2), uses (Fig. 3), and plant-use combinations (Fig. 4). Compared to demographic qualities of informants, interviewer identity explained more of the variation in ordination location when fit as an explanatory variable (plants: interviewer r2 = 0.37, p < 0.001, informant ethnicity r2 = 0.05, p = 0.009; uses: interviewer identity r2 = 0.39, informant ethnicity = 0.05, p = 0.016; plant-uses: interviewer identity r2 = 0.38, p < 0.01, informant ethnicity r2 = 0.05, p < 0.001, informant age r2 = 0.05, p < 0.001).

Fig. 2
figure 2

Identity of interviewer (pane title: BCM, DOA, etc.) has a significant effect on the community of plants reported by informants (points in ordination pane) that interviewer was responsible for (points in color). Density contours indicate the greatest concentration of informants

Fig. 3
figure 3

Identity of interviewer (pane title: BCM, DOA, etc.) has a significant effect on the community of uses reported by informants (points in ordination pane) that interviewer was responsible for (points in color). Density contours indicate the greatest concentration of informants

Fig. 4
figure 4

Identity of interviewer (pane title: BCM, DOA, etc.) has a significant effect on the community of plant-use combinations reported by informants (points in ordination pane) that interviewer was responsible for (points in color). Density contours indicate the greatest concentration of informants

The number of plants and number of use descriptions elicited from interviewees did differ among interviewers, with some interviewers consistently eliciting many more species (Fig. 5a) and uses (Fig. 5b). Interestingly, the external investigators (RBU, CVO, CT, and NPZ), none of whom spoke Chácobo, nor had personal in-depth knowledge of Chácobo plant knowledge, managed to elicit very similar numbers of species and uses in test interviews during training (Fig. 5). This is in accord with the fact that, for interviewers who were themselves interviewed, the number of species and uses a Chácobo interviewer elucidated from their participants did not relate to their own knowledge. That is, interviewers who themselves had higher knowledge often elicited less information from interviewees than interviewers who held comparatively lower knowledge themselves (Fig. 6).

Fig. 5
figure 5

Species (a) and uses (b) elicited by external interviewers (gray) vs. Chácobo interviewers (white)

Fig. 6
figure 6

Interviewers who themselves reported more plants (a) or uses (b) do not tend to elicit more plants or uses from their informants

Supporting our second hypothesis, when considering the subset of the population interviewed multiple times by different interviewers, we did see some evidence of interviewer bias. For plant species mentioned, in most cases, interviewers did “pull” answers—elicit answers that were close to their own knowledge sets (Fig. 7a) and “tighten” answers— elicit answers that were closer to one another (Fig. 7b). To some extent, this was also true of uses (Fig. 8) and plant-use combinations (Fig. 9), although in all cases there were great differences among interviewers: some interviewers should more of an effect (BCM, MOV, SCO), while others were equivocal (DOA), or did not show this effect (GCM, MSM).

Fig. 7
figure 7

Answers elicited by interviewers about species (red) compared to answers elicited from the same informants when interviews are conducted by another interviewer (blue). A vector arrow compares the centroid of each group (a) and the interviewer’s own answers (green). Also shown are the average within each interviewer of the distances of each informant’s answers from their own (b) and the average distances among interviews (c) for both their own interviews (blue) and those conducted by others (red)

Fig. 8
figure 8

Answers elicited by interviewers about uses (red) compared to answers elicited from the same informants when interviews are conducted by another interviewer (blue). A vector arrow compares the centroid of each group (a) and the interviewer’s own answers (green). Also shown are the average within each interviewer of the distances of each informant’s answers from their own (b) and the average distances among interviews (c) for both their own interviews (blue) and those conducted by others (red)

Fig. 9
figure 9

Answers elicited by interviewers about plant-use combinations (red) compared to answers elicited from the same informants when interviews are conducted by another interviewer (blue). A vector arrow compares the centroid of each group (a) and the interviewer’s own answers (green). Also shown are the average within each interviewer of the distances of each informant’s answers from their own (b) and the average distances among interviews (c) for both their own interviews (blue) and those conducted by others (red)

Our third hypothesis related to how greatly answers of those interviewed twice would change in repeat interviews. Ordination indicated that, in fact, answers did differ when comparing the distance between repeat interviews of one person (intra-individual) versus all interviews (inter-individual), and in fact, intra-individual distances are not significantly smaller than inter-individual distances, be it for species mentioned (Fig. 10), uses (Fig. 11), or species-use combinations (Fig. 12). This indicates that double interviews of the same person, done by different interviewers, tend to yield such diverse information that they might be counted as separate informants.

