Local ecological knowledge and perception

Published: 3 June 2024| Version 1 | DOI: 10.17632/yrdhjh37ym.1


Understanding how socio-ecological variables influence Local Ecological Knowledge (LEK) and perceptions of ecosystem services among farmers near protected areas is crucial for designing effective biodiversity conservation initiatives. We used participatory methodologies with 80 farmers from agrarian settlements in the Cerrado biome, Brazil, to quantify LEK and assess ecosystem service perceptions via an adapted Q-methodology. Data on thirteen socio-ecological variables, including age, gender, farm size, education, conservation engagement, and interactions with protected areas, were collected. Using a Random Forest (RF) modelling approach, we identified the most influential variables on LEK and perceptions.Interviews were approved by the Ethics Committee of the University of Brasília (CAAE: 30574620000005540). LEK scores were based on detailed information about species, ecosystems, and conservation actions. Scores ranged from 0 to 60, with a maximum of 62 points for exceptional details. We assessed ecosystem service perceptions using the CICES 5.2 classification, selecting 13 services from regulation, provision, and cultural classes. Data were collected using a Q-sort table ranging from -5 (extremely negative) to 5 (extremely positive), and scores from 0 (not noticed) to 5 (extremely important) were assigned.To understand changes in ecosystem services, we included open-ended questions about perceived landscape changes, specific changes, and future factors affecting ecosystem services. Using RF modelling, we evaluated the variability of socio-ecological variables associated with LEK and perceptions. ANOVA and Tukey's post-hoc test assessed significant variations, while the Kruskal-Wallis test and Dunn's test analyzed non-parametric data.We also explored how LEK and ecosystem service perceptions varied among different farmer types, classifying farms into: (1) self-consumption, (2) soybean monoculture, (3) ecotourism, (4) animal production in silvopastoral systems, and (5) agroecological farms. A descriptive analysis highlighted the contribution of each socio-ecological variable to LEK and perceptions. Principal Component Analysis (PCA) was used to assess variations in LEK and ecosystem service perceptions.


Steps to reproduce

Data processing was carried out in R language. The script is available with all step-by-step instructions.


Instituto Federal de Educacao Ciencia e Tecnologia de Brasilia - Campus Planaltina


Buffer Zone, Random Decision Forest, Family Farming


Fundação de Apoio à Pesquisa do Distrito Federal