The Effect of Reciprocal Connections between Demographic Decision Making and Land Use on Decadal Dynamics of Population and Land-Use Change
Zvoleff, Alex, and Li An. 2014. “The Effect of Reciprocal Connections between Demographic Decision Making and Land Use on Decadal Dynamics of Population and Land-Use Change.” Ecology and Society 19(2):31.
Although much focus has been given to the study of land use and land cover (LULC) and population change, studies have tended to focus on relationships in a single direction, for instance, the consequences of changing LULC for population processes, or the consequences of changing population dynamics for LULC. Given the highly coupled nature of human-environment systems, we cannot fully understand these systems without considering reciprocal causality, or “feedbacks.” This analysis focuses on the Chitwan District of south-central Nepal, a high priority conservation area, and seeks to address the question of how feedbacks between land use and microlevel human decision making impact the decadal time scale dynamics of population and land-use change. It investigates two feedback loops connecting land use and demographic decision making: agricultural land use – marriage timing; and agricultural land use – fertility. Marriage is closely tied to land use in Chitwan because new households in Chitwan are established primarily after marriage. Fertility is connected to land use because of its linkage with population size and future new household formation. However, prior research in Chitwan has shown that residents of agricultural neighborhoods tend to marry earlier, and to have children sooner after marriage. Using an agent-based model, we compare model outcomes from scenarios with and without these feedback loops. Our results indicate that these feedbacks lead to statistically significant differences in population and in land-use outcomes. However, the sizes of these differences are relatively small in magnitude (less than 8% for the scenarios considered here), even over a 50-year time scale. These findings are a reminder that CHANS researchers must be careful to consider both effect size and significance when considering the policy implications of model outcomes.