Fig. 10
figure 10

a The community of plants reported (black points, labeled with interviewer code) in the two interviews of each informant who was interviewed more than once (pane title), contrasted with all other interviews (gray points). Intra-informant distance represented by a solid black line. b The average intra-informant distance compared with the average inter-informant distance

Fig. 11
figure 11

a Community of uses reported (black points, labeled with interviewer code) in the two interviews of each informant who was interviewed more than once (pane title), contrasted with all other interviews (gray points). Intra-informant distance represented by a solid black line. b Average intra-informant distance compared with the average inter-informant distance

Fig. 12
figure 12

a The community of plant-use combinations reported (black points, labeled with interviewer code) in the two interviews of each informant who was interviewed more than once (pane title), contrasted with all other interviews (gray points). Intra-informant distance represented by a solid black line. b Average intra-informant distance compared with the average inter-informant distance

Given this clear effect of interviewer influence, did interviewers then still elicit plants, uses, and plant-uses not included in their own knowledge set, or was interviewer influence so strong that interviewers simply had interviewees reiterate their own set of knowledge? In accord with the results showing that the quantity of knowledge elicited from informants does not relate to the quantity known by the interviewer, our data indicate that interviewer bias does not have an overwhelming effect on the composition of knowledge elicited. For interviewers who elicited responses most closely to their own knowledge set (BCM, MOV, and SCO), 60–69% of the plants they elicited were novel (not reported in their own interviews). Similarly, large proportions of uses (55–68%) and plant-use combinations (79–84%) were novel. This was not at all different from the interviewers who elicited the answers least similar to their own knowledge (GCM and MSM) (Table 1). In other words, in every case, each interviewer managed to collect a wealth of new information they themselves did not know about.

Table 1 Answers elicited by interviewers in comparison to their own knowledge

Discussion

Many studies have found patterns of the influence of age, or accessibility to markets on traditional knowledge (e.g., [31,32,33,34,35,36,37,38,39]). The general trend found in relation to the difference in intergenerational knowledge, where young people know more than older people, suggests that this pattern generally could be a result of both knowledge transmission, as well as in situ learning, and be related to the time during which people acquire and use knowledge, with the older informants taking more responsibility in their households, who have a need to learn and apply their knowledge [32, 40,41,42]. In addition, the trend of a gradual decrease in knowledge from the old to the very young has been related to increased exposure of the new generations to new technology and services (e.g., pharmacies, paramedics, clinics, and different types of building materials, tools, and alternative utensils available in commercial centers) [35, 36, 38, 43, 44]. Some studies confirmed the hypothesis that people who are relatively isolated from the market economy share more traditional knowledge than people who live close to cities or larger towns [32]. Researchers have postulated that some resources may no longer be used due to industrialization or acquisition of technology services such as changes from wood to gas stoves, and a replacement of medicinal plants by modern medicine [45, 46].

General issues of interview methodology have been discussed ad infinitum in standard cognitive social science literature (e.g., [46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65]. In addition, large numbers of studies have discussed issues like interview structure and content, as well as the heterogeneity of interviews [66], or the number of interviews needed for representative studies, as well as the great complexity of interview situations, and the influence of researcher’s experience [67]. Even issues like the influence of researcher confidence [68], the number of researchers in a team [67], resourcing [69], interview saturation [70], and informant selection [71] have been broadly discussed.

