Assessing Biocultural Diversity Across Scales Using Ecological Indicators
Bibliographic record
Abstract
• We propose an indicator of biocultural diversity combining vertebrate richness and cultural data like UNESCO Heritage Sites. • Ecological indices like Shannon and Simpson can be adapted to quantify biocultural diversity. • Correlations between biodiversity and cultural diversity are found at national but not ecoregional scales. • Orinoquia and Amazonia are Colombia’s most biodiverse ecoregions, while the Caribbean ranks highest in cultural diversity. • Valledupar emerged as the most biocultural diverse. municipality in Colombia. Despite considerable efforts to promote biocultural diversity as a conservation objective, the spatial correlation between cultural and biological diversities, as well as its variation across geographic scales, remains unclear. In this study, we used Colombia as a case study to examine the relationships between biodiversity and cultural diversity at both national and ecoregional scales. Using municipality as the unit of analysis, we gathered data on a range of biological and cultural variables. We quantified six biodiversity indicators–species richness of freshwater fishes, mammals, birds, amphibians, reptiles, and number of ecosystems. For cultural diversity, we used seven indicators: music festivals, Indigenous reserves, Afro-Colombian lands, UNESCO World Heritage sites, UNESCO Intangible Cultural Heritage sites, museums, and native languages, as proxies for institutionalized cultural diversity. Diversity metrics adapted from ecology, including the Shannon Diversity Index (SDI) and the Inverse-Simpson Diversity Index (InvSDI), were used to calculate both biodiversity and cultural diversity at national and ecoregional scales. Our results suggest that biodiversity and cultural diversity are partially positively correlated at the national scale, as indicated by the InvSDI, which incorporates cultural data that the SDI omits. However, at the ecoregional scale, we found no consistent correlation, though both positive and negative trends emerged. This study presents a methodological innovation for quantifying biocultural diversity and raises important questions for future research on the connections between nature and culture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".