# Sociodemographic characteristics predict land use patterns by farmers near a protected area in Madagascar

## TL;DR

The study shows how farmers' land use near a Madagascar protected area is influenced by their sociodemographic traits, with implications for conservation and disease prevention.

## Contribution

The novel contribution is applying movement ecology with GPS and survey data to link sociodemographic factors to fine-scale land use patterns in smallholder farming.

## Key findings

- Men traversed 65% more area and spent 30% less time in the village than women.
- Socioeconomic status, education, and having young children influenced time spent in secondary forests and swidden areas.
- The study's GPS and analytical methods can inform policies on human-ecological systems and health disparities.

## Abstract

Globally, most farms are smaller than 10 hectares. Land use by these smallholder farmers in agricultural frontiers is crucial to conservation, food security, and exposure to infectious diseases. However, solely survey-based land use studies miss the fine scale movements that collectively form an individual’s land use and thus environmental exposures, particularly in fragmented landscapes. We applied movement ecology-based approaches with GPS and survey data to investigate how sociodemographic variables corresponded with land use among farmers living adjacent to Marojejy National Park in northeastern Madagascar. Our data on 902 individuals spanning 3 years revealed striking differences in land use by gender and socioeconomic status. Men traversed 65% (95% CI [51%, 82%]) more area and spent 30% less time (95% CI [20, 41%]) in the village than women. Socioeconomic status, educational attainment, and having young children covaried with time spent in secondary forests where vanilla is grown, swidden areas where slash-and-burn farming methods are used, and the national park. By revealing the extent to which social and demographic variables predict individual movement patterns, our work identifies targets for addressing emerging diseases and health disparities. The GPS and analytical approaches developed here can be applied elsewhere to provide policy insights and to understand variation across human-ecological systems.

The online version contains supplementary material available at 10.1038/s41598-026-40592-6.