However, no study has so far considered the influence of individual interviewers on results obtained from large groups of participants in an indigenous setting, although such effects are well known from other fields of research, e.g., public health [3], and especially marketing [1], and their influence on statistical model has been widely discussed [8, 9]. Our study supported our hypotheses that different interviewers elicit different sets of knowledge and that interviewers are more likely to elicit knowledge similar to their own. In fact, and contrary to our expectations, participants interviewed multiple times often gave as different information as any two randomly chosen participants would have given. Despite this, we did not find this effect to be overwhelming—the amount of knowledge of an interviewer on the research subject had comparatively little effect on the amount of knowledge yielded, and even the interviewers who tended to elicit the most similar answers from their informants to their own knowledge also elicited a large percentage of novel information.

The fact that the scientific trainers were able to elucidate similar quantities of knowledge levels local interviewers suggests the corollary: with appropriate support, local interviewers can yield similar results to those of external investigators. Given the unique sets of knowledge available to individuals, and the time constraints that usually exist for external investigators, it is apparent that multiple, local interviewers will allow ethnobotanical studies to most comprehensively document knowledge.

Conclusions

We suggest that the training of indigenous interviewers and plant collectors should be seriously considered for conducting any studies involving the documentation of traditional knowledge. Our results indicate that, at least in case of the Chácobo, the interviewer effect was negligible, given the very large number of participants interviewed. We suggest that the combination of indigenous interviewers, and a very large set of participants, is an excellent strategy to elucidate a maximum of information in ethnobotanical studies.

As final result of our project, all collected knowledge was repatriated to the Chácobo in a plant guide [72].

Abbreviations

BCM:

Bertha Chávez Moreno

CIRABO:

Central Indígena de la Región Amazónica de Bolivia

CT:

Carolina Tellez

CVO:

Carlos Vega Ocaña

DOA:

David Ortiz Álvarez

ESR:

Erlin Siripi

GCM:

Gualberto Chávez Moreno

GOS:

Gere Ortiz Soria

JSM:

Jorge Soria Morán

MOV:

Milton Ortiz Vaca

MSM:

María Soria Morán

NPZ:

Narel Y. Paniagua Zambrana

ORC:

Oscar Roca

RBU:

Rainer W. Bussmann

SCO:

Saúl Chávez

TCO:

Tierra Comunitaria de Origen (Communal lands of original inhabitants)

TEK:

Traditional Ecological Knowledge

TK:

Traditional Knowledge

References

  1. McKenzie JR. An investigation onto interviewer effects in marketing research. J Mar Res. 1977;14(3):330–6.

    Article  Google Scholar 

  2. Singer E, Frankel MR, Glasman MB. The effect of interviewer characteristics and expectations on response. Pub Opin Q. 1983;47(1):68–83.

    Article  Google Scholar 

  3. Davis RE, Couper MP, Janz NK, Caldwell CH, Resnicow K. Interviewer effects in public health surveys. Health Ed Res. 2010;25(1):14–26.

    Article  CAS  Google Scholar 

  4. Huddy L, Billig J, Bracciodieta J, Hoeffler L, Moynihan PJ, Pugliana P. The effect of interviewer gender on the survey response. Pol Beh. 1997;19(3):197–220.

    Article  Google Scholar 

  5. Waterman AH, Blades M, Spencer C. Indicating when you do not know the answer: the effect of question format and interviewer knowledge on children’s ‘don’t know’ responses. British J Dev Psych. 2004;22(3):335–48.

    Article  Google Scholar 

  6. Quinlan M. Considerations for collecting freelists in the field: examples from Ethobotany. Field Meth. 2005;17:219–34.

    Article  Google Scholar 

  7. Martin G. Ethnobotany: A Methods Manual. London: Routledge; 2010.

  8. Brunton-Smith I, Sturgis P, Leckie G. Detecting and understanding interviewer effects on survey data by using a cross-classified mixed effects location–scale model. J R Stat Soc Ser A. 2017;180:551–68. https://doi.org/10.1111/rssa.12205.

    Article  Google Scholar 

  9. West BT, Kreuter F, Jaenichen U. “Interviewer” effects in face-to-face surveys: a function of sampling, measurement error, or nonresponse? J Off Stat. 2013. https://doi.org/10.2478/jos-2013-0023.

