Building and testing models of long-term agricultural intensification and population dynamics: A case study from the Leeward Kohala Field System, Hawai’i

The Malthusian and Boserupian phases of population change, and how these are linked to long-term processes of agricultural intensification, are themes of long-standing interest to anthropologists, archaeologists, demographers, economists, ecologists, and others. The Hawai’i Biocomplexity Project has used the Hawaiian archipelago and more specifically the Leeward Kohala Field System (LKFS) as a model system to investigate the dynamic, often non-linear interactions among soils, agricultural systems, populations, and sociopolitical systems over time scales of several centuries. Two major models have been developed: (1) a model of spatial and temporal variability in agricultural production; and (2) a model of food availability and its linkages to population fertility and mortality. Empirically derived field data were used both to parameterize the models, and to test their predictions. Archaeological data on the distribution and variation in ancient agricultural field infrastructure, derived from high-resolution LiDAR images, were used to test predictions of agricultural production and intensity. Similarly, chronological data on numbers of ancient households derived from archaeological excavation and radiocarbon dating were used to test model predictions of population growth over time. This iterative process of building and testing models has led to improved understanding of how pre-industrial agricultural systems were intensified, and how expansion and intensification were dynamically linked to demographic changes in farming populations.

► Hawai’i provides a model system for investigating agricultural intensification. ► A soil nutrient model of food production is described. ► The food production model is tested with LiDAR-derived archaeological data. ► A model of food availability and human demography is described. ► Model predictions of population growth are tested with archaeological data.