Ethnobotanical Analysis, Decision-Framing, and TEK Modeling
Overview
Tools for quantifying Traditional Ecological Knowledge (TEK), modeling TEK in decision frameworks, and designing structured decision-framing exercises in conservation and development contexts. The package implements quantitative ethnobotany indices (Use Value, Relative Frequency of Citation, etc.) but positions them within a larger framework of Bayesian modeling and participatory decision analysis. Includes critical assessment of indices' limitations and case studies of participatory workshops.
New models, data and tests; fixes to ethno_bayes_consensus() and ethno_boot().
Breaking change
ethno_bayes_consensus(): responses must be whole numbers from 0 toanswers - 1(0/1 for binary data) and result rows are labelled 0 and 1. Earlier results were wrong because 0 responses were ignored. Competence (prior_for_answers) is required.
New functions and data
ethno_beta(): Beta-binomial probability of use per species and use. Default for small samples and rare uses.ethno_saturation(): informant saturation curve.ethno_consensus(): consensus with competence estimated from the data (EM).homegardens: 102 homegardens in southwestern Uganda, 225 species, 14 uses, 3,961 use reports, as analyzed in Whitney et al. (2018). One informant per garden. Companion tableshomegardens_info(garden covariates) andhomegardens_species(life form, family, native).- Tests (
testthat).
Bug fixes
ethno_bayes_consensus(): corrected the likelihood for more than two answers.ethno_boot():n2defaults to the number of observations. Newuse_weightsargument. Warns when all observations are identical (zero-width interval).
Show all changes in 0.3.0Hide the rest of the changes in 0.3.0
- Vignettes no longer rewrite
.bibfiles at build time. honest_ethnobotany: fixed swapped lower/upper labels.- TEK modeling vignette: network chunk runs and compares decisions. Weighted pooling uses effective sample size. Removed arbitrary pseudo-count mapping.
Vignettes
- Modeling and TEK vignettes use
homegardens. The TEK vignette adds a network learned from the survey.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 23
- Examples that run
- 100%20 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 87%
Downloads
Repository
- PRs merged (all time)
- 94%
- Median days to close, 50 most recently updated closed issues
- 462
- Median days to close, 50 most recently updated closed PRs
- 0
Stars over time
Forks over time
Releases over time
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Commits over time
5 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/cwwhitney/ethnobotanyr on 2026-10-22.
This repository shows signs of AI coding tools.
- Claude Codefirst seen on or before 2026-10-06Commits: at least 25 crediting it in the message
- Claude Sonnet 5.525 commits · Oct 2026
Dependencies
Installing ethnobotanyR adds 40 packages (20 with compiled code, 42 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, ggalluvial 2.7 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- 0.3.0Latest2026-10-16 · current release · diff ↗ ··
added 3 exports
ethno_beta, ethno_consensus, ethno_saturationlisted once in CRAN's queue
Seen in one reading of CRAN's incoming queue, at 2026-10-16 07:45 UTC, so it stayed less than the time between readings. - RR 4.6.0 released · 2026-04-24
- 0.2.02026-02-25 · diff ↗
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.92022-12-17 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 0.1.8
- RR 4.0.0 released · 2020-04-24
- 0.1.7
- 0.1.6
- 0.1.5
- RR 3.6.0 released · 2019-04-26
- 0.1.4
Package metadata
- First published
- 2019-01-08
- Total releases
- 11 / 7 yrs
- License
- GPL
- Minimum R
- ≥ 3.5.0
- Bundled data
- 13 KB / 4 files
- Download size
- 3.5 MB
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