  10. de Boer H, Lamxay V. Plants used during pregnancy, childbirth and postpartum healthcare in Lao PDR: a comparative study of the Brou. Saek and Kry ethnic groups J Ethnobiol Enthnobiomed. 2009;5:25.

    Article  Google Scholar 

  11. Pfeiffer JM, Butz RJ. Assessing cultural and ecological variation in ethnobiological research: the importance of gender. J Ethnobiol. 2005;25(2):240–78.

  12. Paniagua Zambrana NY, Bussmann RW, Hart RE, Moya Huanca AL, Ortiz Soria G, Ortiz Vaca M, Ortiz Álvarez D, Soria Morán J, Soria Morán M, Chávez S, Chávez Moreno B, Chávez Moreno G, Roca O, Siripi E. Traditional knowledge hiding in plain sight—21st century ethnobotany of the Chácobo in Beni. Bolivia J Ethnobiol Ethnobiomed. 2017;13:57. https://doi.org/10.1186/s13002-017-0179-2.

    Article  Google Scholar 

  13. Nordenskjöld E. Indianer und Weisse im Nordosten Boliviens. Stuttgart: Strecker und Schröder; 1922.

    Google Scholar 

  14. Haenke W. The Chácobo in Bolivia. Ethnos. 1958;23:100–25.

    Article  Google Scholar 

  15. Prost G. Notas linguisticas de Bolivia. No. II: Phonemas de la lengua Chácobo. La Paz: Instituto Linguistico de Verano; 1960.

  16. Prost MD. Costumbres, habilidades y cuadro de vida entre los Chácobos. La Paz: Instituto Linguistico de Verano; 1970.

  17. Kelm H. Chácobo. Tribus. 1972;21:129–246.

  18. Boom BM. Ethnobotany of the Chácobo Indians, Beni, Bolivia. Advances in Econ Bot. 1987;4:1–68.

    Google Scholar 

  19. Bergeron S. El uso de las plantas por los Chácobos (Alto Ivon, Beni, Bolivia). La Paz: Institut Françáis d'Etudes Andines (IFEA); 1998.

  20. Muñoz V, Sauvain M, Bourdy G, Callapa J, Bergeron S, Rojas I, Bravo JA, Balderrama L, Ortiz B, Gimenez A, Deharo E. A search for natural bioactive compounds in Bolivia through a multidisciplinary approach. Part I. Evaluation of the antimalarial activity of plants used by the Chácobo Indians. J Ethnopharmacol. 2000;69:127–37.

    Article  PubMed  Google Scholar 

  21. Carvalho Pires de Sousa D, Taboada Soldati G, Monteiro JM, de Sousa Araujo TA, Albuquerque UP. Information retrieval during free listing is biased by memory: evidence from medicinal plants. PLoS ONE. 2016;11(11):e0165838. https://doi.org/10.1371/journal.pone.0165838.

  22. Paniagua Zambrana N, Bussmann RW, Blacutt E, Macia MJ, editors. Los Chácobo y las Palmeras. Trujillo: Graficart; 2011.

  23. Paniagua Zambrana NY, Bussmann RW, Tellez C, Vega C. Los Chácobo y su historia en el siglo XX. St. Louis: William L. Brown Center, MBG; 2014.

  24. Paniagua Zambrana NY, Macía MJ, Cámara-Leret R. Toma de datos etnobotánicos de palmeras y variables socioeconómicas en comunidades rurales - Ethnobotanical data gathering of palms and socio–economic variables in rural communities. Ecol Bol. 2010;45(3):44–68.

    Google Scholar 

  25. International Society of Ethnobiology. International Society of Ethnobiology Code of Ethics (with 2008 additions). 2006. http://www.ethnobiology.net/what-we-do/core-programs/ise-ethics-program/code-of-ethics/.

  26. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O'Hara RB, Simpson GL, Solymos P, Henry M, Stevens H, Wagner H. vegan: Community Ecology Package. 2016. https://CRAN.R-project.org/package=vegan.

