10.5061/DRYAD.18931ZCTD
Kavanagh, Patrick
0000-0003-1226-5850
Colorado State University
Gavin, Michael
Colorado State University
Haynie, Hannah
University of Colorado Boulder
Kushnick, Geoff
Australian National University
Vilela, Bruno
Washington University in St. Louis
Tuff, Ty
Washington University in St. Louis
Bowern, Claire
Yale University
Low, Bobbi
University of Michigan–Ann Arbor
Ember, Carol
Yale University
Kirby, Kathryn
Max Planck Institute for the Science of Human History
Botero, Carlos
Washington University in St. Louis
Drivers of global variation in land ownership - dataset
Dryad
dataset
2020
FOS: Other natural sciences
2022-04-18T00:00:00Z
2022-04-18T00:00:00Z
en
21810 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Land ownership shapes natural resource management and social–ecological
resilience, but the factors determining ownership norms in human societies
remain unclear. Here we conduct a global empirical test of long‐standing
theories from ecology, economics and anthropology regarding potential
drivers of land ownership and territoriality. Prior theory suggests that
resource defensibility, subsistence strategies, population pressure,
political complexity and cultural transmission mechanisms may all
influence land ownership. We applied multi‐model inference procedures
based on logistic regression to cultural and environmental data from 102
societies, 71 with some form of land ownership and 31 with no land
ownership. We found an increased probability of land ownership in
mountainous environments, where patchy resources may be more cost
effective to defend via ownership. We also uncovered support for the role
of population pressure, with a greater probability of land ownership in
societies living at higher population densities. Our results also show
more land ownership when neighboring societies also practiced ownership.
We found less support for variables associated with subsistence strategies
and political complexity.
The land tenure data (Main_LT) represents the main landownership norm
which was coded for 102 societies from ethnographic descriptions in eHRAF
World Cultures (http://ehrafworldcultures.yale.edu/. All other data
were acquired from D-PLACE: https://d-place.org/
Please refer to ReadMe file.