  27. Garro L. Intracultural variation in folk medical knowledge: a comparison between curers and non-curers. Amer Anthr. 1986;88:351–70.

    Article  Google Scholar 

  28. Benz BF, Santana-M F, Pineda-L R, Cevallos-E J, Robles-H L, De Niz-L D. Characterization of mestizo plant use in the Sierra de Manantlan, Jalisco-Colima, Mexico. J Ethnobiol. 1994;14(1):23–42.

    Google Scholar 

  29. Alcorn JB. Ethnobotanical knowledge systems: a resource for meeting rural development goals. In: Warren MD, editor. The cultural dimension of development: indigenous knowledge systems. London: Intermediate Technology Publications; 1995. p. 1–12.

    Google Scholar 

  30. Nolan JM. Pursuing the fruits of knowledge: cognitive ethnobotany in Missouri’s Little Dixie. J Ethnobiol. 2002;21(21):29–51.

    Google Scholar 

  31. Benz BF, Cevallos E, Santana M, Rosales A, Graf S. Losing knowledge about plant use in the sierra de Mazatlan biosphere reserve, Mexico. Econ Bot. 2000;54(2):183–91.

    Article  Google Scholar 

  32. Godoy R, Reyes-García V, Byron E, Leonard W, Vadez V. The effect of market economies on the wellbeing of indigenous peoples and on their use of renewable natural resources. Ann Rev Anth. 2005;34:121–38.

    Article  Google Scholar 

  33. Reyes-García V, Vadez V, Byron E, Apaza L, Leonard WR, Perez E, Wilkie D. Market economy and the loss of folk knowledge of plant uses: estimates from the Tsimane’ of the Bolivian Amazon. Curr Anth. 2005;46(4):651–6.

    Article  Google Scholar 

  34. Reyes-García V, Gueze M, Luz AC, Paneque-Gálvez J, Macía MJ, Orta-Martínez M, Pino J, Rubio-Campillo X. Evidence of traditional knowledge loss among a contemporary indigenous society. Evol Hum Beh. 2013;34:249–57.

    Article  Google Scholar 

  35. Reyes-García V, Luz AC, Gueze M, Paneque-Gálvez J, Macia MJ, Orta-Martínez M, Pino J. TAPS Bolivian study team. Secular trends on traditional ecological knowledge: an analysis of different domains of knowledge among Tsimane' men. Learn Indiv Diff. 2013;27:206–12.

    Article  Google Scholar 

  36. Reyes-García V, Godoy R, Vadez V, Apaza L, Byron E, Huanca T, Leonard WR, Pérez E, Wilkie D. Ethnobotanical knowledge shared widely among Tsimane’ Amerindians, Bolivia. Science. 2003;29:1707.

  37. Sternberg R, Nokes C, Geissler P, Prince R, Okatcha F, Bundy D, Grigorenko E. The relationship between academic and practical intelligence: a case study in Kenya. Intell. 2001;29:401–18.

    Article  Google Scholar 

  38. Zarger R, Stepp JR. Persistence of botanical knowledge among Tzeltal Maya children. Curr Anth. 2004;45:413–8.

    Article  Google Scholar 

  39. Zent S. Acculturation and ethnobotanical knowledge loss among the Piaroa of Venezuela. In: Maffi L, editor. On biocultural diversity: linking language, knowledge, and the environment. Washington, D.C: Smithsonian Institution Press; 2001. p. 190–211.

    Google Scholar 

  40. Phillips O, Gentry AH. The useful plants of Tambopata, Peru: II. Additional hypothesis testing in quantitative ethnobotany. Econ Bot. 1993;47(1):33–43.

    Article  Google Scholar 

  41. Zarger R. Acquisition and transmission of subsistence knowledge by Q’eqchi’ Maya in Belize. In: Stepp JR, Wyndham FS, Zarger R, editors. Ethnobiology and biocultural diversity. Athens: International Society of Ethnobiology; 2002. p. 592–603.

    Google Scholar 

  42. Byron E. Market integration and health: the impact of markets on the nutritional status, morbidity, and diet of the Tsimane’ Amerindians of lowland Bolivia. Gainsville: University of Florida; 2003.

  43. Godoy R, Reyes-García V, Broesch J, Fitzpatrick IC, Giovnnini P, Rodriguez MRM, Jha N, Huanca T, Leonard WR, McDade TW, Tanner S. TAPS Bolivia Study Team. Long-term (secular) change of ethnobotanical knowledge of useful plants separating cohort and age effects. J Anth Res. 2009;65(1):51–67.

    Google Scholar 

  44. Vandebroek I, Van Damme P, Puyvelde LV, Arrazola S, De Kimpe NA. Comparison of traditional healers’ medicinal plant knowledge in the Bolivian Andes and Amazon. Soc Sci Med. 2004;59:837–49.

    Article  PubMed  Google Scholar 

  45. Baum JK, Myers RA. Shifting baselines and the decline of pelagic sharks in the Gulf of Mexico. Ecol Lett. 2004;7:135–45.

    Article  Google Scholar 

  46. Hanazaki N, Firme Herbst D, Simionato Marques M, Vandebroek I. Evidence of the shifting baseline syndrome in ethnobotanical research. J Ethnobiol Ethnomed. 2013;9:75.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Bernard HR. Research methods in anthropology. Walnut Creek: AltaMira Press; 1995.

    Google Scholar 

  48. Bernard HR. Social research methods. Thousand Oaks: Sage Publications; 2000.

    Google Scholar 

  49. Glaser BG, Strauss AL. The discovery of grounded theory: strategies for qualitative research. New York: Aldine Publishing Company; 1967.

    Google Scholar 

  50. Flick U. An introduction to qualitative research: theory, method and applications. Thousand Oaks: Sage Publications; 1998.

    Google Scholar 

  51. Fossey E, Harvey C, McDermott F, Davidson L. Understanding and evaluating qualitative research. Aust N Zeal J Psych. 2002;36:717–32.

    Article  Google Scholar 

  52. Patton MQ. Qualitative research and evaluation methods. Thousand Oaks: Sage Publications; 2002.

    Google Scholar 

  53. Seidman I. Interviewing as qualitative research: a guide for researchers in education and the social sciences, 3rd ed. New York: Teachers College Press.

  54. Bluff R. 1997. Evaluating qualitative research. Brit J Midw. 2006;5(4):232–5.

    Article  Google Scholar 

  55. Carey J, Morgan M, Oxtoby M. Intercoder agreement in analysis of responses to open-ended interview questions: examples from tuberculosis research. Cult Anthr Meth J. 1996;8:1–5.

    Google Scholar 

  56. Albuquerque UP, Nóbrega Alves RR, editors. Introduction to Ethnobiology. Stuttgart: Springer; 2016.

  57. Johnson JC. Research design and research strategies. In: Bernard HR, editor. Handbook of methods in cultural anthropology. Walnut Creek: AltaMira Press; 1998. p. 131–72.

    Google Scholar 

  58. Kuzel A. Sampling in qualitative inquiry. In: Crabtree B, Miller W, editors. Doing qualitative research. Newbury Park: Sage Publications; 1992. p. 31–44.

    Google Scholar 

  59. LeCompte M, Schensul J. Designing and conducting ethnographic research. Walnut Creek: AltaMira Press; 1999.

    Google Scholar 

  60. Crosby R, DiClemente R, Holtgrave D, Wingood G. Design, measurement, and analytical considerations for testing hypotheses relative to condom effectiveness against on viral STIs. Sex Trans Inf. 2002;78:228–31.

    Article  CAS  Google Scholar 

  61. Creswell J. Qualitative inquiry and research design: choosing among five traditions. Thousand Oaks: Sage Publications; 1998.

    Google Scholar 

  62. Browne J, Russell S. Recruiting in public places: a strategy to increase diversity in qualitative research samples. Quali Res J. 2003;3(2):75–87.

    Google Scholar 

  63. Byrne M. Evaluating the findings of qualitative research. Assoc Operati Room Nurs J. 2001;73(3):703–6.

    Article  CAS  Google Scholar 

  64. Cheek J. An untold story: doing funded qualitative research. In: Denzin N, Lincoln Y, editors. Handbook for qualitative research. Thousand Oaks: Sage Publications; 2000. p. 401–20.

    Google Scholar 

  65. Bertaux D. From the life-history approach to the transformation of sociological practice. In: Bertaux D, editor. Biography and society: the life history approaches in the social sciences. Beverly Hills: Sage Publications; 1981. p. 29–45.

    Google Scholar 

  66. Guest G, Bunce A, Johnson L. How many interviews are enough?: an experiment with data saturation and variability. Field Meth. 2006;18(1):59–82.

    Article  Google Scholar 

  67. Ryan GW, Bernard HR. Testing an ethnographic decision tree model on a national sample: recycling beverage cans. Hum Org. 2006;65(1):103–14.

    Article  Google Scholar 

  68. Mason M. Sample size and saturation in PhD studies using qualitative interviews. FQS – For Qual Soc Res. 2010;11(3):8.

    Google Scholar 

  69. Kvale S. Interviews: an introduction to qualitative research interviewing. Thousand Oaks: Sage Publications; 1996.

    Google Scholar 

  70. Morse JM. The significance of saturation. Qual Health Res. 1995;5(2):147–9.

    Article  Google Scholar 

  71. Johnson JC. Selecting ethnographic informants. Thousand Oaks: Sage Pubklications; 1990.

    Google Scholar 

  72. Paniagua-Zambrana NY, Bussmann RW. La Etnobotánica de los Chácobo en el Siglo XXI. St. Louis: William L. Brown Center; 2017.

    Google Scholar 

Download references

Acknowledgements

We greatly thank Ravi Ortiz, President of the Central Indígena de la Región Amazónica de Bolivia (CIRABO), and Maro Ortiz, Capitan General of the TCO Chácobo, as well as all our Chácobo friends and counterparts, and the whole Chácobo population for all their friendship and support. We thank the National Geographic Society (Grant #9244-13) for support of the fieldwork.

Funding

This study was funded by the National Geographic Society (Grant 9244–13) and endowment funds of the William L. Brown Center at Missouri Botanical Garden, for which we are grateful.

Availability of data and materials

The raw data contain the names of all participants and cannot be shared publicly. Data without participant data can be obtained upon request after agreeing on an access and benefit sharing agreement with CIRABO.

Author information

Authors and Affiliations

Authors

Contributions

NYPZ and RBU designed the study; NYPZ, RBU, ALHM, GOS, MOV, DOA, JSM, MSM, SC, BCM, GCM, and ES conducted the fieldwork; ALMH curated and identified the collections and entered the original data; NYPZ and RBU analyzed the data; NYPZ, RBU, and NPZ wrote the manuscript; REH conducted the statistical analysis; and all authors read, corrected, and approved the manuscript.

Corresponding author

Correspondence to Narel Y. Paniagua-Zambrana.

Ethics declarations

Ethics approval and consent to participate

Before conducting interviews, both the permission of CIRABO and individual prior informed consent were obtained from all participants. No further ethics approval was required. All work conducted was carried out under the stipulations of the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing of Benefits Arising from their Utilization to the Convention on Biological Diversity. The right to use and authorship of any traditional knowledge of all participants is maintained, and any use of this information, other than for scientific publication, does require additional prior consent of the traditional owners, as well as a consensus on access to benefits resulting from subsequent use.

Consent for publication

This manuscript does not contain any individual person’s data, and further consent for publication is not required.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Paniagua-Zambrana, N.Y., Bussmann, R.W., Hart, R.E. et al. Who should conduct ethnobotanical studies? Effects of different interviewers in the case of the Chácobo Ethnobotany project, Beni, Bolivia. J Ethnobiology Ethnomedicine 14, 9 (2018). https://doi.org/10.1186/s13002-018-0210-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13002-018-0210-2

Keywords